Particulate Matter Mass Research Articles

Variations of black carbon, particulate matter and nitrogen oxides mass concentrations in urban environment with respect to winter heating period and meteorological conditions

The atmospheric concentrations of particulate pollution are of great scientific concern due to their impact on both human health and environment. This study aimed to investigate the concentration of black carbon (BC), particulate matter with an aerodynamic diameter of less than 10 micrometres (PM10) and nitrogen oxides (NOx) at an urban background environment throughout the year, and understand the impact of winter heating and meteorology on its concentration level. The campaign covered heating and non-heating periods, from 1 June 2021 to 31 May 2022. During the heating period, the mass concentrations of BC, PM10 and NOx were 1.17, 24.9 and 19.4 µg m–3, respectively. The analysis revealed that the mass concentrations of BC and NOx were 1.9 and 1.4 times greater during the heating period, respectively, compared to the non-heating period. In contrast, PM10 remained almost constant during the heating (19.4 µg m–3) and non-heating periods (20.0 µg m–3). Throughout the year, the BC mass concentration was dominated by BCFF (71.2%) originating from fossil fuel combustion with a maximum (8.43 µg m–3) during the heating period. Moreover, wind speed presented a weak negative correlation with BC (r = –0.40), PM10 (r = –0.19) and NOx (r = –0.40) during the heating period.

Human health impacts and indoor chemical reactions of VOCs from cleaning products and occupants

Occupants and indoor activities are sources of volatile organic compounds (VOCs). We propose a framework to simulate the pollutant pathway using the INCA-Indoor© model and VOC emission rates to derive dynamic concentrations, and the USEtox model to evaluate health impacts in DALYs (Disability-Adjusted Life Years). The applicability of the framework is tested on a case study, and the effect of indoor chemical reactions on health impacts is assessed. In this case study, health impacts were of 0.3 μDALY/day without and 0.4 μDALY/day (13 s/day) with indoor air chemistry (+28 %) out of which 12 % were linked to occupant breath and skin emissions. Cleaning activities led to the highest impacts without chemical reactions (terpinolene, responsible for 0.14 μDALY/day), but indoor air chemistry led to high impacts linked to formaldehyde formation (0.18 μDALY/day). These reactions led to the formation of more formaldehyde, hence leading to 20% more impacts, in summer than in winter. Occupants’ contribution to CO2 concentrations exceeded recommended limits under the given occupancy and ventilation scenario. Secondary organic aerosol (SOA) formation affected indoor particulate matter mass concentrations by up to a factor 1.2 and their number concentrations by up to a factor 25,000 in the presence of VOC emissions. Results of this study indicate that chemical reactions and SOA formation are important factors to consider in indoor air quality impact assessment. A larger number of activities and scenarios can be tested to improve the robustness of the conclusions, since, under different scenarios (for e.g. activities with lower emission rates) and with more complete toxicity data, these conclusions are likely to change.

Characterization of Particulate Emissions From Thermal Runaway of Lithium-Ion Cells

Abstract Over the past decade, there has been a significant acceleration in the adoption of lithium-ion (Li-ion) batteries for various applications, ranging from portable electronics to automotive, defense, and aerospace applications. Lithium-ion batteries are the most used energy storage technologies due to their high energy densities and capacities. However, this battery technology is a potential safety hazard under off-nominal conditions, which may result in thermal runaway events. Such events can release toxic gaseous and particulate emissions, posing a severe risk to human health and the environment. Particulate emissions from the failure of two different cell chemistries—lithium iron phosphate (LFP) and nickel manganese cobalt oxide (NMC)—were studied. Experiments were conducted at multiple states of charge (SOC), and three repeats were performed at each SOC for each cell chemistry to examine the repeatability/variability of these events. Particulate emissions were characterized in terms of particulate matter mass (PM2.5), black carbon, and particle number (PN)/size. Failure of a single cell led to a significant release of particulate emissions, with peak emission levels being higher at the higher SOCs. A high level of variability was observed for a specific SOC for LFP cells, while NMCs exhibited relatively less variability. In general, much higher particulate emissions were observed for NMCs compared to LFPs at each SOC. For NMCs at 100% SOC, peak PN levels were ∼2.5 × 10+09 particles/cc (part/cc), and black carbon levels were ∼60 mg/m3. For LFPs at 100% SOC, peak PN levels were ∼9.0 × 10+08 part/cc, and black carbon levels were 2.5 mg/m3.

