China experienced severe haze pollution in January 2013. Here we have a detailed characterization of the sources and evolution mechanisms of this haze pollution with a focus on four haze episodes that occurred during 10-14 January in Beijing. The main source of data analyzed is from submicron aerosol measurements by an Aerodyne Aerosol Chemical Speciation Monitor. The average PM1 mass concentration during the four haze episodes ranged from 144 to 300 μg m À3, which was more than 10 times higher than that observed during clean periods. All submicron aerosol species showed substantial increases during haze episodes with sulfate being the largest. Secondary inorganic species played enhanced roles in the haze formation as suggested by their elevated contributions during haze episodes. Positive matrix factorization analysis resolved six organic aerosol (OA) factors including three primary OA (POA) factors from traffic, cooking, and coal combustion emissions, respectively, and three secondary OA (SOA) factors. Overall, SOA contributed 41-59% of OA with the rest being POA. Coal combustion OA (CCOA) was the largest primary source, on average accounting for 20-32% of OA, and showed the most significant enhancement during haze episodes. A regional SOA (RSOA) was resolved for the first time which showed a pronounced peak only during the record-breaking haze episode (Ep3) on 12-13 January. The regional contributions estimated based on the steep evolution of air pollutants were found to play dominant roles for the formation of Ep3, on average accounting for 66% of PM1 during the peak of Ep3 with sulfate, CCOA, and RSOA being the largest fractions (>~75%). Our results suggest that stagnant meteorological conditions, coal combustion, secondary production, and regional transport are four main factors driving the formation and evolution of haze pollution in Beijing during wintertime.
Air pollution is a major environmental concern during all seasons in the megacity of Beijing, China. Here we present the results from a winter study that was conducted from 21 November 2011 to 20 January 2012 with an Aerodyne Aerosol Chemical Speciation Monitor (ACSM) and various collocated instruments. The non-refractory submicron aerosol (NR-PM1) species vary dramatically with clean periods and pollution episodes alternating frequently. Compared to summer, wintertime submicron aerosols show much enhanced organics and chloride, which on average account for 52% and 5%, respectively, of the total NR-PM1 mass. All NR-PM1 species show quite different diurnal behaviors between summer and winter. For example, the wintertime nitrate presents a gradual increase during daytime and correlates well with secondary organic aerosol (OA), indicating a dominant role of photochemical production over gas–particle partitioning. Positive matrix factorization was performed on ACSM OA mass spectra, and identified three primary OA (POA) factors, i.e., hydrocarbon-like OA (HOA), cooking OA (COA), and coal combustion OA (CCOA), and one secondary factor, i.e., oxygenated OA (OOA). The POA dominates OA during wintertime, contributing 69%, with the other 31% being SOA. Further, all POA components show pronounced diurnal cycles with the highest concentrations occurring at nighttime. CCOA is the largest primary source during the heating season, on average accounting for 33% of OA and 17% of NR-PM1. CCOA also plays a significant role in chemically resolved particulate matter (PM) pollution as its mass contribution increases linearly as a function of NR-PM1 mass loadings. The SOA, however, presents a reverse trend, which might indicate the limited SOA formation during high PM pollution episodes in winter. The effects of meteorology on PM pollution and aerosol processing were also explored. In particular, the sulfate mass is largely enhanced during periods with high humidity because of fog processing of high concentration of precursor SO2. In addition, the increased traffic-related HOA emission at low temperature is also highlighted
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.