{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,1]],"date-time":"2026-02-01T19:27:34Z","timestamp":1769974054156,"version":"3.49.0"},"reference-count":67,"publisher":"MDPI AG","issue":"22","license":[{"start":{"date-parts":[[2022,11,20]],"date-time":"2022-11-20T00:00:00Z","timestamp":1668902400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["42175145"],"award-info":[{"award-number":["42175145"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["SAST 2019-045"],"award-info":[{"award-number":["SAST 2019-045"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Shanghai Aerospace Science and Technology Innovation Foundation","award":["42175145"],"award-info":[{"award-number":["42175145"]}]},{"name":"Shanghai Aerospace Science and Technology Innovation Foundation","award":["SAST 2019-045"],"award-info":[{"award-number":["SAST 2019-045"]}]},{"name":"Qinglan Project of Jiangsu Province of China","award":["42175145"],"award-info":[{"award-number":["42175145"]}]},{"name":"Qinglan Project of Jiangsu Province of China","award":["SAST 2019-045"],"award-info":[{"award-number":["SAST 2019-045"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Satellites are an effective source of atmospheric carbon dioxide (CO2) monitoring; however, city-scale monitoring of atmospheric CO2 through space-borne observations is still a challenging task due to the trivial change in atmospheric CO2 concentration compared to its natural variability and background concentration. In this study, we attempted to evaluate the potential of space-based observations to monitor atmospheric CO2 changes at the city scale through simple data-driven analyses. We used the column-averaged dry-air mole fraction of CO2 (XCO2) from the Carbon Observatory 2 (OCO-2) and the anthropogenic CO2 emissions provided by the Open-Data Inventory for Anthropogenic Carbon dioxide (ODIAC) product to explain the scenario of CO2 over 120 districts of Pakistan. To study the anthropogenic CO2 through space-borne observations, XCO2 anomalies (MXCO2) were estimated from OCO-2 retrievals within the spatial boundary of each district, and then the overall spatial distribution pattern of the MXCO2 was analyzed with several datasets including the ODIAC emissions, NO2 tropospheric column, fire locations, cropland, nighttime lights and population density. All the datasets showed a similarity in the spatial distribution pattern. The satellite detected higher CO2 concentrations over the cities located along the China\u2013Pakistan Economic Corridor (CPEC) routes. The CPEC is a large-scale trading partnership between Pakistan and China and large-scale development has been carried out along the CPEC routes over the last decade. Furthermore, the cities were ranked based on mean ODIAC emissions and MXCO2 estimates. The satellite-derived estimates showed a good consistency with the ODIAC emissions at higher values; however, deviations between the two datasets were observed at lower values. To further study the relationship of MXCO2 and ODIAC emissions with each other and with some other datasets such as population density and NO2 tropospheric column, statistical analyses were carried out among the datasets. Strong and significant correlations were observed among all the datasets.<\/jats:p>","DOI":"10.3390\/rs14225882","type":"journal-article","created":{"date-parts":[[2022,11,21]],"date-time":"2022-11-21T04:33:32Z","timestamp":1669005212000},"page":"5882","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":21,"title":["Monitoring of Atmospheric Carbon Dioxide over Pakistan Using Satellite Dataset"],"prefix":"10.3390","volume":"14","author":[{"given":"Ning","family":"An","sequence":"first","affiliation":[{"name":"Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Key Laboratory of Meteorological Disasters, Ministry of Education, Nanjing University of Information Science and Technology (NUIST), Nanjing 210044, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8827-7308","authenticated-orcid":false,"given":"Farhan","family":"Mustafa","sequence":"additional","affiliation":[{"name":"Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Key Laboratory of Meteorological Disasters, Ministry of Education, Nanjing University of Information Science and Technology (NUIST), Nanjing 210044, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9971-3486","authenticated-orcid":false,"given":"Lingbing","family":"Bu","sequence":"additional","affiliation":[{"name":"Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Key Laboratory of Meteorological Disasters, Ministry of Education, Nanjing University of Information Science and Technology (NUIST), Nanjing 210044, China"}]},{"given":"Ming","family":"Xu","sequence":"additional","affiliation":[{"name":"BNU-HKUST Laboratory for Green Innovation, Advanced Institute of Natural Sciences, Beijing Normal University at Zhuhai, Zhuhai 519087, China"},{"name":"Jiangmen Laboratory of Carbon Science and Technology, Hong Kong University of Science and Technology, Jiangmen 529000, China"}]},{"given":"Qin","family":"Wang","sequence":"additional","affiliation":[{"name":"Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Key Laboratory of Meteorological Disasters, Ministry of Education, Nanjing University of Information Science and Technology (NUIST), Nanjing 210044, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1763-829X","authenticated-orcid":false,"given":"Muhammad","family":"Shahzaman","sequence":"additional","affiliation":[{"name":"School of Atmospheric Sciences (SAS), Nanjing University of Information Science and Technology (NUIST), Nanjing 210044, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1022-3999","authenticated-orcid":false,"given":"Muhammad","family":"Bilal","sequence":"additional","affiliation":[{"name":"School of Surveying and Land Information Engineering, Henan Polytechnic University, Jiaozuo 454003, China"}]},{"given":"Safi","family":"Ullah","sequence":"additional","affiliation":[{"name":"Department of Atmospheric and Oceanic Sciences\/Institute of Atmospheric Sciences, Fudan University, Shanghai 200438, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4373-4058","authenticated-orcid":false,"given":"Zhang","family":"Feng","sequence":"additional","affiliation":[{"name":"Department of Atmospheric and Oceanic Sciences\/Institute of Atmospheric Sciences, Fudan University, Shanghai 200438, China"}]}],"member":"1968","published-online":{"date-parts":[[2022,11,20]]},"reference":[{"key":"ref_1","unstructured":"(2014). 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