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

Is replacing missing values of PM2.5 constituents with estimates using machine learning better for source apportionment than exclusion or median replacement?

East Asian countries have been conducting source apportionment of fine particulate matter (PM2.5) by applying positive matrix factorization (PMF) to hourly constituent concentrations. However, some of the constituent data from the supersites in South Korea was missing due to instrument maintenance and calibration. Conventional preprocessing of missing values, such as exclusion or median replacement, causes biases in the estimated source contributions by changing the PMF input. Machine learning (ML) can estimate the missing values by training on constituent data, meteorological data, and gaseous pollutants. Complete data from the Seoul Supersite in 2018 was taken, and a random 20% was set as missing. PMF was performed by replacing missing values with estimates. Percent errors of the source contributions were calculated compared to those estimated from complete data. Missing values were estimated using a random forest analysis. Estimation accuracy (r2) was as high as 0.874 for missing carbon species and low at 0.631 when ionic species and trace elements were missing. For the seven highest contributing sources, replacing the missing values of carbon species with estimates minimized the percent errors to 2.0% on average. However, replacing the missing values of the other chemical species with estimates increased the percent errors to more than 9.7% on average. Percent errors were maximal at 37% on average when missing values of ionic species and trace elements were replaced with estimates. Missing values, except for carbon species, need to be excluded. This approach reduced the percent errors to 7.4% on average, which was lower than those due to median replacement. Our results show that reducing the biases in source apportionment is possible by replacing the missing values of carbon species with estimates. To improve the biases due to missing values of the other chemical species, the estimation accuracy of the ML needs to be improved.

Evaluation of a new real-time source apportionment system of PM2.5 and its implication on rapid aging of vehicle exhaust

Accurate identification and rapid analysis of PM2.5 sources and formation mechanisms are essential to mitigate PM2.5 pollution. However, studies were limited in developing a method to apportion sources to the total PM2.5 mass in real-time. In this study, we developed a real-time source apportionment method based on chemical mass balance (CMB) modeling and a mass-closure PM2.5 composition online monitoring system in Shenzhen, China. Results showed that secondary sulfate, secondary organic aerosol (SOA), vehicle emissions and secondary nitrate were the four major PM2.5 sources during autumn 2019 in Shenzhen, together contributed 76 % of PM2.5 mass. The novel method was verified by comparing with other source apportionment methods, including offline filter analysis, aerosol mass spectrometry, and carbon isotopic analysis. The comparison of these methods showed that the new real-time method obtained results generally consistent with the others, and the differences were interpretable and implicative. SOA and vehicle emissions were the major PM2.5 and OA contributors by all methods. Further investigation on the OA sources indicated that vehicle emissions were not only the main source of primary organic aerosol (POA), but also the main contributor to SOA by rapid aging of the exhaust in the atmosphere. Our results demonstrated the great potential of the new real-time source apportionment method for aerosol pollution control and deep understandings on emission sources.

Atmospheric aerosol chemistry and source apportionment of PM10 using stable carbon isotopes and PMF modelling during fireworks over Hyderabad, southern India

