{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,12]],"date-time":"2026-10-12T16:50:56Z","timestamp":1791823856913,"version":"4.3.4"},"reference-count":104,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2022,8,1]],"date-time":"2022-08-01T00:00:00Z","timestamp":1659312000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2022,8,1]],"date-time":"2022-08-01T00:00:00Z","timestamp":1659312000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2022,4,28]],"date-time":"2022-04-28T00:00:00Z","timestamp":1651104000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001661","name":"Universit\u00e4t Heidelberg","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100001661","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Science of The Total Environment"],"published-print":{"date-parts":[[2022,8]]},"DOI":"10.1016\/j.scitotenv.2022.155512","type":"journal-article","created":{"date-parts":[[2022,4,27]],"date-time":"2022-04-27T11:10:11Z","timestamp":1651057811000},"page":"155512","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":25,"special_numbering":"C","title":["Greenwashing in the US metal industry? A novel approach combining SO2 concentrations from satellite data, a plant-level firm database and web text mining"],"prefix":"10.1016","volume":"835","author":[{"given":"Sebastian","family":"Schmidt","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jan","family":"Kinne","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sven","family":"Lautenbach","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Thomas","family":"Blaschke","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"David","family":"Lenz","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bernd","family":"Resch","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.scitotenv.2022.155512_bb0005","author":"AISI"},{"issue":"5","key":"10.1016\/j.scitotenv.2022.155512_bb0010","doi-asserted-by":"crossref","first-page":"385","DOI":"10.1038\/nmeth.3854","article-title":"Regression diagnostics","volume":"13","author":"Altman","year":"2016","journal-title":"Nat. Methods"},{"key":"10.1016\/j.scitotenv.2022.155512_bb0015","series-title":"A Companion to Theoretical Econometrics","first-page":"310","article-title":"Spatial econometrics","author":"Anselin","year":"2001"},{"key":"10.1016\/j.scitotenv.2022.155512_bb0020","series-title":"The 2006 IEEE International Joint Conference on Neural Network Proceedings","first-page":"5355","article-title":"Variance stabilizing regression ensembles for environmental models","author":"Bagnall","year":"2006"},{"issue":"11","key":"10.1016\/j.scitotenv.2022.155512_bb0025","doi-asserted-by":"crossref","DOI":"10.1029\/2020GL087978","article-title":"Impact of coronavirus outbreak on NO2 pollution assessed using TROPOMI and OMI observations","volume":"47","author":"Bauwens","year":"2020","journal-title":"Geophys. Res. Lett."},{"key":"10.1016\/j.scitotenv.2022.155512_bb0030","series-title":"Conference: CARMA 2016 - 1st International Conference on Advanced Research Methods and Analytics","article-title":"Validation of a web mining technique to measure innovation in the Canadian nanotechnology-related community","author":"Beaudry","year":"2016"},{"key":"10.1016\/j.scitotenv.2022.155512_bb0035","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.atmosenv.2016.11.066","article-title":"Exposure assessment models for elemental components of particulate matter in an urban environment: a comparison of regression and random forest approaches","volume":"151","author":"Brokamp","year":"2017","journal-title":"Atmos. Environ."},{"key":"10.1016\/j.scitotenv.2022.155512_bb0040","author":"Brundtland"},{"issue":"7","key":"10.1016\/j.scitotenv.2022.155512_bb0045","doi-asserted-by":"crossref","first-page":"2231","DOI":"10.3390\/su10072231","article-title":"Corporate social responsibility (CSR): a survey of topics and trends using Twitter data and topic modeling","volume":"10","author":"Chae","year":"2018","journal-title":"Sustainability"},{"key":"10.1016\/j.scitotenv.2022.155512_bb0050","first-page":"1","article-title":"External environmental pollution as a risk factor for asthma","author":"Chatkin","year":"2021","journal-title":"Clin. Rev. Allergy Immunol."