Carbonaceous Aerosols in Contrasting Atmospheric Environments in Greek Cities: Evaluation of the EC-tracer Methods for Secondary Organic Carbon Estimation

Carbonaceous fraction in PM2.5 of six Latin American cities: Seasonal variations, sources and secondary organic carbon contribution

Latin American (LatAm) cities are grappling with elevated levels of gaseous and particulate pollutants, which are having detrimental effects on both the local ecosystem and human health. Of particular concern are aerosols with smaller diameters (lower or equal to 2.5 μm, PM2.5), known for their ability to penetrate deep into the respiratory system. While measurements in the region are increasing, they remain limited. This study addresses this gap by presenting the results of a comprehensive, year-long PM2.5 monitoring campaign conducted in six LatAm cities: Buenos Aires, São Paulo, Medellín, San José, Quito and Ciudad de México. Despite all six monitoring sites being urban, they exhibited significant variations in PM2.5 levels, as well as in the content and seasonal behavior of elemental carbon (EC) and organic carbon (OC). Estimations of secondary organic carbon (SOC) using the EC-tracer method revealed a notable SOC relevance across all cities: secondary organic aerosols (SOA) accounted in average for between 19 % to 48 % of the total carbonaceous matter. Source attribution, conducted through the Positive Matrix Factorization (PMF) model, highlights substantial contributions from gasoline and diesel traffic emissions (29 % to 49 % of total carbon, TC), regional biomass burning (21 % to 27 %), and SOA (20 % to 38 %) in all cities, with similar chemical signatures. Additionally, industrial emissions were significant in two cities (Medellín and San José), while two others experienced minor impacts from construction machinery at nearby sites (Buenos Aires and Quito). This comparative analysis underscores the importance of considering not only the thermal optical EC/OC fractions as tracers of sources but also the OC/EC ratio of the PMF factors. This dual approach not only adds depth to the research but also suggests varied methodologies for addressing this crucial environmental concern. This study lays the groundwork for future investigations into the factors influencing the content and seasonality of SOA in the region.

Spatiotemporal Gradients of PAH Concentrations in Greek Cities and Associated Exposure Impacts

To study the spatiotemporal variability of particle-bound polycyclic aromatic hydrocarbons (PAHs) and assess their carcinogenic potential in six contrasting urban environments in Greece, a total of 305 filter samples were collected and analyzed. Sampling sites included a variety of urban background, traffic (Athens, Ioannina and Heraklion), rural (Xanthi) and near-port locations (Piraeus and Volos). When considering the sum of 16 U.S. EPA priority PAHs, as well as that of the six EU-proposed members, average concentrations observed across locations during summer varied moderately (0.4-2.2 ng m-3) and independently of the population of each site, with the highest values observed in the areas of Piraeus and Volos that are affected by port and industrial activities. Winter levels were significantly higher and more spatially variable compared to summer, with the seasonal enhancement ranging from 7 times in Piraeus to 98 times in Ioannina, indicating the large impact of PAH emissions from residential wood burning. Regarding benzo(a)pyrene (BaP), an IARC Group 1 carcinogen and the only EU-regulated PAH, the winter/summer ratios were 24-33 in Athens, Volos, Heraklion and Xanthi; 60 in Piraeus; and 480 in Ioannina, which is afflicted by severe wood-burning pollution events. An excellent correlation was observed between organic carbon (OC) and benzo(a)pyrene (BaP) during the cold period at all urban sites (r2 > 0.8) with stable BaP/OC slopes (0.09-0.14 × 10-3), highlighting the potential use of OC as a proxy for the estimation of BaP in winter conditions. The identified spatiotemporal contrasts, which were explored for the first time for PAHs at such a scale in the Eastern Mediterranean, provide important insights into sources and controlling atmospheric conditions and reveal large deviations in exposure risks among cities that raise the issue of environmental injustice on a national level.

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.

