Quantifying primary and secondary humic-like substances in urban aerosol based on emission source characterization and a source-oriented air quality model

Abstract

Abstract. Humic-like substances (HULIS) are a mixture of high-molecular-weight, water-soluble organic compounds that are widely distributed in atmospheric aerosol. Their sources are rarely studied quantitatively. Biomass burning is generally accepted as a major primary source of ambient humic-like substances (HULIS) with additional secondary material formed in the atmosphere. However, the present study provides direct evidence that residential coal burning is also a significant source of ambient HULIS, especially in the heating season in northern China based on source measurements, ambient sampling and analysis, and apportionment with source-oriented CMAQ modeling. Emission tests show that residential coal combustion produces 5 % to 24 % of the emitted organic carbon (OC) as HULIS carbon (HULISc). Estimation of primary emissions of HULIS in Beijing indicated that residential biofuel and coal burning contribute about 70 % and 25 % of annual primary HULIS, respectively. Vehicle exhaust, industry, and power plant contributions are negligible. The average concentration of ambient HULIS in PM2.5 was 7.5 µg m−3 in urban Beijing and HULIS exhibited obvious seasonal variations with the highest concentrations in winter. HULISc accounts for 7.2 % of PM2.5 mass, 24.5 % of OC, and 59.5 % of water-soluble organic carbon. HULIS are found to correlate well with K+, Cl−, sulfate, and secondary organic aerosol, suggesting its sources include biomass burning, coal combustion, and secondary aerosol formation. Source apportionment based on CMAQ modeling shows residential biofuel and coal burning and secondary formation are important sources of ambient HULIS, contributing 47.1 %, 15.1 %, and 38.9 %, respectively.

Characteristics, primary sources and secondary formation of water soluble organic aerosols in downtown Beijing

“…In this work, WSOC was further divided into its hydrophobic and hydrophilic portions. As listed in Table 1, the hydrophobic portion dominated in the total WSOC in all seasons, and also exhibited the highest proportion in summer (0.84), followed by winter (0.73), higher than the results previously reported in Beijing (Li et al, 2019a;Huang et al, 2020). The ratio of hydrophilic WSOC to total WSOC showed significant positive correlations with PM2.5 in winter (r=0.58, p<0.01), summer (r=0.48, p<0.05) and autumn (r=0.44, p<0.05), implying that the organic aerosols became more hygroscopic as pollution aggravated in these seasons (Guo et al, 2014).…”

“…Other primary combustion sources (Source 3) also contributed considerably to WSOC (14.4 %), most of which only contributed to the hydrophobic fraction (19.1 %). Recent source apportionment based on CMAQ model in North China reported that coal combustion contributed 15.1 % to watersoluble HULIS (HULISws) annually, which is the major component of hydrophobic WSOC (Li et al, 2019a). High levels of HULISws were also observed in the coal combustion smoke, again suggesting that coal combustion might be a significant source of HULISws (Fan et al, 2016).…”

Characteristics, primary sources and secondary formation of water-soluble organic aerosols in downtown Beijing

“…However, the contribution of Factor 3 to WSOC during the study period in winter was not the highest among four seasons, implying that there could be other sources beyond coal combustion included in Factor 3. Previous studies using the PMF model also found that traffic and waste burning both contributed more than 15 % to HULIS WS in Beijing Li et al, 2019b). Therefore, the mixed primary sources in Factor 3 possibly consisted of coal combustion, traffic emission, waste incineration, etc.…”

“…Previous studies have suggested that coal combustion (Zhang et al, 2018;Li et al, 2019a, b), traffic emissions (Kawamura and Kaplan, 1987;Li et al, 2019b), residual oil combustion (Kuang et al, 2015), cooking (Qiu et al, 2020), soil dust and sea salts (Huang et al, 2006) can all contribute to WSOC. However, it is most commonly recognized that WSOC mainly derives from biomass burning and SOA (Ding et al, 2008;Feng et al, 2013;Du et al, 2014;Zhang et al, 2018).…”

Estimating mean molecular weight, carbon number, and OM∕OC with mid-infrared spectroscopy in organic particulate matter samples from a monitoring network

“…Nevertheless, the extensive fragmentation caused by commonly used ionization method in AMS, i.e., electron impact (EI) ionization, makes the identification of original species difficult (Canagaratna et al, 2007;Faber et al, 2017). In recent years, soft ionization methods such as electrospray ionization (ESI), photoionization (PI), and chemical ionization (CI) have been used frequently for predicting physicochemical properties of organic aerosol (OA), e.g., volatility (Li et al, 2016;Xie et al, 2020), phase state, and viscosity (Li et al, 2020;DeRieux et al, 2018;Shiraiwa et al, 2017a), as a function of measured elemental composition and molecular weight. These methods minimize analyte fragmentation, providing better estimates of molar mass of individual molecules but often have other shortcomings such as ionization efficiency, which varies by molecule (Nozière et al, 2015;Iyer et al, 2016;Hermans et al, 2017;Lopez-Hilfiker et al, 2019).…”