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.

Impacts of Emission Reduction Technological Changes on China’s City-Level PM2.5 Concentration Based on Sustainable Development

“…e data for PM2.5 concentrations were obtained from the real-time monitoring of the Ministry of Ecology and Environment monitoring site (https://106.37.208.233: 20035). We estimated the data for city-level energy consumption based on city-level CO 2 emissions, as proposed by Chen et al [29], due to the significant relationship between energy use and CO 2 emissions. e economic output was taken from the China Statistical Yearbook (2003-2017).…”

“…However, such replacement may cause significant errors, since fluctuations in electronic power use are inconsistent with total energy combustion. erefore, we calculated the energy use of the 262 cities during 2003-2017 based on data on city-level CO 2 emissions, as proposed by Chen et al [29].…”

Carbon Monitor Cities near-real-time daily estimates of CO2 emissions from 1500 cities worldwide

“…Unfortunately, a global, open, and harmonized dataset of city-level emission inventories is yet lacking 7 , 8 . Instead, most CO 2 emission inventories are conducted at the country level, as city-level fossil fuel consumption data are more difficult to acquire 9 . Furthermore, many inventories–including national inventories reported to the United Nations Framework Convention on Climate Change (UNFCCC) often lag reality by one years or more 10 , 11 .…”

Analysis of Dynamic Evolution and Spatial-Temporal Heterogeneity of Carbon Emissions at County Level along “The Belt and Road”—A Case Study of Northwest China

“…With the development of remote sensing technology, nighttime light data are widely used in carbon emission fitting research because of its high spatial correlation with carbon emissions [ 10 , 11 , 12 , 13 ]. The fitting of carbon emissions by nighttime light data can overcome the differences between the statistical caliber and accounting standards of energy data across administrative boundaries in a wide range of research scales [ 14 , 15 ]. However, it can only identify human social and economic activities in light areas [ 16 ].…”