Search Results (28)

Wildfires pose a direct threat to the property, life, and well-being of the population of Montana, USA, and indirectly to their health through hazardous smoke and gases emitted into the atmosphere. Studies have shown that elevated levels of particulate matter cause impacts to human health ranging from early death, to neurological and immune diseases, to cancer. Although there is currently a network of ground-based air quality sensors (n = 20) in Montana, the geographically sparse network has large gaps and lacks the ability to make accurate predictions for air quality in many areas of the state. Using the random forest method, a predictive model was developed in the Google Earth Engine (GEE) environment to estimate PM2.5 concentrations using satellite-based aerosol optical depth (AOD), dewpoint temperature (DPT), relative humidity (RH), wind speed (WIND), wind direction (WDIR), pressure (PRES), and planetary-boundary-layer height (PBLH). The validity of the prediction model was evaluated using 10-fold cross validation with a R² value of 0.572 and RMSE of 9.98 µg/m³. The corresponding R² and RMSE values for ‘held-out data’ were 0.487 and 10.53 µg/m³. Using the validated prediction model, daily PM2.5 concentration maps (1 km-resolution) were estimated from 2012 to 2023 for the state of Montana. These concentration maps are accessible via an application developed using GEE. The product provides valuable insights into spatiotemporal trends of PM2.5 concentrations, which will be useful for communities to take appropriate mitigation strategies and minimize hazardous PM2.5 exposure. Full article

The increase in industrial activities has raised concerns regarding air quality in urban areas within Malawi. To assess the source apportionment of air quality parameters (AQPs) and noise levels, concentrations of AQPs (CO, TSP, PM _2.5, PM₁₀) and noise levels were monitored at 15 sites in Makata, Limbe, Maselema, Chirimba, and Maone during dry and wet seasons, respectively. Active mobile multi-gas monitors and a Dylos DC1100 PRO Laser Particle Counter (2018 model) were used to monitor AQPs, while Integrated Sound Level Meters were used to measure noise levels. Monitoring and analysis were guided by the World Health Organization (WHO) and Malawi Standards (MS). A Positive Matrix Factorization (PMF) model was used to determine source apportionment of AQPs, and matrix trajectories analysed air mass movement. In the wet season, the average concentration values of CO, TSP, PM₁₀, and PM_2.5 were 0.49 ± 0.65 mg/m³, 85.03 ± 62.18 µg/m³, 14.65 ± 8.13 µg/m³, and 11.52 ± 7.19 µg/m³, respectively. Dry season average concentration values increased to 1.31 ± 0.81 mg/m³, 99.86± 30.06 µg/m³, 24.35 ± 9.53 µg/m³, and 18.28 ± 7.14 µg/m³. Noise levels remained below public MS and WHO standards (85 dB). Positive correlations between AQPs and noise levels were observed, strengthening from weak in the dry season to moderately strong in the wet season. PMF analysis identified key factors influencing AQPs accumulation, emphasizing the need for periodic sampling to monitor seasonal pollution trends, considering potential impacts on public health and environmental sustainability. Further studies should look at factors affecting the dynamics of PMF in Blantyre City. Full article

Sidewalk cleaning operations are essential to maintaining a clean and safe urban environment. Despite their vital role, these activities, particularly the blowing of road dust, can lead to the resuspension of road dust and associated pollutants, which poses risks to human health and the environment. While the role of blowers on particulate matter resuspension has been investigated, there is limited information on emitted bioaerosols. This study aimed to compare the occupational exposure of operators and passersby during sidewalk cleaning using two manual methods—blowing and jet washing—in two distinct urban environments. The study focused on metal road traffic tracers (copper (Cu), zinc (Zn), manganese (Mn), cadmium (Cd), and lead (Pb)) and cultivable/non-cultivable microorganisms. We showed that blowing resuspends inhalable particles containing metals (Cu, Zn, and Mn, but not Cd or Pb) and bioaerosols (fungi and Gram-negative bacteria) throughout the year. This represents an important source of exposure for the blower operators and poses a potential long-term respiratory health risk for them. Operators working in cabs are shielded from such exposure, but passersby, especially vulnerable populations, may be at risk. While jet washing reduces operator exposure to Gram-negative bacteria in comparison to blowing, it does not mitigate fungal exposure, particularly in vegetated sites. These findings underscore the necessity for the implementation of effective protective measures and the development of alternative cleaning methods to mitigate exposure risks. Full article

