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Chen Y, Shen H, Shen G, Ma J, Cheng Y, Russell AG, Zhao S, Hakami A, Tao S. Substantial differences in source contributions to carbon emissions and health damage necessitate balanced synergistic control plans in China. Nat Commun 2024; 15:5880. [PMID: 38997317 PMCID: PMC11245606 DOI: 10.1038/s41467-024-50327-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2023] [Accepted: 07/04/2024] [Indexed: 07/14/2024] Open
Abstract
China's strategy to concurrently address climate change and air pollution mitigation is hindered by a lack of comprehensive information on source contributions to health damage and carbon emissions. Here we show notable discrepancies between source contributions to CO2 emissions and fine particulate matter (PM2.5)-related mortality by using adjoint emission sensitivity modeling to attribute premature mortality in 2017 to 53 sector and fuel/process combinations with high spatial resolution. Our findings reveal that monetized PM2.5 health damage exceeds climate impacts in over half of the analyzed subsectors. In addition to coal-fired energy generators and industrial boilers, the combined health and climate costs from energy-intensive processes, diesel-powered vehicles, domestic coal combustion, and agricultural activities exceed 100 billion US dollars, with health-related costs predominating. This research highlights the critical need to integrate the social costs of health damage with climate impacts to develop more balanced mitigation strategies toward these dual goals, particularly during fuel transition and industrial structure upgrading.
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Affiliation(s)
- Yilin Chen
- School of Urban Planning and Design, Peking University Shenzhen Graduate School, Shenzhen, 518055, China.
- Shenzhen Key Laboratory of Precision Measurement and Early Warning Technology for Urban Environmental Health Risks, School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen, 518055, China.
| | - Huizhong Shen
- Shenzhen Key Laboratory of Precision Measurement and Early Warning Technology for Urban Environmental Health Risks, School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen, 518055, China
- Guangdong Provincial Observation and Research Station for Coastal Atmosphere and Climate of the Greater Bay Area, School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen, 518055, China
| | - Guofeng Shen
- College of Urban and Environmental Sciences, Peking University, Beijing, 100871, China
| | - Jianmin Ma
- College of Urban and Environmental Sciences, Peking University, Beijing, 100871, China
| | - Yafang Cheng
- Max Planck Institute for Chemistry, Mainz, 55128, Germany
| | - Armistead G Russell
- School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA, 30332, USA
| | - Shunliu Zhao
- Department of Civil and Environmental Engineering, Carleton University, Ottawa, ON, K1S5B6, Canada
| | - Amir Hakami
- Department of Civil and Environmental Engineering, Carleton University, Ottawa, ON, K1S5B6, Canada
| | - Shu Tao
- Shenzhen Key Laboratory of Precision Measurement and Early Warning Technology for Urban Environmental Health Risks, School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen, 518055, China
- College of Urban and Environmental Sciences, Peking University, Beijing, 100871, China
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2
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Kashfi Yeganeh A, Momeni M, Choi Y, Park J, Jung J. A case study of surface ozone source contributions in the Seoul metropolitan area using the adjoint of CMAQ. JOURNAL OF THE AIR & WASTE MANAGEMENT ASSOCIATION (1995) 2024; 74:511-530. [PMID: 38809877 DOI: 10.1080/10962247.2024.2361021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/04/2023] [Accepted: 05/06/2024] [Indexed: 05/31/2024]
Abstract
To quantitatively investigate the transboundary behaviors and source attributions of ozone (O3) and its precursor species over East Asia, we utilize the adjoint technique in the CMAQ modeling system (the CMAQ adjoint). Our focus is on the Seoul Metropolitan Area (SMA) in South Korea, which is the receptor region of this study. We examine the contributions of both local and transported emissions to an O3 exceedance episode observed on June 3, 2019, estimating up to four days in advance. By using the CMAQ adjoint, we can determine the sensitivity of O3 remaining in the SMA to changes in O3 precursor emissions (emissions-based sensitivity) and concentrations (concentrations-based sensitivity) along the long-range transport pathways and emission source regions overseas. These include Beijing-Tianjin-Hebei (BTH), Shandong, Yangtze River Delta (YRD), and Central China. CMAQ adjoint-derived source attributions suggest that overseas precursor emissions and O3 contributed significantly to the O3 exceedance event in SMA. The emissions-based sensitivities revealed that precursor emissions originating from Shandong, YRD, Central China, and BTH contributed 11.42 ppb, 4.28 ppb, 1.24 ppb, 0.9 ppb, respectively, to the O3 exceedance episode observed in the SMA. Meanwhile, Korean emissions contributed 31.1 ppb. Concentrations-based sensitivities indicated that 19.3 ppb of contributions originated in regions beyond eastern China and directly affected the O3 level in the SMA in the form of background O3. In addition to capturing the transboundary movements of air parcels between the source and receptor regions, we performed HYSPLIT backward trajectory analyses. The results align with the trajectories of O3 and its precursors that we obtained from the adjoint method. This study represents a unique effort in employing the adjoint technique to examine the impacts of regional O3 on South Korea, utilizing a combination of emissions-based and concentrations-based sensitivities.Implications: This research brings to light the critical role of both local and regional precursor emissions in contributing to an ozone (O3) exceedance event in the Seoul Metropolitan Area (SMA), South Korea. Utilizing the CMAQ adjoint technique, a novel approach in the context of South Korea's O3 investigations, we were able to delineate the quantitative contributions of different regions, both within South Korea and from overseas areas such as Beijing, Shandong, Shanghai, and Central China. Importantly, the results underscore the substantial influence of transboundary pollutant transport, emphasizing the need for international collaboration in addressing air quality issues. As metropolitan areas around the globe grapple with similar challenges, the methodology and insights from this study offer a potent tool and framework for regions seeking to understand and mitigate the impacts of O3 on human health and the environment. By integrating different sensitivity types, coupled with HYSPLIT backward trajectory analyses, this research equips policymakers with comprehensive data to design targeted interventions, emphasizing the significance of collaborative efforts in tackling regional air pollution challenges. However, it's important to note the limitation of this study, which is a case study conducted over a short time period. This constraint may impact the generalizability of the findings and suggests a need for further research to validate and expand upon these results.
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Affiliation(s)
- Arash Kashfi Yeganeh
- Department of Earth and Atmospheric Sciences, University of Houston, Houston, TX, USA
| | - Mahmoudreza Momeni
- Department of Earth and Atmospheric Sciences, University of Houston, Houston, TX, USA
| | - Yunsoo Choi
- Department of Earth and Atmospheric Sciences, University of Houston, Houston, TX, USA
| | - Jincheol Park
- Department of Earth and Atmospheric Sciences, University of Houston, Houston, TX, USA
| | - Jia Jung
- Department of Earth and Atmospheric Sciences, University of Houston, Houston, TX, USA
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3
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Patnaik K, Kesarkar AP, Rath S, Bhate JN, Panchal A, Chandrasekar A, Giri R. A 1-D model to retrieve the vertical profiles of minor atmospheric constituents for cloud microphysical modeling: I. Formulation and validation. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 881:163360. [PMID: 37028675 DOI: 10.1016/j.scitotenv.2023.163360] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/29/2022] [Revised: 04/03/2023] [Accepted: 04/03/2023] [Indexed: 06/01/2023]
Abstract
Determining the number concentration of minor constituents in the atmosphere is very important as it determines the whole tropospheric chemistry process. These constituents may act as cloud condensation nuclei (CCN) and ice nuclei (IN), impacting heterogeneous nucleation inside the cloud. However, the estimations of the number concentration of CCN/IN in cloud microphysical parameters are associated with uncertainties. In the present work, a hybrid Monte Carlo Gear solver has been developed to retrieve profiles of CH4, N2O, and SO2. The idealized experiments have been carried out using this solver for retrieving vertical profiles of these constituents over four megacities, viz., Delhi, Mumbai, Chennai, and Kolkata. Community Long-term Infrared Microwave Coupled Atmospheric Product System (CLIMCAPS) dataset around 0800 UTC (2000UTC) has been used for initializing the number concentration of CH4, N2O, and SO2 for daytime (nighttime). The daytime (nighttime) retrieved profiles have been validated using 2000 UTC (next day 0800 UTC) CLIMCAPS products. ERA5 temperature dataset has been used to estimate the kinematic rate of reactions with 1000 perturbations determined using Maximum Likelihood Estimation (MLE). The retrieved profiles and CLIMCAPS products are in very good agreement, as evidenced by the percentage difference between them within the range of 1.3 × 10-5-60.8 % and the coefficient of determination mainly within the range between 81 and 97 %. However, during the passage of tropical cyclone and western disturbance, its value became as low as 27 and 65 % over Chennai and Kolkata, respectively. The enactment of synoptic scale systems such as western disturbances, tropical cyclone Amphan, and easterly waves caused disturbed weather over these megacities-the retrieved profiles during disturbed weather cause large deviations of vertical profiles of N2O. However, the profiles of CH4 and SO2 have less deviation. It is inferred that incorporating this methodology in the dynamical model will be useful to simulate the realistic vertical profiles of the minor constituents in the atmosphere.
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Affiliation(s)
- Kavita Patnaik
- National Atmospheric Research Laboratory, Gadanki, Tirupati, Andhra Pradesh 517112, India; Indian Institute of Space Science and Technology, Valiamala, Kerala 695547, India
| | - Amit P Kesarkar
- National Atmospheric Research Laboratory, Gadanki, Tirupati, Andhra Pradesh 517112, India.
| | - Subhrajit Rath
- National Atmospheric Research Laboratory, Gadanki, Tirupati, Andhra Pradesh 517112, India; Indian Institute of Space Science and Technology, Valiamala, Kerala 695547, India
| | - Jyoti N Bhate
- National Atmospheric Research Laboratory, Gadanki, Tirupati, Andhra Pradesh 517112, India
| | - Abhishek Panchal
- National Atmospheric Research Laboratory, Gadanki, Tirupati, Andhra Pradesh 517112, India
| | | | - Ramakumar Giri
- India Meteorological Department, Mausam Bhavan, Lodhi Road, New Delhi, India
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4
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Wang Y, Bastien L, Jin L, Harley RA. Location-Specific Control of Precursor Emissions to Mitigate Photochemical Air Pollution. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2023. [PMID: 37329338 DOI: 10.1021/acs.est.3c01934] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/19/2023]
Abstract
The effects of precursor emission controls on air quality can vary greatly depending on where emission reductions occur. We use the adjoint of the Community Multiscale Air Quality (CMAQ) model to evaluate impacts of spatially targeted NOx emission reductions on odd oxygen (Ox = O3 + NO2). The air quality responses studied here include one population-weighted regionwide and three city-level receptors in Central California. We map high-priority locations for NOx control and their changes over decadal time scales. The desirability of NOx-focused emission control programs has increased between 2000 and 2022. We find for present-day conditions that reducing NOx emissions by 28% from targeted high-priority locations can achieve 60% of the air quality benefits of uniform NOx reductions at all locations. High-priority source locations are found to differ for individual city-level versus regionwide receptors of interest. While high-impact emission hotspots for improving city-level metrics are found within the city itself or closely adjacent, the spatial pattern of emission hotspots for improving regionwide air quality is more complex and requires comprehensive consideration of upwind sources. Results of this study can help to inform strategic decision-making at local and regional levels about where to prioritize emission control efforts.
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Affiliation(s)
- Yuhan Wang
- Department of Civil and Environmental Engineering, University of California, Berkeley, California 94720, United States
- Lawrence Berkeley National Laboratory, Berkeley, California 94720, United States
| | - Lucas Bastien
- Department of Civil and Environmental Engineering, University of California, Berkeley, California 94720, United States
- Lawrence Berkeley National Laboratory, Berkeley, California 94720, United States
| | - Ling Jin
- Lawrence Berkeley National Laboratory, Berkeley, California 94720, United States
| | - Robert A Harley
- Department of Civil and Environmental Engineering, University of California, Berkeley, California 94720, United States
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5
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Cao M, Xing J, Sahu SK, Duan L, Li J. Accurate prediction of air quality response to emissions for effective control policy design. J Environ Sci (China) 2023; 123:116-126. [PMID: 36521977 DOI: 10.1016/j.jes.2022.02.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2021] [Revised: 02/07/2022] [Accepted: 02/07/2022] [Indexed: 06/17/2023]
Abstract
Designing effective control policy requires accurate quantification of the relationship between the ambient concentrations of O3 and PM2.5 and the emissions of their precursors. However, the challenge is that precursor reduction does not necessarily lead to decreases in the concentrations of O3 and PM2.5, which are formed by multiple precursors under complex physical and chemical processes; this calls for the development of advanced model technologies to provide accurate predictions of the nonlinear responses of air quality to emissions. Different from the traditional sensitivity analysis and source apportionment methods, the reduced form models (RFMs) based on chemical transport models (CTMs) are able to quantify air quality responses to emissions more accurately and efficiently with lower computational cost. Here we review recent approaches used in RFMs and compare their structures, advantages and disadvantages, performance and applications. In general, RFMs are classified into three types including (1) sensitivity-based models, (2) models with simplified chemistry and physical processes, and (3) statistical models, with considerable differences in principles, characteristics and application ranges. The prediction of nonlinear responses by RFMs enables more in-depth analysis, not only in terms of real-time prediction of concentrations and quantification of human exposure, health impacts and economic damage, but also in optimizing control policies. Notably, data assimilation and emission inventory inversion based on the nonlinear response of concentrations to emissions can also be greatly beneficial to air pollution control management. In future studies, improvement in the performance of CTMs is exceedingly crucial to obtain a more reliable baseline for the prediction of air quality responses. Development of models to determine the air quality response to emissions under varying meteorological conditions is also necessary in the context of future climate changes, which pose great challenges to the quantification of response relationships. Additionally, with rising requirements for fine-scale air quality management, improving the performance of urban-scale simulations is worth considering. In short, accurate predictions of the response of air quality to emissions, though challenging, holds great promise for the present as well as for future scenarios.
