Sources Of Particulate Matter Research Articles

Annual variation of source contributions to PM10 and oxidative potential in a mountainous area with traffic, biomass burning, cement-plant and biogenic influences

Toxicity of particulate matter (PM) depends on its sources, size and composition. We identified PM10 sources and determined their contribution to oxidative potential (OP) as a health proxy for PM exposure in an Alpine valley influenced by cement industry. PM10 filter sample chemical analysis and equivalent black carbon (eBC) were measured at an urban background site from November 2020 to November 2021. Using an optimized Positive Matrix Factorization (PMF) model, the source chemical fingerprints and contributions to PM10 were determined. The OP assessed through two assays, ascorbic acid (AA) and dithiothreitol (DTT), was attributed to the PM sources from the PMF model with a multiple linear regression (MLR) model. Ten factors were found at the site, including biomass burning (34, 40 and 38% contribution to annual PM10, OPAA and OPDDT, respectively), traffic (14, 19 and 7%), nitrate- and sulphate-rich (together: 16, 5 and 8%), aged sea salt (2, 2 and 0%) and mineral dust (10, 12 and 17%). The introduction of innovative organic tracers allowed the quantification of the PM primary and secondary biogenic fractions (together: 13, 8 and 21%). In addition, two unusual factors due to local features, a chloride-rich factor and a second mineral dust-rich factor (named the cement dust factor) were found, contributing together 10, 14 and 8%. We associate these two factors to different processes in the cement plant. Despite their rather low contribution to PM10 mass, these sources have one of the highest OPs per µg of source. The results of the study provide vital information about the influence of particular sources on PM10 and OP in complex environments and are thus useful for PM control strategies and actions.

Efficient particulate matter source localization in dynamic indoor environments: An experimental study by a multi-robot system

This study tackles the urgent issue of indoor particulate matter (PM) pollutants, highlighting the critical need for efficient source localization due to its significant health risks. Moving beyond traditional constant-rate gas emission research, we explore real-world PM releases using a multi-robot system, enabling effective PM source localization in dynamically ventilated environments. Initial data collection on airflow and PM concentrations helps optimize our system for mechanical ventilation challenges. Through 90 experiments across six scenarios, we evaluate the improved whale optimization algorithm (IWOA) and improved particle swarm optimization (IPSO) methods, assessing their ability to identify both constant and variable PM sources and their adaptability to different pollutants. The results show a success rate of 73.3 % for both methods in locating constant PM sources, with IPSO offering a slight edge in efficiency. Moreover, in tasks involving ethanol vapor, the methods exhibited higher success rates, indicating uniform performance across a variety of pollutants. This consistency, alongside the noted variations in success rates, is primarily attributed to the complexities of PM dispersion. Importantly, our study highlights the methods' adaptability to periodic PM sources with variable release rates, maintaining high success without extra localization steps. This research advances indoor air quality management and emphasizes the importance of flexible, effective pollutant control strategies for public health protection.

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.

Remote sensing estimation of δ15NPN in the Zhanjiang Bay using Sentinel-3 OLCI data based on machine learning algorithm

Remote sensing estimation of δ15NPN in the Zhanjiang Bay using Sentinel-3 OLCI data based on machine learning algorithm

Integrating spatially distributed data into Positive Matrix Factorization to identify the hotspots of local emission sources

The receptor model of Positive Matrix Factorization (PMF) is widely used to identify the air pollution sources of fine particulate matter (PM2.5). However, using data collected at a single site in PMF analysis limits its ability to characterize the source emission regions. To recognize the hotspots of emission sources, this study incorporated spatially distributed PM2.5 mass concentrations into PMF modeling to estimate the spatial distribution of source-specific PM2.5. A local emission source of road dust/civil construction was retrieved and selected for evaluation of the characterized hotspot regions. The spatial distribution of the corresponding source-specific PM2.5 contributions in the study area was compared with the land use features. The positive correlations (coefficients ≥0.40) were acquired between source-specific PM2.5 and land use characteristics, such as major road length and the number of construction sites. A leave-one-out cross-validation R2 of 0.48 was achieved using the land use regression model. These findings demonstrated the effectiveness of the proposed approach in capturing spatial variations of local emission sources. Future studies are suggested to expand the study area to further assess the extent of application of the PMF spatialization results.

