Aerosol Mass Spectrometer Measurements Research Articles

Cooking emissions are a major source of racial-ethnic air pollution exposure disparities in the United States

Racial-ethnic minority populations in the US are disproportionately exposed to airborne fine particulate matter (PM2.5), but few national studies have focused individually on the sources that contribute to these disparities. We address this gap by conducting a comprehensive analysis of PM2.5 exposure disparities by race-ethnicity in the US, focusing on three source-categories: mobile-sources, cooking, and all other sources combined. Our approach is based on high-resolution, national land-use regression estimates of source-resolved PM2.5 components, derived from high-resolution aerosol mass spectrometer measurements. We find that each of these sources contributes approximately one-third of the overall PM2.5 exposure disparities by race-ethnicity. While the importance of mobile-source tailpipe emissions is well recognized, our study underscores the significance of cooking emissions in creating PM2.5 exposure disparities. This finding represents a potentially significant opportunity to reduce these disparities, as cooking emissions are currently largely unregulated. It has important implications for policymakers and public health advocates aiming to address the persistent issue of racial-ethnic disparities in air pollution.

Insights into characteristics and formation mechanisms of secondary organic aerosols in the Guangzhou urban area

Abstract. Emission controls have substantially brought down aerosol pollution in China; however, aerosol mass reductions have slowed down in recent years in the Pearl River Delta (PRD) region, where secondary organic aerosol (SOA) formation poses a major challenge for air quality improvement. In this study, we characterized the roles of SOA in haze formation in urban Guangzhou in the PRD using year-long aerosol mass spectrometer measurements for the first time and discussed possible pathways of SOA formations. On average, organic aerosols (OA) contribute dominantly (50 %) to nonrefractory submicron aerosol mass (NR-PM1). The average mass concentration of SOA (including by less- and more-oxidized OA, LOOA and MOOA) contributed most to NR-PM1, reaching about 1.7 times that of primary organic aerosols (POA, including hydrocarbon-like and cooking-related OA) and accounting for 32 % of NR-PM1, even more than sulfate (22 %) and nitrate (16 %). Seasonal variations of NR-PM1 revealed that haze-formation mechanisms differed much among distinct seasons. Sulfate mattered more than nitrate in fall, while nitrate was more important than sulfate in spring and winter, with SOA contributing significantly to haze formations in all the seasons. Daytime SOA formation was weak in winter under low oxidant levels and air relative humidity, whereas prominent daytime SOA formation was observed in fall, spring and summer almost on a daily basis, suggesting important roles of photochemistry in SOA formations. Further analysis showed that the coordination of gas-phase photochemistry and subsequent aqueous-phase reactions likely played significant roles in quick daytime SOA formations. Obvious nighttime SOA formations were also frequently observed in spring, fall and winter, and it was found that daytime and nighttime SOA formations together had resulted in the highest SOA concentrations in these seasons and contributed substantially to severe haze formations. Simultaneous increases in nitrate with SOA after sunset suggested the important roles of NO3 radical chemistry in nighttime SOA formations, and this was further confirmed by a continuous increase in the NO+ / NO2+ fragment ratio that related to measured particulate nitrate after sunset. The findings of this study have promoted our understanding of haze pollution characteristics of the PRD and laid down future directions for investigations of SOA-formation mechanisms in urban areas of southern China that share similar emission sources and meteorological conditions.

Insights into the compositional differences of PM1 and PM2.5 from aerosol mass spectrometer measurements in Beijing, China

Aerosol mass spectrometers (AMS) have been widely used for characterization of submicron aerosol (PM1) species in the world. However, the chemical differences between PM1 and fine particles (PM2.5) in megacities are poorly understood. Here a PM1 high-resolution AMS with standard vaporizer (SV) and a PM2.5 time-of-flight aerosol chemical speciation monitor (ToF-ACSM) with capture vaporizer (CV) were deployed simultaneously in summer and winter in Beijing, China, and the chemical differences of non-refractory aerosol species between PM1 and PM2.5 were characterized. Our results showed that aerosol species in PM2.5 were overall highly correlated with those in PM1 (r2 > 0.8), yet the PM1/PM2.5 ratios varied largely for different aerosol species. Nitrate existed dominantly in PM1 (80–90%), while a considerable fraction of sulfate (30–45%) was observed in the range of 1–2.5 μm (PM1–2.5). Comparatively, PM1 organics showed higher fractions in PM2.5 in summer than winter (∼70%). The changes in PM1/PM2.5 ratios of secondary inorganic aerosol (SIA) depended strongly on relative humidity (RH) in summer with considerable decreases as the increase of RH, while such a RH dependence of PM1/PM2.5 ratios was not significant in winter due to the absence of high RH data. We further compared the source apportionment results of organic aerosol (OA) between PM1 and PM2.5. Similar to previous studies, the SV AMS reported ubiquitously higher primary OA than the CV ToF-ACSM, nearly by a factor of 2 for cooking OA, and the difference in secondary OA composition can be substantial, particularly in winter. With the simultaneous measurements of AMS and ACSM, a parameterized relationship between oxygen-to-carbon (O/C) ratio and CV f44 (fraction of m/z 44 in OA) in summer and winter was developed, which has a potential implication for studying the oxidation and hygroscopicity properties of OA considering the rapid increases in CV ToF-ACSM measurements worldwide.