The authors present an analysis of the correlation between demographic and territorial indicators and greenhouse gas (GHG) emissions, emphasizing the spatial aspect using statistical methods. Particular attention is given to the application of correlation techniques, considering the spatial correlation between the involved variables, such as demographic, territorial, and environmental indicators. The demographic data include factors such as population, demographic distribution, and population density; territorial indicators include land use, particularly settlements, and road soil occupancy. The aims of this study are as follows: (1) to identify the direct relationships between these variables and emissions; (2) to evaluate the spatial dependence between geographical entities; and (3) to contribute to generating a deeper understanding of the phenomena under examination. Using spatial autocorrelation analysis, our study aims to provide a comprehensive framework of the territorial dynamics that influence the quantity of emissions. This approach can contribute to formulating more targeted environmental policies, considering the spatial nuances that characterize the relationships between demographics, territory, and GHGs. The outcome of this research is the identification of a direct formula to obtain greenhouse gas emissions from data about land use starting from the case study of Pavia Province in Italy. In the paper, the authors highlight different methodologies to compare land use and GHG emissions to select the most feasible correlation formula. The proposed procedure has been tested and can be used to promote awareness of the spatial dimension in the analysis of complex interactions between anthropogenic factors and environmental impacts. Full article

Airports are significant contributors of atmospheric pollutant aerosols, namely ultrafine particles (UFPs). This study characterizes the particle number concentration (PNC), the median particle size (d_mn50), and the metallic composition of medium-haul area and engine aerosols at two French airports (Paris-CDG and Marseille). This study followed the standard operating procedures for characterizing aerosol emissions from 5 nm to 8 μm (OECD, 2015; EN 17058:2018). It allows determining which are the specific parameters directly related to the emission sources and their contribution to the overall aerosols measured at workplace in airports. The particulate emissions observed during aircraft engine start-up were ~19× higher than the average airborne concentration. The particle size distributions remained mostly <250 nm with d_mn50 < 100 nm (showing a specificity for the medium-haul area with an average d_mn50 of ~12 nm). The d_mn50 can be used to distinguish emission peaks due to aircrafts (d_mn50~15 nm) from those due to apron vehicle activities (d_mn50 > 20 nm). Chemical elements (titanium and zinc) were identified as potential tracers of aircraft emissions and occurred mainly at the micrometric scale. For aircraft engine emissions, UFPs are mainly due to fuel combustion with the presence of carbon/oxygen. The study concludes with suggestions for future research to extend on the findings presented. Full article

Biomass burning is one of the largest sources of particulate matter emissions globally. However, the emission of particulate inorganic species from prescribed grassland burning in Japan has not yet been characterized. In this study, we collected total suspended particulate matter from prescribed grassland burning in Hirado, Akiyoshidai, and Aso, Japan. The collected filter samples were brought to the laboratory, and water-soluble inorganic components were analyzed via ion chromatography. The measurement results showed high excess concentrations of potassium, calcium, and magnesium, and these substances were highly correlated, which agreed with previously reported findings. In contrast, the concentrations of sodium, chloride, nitrate, and sulfate were insignificant, even though their high concentrations were reported in other biomass burning studies. Among these low concentration substances, a high correlation was still observed between sulfate and nitrate. It is possible that the low concentrations of those species could have been biased in the measurements, particularly as a result of subtracting blank and background values from the observed concentrations. Building up more data in this area may allow us to characterize the significance of domestic biomass burning’s contribution to inorganic particulate components in Japanese air, which may consequently contributes to better understanding of adverse health effect of airborne particulate matter. Full article