Particulate Matter Pollution and Health Impacts in Six North African Countries

This paper addresses the issue of outdoor particulate matter pollution in six North African countries-Algeria, Egypt, Libya, Morocco, Sudan, and Tunisia. Major particulate matter sources include various industries and transportation systems, dust storms, and sandstorms. It has been shown that there is a need to increase public awareness and participation and enhance capacities regarding ground-based monitoring of particulate matter, using satellite data, and assessing the health impacts of exposure to particulate matter. There is also a need for improved legislation and better governance regarding its implementation and enforcement. If possible, examples of potential impacts of particulate matter pollution on the Gross National Product (GNP) for various economic and health sectors will be reported. As outdoor particulate matter pollution is one of the major sources of loss to the GNP, air quality management needs to be strengthened.

Systemic effects of settleable atmospheric particulate matter (SePM) on swamp ghost crab Ucides cordatus

Metallurgical activities are a significant source of settleable atmospheric particulate matter (SePM). The material is exposed to wind action, leading to its deposition throughout terrestrial and aquatic ecosystems, thus promoting contamination by metals and metalloids. However, knowledge of the impacts on biota is scarce. In aquatic coastal zones, evaluating hemolymph in invertebrates makes it possible to have insights into the pre-pathogenic effects and health status of organisms. Our study aimed to evaluate bioaccumulation and the sublethal effects of SePM on the mangrove crab Ucides cordatus by assessing biomarkers of cito-genotoxicity in the hemolymph. Organisms underwent a 30-day experiment with four treatments: control; 0.01 g.L−1, 0.1 g.L−1, 1 g.L−1 of SePM, with hemolymph sampled at 2, 7, 15, and 30 days of exposure to assess lipid peroxidation (LPO), DNA damage (strand break), cholinesterase (ChE) and lysosomal membrane stability (LMS). The results revealed metals' bioaccumulation in soft tissues (Al, Fe+, Fe++, Cu, Zr, Nb) and dose-time-dependent responses for LPO, DNA strand break, ChE, and LMS. Significant correlation was found between LPO and Cu (tissue), reduced LMS and Al and Fe (tissue), and Cu, Zn, Ag, and Bi in water. Hemolymph was related to the toxicokinetic and toxicodynamic of metals and metalloids from SePM in Ucides cordatus. New toxicological evidence was obtained to shed light on the impacts of SePM on the ecological status of coastal zones.

Evaluating the Particulate Matter and Carbon Dioxide Reduction of Four Broad-leaved Evergreen Plants

Background and objective: Since people spend 70-80% of their time indoors, the quality of indoor air has become a crucial factor in overall health. Therefore, poor indoor air quality can have significant adverse effects on our well-being. Common indoor air pollutants are particulate matter (PM) and carbon dioxide (CO2). Plants can remove PM and CO2 through the photosynthesis process and leaf surfaces, and regulate the temperature and humidity of the air. By analyzing the PM and CO2 reduction of four broad-leaved evergreen plants, this study aims to provide data for air purification in indoor spaces.Methods: The four different plant species (Neolitsea sericea (Blume) Koidz., Coffea arabica L., Photinia glabra(Thunb.) Franch. and Sav., and Farfugium japonicum (L.) Kitam.) were selected for this study. Mosquito coils and a CO2 cylinder were the primary sources of PM and CO2. These pollutants were injected into a closed acrylic chamber with plants, and the air quality within the chamber was monitored for a duration of five hours. The plants' effectiveness in reducing carbon dioxide was evaluated through the clean air delivery rate (CADR), while their ability to reduce PM was assessed by analyzing the PM reduction rate. Photosynthetic rates and leaf area were also measured to determine the correlation between air pollution removal and these factors.Results: The ability to remove PM and CO2 varied among plants. Plants with higher rates of photosynthesis were more effective in reducing PM and CO2 than those with lower rates. Among the four plant species, C. arabica and P. glabra were more effective in removing PM and CO2 than the other species. The chamber containing plants exhibited higher humidity and lower temperatures compared to the chamber without plants.Conclusion: These findings suggest that plants can play a significant role in improving indoor air quality. Not only do they effectively reduce levels of PM and CO2, but they also contribute to the regulation of indoor temperature and humidity. The implications of these results highlight the potential of integrating plants into indoor spaces as a natural and multifaceted solution for creating healthier and more comfortable environments.

