Articles | Volume 15, issue 11
https://doi.org/10.5194/essd-15-5017-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-15-5017-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
16 Nov 2023
Data description paper |
| 16 Nov 2023
| 16 Nov 2023
High-resolution emission inventory of full-volatility organic compounds from cooking in China during 2015–2021
Zeqi 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
Shuxiao Wang
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
Shengyue 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
Xiaochun Wang
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
Guanghan Huang
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
Xing Chang
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
Laboratory of Transport Pollution Control and Monitoring Technology, Transport Planning and Research Institute, Ministry of Transport, Beijing 100028, China
Lyuyin Huang
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
Chengrui Liang
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
Yun Zhu
Guangdong Provincial Key Laboratory of Atmospheric Environment and Pollution Control, College of Environment and Energy, South China University of Technology, Guangzhou, 510006, China
Haotian Zheng
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
Qian Song
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
Qingru Wu
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
Fenfen Zhang
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
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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Sunling Gong, Hongli Liu, Bihui Zhang, Jianjun He, Hengde Zhang, Yaqiang Wang, Shuxiao Wang, Lei Zhang, and Jie Wang
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Brigitte Rooney, Yuan Wang, Jonathan H. Jiang, Bin Zhao, Zhao-Cheng Zeng, and John H. Seinfeld
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Jia Xing, Siwei Li, Yueqi Jiang, Shuxiao Wang, Dian Ding, Zhaoxin Dong, Yun Zhu, and Jiming Hao
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Quantifying emission changes is a prerequisite for assessment of control effectiveness in improving air quality. However, traditional bottom-up methods usually take months to perform and limit timely assessments. A novel method was developed by using a response model that provides real-time estimation of emission changes based on air quality observations. It was successfully applied to quantify emission changes on the North China Plain due to the COVID-19 pandemic shutdown.
Jia Xing, Dian Ding, Shuxiao Wang, Zhaoxin Dong, James T. Kelly, Carey Jang, Yun Zhu, and Jiming Hao
Atmos. Chem. Phys., 19, 13627–13646, https://doi.org/10.5194/acp-19-13627-2019, https://doi.org/10.5194/acp-19-13627-2019, 2019
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The study aims at addressing the challenge in efficient quantification of the nonlinear response of air pollution to precursor emission perturbations. The newly developed observable response indicators can be easily calculated by a combination of ambient concentrations of certain species. Their capability in representing the spatial and temporal variation in PM2.5 and O3 chemistry has also been well evaluated and applied in China.
Mingchen Ma, Yang Gao, Yuhang Wang, Shaoqing Zhang, L. Ruby Leung, Cheng Liu, Shuxiao Wang, Bin Zhao, Xing Chang, Hang Su, Tianqi Zhang, Lifang Sheng, Xiaohong Yao, and Huiwang Gao
Atmos. Chem. Phys., 19, 12195–12207, https://doi.org/10.5194/acp-19-12195-2019, https://doi.org/10.5194/acp-19-12195-2019, 2019
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Ozone pollution has become severe in China, and extremely high ozone episodes occurred in summer 2017 over the North China Plain. While meteorology impacts are clear, we find that enhanced biogenic emissions, previously ignored by the community, driven by high vapor pressure deficit, land cover change and urban landscape contribute substantially to ozone formation. This study has significant implications for ozone pollution control with more frequent heat waves and urbanization growth in future.
Ling Qi and Shuxiao Wang
Atmos. Chem. Phys., 19, 11545–11557, https://doi.org/10.5194/acp-19-11545-2019, https://doi.org/10.5194/acp-19-11545-2019, 2019
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Black carbon (BC) contributes two-thirds of the climate impact of carbon dioxide, pushing methane into third place of the human contributors to global warming. This study shows that contributions from biomass burning (producing marginal lensing effect) have a strong spatial variation, from 20 % in Europe to 60 % in Africa. Thus, the inclusion of strong lensing-related absorption enhancement to all BC particles in previous estimates may lead to overestimating their positive radiative forcing.
Tuan V. Vu, Zongbo Shi, Jing Cheng, Qiang Zhang, Kebin He, Shuxiao Wang, and Roy M. Harrison
Atmos. Chem. Phys., 19, 11303–11314, https://doi.org/10.5194/acp-19-11303-2019, https://doi.org/10.5194/acp-19-11303-2019, 2019
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A 5-year Clean Air Action Plan was implemented in 2013 to improve ambient air quality in Beijing. Here, we applied a novel machine-learning-based model to determine the real trend in air quality from 2013 to 2017 in Beijing to assess the efficacy of the plan. We showed that the action plan led to a major reduction in primary emissions and significant improvement in air quality. The marked decrease in PM2.5 and SO2 is largely attributable to a reduction in coal combustion.
Xionghui Qiu, Qi Ying, Shuxiao Wang, Lei Duan, Jian Zhao, Jia Xing, Dian Ding, Yele Sun, Baoxian Liu, Aijun Shi, Xiao Yan, Qingcheng Xu, and Jiming Hao
Atmos. Chem. Phys., 19, 6737–6747, https://doi.org/10.5194/acp-19-6737-2019, https://doi.org/10.5194/acp-19-6737-2019, 2019
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Current chemical transport models cannot capture the diurnal and nocturnal variation in atmospheric nitrate, which may be relative to the missing atmospheric chlorine chemistry. In this work, the Community Multiscale Air Quality (CMAQ) model with improved chlorine heterogeneous chemistry is applied to simulate the impact of chlorine chemistry on summer nitrate concentrations in Beijing. The results of this work can improve our understanding of nitrate formation.
Junlan Feng, Yan Zhang, Shanshan Li, Jingbo Mao, Allison P. Patton, Yuyan Zhou, Weichun Ma, Cong Liu, Haidong Kan, Cheng Huang, Jingyu An, Li Li, Yin Shen, Qingyan Fu, Xinning Wang, Juan Liu, Shuxiao Wang, Dian Ding, Jie Cheng, Wangqi Ge, Hong Zhu, and Katherine Walker
Atmos. Chem. Phys., 19, 6167–6183, https://doi.org/10.5194/acp-19-6167-2019, https://doi.org/10.5194/acp-19-6167-2019, 2019
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This study aims to estimate the emissions, air quality and population exposure impacts of shipping in 2015, prior to the implementation of the DECAs. It shows that ship emissions within 12 NM of the shore could account for over 55 % of the shipping impact on air pollution in the YRD in summer. Ships entering the Yangtze River and other inland waterways of Shanghai contribute 40–80 % of the ship-related air pollution and population exposure，which both have important implications regarding policy.
Zhenying Xu, Mingxu Liu, Minsi Zhang, Yu Song, Shuxiao Wang, Lin Zhang, Tingting Xu, Tiantian Wang, Caiqing Yan, Tian Zhou, Yele Sun, Yuepeng Pan, Min Hu, Mei Zheng, and Tong Zhu
Atmos. Chem. Phys., 19, 5605–5613, https://doi.org/10.5194/acp-19-5605-2019, https://doi.org/10.5194/acp-19-5605-2019, 2019
Haotian Zheng, Siyi Cai, Shuxiao Wang, Bin Zhao, Xing Chang, and Jiming Hao
Atmos. Chem. Phys., 19, 3447–3462, https://doi.org/10.5194/acp-19-3447-2019, https://doi.org/10.5194/acp-19-3447-2019, 2019
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The heavy air pollution in the Beijing-Tianjin-Hebei (BTH) region is a global hot topic. We established a unit-based industrial emission inventory for the BTH region. The inventory significantly improved air quality modeling results; this improvement subsequently contributes to an accurate source apportionment of haze pollution and more precisely targeted decision making.
Shaojie Song, Meng Gao, Weiqi Xu, Yele Sun, Douglas R. Worsnop, John T. Jayne, Yuzhong Zhang, Lei Zhu, Mei Li, Zhen Zhou, Chunlei Cheng, Yibing Lv, Ying Wang, Wei Peng, Xiaobin Xu, Nan Lin, Yuxuan Wang, Shuxiao Wang, J. William Munger, Daniel J. Jacob, and Michael B. McElroy
Atmos. Chem. Phys., 19, 1357–1371, https://doi.org/10.5194/acp-19-1357-2019, https://doi.org/10.5194/acp-19-1357-2019, 2019
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Chemistry responsible for sulfate production in northern China winter haze remains mysterious. We propose a potentially key pathway through the reaction of formaldehyde and sulfur dioxide that has not been accounted for in previous studies. The special atmospheric conditions favor the formation and existence of their complex, hydroxymethanesulfonate (HMS).