Intrinsic and extrinsic techniques for quantification uncertainty of an interpretable GRU deep learning model used to predict atmospheric total suspended particulates (TSP) in Zabol, Iran during the dusty period of 120-days wind

Total suspended particulates (TSP), as a key pollutant, is a serious threat for air quality, climate, ecosystems and human health. Therefore, measurements, prediction and forecasting of TSP concentrations are necessary to mitigate their negative effects. This study applies the gated recurrent unit (GRU) deep learning model to predict TSP concentrations in Zabol, Iran, during the dust period of the 120-day wind (3 June - 4 October 2014). Three uncertainty quantification (UQ) techniques consisting of the blackbox metamodel, heteroscedastic regression and infinitesimal jackknife were applied to quantify the uncertainty associated with GRU model. Permutation feature importance measure (PFIM), based on the game theory, was employed for the interpretability of the predictive model's outputs. A total of 80 TSP samples were collected and were randomly divided as training (70%) and validation (30%) datasets, while eight variables were used in the TSP prediction model. Our findings showed that GRU performed very well for TSP prediction (with r and Nash Sutcliffe coefficient (NSC) values above 0.99 for both datasets, and RMSE of 57 μg m-3 and 73 μg m-3 for training and validation datasets, respectively). Among the three UQ techniques, the infinitesimal jackknife was the most accurate one, while all the observed and predicted TSP values fell within the continence limitation estimated by the model. PFIM plots showed that wind speed and air humidity were the most and least important variables, respectively, impacting the predictive model's outputs. This is the first attempt of using an interpretable DL model for TSP prediction modelling, recommending that future research should involve aspects of uncertainty and interpretability of the predictive models. Overall, UQ and interpretability techniques have a key role in reducing the impact of uncertainties during optimization and decision making, resulting in better understanding of sophisticated mechanisms related to the predictive model.

Contrasting compositions of PM2.5 in Northern Thailand during La Niña (2017) and El Niño (2019) years

There have been a very limited number of systematic studies on PM2.5 compositions and their source contribution in Southeast Asia. This study aims to explore the characteristics of PM2.5 composition collected in Chiang Mai (Thailand) during La Niña and El Niño years and to apportion their sources during smoke haze and non-haze periods. The average PM2.5 concentration of smoke haze episode in 2019 (El Niño) was much higher than in 2017 (La Niña). The ratios of organic carbon (OC) to elemental carbon (EC), as well as K (biomass burning (BB) tracer) to PM2.5, were higher during smoke haze episodes in 2019 than in 2017 indicating a significant influence from BB. The ratios of secondary organic carbon (SOC) levels to primary organic carbon (POC) levels during smoke haze episodes were higher than those in non-haze period, which indicated greater SOC contributions or more photo-oxidation of precursors in haze episodes with high ambient temperatures. However, the ratios of soil markers (Ca and Mg) during non-haze period were high implying that soil source contributed more to PM2.5 concentrations when there less BB occurred. The positive Matrix Factorization (PMF) model revealed that the source of BB, characterized by high K fractions, was the largest contributor during smoke haze episodes accounting for 50% (2017) and 79% (2019). Climate conditions influence meteorological patterns, particularly during incidences of extreme weather such as droughts, which affect the scale and frequency of open burning and thus air pollution levels.

Chemical and oxidative properties of fine particulate matter from near-road traffic sources

The toxicity associated with the fine particulate matter (PM2.5) has not been well studied, particularly in relation to the emissions from on-road vehicles and other sources in low- and middle-income countries such as India. Thus, a study was conducted to examine the oxidative potential (OP) of PM2.5 at a roadside (RS) site with heavy vehicular traffic and an urban background (BG) site in Mumbai using the dithiothreitol (DTT) assay. Simultaneous gravimetric PM2.5 was measured at both sites and characterized for carbonaceous constituents and water-soluble trace elements and metals. Results depicted higher PM2.5, elemental carbon (EC), and organic carbon (OC) concentrations on the RS than BG (by a factor of 1.7, 4.6, and 1.2, respectively), while BG had higher water-soluble organic carbon (WSOC) levels (by a factor of 1.4) and a higher WSOC to OC ratio (86%), likely due to the dominance of secondary aerosol formation. In contrast, the measured OPDTTv at RS (8.9 ± 5.5 nmol/min/m3) and BG (8.1 ± 6.4 nmol/min/m3) sites were similar. However, OPDTTv at BG was higher during the afternoon, suggesting the influence of photochemical transformation on measured OPDTTv at BG. At RS, OC and redox-active metals (Cu, Zn, Mn, and Fe) were significantly associated with measured OP (p < 0.05), while at BG, WSOC was most strongly associated (p < 0.05). The coefficient of divergence (COD) for PM2.5, its chemical species, and OPDTTv was >0.2, indicating spatial heterogeneity between the sites, and differences in emission sources and toxicity. The estimated hazard index (HI) was not associated with OPDTTv, indicating that current PM2.5 mass regulations may not adequately capture the health effects of PM2.5. The study highlights the need for further studies examining PM2.5 toxicity and developing toxicity-based air quality regulations.

