Articles | Volume 19, issue 19
08 Oct 2019
Research article | 08 Oct 2019
Estimating ground-level CO concentrations across China based on the national monitoring network and MOPITT: potentially overlooked CO hotspots in the Tibetan Plateau
Dongren Liu et al.
No articles found.
Meng Zhang, Xue Qiao, Barnabas C. Seyler, Baofeng Di, Yuan Wang, and Ya Tang
Nat. Hazards Earth Syst. Sci., 21, 3243–3250,Short summary
Earthquake early warning systems (EEWSs) can help reduce losses, but their effectiveness depends on adequate public perception and understanding of EEWSs. This study examined the performance of the EEWS in China's Sichuan Province during the 2019 Changning earthquake. We found a big gap existed between the EEWS's message, the public's perception of it, and their response. The study highlights the importance of gauging EEWS alert effectiveness and public participation for long-term resiliency.
Jingsha Xu, Shaojie Song, Roy M. Harrison, Congbo Song, Lianfang Wei, Qiang Zhang, Yele Sun, Lu Lei, Chao Zhang, Xiaohong Yao, Dihui Chen, Weijun Li, Miaomiao Wu, Hezhong Tian, Lining Luo, Shengrui Tong, Weiran Li, Junling Wang, Guoliang Shi, Yanqi Huangfu, Yingze Tian, Baozhu Ge, Shaoli Su, Chao Peng, Yang Chen, Fumo Yang, Aleksandra Mihajlidi-Zelić, Dragana Đorđević, Stefan J. Swift, Imogen Andrews, Jacqueline F. Hamilton, Ye Sun, Agung Kramawijaya, Jinxiu Han, Supattarachai Saksakulkrai, Clarissa Baldo, Siqi Hou, Feixue Zheng, Kaspar R. Daellenbach, Chao Yan, Yongchun Liu, Markku Kulmala, Pingqing Fu, and Zongbo Shi
Atmos. Meas. Tech., 13, 6325–6341,Short summary
An interlaboratory comparison was conducted for the first time to examine differences in water-soluble inorganic ions (WSIIs) measured by 10 labs using ion chromatography (IC) and by two online aerosol chemical speciation monitor (ACSM) methods. Major ions including SO42−, NO3− and NH4+ agreed well in 10 IC labs and correlated well with ACSM data. WSII interlab variability strongly affected aerosol acidity results based on ion balance, but aerosol pH computed by ISORROPIA II was very similar.
Yang Chen, Jing Cai, Zhichao Wang, Chao Peng, Xiaojiang Yao, Mi Tian, Yiqun Han, Guangming Shi, Zongbo Shi, Yue Liu, Xi Yang, Mei Zheng, Tong Zhu, Kebin He, Qiang Zhang, and Fumo Yang
Atmos. Chem. Phys., 20, 9231–9247,Short summary
Patterns of particle transport, accumulation, and evolution in both urban and rural areas of Beijing are investigated. The two sites shared 17 common particle types in different stages of atmospheric processing.
Yang Chen, Guangming Shi, Jing Cai, Zongbo Shi, Zhichao Wang, Xiaojiang Yao, Mi Tian, Chao Peng, Yiqun Han, Tong Zhu, Yue Liu, Xi Yang, Mei Zheng, Fumo Yang, Qiang Zhang, and Kebin He
Atmos. Chem. Phys., 20, 9249–9263,Short summary
Individual particles were observed in two field studies during winter 2016 in the urban and rural areas of Beijing. An online single-particle chemical composition analysis was used as a tracing system to investigate the impact of heating activities and the formation of haze events. During the pollution events, a pattern of transport and accumulation was found with evidence of single particles. The transport from Pinggu to Peking University was significant but PKU to PG occurred occasionally.
Zongbo Shi, Tuan Vu, Simone Kotthaus, Roy M. Harrison, Sue Grimmond, Siyao Yue, Tong Zhu, James Lee, Yiqun Han, Matthias Demuzere, Rachel E. Dunmore, Lujie Ren, Di Liu, Yuanlin Wang, Oliver Wild, James Allan, W. Joe Acton, Janet Barlow, Benjamin Barratt, David Beddows, William J. Bloss, Giulia Calzolai, David Carruthers, David C. Carslaw, Queenie Chan, Lia Chatzidiakou, Yang Chen, Leigh Crilley, Hugh Coe, Tie Dai, Ruth Doherty, Fengkui Duan, Pingqing Fu, Baozhu Ge, Maofa Ge, Daobo Guan, Jacqueline F. Hamilton, Kebin He, Mathew Heal, Dwayne Heard, C. Nicholas Hewitt, Michael Hollaway, Min Hu, Dongsheng Ji, Xujiang Jiang, Rod Jones, Markus Kalberer, Frank J. Kelly, Louisa Kramer, Ben Langford, Chun Lin, Alastair C. Lewis, Jie Li, Weijun Li, Huan Liu, Junfeng Liu, Miranda Loh, Keding Lu, Franco Lucarelli, Graham Mann, Gordon McFiggans, Mark R. Miller, Graham Mills, Paul Monk, Eiko Nemitz, Fionna O'Connor, Bin Ouyang, Paul I. Palmer, Carl Percival, Olalekan Popoola, Claire Reeves, Andrew R. Rickard, Longyi Shao, Guangyu Shi, Dominick Spracklen, David Stevenson, Yele Sun, Zhiwei Sun, Shu Tao, Shengrui Tong, Qingqing Wang, Wenhua Wang, Xinming Wang, Xuejun Wang, Zifang Wang, Lianfang Wei, Lisa Whalley, Xuefang Wu, Zhijun Wu, Pinhua Xie, Fumo Yang, Qiang Zhang, Yanli Zhang, Yuanhang Zhang, and Mei Zheng
Atmos. Chem. Phys., 19, 7519–7546,Short summary
APHH-Beijing is a collaborative international research programme to study the sources, processes and health effects of air pollution in Beijing. This introduction to the special issue provides an overview of (i) the APHH-Beijing programme, (ii) the measurement and modelling activities performed as part of it and (iii) the air quality and meteorological conditions during joint intensive field campaigns as a core activity within APHH-Beijing.
Yang Chen, Mi Tian, Ru-Jin Huang, Guangming Shi, Huanbo Wang, Chao Peng, Junji Cao, Qiyuan Wang, Shumin Zhang, Dongmei Guo, Leiming Zhang, and Fumo Yang
Atmos. Chem. Phys., 19, 3245–3255,Short summary
Amine-containing particles were characterized in an urban area of Chongqing during both summer and winter using a single-particle aerosol mass spectrometer (SPAMS). Amines were observed to internally mix with elemental carbon (EC), organic carbon (OC), sulfate, and nitrate. Diethylamine (DEA) was the most abundant in both number and peak area among amine-containing particles. Vegetation and traffic were the primary sources of particulate amines.
Huanbo Wang, Mi Tian, Yang Chen, Guangming Shi, Yuan Liu, Fumo Yang, Leiming Zhang, Liqun Deng, Jiayan Yu, Chao Peng, and Xuyao Cao
Atmos. Chem. Phys., 18, 865–881,
Mi Tian, Huanbo Wang, Yang Chen, Fumo Yang, Xiaohua Zhang, Qiang Zou, Renquan Zhang, Yongliang Ma, and Kebin He
Atmos. Chem. Phys., 16, 7357–7371,Short summary
The discussion was based on high time resolution data which could provide detailed insight into short haze periods. The dominant species in PM2.5 and which were responsible for the visibility reduction were identified in Suzhou. The formation mechanisms of sulfate and nitrate were explored as high secondary aerosol contributions to particulate pollution during haze events. The impact of local and transport sources on the origin of aerosol pollution in Suzhou was discussed.
R. Zhao, A. K. Y. Lee, L. Huang, X. Li, F. Yang, and J. P. D. Abbatt
Atmos. Chem. Phys., 15, 6087–6100,Short summary
Aqueous-phase photochemical decay of light absorbing organic compounds, or atmospheric brown carbon (BrC), is investigated in this study. The absorptive change of laboratory surrogates of BrC, as well as biofuel combustion samples, were monitored during photolysis and OH oxidation experiments. The major finding is the rapid change in the absorptivity of BrC during such photochemical processing. This change should be taken into account to evaluate the importance of BrC in the atmosphere.
Related subject area
Subject: Gases | Research Activity: Atmospheric Modelling | Altitude Range: Troposphere | Science Focus: Physics (physical properties and processes)Updated Global Fuel Exploitation Inventory (GFEI) for methane emissions from the oil, gas, and coal sectors: evaluation with inversions of atmospheric methane observationsHigh-resolution mapping of regional traffic emissions using land-use machine learning modelsLand use and anthropogenic heat modulate ozone by meteorology: a perspective from the Yangtze River Delta regionFour years of global carbon cycle observed from the Orbiting Carbon Observatory 2 (OCO-2) version 9 and in situ data and comparison to OCO-2 version 7Data assimilation of CrIS NH3 satellite observations for improving spatiotemporal NH3 distributions in LOTOS-EUROSOn the cross-tropopause transport of water by tropical convective overshoots: a mesoscale modelling study constrained by in situ observations during the TRO-Pico field campaign in BrazilEffects of ozone–vegetation interactions on meteorology and air quality in China using a two-way coupled land–atmosphere modelThe drivers and health risks of unexpected surface ozone enhancements over the Sichuan Basin, China, in 2020Estimating 2010–2015 anthropogenic and natural methane emissions in Canada using ECCC surface and GOSAT satellite observationsThe impact of peripheral circulation characteristics of typhoon on sustained ozone episodes over the Pearl River Delta region, ChinaTechnical note: AQMEII4 Activity 1: evaluation of wet and dry deposition schemes as an integral part of regional-scale air quality modelsEvaluating the impact of storage-and-release on aircraft-based mass-balance methodology using a regional air-quality modelThe regional impact of urban emissions on air quality in Europe: the role of the urban canopy effectsA new inverse modeling approach for emission sources based on the DDM-3D and 3DVAR techniques: an application to air quality forecasts in the Beijing–Tianjin–Hebei regionQuantifying fossil fuel methane emissions using observations of atmospheric ethane and an uncertain emission ratioAssessing urban methane emissions using column-observing portable Fourier transform infrared (FTIR) spectrometers and a novel Bayesian inversion frameworkEvidence of a recent decline in UK emissions of hydrofluorocarbons determined by the InTEM inverse model and atmospheric measurementsVehicle-induced turbulence and atmospheric pollutionA comparative study to reveal the influence of typhoons on the transport, production and accumulation of O3 in the Pearl River Delta, ChinaSensitivity to the sources of uncertainties in the modeling of atmospheric CO2 concentration within and in the vicinity of ParisEstimating Upper Silesian coal mine methane emissions from airborne in situ observations and dispersion modelingAnalysis of CO2 spatio-temporal variations in China using a weather–biosphere online coupled modelMobile monitoring of urban air quality at high spatial resolution by low-cost sensors: impacts of COVID-19 pandemic lockdownLinking global terrestrial CO2 fluxes and environmental drivers: inferences from the Orbiting Carbon Observatory 2 satellite and terrestrial biospheric modelsUncertainties in the Emissions Database for Global Atmospheric Research (EDGAR) emission inventory of greenhouse gasesUsing TROPOspheric Monitoring Instrument (TROPOMI) measurements and Weather Research and Forecasting (WRF) CO modelling to understand the contribution of meteorology and emissions to an extreme air pollution event in IndiaGlobal methane budget and trend, 2010–2017: complementarity of inverse analyses using in situ (GLOBALVIEWplus CH4 ObsPack) and satellite (GOSAT) observationsCOVID-19 lockdowns highlight a risk of increasing ozone pollution in European urban areasLarge-eddy simulation of traffic-related air pollution at a very high resolution in a mega-city: evaluation against mobile sensors and insights for influencing factorsTechnical note: Emission mapping of key sectors in Ho Chi Minh City, Vietnam, using satellite-derived urban land use dataImpact of western Pacific subtropical high on ozone pollution over eastern ChinaHigh-resolution hybrid inversion of IASI ammonia columns to constrain US ammonia emissions using the CMAQ adjoint modelSimulation of radon-222 with the GEOS-Chem global model: emissions, seasonality, and convective transportRegional CO2 fluxes from 2010 to 2015 inferred from GOSAT XCO2 retrievals using a new version of the Global Carbon Assimilation SystemThe friagem event in the central Amazon and its influence on micrometeorological variables and atmospheric chemistryModeling atmospheric ammonia using agricultural emissions with improved spatial variability and temporal dynamicsQuantifying methane emissions from Queensland's coal seam gas producing Surat Basin using inventory data and a regional Bayesian inversionErrors in top-down estimates of emissions using a known sourceThe impact of urban land-surface on extreme air pollution over central EuropeImpacts of future land use and land cover change on mid-21st-century surface ozone air quality: distinguishing between the biogeophysical and biogeochemical effectsWhat have we missed when studying the impact of aerosols on surface ozone via changing photolysis rates?Stratospheric impact on the Northern Hemisphere winter and spring ozone interannual variability in the troposphereDesign and evaluation of CO2 observation network to optimize surface CO2 fluxes in Asia using observation system simulation experimentsOzone pollution over China and India: seasonality and sourcesInfluences of oceanic ozone deposition on tropospheric photochemistryInvestigating the regional contributions to air pollution in Beijing: a dispersion modelling study using CO as a tracerEvaluation of NU-WRF model performance on air quality simulation under various model resolutions – an investigation within the framework of MICS-Asia Phase IIIUrban canopy meteorological forcing and its impact on ozone and PM2.5: role of vertical turbulent transportUncertainty analysis of a European high-resolution emission inventory of CO2 and CO to support inverse modelling and network designClimate benefits of proposed carbon dioxide mitigation strategies for international shipping and aviation
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,Short summary
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.
Xiaomeng Wu, Daoyuan Yang, Ruoxi Wu, Jiajun Gu, Yifan Wen, Shaojun Zhang, Rui Wu, Renjie Wang, Honglei Xu, K. Max Zhang, Ye Wu, and Jiming Hao
Atmos. Chem. Phys., 22, 1939–1950,Short summary
Our work pioneered land-use machine learning methods for developing link-level emission inventories, utilizing hourly traffic profiles, including volume, speed, and fleet mix, obtained from the governmental intercity highway monitoring network in the "capital circles" of China. This research provides a platform to realize the near-real-time process of establishing high-resolution vehicle emission inventories for policy makers to engage in sophisticated traffic management.
Chenchao Zhan and Min Xie
Atmos. Chem. Phys., 22, 1351–1371,Short summary
The changes of land use and anthropogenic heat (AH) derived from urbanization can affect meteorology and in turn O3 evolution. In this study, we briefly describe the general features of O3 pollution in the Yangtze River Delta (YRD) based on in situ observational data. Then, the impacts of land use and anthropogenic heat on O3 via changing the meteorological factors and local circulations are investigated in this region using the WRF-Chem model.
Hélène Peiro, Sean Crowell, Andrew Schuh, David F. Baker, Chris O'Dell, Andrew R. Jacobson, Frédéric Chevallier, Junjie Liu, Annmarie Eldering, David Crisp, Feng Deng, Brad Weir, Sourish Basu, Matthew S. Johnson, Sajeev Philip, and Ian Baker
Atmos. Chem. Phys., 22, 1097–1130,Short summary
Satellite CO2 observations are constantly improved. We study an ensemble of different atmospheric models (inversions) from 2015 to 2018 using separate ground-based data or two versions of the OCO-2 satellite. Our study aims to determine if different satellite data corrections can yield different estimates of carbon cycle flux. A difference in the carbon budget between the two versions is found over tropical Africa, which seems to show the impact of corrections applied in satellite data.
Shelley van der Graaf, Enrico Dammers, Arjo Segers, Richard Kranenburg, Martijn Schaap, Mark W. Shephard, and Jan Willem Erisman
Atmos. Chem. Phys., 22, 951–972,Short summary
CrIS NH3 satellite observations are assimilated into the LOTOS-EUROS model using two different methods. In the first method the data are used to fit spatially varying NH3 emission time factors. In the second method a local ensemble transform Kalman filter is used. Compared to in situ observations, combining both methods led to the most significant improvements in the modeled concentrations and deposition, illustrating the usefulness of CrIS NH3 to improve the spatiotemporal distribution of NH3.
Abhinna K. Behera, Emmanuel D. Rivière, Sergey M. Khaykin, Virginie Marécal, Mélanie Ghysels, Jérémie Burgalat, and Gerhard Held
Atmos. Chem. Phys., 22, 881–901,Short summary
Deep convection overshooting the stratosphere's contribution to the global stratospheric water budget is still being quantified. We ran three different cloud-resolving simulations of an observed case of overshoots in Bauru during the TRO-Pico balloon campaign in the context of upscaling the impact of overshoots at a large scale. These simulations, which have been validated with balloon-borne and S-band radar measurements, shed light on the local-scale variability and composition of overshoots.
Jiachen Zhu, Amos P. K. Tai, and Steve Hung Lam Yim
Atmos. Chem. Phys., 22, 765–782,Short summary
This study assessed O3 damage to plant and the subsequent effects on meteorology and air quality in China, whereby O3, meteorology, and vegetation can co-evolve with each other. We provided comprehensive understanding about how O3–vegetation impacts adversely affect plant growth and crop production, and contribute to global warming and severe O3 air pollution in China. Our findings clearly pinpoint the need to consider the O3 damage effects in both air quality studies and climate change studies.
Youwen Sun, Hao Yin, Xiao Lu, Justus Notholt, Mathias Palm, Cheng Liu, Yuan Tian, and Bo Zheng
Atmos. Chem. Phys., 21, 18589–18608,Short summary
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.
