Chemical characteristics and source apportionment of PM2.5 using PMF modelling coupled with 1-hr resolution online air pollutant dataset for Linfen, China. (August 2020)

• Record Type: Journal Article
• Authors: Li, Yafei; Liu, Baoshuang; Xue, Zhigang; Zhang, Yufen; Sun, Xiaoyun; Song, Congbo; Dai, Qili; Fu, Ruichen; Tai, Yonggang; Gao, Jinyu; Zheng, Yajun; Feng, Yinchang
• Is Part Of: Environmental pollution. Volume 263(2020)Supplement Part B
• Publication Date: 2020-08
• Subjects: PM2.5 -- Online monitoring -- Positive matrix factorisation -- Source apportionment -- Principal component analysis; Pollution -- Periodicals; Pollution -- Environmental aspects -- Periodicals; Environmental Pollution -- Periodicals; Pollution -- Périodiques; Pollution -- Aspect de l'environnement -- Périodiques; Pollution -- Effets physiologiques -- Périodiques; Pollution; Pollution -- Environmental aspects; Periodicals; Electronic journals; 363.73
• DOI: 10.1016/j.envpol.2020.114532
• Languages: English
• ISSNs: 0269-7491

Abstract

Abstract: The chemical species in PM2.5 and air pollutant concentration data with 1-hr resolution were monitored synchronously between 15 November 2018 and 20 January 2019 in Linfen, China, which were analysed for multiple temporal patterns, and PM2.5 source apportionment using positive matrix factorisation (PMF) modelling coupled with online chemical species data was conducted to obtain the apportionment results of distinct temporal patterns. The mean concentration of PM2.5 was 124 μg/m 3 during the heating period, and NO3 − and organic carbon (OC) were the dominant species. The concentrations and percentages of NO3 −, SO4 2−, and OC increased notably during the growth periods of haze events, thereby indicating secondary particle formation. Six factors were identified by the PMF model during the heating period, including vehicular emissions (VE: 26.5%), secondary nitrate (SN: 16.5%), coal combustion and industrial emissions (CC&IE: 25.7%), secondary sulfate and secondary organic carbon (SS&SOC: 24.4%), biomass burning (BB: 1.0%), and crustal dust (CD: 5.9%). The primary sources of PM2.5 on clean days were CD (33.3%), VE (23.1%), and SS&SOC (20.6%), while they were CC&IE (32.9%) and SS&SOC (28.3%) during the haze events. The contributions of secondary sources and CC&IE increased rapidly during the growth periods of haze events, while that of CD increased during the dissipation period. Diurnal variations in the contribution of secondary sources were mainly related to the accumulation and transformation of corresponding gaseous precursors. In comparison, contributions of CC&IE and VE varied as a function of the domestic heating load and peak levels occurred during the morning and evening rush hours. High contributions of major sources (CC&IE and SS&SOC) during haze events originated mainly from the north and south, while high contribution of a major source (CD) on clean days was from the northwest. Graphical abstract: Image 1 Highlights: Temporal patterns for species and sources of PM2.5 along with gaseous pollutants were discussed. Sources contributions on clean days, and in haze events and different haze stages were analysed. Secondary sources, coal combustion, industrial emissions were primary sources in haze events. High impact of crustal dust was found on clean days and in the dissipation stages of haze events. Abstract : Source apportionment of PM2.5 using a positive matrix factorisation (PMF) model coupled with 1–hr resolution online air pollutant dataset, and applied in a most polluted city of China.