西南背景区冬、夏季黑碳稳定碳同位素组成及来源

为确定中国西南背景区不同季节细颗粒物中黑碳的浓度水平和来源特征,分别于2018年冬季(1月)和夏季(7月)在贵州普定喀斯特生态系统观测研究站采集细颗粒物样品,测定其水溶性离子成分、黑碳浓度及稳定碳同位素组成(δ¹³C_BC),结合贝叶斯模型探讨黑碳来源贡献。结果表明,采样期间黑碳冬季平均浓度为(1.2±0.6)μg/m³,夏季为(1.9±0.6)μg/m³,接近于其他区域背景点浓度水平。δ¹³C_BC平均值冬季为(-23.4±0.9)‰,夏季为(-24.3±0.8)‰,处于煤燃烧及机动车排放来源的δ¹³C值范围。贝叶斯模型结果表明,机动车尾气在冬、夏季节对黑碳贡献较高,分别为(45.1±14.2)%和(69.5±8.6)%,煤燃烧贡献分别为(41.7±9.8)%和(24.1±7.2)%。结合后向轨迹分析结果可知,西南背景区冬季黑碳来源受燃煤、机动车尾气排放及生物质燃烧共同影响;夏季黑碳污染源主要为机动车尾气和煤燃烧,生物质燃烧较少。

Stable carbon isotopic composition and sources of black carbon during winter and summer in Southwest China

To determine the concentration levels and sources apportionment of black carbon(BC)in different seasons in the background area of Southwest China,fine particulate matter samples were collected in winter(January)and summer(July)of 2018 in Puding County,Guizhou Province.Then the water-soluble ion composition,black carbon concentration,and its stable carbon isotope composition in the fine particulate matter were determined.The sources contribution of black carbon was discussed with the Bayesian model.According to the results,the average concentrations of black carbon were(1.2±0.6)μg/m³ and(1.9±0.6)μg/m³ in winter and summer,respectively,both of which are close to the concentration levels of background points in other regions.The average values of δ¹³CBC were(?23.4±0.9)‰ and(?24.3±0.8)‰ in winter and summer,respectively,which fall in the range of δ¹³CBC value of coal combustion and vehicle emission sources.The results of the Bayesian model showed that the contribution of vehicle exhaust to black carbon was the highest,accounting for(45.1±14.2)% and(69.5±8.6)% in winter and summer,respectively.The contributions of coal combustion were(41.7±9.8)% and(24.1±7.2)% in winter and summer,respectively.Combined with the results of backward trajectory analysis,in Puding,the major sources of black carbon were coal combustion,vehicle exhaust emission,and biomass combustion in winter;in summer,vehicle exhaust and coal combustion were still the major resources,whereas biomass combustion contributed less.