This study examined the influence of fireworks on atmospheric aerosols over the Southern Indian city of Hyderabad during festival of Diwali using mass closure, stable carbon isotopes and the EPA-PMF model. Identification of chemical species in day and night time aerosol samples for 2019 and 2020 Diwali weeks showed increased concentrations of NH4+, NO3-, SO42-, K+, organic carbon (OC), Ba, Pb and Li, which were considered as tracers for fireworks. PM10 source apportionment was done using inorganic (trace elements, major ions) and carbonaceous (organic and elemental carbon; OC & EC) constituents, along with stable isotopic compositions of TC and EC. K+/Na+ ∼1 and K+nss/OC > 0.5 indicated contribution from fireworks. High NO3-, NH4+, Na+, Cl- and SO42- suggested the presence of deliquescent salts NaCl, NH4NO3 and (NH4)2SO4. TAE/TCE >1 suggested H+ exclusion, indicating possible presence of H2SO4 and NH4HSO4 in the aerosols. Ba, Pb, Sb, Sr and Fe increased by 305 (87), 12 (11), 12 (3), 3 (2) and 3 (4) times on Diwali nights, compared to pre-Diwali of 2019 (2020), and are considered as metallic tracers of fireworks. δ13CTC and δ13CEC in aerosols closely resembled that of diesel and C3 plant burning emissions, with meagre contribution from firecrackers during Diwali period. The δ13CEC was relatively depleted than δ13CTC and δ13COC. For both years, δ13COC-EC (δ13COC - δ13CEC) were positive, suggesting photochemical aging of aerosols during long-range transport, while for pre-Diwali 2019 and post-Diwali 2020, δ13COC-EC were negative with high OC/EC ratio, implying secondary organic aerosols formation. High toluene during Diwali week contributed to fresh SOA formation, which reacted with precursor 12C, leading to 13C depletions. Eight-factored EPA-PMF source apportionment indicated highest contribution from residue/waste burning, followed by marine/dust soil and fireworks, while least was contributed from solid fuel/coal combustion.

Control priority based on source-specific DALYs of PM2.5-bound heavy metals by PMF-PSCF-IsoSource model in urban and suburban Beijing

To determine the priority control sources, an approach was proposed to evaluate the source-specific contribution to health risks from inhaling PM2.5-bound heavy metals (PBHMs). A total of 482 daily PM2.5 samples were collected from urban and suburban areas of Beijing, China, between 2018 and 2019. In addition to the PMF-PSCF model, a Pb isotopic IsoSource model was built for more reliable source apportionment. By using the comprehensive indicator of disability-adjusted life years (DALYs), carcinogenic and noncarcinogenic health risks could be compared on a unified scale. The study found that the annual average concentrations of the total PBHMs were significantly higher in suburban areas than in urban areas, with significantly higher concentrations during the heating season than during the nonheating season. Comprehensive dust accounted for the largest contribution to the concentration of PBHMs, while coal combustion contributed the most to the DALYs associated with PBHMs. These results suggest that prioritizing the control of coal combustion could effectively reduce the disease burden associated with PBHMs, leading to notable public health benefits.

Characterizing the sources of ambient PM10 organic aerosol in urban and rural Catalonia, Spain

Organic aerosols (OA) have recently been shown to be the dominant contributor to the oxidative potential of airborne particulate matter in northeastern Spain. We collected PM10 filter samples every fourth day from January 2017 to March 2018 at two sampling stations located in Barcelona city and Montseny Natural Park, representing urban and rural areas, respectively. The chemical composition of PM10 was analyzed offline using a broad set of analytical instruments, including high-resolution time-of-flight mass spectrometry (HR-ToF-AMS), a total organic carbon analyzer (TCA), inductively coupled plasma atomic emission spectrometry (ICP-AES), inductively coupled plasma mass spectrometry (ICP-MS), ion chromatography (IC), and thermal-optical carbon analyzer. Source apportionment analysis of the water-soluble organic content of the samples measured via HR-ToF-AMS revealed two primary and two secondary sources of OA, which included biomass-burning OA (BBOA), sulfur-containing OA (SCOA), as well as summer- and winter‑oxygenated OA (SOOA and WOOA). The presence of hydrocarbon-like water-insoluble OA was also identified based on concentration trends in black carbon and nitrogen oxides. The results from the source apportionment analysis of the inorganic composition were correlated with different OA factors to assess potential source contributors. Barcelona showed significantly higher average water-soluble OA concentrations (5.63 ± 0.56 μg m-3) than Montseny (3.27 ± 0.37 μg m-3) over the sampling period. WOOA accounted for nearly 27 % of the averaged OA in Barcelona compared to only 7 % in Montseny. In contrast, SOOA had a greater contribution to OA in Montseny (47 %) than in Barcelona (24 %). SCOA and BBOA were responsible for 15-28 % of the OA at both sites. There were also seasonal variations in the relative contributions of different OA sources. Our overall results showed that local anthropogenic sources were primarily responsible for up to 70 % of ambient soluble OA in Barcelona, and regulating local-scale emissions could significantly improve air quality in urban Spain.

