1
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Xue C, Ye C, Lu K, Liu P, Zhang C, Su H, Bao F, Cheng Y, Wang W, Liu Y, Catoire V, Ma Z, Zhao X, Song Y, Ma X, McGillen MR, Mellouki A, Mu Y, Zhang Y. Reducing Soil-Emitted Nitrous Acid as a Feasible Strategy for Tackling Ozone Pollution. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2024; 58:9227-9235. [PMID: 38751196 PMCID: PMC11137860 DOI: 10.1021/acs.est.4c01070] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/29/2024] [Revised: 05/08/2024] [Accepted: 05/08/2024] [Indexed: 05/29/2024]
Abstract
Severe ozone (O3) pollution has been a major air quality issue and affects environmental sustainability in China. Conventional mitigation strategies focusing on reducing volatile organic compounds and nitrogen oxides (NOx) remain complex and challenging. Here, through field flux measurements and laboratory simulations, we observe substantial nitrous acid (HONO) emissions (FHONO) enhanced by nitrogen fertilizer application at an agricultural site. The observed FHONO significantly improves model performance in predicting atmospheric HONO and leads to regional O3 increases by 37%. We also demonstrate the significant potential of nitrification inhibitors in reducing emissions of reactive nitrogen, including HONO and NOx, by as much as 90%, as well as greenhouse gases like nitrous oxide by up to 60%. Our findings introduce a feasible concept for mitigating O3 pollution: reducing soil HONO emissions. Hence, this study has important implications for policy decisions related to the control of O3 pollution and climate change.
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Affiliation(s)
- Chaoyang Xue
- Research
Centre for Eco-Environmental Sciences, Chinese
Academy of Sciences, Beijing 100085, China
- Max
Planck Institute for Chemistry, Mainz 55128, Germany
- Laboratoire
de Physique et Chimie de l’Environnement et de l’Espace
(LPC2E), CNRS—Université Orléans−CNES, Cedex 2 Orléans 45071, France
| | - Can Ye
- State
Key Joint Laboratory of Environment Simulation and Pollution Control,
College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Keding Lu
- State
Key Joint Laboratory of Environment Simulation and Pollution Control,
College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Pengfei Liu
- Research
Centre for Eco-Environmental Sciences, Chinese
Academy of Sciences, Beijing 100085, China
| | - Chenglong Zhang
- Research
Centre for Eco-Environmental Sciences, Chinese
Academy of Sciences, Beijing 100085, China
| | - Hang Su
- Max
Planck Institute for Chemistry, Mainz 55128, Germany
| | - Fengxia Bao
- Max
Planck Institute for Chemistry, Mainz 55128, Germany
| | - Yafang Cheng
- Max
Planck Institute for Chemistry, Mainz 55128, Germany
| | - Wenjie Wang
- Max
Planck Institute for Chemistry, Mainz 55128, Germany
| | - Yuhan Liu
- State
Key Joint Laboratory of Environment Simulation and Pollution Control,
College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Valéry Catoire
- Laboratoire
de Physique et Chimie de l’Environnement et de l’Espace
(LPC2E), CNRS—Université Orléans−CNES, Cedex 2 Orléans 45071, France
| | - Zhuobiao Ma
- Research
Centre for Eco-Environmental Sciences, Chinese
Academy of Sciences, Beijing 100085, China
| | - Xiaoxi Zhao
- Research
Centre for Eco-Environmental Sciences, Chinese
Academy of Sciences, Beijing 100085, China
| | - Yifei Song
- Research
Centre for Eco-Environmental Sciences, Chinese
Academy of Sciences, Beijing 100085, China
| | - Xuefei Ma
- State
Key Joint Laboratory of Environment Simulation and Pollution Control,
College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Max R. McGillen
- Institut
de Combustion Aérothermique, Réactivité et Environnement,
Centre National de la Recherche Scientifique (ICARE-CNRS), Cedex 2 Orléans 45071, France
| | - Abdelwahid Mellouki
- Institut
de Combustion Aérothermique, Réactivité et Environnement,
Centre National de la Recherche Scientifique (ICARE-CNRS), Cedex 2 Orléans 45071, France
| | - Yujing Mu
- Research
Centre for Eco-Environmental Sciences, Chinese
Academy of Sciences, Beijing 100085, China
| | - Yuanhang Zhang
- State
Key Joint Laboratory of Environment Simulation and Pollution Control,
College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
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2
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Lieb H, Walters W, Maldonado M, Ruiz E, Torres C, Olmedo L, Faloona I. Nitrogen Isotopes Reveal High NOx Emissions from Arid Agricultural Soils in the Salton Sea Air Basin. RESEARCH SQUARE 2024:rs.3.rs-4249148. [PMID: 38699374 PMCID: PMC11065076 DOI: 10.21203/rs.3.rs-4249148/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/05/2024]
Abstract
Air quality management commonly aims to mitigate emissions of oxides of nitrogen (NO x ) from combustion, reducing ozone and particulate matter pollution. Despite such efforts, regulations have recently proven ineffective in rural areas like the Salton Sea Air Basin of Southern California, which routinely violates air quality standards. With $2 billion in annual agricultural sales and low population density, air quality in the region is likely influenced by year-round farming. We conducted NO x source apportionment using nitrogen stable isotopes of ambient NO 2 , which indicate a substantial contribution of soil-emitted NO x . The soil source strength was estimated based on the mean δ 15 N-NO x from each emission category in the California Air Resources Board's NO x inventory. Our annual average soil emission estimate for the air basin was 11.4 ± 4 tons/d, representing ~ 30% of the extant NO x inventory, 10× larger than the state's inventory. Therefore, the impact of soil NO x in agricultural regions must be re-evaluated.
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3
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Gan C, Li B, Dong J, Li Y, Zhao Y, Wang T, Yang Y, Liao H. Atmospheric HONO emissions in China: Unraveling the spatiotemporal patterns and their key influencing factors. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2024; 343:123228. [PMID: 38147951 DOI: 10.1016/j.envpol.2023.123228] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/26/2023] [Revised: 12/22/2023] [Accepted: 12/23/2023] [Indexed: 12/28/2023]
Abstract
Nitrous acid (HONO) can be photolyzed to produce hydroxyl radicals (OH) in the atmosphere. OH plays a critical role in the formation of secondary pollutants like ozone (O3) and secondary organic aerosols (SOA) via various oxidation reactions. Despite the abundance of recent HONO studies, research on national HONO emissions in China remains relatively limited. Therefore, this study employed a "wetting-drying" model and bottom-up approach to develop a high-resolution gridded inventory of HONO emissions for mainland China using multiple data. We used the Monte Carlo method to estimate the uncertainty in HONO emissions. In addition, the primary sources of HONO emissions were identified and their spatiotemporal distribution and main influencing factors were studied. The results indicated that the total HONO emissions in mainland China in 2016 were 0.77 Tg N (R50: 0.28-1.42 Tg N), with soil (0.42 Tg N) and fertilization (0.26 Tg N) as the primary sources, jointly contributing to over 87% of the total. Notably, the North China Plain (NCP) had the highest HONO emission density (3.51 kg N/ha/yr). Seasonal HONO emissions followed the order: summer (0.38 kg N/ha) > spring (0.19 kg N/ha) > autumn (0.17 kg N/ha) > winter (0.06 kg N/ha). Moreover, HONO emissions were strongly correlated with fertilization, cropland, temperature, and precipitation. This study provides vital scientific groundwork for the atmospheric nitrogen cycle and the formation of secondary pollutants.
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Affiliation(s)
- Cong Gan
- Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, School of Environmental Science and Engineering, Nanjing University of Information Science & Technology, Nanjing, 210044, China
| | - Baojie Li
- Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, School of Environmental Science and Engineering, Nanjing University of Information Science & Technology, Nanjing, 210044, China.
| | - Jinyan Dong
- Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, School of Environmental Science and Engineering, Nanjing University of Information Science & Technology, Nanjing, 210044, China
| | - Yan Li
- Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, School of Environmental Science and Engineering, Nanjing University of Information Science & Technology, Nanjing, 210044, China
| | - Yongqi Zhao
- Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, School of Environmental Science and Engineering, Nanjing University of Information Science & Technology, Nanjing, 210044, China
| | - Teng Wang
- College of Oceanography, Hohai University, Nanjing, 210098, China
| | - Yang Yang
- Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, School of Environmental Science and Engineering, Nanjing University of Information Science & Technology, Nanjing, 210044, China
| | - Hong Liao
- Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, School of Environmental Science and Engineering, Nanjing University of Information Science & Technology, Nanjing, 210044, China
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4
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Hu W, Zhao Y, Lu N, Wang X, Zheng B, Henze DK, Zhang L, Fu TM, Zhai S. Changing Responses of PM 2.5 and Ozone to Source Emissions in the Yangtze River Delta Using the Adjoint Model. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2024; 58:628-638. [PMID: 38153406 DOI: 10.1021/acs.est.3c05049] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/29/2023]
Abstract
China's industrial restructuring and pollution controls have altered the contributions of individual sources to varying air quality over the past decade. We used the GEOS-Chem adjoint model and investigated the changing sensitivities of PM2.5 and ozone (O3) to multiple species and sources from 2010 to 2020 in the central Yangtze River Delta (YRDC), the largest economic region in China. Controlling primary particles and SO2 from industrial and residential sectors dominated PM2.5 decline, and reducing CO from multiple sources and ≥C3 alkenes from vehicles restrained O3. The chemical regime of O3 formation became less VOC-limited, attributable to continuous NOX abatement for specific sources, including power plants, industrial combustion, cement production, and off-road traffic. Regional transport was found to be increasingly influential on PM2.5. To further improve air quality, management of agricultural activities to reduce NH3 is essential for alleviating PM2.5 pollution, while controlling aromatics, alkenes, and alkanes from industry and gasoline vehicles is effective for O3. Reducing the level of NOX from nearby industrial combustion and transportation is helpful for both species. Our findings reveal the complexity of coordinating control of PM2.5 and O3 pollution in a fast-developing region and support science-based policymaking for other regions with similar air pollution problems.
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Affiliation(s)
- Weiyang Hu
- State Key Laboratory of Pollution Control and Resource Reuse and School of the Environment, Nanjing University, 163 Xianlin Road, Nanjing, Jiangsu 210023, China
| | - Yu Zhao
- State Key Laboratory of Pollution Control and Resource Reuse and School of the Environment, Nanjing University, 163 Xianlin Road, Nanjing, Jiangsu 210023, China
- Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology (CICAEET), Nanjing University of Information Science and Technology, Jiangsu 210044, China
| | - Ni Lu
- Laboratory for Climate and Ocean-Atmosphere Sciences, Department of Atmospheric and Oceanic Sciences, School of Physics, Peking University, Beijing 100871, China
| | - Xiaolin Wang
- Laboratory for Climate and Ocean-Atmosphere Sciences, Department of Atmospheric and Oceanic Sciences, School of Physics, Peking University, Beijing 100871, China
| | - Bo Zheng
- Institute of Environment and Ecology, Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, Guangdong 518055, China
| | - Daven K Henze
- Department of Mechanical Engineering, University of Colorado Boulder, Boulder, Colorado 80309, United States
| | - Lin Zhang
- Laboratory for Climate and Ocean-Atmosphere Sciences, Department of Atmospheric and Oceanic Sciences, School of Physics, Peking University, Beijing 100871, China
| | - Tzung-May Fu
- State Environmental Protection Key Laboratory of Integrated Surface Water-Groundwater Pollution Control, Guangdong Provincial Key Laboratory of Soil and Groundwater Pollution Control, School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen, Guangdong 518055, China
| | - Shixian Zhai
- John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts 02138, United States
- Division of Environment and Sustainability, HKUST Jockey Club Institute for Advanced Study, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong 999077, China
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5
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Luo Y, Hu Y, Yang J, Zhang M, Yung YL. Coupled atmospheric chemistry, radiation, and dynamics of an exoplanet generate self-sustained oscillations. Proc Natl Acad Sci U S A 2023; 120:e2309312120. [PMID: 38091286 PMCID: PMC10743409 DOI: 10.1073/pnas.2309312120] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2023] [Accepted: 10/13/2023] [Indexed: 12/24/2023] Open
Abstract
Nonlinearity in photochemical systems is known to allow self-sustained oscillations, but they have received little attention in studies of planetary atmospheres. Here, we present a unique, self-oscillatory solution for ozone chemistry of an exoplanet from a numerical simulation using a fully coupled, three-dimensional (3D) atmospheric chemistry-radiation-dynamics model. Forced with nonvarying stellar insolation and emission flux of nitric oxide (NO), atmospheric ozone abundance oscillates by a factor of thirty over a multidecadal timescale. As such self-oscillations can only occur with biological nitrogen fixation contributing to NO emission, we propose that they are a unique class of biosignature. The resulting temporal variability in the atmospheric spectrum is potentially observable. Our results underscore the importance of revisiting the spectra of exoplanets over multidecadal timescales to characterizing the atmospheric chemistry of exoplanets and searching for exoplanet biosignatures. There are also profound implications for comparative planetology and the evolution of the atmospheres of terrestrial planets in the solar system and beyond. Fully coupled, 3D atmospheric chemistry-radiation-dynamics models can reveal new phenomena that may not exist in one-dimensional models, and hence, they are powerful tools for future planetary atmospheric research.
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Affiliation(s)
- Yangcheng Luo
- Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, CA91125
- Department of Atmospheric and Oceanic Sciences, School of Physics, Peking University, Beijing100871, China
- Laboratoire de Météorologie Dynamique/Institut Pierre-Simon Laplace, Sorbonne Université, École Normale Supérieure, Université Paris Sciences et Lettres, Ecole Polytechnique, Institut Polytechnique de Paris, Centre National de la Recherche Scientifique, Paris75005, France
| | - Yongyun Hu
- Department of Atmospheric and Oceanic Sciences, School of Physics, Peking University, Beijing100871, China
| | - Jun Yang
- Department of Atmospheric and Oceanic Sciences, School of Physics, Peking University, Beijing100871, China
| | - Michael Zhang
- Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, CA91125
| | - Yuk L. Yung
- Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, CA91125
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6
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Liu W, Sun J, Li S, Zhao R. Impacts of local soil and vehicle NO x emissions on ground-level NO 2 concentrations on a university campus in the city of Shenyang, China. ENVIRONMENTAL MONITORING AND ASSESSMENT 2023; 196:63. [PMID: 38112882 DOI: 10.1007/s10661-023-12098-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/18/2023] [Accepted: 11/04/2023] [Indexed: 12/21/2023]
Abstract
Nitrogen dioxide (NO2) is a ubiquitous atmospheric pollutant, and fossil fuel combustion is generally considered its predominant source in and around urban areas. As the total nitrogen deposition is high over here, soil NOx emissions from urban green space might also be an important local source of ground-level NO2. In this study, Willems badge samplers were employed to monitor the spatial and seasonal variations of 2-week mean atmospheric NO2 concentrations at a height of 1.7 m on an urban campus in Northeast China from November 2020 to December 2021. We found considerable small-scale spatial variations of ground-level NO2 concentrations on the campus during the growing season, with local soil NOx emissions as the main driver. According to its linear correlation with green space coverage, the increment in ground-level NO2 concentration was partitioned into two components, with one ascribed to the local soil source (referred to as NO2-Isoil) and the other the local vehicle source (NO2-Ivehicle). NO2-Isoil generally reached a maximum (as high as 25.6 μg/m3) during early spring, while its ratio to the background value generally reached a maximum (could be >1) during late spring and could reach 0.52 to 0.92 during summer. Therefore, soil NOx emissions were an important source of ground-level NO2 on the campus, with the contribution even higher than those of other anthropogenic sources during late spring. Even with light traffic on the campus, NO2-Ivehicle could reach 0.48 times the background value at a site with high frequencies of warm starts.
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Affiliation(s)
- Wei Liu
- College of Environment and Safety Engineering, Shenyang University of Chemical Technology, Shenyang, 110142, Liaoning, China.
| | - Jiahui Sun
- College of Environment and Safety Engineering, Shenyang University of Chemical Technology, Shenyang, 110142, Liaoning, China
| | - Sulian Li
- Research Institute No. 240, China National Nuclear Corporation, Shenyang, 110135, Liaoning, China
| | - Rongbo Zhao
- College of Environment and Safety Engineering, Shenyang University of Chemical Technology, Shenyang, 110142, Liaoning, China
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7
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de la Paz D, Borge R, de Andrés JM, Tovar L, Sarwar G, Napelenok SL. Summertime tropospheric ozone source apportionment study in the Madrid region (Spain). ATMOSPHERIC CHEMISTRY AND PHYSICS 2023; 24:4949-4972. [PMID: 38846712 PMCID: PMC11151812 DOI: 10.5194/acp-24-4949-2024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/09/2024]
Abstract
The design of emission abatement measures to effectively reduce high ground-level ozone (O3) concentrations in urban areas is very complex. In addition to the strongly non-linear chemistry of this secondary pollutant, precursors can be released by a variety of sources in different regions, and locally produced O3 is mixed with that transported from the regional or continental scales. All of these processes depend also on the specific meteorological conditions and topography of the study area. Consequently, high-resolution comprehensive modeling tools are needed to understand the drivers of photochemical pollution and to assess the potential of local strategies to reduce adverse impacts from high tropospheric O3 levels. In this study, we apply the Integrated Source Apportionment Method (ISAM) implemented in the Community Multiscale Air Quality (CMAQ v5.3.2) model to investigate the origin of summertime O3 in the Madrid region (Spain). Consistent with previous studies, our results confirm that O3 levels are dominated by non-local contributions, representing around 70 % of mean values across the region. Nonetheless, precursors emitted by local sources, mainly road traffic, play a more important role during O3 peaks, with contributions as high as 25 ppb. The potential impact of local measures is higher under unfavorable meteorological conditions associated with regional accumulation patterns. These findings suggest that this modeling system may be used in the future to simulate the potential outcomes of specific emission abatement measures to prevent high-O3 episodes in the Madrid metropolitan area.