This paper describes an innovative method that recursively applies the machine learning Random Forest to an assumed homogeneous aerographic domain around measurement sites to predict concentrations and emissions of ammonia, an atmospheric pollutant that causes acidification and eutrophication of soil and water and contributes to secondary PM_2.5. The methodology was implemented to understand the effects of weather and emission changes on atmospheric ammonia concentrations. The model was trained and tested by hourly measurements of ammonia concentrations and atmospheric turbulence parameters, starting from a constant emission scenario. The initial values of emissions were calculated based on a bottom-up emission inventory detailed at the municipal level and considering a circular area of about 4 km radius centered on measurement sites. By comparing predicted and measured concentrations for each iteration, the emissions were modified, the model’s training and testing were repeated, and the model converged to a very high performance in predicting ammonia concentrations and establishing hourly time-varying emission profiles. The ammonia concentration predictions were extremely accurate and reliable compared to the measured values. The relationship between NH₃ concentrations and the calculated emissions rates is compatible with physical atmospheric turbulence parameters. The site-specific emissions profiles, estimated by the proposed methodology, clearly show a nonlinear relation with measured concentrations and allow the identification of the effect of atmospheric turbulence on pollutant accumulation. The proposed methodology is suitable for validating and confirming emission time series and defining highly accurate emission profiles for the improvement of the performances of chemical and transport models (CTMs) in combination with in situ measurements and/or optical depth from satellite observation. Full article

Background: Growing evidence suggests that air pollution may influence fetal development, with potential consequences for later health. Alteration of telomere length (TL) is one possible mediating mechanism for the link between fetal exposure to air pollution and the development of disease. However, the few studies exploring associations between prenatal pollution and infant TL have assessed varied trimesters of pregnancy and shown mixed results. The aim of this study was to examine the differential relationships between prenatal exposure to air pollutant PM_2.5 during the first, second, and third trimesters of pregnancy with infant TL at one month of age. Methods: Women (n = 74) were recruited in obstetric clinics during their third trimester. Data on PM_2.5 exposure for each woman’s residential area during each trimester was acquired from the regional Air Quality Management District. At one month postnatal, a salivary sample was collected from the infant, which provided DNA for the telomere assay. Women completed questionnaires about stressors in their lives, perceived stress, depression, and sociodemographics for inclusion as covariates. Multiple linear regression was used to analyze the results. Results: PM_2.5 exposure during the second (β = 0.31, p = 0.003) and third (β = 0.24, p = 0.02) trimesters was associated with longer infant TL. Exposure in the first trimester was not related to TL. Covariates of maternal depression and age and infant female sex were also associated with longer TL. Variables in the model contributed to 34% of the variance in TL (F = 10.58, p = 0.000). Discussion: Fetal programming of longer telomeres in response to pollution may have adaptive value in preparing the neonate for a postnatal environment that is less than optimal in terms of air quality. Alternatively, longer telomeres may forecast later health risks, considering established links between longer TL and diseases such as cancer. Future research needs to address how prenatal pollution interacts with TL to influence health over time. Full article

The global concern of escalating ambient air pollution and its profound impact on human health is paramount. While traffic police personnel are critical for maintaining the road safety and transportation system of any city in India, they are susceptible to occupational health risks due to ambient air pollution. This study investigated health challenges faced by traffic police personnel due to prolonged exposure to air pollutants prevalent in traffic-congested areas, including particulate matter (PM_2.5 and PM₁₀), nitrogen dioxide, and sulfur dioxide. The first phase of this study collected and analyzed secondary air quality data over five years (2019–2023) across six locations in Kolkata, India. The second phase employed a questionnaire-based survey to assess the health implications of air pollution exposure. The survey questionnaire captured information on physical health symptoms, stress-related indicators, lifestyle habits, and work hours of around 100 police personnel from Kolkata with indoor (control group) and outdoor (exposed group) work responsibilities. The results of this study established a strong positive correlation between air pollution and a range of health issues experienced by the exposed group. The outcome of this study is significant for urban planning, policy formulation, and public health interventions geared toward minimizing the adverse impacts of air pollution on traffic police personnel. Full article

