欢迎访问《环境科学学报》编辑部网站！

快速检索			高级检索

研究报告

Estimation of missing stack parameters and its application in improving air quality modeling

摘要：针对源清单中部分点源烟囱参数缺失而采用源排放模型SMOKE(Sparse Matrix Operator Kernel Emissions)默认的烟囱参数对空气质量模型模拟结果造成的不利影响,综合考虑气象观测数据、空气质量监测数据、源排放强度以及相关标准和规范对烟囱设计的要求,分别基于最大落地浓度法和基于统计方法对2009年珠三角地区源清单中缺失烟囱参数点源的烟囱参数进行了估算,并将估算烟囱参数用在WRF/SMOKE-PRD/CMAQ空气质量模型系统分析其对模型模拟的改善情况.相比于采用SMOKE默认烟囱参数,基于最大落地浓度估算烟囱参数对NO₂、NO_x、SO₂、PM₁₀及O₃的模拟结果均具有一定改善作用,而基于统计方法估算烟囱参数仅对SO₂、O₃的模拟结果有所提高.结果表明,使用基于最大落地浓度法估算得到的烟囱参数更为合理,使污染物的垂直排放分配更加合理,可以应用于空气质量模型输入源清单中缺失烟囱参数点源的估算,从而一定程度上改善空气质量模型的模拟效果.

Abstract：To improve air quality modeling, two methods were developed to estimate stack parameters of some point emission sources which are currently not available in the Pearl River Delta. One method is based on the maximum ground concentration considering meteorological observations, air quality monitoring data, air pollutant emission intensity, related standards and regulations about stack design; the other is based on statistics of available point sources with known emissions and stack parameters. The estimated stack parameters were applied to the WRF/SMOKE-PRD/CMAQ modeling system to evaluate the improvement of model performance. In comparison with using the default stack parameters in the modeling system, the maximum ground concentration approach could improve simulated NO₂, NO_x, SO₂, PM₁₀ and O₃, while the statitsic approach only improved the simulation of SO₂ and O₃, with the use of estimated stack parameters. This suggested that the maximum ground concentration method is more reasonable in estimating stack parameters and thus improving vertical emission profiles of pollutants. This approach can be used to estimate missing stack parameters in the air quality modeling, and improve model perfomance to some extent.