Size-resolved particulate matter inside selected fire stations and preliminary evaluation of the effectiveness of washing machines in reducing its concentrations

The study aimed to determine and compare the mass concentration and size distribution of particulate matter (PM) at two Polish fire stations, one equipped with a washing machine intended for the decontamination of uniforms (FSN) and the other not equipped with this type of device (FSC), to assess the effectiveness of washing machines in reducing PM concentrations inside fire stations and estimate PM doses inhaled by firefighters while performing activities in truck bays and changing rooms during one work shift. The average PM concentrations at the FSN were 18.2–28.9 µg/m3 and 27.5–37.3 µg/m3, while at FSC they were 27.4–37.9 µg/m3 and 24.6–32.8 µg/m3 in the truck bays and changing rooms, respectively. At each measurement point, most of the PM mass (65–75%) was accumulated as fine particles. The dominance of fine particles in the total mass of PM results in high values of PM deposition coefficients (0.59–0.61) in three sections of the respiratory tract at each monitoring site. This study initially indicates the effectiveness of washing machines in reducing the concentration of fine particles and demonstrates the necessity, as well as directions for further research in this area.

BWO-BiLSTM & CNN composite model for prediction of atmospheric particulate matter mass concentration

Accurate prediction of the mass concentration of atmospheric particulate matter is of great significance for the rational formulation of atmospheric environment management strategies and the study of the spatial and temporal evolution of atmospheric pollutants. In order to solve the problems of low prediction accuracy and low efficiency of traditional prediction models, aiming at the nonlinear and stochastic characteristics of atmospheric particulate matter mass concentration changes, a composite prediction model based on Random Forest (RF) feature selection, Beluga Whale Optimization (BWO) algorithm, Convolutional Neural Network (CNN) and Bidirectional Long and Short-Term Storage Memory Neural Network (BiLSTM) is proposed in this paper. In this composite prediction model, the input variables are adjusted and screened through RF algorithm to reduce the network complexity. The weights and thresholds of CNN-BiLSTM are optimized using BWO to improve the prediction accuracy of the model. The publicly mass concentration data and Aerodynamic Particle Size Spectrometer (APS) measurements are used to train and compare with the predicted data. The experimental results indicate that this composite model has better prediction performance and prediction accuracy compared with the traditional single and the combined model. The fitting coefficient (R2) of PM2.5 prediction using publicly data and APS data can reach 0.8842 and 0.9762, respectively. The R2 for the prediction of PM10 using publicly data and APS data can reach 0.8635 and 0.976, respectively. It indicates that the model proposed in this paper has better generalization and robustness.

The Bacharach Method: A Low-Cost Tool for Small-Scale Combustion Units’ Flue Gas Quality Control

Although current EU regulations, such as EU Directive 2015/1189 on the eco-design of solid fuel boilers and Directive 2015/1188, in accordance with the Machinery Directive 2006/42/EC, require manufacturers to meet specific emission requirements for CE marking, the routine and regular onsite testing of household heating appliances is still not mandatory in many EU countries. This research endeavour addressed this gap by evaluating the effectiveness of the Bacharach method as a rapid and cost-effective tool for assessing flue gas quality, particularly in terms of particulate matter mass concentration. This study also compared the results of the Bacharach method with those obtained from two commercially available portable analysers. The research outcomes demonstrate that the Bacharach method, in combination with an innovative evaluation approach, offers a viable solution, enabling the swift and economical assessment of flue gas quality with the primary objective of determining the boiler class according to the limits specified by standard EN 303-5 under operating conditions. The modified Bacharach method for measuring TSP in solid fuel-fired boilers provides qualitatively similar results to the commercially used SM500 and STM225 instruments. The modified Bacharach methodology was primarily developed for comparison to the boiler class 3 limit (i.e., 125 and 150 mg/m3). The study revealed that the modified Bacharach method, when applied to biomass-based boilers, exhibited higher accuracies in the case of classification into classes 3 and 4, whereas fossil fuel-based boilers demonstrated higher accuracy in the case of class 5 limits.

Data Evaluation of a Low-Cost Sensor Network for Atmospheric Particulate Matter Monitoring in 15 Municipalities in Serbia.

