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摘要
This paper, which aims at the primary gaseous air pollutants (i.e., SO2, NOx, VOCS and CO), is the third paper in the series papers published in Atmospheric Environment to develop new emission estimation models by the regression method. A group of regression models for various industrial and non-industrial sectors were proposed based on an emission investigation case study of Handan region in northern China. The main data requirements of the regression models for industrial sectors were coal consumption, oil consumption, gaseous fuel consumption and annual industrial output. The data requirements for non-industrial sector emission estimations were the population, the number of resident population households, the vehicle population, the area of construction sites, the forestland area, and the orchard area. The models were then applied to Tangshan region in northern China. The results showed that the developed regression models had relatively satisfactory performance. The modeling errors at the regional level for SO2, NOx, VOCS and CO were -16.5%, -10.6%, -11.8% and -22.6%, respectively. The corresponding modeling errors at the county level were 39.9%, 33.9%, 46.3% and 46.9%, respectively. The models were also applied to other regions in northern China. The results revealed that the new models could develop emission inventories with generally lower error than found in previous emission inventory studies. The developed models had the advantages of only using publicly available statistical information for developing high-accuracy and high-resolution emission inventory, without requiring detailed data investigation which is necessary by conventional "bottom-up" emission inventory development approach.
- 出版日期2014-9
- 单位北京工业大学
