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Spatial and temporal data of particulate matter (PM) are limited in Indonesia; hence cost-effective and robust instruments to monitor PM concentration could complete data coverage. The low-cost sensor (LCS) Alphasense OPC-N2 provides real-time PM concentration data and is relatively simple to install and deploy. This paper presents data from an OPC-N2 sensor collocated with a PM10 Beta Attenuation Monitor (BAM). The study was carried out at an air quality monitoring site in North Jakarta belonging to the provincial government. The location is considered suitable for evaluating the performance of OPC-N2 micro sensor as it is a representative of a typical Indonesian urbanized area with a range of pollutant sources, including sea-sourced aerosols. At the same site, a filter-based Gent Sampler (GS) measuring both PM10 and PM2.5 was also deployed. The study showed that 30-minutely and daily average concentrations data for PM10 measured by OPC-N2 were lower than that of BAM measurements in both averaged durations by approximately 50%. The comparison between OPC-N2 and GS for PM10 showed that OPC-N2 measurement was underestimated but it was overestimated for PM2.5. Nonetheless, correlations of OPC-N2 and BAM were 0.530 and 0.607 for PM10 and PM2.5, respectively. These results were comparable to other low-cost sensor evaluation studies in different countries, suggesting that the sensor can represent temporal variation of the reference measurement.

The nature and origin of organic aerosol in the atmosphere remain unclear. The gas–particle partitioning of semi-volatile organic compounds (SVOCs) that constitute primary organic aerosols (POAs) and the multigenerational chemical aging of SVOCs are particularly poorly understood. The volatility basis set (VBS) approach, implemented in air quality models such as WRF-Chem (Weather Research and Forecasting model with Chemistry), can be a useful tool to describe emissions of POA and its chemical evolution. However, the evaluation of model uncertainty and the optimal model parameterization may be expensive to probe using only WRF-Chem simulations. Gaussian process emulators, trained on simulations from relatively few WRF-Chem simulations, are capable of reproducing model results and estimating the sources of model uncertainty within a defined range of model parameters. In this study, a WRF-Chem VBS parameterization is proposed; we then generate a perturbed parameter ensemble of 111 model runs, perturbing 10 parameters of the WRF-Chem model relating to organic aerosol emissions and the VBS oxidation reactions. This allowed us to cover the model's uncertainty space and to compare outputs from each run to aerosol mass spectrometer observations of organic aerosol concentrations and O:C ratios measured in New Delhi, India. The simulations spanned the organic aerosol concentrations measured with the aerosol mass spectrometer (AMS). However, they also highlighted potential structural errors in the model that may be related to unsuitable diurnal cycles in the emissions and/or failure to adequately represent the dynamics of the planetary boundary layer. While the structural errors prevented us from clearly identifying an optimized VBS approach in WRF-Chem, we were able to apply the emulator in the following two periods: the full period (1–29 May) and a subperiod period of 14:00–16:00 h LT (local time) on 1–29 May. The combination of emulator analysis and model evaluation metrics allowed us to identify plausible parameter combinations for the analyzed periods. We demonstrate that the methodology presented in this study can be used to determine the model uncertainty and to identify the appropriate parameter combination for the VBS approach and hence to provide valuable information to improve our understanding of OA production.