Modelling aerosol molecular markers in a 3D air quality model: Focus on anthropogenic organic markers

We developed and implemented in the 3D air quality model CHIMERE the formation of several key anthropogenic aerosol markers including one primary anthropogenic marker (levoglucosan) and 4 secondary anthropogenic markers (nitrophenols, nitroguaiacols, methylnitrocatechols and phthalic acid). Modelled concentrations have been compared to measurements performed at 12 locations in France for levoglucosan in winter 2014-15, and at a sub-urban station in the Paris region over the whole year 2015 for secondary molecular markers. While a good estimation of levoglucosan concentrations by the model has been obtained for a few sites, a strong underestimation was simulated for most of the stations especially for western locations due to a probable underestimation of residential wood burning emissions. The simulated ratio between wood burning organic matter and particulate phase levoglucosan is constant only at high OM values (>10 μg m^-3) indicating that using marker contribution ratio may be valid only under certain conditions. Concentrations of secondary markers were well reproduced by the model for nitrophenols and nitroguaiacols but were underestimated for methylnitrocatechols and phthalic acid highlighting missing formation pathways and/or precursor emissions. By comparing modelled to measured Gas/Particle Partitioning (GPP) of markers, the simulated partitioning of Semi-Volatile Organic Compounds (SVOCs) was evaluated. Except for nitroguaiacols and nitrophenols when ideality was assumed, the GPP for all the markers was underestimated and mainly driven by the hydrophilic partitioning. SVOCs GPP, and more generally of all SVOC contributing to the formation of SOA, could therefore be significantly underestimated by air quality models, especially when only the partitioning on the organic phase is considered. Our results show that marker modelling can give insights on some processes (such as precursor emissions or missing mechanisms) involved in SOA formation and could prove especially useful to evaluate the GPP in 3D air quality models.

Determination of Volatility Parameters of Secondary Organic Aerosol Components via Thermal Analysis

To date, there are limited data on the thermal properties of secondary organic aerosol (SOA) components. In this study, we employed an experimental method to evaluate the physical properties of some atmospherically relevant compounds. We estimated the thermodynamic properties of SOA components, in particularly some carboxylic acids. The molar heat capacity, melting point and enthalpy, and vaporization enthalpy of the samples were determined via differential scanning calorimetry and thermogravimetric analysis, and their vaporization enthalpy (ΔHvap) was estimated using Clausius–Clapeyron and Langmuir equations based on their thermogravimetric profiles. The thermodynamic properties of benzoic acid as a reference compound agree well with the reported values. The obtained specific heat capacities of benzoic acid, phthalic acid, pinic acid, ketopinic acid, cis-pinonic acid, terpenylic acid and diaterpenylic acid acetate (DTAA) are 118.1, 169.4, 189.9, 223.9, 246.1, 223.2, and 524.1 J mol−1 K−1, respectively. The ΔHvap of benzoic acid, phthalic acid, ketopinic acid, DTAA, and 3-methylbutane-1,2,3-tricarboxylic acid (3-MBTCA) are 93.2 ± 0.4, 131.6, 113.8, and 124.4 kJ mol−1, respectively. The melting and vaporization enthalpies of the SOA components range from 7.3 to 29.7 kJ mol−1.