Ge Zhang, Yang Gao, Wenju Cai, L. Ruby Leung, Shuxiao Wang, Bin Zhao, Minghuai Wang, Huayao Shan, Xiaohong Yao, and Huiwang Gao
Atmos. Chem. Phys., 19, 565–576, https://doi.org/10.5194/acp-19-565-2019, https://doi.org/10.5194/acp-19-565-2019, 2019
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Based on observed data, this study reveals a distinct seesaw feature of abnormally high and low PM2.5 concentrations in December 2015 and January 2016 over North China. The mechanism of the seesaw pattern was found to be linked to a super El Niño and the Arctic Oscillation (AO). During the mature phase of El Niño in December 2015, the weakened East Asian winter monsoon favors strong haze formation; however, the circulation pattern was reversed in the next month due to the phase change of the AO.
Mingxu Liu, Xin Huang, Yu Song, Tingting Xu, Shuxiao Wang, Zhijun Wu, Min Hu, Lin Zhang, Qiang Zhang, Yuepeng Pan, Xuejun Liu, and Tong Zhu
Atmos. Chem. Phys., 18, 17933–17943, https://doi.org/10.5194/acp-18-17933-2018, https://doi.org/10.5194/acp-18-17933-2018, 2018
Bin Zhao, Jonathan H. Jiang, David J. Diner, Hui Su, Yu Gu, Kuo-Nan Liou, Zhe Jiang, Lei Huang, Yoshi Takano, Xuehua Fan, and Ali H. Omar
Atmos. Chem. Phys., 18, 11247–11260, https://doi.org/10.5194/acp-18-11247-2018, https://doi.org/10.5194/acp-18-11247-2018, 2018
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We combine satellite-borne and ground-based observations to investigate the intra-annual variations of regional aerosol column loading, vertical distribution, and particle types. Column aerosol optical depth (AOD), as well as AOD > 800 m, peaks in summer/spring. However, AOD < 800 m and surface PM2.5 concentrations mostly peak in winter. The aerosol intra-annual variations differ significantly according to aerosol types characterized by different sizes, light absorption, and emission sources.
Yi Tang, Shuxiao Wang, Qingru Wu, Kaiyun Liu, Long Wang, Shu Li, Wei Gao, Lei Zhang, Haotian Zheng, Zhijian Li, and Jiming Hao
Atmos. Chem. Phys., 18, 8279–8291, https://doi.org/10.5194/acp-18-8279-2018, https://doi.org/10.5194/acp-18-8279-2018, 2018
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In this study, 3-year measurements of atmospheric Hg were carried out at a rural site in East China. A significant downward trend was observed during the sampling period. This study used a new approach that considers both cluster frequency and the Hg concentration associated with each cluster, and we calculated that atmospheric Hg from the whole region of China has caused a 70 % decline of GEM concentration at the Chongming monitoring site due to strict air pollution control policies in China.
Chandra Venkataraman, Michael Brauer, Kushal Tibrewal, Pankaj Sadavarte, Qiao Ma, Aaron Cohen, Sreelekha Chaliyakunnel, Joseph Frostad, Zbigniew Klimont, Randall V. Martin, Dylan B. Millet, Sajeev Philip, Katherine Walker, and Shuxiao Wang
Atmos. Chem. Phys., 18, 8017–8039, https://doi.org/10.5194/acp-18-8017-2018, https://doi.org/10.5194/acp-18-8017-2018, 2018
Jia Xing, Dian Ding, Shuxiao Wang, Bin Zhao, Carey Jang, Wenjing Wu, Fenfen Zhang, Yun Zhu, and Jiming Hao
Atmos. Chem. Phys., 18, 7799–7814, https://doi.org/10.5194/acp-18-7799-2018, https://doi.org/10.5194/acp-18-7799-2018, 2018
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NOx is the common precursor for both PM2.5 and O3 pollution, while the effectiveness of NOx controls for reducing PM2.5 and O3 are largely influenced by the ambient levels of NH3 and VOCs. This study developed a new method to quantify the nonlinear effectiveness of emission controls for reducing PM2.5 and O3. The new method not only substantially reduces the computational burden but also provides a series of quantitative indicators to quantify the nonlinear control effectiveness.
Shaojie Song, Meng Gao, Weiqi Xu, Jingyuan Shao, Guoliang Shi, Shuxiao Wang, Yuxuan Wang, Yele Sun, and Michael B. McElroy
Atmos. Chem. Phys., 18, 7423–7438, https://doi.org/10.5194/acp-18-7423-2018, https://doi.org/10.5194/acp-18-7423-2018, 2018
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Severe haze events occur frequently over northern China, especially in winter. Acidity plays a critical role in the formation of secondary PM2.5 and its toxicity. Using field measurements of gases and particles to critically evaluate two thermodynamic models routinely employed to determine particle acidity, we found that China's winter haze particles are generally within a moderately acidic range (pH 4–5) and not highly acidic (0) or neutral (7) as has been previously reported in the literature.
Longtao Wu, Yu Gu, Jonathan H. Jiang, Hui Su, Nanpeng Yu, Chun Zhao, Yun Qian, Bin Zhao, Kuo-Nan Liou, and Yong-Sang Choi
Atmos. Chem. Phys., 18, 5529–5547, https://doi.org/10.5194/acp-18-5529-2018, https://doi.org/10.5194/acp-18-5529-2018, 2018
Xing Chang, Shuxiao Wang, Bin Zhao, Siyi Cai, and Jiming Hao
Atmos. Chem. Phys., 18, 4843–4858, https://doi.org/10.5194/acp-18-4843-2018, https://doi.org/10.5194/acp-18-4843-2018, 2018
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The Beijing–Tianjin–Hebei region in China has been suffering from a severe particulate matter pollution, and the inter-city transport of the pollutant plays an important role. The current research quantitatively assesses the transport process. We identify three transport pathways. The southwest–northwest one happens in both winter and summer. The transport is stronger at 300–1000 m, or 1–2 days before a pollution peak. The result may guide the joint emission control along the transport pathway.
Bin Zhao, Kuo-Nan Liou, Yu Gu, Jonathan H. Jiang, Qinbin Li, Rong Fu, Lei Huang, Xiaohong Liu, Xiangjun Shi, Hui Su, and Cenlin He
Atmos. Chem. Phys., 18, 1065–1078, https://doi.org/10.5194/acp-18-1065-2018, https://doi.org/10.5194/acp-18-1065-2018, 2018
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The interactions between aerosols and ice clouds represent one of the largest uncertainties among anthropogenic forcings on climate change. We find that the responses of ice crystal effective radius, a key parameter determining ice clouds' net radiative effect, to aerosol loadings are modulated by water vapor amount and vary from a significant negative correlation in moist conditions (consistent with the “Twomey effect” for liquid clouds) to a strong positive correlation in dry conditions.
Qian Yu, Yao Luo, Shuxiao Wang, Zhiqi Wang, Jiming Hao, and Lei Duan
Atmos. Chem. Phys., 18, 495–509, https://doi.org/10.5194/acp-18-495-2018, https://doi.org/10.5194/acp-18-495-2018, 2018
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This study provides high-quality direct observation data of a clean and a contaminated site in subtropical south China and quantifies the natural forest Hg emission. We find that clean and contaminated forests present a net GEM source with annual average values of 6.67 and 0.30 ng m-2 h-1, respectively; daily variations of GEM fluxes showed a source in the daytime with a peak at 13:00, and as a sink or balance at night; and higher atmospheric GEM concentration restricted the forest GEM emission.
Jianlin Hu, Xun Li, Lin Huang, Qi Ying, Qiang Zhang, Bin Zhao, Shuxiao Wang, and Hongliang Zhang
Atmos. Chem. Phys., 17, 13103–13118, https://doi.org/10.5194/acp-17-13103-2017, https://doi.org/10.5194/acp-17-13103-2017, 2017
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The model performance of CMAQ with WRF using four different emission inventories in China was validated and compared to obtain the best air pollutants prediction for health effect studies of severe air pollution. The differences in performance of chemical transport model were analyzed for different months and regions in the vast part of China and ensemble predictions were firstly obtained from different inventories for health analysis with minimized errors for pollutants including PM2.5 and O3.