Air pollution in urban environments has been shown to have a negative impact on air quality and human health, particularly in megacities. Over recent decades, Delhi, India, has suffered high atmospheric pollution, with significant particulate matter (PM) concentrations as a result of anthropogenic activities. Organic aerosols (OAs) are composed of thousands of different chemical species and are one of the main constituents of submicron particles. However, quantitative knowledge of OA composition, their sources and their processes in urban environments is still limited. This is important particularly in India, as Delhi is a massive, inhomogeneous conurbation, where we would expect the apportionment and concentrations to vary depending on where in Delhi the measurements/source apportionment is performed, indicating the need for multisite measurements. This study presents the first multisite analysis carried out in India over different seasons, with a focus on identifying OA sources. The measurements were taken during 2018 at two sites in Delhi, India. One site was located at the India Meteorological Department, New Delhi (ND). The other site was located at the Indira Gandhi Delhi Technical University for Women, Old Delhi (OD). Non-refractory submicron aerosol (NR-PM1) concentrations (ammonium, nitrate, sulfate, chloride and organic aerosols) of four aerosol mass spectrometers were analysed. Collocated measurements of volatile organic compounds, black carbon, NOx and CO were performed. Positive matrix factorisation (PMF) analysis was performed to separate the organic fraction, identifying a number of conventional factors: hydrocarbon-like OAs (HOAs) related to traffic emissions, biomass burning OAs (BBOAs), cooking OAs (COAs) and secondary OAs (SOAs). A composition-based estimate of PM1 is defined by combining black carbon (BC) and NR-PM1 (C-PM1= BC + NR-PM1). No significant difference was observed in C-PM1 concentrations between sites, OD (142 ± 117 µg m−3) compared to ND (123 ± 71 µg m3), from post-monsoon measurements. A wider variability was observed between seasons, where pre-monsoon and monsoon showed C-PM1 concentrations lower than 60 µg m−3. A seasonal variation in C-PM1 composition was observed; SO42- showed a high contribution over pre-monsoon and monsoon seasons, while NO3- and Cl− had a higher contribution in winter and post-monsoon. The main primary aerosol source was from traffic, which is consistent with the PMF analysis and Aethalometer model analysis. Thus, in order to reduce PM1 concentrations in Delhi through local emission controls, traffic emission control offers the greatest opportunity. PMF–aerosol mass spectrometer (AMS) mass spectra will help to improve future aerosol source apportionment studies. The information generated in this study increases our understanding of PM1 composition and OA sources in Delhi, India. Furthermore, the scientific findings provide significant information to strengthen legislation that aims to improve air quality in India.

Covid lockdown presented an important opportunity to study relatively cleaner conditions in India. The complex factors of power production, industry, and transportation could be more carefully dissected because of the extreme reduction in the influence of the latter two emission sources. Measurements of cloud condensation nuclei (CCN) activity and other chemical properties of atmospheric aerosols showed that newly formed aerosol particles were produced in the SO2 plume from a large coal-fired power plant, contrary to normal conditions of heavy pollution. The sulfate-rich particles had high CCN activity and number concentration, indicating high cloud-forming potential. Examining the sensitivity of CCN properties under relatively clean conditions over India provides important new constraints on the perturbations of past and future climate forcing by anthropogenic emissions. Because most sensitive regime of aerosol climate forcing on cloud development is the midpoint of relatively clean conditions afforded by the Covid lockdown between background and polluted conditions.

The nature and origin of organic aerosol in the atmosphere remain unclear. The gas-particle partitioning of semi-volatile organic compounds (SVOC) that constitute primary organic aerosols (POA) and the multigenerational chemical aging of SVOCs are particularly poorly understood. The volatility basis set (VBS) approach, implemented in air quality models such as WRF-Chem, can be a useful tool to describe POA production and aging. However, the main disadvantage is its complexity, making the evaluation of model uncertainty and the optimal model parameterisation expensive to probe using only WRF-Chem simulations. Gaussian process emulators, trained on simulations from relatively few WRF-Chem simulations, are capable of reproducing model results and estimating the sources of model uncertainty within a defined range of model parameters. In this study, a WRF-Chem VBS parameterisation is proposed; we then generate a perturbed parameter ensemble of 111 model runs, perturbing ten parameters of the WRF-Chem model relating to organic aerosol emissions and the VBS oxidation reactions. This allowed us to cover the model’s uncertainty space and compare output from each run to aerosol mass spectrometer observations of organic aerosol concentrations and O:C ratios measured in New Delhi, India. The simulations spanned the organic aerosol concentrations measured with the AMS. However, they also highlighted potential structural errors in the model that may be related to unsuitable diurnal cycles in the emissions and/or failure to adequately represent the dynamics of the planetary boundary layer. While the structural errors prevented us from clearly identifying an optimised VBS approach in WRF-Chem, we were able to apply the emulator in two periods: the full period (1st–29th May) and the period 14:00–16:00 hrs local time, 1st–29th May. The combination of emulator analysis and model evaluation metrics allowed us to identify plausible parameter combinations for the analysed periods. We demonstrate that the methodology presented in this study can be used to determine the model uncertainty and identify the appropriate parameter combination for the VBS approach, and hence provide valuable information to improve our understanding on SOA production.