MiR-145a-5p/SIK1/cAMP-dependent alteration of synaptic structural plasticity drives cognitive impairment induced by coke oven emissions

Exposure to fine particulate matter (PM) is associated with the neurodegenerative diseases. Coke oven emissions (COEs) in occupational environment are important sources of PM. However, its neurotoxicity is still unclear. Therefore, evaluating the toxicological effects of COE on the nervous system is necessary. In the present study, we constructed mouse models of COE exposure by tracheal instillation. Mice exposed to COE showed signs of cognitive impairment. This was accompanied by a decrease in miR-145a-5p and an increase in SIK1 expression in the hippocampus, along with synaptic structural damage. Our results demonstrated that COE-induced miR-145a-5p downregulation could increase the expression of SIK1 and phosphorylated SIK1, inhibiting the cAMP/PKA/CREB pathway by activating PDE4D, which was associated with reduced synaptic structural plasticity. Furthermore, restoring of miR-145a-5p expression based on COE exposure in HT22 cells could partially reversed the negative effects of COE exposure through the SIK1/PDE4D/cAMP axis. Collectively, our findings link epigenetic regulation with COE-induced neurotoxicity and imply that miR-145a-5p could be an early diagnostic marker for neurological diseases in patients with COE occupational exposure.

Local incomplete combustion emissions define the PM2.5 oxidative potential in Northern India

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.

Chemical composition and trajectories of atmospheric particles at the Machu Picchu Peruvian Antarctic scientific station (62.09º S, 58.47º W)

Antarctica is a remote and relatively pristine region, but the regional transport of aerosols may be a source of pollution, especially in the Antarctic Peninsula. Few studies have characterized atmospheric aerosols and evaluated the contribution of their emission sources. The Peruvian Antarctic research station Machu Pichu (ECAMP, by its Spanish acronym) is located on King George Island in the Antarctic Peninsula. During February 2020, atmospheric particulate mass (PM10 and PM2.5) was sampled and analyzed to characterize its elemental composition and was supplemented by measurements of equivalent black carbon and aerosol size distributions. Chemical elements were analyzed by inductively coupled plasma mass spectrometry (ICP-MS), multivariate techniques, and enrichment factors. The most abundant elements in PM10 and PM2.5 were Na, Fe, Mg, and Si, with the most important local sources being marine (Na, Mg, Mn, Ca) and crustal (Fe, Al, P). Sources of weathering (Ba and Si) from glacial thawing and sources of combustion linked to the use of oil (V) and emission of black carbon were recorded. Air mass back-trajectory analysis using the HYSPLIT model helped identify external sources of particulate matter in the air masses reaching the ECAMP site. Overall, this study supports the growing evidence of the anthropogenic impact of distant and local sources on the white continent.

Comprehending particulate matter dynamics in transit-oriented developments: Traffic as a generator and design as a captivator