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Affiliation(s)
- David de la Paz
- Laboratory of Environmental Modelling, Department of Chemical & Environmental Engineering, Universidad Politécnica de Madrid, (UPM), c/ José Gutiérrez Abascal 2, 28006 Madrid, Spain
| | - Rafael Borge
- Laboratory of Environmental Modelling, Department of Chemical & Environmental Engineering, Universidad Politécnica de Madrid, (UPM), c/ José Gutiérrez Abascal 2, 28006 Madrid, Spain
| | - Juan Manuel de Andrés
- Laboratory of Environmental Modelling, Department of Chemical & Environmental Engineering, Universidad Politécnica de Madrid, (UPM), c/ José Gutiérrez Abascal 2, 28006 Madrid, Spain
| | - Luis Tovar
- Laboratory of Environmental Modelling, Department of Chemical & Environmental Engineering, Universidad Politécnica de Madrid, (UPM), c/ José Gutiérrez Abascal 2, 28006 Madrid, Spain
| | - Golam Sarwar
- Center for Environmental Measurement & Modeling, U.S. Environmental Protection Agency, Research Triangle Park, NC 27711, USA
| | - Sergey L. Napelenok
- Center for Environmental Measurement & Modeling, U.S. Environmental Protection Agency, Research Triangle Park, NC 27711, USA
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8
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Tian X, Yin Y, He K, Qiu R, Cong J, Wang Z, Yu H, Chen Z, Chu Y, Ying H, Cui Z. Data-driven estimation of nitric oxide emissions from global soils based on dominant vegetation covers. GLOBAL CHANGE BIOLOGY 2023; 29:5955-5967. [PMID: 37462298 DOI: 10.1111/gcb.16864] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/06/2023] [Accepted: 06/16/2023] [Indexed: 09/20/2023]
Abstract
Soils are a major source of global nitric oxide (NO) emissions. However, estimates of soil NO emissions have large uncertainties due to limited observations and multifactorial impacts. Here, we mapped global soil NO emissions, integrating 1356 in-situ NO observations from globally distributed sites with high-resolution climate, soil, and management practice data. We then calculated global and national total NO budgets and revealed the contributions of cropland, grassland, and forest to global soil NO emissions at the national level. The results showed that soil NO emissions were explained mainly by N input, water input and soil pH. Total above-soil NO emissions of the three vegetation cover types were 9.4 Tg N year-1 in 2014, including 5.9 Tg N year-1 (1.04, 95% confidence interval [95% CI]: 0.09-1.99 kg N ha-1 year-1 ) emitted from forest, 1.7 Tg N year-1 (0.68, 95% CI: 0.10-1.26 kg N ha-1 year-1 ) from grassland, and 1.8 Tg N year-1 (0.98, 95% CI: 0.42-1.53 kg N ha-1 year-1 ) from cropland. Soil NO emissions in approximately 57% of 213 countries surveyed were dominated by forests. Our results provide updated inventories of global and national soil NO emissions based on robust data-driven models. These estimates are critical to guiding the mitigation of soil NO emissions and can be used in combination with biogeochemical models.
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Affiliation(s)
- Xingshuai Tian
- College of Resources and Environmental Sciences, National Academy of Agriculture Green Development, China Agricultural University, Beijing, China
| | - Yulong Yin
- College of Resources and Environmental Sciences, National Academy of Agriculture Green Development, China Agricultural University, Beijing, China
| | - Kai He
- College of Resources and Environmental Sciences, National Academy of Agriculture Green Development, China Agricultural University, Beijing, China
| | - Ruonan Qiu
- School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, China
| | - Jiahui Cong
- College of Resources and Environmental Sciences, National Academy of Agriculture Green Development, China Agricultural University, Beijing, China
| | - Zihan Wang
- College of Resources and Environmental Sciences, National Academy of Agriculture Green Development, China Agricultural University, Beijing, China
| | - Huitong Yu
- College of Resources and Environmental Sciences, National Academy of Agriculture Green Development, China Agricultural University, Beijing, China
| | - Zhong Chen
- College of Resources and Environmental Sciences, National Academy of Agriculture Green Development, China Agricultural University, Beijing, China
| | - Yiyan Chu
- College of Resources and Environmental Sciences, National Academy of Agriculture Green Development, China Agricultural University, Beijing, China
| | - Hao Ying
- College of Resources and Environmental Sciences, National Academy of Agriculture Green Development, China Agricultural University, Beijing, China
| | - Zhenling Cui
- College of Resources and Environmental Sciences, National Academy of Agriculture Green Development, China Agricultural University, Beijing, China
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9
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Tan W, Wang H, Su J, Sun R, He C, Lu X, Lin J, Xue C, Wang H, Liu Y, Liu L, Zhang L, Wu D, Mu Y, Fan S. Soil Emissions of Reactive Nitrogen Accelerate Summertime Surface Ozone Increases in the North China Plain. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2023; 57:12782-12793. [PMID: 37596963 DOI: 10.1021/acs.est.3c01823] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/21/2023]
Abstract
Summertime surface ozone in China has been increasing since 2013 despite the policy-driven reduction in fuel combustion emissions of nitrogen oxides (NOx). Here we examine the role of soil reactive nitrogen (Nr, including NOx and nitrous acid (HONO)) emissions in the 2013-2019 ozone increase over the North China Plain (NCP), using GEOS-Chem chemical transport model simulations. We update soil NOx emissions and add soil HONO emissions in GEOS-Chem based on observation-constrained parametrization schemes. The model estimates significant daily maximum 8 h average (MDA8) ozone enhancement from soil Nr emissions of 8.0 ppbv over the NCP and 5.5 ppbv over China in June-July 2019. We identify a strong competing effect between combustion and soil Nr sources on ozone production in the NCP region. We find that soil Nr emissions accelerate the 2013-2019 June-July ozone increase over the NCP by 3.0 ppbv. The increase in soil Nr ozone contribution, however, is not primarily driven by weather-induced increases in soil Nr emissions, but by the concurrent decreases in fuel combustion NOx emissions, which enhance ozone production efficiency from soil by pushing ozone production toward a more NOx-sensitive regime. Our results reveal an important indirect effect from fuel combustion NOx emission reduction on ozone trends by increasing ozone production from soil Nr emissions, highlighting the necessity to consider the interaction between anthropogenic and biogenic sources in ozone mitigation in the North China Plain.
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Affiliation(s)
- Wanshan Tan
- School of Atmospheric Sciences, Sun Yat-sen University, and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, Guangdong 519082, People's Republic of China
- Guangdong Provincial Observation and Research Station for Climate Environment and Air Quality Change in the Pearl River Estuary, Zhuhai, Guangdong 519082, People's Republic of China
- Key Laboratory of Tropical Atmosphere-Ocean System, Ministry of Education, Zhuhai, China, Zhuhai, Guangdong 519082, People's Republic of China
| | - Haolin Wang
- School of Atmospheric Sciences, Sun Yat-sen University, and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, Guangdong 519082, People's Republic of China
- Guangdong Provincial Observation and Research Station for Climate Environment and Air Quality Change in the Pearl River Estuary, Zhuhai, Guangdong 519082, People's Republic of China
- Key Laboratory of Tropical Atmosphere-Ocean System, Ministry of Education, Zhuhai, China, Zhuhai, Guangdong 519082, People's Republic of China
| | - Jiayin Su
- School of Atmospheric Sciences, Sun Yat-sen University, and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, Guangdong 519082, People's Republic of China
- Guangdong Provincial Observation and Research Station for Climate Environment and Air Quality Change in the Pearl River Estuary, Zhuhai, Guangdong 519082, People's Republic of China
- Key Laboratory of Tropical Atmosphere-Ocean System, Ministry of Education, Zhuhai, China, Zhuhai, Guangdong 519082, People's Republic of China
| | - Ruize Sun
- School of Atmospheric Sciences, Sun Yat-sen University, and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, Guangdong 519082, People's Republic of China
- Guangdong Provincial Observation and Research Station for Climate Environment and Air Quality Change in the Pearl River Estuary, Zhuhai, Guangdong 519082, People's Republic of China
- Key Laboratory of Tropical Atmosphere-Ocean System, Ministry of Education, Zhuhai, China, Zhuhai, Guangdong 519082, People's Republic of China
| | - Cheng He
- School of Atmospheric Sciences, Sun Yat-sen University, and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, Guangdong 519082, People's Republic of China
- Guangdong Provincial Observation and Research Station for Climate Environment and Air Quality Change in the Pearl River Estuary, Zhuhai, Guangdong 519082, People's Republic of China
- Key Laboratory of Tropical Atmosphere-Ocean System, Ministry of Education, Zhuhai, China, Zhuhai, Guangdong 519082, People's Republic of China
| | - Xiao Lu
- School of Atmospheric Sciences, Sun Yat-sen University, and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, Guangdong 519082, People's Republic of China
- Guangdong Provincial Observation and Research Station for Climate Environment and Air Quality Change in the Pearl River Estuary, Zhuhai, Guangdong 519082, People's Republic of China
- Key Laboratory of Tropical Atmosphere-Ocean System, Ministry of Education, Zhuhai, China, Zhuhai, Guangdong 519082, People's Republic of China
| | - Jintai Lin
- Laboratory for Climate and Ocean-Atmosphere Studies, Department of Atmospheric and Oceanic Sciences, School of Physics, Peking University, Beijing 100871, People's Republic of China
| | - Chaoyang Xue
- Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
- Laboratoire de Physique et Chimie de l'Environnement et de l'Espace (LPC2E), CNRS-Université Orléans-CNES, CEDEX 2 Orléans 45071, France
| | - Haichao Wang
- School of Atmospheric Sciences, Sun Yat-sen University, and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, Guangdong 519082, People's Republic of China
- Guangdong Provincial Observation and Research Station for Climate Environment and Air Quality Change in the Pearl River Estuary, Zhuhai, Guangdong 519082, People's Republic of China
- Key Laboratory of Tropical Atmosphere-Ocean System, Ministry of Education, Zhuhai, China, Zhuhai, Guangdong 519082, People's Republic of China
| | - Yiming Liu
- School of Atmospheric Sciences, Sun Yat-sen University, and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, Guangdong 519082, People's Republic of China
- Guangdong Provincial Observation and Research Station for Climate Environment and Air Quality Change in the Pearl River Estuary, Zhuhai, Guangdong 519082, People's Republic of China
- Key Laboratory of Tropical Atmosphere-Ocean System, Ministry of Education, Zhuhai, China, Zhuhai, Guangdong 519082, People's Republic of China
| | - Lei Liu
- College of Earth and Environmental Sciences, Lanzhou University, Lanzhou 730000, People's Republic of China
| | - Lin Zhang
- Laboratory for Climate and Ocean-Atmosphere Studies, Department of Atmospheric and Oceanic Sciences, School of Physics, Peking University, Beijing 100871, People's Republic of China
| | - Dianming Wu
- Key Laboratory of Geographic Information Science (Ministry of Education), School of Geographic Sciences, East China Normal University, Shanghai 200241, People's Republic of China
- Institute of Eco-Chongming (IEC), Shanghai 202162, People's Republic of China
| | - Yujing Mu
- Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - Shaojia Fan
- School of Atmospheric Sciences, Sun Yat-sen University, and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, Guangdong 519082, People's Republic of China
- Guangdong Provincial Observation and Research Station for Climate Environment and Air Quality Change in the Pearl River Estuary, Zhuhai, Guangdong 519082, People's Republic of China
- Key Laboratory of Tropical Atmosphere-Ocean System, Ministry of Education, Zhuhai, China, Zhuhai, Guangdong 519082, People's Republic of China
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10
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Sekiya T, Miyazaki K, Eskes H, Bowman K, Sudo K, Kanaya Y, Takigawa M. The worldwide COVID-19 lockdown impacts on global secondary inorganic aerosols and radiative budget. SCIENCE ADVANCES 2023; 9:eadh2688. [PMID: 37506199 PMCID: PMC10381952 DOI: 10.1126/sciadv.adh2688] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/21/2023] [Accepted: 06/27/2023] [Indexed: 07/30/2023]
Abstract
Global lockdown measures to prevent the spread of the coronavirus disease 2019 (COVID-19) led to air pollutant emission reductions. While the COVID-19 lockdown impacts on both trace gas and total particulate pollutants have been widely investigated, secondary aerosol formation from trace gases remains unclear. To that end, we quantify the COVID-19 lockdown impacts on NOx and SO2 emissions and sulfate-nitrate-ammonium aerosols using multiconstituent satellite data assimilation and model simulations. We find that anthropogenic emissions over major polluted regions were reduced by 19 to 25% for NOx and 14 to 20% for SO2 during April 2020. These emission reductions led to 8 to 21% decreases in sulfate and nitrate aerosols over highly polluted areas, corresponding to >34% of the observed aerosol optical depth declines and a global aerosol radiative forcing of +0.14 watts per square meter relative to business-as-usual scenario. These results point to the critical importance of secondary aerosol pollutants in quantifying climate impacts of future mitigation measures.
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Affiliation(s)
- Takashi Sekiya
- Japan Agency for Marine-Earth Science and Technology, Yokohama, Japan
| | - Kazuyuki Miyazaki
- Japan Agency for Marine-Earth Science and Technology, Yokohama, Japan
- Jet Propulsion Laboratory/California Institute for Technology, Pasadena, CA, USA
| | - Henk Eskes
- Royal Netherlands Meteorological Institute (KNMI), De Bilt, Netherlands
| | - Kevin Bowman
- Jet Propulsion Laboratory/California Institute for Technology, Pasadena, CA, USA
- Joint Institute for Regional Earth System Science and Engineering, University of California, Los Angeles, CA, USA
| | - Kengo Sudo
- Japan Agency for Marine-Earth Science and Technology, Yokohama, Japan
- Graduate School of Environmental Studies, Nagoya University, Nagoya, Japan
| | - Yugo Kanaya
- Japan Agency for Marine-Earth Science and Technology, Yokohama, Japan
| | - Masayuki Takigawa
- Japan Agency for Marine-Earth Science and Technology, Yokohama, Japan
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11
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Wang J, Zhang Y, Zhang C, Wang Y, Zhou J, Whalley LK, Slater EJ, Dyson JE, Xu W, Cheng P, Han B, Wang L, Yu X, Wang Y, Woodward-Massey R, Lin W, Zhao W, Zeng L, Ma Z, Heard DE, Ye C. Validating HONO as an Intermediate Tracer of the External Cycling of Reactive Nitrogen in the Background Atmosphere. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2023; 57:5474-5484. [PMID: 36931264 DOI: 10.1021/acs.est.2c06731] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/18/2023]
Abstract
In the urban atmosphere, nitrogen oxide (NOx═NO + NO2)-related reactions dominate the formation of nitrous acid (HONO). Here, we validated an external cycling route of HONO and NOx, i.e., formation of HONO resulting from precursors other than NOx, in the background atmosphere. A chemical budget closure experiment of HONO and NOx was conducted at a background site on the Tibetan Plateau and provided direct evidence of the external cycling. An external daytime HONO source of 100 pptv h-1 was determined. Both soil emissions and photolysis of nitrate on ambient surfaces constituted likely candidate mechanisms characterizing this external source. The external source dominated the chemical production of NOx with HONO as an intermediate tracer. The OH production was doubled as a result of the external cycling. A high HONO/NOx ratio (0.31 ± 0.06) during the daytime was deduced as a sufficient condition for the external cycling. Literature review suggested the prevalence of high HONO/NOx ratios in various background environments, e.g., polar regions, pristine mountains, and forests. Our analysis validates the prevalence of external cycling in general background atmosphere and highlights the promotional role of external cycling regarding the atmospheric oxidative capacity.
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Affiliation(s)
- Jianshu Wang
- State Key Joint Laboratory for Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Yingjie Zhang
- State Key Joint Laboratory for Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Chong Zhang
- State Key Joint Laboratory for Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Yaru Wang
- State Key Joint Laboratory for Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Jiacheng Zhou
- Laboratory of Atmospheric Physico-Chemistry, Hefei Institutes of Physical Science Anhui Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Hefei 230031, Anhui, China
| | - Lisa K Whalley
- School of Chemistry, University of Leeds, Leeds LS2 9JT, U.K
| | - Eloise J Slater
- School of Chemistry, University of Leeds, Leeds LS2 9JT, U.K
| | - Joanna E Dyson
- School of Chemistry, University of Leeds, Leeds LS2 9JT, U.K
| | - Wanyun Xu
- Chinese Academy of Meteorological Science, Institute of Atmospheric Composition, Beijing 100081, China
| | - Peng Cheng
- Institute of Mass Spectrometry and Atmospheric Environment, Jinan University, Guangzhou 510632, China
| | - Baobin Han
- Institute of Mass Spectrometry and Atmospheric Environment, Jinan University, Guangzhou 510632, China
| | - Lifan Wang
- State Key Joint Laboratory for Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Xuena Yu
- State Key Joint Laboratory for Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Youfeng Wang
- State Key Joint Laboratory for Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Robert Woodward-Massey
- State Key Joint Laboratory for Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Weili Lin
- Key Laboratory of Ecology and Environment in Minority Areas, Minzu University of China, National Ethnic Affairs Commission, Beijing 100081, China
| | - Weixiong Zhao
- Laboratory of Atmospheric Physico-Chemistry, Hefei Institutes of Physical Science Anhui Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Hefei 230031, Anhui, China
| | - Limin Zeng
- State Key Joint Laboratory for Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Zhiqiang Ma
- China Meteorological Administration Beijing Institute of Urban Meteorology, Beijing 100089, China
| | - Dwayne E Heard
- School of Chemistry, University of Leeds, Leeds LS2 9JT, U.K
| | - Chunxiang Ye
- State Key Joint Laboratory for Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
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12
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Sarwar G, Hogrefe C, Henderson BH, Foley K, Mathur R, Murphy B, Ahmed S. Characterizing variations in ambient PM 2.5 concentrations at the U.S. Embassy in Dhaka, Bangladesh using observations and the CMAQ modeling system. ATMOSPHERIC ENVIRONMENT (OXFORD, ENGLAND : 1994) 2023; 296:119587. [PMID: 37854171 PMCID: PMC10581604 DOI: 10.1016/j.atmosenv.2023.119587] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/20/2023]
Abstract
We analyze hourly PM2.5 (particles with an aerodynamic diameter of ≤ 2.5 μm) concentrations measured at the U.S. Embassy in Dhaka over the 2016 - 2021 time period and find that concentrations are seasonally dependent with the highest occurring in winter and the lowest in monsoon seasons. Mean winter PM2.5 concentrations reached ~165-175 μg/m3 while monsoon concentrations remained ~30-35 μg/m3. Annual mean PM2.5 concentration reached ~5-6 times greater than the Bangladesh annual PM2.5 standard of 15 μg/m3. The number of days exceeding the daily PM2.5 standard of 65 μg/m3 in a year approached nearly 50%. Daily-mean PM2.5 concentrations remained elevated (>65 μg/m3) for more than 80 consecutive days. Night-time concentrations were greater than daytime concentrations. The comparison of results obtained from the Community Multiscale Air Quality (CMAQ) model simulations over the Northern Hemisphere using 108-km horizontal grids with observed data suggests that the model can reproduce the seasonal variation of observed data but underpredicts observed PM2.5 in winter months with a normalized mean bias of 13-32%. In the model, organic aerosol is the largest component of PM2.5, of which secondary organic aerosol plays a dominant role. Transboundary pollution has a large impact on the PM2.5 concentration in Dhaka, with an annual mean contribution of ~40 μg/m3.
