Regional Carbon Emission Performance of Pig Production in China according to Malmquist-DEA Approach

As pig production is a main contributor of greenhouse gas(GHG) emissions from livestock sector,the carbon emissions of pig production are attracting increasing attention,especially in the developing countries. Based on the panel data of 30 provinces in China from 2001 to 2012,this paper measures the provincial carbon emission performance(CEP) of pig production and we use a Malmquist DEA approach to analyze the decomposition which includes desirable and undesirable output. Furthermore,the regional disparity in carbon emission performance of pig production is also analyzed and finally the convergence is tested. The main results are as follows:(i) there are provincial differences in carbon emission performance changing of pig production in China,and the carbon emission performance of pig production in 30 provinces has a downward trend during this period;(ii) among China’s three major economic regions,in terms of carbon emission performance of pig production,they are ranked in descending order as follows: Western China,Central China and Eastern China;(iii) convergence testing shows that there is a convergence trend for carbon emission performance both nationally and for the three regions.

Spatiotemporal evolution of urban carbon emission performance in China and prediction of future trends

Climate change resulting from CO_2 emissions has become an important global environmental issue in recent years.Improving carbon emission performance is one way to reduce carbon emissions.Although carbon emission performance has been discussed at the national and industrial levels,city-level studies are lacking due to the limited availability of statistics on energy consumption.In this study,based on city-level remote sensing data on carbon emissions in China from 1992–2013,we used the slacks-based measure of super-efficiency to evaluate urban carbon emission performance.The traditional Markov probability transfer matrix and spatial Markov probability transfer matrix were constructed to explore the spatiotemporal evolution of urban carbon emission performance in China for the first time and predict long-term trends in carbon emission performance.The results show that urban carbon emission performance in China steadily increased during the study period with some fluctuations.However,the overall level of carbon emission performance remains low,indicating great potential for improvements in energy conservation and emission reduction.The spatial pattern of urban carbon emission performance in China can be described as"high in the south and low in the north,"and significant differences in carbon emission performance were found between cities.The spatial Markov probabilistic transfer matrix results indicate that the transfer of carbon emission performance in Chinese cities is stable,resulting in a"club convergence"phenomenon.Furthermore,neighborhood backgrounds play an important role in the transfer between carbon emission performance types.Based on the prediction of long-term trends in carbon emission performance,carbon emission performance is expected to improve gradually over time.Therefore,China should continue to strengthen research and development aimed at improving urban carbon emission performance and achieving the national energy conservation and emission reduction goals.Meanwhile,neighboring cities with different neighborhood backgrounds should pursue cooperative economic strategies that balance economic growth,energy conservation,and emission reductions to realize low-carbon construction and sustainable development.

Evolutionary characteristics and driving factors of carbon emission performance at the city level in China

To achieve carbon peak targets,realize carbon neutrality vision,and tackle global climate change,China must improve the carbon emission performance at the city level.Based on the carbon emission performance of 191 prefecture-level cities in China from 1997 to 2017,this paper analyses the evolution characteristics of urban carbon emission performance from three aspects:the overall spatial and temporal evolution,the differences according to both region and city size,and the differences among clusters categorized by carbon emission performance at the city level.This paper also reveals the impact of the social and economic transition on China’s carbon emission performance.The results show that:(1)The overall level of carbon emission performance of Chinese cities is low,and there is a downward trend during the study period.The differences in carbon emission performance among cities are convergent,but there is a wide gap between high and low values.(2)The carbon emission performance of cities in eastern coastal areas is higher than that in non-coastal areas cities.Large urban agglomerations and economically developed regions,such as provincial capitals,are the agglomeration areas of high urban carbon emission performance values.(3)The carbon emission performance level of cities with similar sizes will converge.At the same time,such changes will enhance the differences among carbon emission performances at the city level within the same region.(4)Cities that belong to high urban carbon emission performance clusters are mainly distributed in the eastern region.Such cities are classified into large cities,supercities,and megacities.Compared with low urban carbon emission performance clusters,cities in high urban carbon emission performance clusters show a higher proportion in the medium-high level and high level of carbon emission performance.Moreover,cities in high urban carbon emission performance clusters are more likely to improve their urban carbon emission performance.(5)The economic agglomeration effect,industrial structure adjustment and carbon intensity reduction have a significant impact on improving urban carbon emission performance.Population agglomeration has an incremental effect,and the anticipated benefits of environmental regulation have yet to be fully realized.The impacts of different clusters and different regions are variable.Finally,this paper advances policy enlightenment according to its research findings.