In Transit-Oriented Development (TOD), the close integration of residential structures with community activities and traffic heightens residents' exposure to traffic-related pollutants. Despite traffic being a primary source of particulate matter (PM), the compact design of TODs, together with the impact of urban heat island (UHI), increases the likelihood of trapping emitted PM from traffic, leading to heightened exposure of TOD residents to PM. Although PM originates from two distinct sources in road traffic, exhaust and non-exhaust emissions (NEE), current legislation addressing traffic-related PM from non-exhaust emissions sources remains limited. This paper focuses on two TOD typologies in Manchester City—Manchester Piccadilly and East Didsbury—to understand the roles of TOD traffic as a PM generator and TOD place design as a PM container and trapper. The investigation aims to establish correlations between street design canyon ratios, vehicular Speed, and PM10/PM2.5, providing design guidance and effective traffic management strategies to control PM emissions within TODs. Through mapping the canyon ratio and utilising the Breezometer API for PM monitoring, the paper revealed elevated PM levels in both TOD areas, exceeding World Health Organization (WHO) recommendations, particularly for PM2.5. Correlation analysis between canyon configuration and PM2.5/PM10 highlighted the importance of considering building heights and avoiding the creation of deep canyons in TOD design to minimise the limited dispersion of PM. Leveraging UK road statistics and the PTV Group API for vehicle speed calculations, the paper studied the average speeds on the TOD roads concerning PM. Contrary to conventional assumption, the correlation analyses have revealed a noteworthy association shift between vehicular speed and PM concentrations. A positive correlation existed between speed increase and PM increases on arterial roads. However, a negative correlation emerged on main, collector, and local streets, indicating that PM levels rise for both PM10 and PM2.5 as Speed decreases. These findings challenge the traditional assumption that higher Speed leads to increased emissions, highlighting the potential impact of NEE on PM concentrations. This paper calls for thorough design considerations and traffic management strategies in TOD, especially in dense areas, considering building height, optimising traffic flow, and enhancing compromised air quality associated with vehicular emissions.

Image based analytical approaches for study of particulate matter (PM) in air

Particulate matter (PM) stands as a predominant pollutant in developing countries, demanding effective source identification and remediation strategies. This review centers on the scanning electron microscopy (SEM) image-based methodology for PM analysis, particularly emphasizing the passive technique of utilizing plant leaves for PM capture. The SEM-image-based approach serves as a powerful tool for unraveling the morphological characteristics of PM, crucial for source identification. Additionally, SEM, when equipped with energy dispersive spectroscopy (EDS), enables chemical and mineralogical characterization, providing insights into the origin of PM. The first part of the review describes the plant as the best bio-sampler for PM. In this context, removal of PM from the environment through plant-based interventions is described. Subsequently, the application of SEM for size-based analysis using ImageJ and morphological analysis for source identification of PM is detailed. Following this, the PM chemical and mineralogical composition for source identification are described based on EDS analysis. Image-based techniques play a pivotal role in selecting the most effective plant species for PM removal from the air. The review comprehensively outlines the morphological, chemical, and mineralogical attributes utilized for PM source identification and their subsequent remediation by plants. Finally, the benefits of SEM-image-based techniques for PM analysis are elucidated. This review offers a holistic understanding of the SEM-EDS and plant-based approach, presenting a promising avenue for addressing PM pollution and enhancing environmental quality.

Contributions and limitations of environmental magnetism to characterize traffic-related particulate matter sources

SUMMARY The chronic exposure to particulate matter (PM) pollution causes societal and environmental issues, in particular in urban areas where most citizen are regularly exposed to vehicular traffic. Since almost two decades, environmental magnetic monitoring has demonstrated its efficiency to successfully map relative concentrations of airborne particle deposition on accumulative surfaces. A better understanding of the magnetic results requires discriminating the main traffic-related sources of the observed signal on particle collectors. To meet this objective, we investigated a sample set of exhaust and non-exhaust sources with respect to their magnetic fingerprints inferred from hysteresis loops, first-order reversal curve (FORC) diagrams, temperature dependency of initial susceptibility and unmixing of isothermal remanent magnetization acquisition curves. The source sample set comprises 14 diesel and gasoline exhaust smoke residues, 12 abrasive-fatigue wear test pieces from worn brake-pads, brake powders, worn tire-tread and three resuspension products: asphalt concrete, street dust and Saharan mineral dust deposited by precipitation after long-range eolian transport. Magnetic properties of the source samples were compared to those from various accumulative surfaces exposed to urban traffic (passive collectors, filters of facemasks for cycling, plant leaves and tree barks). We found some fingerprints of exhaust pipes and brake wear products on these collectors. The findings highlight the relevance of environmental magnetism tools to characterize different traffic-related source signals in accumulative surfaces in urban environment.

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.