Source apportionment of observed PM_2.5 concentrations is of growing interest as communities seek ways to improve their air quality. We evaluated publicly available PM_2.5 data from the USEPA in the Dallas–Fort Worth metropolitan area to determine the contributions from various PM_2.5 sources to the total PM_2.5 observed. The approach combines interpolation and fixed effect regression models to disentangle background from local PM_2.5 contributions. These models found that January had the lowest total PM_2.5 mean concentrations, ranging from 5.0 µg/m³ to 6.4 µg/m³, depending on monitoring location. July had the highest total PM_2.5 mean concentrations, ranging from 8.7 µg/m³ to 11.1 µg/m³, depending on the location. January also had the lowest mean local PM_2.5 concentrations, ranging from 2.6 µg/m³ to 3.6 µg/m³, depending on the location. Despite having the lowest local PM_2.5 concentrations, January had the highest local attributions [51–57%]. July had the highest mean local PM_2.5 concentrations, ranging from 2.9 µg/m³ to 4.1 µg/m³, depending on the location. Despite having the highest local PM_2.5 concentrations, July had the lowest local attributions [33–37%]. These results suggest that local contributions have a limited effect on total PM_2.5 concentrations and that the observed seasonal changes are likely the result of background influence, as opposed to modest changes in local contributions. Overall, the results demonstrate that in the Dallas–Fort Worth metropolitan area, approximately half of the observed total PM_2.5 is from background PM_2.5 sources and half is from local PM_2.5 sources_. Among the local PM_2.5 source contributions in the Dallas–Fort Worth metropolitan area, our analysis shows that the vast majority is from non-point sources, such as from the transportation sector. While local point sources may have some incremental site-specific local contribution, such contributions are not clearly distinguishable in the data evaluated. We present this approach as a roadmap for disentangling PM_2.5 concentrations at different spatial levels (i.e., the local, regional, or state level) and from various sectors (i.e., residential, industrial, transport, etc.). This roadmap can help decision-makers to optimize mitigatory, regulatory, and/or community efforts towards reducing total community PM_2.5 exposure. Full article

The urban areas of Pakistan exhibit some of the world’s highest levels of air pollution, primarily due to sub-2.5 μm particulate emissions. This issue significantly impairs both the country’s economy and the quality of life of its residents. Road transport is a significant contributor to anthropogenic air pollution but there are discrepancies about the extent of its share. Source apportionment and sectoral inventory studies attribute anywhere between 5 and >80% of the total air pollution to vehicular sources. This uncertainty propagates into the transport policy interventions that are informed by such studies and can thus hinder the achievement of desired pollution mitigation targets. In an effort to reconcile such discrepancies and guide future studies and policy-making efforts, this paper critically reviews source apportionment studies conducted in the urban centres of Pakistan over the past two decades. The strengths and weaknesses of different approaches are compared, and results from the studies are discussed based on the emissions profile of Pakistan’s automotive fleet that emerges. Inconsistencies in the reporting of pollutant concentrations and interpreting their impacts without accounting for the relative disease burden of different pollutant species are found to be the major reasons for the large variations in the reported sectoral shares. At the end, a framework for regular air pollution monitoring and source tracking is proposed in which high-fidelity receptor-based studies inform lower-fidelity but economical sectoral inventory assessments. Full article

The impact of relative humidity (RH) on organic new particle formation (NPF) from the ozonolysis of biogenic volatile organic compounds (BVOCs) remains an area of active debate. Previous reports provide contradictory results, indicating both the depression and enhancement of NPF under conditions of high RH. Herein, we report on the impact of RH on NPF from the dark ozonolysis of cis-3-hexenyl acetate (CHA), a green-leaf volatile (GLV) emitted by vegetation. We show that RH inhibits NPF by this BVOC, essentially shutting it down at RH levels > 1%. While the mechanism for the inhibition of NPF remains unclear, we demonstrate that it is likely not due to increased losses of CHA to the humid chamber walls. New oxidation products dominant under humid conditions are proposed that, based on estimated vapor pressures (VPs), should enhance NPF; however, it is possible that the vapor phase concentration of these low-volatility products is not sufficient to initiate NPF. Furthermore, the reaction of C₃-excited state Criegee intermediates (CIs) with water may lead to the formation of small carboxylic acids that do not contribute to NPF. This hypothesis is supported by experiments with quaternary O₃ + CHA + α-pinene + RH systems, which showed decreases in total α-pinene-derived NPF at ~0% RH and subsequent recovery at elevated RH. Full article

