西宁市生物质燃烧源大气污染物排放清单

Pollutant Emission Inventory of Biomass Combustion Sources in Xining City

本研究根据调查的西宁市生物质燃烧源活动水平数据,采用排放因子方法,建立了2018年西宁市生物质燃烧源9种大气污染物的排放清单,并分析了清单的时空分布特征和不确定性.结果表明,西宁市2018年生物质燃烧源CO、NO_(x)、SO_(2)、NH_(3)、VOCs、PM_(2.5)、PM_(10)、BC和OC的排放量分别为11718.34、604.41、167.80、209.72、1617.97、2054.04、2135.04、281.07和1224.78 t.秸秆露天焚烧CO、NO_(x)、VOCs、PM_(2.5)、PM_(10)、BC和OC的排放对生物质燃烧源的排放贡献率最高;其中,秸秆露天焚烧NO_(x)、VOCs和CO的贡献率分别为72.35%、63.94%和53.18%.户用生物质炉NH_(3)和SO_(2)的排放对生物质燃烧源的贡献率最大,分别为41.49%和42.05%.生物质燃烧源大气污染物排放地区分布不均衡,主要集中于大通县和湟中区.生物质燃烧源9项污染物的排放量在1、2、3、10、11和12月较大,占比在5%~33%.蒙特卡罗模拟结果表明,在95%置信区间下,不确定度最高的是森林和草原火灾的M_(2.5)排放,不确定度为-26.71%~29.78%.

Based on the data of biomass combustion source activity level collected in Xining City and the emission factors,emission inventories of nine air pollutants from biomass combustion sources were established in Xining City in 2018,after which the temporal and spatial distribution characteristics and uncertainties of the inventory were analyzed.The results indicated that the total emissions of CO,NO_(x),SO_(2),NH_(3),VOCs,M_(2.5),M_(10),BC,and OC from biomass combustion sources in Xining City in 2018 were 11718.34,604.41,167.80,209.72,1617.97,2054.04,2135.04,281.07,and 1224.78 t,respectively.The emission contributions of CO,NO_(x),VOCs,M_(2.5),M_(10),BC,and OC from straw open burning were the highest for biomass combustion sources.Among them,the contributions of NO_(x),VOCs,and CO from straw open burning were 72.35%,63.94%,and 53.18%,respectively,and the contributions of NH_(3) and SO_(2) from household biomass furnaces were the largest,41.49%and 42.05%,respectively.The spatial distribution from biomass combustion sources was not balanced;the air pollutants were mainly concentrated in Datong County and Huangzhong District.The temporal distributions from biomass combustion sources in Xining City were relatively large in January,February,March,October,November,and December,accounting for 5%-33%.The Monte Carlo simulation results showed that,under the 95%confidence interval,the M_(2.5) emissions from forest and grassland fires had the highest uncertainty,with the uncertainty ranging from-26.71%-29.78%.