Source apportionment of fine particulate matter at a megacity in China, using an improved regularization supervised PMF model

The source apportionment of particulate matter plays an important role in solving the atmospheric particulate pollution. Positive matrix factorization (PMF) is a widely used source apportionment model. At present, high resolution online datasets are increasingly rich, but acquiring accurate and timely source apportionment results is still challenging. Integrating prior knowledge into modelling process is an effective solution and can yield reliable results. This study proposed an improved source apportionment method for the regularization supervised PMF model (RSPMF). This method leveraged actual source profile to guide factor profile for rapidly and automatically identifying source categories and quantifying source contributions. The results showed that the factor profile from RSPMF could be interpreted as seven factors and approach to actual source profile. Average source contributions were also an agreement between RSPMF and EPAPMF, including secondary nitrate (26 %, 27 %), secondary sulfate (23 %, 24 %), coal combustion (18 %, 18 %), vehicle exhaust (15 %, 15 %), biomass burning (10 %, 9 %), dust (5 %, 4 %), industrial emission (3 %, 3 %). The solutions of RSPMF also exhibited good generalizability during different episodes. This study reveals the superiority of supervised model, this model embeds prior knowledge into modelling process to guide model for obtaining more reliable results.

A study on optical properties, classification, and transport of aerosols during the smog period over South Asia using remote sensing

Over the past few years, South Asian region has experienced frequent and thick smog events because of rapid population growth and enhanced anthropogenic activities, particularly in the Indo-Gangetic Plain (IGP). Therefore, the present study investigates aerosol properties such as aerosol optical depth (AOD) (500 nm), Angstrom exponent (AE) (440-870 nm), single scattering albedo (SSA), fine-mode fraction (FMF), absorption aerosol optical depth (AAOD), and absorption aerosol exponent (AAE) over selected AERONET sites namely Bhola (2012-2021), Dhaka (2012-2021), Jaipur (2011-2021), Kanpur (2011-2021), Karachi (2011-2021), Lahore (2011-2021), and Pokhara (2011-2021) in the IGP during the smog period (October, November, and December). Additionally, different aerosol types were categorized using AERONET direct sun (AOD, AE) and inversion products (VSD, SSA, RI, FMF, and ASY). The monthly mean AOD, AE, and FMF varied from ⁓0.33 to 1.07, ⁓0.3 to 1.4, and 0.6-0.9 µm over all selected AERONET sites during the smog period. Moreover, the outcomes revealed the dominance of biomass-burning and urban/ industrial aerosols over Lahore, Karachi, Dhaka, and Bhola during the smog period. Contrary to this, dust and mixed aerosols were abundant over Jaipur and Karachi, respectively. Furthermore, HYSPLIT cluster analysis is used to trace the transmission paths and potential sources of aerosols over selected sites.

Brown carbon absorption and radiative effects under intense residential wood burning conditions in Southeastern Europe: New insights into the abundance and absorptivity of methanol-soluble organic aerosols

