z-logo
open-access-imgOpen Access
An Empirical Study on the Identification of Driving Factors for Two Types of Typical Atmospheric Pollutant Emissions from Power Generation in China
Author(s) -
Kun Xiao,
Jingdong Zhang
Publication year - 2019
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/358/2/022051
Subject(s) - pollutant , air pollution , electricity generation , environmental economics , environmental science , china , driving factors , air pollutants , empirical research , criteria air contaminants , environmental engineering , greenhouse gas , pollution , power (physics) , natural resource economics , economics , chemistry , physics , philosophy , organic chemistry , epistemology , quantum mechanics , ecology , political science , law , biology
Emission of air pollutants from the power generation industry is a major cause for severe air pollution prevention in China. Identifying the important driving factors of air pollutant emissions from power generation, and evaluating the importance of these factors are of great significance to formulate air pollution prevention policies. Based on the classic STIRPAT model, this paper expands the indexes of relevant economic, social and technical factors, and creatively takes the input of power generation environmental protection facilities as an important technical factor to evaluate the contribution of these factors to two typical air pollutants (SO2 and smoke dust) of power generation. The empirical study results show that the indicators of economic, social and technical factors proposed and expanded in this paper are significant and effective, and “annual operating cost of industrial waste gas treatment facilities”, “power consumption intensity of secondary industry” and “power generation structure” are the variables that have the strongest impact on the emission of two typical air pollutants of power generation. These empirical study results provide scientific guidance for further policy making.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here