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Affiliation(s)
- Min Cao
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
| | - Jia Xing
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China; State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China.
| | - Shovan Kumar Sahu
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
| | - Lei Duan
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China; State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
| | - Junhua Li
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China; State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
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6
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Mathur R, Kang D, Napelenok SL, Xing J, Hogrefe C, Sarwar G, Itahashi S, Henderson BH. How have Divergent Global Emission Trends Influenced Long-range Transported Ozone to North America? JOURNAL OF GEOPHYSICAL RESEARCH. ATMOSPHERES : JGR 2022; 127:0. [PMID: 36275858 PMCID: PMC9580341 DOI: 10.1029/2022jd036926] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/12/2022] [Accepted: 08/07/2022] [Indexed: 05/31/2023]
Abstract
Several locations across the United States in non-compliance with the national standard for ground-level ozone (O3) are thought to have sizeable influences from distant extra-regional emission sources or natural stratospheric O3, which complicates design of local emission control measures. To quantify the amount of long-range transported O3 (LRT O3), its origin, and change over time, we conduct and analyze detailed sensitivity calculations characterizing the response of O3 to emissions from different source regions across the Northern Hemisphere in conjunction with multi-decadal simulations of tropospheric O3 distributions and changes. Model calculations show that the amount of O3 at any location attributable to sources outside North America varies both spatially and seasonally. On a seasonal-mean basis, during 1990-2010, LRT O3 attributable to international sources steadily increased by 0.06-0.2 ppb yr-1 at locations across the United States and arose from superposition of unequal and contrasting trends in individual source-region contributions, which help inform attribution of the trend evident in O3 measurements. Contributions of emissions from Europe steadily declined through 2010, while those from Asian emissions increased and remained dominant. Steadily rising NOx emissions from international shipping resulted in increasing contributions to LRT O3, comparable to those from Asian emissions in recent years. Central American emissions contribute a significant fraction of LRT O3 in southwestern United States. In addition to the LRT O3 attributable to emissions outside of North America, background O3 across the continental United States is comprised of a sizeable and spatially variable fraction that is of stratospheric origin (29-78%).
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Affiliation(s)
- Rohit Mathur
- Center for Environmental Measurement and Modeling, Office of Research and Development, U.S. Environmental Protection Agency, RTP, NC, USA
| | - Daiwen Kang
- Center for Environmental Measurement and Modeling, Office of Research and Development, U.S. Environmental Protection Agency, RTP, NC, USA
| | - Sergey L. Napelenok
- Center for Environmental Measurement and Modeling, Office of Research and Development, U.S. Environmental Protection Agency, RTP, NC, USA
| | - Jia Xing
- Tsinghua University, Beijing, China
| | - Christian Hogrefe
- Center for Environmental Measurement and Modeling, Office of Research and Development, U.S. Environmental Protection Agency, RTP, NC, USA
| | - Golam Sarwar
- Center for Environmental Measurement and Modeling, Office of Research and Development, U.S. Environmental Protection Agency, RTP, NC, USA
| | - Syuichi Itahashi
- Environmental Science Research Laboratory, Central Research Institute of Electric Power Industry (CRIEPI), Japan
| | - Barron H. Henderson
- Office of Air Quality Planning and Standards, U.S. Environmental Protection Agency, RTP, NC, USA
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Wang C, An X, Zhao D, Sun Z, Jiang L, Li J, Hou Q. Development of GRAPES-CUACE adjoint model version 2.0 and its application in sensitivity analysis of ozone pollution in north China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 826:153879. [PMID: 35182623 DOI: 10.1016/j.scitotenv.2022.153879] [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: 10/30/2021] [Revised: 02/10/2022] [Accepted: 02/10/2022] [Indexed: 06/14/2023]
Abstract
We presented the development of the gaseous chemistry adjoint module of the meteorological-chemical model system GRAPES-CUACE (Global/Regional Assimilation and PrEdiction System coupled with CMA Unified Atmospheric Chemistry Environmental Forecasting System) on the basis of the previously constructed aerosol adjoint module. The latest version of the GRAPES-CUACE adjoint model mainly includes the adjoint of the physical and chemical processes, the adjoint of the transport processes, and the adjoint of interface programs, of both gas and aerosol. The adjoint implementation was validated for the full model, and adjoint results showed good agreement with brute force sensitivities. We also applied the newly developed adjoint model to the sensitivity analysis of an ozone episode occurred in Beijing on July 2, 2017, as well as the design of emission-reduction strategies for this episode. The relationships between the ozone concentration and precursor emissions were well captured by the adjoint model. It is indicated that for a case used here, the Beijing peak ozone concentration was influenced mostly by local emissions (6.2-24.3%), as well as by surrounding emissions, including Hebei (4.4-16.8%), Tianjin (1.8-6.6%), Shandong (1.8-2.6%), and Shanxi (<1%). In addition, reduction of NOx, VOCs, and CO emissions in these regions would effectively decrease the Beijing peak ozone concentration. This study highlights the capability of GRAPES-CUACE adjoint model in quantifying "emission-concentration" relationship and in providing guidance for environmental control policy.
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Affiliation(s)
- Chao Wang
- Department of Atmospheric and Oceanic Sciences & Institute of Atmospheric Sciences, Fudan University, Shanghai 200438, China; State Key Laboratory of Severe Weather & Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing 100081, China
| | - Xingqin An
- State Key Laboratory of Severe Weather & Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing 100081, China.
| | - Defeng Zhao
- Department of Atmospheric and Oceanic Sciences & Institute of Atmospheric Sciences, Fudan University, Shanghai 200438, China.
| | - Zhaobin Sun
- Institute of Urban Meteorology, China Meteorological Administration, Beijing 100089, China
| | - Linsen Jiang
- Institute of Electrical Engineering, Chinese Academy of Sciences, Beijing 100190, China
| | - Jiangtao Li
- State Key Laboratory of Severe Weather & Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing 100081, China
| | - Qing Hou
- State Key Laboratory of Severe Weather & Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing 100081, China
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8
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Wang Y, Bastien L, Jin L, Harley RA. Responses of Photochemical Air Pollution in California's San Joaquin Valley to Spatially and Temporally Resolved Changes in Precursor Emissions. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2022; 56:7074-7082. [PMID: 35467865 DOI: 10.1021/acs.est.1c07011] [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: 06/14/2023]
Abstract
Ground-level ozone adversely affects human health and ecosystems. The effectiveness of control programs depends on which precursor(s) are controlled, by how much, and where and when emission reductions occur. We use the adjoint of the Community Multiscale Air Quality model to investigate odd oxygen (Ox ≡ O3 + NO2) sensitivities in California's San Joaquin Valley (SJV) to precursor emissions from local and upwind sources. Sensitivities are mapped and disaggregated by hour and day. Taken together, impacts of precursor emissions in the San Francisco Bay area and Sacramento Valley are similar in magnitude to impacts of local SJV emissions. Same-day emission sensitivities are mostly attributable to local sources, with the most influential anthropogenic emissions of VOCs (volatile organic compounds) and NOx (nitrogen oxides) occurring in the morning (9-11 am) and early afternoon hours (1-3 pm), respectively. For the northernmost SJV receptor, the influence from Sacramento Valley emissions peaks 5-6 h later than Bay area emissions; this difference diminishes for SJV receptors located further downwind. Results show a shift toward more NOx-sensitive conditions in the afternoon with all but the southernmost receptor shifting from VOC- to NOx-sensitive conditions. We also evaluate opportunities to control pollution through shifts in precursor emission location and timing.
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Affiliation(s)
- Yuhan Wang
- Department of Civil and Environmental Engineering, University of California, Berkeley, California 94720, United States
| | - Lucas Bastien
- Department of Civil and Environmental Engineering, University of California, Berkeley, California 94720, United States
- Lawrence Berkeley National Laboratory, Berkeley, California 94720, United States
| | - Ling Jin
- Lawrence Berkeley National Laboratory, Berkeley, California 94720, United States
| | - Robert A Harley
- Department of Civil and Environmental Engineering, University of California, Berkeley, California 94720, United States
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9
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Thind MPS, Heath G, Zhang Y, Bhatt A. Characterization factors and other air quality impact metrics: Case study for PM 2.5-emitting area sources from biofuel feedstock supply. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 822:153418. [PMID: 35092782 DOI: 10.1016/j.scitotenv.2022.153418] [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] [Received: 01/26/2020] [Revised: 01/08/2022] [Accepted: 01/21/2022] [Indexed: 06/14/2023]
Abstract
In this paper, we develop a framework and metrics for estimating the impact of emission sources on regulatory compliance and human health for applications in air quality planning and life cycle impact assessment (LCIA). Our framework is based on a pollutant's characterization factor (CF) and three new metrics: Available Regulatory Capacity for Incremental Emissions (ARCIE), Source CF Ratio, and Activity Health Impact (AHI) Ratio. ARCIE can be used to assess whether a receptor location has capacity to accommodate additional source emissions while complying with regulatory limits. We present CF as a midpoint indicator of health impacts per unit mass of emitted pollutant. Source CF Ratio enables comparison of potential new-source locations based on human health impacts. The AHI Ratio estimates the health impacts of a pollutant in relation to the utilization of the source for each unit of product or service. These metrics can be applied to any pollutant, energy source sector (e.g., agriculture, electricity), source type (point, line, area), and spatial modeling domain (nation, state, city, region). We demonstrate these metrics through a case study of fine particulate (PM2.5) emissions from U.S. corn stover harvesting and local processing at various scales, representing steps in the biofuel production process. We model PM2.5 formation in the atmosphere using a novel reduced-complexity chemical transport model called the Intervention Model for Air Pollution (InMAP). Through this case study, we present the first area-source PM2.5 CFs that address the recommendations of several LCIA studies to establish spatially explicit CFs specific to an energy source sector or type. Overall, the framework developed in this work provides multiple new ways to consider the potential impacts of air emissions through spatially differentiated metrics.
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Affiliation(s)
- Maninder P S Thind
- National Renewable Energy Laboratory, Golden, CO 80401, United States; Department of Civil and Environmental Engineering, University of Washington, Seattle, WA 98195, United States
| | - Garvin Heath
- National Renewable Energy Laboratory, Golden, CO 80401, United States.
| | - Yimin Zhang
- National Renewable Energy Laboratory, Golden, CO 80401, United States
| | - Arpit Bhatt
- National Renewable Energy Laboratory, Golden, CO 80401, United States
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Quantification of SO2 Emission Variations and the Corresponding Prediction Improvements Made by Assimilating Ground-Based Observations. ATMOSPHERE 2022. [DOI: 10.3390/atmos13030470] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
In this research, a new time-resolved emission inversion system was developed to investigate variations in SO2 emission in China during the COVID-19 (Corona Virus Disease 2019) lockdown period based on a four-dimensional variational (4DVar) inversion method to dynamically optimize the SO2 inventory by assimilating the ground-based hourly observation data. The inversion results obtained were validated in the North China Plain (NCP). Two sets of experiments were carried out based on the original and optimized inventories during the pre-lockdown and lockdown period to quantify the SO2 emission variations and the corresponding prediction improvement. The SO2 emission changes due to the lockdown in the NCP were quantified by the differences in the averaged optimized inventories between the pre-lockdown and lockdown period. As a response to the lockdown control, the SO2 emissions were reduced by 20.1% on average in the NCP, with ratios of 20.7% in Beijing, 20.2% in Tianjin, 26.1% in Hebei, 18.3% in Shanxi, 19.1% in Shandong, and 25.9% in Henan, respectively. These were mainly attributed to the changes caused by the heavy industry lockdown in these areas. Compared to the model performance based on the original inventory, the optimized daily SO2 emission inventory significantly improved the model SO2 predictions during the lockdown period, with the correlation coefficient (R) value increasing from 0.28 to 0.79 and the root-mean-square error (RMSE) being reduced by more than 30%. Correspondingly, the performance of PM2.5 was slightly improved, with R-value increasing from 0.67 to 0.74 and the RMSE being reduced by 8% in the meantime. These statistics indicate the good optimization ability of the time-resolved emission inversion system.