},{"key":"10.1016\/j.scitotenv.2022.155512_bb0055","doi-asserted-by":"crossref","first-page":"67","DOI":"10.1016\/j.resconrec.2016.04.014","article-title":"Analysis of copper flows in the United States: 1975\u20132012","volume":"111","author":"Chen","year":"2016","journal-title":"Resour. Conserv. Recycl."},{"key":"10.1016\/j.scitotenv.2022.155512_bb0060","series-title":"Environment for Development. Discussion Paper Series","first-page":"1","article-title":"When the wind blows: spatial spillover effects of urban air pollution","author":"Chen","year":"2015"},{"issue":"Part 2","key":"10.1016\/j.scitotenv.2022.155512_bb0065","doi-asserted-by":"crossref","first-page":"915","DOI":"10.1016\/j.jclepro.2016.02.119","article-title":"Impacts of air pollution and its spatial spillover effect on public health based on China\u2019s big data sample","volume":"142","author":"Chen","year":"2017","journal-title":"J. Clean. Prod."},{"key":"10.1016\/j.scitotenv.2022.155512_bb0070","doi-asserted-by":"crossref","first-page":"61","DOI":"10.1016\/j.ecolind.2017.06.043","article-title":"Identifying the spatial effects and driving factors of urban PM2.5 pollution in China","volume":"82","author":"Cheng","year":"2017","journal-title":"Ecol. Indic."},{"issue":"1","key":"10.1016\/j.scitotenv.2022.155512_bb0075","first-page":"11","article-title":"Assessment of air pollutants produced by industrial activity from an aluminium alloys foundry","volume":"55","author":"Cirtina","year":"2016","journal-title":"Metalurgija"},{"issue":"7","key":"10.1016\/j.scitotenv.2022.155512_bb0080","doi-asserted-by":"crossref","first-page":"1991","DOI":"10.5194\/gmd-8-1991-2015","article-title":"System for automated geoscientific analyses (SAGA) v. 2.1. 4","volume":"8","author":"Conrad","year":"2015","journal-title":"Geosci. Model Dev."},{"key":"10.1016\/j.scitotenv.2022.155512_bb0085","series-title":"American Thoracic Society Documents","first-page":"1207","article-title":"Air pollution monitoring for health research and patient care. An official American Thoracic Society workshop report","volume":"16(10)","author":"Cromar","year":"2019"},{"issue":"3","key":"10.1016\/j.scitotenv.2022.155512_bb0090","doi-asserted-by":"crossref","first-page":"273","DOI":"10.1037\/met0000079","article-title":"Comparing the Pearson and Spearman correlation coefficients across distributions and sample sizes: a tutorial using simulations and empirical data","volume":"21","author":"de Winter","year":"2016","journal-title":"Psychol. Methods"},{"issue":"1","key":"10.1016\/j.scitotenv.2022.155512_bb0095","doi-asserted-by":"crossref","first-page":"64","DOI":"10.1525\/cmr.2011.54.1.64","article-title":"The drivers of greenwashing","volume":"54","author":"Delmas","year":"2011","journal-title":"Calif. Manag. Rev."},{"issue":"1","key":"10.1016\/j.scitotenv.2022.155512_bb0100","doi-asserted-by":"crossref","first-page":"27","DOI":"10.1111\/j.1600-0587.2012.07348.x","article-title":"Collinearity: a review of methods to deal with it and a simulation study evaluating their performance","volume":"36","author":"Dormann","year":"2013","journal-title":"Ecography"},{"key":"10.1016\/j.scitotenv.2022.155512_bb0105","series-title":"ZEW Discussion Paper No. 21-062","article-title":"An integrated data framework for policy guidance in times of dynamic economic shocks","author":"D\u00f6rr","year":"2021"},{"key":"10.1016\/j.scitotenv.2022.155512_bb0110","author":"ESA"},{"key":"10.1016\/j.scitotenv.2022.155512_bb0115","author":"Fenton"},{"key":"10.1016\/j.scitotenv.2022.155512_bb0120","author":"Financial Times"},{"issue":"20","key":"10.1016\/j.scitotenv.2022.155512_bb0125","doi-asserted-by":"crossref","first-page":"12597","DOI":"10.5194\/acp-17-12597-2017","article-title":"Multi-source SO2 emission retrievals and consistency of satellite and surface measurements with reported emissions","volume":"17","author":"Fioletov","year":"2017","journal-title":"Atmos. Chem. Phys."