Molecular tracers, mass spectral tracers and oxidation of organic aerosols emitted from cooking and fossil fuel burning sources

Secondary organic aerosol (SOA) composes a substantial fraction of atmospheric particles, yet the formation and aging mechanism of SOA remains unclear. Here we investigate the initial oxidation of primary organic aerosol (POA) and further aging of SOA in winter Beijing by using aerosol mass spectrometer (AMS) measurements along with offline molecular tracer analysis. Multilinear engine (ME-2) source apportionment was conducted to capture the characteristic of source-related SOA, and connect them with specific POA. Our results show that urban cooking and fossil fuel burning sources contribute significantly (17 % and 20 %) to total organic aerosol (OA) in winter Beijing. Molecular tracer analysis by two-dimensional gas chromatography-time-of-flight mass spectrometer (GC × GC-ToF-MS) reveals that cooking SOA (CSOA) is produced through both photooxidation and aqueous-phase processing, while less oxidized SOA (LO-SOA) is the photooxidation product of fossil fuel burning OA (FFOA) and may experience aqueous-phase aging to form more-oxidized oxygenated OA (MO-OOA). Furthermore, CHOm/z 69 and CHOm/z 85 are mass spectral tracers indicating the initial photooxidation, while CHO2+ and C2H2O2+ imply further aqueous-phase aging of OA. Tracer analysis indicates that the formation of diketones is involved in the initial photooxidation of POA, while the formation of glyoxal and diacids is involved in the further aqueous-phase aging of SOA.

Quantification of primary and secondary organic aerosol sources by combined factor analysis of extractive electrospray ionisation and aerosol mass spectrometer measurements (EESI-TOF and AMS)

Abstract. Source apportionment studies have struggled to quantitatively link secondary organic aerosols (SOAs) to their precursor sources due largely to instrument limitations. For example, aerosol mass spectrometer (AMS) provides quantitative measurements of the total SOA fraction but lacks the chemical resolution to resolve most SOA sources. In contrast, instruments based on soft ionisation techniques, such as extractive electrospray ionisation mass spectrometry (EESI, e.g. the EESI time-of-flight mass spectrometer, EESI-TOF), have demonstrated the resolution to identify specific SOA sources but provide only a semi-quantitative apportionment due to uncertainties in the dependence of instrument sensitivity on molecular identity. We address this challenge by presenting a method for positive matrix factorisation (PMF) analysis on a single dataset which includes measurements from both AMS and EESI-TOF instruments, denoted “combined PMF” (cPMF). Because each factor profile includes both AMS and EESI-TOF components, the cPMF analysis maintains the source resolution capability of the EESI-TOF while also providing quantitative factor mass concentrations. Therefore, the bulk EESI-TOF sensitivity to each factor can also be directly determined from the analysis. We present metrics for ensuring that both instruments are well represented in the solution, a method for optionally constraining the profiles of factors that are detectable by one or both instruments, and a protocol for uncertainty analysis. As a proof of concept, the cPMF analysis was applied to summer and winter measurements in Zurich, Switzerland. Factors related to biogenic and wood-burning-derived SOAs are quantified, as well as POA sources such as wood burning, cigarette smoke, cooking, and traffic. The retrieved EESI-TOF factor-dependent sensitivities are consistent with both laboratory measurements of SOA from model precursors and bulk sensitivity parameterisations based on ion chemical formulae. The cPMF analysis shows that, with the standalone EESI-TOF PMF, in which factor-dependent sensitivities are not accounted for, some factors are significantly under- or overestimated. For example, when factor-dependent sensitivities are not considered in the winter dataset, the SOA fraction is underestimated by ∼25 % due to the high EESI-TOF sensitivity to components of primary biomass burning such as levoglucosan. In the summer dataset, where both SOA and total OA are dominated by monoterpene oxidation products, the uncorrected EESI-TOF underestimates the fraction of daytime SOA relative to nighttime SOA (in which organonitrates and less oxygenated CxHyOz molecules are enhanced). Although applied here to an AMS and EESI-TOF pairing, cPMF is suitable for the general case of a multi-instrument dataset, thereby providing a framework for exploiting semi-quantitative, high-resolution instrumentation for quantitative source apportionment.

