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The oxidative potential (OP) of particulate matter (PM) is a major driver of PM-associated health effects. In India, the emission sources defining PM-OP, and their local/regional nature, are yet to be established. Here, to address this gap we determine the geographical origin, sources of PM, and its OP at five Indo-Gangetic Plain sites inside and outside Delhi. Our findings reveal that although uniformly high PM concentrations are recorded across the entire region, local emission sources and formation processes dominate PM pollution. Specifically, ammonium chloride, and organic aerosols (OA) from traffic exhaust, residential heating, and oxidation of unsaturated vapors from fossil fuels are the dominant PM sources inside Delhi. Ammonium sulfate and nitrate, and secondary OA from biomass burning vapors, are produced outside Delhi. Nevertheless, PM-OP is overwhelmingly driven by OA from incomplete combustion of biomass and fossil fuels, including traffic. These findings suggest that addressing local inefficient combustion processes can effectively mitigate PM health exposure in northern India.
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Air quality is of large concern in the city of Krakow, southern Poland. A comprehensive study was launched by us in which two PM fractions (PM1 and PM10) were sampled during 1-year campaign, lasting from April 21, 2018 to March 19, 2019. A suite of modern analytical methods was used to characterize the chemical composition of the collected samples. The contents of 14 sugars, sugar alcohols and anhydrosugars, 16 polycyclic aromatic hydrocarbons, selected metals and non-metals and ions were analyzed, in addition to organic and elemental carbon content. The carbon isotope composition in both analysed PM fractions, combined with an isotope-mass balance method, allowed to distinguish three main components of carbonaceous emissions in the city: (1) emissions related to combustion of hard coal, (2) emissions related to road transport, and (3) biogenic emissions. The heating season emissions from coal combustion had the biggest contribution to the reservoir of carbonaceous aerosols in the PM10 fraction (44%) and, together with the biogenic emission, they were the biggest contributors to the PM1 fraction (41% and 44%, respectively). In the non-heating season, the dominant source of carbon in PM10 and PM1 fraction were the biogenic emissions (48 and 54%, respectively).
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97% of the urban population in the EU in 2019 were exposed to an annual fine particulate matter level higher than the World Health Organization (WHO) guidelines (5 µg/m3). Organic aerosol (OA) is one of the major air pollutants, and the knowledge of its sources is crucial for designing cost-effective mitigation strategies. Positive matrix factorization (PMF) on aerosol mass spectrometer (AMS) or aerosol chemical speciation monitor (ACSM) data is the most common method for source apportionment (SA) analysis on ambient OA. However, conventional PMF requires extensive human labor, preventing the implementation of SA for routine monitoring applications. This study proposes the source finder real-time (SoFi RT, Datalystica Ltd.) approach for efficient retrieval of OA sources. The results generated by SoFi RT agree remarkably well with the conventional rolling PMF results regarding factor profiles, time series, diurnal patterns, and yearly relative contributions of OA factor on three year-long ACSM data sets collected in Athens, Paris, and Zurich. Although the initialization of SoFi RT requires a priori knowledge of OA sources (i.e., the approximate number of factors and relevant factor profiles) for the sampling site, this technique minimizes user interactions. Eventually, it could provide up-to-date trustable information on timescales useful to policymakers and air quality modelers.
Assuntos
Poluentes Atmosféricos , Poluição do Ar , Humanos , Cidades , Monitoramento Ambiental/métodos , Aerossóis/análise , Poluentes Atmosféricos/análise , Material Particulado/análise , Poluição do Ar/prevenção & controle , Poluição do Ar/análiseRESUMO
Organic aerosol (OA) is a key component of total submicron particulate matter (PM1), and comprehensive knowledge of OA sources across Europe is crucial to mitigate PM1 levels. Europe has a well-established air quality research infrastructure from which yearlong datasets using 21 aerosol chemical speciation monitors (ACSMs) and 1 aerosol mass spectrometer (AMS) were gathered during 2013-2019. It includes 9 non-urban and 13 urban sites. This study developed a state-of-the-art source apportionment protocol to analyse long-term OA mass spectrum data by applying the most advanced source apportionment strategies (i.e., rolling PMF, ME-2, and bootstrap). This harmonised protocol was followed strictly for all 22 datasets, making the source apportionment results more comparable. In addition, it enables quantification of the most common OA components such as hydrocarbon-like OA (HOA), biomass burning OA (BBOA), cooking-like OA (COA), more oxidised-oxygenated OA (MO-OOA), and less oxidised-oxygenated OA (LO-OOA). Other components such as coal combustion OA (CCOA), solid fuel OA (SFOA: mainly mixture of coal and peat combustion), cigarette smoke OA (CSOA), sea salt (mostly inorganic but part of the OA mass spectrum), coffee OA, and ship industry OA could also be separated at a few specific sites. Oxygenated OA (OOA) components make up most of the submicron OA mass (average = 71.1%, range from 43.7 to 100%). Solid fuel combustion-related OA components (i.e., BBOA, CCOA, and SFOA) are still considerable with in total 16.0% yearly contribution to the OA, yet mainly during winter months (21.4%). Overall, this comprehensive protocol works effectively across all sites governed by different sources and generates robust and consistent source apportionment results. Our work presents a comprehensive overview of OA sources in Europe with a unique combination of high time resolution (30-240 min) and long-term data coverage (9-36 months), providing essential information to improve/validate air quality, health impact, and climate models.