Sabour Baray, Daniel J. Jacob, Joannes D. Maasakkers, Jian-Xiong Sheng, Melissa P. Sulprizio, Dylan B. A. Jones, A. Anthony Bloom, and Robert McLaren
Atmos. Chem. Phys., 21, 18101–18121,Short summary
We use 2010–2015 surface and satellite observations to disentangle methane from anthropogenic and natural sources in Canada. Using a chemical transport model (GEOS-Chem), the mismatch between modelled and observed methane concentrations can be used to infer emissions according to Bayesian statistics. Compared to prior knowledge, we show higher anthropogenic emissions attributed to energy and/or agriculture in Western Canada and lower natural emissions from Boreal wetlands.
Ying Li, Xiangjun Zhao, Xuejiao Deng, and Jinhui Gao
Atmos. Chem. Phys. Discuss.,
Revised manuscript accepted for ACPShort summary
This study finds a new phenomenon of weak wind depth deepening (WWDD) associated with the peripheral circulation of typhoon and gives the influence mechanism of WWDD on contributing to sustained ozone episodes. The WWD provide the premise for the pollution accumulation in the whole PBL and continue enhancement of ground-level ozone via the vertical mixing processes. This findings could benefit for the daily daytime ozone forecast in the PRD region and other areas.
Stefano Galmarini, Paul Makar, Olivia E. Clifton, Christian Hogrefe, Jesse O. Bash, Roberto Bellasio, Roberto Bianconi, Johannes Bieser, Tim Butler, Jason Ducker, Johannes Flemming, Alma Hodzic, Christopher D. Holmes, Ioannis Kioutsioukis, Richard Kranenburg, Aurelia Lupascu, Juan Luis Perez-Camanyo, Jonathan Pleim, Young-Hee Ryu, Roberto San Jose, Donna Schwede, Sam Silva, and Ralf Wolke
Atmos. Chem. Phys., 21, 15663–15697,Short summary
This technical note presents the research protocols for phase 4 of the Air Quality Model Evaluation International Initiative (AQMEII4). This initiative has three goals: (i) to define the state of wet and dry deposition in regional models, (ii) to evaluate how dry deposition influences air concentration and flux predictions, and (iii) to identify the causes for prediction differences. The evaluation compares LULC-specific dry deposition and effective conductances and fluxes.
Sepehr Fathi, Mark Gordon, Paul A. Makar, Ayodeji Akingunola, Andrea Darlington, John Liggio, Katherine Hayden, and Shao-Meng Li
Atmos. Chem. Phys., 21, 15461–15491,Short summary
We have investigated the accuracy of aircraft-based mass balance methodologies through computer model simulations of the atmosphere and air quality at a regional high-resolution scale. We have defined new quantitative metrics to reduce emission retrieval uncertainty by evaluating top-down mass balance estimates against the known simulated meteorology and input emissions. We also recommend methodologies and flight strategies for improved retrievals in future aircraft-based studies.
Peter Huszar, Jan Karlický, Jana Marková, Tereza Nováková, Marina Liaskoni, and Lukáš Bartík
Atmos. Chem. Phys., 21, 14309–14332,Short summary
Urban areas are strong hot spots of emissions influencing local and regional air quality. Cities furthermore influence the meteorological conditions due to their characteristic surface properties and geometry. We found that if these latter effects are not included in the quantification of the impact of urban emissions on regional air quality, this impact will be overestimated, and this overestimation is mainly due to the enhanced turbulence that is present in cities compared to rural areas.
Xinghong Cheng, Zilong Hao, Zengliang Zang, Zhiquan Liu, Xiangde Xu, Shuisheng Wang, Yuelin Liu, Yiwen Hu, and Xiaodan Ma
Atmos. Chem. Phys., 21, 13747–13761,Short summary
We develop a new inversion method of emission sources based on sensitivity analysis and the three-dimension variational technique. The novel explicit observation operator matrix between emission sources and the receptor’s concentrations is established. Then this method is applied to a typical heavy haze episode in North China, and spatiotemporal variations of SO2, NO2, and O3 concentrations simulated using a posterior emission sources are compared with results using an a priori inventory.
Alice E. Ramsden, Anita L. Ganesan, Luke M. Western, Matthew Rigby, Alistair J. Manning, Amy Foulds, James L. France, Patrick Barker, Peter Levy, Daniel Say, Adam Wisher, Tim Arnold, Chris Rennick, Kieran M. Stanley, Dickon Young, and Simon O'Doherty
Atmos. Chem. Phys. Discuss.,
Revised manuscript accepted for ACPShort summary
Quantifying methane emissions from different sources is a key focus of current research. We present a method for estimating sectoral methane emissions that uses ethane as a tracer for fossil fuel methane. By incorporating variable ethane:methane emission ratios into this model, we produce emissions estimates with improved uncertainty characterisation. This method will be particularly useful for studying methane emissions in areas with complex distributions of sources.
Taylor S. Jones, Jonathan E. Franklin, Jia Chen, Florian Dietrich, Kristian D. Hajny, Johannes C. Paetzold, Adrian Wenzel, Conor Gately, Elaine Gottlieb, Harrison Parker, Manvendra Dubey, Frank Hase, Paul B. Shepson, Levi H. Mielke, and Steven C. Wofsy
Atmos. Chem. Phys., 21, 13131–13147,Short summary
Methane emissions from leaks in natural gas pipes are often a large source in urban areas, but they are difficult to measure on a city-wide scale. Here we use an array of innovative methane sensors distributed around the city of Indianapolis and a new method of combining their data with an atmospheric model to accurately determine the magnitude of these emissions, which are about 70 % larger than predicted. This method can serve as a framework for cities trying to account for their emissions.
Alistair J. Manning, Alison L. Redington, Daniel Say, Simon O'Doherty, Dickon Young, Peter G. Simmonds, Martin K. Vollmer, Jens Mühle, Jgor Arduini, Gerard Spain, Adam Wisher, Michela Maione, Tanja J. Schuck, Kieran Stanley, Stefan Reimann, Andreas Engel, Paul B. Krummel, Paul J. Fraser, Christina M. Harth, Peter K. Salameh, Ray F. Weiss, Ray Gluckman, Peter N. Brown, John D. Watterson, and Tim Arnold
Atmos. Chem. Phys., 21, 12739–12755,Short summary
This paper estimates UK emissions of important greenhouse gases (hydrofluorocarbons (HFCs)) using high-quality atmospheric observations and atmospheric modelling. We compare these estimates with those submitted by the UK to the United Nations. We conclude that global concentrations of these gases are still increasing. Our estimates for the UK are 73 % of those reported and that the UK emissions are now falling, demonstrating an impact of UK government policy.
Paul A. Makar, Craig Stroud, Ayodeji Akingunola, Junhua Zhang, Shuzhan Ren, Philip Cheung, and Qiong Zheng
Atmos. Chem. Phys., 21, 12291–12316,Short summary
Vehicle pollutant emissions occur in an environment where upward transport can be enhanced due to the turbulence created by the vehicles as they move through the atmosphere. An approach for including these turbulence effects in regional air pollution forecast models has been derived from theoretical, observation, and higher-resolution modeling. The enhanced mixing, which occurs in the immediate vicinity of roadways, changes pollutant concentrations on the regional to continental scale.
Kun Qu, Xuesong Wang, Yu Yan, Jin Shen, Teng Xiao, Huabin Dong, Limin Zeng, and Yuanhang Zhang
Atmos. Chem. Phys., 21, 11593–11612,Short summary
Typhoons above the Northwest Pacific frequently lead to severe ambient ozone pollution in the Pearl River Delta, China, in autumn and summer. However, typhoons do not enhance ozone transport, production and accumulation at the same time, and differences also exist between these influences in two seasons. Through systematic comparisons, we revealed the complex interactions between local meteorology and ozone processes, which is essential for understanding the causes of regional ozone pollution.
Jinghui Lian, François-Marie Bréon, Grégoire Broquet, Thomas Lauvaux, Bo Zheng, Michel Ramonet, Irène Xueref-Remy, Simone Kotthaus, Martial Haeffelin, and Philippe Ciais
Atmos. Chem. Phys., 21, 10707–10726,Short summary
Currently there is growing interest in monitoring city-scale CO2 emissions based on atmospheric CO2 measurements, atmospheric transport modeling, and inversion technique. We analyze the various sources of uncertainty that impact the atmospheric CO2 modeling and that may compromise the potential of this method for the monitoring of CO2 emission over Paris. Results suggest selection criteria for the assimilation of CO2 measurements into the inversion system that aims at retrieving city emissions.
Julian Kostinek, Anke Roiger, Maximilian Eckl, Alina Fiehn, Andreas Luther, Norman Wildmann, Theresa Klausner, Andreas Fix, Christoph Knote, Andreas Stohl, and André Butz
Atmos. Chem. Phys., 21, 8791–8807,Short summary
Abundant mining and industrial activities in the Upper Silesian Coal Basin lead to large emissions of the potent greenhouse gas methane. This study quantifies these emissions with continuous, high-precision airborne measurements and dispersion modeling. Our emission estimates are in line with values reported in the European Pollutant Release and Transfer Register (E-PRTR 2017) but significantly lower than values reported in the Emissions Database for Global Atmospheric Research (EDGAR v4.3.2).
