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Currently, the hazy weather in China is increasingly serious. It is urgent for China to reduce haze emissions in environmental governance. A feasible way is to control haze emissions by optimizing the input sources. This paper proposed an innovative method in which the haze emission is controlled by readjusting input indicators. The output efficiency of input indicators in 29 provinces in China is calculated through 7 input indicators (namely, SO emissions, NO emissions, soot emissions, coal consumption, car ownership, capital, and labor force) as well as GDP (desirable output) and PM emissions (undesirable output). The results showed that the input indicators are excessive in redundancy on condition that PM emissions and GDP are equal. The input indicators are high in redundancy rate except labor force. The redundancy rates of soot emissions, SO emissions and coal consumption are relatively high and, respectively, are 78, 67.18, and 61.14%. Moreover, all the provinces are redundant in inputs except Beijing, Tianjin, and Shanghai which are optimal in input-output efficiency. The redundancy of middle and western provinces, such as Ningxia, Guizhou, and Shanxi, is relatively large. The ideas and methods proposed in this paper can provide a reference for the future researches that aim to reduce the input indicators of undesirable output, and the empirical results can provide empirical support for the PM abatement in China. [ABSTRACT FROM AUTHOR]

To improve the air pollution of China fundamentally, effective measures should be proposed based on the thorough understanding of the characteristics of air pollution. Based on spatial econometrics, this paper investigates the characteristics and analyzes the determinants of the spatial concentration of PM pollution in China. Results show that: (1) PM pollution is highly concentrated in Central and Eastern China, covering 17 regions which accounts for 75% of the total population and GDP (gross domestic product). (2) The PM values in China show a significant spatial correlation. Provinces such as Shandong, Henan, Anhui, and Hubei are high in PM2.5 concentration. Meanwhile, these provinces are high in population density, GDP, and coal consumptions and have a large amount of civilian cars. (3) PM pollution shows spatial spillover effects. A 1% increase in the PM values of neighboring provinces will lead to a 0.78% increase in that of one province. (4) An upward U-shaped relationship is observed between the density of per capita GDP and PM, and the PM value is far from the turning point of growth. With the further growth of the density of per capita GDP, the PM value is expected to increase rapidly and continuously. (5) Based on the characteristics of spatial concentration and spatial spillover, this paper proposes several prevention-control measures for haze pollution, such as stressing on the treatment of air pollution in severely polluted provinces, avoiding moving pollution industries to neighboring areas, performing joint prevention and control nationwide. Air pollution may only be rooted by transforming the pattern of economic growth. [ABSTRACT FROM AUTHOR]

This paper introduces the computable general equilibrium (CGE) model into the comprehensive economic loss assessment due to rainstorm, using Beijing as an example. The article has constructed a regional storm disaster CGE model to measure the impacts made by rainstorm occurence on sectors and the whole economic system by adding four disaster impact parameters corresponding to the four most affected sectors. The evaluation results show that the torrential rain on July 21 of 2012 in Beijing has caused a total of more than 27 billion RMB of indirect economic loss, which is much more than 11.64 billion RMB of direct economic loss, and on the other hand, we find that, although the rainstorm has brought immense losses to multiple economic departments, it stimulates the increase of social employment rate and investment in fixed assets. [ABSTRACT FROM AUTHOR]