Biomass burning is a major source of Brown Carbon (BrC), strongly contributing to radiative forcing. In urban areas of the climate-sensitive Southeastern European region, where strong emissions from residential wood burning (RWB) are reported, radiative impacts of carbonaceous aerosols remain largely unknown. This study examines the absorption properties of water- and methanol-soluble organic carbon (WSOC, MeS_OC) in a city (Ioannina, Greece) heavily impacted by RWB. Measurements were performed during winter (December 2019 - February 2020) and summer (July - August 2019) periods, characterized by RWB and photochemical processing of organic aerosol (OA), respectively. PM_2.5 filter extracts were analyzed spectrophotometrically for water- and methanol-soluble BrC (WS_BrC, MeS_BrC) absorption. WSOC concentrations were quantified using TOC analysis, while those of MeS_OC were determined using a newly developed direct quantification protocol, applied for the first time to an extended series of ambient samples. The direct method led to a mean MeS_OC/OC of 0.68 and a more accurate subsequent estimation of absorption efficiencies. The mean winter WS_BrC and MeS_BrC absorptions at 365 nm were 13.9 Mm^-1 and 21.9 Mm^-1, respectively, suggesting an important fraction of water-insoluble OA. Mean winter WS_BrC and MeS_BrC absorptions were over 10 times those observed in summer. MeS_OC was more absorptive than WSOC in winter (mean mass absorption efficiencies - MAE₃₆₅: 1.81 vs 1.15 m² gC^-1) and especially in summer (MAE: 1.12 vs 0.27 m² gC^-1) due to photo-dissociation and volatilization of BrC chromophores. The winter radiative forcing (RF) of WS_BrC and MeS_BrC relative to elemental carbon (EC) was estimated at 8.7 % and 16.7 %, respectively, in the 300-2500 nm band. However, those values increased to 48.5 % and 60.2 % at 300-400 nm, indicating that, under intense RWB, BrC forcing becomes comparable to that of soot. The results highlight the consideration of urban BrC emissions in radiative transfer models, as a considerable climate forcing factor.

Daytime and nighttime chemical and optical properties of fine and coarse particles at a central Mediterranean coastal site

The characterization of the day-to-night changes of the atmospheric particle chemical and optical properties in autumn-winter (AW) and spring-summer (SS) is the main goal of this study to contribute to the characterization and understanding of the particulate matter (PM) impact on the environment and climate at one of the most vulnerable areas of the planet to climate change. To this end, PM10 and PM2.5 samples from 14 January 2016 to 5 January 2017 have been collected in Lecce, a coastal site of South-Eastern Italy (40.33°N, 18.11°E), and day-to-night changes of mass concentrations of both fine (PM2.5) and coarse (PM10-PM2.5) particles and corresponding chemical species have been assessed both in AW and in SS. The statistical analysis of local meteorological parameters and their correlations with PM2.5 and chemical species mass concentrations have indicated that the day-to-night changes of temperature (T) and wind speed (WS) likely affected the day-to-night changes of mass concentrations, because of the T and WS impact on the atmospheric turbulence and air particle dispersion. The daily evolution of the anthropogenic activities and the planetary-boundary-layer height likely contributed to the day-to-night changes of the particle chemical composition. The stagnant atmospheric conditions prevailing in SS all over the Mediterranean basin, which favoured the mixing and the accumulation of atmospheric particles from different pollution sources, likely contributed to the changes of the relationships between chemical species and meteorological parameters from AW to SS at daytime and nighttime. The analysis of the aerosol scattering coefficient, scattering Ångström exponent, and scattering Ångström exponent difference, retrieved from nephelometer measurements co-located in space and time with the PM samplings, has allowed characterizing the day-to-night change of the aerosol optical properties. The relationships between the particle chemical and optical properties allowed a good understanding of their changes both in AW and in SS.

“On-Line” Heating Emissions Based on WRF Meteorology—Application and Evaluation of a Modeling System over Greece

The main objective of the present study is the development of an “on-line” heating emissions modeling system based on simulated meteorological data and its integration with air quality modeling systems in order to improve their accuracy. The WRF-CAMx air quality modeling system is applied over Greece for the cold period of 2015 (January–April, October–December) for two emissions scenarios: using the (a) “on-line” heating emissions based on WRF meteorology and (b) “static” heating emissions based on static temporal profiles. The monthly variation in total “on-line” heating emissions followed the temporal pattern of the air temperature over Greece, leading to the highest heating emissions in January and February, while higher differences in emissions between winter and spring/autumn months were identified in comparison with the static ones. The overall evaluation of the WRF-CAMx modeling system using the “on-line” heating emissions revealed satisfactory model performance for the mean daily air quality levels. The comparison between the simulated and observed mean monthly concentrations revealed an improvement in the pattern of mean monthly concentrations for the “on-line” scenario. Higher values of the index of agreement and correlation for the mean daily values were also identified for the “on-line” scenario in most monitoring sites.