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11
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Assimilation of GOSAT Methane in the Hemispheric CMAQ; Part I: Design of the Assimilation System. REMOTE SENSING 2022. [DOI: 10.3390/rs14020371] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Abstract
We present a parametric Kalman filter data assimilation system using GOSAT methane observations within the hemispheric CMAQ model. The assimilation system produces forecasts and analyses of concentrations and explicitly computes its evolving error variance while remaining computationally competitive with other data assimilation schemes such as 4-dimensional variational (4D-Var) and ensemble Kalman filter (EnKF). The error variance in this system is advected using the native advection scheme of the CMAQ model and updated at each analysis while the error correlations are kept fixed. We discuss extensions to the CMAQ model to include methane transport and emissions (both anthropogenic and natural) and perform a bias correction for the GOSAT observations. The results using synthetic observations show that the analysis error and analysis increments follow the advective flow while conserving the information content (i.e., total variance). We also demonstrate that the vertical error correlation contributes to the inference of variables down to the surface. In a companion paper, we use this assimilation system to obtain optimal assimilation of GOSAT observations.
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12
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Shen H, Sun Z, Chen Y, Russell AG, Hu Y, Odman MT, Qian Y, Archibald AT, Tao S. Novel Method for Ozone Isopleth Construction and Diagnosis for the Ozone Control Strategy of Chinese Cities. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2021; 55:15625-15636. [PMID: 34787397 DOI: 10.1021/acs.est.1c01567] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
Ozone (O3) isopleths describe the nonlinear responses of O3 concentrations to changes in nitrogen oxides (NOX) and volatile organic compounds (VOCs) and thus are pivotal to the determination of O3 control requirements. In this study, we innovatively use the Community Multiscale Air Quality model with the high-order decoupled direct method (CMAQ-HDDM) to simulate O3 pollution of China in 2017 and derive O3 isopleths for individual cities. Our simulation covering the entire China Mainland suggests severe O3 pollution as 97% of the residents experienced at least 1 day, in 2017, in excess of Chinese Level-II Ambient Air Quality Standards for O3 as 160 μg·m-3 (81.5 ppbV equally). The O3 responses to emissions of precursors vary widely across individual cities. Densely populated metropolitan areas such as Jing-Jin-Ji, Yangtze River Delta, and Pearl River Delta are following NOX-saturated regimes, where a small amount of NOX reduction increases O3. Ambient O3 pollution in the eastern region generally is limited by VOCs, while in the west by NOX. The city-specific O3 isopleths generated in this study are instrumental in forming hybrid and differentiated strategies for O3 abatement in China.
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Affiliation(s)
- Huizhong Shen
- School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, China
- School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, United States
| | - Zhe Sun
- Centre for Atmospheric Science, Yusuf Hamied Department of Chemistry, University of Cambridge, Cambridge CB2 1EW, United Kingdom
| | - Yilin Chen
- School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, China
- School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, United States
| | - Armistead G Russell
- School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, United States
| | - Yongtao Hu
- School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, United States
| | - Mehmet Talât Odman
- School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, United States
| | - Yu Qian
- School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, United States
| | - Alexander T Archibald
- Centre for Atmospheric Science, Yusuf Hamied Department of Chemistry, University of Cambridge, Cambridge CB2 1EW, United Kingdom
| | - Shu Tao
- College of Urban and Environmental Sciences, Laboratory for Earth Surface Processes, Sino-French Institute for Earth System Science, Peking University, Beijing 100871, China
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13
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Wang M, Huang T, Wong DC, Ho KF, Dong G, Yim SHL. A new approach for health-oriented ozone control strategy: Adjoint-based optimization of NO x emission reductions using metaheuristic algorithms. JOURNAL OF CLEANER PRODUCTION 2021; 312:127533. [PMID: 34248301 PMCID: PMC8262626 DOI: 10.1016/j.jclepro.2021.127533] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
While levels of particulate matters in the Pearl River Delta Region (PRD) show a significant reduction, ozone (O3) has an opposite increasing trend, becoming the critical air quality target in this decade. Emission control strategies are typically formulated sector by sector, spatial variability in emissions reductions and health impacts of air pollutants may not be taken into account, affecting the overall effectiveness of control strategies. This study proposes an adjoint-based optimization framework to facilitate health-oriented O3 control over PRD. The location-specific adjoint sensitivity coefficients, which reflect the spatiotemporal influences from emissions of nitrogen dioxide (NOx) on O3 health impacts, are combined with metaheuristic algorithms to minimize the O3-related premature mortalities over receptor regions. Using the proposed optimization methodology, the regional O3 health benefits under current emission reduction policy can be increased by 16-27%. The results show that relatively larger NOx emissions reductions occurred at highly developed and populated areas. Particularly, significant reductions in NOx emissions are observed at Shenzhen and urban Guangzhou. Furthermore, implementing regional NOx emissions abatement has advantages to achieve an overall O3 health benefits for all cities. The interregional influences of NOx emissions abatement between cities indicate a promising strategy of health-oriented O3 control in PRD.
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Affiliation(s)
- Mengya Wang
- Department of Geography and Resource Management, The Chinese University of Hong Kong, Sha Tin, N.T., Hong Kong, China
| | - Tao Huang
- Department of Geography and Resource Management, The Chinese University of Hong Kong, Sha Tin, N.T., Hong Kong, China
| | - David C. Wong
- Computational Exposure Division, National Exposure Research Laboratory, US Environmental Protection Agency, Hong Kong, China
| | - Kin Fai Ho
- The Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong, China
- Institute of Environment, Energy and Sustainability, The Chinese University of Hong Kong, Sha Tin, N.T., Hong Kong, China
| | - Guanghui Dong
- Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Guangzhou Key Laboratory of Environmental Pollution and Health Risk Assessment, Department of Preventive Medicine, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
| | - Steve H. L. Yim
- Department of Geography and Resource Management, The Chinese University of Hong Kong, Sha Tin, N.T., Hong Kong, China
- Institute of Environment, Energy and Sustainability, The Chinese University of Hong Kong, Sha Tin, N.T., Hong Kong, China
- Stanley Ho Big Data Decision Analytics Research Centre, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong, China
- Asian School of the Environment, Nanyang Technological University, Singapore
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14
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Liu C, Zhang S, Gao Y, Wang Y, Sheng L, Gao H, Fung JCH. Optimal estimation of initial concentrations and emission sources with 4D-Var for air pollution prediction in a 2D transport model. THE SCIENCE OF THE TOTAL ENVIRONMENT 2021; 773:145580. [PMID: 33582338 DOI: 10.1016/j.scitotenv.2021.145580] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/31/2020] [Revised: 01/13/2021] [Accepted: 01/28/2021] [Indexed: 06/12/2023]
Abstract
Attributing sources of air pollution events by deploying an efficient observational network is an important and interesting problem in air quality control and forecast studies, but it is very challenging. In order to estimate the sensitivities of pollution events to emission sources, a comprehensive framework is built based on a horizontal 2-dimensional transport model and its adjoint in solving this problem. In an analysis of an idealized air pollution event of PM2.5 over the region of North China, an objective function is defined to optimally estimate the initial concentrations and emission sources through a series of minimization procedures. Results by means of the 4-dimensional variational approach show that, with the optimal initial conditions and emission sources, the model can successfully forecast the pollution event in a few days. The optimal observing network based on sensitivity analysis takes only one third of the cost but greatly retains predictability skill compared to the full-grid observing system, while nearly no predictability skill is detectable if the same number of observational sites is randomly deployed. We evaluate air pollution predictability in the point of focusing on to what degree the root mean square errors between the modeled concentration and the targeted air pollution are limited by the optimal observational network. Results show that air pollution predictability in association with the optimal observational network is limited in the time scales about 6 days. With the high efficiency and in an economic fashion, such a sensitivity-based optimal observing system holds promise for accurately predicting an air pollution event in the targeted area once the adjoint and variational procedure of a realistic atmosphere model including transport and chemical processes is performed.
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Affiliation(s)
- Caili Liu
- The College of Oceanic and Atmospheric Sciences, Ocean University of China, Qingdao, China
| | - Shaoqing Zhang
- The College of Oceanic and Atmospheric Sciences, Ocean University of China, Qingdao, China; Key Laboratory of Physical Oceanography, MOE, Institute for Advanced Ocean Study, Frontiers Science Center for Deep Ocean Multispheres and Earth System (FDOMES), Ocean University of China, China; Ocean Dynamics and Climate Function Lab, Pilot National Laboratory for Marine Science and Technology (QNLM), Qingdao, China; International Laboratory for High-Resolution Earth System Model and Prediction (iHESP), Qingdao, China.
| | - Yang Gao
- Key Laboratory of Marine Environment and Ecology, and Frontiers Science Center for Deep Ocean Multispheres and Earth System (FDOMES), Ministry of Education, Ocean University of China, Qingdao 266100, China; Ocean Dynamics and Climate Function Lab, Pilot National Laboratory for Marine Science and Technology (QNLM), Qingdao, China.
| | - Yuhang Wang
- School of Earth and Atmospheric Sciences, Georgia Institute of Technology, Atlanta, GA 30332, United States of America
| | - Lifang Sheng
- The College of Oceanic and Atmospheric Sciences, Ocean University of China, Qingdao, China
| | - Huiwang Gao
- Key Laboratory of Marine Environment and Ecology, and Frontiers Science Center for Deep Ocean Multispheres and Earth System (FDOMES), Ministry of Education, Ocean University of China, Qingdao 266100, China
| | - J C H Fung
- Division of Environment and Sustainability, Hong Kong University of Science and Technology, China
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15
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The Combined Effects of Fine Particulate Matter and Temperature on Preterm Birth in Seoul, 2010-2016. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2021; 18:ijerph18041463. [PMID: 33557331 PMCID: PMC7914592 DOI: 10.3390/ijerph18041463] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/30/2020] [Revised: 01/22/2021] [Accepted: 01/29/2021] [Indexed: 12/13/2022]
Abstract
Background: Preterm birth contributes to the morbidity and mortality of newborns and infants. Recent studies have shown that maternal exposure to particulate matter and extreme temperatures results in immune dysfunction, which can induce preterm birth. This study aimed to evaluate the association between fine particulate matter (PM2.5) exposure, temperature, and preterm birth in Seoul, Republic of Korea. Methods: We used 2010–2016 birth data from Seoul, obtained from the Korea National Statistical Office Microdata. PM2.5 concentration data from Seoul were generated through the Community Multiscale Air Quality (CMAQ) model. Seoul temperature data were collected from the Korea Meteorological Administration (KMA). The exposure period of PM2.5 and temperature were divided into the first (TR1), second (TR2), and third (TR3) trimesters of pregnancy. The mean PM2.5 concentration was used in units of ×10 µg/m3 and the mean temperature was divided into four categories based on quartiles. Logistic regression analyses were performed to evaluate the association between PM2.5 exposure and preterm birth, as well as the combined effects of PM2.5 exposure and temperature on preterm birth. Result: In a model that includes three trimesters of PM2.5 and temperature data as exposures, which assumes an interaction between PM2.5 and temperature in each trimester, the risk of preterm birth was positively associated with TR1 PM2.5 exposure among pregnant women exposed to relatively low mean temperatures (<3.4 °C) during TR1 (OR 1.134, 95% CI 1.061–1.213, p < 0.001). Conclusions: When we assumed the interaction between PM2.5 exposure and temperature exposure, PM2.5 exposure during TR1 increased the risk of preterm birth among pregnant women exposed to low temperatures during TR1. Pregnant women should be aware of the risk associated with combined exposure to particulate matter and low temperatures during TR1 to prevent preterm birth.