},{"issue":"4","key":"10.1016\/j.scitotenv.2022.155512_bb0130","doi-asserted-by":"crossref","first-page":"703","DOI":"10.1016\/S1352-2310(00)00316-2","article-title":"Sub-region (district) and sector level SO2 and NOx emissions for India: assessment of inventories and mitigation flexibility","volume":"35","author":"Garg","year":"2001","journal-title":"Atmos. Environ."},{"key":"10.1016\/j.scitotenv.2022.155512_bb0135","doi-asserted-by":"crossref","first-page":"653","DOI":"10.1007\/s11192-014-1434-0","article-title":"Use of web mining in studying innovation","volume":"102","author":"G\u00f6k","year":"2015","journal-title":"Scientometrics"},{"key":"10.1016\/j.scitotenv.2022.155512_bb0140","doi-asserted-by":"crossref","first-page":"175","DOI":"10.1007\/s40980-015-0016-y","article-title":"How to interpret the coefficients of spatial models: spillovers, direct and indirect effects","volume":"4","author":"Golgher","year":"2016","journal-title":"Spatial Demography"},{"key":"10.1016\/j.scitotenv.2022.155512_bb0145","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1016\/j.rse.2017.06.031","article-title":"Google earth engine: planetary-scale geospatial analysis for everyone","volume":"202","author":"Gorelick","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"10.1016\/j.scitotenv.2022.155512_bb0150","doi-asserted-by":"crossref","first-page":"22001","DOI":"10.1007\/s11356-016-7447-x","article-title":"An evaluation of hospital admission respiratory disease attributed to sulfur dioxide ambient concentration in Ahvaz from 2011 through 2013","volume":"23","author":"Goudarzi","year":"2016","journal-title":"Environ. Sci. Pollut. Res."},{"issue":"3","key":"10.1016\/j.scitotenv.2022.155512_bb0155","doi-asserted-by":"crossref","first-page":"339","DOI":"10.1111\/jors.12188","article-title":"The SLX model","volume":"55","author":"Halleck Vega","year":"2015","journal-title":"J. Reg. Sci."},{"key":"10.1016\/j.scitotenv.2022.155512_bb0160","doi-asserted-by":"crossref","first-page":"102329","DOI":"10.1016\/j.scs.2020.102329","article-title":"Spatial distribution characteristics of PM2.5 and PM10 in Xi\u2019an City predicted by land use regression models","volume":"61","author":"Han","year":"2020","journal-title":"Sustain. Cities Soc."},{"key":"10.1016\/j.scitotenv.2022.155512_bb0165","author":"Hasanbeigi"},{"key":"10.1016\/j.scitotenv.2022.155512_bb0170","doi-asserted-by":"crossref","DOI":"10.1016\/j.scitotenv.2020.141978","article-title":"Impact of COVID-19 lockdown on NO2, O3, PM2.5 and PM10 concentrations and assessing air quality changes in Baghdad, Iraq","volume":"754","author":"Hashim","year":"2021","journal-title":"Sci. Total Environ."},{"issue":"4","key":"10.1016\/j.scitotenv.2022.155512_bb0175","doi-asserted-by":"crossref","first-page":"94","DOI":"10.1002\/2015EF000330","article-title":"Response of SO2 and particulate air pollution to local and regional emission controls: a case study in Maryland","volume":"4","author":"He","year":"2016","journal-title":"Earth\u2019s Future"},{"issue":"10","key":"10.1016\/j.scitotenv.2022.155512_bb0180","doi-asserted-by":"crossref","first-page":"5503","DOI":"10.5194\/amt-12-5503-2019","article-title":"Sulfur dioxide layer height retrieval from Sentinel-5 Precursor\/TROPOMI using FP_ILM","volume":"12","author":"Hedelt","year":"2019","journal-title":"Atmos. Meas. Tech."},{"key":"10.1016\/j.scitotenv.2022.155512_bb0185","first-page":"4","article-title":"The changing face of lower tropospheric sulfur oxides in the United States","author":"Hidy","year":"2016","journal-title":"Elementa (Wash. D.C.)"