Vertical Profiling of Fresh Biomass Burning Aerosol Optical Properties over the Greek Urban City of Ioannina, during the PANACEA Winter Campaign

Vertical profiling of aerosol particles was performed during the PANhellenic infrastructure for Atmospheric Composition and climatE chAnge (PANACEA) winter campaign (10 January 2020–7 February 2020) over the city of Ioannina, Greece (39.65° N, 20.85° E, 500 m a.s.l.). The middle-sized city of Ioannina suffers from wintertime air pollution episodes due to biomass burning (BB) domestic heating activities. The lidar technique was applied during the PANACEA winter campaign on Ioannina city, to fill the gap of knowledge of the spatio-temporal evolution of the vertical mixing of the particles occurring during these winter-time air pollution episodes. During this campaign the mobile single-wavelength (532 nm) depolarization Aerosol lIdAr System (AIAS) was used to measure the spatio-temporal evolution of the aerosols’ vertical profiles within the Planetary Boundary Layer (PBL) and the lower free troposphere (LFT; up to 4 km height a.s.l.). AIAS performed almost continuous lidar measurements from morning to late evening hours (typically from 07:00 to 19:00 UTC), under cloud-free conditions, to provide the vertical profiles of the aerosol backscatter coefficient (baer) and the particle linear depolarization ratio (PLDR), both at 532 nm. In this study we emphasized on the vertical profiling of very fresh (~hours) biomass burning (BB) particles originating from local domestic heating activities in the area. In total, 33 out of 34 aerosol layers in the lower free troposphere were characterized as fresh biomass burning ones of local origin, showing a mean particle linear depolarization value of 0.04 ± 0.02 with a range of 0.01 to 0.09 (532 nm) in a height region 1.21–2.23 km a.s.l. To corroborate our findings, we used in situ data, particulate matter (PM) concentrations (PM2.5) from a particulate sensor located close to our station, and the total black carbon (BC) concentrations along with the respective contribution of the fossil fuel (BCff) and biomass/wood burning (BCwb) from the Aethalometer. The PM2.5 mass concentrations ranged from 5.6 to 175.7 μg/m3, while the wood burning emissions from residential heating were increasing during the evening hours, with decreasing temperatures. The BCwb concentrations ranged from 0.5 to 17.5 μg/m3, with an extremely high mean contribution of BCwb equal to 85.4%, which in some cases during night-time reached up to 100% during the studied period.

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.

Carbonaceous aerosols in urban Chongqing, China: Seasonal variation, source apportionment, and long-range transport

Seventy-seven PM2.5 samples were collected at an urban site (Chongqing University Campus A) in October 2015 (autumn), December 2015 (winter), March 2016 (spring), and August 2016 (summer). These samples were analysed for organic carbon (OC), elemental carbon (EC), and their associated char, soot, 16 PAHs, and 28 n-alkanes to trace sources, and atmospheric transport pathways. The annual average of OC, EC, char, soot, ΣPAHs, and Σn-alkanes were 20.75 μg/m³, 6.18 μg/m³, 5.43 μg/m³, 0.75 μg/m³, 38.29 ng/m³, and 328.69 ng/m³, respectively. OC, ΣPAHs, and Σn-alkane concentrations were highest in winter and lowest in summer. EC, char, and soot concentrations were highest in autumn and lowest in winter. Source apportionment via positive matrix factorization (PMF) indicated that coal/biomass combustion-natural gas emissions (23.8%) and motor vehicle exhaust (20.2%) were the two major sources, followed by diesel and petroleum residue (21.1%), natural biogenic sources (17.7%), and evaporative/petrogenic sources (17.2%). The highest source contributor in autumn and winter was evaporative/petrogenic sources (30.6%) and natural biogenic sources (34.5%), respectively, whereas diesel engine emission contributed the most in spring and summer (32.1% and 38.0%, respectively). Potential source contribution function (PSCF) analysis identified southeastern Sichuan and northwestern Chongqing as the major potential sources of these pollutants. These datasets provide critical information for policymakers to establish abatement strategies for the reduction of carbonaceous pollutant emissions and improve air quality in Chongqing and other similar urban centres across China.