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16
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Kwag Y, Kim MH, Oh J, Shah S, Ye S, Ha EH. Effect of heat waves and fine particulate matter on preterm births in Korea from 2010 to 2016. ENVIRONMENT INTERNATIONAL 2021; 147:106239. [PMID: 33341584 DOI: 10.1016/j.envint.2020.106239] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/29/2020] [Revised: 10/21/2020] [Accepted: 10/21/2020] [Indexed: 06/12/2023]
Abstract
BACKGROUND Previous studies have reported that fine particulate matter (PM2.5) affects the incidence of premature births. In addition, recent studies have suggested that heat waves have a negative impact on birth outcomes. However, the combined effect of PM2.5 and heat waves on the incidence of premature birth is controversial. This study investigated the independent and combined effects of PM2.5 and heat wave exposures during the 1st and 2nd trimesters on premature birth. METHODS The National Statistical Office of Korea provided birth data from 2010 to 2016. Preterm birth was defined as birth between 22 and 36 weeks. To assess the exposure to PM2.5 and heat waves, we used PM2.5 data estimated by the Community Multiscale Air Quality Modeling System (CMAQ) and heat wave warning data provided by the Korea Meteorological Administration. A multivariate logistic regression was used to investigate the risk of preterm birth according to the exposure to PM2.5 and heat waves during the 1st and 2nd trimesters, and it was adjusted for residential area, year of birth, season of birth, parity, education level of the mother, age of the mother, and sex of the baby. RESULTS In the 2nd trimester, compared with the 0 h of heat wave exposure (≤67 percentile), 62.50-314.00 h (79-88 percentile) and>315.00 h of heat wave exposure (>88 percentile) were both significantly associated with preterm birth (OR for 79-88 percentile, 1.037, 95% CI, 1.003-1.073; OR for > 88 percentile, 1.174, 95% CI, 1.134-1.215). However, PM2.5 exposure was not significantly associated with preterm birth. On the other hand, in the analysis to evaluate the combined effect of PM2.5 and heat wave exposures of the 2nd trimester, compared with 0 h of heat wave exposure (≤67 percentile) and<11.64 μg/m3 (≤25 percentile) of PM2.5, 11.64-22.74 μg/m3 (≤25 percentile), 22.74-27.58 μg/m3 (26-50 percentile), and 27.57-32.39 μg/m3 (51-75 percentile) of PM2.5 exposure combined with>315.00 h of heat wave exposure (>88 percentile) were all significantly associated with preterm birth. In addition, the effect size was increased with an increase of PM2.5 exposure (OR for ≤ 25 percentile, 1.148, 95% CI, 1.095-1.203; OR for 26-50 percentile, 1.248, 95% CI, 1.178-1.323; OR for 51-75 percentile, 1.370, 95% CI, 1.245-1.507). CONCLUSION Our findings suggest that the combined effect of heat wave and PM2.5 exposure during the 2nd trimester on the risk of preterm birth was greater than that of each exposure alone. In other words, exposure to PM2.5 increases the impact of heat waves on the risk of preterm birth. These results indicate that control of prenatal exposure to fine particular matter and extreme temperatures is important for the prevention of preterm birth.
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Affiliation(s)
- Youngrin Kwag
- Department of Occupational and Environmental Medicine, School of Medicine, Ewha Womans University, Seoul, Republic of Korea
| | - Min-Ho Kim
- Ewha University-Industry Collaboration Foundation Ewha Womans University, Seoul, Republic of Korea
| | - Jongmin Oh
- Department of Occupational and Environmental Medicine, School of Medicine, Ewha Womans University, Seoul, Republic of Korea
| | - Surabhi Shah
- Department of Occupational and Environmental Medicine, School of Medicine, Ewha Womans University, Seoul, Republic of Korea
| | - Shinhee Ye
- Occupational Safety and Health Research Institute, Korea Occupational Safety and Health Agency, Incheon, Republic of Korea.
| | - Eun-Hee Ha
- Department of Occupational and Environmental Medicine, School of Medicine, Ewha Womans University, Seoul, Republic of Korea.
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17
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Shen H, Shen G, Chen Y, Russell AG, Hu Y, Duan X, Meng W, Xu Y, Yun X, Lyu B, Zhao S, Hakami A, Guo J, Tao S, Smith KR. Increased air pollution exposure among the Chinese population during the national quarantine in 2020. Nat Hum Behav 2021; 5:239-246. [PMID: 33398145 DOI: 10.31223/osf.io/6d9rn] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2020] [Accepted: 11/18/2020] [Indexed: 05/26/2023]
Abstract
The COVID-19 quarantine in China is thought to have reduced ambient air pollution. The overall exposure of the population also depends, however, on indoor air quality and human mobility and activities. Here, by integrating real-time mobility data and a questionnaire survey on time-activity patterns during the pandemic, we show that despite a decrease in ambient PM2.5 during the quarantine, the total population-weighted exposure to PM2.5 considering both indoor and outdoor environments increased by 5.7 μg m-3 (95% confidence interval, 1.2-11.0 μg m-3). The increase in population-weighted exposure was mainly driven by a nationwide urban-to-rural population migration before the Spring Festival coupled with the freezing of the migration backward due to the quarantine, which increased household energy consumption and the fraction of people exposed to rural household air pollution indoors. Our analysis reveals an increased inequality of air pollution exposure during the quarantine and highlights the importance of household air pollution for population health in China.
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Affiliation(s)
- Huizhong Shen
- School of Civil & Environmental Engineering, Georgia Institute of Technology, Atlanta, GA, USA
- College of Urban and Environmental Sciences, Laboratory for Earth Surface Processes, Sino-French Institute for Earth System Science, Peking University, Beijing, China
| | - Guofeng Shen
- College of Urban and Environmental Sciences, Laboratory for Earth Surface Processes, Sino-French Institute for Earth System Science, Peking University, Beijing, China.
| | - Yilin Chen
- School of Civil & Environmental Engineering, Georgia Institute of Technology, Atlanta, GA, USA
| | - Armistead G Russell
- School of Civil & Environmental Engineering, Georgia Institute of Technology, Atlanta, GA, USA
| | - Yongtao Hu
- School of Civil & Environmental Engineering, Georgia Institute of Technology, Atlanta, GA, USA
| | - Xiaoli Duan
- School of Energy and Environmental Engineering, University of Science and Technology Beijing, Beijing, China
| | - Wenjun Meng
- College of Urban and Environmental Sciences, Laboratory for Earth Surface Processes, Sino-French Institute for Earth System Science, Peking University, Beijing, China
| | - Yang Xu
- College of Urban and Environmental Sciences, Laboratory for Earth Surface Processes, Sino-French Institute for Earth System Science, Peking University, Beijing, China
| | - Xiao Yun
- College of Urban and Environmental Sciences, Laboratory for Earth Surface Processes, Sino-French Institute for Earth System Science, Peking University, Beijing, China
| | - Baolei Lyu
- Huayun Sounding Meteorology Technology Corporation, Beijing, China
| | - Shunliu Zhao
- Department of Civil and Environmental Engineering, Carleton University, Ottawa, Ontario, Canada
| | - Amir Hakami
- Department of Civil and Environmental Engineering, Carleton University, Ottawa, Ontario, Canada
| | - Jianping Guo
- The State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing, China
| | - Shu Tao
- College of Urban and Environmental Sciences, Laboratory for Earth Surface Processes, Sino-French Institute for Earth System Science, Peking University, Beijing, China
| | - Kirk R Smith
- Environmental Health Sciences, School of Public Health, University of California, Berkeley, CA, USA
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18
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Shen H, Shen G, Chen Y, Russell AG, Hu Y, Duan X, Meng W, Xu Y, Yun X, Lyu B, Zhao S, Hakami A, Guo J, Tao S, Smith KR. Increased air pollution exposure among the Chinese population during the national quarantine in 2020. Nat Hum Behav 2021; 5:239-246. [PMID: 33398145 DOI: 10.1038/s41562-020-01018-z] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2020] [Accepted: 11/18/2020] [Indexed: 12/12/2022]
Abstract
The COVID-19 quarantine in China is thought to have reduced ambient air pollution. The overall exposure of the population also depends, however, on indoor air quality and human mobility and activities. Here, by integrating real-time mobility data and a questionnaire survey on time-activity patterns during the pandemic, we show that despite a decrease in ambient PM2.5 during the quarantine, the total population-weighted exposure to PM2.5 considering both indoor and outdoor environments increased by 5.7 μg m-3 (95% confidence interval, 1.2-11.0 μg m-3). The increase in population-weighted exposure was mainly driven by a nationwide urban-to-rural population migration before the Spring Festival coupled with the freezing of the migration backward due to the quarantine, which increased household energy consumption and the fraction of people exposed to rural household air pollution indoors. Our analysis reveals an increased inequality of air pollution exposure during the quarantine and highlights the importance of household air pollution for population health in China.
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Affiliation(s)
- Huizhong Shen
- School of Civil & Environmental Engineering, Georgia Institute of Technology, Atlanta, GA, USA.,College of Urban and Environmental Sciences, Laboratory for Earth Surface Processes, Sino-French Institute for Earth System Science, Peking University, Beijing, China
| | - Guofeng Shen
- College of Urban and Environmental Sciences, Laboratory for Earth Surface Processes, Sino-French Institute for Earth System Science, Peking University, Beijing, China.
| | - Yilin Chen
- School of Civil & Environmental Engineering, Georgia Institute of Technology, Atlanta, GA, USA
| | - Armistead G Russell
- School of Civil & Environmental Engineering, Georgia Institute of Technology, Atlanta, GA, USA
| | - Yongtao Hu
- School of Civil & Environmental Engineering, Georgia Institute of Technology, Atlanta, GA, USA
| | - Xiaoli Duan
- School of Energy and Environmental Engineering, University of Science and Technology Beijing, Beijing, China
| | - Wenjun Meng
- College of Urban and Environmental Sciences, Laboratory for Earth Surface Processes, Sino-French Institute for Earth System Science, Peking University, Beijing, China
| | - Yang Xu
- College of Urban and Environmental Sciences, Laboratory for Earth Surface Processes, Sino-French Institute for Earth System Science, Peking University, Beijing, China
| | - Xiao Yun
- College of Urban and Environmental Sciences, Laboratory for Earth Surface Processes, Sino-French Institute for Earth System Science, Peking University, Beijing, China
| | - Baolei Lyu
- Huayun Sounding Meteorology Technology Corporation, Beijing, China
| | - Shunliu Zhao
- Department of Civil and Environmental Engineering, Carleton University, Ottawa, Ontario, Canada
| | - Amir Hakami
- Department of Civil and Environmental Engineering, Carleton University, Ottawa, Ontario, Canada
| | - Jianping Guo
- The State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing, China
| | - Shu Tao
- College of Urban and Environmental Sciences, Laboratory for Earth Surface Processes, Sino-French Institute for Earth System Science, Peking University, Beijing, China
| | - Kirk R Smith
- Environmental Health Sciences, School of Public Health, University of California, Berkeley, CA, USA
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19
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Zhao S, Russell MG, Hakami A, Capps SL, Turner MD, Henze DK, Percell PB, Resler J, Shen H, Russell AG, Nenes A, Pappin AJ, Napelenok SL, Bash JO, Fahey KM, Carmichael GR, Stanier CO, Chai T. A multiphase CMAQ version 5.0 adjoint. GEOSCIENTIFIC MODEL DEVELOPMENT 2020; 13:2925-2944. [PMID: 33343831 PMCID: PMC7745733 DOI: 10.5194/gmd-13-2925-2020] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/31/2023]
Abstract
We present the development of a multiphase adjoint for the Community Multiscale Air Quality (CMAQ) model, a widely used chemical transport model. The adjoint model provides location- and time-specific gradients that can be used in various applications such as backward sensitivity analysis, source attribution, optimal pollution control, data assimilation, and inverse modeling. The science processes of the CMAQ model include gas-phase chemistry, aerosol dynamics and thermodynamics, cloud chemistry and dynamics, diffusion, and advection. Discrete adjoints are implemented for all the science processes, with an additional continuous adjoint for advection. The development of discrete adjoints is assisted with algorithmic differentiation (AD) tools. Particularly, the Kinetic PreProcessor (KPP) is implemented for gas-phase and aqueous chemistry, and two different automatic differentiation tools are used for other processes such as clouds, aerosols, diffusion, and advection. The continuous adjoint of advection is developed manually. For adjoint validation, the brute-force or finite-difference method (FDM) is implemented process by process with box- or column-model simulations. Due to the inherent limitations of the FDM caused by numerical round-off errors, the complex variable method (CVM) is adopted where necessary. The adjoint model often shows better agreement with the CVM than with the FDM. The adjoints of all science processes compare favorably with the FDM and CVM. In an example application of the full multiphase adjoint model, we provide the first estimates of how emissions of particulate matter (PM2.5) affect public health across the US.