},{"key":"10.1016\/j.scitotenv.2022.155512_bb0190","doi-asserted-by":"crossref","first-page":"1132","DOI":"10.1016\/j.chemosphere.2015.09.080","article-title":"State of remediation and metal toxicity in the Tri-State Mining District, USA","volume":"144","author":"Johnson","year":"2016","journal-title":"Chemosphere"},{"key":"10.1016\/j.scitotenv.2022.155512_bb0195","series-title":"geopandas\/geopandas: v0.8.1","author":"Jordahl","year":"2020"},{"issue":"3","key":"10.1016\/j.scitotenv.2022.155512_bb0200","doi-asserted-by":"crossref","first-page":"130","DOI":"10.26833\/ijeg.644089","article-title":"Space-borne air pollution observation from Sentinel-5p TROPOMI: Relationship between pollutants, geographical and demographic data","volume":"5","author":"Kaplan","year":"2020","journal-title":"Int. J. Eng. Geosci."},{"issue":"1","key":"10.1016\/j.scitotenv.2022.155512_bb0205","first-page":"1","article-title":"Spaceborne nitrogen dioxide observations from the Sentinel-5P TROPOMI over Turkey","volume":"18","author":"Kaplan","year":"2019","journal-title":"Proceedings"},{"key":"10.1016\/j.scitotenv.2022.155512_bb0210","doi-asserted-by":"crossref","first-page":"1400","DOI":"10.4209\/aaqr.2018.12.0450","article-title":"Evaluation of different machine learning approaches in forecasting PM2.5 mass concentrations","volume":"19","author":"Karimian","year":"2019","journal-title":"Aerosol Air Qual. Res."},{"key":"10.1016\/j.scitotenv.2022.155512_bb0215","doi-asserted-by":"crossref","first-page":"2011","DOI":"10.1007\/s11192-020-03726-9","article-title":"Web mining for innovation ecosystem mapping: a framework and a large-scale pilot study","volume":"125","author":"Kinne","year":"2020","journal-title":"Scientometrics"},{"key":"10.1016\/j.scitotenv.2022.155512_bb0220","series-title":"ZEW Expert Brief 20-05","article-title":"Coronavirus pandemic affects companies differently. A high-frequency website analysis of companies\u2019 reactions to the coronavirus pandemic in Germany","author":"Kinne","year":"2020"},{"issue":"4","key":"10.1016\/j.scitotenv.2022.155512_bb0225","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pone.0249071","article-title":"Predicting innovative firms using web mining and deep learning","volume":"16","author":"Kinne","year":"2021","journal-title":"Plos One"},{"issue":"3","key":"10.1016\/j.scitotenv.2022.155512_bb0230","first-page":"351","article-title":"Atmospheric dispersion model to predict the impact of gaseous pollutant in an industrial and mining cluster","volume":"4","author":"Kumar","year":"2018","journal-title":"Glob. J. Environ. Sci. Manag."},{"issue":"D6","key":"10.1016\/j.scitotenv.2022.155512_bb0235","doi-asserted-by":"crossref","DOI":"10.1029\/2010JD014758","article-title":"SO2 emissions and lifetimes: estimates from inverse modeling using in situ and global, space-based (SCIAMACHY and OMI) observations","volume":"116","author":"Lee","year":"2011","journal-title":"J. Geophys. Res. Atmos."},{"issue":"2","key":"10.1016\/j.scitotenv.2022.155512_bb0240","doi-asserted-by":"crossref","first-page":"209","DOI":"10.1002\/bse.1910","article-title":"Does size matter? Evaluating corporate environmental disclosure in the Australian mining and metal industry: a combined approach of quantity and quality measurement","volume":"26","author":"Lee","year":"2017","journal-title":"Bus. Strateg. Environ."},{"issue":"4","key":"10.1016\/j.scitotenv.2022.155512_bb0245","doi-asserted-by":"crossref","first-page":"2385","DOI":"10.5194\/acp-19-2385-2019","article-title":"Local and remote temperature response of regional SO2 emissions","volume":"19","author":"Lewinschal","year":"2019","journal-title":"Atmos. Chem. Phys."},{"issue":"1","key":"10.1016\/j.scitotenv.2022.155512_bb0250","article-title":"India is overtaking China as the world\u2019s largest emitter of anthropogenic sulfur dioxide","volume":"7","author":"Li","year":"2017","journal-title":"Sci. Rep."