Carbon emission accounting and spatial distribution of industrial entities in Beijing-Combining nighttime light data and urban functional areas
文献类型：期刊论文
| 作者 | Wang, Xiaoyu4,5; Cai, Ying6; Liu, Gang1,7; Zhang, Mengyi3; Bai, Yuping3; Zhang, Fan1,2,7 |
| 刊名 | ECOLOGICAL INFORMATICS
 |
| 出版日期 | 2022-09-01 |
| 卷号 | 70页码:14 |
| ISSN号 | 1574-9541 |
| 关键词 | Industrial entities Nighttime light data Functional urban areas Carbon emission accounting Carbon reduction strategies |
| DOI | 10.1016/j.ecoinf.2022.101759 |
| 通讯作者 | Zhang, Fan(zhangf.ccap@igsnrr.ac.cn) |
| 英文摘要 | Quantifying current carbon emissions their fine scale spatial distribution is necessary to improve carbon emission management, requirements, and emission reduction strategies of key industries. This study established an entity -level model to estimate carbon emissions by combining geographic information of points of interest (POIs) and nighttime light data from Beijing in 2018. The model accounted for the carbon emissions of Beijing's key entities and industries and simulated their spatial distribution. The results showed a good fit between the carbon emissions of the entities and nighttime light brightness values. The 130-m resolution of the urban carbon emission distribution data had a higher spatial simulation accuracy than that of the 1-km Open-Data inventory for anthropogenic carbon dioxide (ODIAC) data. Through the lens of urban functional areas, the average value of carbon emissions was highest in commercial areas and lowest in public management and service areas, at 78,840.11 tC/km2 and 6844.79 tC/km(2), respectively. In terms of the industrial sector, the transportation in-dustry had the highest carbon emissions, with a total of 31.86 Mt., while non-metal mining and oil and gas extraction had almost no energy consumption, with total carbon emissions of 1.38 Mt. The spatial clustering results showed that the distribution of carbon emissions in Beijing had a significant positive spatial correlation; forming high-high aggregation clusters dominated by the city center and major business districts and a low-low aggregation clusters dominated by the city's suburban areas. The simulation model clearly reflected the fine scale characteristics of carbon emissions, in terms of their quantity and spatial distribution. Results obtained in this study can aid relevant departments to formulate appropriate strategies for collectively guiding industrial en-terprises towards carbon neutrality. |
| WOS关键词 | LAND-USE CHANGES ; ENERGY-CONSUMPTION ; CHINA ; CO2 ; DECOMPOSITION ; METABOLISM ; SIMULATION ; INVENTORY ; CITIES |
| 资助项目 | National Natural Science Foundation of China[72004215] |
| WOS研究方向 | Environmental Sciences & Ecology |
| 语种 | 英语 |
| 出版者 | ELSEVIER |
| WOS记录号 | WOS:000842910000005 |
| 资助机构 | National Natural Science Foundation of China |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/166618]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Zhang, Fan |
| 作者单位 | 1.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Land Surface Pattern & Simulat, Beijing 100101, Peoples R China 2.11A,Datun Rd, Beijing 100101, Peoples R China 3.China Univ Geosci, Sch Land Sci & Technol, Beijing 100083, Peoples R China 4.Capital Normal Univ, Coll Resource Environm & Tourism, Beijing 100048, Peoples R China 5.Capital Normal Univ, Key Lab 3D Informat Acquisit & Applicat Minist, Beijing 100048, Peoples R China 6.Beijing Forestry Univ, Sch Soil & Water Conservat, Beijing 100038, Peoples R China 7.Univ Chinese Acad Sci, Beijing 100149, Peoples R China |
| 推荐引用方式 GB/T 7714 | Wang, Xiaoyu,Cai, Ying,Liu, Gang,et al. Carbon emission accounting and spatial distribution of industrial entities in Beijing-Combining nighttime light data and urban functional areas[J]. ECOLOGICAL INFORMATICS,2022,70:14. |
| APA | Wang, Xiaoyu,Cai, Ying,Liu, Gang,Zhang, Mengyi,Bai, Yuping,&Zhang, Fan.(2022).Carbon emission accounting and spatial distribution of industrial entities in Beijing-Combining nighttime light data and urban functional areas.ECOLOGICAL INFORMATICS,70,14. |
| MLA | Wang, Xiaoyu,et al."Carbon emission accounting and spatial distribution of industrial entities in Beijing-Combining nighttime light data and urban functional areas".ECOLOGICAL INFORMATICS 70(2022):14. |
入库方式： OAI收割
来源：地理科学与资源研究所
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