Many cities in India experience severe deterioration of air quality in winter. Particulate matter is a key atmospheric pollutant that impacts millions of people. In particular, the high mass concentration of particulate matter reduces visibility, which has severely damaged the economy and endangered human lives. But the underlying chemical mechanisms and physical processes responsible for initiating haze and fog formation remain poorly understood. Here we present the measurement results of chemical composition of particulate matter in Delhi and Chennai. We find persistently high chloride in Delhi and episodically high chloride in Chennai. These measurements, combined with thermodynamic modelling, suggest that in the presence of excess ammonia in Delhi, high local emission of hydrochloric acid partitions into aerosol water. The highly water-absorbing and soluble chloride in the aqueous phase substantially enhances aerosol water uptake through co-condensation, which sustains particle growth, leading to haze and fog formation. We therefore suggest that the high local concentration of gas-phase hydrochloric acid, possibly emitted from plastic-contained waste burning and industry, causes some 50% of the reduced visibility. Our work implies that identifying and regulating gaseous hydrochloric acid emissions could be critical to improve visibility and human health in India. Half of the reduced visibility due to haze formation in cities in India is attributed to local emission of gas-phase hydrochloric acid from waste-burning and industry, according to measurements of particulate matter and thermodynamic modelling.

In this paper, the characteristics of non-refractory aerosol using an International Civil Aviation Organization (ICAO) compliant sampling system emitted from two gas turbine relevant sources are reported, namely: an in-service turboshaft helicopter engine and a development combustor rig. Positive Matrix Factorisation (PMF) analysis was applied on an Aerosol Mass Spectrometer's (AMS) Unit Mass Resolution (UMR) organic aerosol (OA) data to identify three chemical factors: one unburnt fuel factor (AlkOA; Alkane Organic Aerosol) and two factors formed through oxidative processes: Semi Volatile Oxygenated Organic Aerosol (SV-OOA) and Quenched Organic Aerosol (QOA). The AlkOA factor's mass concentration correlated with Elemental Carbon (EC), an incomplete combustion tracer. The SV-OOA factor's mass concentration correlated with AMS-detected sulphate and Organic Carbon (OC) as characterised by a Sunset semi-continuous Analyser, with a high proportion of the OC converted to CO2 at lower temperatures (≤475 °C) during the OC analysis, suggesting a higher volatility. The QOA factor's mass concentration corresponded with higher quantities of OC converted to CO2 at the highest temperature (870 °C) during the OCEC analysis protocol. The QOA factor comprised large quantities of AMS-detected organic mass concentrations (20–50%) for the IP Rig. In addition, issues were seen with the OCEC analyser, and future strategies for operation for sampling from aviation sources are considered. The work characterises the available chemical speciation present in the particulate matter phase within an ICAO compliant nvPM sampling system for in-service and development combustor rigs, and comparisons are made between mass spectra seen within this methodology and in evolved plumes.