},{"issue":"1","key":"10.1016\/j.scitotenv.2022.155512_bb0255","doi-asserted-by":"crossref","first-page":"24","DOI":"10.1093\/nsr\/nwx110","article-title":"Deep learning for natural language processing: advantages and challenges","volume":"5","author":"Li","year":"2017","journal-title":"Natl. Sci. Rev."},{"key":"10.1016\/j.scitotenv.2022.155512_bb0260","doi-asserted-by":"crossref","first-page":"429","DOI":"10.1007\/s00477-013-0762-6","article-title":"Economic growth and pollutant emissions in China: a spatial econometric analysis","volume":"28","author":"Li","year":"2014","journal-title":"Stoch. Env. Res. Risk A."},{"key":"10.1016\/j.scitotenv.2022.155512_bb0265","doi-asserted-by":"crossref","first-page":"10","DOI":"10.1016\/j.atmosenv.2019.03.029","article-title":"Satellite-based prediction of daily SO2 exposure across China using a high-quality random forest-spatiotemporal kriging (RF-STK) model for health risk assessment","volume":"208","author":"Li","year":"2019","journal-title":"Atmos. Environ."},{"issue":"4","key":"10.1016\/j.scitotenv.2022.155512_bb0270","doi-asserted-by":"crossref","first-page":"506","DOI":"10.1111\/j.1530-9290.2011.00418.x","article-title":"Scenario analysis of sulfur dioxide emissions reduction potential in China\u2019s iron and steel industry","volume":"16","author":"Ma","year":"2012","journal-title":"J. Ind. Ecol."},{"key":"10.1016\/j.scitotenv.2022.155512_bb0275","doi-asserted-by":"crossref","first-page":"220","DOI":"10.1016\/j.atmosenv.2019.04.006","article-title":"Influence of regional emissions on SO2 concentrations over Bhubaneswar, a capital city in eastern India downwind of the indian SO2 hotspots","volume":"209","author":"Mallik","year":"2019","journal-title":"Atmos. Environ."},{"key":"10.1016\/j.scitotenv.2022.155512_bb0280","series-title":"Computing Research Repository","article-title":"Evolution of transfer learning in natural language processing","author":"Malte","year":"2019"},{"issue":"4","key":"10.1016\/j.scitotenv.2022.155512_bb0285","doi-asserted-by":"crossref","first-page":"253","DOI":"10.1016\/j.envsci.2004.05.005","article-title":"Acid rain in Europe and the United States: an update","volume":"7","author":"Menz","year":"2004","journal-title":"Environ. Sci. Pol."},{"issue":"2","key":"10.1016\/j.scitotenv.2022.155512_bb0290","doi-asserted-by":"crossref","first-page":"254","DOI":"10.1111\/gean.12205","article-title":"Estimation of anisotropic, time-varying spatial spillovers of fine particulate matter due to wind direction","volume":"52","author":"Merk","year":"2020","journal-title":"Geogr. Anal."},{"issue":"8","key":"10.1016\/j.scitotenv.2022.155512_bb0295","doi-asserted-by":"crossref","first-page":"1772","DOI":"10.4209\/aaqr.2020.05.0240","article-title":"COVID-19 lockdowns improve air quality in the South-East Asian regions, as seen by the remote sensing satellites","volume":"20","author":"Metya","year":"2020","journal-title":"Aerosol Air Qual. Res."},{"issue":"12","key":"10.1016\/j.scitotenv.2022.155512_bb0300","doi-asserted-by":"crossref","first-page":"5267","DOI":"10.1021\/es200844n","article-title":"Watershed sulfur biogeochemistry: shift from atmospheric deposition dominance to climatic regulation","volume":"45","author":"Mitchell","year":"2011","journal-title":"Environ. Sci. Technol."},{"key":"10.1016\/j.scitotenv.2022.155512_bb0310","doi-asserted-by":"crossref","first-page":"1324","DOI":"10.1016\/j.scitotenv.2018.02.317","article-title":"A land use regression model for explaining spatial variation in air pollution levels using a wind sector based approach","volume":"630","author":"Naughton","year":"2018","journal-title":"Sci. Total Environ."