Determination of Occupational Exposure to Ultrafine Particles in Different Sectors of Activity

The primary sources of ultrafine particulate matter are linked to human activity. Certain particulate emissions, particularly those of a finer nature, can significantly impact human health, making them one of the most concerning pollutants. Ultrafine particles (UFPs), which have a diameter of less than 100 nm, are of particular concern due to their impact on human health and the difficulty in controlling them. The concentration of ultrafine particles (UFPs) in the workplace is a growing concern and is classified as an emerging risk. Workers may be exposed to UFPs through inhalation, skin absorption, ingestion, or a combination of these routes. This study aims to determine the levels of UFP exposure among workers in environments with varying direct particle emission patterns. Measurements were conducted to compare the results with the levels recommended by the WHO. The study monitored industrial workplaces with direct particulate matter emissions, such as a carpentry workshop and a bakery, as well as social sector sites without or almost without direct particle emissions, such as a school and a health clinic. One conclusion drawn from this study is that all tasks and occupations are susceptible to high levels of UFPs, exceeding WHO recommended values in virtually all monitored environments. Therefore, monitoring and controlling UFPs is crucial. Further in-depth studies on this subject are also necessary.

Using stable carbon isotopes of lignin-derived methoxy to improve historical apportionments of particulate organic matter and sediment sources incorporating multiple Suess corrections

PurposeSoil erosion models are essential to improving sediment management strategies. Sediment source fingerprinting is used to help validate erosion models. Fingerprinting sediment sources with organic isotopic tracers faces challenges from aquatic sources and co-linearity. To address these complexities, integrating another land-use-specific tracer is essential. Suess corrections incorporating multiple mean-residence-times are necessary to accurately model historical sediment apportionments. In previous studies, compound specific isotopic tracers indicated forest as the dominant source. We hypothesize that there is an overestimation of forest contribution, attributed to the misclassification of particulate organic matter as forest.MethodsIn this study, we utilize stable carbon isotope (δ13C) values of fatty acids and the average chain length in combination with the δ13C values of lignin-derived methoxy groups as an additional tracer. We apply different Suess corrections to explore the effect of the changing atmospheric δ13CO2 values on sediment apportionment. The performance of the unmixing model is evaluated with 300 mathematical mixtures. To determine shifts in sediment sources throughout the last 130 years, particulate organic matter contributions are determined and removed to apportion sediment soil sources. We investigate the potential misclassification of forest contributions by merging particulate organic matter and forest sources to simulate tracers which are unable to discriminate.ResultsThe inclusion of δ13C values of lignin methoxy groups and the alkane average chain length as additional tracers successfully removed tracer co-linearity. Additionally, we used an updated concentration dependent point in polygon test to identify sediment with increased potential for incorrect source apportionments. Changes in the dominant sediment sources over time (Forest: pre-1990, Pasture: 1910–1940, Arable: post 1940) highlight the effect of policy-induced land-use changes. Additionally, the inability to discriminate particulate organic matter and forest sources was revealed to cause a 37% overestimation of forest contributions from 1944 to 1990.ConclusionUsing δ13C values of lignin methoxy groups as an additional tracer, we identified critical points in the 130-year sediment history of Lake Baldegg. Furthermore, we highlight the importance of incorporating multiple Suess effects. Through mathematical mixtures, we assessed the confidence that should accompany apportionment estimates. While merging forest and particulate organic matter sources did not result in forest as the dominant source over the last 130 years, separating these sources resulted in more accurate apportionment. These insights offer valuable information to enhance the accuracy of sediment fingerprinting, which can then be used to assist soil erosion models employed for sediment mitigation policies.