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National Capital Region (NCR) encompassing New Delhi is one of the most polluted urban metropolitan areas in the world. Real-time chemical characterization of fine particulate matter (PM1 and PM2.5) was carried out using three aerosol mass spectrometers, two aethalometers, and one single particle soot photometer (SP2) at two sites in Delhi (urban) and one site located ~40 km downwind of Delhi, during January-March 2018. The campaign mean PM2.5 (NR-PM2.5 + BC) concentrations at the two urban sites were 153.8 ± 109.4 µg.m-3 and 127.8 ± 83.2 µg.m-3, respectively, whereas PM1 (NR-PM1 + BC) was 72.3 ± 44.0 µg.m-3 at the downwind site. PM2.5 particles were composed mostly of organics (43-44)% followed by chloride (14-17)%, ammonium (9-11)%, nitrate (9%), sulfate (8-10)%, and black carbon (11-16)%, whereas PM1 particles were composed of 47% organics, 13% sulfate as well as ammonium, 11% nitrate as well as chloride, and 5% black carbon. Organic aerosol (OA) source apportionment was done using positive matrix factorization (PMF), solved using an advanced multi-linear engine (ME-2) model. Highly mass-resolved OA mass spectra at one urban and downwind site were factorized into three primary organic aerosol (POA) factors including one traffic-related and two solid-fuel combustion (SFC), and three oxidized OA (OOA) factors. Whereas unit mass resolution OA at the other urban site was factorized into two POA factors related to traffic and SFC, and one OOA factor. OOA constituted a majority of the total OA mass (45-55)% with maximum contribution during afternoon hours ~(70-80)%. Significant differences in the absolute OOA concentration between the two urban sites indicated the influence of local emissions on the oxidized OA formation. Similar PM chemical composition, diurnal and temporal variations at the three sites suggest similar type of sources affecting the particulate pollution in Delhi and adjoining cities, but variability in mass concentration suggest more local influence than regional.
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Delhi is one of the most polluted cities worldwide and a comprehensive understanding and deeper insight into the air pollution and its sources is of high importance. We report 5 months of highly time-resolved measurements of non-refractory PM2.5 and black carbon (BC). Additionally, source apportionment based on positive matrix factorization (PMF) of the organic aerosol (OA) fraction is presented. The highest pollution levels are observed during winter in December/January. During that time, also uniquely high chloride concentrations are measured, which are sometimes even the most dominant NR-species in the morning hours. With increasing temperature, the total PM2.5 concentration decreases steadily, whereas the chloride concentrations decrease sharply. The concentrations measured in May are roughly 6 times lower than in December/January. PMF analysis resolves two primary factors, namely hydrocarbon-like (traffic-related) OA (HOA) and solid fuel combustion OA (SFC-OA), and one or two secondary factors depending on the season. The uncertainties of the PMF analysis are assessed by combining the random a-value approach and the bootstrap resampling technique of the PMF input. The uncertainties for the resolved factors range from ±18% to ±19% for HOA, ±7% to ±19% for SFC-OA and ±6 % to ±11% for the OOAs. The average correlation of HOA with equivalent black carbon from traffic (eBCtr) is R2 = 0.40, while SFC-OA has a correlation of R2 = 0.78 with equivalent black carbon from solid fuel combustion (eBCsf). Anthracene (m/z 178) and pyrene (m/z 202) (PAHs) are mostly explained by SFC-OA and follow its diurnal trend (R2 = 0.98 and R2 = 0.97). The secondary oxygenated aerosols are dominant during daytime. The average contribution during the afternoon hours (1 pm-5 pm) is 59% to the total OA mass, with contributions up to 96% in May. In contrast, the primary sources are more important during nighttime: the mean nightly contribution (22 pm-3 am) to the total OA mass is 48%, with contributions up to 88% during some episodes in April.