Rapid economic growth and development have exacerbated air quality problems across India, driven by many poorly understood pollution sources and understanding their relative importance remains critical to characterising the key drivers of air pollution. A comprehensive suite of measurements of 90 non-methane hydrocarbons (NMHCs) (C2–C14), including 12 speciated monoterpenes and higher molecular weight monoaromatics, were made at an urban site in Old Delhi during the pre-monsoon (28-May to 05-Jun 2018) and post-monsoon (11 to 27-Oct 2018) seasons using dual-channel gas chromatography (DC-GC-FID) and two-dimensional gas chromatography (GC×GC-FID). Significantly higher mixing ratios of NMHCs were measured during the post-monsoon campaign, with a mean night-time enhancement of around 6. Like with NOx and CO, strong diurnal profiles were observed for all NMHCs, except isoprene, with very high NMHC mixing ratios between 35–1485 ppbv. The sum of mixing ratios of benzene, toluene, ethylbenzene and xylenes (BTEX) routinely exceeded 100 ppbv at night during the post-monsoon period, with a maximum measured mixing ratio of monoaromatic species of 370 ppbv. The mixing ratio of highly reactive monoterpenes peaked at around 6 ppbv in the post-monsoon campaign and correlated strongly with anthropogenic NMHCs, suggesting a strong non-biogenic source in Delhi. A detailed source apportionment study was conducted which included regression analysis to CO, acetylene and other NMHCs, hierarchical cluster analysis, EPA UNMIX 6.0, principal component analysis/absolute principal component scores (PCA/APCS) and comparison with NMHC ratios (benzene/toluene and i-/n-pentane) in ambient samples to liquid and solid fuels. These analyses suggested the primary source of anthropogenic NMHCs in Delhi was from traffic emissions (petrol and diesel), with average mixing ratio contributions from Unmix and PCA/APCS models of 38% from petrol, 14% from diesel and 32% from liquified petroleum gas (LPG) with a smaller contribution (16%) from solid fuel combustion. Detailed consideration of the underlying meteorology during the campaigns showed that the extreme night-time mixing ratios of NMHCs during the post-monsoon campaign were the result of emissions into a very shallow and stagnant boundary layer. The results of this study suggest that despite widespread open burning in India, traffic-related petrol and diesel emissions remain the key drivers of gas-phase urban air pollution in Delhi.

Air pollution in urban environments has been shown to have a negative impact on air quality and human health, particularly in megacities. Over recent decades, Delhi, India has suffered high atmospheric pollution, with significant particulate matter (PM) concentrations as result of anthropogenic activities. Organic aerosols (OA) are composed of thousands of different chemical species and are one of the main constituents of submicron particles. However, quantitative knowledge of OA composition, their sources and processes in urban environments is still limited. This is important particularly in India, as Delhi is a massive, inhomogeneous conurbation, which we would expect that the apportionment and concentrations will vary depending on where in Delhi the measurements/source apportionment is performed, indicating the need of multi-site measurements. This study presents the first multisite analysis carried out in India over different seasons, with a focus on identifying OA sources. The measurements were taken during 2018 at two sites in Delhi, India. One site was located at the India Meteorological Department, New Delhi (ND). The other site was located at the Indira Gandhi Delhi Technical University for Women, Old Delhi (OD). Non-refractory submicron aerosol (NR-PM1) concentrations (ammonium, nitrate, sulphate, chloride and organic aerosols) of four aerosol mass spectrometers were analysed. Collocated measurements of VOC, black carbon, NOx and CO were performed. Positive matrix factorization (PMF) analysis was performed to separate the organic fraction, identifying a number of conventional factors: hydrocarbon-like OA (HOA) related to traffic emissions, biomass burning OA (BBOA), cooking OA (COA) and secondary OA (SOA). A composition-based estimate of PM1 is defined by combining BC and NR-PM1 (C-PM1 = BC + NR-PM1). No significant difference was observed on C-PM1 concentrations between sites; OD (142 ± 117 µg m−3) compared to ND (123 ± 71 µg m−3), from post-monsoon measurements. A wider variability was observed between seasons, where pre-monsoon and monsoon showed C-PM1 concentrations lower than 60 µg m−3. A seasonal variation in C-PM1 composition was observed; SO42− showed a high contribution over pre-monsoon and monsoon seasons while NO3− and Cl− had a higher contribution in winter and post-monsoon. The main primary aerosol source was from traffic, which is consistent with the PMF analysis and aethalometer model analysis. Thus, in order to reduce PM1 concentrations in Delhi through local emission controls traffic emissions control offers the greatest opportunity. PMF-AMS mass spectra will help to improve future aerosol source apportionment studies. The information generated in this study increases our understanding of PM1 composition and OA sources in Delhi, India. Furthermore, the scientific findings provide significant information to strengthen legislation that aims to improve air quality in India.