The effect of the averaging period for PMF analysis of aerosol mass spectrometer measurements during offline applications

Abstract. Offline aerosol mass spectrometer (AMS) measurements can provide valuable information about ambient organic aerosols in areas and periods in which online AMS measurements are not available. However, these offline measurements have a low temporal resolution, as they are based on filter samples usually collected over 24 h. In this study, we examine whether and how this low time resolution affects source apportionment results. We used a five-month period (November 2016–March 2017) of online measurements in Athens, Greece, and performed positive matrix factorization (PMF) analysis to both the original dataset, which consists of 30 min measurements, and to time averages from 1 up to 24 h. The 30 min results indicated that five factors were able to represent the ambient organic aerosol (OA): a biomass burning organic aerosol factor (BBOA), which contributed 16 % of the total OA; hydrocarbon-like OA (HOA) (29 %); cooking OA (COA) (20 %); more-oxygenated OA (MO-OOA) (18 %); and less-oxygenated OA (LO-OOA) (17 %). Use of the daily averages resulted in estimated average contributions that were within 8 % of the total OA compared with the high-resolution analysis for the five-month period. The most important difference was for the BBOA contribution, which was overestimated (25 % for low resolution versus 17 % for high resolution) when daily averages were used. The estimated secondary OA varied from 35 % to 28 % when the averaging interval varied between 30 min and 24 h. The high-resolution results are expected to be more accurate, both because they are based on much larger datasets and because they are based on additional information about the temporal source variability. The error for the low-resolution analysis was much higher for individual days, and its results for high-concentration days in particular are quite uncertain. The low-resolution analysis introduces errors in the determined AMS profiles for the BBOA and LO-OOA factors but determines the rest relatively accurately (theta angle around 10∘ or less).

Quantification of primary and secondary organic aerosol sources by combined factor analysis of extractive electrospray ionisation and aerosol mass spectrometer measurements (EESI-TOF and AMS)

Quantification of primary and secondary organic aerosol sources by combined factor analysis of extractive electrospray ionisation and aerosol mass spectrometer measurements (EESI-TOF and AMS)

Hygroscopicity and CCN potential of DMS-derived aerosol particles

Abstract. Dimethyl sulfide (DMS) is emitted by phytoplankton species in the oceans and constitutes the largest source of naturally emitted sulfur to the atmosphere. The climate impact of secondary particles, formed through the oxidation of DMS by hydroxyl radicals, is still elusive. This study investigates the hygroscopicity and cloud condensation nuclei activity of such particles and discusses the results in relation to their chemical composition. We show that mean hygroscopicity parameters, κ, during an experiment for particles of 80 nm in diameter range from 0.46 to 0.52 or higher, as measured at both sub- and supersaturated water vapour conditions. Ageing of the particles leads to an increase in κ from, for example, 0.50 to 0.58 over the course of 3 h (Exp. 7). Aerosol mass spectrometer measurements from this study indicate that this change most probably stems from a change in chemical composition leading to slightly higher fractions of ammonium sulfate compared to methanesulfonic acid (MSA) within the particles with ageing time. Lowering the temperature to 258 K increases κ slightly, particularly for small particles. These κ values are well comparable to previously reported model values for MSA or mixtures between MSA and ammonium sulfate. Particle nucleation and growth rates suggest a clear temperature dependence, with slower rates at cold temperatures. Quantum chemical calculations show that gas-phase MSA clusters are predominantly not hydrated, even at high humidity conditions, indicating that their gas-phase chemistry should be independent of relative humidity.

Secondary Organic Aerosol Mass Yields from NO3 Oxidation of α-Pinene and Δ-Carene: Effect of RO2 Radical Fate.