Machine learning and theoretical analysis release the non-linear relationship among ozone, secondary organic aerosol and volatile organic compounds

Fine particulate matter (PM_2.5) and ozone (O₃) pollutions are prevalent air quality issues in China. Volatile organic compounds (VOCs) have significant impact on the formation of O₃ and secondary organic aerosols (SOA) contributing PM_2.5. Herein, we investigated 54 VOCs, O₃ and SOA in Tianjin from June 2017 to May 2019 to explore the non-linear relationship among O₃, SOA and VOCs. The monthly patterns of VOCs and SOA concentrations were characterized by peak values during October to March and reached a minimum from April to September, but the observed O₃ was exactly the opposite. Machine learning methods resolved the importance of individual VOCs on O₃ and SOA that alkenes (mainly ethylene, propylene, and isoprene) have the highest importance to O₃ formation; alkanes (C_n, n ≥ 6) and aromatics were the main source of SOA formation. Machine learning methods revealed and emphasized the importance of photochemical consumptions of VOCs to O₃ and SOA formation. Ozone formation potential (OFP) and secondary organic aerosol formation potential (SOAFP) calculated by consumed VOCs quantitatively indicated that more than 80% of the consumed VOCs were alkenes which dominated the O₃ formation, and the importance of consumed aromatics and alkenes to SOAFP were 40.84% and 56.65%, respectively. Therein, isoprene contributed the most to OFP at 41.45% regardless of the season, while aromatics (58.27%) contributed the most to SOAFP in winter. Collectively, our findings can provide scientific evidence on policymaking for VOCs controls on seasonal scales to achieve effective reduction in both SOA and O₃.

Source apportionment of carbonaceous aerosols in diverse atmospheric environments of China by dual-carbon isotope method

Carbonaceous aerosols are major components in PM_2.5 of both polluted and clean atmosphere. Accurate source apportionment of carbonaceous aerosols may support effective PM_2.5 control. Dual-carbon isotope method (¹⁴C and ¹³C) was adopted to identify the contribution of three main air pollution sources biogenic and biomass (f_bb), liquid fossil (f_liq.fossil) and coal (f_coal). The aerosol samples were collected at three types of sites with distinctly different degree of air pollution: urban, rural and regional background. The seasonal variation of source apportionment of the carbonaceous aerosols in urban Beijing was discussed. Modern biogenic and biomass made an absolute dominance of 92.9 ± 0.5% contribution to the carbonaceous aerosols at the background site Mt. Yulong due to long-range transport from Southeast Asia. The three main sources contributed jointly to the atmospheric carbonaceous aerosols at the rural site Wangdu and the urban site Beijing. The biogenic and biomass source was the major contribution in summer (47.0 ± 0.3%) and autumn (49.3 ± 0.3%) of Beijing, while coal source increased from summer (26.8 ± 13.8%) to autumn (34.7 ± 11.5%). Heating significantly increased the coal source to the dominant contribution (47.0 ± 16.9%) in winter of Beijing. Separate day and night time coal contributions were used to evaluate the two origins of coal combustion: industrial use vs. residential use. The results of source apportionment for carbonaceous aerosols provide scientific support for the prevention and control of air pollution.

Apportionment of black and brown carbon spectral absorption sources in the urban environment of Athens, Greece, during winter

This study examines the spectral properties and source characteristics of absorbing aerosols (BC: Black Carbon; BrC: Brown Carbon, based on aethalometer measurements) in the urban background of Athens during December 2016-February 2017. Using common assumptions regarding the spectral dependence of absorption due to BC (AAE_BC = 1) and biomass burning (AAE_bb = 2), and calculating an optimal AAE_ff value for the dataset (1.18), the total spectral absorption was decomposed into five components, corresponding to absorption of BC and BrC from fossil-fuel (ff) combustion and biomass burning (bb), and to secondary BrC estimated using the BC-tracer minimum R-squared (MRS) method. Substantial differences in the contribution of various components to the total absorption were found between day and night, due to differences in emissions and meteorological dynamics, while BrC and biomass burning aerosols presented higher contributions at shorter wavelengths. At 370 nm, the absorption due to BC_ff contributed 36.3% on average, exhibiting a higher fraction (58.1%) during daytime, while the mean BC_bb absorption was estimated at 18.4%. The mean absorption contributions due to BrC_ff, BrC_bb and BrC_sec were 6.7%, 32.3% and 4.9%, respectively. The AbsBC_ff,370 component maximized during the morning traffic hours and was strongly correlated with NO_x (R² = 0.76) and CO (R² = 0.77), while a similar behavior was seen for the AbsBrC_ff,370 component. AbsBC_bb and AbsBrC_bb levels escalated during nighttime and were highly associated with nss-K⁺ and with the organic aerosol (OA) components related to fresh and fast-oxidized biomass burning (BBOA and SV-OOA) as obtained from ACSM measurements. Multiple linear regression was used to attribute BrC absorption to five OA components and to determine their absorption contributions and efficiencies, revealing maximum contributions of BBOA (33%) and SV-OOA (21%). Sensitivity analysis was performed in view of the methodological uncertainties and supported the reliability of the results, which can have important implications for radiative transfer models.

