Mapping urban CO 2 emissions using DMSP/OLS ‘city lights’ satellite data in China

Abstract

China, the world’s top CO₂ emitter, is faced with pressure of energy-saving emission reduction. In the 2015 Paris Climate Conference (COP21), China announced its plan, aiming to cut down CO₂ emissions by 60%–65% per unit of GDP in comparison to 2005’s level by 2030. To achieve this ambitious goal, reliable national, provincial, and city-level statistics are fundamental for multi-scale mitigation policy-makings as well as for the allocation of responsibilities among different administrative units. However, China implemented a top-down energy statistical system. The National Bureau of Statistics only publishes annually both national and provincial energy statistics. Only part of cities released their statistics, which results in missing data in city-level energy statistics. This also affects data transparency and accuracy of energy and CO₂ emission statistics, and as a result, increases difficulty in allocation of CO₂ emission reduction responsibilities. In order to fill this lacuna, we employed a standardized remote sensing inversion approach for estimating China’s city-level CO₂ emissions from energy consumptions by integrating DMSP/OLS ‘city lights’ satellite data and statistical data. The end product is a map of city-level CO₂ emissions in China. The most topping CO₂ emitters are located in the major urban agglomerations along the more economically developed eastern coast (e.g. Yangtze River Delta, Beijing–Tianjin–Hebei, Shandong Peninsula, and Pearl River Delta). Other regions with high CO₂ emissions are Shanxi and Henan in Central China, as well as the Chengdu–Chongqing and Shaanxi in West China. Regions with low CO₂ emissions are western China, and most of Central China and South China.