Articles | Volume 25, issue 10
https://doi.org/10.5194/acp-25-5233-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-25-5233-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
26 May 2025
Research article |
| 26 May 2025
| 26 May 2025
Underappreciated contributions of biogenic volatile organic compounds from urban green spaces to ozone pollution
Haofan Wang
School of Atmospheric Sciences, Sun Yat-sen University, and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, 519082, PR China
Guangdong Provincial Field Observation and Research Station for Climate Environment and Air Quality Change in the Pearl River Estuary, Guangzhou, 510275, PR China
Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies, Sun Yat-sen University, Zhuhai, 519082, PR China
Centre for Atmospheric Science, Department of Earth and Environmental Sciences, The University of Manchester, Manchester, United Kingdom
Yuejin Li
School of Atmospheric Sciences, Sun Yat-sen University, and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, 519082, PR China
Guangdong Provincial Field Observation and Research Station for Climate Environment and Air Quality Change in the Pearl River Estuary, Guangzhou, 510275, PR China
Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies, Sun Yat-sen University, Zhuhai, 519082, PR China
School of Atmospheric Sciences, Sun Yat-sen University, and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, 519082, PR China
Guangdong Provincial Field Observation and Research Station for Climate Environment and Air Quality Change in the Pearl River Estuary, Guangzhou, 510275, PR China
Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies, Sun Yat-sen University, Zhuhai, 519082, PR China
School of Atmospheric Sciences, Sun Yat-sen University, and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, 519082, PR China
Guangdong Provincial Field Observation and Research Station for Climate Environment and Air Quality Change in the Pearl River Estuary, Guangzhou, 510275, PR China
Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies, Sun Yat-sen University, Zhuhai, 519082, PR China
Yang Zhang
College of Resources and Environment, Chengdu University of Information Technology, Chengdu, 610225, PR China
Qi Fan
CORRESPONDING AUTHOR
School of Atmospheric Sciences, Sun Yat-sen University, and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, 519082, PR China
Guangdong Provincial Field Observation and Research Station for Climate Environment and Air Quality Change in the Pearl River Estuary, Guangzhou, 510275, PR China
Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies, Sun Yat-sen University, Zhuhai, 519082, PR China
Chong Shen
Guangzhou Ecological and Agricultural Meteorological Center, Guangzhou, 511430, PR China
Senchao Lai
The Key Lab of Pollution Control and Ecosystem Restoration in Industry Clusters, Ministry of Education, School of Environment and Energy, South China University of Technology, Guangzhou, 510006, PR China
Yan Zhou
National Key Laboratory for Regional Air Quality Monitoring of Environmental Protection/Guangdong Ecological Environment Monitoring Center, Guangzhou, 510308, PR China
Tao Zhang
National Key Laboratory for Regional Air Quality Monitoring of Environmental Protection/Guangdong Ecological Environment Monitoring Center, Guangzhou, 510308, PR China
Dingli Yue
National Key Laboratory for Regional Air Quality Monitoring of Environmental Protection/Guangdong Ecological Environment Monitoring Center, Guangzhou, 510308, PR China
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We use 22 months of TROPOMI satellite observations to quantity methane emissions from the oil (O) and natural gas (G) sector in the US and Canada at the scale of both individual basins as well as country-wide aggregates. We find that O/G-related methane emissions are underestimated in these inventories by 80 % for the US and 40 % for Canada, and 70 % of the underestimate in the US is from five O/G basins, including Permian, Haynesville, Anadarko, Eagle Ford, and Barnett.
Zichong Chen, Daniel J. Jacob, Hannah Nesser, Melissa P. Sulprizio, Alba Lorente, Daniel J. Varon, Xiao Lu, Lu Shen, Zhen Qu, Elise Penn, and Xueying Yu
Atmos. Chem. Phys., 22, 10809–10826, https://doi.org/10.5194/acp-22-10809-2022, https://doi.org/10.5194/acp-22-10809-2022, 2022
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We quantify methane emissions in China and contributions from different sectors by inverse analysis of 2019 TROPOMI satellite observations of atmospheric methane. We find that anthropogenic methane emissions for China are underestimated in the national inventory. Our estimate of emissions indicates a small life-cycle loss rate, implying net climate benefits from the current
coal-to-gasenergy transition in China. However, this small loss rate can be misleading given China's high gas imports.