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Affiliation(s)
- Golam Sarwar
- Center for Environmental Measurement & Modeling, U.S. Environmental Protection Agency, Research Triangle Park, NC 27711, USA
| | - Christian Hogrefe
- Center for Environmental Measurement & Modeling, U.S. Environmental Protection Agency, Research Triangle Park, NC 27711, USA
| | - Barron H. Henderson
- Office of Air Quality Planning and Standards, U.S. Environmental Protection Agency, Research Triangle Park, NC 27711, USA
| | - Kristen Foley
- Center for Environmental Measurement & Modeling, U.S. Environmental Protection Agency, Research Triangle Park, NC 27711, USA
| | - Rohit Mathur
- Center for Environmental Measurement & Modeling, U.S. Environmental Protection Agency, Research Triangle Park, NC 27711, USA
| | - Ben Murphy
- Center for Environmental Measurement & Modeling, U.S. Environmental Protection Agency, Research Triangle Park, NC 27711, USA
| | - Shoeb Ahmed
- Department of Chemical Engineering, Bangladesh University of Engineering and Technology, Dhaka-1000, Bangladesh
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13
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Wang R, Bei N, Pan Y, Wu J, Liu S, Li X, Yu J, Jiang Q, Tie X, Li G. Urgency of controlling agricultural nitrogen sources to alleviate summertime air pollution in the North China Plain. CHEMOSPHERE 2023; 311:137124. [PMID: 36351470 DOI: 10.1016/j.chemosphere.2022.137124] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/30/2022] [Revised: 08/31/2022] [Accepted: 10/31/2022] [Indexed: 06/16/2023]
Abstract
Agricultural nitrogen sources (ANS) have played an increasingly important role in the air quality since ANS emission controls are much weaker than those for fossil fuel combustion sources due to the increasing food demand. However, ANS emissions are highly uncertain due to stochastic agricultural management activities and limited field measurements, and impacts of ANS on the air quality remain elusive. In the study, the WRF-Chem model has been used to investigate ANS shares in near surface air pollutant concentrations during a growing season in the North China Plain (NCP), with ANS emissions constrained by satellite retrievals. Soil NOX and agricultural NH3 emissions are about 36% and 92% of their total emissions during the growing season. Sensitivity studies demonstrate that ANS count 16.9 μg m-3 (9.9%) of the mean maximum daily average 8-h ozone concentrations (MDA8 [O3]) and 8.9 μg m-3 (31.7%) of fine particulate matter concentrations ([PM2.5]) on average in the NCP. Additionally, the contributions of ANS to MDA8 [O3] and [PM2.5] increase with the deterioration of air pollution in cities. A 50% emission reduction in ANS decreases MDA8 [O3] ([PM2.5]) from 4.2% to 8.4% (from 19.7% to 31.9%) when the air quality changes from being lightly to heavily polluted in terms of MDA8 [O3] (hourly [PM2.5]). Without fossil fuel combustion emissions, the simulated average MDA8 [O3] and [PM2.5] are 111.7 and 8.2 μg m-3 in cities of the NCP, respectively, exceeding the new standards from the World Health Organization. Our study highlights important contributions of ANS to air quality and the urgency of ANS emission abatement for air pollution alleviation during summertime in the NCP.
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Affiliation(s)
- Ruonan Wang
- Key Lab of Aerosol Chemistry and Physics, SKLLQG, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an, 710061, China; University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Naifang Bei
- School of Human Settlements and Civil Engineering, Xi'an Jiaotong University, Xi'an, 710049, China
| | - Yuepeng Pan
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China
| | - Jiarui Wu
- Key Lab of Aerosol Chemistry and Physics, SKLLQG, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an, 710061, China
| | - Suixin Liu
- Key Lab of Aerosol Chemistry and Physics, SKLLQG, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an, 710061, China
| | - Xia Li
- Key Lab of Aerosol Chemistry and Physics, SKLLQG, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an, 710061, China
| | - Jiaoyang Yu
- Key Lab of Aerosol Chemistry and Physics, SKLLQG, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an, 710061, China
| | - Qian Jiang
- Key Lab of Aerosol Chemistry and Physics, SKLLQG, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an, 710061, China
| | - Xuexi Tie
- Key Lab of Aerosol Chemistry and Physics, SKLLQG, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an, 710061, China
| | - Guohui Li
- Key Lab of Aerosol Chemistry and Physics, SKLLQG, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an, 710061, China; CAS Center for Excellence in Quaternary Science and Global Change, Xi'an, 710061, China.
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14
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Gao Z, Ivey CE, Blanchard CL, Do K, Lee SM, Russell AG. Separating emissions and meteorological impacts on peak ozone concentrations in Southern California using generalized additive modeling. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2022; 307:119503. [PMID: 35598815 DOI: 10.1016/j.envpol.2022.119503] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/17/2022] [Revised: 04/29/2022] [Accepted: 05/16/2022] [Indexed: 06/15/2023]
Abstract
Ozone levels have been declining in the Los Angeles, CA, USA area for the last four decades, but there was a recent uptick in the 4th highest daily maximum 8-h (MDA8) ozone concentrations from 2014 to 2018 despite continued reductions in the estimated precursor emissions. In this study, we assess the emissions and meteorological impacts on the 4th highest MDA8 ozone concentrations to better understand the factors affecting the observed MDA8 ozone using a two-step generalized additive model (GAM)/least squares approach applied to the South Coast Air Basin (SoCAB) for the 1990 to 2019 period. The GAM model includes emissions, meteorological factors, large-scale climate variables, date, and the interactions between meteorology and emissions. A least squares method was applied to the GAM output to better capture the 4th highest MDA8 ozone. The resulting two-step model had an R2 of 0.98 and a slope of 1 between the observed and predicted 4th highest MDA8 ozone. Emissions and the interactions between the maximum temperature and emissions explain most of the variation in the peak MDA8 ozone concentrations. Declining emissions have lowered the 4th highest MDA8 ozone concentration. Meteorology explains the higher than expected 4th-high, ozone levels observed in 2014-2018, indicating that meteorology was a stronger forcer than the continued reductions in emissions during that time period. The model was applied to estimate future ozone levels. Meteorology developed from climate modeling of the representative concentration pathway (RCP) scenarios, and two sets of emissions were used in the application. The modeling results indicated climate trends will push ozone levels slightly higher if no further emissions reductions are realized and that of two emissions trajectories modeled, the more stringent is required to reliably meet the federal ozone standard given annual meteorological variability.
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Affiliation(s)
- Ziqi Gao
- School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA, USA.
| | - Cesunica E Ivey
- Department of Civil and Environmental Engineering, University of California, Berkeley, CA, USA
| | | | - Khanh Do
- Department of Chemical and Environmental Engineering, University of California, Riverside, CA, USA; Center for Environmental Research and Technology, Riverside, CA, USA
| | - Sang-Mi Lee
- South Coast Air Quality Management District, Diamond Bar, CA, USA
| | - Armistead G Russell
- School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA, USA
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15
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Luo L, Ran L, Rasool QZ, Cohan DS. Integrated Modeling of U.S. Agricultural Soil Emissions of Reactive Nitrogen and Associated Impacts on Air Pollution, Health, and Climate. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2022; 56:9265-9276. [PMID: 35712939 DOI: 10.1021/acs.est.1c08660] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Agricultural soils are leading sources of reactive nitrogen (Nr) species including nitrogen oxides (NOx), ammonia (NH3), and nitrous oxide (N2O). The propensity of NOx and NH3 to generate ozone and fine particulate matter and associated impacts on health are highly variable, whereas the climate impacts of long-lived N2O are independent of emission timing and location. However, these impacts have rarely been compared on a spatially resolved monetized basis. In this study, we update the nitrogen scheme in an agroecosystem model to simulate the Nr emissions from fertilized soils across the contiguous United States. We then apply a reduced-form air pollution health effect model to assess air quality impacts from NOx and NH3 and a social cost of N2O to assess the climate impacts. Assuming an $8.2 million value of a statistical life and a $13,100/ton social cost of N2O, the air quality impacts are a factor of ∼7 to 15 times as large as the climate impacts in heavily populated coastal regions, whereas the ratios are closer to 2.5 in sparsely populated regions. Our results show that air pollution, health, and climate should be considered jointly in future assessments of how farming practices affect Nr emissions.
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Affiliation(s)
- Lina Luo
- Department of Civil and Environmental Engineering, Rice University, Houston, Texas 77005, United States
| | - Limei Ran
- Nature Resources Conservation Service, United States Department of Agriculture, Greensboro, North Carolina 27401, United States
| | - Quazi Z Rasool
- Pacific Northwest National Laboratory, Richland, Washington 99352, United States
| | - Daniel S Cohan
- Department of Civil and Environmental Engineering, Rice University, Houston, Texas 77005, United States
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16
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Wang Y, Yao Z, Zheng X, Subramaniam L, Butterbach-Bahl K. A synthesis of nitric oxide emissions across global fertilized croplands from crop-specific emission factors. GLOBAL CHANGE BIOLOGY 2022; 28:4395-4408. [PMID: 35403777 DOI: 10.1111/gcb.16193] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/21/2022] [Accepted: 03/25/2022] [Indexed: 06/14/2023]
Abstract
Nitrogen (N) fertilizer application to agricultural soils results in substantial emissions of nitric oxide (NO), a key substance in tropospheric chemistry involved in climate forcing and air pollution. However, the estimates of global cropland NO emissions remain uncertain due to a lack of information on direct NO emission factors (EFd s) of applied N for various cropping systems at seasonal or annual scales. Here we quantified the crop-specific seasonal and annual-scale NO EFd s through synthesizing 1094 measurements from 125 field-based studies worldwide. The global mean crop-specific seasonal EFd was 0.53%, with the highest for vegetables (0.75%). Among cereal crops, the EFd of maize (0.45%) or wheat (0.47%) was about three times higher than for rice (0.12%). At annual scale, the mean EFd across all cropping systems was 0.58%, with tea plantations having the highest (1.54%). For other cropping systems, the annual-scale EFd s ranged from 0.02% to 1.07%. Besides crop type, also soil organic carbon, total N, and pH as well as N fertilizer type were the main factors explaining the variations of NO EFd s. Based on obtained specific EFd s for each crop type, we estimated that NO emissions due to the use of synthetic fertilizers from global croplands are about 0.42-0.62 Tg N year-1 . Our budgets are relatively lower if compared to estimates derived by the use of IPCC defaults for NO emissions (0.72-1.66 Tg N year-1 ) or reported elsewhere (0.67-1.04 Tg N year-1 ). In our estimates, cash crops (vegetable, tea and orchard), which cover only 9% of the world cropland area, contributed about 31% to total NO emissions from global fertilized croplands. Overall, our meta-analysis provides improved crop-specific NO EFd s reflecting current stage of knowledge. The work also highlights the relative importance of cash crop production as sources for atmospheric NO, that is, agricultural systems on which mitigation efforts may focus.
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Affiliation(s)
- Yan Wang
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, PR China
- College of Earth and Planetary Science, University of Chinese Academy of Sciences, Beijing, PR China
| | - Zhisheng Yao
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, PR China
| | - Xunhua Zheng
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, PR China
- College of Earth and Planetary Science, University of Chinese Academy of Sciences, Beijing, PR China
| | - Logapragasan Subramaniam
- Institute for Meteorology and Climate Research, Atmospheric Environmental Research, Karlsruhe Institute of Technology, Garmisch-Partenkirchen, Germany
| | - Klaus Butterbach-Bahl
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, PR China
- Institute for Meteorology and Climate Research, Atmospheric Environmental Research, Karlsruhe Institute of Technology, Garmisch-Partenkirchen, Germany
- Land-CRAFT, Department of Agroecology, Aarhus University, Tjele, Denmark
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17
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Chen W, Guenther AB, Jia S, Mao J, Yan F, Wang X, Shao M. Synergistic effects of biogenic volatile organic compounds and soil nitric oxide emissions on summertime ozone formation in China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 828:154218. [PMID: 35245546 DOI: 10.1016/j.scitotenv.2022.154218] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/21/2021] [Revised: 02/24/2022] [Accepted: 02/25/2022] [Indexed: 06/14/2023]
Abstract
Natural emissions play a key role in modulating the formation of ground-level ozone (O3), especially emissions of biogenic volatile organic compounds (BVOCs) and soil nitric oxide (SNO), and their individual effects on O3 formation have been previously quantified and evaluated. However, their synergistic effects remain unclear and have not yet been well assessed. By applying the Weather Research and Forecasting (WRF) model coupled with the Chemistry-Model of Emissions of Gases and Aerosols from Nature (WRF/Chem-MEGAN) model, this study reveals that in the presence of sufficient BVOC emissions, which act as a fuel, SNO emissions act as a fuel additive and promote the chemical reactions of BVOCs and the subsequent production of O3. Consequently, the synergistic effects of BVOC and SNO emissions on summertime O3 production surpassed the sum of their individual effects by as much as 10-20 μg m-3 in eastern China in 2014. In order to reduce O3 concentration to a level corresponding to no natural emissions of BVOC or SNO (i.e., the BASE scenario), the anthropogenic volatile organic compound (AVOC) emissions in the scenario considers BVOC and SNO emissions must be reduced by 1.76 times that of the BASE scenario. This study demonstrates that the synergistic effects of BVOC and SNO emissions can impede ground-level O3 regulation and can subsequently impose stricter requirements on anthropogenic precursor emission control in China. The results of this study can also inform efforts in other regions that are still combating ground-level O3 pollution.
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Affiliation(s)
- Weihua Chen
- Guangdong-Hong Kong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Institute for Environmental and Climate Research, Jinan University, Guangzhou 510632, China
| | - Alex B Guenther
- Department of Earth System Science, University of California, Irvine, CA 92697, USA
| | - Shiguo Jia
- School of Atmospheric Sciences, Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies, Sun Yat-sen University, Guangzhou 510275, China
| | - Jingying Mao
- Guangdong-Hong Kong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Institute for Environmental and Climate Research, Jinan University, Guangzhou 510632, China
| | - Fenghua Yan
- Guangdong-Hong Kong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Institute for Environmental and Climate Research, Jinan University, Guangzhou 510632, China
| | - Xuemei Wang
- Guangdong-Hong Kong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Institute for Environmental and Climate Research, Jinan University, Guangzhou 510632, China.
| | - Min Shao
- Guangdong-Hong Kong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Institute for Environmental and Climate Research, Jinan University, Guangzhou 510632, China.
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18
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Li Y, Wu W, Yang J, Cheng K, Smith P, Sun J, Xu X, Yue Q, Pan G. Exploring the environmental impact of crop production in China using a comprehensive footprint approach. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 824:153898. [PMID: 35182617 DOI: 10.1016/j.scitotenv.2022.153898] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/07/2021] [Revised: 01/25/2022] [Accepted: 02/11/2022] [Indexed: 06/14/2023]
Abstract
The carbon-nutrient-water cycles of farmland ecosystem not only provides support for crop production, but also has an impact on the environment. Comprehensively quantifying the impact of crop production on the environment can provide a basis for crop sustainable production. A series of environmental footprint approaches, including carbon footprint (CF), nitrogen footprint (NF) and water footprint (WF), were optimized to evaluate greenhouse gas (GHG) emissions, reactive nitrogen (Nr) loss and water resource consumption in crop production, and a comprehensive footprint method based on Endpoint modeling was proposed to evaluate the overall environmental impact of crop production in China. The CF, NF and WF of 28 forms of crop production varied from 1206.29 kg CO2 equivalent (CO2-eq) ha-1 of oil crops to 7326.37 kg CO2-eq ha-1 of fiber crops, 16.07 kg Nr-eq ha-1 of oil crops to 60.70 kg Nr-eq ha-1 of sugar crops, and 4032.04 m3 ha-1 oil crops to 12,476.28 m3 ha-1 of sugar crops, respectively. The contribution of each component to footprints varied greatly among different crops, and fertilizer manufacture, NH3 volatilization and green WF were generally the main contributors of CF, NF and WF, respectively. The total GHG emissions, Nr loss and water consumption were estimated to be 670.11 Tg CO2-eq, 5.50 Tg Nr-eq and 837.06 G m3 for all crop production of China. The greenhouse vegetable with the highest area-scaled comprehensive footprint was 4.5 times that of the oil crops which had the lowest one. The contribution of crop production to the corresponding environmental impact in China was as low as 3.7%, of which NH3 volatilization contributed 48% and grain production contributed 72%. Mineral N fertilization was the main driver of the variation of comprehensive footprint between provinces, with reduction of N fertilizer application as an important way to reduce the environmental impact of crop production.