},{"key":"10.1016\/j.scitotenv.2022.155512_bb0315","series-title":"The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XLIV-3\/W1-2020, 2020 Gi4DM 2020 \u2013 13th GeoInformation for Disaster Management conference, 30 November\u20134 December 2020, Sydney, Australia","first-page":"111","article-title":"Assessment of Sentinel-5P performance for ground-level air quality monitoring: preparatory experiments over the COVID-19 lockdown period","author":"Oxoli","year":"2020"},{"key":"10.1016\/j.scitotenv.2022.155512_bb0320","series-title":"QGIS Geographic Information System","author":"QGIS Development Team","year":"2021"},{"key":"10.1016\/j.scitotenv.2022.155512_bb0325","doi-asserted-by":"crossref","DOI":"10.1038\/s41598-018-37807-w","article-title":"TROPOMI enables high resolution SO2 flux observations from Mt. Etna, Italy, and beyond","volume":"9","author":"Quei\u00dfer","year":"2019","journal-title":"Sci. Rep."},{"key":"10.1016\/j.scitotenv.2022.155512_bb0330","doi-asserted-by":"crossref","DOI":"10.1016\/j.scitotenv.2020.140155","article-title":"Effects of socioeconomic and natural factors on air pollution in China: a spatial panel data analysis","volume":"740","author":"Ren","year":"2020","journal-title":"Sci. Total Environ."},{"issue":"1","key":"10.1016\/j.scitotenv.2022.155512_bb0335","first-page":"5","article-title":"PySAL: a python library of spatial analytical methods","volume":"37","author":"Rey","year":"2007","journal-title":"Rev. Reg. Stud."},{"key":"10.1016\/j.scitotenv.2022.155512_bb0340","author":"Romahn"},{"issue":"12","key":"10.1016\/j.scitotenv.2022.155512_bb0345","doi-asserted-by":"crossref","DOI":"10.1088\/1748-9326\/aaece2","article-title":"The long-term relationship between emissions and economic growth for SO2, CO2, and BC","volume":"13","author":"Ru","year":"2018","journal-title":"Environ. Res. Lett."},{"issue":"1","key":"10.1016\/j.scitotenv.2022.155512_bb0350","doi-asserted-by":"crossref","first-page":"103","DOI":"10.1257\/jep.27.1.103","article-title":"The SO2 allowance trading system: the ironic history of a grand policy experiment","volume":"27","author":"Schmalensee","year":"2013","journal-title":"J. Econ. Perspect."},{"key":"10.1016\/j.scitotenv.2022.155512_bb0355","author":"Schwierzy"},{"issue":"3","key":"10.1016\/j.scitotenv.2022.155512_bb0360","doi-asserted-by":"crossref","first-page":"1101","DOI":"10.5194\/acp-11-1101-2011","article-title":"Anthropogenic sulfur dioxide emissions: 1850\u20132005","volume":"11","author":"Smith","year":"2011","journal-title":"Atmos. Chem. Phys."},{"issue":"4","key":"10.1016\/j.scitotenv.2022.155512_bb0365","doi-asserted-by":"crossref","first-page":"830","DOI":"10.3390\/atmos5040830","article-title":"Analysis on effectiveness of SO2 emission reduction in Shanxi, China by satellite remote sensing","volume":"5","author":"Song","year":"2014","journal-title":"Atmosphere"},{"key":"10.1016\/j.scitotenv.2022.155512_bb0370","doi-asserted-by":"crossref","DOI":"10.1038\/s41598-019-39279-y","article-title":"Global monitoring of volcanic SO2 degassing with unprecedented resolution from TROPOMI onboard Sentinel-5 Precursor","volume":"9","author":"Theys","year":"2019","journal-title":"Sci. Rep."},{"key":"10.1016\/j.scitotenv.2022.155512_bb0375","doi-asserted-by":"crossref","first-page":"119","DOI":"10.5194\/amt-10-119-2017","article-title":"Sulfur dioxide retrievals from TROPOMI onboard Sentinel-5 precursor: algorithm theoretical basis","volume":"10","author":"Theys","year":"2017","journal-title":"Atmos. Meas. Tech."},{"issue":"1","key":"10.1016\/j.scitotenv.2022.155512_bb0380","doi-asserted-by":"crossref","first-page":"165","DOI":"10.1068\/a310165","article-title":"A variance-stabilizing coding scheme for spatial link matrices","volume":"31","author":"Tiefelsdorf","year":"1999","journal-title":"Environ. Plan. A"},{"key":"10.1016\/j.scitotenv.2022.155512_bb0385","author":"Uscb"},{"key":"10.1016\/j.scitotenv.2022.155512_bb0390","author":"Usgs"},{"key":"10.1016\/j.scitotenv.2022.155512_bb0395","doi-asserted-by":"crossref","first-page":"70","DOI":"10.1016\/j.rse.2011.09.027","article-title":"TROPOMI on the ESA Sentinel-5 precursor: a GMES mission for global observations of the atmospheric composition for climate, air quality and ozone layer applications","volume":"120","author":"Veefkind","year":"2012","journal-title":"Remote Sens. Environ."