Bin Zhao, Wenjing Wu, Shuxiao Wang, Jia Xing, Xing Chang, Kuo-Nan Liou, Jonathan H. Jiang, Yu Gu, Carey Jang, Joshua S. Fu, Yun Zhu, Jiandong Wang, Yan Lin, and Jiming Hao
Atmos. Chem. Phys., 17, 12031–12050, https://doi.org/10.5194/acp-17-12031-2017, https://doi.org/10.5194/acp-17-12031-2017, 2017
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Using over 1000 chemical transport model simulations in the Beijing–Tianjin–Hebei region, we find that the emissions of primary inorganic PM2.5 make the largest contribution to PM2.5 concentrations and thus should be prioritized in PM2.5 control strategies. Among the precursors, PM2.5 concentrations are primarily sensitive to the emissions of NH3, NMVOC+IVOC, and POA, and the sensitivities increase substantially for NH3 and NHx with the increase in emission reduction ratio.
Qingru Wu, Wei Gao, Shuxiao Wang, and Jiming Hao
Atmos. Chem. Phys., 17, 10423–10433, https://doi.org/10.5194/acp-17-10423-2017, https://doi.org/10.5194/acp-17-10423-2017, 2017
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Iron and steel production (ISP) is one of the most significant atmospheric Hg emission sources in China. Atmospheric Hg emissions from ISP increased from 11.5 t in 2000 to 32.75 t in 2015 with a peak of 35.65 t in 2013. In the coming years, emissions from ISP are expected to decrease. Although sinter/pellet plants and blast furnaces were the largest two emission processes, emissions from roasting plants and coke ovens accounted for 22 %–34 % of ISP’s emissions.
Jia Xing, Jiandong Wang, Rohit Mathur, Shuxiao Wang, Golam Sarwar, Jonathan Pleim, Christian Hogrefe, Yuqiang Zhang, Jingkun Jiang, David C. Wong, and Jiming Hao
Atmos. Chem. Phys., 17, 9869–9883, https://doi.org/10.5194/acp-17-9869-2017, https://doi.org/10.5194/acp-17-9869-2017, 2017
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The assessment of the impacts of aerosol direct effects (ADE) is important for understanding emission reduction strategies that seek co-benefits associated with reductions in both particulate matter and ozone. This study quantifies the ADE impacts on tropospheric ozone by using a two-way coupled meteorology and atmospheric chemistry model. Results suggest that reducing ADE may have the potential risk of increasing ozone in winter, but it will benefit the reduction of maxima ozone in summer.
Leiming Zhang, Seth Lyman, Huiting Mao, Che-Jen Lin, David A. Gay, Shuxiao Wang, Mae Sexauer Gustin, Xinbin Feng, and Frank Wania
Atmos. Chem. Phys., 17, 9133–9144, https://doi.org/10.5194/acp-17-9133-2017, https://doi.org/10.5194/acp-17-9133-2017, 2017
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Future research needs are proposed for improving the understanding of atmospheric mercury cycling. These include refinement of mercury emission estimations, quantification of dry deposition and air–surface exchange, improvement of the treatment of chemical mechanisms in chemical transport models, increase in the accuracy of oxidized mercury measurements, better interpretation of atmospheric mercury chemistry data, and harmonization of network operation.
Johannes Bieser, Franz Slemr, Jesse Ambrose, Carl Brenninkmeijer, Steve Brooks, Ashu Dastoor, Francesco DeSimone, Ralf Ebinghaus, Christian N. Gencarelli, Beate Geyer, Lynne E. Gratz, Ian M. Hedgecock, Daniel Jaffe, Paul Kelley, Che-Jen Lin, Lyatt Jaegle, Volker Matthias, Andrei Ryjkov, Noelle E. Selin, Shaojie Song, Oleg Travnikov, Andreas Weigelt, Winston Luke, Xinrong Ren, Andreas Zahn, Xin Yang, Yun Zhu, and Nicola Pirrone
Atmos. Chem. Phys., 17, 6925–6955, https://doi.org/10.5194/acp-17-6925-2017, https://doi.org/10.5194/acp-17-6925-2017, 2017
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We conducted a multi model study to investigate our ability to reproduce the vertical distribution of mercury in the atmosphere. For this, we used observational data from over 40 aircraft flights in EU and US. We compared observations to the results of seven chemistry transport models and found that the models are able to reproduce vertical gradients of total and elemental Hg. Finally, we found that different chemical reactions seem responsible for the oxidation of Hg depending on altitude.
Qiao Ma, Siyi Cai, Shuxiao Wang, Bin Zhao, Randall V. Martin, Michael Brauer, Aaron Cohen, Jingkun Jiang, Wei Zhou, Jiming Hao, Joseph Frostad, Mohammad H. Forouzanfar, and Richard T. Burnett
Atmos. Chem. Phys., 17, 4477–4491, https://doi.org/10.5194/acp-17-4477-2017, https://doi.org/10.5194/acp-17-4477-2017, 2017
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In order to quantitatively identify the contributions of coal combustion to airborne fine particles, we developed an emission inventory using up-to-date information and conducted simulations using an atmospheric model. Results show that coal combustion contributes 40 % of the airborne fine-particle concentration on national average in China. Among the subsectors of coal combustion, industrial coal burning is the dominant contributor, which should be prioritized when policies are applied.
Jianlin Hu, Peng Wang, Qi Ying, Hongliang Zhang, Jianjun Chen, Xinlei Ge, Xinghua Li, Jingkun Jiang, Shuxiao Wang, Jie Zhang, Yu Zhao, and Yingyi Zhang
Atmos. Chem. Phys., 17, 77–92, https://doi.org/10.5194/acp-17-77-2017, https://doi.org/10.5194/acp-17-77-2017, 2017
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An annual simulation of secondary organic aerosol (SOA) concentrations in China with updated SOA formation pathways reveals that SOA can be a significant contributor to PM2.5 in major urban areas. Summer SOA is dominated by emissions from biogenic sources, while winter SOA is dominated by anthropogenic emissions such as alkanes and aromatic compounds. Reactive surface uptake of dicarbonyls throughout the year and isoprene epoxides in summer is the most important contributor.
Yang Hua, Shuxiao Wang, Jiandong Wang, Jingkun Jiang, Tianshu Zhang, Yu Song, Ling Kang, Wei Zhou, Runlong Cai, Di Wu, Siwei Fan, Tong Wang, Xiaoqing Tang, Qiang Wei, Feng Sun, and Zhimei Xiao
Atmos. Chem. Phys., 16, 15451–15460, https://doi.org/10.5194/acp-16-15451-2016, https://doi.org/10.5194/acp-16-15451-2016, 2016
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The characteristics of three PM2.5 pollution episodes were analyzed during the APEC Summit at a rural site outside of Beijing. It was found that meteorological conditions on the ground could not explain the pollution process, while vertical parameters helped improve the understanding of heavy pollution processes. Our research suggests that regional transport of air pollutants contributes significantly to severe secondary particle pollution, even when local emission is controlled effectively.
Bin Zhao, Kuo-Nan Liou, Yu Gu, Cenlin He, Wee-Liang Lee, Xing Chang, Qinbin Li, Shuxiao Wang, Hsien-Liang R. Tseng, Lai-Yung R. Leung, and Jiming Hao
Atmos. Chem. Phys., 16, 5841–5852, https://doi.org/10.5194/acp-16-5841-2016, https://doi.org/10.5194/acp-16-5841-2016, 2016
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We examine the impact of buildings on surface solar fluxes in Beijing by accounting for their 3-D structures. We find that inclusion of buildings changes surface solar fluxes by within ±1 W m−2, ±1–10 W m−2, and up to ±100 W m−2 at grid resolutions of 4 km, 800 m, and 90 m, respectively. We can resolve pairs of positive-negative flux deviations on different sides of buildings at ≤ 800 m resolutions. We should treat building-effect on solar fluxes differently in models with different resolutions.
Lei Zhang, Shuxiao Wang, Qingru Wu, Fengyang Wang, Che-Jen Lin, Leiming Zhang, Mulin Hui, Mei Yang, Haitao Su, and Jiming Hao
Atmos. Chem. Phys., 16, 2417–2433, https://doi.org/10.5194/acp-16-2417-2016, https://doi.org/10.5194/acp-16-2417-2016, 2016
A. Stohl, B. Aamaas, M. Amann, L. H. Baker, N. Bellouin, T. K. Berntsen, O. Boucher, R. Cherian, W. Collins, N. Daskalakis, M. Dusinska, S. Eckhardt, J. S. Fuglestvedt, M. Harju, C. Heyes, Ø. Hodnebrog, J. Hao, U. Im, M. Kanakidou, Z. Klimont, K. Kupiainen, K. S. Law, M. T. Lund, R. Maas, C. R. MacIntosh, G. Myhre, S. Myriokefalitakis, D. Olivié, J. Quaas, B. Quennehen, J.-C. Raut, S. T. Rumbold, B. H. Samset, M. Schulz, Ø. Seland, K. P. Shine, R. B. Skeie, S. Wang, K. E. Yttri, and T. Zhu
Atmos. Chem. Phys., 15, 10529–10566, https://doi.org/10.5194/acp-15-10529-2015, https://doi.org/10.5194/acp-15-10529-2015, 2015
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This paper presents a summary of the findings of the ECLIPSE EU project. The project has investigated the climate and air quality impacts of short-lived climate pollutants (especially methane, ozone, aerosols) and has designed a global mitigation strategy that maximizes co-benefits between air quality and climate policy. Transient climate model simulations allowed quantifying the impacts on temperature (e.g., reduction in global warming by 0.22K for the decade 2041-2050) and precipitation.
B. Zhao, S. X. Wang, J. Xing, K. Fu, J. S. Fu, C. Jang, Y. Zhu, X. Y. Dong, Y. Gao, W. J. Wu, J. D. Wang, and J. M. Hao
Geosci. Model Dev., 8, 115–128, https://doi.org/10.5194/gmd-8-115-2015, https://doi.org/10.5194/gmd-8-115-2015, 2015
S. X. Wang, B. Zhao, S. Y. Cai, Z. Klimont, C. P. Nielsen, T. Morikawa, J. H. Woo, Y. Kim, X. Fu, J. Y. Xu, J. M. Hao, and K. B. He
Atmos. Chem. Phys., 14, 6571–6603, https://doi.org/10.5194/acp-14-6571-2014, https://doi.org/10.5194/acp-14-6571-2014, 2014
Z. Cheng, S. Wang, X. Fu, J. G. Watson, J. Jiang, Q. Fu, C. Chen, B. Xu, J. Yu, J. C. Chow, and J. Hao
Atmos. Chem. Phys., 14, 4573–4585, https://doi.org/10.5194/acp-14-4573-2014, https://doi.org/10.5194/acp-14-4573-2014, 2014
X. Fu, S. X. Wang, Z. Cheng, J. Xing, B. Zhao, J. D. Wang, and J. M. Hao
Atmos. Chem. Phys., 14, 1239–1254, https://doi.org/10.5194/acp-14-1239-2014, https://doi.org/10.5194/acp-14-1239-2014, 2014
L. Zhang, S. X. Wang, L. Wang, and J. M. Hao
Atmos. Chem. Phys., 13, 10505–10516, https://doi.org/10.5194/acp-13-10505-2013, https://doi.org/10.5194/acp-13-10505-2013, 2013
Related subject area
Domain: ESSD – Atmosphere | Subject: Energy and Emissions
The global daily High Spatial–Temporal Coverage Merged tropospheric NO2 dataset (HSTCM-NO2) from 2007 to 2022 based on OMI and GOME-2
In situ airborne measurements of atmospheric parameters and airborne sea surface properties related to offshore wind parks in the German Bight during the project X-Wakes
Modeling fuel-, vehicle-type-, and age-specific CO2 emissions from global on-road vehicles in 1970–2020
Comparison of observation- and inventory-based methane emissions for eight large global emitters
Constructing a measurement-based spatially explicit inventory of US oil and gas methane emissions (2021)
State of Wildfires 2023–2024
Global Emissions Inventory from Open Biomass Burning (GEIOBB): utilizing Fengyun-3D global fire spot monitoring data
Development of a high-resolution integrated emission inventory of air pollutants for China
Brazilian Atmospheric Inventories – BRAIN: a comprehensive database of air quality in Brazil
Air pollution emission inventory using national high-resolution spatial parameters for the Nordic countries and analysis of PM2.5 spatial distribution for road transport and machinery and off-road sectors
A quality-assured dataset of nine radiation components observed at the Shangdianzi regional GAW station in China (2013–2022)
CoCO2-MOSAIC 1.0: a global mosaic of regional, gridded, fossil, and biofuel CO2 emission inventories
A global catalogue of CO2 emissions and co-emitted species from power plants, including high-resolution vertical and temporal profiles
Global Carbon Budget 2023
Spatiotemporally resolved emissions and concentrations of styrene, benzene, toluene, ethylbenzene, and xylenes (SBTEX) in the US Gulf region
Global carbon uptake of cement carbonation accounts 1930–2021
A dense station-based, long-term and high-accuracy dataset of daily surface solar radiation in China
The consolidated European synthesis of CO2 emissions and removals for the European Union and United Kingdom: 1990–2020
Decadal growth in emission load of major air pollutants in Delhi
Improved catalog of NOx point source emissions (version 2)
The HTAP_v3 emission mosaic: merging regional and global monthly emissions (2000–2018) to support air quality modelling and policies
Indicators of Global Climate Change 2022: annual update of large-scale indicators of the state of the climate system and human influence
Emission trends of air pollutants and CO2 in China from 2005 to 2021
Ten years of 1 Hz solar irradiance observations at Cabauw, the Netherlands, with cloud observations, variability classifications, and statistics
The consolidated European synthesis of CH4 and N2O emissions for the European Union and United Kingdom: 1990–2019
Spatially resolved hourly traffic emission over megacity Delhi using advanced traffic flow data
Near-real-time CO2 fluxes from CarbonTracker Europe for high-resolution atmospheric modeling
Retrievals of XCO2, XCH4 and XCO from portable, near-infrared Fourier transform spectrometer solar observations in Antarctica
Carbon fluxes from land 2000–2020: bringing clarity to countries' reporting
DeepOWT: a global offshore wind turbine data set derived with deep learning from Sentinel-1 data
Kai Qin, Hongrui Gao, Xuancen Liu, Qin He, Pravash Tiwari, and Jason Blake Cohen
Earth Syst. Sci. Data, 16, 5287–5310, https://doi.org/10.5194/essd-16-5287-2024, https://doi.org/10.5194/essd-16-5287-2024, 2024
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Satellites have brought new opportunities for monitoring atmospheric NO2, although the results are limited by clouds and other factors, resulting in missing data. This work proposes a new process to obtain reliable data products with high coverage by reconstructing the raw data from multiple satellites. The results are validated in terms of traditional methods as well as variance maximization and demonstrate a good ability to reproduce known polluted and clean areas around the world.
Astrid Lampert, Rudolf Hankers, Thomas Feuerle, Thomas Rausch, Matthias Cremer, Maik Angermann, Mark Bitter, Jonas Füllgraf, Helmut Schulz, Ulf Bestmann, and Konrad B. Bärfuss
Earth Syst. Sci. Data, 16, 4777–4792, https://doi.org/10.5194/essd-16-4777-2024, https://doi.org/10.5194/essd-16-4777-2024, 2024
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We conducted flights above the North Sea and investigated changes in the wind field. The research aircraft measured wind speed, wind direction, temperature, humidity and sea surface at high resolution. Wind parks reduce the wind speed, and the data help to determine how long it takes for the wind speed to recover. The coast also plays an important role, and the wind speed varies with distance from the coast. The results help in wind park planning and better estimating the energy yield.
Liu Yan, Qiang Zhang, Bo Zheng, and Kebin He
Earth Syst. Sci. Data, 16, 4497–4509, https://doi.org/10.5194/essd-16-4497-2024, https://doi.org/10.5194/essd-16-4497-2024, 2024
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A new database of fuel-, vehicle-type-, and age-specific CO2 emissions from global on-road vehicles from 1970 to 2020 is developed with the fleet turnover model built in this study. Based on this database, the evolution of the global vehicle stock over 50 years is analyzed, the dominant emission contributors by vehicle and fuel type are identified, and the age distribution of on-road CO2 emissions is characterized further.
