大气污染物排放源清单不确定性定量分析方法及案例研究

Quantitative Uncertainty Analysis in Air Pollutant Emission Inventories: Methodology and Case Study

大气污染物排放源清单由于在数据收集过程中存在的不可避免的监测误差、随机误差、关键数据缺乏以及数据代表性不足等因素而具有不确定性,而排放源清单的不确定性指的是人们对排放清单的真实值缺乏认识和了解.介绍了目前大气排放源清单定量不确定性方法框架,并使用电厂NOx在线监测数据,通过实际案例量化排放源清单中的不确定性.结果表明:即使对被认为具有较高准确性的火电厂点源排放清单,案例中NOx的排放源清单来自随机误差的不确定性在±15%左右.对排放源清单的不确定性量化有助于决策者确定污染物排放削减目标的可达性和科学制定大气污染物控制策略,指导排放源清单的改进和数据收集工作.同时,对我国排放源清单开发中不确定性分析提出建议.

Air pollutant emission inventories are often uncertain due to unavoidable measurement errors, random errors, data gap, non- representativeness of sample data, and other factors. Uncertainty in emission inventories refers to the lack of knowledge of the true emissions. On the basis of introducing the current methodological framework for quantifying uncertainty in emission inventories, it is demonstrated how uncertainty in emission inventories is quantified by using a real-world case study with continuous emission monitoring NOx data of power plants. The results show that the NOx emission inventory from power plants in this case study has about ± 15% uncertainty though the inventories are generally believed to be less uncertain. Quantification of uncertainty in emission inventories helps decision-makers determine the likelihood of complying with emission reduction objectives, and more properly make air pollution control strategies. Identification of key sources of uncertainty helps guide future emission inventory improvement and further data collection. Also, suggestions are made regarding how to initiate uncertainty analysis in emission inventory development in China.