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Shutter JD, Millet DB, Wells KC, Payne VH, Nowlan CR, Abad GG. Interannual changes in atmospheric oxidation over forests determined from space. SCIENCE ADVANCES 2024; 10:eadn1115. [PMID: 38748807 PMCID: PMC11095458 DOI: 10.1126/sciadv.adn1115] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/22/2023] [Accepted: 04/10/2024] [Indexed: 05/19/2024]
Abstract
The hydroxyl radical (OH) is the central oxidant in Earth's troposphere, but its temporal variability is poorly understood. We combine 2012-2020 satellite-based isoprene and formaldehyde measurements to identify coherent OH changes over temperate and tropical forests with attribution to emission trends, biotic stressors, and climate. We identify a multiyear OH decrease over the Southeast United States and show that with increasingly hot/dry summers the regional chemistry could become even less oxidizing depending on competing temperature/drought impacts on isoprene. Furthermore, while global mean OH decreases during El Niño, we show that near-field effects over tropical rainforests can alternate between high/low OH anomalies due to opposing fire and biogenic emission impacts. Results provide insights into how atmospheric oxidation will evolve with changing emissions and climate.
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Affiliation(s)
- Joshua D. Shutter
- Department of Soil, Water, and Climate, University of Minnesota, St. Paul, MN 55108, USA
| | - Dylan B. Millet
- Department of Soil, Water, and Climate, University of Minnesota, St. Paul, MN 55108, USA
| | - Kelley C. Wells
- Department of Soil, Water, and Climate, University of Minnesota, St. Paul, MN 55108, USA
| | - Vivienne H. Payne
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91011, USA
| | - Caroline R. Nowlan
- Center for Astrophysics | Harvard & Smithsonian, Cambridge, MA 02138, USA
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Yang C, Dong H, Chen Y, Xu L, Chen G, Fan X, Wang Y, Tham YJ, Lin Z, Li M, Hong Y, Chen J. New Insights on the Formation of Nucleation Mode Particles in a Coastal City Based on a Machine Learning Approach. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2024; 58:1187-1198. [PMID: 38117945 DOI: 10.1021/acs.est.3c07042] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/22/2023]
Abstract
Atmospheric particles have profound implications for the global climate and human health. Among them, ultrafine particles dominate in terms of the number concentration and exhibit enhanced toxic effects as a result of their large total surface area. Therefore, understanding the driving factors behind ultrafine particle behavior is crucial. Machine learning (ML) provides a promising approach for handling complex relationships. In this study, three ML models were constructed on the basis of field observations to simulate the particle number concentration of nucleation mode (PNCN). All three models exhibited robust PNCN reproduction (R2 > 0.80), with the random forest (RF) model excelling on the test data (R2 = 0.89). Multiple methods of feature importance analysis revealed that ultraviolet (UV), H2SO4, low-volatility oxygenated organic molecules (LOOMs), temperature, and O3 were the primary factors influencing PNCN. Bivariate partial dependency plots (PDPs) indicated that during nighttime and overcast conditions, the presence of H2SO4 and LOOMs may play a crucial role in influencing PNCN. Additionally, integrating additional detailed information related to emissions or meteorology would further enhance the model performance. This pilot study shows that ML can be a novel approach for simulating atmospheric pollutants and contributes to a better understanding of the formation and growth mechanisms of nucleation mode particles.
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Affiliation(s)
- Chen Yang
- Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen, Fujian 361021, People's Republic of China
- Fujian Key Laboratory of Atmospheric Ozone Pollution Prevention, Chinese Academy of Sciences, Xiamen, Fujian 361021, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - Hesong Dong
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
- Key Laboratory of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen, Fujian 361021, People's Republic of China
| | - Yuping Chen
- Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen, Fujian 361021, People's Republic of China
- Fujian Key Laboratory of Atmospheric Ozone Pollution Prevention, Chinese Academy of Sciences, Xiamen, Fujian 361021, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - Lingling Xu
- Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen, Fujian 361021, People's Republic of China
- Fujian Key Laboratory of Atmospheric Ozone Pollution Prevention, Chinese Academy of Sciences, Xiamen, Fujian 361021, People's Republic of China
| | - Gaojie Chen
- Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen, Fujian 361021, People's Republic of China
- Fujian Key Laboratory of Atmospheric Ozone Pollution Prevention, Chinese Academy of Sciences, Xiamen, Fujian 361021, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - Xiaolong Fan
- Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen, Fujian 361021, People's Republic of China
- Fujian Key Laboratory of Atmospheric Ozone Pollution Prevention, Chinese Academy of Sciences, Xiamen, Fujian 361021, People's Republic of China
| | - Yonghong Wang
- State Key Joint Laboratory of Environment Simulation and Pollution Control, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, People's Republic of China
| | - Yee Jun Tham
- School of Marine Sciences, Sun Yat-sen University, Zhuhai, Guangdong 519082, People's Republic of China
| | - Ziyi Lin
- Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen, Fujian 361021, People's Republic of China
- Fujian Key Laboratory of Atmospheric Ozone Pollution Prevention, Chinese Academy of Sciences, Xiamen, Fujian 361021, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - Mengren Li
- Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen, Fujian 361021, People's Republic of China
- Fujian Key Laboratory of Atmospheric Ozone Pollution Prevention, Chinese Academy of Sciences, Xiamen, Fujian 361021, People's Republic of China
| | - Youwei Hong
- Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen, Fujian 361021, People's Republic of China
- Fujian Key Laboratory of Atmospheric Ozone Pollution Prevention, Chinese Academy of Sciences, Xiamen, Fujian 361021, People's Republic of China
| | - Jinsheng Chen
- Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen, Fujian 361021, People's Republic of China
- Fujian Key Laboratory of Atmospheric Ozone Pollution Prevention, Chinese Academy of Sciences, Xiamen, Fujian 361021, People's Republic of China
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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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Zhang Y, Shi M, Chen J, Fu S, Wang H. Spatiotemporal variations of NO 2 and its driving factors in the coastal ports of China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 871:162041. [PMID: 36754320 DOI: 10.1016/j.scitotenv.2023.162041] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/04/2022] [Revised: 02/01/2023] [Accepted: 02/01/2023] [Indexed: 06/18/2023]
Abstract
Nitrogen Dioxide (NO2) is one of the major air pollutants in coastal ports of China. Understanding the spatiotemporal varying effects of driving factors of NO2 is vital for the implementation of differentiated air pollution control measures for different port areas. Based on the Ozone Monitoring Instrument (OMI) satellite data, we adopted a Geographically and Temporally Weighted Regression (GTWR) model to explore the influences of meteorological and socioeconomic factors on the NO2 Vertical Column Concentrations (VCDs) in coastal ports of China from 2015 to 2021. The results indicate that NO2 VCD in most ports has decreased since 2016 and the ports with serious NO2 pollution are mainly distributed in northern China. The associations between NO2 VCD levels and their drivers exhibit obvious spatiotemporal heterogeneity. Higher wind speed and relative humidity are more helpful to alleviate NO2 pollution in ports of the Bohai Rim and the Pearl River Delta. Cargo throughput has more closely associated with NO2 pollution in Beibu Gulf in recent years, yet there is no significant association found for Shanghai ports. The positive relationship between transportation emissions and NO2 VCD is more significant in southern ports. This work provides some implications for the formulation of targeted emission reduction policies for different ports along the Chinese coast.
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Affiliation(s)
- Yang Zhang
- College of Transport and Communications, Shanghai Maritime University, Shanghai 201306, China
| | - Meiyu Shi
- College of Transport and Communications, Shanghai Maritime University, Shanghai 201306, China
| | - Jihong Chen
- College of Management, Shenzhen University, Shenzhen 518073, China; Shenzhen International Maritime Institute, Shenzhen 518081, China; Business School, Xi'an International University, Xi'an 710077, China.
| | - Shanshan Fu
- College of Transport and Communications, Shanghai Maritime University, Shanghai 201306, China
| | - Huizhen Wang
- Business School, Xi'an International University, Xi'an 710077, China
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Li C, Zhu Q, Jin X, Cohen RC. Elucidating Contributions of Anthropogenic Volatile Organic Compounds and Particulate Matter to Ozone Trends over China. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2022; 56:12906-12916. [PMID: 36083302 DOI: 10.1021/acs.est.2c03315] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
In China, emissions of ozone (O3)-producing pollutants have been targeted for mitigation to reduce O3 pollution. However, the observed O3 decrease is slower than/opposite to expectations affecting the health of millions of people. For a better understanding of this failure and its connection with anthropogenic emissions, we quantify the summer O3 trends that would have occurred had the weather stayed constant by applying a numerical tool that "de-weathers" observations across 31 urban regions (123 cities and 392 sites) over 8 years. O3 trends are significant (p < 0.05) over 234 sites after de-weathering, contrary to the directly observed trends (only 39 significant due to high meteorology-induced variability). The de-weathered data allow categorizing cities in China into four different groups regarding O3 mitigation, with group 1 exhibiting steady O3 reductions, while group 4 showing significant (p < 0.05) O3 increases. Analysis of the relationships between de-weathered odd oxygen and nitrogen oxides illustrates how the changes in NOx, in anthropogenic volatile organic compounds (VOCs), and reductions in fine particulate matter (PM2.5) affect the O3 trends differently in these groups. While this analysis suggests that VOC reductions are the main driver of O3 decreases in group 1, groups 3 and 4 are primarily affected by decreasing PM2.5, which results in enhanced O3 formation. Our analysis demonstrates both the importance of and possibility for isolating emission-driven changes from climate and weather for interpreting short-term air quality observations.
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Affiliation(s)
- Chi Li
- Department of Chemistry, University of California, Berkeley, Berkeley, California 94720, United States
| | - Qindan Zhu
- Department of Earth and Planetary Science, University of California, Berkeley, Berkeley, California 94720, United States
| | - Xiaomeng Jin
- Department of Chemistry, University of California, Berkeley, Berkeley, California 94720, United States
| | - Ronald C Cohen
- Department of Chemistry, University of California, Berkeley, Berkeley, California 94720, United States
- Department of Earth and Planetary Science, University of California, Berkeley, Berkeley, California 94720, United States
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