Conventional air quality monitoring networks typically tend to be sparse over areas of interest. Because of the high cost of establishing such monitoring systems, some areas are often completely left out of regulatory monitoring networks. Recently, a new paradigm in monitoring has emerged that utilizes low-cost air pollution sensors, thus making it possible to reduce the knowledge gap in air pollution levels for areas not covered by regulatory monitoring networks and increase the spatial resolution of monitoring in others. The benefits of such networks for the community are almost self-evident since information about the level of air pollution can be transmitted in real time and the data can be analysed immediately over the wider area. However, the accuracy and reliability of newly produced data must also be taken into account in order to be able to correctly interpret the results. In this study, we analyse particulate matter pollution data from a large network of low-cost particulate matter monitors that was deployed and placed in outdoor spaces in schools in central and western Serbia under the Schools for Better Air Quality UNICEF pilot initiative in the period from April 2022 to June 2023. The network consisted of 129 devices in 15 municipalities, with 11 of the municipalities having such extensive real-time measurements of particulate matter concentration for the first time. The analysis showed that the maximum concentrations of PM2.5 and PM10 were in the winter months (heating season), while during the summer months (non-heating season), the concentrations were several times lower. Also, in some municipalities, the maximum values and number of daily exceedances of PM10 (50 μg/m3) were much higher than in the others because of diversity and differences in the low-cost sensor sampling sites. The particulate matter mass daily concentrations obtained by low-cost sensors were analysed and also classified according to the European AQI (air quality index) applied to low-cost sensor data. This study confirmed that the large network of low-cost air pollution sensors can be useful in providing real-time information and warnings about higher pollution days and episodes, particularly in situations where there is a lack of local or national regulatory monitoring stations in the area.

Characterizing and Predicting nvPM Size Distributions for Aviation Emission Inventories and Environmental Impact.

Concerns about civil aviation's air quality and environmental impacts have led to recent regulations on nonvolatile particulate matter (nvPM) mass and number emissions. Although these regulations do not mandate measuring particle size distribution (PSD), understanding PSDs is vital for assessing the environmental impacts of aviation nvPM. This study introduces a comprehensive data set detailing PSD characteristics of 42 engines across 19 turbofan types, ranging from unregulated small business jets to regulated large commercial aircraft. Emission tests were independently performed by using the European and Swiss reference nvPM sampling and measurement systems with parallel PSD measurements. The geometric mean diameter (GMD) at the engine exit strongly correlated with the nvPM number-to-mass ratio (N/M) and thrust, varying from 7 to 52 nm. The engine-exit geometric standard deviation ranged from 1.7 to 2.5 (mean of 2.05). The study proposes empirical correlations to predict GMD from N/M data of emissions-certified engines. These predictions are expected to be effective for conventional rich-burn engines and might be extended to novel combustor technologies if additional data become available. The findings support the refinement of emission models and help in assessing the aviation non-CO2 climate and air quality impacts.

Physicochemical metamorphosis of re-aerosolized urban PM2.5

The toxicity of particulate matter (PM) is dependent on particle physical and chemical properties and is commonly studied using in vivo and in vitro approaches. PM to be used for in vivo and in vitro studies is often collected on filters and then extracted from the filter surface using a solvent. During extraction and further PM sample handling, particle properties change, but this is often neglected in toxicology studies, with possible implications for health effect assessment. To address the current lack of knowledge and investigate changes in particle properties further, ambient PM with diameter less than 2.5 μm (PM2.5) was collected on filters at an urban site and extracted using a standard methanol protocol. After extraction, the PM was dried, dispersed in water and subsequently nebulized. The resulting aerosol properties were then compared to those of the ambient PM2.5. The number size distribution for the nebulized aerosol resembled the ambient in terms of the main mode diameter, and >90 % of particle mass in the nebulized size distribution was still in the PM2.5 range. Black carbon made up a similar fraction of PM mass in nebulized as in ambient aerosol. The sulfate content in the nebulized aerosol seemed depleted and the chemical composition of the organic fraction was altered, but it remains unclear to what extent other non-refractory components were affected by the extraction process. Trace elements were not distributed equally across size fractions, neither in ambient nor nebulized PM. Change in chemical form was studied for zinc, copper and iron. The form did not appear to be different between the ambient and nebulized PM for iron and copper, but seemed altered for zinc. Although many of the studied properties were reasonably well preserved, it is clear that the PM2.5 collection and re-aerosolization process affects particles, and thus potentially also their health effects. Because of this, the effect of the particle collection and extraction process must be considered when evaluating cellular and physiological outcomes upon PM2.5 exposure.