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Affiliation(s)
- Yunpeng Li
- Institute of Resource, Ecosystem and Environment of Agriculture, Center of Climate Change and Agriculture, Nanjing Agricultural University, 1 Weigang, Nanjing, Jiangsu 210095, China
| | - Wenao Wu
- Institute of Resource, Ecosystem and Environment of Agriculture, Center of Climate Change and Agriculture, Nanjing Agricultural University, 1 Weigang, Nanjing, Jiangsu 210095, China
| | - Jiaxin Yang
- Institute of Resource, Ecosystem and Environment of Agriculture, Center of Climate Change and Agriculture, Nanjing Agricultural University, 1 Weigang, Nanjing, Jiangsu 210095, China
| | - Kun Cheng
- Institute of Resource, Ecosystem and Environment of Agriculture, Center of Climate Change and Agriculture, Nanjing Agricultural University, 1 Weigang, Nanjing, Jiangsu 210095, China.
| | - Pete Smith
- Institute of Biological and Environmental Sciences, School of Biological Sciences, University of Aberdeen, 23 St Machar Drive, Aberdeen AB24 3UU, UK
| | - Jianfei Sun
- Institute of Resource, Ecosystem and Environment of Agriculture, Center of Climate Change and Agriculture, Nanjing Agricultural University, 1 Weigang, Nanjing, Jiangsu 210095, China
| | - Xiangrui Xu
- Institute of Resource, Ecosystem and Environment of Agriculture, Center of Climate Change and Agriculture, Nanjing Agricultural University, 1 Weigang, Nanjing, Jiangsu 210095, China
| | - Qian Yue
- Key Laboratory for Crop and Animal Integrated Farming of Ministry of Agriculture and Rural Affairs, Institute of Agricultural Resources and Environment, Jiangsu Academy of Agricultural Sciences, Nanjing 210014, China
| | - Genxing Pan
- Institute of Resource, Ecosystem and Environment of Agriculture, Center of Climate Change and Agriculture, Nanjing Agricultural University, 1 Weigang, Nanjing, Jiangsu 210095, China
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19
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Zhu Q, Laughner JL, Cohen RC. Combining Machine Learning and Satellite Observations to Predict Spatial and Temporal Variation of near Surface OH in North American Cities. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2022; 56:7362-7371. [PMID: 35302754 DOI: 10.1021/acs.est.1c05636] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
The hydroxyl radical (OH) is the primary cleansing agent in the atmosphere. The abundance of OH in cities initiates the removal of local pollutants; therefore, it serves as the key species describing the urban chemical environment. We propose a machine learning (ML) approach as an efficient alternative to OH simulation using a computationally expensive chemical transport model. The ML model is trained on the parameters simulated from the WRF-Chem model, and it suggests that six predictive parameters are capable of explaining 76% of the OH variability. The parameters are the tropospheric NO2 column, the tropospheric HCHO column, J(O1D), H2O, temperature, and pressure. We then use observations of the tropospheric NO2 column and HCHO column from OMI as input to the ML model to enable measurement-based prediction of daily near surface OH at 1:30 pm local time across 49 North American cities over the course of 10 years between 2005 and 2014. The result is validated by comparing the OH predictions to measurements of isoprene, which has a source that is uncorrelated with OH and is removed rapidly and almost exclusively by OH in the daytime. We demonstrate that the predicted OH is, as expected, anticorrelated with isoprene. We also show that this ML model is consistent with our understanding of OH chemistry given the solely data-driven nature.
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Affiliation(s)
- Qindan Zhu
- Department of Earth and Planetary Science, University of California at Berkeley, Berkeley, California 94720, United States
| | - Joshua L Laughner
- Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, California 91125, United States
| | - Ronald C Cohen
- Department of Earth and Planetary Science, University of California at Berkeley, Berkeley, California 94720, United States
- Department of Chemistry, University of California at Berkeley, Berkeley, California 94720, United States
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20
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Song W, Liu XY, Houlton BZ, Liu CQ. Isotopic constraints confirm the significant role of microbial nitrogen oxides emissions from the land and ocean environment. Natl Sci Rev 2022; 9:nwac106. [PMID: 36128454 PMCID: PMC9477198 DOI: 10.1093/nsr/nwac106] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2022] [Revised: 05/28/2022] [Accepted: 05/31/2022] [Indexed: 12/02/2022] Open
Abstract
Nitrogen oxides (NOx, the sum of nitric oxide (NO) and N dioxide (NO2)) emissions and deposition have increased markedly over the past several decades, resulting in many adverse outcomes in both terrestrial and oceanic environments. However, because the microbial NOx emissions have been substantially underestimated on the land and unconstrained in the ocean, the global microbial NOx emissions and their importance relative to the known fossil-fuel NOx emissions remain unclear. Here we complied data on stable N isotopes of nitrate in atmospheric particulates over the land and ocean to ground-truth estimates of NOx emissions worldwide. By considering the N isotope effect of NOx transformations to particulate nitrate combined with dominant NOx emissions in the land (coal combustion, oil combustion, biomass burning and microbial N cycle) and ocean (oil combustion, microbial N cycle), we demonstrated that microbial NOx emissions account for 24 ± 4%, 58 ± 3% and 31 ± 12% in the land, ocean and global environment, respectively. Corresponding amounts of microbial NOx emissions in the land (13.6 ± 4.7 Tg N yr−1), ocean (8.8 ± 1.5 Tg N yr−1) and globe (22.5 ± 4.7 Tg N yr−1) are about 0.5, 1.4 and 0.6 times on average those of fossil-fuel NOx emissions in these sectors. Our findings provide empirical constraints on model predictions, revealing significant contributions of the microbial N cycle to regional NOx emissions into the atmospheric system, which is critical information for mitigating strategies, budgeting N deposition and evaluating the effects of atmospheric NOx loading on the world.
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Affiliation(s)
- Wei Song
- School of Earth System Science, Tianjin University , Tianjin , 300072 , China
| | - Xue-Yan Liu
- School of Earth System Science, Tianjin University , Tianjin , 300072 , China
| | - Benjamin Z Houlton
- Department of Global Development and Department of Ecology and Evolutionary Biology, Cornell University , Ithaca, NY 14850 , USA
| | - Cong-Qiang Liu
- School of Earth System Science, Tianjin University , Tianjin , 300072 , China
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21
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Wang R, Bei N, Wu J, Li X, Liu S, Yu J, Jiang Q, Tie X, Li G. Cropland nitrogen dioxide emissions and effects on the ozone pollution in the North China plain. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2022; 294:118617. [PMID: 34863895 DOI: 10.1016/j.envpol.2021.118617] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/04/2021] [Revised: 11/25/2021] [Accepted: 11/30/2021] [Indexed: 06/13/2023]
Abstract
Soil nitrogen dioxide (NOX = NO2 + NO) emissions have been measured and estimated to be the second most significant contributor to the NOX burden following the fossil fuel combustion source globally. NOX emissions from croplands are subject to being underestimated or overlooked in air pollution simulations of regional atmospheric chemistry models. With constraints of ground and space observations of NO2, the WRF-Chem model is used to investigate the cropland NOX emission and its contribution to the near-surface ozone (O3) pollution in North China Plain (NCP) during a growing season as a case study. Model simulations have revealed that the cropland NOX emissions are underestimated by around 80% without constraints of satellite measured NO2 column densities. The biogenic NOX source is estimated to account for half of the anthropogenic NOX emissions in the NCP during the growing season. Additionally, the cropland NOX source contributes around 5.0% of the maximum daily average 8h O3 concentration and 27.7% of NO2 concentration in the NCP. Our results suggest the agriculture NOX emission exerts non-negligible impacts on the summertime air quality and needs to be considered when designing emission abatement strategies.
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Affiliation(s)
- Ruonan Wang
- Key Lab of Aerosol Chemistry and Physics, SKLLQG, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an, 710061, China; University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Naifang Bei
- School of Human Settlements and Civil Engineering, Xi'an Jiaotong University, Xi'an, 710049, China
| | - Jiarui Wu
- Key Lab of Aerosol Chemistry and Physics, SKLLQG, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an, 710061, China
| | - Xia Li
- Key Lab of Aerosol Chemistry and Physics, SKLLQG, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an, 710061, China
| | - Suixin Liu
- Key Lab of Aerosol Chemistry and Physics, SKLLQG, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an, 710061, China
| | - Jiaoyang Yu
- Key Lab of Aerosol Chemistry and Physics, SKLLQG, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an, 710061, China
| | - Qian Jiang
- Key Lab of Aerosol Chemistry and Physics, SKLLQG, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an, 710061, China
| | - Xuexi Tie
- Key Lab of Aerosol Chemistry and Physics, SKLLQG, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an, 710061, China
| | - Guohui Li
- Key Lab of Aerosol Chemistry and Physics, SKLLQG, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an, 710061, China; CAS Center for Excellence in Quaternary Science and Global Change, Xi'an, 710061, China.
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22
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Souri AH, Chance K, Bak J, Nowlan CR, Abad GG, Jung Y, Wong DC, Mao J, Liu X. Unraveling pathways of elevated ozone induced by the 2020 lockdown in Europe by an observationally constrained regional model using TROPOMI. ATMOSPHERIC CHEMISTRY AND PHYSICS 2021; 21:1-19. [PMID: 34987561 PMCID: PMC8721815 DOI: 10.5194/acp-21-18227-2021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Questions about how emissions are changing during the COVID-19 lockdown periods cannot be answered by observations of atmospheric trace gas concentrations alone, in part due to simultaneous changes in atmospheric transport, emissions, dynamics, photochemistry, and chemical feedback. A chemical transport model simulation benefiting from a multi-species inversion framework using well-characterized observations should differentiate those influences enabling to closely examine changes in emissions. Accordingly, we jointly constrain NO x and VOC emissions using well-characterized TROPOspheric Monitoring Instrument (TROPOMI) HCHO and NO2 columns during the months of March, April, and May 2020 (lockdown) and 2019 (baseline). We observe a noticeable decline in the magnitude of NO x emissions in March 2020 (14 %-31 %) in several major cities including Paris, London, Madrid, and Milan, expanding further to Rome, Brussels, Frankfurt, Warsaw, Belgrade, Kyiv, and Moscow (34 %-51 %) in April. However, NO x emissions remain at somewhat similar values or even higher in some portions of the UK, Poland, and Moscow in March 2020 compared to the baseline, possibly due to the timeline of restrictions. Comparisons against surface monitoring stations indicate that the constrained model underrepresents the reduction in surface NO2. This underrepresentation correlates with the TROPOMI frequency impacted by cloudiness. During the month of April, when ample TROPOMI samples are present, the surface NO2 reductions occurring in polluted areas are described fairly well by the model (model: -21 ± 17 %, observation: -29 ± 21 %). The observational constraint on VOC emissions is found to be generally weak except for lower latitudes. Results support an increase in surface ozone during the lockdown. In April, the constrained model features a reasonable agreement with maximum daily 8 h average (MDA8) ozone changes observed at the surface (r = 0.43), specifically over central Europe where ozone enhancements prevail (model: +3.73 ± 3.94 %, + 1.79 ppbv, observation: +7.35 ± 11.27 %, +3.76 ppbv). The model suggests that physical processes (dry deposition, advection, and diffusion) decrease MDA8 surface ozone in the same month on average by -4.83 ppbv, while ozone production rates dampened by largely negative J NO 2 [ NO 2 ] - k NO + O 3 [ NO ] [ O 3 ] become less negative, leading ozone to increase by +5.89 ppbv. Experiments involving fixed anthropogenic emissions suggest that meteorology contributes to 42 % enhancement in MDA8 surface ozone over the same region with the remaining part (58 %) coming from changes in anthropogenic emissions. Results illustrate the capability of satellite data of major ozone precursors to help atmospheric models capture ozone changes induced by abrupt emission anomalies.
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Affiliation(s)
- Amir H. Souri
- Atomic and Molecular Physics (AMP) Division, Harvard–Smithsonian Center for Astrophysics, Cambridge, MA, USA
| | - Kelly Chance
- Atomic and Molecular Physics (AMP) Division, Harvard–Smithsonian Center for Astrophysics, Cambridge, MA, USA
| | - Juseon Bak
- Institute of Environmental Studies, Pusan National University, Busan, South Korea
| | - Caroline R. Nowlan
- Atomic and Molecular Physics (AMP) Division, Harvard–Smithsonian Center for Astrophysics, Cambridge, MA, USA
| | - Gonzalo González Abad
- Atomic and Molecular Physics (AMP) Division, Harvard–Smithsonian Center for Astrophysics, Cambridge, MA, USA
| | - Yeonjin Jung
- Atomic and Molecular Physics (AMP) Division, Harvard–Smithsonian Center for Astrophysics, Cambridge, MA, USA
| | - David C. Wong
- US Environmental Protection Agency, Center for Environmental Measurement & Modeling, Research Triangle Park, NC, USA
| | - Jingqiu Mao
- Geophysical Institute, University of Alaska Fairbanks, Fairbanks, AK, USA
- Department of Chemistry and Biochemistry, University of Alaska Fairbanks, Fairbanks, AK, USA
| | - Xiong Liu
- Atomic and Molecular Physics (AMP) Division, Harvard–Smithsonian Center for Astrophysics, Cambridge, MA, USA
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23
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Xu JW, Martin RV, Evans GJ, Umbrio D, Traub A, Meng J, van Donkelaar A, You H, Kulka R, Burnett RT, Godri Pollitt KJ, Weichenthal S. Predicting Spatial Variations in Multiple Measures of Oxidative Burden for Outdoor Fine Particulate Air Pollution across Canada. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2021; 55:9750-9760. [PMID: 34241996 DOI: 10.1021/acs.est.1c01210] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
Fine particulate air pollution (PM2.5) is a leading contributor to the overall global burden of disease. Traditionally, outdoor PM2.5 has been characterized using mass concentrations which treat all particles as equally harmful. Oxidative potential (OP) (per μg) and oxidative burden (OB) (per m3) are complementary metrics that estimate the ability of PM2.5 to cause oxidative stress, which is an important mechanism in air pollution health effects. Here, we provide the first national estimates of spatial variations in multiple measures (glutathione, ascorbate, and dithiothreitol depletion) of annual median outdoor PM2.5 OB across Canada. To do this, we combined a large database of ground-level OB measurements collected monthly prospectively across Canada for 2 years (2016-2018) with PM2.5 components estimated using a chemical transport model (GEOS-Chem) and satellite aerosol observations. Our predicted ground-level OB values of all three methods were consistent with ground-level observations (cross-validation R2 = 0.63-0.74). We found that forested regions and urban areas had the highest OB, predicted primarily by black carbon and organic carbon from wildfires and transportation sources. Importantly, the dominant components associated with OB were different than those contributing to PM2.5 mass concentrations (secondary inorganic aerosol); thus, OB metrics may better indicate harmful components and sources on health than the bulk PM2.5 mass, reinforcing that OB estimates can complement the existing PM2.5 data in future national-level epidemiological studies.
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Affiliation(s)
- Jun-Wei Xu
- Department of Physics and Atmospheric Science, Dalhousie University, 6310 Coburg Road, Halifax, Nova Scotia B3H 4R2, Canada
| | - Randall V Martin
- Department of Physics and Atmospheric Science, Dalhousie University, 6310 Coburg Road, Halifax, Nova Scotia B3H 4R2, Canada
- Department of Energy, Environmental & Chemical Engineering, Washington University in St. Louis, 1 Brookings Drive, St. Louis, Missouri 63130, United States
- Harvard-Smithsonian Center for Astrophysics, 60 Garden Street, Cambridge, Massachusetts 02138, United States
| | - Greg J Evans
- Southern Ontario Centre for Atmospheric Aerosol Research, University of Toronto, 200 College Street, Toronto, Ontario M5S 3E5, Canada
- Dalla Lana School of Public Health, University of Toronto, 480 University Avenue, Toronto, Ontario M5G 1V2, Canada
| | - Dana Umbrio
- Southern Ontario Centre for Atmospheric Aerosol Research, University of Toronto, 200 College Street, Toronto, Ontario M5S 3E5, Canada
| | - Alison Traub
- Southern Ontario Centre for Atmospheric Aerosol Research, University of Toronto, 200 College Street, Toronto, Ontario M5S 3E5, Canada
| | - Jun Meng
- Department of Physics and Atmospheric Science, Dalhousie University, 6310 Coburg Road, Halifax, Nova Scotia B3H 4R2, Canada
| | - Aaron van Donkelaar
- Department of Physics and Atmospheric Science, Dalhousie University, 6310 Coburg Road, Halifax, Nova Scotia B3H 4R2, Canada
- Department of Energy, Environmental & Chemical Engineering, Washington University in St. Louis, 1 Brookings Drive, St. Louis, Missouri 63130, United States
| | - Hongyu You
- Air Health Science Division, Health Canada, 269 Laurier Avenue West, Ottawa, Ontario K1A 0K0, Canada
| | - Ryan Kulka
- Air Health Science Division, Health Canada, 269 Laurier Avenue West, Ottawa, Ontario K1A 0K0, Canada
| | - Richard T Burnett
- Population Studies Division, Health Canada, 101 Tunney's Pasture Dr., Ottawa, Ontario K1A 0K9, Canada
| | - Krystal J Godri Pollitt
- Department of Environmental Health Sciences, Yale School of Public Health, 60 College Street, New Haven, Connecticut 06520, United States
| | - Scott Weichenthal
- Air Health Science Division, Health Canada, 269 Laurier Avenue West, Ottawa, Ontario K1A 0K0, Canada
- Department of Epidemiology, Biostatistics and Occupational Health, McGill University, 1020 Pine Avenue West, Montreal, Quebec H3A 1A2, Canada
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24
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Sha T, Ma X, Zhang H, Janechek N, Wang Y, Wang Y, Castro García L, Jenerette GD, Wang J. Impacts of Soil NO x Emission on O 3 Air Quality in Rural California. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2021; 55:7113-7122. [PMID: 33576617 DOI: 10.1021/acs.est.0c06834] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
Nitrogen oxides (NOx) are a key precursor in O3 formation. Although stringent anthropogenic NOx emission controls have been implemented since the early 2000s in the United States, several rural regions of California still suffer from O3 pollution. Previous findings suggest that soils are a dominant source of NOx emissions in California; however, a statewide assessment of the impacts of soil NOx emission (SNOx) on air quality is still lacking. Here we quantified the contribution of SNOx to the NOx budget and the effects of SNOx on surface O3 in California during summer by using WRF-Chem with an updated SNOx scheme, the Berkeley Dalhousie Iowa Soil NO Parameterization (BDISNP). The model with BDISNP shows a better agreement with TROPOMI NO2 columns, giving confidence in the SNOx estimates. We estimate that 40.1% of the state's total NOx emissions in July 2018 are from soils, and SNOx could exceed anthropogenic sources over croplands, which accounts for 50.7% of NOx emissions. Such considerable amounts of SNOx enhance the monthly mean NO2 columns by 34.7% (53.3%) and surface NO2 concentrations by 176.5% (114.0%), leading to an additional 23.0% (23.2%) of surface O3 concentration in California (cropland). Our results highlight the cobenefits of limiting SNOx to help improve air quality and human health in rural California.
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Affiliation(s)
- Tong Sha
- Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, Nanjing University of Information Science & Technology, Nanjing 210044, People's Republic of China
- Department of Chemical and Biochemical Engineering, Center for Global and Regional Environmental Research, and Iowa Technology Institute, University of Iowa, Iowa City, Iowa 52242, United States
| | - Xiaoyan Ma
- Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, Nanjing University of Information Science & Technology, Nanjing 210044, People's Republic of China
| | - Huanxin Zhang
- Department of Chemical and Biochemical Engineering, Center for Global and Regional Environmental Research, and Iowa Technology Institute, University of Iowa, Iowa City, Iowa 52242, United States
| | - Nathan Janechek
- Department of Chemical and Biochemical Engineering, Center for Global and Regional Environmental Research, and Iowa Technology Institute, University of Iowa, Iowa City, Iowa 52242, United States
| | - Yanyu Wang
- Department of Chemical and Biochemical Engineering, Center for Global and Regional Environmental Research, and Iowa Technology Institute, University of Iowa, Iowa City, Iowa 52242, United States
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), Department of Environmental Science and Engineering, Institute of Atmospheric Sciences, Fudan University, Shanghai 200438, People's Republic of China
| | - Yi Wang
- Department of Chemical and Biochemical Engineering, Center for Global and Regional Environmental Research, and Iowa Technology Institute, University of Iowa, Iowa City, Iowa 52242, United States
| | - Lorena Castro García
- Department of Chemical and Biochemical Engineering, Center for Global and Regional Environmental Research, and Iowa Technology Institute, University of Iowa, Iowa City, Iowa 52242, United States
| | - G Darrel Jenerette
- Department of Botany and Plant Sciences, University of California, Riverside, California 92521, United States
| | - Jun Wang
- Department of Chemical and Biochemical Engineering, Center for Global and Regional Environmental Research, and Iowa Technology Institute, University of Iowa, Iowa City, Iowa 52242, United States
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25
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Wang X, Fu TM, Zhang L, Cao H, Zhang Q, Ma H, Shen L, Evans MJ, Ivatt PD, Lu X, Chen Y, Zhang L, Feng X, Yang X, Zhu L, Henze DK. Sensitivities of Ozone Air Pollution in the Beijing-Tianjin-Hebei Area to Local and Upwind Precursor Emissions Using Adjoint Modeling. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2021; 55:5752-5762. [PMID: 33890767 DOI: 10.1021/acs.est.1c00131] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
Effective mitigation of surface ozone pollution entails detailed knowledge of the contributing precursors' sources. We use the GEOS-Chem adjoint model to analyze the precursors contributing to surface ozone in the Beijing-Tianjin-Hebei area (BTH) of China on days of different ozone pollution severities in June 2019. We find that BTH ozone on heavily polluted days is sensitive to local emissions, as well as to precursors emitted from the provinces south of BTH (Shandong, Henan, and Jiangsu, collectively the SHJ area). Heavy ozone pollution in BTH can be mitigated effectively by reducing NOx (from industrial processes and transportation), ≥C3 alkenes (from on-road gasoline vehicles and industrial processes), and xylenes (from paint use) emitted from both BTH and SHJ, as well as by reducing CO (from industrial processes, transportation, and power generation) and ≥C4 alkanes (from industrial processes, paint and solvent use, and on-road gasoline vehicles) emissions from SHJ. In addition, reduction of NOx, xylene, and ≥C3 alkene emissions within BTH would effectively decrease the number of BTH ozone-exceedance days. Our analysis pinpoint the key areas and activities for locally and regionally coordinated emission control efforts to improve surface ozone air quality in BTH.
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Affiliation(s)
- Xiaolin Wang
- Department of Atmospheric and Oceanic Sciences, School of Physics, Peking University, Beijing 100871, China
| | - Tzung-May Fu
- State Environmental Protection Key Laboratory of Integrated Surface Water-Groundwater Pollution Control, School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen, Guangdong 518055, China
- Guangdong Provincial Key Laboratory of Soil and Groundwater Pollution Control, School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen, Guangdong 518055, China
| | - Lin Zhang
- Department of Atmospheric and Oceanic Sciences, School of Physics, Peking University, Beijing 100871, China
| | - Hansen Cao
- Department of Mechanical Engineering, University of Colorado Boulder, Boulder, Colorado 80309, United States
| | - Qiang Zhang
- Ministry of Education Key Laboratory for Earth System Modeling, Center for Earth System Science, Tsinghua University, Beijing 100084, China
| | - Hanchen Ma
- Ministry of Education Key Laboratory for Earth System Modeling, Center for Earth System Science, Tsinghua University, Beijing 100084, China
| | - Lu Shen
- Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts 02138, United States
| | - Mathew J Evans
- Wolfson Atmospheric Chemistry Laboratories, Department of Chemistry, University of York, York YO10 5DD, U.K
- National Centre for Atmospheric Science, Department of Chemistry, University of York, York YO10 5DD, U.K
| | - Peter D Ivatt
- Wolfson Atmospheric Chemistry Laboratories, Department of Chemistry, University of York, York YO10 5DD, U.K
- National Centre for Atmospheric Science, Department of Chemistry, University of York, York YO10 5DD, U.K
| | - Xiao Lu
- Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts 02138, United States
| | - Youfan Chen
- Sichuan Academy of Environmental policy and planning, Chengdu, Sichuan 610041, China
| | - Lijuan Zhang
- State Environmental Protection Key Laboratory of Integrated Surface Water-Groundwater Pollution Control, School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen, Guangdong 518055, China
- Guangdong Provincial Key Laboratory of Soil and Groundwater Pollution Control, School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen, Guangdong 518055, China
- Shanghai Central Meteorological Observatory, Shanghai 200030, China
| | - Xu Feng
- Department of Atmospheric and Oceanic Sciences, School of Physics, Peking University, Beijing 100871, China
- State Environmental Protection Key Laboratory of Integrated Surface Water-Groundwater Pollution Control, School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen, Guangdong 518055, China
- Guangdong Provincial Key Laboratory of Soil and Groundwater Pollution Control, School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen, Guangdong 518055, China
| | - Xin Yang
- State Environmental Protection Key Laboratory of Integrated Surface Water-Groundwater Pollution Control, School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen, Guangdong 518055, China
- Guangdong Provincial Key Laboratory of Soil and Groundwater Pollution Control, School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen, Guangdong 518055, China
| | - Lei Zhu
- State Environmental Protection Key Laboratory of Integrated Surface Water-Groundwater Pollution Control, School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen, Guangdong 518055, China
- Guangdong Provincial Key Laboratory of Soil and Groundwater Pollution Control, School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen, Guangdong 518055, China
| | - Daven K Henze
- Department of Mechanical Engineering, University of Colorado Boulder, Boulder, Colorado 80309, United States
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Naimark JG, Fiore AM, Jin X, Wang Y, Klovenski E, Braneon C. Evaluating Drought Responses of Surface Ozone Precursor Proxies: Variations With Land Cover Type, Precipitation, and Temperature. GEOPHYSICAL RESEARCH LETTERS 2021; 48:e2020GL091520. [PMID: 35860786 PMCID: PMC9285578 DOI: 10.1029/2020gl091520] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/04/2020] [Revised: 02/02/2021] [Accepted: 03/05/2021] [Indexed: 06/15/2023]
Abstract
Prior work suggests drought exacerbates US air quality by increasing surface ozone concentrations. We analyze 2005-2015 tropospheric column concentrations of two trace gases that serve as proxies for surface ozone precursors retrieved from the OMI/Aura satellite: Nitrogen dioxide (ΩNO2; NOx proxy) and formaldehyde (ΩHCHO; VOC proxy). We find 3.5% and 7.7% summer drought enhancements (classified by SPEI) for ΩNO2 and ΩHCHO, respectively, corroborating signals previously extracted from ground-level observations. When we subset by land cover type, the strongest ΩHCHO drought enhancement (10%) occurs in the woody savannas of the Southeast US. By isolating the influences of precipitation and temperature, we infer that enhanced biogenic VOC emissions in this region increase ΩHCHO independently with both high temperature and low precipitation during drought. The strongest ΩNO2 drought enhancement (6.0%) occurs over Midwest US croplands and grasslands, which we infer to reflect the sensitivity of soil NOx emissions to temperature.
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Affiliation(s)
- Jacob G. Naimark
- Department of Earth and Environmental Sciences, Columbia CollegeColumbia UniversityNew YorkNYUSA
- Department of Earth and Environmental Sciences, Lamont‐Doherty Earth ObservatoryColumbia UniversityPalisadesNYUSA
| | - Arlene M. Fiore
- Department of Earth and Environmental Sciences, Lamont‐Doherty Earth ObservatoryColumbia UniversityPalisadesNYUSA
| | - Xiaomeng Jin
- Department of ChemistryUniversity of California BerkeleyBerkeleyNYUSA
| | - Yuxuan Wang
- Department of Earth and Atmospheric SciencesUniversity of HoustonHoustonTXUSA
| | - Elizabeth Klovenski
- Department of Earth and Atmospheric SciencesUniversity of HoustonHoustonTXUSA
| | - Christian Braneon
- NASA Goddard Institute for Space Studies (GISS)New YorkNYUSA
- SciSpaceLLCBethesdaMDUSA
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Wowra K, Zeller V, Schebek L. Nitrogen in Life Cycle Assessment (LCA) of agricultural crop production systems: Comparative analysis of regionalization approaches. THE SCIENCE OF THE TOTAL ENVIRONMENT 2021; 763:143009. [PMID: 33139006 DOI: 10.1016/j.scitotenv.2020.143009] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/19/2020] [Revised: 09/14/2020] [Accepted: 10/08/2020] [Indexed: 06/11/2023]
Abstract
Assessing reactive nitrogen (Nr) flows resulting from agricultural crop production systems (ACPS) with LCA requires regionalization. However, methodological approaches for regionalized LCA of ACPS may not necessarily reflect a comprehensive picture of Nr compounds and their complex interaction with the environment. This study presents a comprehensive analysis of the consideration of Nr in methodological approaches for regionalized LCA applied to ACPS. We conducted a review comprehending scientific literature on regionalization approaches applied to ACPS and compared these with general requirements of LCA and the scientific background of the N-cycle following the LCA framework. Special focus was placed on the analysis of process-based models (PBM) and life cycle impact assessment (LCIA) methods. We derived key factors relevant for a regional assessment of N flows in LCA and compared these to 23 regionalization approaches applied to ACPS. Main obstacles identified to conduct a regionalized LCA for ACPS involved the consideration of different regional scales and thus a missing common regionalization approach suitable for ACPS. Although, N related key-factors were mainly considered by the analyzed approaches in the different LCA phases, critical points involved the consideration of N field emissions and N impact assessment. Based on these findings, practical recommendations were given. Our comprehensive review provides relevant requirements for an improved regional N assessment in regionalized LCA of ACPS and aims to present a realistic picture when comparing different alternatives considering N specific regional impacts.
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Affiliation(s)
- Karoline Wowra
- Institute IWAR, Technische Universität Darmstadt, Franziska-Braun-Straße 7, 64287 Darmstadt, Germany.
| | - Vanessa Zeller
- Institute IWAR, Technische Universität Darmstadt, Franziska-Braun-Straße 7, 64287 Darmstadt, Germany
| | - Liselotte Schebek
- Institute IWAR, Technische Universität Darmstadt, Franziska-Braun-Straße 7, 64287 Darmstadt, Germany
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Ghahremanloo M, Lops Y, Choi Y, Mousavinezhad S. Impact of the COVID-19 outbreak on air pollution levels in East Asia. THE SCIENCE OF THE TOTAL ENVIRONMENT 2021; 754:142226. [PMID: 33254896 PMCID: PMC7476443 DOI: 10.1016/j.scitotenv.2020.142226] [Citation(s) in RCA: 60] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/19/2020] [Revised: 08/13/2020] [Accepted: 09/03/2020] [Indexed: 05/18/2023]
Abstract
This study leverages satellite remote sensing to investigate the impact of the coronavirus outbreak and the resulting lockdown of public venues on air pollution levels in East Asia. We analyze data from the Sentinel-5P and the Himawari-8 satellites to examine concentrations of NO2, HCHO, SO2, and CO, and the aerosol optical depth (AOD) over the BTH, Wuhan, Seoul, and Tokyo regions in February 2019 and February 2020. Results show that most of the concentrations of pollutants are lower than those of February 2019. Compared to other pollutants, NO2 experienced the most significant reductions by almost 54%, 83%, 33%, and 19% decrease in BTH, Wuhan, Seoul, and Tokyo, respectively. The greatest reductions in pollutants occurred in Wuhan, with a decrease of almost 83%, 11%, 71%, and 4% in the column densities of NO2, HCHO, SO2, and CO, respectively, and a decrease of about 62% in the AOD. Although NO2, CO, and formaldehyde concentrations decreased in the Seoul and Tokyo metropolitan areas compared to the previous year, concentrations of SO2 showed an increase in these two regions due to the effect of transport from polluted upwind regions. We also show that meteorological factors were not the main reason for the dramatic reductions of pollutants in the atmosphere. Moreover, an investigation of the HCHO/NO2 ratio shows that in many regions of East China, particularly in Wuhan, ozone production in February 2020 is less NOX saturated during the daytime than it was in February 2019. With large reductions in the concentrations of NO2 during lockdown situations, we find that significant increases in surface ozone in East China from February 2019 to February 2020 are likely the result of less reaction of NO and O3 caused by significantly reduced NOX concentrations and less NOX saturation in East China during the daytime.
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Affiliation(s)
- Masoud Ghahremanloo
- Department of Earth and Atmospheric Sciences, University of Houston, Houston, TX 77004, USA.
| | - Yannic Lops
- Department of Earth and Atmospheric Sciences, University of Houston, Houston, TX 77004, USA.
| | - Yunsoo Choi
- Department of Earth and Atmospheric Sciences, University of Houston, Houston, TX 77004, USA.
| | - Seyedali Mousavinezhad
- Department of Earth and Atmospheric Sciences, University of Houston, Houston, TX 77004, USA.
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29
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Schuch D, Andrade MDF, Zhang Y, de Freitas ED, Bell ML. Short-Term Responses of Air Quality to Changes in Emissions under the Representative Concentration Pathway 4.5 Scenario over Brazil. ATMOSPHERE 2020; 11:799. [PMID: 38803806 PMCID: PMC7615996 DOI: 10.3390/atmos11080799] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 05/29/2024]
Abstract
Brazil, one of the world's fastest-growing economies, is the fifth most populous country and is experiencing accelerated urbanization. This combination of factors causes an increase in urban population that is exposed to poor air quality, leading to public health burdens. In this work, the Weather Research and Forecasting Model with Chemistry is applied to simulate air quality over Brazil for a short time period under three future emission scenarios, including current legislation (CLE), mitigation scenario (MIT), and maximum feasible reduction (MFR) under the Representative Concentration Pathway 4.5 (RCP4.5), which is a climate change scenario under which radiative forcing of greenhouse gases (GHGs) reach 4.5 W m-2 by 2100. The main objective of this study is to determine the sensitivity of the concentrations of ozone (O3) and particulate matter with aerodynamic diameter 2.5 µm or less (PM2.5) to changes in emissions under these emission scenarios and to determine the signal and spatial patterns of these changes for Brazil. The model is evaluated with observations and shows reasonably good agreement. The MFR scenario leads to a reduction of 3% and 75% for O3 and PM2.5 respectively, considering the average of grid cells within Brazil, whereas the CLE scenario leads to an increase of 1% and 11% for O3 and PM2.5 respectively, concentrated near urban centers. These results indicate that of the three emission control scenarios, the CLE leads to poor air quality, while the MFR scenario leads to the maximum improvement in air quality. To the best of our knowledge, this work is the first to investigate the responses of air quality to changes in emissions under these emission scenarios for Brazil. The results shed light on the linkage between changes of emissions and air quality.
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Affiliation(s)
- Daniel Schuch
- Department of Civil and Environmental Engineering, Northeastern University, Boston, MA 02115, USA
| | - Maria de Fatima Andrade
- Instituto de Astronomia, Geofísica e Ciências Atmosféricas, Universidade de São Paulo, São Paulo 05508-090, Brazil
| | - Yang Zhang
- Department of Civil and Environmental Engineering, Northeastern University, Boston, MA 02115, USA
| | - Edmilson Dias de Freitas
- Instituto de Astronomia, Geofísica e Ciências Atmosféricas, Universidade de São Paulo, São Paulo 05508-090, Brazil
| | - Michelle L. Bell
- School of Forestry & Environmental Studies, Yale University, New Haven, CT 06511, USA
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Unprecedented Temporary Reduction in Global Air Pollution Associated with COVID-19 Forced Confinement: A Continental and City Scale Analysis. REMOTE SENSING 2020. [DOI: 10.3390/rs12152420] [Citation(s) in RCA: 38] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Shortly after the outbreak of the novel infectious disease (COVID-19) started at the end of 2019, it turned into a global pandemic, which caused the lockdown of many countries across the world. Various strict measures were adopted to reduce anthropogenic activities in order to prevent further spread and infection of the disease. In this study, we utilized continental scale remotely sensed data along with city scale in situ air quality observations for 2020 as well as data from the baseline period (2015–2019) to provide an early insight on air pollution changes in response to the COVID-19 pandemic lockdown, by combining both continental and city scales. For the continental scale analysis, data of NO2, SO2, and O3 were acquired from the ozone monitoring instrument (OMI) and data of aerosol optical depth (AOD) were collected from the moderate resolution imaging spectroradiometer (MODIS). For city scale analysis, data of NO2, CO, PM2.5, O3, and SO2 were derived from ground-based air quality observations. Results from satellite observations at the continental scale showed that concentrations of NO2, SO2, and AOD substantially dropped in 2020 during the lockdown period compared to their averages for the baseline period over all continents, with a maximum reduction of ~33% for NO2 in East Asia, ~41% for SO2 in East Asia, and ~37% for AOD in South Asia. In the case of O3, the maximum overall reduction was observed as ~11% in Europe, followed by ~10% in North America, while a slight increase was found in other study regions. These findings align with ground-based air quality observations, which showed that pollutants such as NO2, CO, PM2.5, and SO2 during the 2020 lockdown period decreased significantly except that O3 had varying patterns in different cities. Specifically, a maximum reduction of ~49% in NO2 was found in London, ~43% in CO in Wuhan, ~38% in PM2.5 in Chennai, and ~48% in SO2 in Beijing. In the case of urban O3, a maximum reduction of ~43% was found in Wuhan, but a significant increase of ~47% was observed in Chennai. It is obvious that restricted human activities during the lockdown have reduced the anthropogenic emissions and subsequently improved air quality, especially across the metropolitan cities.
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31
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Weng H, Lin J, Martin R, Millet DB, Jaeglé L, Ridley D, Keller C, Li C, Du M, Meng J. Global high-resolution emissions of soil NO x, sea salt aerosols, and biogenic volatile organic compounds. Sci Data 2020; 7:148. [PMID: 32433468 PMCID: PMC7239948 DOI: 10.1038/s41597-020-0488-5] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2019] [Accepted: 04/16/2020] [Indexed: 11/09/2022] Open
Abstract
Natural emissions of air pollutants from the surface play major roles in air quality and climate change. In particular, nitrogen oxides (NOx) emitted from soils contribute ~15% of global NOx emissions, sea salt aerosols are a major player in the climate and chemistry of the marine atmosphere, and biogenic emissions are the dominant source of non-methane volatile organic compounds at the global scale. These natural emissions are often estimated using nonlinear parameterizations, which are sensitive to the horizontal resolutions of inputted meteorological and ancillary data. Here we use the HEMCO model to compute these emissions worldwide at horizontal resolutions of 0.5° lat. × 0.625° lon. for 1980-2017 and 0.25° lat. × 0.3125° lon. for 2014-2017. We further offer the respective emissions at lower resolutions, which can be used to evaluate the impacts of resolution on estimated global and regional emissions. Our long-term high-resolution emission datasets offer useful information to study natural pollution sources and their impacts on air quality, climate, and the carbon cycle.