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Affiliation(s)
- Shunliu Zhao
- Department of Civil and Environmental Engineering, Carleton University, Ottawa, ON K1S 5B6, Canada
| | - Matthew G. Russell
- Department of Civil and Environmental Engineering, Carleton University, Ottawa, ON K1S 5B6, Canada
| | - Amir Hakami
- Department of Civil and Environmental Engineering, Carleton University, Ottawa, ON K1S 5B6, Canada
| | - Shannon L. Capps
- Civil, Architectural, and Environmental Engineering, Drexel University, Philadelphia, PA 19104, USA
| | | | - Daven K. Henze
- Mechanical Engineering Department, University of Colorado, Boulder, CO 80309, USA
| | - Peter B. Percell
- Department of Earth & Atmospheric Sciences, University of Houston, Houston, TX 77204, USA
| | - Jaroslav Resler
- Institute of Computer Science of the Czech Academy of Sciences, Prague, 182 07, Czech Republic
| | - Huizhong Shen
- School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA 30331, USA
| | - Armistead G. Russell
- School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA 30331, USA
| | - Athanasios Nenes
- School of Earth and Atmospheric Sciences, Georgia Institute of Technology, Atlanta, GA 30331, USA
- School of Architecture, Civil & Environmental Engineering, École polytechnique fédérale de Lausanne, 1015, Lausanne, Switzerland
- Institute for Chemical Engineering Sciences, Foundation for Research and Technology Hellas, Patras, 26504, Greece
| | - Amanda J. Pappin
- Air Health Effects Division, Health Canada, Ottawa, ON K1A 0K9, Canada
| | - Sergey L. Napelenok
- Atmospheric & Environmental Systems Modeling Division, U.S. EPA, Research Triangle Park, NC 27711, USA
| | - Jesse O. Bash
- Atmospheric & Environmental Systems Modeling Division, U.S. EPA, Research Triangle Park, NC 27711, USA
| | - Kathleen M. Fahey
- Atmospheric & Environmental Systems Modeling Division, U.S. EPA, Research Triangle Park, NC 27711, USA
| | - Gregory R. Carmichael
- Department of Chemical and Biochemical Engineering, University of Iowa, Iowa City, IA 52242, USA
| | - Charles O. Stanier
- Department of Chemical and Biochemical Engineering, University of Iowa, Iowa City, IA 52242, USA
| | - Tianfeng Chai
- College of Computer, Mathematical, and Natural Sciences, University of Maryland, College Park, MD 20742, USA
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20
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Yang X, Xiao H, Wu Q, Wang L, Guo Q, Cheng H, Wang R, Tang Z. Numerical study of air pollution over a typical basin topography: Source appointment of fine particulate matter during one severe haze in the megacity Xi'an. THE SCIENCE OF THE TOTAL ENVIRONMENT 2020; 708:135213. [PMID: 31812406 DOI: 10.1016/j.scitotenv.2019.135213] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/12/2019] [Revised: 10/23/2019] [Accepted: 10/24/2019] [Indexed: 06/10/2023]
Abstract
Many cities are located in lands with typical basin topographies, which are not conducive to the spread of air pollutants. In the winter of 2016/2017, a severe haze happened in Xi'an, the main city in the Guanzhong Basin in central China. When the peak daily concentration of fine particulate matter (PM2.5) reaches 499 μg/m3, the source of the atmospheric pollution needs to be found urgently in order to take countermeasures. The comprehensive air quality model with extensions, coupled with the tracer tagging particulate source apportionment technology (PSAT) module, and an improved emission inventory, higher grid resolution, and bigger inner domain area, have been applied to quantify the contributions of local and regional emissions to the PM2.5 pollutions. The model performed well in time period considered in this study. The correlation of the simulated daily PM2.5 concentration data reaches 0.82, and the fraction of predictions within a factor of two of observations approaches 84%. With the PSAT module, the PM2.5 contributions from local and regional sources to the urban centre and rural areas during the severe winter haze event are analysed in detail. The PM2.5 concentrations in the urban centre in Xi'an is mainly originating from local emissions (60%), and Xianyang City is the largest contributor among the surrounding source regions (11.6%), while the transportation sector outside the Shaanxi Province (5.1%) also contributes significantly. Comparatively, the rural areas have lower local contributions and higher transport contributions. In particular, in the northern rural area Yanliang, the contribution from surrounding source regions approaches 82%. The results of this study suggest that to improve the air quality in a typical basin city, a regional-scale coordinated emissions control should be used, focusing on the emissions from both local and surrounding areas.
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Affiliation(s)
- Xiaochun Yang
- College of Global Change and Earth System Science, Beijing Normal University, Beijing 100875, China; Xi'an Meteorological Bureau, Xi'an, Shaanxi Province 710016, China; Joint Centre for Global Change Studies, Beijing Normal University, Beijing 100875, China
| | - Han Xiao
- College of Global Change and Earth System Science, Beijing Normal University, Beijing 100875, China; Joint Centre for Global Change Studies, Beijing Normal University, Beijing 100875, China
| | - Qizhong Wu
- College of Global Change and Earth System Science, Beijing Normal University, Beijing 100875, China; Joint Centre for Global Change Studies, Beijing Normal University, Beijing 100875, China.
| | - Lanning Wang
- College of Global Change and Earth System Science, Beijing Normal University, Beijing 100875, China; Joint Centre for Global Change Studies, Beijing Normal University, Beijing 100875, China
| | - Qingyuan Guo
- Xi'an Meteorological Bureau, Xi'an, Shaanxi Province 710016, China
| | - Huaqiong Cheng
- College of Global Change and Earth System Science, Beijing Normal University, Beijing 100875, China; Joint Centre for Global Change Studies, Beijing Normal University, Beijing 100875, China
| | - Rongrong Wang
- College of Global Change and Earth System Science, Beijing Normal University, Beijing 100875, China; Joint Centre for Global Change Studies, Beijing Normal University, Beijing 100875, China
| | - Zhiyi Tang
- Department of Engineering Mechanics, School of Aerospace Engineering, Xi'an Jiaotong University, Shaanxi Province 710049, China
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21
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Wang M, Yim SH, Dong G, Ho K, Wong D. Mapping ozone source-receptor relationship and apportioning the health impact in the Pearl River Delta region using adjoint sensitivity analysis. ATMOSPHERIC ENVIRONMENT (OXFORD, ENGLAND : 1994) 2020; 222:1-117026. [PMID: 32461735 PMCID: PMC7252566 DOI: 10.1016/j.atmosenv.2019.117026] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
While fine particulate matters are decreasing in the Pearl River Delta (PRD) region, the regional ozone (O3) shows an increasing trend that affects human health, leading to an urgent need for scientific understanding of source-receptor relationship between O3 and its precursor emissions given the changing background composition. We advanced and applied an adjoint air quality model to map contributions of individual O3 precursor emission sources [nitrogen oxides (NOx) and volatile organic compound (VOC)] at each location to annual regional O3 concentrations and to identify the possible dominant influential pathways of emission sources to O3 at different spatiotemporal scales. Additionally, we introduced the novel adjoint sensitivity approach to assess the relationship between precursor emissions and O3-induced premature mortality. Adjoint results show that Shenzhen was a major source contributor to regional O3 throughout all seasons, of which 49.4% (3.8%) were from its NOx (VOC) emissions. Local emissions (within PRD) contributed to 83% of the regional O3 whereas only ~54% of the estimated ~4000 regional O3-induced premature mortalities. The discrepancy between these two contributions was because O3-induced mortalities are dependent on not only O3 concentration, but incident rate and population density. We also found that a city with low O3-induced mortalities could have significant emission contributions to health impact in the region since the transport pathways could be through transport of local O3 or through transport of O3 precursors that form regional O3 thereafter. It is therefore necessary to formulate emission control policies from both air quality and public health perspectives, and it is also critical to have better understanding of influential pathways of emission sources to O3.
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Affiliation(s)
- M.Y. Wang
- Department of Geography and Resource Management, The Chinese University of Hong Kong, Sha Tin, N.T., Hong Kong, China
| | - Steve H.L. Yim
- Department of Geography and Resource Management, The Chinese University of Hong Kong, Sha Tin, N.T., Hong Kong, China
- Institute of Environment, Energy and Sustainability, The Chinese University of Hong Kong, Sha Tin, N.T., Hong Kong, China
- Stanley Ho Big Data Decision Analytics Research Centre, The Chinese University of Hong Kong, Sha Tin, N.T., Hong Kong, China
| | - G.H. Dong
- Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Guangzhou Key Laboratory of Environmental Pollution and Health Risk Assessment, Department of Preventive Medicine, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
| | - K.F. Ho
- Institute of Environment, Energy and Sustainability, The Chinese University of Hong Kong, Sha Tin, N.T., Hong Kong, China
- The Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Sha Tin, N.T., Hong Kong, China
| | - D.C. Wong
- Computational Exposure Division, National Exposure Research Laboratory, US Environmental Protection Agency, USA
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22
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Thind MPS, Tessum CW, Azevedo IL, Marshall JD. Fine Particulate Air Pollution from Electricity Generation in the US: Health Impacts by Race, Income, and Geography. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2019; 53:14010-14019. [PMID: 31746196 DOI: 10.1021/acs.est.9b02527] [Citation(s) in RCA: 34] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/18/2023]
Abstract
Electricity generation is a large contributor to fine particulate matter (PM2.5) air pollution. However, the demographic distribution of the resulting exposure is largely unknown. We estimate exposures to and health impacts of PM2.5 from electricity generation in the US, for each of the seven Regional Transmission Organizations (RTOs), for each US state, by income and by race. We find that average exposures are the highest for blacks, followed by non-Latino whites. Exposures for remaining groups (e.g., Asians, Native Americans, Latinos) are somewhat lower. Disparities by race/ethnicity are observed for each income category, indicating that the racial/ethnic differences hold even after accounting for differences in income. Levels of disparity differ by state and RTO. Exposures are higher for lower-income than for higher-income, but disparities are larger by race than by income. Geographically, we observe large differences between where electricity is generated and where people experience the resulting PM2.5 health consequences; some states are net exporters of health impacts, other are net importers. For 36 US states, most of the health impacts are attributable to emissions in other states. Most of the total impacts are attributable to coal rather than other fuels.
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Affiliation(s)
- Maninder P S Thind
- Department of Civil and Environmental Engineering , University of Washington , Seattle , Washington 98195 , United States
| | - Christopher W Tessum
- Department of Civil and Environmental Engineering , University of Washington , Seattle , Washington 98195 , United States
| | - Inês L Azevedo
- Department of Energy Resources Engineering, School of Earth, Energy and the Environment , Stanford University , Stanford , California 94305 , United States
| | - Julian D Marshall
- Department of Civil and Environmental Engineering , University of Washington , Seattle , Washington 98195 , United States
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23
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Wang MY, Yim SHL, Wong DC, Ho KF. Source contributions of surface ozone in China using an adjoint sensitivity analysis. THE SCIENCE OF THE TOTAL ENVIRONMENT 2019; 662:385-392. [PMID: 30690372 PMCID: PMC6875754 DOI: 10.1016/j.scitotenv.2019.01.116] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/10/2018] [Revised: 11/27/2018] [Accepted: 01/10/2019] [Indexed: 05/26/2023]
Abstract
Air pollution has become an adverse environmental problem in China, resulting in serious public health impacts. This study advanced and applied the CMAQ adjoint model to quantitatively assess the source-receptor relationships between surface ozone (O3) changes over different receptor regions and precursor emissions across all locations in China. Five receptor regions were defined based on the administrative division, including northern China (NC), southern China (SC), Pearl River Delta region (PRD), Yangtz River Delta region (YRD), and Beijing-Tianjin-Hebei region (BTH). Our results identified the different influential pathways of atmospheric processes and emissions to O3 pollution. We found that the atmospheric processes such as horizontal and vertical advection could offset the O3 removal through chemical reactions in VOC-limited areas inside the receptor regions. In addition, O3 pollution can be induced by transport of O3 directly or its precursors. Our results of relative source contributions to O3 show that transboundary O3 pollution was significant in SC, NC and YRD, while the O3 pollution in PRD and BTH were more contributed by local sources. Anhui, Hubei and Jiangsu provinces were the three largest source areas of NOx and VOC emissions to O3 in SC (>52%) and YRD (>69%). NOx and VOC emissions from Tianjin and Beijing were the largest contributors to O3 in NC (>34%) and BTH (>51%). PRD was the dominant source areas of NOx (>89%) and VOC emissions (~98%) to its own regional O3.
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Affiliation(s)
- M Y Wang
- Department of Geography and Resource Management, The Chinese University of Hong Kong, Sha Tin, N.T., Hong Kong
| | - Steve H L Yim
- Department of Geography and Resource Management, The Chinese University of Hong Kong, Sha Tin, N.T., Hong Kong; Institute of Environment, Energy and Sustainability, The Chinese University of Hong Kong, Sha Tin, N.T., Hong Kong; Stanley Ho Big Data Decision Analytics Research Centre, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong.
| | - D C Wong
- Computational Exposure Division, National Exposure Research Laboratory, US Environmental Protection Agency, United States of America
| | - K F Ho
- The Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong; Institute of Environment, Energy and Sustainability, The Chinese University of Hong Kong, Sha Tin, N.T., Hong Kong
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24
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Lu L, Chen B, Guo L, Zhang H, Li Y. A regional data assimilation system for estimating CO surface flux from atmospheric mixing ratio observations-a case study of Xuzhou, China. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2019; 26:8748-8757. [PMID: 30712203 DOI: 10.1007/s11356-019-04246-7] [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: 09/04/2018] [Accepted: 01/14/2019] [Indexed: 06/09/2023]
Abstract
Carbon monoxide (CO) emission inventory data are crucial for air quality control. However, the emission inventories are labor-intensive and time-consuming and generally have large uncertainties. In this study, we developed a new regional data assimilation system (TracersTracker) for estimating the surface CO emission flux from continuous mixing ratio observations using the proper orthogonal decomposition (POD)-based four-dimensional variational (4D-VAR) data assimilation method (POD-4DVar) and a coupled regional model (Weather Research and Forecasting model (WRF) with the Models-3 Community Multi-scale Air Quality (CMAQ) model). This system was applied to estimate CO emissions in Xuzhou city, China. An experiment was conducted with the continuous hourly surface CO mixing ratio observations from 21 monitoring towers in January and July of 2016. The experimental results of the system were examined and compared with the continuous surface CO observations (a priori emission). We found that the retrieved CO emission fluxes were higher than the a priori emission and were mainly distributed in urban and industrial areas, which were 104% higher in January (winter) and 44% higher in July (summer).