Chemical Composition and Source Apportionment of Total Suspended Particulate in the Central Himalayan Region

The present study analyzes data from total suspended particulate (TSP) samples collected during 3 years (2005–2008) at Nainital, central Himalayas, India and analyzed for carbonaceous aerosols (organic carbon (OC) and elemental carbon (EC)) and inorganic species, focusing on the assessment of primary and secondary organic carbon contributions (POC, SOC, respectively) and on source apportionment by positive matrix factorization (PMF). An average TSP concentration of 69.6 ± 51.8 µg m−3 was found, exhibiting a pre-monsoon (March–May) maximum (92.9 ± 48.5 µg m−3) due to dust transport and forest fires and a monsoon (June–August) minimum due to atmospheric washout, while carbonaceous aerosols and inorganic species expressed a similar seasonality. The mean OC/EC ratio (8.0 ± 3.3) and the good correlations between OC, EC, and nss-K+ suggested that biomass burning (BB) was one of the major contributing factors to aerosols in Nainital. Using the EC tracer method, along with several approaches for the determination of the (OC/EC)pri ratio, the estimated SOC component accounted for ~25% (19.3–29.7%). Furthermore, TSP source apportionment via PMF allowed for a better understanding of the aerosol sources in the Central Himalayan region. The key aerosol sources over Nainital were BB (27%), secondary sulfate (20%), secondary nitrate (9%), mineral dust (34%), and long-range transported mixed marine aerosol (10%). The potential source contribution function (PSCF) and concentration weighted trajectory (CWT) analyses were also used to identify the probable regional source areas of resolved aerosol sources. The main source regions for aerosols in Nainital were the plains in northwest India and Pakistan, polluted cities like Delhi, the Thar Desert, and the Arabian Sea area. The outcomes of the present study are expected to elucidate the atmospheric chemistry, emission source origins, and transport pathways of aerosols over the central Himalayan region.

Identification of key aerosol types and mixing states in the central Indian Himalayas during the GVAX campaign: the role of particle size in aerosol classification

Studies in aerosol properties, types and sources in the Himalayas are important for atmospheric and climatic issues due to high aerosol loading in the neighboring plains. This study uses in situ measurements of aerosol optical and microphysical properties obtained during the Ganges Valley Aerosol eXperiment (GVAX) at Nainital, India over the period June 2011-March 2012, aiming to identify key aerosol types and mixing states for two particle sizes (PM₁ and PM₁₀). Using a classification matrix based on SAE vs. AAE thresholds (scattering vs. absorption Ångström exponents, respectively), seven aerosol types are identified, which are highly dependent on particle size. An aerosol type named "large/BC mix" dominates in both PM₁ (45.4%) and PM₁₀ (46.9%) mass, characterized by aged BC mixed with other aerosols, indicating a wide range of particle sizes and mixing states. Small particles with low spectral dependence of the absorption (AAE < 1) account for 31.6% and BC-dominated aerosols for 14.8% in PM₁, while in PM₁₀, a large fraction (39%) corresponds to "large/low-absorbing" aerosols and only 3.9% is characterized as "BC-dominated". The remaining types consist of mixtures of dust and local emissions from biofuel burning and display very small fractions. The main optical properties e.g. spectral scattering, absorption, single scattering albedo, activation ratio, as well as seasonality and dependence on wind speed and direction of identified types are examined, revealing a large influence of air masses originating from the Indo-Gangetic Plains. This indicates that aerosols over the central Himalayas are mostly composed by mixtures of processed and transported polluted plumes from the plains. This is the first study that identifies key aerosol populations in the central Indian Himalayas based on in situ measurements and the results are highly important for aerosol-type inventories, chemical transport models and reducing the uncertainty in aerosol radiative forcing over the third pole.