Xinyi Dong, Man Yue, Yujun Jiang, Xiao-Ming Hu, Qianli Ma, Jingjiao Pu, and Guangqiang Zhou
Atmos. Chem. Phys., 21, 7217–7233,Short summary
The dynamics of CO2 has received considerable attention in the literature, yet uncertainties remain. We applied an online coupled weather-biosphere model to simulate biosphere processes and meteorology simultaneously to characterize CO2 dynamics in China. Anthropogenic emission was more influential in upper air, and the biosphere flux played a more important role in surface CO2, suggesting a significant influence of the boundary layer thermal structure on the accumulation and depletion of CO2.
Shibao Wang, Yun Ma, Zhongrui Wang, Lei Wang, Xuguang Chi, Aijun Ding, Mingzhi Yao, Yunpeng Li, Qilin Li, Mengxian Wu, Ling Zhang, Yongle Xiao, and Yanxu Zhang
Atmos. Chem. Phys., 21, 7199–7215,Short summary
Mobile monitoring with low-cost sensors is a promising approach to garner high-spatial-resolution observations representative of the community scale. We develop a grid analysis method to obtain 50 m resolution maps of major air pollutants (CO, NO2, and O3) based on GIS technology. Our results demonstrate the sensing power of mobile monitoring for urban air pollution, which provides detailed information for source attribution and accurate traceability at the urban micro-scale.
Zichong Chen, Junjie Liu, Daven K. Henze, Deborah N. Huntzinger, Kelley C. Wells, Stephen Sitch, Pierre Friedlingstein, Emilie Joetzjer, Vladislav Bastrikov, Daniel S. Goll, Vanessa Haverd, Atul K. Jain, Etsushi Kato, Sebastian Lienert, Danica L. Lombardozzi, Patrick C. McGuire, Joe R. Melton, Julia E. M. S. Nabel, Benjamin Poulter, Hanqin Tian, Andrew J. Wiltshire, Sönke Zaehle, and Scot M. Miller
Atmos. Chem. Phys., 21, 6663–6680,Short summary
NASA's Orbiting Carbon Observatory 2 (OCO-2) satellite observes atmospheric CO2 globally. We use a multiple regression and inverse model to quantify the relationships between OCO-2 and environmental drivers within individual years for 2015–2018 and within seven global biomes. Our results point to limitations of current space-based observations for inferring environmental relationships but also indicate the potential to inform key relationships that are very uncertain in process-based models.
Efisio Solazzo, Monica Crippa, Diego Guizzardi, Marilena Muntean, Margarita Choulga, and Greet Janssens-Maenhout
Atmos. Chem. Phys., 21, 5655–5683,Short summary
We conducted an extensive analysis of the structural uncertainty of the Emissions Database for Global Atmospheric Research (EDGAR) emission inventory of greenhouse gases, which adds a much needed reliability dimension to the accuracy of the emission estimates. The study undertakes in-depth analyses of the implication of aggregating emissions from different sources and/or countries on the accuracy. Results are presented for all emissions sectors according to IPCC definitions.
Ashique Vellalassery, Dhanyalekshmi Pillai, Julia Marshall, Christoph Gerbig, Michael Buchwitz, Oliver Schneising, and Aparnna Ravi
Atmos. Chem. Phys., 21, 5393–5414,Short summary
We investigate factors contributing to the severe and persistent air quality degradation in northern India that has worsened during every winter over the last decade. This is achieved by implementing atmospheric modelling and using recently available Sentinel-5 P satellite data for carbon monoxide. We see a minimal role of biomass burning, except for the state of Punjab. The aim is to focus on residential and industrial emission reduction strategies to tackle air pollution over northern India.
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,Short summary
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.
Stuart K. Grange, James D. Lee, Will S. Drysdale, Alastair C. Lewis, Christoph Hueglin, Lukas Emmenegger, and David C. Carslaw
Atmos. Chem. Phys., 21, 4169–4185,Short summary
The changes in mobility across Europe due to the COVID-19 lockdowns had consequences for air quality. We compare what was experienced to estimates of "what would have been" without the lockdowns. Nitrogen dioxide (NO2), an important vehicle-sourced pollutant, decreased by a third. However, ozone (O3) increased in response to lower NO2. Because NO2 is decreasing over time, increases in O3 can be expected in European urban areas and will require management to avoid future negative outcomes.
Yanxu Zhang, Xingpei Ye, Shibao Wang, Xiaojing He, Lingyao Dong, Ning Zhang, Haikun Wang, Zhongrui Wang, Yun Ma, Lei Wang, Xuguang Chi, Aijun Ding, Mingzhi Yao, Yunpeng Li, Qilin Li, Ling Zhang, and Yongle Xiao
Atmos. Chem. Phys., 21, 2917–2929,Short summary
Urban air quality varies drastically at street scale, but traditional methods are too coarse to resolve it. We develop a 10 m resolution air quality model and apply it for traffic-related carbon monoxide air quality in Nanjing megacity. The model reveals a detailed geographical dispersion pattern of air pollution in and out of the road network and agrees well with a validation dataset. The model can be a vigorous part of the smart city system and inform urban planning and air quality management.
Trang Thi Quynh Nguyen, Wataru Takeuchi, Prakhar Misra, and Sachiko Hayashida
Atmos. Chem. Phys., 21, 2795–2818,Short summary
This study provides annual emissions of transportation, manufacturing industries and construction, and residential areas at 1 km resolution from 2009 to 2016 for Ho Chi Minh City, Vietnam. Our originality is our use of satellite-derived urban land use morphological maps. These maps which are based on building height provided by a coarse-resolution satellite-derived digital surface model (DSM) and urban built-up area classified from Landsat images allow spatial disaggregation of annual emissions.
Zhongjing Jiang, Jing Li, Xiao Lu, Cheng Gong, Lin Zhang, and Hong Liao
Atmos. Chem. Phys., 21, 2601–2613,Short summary
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 %.
Yilin Chen, Huizhong Shen, Jennifer Kaiser, Yongtao Hu, Shannon L. Capps, Shunliu Zhao, Amir Hakami, Jhih-Shyang Shih, Gertrude K. Pavur, Matthew D. Turner, Daven K. Henze, Jaroslav Resler, Athanasios Nenes, Sergey L. Napelenok, Jesse O. Bash, Kathleen M. Fahey, Gregory R. Carmichael, Tianfeng Chai, Lieven Clarisse, Pierre-François Coheur, Martin Van Damme, and Armistead G. Russell
Atmos. Chem. Phys., 21, 2067–2082,Short summary
Ammonia (NH3) emissions can exert adverse impacts on air quality and ecosystem well-being. NH3 emission inventories are viewed as highly uncertain. Here we optimize the NH3 emission estimates in the US using an air quality model and NH3 measurements from the IASI satellite instruments. The optimized NH3 emissions are much higher than the National Emissions Inventory estimates in April. The optimized NH3 emissions improved model performance when evaluated against independent observation.
Bo Zhang, Hongyu Liu, James H. Crawford, Gao Chen, T. Duncan Fairlie, Scott Chambers, Chang-Hee Kang, Alastair G. Williams, Kai Zhang, David B. Considine, Melissa P. Sulprizio, and Robert M. Yantosca
Atmos. Chem. Phys., 21, 1861–1887,Short summary
We simulate atmospheric 222Rn using the GEOS-Chem model to improve understanding of 222Rn emissions and characterize convective transport in the model. We demonstrate the potential of a customized global 222Rn emission scenario to improve simulated surface 222Rn concentrations and seasonality. We assess convective transport using observed 222Rn vertical profiles. Results have important implications for using chemical transport models to interpret the transport of trace gases and aerosols.
Fei Jiang, Hengmao Wang, Jing M. Chen, Weimin Ju, Xiangjun Tian, Shuzhuang Feng, Guicai Li, Zhuoqi Chen, Shupeng Zhang, Xuehe Lu, Jane Liu, Haikun Wang, Jun Wang, Wei He, and Mousong Wu
Atmos. Chem. Phys., 21, 1963–1985,Short summary
We present a 6-year inversion from 2010 to 2015 for the global and regional carbon fluxes using only the GOSAT XCO2 retrievals. We find that the XCO2 retrievals could significantly improve the modeling of atmospheric CO2 concentrations and that the inferred interannual variations in the terrestrial carbon fluxes in most land regions have a better relationship with the changes in severe drought area or leaf area index, or are more consistent with the previous estimates about drought impact.
