Source apportionment of PM<sub>2.5</sub> in Shanghai based on hourly molecular organic markers and other source tracers

Abstract

Abstract. Identification of various sources and quantification of their contributions are a necessary step to formulating scientifically sound pollution control strategies. Receptor model is widely used in source apportionment of fine particles. However, most of the previous studies are based on traditional filter collection and lab analysis of aerosol chemical species (usually ions, elemental carbon (EC), organic carbon (OC) and elements) as inputs. In this study, we conducted robust online measurements of a range of organic molecular makers and trace elements, in addition to the major aerosol components (ions, OC and EC), in urban Shanghai in the Yangtze River Delta region, China. The large suite of molecular and elemental tracers, together with water-soluble ions, OC and EC, provide data for establishing measurement-based source apportionment methodology for PM2.5. We conducted source apportionment using positive matrix factorization (PMF) and compared PMF solutions with molecular makers added (i.e. MM-PMF) and those without organic markers. MM-PMF identified 11 types of pollution sources, with biomass burning, cooking and secondary organic aerosol (SOA) as the additional sources identified. The three sources accounted for 4.9 %, 2.6 % and 14.7 % of the total PM2.5 mass, respectively. During the whole campaign, the secondary source is an important source of atmospheric pollution, the average contribution of secondary pollution sources is as high as 63.8 % of the total PM2.5 mass. Grouping different sources to secondary and primary, we note that SOC and POC contributed 45.1 % and 54.9 %, respectively. It is worth noting that the contribution of cooking to PM2.5 mass only account for 2.6 %, but it contributed to 10.7 % of OC. Episodic analysis indicated that secondary nitrate was the always the main cause of PM2.5 pollution, while during non-episodic hours, vehicle exhaust made a significant contribution. Through the application of the above-mentioned techniques to the Yangtze River Delta, more insights are gained on the sources, formation mechanism and pollution characteristics of PM2.5 in this region.

Hourly Measurements of Organic Molecular Markers in Urban Shanghai, China: Primary Organic Aerosol Source Identification and Observation of Cooking Aerosol Aging

“…Such a high degree of similarity in PM 2.5 indicates that the two sites are influenced by the same PM pollution sources. Expectedly, PMF results in this work are essentially similar to those obtained by Li et al We refer readers to the study by Li et al for details of the PMF modeling and discussion of source apportionment results. Below we will only present PMF results related to the abovementioned POA markers.…”

“…At our monitoring site (SAES), OC and EC were not available; we thereby "borrowed" the OC and EC data from a nearby urban monitoring station, which was 12 km away (site name: Pudong). We note that a detailed source apportionment analysis utilizing the same set of organic source markers measured in this field campaign is reported in a separate paper by Li et al, 29 in combination with inorganic ions and elemental species at Pudong. 29 Between the SAES site in this work and the Pudong site, their PM 2.5 levels were in excellent agreement and highly in sync, as seen in their nearly overlapping time series, and a slope of 0.95 and a correlation coefficient of 0.96 in their scatter correlation plot (Figure S17).…”

“…The resolved sources are the secondary nitrate formation process, secondary sulfate formation process, SOA factor, vehicle exhaust, industrial emission/tire wear, industrial emission, residual oil combustion, coal combustion, dust, BB, and cooking. Among them, three factors that are dominated by OA, namely the SOA factor, BB, and cooking emissions, were only resolved by PMF due to the incorporation of the unique organic tracer data in PMF . The resolved factor profiles and time series of factor contributions to OC are shown in Figure S18.…”

“…The hourly resolution organic marker data from TAG have been demonstrated to be effective in apportioning OA sources in California , and sources of black carbon in downtown Pittsburgh . The high time-resolution data are also expected to provide information for examining the evolution of OA in the real atmospheric environment …”

“…25 The high time-resolution data are also expected to provide information for examining the evolution of OA in the real atmospheric environment. 29 In this study, we deployed a commercial TAG instrument from Aerodyne Research Inc. at an urban location in Shanghai, China, in a consecutive three-week field campaign from 9 November to 3 December, 2018, along with an array of other online aerosol instruments. A set of 72 individual organic compounds, including POA and SOA source tracers, were quantified.…”