},{"issue":"1","key":"10.1016\/j.scitotenv.2022.155512_bb0400","doi-asserted-by":"crossref","first-page":"481","DOI":"10.5194\/amt-14-481-2021","article-title":"Ground-based validation of the Copernicus Sentinel-5P TROPOMI NO2 measurements with the NDACC ZSL-DOAS, MAX-DOAS and Pandonia global networks","volume":"14","author":"Verhoelst","year":"2021","journal-title":"Atmos. Meas. Tech."},{"key":"10.1016\/j.scitotenv.2022.155512_bb0405","doi-asserted-by":"crossref","first-page":"157","DOI":"10.1007\/s11869-020-00922-7","article-title":"Systematics of atmospheric environment monitoring in China via satellite remote sensing","volume":"14","author":"Wang","year":"2020","journal-title":"Air Qual. Atmos. Health"},{"key":"10.1016\/j.scitotenv.2022.155512_bb0410","author":"Worrell"},{"key":"10.1016\/j.scitotenv.2022.155512_bb0415","doi-asserted-by":"crossref","DOI":"10.1016\/j.scitotenv.2020.137212","article-title":"Identifying the influencing factors controlling the spatial variation of heavy metals in suburban soil using spatial regression models","volume":"717","author":"Wu","year":"2020","journal-title":"Sci. Total Environ."},{"key":"10.1016\/j.scitotenv.2022.155512_bb0420","first-page":"206","article-title":"Investigating drivers of CO2 emission in China\u2019s heavy industry: a quantile regression analysis","author":"Xu","year":"2020","journal-title":"Energy"},{"issue":"Part B","key":"10.1016\/j.scitotenv.2022.155512_bb0425","doi-asserted-by":"crossref","first-page":"1417","DOI":"10.1016\/j.envpol.2018.08.029","article-title":"Evaluation of machine learning techniques with multiple remote sensing datasets in estimating monthly concentrations of ground-level PM2.5","volume":"242","author":"Xu","year":"2018","journal-title":"Environ. Pollut."},{"key":"10.1016\/j.scitotenv.2022.155512_bb0430","doi-asserted-by":"crossref","first-page":"318","DOI":"10.1016\/j.scitotenv.2016.12.145","article-title":"The impact of anthropogenic emissions and meteorological conditions on the spatial variation of ambient SO2 concentrations: a panel study of 113 chinese cities","volume":"584\u2013585","author":"Yang","year":"2017","journal-title":"Sci. Total Environ."},{"key":"10.1016\/j.scitotenv.2022.155512_bb0435","doi-asserted-by":"crossref","first-page":"824","DOI":"10.1016\/j.jclepro.2017.08.215","article-title":"Are the temporal variation and spatial variation of ambient SO2 concentrations determined by different factors?","volume":"167","author":"Yang","year":"2017","journal-title":"J. Clean. Prod."},{"issue":"13","key":"10.1016\/j.scitotenv.2022.155512_bb0440","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1029\/2007GL029979","article-title":"Ubiquity and dominance of oxygenated species in organic aerosols in anthropogenically-influenced northern hemisphere midlatitudes","volume":"34","author":"Zhang","year":"2007","journal-title":"Geophys. Res. Lett."},{"key":"10.1016\/j.scitotenv.2022.155512_bb0445","doi-asserted-by":"crossref","DOI":"10.1016\/j.scs.2020.102106","article-title":"A geographically weighted regression model augmented by Geodetector analysis and principal component analysis for the spatial distribution of PM2.5","volume":"56","author":"Zhao","year":"2020","journal-title":"Sustain. Cities Soc."},{"issue":"Part A","key":"10.1016\/j.scitotenv.2022.155512_bb0450","doi-asserted-by":"crossref","first-page":"105145","DOI":"10.1016\/j.envint.2019.105145","article-title":"Spatiotemporal variation in PM2.5 concentrations and their relationship with socioeconomic factors in China\u2019s major cities","volume":"133","author":"Zhao","year":"2019","journal-title":"Environ. Int."},{"key":"10.1016\/j.scitotenv.2022.155512_bb0455","doi-asserted-by":"crossref","first-page":"50","DOI":"10.1016\/j.atmosenv.2018.06.029","article-title":"Spatial and temporal distribution of NO2 and SO2 in Inner Mongolia urban agglomeration obtained from satellite remote sensing and ground observations","volume":"188","author":"Zheng","year":"2018","journal-title":"Atmos. Environ."