Guilherme F. Camarinha-Neto, Julia C. P. Cohen, Cléo Q. Dias-Júnior, Matthias Sörgel, José Henrique Cattanio, Alessandro Araújo, Stefan Wolff, Paulo A. F. Kuhn, Rodrigo A. F. Souza, Luciana V. Rizzo, and Paulo Artaxo
Atmos. Chem. Phys., 21, 339–356,Short summary
It was observed that friagem phenomena (incursion of cold waves from the high latitudes of the Southern Hemisphere to the Amazon region), very common in the dry season of the Amazon region, produced significant changes in microclimate and atmospheric chemistry. Moreover, the effects of the friagem change the surface O3 and CO2 mixing ratios and therefore interfere deeply in the microclimatic conditions and the chemical composition of the atmosphere above the rainforest.
Xinrui Ge, Martijn Schaap, Richard Kranenburg, Arjo Segers, Gert Jan Reinds, Hans Kros, and Wim de Vries
Atmos. Chem. Phys., 20, 16055–16087,Short summary
This article is about improving the modeling of agricultural ammonia emissions. By considering land use, meteorology and agricultural practices, ammonia emission totals officially reported by countries are distributed in space and time. We illustrated the first step for a better understanding of the variability of ammonia emission, with the possibility of being applied at a European scale, which is of great significance for ammonia budget research and future policy-making.
Ashok K. Luhar, David M. Etheridge, Zoë M. Loh, Julie Noonan, Darren Spencer, Lisa Smith, and Cindy Ong
Atmos. Chem. Phys., 20, 15487–15511,Short summary
With the sharp rise in coal seam gas (CSG) production in Queensland’s Surat Basin, there is much interest in quantifying methane emissions from this area and from unconventional gas production in general. We develop and apply a regional Bayesian inverse model that uses hourly methane concentration data from two sites and modelled backward dispersion to quantify emissions. The model requires a narrow prior and suggests that the emissions from the CSG areas are 33% larger than bottom-up estimates.
Wayne M. Angevine, Jeff Peischl, Alice Crawford, Christopher P. Loughner, Ilana B. Pollack, and Chelsea R. Thompson
Atmos. Chem. Phys., 20, 11855–11868,Short summary
Emissions of air pollutants must be known for a wide variety of applications. Different methods of estimating emissions often disagree substantially. In this study, we apply standard methods to a well-known source, a power plant. We explore the uncertainty implied by the different answers that come from the different methods, different samples taken over several years, and different pollutants. We find that the overall uncertainty of emissions estimates is about 30 %.
Peter Huszar, Jan Karlický, Jana Ďoubalová, Tereza Nováková, Kateřina Šindelářová, Filip Švábik, Michal Belda, Tomáš Halenka, and Michal Žák
Atmos. Chem. Phys., 20, 11655–11681,Short summary
The paper shows how extreme meteorological conditions change due to the urban land-cover forcing and how this translates to the impact on the extreme air pollution over central European cities. It focuses on ozone, nitrogen dioxide, and particulate matter with a diameter of less than 2.5 μm and shows that, while for the extreme daily maximum 8 h ozone, changes are same as for the mean ones, much larger modifications are calculated for extreme NO2 and PM2.5 compared to their mean changes.
Lang Wang, Amos P. K. Tai, Chi-Yung Tam, Mehliyar Sadiq, Peng Wang, and Kevin K. W. Cheung
Atmos. Chem. Phys., 20, 11349–11369,Short summary
We investigate the effects of future land use and land cover change (LULCC) on surface ozone air quality worldwide and find that LULCC can significantly influence ozone in North America and Europe via modifying surface energy balance, boundary-layer meteorology, and regional circulation. The strength of such “biogeophysical effects” of LULCC is strongly dependent on forest type and generally greater than the “biogeochemical effects” via changing deposition and emission fluxes alone.
Jinhui Gao, Ying Li, Bin Zhu, Bo Hu, Lili Wang, and Fangwen Bao
Atmos. Chem. Phys., 20, 10831–10844,Short summary
Light extinction of aerosols can decease surface ozone mainly via reducing photochemical production of ozone. However, it also leads to high levels of ozone aloft being entrained down to the surface which partly counteracts the reduction in surface ozone. The impact of aerosols is more sensitive to local ozone, which suggests that while controlling the levels of aerosols, controlling the local ozone precursors is an effective way to suppress the increase of ozone over China at present.
Junhua Liu, Jose M. Rodriguez, Luke D. Oman, Anne R. Douglass, Mark A. Olsen, and Lu Hu
Atmos. Chem. Phys., 20, 6417–6433,Short summary
Our paper quantifies and identifies the importance of stratospheric ozone influence on the tropospheric ozone IAV in Northern Hemisphere mid-high latitudes. Our analysis provides an in-depth understanding of how 3-D dynamics influences the O3 redistribution in the troposphere. These findings are particularly important considering the potential changes in these dynamical conditions in the future as a result of climate change
Jun Park and Hyun Mee Kim
Atmos. Chem. Phys., 20, 5175–5195,Short summary
Observation network experiments were conducted to optimize the surface CO2 flux in Asia. The impacts of the redistribution of and additions to the existing observation network were evaluated. The addition experiments revealed that considering both the normalized self-sensitivity and ecoregion information can yield better simulated surface CO2 fluxes compared to random addition. This study provides useful information for future observation network design to estimate the surface CO2 flux.
Meng Gao, Jinhui Gao, Bin Zhu, Rajesh Kumar, Xiao Lu, Shaojie Song, Yuzhong Zhang, Beixi Jia, Peng Wang, Gufran Beig, Jianlin Hu, Qi Ying, Hongliang Zhang, Peter Sherman, and Michael B. McElroy
Atmos. Chem. Phys., 20, 4399–4414,Short summary
A regional fully coupled meteorology–chemistry model, Weather Research and Forecasting model with Chemistry (WRF-Chem), was employed to study the seasonality of ozone (O3) pollution and its sources in both China and India.
Ryan J. Pound, Tomás Sherwen, Detlev Helmig, Lucy J. Carpenter, and Mat J. Evans
Atmos. Chem. Phys., 20, 4227–4239,Short summary
Ozone is an important pollutant with impacts on health and the environment. Ozone is lost to plants, land and the oceans. Loss to the ocean is slow compared to all other types of land cover and has not received as much attention. We build on previous work to more accurately model ozone loss to the ocean. We find changes in the concentration of ozone over the oceans, notably the Southern Ocean, which improves model performance.
Marios Panagi, Zoë L. Fleming, Paul S. Monks, Matthew J. Ashfold, Oliver Wild, Michael Hollaway, Qiang Zhang, Freya A. Squires, and Joshua D. Vande Hey
Atmos. Chem. Phys., 20, 2825–2838,Short summary
In this paper, using dispersion modelling with emission inventories it was determined that on average 45 % of the total CO pollution that affects Beijing is transported from other areas. About half of the CO comes from beyond the immediate surrounding areas. Finally three classification types of pollution were identified and used to analyse the APHH winter campaign. The results can inform targeted control measures to be implemented in Beijing and the other regions to tackle air quality problems.
Zhining Tao, Mian Chin, Meng Gao, Tom Kucsera, Dongchul Kim, Huisheng Bian, Jun-ichi Kurokawa, Yuesi Wang, Zirui Liu, Gregory R. Carmichael, Zifa Wang, and Hajime Akimoto
Atmos. Chem. Phys., 20, 2319–2339,Short summary
One goal of the Model Inter-Comparison Study for Asia (MICS-Asia) Phase III is to identify strengths and weaknesses of current air quality models to provide insights into reducing uncertainties. This study identified that a 15 km grid would be the optimal horizontal resolution in terms of performance and resource usage to capture average and extreme air quality over East Asia and is thus suggested for use in future MICS-Asia modeling activities if the investigation domain remains the same.
Peter Huszar, Jan Karlický, Jana Ďoubalová, Kateřina Šindelářová, Tereza Nováková, Michal Belda, Tomáš Halenka, Michal Žák, and Petr Pišoft
Atmos. Chem. Phys., 20, 1977–2016,Short summary
Urban surfaces alter meteorological conditions which consequently alter air pollution due to modified transport and chemical reactions. Here, we focus on a major component of this influence, enhanced vertical eddy diffusion. Using a regional climate model coupled to a chemistry transport model, we investigate how different representations of turbulent transport translate to urban canopy impact on ozone and PM2.5 concentrations and whether turbulence remains the most important component.
Ingrid Super, Stijn N. C. Dellaert, Antoon J. H. Visschedijk, and Hugo A. C. Denier van der Gon
Atmos. Chem. Phys., 20, 1795–1816,Short summary
Emission data contain uncertainties introduced by the methodology and the data used. We quantified uncertainties in gridded emissions using the uncertainty in underlying data, showing that disaggregation in space and time significantly increases the uncertainty. Understanding uncertainties helps to interpret atmospheric measurements and the gap with modelled concentrations. Moreover, our analyses help identify regions with large uncertainties, which require further scrutiny.
Catherine C. Ivanovich, Ilissa B. Ocko, Pedro Piris-Cabezas, and Annie Petsonk
Atmos. Chem. Phys., 19, 14949–14965,Short summary
The Paris Agreement set the goal of remaining well below a 2 °C global temperature rise, but it is unclear how future emissions from international shipping and aviation will contribute to this threshold. Here we estimate that the sectors' future emissions of carbon dioxide will contribute a combined 0.12 °C by the end of the century should no action be taken, but proposed mitigation policies have the potential to reduce this warming by almost 90 %.