Dark chamber experiments were conducted to study the SOA formed from the oxidation of α-pinene and Δ-carene under different peroxy radical (RO2) fate regimes: RO2 + NO3, RO2 + RO2, and RO2 + HO2. SOA mass yields from α-pinene oxidation were <1 to ∼25% and strongly dependent on available OA mass up to ∼100 μg m-3. The strong yield dependence of α-pinene oxidation is driven by absorptive partitioning to OA and not by available surface area for condensation. Yields from Δ-carene + NO3 were consistently higher, ranging from ∼10-50% with some dependence on OA for <25 μg m-3. Explicit kinetic modeling including vapor wall losses was conducted to enable comparisons across VOC precursors and RO2 fate regimes and to determine atmospherically relevant yields. Furthermore, SOA yields were similar for each monoterpene across the nominal RO2 + NO3, RO2 + RO2, or RO2 + HO2 regimes; thus, the volatility basis sets (VBS) constructed were independent of the chemical regime. Elemental O/C ratios of ∼0.4-0.6 and nitrate/organic mass ratios of ∼0.15 were observed in the particle phase for both monoterpenes in all regimes, using aerosol mass spectrometer (AMS) measurements. An empirical relationship for estimating particle density using AMS-derived elemental ratios, previously reported in the literature for non-nitrate containing OA, was successfully adapted to organic nitrate-rich SOA. Observations from an NO3- chemical ionization mass spectrometer (NO3-CIMS) suggest that Δ-carene more readily forms low-volatility gas-phase highly oxygenated molecules (HOMs) than α-pinene, which primarily forms volatile and semivolatile species, when reacted with NO3, regardless of RO2 regime. The similar Δ-carene SOA yields across regimes, high O/C ratios, and presence of HOMs, suggest that unimolecular and multistep processes such as alkoxy radical isomerization and decomposition may play a role in the formation of SOA from Δ-carene + NO3. The scarcity of peroxide functional groups (on average, 14% of C10 groups carried a peroxide functional group in one test experiment in the RO2 + RO2 regime) appears to rule out a major role for autoxidation and organic peroxide (ROOH, ROOR) formation. The consistently substantially lower SOA yields observed for α-pinene + NO3 suggest such pathways are less available for this precursor. The marked and robust regime-independent difference in SOA yield from two different precursor monoterpenes suggests that in order to accurately model SOA production in forested regions the chemical mechanism must feature some distinction among different monoterpenes.

Chemical composition, sources and optical properties of nitrated aromatic compounds in fine particulate matter during winter foggy days in Nanjing, China

Functionalized aromatic compounds are one of the most important light-absorbing organic chromophores – so-called brown carbon (BrC) – in fine particulate matter (PM2.5). In this study, we conducted a wintertime field campaign to measure eight nitrated aromatic compounds (NACs) in PM2.5 with offline analysis techniques, including liquid chromatograph mass spectrometer (LC-MS) and aerodyne high-resolution aerosol mass spectrometer (AMS) measurements, during foggy and nonfoggy days in suburban Nanjing in the Yangtze River Delta region, China. On average, 4-nitrophenol could be one of the most important light absorbing materials in the observed BrC, which accounted for over 40% of the mass concentration of identified chromophores. The mass concentration of 2-methyl-4-nitrophenol and 2,6-dimethyl-4-nitrophenol were evidently increased during foggy days, contribution of which to total NACs were increased by 10% and 5%, respectively. Positive matrix factorization analysis of combining LC-MS and AMS dataset was performed to identify the primary and secondary sources of NACs. Primary sources, e.g., traffic and solid-fuel combustion, accounted for 71% of the sum of 4-nitrophenol, 2,6-dimethyl-4-nitrophenol and 3-nitrosalicylic acid, suggesting important contribution of primary emissions to these NACs. The contribution of secondary sources, associated with two oxygenated organic aerosols, could contribute 66% to 4-nitrophenol, reflecting the link of such nitrated aromatic compounds to secondary organic aerosol source. Together with optical measurements, 4-nitrophenol presented a high contribution (>50%) to the identified BrC absorbance in the light range 250 and 550 nm was observed. This could highlight an important role of such NACs in ambient BrC light absorption, despite its mass contribution to total organic carbon was negligible. Our work could improve the understanding of the links between optical properties and chemical composition of BrC, and the difference between BrC chromophores from nonfoggy days and foggy days under the typical polluted atmospheric conditions.

Contrasting effects of secondary organic aerosol formations on organic aerosol hygroscopicity

Abstract. Water uptake abilities of organic aerosol under sub-saturated conditions play critical roles in direct aerosol radiative effects and atmospheric chemistry; however, field characterizations of the organic aerosol hygroscopicity parameter κOA under sub-saturated conditions remain limited. In this study, a field campaign was conducted to characterize κOA at a relative humidity of 80 % with hourly time resolution for the first time in the Pearl River Delta region of China. Observation results show that, during this campaign, secondary organic aerosol (SOA) dominated total organic aerosol mass (mass fraction &gt; 70 % on average), which provides a unique opportunity to investigate influences of SOA formation on κOA. Results demonstrate that the commonly used organic aerosol oxidation level parameter O/C was weakly correlated with κOA and failed to describe the variations in κOA. However, the variations in κOA were well reproduced by mass fractions of organic aerosol factor resolved based on aerosol mass spectrometer measurements. The more oxygenated organic aerosol (MOOA) factor, exhibiting the highest average O/C (∼ 1) among all organic aerosol factors, was the most important factor driving the increase in κOA and was commonly associated with regional air masses. The less oxygenated organic aerosol (LOOA; average O/C of 0.72) factor revealed strong daytime production, exerting negative effects on κOA. Surprisingly, the aged biomass burning organic aerosol (aBBOA) factor also formed quickly during daytime and shared a similar diurnal pattern with LOOA but had much lower O/C (0.39) and had positive effects on κOA. The correlation coefficient between κOA and mass fractions of aBBOA and MOOA in total organic aerosol mass reached above 0.8. The contrasting effects of LOOA and aBBOA formation on κOA demonstrate that volatile organic compound (VOC) precursors from diverse sources and different SOA formation processes may result in SOA with different chemical composition, functional properties and microphysical structure, consequently exerting distinct influences on κOA and rendering single oxidation level parameters (such as O/C) unable to capture those differences. Aside from that, distinct effects of aBBOA on κOA were observed during different episodes, suggesting that the hygroscopicity of SOA associated with similar sources might also differ much under different emission and atmospheric conditions. Overall, these results highlight that it is imperative to conduct more research on κOA characterization under different meteorological and source conditions and examine its relationship with VOC precursor profiles and formation pathways to formulate a better characterization and develop more appropriate parameterization approaches in chemical and climate models.