Dissecting PM sensor capabilities: A combined experimental and theoretical study on particle sizing and physicochemical properties

Recent advancements in particulate matter (PM) optical measurement technology have enhanced the characterization of particle size distributions (PSDs) across various temporal and spatial scales, offering a more detailed analysis than traditional PM mass concentration monitoring. This study employs field experiments, laboratory tests, and model simulations to evaluate the influence of physicochemical characteristics of particulate matter (PM) on the performance of a compact, multi-channel PM sizing sensor. The sensor is integrated within a mini air station (MAS) designed to detect particles across 52 channels. The field experiments highlighted the sensor's ability to track hygroscopicity parameter κ-values across particle sizes, noting an increasing trend with particle size. The sensor's capability in identifying the size and mass concentration of different PM types, including ammonium nitrate, sodium chloride, smoke, incense, and silica dust particles, was assessed through laboratory tests. Laboratory comparisons with the Aerodynamic Particle Sizer (APS) showed high consistency (R2 > 0.96) for various PM sources, supported by Kolmogorov-Smirnov tests confirming the sensor's capability to match APSsize distributions. Model simulations further elucidated the influence of particle refractive index and size distributions on sensor performance, leading to optimized calibrant selection and application-specific recommendations. These comprehensive evaluations underscore the critical interplay between the chemical composition and physical properties of PM, significantly advancing the application and reliability of optical PM sensors in environmental monitoring.

Characterization of particle exposure during tunnel excavation by tunnel boring machines.

Tunnel boring machines (TBMs) are used to excavate tunnels in a manner where the rock is constantly penetrated with rotating cutter heads. Fine particles of the rock minerals are thereby generated. Workers on and in the vicinity of the TBM are exposed to particulate matter (PM) consisting of bedrock minerals including α-quartz. Exposure to respirable α-quartz remains a concern because of the respiratory diseases associated with this exposure. The particle size distribution of PM and α-quartz is of special importance because of its influence on adverse health effects, monitoring and control strategies as well as accurate quantification of α-quartz concentrations. The major aim of our study was therefore to investigate the particle size distribution of airborne PM and α-quartz generated during tunnel excavation using TBMs in an area dominated by gneiss, a metamorphic type of rock. Sioutas cascade impactors were used to collect personal samples on 3 separate days. The impactor fractionates the dust in 5 size fractions, from 10 µm down to below 0.25 µm. The filters were weighted, and the α-quartz concentrations were quantified using X-ray diffraction (XRD) analysis and the NIOSH 7500 method on the 5 size fractions. Other minerals were determined using Rietveld refinement XRD analysis. The size and elemental composition of individual particles were investigated by scanning electron microscopy. The majority of PM mass was collected on the first 3 stages (aerodynamic diameter = 10 to 0.5 µm) of the Sioutas cascade impactor. No observable differences were found for the size distribution of the collected PM and α-quartz for the 3 sampling days nor the various work tasks. However, the α-quartz proportion varied for the 3 sampling days demonstrating a dependence on geology. The collected α-quartz consisted of more particles with sizes below 1 µm than the calibration material, which most likely affected the accuracy of the measured respirable α-quartz concentrations. This potential systematic error is important to keep in mind when analyzing α-quartz from occupational samples. Knowledge of the particle size distribution is also important for control measures, which should target particle sizes that efficiently capture the respirable α-quartz concentration.

Oxidative potential of particulate matter and its association to respiratory health endpoints in high-altitude cities in Bolivia

Exposure to particulate matter (PM) pollution is a significant health risk, driving the search for innovative metrics that more accurately reflect the potential harm to human health. Among these, oxidative potential (OP) has emerged as a promising health-based metric, yet its application and relevance across different environments remain to be further explored. This study, set in two high-altitude Bolivian cities, aims to identify the most significant sources of PM-induced oxidation in the lungs and assess the utility of OP in assessing PM health impacts. Utilizing two distinct assays, OPDTT and OPDCFH, we measured the OP of PM samples, while also examining the associations between PM mass, OP, and black carbon (BC) concentrations with hospital visits for acute respiratory infections (ARI) and pneumonia over a range of exposure lags (0–2 weeks) using a Poisson regression model adjusted for meteorological conditions. The analysis also leveraged Positive Matrix Factorization (PMF) to link these health outcomes to specific PM sources, building on a prior source apportionment study utilizing the same dataset. Our findings highlight anthropogenic combustion, particularly from traffic and biomass burning, as the primary contributors to OP in these urban sites. Significant correlations were observed between both OPDTT and PM2.5 concentration exposure and ARI hospital visits, alongside a notable association with pneumonia cases and OPDTT levels. Furthermore, PMF analysis demonstrated a clear link between traffic-related pollution and increased hospital admissions for respiratory issues, affirming the health impact of these sources. These results underscore the potential of OPDTT as a valuable metric for assessing the health risks associated with acute PM exposure, showcasing its broader application in environmental health studies.

