China\u2019s city-level carbon emissions during 1992\u20132017 based on the inter-calibration of nighttime light data

Jiandong Chen,Malin Song,Xin Liu,Wenxuan Hou,Ding Li,Wei Fan,Ming Gao,Shulei Cheng

doi:10.1038/s41598-021-81754-y

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.

Highlights

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
If only the national or provincial carbon emissions and corresponding driving forces receive attention, the heterogeneous characteristics of city-level carbon emissions will be ignored, and this will not be beneficial for the development of strategies that can support city-level sustainable development
To further eliminate the unstable pixel DN values and the obvious over-glow effect of DMSP/OLS data, we assumed that the bright areas of the corrected and transformed NPP/VIIRS image in 2017 were stable, used the data to extract the DMSP/OLS images, and replaced the remaining lit pixels with values of zero, which is consistent with Liu et al.[33]

Summary

Introduction

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. An increasing number of scholars are focusing their efforts on the development of effective carbon emission reduction strategies and ways to promote a sustainable low-carbon economy[2,3] These studies mainly have been concentrated at the national and provincial levels, and research on city-level carbon emissions remains scarce. The first group directly estimates carbon emissions of several cities in certain years based on energy inventory data, which were collected from China City Statistical Yearbooks, Local Government Work Reports, or other relevant statistical sources in local g overnments[8,10,11,12,13,14,15] These studies collectively represent an extensive effort to organize relevant data and produce relatively reliable data on city-level carbon emissions. Even when another type of nighttime light data, such as NPP/VIIRS (Suomi National Polar-orbiting Partnership’s Visible Infrared Imaging Radiometer Suite) images, is used to generate data from 2012 onwards, there are evident discrepancies between the two types of data

Methods

Results

Conclusion