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Affiliation(s)
- Hongjian Weng
- Laboratory for Climate and Ocean-Atmosphere Studies, Department of Atmospheric and Oceanic Sciences, School of Physics, Peking University, Beijing, 100871, China
| | - Jintai Lin
- Laboratory for Climate and Ocean-Atmosphere Studies, Department of Atmospheric and Oceanic Sciences, School of Physics, Peking University, Beijing, 100871, China.
| | - Randall Martin
- Energy, Environmental & Chemical Engineering, Washington University in St. Louis, St. Louis, 63130, MO, USA
| | - Dylan B Millet
- Department of Soil, Water, and Climate, University of Minnesota Twin Cities, St Paul, MN, 55455, USA
| | - Lyatt Jaeglé
- Department of Atmospheric Sciences, University of Washington, Seattle, WA, 98195, USA
| | - David Ridley
- Department of Civil and Environmental, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
| | - Christoph Keller
- Goddard Space Flight Center, NASA Global Modeling and Assimilation Office, Greenbelt, MD, 20771, USA
| | - Chi Li
- Department of Physics and Atmospheric Science, Dalhousie University, Halifax, NS, B3H 4R2, Canada
| | - Mingxi Du
- Laboratory for Climate and Ocean-Atmosphere Studies, Department of Atmospheric and Oceanic Sciences, School of Physics, Peking University, Beijing, 100871, China
| | - Jun Meng
- Energy, Environmental & Chemical Engineering, Washington University in St. Louis, St. Louis, 63130, MO, USA
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32
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Li Z, Hastings MG, Walters WW, Tian L, Clemens SC, Song L, Shao L, Fang Y. Isotopic evidence that recent agriculture overprints climate variability in nitrogen deposition to the Tibetan Plateau. ENVIRONMENT INTERNATIONAL 2020; 138:105614. [PMID: 32155512 DOI: 10.1016/j.envint.2020.105614] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/27/2019] [Revised: 02/08/2020] [Accepted: 02/26/2020] [Indexed: 06/10/2023]
Abstract
The stable isotopes of nitrogen in nitrate archived in polar ice have been interpreted as reflecting a shift in reactive nitrogen sources or changes in atmospheric chemical reactivity. Here, we present a novel concentration and isotopic record of nitrate (δ15N-NO3-) from a central Tibetan Plateau ice core over the last ~200 years. We find that nitrate concentration increased from 6.0 ± 2.3 μeq/L (mean ± 1σ) in the preindustrial period (prior to 1900s) to 7.3 ± 2.7 μeq/L in post-1950. Over the same time period, the δ15N-NO3- decreased from 8.7 ± 3.7‰ to 4.2 ± 3.1‰, with much larger interannual variation in δ15N-NO3- during the preindustrial period. We present a useful framework for quantifying the sensitivity of the isotopic composition of atmospheric nitrate to changes in both sources and chemistry (gas and aerosol phase). After 1950, nitrogen deposition is primarily driven by fertilizer use, leading to significant increases in concentration and decreases in δ15N-NO3-. The large interannual variability of ice core δ15N-NO3- in the preindustrial reflects natural processes, namely the El Niño Southern Oscillation (ENSO) and dust events. Our results highlight a new connection between the nitrogen cycle and ENSO, and the overprinting of natural climate signals by recent anthropogenic increases in reactive nitrogen release.
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Affiliation(s)
- Zhengjie Li
- CAS Key Laboratory of Forest Ecology and Management, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang, Liaoning 110016, China; Department of Earth, Environmental and Planetary Sciences, Brown University, Providence, Rhode Island 02912, USA; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China; Key Laboratory of Stable Isotope Techniques and Applications, Shenyang, Liaoning 110016, China
| | - Meredith G Hastings
- Department of Earth, Environmental and Planetary Sciences, Brown University, Providence, Rhode Island 02912, USA; Institute at Brown for Environment and Society, Brown University, Providence, Rhode Island 02912, USA.
| | - Wendell W Walters
- Department of Earth, Environmental and Planetary Sciences, Brown University, Providence, Rhode Island 02912, USA; Institute at Brown for Environment and Society, Brown University, Providence, Rhode Island 02912, USA
| | - Lide Tian
- Institute of International Rivers and Eco-Security, Yunnan University, Kunming, Yunnan 650500, China; Institute of Tibetan Plateau Research, Chinese Academy of Sciences (CAS), Beijing 100101, China
| | - Steven C Clemens
- Department of Earth, Environmental and Planetary Sciences, Brown University, Providence, Rhode Island 02912, USA
| | - Linlin Song
- CAS Key Laboratory of Forest Ecology and Management, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang, Liaoning 110016, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China; Key Laboratory of Stable Isotope Techniques and Applications, Shenyang, Liaoning 110016, China
| | - Lili Shao
- Institute of International Rivers and Eco-Security, Yunnan University, Kunming, Yunnan 650500, China
| | - Yunting Fang
- CAS Key Laboratory of Forest Ecology and Management, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang, Liaoning 110016, China; Qingyuan Forest CERN, Shenyang, Liaoning 110016, China; Key Laboratory of Stable Isotope Techniques and Applications, Shenyang, Liaoning 110016, China.
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33
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Temporal Analysis of OMI-Observed Tropospheric NO2 Columns over East Asia during 2006–2015. ATMOSPHERE 2019. [DOI: 10.3390/atmos10110658] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
The study analyzed temporal variations of Ozone Monitoring Instrument (OMI)-observed NO2 columns, interregional correlation, and comparison between NO2 columns and NOx emissions during the period from 2006 to 2015. Regarding the trend of the NO2 columns, the linear lines were classified into four groups: (1) ‘upward and downward’ over six defined geographic regions in central-east Asia; (2) ‘downward’ over Guangzhou, Japan, and Taiwan; (3) ‘stagnant’ over South Korea; and (4) ‘upward’ over North Korea, Mongolia, Qinghai, and Northwestern Pacific ocean. In particular, the levels of NO2 columns in 2015 returned to those in 2006 over most of the polluted regions in China. Quantitatively, their relative changes in 2015 compared to 2006 were approximately 10%. From the interregional correlation analysis, it was found that unlike positive relationships between the polluted areas, the different variations of monthly NO2 columns led to negative relationships in Mongolia and Qinghai. Regarding the comparison between NO2 columns and NOx emission, the NOx emissions from the Copernicus Atmosphere Monitoring Service (CAMS) and Clean Air Policy Support System (CAPSS) inventories did not follow the year-to-year variations of NO2 columns over the polluted regions. In addition, the weekly effect was only clearly shown in South Korea, Japan, and Taiwan, indicating that the amounts of NOx emissions are significantly contributed to by the transportation sector.
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Xu JW, Martin RV, Henderson BH, Meng J, Oztaner B, Hand JL, Hakami A, Strum M, Phillips SB. Simulation of airborne trace metals in fine particulate matter over North America. ATMOSPHERIC ENVIRONMENT (OXFORD, ENGLAND : 1994) 2019; 214:10.1016/j.atmosenv.2019.116883. [PMID: 32665763 PMCID: PMC7359884 DOI: 10.1016/j.atmosenv.2019.116883] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/21/2023]
Abstract
Trace metal distributions are of relevance to understand sources of fine particulate matter (PM2.5), PM2.5-related health effects, and atmospheric chemistry. However, knowledge of trace metal distributions is lacking due to limited ground-based measurements and model simulations. This study develops a simulation of 12 trace metal concentrations (Si, Ca, Al, Fe, Ti, Mn, K, Mg, As, Cd, Ni and Pb) over continental North America for 2013 using the GEOS-Chem chemical transport model. Evaluation of modeled trace metal concentrations with observations indicates a spatial consistency within a factor of 2, an improvement over previous studies that were within a factor of 3-6. The spatial distribution of trace metal concentrations reflects their primary emission sources. Crustal element (Si, Ca, Al, Fe, Ti, Mn, K) concentrations are enhanced over the central US from anthropogenic fugitive dust and over the southwestern U.S. due to natural mineral dust. Heavy metal (As, Cd, Ni and Pb) concentrations are high over the eastern U.S. from industry. K is abundance in the southeast from biomass burning and high concentrations of Mg is observed along the coast from sea spray. The spatial pattern of PM2.5 mass is most strongly correlated with Pb, Ni, As and K due to their signature emission sources. Challenges remain in accurately simulating observed trace metal concentrations. Halving anthropogenic fugitive dust emissions in the 2011 National Air Toxic Assessment (NATA) inventory and doubling natural dust emissions in the default GEOS-Chem simulation was necessary to reduce biases in crustal element concentrations. A fivefold increase of anthropogenic emissions of As and Pb was necessary in the NATA inventory to reduce the national-scale bias versus observations by more than 80 %, potentially reflecting missing sources.
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Affiliation(s)
- Jun-Wei Xu
- Department of Physics and Atmospheric Science, Dalhousie University, Halifax, NS, Canada
| | - Randall V Martin
- Department of Physics and Atmospheric Science, Dalhousie University, Halifax, NS, Canada
- Department of Energy, Environmental & Chemical Engineering, Washington University in St. Louis, St. Louis, Missouri, United States
- Harvard-Smithsonian Center for Astrophysics, Cambridge, MA, USA
| | | | - Jun Meng
- Department of Physics and Atmospheric Science, Dalhousie University, Halifax, NS, Canada
| | - Burak Oztaner
- Department of Civil and Environmental Engineering, Carleton University, Ottawa, ON, Canada
| | - Jenny L Hand
- Cooperative Institute for Research in the Atmosphere, Colorado State University, Fort Collins, CO, USA
| | - Amir Hakami
- Department of Civil and Environmental Engineering, Carleton University, Ottawa, ON, Canada
| | - Madeleine Strum
- Environmental Protection Agency, Research Triangle Park, NC, USA
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35
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The Spatial–Temporal Variation of Tropospheric NO2 over China during 2005 to 2018. ATMOSPHERE 2019. [DOI: 10.3390/atmos10080444] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
In recent years, new and strict air quality regulations have been implemented in China. Therefore, it is of great significance to evaluate the current air pollution situation and effectiveness of actions. In this study, Ozone Monitoring Instrument (OMI) satellite data were used to detect the spatiotemporal characteristics of tropospheric NO2 columns over China from 2005 to 2018, including spatial distribution, seasonal cycles and long-term trends. The averaged NO2 pollution is higher in southeastern China and lower in the northwest, which are well delineated by the Heihe–Tengchong line. Furthermore, the NO2 loadings are highest in the North China Plain, with vertical column density (VCD) exceeding 13 × 1015 molec cm−2. Regarding the seasonal cycle, the NO2 loadings in eastern China is highest in winter and lowest in summer, while the western region shows the opposite feature. The amplitude of annual range increase gradually from the south to the north. If the entire period of 2005–2018 is taken into account, China has experienced little change in NO2. In fact, however, there appears to be significant trends of an increase followed by a downward tendency, with the turning point in the year 2012. In the former episode of 2005–2012, increasing trends overwhelm nearly the whole nation, especially in the Jing–Jin–Tang region, Shandong Province, and Northern Henan and Southern Hebei combined regions, where the rising rates were as high as 1.0–1.8 × 1015 molec cm−2 year−1. In contrast, the latter episode of 2013–2018 features remarkable declines in NO2 columns over China. Particularly, the regions where the decreased degree was remarkable in 2013–2018 were consistent with the regions where the upward trend was obvious in 2005–2012. Overall, this upward–downward pattern is true for most parts of China. However, some of the largest metropolises, such as Beijing, Shanghai and Guangzhou, witnessed a continuous decrease in the NO2 amounts, indicating earlier and more stringent measures adopted in these areas. Finally, it can be concluded that China’s recent efforts to cut NO2 pollution are successful, especially in mega cities.
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36
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Qu Z, Henze DK, Theys N, Wang J, Wang W. Hybrid Mass Balance/4D-Var Joint Inversion of NO x and SO 2 Emissions in East Asia. JOURNAL OF GEOPHYSICAL RESEARCH. ATMOSPHERES : JGR 2019; 124:8203-8224. [PMID: 31763108 PMCID: PMC6853212 DOI: 10.1029/2018jd030240] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/01/2019] [Revised: 05/22/2019] [Accepted: 05/27/2019] [Indexed: 05/27/2023]
Abstract
Accurate estimates of NO x and SO2 emissions are important for air quality modeling and management. To incorporate chemical interactions of the two species in emission estimates, we develop a joint hybrid inversion framework to estimate their emissions in China and India (2005-2012). Pseudo observation tests and posterior evaluation with surface measurements demonstrate that joint assimilation of SO2 and NO2 can provide more accurate constraints on emissions than single-species inversions. This occurs through synergistic change of O3 and OH concentrations, particularly in conditions where satellite retrievals of the species being optimized have large uncertainties. The percentage changes of joint posterior emissions from the single-species posterior emissions go up to 242% at grid scales, although the national average of monthly emissions, seasonality, and interannual variations are similar. In China and India, the annual budget of joint posterior SO2 emissions is lower, but joint NO x posterior emissions are higher, because NO x emissions increase to increase SO2 concentration and better match Ozone Monitoring Instrument SO2 observations in high-NO x regions. Joint SO2 posterior emissions decrease by 16.5% from 2008 to 2012, while NO x posterior emissions increase by 24.9% from 2005 to 2011 in China-trends which are consistent with the MEIC inventory. Joint NO x and SO2 posterior emissions in India increase by 15.9% and 19.2% from 2005 to 2012, smaller than the 59.9% and 76.2% growth rate using anthropogenic emissions from EDGARv4.3.2. This work shows the benefit and limitation of joint assimilation in emission estimates and provides an efficient framework to perform the inversion.
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Affiliation(s)
- Zhen Qu
- Department of Mechanical EngineeringUniversity of Colorado BoulderBoulderCOUSA
| | - Daven K. Henze
- Department of Mechanical EngineeringUniversity of Colorado BoulderBoulderCOUSA
| | - Nicolas Theys
- Belgian Institute for Space Aeronomy (BIRA‐IASB)BrusselsBelgium
| | - Jun Wang
- Center for Global and Regional Environmental Research, Department of Chemical and Biochemical EngineeringUniversity of IowaIowa CityIAUSA
| | - Wei Wang
- China National Environmental Monitoring CenterBeijingChina
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37
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Shrivastava M, Andreae MO, Artaxo P, Barbosa HMJ, Berg LK, Brito J, Ching J, Easter RC, Fan J, Fast JD, Feng Z, Fuentes JD, Glasius M, Goldstein AH, Alves EG, Gomes H, Gu D, Guenther A, Jathar SH, Kim S, Liu Y, Lou S, Martin ST, McNeill VF, Medeiros A, de Sá SS, Shilling JE, Springston SR, Souza RAF, Thornton JA, Isaacman-VanWertz G, Yee LD, Ynoue R, Zaveri RA, Zelenyuk A, Zhao C. Urban pollution greatly enhances formation of natural aerosols over the Amazon rainforest. Nat Commun 2019; 10:1046. [PMID: 30837467 PMCID: PMC6401186 DOI: 10.1038/s41467-019-08909-4] [Citation(s) in RCA: 48] [Impact Index Per Article: 9.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2018] [Accepted: 01/18/2019] [Indexed: 11/10/2022] Open
Abstract
One of the least understood aspects in atmospheric chemistry is how urban emissions influence the formation of natural organic aerosols, which affect Earth's energy budget. The Amazon rainforest, during its wet season, is one of the few remaining places on Earth where atmospheric chemistry transitions between preindustrial and urban-influenced conditions. Here, we integrate insights from several laboratory measurements and simulate the formation of secondary organic aerosols (SOA) in the Amazon using a high-resolution chemical transport model. Simulations show that emissions of nitrogen-oxides from Manaus, a city of ~2 million people, greatly enhance production of biogenic SOA by 60-200% on average with peak enhancements of 400%, through the increased oxidation of gas-phase organic carbon emitted by the forests. Simulated enhancements agree with aircraft measurements, and are much larger than those reported over other locations. The implication is that increasing anthropogenic emissions in the future might substantially enhance biogenic SOA in pristine locations like the Amazon.