Daniel J. Varon, Daniel J. Jacob, Melissa Sulprizio, Lucas A. Estrada, William B. Downs, Lu Shen, Sarah E. Hancock, Hannah Nesser, Zhen Qu, Elise Penn, Zichong Chen, Xiao Lu, Alba Lorente, Ashutosh Tewari, and Cynthia A. Randles
Geosci. Model Dev., 15, 5787–5805, https://doi.org/10.5194/gmd-15-5787-2022, https://doi.org/10.5194/gmd-15-5787-2022, 2022
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Reducing atmospheric methane emissions is critical to slow near-term climate change. Globally surveying satellite instruments like the TROPOspheric Monitoring Instrument (TROPOMI) have unique capabilities for monitoring atmospheric methane around the world. Here we present a user-friendly cloud-computing tool that enables researchers and stakeholders to quantify methane emissions across user-selected regions of interest using TROPOMI satellite observations.
Chenhong Zhou, Fan Wang, Yike Guo, Cheng Liu, Dongsheng Ji, Yuesi Wang, Xiaobin Xu, Xiao Lu, Yan Wang, Gregory Carmichael, and Meng Gao
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2022-187, https://doi.org/10.5194/essd-2022-187, 2022
Manuscript not accepted for further review
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We develop an eXtreme Gradient Boosting (XGBoost) model integrating high-resolution meteorological data, satellite retrievals of trace gases, etc. to provide reconstructed daily ground-level O3 over 2005–2021 in China. It can facilitate climatological, ecological, and health research. The dataset is freely available at Zenodo (https://zenodo.org/record/6507706#.Yo8hKujP13g; Zhou, 2022).
Tia R. Scarpelli, Daniel J. Jacob, Shayna Grossman, Xiao Lu, Zhen Qu, Melissa P. Sulprizio, Yuzhong Zhang, Frances Reuland, Deborah Gordon, and John R. Worden
Atmos. Chem. Phys., 22, 3235–3249, https://doi.org/10.5194/acp-22-3235-2022, https://doi.org/10.5194/acp-22-3235-2022, 2022
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We present a spatially explicit version of the national inventories of oil, gas, and coal methane emissions as submitted by individual countries to the United Nations Framework Convention on Climate Change (UNFCCC) in 2021. We then use atmospheric modeling to compare our inventory emissions to atmospheric methane observations with the goal of identifying potential under- and overestimates of oil–gas methane emissions in the national inventories.
Dianyi Li, Drew Shindell, Dian Ding, Xiao Lu, Lin Zhang, and Yuqiang Zhang
Atmos. Chem. Phys., 22, 2625–2638, https://doi.org/10.5194/acp-22-2625-2022, https://doi.org/10.5194/acp-22-2625-2022, 2022
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In this study, we applied chemical transport model simulation with the latest annual anthropogenic emission inventory to study the long-term trend of ozone-induced crop production losses from 2010 to 2017 in China. We find that overall the ozone-induced crop production loss in China is significant and the annual average economic losses for wheat, rice, maize, and soybean in China are USD 9.55 billion, USD 8.53 billion, USD 2.23 billion, and USD 1.16 billion respectively, over the 8 years.
Haiyue Tan, Lin Zhang, Xiao Lu, Yuanhong Zhao, Bo Yao, Robert J. Parker, and Hartmut Boesch
Atmos. Chem. Phys., 22, 1229–1249, https://doi.org/10.5194/acp-22-1229-2022, https://doi.org/10.5194/acp-22-1229-2022, 2022
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Methane is the second most important anthropogenic greenhouse gas. Understanding methane emissions and concentration growth over China in the past decade is important to support its mitigation. This study analyzes the contributions of methane emissions from different regions and sources over the globe to methane changes over China in 2007–2018. Our results show strong international transport influences and emphasize the need of intensive methane measurements covering eastern China.