Arellano, A. F. and Hess, P. G.: Sensitivity of top-down estimates of CO sources to GCTM transport, Geophys. Res. Lett., 33, 493–495, https://doi.org/10.1029/2006gl027371, 2006.
Barret, B., Sauvage, B., Bennouna, Y., and Le Flochmoen, E.: Upper-tropospheric CO and O3 budget during the Asian summer monsoon, Atmos. Chem. Phys., 16, 9129–9147, https://doi.org/10.5194/acp-16-9129-2016, 2016.
Boria, R. A., Olson, L. E., Goodman, S. M., and Anderson, R. P.: Spatial filtering to reduce sampling bias can improve the performance of ecological niche models, Ecol. Model., 275, 73–77, https://doi.org/10.1016/j.ecolmodel.2013.12.012, 2014.
Borsdorff, T., Aan de Brugh, J., Hu, H., Aben, I., Hasekamp, O., and Landgraf, J.: Measuring Carbon Monoxide with TROPOMI: First Results and a Comparison With ECMWF-IFS Analysis Data, Geophys. Res. Lett., 45, 2826–2832, https://doi.org/10.1002/2018gl077045, 2018.
Buchholz, R. R., Deeter, M. N., Worden, H. M., Gille, J., Edwards, D. P., Hannigan, J. W., Jones, N. B., Paton-Walsh, C., Griffith, D. W. T., Smale, D., Robinson, J., Strong, K., Conway, S., Sussmann, R., Hase, F., Blumenstock, T., Mahieu, E., and Langerock, B.: Validation of MOPITT carbon monoxide using ground-based Fourier transform infrared spectrometer data from NDACC, Atmos. Meas. Tech., 10, 1927–1956, https://doi.org/10.5194/amt-10-1927-2017, 2017.
Cai, G. and Zhang, L.: The Present Situation and Development of Energy Utilization in Tibet (in Chinese with English abstract), Energy. China., 28, 38–42, 2006.
Chen, P., Kang, S., Bai, J., Sillanpää, M., and Li, C.: Yak dung combustion aerosols in the Tibetan Plateau: Chemical characteristics and influence on the local atmospheric environment, Atmos. Res., 156, 58–66, https://doi.org/10.1016/j.atmosres.2015.01.001, 2015.
China's sixth census: available at: http://www.stats.gov.cn/tjsj/pcsj/rkpc/6rp/indexch.htm (last access: 19 July 2017), 2010.
China Statistical Yearbook: available at: http://www.stats.gov.cn/tjsj/ndsj/, last access: 1 June 2018.
Classes and Methods for Spatial Data in R: the sp Package: available at: https://cran.r-project.org/doc/Rnews/ (last access: 17 May 2017), 2005.
Clerbaux, C., Boynard, A., Clarisse, L., George, M., Hadji-Lazaro, J., Herbin, H., Hurtmans, D., Pommier, M., Razavi, A., Turquety, S., Wespes, C., and Coheur, P.-F.: Monitoring of atmospheric composition using the thermal infrared IASI/MetOp sounder, Atmos. Chem. Phys., 9, 6041–6054, https://doi.org/10.5194/acp-9-6041-2009, 2009.
Cleveland, R. B.: STL: A Seasonal-Trend Decomposition Procedure Based on Loess, J. Off. Stat., 6, 3–33, 1990.
CNEMC: Technical Specifications for Installation and Acceptance of Ambient air Quality Continuous Automated Monitoring System for SO2, NO2, O3 and CO, Ministry of Ecology and Environment of the People's Republic of China, 2013.
CREAS and CNEMC: Ambient Air Quality Standard (in Chinese), Ministry of Ecology and Environment of the People's Republic of China, 2012.
De'Ath, G. and Fabricius, K. E.: Classification and Regression Trees: A Powerful Yet Simple Technique for Ecological Data Analysis, Ecology, 81, 3178–3192, 2000.
Deeter, M. N.: A new satellite retrieval method for precipitable water vapor over land and ocean, Geophys. Res. Lett., 34, L02815, https://doi.org/10.1029/2006gl028019, 2007.
Deeter, M. N.: Measurements of Pollution in the Troposphere (MOPITT) Version 7 Product User's Guide, available at: https://www2.acom.ucar.edu/sites/default/files/mopitt/v7_users_guide_201707.pdf, 2017.
Deeter, M. N., Emmons, L. K., Francis, G. L., Edwards, D. P., Gille, J. C., Warner, J. X., Khattatov, B., Ziskin, D., Lamarque, J. F., Ho, S. P., Yudin, V., Attié, J. L., Packman, D., Chen, J., Mao, D., and Drummond, J. R.: Operational carbon monoxide retrieval algorithm and selected results for the MOPITT instrument, J. Geophys. Res.-Atmos., 108, 4399, https://doi.org/10.1029/2002jd003186, 2003.
Deeter, M. N., Martínez-Alonso, S., Edwards, D. P., Emmons, L. K., Gille, J. C., Worden, H. M., Sweeney, C., Pittman, J. V., Daube, B. C., and Wofsy, S. C.: The MOPITT Version 6 product: algorithm enhancements and validation, Atmos. Meas. Tech., 7, 3623–3632, https://doi.org/10.5194/amt-7-3623-2014, 2014.
Deeter, M. N., Edwards, D. P., Francis, G. L., Gille, J. C., Martínez-Alonso, S., Worden, H. M., and Sweeney, C.: A climate-scale satellite record for carbon monoxide: the MOPITT Version 7 product, Atmos. Meas. Tech., 10, 2533–2555, https://doi.org/10.5194/amt-10-2533-2017, 2017.
Dekker, I. N., Houweling, S., Aben, I., Röckmann, T., Krol, M., Martínez-Alonso, S., Deeter, M. N., and Worden, H. M.: Quantification of CO emissions from the city of Madrid using MOPITT satellite retrievals and WRF simulations, Atmos. Chem. Phys., 17, 14675–14694, https://doi.org/10.5194/acp-17-14675-2017, 2017.
Drummond, J. R., Zou, J., Nichitiu, F., Kar, J., Deschambaut, R., and Hackett, J.: A review of 9-year performance and operation of the MOPITT instrument, Adv. Space Res., 45, 760–774, https://doi.org/10.1016/j.asr.2009.11.019, 2010.
Duncan, B. N., Logan, J. A., Bey, I., Megretskaia, I. A., Yantosca, R. M., Novelli, P. C., Jones, N. B., and Rinsland, C. P.: Global budget of CO, 1988-1997: Source estimates and validation with a global model, J. Geophys. Res.-Atmos, 112, https://doi.org/10.1029/2007jd008459, 2007a.
Duncan, B. N., Strahan, S. E., Yoshida, Y., Steenrod, S. D., and Livesey, N.: Model study of the cross-tropopause transport of biomass burning pollution, Atmos. Chem. Phys., 7, 3713–3736, https://doi.org/10.5194/acp-7-3713-2007, 2007b.
Edwards, D. P., Emmons, L. K., Hauglustaine, D. A., Chu, D. A., Gille, J. C., Kaufman, Y. J., Pétron, G., Yurganov, L. N., Giglio, L., Deeter, M. N., Yudin, V., Ziskin, D. C., Warner, J., Lamarque, J. F., Francis, G. L., Ho, S. P., Mao, D., Chen, J., Grechko, E. I., and Drummond, J. R.: Observations of carbon monoxide and aerosols from the Terra satellite: Northern Hemisphere variability, J. Geophys. Res.-Atmos., 109, https://doi.org/10.1029/2004JD004727, 2004.
Fortems-Cheiney, A., Chevallier, F., Pison, I., Bousquet, P., Carouge, C., Clerbaux, C., Coheur, P.-F., George, M., Hurtmans, D., and Szopa, S.: On the capability of IASI measurements to inform about CO surface emissions, Atmos. Chem. Phys., 9, 8735–8743, https://doi.org/10.5194/acp-9-8735-2009, 2009.
Friedman, J. H.: Greedy Function Approximation: A Gradient Boosting Machine, Ann. Stat., 29, 1189–1232, 2001.
Goldan, P. D., Parrish, D. D., Kuster, W. C., Trainer, M., McKeen, S. A., Holloway, J., Jobson, B. T., Sueper, D. T., and Fehsenfeld, F. C.: Airborne measurements of isoprene, CO, and anthropogenic hydrocarbons and their implications, J. Geophys. Res.-Atmos., 105, 9091–9105, https://doi.org/10.1029/1999jd900429, 2000.
Goodfellow, I., Bengio, Y., and Courville, A.: Deep Learning, The MIT Press, Cambridge, MA 02142, 2016.
Gräler, B., Pebesma, E., and Heuvelink, G. B. M.: Spatio-Temporal Interpolation using gstat, R. Journal, 204–218, https://doi.org/10.1007/978-3-319-17885-1_1647, 2016.