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Affiliation(s)
| | - Meinrat O Andreae
- Department of Geology and Geophysics, King Saud University, Riyadh 11451, Saudi Arabia
- Scripps Institution of Oceanography, University of California San Diego, La Jolla, CA, 92093-0230, USA
- Max Planck Institute for Chemistry, P.O. Box 3060, Mainz, D-55020, Germany
| | - Paulo Artaxo
- Institute of Physics, University of São Paulo, São Paulo, 05508-090, Brazil
| | | | - Larry K Berg
- Pacific Northwest National Laboratory, Richland, WA, 99352, USA
| | - Joel Brito
- IMT Lille Douai, University of Lille, SAGE, Lille, 59000, France
| | - Joseph Ching
- Meteorological Research Institute, Japan Meteorological Agency, 1-1, Nagamine, Tsukuba, 305-0052, Ibaraki, Japan
| | | | - Jiwen Fan
- Pacific Northwest National Laboratory, Richland, WA, 99352, USA
| | - Jerome D Fast
- Pacific Northwest National Laboratory, Richland, WA, 99352, USA
| | - Zhe Feng
- Pacific Northwest National Laboratory, Richland, WA, 99352, USA
| | - Jose D Fuentes
- Department of Meteorology and Atmospheric Science, Penn State University, University Park, PA, 16802, USA
| | - Marianne Glasius
- Department of Chemistry, Aarhus University, Aarhus, 8000, Denmark
| | - Allen H Goldstein
- Department of Environmental Science, Policy, and Management, University of California, Berkeley, 94720, USA
| | - Eliane Gomes Alves
- Instituto Nacional de Pesquisas da Amazônia (INPA), Av. André Araújo, Manaus, AM, 69.060-000, Brazil
| | - Helber Gomes
- Institute of Atmospheric Sciences, Federal University of Alagoas, Maceió, AL, 57072-900, Brazil
| | - Dasa Gu
- Department of Earth System Science, University of California, Irvine, CA, 92697, USA
| | - Alex Guenther
- Pacific Northwest National Laboratory, Richland, WA, 99352, USA
- Department of Earth System Science, University of California, Irvine, CA, 92697, USA
| | - Shantanu H Jathar
- Department of Mechanical Engineering, Colorado State University, Fort Collins, 80523, USA
| | - Saewung Kim
- Department of Earth System Science, University of California, Irvine, CA, 92697, USA
| | - Ying Liu
- Pacific Northwest National Laboratory, Richland, WA, 99352, USA
| | - Sijia Lou
- Pacific Northwest National Laboratory, Richland, WA, 99352, USA
| | - Scot T Martin
- School of Engineering and Applied Sciences and Department of Earth and Planetary Sciences, Harvard University, Cambridge, MA, 02138, USA
| | - V Faye McNeill
- Department of Chemical Engineering, Columbia University, New York, NY, 10027, USA
| | - Adan Medeiros
- Amazonas State University, Center of Superior Studies of Tefé, R. Brasília, Tefé, AM, 69470000, Brazil
| | - Suzane S de Sá
- School of Engineering and Applied Sciences and Department of Earth and Planetary Sciences, Harvard University, Cambridge, MA, 02138, USA
| | - John E Shilling
- Pacific Northwest National Laboratory, Richland, WA, 99352, USA
| | - Stephen R Springston
- Environmental and Climate Sciences Department, Brookhaven National Laboratory, Brookhaven, NY, 11973, USA
| | - R A F Souza
- Amazonas State University, Superior School of Technology, Av Darcy Vargas, Manaus, AM, 69050020, Brazil
| | - Joel A Thornton
- Department of Atmospheric Sciences, University of Washington, Seattle, 98195, USA
| | | | - Lindsay D Yee
- Department of Environmental Science, Policy, and Management, University of California, Berkeley, 94720, USA
| | - Rita Ynoue
- Department of Atmospheric Sciences, Institute of Astronomy, Geophysics and Atmospheric Sciences, University of Sao Paulo, Sao Paulo, 05508090, Brazil
| | - Rahul A Zaveri
- Pacific Northwest National Laboratory, Richland, WA, 99352, USA
| | - Alla Zelenyuk
- Pacific Northwest National Laboratory, Richland, WA, 99352, USA
| | - Chun Zhao
- School of Earth and Space Sciences, University of Science and Technology of China, Hefei, 230026, China
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Archibald AT, Folberth G, Wade DC, Scott D. A world avoided: impacts of changes in anthropogenic emissions on the burden and effects of air pollutants in Europe and North America. Faraday Discuss 2018; 200:475-500. [PMID: 28580997 DOI: 10.1039/c7fd00004a] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
Emissions from anthropogenic activity are known to have deleterious impacts on human and ecosystem health and as such a significant amount of time, effort and money has been spent developing legislation to minimise their effects. Here we use a state of the art coupled chemistry-climate model HadGEM2-ES, with extended tropospheric chemistry, to assess the impacts that changes in emissions from anthropogenic activity have had on the burden and impacts of air pollutants over the last three decades. We use HadGEM2-ES to assess an alternative trajectory in air pollutant emissions to that which we have seen, with a regional focus on the contiguous United States and areas of Western Europe. This alternative trajectory can be considered to reflect a world avoided. In this world avoided, the significant levels of air pollution legislation imposed over the last three decades are simulated to not have come into effect in the contiguous United States and Western Europe. Rather a business as usual emission scenario is followed from 1970 to the present day. By combining the results of simulations of the world avoided with a base case present day atmosphere our model runs demonstrate that as a result of air pollution legislation, over 500 000 early mortalities a year have been mitigated owing to extensive reduction in sulfate aerosol and up to 8000 early mortalities a year have been mitigated as a result of improvements in ozone and nitrogen dioxide pollution. These results highlight the important role of legislation in reducing air pollution related mortality in these areas of the globe and highlight a compelling case for developing regions to follow.
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Affiliation(s)
- A T Archibald
- Department of Chemistry, University of Cambridge, CB2 1EW, UK.
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Abstract
Poor air quality is often associated with hot weather, but the quantitative attribution of high temperatures on air quality remains unclear. In this study, the effect of elevated temperatures on air quality is investigated in Greater Sydney using January 2013, a period of extreme heat during which temperatures at times exceeded 40 ∘ C, as a case study. Using observations from 17 measurement sites and the Weather Research and Forecasting Chemistry (WRF-Chem) model, we analyse the effect of elevated temperatures on ozone in Sydney by running a number of sensitivity studies in which: (1) the model is run with biogenic emissions generated by MEGAN and separately run with monthly average Model of Emissions of Gases and Aerosols from Nature ( MEGAN) biogenic emissions (for January 2013); (2) the model results from the standard run are compared with those in which average temperatures (for January 2013) are only applied to the chemistry; (3) the model is run using both averaged biogenic emissions and temperatures; and (4 and 5) the model is run with half and zero biogenic emissions. The results show that the impact on simulated ozone through the effect of temperature on reaction rates is similar to the impact via the effect of temperature on biogenic emissions and the relative impacts are largely additive when compared to the run in which both are averaged. When averaged across 17 sites in Greater Sydney, the differences between ozone simulated under standard and averaged model conditions are as high as 16 ppbv. Removing biogenic emissions in the model has the effect of removing all simulated ozone episodes during extreme heat periods, highlighting the important role of biogenic emissions in Australia, where Eucalypts are a key biogenic source.
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Mielnik A, Link M, Mattila J, Fulgham SR, Farmer DK. Emission of formic and acetic acids from two Colorado soils. ENVIRONMENTAL SCIENCE. PROCESSES & IMPACTS 2018; 20:1537-1545. [PMID: 30284577 DOI: 10.1039/c8em00356d] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/10/2023]
Abstract
A 'missing source' of atmospheric formic acid is consistently observed during model-measurement comparisons, and evidence from multiple environments suggests a near-surface source. Soil emissions are considered to be a small formic acid source, but estimates are based on a single study from a tropical site. Here, we investigate soil emissions of organic acids from two soils - a ponderosa pine forest (Manitou Experimental Forest Observatory), and a managed lawn (Colorado State University) using a laboratory chamber. Both soils are a source of formic and acetic acids. Under ambient conditions, formic acid emissions are 0.11 (pine forest) and 0.15 (lawn) nmol m-2 s-1, and acetic acid emissions are 0.05 (pine forest) and 0.71 (lawn) nmol m-2 s-1. Only acetic acid emissions from the forest site correlate with CO2 fluxes, but all formic and acetic acid emissions increase exponentially with temperature. Increasing soil moisture only enhances acetic acid emissions from the forest. Considering this temperature and moisture dependence, we hypothesize that while equilibrium partitioning may contribute to the forest emissions, organic acid emissions from the lawn are likely driven by microbial activity. Lactic acid was emitted from both soils, but not quantified. The observed formic acid emissions are higher than previous measurements, but still low enough that soils are unlikely the 'missing source' of atmospheric organic acids, although the variability in the soil source is substantial. We contrast observations to previous parameterizations used in models, and present recommendations for modified parameterizations for formic and acetic acid emission.
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Affiliation(s)
- Anne Mielnik
- Department of Chemistry, Colorado State University, Fort Collins, CO 80523, USA.
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Matthias V, Arndt JA, Aulinger A, Bieser J, Denier van der Gon H, Kranenburg R, Kuenen J, Neumann D, Pouliot G, Quante M. Modeling emissions for three-dimensional atmospheric chemistry transport models. JOURNAL OF THE AIR & WASTE MANAGEMENT ASSOCIATION (1995) 2018; 68:763-800. [PMID: 29364776 DOI: 10.1080/10962247.2018.1424057] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/31/2017] [Revised: 12/20/2017] [Accepted: 12/21/2017] [Indexed: 05/21/2023]
Abstract
UNLABELLED Poor air quality is still a threat for human health in many parts of the world. In order to assess measures for emission reductions and improved air quality, three-dimensional atmospheric chemistry transport modeling systems are used in numerous research institutions and public authorities. These models need accurate emission data in appropriate spatial and temporal resolution as input. This paper reviews the most widely used emission inventories on global and regional scales and looks into the methods used to make the inventory data model ready. Shortcomings of using standard temporal profiles for each emission sector are discussed, and new methods to improve the spatiotemporal distribution of the emissions are presented. These methods are often neither top-down nor bottom-up approaches but can be seen as hybrid methods that use detailed information about the emission process to derive spatially varying temporal emission profiles. These profiles are subsequently used to distribute bulk emissions such as national totals on appropriate grids. The wide area of natural emissions is also summarized, and the calculation methods are described. Almost all types of natural emissions depend on meteorological information, which is why they are highly variable in time and space and frequently calculated within the chemistry transport models themselves. The paper closes with an outlook for new ways to improve model ready emission data, for example, by using external databases about road traffic flow or satellite data to determine actual land use or leaf area. In a world where emission patterns change rapidly, it seems appropriate to use new types of statistical and observational data to create detailed emission data sets and keep emission inventories up-to-date. IMPLICATIONS Emission data are probably the most important input for chemistry transport model (CTM) systems. They need to be provided in high spatial and temporal resolution and on a grid that is in agreement with the CTM grid. Simple methods to distribute the emissions in time and space need to be replaced by sophisticated emission models in order to improve the CTM results. New methods, e.g., for ammonia emissions, provide grid cell-dependent temporal profiles. In the future, large data fields from traffic observations or satellite observations could be used for more detailed emission data.
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Affiliation(s)
- Volker Matthias
- a Chemistry Transport Modelling Department, Institute of Coastal Research , Helmholtz-Zentrum Geesthacht , Geesthacht , Germany
| | - Jan A Arndt
- a Chemistry Transport Modelling Department, Institute of Coastal Research , Helmholtz-Zentrum Geesthacht , Geesthacht , Germany
| | - Armin Aulinger
- a Chemistry Transport Modelling Department, Institute of Coastal Research , Helmholtz-Zentrum Geesthacht , Geesthacht , Germany
| | - Johannes Bieser
- a Chemistry Transport Modelling Department, Institute of Coastal Research , Helmholtz-Zentrum Geesthacht , Geesthacht , Germany
| | - Hugo Denier van der Gon
- b Climate, Air, and Sustainability Department , TNO, Netherlands Organisation for Applied Scientific Research , Utrecht , The Netherlands
| | - Richard Kranenburg
- b Climate, Air, and Sustainability Department , TNO, Netherlands Organisation for Applied Scientific Research , Utrecht , The Netherlands
| | - Jeroen Kuenen
- b Climate, Air, and Sustainability Department , TNO, Netherlands Organisation for Applied Scientific Research , Utrecht , The Netherlands
| | - Daniel Neumann
- c Department of Physical Oceanography and Instrumentation , Leibniz-Institut für Ostseeforschung Warnemünde , Rostock , Germany
| | - George Pouliot
- d Computational Exposure Division, National Exposure Research Laboratory , U.S. Environmental Protection Agency , Research Triangle Park , NC , USA
| | - Markus Quante
- a Chemistry Transport Modelling Department, Institute of Coastal Research , Helmholtz-Zentrum Geesthacht , Geesthacht , Germany
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Abel DW, Holloway T, Harkey M, Meier P, Ahl D, Limaye VS, Patz JA. Air-quality-related health impacts from climate change and from adaptation of cooling demand for buildings in the eastern United States: An interdisciplinary modeling study. PLoS Med 2018; 15:e1002599. [PMID: 29969461 PMCID: PMC6029751 DOI: 10.1371/journal.pmed.1002599] [Citation(s) in RCA: 32] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/09/2018] [Accepted: 05/30/2018] [Indexed: 01/13/2023] Open
Abstract
BACKGROUND Climate change negatively impacts human health through heat stress and exposure to worsened air pollution, amongst other pathways. Indoor use of air conditioning can be an effective strategy to reduce heat exposure. However, increased air conditioning use increases emissions of air pollutants from power plants, in turn worsening air quality and human health impacts. We used an interdisciplinary linked model system to quantify the impacts of heat-driven adaptation through building cooling demand on air-quality-related health outcomes in a representative mid-century climate scenario. METHODS AND FINDINGS We used a modeling system that included downscaling historical and future climate data with the Weather Research and Forecasting (WRF) model, simulating building electricity demand using the Regional Building Energy Simulation System (RBESS), simulating power sector production and emissions using MyPower, simulating ambient air quality using the Community Multiscale Air Quality (CMAQ) model, and calculating the incidence of adverse health outcomes using the Environmental Benefits Mapping and Analysis Program (BenMAP). We performed simulations for a representative present-day climate scenario and 2 representative mid-century climate scenarios, with and without exacerbated power sector emissions from adaptation in building energy use. We find that by mid-century, climate change alone can increase fine particulate matter (PM2.5) concentrations by 58.6% (2.50 μg/m3) and ozone (O3) by 14.9% (8.06 parts per billion by volume [ppbv]) for the month of July. A larger change is found when comparing the present day to the combined impact of climate change and increased building energy use, where PM2.5 increases 61.1% (2.60 μg/m3) and O3 increases 15.9% (8.64 ppbv). Therefore, 3.8% of the total increase in PM2.5 and 6.7% of the total increase in O3 is attributable to adaptive behavior (extra air conditioning use). Health impacts assessment finds that for a mid-century climate change scenario (with adaptation), annual PM2.5-related adult mortality increases by 13,547 deaths (14 concentration-response functions with mean incidence range of 1,320 to 26,481, approximately US$126 billion cost) and annual O3-related adult mortality increases by 3,514 deaths (3 functions with mean incidence range of 2,175 to 4,920, approximately US$32.5 billion cost), calculated as a 3-month summer estimate based on July modeling. Air conditioning adaptation accounts for 654 (range of 87 to 1,245) of the PM2.5-related deaths (approximately US$6 billion cost, a 4.8% increase above climate change impacts alone) and 315 (range of 198 to 438) of the O3-related deaths (approximately US$3 billion cost, an 8.7% increase above climate change impacts alone). Limitations of this study include modeling only a single month, based on 1 model-year of future climate simulations. As a result, we do not project the future, but rather describe the potential damages from interactions arising between climate, energy use, and air quality. CONCLUSIONS This study examines the contribution of future air-pollution-related health damages that are caused by the power sector through heat-driven air conditioning adaptation in buildings. Results show that without intervention, approximately 5%-9% of exacerbated air-pollution-related mortality will be due to increases in power sector emissions from heat-driven building electricity demand. This analysis highlights the need for cleaner energy sources, energy efficiency, and energy conservation to meet our growing dependence on building cooling systems and simultaneously mitigate climate change.
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Affiliation(s)
- David W. Abel
- Center for Sustainability and the Global Environment (SAGE), Nelson Institute for Environmental Studies, University of Wisconsin–Madison, Madison, Wisconsin, United States of America
| | - Tracey Holloway
- Center for Sustainability and the Global Environment (SAGE), Nelson Institute for Environmental Studies, University of Wisconsin–Madison, Madison, Wisconsin, United States of America
- Department of Atmospheric and Oceanic Sciences, University of Wisconsin–Madison, Madison, Wisconsin, United States of America
| | - Monica Harkey
- Center for Sustainability and the Global Environment (SAGE), Nelson Institute for Environmental Studies, University of Wisconsin–Madison, Madison, Wisconsin, United States of America
| | - Paul Meier
- Wisconsin Energy Institute (WEI), University of Wisconsin–Madison, Madison, Wisconsin, United States of America
- Great Lakes Bioenergy Research Center (GLBRC), University of Wisconsin–Madison, Madison, Wisconsin, United States of America
- Meier Engineering Research LLC, Stoughton, Wisconsin, United States of America
| | - Doug Ahl
- Seventhwave, Madison, Wisconsin, United States of America
| | - Vijay S. Limaye
- Center for Sustainability and the Global Environment (SAGE), Nelson Institute for Environmental Studies, University of Wisconsin–Madison, Madison, Wisconsin, United States of America
- Global Health Institute, University of Wisconsin–Madison, Madison, Wisconsin, United States of America
| | - Jonathan A. Patz
- Center for Sustainability and the Global Environment (SAGE), Nelson Institute for Environmental Studies, University of Wisconsin–Madison, Madison, Wisconsin, United States of America
- Global Health Institute, University of Wisconsin–Madison, Madison, Wisconsin, United States of America
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Noreen A, Khokhar MF, Zeb N, Yasmin N, Hakeem KR. Spatio-temporal assessment and seasonal variation of tropospheric ozone in Pakistan during the last decade. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2018; 25:8441-8454. [PMID: 29307068 DOI: 10.1007/s11356-017-1010-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/28/2017] [Accepted: 12/11/2017] [Indexed: 06/07/2023]
Abstract
This study uses the tropospheric ozone data derived from combined observations of Ozone Monitoring Instrument/Microwave Limb Sounder instruments by using the tropospheric ozone residual method. The main objective was to study the spatial distribution and temporal evolution in the troposphere ozone columns over Pakistan during the time period of 2004 to 2014. Results showed an overall increase of 3.2 ± 1.1 DU in tropospheric ozone columns over Pakistan. Spatial distribution showed enhanced ozone columns in the Punjab and southern Sindh consistent to high population, urbanization, and extensive anthropogenic activities, and exhibited statistically significant temporal increase. Seasonal variations in tropospheric ozone columns are driven by various factors such as seasonality in UV-B fluxes, seasonality in ozone precursor gases such as NOx and volatile organic compounds (caused by temperature dependent biogenic emission) and agricultural fire activities in Pakistan. A strong correlation of 96% (r = 0.96) was found between fire events and tropospheric ozone columns in Pakistan.
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Affiliation(s)
- Asma Noreen
- Institute of Environmental Sciences and Engineering, National University of Sciences and Technology, Sector H-12, Islamabad, 44000, Pakistan
| | - Muhammad Fahim Khokhar
- Institute of Environmental Sciences and Engineering, National University of Sciences and Technology, Sector H-12, Islamabad, 44000, Pakistan.
| | - Naila Zeb
- Institute of Environmental Sciences and Engineering, National University of Sciences and Technology, Sector H-12, Islamabad, 44000, Pakistan
| | - Naila Yasmin
- Institute of Environmental Sciences and Engineering, National University of Sciences and Technology, Sector H-12, Islamabad, 44000, Pakistan
| | - Khalid Rehman Hakeem
- Department of Biological Sciences, Faculty of Science, King Abdulaziz University, Jeddah, 21589, Saudi Arabia.