Polycyclic aromatic hydrocarbons (PAHs) are ubiquitous pollutants in air, soil and water and known to have harmful effects on human health and the environment. The diurnal and nocturnal variation of 17-PAHs in ambient particle-bound PAHs were measured in urban Beijing (China) and Delhi (India) during the summer season using GC-Q-TOF-MS. The mean concentration of particles less than 2.5 microns (PM2.5) observed in Delhi was 3.6 times higher than in Beijing during the measurement period in both the day-time and night-time. In Beijing, the mean concentration of the sum of the 17 PAHs (∑17-PAHs) was 8.2 ± 5.1 ng m−3 in daytime, with the highest contribution from Indeno[1,2,3-cd]pyrene (12 %), while at night-time the total PAHs was 7.2 ± 2.0 ng m−3, with the largest contribution from Benzo[b]fluoranthene (14 %). In Delhi, the mean ∑17-PAHs was 13.6 ± 5.9 ng m−3 in daytime, and 22.7 ± 9.4 ng m−3 at night-time, with the largest contribution from Indeno[1,2,3-cd]pyrene in both the day (17 %) and night (20 %). Elevated mean concentrations of total PAHs in Delhi observed at night were attributed to emissions from vehicles and biomass burning and to meteorological conditions leading to their accumulation from a stable and low atmospheric boundary layer. Local emission sources were typically identified as the major contributors to total measured PAHs, however, in Delhi 25 % of the emissions were attributed to long-range atmospheric transport. Major emission sources were characterized based on the contribution from each class of PAHs, with the 4, 5, and 6 ring PAHs accounting ~ 95 % of the total PM2.5-bound PAHs mass in both locations. The high contribution of 5 ring PAHs to total PAH concentration in summer Beijing and Delhi suggests a high contribution from petroleum combustion. In Delhi, a high contribution from 6 ring PAHs was observed at night, suggesting a potential emission source from the combustion of fuel and oil in power generators, widely used in Delhi. The lifetime excess lung cancer risk (LECR) was calculated for Beijing and Delhi, with the highest estimated risk attributed to Delhi (LECR = 155 per million people), 2.2 times higher than Beijing risk assessment value (LECR = 70 per million people). Finally, we have assessed the emission control policies in each city and identified those major sectors that could be subject to mitigation measures.

