[Micro-simulation of firms' heterogeneity on pollution intensity and regional characteristics].
In the same industrial sector, heterogeneity of pollution intensity exists among firms. There are some errors if using sector's average pollution intensity, which are calculated by limited number of firms in environmental statistic database to represent the sector's regional economic-environmental status. Based on the production function which includes environmental depletion as input, a micro-simulation model on firms' operational decision making is proposed. Then the heterogeneity of firms' pollution intensity can be mechanically described. Taking the mechanical manufacturing sector in Deyang city, 2005 as the case, the model's parameters were estimated. And the actual COD emission intensities of environmental statistic firms can be properly matched by the simulation. The model's results also show that the regional average COD emission intensity calculated by the environmental statistic firms (0.002 6 t per 10 000 yuan fixed asset, 0.001 5 t per 10 000 yuan production value) is lower than the regional average intensity calculated by all the firms in the region (0.003 0 t per 10 000 yuan fixed asset, 0.002 3 t per 10 000 yuan production value). The difference among average intensities in the six counties is significant as well. These regional characteristics of pollution intensity attribute to the sector's inner-structure (firms' scale distribution, technology distribution) and its spatial deviation.
Zhao
Nan
N
Department of Environmental Science and Engineering, Tsinghua University, Beijing 100084, China. zhaon@mails.tsinghua.edu.cn
Liu
Yi
Y
Chen
Ji-Ning
JN
D003198:Computer Simulation; D004784:Environmental Monitoring / Q000379:methods*; D004787:Environmental Pollution / Q000191:economics / Q000517:prevention & control / Q000706:statistics & numerical data*; D007220:Industrial Waste / Q000032:analysis; D008962:Models, Theoretical; D009930:Organic Chemicals / Q000032:analysis*; D018505:Waste Management / Q000191:economics / Q000379:methods / Q000706:statistics & numerical data*
D007220:Industrial Waste; D009930:Organic Chemicals