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Almaraz M, Bai E, Wang C, Trousdell J, Conley S, Faloona I, Houlton BZ. Agriculture is a major source of NO x pollution in California. SCIENCE ADVANCES 2018; 4:eaao3477. [PMID: 29399630 PMCID: PMC5792222 DOI: 10.1126/sciadv.aao3477] [Citation(s) in RCA: 59] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/10/2017] [Accepted: 01/05/2018] [Indexed: 05/02/2023]
Abstract
Nitrogen oxides (NO x = NO + NO2) are a primary component of air pollution-a leading cause of premature death in humans and biodiversity declines worldwide. Although regulatory policies in California have successfully limited transportation sources of NO x pollution, several of the United States' worst-air quality districts remain in rural regions of the state. Site-based findings suggest that NO x emissions from California's agricultural soils could contribute to air quality issues; however, a statewide estimate is hitherto lacking. We show that agricultural soils are a dominant source of NO x pollution in California, with especially high soil NO x emissions from the state's Central Valley region. We base our conclusion on two independent approaches: (i) a bottom-up spatial model of soil NO x emissions and (ii) top-down airborne observations of atmospheric NO x concentrations over the San Joaquin Valley. These approaches point to a large, overlooked NO x source from cropland soil, which is estimated to increase the NO x budget by 20 to 51%. These estimates are consistent with previous studies of point-scale measurements of NO x emissions from the soil. Our results highlight opportunities to limit NO x emissions from agriculture by investing in management practices that will bring co-benefits to the economy, ecosystems, and human health in rural areas of California.
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Affiliation(s)
- Maya Almaraz
- Department of Land, Air and Water Resources, University of California, Davis, Davis, CA 95616, USA
- Corresponding author.
| | - Edith Bai
- CAS Key Laboratory of Forest and Management, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016, China
- School of Geographical Sciences, Northeast Normal University, Changchun 130024, China
| | - Chao Wang
- CAS Key Laboratory of Forest and Management, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016, China
| | - Justin Trousdell
- Department of Land, Air and Water Resources, University of California, Davis, Davis, CA 95616, USA
| | - Stephen Conley
- Department of Land, Air and Water Resources, University of California, Davis, Davis, CA 95616, USA
| | - Ian Faloona
- Department of Land, Air and Water Resources, University of California, Davis, Davis, CA 95616, USA
| | - Benjamin Z. Houlton
- Department of Land, Air and Water Resources, University of California, Davis, Davis, CA 95616, USA
- John Muir Institute of the Environment, University of California, Davis, Davis, CA 95616, USA
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Nielsen JE, Pawson S, Molod A, Auer B, da Silva AM, Douglass AR, Duncan B, Liang Q, Manyin M, Oman LD, Putman W, Strahan SE, Wargan K. Chemical Mechanisms and Their Applications in the Goddard Earth Observing System (GEOS) Earth System Model. JOURNAL OF ADVANCES IN MODELING EARTH SYSTEMS 2017; 9:3019-3044. [PMID: 29497478 PMCID: PMC5815385 DOI: 10.1002/2017ms001011] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/06/2017] [Accepted: 11/19/2017] [Indexed: 05/14/2023]
Abstract
NASA's Goddard Earth Observing System (GEOS) Earth System Model (ESM) is a modular, general circulation model (GCM), and data assimilation system (DAS) that is used to simulate and study the coupled dynamics, physics, chemistry, and biology of our planet. GEOS is developed by the Global Modeling and Assimilation Office (GMAO) at NASA Goddard Space Flight Center. It generates near-real-time analyzed data products, reanalyses, and weather and seasonal forecasts to support research targeted to understanding interactions among Earth System processes. For chemistry, our efforts are focused on ozone and its influence on the state of the atmosphere and oceans, and on trace gas data assimilation and global forecasting at mesoscale discretization. Several chemistry and aerosol modules are coupled to the GCM, which enables GEOS to address topics pertinent to NASA's Earth Science Mission. This paper describes the atmospheric chemistry components of GEOS and provides an overview of its Earth System Modeling Framework (ESMF)-based software infrastructure, which promotes a rich spectrum of feedbacks that influence circulation and climate, and impact human and ecosystem health. We detail how GEOS allows model users to select chemical mechanisms and emission scenarios at run time, establish the extent to which the aerosol and chemical components communicate, and decide whether either or both influence the radiative transfer calculations. A variety of resolutions facilitates research on spatial and temporal scales relevant to problems ranging from hourly changes in air quality to trace gas trends in a changing climate. Samples of recent GEOS chemistry applications are provided.
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Affiliation(s)
- J. Eric Nielsen
- Science Systems and Applications, Inc.LanhamMDUSA
- Global Modeling and Assimilation OfficeNASA Goddard Space Flight CenterGreenbeltMDUSA
| | - Steven Pawson
- Global Modeling and Assimilation OfficeNASA Goddard Space Flight CenterGreenbeltMDUSA
| | - Andrea Molod
- Global Modeling and Assimilation OfficeNASA Goddard Space Flight CenterGreenbeltMDUSA
| | - Benjamin Auer
- Science Systems and Applications, Inc.LanhamMDUSA
- Global Modeling and Assimilation OfficeNASA Goddard Space Flight CenterGreenbeltMDUSA
| | - Arlindo M. da Silva
- Global Modeling and Assimilation OfficeNASA Goddard Space Flight CenterGreenbeltMDUSA
| | - Anne R. Douglass
- Atmospheric Chemistry and Dynamics LaboratoryNASA Goddard Space Flight CenterGreenbeltMDUSA
| | - Bryan Duncan
- Atmospheric Chemistry and Dynamics LaboratoryNASA Goddard Space Flight CenterGreenbeltMDUSA
| | - Qing Liang
- Atmospheric Chemistry and Dynamics LaboratoryNASA Goddard Space Flight CenterGreenbeltMDUSA
- Goddard Earth Science and Technology Center, Universities Space Research AssociationColumbiaMDUSA
| | - Michael Manyin
- Science Systems and Applications, Inc.LanhamMDUSA
- Atmospheric Chemistry and Dynamics LaboratoryNASA Goddard Space Flight CenterGreenbeltMDUSA
| | - Luke D. Oman
- Atmospheric Chemistry and Dynamics LaboratoryNASA Goddard Space Flight CenterGreenbeltMDUSA
| | - William Putman
- Global Modeling and Assimilation OfficeNASA Goddard Space Flight CenterGreenbeltMDUSA
| | - Susan E. Strahan
- Atmospheric Chemistry and Dynamics LaboratoryNASA Goddard Space Flight CenterGreenbeltMDUSA
- Goddard Earth Science and Technology Center, Universities Space Research AssociationColumbiaMDUSA
| | - Krzysztof Wargan
- Science Systems and Applications, Inc.LanhamMDUSA
- Global Modeling and Assimilation OfficeNASA Goddard Space Flight CenterGreenbeltMDUSA
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Hickman JE, Huang Y, Wu S, Diru W, Groffman PM, Tully KL, Palm CA. Nonlinear response of nitric oxide fluxes to fertilizer inputs and the impacts of agricultural intensification on tropospheric ozone pollution in Kenya. GLOBAL CHANGE BIOLOGY 2017; 23:3193-3204. [PMID: 28145106 DOI: 10.1111/gcb.13644] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/14/2016] [Accepted: 11/17/2016] [Indexed: 06/06/2023]
Abstract
Crop yields in sub-Saharan Africa remain stagnant at 1 ton ha-1 , and 260 million people lack access to adequate food resources. Order-of-magnitude increases in fertilizer use are seen as a critical step in attaining food security. This increase represents an unprecedented input of nitrogen (N) to African ecosystems and will likely be accompanied by increased soil emissions of nitric oxide (NO). NO is a precursor to tropospheric ozone, an air pollutant and greenhouse gas. Emissions of NO from soils occur primarily during denitrification and nitrification, and N input rates are a key determinant of emission rates. We established experimental maize plots in western Kenya to allow us to quantify the response function relating NO flux to N input rate during the main 2011 and 2012 growing seasons. NO emissions followed a sigmoid response to fertilizer inputs and have emission factors under 1% for the roughly two-month measurement period in each year, although linear and step relationships could not be excluded in 2011. At fertilization rates above 100 kg N ha-1 , NO emissions increased without a concomitant increase in yields. We used the geos-chem chemical transport model to evaluate local impacts of increased NO emissions on tropospheric ozone concentrations. Mean 4-hour afternoon tropospheric ozone concentrations in Western Kenya increased by up to roughly 2.63 ppbv under fertilization rates of 150 kg N ha-1 or higher. Using AOT40, a metric for assessing crop damage from ozone, we find that the increased ozone concentrations result in an increase in AOT40 exposure of approximately 110 ppbh for inputs of 150 kg N ha-1 during the March-April-May crop growing season, compared with unfertilized simulations, with negligible impacts on crop productivity. Our results suggest that it may be possible to manage Kenyan agricultural systems for high yields while avoiding substantial impacts on air quality.
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Affiliation(s)
- Jonathan E Hickman
- The Earth Institute of Columbia University, 61 Route 9W, Lamont Hall, PO Box 1000, Palisades, NY, 10964, USA
| | - Yaoxian Huang
- Department of Geological & Mining Engineering & Sciences, Michigan Technological University, 1400 Townsend Drive, Houghton, MI, 49931, USA
- Now at the School of Forestry and Environmental Studies, Yale University, 195 Prospect St., New Haven, CT, 06511, USA
| | - Shiliang Wu
- Department of Geological & Mining Engineering & Sciences, Michigan Technological University, 1400 Townsend Drive, Houghton, MI, 49931, USA
- Department of Civil and Environmental Engineering, Michigan Technological University, 1400 Townsend Drive, Houghton, MI, 49931, USA
| | - Willy Diru
- Millennium Village Project, Milimani Block 10/35, Busia Road, PO Box 2389-40100, Kisumu, Kenya
| | - Peter M Groffman
- Cary Institute of Ecosystem Studies, 2801 Sharon Turnpike, PO Box AB, Millbrook, NY, 12545, USA
- City University of New York Advanced Science Research Center and Brooklyn College Department of Earth and Environmental Sciences, 85 St. Nicholas Terrace, 5th Floor, New York, NY, 10031, USA
| | - Katherine L Tully
- University of Maryland, 2108 Plant Sciences Building, College Park, MD, 20742, USA
| | - Cheryl A Palm
- The Earth Institute of Columbia University, 61 Route 9W, Lamont Hall, PO Box 1000, Palisades, NY, 10964, USA
- Now at the University of Florida, P.O. Box 110180, Gainesville, FL, 32611, USA
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Yang Y, Ingwersen WW, Hawkins TR, Srocka M, Meyer DE. USEEIO: a New and Transparent United States Environmentally-Extended Input-Output Model. JOURNAL OF CLEANER PRODUCTION 2017; 158:308-318. [PMID: 30344374 PMCID: PMC6192422 DOI: 10.1016/j.jclepro.2017.04.150] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/17/2023]
Abstract
National-scope environmental life cycle models of goods and services may be used for many purposes, not limited to quantifying impacts of production and consumption of nations, assessing organization-wide impacts, identifying purchasing hotspots, analyzing environmental impacts of policies, and performing streamlined life cycle assessment. USEEIO is a new environmentally-extended input-output model of the United States fit for such purposes and other sustainable materials management applications. USEEIO melds data on economic transactions between 389 industry sectors with environmental data for these sectors covering land, water, energy and mineral usage and emissions of greenhouse gases, criteria air pollutants, nutrients and toxics, to build a life cycle model of 385 US goods and services. In comparison with existing US models, USEEIO is more current with most data representing year 2013, more extensive in its coverage of resources and emissions, more deliberate and detailed in its interpretation and combination of data sources, and includes formal data quality evaluation and description. USEEIO is assembled with a new Python module called the IO Model Builder capable of assembling and calculating results of user-defined input-output models and exporting the models into LCA software. The model and data quality evaluation capabilities are demonstrated with an analysis of the environmental performance of an average hospital in the US. All USEEIO files are publicly available bringing a new level of transparency for environmentally-extended input-output models.
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Affiliation(s)
- Yi Yang
- CSRA Inc., Falls Church, VA 22042
- Correspondence: , 1-513-569-7602;
| | - Wesley W. Ingwersen
- US Environmental Protection Agency, National Risk Management Research Laboratory, Cincinnati, OH 45268
- Correspondence: , 1-513-569-7602;
| | - Troy R. Hawkins
- Franklin Associates, a Division of Eastern Research Group, Inc., Lexington, MA 022421
| | | | - David E. Meyer
- US Environmental Protection Agency, National Risk Management Research Laboratory, Cincinnati, OH 45268
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Yu Z, Elliott EM. Novel Method for Nitrogen Isotopic Analysis of Soil-Emitted Nitric Oxide. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2017; 51:6268-6278. [PMID: 28467082 DOI: 10.1021/acs.est.7b00592] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/20/2023]
Abstract
The global inventory of NOx (NOx = NO + NO2) emissions is poorly constrained, with a large portion of the uncertainty attributed to soil NO emissions that result from soil abiotic and microbial processes. While natural abundance stable N isotopes (δ15N) in various soil N-containing compounds have proven to be a robust tracer of soil N cycling, soil δ15N-NO is rarely quantified due to the measurement difficulties. Here, we present a new method that collects soil-emitted NO through NO conversion to NO2 in excess ozone (O3) and subsequent NO2 collection in a 20% triethanolamine (TEA) solution as nitrite and nitrate for δ15N analysis using the denitrifier method. The precision and accuracy of the method were quantified through repeated collection of an analytical NO tank and intercalibration with a modified EPA NOx collection method. The results show that the efficiency of NO conversion to NO2 and subsequent NO2 collection in the TEA solution is >98% under a variety of controlled conditions. The method precision (1σ) and accuracy across the entire analytical procedure are ±1.1‰. We report the first analyses of soil δ15N-NO (-59.8‰ to -23.4‰) from wetting-induced NO pulses at both laboratory and field scales that have important implications for understanding soil NO dynamics.
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Affiliation(s)
- Zhongjie Yu
- Department of Geology and Environmental Science, University of Pittsburgh , Pittsburgh, Pennsylvania 15260, United States
| | - Emily M Elliott
- Department of Geology and Environmental Science, University of Pittsburgh , Pittsburgh, Pennsylvania 15260, United States
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Abel D, Holloway T, Kladar RM, Meier P, Ahl D, Harkey M, Patz J. Response of Power Plant Emissions to Ambient Temperature in the Eastern United States. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2017; 51:5838-5846. [PMID: 28466642 DOI: 10.1021/acs.est.6b06201] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/28/2023]
Abstract
Past studies have established strong connections between meteorology and air quality, via chemistry, transport, and natural emissions. A less understood linkage between weather and air quality is the temperature-dependence of emissions from electricity generating units (EGUs), associated with high electricity demand to support building cooling on hot days. This study quantifies the relationship between ambient surface temperatures and EGU air emissions (CO2, SO2, and NOX) using historical data. We find that EGUs in the Eastern U.S. region from 2007 to 2012 exhibited a 3.87% ± 0.41% increase in electricity generation per °C increase during summer months. This is associated with a 3.35%/°C ± 0.50%/°C increase in SO2 emissions, a 3.60%/°C ± 0.49%/°C increase in NOX emissions, and a 3.32%/°C ± 0.36%/°C increase in CO2 emissions. Sensitivities vary by year and by pollutant, with SO2 both the highest sensitivity (5.04% in 2012) and lowest sensitivity (2.19% in 2007) in terms of a regional average. Texas displays 2007-2012 sensitivities of 2.34%/°C ± 0.28%/°C for generation, 0.91%/°C ± 0.25%/°C for SO2 emissions, 2.15%/°C ± 0.29%/°C for NOX emissions, and 1.78%/°C ± 0.22%/°C for CO2 emissions. These results suggest demand-side and supply side technological improvements and fuel choice could play an important role in cost-effective reduction of carbon emissions and air pollution.
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Affiliation(s)
- David Abel
- Center for Sustainability and the Global Environment (SAGE) Nelson Institute for Environmental Studies University of Wisconsin - Madison , Madison Wisconsin 53726, United States
| | - Tracey Holloway
- Center for Sustainability and the Global Environment (SAGE) Nelson Institute for Environmental Studies University of Wisconsin - Madison , Madison Wisconsin 53726, United States
- Department of Atmospheric and Oceanic Sciences University of Wisconsin - Madison , Madison Wisconsin 53726, United States
| | - Ryan M Kladar
- Center for Sustainability and the Global Environment (SAGE) Nelson Institute for Environmental Studies University of Wisconsin - Madison , Madison Wisconsin 53726, United States
| | - Paul Meier
- Wisconsin Energy Institute (WEI) University of Wisconsin - Madison , Madison Wisconsin 53726, United States
- University of Wisconsin - Madison - Great Lakes Bioenergy Research Center 905 Engineering Research Building, 1500 Engineering Dr., Madison, Wisconsin 53706, United States
| | - Doug Ahl
- Seventhwave, 749 University Row , Suite 320, Madison, Wisconsin 53705, United States
| | - Monica Harkey
- Center for Sustainability and the Global Environment (SAGE) Nelson Institute for Environmental Studies University of Wisconsin - Madison , Madison Wisconsin 53726, United States
| | - Jonathan Patz
- Center for Sustainability and the Global Environment (SAGE) Nelson Institute for Environmental Studies University of Wisconsin - Madison , Madison Wisconsin 53726, United States
- Global Health Institute University of Wisconsin - Madison , Madison Wisconsin 53726, United States
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50
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Abstract
Atmospheric methane (CH4) varied with climate during the Quaternary, rising from a concentration of 375 p.p.b.v. during the last glacial maximum (LGM) 21,000 years ago, to 680 p.p.b.v. at the beginning of the industrial revolution. However, the causes of this increase remain unclear; proposed hypotheses rely on fluctuations in either the magnitude of CH4 sources or CH4 atmospheric lifetime, or both. Here we use an Earth System model to provide a comprehensive assessment of these competing hypotheses, including estimates of uncertainty. We show that in this model, the global LGM CH4 source was reduced by 28–46%, and the lifetime increased by 2–8%, with a best-estimate LGM CH4 concentration of 463–480 p.p.b.v. Simulating the observed LGM concentration requires a 46–49% reduction in sources, indicating that we cannot reconcile the observed amplitude. This highlights the need for better understanding of the effects of low CO2 and cooler climate on wetlands and other natural CH4 sources. The cause of the increase in atmospheric methane from 375 p.p.b.v. during the last ice age to 680 p.p.b.v. at the onset of Industrialization remains uncertain. Here, using an Earth system model, the authors show that we cannot reconcile this rise based on our current understanding of natural methane sources.
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