Assessment of the COVID-19 Lockdown Effects on Spectral Aerosol Scattering and Absorption Properties in Athens, Greece

COVID-19 is evolving into one of the worst pandemics in recent history, claiming a death toll of over 1.5 million as of December 2020. In an attempt to limit the expansion of the pandemic in its initial phase, nearly all countries imposed restriction measures, which resulted in an unprecedented reduction of air pollution. This study aims to assess the impact of the lockdown effects due to COVID-19 on in situ measured aerosol properties, namely spectral-scattering (bsca) and absorption (babs) coefficients, black carbon (BC) concentrations, single-scattering albedo (SSA), scattering and absorption Ångström exponents (SAE, AAE) in Athens, Greece. Moreover, a comparison is performed with the regional background site of Finokalia, Crete, for a better assessment of the urban impact on observed differences. The study examines pre-lockdown (1–22 March 2020), lockdown (23 March–3 May 2020) and post-lockdown (4–31 May 2020) periods, while the aerosol properties are also compared with a 3–4 year preceding period (2016/2017–2019). Comparison of meteorological parameters in Athens, between the lockdown period and respective days in previous years, showed only marginal variation, which is not deemed sufficient in order to justify the notable changes in aerosol concentrations and optical properties. The largest reduction during the lockdown period was observed for babs compared to the pre-lockdown (−39%) and to the same period in previous years (−36%). This was intensified during the morning traffic hours (−60%), reflecting the large decrease in vehicular emissions. Furthermore, AAE increased during the lockdown period due to reduced emissions from fossil-fuel combustion, while a smaller (−21%) decrease was observed for bsca along with slight increases (6%) in SAE and SSA values, indicating that scattering aerosol properties were less affected by the decrease in vehicular emissions, as they are more dependent on regional sources and atmospheric processing. Nighttime BC emissions related to residential wood-burning were slightly increased during the lockdown period, with respect to previous-year means. On the contrary, aerosol and pollution changes during the lockdown period at Finokalia were low and highly sensitive to natural sources and processes.

Field Evaluation of Low-Cost PM Sensors (Purple Air PA-II) Under Variable Urban Air Quality Conditions, in Greece

Recent advances in particle sensor technologies have led to an increased development and utilization of low-cost, compact, particulate matter (PM) monitors. These devices can be deployed in dense monitoring networks, enabling an improved characterization of the spatiotemporal variability in ambient levels and exposure. However, the reliability of their measurements is an important prerequisite, necessitating rigorous performance evaluation and calibration in comparison to reference-grade instrumentation. In this study, field evaluation of Purple Air PA-II devices (low-cost PM sensors) is performed in two urban environments and across three seasons in Greece, in comparison to different types of reference instruments. Measurements were conducted in Athens (the largest city in Greece with nearly four-million inhabitants) for five months spanning over the summer of 2019 and winter/spring of 2020 and in Ioannina, a medium-sized city in northwestern Greece (100,000 inhabitants) during winter/spring 2019–2020. The PM2.5 sensor output correlates strongly with reference measurements (R2 = 0.87 against a beta attenuation monitor and R2 = 0.98 against an optical reference-grade monitor). Deviations in the sensor-reference agreement are identified as mainly related to elevated coarse particle concentrations and high ambient relative humidity. Simple and multiple regression models are tested to compensate for these biases, drastically improving the sensor’s response. Large decreases in sensor error are observed after implementation of models, leading to mean absolute percentage errors of 0.18 and 0.12 for the Athens and Ioannina datasets, respectively. Overall, a quality-controlled and robustly evaluated low-cost network can be an integral component for air quality monitoring in a smart city. Case studies are presented along this line, where a network of PA-II devices is used to monitor the air quality deterioration during a peri-urban forest fire event affecting the area of Athens and during extreme wintertime smog events in Ioannina, related to wood burning for residential heating.

Combination of Different Approaches to Infer Local or Regional Contributions to PM2.5 Burdens in Graz, Austria

In early 2017 high particulate matter (PM) levels were observed across mid-Europe, including Austria. Here we characterize PM pollution in the city of Graz during January to March 2017, a period with substantial exceedances (34 days) of the European Union (EU) PM10 short time limit value. This study evaluates whether the observed exceedances can be attributed to the accumulation of pollutants emitted by local sources or to a larger scale pollution episode including transport. The analyses are based on the ratios of PM10 concentrations determined at an urban and background site, and the analyses of chemical composition of PM2.5 samples (i.e., water soluble ions, organic and elemental carbon, anhydro-sugars, humic-like substances, aluminum, and polycyclic aromatic hydrocarbons). Source apportionment was realized using a macro-tracer model. Overall, the combination of different approaches (PM10 ratios, chemical composition, and macro-tracer derived source apportionment) enabled a conclusive identification of time periods characterized by the accumulation of emissions from local sources or regional pollution episodes.