Ana Maria Roxana Petrescu, Glen P. Peters, Richard Engelen, Sander Houweling, Dominik Brunner, Aki Tsuruta, Bradley Matthews, Prabir K. Patra, Dmitry Belikov, Rona L. Thompson, Lena Höglund-Isaksson, Wenxin Zhang, Arjo J. Segers, Giuseppe Etiope, Giancarlo Ciotoli, Philippe Peylin, Frédéric Chevallier, Tuula Aalto, Robbie M. Andrew, David Bastviken, Antoine Berchet, Grégoire Broquet, Giulia Conchedda, Stijn N. C. Dellaert, Hugo Denier van der Gon, Johannes Gütschow, Jean-Matthieu Haussaire, Ronny Lauerwald, Tiina Markkanen, Jacob C. A. van Peet, Isabelle Pison, Pierre Regnier, Espen Solum, Marko Scholze, Maria Tenkanen, Francesco N. Tubiello, Guido R. van der Werf, and John R. Worden
Earth Syst. Sci. Data, 16, 4325–4350, https://doi.org/10.5194/essd-16-4325-2024, https://doi.org/10.5194/essd-16-4325-2024, 2024
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This study provides an overview of data availability from observation- and inventory-based CH4 emission estimates. It systematically compares them and provides recommendations for robust comparisons, aiming to steadily engage more parties in using observational methods to complement their UNFCCC submissions. Anticipating improvements in atmospheric modelling and observations, future developments need to resolve knowledge gaps in both approaches and to better quantify remaining uncertainty.
Mark Omara, Anthony Himmelberger, Katlyn MacKay, James P. Williams, Joshua Benmergui, Maryann Sargent, Steven C. Wofsy, and Ritesh Gautam
Earth Syst. Sci. Data, 16, 3973–3991, https://doi.org/10.5194/essd-16-3973-2024, https://doi.org/10.5194/essd-16-3973-2024, 2024
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We review, analyze, and synthesize previous peer-reviewed measurement-based data on facility-level oil and gas methane emissions and use these data to develop a high-resolution spatially explicit inventory of US basin-level and national methane emissions. This work provides an improved assessment of national methane emissions relative to government inventories in support of accurate and comprehensive methane emissions assessment, attribution, and mitigation.
Matthew W. Jones, Douglas I. Kelley, Chantelle A. Burton, Francesca Di Giuseppe, Maria Lucia F. Barbosa, Esther Brambleby, Andrew J. Hartley, Anna Lombardi, Guilherme Mataveli, Joe R. McNorton, Fiona R. Spuler, Jakob B. Wessel, John T. Abatzoglou, Liana O. Anderson, Niels Andela, Sally Archibald, Dolors Armenteras, Eleanor Burke, Rachel Carmenta, Emilio Chuvieco, Hamish Clarke, Stefan H. Doerr, Paulo M. Fernandes, Louis Giglio, Douglas S. Hamilton, Stijn Hantson, Sarah Harris, Piyush Jain, Crystal A. Kolden, Tiina Kurvits, Seppe Lampe, Sarah Meier, Stacey New, Mark Parrington, Morgane M. G. Perron, Yuquan Qu, Natasha S. Ribeiro, Bambang H. Saharjo, Jesus San-Miguel-Ayanz, Jacquelyn K. Shuman, Veerachai Tanpipat, Guido R. van der Werf, Sander Veraverbeke, and Gavriil Xanthopoulos
Earth Syst. Sci. Data, 16, 3601–3685, https://doi.org/10.5194/essd-16-3601-2024, https://doi.org/10.5194/essd-16-3601-2024, 2024
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This inaugural State of Wildfires report catalogues extreme fires of the 2023–2024 fire season. For key events, we analyse their predictability and drivers and attribute them to climate change and land use. We provide a seasonal outlook and decadal projections. Key anomalies occurred in Canada, Greece, and western Amazonia, with other high-impact events catalogued worldwide. Climate change significantly increased the likelihood of extreme fires, and mitigation is required to lessen future risk.
Yang Liu, Jie Chen, Yusheng Shi, Wei Zheng, Tianchan Shan, and Gang Wang
Earth Syst. Sci. Data, 16, 3495–3515, https://doi.org/10.5194/essd-16-3495-2024, https://doi.org/10.5194/essd-16-3495-2024, 2024
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Open biomass burning has a significant impact on regional and global air quality. To enhance the quantification of global emissions from open biomass burning, we have developed the Global Emissions Inventory from Open Biomass Burning (GEIOBB) dataset, which provides a global daily-scale database at 1 km resolution of multiple pollutant emissions. This database aids global-scale environmental analysis of biomass burning.
Nana Wu, Guannan Geng, Ruochong Xu, Shigan Liu, Xiaodong Liu, Qinren Shi, Ying Zhou, Yu Zhao, Huan Liu, Yu Song, Junyu Zheng, Qiang Zhang, and Kebin He
Earth Syst. Sci. Data, 16, 2893–2915, https://doi.org/10.5194/essd-16-2893-2024, https://doi.org/10.5194/essd-16-2893-2024, 2024
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The commonly used method for developing large-scale air pollutant emission datasets for China faces challenges due to limited availability of detailed parameter information. In this study, we develop an efficient integrated framework to gather such information by harmonizing seven heterogeneous inventories from five research institutions. Emission characterizations are analyzed and validated, demonstrating that the dataset provides more accurate emission magnitudes and spatiotemporal patterns.
Leonardo Hoinaski, Robson Will, and Camilo Bastos Ribeiro
Earth Syst. Sci. Data, 16, 2385–2405, https://doi.org/10.5194/essd-16-2385-2024, https://doi.org/10.5194/essd-16-2385-2024, 2024
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We introduce the Brazilian Atmospheric Inventories (BRAIN), the first comprehensive database for air quality studies in Brazil. The database encompasses hourly datasets of meteorology, emission sources, and ambient concentrations of multiple air pollutants covering the Brazilian territory. It combines local inventories, consolidated datasets, and internationally recommended models to provide essential data for developing air pollution control policies, even in data-scarce areas.
Ville-Veikko Paunu, Niko Karvosenoja, David Segersson, Susana López-Aparicio, Ole-Kenneth Nielsen, Marlene Schmidt Plejdrup, Throstur Thorsteinsson, Dam Thanh Vo, Jeroen Kuenen, Hugo Denier van der Gon, Jukka-Pekka Jalkanen, Jørgen Brandt, and Camilla Geels
Earth Syst. Sci. Data, 16, 1453–1474, https://doi.org/10.5194/essd-16-1453-2024, https://doi.org/10.5194/essd-16-1453-2024, 2024
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Air pollution is an important cause of adverse health effects, even in Nordic countries. To assess their health impacts, emission inventories with high spatial resolution are needed. We studied how national data and methods for the spatial distribution of the emissions compare to a European level inventory. For road transport the methods are well established, but for machinery and off-road emissions the current recommendations for the spatial distribution of these emissions should be improved.
Weijun Quan, Zhenfa Wang, Lin Qiao, Xiangdong Zheng, Junli Jin, Yinruo Li, Xiaomei Yin, Zhiqiang Ma, and Martin Wild
Earth Syst. Sci. Data, 16, 961–983, https://doi.org/10.5194/essd-16-961-2024, https://doi.org/10.5194/essd-16-961-2024, 2024
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Radiation components play important roles in various fields such as the Earth’s surface radiation budget, ecosystem productivity, and human health. In this study, a dataset consisting of quality-assured daily data of nine radiation components is presented based on the in situ measurements at the Shangdianzi regional GAW station in China during 2013–2022. The dataset can be applied in the validation of satellite products and numerical models and investigation of atmospheric radiation.