Key drivers of the oxidative potential of PM2.5 in Beijing in the context of air quality improvement from 2018 to 2022

The mass concentration of atmospheric particulate matter (PM) has been continuously decreasing in the Beijing-Tianjin-Hebei region. However, health endpoints do not exhibit a linear correlation with PM mass concentrations. Thus, it is urgent to clarify the prior toxicological components of PM to further improve air quality. In this study, we analyzed the long-term oxidative potential (OP) of water-soluble PM2.5, which is generally considered more effective in assessing hazardous exposure to PM in Beijing from 2018 to 2022 based on the dithiothreitol assay and identified the crucial drivers of the OP of PM2.5 based on online monitoring of air pollutants, receptor model, and random forest (RF) model. Our results indicate that dust, traffic, and biomass combustion are the main sources of the OP of PM2.5 in Beijing. The complex interactions of dust particles, black carbon, and gaseous pollutants (nitrogen dioxide and sulfur dioxide) are the main factors driving the OP evolution, in particular, leading to the abnormal rise of OP in Beijing in 2022. Our data shows that a higher OP is observed in winter and spring compared to summer and autumn. The diurnal variation of the OP is characterized by a declining trend from 0:00 to 14:00 and an increasing trend from 14:00 to 23:00. The spatial variation in OP of PM2.5 was observed as the OP in Beijing is lower than that in Shijiazhuang, while it is higher than that in Zhenjiang and Haikou, which is primarily influenced by the distribution of black carbon. Our results are of significance in identifying the key drivers influencing the OP of PM2.5 and provide new insights for advancing air quality improvement efforts with a focus on safeguarding human health in Beijing.

Indoor Microclimatic Conditions and Air Pollutant Concentrations in the Archaeological Museum of Abdera, Greece

Indoor microclimate conditions and air pollutant concentrations (O3, TVOC, CO, CO2, and particulate matter mass concentrations in six size bins) were measured in the Greek Archaeological Museum of Abdera, which houses priceless works of art from the birthplace of the ancient philosopher Democritus. The monitoring campaign took place during the spring and summer months, when there were the greatest number of visitors. In the exhibition rooms, daily variations in relative humidity ranged from 4% to 10%, and daily variations in air temperature ranged from 0.9 °C to 2.6 °C. These uncontrolled changes may endanger the housed antiquities. The microclimate in the storage rooms varied substantially less than in the exhibition halls due to dehumidifiers and the lack of visitors. Concerning air pollution, indoor O3 concentrations were higher than the recommended limit values for the conservation of artwork. Even more worrisome are particulate matter mass concentrations above the air quality guidelines. Despite the fact that the building is well insulated and that only artificial lighting is used in the exhibition halls, it is difficult to achieve adequate conditions for the protection of the works of art.

Oxidative potential of the inhalation bioaccessible fraction of PM10 and bioaccessible concentrations of polycyclic aromatic hydrocarbons and metal(oid)s in PM10

Atmospheric particulate matter (PM) has been related to numerous adverse health effects in humans. Nowadays, it is believed that one of the possible mechanisms of toxicity could be the oxidative stress, which involves the development of reactive oxygen species (ROS). Different assays have been proposed to characterize oxidative stress, such as dithiothreitol (DTT) and ascorbic acid (AA) acellular assays (OPDTT and OPAA), as a metric more relevant than PM mass measurement for PM toxicity. This study evaluates the OP of the bioaccessible fraction of 65 PM10 samples collected at an Atlantic Coastal European urban site using DTT and AA assays. A physiologically based extraction (PBET) using Gamble’s solution (GS) as a simulated lung fluid (SLF) was used for the assessment of the bioaccessible fraction of PM10. The use of the bioaccessible fraction, instead of the fraction assessed using conventional phosphate buffer and ultrasounds assisted extraction (UAE), was compared for OP assessment. Correlations between OPDTT and OPAA, as well as total and bioaccessible concentrations of polycyclic aromatic hydrocarbons (PAHs) and metal(oid)s, were investigated to explore the association between those compounds and OP. A correlation was found between both OP (OPDTT and OPAA) and total and bioaccessible concentrations of PAHs and several metal(oid)s such as As, Bi, Cd, Cu, Ni, and V. Additionally, OPDTT was found to be related to the level of K+.