},{"issue":"16","key":"10.1016\/j.scitotenv.2022.155512_bb0460","doi-asserted-by":"crossref","first-page":"1939","DOI":"10.3390\/rs11161939","article-title":"Spatial variation of NO2 and its impact factors in China: an application of Sentinel-5P products","volume":"11","author":"Zheng","year":"2019","journal-title":"Remote Sens."},{"issue":"11","key":"10.1016\/j.scitotenv.2022.155512_bb0465","doi-asserted-by":"crossref","first-page":"6508","DOI":"10.1021\/acs.est.9b07696","article-title":"Global sulfur dioxide emissions and the driving forces","volume":"54","author":"Zhong","year":"2020","journal-title":"Environ. Sci. Technol."},{"key":"10.1016\/j.scitotenv.2022.155512_bb0470","doi-asserted-by":"crossref","first-page":"436","DOI":"10.1016\/j.scitotenv.2017.11.124","article-title":"Examining the effects of socioeconomic development on fine particulate matter (PM2.5) in China\u2019s cities using spatial regression and the geographical detector technique","volume":"619\u2013620","author":"Zhou","year":"2018","journal-title":"Sci. Total Environ."},{"issue":"1","key":"10.1016\/j.scitotenv.2022.155512_bb0475","doi-asserted-by":"crossref","first-page":"121","DOI":"10.1002\/joc.3413","article-title":"Development of gridded surface meteorological data for ecological applications and modelling","volume":"33","author":"Abatzoglou","year":"2012","journal-title":"Int. J. Climatol."},{"key":"10.1016\/j.scitotenv.2022.155512_bb0480","author":"EPA"},{"key":"10.1016\/j.scitotenv.2022.155512_bb0485","author":"Gately"},{"key":"10.1016\/j.scitotenv.2022.155512_bb0490","author":"Infogroup"},{"key":"10.1016\/j.scitotenv.2022.155512_bb0495","series-title":"Copernicus Climate Change Service (C3S) Climate Data Store (CDS)","article-title":"ERA5-Land monthly averaged data from 1981 to present","author":"Mu\u00f1oz Sabater","year":"2019"},{"key":"10.1016\/j.scitotenv.2022.155512_bb0500","author":"Npms"},{"key":"10.1016\/j.scitotenv.2022.155512_bb0505","author":"Sentinel-5P"},{"key":"10.1016\/j.scitotenv.2022.155512_bb0510","author":"Usgs"},{"key":"10.1016\/j.scitotenv.2022.155512_bb0515","author":"Usgs"},{"key":"10.1016\/j.scitotenv.2022.155512_bb0520","author":"WorldPop"},{"key":"10.1016\/j.scitotenv.2022.155512_bb0525","doi-asserted-by":"crossref","first-page":"108","DOI":"10.1016\/j.isprsjprs.2018.09.006","article-title":"A new generation of the United States National Land Cover Database: requirements, research priorities, design, and implementation strategies","volume":"146","author":"Yang","year":"2018","journal-title":"ISPRS J. Photogramm. Remote Sens."}],"container-title":["Science of The Total Environment"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0048969722026080?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0048969722026080?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2025,9,24]],"date-time":"2025-09-24T14:32:36Z","timestamp":1758724356000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0048969722026080"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,8]]},"references-count":104,"alternative-id":["S0048969722026080"],"URL":"https:\/\/doi.org\/10.1016\/j.scitotenv.2022.155512","relation":{},"ISSN":["0048-9697"],"issn-type":[{"value":"0048-9697","type":"print"}],"subject":[],"published":{"date-parts":[[2022,8]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Greenwashing in the US metal industry? A novel approach combining SO2 concentrations from satellite data, a plant-level firm database and web text mining","name":"articletitle","label":"Article Title"},{"value":"Science of The Total Environment","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.scitotenv.2022.155512","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2022 The Authors. Published by Elsevier B.V.","name":"copyright","label":"Copyright"}],"article-number":"155512"}}