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Abstract Ecological balance and carbon sink economies have gained increased attention for tackling global warming. Based on an improved Carnegie–Ames–Stanford Approach model, this study demonstrated regional Net Primary Productivity (NPP) and analyzed regional carbon overdraft situations in China during 2005–2015. Regional carbon allowances were allocated according to carrying capacity of carbon sequestration and China's carbon intensity reduction goals in “13th Five-year plan”. Data Envelopment Analysis (DEA) technology with panel data was further employed to estimate potential benefits resulting from carbon trading and a carbon sink economy. Regional NPP decreased from south to north and from coast to inland, while regions with severe carbon overdrafts were gathered in North and East China. In order to maintain a regional carbon balance with lower abatement costs, regional cooperation of emission reduction within either North or East China is proposed in this study. It is concluded that the majority of provinces and cities in Eastern China and some provinces in the west would be the major purchasers of carbon credits under a national carbon emissions trading (CET) market. Following the introduction of emissions offset mechanisms, Yunnan, Sichuan, and Heilongjiang would be the major providers of carbon sinks in China.

AbstractAccurate, 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.

AbstractWith the implementation of China’s top-down CO2 emissions reduction strategy, the regional differences should be considered. As the most basic governmental unit in China, counties could better capture the regional heterogeneity than provinces and prefecture-level city, and county-level CO2 emissions could be used for the development of strategic policies tailored to local conditions. However, most of the previous accounts of CO2 emissions in China have only focused on the national, provincial, or city levels, owing to limited methods and smaller-scale data. In this study, a particle swarm optimization-back propagation (PSO-BP) algorithm was employed to unify the scale of DMSP/OLS and NPP/VIIRS satellite imagery and estimate the CO2 emissions in 2,735 Chinese counties during 1997–2017. Moreover, as vegetation has a significant ability to sequester and reduce CO2 emissions, we calculated the county-level carbon sequestration value of terrestrial vegetation. The results presented here can contribute to existing data gaps and enable the development of strategies to reduce CO2 emissions in China.

Abstract Carbon sequestration capacity of vegetation plays an important role in global carbon emission reduction. Based on vegetation carbon sequestration, this paper establishes a carbon footprint pressure index to evaluate the carbon footprint pressure in 60 sample countries, and discusses the driving factors that influence carbon footprint pressure in various countries through IPAT equation and Logarithmic Mean Divisia Index decomposition approach. The results indicate that the global carbon footprint pressure shows an upward trend from 2000 to 2015, mainly owing to population growth and rapid socioeconomic development; technological progress has a certain inhibitory effect on the rise of carbon footprint pressure. Furthermore, the overall carbon footprint pressure in the Organisation for Economic Co-operation and Development (OECD) countries shows a downward trend, while the carbon footprint pressure in non-OECD countries is rising, even exceeding the economic growth rate, which is probably related to the transfer of a large number of implied carbon emissions from OECD countries to non-OECD countries.