Ruben Urraca, Greet Janssens-Maenhout, Nicolás Álamos, Lucas Berna-Peña, Monica Crippa, Sabine Darras, Stijn Dellaert, Hugo Denier van der Gon, Mark Dowell, Nadine Gobron, Claire Granier, Giacomo Grassi, Marc Guevara, Diego Guizzardi, Kevin Gurney, Nicolás Huneeus, Sekou Keita, Jeroen Kuenen, Ana Lopez-Noreña, Enrique Puliafito, Geoffrey Roest, Simone Rossi, Antonin Soulie, and Antoon Visschedijk
Earth Syst. Sci. Data, 16, 501–523, https://doi.org/10.5194/essd-16-501-2024, https://doi.org/10.5194/essd-16-501-2024, 2024
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CoCO2-MOSAIC 1.0 is a global mosaic of regional bottom-up inventories providing gridded (0.1×0.1) monthly emissions of anthropogenic CO2. Regional inventories include country-specific information and finer spatial resolution than global inventories. CoCO2-MOSAIC provides harmonized access to these datasets and can be considered as a regionally accepted reference to assess the quality of global inventories, as done in the current paper.
Marc Guevara, Santiago Enciso, Carles Tena, Oriol Jorba, Stijn Dellaert, Hugo Denier van der Gon, and Carlos Pérez García-Pando
Earth Syst. Sci. Data, 16, 337–373, https://doi.org/10.5194/essd-16-337-2024, https://doi.org/10.5194/essd-16-337-2024, 2024
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A global dataset of emissions from thermal power plants was created for the year 2018. The resulting catalogue reports annual emissions of CO2 and co-emitted species (NOx, CO, SO2 and CH4) for more than 16000 individual facilities at their exact geographical locations. Information on the temporal and vertical distributions of the emissions is also provided at the facility level. The dataset is intended to support current and future satellite emission monitoring and inverse modelling efforts.
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Dorothee C. E. Bakker, Judith Hauck, Peter Landschützer, Corinne Le Quéré, Ingrid T. Luijkx, Glen P. Peters, Wouter Peters, Julia Pongratz, Clemens Schwingshackl, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Simone R. Alin, Peter Anthoni, Leticia Barbero, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Bertrand Decharme, Laurent Bopp, Ida Bagus Mandhara Brasika, Patricia Cadule, Matthew A. Chamberlain, Naveen Chandra, Thi-Tuyet-Trang Chau, Frédéric Chevallier, Louise P. Chini, Margot Cronin, Xinyu Dou, Kazutaka Enyo, Wiley Evans, Stefanie Falk, Richard A. Feely, Liang Feng, Daniel J. Ford, Thomas Gasser, Josefine Ghattas, Thanos Gkritzalis, Giacomo Grassi, Luke Gregor, Nicolas Gruber, Özgür Gürses, Ian Harris, Matthew Hefner, Jens Heinke, Richard A. Houghton, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Andrew R. Jacobson, Atul Jain, Tereza Jarníková, Annika Jersild, Fei Jiang, Zhe Jin, Fortunat Joos, Etsushi Kato, Ralph F. Keeling, Daniel Kennedy, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Arne Körtzinger, Xin Lan, Nathalie Lefèvre, Hongmei Li, Junjie Liu, Zhiqiang Liu, Lei Ma, Greg Marland, Nicolas Mayot, Patrick C. McGuire, Galen A. McKinley, Gesa Meyer, Eric J. Morgan, David R. Munro, Shin-Ichiro Nakaoka, Yosuke Niwa, Kevin M. O'Brien, Are Olsen, Abdirahman M. Omar, Tsuneo Ono, Melf Paulsen, Denis Pierrot, Katie Pocock, Benjamin Poulter, Carter M. Powis, Gregor Rehder, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Thais M. Rosan, Jörg Schwinger, Roland Séférian, T. Luke Smallman, Stephen M. Smith, Reinel Sospedra-Alfonso, Qing Sun, Adrienne J. Sutton, Colm Sweeney, Shintaro Takao, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Hiroyuki Tsujino, Francesco Tubiello, Guido R. van der Werf, Erik van Ooijen, Rik Wanninkhof, Michio Watanabe, Cathy Wimart-Rousseau, Dongxu Yang, Xiaojuan Yang, Wenping Yuan, Xu Yue, Sönke Zaehle, Jiye Zeng, and Bo Zheng
Earth Syst. Sci. Data, 15, 5301–5369, https://doi.org/10.5194/essd-15-5301-2023, https://doi.org/10.5194/essd-15-5301-2023, 2023
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The Global Carbon Budget 2023 describes the methodology, main results, and data sets used to quantify the anthropogenic emissions of carbon dioxide (CO2) and their partitioning among the atmosphere, land ecosystems, and the ocean over the historical period (1750–2023). These living datasets are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Chi-Tsan Wang, Bok H. Baek, William Vizuete, Lawrence S. Engel, Jia Xing, Jaime Green, Marc Serre, Richard Strott, Jared Bowden, and Jung-Hun Woo
Earth Syst. Sci. Data, 15, 5261–5279, https://doi.org/10.5194/essd-15-5261-2023, https://doi.org/10.5194/essd-15-5261-2023, 2023
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Hazardous air pollutant (HAP) human exposure studies usually rely on local measurements or dispersion model methods, but those methods are limited under spatial and temporal conditions. We processed the US EPA emission data to simulate the hourly HAP emission patterns and applied the chemical transport model to simulate the HAP concentrations. The modeled HAP results exhibit good agreement (R is 0.75 and NMB is −5.6 %) with observational data.
Zi Huang, Jiaoyue Wang, Longfei Bing, Yijiao Qiu, Rui Guo, Ying Yu, Mingjing Ma, Le Niu, Dan Tong, Robbie M. Andrew, Pierre Friedlingstein, Josep G. Canadell, Fengming Xi, and Zhu Liu
Earth Syst. Sci. Data, 15, 4947–4958, https://doi.org/10.5194/essd-15-4947-2023, https://doi.org/10.5194/essd-15-4947-2023, 2023
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This is about global and regional cement process carbon emissions and CO2 uptake calculations from 1930 to 2019. The global cement production is rising to 4.4 Gt, causing processing carbon emission of 1.81 Gt (95% CI: 1.75–1.88 Gt CO2) in 2021. Plus, in 2021, cement’s carbon accumulated uptake (22.9 Gt, 95% CI: 19.6–22.6 Gt CO2) has offset 55.2% of cement process CO2 emissions (41.5 Gt, 95% CI: 38.7–47.1 Gt CO2) since 1930.
Wenjun Tang, Junmei He, Jingwen Qi, and Kun Yang
Earth Syst. Sci. Data, 15, 4537–4551, https://doi.org/10.5194/essd-15-4537-2023, https://doi.org/10.5194/essd-15-4537-2023, 2023
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In this study, we have developed a dense station-based, long-term dataset of daily surface solar radiation in China with high accuracy. The dataset consists of estimates of global, direct and diffuse radiation at 2473 meteorological stations from the 1950s to 2021. Validation indicates that our station-based radiation dataset clearly outperforms the satellite-based radiation products. Our dataset will contribute to climate change research and solar energy applications in the future.
Matthew J. McGrath, Ana Maria Roxana Petrescu, Philippe Peylin, Robbie M. Andrew, Bradley Matthews, Frank Dentener, Juraj Balkovič, Vladislav Bastrikov, Meike Becker, Gregoire Broquet, Philippe Ciais, Audrey Fortems-Cheiney, Raphael Ganzenmüller, Giacomo Grassi, Ian Harris, Matthew Jones, Jürgen Knauer, Matthias Kuhnert, Guillaume Monteil, Saqr Munassar, Paul I. Palmer, Glen P. Peters, Chunjing Qiu, Mart-Jan Schelhaas, Oksana Tarasova, Matteo Vizzarri, Karina Winkler, Gianpaolo Balsamo, Antoine Berchet, Peter Briggs, Patrick Brockmann, Frédéric Chevallier, Giulia Conchedda, Monica Crippa, Stijn N. C. Dellaert, Hugo A. C. Denier van der Gon, Sara Filipek, Pierre Friedlingstein, Richard Fuchs, Michael Gauss, Christoph Gerbig, Diego Guizzardi, Dirk Günther, Richard A. Houghton, Greet Janssens-Maenhout, Ronny Lauerwald, Bas Lerink, Ingrid T. Luijkx, Géraud Moulas, Marilena Muntean, Gert-Jan Nabuurs, Aurélie Paquirissamy, Lucia Perugini, Wouter Peters, Roberto Pilli, Julia Pongratz, Pierre Regnier, Marko Scholze, Yusuf Serengil, Pete Smith, Efisio Solazzo, Rona L. Thompson, Francesco N. Tubiello, Timo Vesala, and Sophia Walther
Earth Syst. Sci. Data, 15, 4295–4370, https://doi.org/10.5194/essd-15-4295-2023, https://doi.org/10.5194/essd-15-4295-2023, 2023
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Accurate estimation of fluxes of carbon dioxide from the land surface is essential for understanding future impacts of greenhouse gas emissions on the climate system. A wide variety of methods currently exist to estimate these sources and sinks. We are continuing work to develop annual comparisons of these diverse methods in order to clarify what they all actually calculate and to resolve apparent disagreement, in addition to highlighting opportunities for increased understanding.