Eight years of sub-micrometre organic aerosol composition data from the boreal forest characterized using a machine-learning approach

Abstract. The Station for Measuring Ecosystem–Atmosphere Relations (SMEAR) II, located within the boreal forest of Finland, is a unique station in the world due to the wide range of long-term measurements tracking the Earth–atmosphere interface. In this study, we characterize the composition of organic aerosol (OA) at SMEAR II by quantifying its driving constituents. We utilize a multi-year data set of OA mass spectra measured in situ with an Aerosol Chemical Speciation Monitor (ACSM) at the station. To our knowledge, this mass spectral time series is the longest of its kind published to date. Similarly to other previously reported efforts in OA source apportionment from multi-seasonal or multi-annual data sets, we approached the OA characterization challenge through positive matrix factorization (PMF) using a rolling window approach. However, the existing methods for extracting minor OA components were found to be insufficient for our rather remote site. To overcome this issue, we tested a new statistical analysis framework. This included unsupervised feature extraction and classification stages to explore a large number of unconstrained PMF runs conducted on the measured OA mass spectra. Anchored by these results, we finally constructed a relaxed chemical mass balance (CMB) run that resolved different OA components from our observations. The presented combination of statistical tools provided a data-driven analysis methodology, which in our case achieved robust solutions with minimal subjectivity. Following the extensive statistical analyses, we were able to divide the 2012–2019 SMEAR II OA data (mass concentration interquartile range (IQR): 0.7, 1.3, and 2.6 µg m−3) into three sub-categories – low-volatility oxygenated OA (LV-OOA), semi-volatile oxygenated OA (SV-OOA), and primary OA (POA) – proving that the tested methodology was able to provide results consistent with literature. LV-OOA was the most dominant OA type (organic mass fraction IQR: 49 %, 62 %, and 73 %). The seasonal cycle of LV-OOA was bimodal, with peaks both in summer and in February. We associated the wintertime LV-OOA with anthropogenic sources and assumed biogenic influence in LV-OOA formation in summer. Through a brief trajectory analysis, we estimated summertime natural LV-OOA formation of tens of ng m−3 h−1 over the boreal forest. SV-OOA was the second highest contributor to OA mass (organic mass fraction IQR: 19 %, 31 %, and 43 %). Due to SV-OOA's clear peak in summer, we estimate biogenic processes as the main drivers in its formation. Unlike for LV-OOA, the highest SV-OOA concentrations were detected in stable summertime nocturnal surface layers. Two nearby sawmills also played a significant role in SV-OOA production as also exemplified by previous studies at SMEAR II. POA, taken as a mix of two different OA types reported previously, hydrocarbon-like OA (HOA) and biomass burning OA (BBOA), made up a minimal OA mass fraction (IQR: 2 %, 6 %, and 13 %). Notably, the quantification of POA at SMEAR II using ACSM data was not possible following existing rolling PMF methodologies. Both POA organic mass fraction and mass concentration peaked in winter. Its appearance at SMEAR II was linked to strong southerly winds. Similar wind direction and speed dependence was not observed among other OA types. The high wind speeds probably enabled the POA transport to SMEAR II from faraway sources in a relatively fresh state. In the event of slower wind speeds, POA likely evaporated and/or aged into oxidized organic aerosol before detection. The POA organic mass fraction was significantly lower than reported by aerosol mass spectrometer (AMS) measurements 2 to 4 years prior to the ACSM measurements. While the co-located long-term measurements of black carbon supported the hypothesis of higher POA loadings prior to year 2012, it is also possible that short-term (POA) pollution plumes were averaged out due to the slow time resolution of the ACSM combined with the further 3 h data averaging needed to ensure good signal-to-noise ratios (SNRs). Despite the length of the ACSM data set, we did not focus on quantifying long-term trends of POA (nor other components) due to the high sensitivity of OA composition to meteorological anomalies, the occurrence of which is likely not normally distributed over the 8-year measurement period. Due to the unique and realistic seasonal cycles and meteorology dependences of the independent OA subtypes complemented by the reasonably low degree of unexplained OA variability, we believe that the presented data analysis approach performs well. Therefore, we hope that these results encourage also other researchers possessing several-year-long time series of similar data to tackle the data analysis via similar semi- or unsupervised machine-learning approaches. This way the presented method could be further optimized and its usability explored and evaluated also in other environments.

Estimation of particulate organic nitrates from thermodenuder–aerosol mass spectrometer measurements in the North China Plain

Abstract. Particulate organic nitrates (pON) are an important component of secondary organic aerosol in biogenic-emission-dominant environments and play a critical role in NOx cycles. However, estimation of pON has been a challenge in polluted environments, e.g., North China Plain, with high concentrations of inorganic nitrate and NOx. Here we developed a method for estimation of pON from the measurements of high-resolution aerosol mass spectrometer coupled with a thermodenuder based on the volatility differences between inorganic nitrate and pON. The results generally correlated well with those estimated from positive matrix factorization of combined organic and inorganic mass spectra and from the ratio of NO+ to NO2+ (NOx+ ratio), yet they had improvements in reducing negative values due to the influences of high concentration of inorganic nitrate and constant NOx+ ratio of organic nitrates (RON). By applying this approach to the measurements at an urban (Beijing) and a rural site (Gucheng) in summer and winter in the North China Plain, we estimated that the average mass concentrations of NO3,org (1.8 µg m−3 vs. 1.0 µg m−3) and pON to OA (27.5 % vs. 14.8 %) were higher in summer than in winter in Beijing, indicating more pON formation in biogenically and anthropogenically mixed environments. In addition, the average NO3,org loading in Gucheng was 1.9 µg m−3, and the pON at the rural site also showed higher contribution to OA than that in Beijing during wintertime due to higher primary emissions and gaseous precursors in Gucheng. In addition, RON was determined and showed considerable differences between day–night and clean–polluted periods, highlighting the complexity of pON compounds from different chemical pathways (e.g., OH and NO3 oxidation) and sources.

Characterization of Organic Aerosol at a Rural Site in the North China Plain Region: Sources, Volatility and Organonitrates

The North China Plain (NCP) is a region that experiences serious aerosol pollution. A number of studies have focused on aerosol pollution in urban areas in the NCP region; however, research on characterizing aerosols in rural NCP areas is comparatively limited. In this study, we deployed a TD-HR-AMS (thermodenuder high-resolution aerosol mass spectrometer) system at a rural site in the NCP region in summer 2013 to characterize the chemical compositions and volatility of submicron aerosols (PM1). The average PM1 mass concentration was 51.2 ± 48.0 µg m−3 and organic aerosol (OA) contributed most (35.4%) to PM1. Positive matrix factorization (PMF) analysis of OA measurements identified four OA factors, including hydrocarbon-like OA (HOA, accounting for 18.4%), biomass burning OA (BBOA, 29.4%), less-oxidized oxygenated OA (LO-OOA, 30.8%) and more-oxidized oxygenated OA (MO-OOA, 21.4%). The volatility sequence of the OA factors was HOA > BBOA > LO-OOA > MO-OOA, consistent with their oxygen-to-carbon (O:C) ratios. Additionally, the mean concentration of organonitrates (ON) was 1.48–3.39 µg m−3, contributing 8.1%–19% of OA based on cross validation of two estimation methods with the high-resolution time-of-flight aerosol mass spectrometer (HR-ToF-AMS) measurement. Correlation analysis shows that ON were more correlated with BBOA and black carbon emitted from biomass burning but poorly correlated with LO-OOA. Also, volatility analysis for ON further confirmed that particulate ON formation might be closely associated with primary emissions in rural NCP areas.

Seasonal variation of aerosol compositions in Shanghai, China: Insights from particle aerosol mass spectrometer observations

The variations of non-refractory submicron aerosol (NR-PM1) were characterized using an high-resolution time-of-flight aerosol mass spectrometer (HR-ToF-AMS) and other online instruments measurements sampled at an urban site in Shanghai from 2016 to 2017. Spring (from 18 May to 4 June 2017), summer (from 23 August to 10 September 2017) and winter (from 28 November 2016 to 23 January 2017) seasons were chosen for detail investigating the seasonal variations in the aerosol chemical characteristics. The average PM1 (NR-PM1 + BC) mass concentration showed little difference in the three seasons in Shanghai. The average mass concentrations of total PM1 during spring, summer, and winter observations in Shanghai were 23.9 ± 20.7 μg/m3, 28.5 ± 17.6 μg/m3, and 31.9 ± 22.7 μg/m3, respectively. The seasonal difference on chemical compositions was more significant between them. Organic aerosol (OA) and sulfate were dominant contributor of PM1 in summer, whereas OA and nitrate primarily contribution to the increase of PM1 mass loading in spring and winter. As an abundant component in PM1 (accounting for 39%–49%), OA were resolved into two primary organic aerosol (POA) factors and two secondary aerosol (SOA) factors by using positive matrix factorization (PMF), of which OA was overwhelmingly dominated by the SOA (50–60%) across the three seasons in Shanghai. Correlation analysis with relative humidity and odd oxygen indicated that aqueous-phase processing and played an important role in more aged SOA formation in summer and winter. In spring, both aqueous-phase and photochemical processing contributed significantly to fresh SOA formation. Our results suggest the significant role of secondary particles in PM pollution in Shanghai and highlight the importance of control measures for reducing emissions of gaseous precursors, especially need to consider seasonal characteristics.

Evolution of Aerosol Under Moist and Fog Conditions in a Rural Forest Environment: Insights From High‐Resolution Aerosol Mass Spectrometry

AbstractThe effect of foggy/moist conditions on the characteristics of secondary organic aerosol (SOA) was studied. Analysis of the high‐resolution time‐of‐flight aerosol mass spectrometer measurements identified two fresh biogenic SOA factors (BSOA: BSOA‐1 and BSOA‐2), hypothesized to be formed through the nighttime reaction of biogenic volatile organic compounds with nitrate radical. During foggy periods, the more oxidized oxygenated OA (MO‐OOA) was scavenged most efficiently (86% removal), followed by the less oxidized OOA (LO‐OOA) (55%), SO4 (53%), and BSOA (25%). Aerosol mass increased during fog events, and the post‐fog aerosol mass was higher (11%) than during the prefog period, with a reduction for MO‐OOA and an enhancement for LO‐OOA and BSOA. The high positive correlation observed between aerosol liquid water (ALW) and BSOA suggests the importance of aqueous‐phase processing on the BSOA formation, and an increase in log10(ALW) of 1 corresponded to an average increase of about 0.9 μg m−3 in BSOA.

Seasonal Differences and Variability of Concentrations, Chemical Composition, and Cloud Condensation Nuclei of Marine Aerosol Over the North Atlantic

AbstractThe majority of the aerosol particle number (condensation nuclei or CN) in the marine boundary layer (MBL) consists of sulfate and organic compounds that have been shown to provide a large fraction of the cloud condensation nuclei (CCN). Here we use submicron non‐refractory Aerosol Mass Spectrometer (AMS) and filter measurements of organic and sulfate components of aerosol particles measured during four North Atlantic Aerosol and Marine Ecosystems Study (NAAMES) research cruises to assess the sources and contributions of submicron organic and sulfate components for CCN concentrations in the MBL during four different seasons. Submicron hydroxyl group organic mass (OM) correlated strongly to sodium concentrations during clean marine periods (R = 0.9), indicating that hydroxyl group OM can serve as a proxy for sea‐spray OM in ambient measurements. Sea‐spray OM contributed 45% of the sum of sea‐spray OM and sea salt during late spring (biomass climax phase) compared to &lt;20% for other seasons, but the seasonal difference was not statistically significant. The contribution of non‐combustion sources during clean marine periods to submicron OM was 47 to 88% and to non‐sea‐salt sulfate 31 to 86%, with likely sources being marine and biogenic. The remaining submicron OM and sulfate were likely associated with ship or continental sources, including biomass burning, even during clean marine periods. The seasonal contribution from secondary sulfate and OM components to submicron aerosol mass was highest during late spring (60%), when biogenic emissions are expected to be highest, and lowest during winter (18%). Removing submicron sea‐spray OM decreased CCN concentrations by &lt;10% because of competing effects from increased hygroscopicity and decreased particle size. During all seasons, adding biogenic secondary sulfate increased hygroscopicity, particle size, and CCN concentrations at 0.1–0.3% supersaturations by 5–66%. The largest change was during early spring when the fraction of hygroscopic sulfate components in the 0.1–0.2 μm size range was highest (80%). During continental periods, the increased contribution from low‐hygroscopicity organic components to 0.1–0.2 μm diameter particles reduces the CCN/CN by 20–100% for three seasons despite the increased CN and mass concentrations. These results illustrate the important role of the chemical composition of particles with diameters 0.1–0.2 μm for controlling CCN in the MBL.

Chemical characterization of secondary organic aerosol at a rural site in the southeastern US: insights from simultaneous high-resolution time-of-flight aerosol mass spectrometer (HR-ToF-AMS) and FIGAERO chemical ionization mass spectrometer (CIMS) measurements

Abstract. The formation and evolution of secondary organic aerosol (SOA) were investigated at Yorkville, GA, in late summer (mid-August to mid-October 2016). The organic aerosol (OA) composition was measured using two online mass spectrometry instruments, the high-resolution time-of-flight aerosol mass spectrometer (AMS) and the Filter Inlet for Gases and AEROsols coupled to a high-resolution time-of-flight iodide-adduct chemical ionization mass spectrometer (FIGAERO-CIMS). Through analysis of speciated organics data from FIGAERO-CIMS and factorization analysis of data obtained from both instruments, we observed notable SOA formation from isoprene and monoterpenes during both day and night. Specifically, in addition to isoprene epoxydiol (IEPOX) uptake, we identified isoprene SOA formation from non-IEPOX pathways and isoprene organic nitrate formation via photooxidation in the presence of NOx and nitrate radical oxidation. Monoterpenes were found to be the most important SOA precursors at night. We observed significant contributions from highly oxidized acid-like compounds to the aged OA factor from FIGAERO-CIMS. Taken together, our results showed that FIGAERO-CIMS measurements are highly complementary to the extensively used AMS factorization analysis, and together they provide more comprehensive insights into OA sources and composition.

Characterization of Aerosol Hygroscopicity Over the Northeast Pacific Ocean: Impacts on Prediction of CCN and Stratocumulus Cloud Droplet Number Concentrations.

During the Marine Aerosol Cloud and Wildfire Study (MACAWS) in June and July of 2018, aerosol composition and cloud condensation nuclei (CCN) properties were measured over the N.E. Pacific to characterize the influence of aerosol hygroscopicity on predictions of ambient CCN and stratocumulus cloud droplet number concentrations (CDNC). Three vertical regions were characterized, corresponding to the marine boundary layer (MBL), an above-cloud organic aerosol layer (AC-OAL), and the free troposphere (FT) above the AC-OAL. The aerosol hygroscopicity parameter (κ) was calculated from CCN measurements (κCCN) and bulk aerosol mass spectrometer (AMS) measurements (κAMS). Within the MBL, measured hygroscopicities varied between values typical of both continental environments (~0.2) and remote marine locations (~0.7). For most flights, CCN closure was achieved within 20% in the MBL. For five of the seven flights, assuming a constant aerosol size distribution produced similar or better CCN closure than assuming a constant “marine” hygroscopicity (κ = 0.72). An aerosol-cloud parcel model was used to characterize the sensitivity of predicted stratocumulus CDNC to aerosol hygroscopicity, size distribution properties, and updraft velocity. Average CDNC sensitivity to accumulation mode aerosol hygroscopicity is 39% as large as the sensitivity to the geometric median diameter in this environment. Simulations suggest CDNC sensitivity to hygroscopicity is largest in marine stratocumulus with low updraft velocities (<0.2 m s−1), where accumulation mode particles are most relevant to CDNC, and in marine stratocumulus or cumulus with large updraft velocities (>0.6 m s−1), where hygroscopic properties of the Aitken mode dominate hygroscopicity sensitivity.

Mass spectral characterization of primary emissions and implications in source apportionment of organic aerosol

Abstract. Source apportionment of organic aerosol (OA) from aerosol mass spectrometer (AMS) or aerosol chemical speciation monitor (ACSM) measurements relies largely upon mass spectral profiles from different source emissions. However, the changes in mass spectra of primary emissions from AMS–ACSM with the newly developed capture vaporizer (CV) are poorly understood. Here we conducted 21 cooking, crop straw, wood, and coal burning experiments to characterize the mass spectral features of OA and water-soluble OA (WSOA) using SV-AMS and CV-ACSM. Our results show overall similar spectral characteristics between SV-AMS and CV-ACSM for different primary emissions despite additional thermal decomposition in CV, and the previous spectral features for diagnostics of primary OA factors are generally well retained. However, the mass spectral differences between OA and WSOA can be substantial for both SV-AMS and CV-ACSM. The changes in f55 (fraction of m∕z 55 in OA) vs. f57, f44 vs. f60, and f44 vs. f43 in CV-ACSM are also observed, yet the evolving trends are similar to those of SV-AMS. By applying the source spectral profiles to a winter CV-ACSM study at a highly polluted rural site in the North China Plain, the source apportionment of primary OA was much improved, highlighting the two most important primary sources of biomass burning and coal combustion (32 % and 21 %). Considering the rapidly increasing deployments of CV-ACSM and WSOA studies worldwide, the mass spectral characterization has significant implications by providing essential constraints for more accurate source apportionment and making better strategies for air pollution control in regions with diverse primary emissions.