Contribution of biogenic sources to secondary organic aerosol in the summertime in Shaanxi, China

Highlights

• BVOCs concentration matched well with the vegetation coverage.

• Isoprene and its intermediate semi-volatile gases were the highest.

• BSOA accounted for 84% of SOA in Shaanxi, of which ISOP made up 67%.

• BSOA was unexpectedly high in Guanzhong.

Abstract

A revised Community Multi-scale Air Quality (CMAQ) model with updated secondary organic aerosol (SOA) yields and a more detailed description of SOA formation from isoprene (ISOP) oxidation was applied to study the spatial distribution of SOA, its components and precursors in Shaanxi in July of 2013. The emissions of biogenic volatile organic compounds (BVOCs) were generated using the Model of Emissions of Gases and Aerosols from Nature (MEGAN), of which ISOP and monoterpene (MONO) were the top two, with 1.73 × 10⁹ mol and 1.82 × 10⁸ mol, respectively. The spatial distribution of BVOCs emission was significantly correlated with the vegetation coverage distribution. ISOP and its intermediate semi-volatile gases were up to ∼7.0 and ∼1.4 ppb respectively in the ambient. SOA was generally 2–6 μg/m³, of which biogenic SOA (BSOA) accounted for as high as 84% on average. There were three main BVOCs Precursors including ISOP (58%) and MONO (8%) emit in the studied domain, and ISOP (9%) transported. The Guanzhong Plain had the highest BSOA concentrations of 3–5 μg/m³, and the North Shaanxi had the lowest of 2–3 μg/m³. More than half of BSOA was due to reactive surface uptake of ISOP epoxide (0.2–0.7 μg/m³, ∼19%), glyoxal (GLY) (0.2–0.5 μg/m³, ∼11%) and methylglyoxal (MGLY) (0.4–1.4 μg/m³, ∼32%), while the remaining was due to the traditional equilibrium partitioning of semi-volatile components (0.1–1.2 μg/m³, ∼25%) and oligomerization (0.2–0.4 μg/m³, ∼12%). Overall, SOA formed from ISOP contributed 1–3 μg/m³ (∼80%) to BSOA.

Introduction

China is suffering heavy air pollution in recent years due to rapid economic development, and PM_2.5 (airborne particles with aerodynamic diameters less than 2.5 μm) was usually the major pollutant in most regions (Wang et al., 2014b; Xu et al., 2018; Zhang and Cao, 2015). Huang et al. (2014) studied that the composition of PM_2.5 in four large representative cities (Beijing, Shanghai, Guangzhou, and Xi’an) during the heavy haze in China in 2013 and showed that secondary aerosol (SA) accounted for about 30–77% of PM_2.5 and 37.5–58.3% of SA was made up of secondary organic aerosol (SOA). It has been demonstrated that SOA in the ambient could modulate the oxidation capacity of the atmosphere (McCann et al., 2006), have important climate feedbacks (Yang et al., 1994), and impact visibility, climate, and health (Carter, 2000; Pui et al., 2014).

The formation of low-volatility (semi-volatile and nonvolatile) compounds that make up SOA is governed by a large number of volatile organic compounds (VOCs) reacting with oxidants (e.g., O₃, OH, NO₃) (Carter et al., 2012; Robinson et al., 2007), which can be absorbed into the organic fraction of particulate matter (PM) (Carter, 2000; Castro Neto and Guinea, 2009; Lobanov et al., 2006; Zhang et al., 2007). Biogenic sources (vegetation in special) emit large amounts of biogenic VOCs (BVOCs) annually in the global scale, greatly exceeding those from anthropogenic sources, and about half of the BVOCs emission is isoprene (ISOP) (Guenther et al., 1995, 2012). BVOCs emission increases during warm seasons with high insolation, often exhibiting exponential temperature dependence (Guenther et al., 1993). Lee et al. (2006) showed a rise in concentrations of ISOP from vegetation from 60 to 500 ppt when air temperature increased from 20 to 30 °C. It is demonstrated that the concentration of PM could increase with rising temperatures in densely populated areas during heat waves (Churkina et al., 2017). In a modeling study, Megaritis et al. (2013) found that a temperature increase of 2.5 °C led to a 20% increase in summertime biogenic SOA (BSOA) over the northern parts of Europe, and other studies suggested that ISOP played an important role in global and regional SOA budgets (Foley et al., 2010; Liao et al., 2007). BVOCs also have an important impact on the environment at the downwind of a city though they are mostly from forests (Dreyfus et al., 2002; Zhang et al., 2014).

Modeling analyses are typically needed to illustrate the spatial distribution and regional source apportionment of SOA. The development of reliable and effective SOA control strategies depends on models that can reliably simulate its formation. However, the SOA modules used in most studies applied the relatively simple traditional two-product approach (Ciccioli et al., 2014; Pankow, 1994) or the more complex volatility basis set (VBS) approach to represent multi-generation oxidation of SOA precursors in the gas phase and their aging processes in the aerosol phase (Hellén et al., 2012). Both assume equilibrium partitioning of semi-volatile aerosol (SEMI) products, ignoring the formation of low volatile oligomers and non-volatile compounds. Therefore, air quality models consistently underestimate ground-level SOA (Foley et al., 2010; Liao et al., 2007; Tesche et al., 2006). New findings indicate that several atmospherically important SOA precursors and formation pathways are not widely incorporated. Additions include several recently identified SOA precursors as following. The general reaction from benzene, ISOP, and sesquiterpenes (SESQ). The heterogeneous pathways include in-cloud oxidation of glyoxal (GLY) and methylglyoxal (MGLY) and glycolaldehyde (Lim et al., 2005), as well as particle-phase oligomerization (George et al., 2015). The acid enhancement of isoprene SOA (iSOA) regards to isoprene epoxydiols (IEPOX) and methacrylic acid epoxide (MAE) formed under low and high-NO_x conditions (Lin et al., 2013; Surratt et al., 2010). Adapting existing gas-phase mechanisms to SOA modeling is essential for SOA mechanism development.

Mechanistic modeling analyses of SOA formation in China were seldom reported in the literature except that Hu et al. (2017) studied the whole country, and other studies mostly focused on the Pearl River Delta region in southern China (Ciccioli et al., 2014; Li et al., 2015; Setyan et al., 2014) and eastern China (Hellén et al., 2012). Although poor urban air quality has been documented during excessively hot periods (Xu et al., 2018), the relative contribution of biogenic sources to the poor air quality episodes in northwestern China has not been quantified. As the spatial distribution of vegetation coverage in Shaanxi increases from north to south significantly (Fig. 1), the contribution of the biogenic sources to SOA and their spatial relationship can be well studied in Shaanxi.

In this study, we applied a photochemical mechanism that incorporates the most recent updates on the gas phase ISOP oxidation pathways as well as SOA formation from aerosol surface uptake processes of GLY, MGLY, IEPOX, and MAE, in addition to the traditional 2-product equilibrium partitioning approach, to study SOA formation in Shaanxi. A source-oriented version of the photochemical mechanism was used to track the formation of SOA from different precursors. The potential contribution of biogenic sources to air quality in the summertime in Shaanxi was estimated, including the spatial distribution of BVOCs emissions, the concentrations of BVOCs and their intermediate products, and the contribution of BVOCs to SOA.