Regional carbon emission efficiency and its dynamic evolution in China: A novel cross efficiency-malmquist productivity index

Ding, Lili; Yang, Ying; Wang, Wei; Călin, Adrian Cantemir

doi:10.1016/j.jclepro.2019.118260

Cited by 78 publications

(18 citation statements)

References 35 publications

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“…Since scholars have gradually realized the importance of resources and the environment for human survival and sustainable economic development, they have incorporated the environment as an essential factor into the economic research framework. In the subsequent research, many early studies mainly investigated energy-related carbon emissions and its influencing factors (Geng et al 2013;Zhang and Da 2015), the law of Spatio-temporal evolution (Shi et al 2014;Ding et al 2019) and driving mechanism (Tian et al 2013;Jiang et al 2017). In recent years, an increasing number of studies have discussed the carbon emission reduction cost and reduction potential worldwide (Criqui et al 1999;Guo et al 2011;Chen and Xiang 2019).…”

Section: Literature Reviewmentioning

confidence: 99%

Spatio-temporal evolution characteristics and influencing factors of carbon emission reduction potential in China

Cai-jiang

2021

Environ Sci Pollut Res

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This study first attempts to use the parameterized quadratic Directional Distance Function (DDF) approach to calculate China's provincial carbon abatement cost and carbon reduction potential (CRP) under different scenarios from 2000 to 2017. Afterward, considering three different scenarios, we analyze the Spatio-temporal characteristics and the dynamic evolution pattern of CRP. We also conduct the spatial autocorrelation test and spatial Durbin model to analyze the spatial spillover effects and influencing factors of CRP. The results are obtained as follows: CRP across the three scenarios varies considerably across provinces and different-located groups. CRP higher areas are mainly located in the economically developed eastern coastal regions, while most provinces with low CRP are concentrated in the western region. The spatial autocorrelation test indicated that provinces with a similar CRP showed a significant geographic agglomeration, and the agglomeration effect was strengthened first and then weakened. Simultaneously, the local spatial distribution of MCRP, FCRP, and ECRP shows a slight spatial polarization feature. Finally, through the SDM analysis and spillover effect decomposition, we find that improvement of regional CRP not only depends on economic development, industrial structure adjustment, and energy efficiency elevation, but also involves energy structure optimization, low-carbon innovation, and population. The low-carbon innovation provides critical support for local CRP under the efficiency scenario but restrains the local CRP under the fairness scenario. Therefore, the central government should emphasize local conditions and the ex-ante scenario assessment, strengthen regional interactive governance, optimize energy efficiency, and promote the application of clean energy to enhance CRP.

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Section: Literature Reviewmentioning

confidence: 99%

Spatio-temporal evolution characteristics and influencing factors of carbon emission reduction potential in China

Cai-jiang

2021

Environ Sci Pollut Res

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“…The yield distance function at this point: D G c ðx; yÞ ¼ minfW > 0jðx; y=WÞ 2 Q G c g. The current Malmquist productivity index and the global Malmquist productivity index have one thing in common [27]. That is (x q+1 , y q+1 ) and (x q , y q ) the difference is that the two indexes are compared with different benchmarks.…”

Section: Plos Onementioning

confidence: 99%

Research on grain production efficiency in China’s main grain producing areas from the perspective of financial support

et al. 2021

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Grain production is vital to the national economy and people’s livelihood, and improving grain production efficiency is of great significance to the sustainable development of China’s economy and society. From the perspective of financial support, using the DEA global Malmquist productivity index model and based on the data of 13 main grain producing areas in China from 2001 to 2017, this paper discusses the evolution characteristics and regional distribution differences of the total factor productivity index of grain production in China’s main grain producing areas. The results show that from 2001 to 2017, the total factor productivity index of grain production in China’s main grain producing areas showed an overall fluctuation trend of gradual decline, with an average annual decline of 7.3%. From the perspective of spatial analysis, the grain production efficiency in China’s main grain producing areas is characterized by uneven spatial development, which is generally manifested as the decreasing trend from the central region to the eastern and western regions. Meanwhile, it can be seen from the decomposition index that the change of total factor productivity of grain production in China’s main grain producing areas mainly depends on the change of technical efficiency.

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“…The three RCPs, namely RCP2.6, RCP4.5, and RCP8.5, are labelled after a possible range of radiative forcing values in the year 2100. Among all scenarios, RCP 2.6 are the scenarios with low radiation propulsion patterns and consist B1 (convergence and ecologically friendly) and B2 scenarios [28] and the scenarios of RCP 8.5 show a scenario of radiative drives with high radiation propulsion patterns.…”

Section: Snow-melt Runoff Modelmentioning

confidence: 99%

Climate Change Scenarios and Effects on Snow-Melt Runoff

2020

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Climate change is an important environmental issue, as progression of melting glaciers and snow cover is sensitive to climate alteration. The aim of this research was to model climate alterations forecasts, and to assess potential changes in snow cover and snow-melt runoff under the different climate change scenarios in the case study of the Zayandeh-rud River Basin. Three cluster models for climate change (NorESM1-M, IPSL-CM5A-LR and CSIRO-MK3.6.0) were applied under RCP 8.5, 4.5 and 2.6 scenarios, to examine climate influences on precipitation and temperature in the basin. Temperature and precipitation were determined for all three scenarios for four periods of 2021-2030, 2031-2040, 2041-2050 and 2051-2060. MODIS (MOD10A1) was also applied to examine snow cover using temperature and precipitation data. The relationship between snow-covered area, temperature and precipitation was used to forecast future snow cover. For modeling future snow melt runoff, a hydrologic model of SRM was used including input data of precipitation, temperature and snow cover. The results indicated that all three RCP scenarios lead to an increase in temperature, and reduction in precipitation and snow cover. Investigation in snowmelt runoff throughout the observation period (November 1970 to May 2006) showed that most of annual runoff is derived from snow melting. Maximum snowmelt runoff is generated in winter. The share of melt water in the autumn and spring runoff is estimated at 35 and 53%, respectively. The results of this study can assist water manager in making better decisions for future water supply.

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Regional carbon emission efficiency and its dynamic evolution in China: A novel cross efficiency-malmquist productivity index

Cited by 78 publications

References 35 publications

Spatio-temporal evolution characteristics and influencing factors of carbon emission reduction potential in China

Spatio-temporal evolution characteristics and influencing factors of carbon emission reduction potential in China

Research on grain production efficiency in China’s main grain producing areas from the perspective of financial support

Climate Change Scenarios and Effects on Snow-Melt Runoff

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