WSOC in accumulation mode aerosols: Distribution and relationship with BrC light absorption at an urban background site

This paper presents the outcomes of a one-month long campaign (Jan 11, 2021 to Feb 11, 2021) of size segregated particulate matter (PM) in the accumulation mode (AM). Samples were collected at an urban background station (southeastern Iberian Peninsula) using a micro-orifice uniform deposit impactor (MOUDI). PM mass and water-soluble organic carbon (WSOC) were subsequently measured. The main goals of this research were: (1) to explore differences in WSOC mass size distributions under different meteorological conditions and (2) to determine the most efficient size for light absorption by WSOC. For the second objective, measurements of absorption coefficients (σap,λ) were obtained by means of an Aethalometer (AE33). Significant differences in WSOC concentrations and σap,λ values during stagnation episodes compared to non-event days were observed. Increases in WSOC concentrations during these episodes were most likely associated with the photochemical production of secondary compounds (in small-size ranges of the AM) and with water uptake (in large-size ranges of the AM). The average σap,λ value during this type of event was 2.6 higher than for non-event days. No significant increases in WSOC levels were detected under Saharan dust events. The average contribution of BrC to light absorption at 370 nm was ∼35%, revealing a significant influence of BrC on the absorption process. High contributions from BrC to light absorption were associated with AAE values above 1.5 and, in general, with high WSOC concentrations. WSOC in the smallest size mode (0.25 μm) was mainly emitted from biomass burning (BB) and showed the highest light absorption efficiency.

Important Contribution to Aerosol Oxidative Potential from Residential Solid Fuel Burning in Central Ireland

Numerous studies have shown negative health effects related to exposure to ambient particulate matter (PM), likely due to induced oxidative stress. In this study, we have examined ambient PM samples from Birr, a small (~5000 inhabitants) town in central Ireland, for their water-soluble DTT-based oxidative potential (OP_DTT) with a resolution of 6 h, together with online chemical characterization measurements, to assess the OP of organic aerosols, in particular from residential solid fuel burning. The OP_DTT normalized by the volume of sampled air shows a high variability, ranging from <0.1 to 3.8 nmol min−1 m−3, and a high correlation with PM mass. A lower variability was associated with the mass-normalized OP. Nevertheless, both tended to present higher values during night-time pollution episodes. Simple and multivariate linear regression approaches linked OP_DTT to residential solid fuel burning, and in particular to wood (~87%) and peat (~13%) combustion. The results of the present study show how residential solid fuel burning can have a severe impact on air quality, even in small towns, with potential negative health effects on the exposed population.

Redox-activity and in vitro effects of regional atmospheric aerosol pollution: Seasonal differences and correlation between oxidative potential and in vitro toxicity of PM1

Particulate Matter (PM) is a complex and heterogeneous mixture of atmospheric particles recognized as a threat to human health. Oxidative Potential (OP) measurement is a promising and integrative method for estimating PM-induced health impacts since it is recognized as more closely associated with adverse health effects than ordinarily used PM mass concentrations. OP measurements could be introduced in the air quality monitoring, along with the parameters currently evaluated. PM deposition in the lungs induces oxidative stress, inflammation, and DNA damage.The study aimed to compare the OP measurements with toxicological effects on BEAS-2B and THP-1 cells of winter and summer PM1 collected in the Po Valley (Italy) during 2021. PM1 was extracted in deionized water by mechanical agitation and tested for OP and, in parallel, used to treat cells. Cytotoxicity, genotoxicity, oxidative stress, and inflammatory responses were assessed by MTT test, DCFH-DA assay, micronucleus, γ-H2AX, comet assay modified with endonucleases, ELISA, and Real-Time PCR. The evaluation of OP was performed by applying three different assays: dithiothreitol (OPDTT), ascorbic acid (OPAA), and 2′,7′-dichlorofluorescein (OPDCFH), in addition, the reducing potential was also analysed (RPDPPH).Seasonal differences were detected in all the parameters investigated. The amount of DNA damage detected with the Comet assay and ROS formation highlights the presence of oxidative damage both in winter and in summer samples, while DNA damage (micronucleus) and genes regulation were mainly detected in winter samples. A positive correlation with OPDCFH (Spearman's analysis, p < 0.05) was detected for IL-8 secretion and γ-H2AX.These results provide a biological support to the implementation in air quality monitoring of OP measurements as a useful proxy to estimate PM-induced cellular toxicological responses. In addition, these results provide new insights for the assessment of the ability of secondary aerosol in the background atmosphere to induce oxidative stress and health effects.