Atmospheric aerosol particles, known for their direct interaction with incoming solar radiations (direct effect) and for perturbation of the cloud properties (indirect effect) by acting as cloud condensation nuclei (CCN), represents largest uncertainty in the current and future understanding of the climate change. In part, this uncertainty is attributed to the lack of accurate measurements of aerosol physical and chemical properties for the improvement of various schemes in prognostic modelling useful for the effective prediction of cloud and precipitation formation. The Indian tropical region, constitutes ~18% of the world’s total population spread heterogeneously over diverse land cover, experiences a distinctive meteorological phenomenon by means of Indian Summer Monsoon (ISM). Thus, the sources, chemical properties and characteristics of aerosols are also expected to have significant variations over the Indian subcontinent depending upon the location and seasons. Online continuous measurements of NR-PM1 (Non refractory particulate matter ≤1 µm) have been carried out in near real-time using ACSM (Aerosol Chemical Speciation Monitor) at a marine urban location of Chennai, from 4th January to 2nd February, 2019, complimented by simultaneous measurements of meteorological parameters. Average NR-PM1 mass concentration for the duration of the measurements was 30.37±28.31 µg/m3 with organics constituting major fraction of ~47.43% followed by sulphate (~33.34%), ammonium (~11.89%), nitrate (~4.57%) and chloride (~2.74%). Back trajectory analysis using HYSPLIT model enabled the classification of air samples measured in to three periods: “Continental polluted”, “Marine polluted” and “Clean marine”. The polluted periods were distinguished by the potential biomass burning event, which occurs during the regional festival Bhogi, celebrated on 14th of January in this part of the country. During this period the organics had a peak concentration of 211 µg/m3 followed by chloride ~ 42 µg/m3. During the clean marine period, low mass concentration of PM1 is attributed to change in meteorological conditions accompanied by airmass originating from the Bay of Bengal. The average mass concentration of NR-PM1 during this period was observed to be 7.14±2.78 µg/m3, which is ~5 times lesser than the polluted period. A comprehensive source apportionment study was carried out using Positive Matrix Factorization (PMF) model implemented through the multilinear engine tool (ME-2) in Source Finder (SoFi) graphical user interface, to understand the contribution of primary and secondary sources to the organic aerosols. Primary anthropogenic emissions contributed on average ~45% (~19% from traffic, ~16.7% from cooking, ~10% from biomass burning) to the total organic mass for entire measurement period, while the major contribution was associated with secondary formation ~55%. On the other hand, for clean marine period, the fractional contribution of secondary formation to PM1 increased to ~75% to 85%, while that of primary emissions decreased to less than ~15%.In brief, these findings indicate the influence of oceanic air masses on aerosol mass concentration and composition. Further details will be presented.

Atmospheric black carbon makes an important but poorly quantified contribution to the warming of the global atmosphere. Laboratory and modelling studies have shown that the addition of non-black carbon materials to black carbon particles may enhance the particles’ light absorption by 50 to 60% by refracting and reflecting light. Real world experimental evidence for this ‘lensing’ effect is scant and conflicting, showing that absorption enhancements can be less than 5% or as large as 140%. Here we present simultaneous quantifications of the composition and optical properties of individual atmospheric black carbon particles. We show that particles with a mass ratio of non-black carbon to black carbon of less than 1.5, which is typical of fresh traffic sources, are best represented as having no absorption enhancement. In contrast, black carbon particles with a ratio greater than 3, which is typical of biomass burning emissions, are best described assuming optical lensing leading to an absorption enhancement. We introduce a generalised hybrid model approach for estimating scattering and absorption enhancements based on laboratory and atmospheric observations. We conclude that the occurrence of the absorption enhancement of black carbon particles is determined by the particles’ mass ratio of non-black carbon to black carbon.

A number of inorganic (nitryl chloride, ClNO2; chlorine, Cl2; and hypochlorous acid, HOCl) and chlorinated, oxygenated volatile organic compounds (ClOVOCs) have been measured in Manchester, UK during October and November 2014 using time-of-flight chemical ionisation mass spectrometry (ToF-CIMS) with the I− reagent ion. ClOVOCs appear to be mostly photochemical in origin, although direct emission from vehicles is also suggested. Peak concentrations of ClNO2, Cl2 and HOCl reach 506, 16 and 9 ppt respectively. The concentrations of ClNO2 are comparable to measurements made in London, but measurements of ClOVOCs, Cl2 and HOCl by this method are the first reported in the UK. Maximum HOCl and Cl2 concentrations are found during the day and ClNO2 concentrations remain elevated into the afternoon if photolysis rates are low. Cl2 exhibits a strong dependency on shortwave radiation, further adding to the growing body of evidence that it is a product of secondary chemistry. However, night-time emission is also observed. The contribution of ClNO2, Cl2 and ClOVOCs to the chlorine radical budget suggests that Cl2 can be a greater source of Cl than ClNO2, contributing 74 % of the Cl radicals produced on a high radiant-flux day. In contrast, on a low radiant-flux day, this drops to 14 %, as both Cl2 production and loss pathways are inhibited by reduced photolysis rates. This results in ClNO2 making up the dominant fraction (83 %) on low radiant-flux days, as its concentrations are still high. As most ClOVOCs appear to be formed photochemically, they exhibit a similar dependence on photolysis, contributing 3 % of the Cl radical budget observed here.