NPAHs and OPAHs in the atmosphere of two central European cities: Seasonality, urban-to-background gradients, cancer risks and gas-to-particle partitioning

Derivatives of polycyclic aromatic hydrocarbons (PAHs) such as nitrated- and oxygenated-PAHs (NPAHs and OPAHs) could be even more toxic and harmful for the environment and humans than PAHs. We assessed the spatial and seasonal variations of NPAHs and OPAHs atmospheric levels, their cancer risks and their gas-to-particle partitioning. To this end, about 250 samples of fine particulate matter (PM2.5) and 50 gaseous samples were collected in 2017 in central Europe in the cities of Brno and Ljubljana (two traffic and two urban background sites) as well as one rural site. The average particulate concentrations were ranging from below limit of quantification to 593 pg m-3 for Σ9NPAHs and from 1.64 to 4330 pg m-3 for Σ11OPAHs, with significantly higher concentrations in winter compared to summer. In winter, the particulate levels of NPAHs and OPAHs were higher at the traffic site compared to the urban background site in Brno while the opposite was found in Ljubljana. NPAHs and OPAHs particulate levels were influenced by the meteorological parameters and co-varied with several air pollutants. The significance of secondary formation on the occurrence of some NPAHs and OPAHs is indicated. In winter, 27-47% of samples collected at all sites were above the acceptable lifetime carcinogenic risk. The gas-particle partitioning of NPAHs and OPAHs was influenced by their physico-chemical properties, the season and the site-specific aerosol composition. Three NPAHs and five OPAHs had higher particulate mass fractions at the traffic site, suggesting they could be primarily emitted as particles from vehicle traffic and subsequently partitioning to the gas phase along air transport. This study underlines the importance of inclusion of the gas phase in addition to the particulate phase when assessing the atmospheric fate of polycyclic aromatic compounds and also when assessing the related health risk.

Overview of the French Operational Network for In Situ Observation of PM Chemical Composition and Sources in Urban Environments (CARA Program)

The CARA program has been running since 2008 by the French reference laboratory for air quality monitoring (LCSQA) and the regional monitoring networks, to gain better knowledge—at a national level—on particulate matter (PM) chemistry and its diverse origins in urban environments. It results in strong collaborations with international-level academic partners for state-of-the-art, straightforward, and robust results and methodologies within operational air quality stakeholders (and subsequently, decision makers). Here, we illustrate some of the main outputs obtained over the last decade, thanks to this program, regarding methodological aspects (both in terms of measurement techniques and data treatment procedures) as well as acquired knowledge on the predominant PM sources. Offline and online methods are used following well-suited quality assurance and quality control procedures, notably including inter-laboratory comparison exercises. Source apportionment studies are conducted using various receptor modeling approaches. Overall, the results presented herewith underline the major influences of residential wood burning (during the cold period) and road transport emissions (exhaust and non-exhaust ones, all throughout the year), as well as substantial contributions of mineral dust and primary biogenic particles (mostly during the warm period). Long-range transport phenomena, e.g., advection of secondary inorganic aerosols from the European continental sector and of Saharan dust into the French West Indies, are also discussed in this paper. Finally, we briefly address the use of stable isotope measurements (δ15N) and of various organic molecular markers for a better understanding of the origins of ammonium and of the different organic aerosol fractions, respectively.