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Affiliation(s)
- Lijiang Lu
- School of Environment Science and Spatial Information, China University of Mining and Technology, Xuzhou, 221116, China
| | - Baozhang Chen
- School of Environment Science and Spatial Information, China University of Mining and Technology, Xuzhou, 221116, China.
- Chinese Academy of Sciences, Institute of Geographic Sciences & Nature Resources Research, Beijing, 100101, China.
- University of Chinese Academy of Sciences, No. 19A, Yuquan Road, Beijing, 100049, China.
| | - Lifeng Guo
- Chinese Academy of Sciences, Institute of Geographic Sciences & Nature Resources Research, Beijing, 100101, China
- University of Chinese Academy of Sciences, No. 19A, Yuquan Road, Beijing, 100049, China
| | - Huifang Zhang
- Chinese Academy of Sciences, Institute of Geographic Sciences & Nature Resources Research, Beijing, 100101, China
- University of Chinese Academy of Sciences, No. 19A, Yuquan Road, Beijing, 100049, China
| | - Yanpeng Li
- School of Environment Science and Spatial Information, China University of Mining and Technology, Xuzhou, 221116, China
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25
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Mathur R, Hogrefe C, Hakami A, Zhao S, Szykman J, Hagler G. A Call for an Aloft Air Quality Monitoring Network: Need, Feasibility, and Potential Value. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2018; 52:10903-10908. [PMID: 30180558 PMCID: PMC6261453 DOI: 10.1021/acs.est.8b02496] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/30/2023]
Abstract
Changing precursor emission patterns in conjunction with stringent health protective air quality standards necessitate accurate quantification of nonlocal contributions to ozone pollution at a location due to atmospheric transport, that by nature predominantly occurs aloft nocturnally. Concerted efforts to characterize ozone aloft on a continuous basis to quantify its contribution to ground-level concentrations, however, are lacking. By applying our classical understanding of air pollution dynamics to analyze variations in widespread surface-level ozone measurements, in conjunction with process-based interpretation from a comprehensive air pollution modeling system and detailed backward-sensitivity calculations that quantitatively link surface-level and aloft pollution, we show that accurate quantification of the amount of ozone in the air entrained from aloft every morning as the atmospheric boundary layer grows is the key missing component for characterizing background pollution at a location, and we propose a cost-effective continuous aloft ozone measurement strategy to address critical scientific gaps in current air quality management. Continuous aloft air pollution measurements can be achieved cost-effectively through leveraging advances in sensor technology and proliferation of tall telecommunications masts. Resultant improvements in ozone distribution characterization at 400-500 m altitude are estimated to be 3-4 times more effective in characterizing the surface-level daily maximum 8-h average ozone (DM8O3) than improvements from surface measurements since they directly quantify the amount of pollution imported to a location and furnish key missing information on processes and sources regulating background ozone and its modulation of ground-level concentrations. Since >80% of the DM8O3 sensitivity to tropospheric ozone is potentially captured through measurements between 200 and 1200 m altitude (a possible design goal for future remote sensing instrumentation), their assimilation will dramatically improve air quality forecast and health advisories.
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Affiliation(s)
- Rohit Mathur
- National Exposure Research Laboratory, Office of Research and Development, U.S. Environmental Protection Agency, RTP, NC, USA
| | - Christian Hogrefe
- National Exposure Research Laboratory, Office of Research and Development, U.S. Environmental Protection Agency, RTP, NC, USA
| | - Amir Hakami
- Department of Civil and Environmental Engineering, Carleton University, Ottawa, Canada
| | - Shunliu Zhao
- Department of Civil and Environmental Engineering, Carleton University, Ottawa, Canada
| | - James Szykman
- National Exposure Research Laboratory, Office of Research and Development, U.S. Environmental Protection Agency, RTP, NC, USA
| | - Gayle Hagler
- National Exposure Research Laboratory, Office of Research and Development, U.S. Environmental Protection Agency, RTP, NC, USA
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26
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Heo J, Adams PJ, Gao HO. Public health costs accounting of inorganic PM 2.5 pollution in metropolitan areas of the United States using a risk-based source-receptor model. ENVIRONMENT INTERNATIONAL 2017; 106:119-126. [PMID: 28633084 DOI: 10.1016/j.envint.2017.06.006] [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: 02/23/2017] [Revised: 06/02/2017] [Accepted: 06/07/2017] [Indexed: 05/25/2023]
Abstract
In order to design effective strategies to reduce the public health burden of ambient fine particulate matter (PM2.5) imposed in an area, it is necessary to identify the emissions sources affecting that location and quantify their contributions. However, it is challenging because PM2.5 travels long distances and most constituents are the result of complex chemical processes. We developed a reduced-form source-receptor model for estimating locations and magnitudes of downwind health costs from a source or, conversely, the upwind sources that contribute to health costs at a receptor location. Built upon outputs from a state-of-the-art air quality model, our model produces comprehensive risk-based source apportionment results with trivial computational costs. Using the model, we analyzed all the sources contributing to the inorganic PM2.5 health burden in 14 metropolitan statistical areas (MSAs) in the United States. Our analysis for 12 source categories shows that 80-90% of the burden borne by these areas originates from emissions sources outside of the area and that emissions sources up to 800 km away need to be included to account for 80% of the burden. Conversely, 60-80% of the impacts of an MSA's emissions occurs outside of that MSA. The results demonstrate the importance of regionally coordinated measures to improve air quality in metropolitan areas.
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Affiliation(s)
- Jinhyok Heo
- School of Civil and Environmental Engineering, Cornell University, Ithaca, NY 14853, United States
| | - Peter J Adams
- Department of Civil and Environmental Engineering, Carnegie Mellon University, Pittsburgh, PA 15213, United States; Department of Engineering and Public Policy, Carnegie Mellon University, Pittsburgh, PA 15213, United States
| | - H Oliver Gao
- School of Civil and Environmental Engineering, Cornell University, Ithaca, NY 14853, United States.
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27
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Li X, Zhang Q, Zhang Y, Zhang L, Wang Y, Zhang Q, Li M, Zheng Y, Geng G, Wallington TJ, Han W, Shen W, He K. Attribution of PM 2.5 exposure in Beijing-Tianjin-Hebei region to emissions: implication to control strategies. Sci Bull (Beijing) 2017; 62:957-964. [PMID: 36659467 DOI: 10.1016/j.scib.2017.06.005] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2017] [Revised: 06/07/2017] [Accepted: 06/09/2017] [Indexed: 01/21/2023]
Abstract
The Beijing-Tianjin-Hebei (BTH) region is one of the most heavily polluted regions in China, with both high PM2.5 concentrations and a high population density. A quantitative source-receptor relationship can provide valuable insights that can inform effective emission control strategies. Both source apportionment (SA) and source sensitivity (SS) can provide such information from different perspectives. In this study, both methods are applied in northern China to identify the most significant emission categories and source regions for PM2.5 exposure in BTH in 2013. Despite their differences, both models show similar distribution patterns for population and simulated PM2.5 concentrations, resulting in overall high PM2.5 exposure values (approximately 110μg/m3) and particularly high exposure values during the winter (approximately 200μg/m3). Both methods show that local emissions play a dominant role (70%), with some contribution from surrounding provinces (e.g., Shandong) via regional transport. The two methods also agree on the priority of local emission controls: both identify industrial, residential, and agricultural emissions as the top three categories that should be controlled locally. In addition, the effect of controlling agricultural ammonia emissions is approximately doubled when the co-benefits of reducing nitrate are considered. The synthesis of SA and SS for addressing specific categories of emissions provides a quantitative basis for the development of emission control strategies and policies for controlling PM2.5 in China.
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Affiliation(s)
- Xin Li
- Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing 100084, China; Department of Marine, Earth, and Atmospheric Sciences, North Carolina State University, Raleigh, NC 27695, USA
| | - Qiang Zhang
- Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing 100084, China; Collaborative Innovation Center for Regional Environmental Quality, Beijing 100084, China.
| | - Yang Zhang
- Department of Marine, Earth, and Atmospheric Sciences, North Carolina State University, Raleigh, NC 27695, USA; Collaborative Innovation Center for Regional Environmental Quality, Beijing 100084, China
| | - Lin Zhang
- Laboratory for Climate and Ocean-Atmosphere Sciences, Department of Atmospheric and Oceanic Sciences, School of Physics, Peking University, Beijing 100871, China
| | - Yuxuan Wang
- Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing 100084, China; Department of Marine Sciences, Texas A&M University at Galveston, Galveston, TX, USA; Department of Atmospheric Sciences, Texas A&M University, College Station, TX, USA
| | - Qianqian Zhang
- National Satellite Meteorological Center, China Meteorological Administration, Beijing 100081, China
| | - Meng Li
- Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing 100084, China
| | - Yixuan Zheng
- Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing 100084, China
| | - Guannan Geng
- Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing 100084, China
| | - Timothy J Wallington
- Research and Advanced Engineering, Ford Motor Company, Village Road, Dearborn MI 48121, USA
| | - Weijian Han
- Research and Advanced Engineering, Ford Motor Company, Village Road, Dearborn MI 48121, USA
| | - Wei Shen
- Asia Pacific Research, Ford Motor Company, Beijing 100022, China
| | - Kebin He
- Collaborative Innovation Center for Regional Environmental Quality, Beijing 100084, China; State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
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28
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Tessum CW, Hill JD, Marshall JD. InMAP: A model for air pollution interventions. PLoS One 2017; 12:e0176131. [PMID: 28423049 PMCID: PMC5397056 DOI: 10.1371/journal.pone.0176131] [Citation(s) in RCA: 68] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2016] [Accepted: 04/05/2017] [Indexed: 01/24/2023] Open
Abstract
Mechanistic air pollution modeling is essential in air quality management, yet the extensive expertise and computational resources required to run most models prevent their use in many situations where their results would be useful. Here, we present InMAP (Intervention Model for Air Pollution), which offers an alternative to comprehensive air quality models for estimating the air pollution health impacts of emission reductions and other potential interventions. InMAP estimates annual-average changes in primary and secondary fine particle (PM2.5) concentrations-the air pollution outcome generally causing the largest monetized health damages-attributable to annual changes in precursor emissions. InMAP leverages pre-processed physical and chemical information from the output of a state-of-the-science chemical transport model and a variable spatial resolution computational grid to perform simulations that are several orders of magnitude less computationally intensive than comprehensive model simulations. In comparisons run here, InMAP recreates comprehensive model predictions of changes in total PM2.5 concentrations with population-weighted mean fractional bias (MFB) of -17% and population-weighted R2 = 0.90. Although InMAP is not specifically designed to reproduce total observed concentrations, it is able to do so within published air quality model performance criteria for total PM2.5. Potential uses of InMAP include studying exposure, health, and environmental justice impacts of potential shifts in emissions for annual-average PM2.5. InMAP can be trained to run for any spatial and temporal domain given the availability of appropriate simulation output from a comprehensive model. The InMAP model source code and input data are freely available online under an open-source license.
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Affiliation(s)
- Christopher W. Tessum
- Department of Civil and Environmental Engineering, University of Washington, Seattle, Washington, United States of America
- * E-mail:
| | - Jason D. Hill
- Department of Bioproducts and Biosystems Engineering, University of Minnesota, St. Paul, Minnesota, United States of America
| | - Julian D. Marshall
- Department of Civil and Environmental Engineering, University of Washington, Seattle, Washington, United States of America
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29
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Mesbah SM, Hakami A, Schott S. Optimal Ozone Control with Inclusion of Spatiotemporal Marginal Damages and Electricity Demand. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2015; 49:7870-7878. [PMID: 26053406 DOI: 10.1021/acs.est.5b01178] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/04/2023]
Abstract
Marginal damage (MD), or damage per ton of emission, is a policy metric used for effective pollution control and reducing the corresponding adverse health impacts. However, for a pollutant such as NOx, the MD varies by the time and location of the emissions, a complication that is not adequately accounted for in the currently implemented economic instruments. Policies accounting for MD information would aim to encourage emitters with large MDs to reduce their emissions. An optimization framework is implemented to account for NOx spatiotemporal MDs calculated through adjoint sensitivity analysis and to simulate power plants' behavior under emission and simplified electricity constraints. The results from a case study of U.S. power plants indicate that time-specific MDs are high around noon and low in the evening. Furthermore, an emissions reduction of about 40% and a net benefit of about $1200 million can be gained for this subset of power plants if a larger fraction of the electricity demand is supplied by power plants at low-damage times and in low-damage locations. The results also indicate that the consideration of temporal effects in NOx control policies results in a comparable net benefit to the consideration of spatial or spatiotemporal effects, thus providing a promising option for policy development.
