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RELATION BETWEEN AGRICULTURAL NON-POINT SOURCE POLLUTION AND AGRICULTURAL ECONOMIC GROWTH IN XINJIANG BASED ON DECOUPLING MODEL AND LMDI MODEL 
XIE Wenbao, CHEN Tong, LIU Guoyong
Resources & Industries    2018, 20 (1): 68-75.   DOI: 10.13776/j.cnki.resourcesindustries.20180212.004
Abstract127)      PDF(pc) (1380KB)(188)       Save
This paper measures ANPSP(agricultural non-point source pollution), COD, TN, TP and total emission intensity in Xinjiang from 1996—2015, analyzes the changes in emission proportion of pollutants and emission contribution rate in each pollution unit, and applies Tapio model to study their decoupling relation between ANPSP and agricultural economic growth in Xinjiang, and uses LMDI model to decompose the temporal changes of each pollutant emission. Changes in emission volume and emission intensity of ANPSP can be classified as ascending\|descending\|ascending stages with the major pollutant COD emission and the chief pollution unit livestock and poultry breeding and farmland solid wastes. The decoupling relation between ANPSP and agricultural economic growth of Xinjiang had undergone weak decoupling, negative decoupling, dilating connection and unstable stages. The scale effect, benefits effect and efficiency effect of agricultural economic growth variably influence ANPSP that scale effect has little contribution, benefits effect expands the emission of ANPSP, but blocked by efficiency effect. To downsize the pollution emission of unit agricultural production is the leading path against ANPSP in Xinjiang. 
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CHINA'S TOTAL FACTORS ENERGY EFFICIENCY UNDER ENVIRONMENTAL CONSTRAINTS BASED ON DEA TOBIT MODEL
SHEN Jianliang, RAN Qiying, CHEN Tong
Resources & Industries    2016, 18 (4): 116-121.   DOI: 10.13776/j.cnki.resourcesindustries.2016.04.018
Abstract11153)      PDF(pc) (1149KB)(10776)       Save

This paper, based on China's 29 cities' panel data, uses DEA model, at the constant scale benefits, to measure China's total factors energy efficiency under environmental constraints from 1995—2013. The result shows a declining trend from the east to the west and a rising regional gap. Foreign direct investment, GDP per capita and industrial structure have a positive influence on energy efficiency, but the capital per capita, coal consumption and governmental interference are negative. From the view of region, each factor is different in 〖JP3〗influence direction and intensity on energy efficiency in different regions. Capita per capita and coal consumption are negative and GDP per capita is positive. Industrial structure is outstanding positive in the eastern China, not outstanding in the central and western China. Foreign direct investment is not outstanding in the eastern China, outstanding positive in the central, negative in the western. Governmental interference is outstanding negative in the eastern and central, not outstanding in the western.

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