Xiao Lu, Daniel J. Jacob, Haolin Wang, Joannes D. Maasakkers, Yuzhong Zhang, Tia R. Scarpelli, Lu Shen, Zhen Qu, Melissa P. Sulprizio, Hannah Nesser, A. Anthony Bloom, Shuang Ma, John R. Worden, Shaojia Fan, Robert J. Parker, Hartmut Boesch, Ritesh Gautam, Deborah Gordon, Michael D. Moran, Frances Reuland, Claudia A. Octaviano Villasana, and Arlyn Andrews
Atmos. Chem. Phys., 22, 395–418, https://doi.org/10.5194/acp-22-395-2022, https://doi.org/10.5194/acp-22-395-2022, 2022
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We evaluate methane emissions and trends for 2010–2017 in the gridded national emission inventories for the United States, Canada, and Mexico by inversion of in situ and satellite methane observations. We find that anthropogenic methane emissions for all three countries are underestimated in the national inventories, largely driven by oil emissions. Anthropogenic methane emissions in the US peak in 2014, in contrast to the report of a steadily decreasing trend over 2010–2017 from the US EPA.
Youwen Sun, Hao Yin, Xiao Lu, Justus Notholt, Mathias Palm, Cheng Liu, Yuan Tian, and Bo Zheng
Atmos. Chem. Phys., 21, 18589–18608, https://doi.org/10.5194/acp-21-18589-2021, https://doi.org/10.5194/acp-21-18589-2021, 2021
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This study uses high-resolution nested-grid GEOS-Chem simulation, the eXtreme Gradient Boosting (XGBoost) machine learning method, and the exposure–response relationship to determine the drivers and evaluate the health risks of the unexpected surface O3 enhancements over the Sichuan Basin in 2020. These unexpected O3 enhancements were induced by meteorological anomalies and caused dramatically high health risks.
Zhen Qu, Daniel J. Jacob, Lu Shen, Xiao Lu, Yuzhong Zhang, Tia R. Scarpelli, Hannah Nesser, Melissa P. Sulprizio, Joannes D. Maasakkers, A. Anthony Bloom, John R. Worden, Robert J. Parker, and Alba L. Delgado
Atmos. Chem. Phys., 21, 14159–14175, https://doi.org/10.5194/acp-21-14159-2021, https://doi.org/10.5194/acp-21-14159-2021, 2021
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The recent launch of TROPOMI offers an unprecedented opportunity to quantify the methane budget from a top-down perspective. We use TROPOMI and the more mature GOSAT methane observations to estimate methane emissions and get consistent global budgets. However, TROPOMI shows biases over regions where surface albedo is small and provides less information for the coarse-resolution inversion due to the larger error correlations and spatial variations in the number of observations.
Youwen Sun, Hao Yin, Cheng Liu, Emmanuel Mahieu, Justus Notholt, Yao Té, Xiao Lu, Mathias Palm, Wei Wang, Changgong Shan, Qihou Hu, Min Qin, Yuan Tian, and Bo Zheng
Atmos. Chem. Phys., 21, 11759–11779, https://doi.org/10.5194/acp-21-11759-2021, https://doi.org/10.5194/acp-21-11759-2021, 2021
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The variability, sources, and transport of ethane (C2H6) over eastern China from 2015 to 2020 were studied using ground-based Fourier transform infrared (FTIR) spectroscopy and GEOS-Chem simulations. C2H6 variability is driven by both meteorological and emission factors. The reduction in C2H6 in recent years over eastern China points to air quality improvement in China.