Air quality monitoring in Ireland is under the jurisdiction of the Environmental Protection Agency in compliance with the Gothenburg Protocol, EU/national legislation, and the National Clean Air Strategy. Secondary inorganic aerosols (SIAS) have been acknowledged as a key atmospheric pollutant, with serious public health impacts and no safe exposure threshold in place to date. Ammonia (NH₃) emissions are linked to the secondary production of aerosols through atmospheric reactions occurring with acidic atmospheric components such as sulfuric, nitric, and hydrochloric acid. These reactions result in the formation of ammonium sulfate, ammonium nitrate and ammonium chloride, among others. Approximately 98% of NH₃ emissions occurring in Ireland arise from agriculture, with minor contributions from transport and natural sources. A better understanding of NH₃ emissions and SIA formation can be achieved through monitoring emissions at the source level. Additionally, mitigation strategies with a more thorough understanding of NH₃ dynamics at the source level and consequential SIA formation allow for more efficient action. This project monitored ambient NH₃ and SIA on two selected arable agricultural sites and a control site in a rural site close to Dublin on the east coast of Ireland to establish emission levels. Meteorological factors affecting emissions and SIA formation were also measured and cross-correlated to determine micro-meteorological effects. Monitoring at the agricultural sites observed ambient NH₃ concentrations ranging from 0.52 µg m⁻³ to 1.70 µg m⁻³, with an average of 1.45 µg m⁻³. At the control site, ambient NH₃ measured concentrations ranged from 0.05 µg m⁻³ to 1.76 µg m⁻³ with an average of 0.516 µg m⁻³. Aerosol NH₄⁺ ranged from 0.03 µg m⁻³ to 1.05 µg m⁻³ with an average concentration of 0.27 µg m⁻³ at the agricultural site. The potential effects of meteorological conditions and the implications for the effects of these emissions are discussed, with recommendations to aid compliance with the National Emissions Ceiling and the National Clean Air Strategy (Directive 2001/81/EC). Full article

Air pollution is a leading cause of death in the United States and is associated with adverse health outcomes, including increased vulnerability to coronavirus disease 2019 (COVID-19). The AirBeam2 was used to measure particulate matter with a diameter of 2.5 μm or smaller (PM_2.5) to investigate differences between indoor and ambient levels at seven private homes in New York during and after the COVID-19 lockdown. Measurements taken in 2020 fall, 2021 winter, and 2022 fall showed that at 90% of the sites, indoor PM_2.5 levels exceeded outdoor levels both during and after the COVID-19 lockdown, p = 0.03, possibly exceeding safety levels. Higher indoor PM_2.5 levels attributed to little or no ventilation in the basement and kitchens from cooking and smoke were greater in fall than in winter. Higher ambient PM_2.5 levels were attributed to vehicular traffic at a street-facing sampling site. PM_2.5 sources identified in this study may help in devising control strategies to improve indoor air quality (IAQ) and consequently alleviate respiratory health effects. These findings may be used as a basis for in-house modifications, including natural ventilation and the use of air purifiers to reduce exposures, mitigate future risks, and prevent potential harm to vulnerable residents. Full article

The vehicle in-cabin is subject to several types of pollutants infiltrating from the outdoors or emitted directly inside it, such as Volatile Organic Compounds (VOCs). The concentration of TVOC (total volatile organic compounds) is the result of the emission from different equipment surfaces that compose the car cabin. In the present study, the experimental characterization of TVOC emission from the interior surfaces of a car cabin is discussed by considering the influence of two parameters: the temperature and ventilation modes. A measurement location grid was used to measure TVOC’s emissions from 267 points on all surfaces of the car’s interior equipment. Three different temperatures and two ventilation modes (recirculation and outdoor air) were investigated. The results indicate that the concentration of TVOC increases with the temperature inside the cabin with a contribution that varies with the type of cabin equipment including the dashboard, center console, seats, and carpets. On the other hand, the concentration distributions of TVOC showed relative differences of 10–13% and 2–5% for surface and volumetric measurements, respectively. This implies no preferential positioning of the in-cabin probe for TVOC volumetric concentration measurements. In addition, the recirculation ventilation mode results in a higher accumulation of TVOC; therefore, higher concentrations are measured. Full article