Identification and quantification of trace metal(loid)s in water-extractable road dust nanoparticles using SP-ICP-MS

Resuspension of road dust is a major source of airborne particulate matter (PM) in urban environments. Inhalation of ultrafine particles (UFP; < 0.1 μm) represents a health concern due to their ability to reach the alveoli and be translocated into the blood stream. It is therefore important to characterize chemical properties of UFPs associated with vehicle emissions. We investigated the capability of Single-Particle ICP-MS (SP-ICP-MS) to quantify key metal(loid)s in nanoparticles (NPs; < 0.1 μm) isolated from road dust collected in Toronto, Canada. Water extraction was performed to separate the <1-μm fraction from two different road dust samples (local road vs. arterial road) and a multi-element SP-ICP-MS analysis was then conducted on the samples' supernatants. Based on the particle number concentrations obtained for both supernatants, the metal(loid)-containing NPs could be grouped in the following categories: high (Cu and Zn, > 1.3 × 1011 particles/L), medium (V, Cr, Ba, Pb, Sb, Ce, La), low (As, Co, Ni, < 4.6 × 109 particles/L). The limit of detection for particle number concentration was below 5.5 × 106 particles/L for most elements, except for Cu, Co, Ni, Cr, and V (between 0.9 and 7.7 × 107 particles/L). The results demonstrate that road dust contains a wide range of readily mobilizable metal(loid)-bearing NPs and that NP numbers may vary as a function of road type. These findings have important implications for human health risk assessments in urban areas. Further research is needed, however, to comprehensively assess the NP content of road dust as influenced by various factors, including traffic volume and speed, fleet composition, and street sweeping frequency. The described method can quickly characterize multiple isotopes per sample in complex matrices, and offers the advantage of rapid sample scanning for the identification of NPs containing potentially toxic transition metal(loid)s at a low detection limit.

Cohort profile: The Assessing Imperial Valley Respiratory Health and the Environment (AIRE) study.

The Children's Assessing Imperial Valley Respiratory Health and the Environment (AIRE) study is a prospective cohort study of environmental influences on respiratory health in a rural, southeastern region of California (CA), which aims to longitudinally examine the contribution of a drying saline lake to adverse health impacts in children. This cohort was established through a community-academic partnership with the goal of assessing the health effects of childhood exposures to wind-blown particulate matter (PM) and inform public health action. We hypothesize that local PM sources are related to poorer children's respiratory health. Elementary school children in Imperial Valley, CA. Prospective cohort study. Between 2017 and 2019, we collected baseline information on 731 children, then follow-up assessments yearly or twice-yearly since 2019. Data have been collected on children's respiratory health, demographics, household characteristics, physical activity and lifestyle, via questionnaires completed by parents or primary caregivers. In-person measurements, conducted since 2019, repeatedly assessed lung function, height, weight and blood pressure. Exposure to air pollutants has been assessed by multiple methods and individually assigned to participants using residential and school addresses. Health data will be linked to ambient and local sources of PM, during and preceding the study period to understand how spatiotemporal trends in these environmental exposures may relate to respiratory health. Analyses of respiratory symptoms indicate a high prevalence of allergies, bronchitic symptoms and wheezing. Asthma diagnosis was reported in 24% of children at enrolment, which exceeds both CA state and US national prevalence estimates for children. The Children's AIRE cohort, while focused on the health impacts of the drying Salton Sea and air quality in Imperial Valley, is poised to elucidate the growing threat of drying saline lakes and wind-blown dust sources to respiratory health worldwide, as sources of wind-blown dust emerge in our changing climate.

Impact of altitude on the dosage of indoor particulates entering an individual’s small airways

The complexity of indoor particulate exposure intensifies at higher altitudes owing to the increased lung capacity that residents develop to meet the higher oxygen demands. Altitude variations impact atmospheric pressure and alter particulate dynamics in ambient air and the human respiratory tract, complicating particulate inhalation. This study assessed the fraction of PM2.5 and PM10 entering small airways. This assessment covered an altitude range from 400 m above sea level to 3650 m, and an in vitro respiratory tract model was used. The experimental results confirmed that with increasing altitude, the penetration fractions of PM2.5 and PM10 significantly increased from 0.133 ± 0.031 and 0.141 ± 0.045 to 0.404 ± 0.159 and 0.353 ± 0.132, respectively. Additionally, the computational fluid dynamics simulation results revealed that among particles with sizes of 0.1 to 10 µm, the 7.5-μm particles exhibited the most substantial reduction in deposition in the upper airway, displaying a decrease of 6.27%. Our findings underscore the health risks faced by low-altitude residents during acclimatization to higher altitudes, as they experience heightened exposure to particulate matter sources.