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Affiliation(s)
- S Morteza Mesbah
- Department of Civil and Environmental Engineering, Carleton University, 1125 Colonel By Drive, Ottawa, Ontario K1S 5B6, Canada
- Department of Civil and Environmental Engineering, Carleton University, 1125 Colonel By Drive, Ottawa, Ontario K1S 5B6, Canada
- School of Public Policy and Administration, Carleton University, 1125 Colonel By Drive, Ottawa, Ontario K1S 5B6, Canada
| | - Amir Hakami
- Department of Civil and Environmental Engineering, Carleton University, 1125 Colonel By Drive, Ottawa, Ontario K1S 5B6, Canada
- Department of Civil and Environmental Engineering, Carleton University, 1125 Colonel By Drive, Ottawa, Ontario K1S 5B6, Canada
- School of Public Policy and Administration, Carleton University, 1125 Colonel By Drive, Ottawa, Ontario K1S 5B6, Canada
| | - Stephan Schott
- Department of Civil and Environmental Engineering, Carleton University, 1125 Colonel By Drive, Ottawa, Ontario K1S 5B6, Canada
- Department of Civil and Environmental Engineering, Carleton University, 1125 Colonel By Drive, Ottawa, Ontario K1S 5B6, Canada
- School of Public Policy and Administration, Carleton University, 1125 Colonel By Drive, Ottawa, Ontario K1S 5B6, Canada
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30
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Bastien LAJ, McDonald BC, Brown NJ, Harley RA. High-resolution mapping of sources contributing to urban air pollution using adjoint sensitivity analysis: benzene and diesel black carbon. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2015; 49:7276-7284. [PMID: 26001097 DOI: 10.1021/acs.est.5b00686] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/04/2023]
Abstract
The adjoint of the Community Multiscale Air Quality (CMAQ) model at 1 km horizontal resolution is used to map emissions that contribute to ambient concentrations of benzene and diesel black carbon (BC) in the San Francisco Bay area. Model responses of interest include population-weighted average concentrations for three highly polluted receptor areas and the entire air basin. We consider both summer (July) and winter (December) conditions. We introduce a novel approach to evaluate adjoint sensitivity calculations that complements existing methods. Adjoint sensitivities to emissions are found to be accurate to within a few percent, except at some locations associated with large sensitivities to emissions. Sensitivity of model responses to emissions is larger in winter, reflecting weaker atmospheric transport and mixing. The contribution of sources located within each receptor area to the same receptor's air pollution burden increases from 38-74% in summer to 56-85% in winter. The contribution of local sources is higher for diesel BC (62-85%) than for benzene (38-71%), reflecting the difference in these pollutants' atmospheric lifetimes. Morning (6-9am) and afternoon (4-7 pm) commuting-related emissions dominate region-wide benzene levels in winter (14 and 25% of the total response, respectively). In contrast, afternoon rush hour emissions do not contribute significantly in summer. Similar morning and afternoon peaks in sensitivity to emissions are observed for the BC response; these peaks are shifted toward midday because most diesel truck traffic occurs during off-peak hours.
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Affiliation(s)
- Lucas A J Bastien
- †University of California at Berkeley, Berkeley, California 94720, United States
- ‡Lawrence Berkeley National Laboratory, Berkeley, California 94720, United States
| | - Brian C McDonald
- †University of California at Berkeley, Berkeley, California 94720, United States
| | - Nancy J Brown
- †University of California at Berkeley, Berkeley, California 94720, United States
- ‡Lawrence Berkeley National Laboratory, Berkeley, California 94720, United States
| | - Robert A Harley
- †University of California at Berkeley, Berkeley, California 94720, United States
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31
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Liao KJ, Hou X. Optimization of multipollutant air quality management strategies: A case study for five cities in the United States. JOURNAL OF THE AIR & WASTE MANAGEMENT ASSOCIATION (1995) 2015; 65:732-742. [PMID: 25976486 DOI: 10.1080/10962247.2015.1014073] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/04/2023]
Abstract
UNLABELLED Developing regional air quality management strategies is a difficult task because formation of air pollutants is interdependent and air quality at different locations may have different responses to emissions from common sources. We developed an optimization-based model, OPtimal integrated Emission Reduction Alternatives (OPERA), which allows for identifications of least-cost control strategies for attaining multipollutant air quality targets at multiple locations simultaneously. To implement OPERA, first, sensitivities of air quality to precursor emission changes are quantified. Second, cost functions of emission reductions are estimated using a cost analysis tool that includes a pool of available control measures. The third step is to determine desired reductions in concentrations of air pollutants. The last step is to identify the optimal control strategies by minimizing costs of emission controls using the sensitivities of air pollutants to emission changes, cost functions, and constraints for feasible emission reduction ratios. A case study that investigates ozone and PM2.5 air quality in the summer of 2007 for five major cities in the eastern United States is presented in this paper. The results of the OPERA calculations show that reductions in regional NOx and VOC as well as local primary PM2.5 emissions were more cost-effective than SO2 controls for decreasing ozone and total PM2.5 concentrations in the summer of 2007. This was because reductions in SO2 emissions would only decrease PM2.5 concentrations, and reductions in primary PM2.5 emissions were more cost-effective than SO2 emission controls. IMPLICATIONS We developed an optimization-based model, OPtimal integrated Emission Reduction Alternatives (OPERA), which allows for identification of least-cost emission control strategies for attaining multipollutant air quality targets at multiple locations simultaneously. A major strength of OPERA is its flexibility, which allows for changes in air quality regulations, involving agencies, study regions, and so on, to be readily incorporated. Overall, it has been demonstrated that OPERA is useful in developing least-cost emission control strategies for achieving multipollutant air quality targets at multiple locations simultaneously and could be useful for policymakers developing integrated air quality management plans.
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Affiliation(s)
- Kuo-Jen Liao
- a Department of Environmental Engineering , Texas A&M University-Kingsville , Kingsville , TX , USA
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Holt J, Selin NE, Solomon S. Changes in inorganic fine particulate matter sensitivities to precursors due to large-scale US emissions reductions. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2015; 49:4834-41. [PMID: 25816113 DOI: 10.1021/acs.est.5b00008] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/25/2023]
Abstract
We examined the impact of large US emissions changes, similar to those estimated to have occurred between 2005 and 2012 (high and low emissions cases, respectively), on inorganic PM2.5 sensitivities to further NOx, SO2, and NH3 emissions reductions using the chemical transport model GEOS-Chem. Sensitivities to SO2 emissions are larger year-round and across the US in the low emissions case than the high emissions case due to more aqueous-phase SO2 oxidation. Sensitivities to winter NOx emissions are larger in the low emissions case, more than 2× those of the high emissions case in parts of the northern Midwest. Sensitivities to NH3 emissions are smaller (∼40%) in the low emissions case, year-round, and across the US. Differences in NOx and NH3 sensitivities indicate an altered atmospheric acidity. Larger sensitivities to SO2 and NOx in the low emissions case imply that reducing these emissions may improve air quality more now than they would have in 2005; conversely, NH3 reductions may not improve air quality as much as previously assumed.
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Affiliation(s)
- Jareth Holt
- †Department of Earth, Atmospheric and Planetary Sciences, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Building 54-1711, Cambridge, Massachusetts 02139, United States
| | - Noelle E Selin
- †Department of Earth, Atmospheric and Planetary Sciences, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Building 54-1711, Cambridge, Massachusetts 02139, United States
- ‡Engineering Systems Division, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
| | - Susan Solomon
- †Department of Earth, Atmospheric and Planetary Sciences, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Building 54-1711, Cambridge, Massachusetts 02139, United States
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Turner MD, Henze DK, Hakami A, Zhao S, Resler J, Carmichael GR, Stanier CO, Baek J, Sandu A, Russell AG, Nenes A, Jeong GR, Capps SL, Percell PB, Pinder RW, Napelenok SL, Bash JO, Chai T. Differences between magnitudes and health impacts of BC emissions across the United States using 12 km scale seasonal source apportionment. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2015; 49:4362-4371. [PMID: 25729920 DOI: 10.1021/es505968b] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/04/2023]
Abstract
Recent assessments have analyzed the health impacts of PM2.5 from emissions from different locations and sectors using simplified or reduced-form air quality models. Here we present an alternative approach using the adjoint of the Community Multiscale Air Quality (CMAQ) model, which provides source-receptor relationships at highly resolved sectoral, spatial, and temporal scales. While damage resulting from anthropogenic emissions of BC is strongly correlated with population and premature death, we found little correlation between damage and emission magnitude, suggesting that controls on the largest emissions may not be the most efficient means of reducing damage resulting from anthropogenic BC emissions. Rather, the best proxy for locations with damaging BC emissions is locations where premature deaths occur. Onroad diesel and nonroad vehicle emissions are the largest contributors to premature deaths attributed to exposure to BC, while onroad gasoline emissions cause the highest deaths per amount emitted. Emissions in fall and winter contribute to more premature deaths (and more per amount emitted) than emissions in spring and summer. Overall, these results show the value of the high-resolution source attribution for determining the locations, seasons, and sectors for which BC emission controls have the most effective health benefits.
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Affiliation(s)
- Matthew D Turner
- †Mechanical Engineering Department, University of Colorado, Boulder, Colorado 80309, United States
| | - Daven K Henze
- †Mechanical Engineering Department, University of Colorado, Boulder, Colorado 80309, United States
| | - Amir Hakami
- ‡Department of Civil and Environmental Engineering, Carleton University, Ottawa, Ontario K1S 5B6, Canada
| | - Shunliu Zhao
- ‡Department of Civil and Environmental Engineering, Carleton University, Ottawa, Ontario K1S 5B6, Canada
| | - Jaroslav Resler
- §Nonlinear Modeling, Institute of Computer Science, Prague 182 07, Czech Republic
| | - Gregory R Carmichael
- ∥Department of Chemical and Biochemical Engineering, University of Iowa, Iowa City, Iowa 52242, United States
| | - Charles O Stanier
- ∥Department of Chemical and Biochemical Engineering, University of Iowa, Iowa City, Iowa 52242, United States
| | - Jaemeen Baek
- ∥Department of Chemical and Biochemical Engineering, University of Iowa, Iowa City, Iowa 52242, United States
| | - Adrian Sandu
- ⊥Computer Science, Virginia Tech, Blacksburg, Virginia 24061, United States
| | | | - Athanasios Nenes
- ▲School of Chemical and Biomolecular Engineering, Georgia Tech, Atlanta, Georgia 30332, United States
| | - Gill-Ran Jeong
- ◇Korea Institute of Atmospheric Prediction Systems, Seoul 156-849, Republic of Korea
| | - Shannon L Capps
- □Atmospheric Modeling and Analysis Division, U.S. EPA, Research Triangle Park, North Carolina 27711, United States
| | - Peter B Percell
- ◆Department of Geosciences, University of Houston, Houston, Texas 77004, United States
| | - Rob W Pinder
- □Atmospheric Modeling and Analysis Division, U.S. EPA, Research Triangle Park, North Carolina 27711, United States
| | - Sergey L Napelenok
- □Atmospheric Modeling and Analysis Division, U.S. EPA, Research Triangle Park, North Carolina 27711, United States
| | - Jesse O Bash
- □Atmospheric Modeling and Analysis Division, U.S. EPA, Research Triangle Park, North Carolina 27711, United States
| | - Tianfeng Chai
- ■College of Computer, Mathematical, and Natural Sciences, University of Maryland, College Park, Maryland 20742, United States
- △Air Resources Laboratory, National Oceanic and Atmospheric Administration, College Park, Maryland 20740, United States
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Lin JC, Wen D. A method to quantitatively apportion pollutants at high spatial and temporal resolution: the Stochastic Lagrangian Apportionment Method (SLAM). ENVIRONMENTAL SCIENCE & TECHNOLOGY 2015; 49:351-360. [PMID: 25437345 DOI: 10.1021/es505603v] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/04/2023]
Abstract
We introduce a method to quantify upwind contributions to concentrations of atmospheric pollutants. The Stochastic Lagrangian Apportionment Method (SLAM) carries out the following: (1) account for chemical transformations and depositional losses; (2) incorporate the effects of turbulent dispersion; (3) simulate the locations of the sources with high spatial and temporal resolution; and (4) minimize the impact from numerical diffusion. SLAM accomplishes these four features by using a time-reversed Lagrangian particle dispersion model and then simulating chemical changes forward in time, while tagging and keeping track of different sources. As an example of SLAM's application, we show its use in apportioning sources contributing to ammonia (NH3) and ammonium particulates (p-NH4(+)) at a site in southern Ontario, Canada. Agricultural emissions are seen to dominate contributions to NH3 and p-NH4(+) at the site. The source region of NH3 was significantly smaller than that of p-NH4(+), which covered numerous states of the American Midwest. The source apportionment results from SLAM were compared against those from zeroing-out individual sources ("brute force method"; BFM). The comparisons show SLAM to produce almost identical results as BFM for NH3, but higher concentrations of p-NH4(+), likely due to indirect effects that affect BFM. Finally, uncertainties in the SLAM approach and ways to address such shortcomings by combining SLAM with inverse methods are discussed.