Oxidative potential apportionment of atmospheric PM1: a new approach combining high-sensitive online analysers for chemical composition and offline OP measurement technique

Abstract. Source apportionment models were widely used to successfully assign highly time-resolved aerosol data to specific emissions and/or atmospheric chemical processes. These techniques are necessary for targeting the sources affecting air quality and for designing effective mitigation strategies. Moreover, evaluation of the toxicity of airborne particulate matter is important since the classically measured particulate matter (PM) concentrations appear insufficient for characterizing the impact on human health. Oxidative potential (OP) measurement has recently been developed to quantify the capability of PM to induce an oxidative imbalance in the lungs. As a result, this measurement unit could be a better proxy than PM mass concentration to represent PM toxicity. In the present study, two source apportionment analyses were performed using positive matrix factorization (PMF) from organic aerosol (OA) mass spectra measured at a 15 min time resolution using a time-of-flight aerosol chemical speciation monitor (ToF-ACSM) and from 19 trace elements measured on an hourly basis using an online metal analyser (Xact 625i). The field measurements were carried out in summer 2018. While it is common to perform PMF studies individually on ACSMs and more recently on Xact datasets, here we used a two-step methodology leading to a complete PM1 source apportionment. The outputs from both OA PMF and Xact PMF, the inorganic species concentrations from the ACSM, and the black carbon (BC) fractions (fossil fuel and wood burning) measured using an Aethalometer (AE33) were gathered into a single dataset and subjected to a combined PMF analysis. Overall, eight factors were identified, each of them corresponding to a more precise source than performing single PMF analyses. The results show that besides the high contribution of secondary ammonium sulfate (28 %) and organic nitrate (19 %), about 50 % of PM1 originated from distinct combustion sources, including emissions from traffic, shipping, industrial activities, cooking, and biomass burning. Simultaneously, PM1 filters were collected during the experimental period on a 4 h sampling basis. On these filters, two acellular OP assays were performed (dithiothreitol; OPDTT and ascorbic acid; OPAA) and an inversion method was applied on factors issued from all PMFs to assess the contribution of the PM sources to the OP. This work highlights the sensitivity of OPAA to industrial and dust resuspension sources and those of OPDTT to secondary ammonium sulfate, shipping, and biomass burning.

Influence of anthropogenic activities on metals, sugars and PAHs in PM10 in the city of Fez, Morocco: Implications on air quality

Particulate matter (PM) is an important component in the atmosphere, affecting air quality, health, radiation balance, and global climate. To assess regional air quality in the city of Fez, an intensive field campaign was carried out in the autumn of 2019 in the Middle Atlas region of Morocco. Aerosol sampling was performed simultaneously at two urban sites in the city of Fez: (1) Fez University (FU), a sub-urban site, and (2) Fez Parc (FP), an urban site located in the city center of Fez, using PM10 collectors. Various laboratory analyses were carried out, including PM mass, trace metals, inorganic ions, OC/EC, sugar compounds, and PAHs. The results indicate that the PM10 mass (61 ng m−3) was comparable at both sites, with a 37–107 ng m−3 range. Most of the 19 investigated PAHs at the FU site (10.2 ± 6.2 ng m−3) were low-molecular-weight PAHs, while the most abundant PAHs at the FP site (6.9 ± 3.8 ng m−3) were mainly higher-molecular-weight PAHs. A diagnostic ratio analysis at both sites indicated that PAHs originated from fossil fuel combustion and traffic emissions from diesel engines, with Ant/(Ant + Phe) and Flu/(Flu + Pyr) ratios averaging 0.22 and 0.84, respectively. PMF analysis identified traffic emissions as a major source (30%), with secondary inorganic aerosols (20%) and biomass burning (14%). Polar plots highlight the dominance of local anthropogenic activities in PM pollution, with vehicular emissions, industrial activities, and biomass burning. This study shows that local sources and combustion processes significantly contribute to PM10 sources in Morocco, providing insights into air pollution mitigation in North Africa.