Meng Gao, Yang Yang, Hong Liao, Bin Zhu, Yuxuan Zhang, Zirui Liu, Xiao Lu, Chen Wang, Qiming Zhou, Yuesi Wang, Qiang Zhang, Gregory R. Carmichael, and Jianlin Hu
Atmos. Chem. Phys., 21, 11405–11421, https://doi.org/10.5194/acp-21-11405-2021, https://doi.org/10.5194/acp-21-11405-2021, 2021
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Light absorption and radiative forcing of black carbon (BC) is influenced by both BC itself and its interactions with other aerosol chemical compositions. In this study, we used the online coupled WRF-Chem model to examine how emission control measures during the Asian-Pacific Economic Cooperation (APEC) conference affect the mixing state and light absorption of BC and the associated implications for BC-PBL interactions.
Youwen Sun, Hao Yin, Yuan Cheng, Qianggong Zhang, Bo Zheng, Justus Notholt, Xiao Lu, Cheng Liu, Yuan Tian, and Jianguo Liu
Atmos. Chem. Phys., 21, 9201–9222, https://doi.org/10.5194/acp-21-9201-2021, https://doi.org/10.5194/acp-21-9201-2021, 2021
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We quantified the variability, source, and transport of urban CO over the Himalayas and Tibetan Plateau (HTP) by using measurement, model simulation, and the analysis of meteorological fields. Urban CO over the HTP is dominated by anthropogenic and biomass burning emissions from local, South Asia and East Asia, and oxidation sources. The decreasing trends in surface CO since 2015 in most cities over the HTP are attributed to the reduction in local and transported CO emissions in recent years.
Youwen Sun, Hao Yin, Cheng Liu, Lin Zhang, Yuan Cheng, Mathias Palm, Justus Notholt, Xiao Lu, Corinne Vigouroux, Bo Zheng, Wei Wang, Nicholas Jones, Changong Shan, Min Qin, Yuan Tian, Qihou Hu, Fanhao Meng, and Jianguo Liu
Atmos. Chem. Phys., 21, 6365–6387, https://doi.org/10.5194/acp-21-6365-2021, https://doi.org/10.5194/acp-21-6365-2021, 2021
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This study mapped the drivers of HCHO variability from 2015 to 2019 over eastern China. Hydroxyl (OH) radical production rates from HCHO photolysis were evaluated. The relative contributions of emitted and photochemical sources to the observed HCHO abundance were analyzed. Contributions of various emission sources and geographical regions to the observed HCHO summertime enhancements were determined.
Xiao Lu, Daniel J. Jacob, Yuzhong Zhang, Joannes D. Maasakkers, Melissa P. Sulprizio, Lu Shen, Zhen Qu, Tia R. Scarpelli, Hannah Nesser, Robert M. Yantosca, Jianxiong Sheng, Arlyn Andrews, Robert J. Parker, Hartmut Boesch, A. Anthony Bloom, and Shuang Ma
Atmos. Chem. Phys., 21, 4637–4657, https://doi.org/10.5194/acp-21-4637-2021, https://doi.org/10.5194/acp-21-4637-2021, 2021
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We use an analytical solution to the Bayesian inverse problem to quantitatively compare and combine the information from satellite and in situ observations, and to estimate global methane budget and their trends over the 2010–2017 period. We find that satellite and in situ observations are to a large extent complementary in the inversion for estimating global methane budget, and reveal consistent corrections of regional anthropogenic and wetland methane emissions relative to the prior inventory.
Joannes D. Maasakkers, Daniel J. Jacob, Melissa P. Sulprizio, Tia R. Scarpelli, Hannah Nesser, Jianxiong Sheng, Yuzhong Zhang, Xiao Lu, A. Anthony Bloom, Kevin W. Bowman, John R. Worden, and Robert J. Parker
Atmos. Chem. Phys., 21, 4339–4356, https://doi.org/10.5194/acp-21-4339-2021, https://doi.org/10.5194/acp-21-4339-2021, 2021
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We use 2010–2015 GOSAT satellite observations of atmospheric methane over North America in a high-resolution inversion to estimate methane emissions. We find general consistency with the gridded EPA inventory but higher oil and gas production emissions, with oil production emissions twice as large as in the latest EPA Greenhouse Gas Inventory. We find lower wetland emissions than predicted by WetCHARTs and a small increasing trend in the eastern US, apparently related to unconventional oil/gas.