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Affiliation(s)
- John C Lin
- Department of Atmospheric Sciences, University of Utah , Salt Lake City, Utah 84112-0102, United States
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Liu Z, Bambha RP, Pinto JP, Zeng T, Boylan J, Huang M, Lei H, Zhao C, Liu S, Mao J, Schwalm CR, Shi X, Wei Y, Michelsen HA. Toward verifying fossil fuel CO2 emissions with the CMAQ model: motivation, model description and initial simulation. JOURNAL OF THE AIR & WASTE MANAGEMENT ASSOCIATION (1995) 2014; 64:419-435. [PMID: 24843913 DOI: 10.1080/10962247.2013.816642] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/03/2023]
Abstract
UNLABELLED Motivated by the question of whether and how a state-of-the-art regional chemical transport model (CTM) can facilitate characterization of CO2 spatiotemporal variability and verify CO2 fossil-fuel emissions, we for the first time applied the Community Multiscale Air Quality (CMAQ) model to simulate CO2. This paper presents methods, input data, and initial results for CO2 simulation using CMAQ over the contiguous United States in October 2007. Modeling experiments have been performed to understand the roles of fossil-fuel emissions, biosphere-atmosphere exchange, and meteorology in regulating the spatial distribution of CO2 near the surface over the contiguous United States. Three sets of net ecosystem exchange (NEE) fluxes were used as input to assess the impact of uncertainty of NEE on CO2 concentrations simulated by CMAQ. Observational data from six tall tower sites across the country were used to evaluate model performance. In particular, at the Boulder Atmospheric Observatory (BAO), a tall tower site that receives urban emissions from Denver CO, the CMAQ model using hourly varying, high-resolution CO2 fossil-fuel emissions from the Vulcan inventory and Carbon Tracker optimized NEE reproduced the observed diurnal profile of CO2 reasonably well but with a low bias in the early morning. The spatial distribution of CO2 was found to correlate with NO(x), SO2, and CO, because of their similar fossil-fuel emission sources and common transport processes. These initial results from CMAQ demonstrate the potential of using a regional CTM to help interpret CO2 observations and understand CO2 variability in space and time. The ability to simulate a full suite of air pollutants in CMAQ will also facilitate investigations of their use as tracers for CO2 source attribution. This work serves as a proof of concept and the foundation for more comprehensive examinations of CO2 spatiotemporal variability and various uncertainties in the future. IMPLICATIONS Atmospheric CO2 has long been modeled and studied on continental to global scales to understand the global carbon cycle. This work demonstrates the potential of modeling and studying CO2 variability at fine spatiotemporal scales with CMAQ, which has been applied extensively, to study traditionally regulated air pollutants. The abundant observational records of these air pollutants and successful experience in studying and reducing their emissions may be useful for verifying CO2 emissions. Although there remains much more to further investigate, this work opens up a discussion on whether and how to study CO2 as an air pollutant.
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Pappin AJ, Hakami A. Attainment vs exposure: ozone metric responses to source-specific NOx controls using adjoint sensitivity analysis. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2013; 47:13519-13527. [PMID: 24143935 DOI: 10.1021/es4024145] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/02/2023]
Abstract
We establish linkages between sources of NOx emissions and two types of national ozone metrics in Canada and the U.S. using the adjoint of an air quality model. We define an attainment-based metric using probabilistic design values (PDVs) exceeding 65 ppb to represent polluted regions and define an exposure-based metric as the premature mortality count related to short-term ozone exposure, both in Canada and the U.S. Our results reveal differences in both temporally averaged and day-specific influences of NOx emission controls across source locations. We find NOx emission reductions in California and the eastern U.S. to be most effective for reducing attainment- and exposure-based metrics, amounting to a total reduction of 6500 ppb in PDVs and 613 deaths/season nationally from a 10% reduction in NOx emissions from those source locations. While source controls in the remainder of the western U.S. are beneficial at reducing nonattainment, these reductions are less influential on ozone mortality. We also find that while exposure-based metrics are sensitive to daily emission reductions, much of the reduction in PDVs arises from controlling emissions on only a fraction of simulation days. We further illustrate the dependency of adjoint estimates of emission influences on the choice of averaging period as a follow-up to previous work.
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Affiliation(s)
- Amanda J Pappin
- Department of Civil and Environmental Engineering, Carleton University , 1125 Colonel By Drive, Ottawa, ON, Canada K1S 5B6
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Mesbah SM, Hakami A, Schott S. Optimal ozone reduction policy design using adjoint-based NOx marginal damage information. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2013; 47:13528-13535. [PMID: 24144173 DOI: 10.1021/es402531n] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/02/2023]
Abstract
Despite substantial reductions in nitrogen oxide (NOx) emissions in the United States, the success of emission control programs in optimal ozone reduction is disputable because they do not consider the spatial and temporal differences in health and environmental damages caused by NOx emissions. This shortcoming in the current U.S. NOx control policy is explored, and various methodologies for identifying optimal NOx emission control strategies are evaluated. The proposed approach combines an optimization platform with an adjoint (or backward) sensitivity analysis model and is able to examine the environmental performance of the current cap-and-trade policy and two damage-based emissions-differentiated policies. Using the proposed methodology, a 2007 case study of 218 U.S. electricity generation units participating in the NOx trading program is examined. The results indicate that inclusion of damage information can significantly enhance public health performance of an economic instrument. The net benefit under the policy that minimizes the social cost (i.e., health costs plus abatement costs) is six times larger than that of an exchange rate cap-and-trade policy.
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Affiliation(s)
- S Morteza Mesbah
- Department of Civil and Environmental Engineering and ‡Department of Public Policy and Administration, Carleton University , 1125 Colonel By Dr., Ottawa, ON K1S 5B6, Canada
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Pappin AJ, Hakami A. Source attribution of health benefits from air pollution abatement in Canada and the United States: an adjoint sensitivity analysis. ENVIRONMENTAL HEALTH PERSPECTIVES 2013; 121:572-9. [PMID: 23434744 PMCID: PMC3673189 DOI: 10.1289/ehp.1205561] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/02/2012] [Accepted: 02/21/2013] [Indexed: 05/06/2023]
Abstract
BACKGROUND Decision making regarding air pollution can be better informed if air quality impacts are traced back to individual emission sources. Adjoint or backward sensitivity analysis is a modeling tool that can achieve this goal by allowing for quantification of how emissions from sources in different locations influence human health metrics. OBJECTIVES We attributed short-term mortality (valuated as an overall "health benefit") in Canada and the United States to anthropogenic nitrogen oxides (NO(x)) and volatile organic compound (VOC) emissions across North America. METHODS We integrated epidemiological data derived from Canadian and U.S. time-series studies with the adjoint of an air quality model and also estimated influences of anthropogenic emissions at each location on nationwide health benefits. RESULTS We found significant spatiotemporal variability in estimated health benefit influences of NO(x) and VOC emission reductions on Canada and U.S. mortality. The largest estimated influences on Canada (up to $250,000/day) were from emissions originating in the Quebec City-Windsor Corridor, where population centers are concentrated. Estimated influences on the United States tend to be widespread and more substantial owing to both larger emissions and larger populations. The health benefit influences calculated using 24-hr average ozone (O(3)) concentrations are lower in magnitude than estimates calculated using daily 1-hr maximum O(3) concentrations. CONCLUSIONS Source specificity of the adjoint approach provides valuable information for guiding air quality decision making. Adjoint results suggest that the health benefits of reducing NO(x) and VOC emissions are substantial and highly variable across North America.
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Affiliation(s)
- Amanda Joy Pappin
- Department of Civil and Environmental Engineering, Carleton University, Ottawa, Ontario, Canada
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Mesbah SM, Hakami A, Schott S. Improving NO(x) cap-and-trade system with adjoint-based emission exchange rates. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2012; 46:11905-11912. [PMID: 23050674 DOI: 10.1021/es302406y] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/01/2023]
Abstract
Cap-and-trade programs have proven to be effective instruments for achieving environmental goals while incurring minimum cost. The nature of the pollutant, however, affects the design of these programs. NO(x), an ozone precursor, is a nonuniformly mixed pollutant with a short atmospheric lifetime. NO(x) cap-and-trade programs in the U.S. are successful in reducing total NO(x) emissions but may result in suboptimal environmental performance because location-specific ozone formation potentials are neglected. In this paper, the current NO(x) cap-and-trade system is contrasted to a hypothetical NO(x) trading policy with sensitivity-based exchange rates. Location-specific exchange rates, calculated through adjoint sensitivity analysis, are combined with constrained optimization for prediction of NO(x) emissions trading behavior and post-trade ozone concentrations. The current and proposed policies are examined in a case study for 218 coal-fired power plants that participated in the NO(x) Budget Trading Program in 2007. We find that better environmental performance at negligibly higher system-wide abatement cost can be achieved through inclusion of emission exchange rates. Exposure-based exchange rates result in better environmental performance than those based on concentrations.
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Affiliation(s)
- S Morteza Mesbah
- Department of Civil and Environmental Engineering, Carleton University, 1125 Colonel By Drive, Ottawa, Ontario, Canada
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Liao KJ, Amar P, Tagaris E, Russell AG. Development of risk-based air quality management strategies under impacts of climate change. JOURNAL OF THE AIR & WASTE MANAGEMENT ASSOCIATION (1995) 2012; 62:557-565. [PMID: 22696805 DOI: 10.1080/10962247.2012.662928] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/01/2023]
Abstract
UNLABELLED Climate change is forecast to adversely affect air quality through perturbations in meteorological conditions, photochemical reactions, and precursor emissions. To protect the environment and human health from air pollution, there is an increasing recognition of the necessity of developing effective air quality management strategies under the impacts of climate change. This paper presents a framework for developing risk-based air quality management strategies that can help policy makers improve their decision-making processes in response to current and future climate change about 30-50 years from now. Development of air quality management strategies under the impacts of climate change is fundamentally a risk assessment and risk management process involving four steps: (1) assessment of the impacts of climate change and associated uncertainties; (2) determination of air quality targets; (3) selections of potential air quality management options; and (4) identification of preferred air quality management strategies that minimize control costs, maximize benefits, or limit the adverse effects of climate change on air quality when considering the scarcity of resources. The main challenge relates to the level of uncertainties associated with climate change forecasts and advancements in future control measures, since they will significantly affect the risk assessment results and development of effective air quality management plans. The concept presented in this paper can help decision makers make appropriate responses to climate change, since it provides an integrated approach for climate risk assessment and management when developing air quality management strategies. IMPLICATIONS Development of climate-responsive air quality management strategies is fundamentally a risk assessment and risk management process. The risk assessment process includes quantification of climate change impacts on air quality and associated uncertainties. Risk management for air quality under the impacts of climate change includes determination of air quality targets, selections of potential management options, and identification of effective air quality management strategies through decision-making models. The risk-based decision-making framework can also be applied to develop climate-responsive management strategies for the other environmental dimensions and assess costs and benefits of future environmental management policies.
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Affiliation(s)
- Kuo-Jen Liao
- Department of Environmental Engineering, Texas A&M University-Kingsville, Kingsville, TX, USA.
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Walker TW, Jones DBA, Parrington M, Henze DK, Murray LT, Bottenheim JW, Anlauf K, Worden JR, Bowman KW, Shim C, Singh K, Kopacz M, Tarasick DW, Davies J, von der Gathen P, Thompson AM, Carouge CC. Impacts of midlatitude precursor emissions and local photochemistry on ozone abundances in the Arctic. ACTA ACUST UNITED AC 2012. [DOI: 10.1029/2011jd016370] [Citation(s) in RCA: 42] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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Kopacz M, Jacob DJ, Henze DK, Heald CL, Streets DG, Zhang Q. Comparison of adjoint and analytical Bayesian inversion methods for constraining Asian sources of carbon monoxide using satellite (MOPITT) measurements of CO columns. ACTA ACUST UNITED AC 2009. [DOI: 10.1029/2007jd009264] [Citation(s) in RCA: 130] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
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