Gulliver, J., de Hoogh, K., Hoek, G., Vienneau, D., Fecht, D., and Hansell, A.: Back-extrapolated and year-specific NO2 land use regression models for Great Britain – Do they yield different exposure assessment?, Environ. Int., 92, 202–209, https://doi.org/10.1016/j.envint.2016.03.037, 2016.
Guo, Y., Zeng, H., Zheng, R., Li, S., Barnett, A. G., Zhang, S., Zou, X., Huxley, R., Chen, W., and Williams, G.: The association between lung cancer incidence and ambient air pollution in China: A spatiotemporal analysis, Environ. Res., 144, 60–65, https://doi.org/10.1016/j.envres.2015.11.004, 2016.
Hastie, T., Tibshirani, R., and Friedman, J.: The Elements of Statistical Learning Data Mining, Inference, and Prediction, Second Edition, World Book Inc, Beijing, 192–192, 2009.
Hong Kong air quality monitoring data: http://epic.epd.gov.hk/EPICDI/air/station/, last access: 18 March 2017.
Holloway, T., Levy, H., and Kasibhatla, P.: Global distribution of carbon monoxide, J. Geophys. Res.-Atmos, 105, 12123–12147, https://doi.org/10.1029/1999jd901173, 2000.
Hooghiemstra, P. B., Krol, M. C., van Leeuwen, T. T., van der Werf, G. R., Novelli, P. C., Deeter, M. N., Aben, I., and Röckmann, T.: Interannual variability of carbon monoxide emission estimates over South America from 2006 to 2010, J. Geophys. Res.-Atmos., 117, D15308, https://doi.org/10.1029/2012jd017758, 2012.
Hu, J., Chen, J., Ying, Q., and Zhang, H.: One-year simulation of ozone and particulate matter in China using WRF/CMAQ modeling system, Atmos. Chem. Phys., 16, 10333–10350, https://doi.org/10.5194/acp-16-10333-2016, 2016.
Hu, J., Li, X., Huang, L., Ying, Q., Zhang, Q., Zhao, B., Wang, S., and Zhang, H.: Ensemble prediction of air quality using the WRF/CMAQ model system for health effect studies in China, Atmos. Chem. Phys., 17, 13103–13118, https://doi.org/10.5194/acp-17-13103-2017, 2017a.
Hu, X., Belle, J. H., Meng, X., Wildani, A., Waller, L. A., Strickland, M. J., and Liu, Y.: Estimating PM2.5 Concentrations in the Conterminous United States Using the Random Forest Approach, Environ. Sci. Technol., 51, 6936–6944, https://doi.org/10.1021/acs.est.7b01210, 2017b.
Jiang, Z., Jones, D. B. A., Worden, J., Worden, H. M., Henze, D. K., and Wang, Y. X.: Regional data assimilation of multi-spectral MOPITT observations of CO over North America, Atmos. Chem. Phys., 15, 6801–6814, https://doi.org/10.5194/acp-15-6801-2015, 2015.
Kazmier, L.: Schaum's Outline of Business Statistics (eBook), MCGRAW-HILL, New York, 2003.
Kopacz, M., Jacob, D. J., Fisher, J. A., Logan, J. A., Zhang, L., Megretskaia, I. A., Yantosca, R. M., Singh, K., Henze, D. K., Burrows, J. P., Buchwitz, M., Khlystova, I., McMillan, W. W., Gille, J. C., Edwards, D. P., Eldering, A., Thouret, V., and Nedelec, P.: Global estimates of CO sources with high resolution by adjoint inversion of multiple satellite datasets (MOPITT, AIRS, SCIAMACHY, TES), Atmos. Chem. Phys., 10, 855–876, https://doi.org/10.5194/acp-10-855-2010, 2010.
Krotkov, N. A., McLinden, C. A., Li, C., Lamsal, L. N., Celarier, E. A., Marchenko, S. V., Swartz, W. H., Bucsela, E. J., Joiner, J., Duncan, B. N., Boersma, K. F., Veefkind, J. P., Levelt, P. F., Fioletov, V. E., Dickerson, R. R., He, H., Lu, Z., and Streets, D. G.: Aura OMI observations of regional SO2 and NO2 pollution changes from 2005 to 2015, Atmos. Chem. Phys., 16, 4605–4629, https://doi.org/10.5194/acp-16-4605-2016, 2016.
Level-2 Product of MOPITT Version 7: available at: https://eosweb.larc.nasa.gov/project/mopitt/mop02j_v007 (last access: 18 March 2018), 2017.
Li, L. and Liu, Y.: Space-borne and ground observations of the characteristics of CO pollution in Beijing, 2000–2010, Atmos. Environ., 45, 2367–2372, https://doi.org/10.1016/j.atmosenv.2011.02.026, 2011.
Li, M., Zhang, Q., Kurokawa, J.-I., Woo, J.-H., He, K., Lu, Z., Ohara, T., Song, Y., Streets, D. G., Carmichael, G. R., Cheng, Y., Hong, C., Huo, H., Jiang, X., Kang, S., Liu, F., Su, H., and Zheng, B.: MIX: a mosaic Asian anthropogenic emission inventory under the international collaboration framework of the MICS-Asia and HTAP, Atmos. Chem. Phys., 17, 935–963, https://doi.org/10.5194/acp-17-935-2017, 2017.
Li, M. J., Chen, D. S., Cheng, S. Y., Wang, F., Li, Y., Zhou, Y., and Lang, J. L.: Optimizing emission inventory for chemical transport models by using genetic algorithm, Atmos. Environ., 44, 3926–3934, https://doi.org/10.1016/j.atmosenv.2010.07.010, 2010.
Ma, Z., Hu, X., Sayer, A. M., Levy, R., Zhang, Q., Xue, Y., Tong, S., Bi, J., Huang, L., and Liu, Y.: Satellite-Based Spatiotemporal Trends in PM2.5 Concentrations: China, 2004–2013, Environ. Health. Perspect., 124, 184–192, https://doi.org/10.1289/ehp.1409481, 2016.
McMillan, W. W.: Daily global maps of carbon monoxide from NASA's Atmospheric Infrared Sounder, Geophys. Res. Lett., 32, L11801, https://doi.org/10.1029/2004gl021821, 2005.
MEPC Air quality daily report for China: available at: http://datacenter.mep.gov.cn/, last access: 30 January 2017.
Pedregosa, F., Gramfort, A., Michel, V., Thirion, B., Grisel, O., Blondel, M., Prettenhofer, P., Weiss, R., Dubourg, V., and Vanderplas, J.: Scikit-learn: Machine Learning in Python, available at: https://scikit-learn.org/stable/modules/ensemble.html#random-forests (last access: 10 April 2019), J. Mach. Learn, Res., 12, 2825–2830, 2012.
Pebesma, E. J.: Multivariable geostatistics in S: the gstat package, available at: https://cran.r-project.org/web/packages/gstat/index.html (last access: 5 May 2019), Computers & Geosciences, 30, 683–691, 2004.
Pommier, M., Law, K. S., Clerbaux, C., Turquety, S., Hurtmans, D., Hadji-Lazaro, J., Coheur, P.-F., Schlager, H., Ancellet, G., Paris, J.-D., Nédélec, P., Diskin, G. S., Podolske, J. R., Holloway, J. S., and Bernath, P.: IASI carbon monoxide validation over the Arctic during POLARCAT spring and summer campaigns, Atmos. Chem. Phys., 10, 10655–10678, https://doi.org/10.5194/acp-10-10655-2010, 2010.
Pommier, M., McLinden, C. A., and Deeter, M.: Relative changes in CO emissions over megacities based on observations from space, Geophys. Res. Lett., 40, 3766–3771, https://doi.org/10.1002/grl.50704, 2013.
R: A Language and Environment for Statistical Computing: available at: https://www.R-project.org/, last access: 11 July 2018.
Reeves, C. E., Penkett, S. A., Bauguitte, S., Law, K. S., Evans, M. J., Bandy, B. J., Monks, P. S., Edwards, G. D., Phillips, G., Barjat, H., Kent, J., Dewey, K., Schmitgen, S., and Kley, D.: Potential for photochemical ozone formation in the troposphere over the North Atlantic as derived from aircraft observations during ACSOE, J. Geophys. Res.-Atmos., 107, ACH 14-11-ACH 14-14, https://doi.org/10.1029/2002jd002415, 2002.
Reid, C. E., Jerrett, M., Petersen, M. L., Pfister, G. G., Morefield, P. E., Tager, I. B., Raffuse, S. M., and Balmes, J. R.: Spatiotemporal prediction of fine particulate matter during the 2008 northern California wildfires using machine learning, Environ. Sci. Technol., 49, 3887–3896, https://doi.org/10.1021/es505846r, 2015.
Rgdal: Bindings for the “Geospatial” Data Abstraction Library: available at: https://CRAN.R-project.org/package=rgdal, last access: 19 July 2017.
