Dataset Information

China's city-level carbon emissions during 1992-2017 based on the inter-calibration of nighttime light data.

ABSTRACT: Accurate, long-term, full-coverage carbon dioxide (CO₂) data in units of prefecture-level cities are necessary for evaluations of CO₂ emission reductions in China, which has become one of the world's largest carbon-emitting countries. This study develops a novel method to match satellite-based Defense Meteorological Satellite Program's Operational Landscan System (DMSP/OLS) and Suomi National Polar-orbiting Partnership's Visible Infrared Imaging Radiometer Suite (NPP/VIIRS) nighttime light data, and estimates the CO₂ emissions of 334 prefecture-level cities in China from 1992 to 2017. Results indicated that the eastern and coastal regions had higher carbon emissions, but their carbon intensity decreased more rapidly than other regions. Compared to previous studies, we provide the most extensive and long-term CO₂ dataset to date, and these data will be of great value for further socioeconomic research. Specifically, this dataset provides a foundational data source for China's future CO₂ research and emission reduction strategies. Additionally, the methodology can be applied to other regions around the world.

SUBMITTER: Chen J

PROVIDER: S-EPMC7870850 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

China's city-level carbon emissions during 1992-2017 based on the inter-calibration of nighttime light data.

Chen Jiandong J Gao Ming M Cheng Shulei S Liu Xin X Hou Wenxuan W Song Malin M Li Ding D Fan Wei W

Scientific reports 20210208 1

Accurate, long-term, full-coverage carbon dioxide (CO<sub>2</sub>) data in units of prefecture-level cities are necessary for evaluations of CO<sub>2</sub> emission reductions in China, which has become one of the world's largest carbon-emitting countries. This study develops a novel method to match satellite-based Defense Meteorological Satellite Program's Operational Landscan System (DMSP/OLS) and Suomi National Polar-orbiting Partnership's Visible Infrared Imaging Radiometer Suite (NPP/VIIRS) ...[more]

PMID: 33558535

Similar Datasets

Project description:With the rapid economic development of Xinjiang Uygur Autonomous Region (Xinjiang), energy consumption became the primary source of carbon emissions. The growth trend in energy consumption and coal-dominated energy structure are unlikely to change significantly in the short term, meaning that carbon emissions are expected to continue rising. To clarify the changes in energy-related carbon emissions in Xinjiang over the past 15 years, this paper integrates DMSP/OLS and NPP/VIIRS data to generate long-term nighttime light remote sensing data from 2005 to 2020. The data is used to analyze the distribution characteristics of carbon emissions, spatial autocorrelation, frequency of changes, and the standard deviation ellipse. The results show that: (1) From 2005 to 2020, the total carbon emissions in Xinjiang continued to grow, with noticeable urban additions although the growth rate fluctuated. In spatial distribution, non-carbon emission areas were mainly located in the northwest; low-carbon emission areas mostly small and medium-sized towns; and high-carbon emission areas were concentrated around the provincial capital and urban agglomerations. (2) There were significant regional differences in carbon emissions, with clear spatial clustering of energy consumption. The clustering stabilized, showing distinct "high-high" and "low-low" patterns. (3) Carbon emissions in central urban areas remained stable, while higher frequencies of change were seen in the peripheral areas of provincial capitals and key cities. The center of carbon emissions shifted towards southeast but later showed a trend of moving northwest. (4) Temporal and spatial variations in carbon emissions were closely linked to energy consumption intensity, population size, and economic growth. These findings provided a basis for formulating differentiated carbon emission targets and strategies, optimizing energy structures, and promoting industrial transformation to achieve low-carbon economic development in Xinjiang.

Project description:China's "plain-mountain transition zone" (hereinafter referred to as the "transition zone") has experienced rapid and diverse urbanization processes. Assessing the dynamic characteristics of urbanization is particularly important for sustainable development of the transition zone. Nighttime light (NTL) data have been widely used to monitor urbanization. Based on the prolonged artificial nighttime-light dataset of China (PANDA) from 1984 to 2020, we partitioned the nighttime light of the study area into four types (low, medium, high, and extremely high) by adjusting the threshold of the brightness gradient (BG) method. The spatiotemporal characteristics of urbanization in 426 districts and counties of 71 prefecture-level cities in the transition zone were analyzed. Our results indicated that the middle region of the transition zone (Yanshan Mountains and Taihang Mountains) experienced the fastest urbanization development, and the urban expansion speed broke through the topographic limitation of the plain-mountain. However, the rapid development of urbanization in the middle plains resulted in the nighttime lighting area (NTLA) tending to become saturated, which caused an unsustainable potential crisis in urban development in this area. Urbanization was mainly manifested in the transition of the low nighttime lighting type (NTLT) to the medium NTLT or higher NTLT. The northern region of the transition zone (Greater Khingan Mountains) experienced the slowest urbanization development, with the lowest nighttime lighting density (NTLD) in the northern mountainous area, where the urbanization was mainly manifested by the expansion of the low NTLT. The urbanization development of the southern region in the transition zone (Wushan and Xuefeng Mountains) was at a medium level, and the urbanization of the plain in the southern region was also better than that of the mountainous area. Urbanization was mainly manifested in the expansion of the low NTLT, supplemented by the transition from the low NTLT to high NTLT. Whether in the north, middle, or south of the transition zone, the plain-mountain topographic variations caused a gap in urbanization, making the urbanization development of the mountains and plains unbalanced.

Dataset Information

China's city-level carbon emissions during 1992-2017 based on the inter-calibration of nighttime light data.

Publications

China's city-level carbon emissions during 1992-2017 based on the inter-calibration of nighttime light data.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets