Aerosol Chemical Speciation Monitor Research Articles

Source apportionment of marine atmospheric aerosols in northern South China Sea during summertime 2018

Marine atmospheric aerosols play important roles in the global radiation balance and climate change. Hence, measuring physiochemical aerosol properties is essential to better understand their formation, aging processes, and source origins. However, high temporal resolution measurements of submicron particles are currently scarce in the northern South China Sea (SCS). In this study, we conducted a ship-based cruise campaign with a scanning mobility particle sizer and an online time of flight aerosol chemical speciation monitor to measure the particle number size distribution (PNSD) and the chemical composition of submicron particles over the northern SCS during summer 2018. The mean concentration of non-refractory submicron particulate matter (NR-PM1) was generally 9.11 ± 4.86 μg m−3; sulfate was the most abundant component, followed by organics, ammonium, nitrate, and chloride. Positive matrix factorization (PMF) analysis was applied to the PNSD (size PMF) and organic aerosols (OA PMF) and further investigated the source apportionment of the submicron particles. The size PMF identified four factors, including ship exhaust, ship influencing marine primary, continent affected marine secondary, and mixed accumulation aerosols. The most abundant particles in the number concentration were associated with ship emissions, which accounted for approximately 44 %. The submicron organic aerosols were highly oxidized and composed of low-volatility oxygenated OA (LV-OOA, 68 %), semi-volatile OOA (SV-OOA, 21 %), and hydrocarbon-like OA (HOA, 11 %). The backward trajectory of air masses showed that the northern SCS was most frequently (64.7 %) influenced by air masses from the Indo-Chinese Peninsula (ICP) during the campaign, implying that pollutants from ICP have a significant impact on the atmosphere of the northern SCS during summer. Thus, in situ ship-based cruise measurements can provide valuable data on the physiochemical characteristics of marine atmospheric aerosols to better understand their source origins.

Mediterranean nascent sea spray organic aerosol and relationships with seawater biogeochemistry

Abstract. The organic mass fraction from sea spray aerosol (SSA) is currently a subject of intense research. The majority of this research is dedicated to measurements in ambient air. However a number of studies have recently started to focus on nascent sea spray aerosol. This work presents measurements collected during a 5-week cruise in May and June 2017 in the central and western Mediterranean Sea, an oligotrophic marine region with low phytoplankton biomass. Surface seawater was continuously pumped into a bubble-bursting apparatus to generate nascent sea spray aerosol. Size distributions were measured with a differential mobility particle sizer (DMPS). Chemical characterization of the submicron aerosol was performed with a time-of-flight aerosol chemical speciation monitor (ToF-ACSM) operating with 10 min time resolution and with filter-based chemical analysis on a daily basis. Using positive matrix factorization analysis, the ToF-ACSM non-refractory organic matter (OMNR) was separated into four different organic aerosol types, identified as primary OA (POANR), oxidized OA (OOANR), methanesulfonic acid type OA (MSA-OANR), and mixed OA (MOANR). In parallel, surface seawater biogeochemical properties were monitored providing information on phytoplankton cell abundance and seawater particulate organic carbon (1 h time resolution) and seawater surface microlayer (SML) dissolved organic carbon (DOC) (on a daily basis). Statistically robust correlations (for n>500) were found between MOANR and nanophytoplankton cell abundance, as well as between POANR, OOANR, and particulate organic carbon (POC). Parameterizations of the contributions of different types of organics to the submicron nascent sea spray aerosol are proposed as a function of the seawater biogeochemical properties for use in 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.

Mixing state of refractory black carbon aerosol in the South Asian outflow over the northern Indian Ocean during winter

Abstract. Regional climatic implications of aerosol black carbon (BC), which has a wide variety of anthropogenic sources in large abundance, are well recognized over South Asia. Significant uncertainties remain in its quantification due to a lack of sufficient information on the microphysical properties (its concentration, size, and mixing state with other aerosol components) that determine the absorption potential of BC. In particular, the information on the mixing state of BC is extremely sparse over this region. In this study, the first observations of the size distribution and mixing state of individual refractory black carbon (rBC) particles in the South Asian outflow to the south-eastern Arabian Sea and the northern and equatorial Indian Ocean regions are presented based on measurements using a single particle soot photometer (SP2) aboard the Integrated Campaign for Aerosols, gases, and Radiation Budget (ICARB-2018) ship during winter 2018 (16 January to 13 February). The results revealed significant spatial heterogeneity of BC characteristics. The highest rBC mass concentrations (∼938±293 ng m−3) with the highest relative coating thickness (RCT; the ratio of BC core to its coating diameters) of ∼2.16±0.19 are found over the south-east Arabian Sea (SEAS) region, which is in the proximity of the continental outflow. As we move to farther oceanic regions, though the mass concentrations decreased by nearly half (∼546±80 ng m−3), BC still remained thickly coated (RCT∼2.05±0.07). The air over the remote equatorial Indian Ocean, which received considerable marine air masses compared to the other regions, showed the lowest rBC mass concentrations (∼206±114 ng m−3) with a moderately thick coating (RCT∼1.73±0.16). Even over oceanic regions far from the landmass, regions that received the outflow from the more industrialized east coast/the Bay of Bengal had a thicker coating (∼104 nm) compared to regions that received outflow from the west coast and/or peninsular India (∼86 nm). Although different regions of the ocean depicted contrasting concentrations and mixing state parameters due to the varied extent and nature of the continental outflow as well as the atmospheric lifetime of air masses, the modal parameters of rBC mass–size distributions (mean mass median diameters ∼ 0.19–0.20 µm) were similar over all regions. The mean fraction of BC-containing particles (FBC) varied in the range of 0.08–0.12 (suggesting significant amounts of non-BC particles), whereas the bulk mixing ratio of coating mass to rBC mass was highest (8.31±2.40) over the outflow regions compared to the remote ocean (4.24±1.45), highlighting the role of outflow in providing condensable material for coatings on rBC. These parameters, along with the information on the size-resolved mixing state of BC cores, throw light on the role of sources and secondary processing of their complex mixtures for coatings on BC under highly polluted conditions. Examination of the non-refractory sub-micrometre aerosol chemical composition obtained using the aerosol chemical speciation monitor (ACSM) suggested that the overall aerosol system was sulfate-dominated over the far-oceanic regions. In contrast, organics were equally prominent adjacent to the coastal landmass. An association between the BC mixing state and aerosol chemical composition suggested that sulfate was the probable dominant coating material on rBC cores.

Physical and chemical properties of urban aerosols in São Paulo, Brazil: links between composition and size distribution of submicron particles

Abstract. In this work, the relationships between size and composition of submicron particles (PM1) were analyzed at an urban site in the Metropolitan Area of São Paulo (MASP), a megacity with about 21 million inhabitants. The measurements were carried out from 20 December 2016 to 15 March 2017. The chemical composition was measured with an Aerodyne Aerosol Chemical Speciation Monitor and size distribution with a TSI Scanning Mobility Particle Sizer 3082. PM1 mass concentrations in the MASP had an average mass concentration of 11.4 µg m−3. Organic aerosol (OA) dominated the PM1 composition (56 %), followed by sulfate (15 %) and equivalent black carbon (eBC, 13 %). Four OA classes were identified using positive matrix factorization: oxygenated organic aerosol (OOA, 40 % of OA), biomass burning organic aerosol (BBOA, 13 %), and two hydrocarbon-like OA components (a typical HOA related to vehicular emissions (16 %) and a second HOA (21 %) representing a mix of anthropogenic sources). Particle number concentrations averaged 12 100±6900 cm−3, dominated by the Aitken mode. The accumulation mode increased under relatively high-PM1 conditions, suggesting an enhancement of secondary organic aerosol (SOA) production. Conversely, the contribution of nucleation-mode particles was less dependent on PM1 levels, consistent with vehicular emissions. The relationship between aerosol size modes and PM1 composition was assessed by multilinear regression (MLR) models. Secondary inorganic aerosols were partitioned between Aitken and accumulation modes, related to condensation particle growth processes. Submicron mass loading in the accumulation mode was mostly associated with highly oxidized OOA and also traffic-related emissions. To the authors' knowledge, this is the first work that uses the MLR methodology to estimate the chemical composition of the different aerosol size modes. The chemical composition with size-dependent PM provides innovative information on the properties of both primary and secondary organic aerosols, as well as inorganic aerosols in a complex urban environment. The results emphasize the relevance of vehicular emissions to the air quality at MASP and highlight the key role of secondary processes on the PM1 ambient concentrations in the region since 56 % of PM1 mass loading was attributed to SOA and secondary inorganic aerosol.

Measurement report: Fourteen months of real-time characterisation of the submicronic aerosol and its atmospheric dynamics at the Marseille–Longchamp supersite

Abstract. This study reports results of PM1 chemical composition determined using a Time-of-Flight Aerosol Chemical Speciation Monitor (ToF-ACSM) over a 14-month period (1 February 2017–13 April 2018) at the Marseille–Longchamp supersite (MRS-LCP) in France. Parallel measurements were performed with an aethalometer, an ultrafine particle monitor and a suite of instruments to monitor regulated pollutants (PM2.5, PM10, NOx, O3 and SO2). The average PM1 chemical composition over the period was dominated by organic aerosol (OA; 49.7 %) and black carbon (BC; 17.1 %), while sulfate accounted for 14.6 %, nitrate for 10.2 %, ammonium for 7.9 % and chloride for 0.5 % only. Wintertime was found to be the season contributing the most to the annual PM1 mass concentration (30 %), followed by autumn (26 %), summer (24 %) and spring (20 %). During this season, OA and BC concentrations were found to contribute 32 % and 31 % of their annual concentrations, respectively, as a combined result of heavy urban traffic, high emissions from residential heating and low planetary boundary layer (PBL) height. Most (75 %) of the 15 days exceeding the target daily PM2.5 concentration value recommended by the World Health Organization (WHO) occurred during this season. Local and long-range pollution episodes with contrasting chemical composition could be distinguished, accounting for 40 % and 60 % of the exceedance days, respectively. Enhanced OA and BC concentrations, mostly originating from domestic wood burning under nocturnal land breeze conditions, were observed during local pollution episodes, while high levels of oxygenated OA and inorganic nitrate were associated with medium-/long-range transported particles. In summertime, substantially higher concentrations of sulfate were found, with an average and a maximum contribution to the PM1 mass of 24 % and 66 %, respectively. Results from k-means clustering analysis of daily profiles of sulfate concentrations clearly reveal the significant influence of local harbour/industrial activities on air quality in addition to the more regional contribution of shipping traffic that originates from the Mediterranean basin.

In-depth characterization of submicron particulate matter inter-annual variations at a street canyon site in northern Europe

Abstract. Atmospheric aerosols play an important role in air pollution. Aerosol particle chemical composition is highly variable depending on the season, hour of the day, day of the week, meteorology, and location of the measurement site. Long measurement periods and highly time-resolved data are required in order to achieve a statistically relevant amount of data for assessing those variations and evaluating pollution episodes. In this study, we present continuous atmospheric PM1 (particulate matter < 1 µm) concentration and composition measurements at an urban street canyon site located in Helsinki, Finland. The study was performed for 4.5 years (2015–2019) and involved highly time-resolved measurements by taking advantage of a suite of online state-of-the-art instruments such as an aerosol chemical speciation monitor (ACSM), a multi-angle absorption photometer (MAAP), a differential mobility particle sizer (DMPS), and an Aethalometer (AE). PM1 consisted mostly of organics, with mean mass concentrations of 2.89 µg m−3 (53 % of PM1) followed by inorganic species (1.56 µg m−3, 29 %) and equivalent black carbon (eBC, 0.97 µg m−3, 18 %). A trend analysis revealed a decrease in BC from fossil fuel (BCFF), organics, and nitrate over the studied years. Clear seasonal and/or diurnal variations were found for the measured atmospheric PM1 constituents. Particle number and mass size distributions over different seasons revealed the possible influence of secondary organic aerosols (SOAs) during summer and the dominance of ultrafine traffic aerosols during winter. The seasonality of measured constituents also impacted the particle's coating and absorptive properties. The investigation of pollution episodes observed at the site showed that a large fraction of aerosol particle mass was comprised of inorganic species during long-range transport, while during local episodes eBC and organics prevailed together with elevated particle number concentration. Overall, the results increased knowledge of the variability of PM1 concentration and composition in a Nordic traffic site and its implications on urban air quality. Considering the effects of PM mitigation policies in northern Europe in the last decades, the results obtained in this study may be considered illustrative of probable future air quality challenges in countries currently adopting similar environmental regulations.

Influence of biomass burning vapor wall loss correction on modeling organic aerosols in Europe by CAMx v6.50

Abstract. Increasing evidence from experimental studies suggests that the losses of semi-volatile vapors to chamber walls could be responsible for the underestimation of organic aerosol (OA) in air quality models that use parameters obtained from chamber experiments. In this study, a box model with a volatility basis set (VBS) scheme was developed, and the secondary organic aerosol (SOA) yields with vapor wall loss correction were optimized by a genetic algorithm based on advanced chamber experimental data for biomass burning. The vapor wall loss correction increases the SOA yields by a factor of 1.9–4.9 and leads to better agreement with measured OA for 14 chamber experiments under different temperatures and emission loads. To investigate the influence of vapor wall loss correction on regional OA simulations, the optimized parameterizations (SOA yields, emissions of intermediate-volatility organic compounds from biomass burning, and enthalpy of vaporization) were implemented in the regional air quality model CAMx (Comprehensive Air Quality Model with extensions). The model results from the VBS schemes with standard (VBS_BASE) and vapor-wall-loss-corrected parameters (VBS_WLS), as well as the traditional two-product approach, were compared and evaluated by OA measurements from five Aerodyne aerosol chemical speciation monitor (ACSM) or aerosol mass spectrometer (AMS) stations in the winter of 2011. An additional reference scenario, VBS_noWLS, was also developed using the same parameterization as VBS_WLS except for the SOA yields, which were optimized by assuming there is no vapor wall loss. The VBS_WLS generally shows the best performance for predicting OA among all OA schemes and reduces the mean fractional bias from −72.9 % (VBS_BASE) to −1.6 % for the winter OA. In Europe, the VBS_WLS produces the highest domain average OA in winter (2.3 µg m−3), which is 106.6 % and 26.2 % higher than VBS_BASE and VBS_noWLS, respectively. Compared to VBS_noWLS, VBS_WLS leads to an increase in SOA by up to ∼80 % (in the Balkans). VBS_WLS also leads to better agreement between the modeled SOA fraction in OA (fSOA) and the estimated values in the literature. The substantial influence of vapor wall loss correction on modeled OA in Europe highlights the importance of further improvements in parameterizations based on laboratory studies for a wider range of chamber conditions and field observations with higher spatial and temporal coverage.

Altitude Aerosol Measurements in Central France: Seasonality, Sources and Free‐Troposphere/Boundary Layer Segregation

AbstractThe chemical composition of nonrefractory submicron aerosol particles was measured at the Puy‐de‐Dôme (PUY) station (1,465 m a.s.l) during 2015 using a Time‐of‐Flight Aerosol Chemical Speciation Monitor (ToF‐ACSM). These aerosol chemistry measurements are combined with online black carbon (BC) measurements to provide an overview of the submicron aerosol composition. Averaged over the entire year, and normalized to standard temperature and pressure, organic aerosol (OA) dominates the PM1 concentration during all seasons and within all air mass types (2.12 ± 1.73 µgm−3), and is responsible for summertime increases in aerosol concentration. Highest mass concentrations were measured during the summer, when air masses were arriving over mainland Europe and lowest in the winter months (when most air masses were of Atlantic origin). OA source apportionment was performed separately during each season, using the Source Finder (SoFi) interface for the multilinear engine. The PUY site, situated at 1,465 m a.s.l, although mainly sampling in the atmospheric boundary layer, it is sometimes sampling in the lower free troposphere (FT), providing the opportunity to identify the characteristics of FT aerosol. In order to accurately identify these sampling periods, the methodology described in Farah et al. (2018), during the same time period (2015/2016), was applied to the data. During this period, FT air masses are sampled approximately 20% of the time. This work provides, on one hand, a description of long‐term aerosol chemical properties at a remote regional site in central Europe and, on the other hand a characteristic chemical signature of FT aerosols over this region. This data can be used to improve our understanding of the transport and aging properties of aerosols at regional observation sites.

Study of Emissions from Domestic Solid-Fuel Stove Combustion in Ireland.

Solid-fuel stoves are at the heart of many homes not only in developing nations, but also in developed regions where there is significant deployment of such heating appliances. They are often operated inefficiently and in association with high emission fuels like wood. This leads to disproportionate air pollution contributions. Despite the proliferation of these appliances, an understanding of particulate matter (PM) emissions from these sources remains relatively low. Emissions from five solid fuels are quantified using a “conventional” and an Ecodesign stove. PM measurements are obtained using both “hot filter” sampling of the raw flue gas, and sampling of cooled, diluted flue gas using an Aerosol Chemical Speciation Monitor and AE33 aethalometer. PM emissions factors (EF) derived from diluted flue gas incorporate light condensable organic compounds; hence they are generally higher than those obtained with “hot filter” sampling, which do not. Overall, the PM EFs ranged from 0.2 to 108.2 g GJ–1 for solid fuels. The PM EF determined for a solid fuel depends strongly on the measurement method employed and on user behavior, and less strongly on secondary air supply and stove type. Kerosene-based firelighters were found to make a disproportionately high contribution to PM emissions. Organic aerosol dominated PM composition for all fuels, constituting 50–65% of PM from bituminous and low-smoke ovoids, and 85–95% from torrefied olive stone (TOS) briquettes, sod peat, and wood logs. Torrefied biomass and low-smoke ovoids were found to yield the lowest PM emissions. Substituting these fuels for smoky coal, peat, and wood could reduce PM2.5 emissions by approximately 63%.

Characteristics, formation mechanisms, and sources of non-refractory submicron aerosols in Guangzhou, China

Submicron aerosols (PM1) have more serious effect on the visibility, air quality, human health and climate change compared to coarse particles (particle size between 2.5 and 10 μm). There is practical significance in understanding the formation mechanisms and sources of these particles. In this study, we conducted real-time measurements on the composition of non-refractory submicron aerosols (NR-PM1) in Guangzhou from 20 October to 1 December, 2016, using a quadripole aerosol chemical speciation monitor (Q-ACSM). Overall, the composition of NR-PM1 was dominated by organics (48.2%), followed by nitrate (NO3−, 20.3%), sulfate (SO42−, 17.4%), ammonium (NH4+, 11.4%), and chloride (Cl−, 2.7%). The high contribution of NO3− and NO3−/SO42− mass ratios were observed in high-PM episodes, suggesting that NOx emission control should be a priority in mitigating PM-pollution in South China. Primary organic aerosols (POA) accounted for 51% of organics as the campaign average, and POA contribution increased with PM concentrations especially during high PM episodes, indicating that local emissions played a very important role in high-PM pollution. The conversion of SO2 to SO42− and aqueous, heterogeneous production may not be the dominant source of SO42− in NR-PM1, while regional transport is likely to be the main source during high-sulfate episodes. The formation of NO3− in this study was related to gas-phase reactions of NO2 (photochemical reaction) during daytime, and heterogeneous reactions (hydrolysis reaction of N2O5) during the nighttime. Gas-phase reactions would be less important for nitrate formation during severe polluted events. Particle acidity analyses showed that particles were generally acidic and the NH4+ was not enough to fully neutralise the NO3− and SO42−, the existing forms of SO42− could be (NH4)2SO4, NH4HSO4 or (NH4)3H(SO4)2. Controlling the emissions of NH3 to reduce the NH4+ concentration can probably be a feasible direction in the future in Guangzhou if the problem of agriculture and aerosol acidity can be solved. Wind rose plots and back-trajectory analyses also demonstrated that local emission was more important to the formation of NO3− and regional transport was more conducive to the increase of SO42− concentration.

A new method for long-term source apportionment with time-dependent factor profiles and uncertainty assessment using SoFi Pro: application to 1 year of organic aerosol data

Abstract. A new methodology for performing long-term source apportionment (SA) using positive matrix factorization (PMF) is presented. The method is implemented within the SoFi Pro software package and uses the multilinear engine (ME-2) as a PMF solver. The technique is applied to a 1-year aerosol chemical speciation monitor (ACSM) dataset from downtown Zurich, Switzerland. The measured organic aerosol mass spectra were analyzed by PMF using a small (14 d) and rolling PMF window to account for the temporal evolution of the sources. The rotational ambiguity is explored and the uncertainties of the PMF solutions were estimated. Factor–tracer correlations for averaged seasonal results from the rolling window analysis are higher than those retrieved from conventional PMF analyses of individual seasons, highlighting the improved performance of the rolling window algorithm for long-term data. In this study four to five factors were tested for every PMF window. Factor profiles for primary organic aerosol from traffic (HOA), cooking (COA) and biomass burning (BBOA) were constrained. Secondary organic aerosol was represented by either the combination of semi-volatile and low-volatility organic aerosol (SV-OOA and LV-OOA, respectively) or by a single OOA when this separation was not robust. This scheme led to roughly 40 000 PMF runs. Full visual inspection of all these PMF runs is unrealistic and is replaced by predefined user-selected criteria, which allow factor sorting and PMF run acceptance/rejection. The selected criteria for traffic (HOA) and BBOA were the correlation with equivalent black carbon from traffic (eBCtr) and the explained variation of m/z 60, respectively. COA was assessed by the prominence of a lunchtime concentration peak within the diurnal cycle. SV-OOA and LV-OOA were evaluated based on the fractions of m/z 43 and 44 in their respective factor profiles. Seasonal pre-tests revealed a non-continuous separation of OOA into SV-OOA and LV-OOA, in particular during the warm seasons. Therefore, a differentiation between four-factor solutions (HOA, COA, BBOA and OOA) and five-factor solutions (HOA, COA, BBOA, SV-OOA and LV-OOA) was also conducted based on the criterion for SV-OOA. HOA and COA contribute between 0.4–0.7 µg m−3 (7.8 %–9.0 %) and 0.7–1.2 µg m−3 (12.2 %–15.7 %) on average throughout the year, respectively. BBOA shows a strong yearly cycle with the lowest mean concentrations in summer (0.6 µg m−3, 12.0 %), slightly higher mean concentrations during spring and fall (1.0 and 1.5 µg m−3, or 15.6 % and 18.6 %, respectively), and the highest mean concentrations during winter (1.9 µg m−3, 25.0 %). In summer, OOA is separated into SV-OOA and LV-OOA, with mean concentrations of 1.4 µg m−3 (26.5 %) and 2.2 µg m−3 (40.3 %), respectively. For the remaining seasons the seasonal concentrations of SV-OOA, LV-OOA and OOA range from 0.3 to 1.1 µg m−3 (3.4 %–15.9 %), from 0.6 to 2.2 µg m−3 (7.7 %–33.7 %) and from 0.9 to 3.1 µg m−3 (13.7 %–39.9 %), respectively. The relative PMF errors modeled for this study for HOA, COA, BBOA, LV-OOA, SV-OOA and OOA are on average ±34 %, ±27 %, ±30 %, ±11 %, ±25 % and ±12 %, respectively.

An evaluation of source apportionment of fine OC and PM2.5 by multiple methods: APHH-Beijing campaigns as a case study.

This study aims to critically evaluate the source apportionment of fine particles by multiple receptor modelling approaches, including carbon mass balance modelling of filter-based radiocarbon (14C) data, Chemical Mass Balance (CMB) and Positive Matrix Factorization (PMF) analysis on filter-based chemical speciation data, and PMF analysis on Aerosol Mass Spectrometer (AMS-PMF) or Aerosol Chemical Speciation Monitor (ACSM-PMF) data. These data were collected as part of the APHH-Beijing (Atmospheric Pollution and Human Health in a Chinese Megacity) field observation campaigns from 10th November to 12th December in winter 2016 and from 22nd May to 24th June in summer 2017. 14C analysis revealed the predominant contribution of fossil fuel combustion to carbonaceous aerosols in winter compared with non-fossil fuel sources, which is supported by the results from other methods. An extended Gelencsér (EG) method incorporating 14C data, as well as the CMB and AMS/ACSM-PMF methods, generated a consistent source apportionment for fossil fuel related primary organic carbon. Coal combustion, traffic and biomass burning POC were comparable for CMB and AMS/ACSM-PMF. There are uncertainties in the EG method when estimating biomass burning and cooking OC. The POC from cooking estimated by different methods was poorly correlated, suggesting a large uncertainty when differentiating this source type. The PM2.5 source apportionment results varied between different methods. Through a comparison and correlation analysis of CMB, PMF and AMS/ACSM-PMF, the CMB method appears to give the most complete and representative source apportionment of Beijing aerosols. Based upon the CMB results, fine aerosols in Beijing were mainly secondary inorganic ion formation, secondary organic aerosol formation, primary coal combustion and from biomass burning emissions.

Aerosol characterization in a city in central China plain and implications for emission control

Extensive studies on aerosol chemistry have been carried out in megacities in China, however, aerosol characterization in Central China Plain (CCP) is limited. Here we conducted real-time measurements of fine particle composition with a time-of-flight aerosol chemical speciation monitor in Kaifeng, Henan province in October 2019. Our results showed that nitrate and organics constituted the major fraction of non-refractory PM2.5 for the entire study, on average accounting for 34% and 33%, respectively. However, aerosol composition was substantially different among four periods due to different meteorological conditions and chemical processing. For instance, nitrate presented the lowest contribution during the first period due to evaporative loss associated with high temperature (T), and then rapidly increased during polluted periods as a function of relative humidity (RH). Positive matrix factorization analysis showed the dominance of secondary organic aerosol (SOA) in OA, and also the changes in OA composition under different T and RH levels. In addition, this study is unique with two periods of local emission controls. Back trajectory and coefficient of divergence analysis showed that air pollution in CCP was overall homogeneously distributed. As a result, the effectiveness of local emission controls in this region was strongly affected by meteorological conditions and regional transport. We found that one of the periods with emission control even showed the highest concentrations for the entire study. Our results point towards the limited effect of local emission controls in mitigating air pollution in CCP, and highlight the importance of joint emission controls under unfavorable meteorological conditions.

Characteristics, evolution, and potential source regions of submicron aerosol in Beijing, China

Atmospheric fine particulate pollution has been a dramatically environmental concern in all seasons in the megacity Beijing in recent years. A long-term real-time monitoring campaign of non-refractory submicron aerosol (NR-PM1) at a southeastern urban site in Beijing from July 13, 2017 to May 26, 2018 using an Aerodyne Aerosol Chemical Speciation Monitor (ACSM) was carried out to investigate the characteristics and evolution processes of NR-PM1 and its potential source effects. The annual average concentration of NR-PM1 during the entire study period was 40.8 μg/m3, lower than that of NR-PM1 from July 2011 to June 2012, and its seasonal variation presented the order of autumn and spring > winter > summer. The average concentration of organic species Org in the entire study was 15.1 μg/m3 and accounted for 37% of NR-PM1, being consistently a significant component of NR-PM1 in the four seasons. The average concentrations of SO42− and NO3− were 8.6 and 11.1 μg/m3, respectively, accounting for 21% and 27% of NR-PM1, and NO3− and its contribution to NR-PM1 exceeded those of SO42−, suggesting that secondary nitrate became a more dramatic pollutant. Note that SO42− in summer accounted for 27% of NR-PM1, higher than those in the other seasons, indicating that secondary sulfate formation was greatly important in summer, however, NO3− in summer accounted for 22% of NR-PM1, lower than those in the other seasons, more likely due to relatively high temperature in summer being favorable for dissociation of nitrate. NH4+ and Cl− species presented lower mass concentrations and mass fractions, and the seasonal variation of NH4+ was similar to NO3−, yet Cl− presented a typical seasonal change related to intense fossil fuel combustion during the heating period in winter and biomass burning in autumn with an order of winter > autumn > spring > summer. All aerosol species exhibited different diurnal cycles, of which Org presented a bimodal mode, SO42− and Cl− showed a flatter diurnal pattern, however, NO3− and NH4+ displayed more similar single-peak patterns. The conversion of SO2 to SO42− presented an obvious seasonal variation with summer > autumn > spring > winter driven by different factors. The conversion of NO2 to NO3− also showed a significant seasonal change characterized by autumn > summer and spring > winter controlled by different factors. Relative humidity, temperature and wind speed during the study period were significant meteorological elements influencing NR-PM1 and its species, and heavy haze pollution episodes largely occurred under high relative humidity and low wind speed. High potential source regions influencing NR-PM1 pollution in Beijing in all seasons presented dramatically distributions related to wind directions.

Characteristics and sources of water-soluble organic aerosol in a heavily polluted environment in Northern China

Water-soluble organic aerosol (WSOA) in fine particles (PM2.5) collected during wintertime in a polluted city (Handan) in Northern China was characterized using a High-Resolution Time-of-Flight Aerosol Mass Spectrometer (AMS). Through comparing with real-time measurements from a collocated Aerosol Chemical Speciation Monitor (ACSM), we determined that WSOA on average accounts for 29% of total organic aerosol (OA) mass and correlates tightly with secondary organic aerosol (SOA; Pearson's r = 0.95). The mass spectra of WSOA closely resemble those of ambient SOA, but also show obvious influences from coal combustion and biomass burning. Positive matrix factorization (PMF) analysis of the WSOA mass spectra resolved a water-soluble coal combustion OA (WS-CCOA; O/C = 0.17), a water-soluble biomass burning OA (WS-BBOA; O/C = 0.32), and a water-soluble oxygenated OA (WS-OOA; O/C = 0.89), which account for 10.3%, 29.3% and 60.4% of the total WSOA mass, respectively. The water-solubility of the OA factors was estimated by comparing the offline AMS analysis results with the ambient ACSM measurements. OOA has the highest water-solubility of 49%, consistent with increased hygroscopicity of oxidized organics induced by atmospheric aging processes. In contrast, CCOA is the least water soluble, containing 17% WS-CCOA. The distinct characteristics of WSOA from different sources extend our knowledge of the complex aerosol chemistry in the polluted atmosphere of Northern China and the water-solubility analysis may help us to understand better aerosol hygroscopicity and its effects on radiative forcing in this region.

An interlaboratory comparison of aerosol inorganic ion measurements by ion chromatography: implications for aerosol pH estimate

Abstract. Water-soluble inorganic ions such as ammonium, nitrate and sulfate are major components of fine aerosols in the atmosphere and are widely used in the estimation of aerosol acidity. However, different experimental practices and instrumentation may lead to uncertainties in ion concentrations. Here, an intercomparison experiment was conducted in 10 different laboratories (labs) to investigate the consistency of inorganic ion concentrations and resultant aerosol acidity estimates using the same set of aerosol filter samples. The results mostly exhibited good agreement for major ions Cl−, SO42-, NO3-, NH4+ and K+. However, F−, Mg2+ and Ca2+ were observed with more variations across the different labs. The Aerosol Chemical Speciation Monitor (ACSM) data of nonrefractory SO42-, NO3- and NH4+ generally correlated very well with the filter-analysis-based data in our study, but the absolute concentrations differ by up to 42 %. Cl− from the two methods are correlated, but the concentration differ by more than a factor of 3. The analyses of certified reference materials (CRMs) generally showed a good detection accuracy (DA) of all ions in all the labs, the majority of which ranged between 90 % and 110 %. The DA was also used to correct the ion concentrations to showcase the importance of using CRMs for calibration check and quality control. Better agreements were found for Cl−, SO42-, NO3-, NH4+ and K+ across the labs after their concentrations were corrected with DA; the coefficient of variation (CV) of Cl−, SO42-, NO3-, NH4+ and K+ decreased by 1.7 %, 3.4 %, 3.4 %, 1.2 % and 2.6 %, respectively, after DA correction. We found that the ratio of anion to cation equivalent concentrations (AE / CE) and ion balance (anions–cations) are not good indicators for aerosol acidity estimates, as the results in different labs did not agree well with each other. In situ aerosol pH calculated from the ISORROPIA II thermodynamic equilibrium model with measured ion and ammonia concentrations showed a similar trend and good agreement across the 10 labs. Our results indicate that although there are important uncertainties in aerosol ion concentration measurements, the estimated aerosol pH from the ISORROPIA II model is more consistent.

Comparison of five methodologies to apportion organic aerosol sources during a PM pollution event

This study presents a comparison of five methodologies to apportion primary (POA) and secondary organic aerosol (SOA) sources from measurements performed in the Paris region (France) during a highly processed PM pollution event. POA fractions, estimated from EC-tracer method and positive matrix factorization (PMF) analyses, conducted on measurements from PM10 filters, aerosol chemical speciation monitor (ACSM) and offline aerosol mass spectrometry (AMS), were all comparable (2.2–3.7 μg m−3 as primary organic carbon (POC)). Associated relative uncertainties (measurement + model) on POC estimations ranged from 8 to 50%. The best apportionment of primary traffic OA was achieved using key markers (EC and 1-nitropyrene) in the chemical speciation-based PMF showing more pronounced rush-hour peaks and greater correlation with NOx than other traffic related POC factors. All biomass burning-related factors were in good agreement, with a typical diel profile and a night-time increase linked to residential heating. If PMF applied to ACSM data showed good agreement with other PMF outputs corrected from dust-related factors (coarse PM), discrepancies were observed between individual POA factors (traffic, biomass burning) and directly comparable SOA factors and highly oxidized OA. Similar secondary organic carbon (SOC) concentrations (3.3 ± 0.1 μg m−3) were obtained from all approaches, except the SOA-tracer method (1.8 μg m−3). Associated uncertainties ranged from 14 to 52% with larger uncertainties obtained for PMF-chemical data, EC- and SOA-tracer methods. This latter significantly underestimated total SOA loadings, even including biomass burning SOA, due to missing SOA classes and precursors. None of the approaches was able to identify the formation mechanisms and/or precursors responsible for the highly oxidized SOA fraction associated with nitrate- and/or sulfate-rich aerosols (35% of OA). We recommend the use of a combination of different methodologies to apportion the POC/SOC concentrations/contributions to get the highest level of confidence in the estimates obtained.

Real-time non-refractory PM1 chemical composition, size distribution and source apportionment at a coastal industrial park in the Yangtze River Delta region, China

This study present real-time measurements of the chemical composition and particle number size distributions (PNSD) of submicron particulate matter (PM1) in winter at a coastal industrial park in the Yangtze River Delta region of China. Positive matrix factorization (PMF) analysis identified three PNSD factors and three organic aerosol (OA) factors. Contributions and potential source regions of these factors were investigated for four typical periods during the PM1 formation and dissipation process. Results show that the relative contributions from aged 250 nm- factor, fresh 35 nm- and 80 nm- factors were strongly affected by local fresh emissions and regional new particle formation. The non-refractory PM1 measured by Aerodyne aerosol chemical speciation monitor is indicative of the chemical composition of aged 250 nm-factor, but not fresh 35 nm- and 80 nm-factors. The contributions of NO3− and SO42− to NR-PM1 were largely dictated by whether the air mass trajectory went over the sea or the continent. NO3− was abundant (up to 44% of NR-PM1) in cold and dry continental air masses, while SO42− formation (up to 39% of NR-PM1) was preferred in humid and warm marine air masses. Among the three OA source factors, more-oxidized oxygenated OA (MO-OOA) was the most abundant OA factor (44–66% of total OA) throughout the entire field campaign, while an enhanced contribution of 39% from hydrocarbon-like OA (HOA) was observed prior to heavy pollution period. On average, secondary components SO42−, NO3−, NH4+, MO-OOA and less-oxidized oxygenated OA (LO-OOA) contributed 90 ± 7% of NR-PM1, while primary components HOA and Cl− accounted for the remaining 10 ± 7%.

Development and application of a mass closure PM<sub>2.5</sub> composition online monitoring system

Abstract. Online instruments have been widely applied for the measurement of PM2.5 and its chemical components; however, these instruments have a major shortcoming in terms of the lack or limited number of species in field measurements. To this end, a new mass closure PM2.5 online integrated system was developed and applied in this work to develop more comprehensive information on chemical species in PM2.5. For the new system, one isokinetic sampling system for PM2.5 was coupled with an aerosol chemical speciation monitor (Aerodyne, ACSM), an aethalometer (Magee, AE-31), an automated multi-metals monitor (Cooper Corporation, Xact-625) and a hybrid synchronized ambient particulate real-time analyzer monitor (Thermo Scientific, SHARP-5030i) to enable high-resolution temporal (1 h) measurements of organic matter, SO42-, NO3-, Cl−, NH4+, black carbon, important elements and PM2.5 mass concentrations. The new online integrated system was first deployed in Shenzhen, China, to measure the PM2.5 composition from 25 September to 30 October 2019. Our results showed that the average PM2.5 concentration in this work was 33 µg m−3, and the measured species reconstructed the PM2.5 well and almost formed a mass closure (94 %). The multi-linear engine (ME-2) model was employed for the comprehensive online PM2.5 chemical dataset to apportion the sources with predetermined constraints, in which the organic ion fragment m/z 44 in ACSM data was used as the tracer for secondary organic aerosol (SOA). Nine sources were determined and obtained reasonable time series and diurnal variations in this study, including identified SOA (23 %), secondary sulfate (22 %), vehicle emissions (18 %), biomass burning (11 %), coal burning (8.0 %), secondary nitrate (5.3 %), fugitive dust (3.8 %), ship emissions (3.7 %) and industrial emissions (2.1 %). The potential source contribution function (PSCF) analysis indicated that the major source area could be the region north of the sampling site. This is the first system in the world that can perform online measurements of PM2.5 components with a mass closure, thus providing a new powerful tool for PM2.5 long-term daily measurement and source apportionment.