Streets, D. G., Yarber, K. F., Woo, J. H., and Carmichael, G. R.: Biomass burning in Asia: Annual and seasonal estimates and atmospheric emissions, Global Biogeochem. Cy., 17, 1099, https://doi.org/10.1029/2003gb002040, 2003.
Streets, D. G., Canty, T., Carmichael, G. R., de Foy, B., Dickerson, R. R., Duncan, B. N., Edwards, D. P., Haynes, J. A., Henze, D. K., Houyoux, M. R., Jacob, D. J., Krotkov, N. A., Lamsal, L. N., Liu, Y., Lu, Z., Martin, R. V., Pfister, G. G., Pinder, R. W., Salawitch, R. J., and Wecht, K. J.: Emissions estimation from satellite retrievals: A review of current capability, Atmos. Environ., 77, 1011–1042, https://doi.org/10.1016/j.atmosenv.2013.05.051, 2013.
Strode, S. A., Worden, H. M., Damon, M., Douglass, A. R., Duncan, B. N., Emmons, L. K., Lamarque, J.-F., Manyin, M., Oman, L. D., Rodriguez, J. M., Strahan, S. E., and Tilmes, S.: Interpreting space-based trends in carbon monoxide with multiple models, Atmos. Chem. Phys., 16, 7285–7294, https://doi.org/10.5194/acp-16-7285-2016, 2016.
Taiwan air quality monitoring networks: available at: http://taqm.epa.gov.tw, last access: 20 February 2017.
Level-2 Product of MOPITT Version 7: available at: https://eosweb.larc.nasa.gov/project/mopitt/mop02j_v007 (last access: 18 March 2018), 2017.
Ul-Haq, Z., Tariq, S., and Ali, M.: Anthropogenic emissions and space-borne observations of carbon monoxide over South Asia, Adv. Space Res., 58, 1610–1626, https://doi.org/10.1016/j.asr.2016.06.033, 2016.
Wang, P., Elansky, N. F., Timofeev, Y. M., Wang, G., Golitsyn, G. S., Makarova, M. V., Rakitin, V. S., Shtabkin, Y., Skorokhod, A. I., Grechko, E. I., Fokeeva, E. V., Safronov, A. N., Ran, L., and Wang, T.: Long-Term Trends of Carbon Monoxide Total Columnar Amount in Urban Areas and Background Regions: Ground- and Satellite-based Spectroscopic Measurements, Adv. Atmos. Sci., 35, 785–795, https://doi.org/10.1007/s00376-017-6327-8, 2018.
Wang, T., Cheung, T. F., Li, Y. S., Yu, X. M., and Blake, D. R.: Emission characteristics of CO, NOx, SO2 and indications of biomass burning observed at a rural site in eastern China, J. Geophys. Res.-Atmos., 107, 4157, https://doi.org/10.1029/2001JD000724, 2002.
Wang, Y., Ying, Q., Hu, J., and Zhang, H.: Spatial and temporal variations of six criteria air pollutants in 31 provincial capital cities in China during 2013–2014, Environ. Int., 73, 413–422, https://doi.org/10.1016/j.envint.2014.08.016, 2014.
Wang, Y. X., Mcelroy, M. B., Wang, T., and Palmer, P. I.: Asian emissions of CO and NOx: Constraints from aircraft and Chinese station data, J. Geophys. Res.-Atmos., 109, D24304, https://doi.org/10.1029/2004jd005250, 2004.
Warner, J., Comer, M. M., Barnet, C. D., McMillan, W. W., Wolf, W., Maddy, E., and Sachse, G.: A comparison of satellite tropospheric carbon monoxide measurements from AIRS and MOPITT during INTEX-A, J. Geophys. Res.-Atmos., 112, D12S17, https://doi.org/10.1029/2006jd007925, 2007.
Wen, X. and Tu, Y.: Utilization and Prospect of Biomass Energy in Tibet, Tibet. Sc. Technol., 11, 26–28, 2011 (in Chinese).
White, J. C., Wagner, W., and Beale, C. N.: Global climate change linkages: acid rain, air quality and stratospheric ozone, Atmos. Environ. Part A, 24, 2898–2899, 1990.
Worden, H. M., Deeter, M. N., Edwards, D. P., Gille, J., Drummond, J., Emmons, L. K., Francis, G., and Martínez-Alonso, S.: 13 years of MOPITT operations: lessons from MOPITT retrieval algorithm development, Ann. Geophys., 56, 969–975, https://doi.org/10.4401/ag-6330, 2013a.
Worden, H. M., Deeter, M. N., Frankenberg, C., George, M., Nichitiu, F., Worden, J., Aben, I., Bowman, K. W., Clerbaux, C., Coheur, P. F., de Laat, A. T. J., Detweiler, R., Drummond, J. R., Edwards, D. P., Gille, J. C., Hurtmans, D., Luo, M., Martínez-Alonso, S., Massie, S., Pfister, G., and Warner, J. X.: Decadal record of satellite carbon monoxide observations, Atmos. Chem. Phys., 13, 837–850, https://doi.org/10.5194/acp-13-837-2013, 2013b.
Xia, Y., Zhao, Y., and Nielsen, C. P.: Benefits of China's efforts in gaseous pollutant control indicated by the bottom-up emissions and satellite observations 2000–2014, Atmos. Environ., 136, 43–53, https://doi.org/10.1016/j.atmosenv.2016.04.013, 2016.
Xu, L., Chen, F., Chen, F., Chen, W., Yu, H., Huang, X., Zeng, Y., Li, X., Hong, S., Feng, Y., and Zhong, X.: Spatial and temporal variation of near-ground CO concentration in the Eight Economic Regions in china in May and July, Acta. Sci. Circumst., 34, 1934–1941, https://doi.org/10.13671/j.hjkxxb.2014.0642, 2014 (in Chinese with English abstract).
Xu, W. Y., Zhao, C. S., Ran, L., Deng, Z. Z., Liu, P. F., Ma, N., Lin, W. L., Xu, X. B., Yan, P., He, X., Yu, J., Liang, W. D., and Chen, L. L.: Characteristics of pollutants and their correlation to meteorological conditions at a suburban site in the North China Plain, Atmos. Chem. Phys., 11, 4353–4369, https://doi.org/10.5194/acp-11-4353-2011, 2011.
Yang, T. and Zheng, Y.: Study on energy poverty of herdsmen in Naqu region, Tibet, China. Tibet., 127–133, 2015 (in Chinese).
Yeganeh, B., Motlagh, M. S. P., Rashidi, Y., and Kamalan, H.: Prediction of CO concentrations based on a hybrid Partial Least Square and Support Vector Machine model, Atmos. Environ., 55, 357–365, https://doi.org/10.1016/j.atmosenv.2012.02.092, 2012.
Young, M. T., Bechle, M. J., Sampson, P. D., Szpiro, A. A., Marshall, J. D., Sheppard, L., and Kaufman, J. D.: Satellite-Based NO2 and Model Validation in a National Prediction Model Based on Universal Kriging and Land-Use Regression, Environ. Sci. Technol., 50, 3686–3694, https://doi.org/10.1021/acs.est.5b05099, 2016.
Zhan, Y., Luo, Y., Deng, X., Chen, H., Grieneisen, M. L., Shen, X., Zhu, L., and Zhang, M.: Spatiotemporal prediction of continuous daily PM2.5 concentrations across China using a spatially explicit machine learning algorithm, Atmos. Environ., 155, 129–139, https://doi.org/10.1016/j.atmosenv.2017.02.023, 2017.
Zhan, Y., Luo, Y., Deng, X., Zhang, K., Zhang, M., Grieneisen, M. L., and Di, B.: Satellite-Based Estimates of Daily NO2 Exposure in China Using Hybrid Random Forest and Spatiotemporal Kriging Model, Environ. Sci. Technol., 52, 4180–4189, https://doi.org/10.1021/acs.est.7b05669, 2018.
Zhao, C., Tie, X., Wang, G., Qin, Y., and Wang, P.: Analysis of Air Quality in Eastern China and its Interaction with Other Regions of the World, J. Atmos. Chem., 55, 189–204, https://doi.org/10.1007/s10874-006-9022-1, 2006.
Zheng, B., Chevallier, F., Ciais, P., Yin, Y., Deeter, M. N., Worden, H. M., Wang, Y., Zhang, Q., and He, K.: Rapid decline in carbon monoxide emissions and export from East Asia between years 2005 and 2016, Environ. Res. Lett., 13, 044007, https://doi.org/10.1088/1748-9326/aab2b3, 2018.
The spatiotemporal distributions of daily ground-level CO concentrations across China during 2013–2016 are derived by fusing the data from remote sensing and ground monitoring. The population–weighted CO was predicted to be 0.99 ± 0.30 mg m−3 and showed a decreasing trend of −0.021 ± 0.004 mg m−3 per year. The CO pollution was the most severe in the North China Plain. The hotspots in the Tibetan Plateau overlooked by the remote sensing were depicted by the data-fusion approach.
The spatiotemporal distributions of daily ground-level CO concentrations across China during...