Saroj Kumar Sahu, Poonam Mangaraj, and Gufran Beig
Earth Syst. Sci. Data, 15, 3183–3202, https://doi.org/10.5194/essd-15-3183-2023, https://doi.org/10.5194/essd-15-3183-2023, 2023
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The developed emission inventory identifies all the potential anthropogenic sources active in the Delhi NCR. The decadal change (2010–2020) and the changing policies have also been illustrated to observe the modulation in the sectorial emission trend. Emission hotspots with possible source-specific mitigation strategies have also been highlighted to improve the air quality of the Delhi NCR. The provided dataset is a vital tool for air quality and chemical transport modeling studies.
Steffen Beirle, Christian Borger, Adrian Jost, and Thomas Wagner
Earth Syst. Sci. Data, 15, 3051–3073, https://doi.org/10.5194/essd-15-3051-2023, https://doi.org/10.5194/essd-15-3051-2023, 2023
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We present a catalog of nitrogen oxide emissions from point sources (like power plants or metal smelters) based on satellite observations of NO2 combined with meteorological wind fields.
Monica Crippa, Diego Guizzardi, Tim Butler, Terry Keating, Rosa Wu, Jacek Kaminski, Jeroen Kuenen, Junichi Kurokawa, Satoru Chatani, Tazuko Morikawa, George Pouliot, Jacinthe Racine, Michael D. Moran, Zbigniew Klimont, Patrick M. Manseau, Rabab Mashayekhi, Barron H. Henderson, Steven J. Smith, Harrison Suchyta, Marilena Muntean, Efisio Solazzo, Manjola Banja, Edwin Schaaf, Federico Pagani, Jung-Hun Woo, Jinseok Kim, Fabio Monforti-Ferrario, Enrico Pisoni, Junhua Zhang, David Niemi, Mourad Sassi, Tabish Ansari, and Kristen Foley
Earth Syst. Sci. Data, 15, 2667–2694, https://doi.org/10.5194/essd-15-2667-2023, https://doi.org/10.5194/essd-15-2667-2023, 2023
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This study responds to the global and regional atmospheric modelling community's need for a mosaic of air pollutant emissions with global coverage, long time series, spatially distributed data at a high time resolution, and a high sectoral resolution in order to enhance the understanding of transboundary air pollution. The mosaic approach to integrating official regional emission inventories with a global inventory based on a consistent methodology ensures policy-relevant results.
Piers M. Forster, Christopher J. Smith, Tristram Walsh, William F. Lamb, Robin Lamboll, Mathias Hauser, Aurélien Ribes, Debbie Rosen, Nathan Gillett, Matthew D. Palmer, Joeri Rogelj, Karina von Schuckmann, Sonia I. Seneviratne, Blair Trewin, Xuebin Zhang, Myles Allen, Robbie Andrew, Arlene Birt, Alex Borger, Tim Boyer, Jiddu A. Broersma, Lijing Cheng, Frank Dentener, Pierre Friedlingstein, José M. Gutiérrez, Johannes Gütschow, Bradley Hall, Masayoshi Ishii, Stuart Jenkins, Xin Lan, June-Yi Lee, Colin Morice, Christopher Kadow, John Kennedy, Rachel Killick, Jan C. Minx, Vaishali Naik, Glen P. Peters, Anna Pirani, Julia Pongratz, Carl-Friedrich Schleussner, Sophie Szopa, Peter Thorne, Robert Rohde, Maisa Rojas Corradi, Dominik Schumacher, Russell Vose, Kirsten Zickfeld, Valérie Masson-Delmotte, and Panmao Zhai
Earth Syst. Sci. Data, 15, 2295–2327, https://doi.org/10.5194/essd-15-2295-2023, https://doi.org/10.5194/essd-15-2295-2023, 2023
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This is a critical decade for climate action, but there is no annual tracking of the level of human-induced warming. We build on the Intergovernmental Panel on Climate Change assessment reports that are authoritative but published infrequently to create a set of key global climate indicators that can be tracked through time. Our hope is that this becomes an important annual publication that policymakers, media, scientists and the public can refer to.
Shengyue Li, Shuxiao Wang, Qingru Wu, Yanning Zhang, Daiwei Ouyang, Haotian Zheng, Licong Han, Xionghui Qiu, Yifan Wen, Min Liu, Yueqi Jiang, Dejia Yin, Kaiyun Liu, Bin Zhao, Shaojun Zhang, Ye Wu, and Jiming Hao
Earth Syst. Sci. Data, 15, 2279–2294, https://doi.org/10.5194/essd-15-2279-2023, https://doi.org/10.5194/essd-15-2279-2023, 2023
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This study compiled China's emission inventory of air pollutants and CO2 during 2005–2021 (ABaCAS-EI v2.0) based on unified emission-source framework. The emission trends and its drivers are analyzed. Key sectors and regions with higher synergistic reduction potential of air pollutants and CO2 are identified. Future control measures are suggested. The dataset and analyses provide insights into the synergistic reduction of air pollutants and CO2 emissions for China and other developing countries.
Wouter B. Mol, Wouter H. Knap, and Chiel C. van Heerwaarden
Earth Syst. Sci. Data, 15, 2139–2151, https://doi.org/10.5194/essd-15-2139-2023, https://doi.org/10.5194/essd-15-2139-2023, 2023
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We describe a dataset of detailed measurements of sunlight reaching the surface, recorded at a rate of one measurement per second for 10 years. The dataset includes detailed information on direct and scattered sunlight; classifications and statistics of variability; and observations of clouds, atmospheric composition, and wind. The dataset can be used to study how the atmosphere influences sunlight variability and to validate models that aim to predict this variability with greater accuracy.
Ana Maria Roxana Petrescu, Chunjing Qiu, Matthew J. McGrath, Philippe Peylin, Glen P. Peters, Philippe Ciais, Rona L. Thompson, Aki Tsuruta, Dominik Brunner, Matthias Kuhnert, Bradley Matthews, Paul I. Palmer, Oksana Tarasova, Pierre Regnier, Ronny Lauerwald, David Bastviken, Lena Höglund-Isaksson, Wilfried Winiwarter, Giuseppe Etiope, Tuula Aalto, Gianpaolo Balsamo, Vladislav Bastrikov, Antoine Berchet, Patrick Brockmann, Giancarlo Ciotoli, Giulia Conchedda, Monica Crippa, Frank Dentener, Christine D. Groot Zwaaftink, Diego Guizzardi, Dirk Günther, Jean-Matthieu Haussaire, Sander Houweling, Greet Janssens-Maenhout, Massaer Kouyate, Adrian Leip, Antti Leppänen, Emanuele Lugato, Manon Maisonnier, Alistair J. Manning, Tiina Markkanen, Joe McNorton, Marilena Muntean, Gabriel D. Oreggioni, Prabir K. Patra, Lucia Perugini, Isabelle Pison, Maarit T. Raivonen, Marielle Saunois, Arjo J. Segers, Pete Smith, Efisio Solazzo, Hanqin Tian, Francesco N. Tubiello, Timo Vesala, Guido R. van der Werf, Chris Wilson, and Sönke Zaehle
Earth Syst. Sci. Data, 15, 1197–1268, https://doi.org/10.5194/essd-15-1197-2023, https://doi.org/10.5194/essd-15-1197-2023, 2023
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This study updates the state-of-the-art scientific overview of CH4 and N2O emissions in the EU27 and UK in Petrescu et al. (2021a). Yearly updates are needed to improve the different respective approaches and to inform on the development of formal verification systems. It integrates the most recent emission inventories, process-based model and regional/global inversions, comparing them with UNFCCC national GHG inventories, in support to policy to facilitate real-time verification procedures.
