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2018 | 27 | 4 |
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Mutual influence of energy consumption and foreign direct investment on haze pollution in China: a spatial econometric approach

Autorzy
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Based on the data of annual average values of PM₁₀ concentrations in China, this study empirically investigates the spatial autocorrelation of haze pollution in China and the mutual influence of energy consumption and foreign direct investment on haze pollution in China from 2004 to 2014 using the spatial econometric method. Moran’s I values are all above 0 during the 10 years, which indicates that haze pollution in China exists with significant spatial autocorrelation. Then the spatial econometric model estimation results show that energy consumption has a significant and positive effect on haze pollution in China while foreign direct investment has a significant and negative effect on haze pollution. Meanwhile, the regression coefficient of mutual variable of energy consumption and foreign direct investment is 0.063 at the 5% level, which suggests that foreign direct investment plays an important role in regulating the relationship between energy consumption and haze pollution, namely that the aggravation effect of energy consumption on haze pollution will increase with the increase of foreign direct investment. Finally, we provide some policy guidance for controlling haze pollution in China.
Słowa kluczowe
Wydawca
-
Rocznik
Tom
27
Numer
4
Opis fizyczny
p.1743-1752,fig.,ref.
Twórcy
autor
  • School of Business Administration, Guangdong University of Finance and Economics, Guangzhou, China
autor
  • School of Business Administration, Guangdong University of Finance and Economics, Guangzhou, China
autor
  • Public Management School, Guangdong University of Finance and Economics, Guangzhou, China
Bibliografia
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  • 3. CHENG Z., WANG S., JIANG J., FU Q., CHEN C., XU B., YU J., FU X., HAO J. Long-term trend of haze pollution and impact of particulate matter in the Yangtze River Delta, China. Environ. Pollut. 182, 101, 2013.
  • 4. VAN DONKELAAR A., MARTIN R.V., BRAUER M., KAHN R., LEVY R., VERDUZCO C., VILLENEUVE P.J. Global estimates of ambient fine particulate matter concentrations from satellite-based aerosol optical depth: development and application. Environ. Health. Persp. 118 (6), 847, 2010.
  • 5. WANG L., XU J., YANG J., ZHAO X., WEI W., CHENG D., PAN X., SU J. Understanding haze pollution over the southern Hebei area of China using the CMAQ model. Atmos. Environ. 56, 69, 2012.
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  • 8. WANG Y., YAO L., WANG L., LIU Z., JI D., TANG G., ZHANG J., SUN Y., HU B., XIN J. Mechanism for the formation of the January 2013 heavy haze pollution episode over central and eastern China. Sci. China. Earth. Sci. 57 (1), 14, 2014.
  • 9. TANG D., LI L., YANG Y. Spatial econometric model analysis of foreign direct investment and haze pollution in china. Pol. J. Environ. Stud. 25(1), 317, 2016.
  • 10. ZHA Y., GAO J., JIANG J., LU H., HUANG J. Normalized difference haze index: a new spectral index for monitoring urban air pollution. Int. J. Remote. Sens. 33 (1), 309, 2012.
  • 11. ZHANG Z., WANG J., CHEN L., CHEN X., SUN G., ZHONG N., KAN H., LU W. Impact of haze and air pollution-related hazards on hospital admissions in Guangzhou, China. Environ. Sci. Pollut. R. 21 (6), 4236, 2014.
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Typ dokumentu
Bibliografia
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