Yuzhong Zhang, Daniel J. Jacob, Xiao Lu, Joannes D. Maasakkers, Tia R. Scarpelli, Jian-Xiong Sheng, Lu Shen, Zhen Qu, Melissa P. Sulprizio, Jinfeng Chang, A. Anthony Bloom, Shuang Ma, John Worden, Robert J. Parker, and Hartmut Boesch
Atmos. Chem. Phys., 21, 3643–3666, https://doi.org/10.5194/acp-21-3643-2021, https://doi.org/10.5194/acp-21-3643-2021, 2021
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We use 2010–2018 satellite observations of atmospheric methane to interpret the factors controlling atmospheric methane and its accelerating increase during the period. The 2010–2018 increase in global methane emissions is driven by tropical and boreal wetlands and tropical livestock (South Asia, Africa, Brazil), with an insignificant positive trend in emissions from the fossil fuel sector. The peak methane growth rates in 2014–2015 are also contributed by low OH and high fire emissions.
Yang Zhang, Zhengqiang Li, Zhihong Liu, Yongqian Wang, Lili Qie, Yisong Xie, Weizhen Hou, and Lu Leng
Atmos. Meas. Tech., 14, 1655–1672, https://doi.org/10.5194/amt-14-1655-2021, https://doi.org/10.5194/amt-14-1655-2021, 2021
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The aerosol fine-mode fraction (FMF) is an important parameter reflecting the content of man-made aerosols. This study carried out the retrieval of FMF in China based on multi-angle polarization data and validated the results. The results of this study can contribute to the FMF retrieval algorithm of multi-angle polarization sensors. At the same time, a high-precision FMF dataset of China was obtained, which can provide basic data for atmospheric environment research.
Zhongjing Jiang, Jing Li, Xiao Lu, Cheng Gong, Lin Zhang, and Hong Liao
Atmos. Chem. Phys., 21, 2601–2613, https://doi.org/10.5194/acp-21-2601-2021, https://doi.org/10.5194/acp-21-2601-2021, 2021
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This study demonstrates that the intensity of the western Pacific subtropical high (WPSH), a major synoptic pattern in the northern Pacific during summer, can induce a dipole change in surface ozone pollution over eastern China. Ozone concentration increases in the north and decreases in the south during the strong WPSH phase, and vice versa. The change in chemical processes associated with the WPSH change plays a decisive role, whereas the natural emission of ozone precursors accounts for ~ 30 %.
Ke Li, Daniel J. Jacob, Lu Shen, Xiao Lu, Isabelle De Smedt, and Hong Liao
Atmos. Chem. Phys., 20, 11423–11433, https://doi.org/10.5194/acp-20-11423-2020, https://doi.org/10.5194/acp-20-11423-2020, 2020
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Surface summer ozone increased in China from 2013 to 2019 despite new governmental efforts targeting ozone pollution. We find that the ozone increase is mostly due to anthropogenic drivers, although meteorology also plays a role. Further analysis for the North China Plain shows that PM2.5 continued to decrease through 2019, while emissions of volatile organic compounds (VOCs) stayed flat. This could explain the anthropogenic increase in ozone, as PM2.5 scavenges the radical precursors of ozone.
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Short summary
This study explores how urban green spaces (UGSs) in Guangzhou influence ozone levels. By using advanced models, we found that natural emissions from these areas can significantly affect air quality. Our results suggest that the design and planning of UGSs should not only consider aesthetics and social factors but also their environmental impacts on air quality.
This study explores how urban green spaces (UGSs) in Guangzhou influence ozone levels. By using...
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