Akash Biswal, Vikas Singh, Leeza Malik, Geetam Tiwari, Khaiwal Ravindra, and Suman Mor
Earth Syst. Sci. Data, 15, 661–680, https://doi.org/10.5194/essd-15-661-2023, https://doi.org/10.5194/essd-15-661-2023, 2023
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This paper presents detailed emission estimates of on-road traffic exhaust emissions of nine major pollutants for Delhi. We use advanced traffic data and emission factors as a function of speed to estimate emissions for each hour and 100 m × 100 m spatial resolution. We examine the source contribution according to the vehicle, fuel, road and Euro types to identify the most polluting vehicles. These data are useful for high-resolution air quality modelling for developing suitable strategies.
Auke M. van der Woude, Remco de Kok, Naomi Smith, Ingrid T. Luijkx, Santiago Botía, Ute Karstens, Linda M. J. Kooijmans, Gerbrand Koren, Harro A. J. Meijer, Gert-Jan Steeneveld, Ida Storm, Ingrid Super, Hubertus A. Scheeren, Alex Vermeulen, and Wouter Peters
Earth Syst. Sci. Data, 15, 579–605, https://doi.org/10.5194/essd-15-579-2023, https://doi.org/10.5194/essd-15-579-2023, 2023
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To monitor the progress towards the CO2 emission goals set out in the Paris Agreement, the European Union requires an independent validation of emitted CO2. For this validation, atmospheric measurements of CO2 can be used, together with first-guess estimates of CO2 emissions and uptake. To quickly inform end users, it is imperative that this happens in near real-time. To aid these efforts, we create estimates of European CO2 exchange at high resolution in near real time.
David F. Pollard, Frank Hase, Mahesh Kumar Sha, Darko Dubravica, Carlos Alberti, and Dan Smale
Earth Syst. Sci. Data, 14, 5427–5437, https://doi.org/10.5194/essd-14-5427-2022, https://doi.org/10.5194/essd-14-5427-2022, 2022
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We describe measurements made in Antarctica using an EM27/SUN, a near-infrared, portable, low-resolution spectrometer from which we can retrieve the average atmospheric concentration of several greenhouse gases. We show that these measurements are reliable and comparable to other, similar ground-based measurements. Comparisons to the ESA's Sentinel-5 precursor (S5P) satellite demonstrate the usefulness of these data for satellite validation.
Giacomo Grassi, Giulia Conchedda, Sandro Federici, Raul Abad Viñas, Anu Korosuo, Joana Melo, Simone Rossi, Marieke Sandker, Zoltan Somogyi, Matteo Vizzarri, and Francesco N. Tubiello
Earth Syst. Sci. Data, 14, 4643–4666, https://doi.org/10.5194/essd-14-4643-2022, https://doi.org/10.5194/essd-14-4643-2022, 2022
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Despite increasing attention on the role of land use CO2 fluxes in climate change mitigation, there are large differences in available databases. Here we present the most updated and complete compilation of land use CO2 data based on country submissions to United Nations Framework Convention on Climate Change and explain differences with other datasets. Our dataset brings clarity of land use CO2 fluxes and helps track country progress under the Paris Agreement.
Thorsten Hoeser, Stefanie Feuerstein, and Claudia Kuenzer
Earth Syst. Sci. Data, 14, 4251–4270, https://doi.org/10.5194/essd-14-4251-2022, https://doi.org/10.5194/essd-14-4251-2022, 2022
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The DeepOWT (Deep-learning-derived Offshore Wind Turbines) data set provides offshore wind energy infrastructure locations and their temporal deployment dynamics from July 2016 until June 2021 on a global scale. It differentiates between offshore wind turbines, platforms under construction, and offshore wind farm substations. It is derived by applying deep-learning-based object detection to Sentinel-1 imagery.
Cited articles
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Amouei Torkmahalleh, M., Gorjinezhad, S., Unluevcek, H. S., and Hopke, P. K.: Review of factors impacting emission/concentration of cooking generated particulate matter, Sci. Total Environ., 586, 1046–1056, https://doi.org/10.1016/j.scitotenv.2017.02.088, 2017.
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Chang, X., Zhao, B., Zheng, H., Wang, S., Cai, S., Guo, F., Gui, P., Huang, G., Wu, D., Han, L., Xing, J., Man, H., Hu, R., Liang, C., Xu, Q., Qiu, X., Ding, D., Liu, K., Han, R., Robinson, A. L., and Donahue, N. M.: Full-volatility emission framework corrects missing and underestimated secondary organic aerosol sources, One Earth, 5, 403–412, https://doi.org/10.1016/j.oneear.2022.03.015, 2022.
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Cheng, S., Wang, G., Lang, J., Wen, W., Wang, X., and Yao, S.: Characterization of volatile organic compounds from different cooking emissions, Atmos. Environ., 145, 299–307, https://doi.org/10.1016/j.atmosenv.2016.09.037, 2016.
Cheng, Y., Kong, S., Yao, L., Zheng, H., Wu, J., Yan, Q., Zheng, S., Hu, Y., Niu, Z., Yan, Y., Shen, Z., Shen, G., Liu, D., Wang, S., and Qi, S.: Multiyear emissions of carbonaceous aerosols from cooking, fireworks, sacrificial incense, joss paper burning, and barbecue as well as their key driving forces in China, Earth Syst. Sci. Data, 14, 4757–4775, https://doi.org/10.5194/essd-14-4757-2022, 2022.
Donahue, N. M., Kroll, J. H., Pandis, S. N., and Robinson, A. L.: A two-dimensional volatility basis set – Part 2: Diagnostics of organic-aerosol evolution, Atmos. Chem. Phys., 12, 615–634, https://doi.org/10.5194/acp-12-615-2012, 2012.
He, L., Hu, M., Huang, X., Yu, B., Zhang, Y., and Liu, D.: Measurement of emissions of fine particulate organic matter from Chinese cooking, Atmos. Environ., 38, 6557–6564, https://doi.org/10.1016/j.atmosenv.2004.08.034, 2004.
He, W., Wang, T., Shao, X., Nie, L., and Shi, A.: Pollution Characteristics of Cooking Fumes, Particulates, and Non-methane Hydrocarbons in the Exhaust of Typical Beijing Restaurants, Environ. Sci., 41, 2050–2056, https://doi.org/10.13227/j.hjkx.201908063, 2020.
Huang, D. D., Zhu, S., An, J., Wang, Q., Qiao, L., Zhou, M., He, X., Ma, Y., Sun, Y., Huang, C., Yu, J. Z., and Zhang, Q.: Comparative Assessment of Cooking Emission Contributions to Urban Organic Aerosol Using Online Molecular Tracers and Aerosol Mass Spectrometry Measurements, Environ. Sci. Technol., 55, 14526–14535, https://doi.org/10.1021/acs.est.1c03280, 2021.
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Huang, X., Han, D., Cheng, J., Chen, X., Zhou, Y., Liao, H., Dong, W., and Yuan, C.: Characteristics and health risk assessment of volatile organic compounds (VOCs) in restaurants in Shanghai, Environ. Sci. Pollut. Res., 27, 490–499, https://doi.org/10.1007/s11356-019-06881-6, 2020.
Jathar, S. H., Gordon, T. D., Hennigan, C. J., Pye, H. O. T., Pouliot, G., Adams, P. J., Donahue, N. M., and Robinson, A. L.: Unspeciated organic emissions from combustion sources and their influence on the secondary organic aerosol budget in the United States, P. Natl. Acad. Sci. USA, 111, 10473–10478, https://doi.org/10.1073/pnas.1323740111, 2014.
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Short summary
This study developed the first full-volatility organic emission inventory for cooking sources in China, presenting high-resolution cooking emissions during 2015–2021. It identified the key subsectors and hotspots of cooking emissions, analyzed emission trends and drivers, and proposed future control strategies. The dataset is valuable for accurately simulating organic aerosol formation and evolution and for understanding the impact of organic emissions on air pollution and climate change.
This study developed the first full-volatility organic emission inventory for cooking sources in...
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