Monitoring of Atmospheric Carbon Dioxide over Pakistan Using Satellite Dataset
Satellites are an effective source of atmospheric carbon dioxide (CO<sub>2</sub>) monitoring; however, city-scale monitoring of atmospheric CO<sub>2</sub> through space-borne observations is still a challenging task due to the trivial change in atmospheric CO<sub>2</...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-11-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/14/22/5882 |
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| author | Ning An Farhan Mustafa Lingbing Bu Ming Xu Qin Wang Muhammad Shahzaman Muhammad Bilal Safi Ullah Zhang Feng |
| author_facet | Ning An Farhan Mustafa Lingbing Bu Ming Xu Qin Wang Muhammad Shahzaman Muhammad Bilal Safi Ullah Zhang Feng |
| author_sort | Ning An |
| collection | DOAJ |
| description | Satellites are an effective source of atmospheric carbon dioxide (CO<sub>2</sub>) monitoring; however, city-scale monitoring of atmospheric CO<sub>2</sub> through space-borne observations is still a challenging task due to the trivial change in atmospheric CO<sub>2</sub> 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 CO<sub>2</sub> changes at the city scale through simple data-driven analyses. We used the column-averaged dry-air mole fraction of CO<sub>2</sub> (XCO<sub>2</sub>) from the Carbon Observatory 2 (OCO-2) and the anthropogenic CO<sub>2</sub> emissions provided by the Open-Data Inventory for Anthropogenic Carbon dioxide (ODIAC) product to explain the scenario of CO<sub>2</sub> over 120 districts of Pakistan. To study the anthropogenic CO<sub>2</sub> through space-borne observations, XCO<sub>2</sub> anomalies (MXCO<sub>2</sub>) were estimated from OCO-2 retrievals within the spatial boundary of each district, and then the overall spatial distribution pattern of the MXCO<sub>2</sub> was analyzed with several datasets including the ODIAC emissions, NO<sub>2</sub> 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 CO<sub>2</sub> concentrations over the cities located along the China–Pakistan 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 MXCO<sub>2</sub> 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 MXCO<sub>2</sub> and ODIAC emissions with each other and with some other datasets such as population density and NO<sub>2</sub> tropospheric column, statistical analyses were carried out among the datasets. Strong and significant correlations were observed among all the datasets. |
| first_indexed | 2024-03-09T18:01:54Z |
| format | Article |
| id | doaj.art-470ca7ccf95d4671970916aca80ae19d |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-09T18:01:54Z |
| publishDate | 2022-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-470ca7ccf95d4671970916aca80ae19d2023-11-24T09:51:56ZengMDPI AGRemote Sensing2072-42922022-11-011422588210.3390/rs14225882Monitoring of Atmospheric Carbon Dioxide over Pakistan Using Satellite DatasetNing An0Farhan Mustafa1Lingbing Bu2Ming Xu3Qin Wang4Muhammad Shahzaman5Muhammad Bilal6Safi Ullah7Zhang Feng8Collaborative 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, ChinaCollaborative 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, ChinaCollaborative 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, ChinaBNU-HKUST Laboratory for Green Innovation, Advanced Institute of Natural Sciences, Beijing Normal University at Zhuhai, Zhuhai 519087, ChinaCollaborative 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, ChinaSchool of Atmospheric Sciences (SAS), Nanjing University of Information Science and Technology (NUIST), Nanjing 210044, ChinaSchool of Surveying and Land Information Engineering, Henan Polytechnic University, Jiaozuo 454003, ChinaDepartment of Atmospheric and Oceanic Sciences/Institute of Atmospheric Sciences, Fudan University, Shanghai 200438, ChinaDepartment of Atmospheric and Oceanic Sciences/Institute of Atmospheric Sciences, Fudan University, Shanghai 200438, ChinaSatellites are an effective source of atmospheric carbon dioxide (CO<sub>2</sub>) monitoring; however, city-scale monitoring of atmospheric CO<sub>2</sub> through space-borne observations is still a challenging task due to the trivial change in atmospheric CO<sub>2</sub> 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 CO<sub>2</sub> changes at the city scale through simple data-driven analyses. We used the column-averaged dry-air mole fraction of CO<sub>2</sub> (XCO<sub>2</sub>) from the Carbon Observatory 2 (OCO-2) and the anthropogenic CO<sub>2</sub> emissions provided by the Open-Data Inventory for Anthropogenic Carbon dioxide (ODIAC) product to explain the scenario of CO<sub>2</sub> over 120 districts of Pakistan. To study the anthropogenic CO<sub>2</sub> through space-borne observations, XCO<sub>2</sub> anomalies (MXCO<sub>2</sub>) were estimated from OCO-2 retrievals within the spatial boundary of each district, and then the overall spatial distribution pattern of the MXCO<sub>2</sub> was analyzed with several datasets including the ODIAC emissions, NO<sub>2</sub> 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 CO<sub>2</sub> concentrations over the cities located along the China–Pakistan 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 MXCO<sub>2</sub> 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 MXCO<sub>2</sub> and ODIAC emissions with each other and with some other datasets such as population density and NO<sub>2</sub> tropospheric column, statistical analyses were carried out among the datasets. Strong and significant correlations were observed among all the datasets.https://www.mdpi.com/2072-4292/14/22/5882climate changecarbon dioxideOCO-2PakistanCPEC |
| spellingShingle | Ning An Farhan Mustafa Lingbing Bu Ming Xu Qin Wang Muhammad Shahzaman Muhammad Bilal Safi Ullah Zhang Feng Monitoring of Atmospheric Carbon Dioxide over Pakistan Using Satellite Dataset Remote Sensing climate change carbon dioxide OCO-2 Pakistan CPEC |
| title | Monitoring of Atmospheric Carbon Dioxide over Pakistan Using Satellite Dataset |
| title_full | Monitoring of Atmospheric Carbon Dioxide over Pakistan Using Satellite Dataset |
| title_fullStr | Monitoring of Atmospheric Carbon Dioxide over Pakistan Using Satellite Dataset |
| title_full_unstemmed | Monitoring of Atmospheric Carbon Dioxide over Pakistan Using Satellite Dataset |
| title_short | Monitoring of Atmospheric Carbon Dioxide over Pakistan Using Satellite Dataset |
| title_sort | monitoring of atmospheric carbon dioxide over pakistan using satellite dataset |
| topic | climate change carbon dioxide OCO-2 Pakistan CPEC |
| url | https://www.mdpi.com/2072-4292/14/22/5882 |
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