Food-cooking organic aerosols (COA) are one of the primary sources of submicron particulate matter in urban environments. However, there are still many questions surrounding source apportionment related to instrumentation as well as semivolatile partitioning because COA evolve rapidly in the ambient air, making source apportionment more complex. Online measurements of emissions from cooking different types of food were performed in a laboratory to characterize particles and gases. Aerosol mass spectrometer (AMS) measurements showed that the relative ionization efficiency for OA was higher (1.56-3.06) relative to a typical value of 1.4, concluding that AMS is over-estimating COA and suggesting that previous studies likely over-estimated COA concentrations. Food-cooking mass spectra were generated using AMS, and gas and particle food markers were identified with filter inlets for gases and aerosols-chemical ionization mass spectrometer (CIMS) measurements to be used in future food cooking-source apportionment studies. However, there is a considerable variability in both gas and particle markers, and dilution plays an important role in the particle mass budget, showing the importance of using these markers with caution during receptor modeling. These findings can be used to better understand the chemical composition of COA, and they provides useful information to be used in future source-apportionment studies.

Over the past decade, there has been an increasing interest in short-term events that negatively affect air quality such as bonfires and fireworks. High aerosol and gas concentrations generated from public bonfires or fireworks were measured in order to understand the night-time chemical processes and their atmospheric implications. Nitrogen chemistry was observed during Bonfire Night with nitrogen containing compounds in both gas and aerosol phases and further N2O5 and ClNO2 concentrations, which depleted early next morning due to photolysis of NO3 radicals and ceasing production. Particulate organic oxides of nitrogen (PONs) concentrations of 2.8 μg m-3 were estimated using the m / z 46 : 30 ratios from aerosol mass spectrometer (AMS) measurements, according to previously published methods. Multilinear engine 2 (ME-2) source apportionment was performed to determine organic aerosol (OA) concentrations from different sources after modifying the fragmentation table and it was possible to identify two PON factors representing primary (pPON-ME2) and secondary (sPON-ME2) contributions. A slight improvement in the agreement between the source apportionment of the AMS and a collocated AE-31 Aethalometer was observed after modifying the prescribed fragmentation in the AMS organic spectrum (the fragmentation table) to determine PON sources, which resulted in an r2 Combining double low line 0.894 between biomass burning organic aerosol (BBOA) and babs-470wb compared to an r2 Combining double low line 0.861 obtained without the modification. Correlations between OA sources and measurements made using time-of-flight chemical ionisation mass spectrometry with an iodide adduct ion were performed in order to determine possible gas tracers to be used in future ME-2 analyses to constrain solutions. During Bonfire Night, strong correlations (r2) were observed between BBOA and methacrylic acid (0.92), acrylic acid (0.90), nitrous acid (0.86), propionic acid, (0.85) and hydrogen cyanide (0.76). A series of oxygenated species and chlorine compounds showed good correlations with sPON-ME2 and the low volatility oxygenated organic aerosol (LVOOA) factor during Bonfire Night and an event with low pollutant concentrations. Further analysis of pPON-ME2 and sPON-ME2 was performed in order to determine whether these PON sources absorb light near the UV region using an Aethalometer. This hypothesis was tested by doing multilinear regressions between babs-470wb and BBOA, sPON-ME2 and pPON-ME2. Our results suggest that sPON-ME2 does not absorb light at 470 nm, while pPON-ME2 and LVOOA do absorb light at 470 nm. This may inform black carbon (BC) source apportionment studies from Aethalometer measurements, through investigation of the brown carbon contribution to babs-470wb.