Air Quality Atmosphere and Health最新文献

It is useful to analyze the factors, polluting the livable environment, whose sustainability and protection are vital to all living things, and to take the necessary precautions promptly. Within this scope, the effects of foreign trade and investments on environmental pollution in BRICMT (Brazil, Russia, India, China, Mexico, and Turkey) countries were analyzed with the Fourier Kwiatkowski–Phillips–Schmidt–Shin (KPSS) stationarity test, Fourier Bootstrap augumented autoregressive distributive lag (AARDL) method, and Fourier Bootstrap Toda-Yamamoto causality test for the period 1980–2021 in this study. According to the findings, the pollution haven hypothesis is valid since increasing exports and foreign investment in China increased environmental pollution both in the short term and the long term. While environmental pollution increased in China, Brazil, Mexico, and Turkey with increasing imports, it decreased in Russia. The short-term impact of imports on rising environmental pollution is also valid for Brazil. Since foreign investment increases environmental pollution in Brazil and Mexico in the long run, the pollution haven hypothesis is valid in these countries. In Russia and Mexico, where there are findings that foreign investment reduces environmental pollution in the short term, the pollution halo hypothesis is valid in the short run. According to the Fourier Bootstrap Toda-Yamamoto causality test results, it was determined that there is causality from exports and imports to environmental pollution in China and India and from foreign investment to environmental pollution in Russia and Brazil.

The chemical composition studies of indoor particulate matter (PM_2.5 and PM_0.1) are lacking in the developing world, yet the attention to indoor air pollution and occupant health risks is rising. This study therefore aims to investigate the chemical compositions of indoor and outdoor PM_2.5 and PM_0.1 in residential and school buildings in Vietnam during different seasons and the effects of emission sources on particle characteristics. The results show that the concentration of indoor PM_2.5 in the residential house was higher than that outdoors, and the indoor-to-outdoor ratios (I/O) exceeded 1, indicating the contribution of indoor sources. The peak concentration of indoor particles was observed during the incense burning days, whereas a higher indoor organic carbon concentration may be due to cooking activities. A similar variation of indoor and outdoor PM_2.5 indicates the penetration of outdoor particles. In the school building, seasonal variations in indoor PM_0.1 and its chemical species were observed, suggesting outdoor sources had a significant effect. Several factors may affect I/O and the infiltration factor of PM_0.1, such as indoor sources, air exchange rate, cracks in the door and window, and particle deposition rate. The reason for the I/O value slightly above 1 for PM_0.1 in this study remained unclear. Further investigations are recommended to obtain knowledge regarding the penetration of particles, particularly PM_0.1. The findings provide a better understanding of the chemical components of indoor particles and the effects of emission sources, which is crucial to developing management measures for indoor air quality and mitigating exposures.

Modeling dispersion of aircraft emissions is challenging because aircraft are mobile sources with varying emissions rates at different elevations depending on the operating mode. Aircraft emissions during landing and take-off cycle (LTO) influence air quality in and around the airport, and depending on the number of aircraft operations and location of the airport, this influence may be significant. AERMOD (v22112) incorporates a variety of conventional source types to characterize the intended emissions source, leaving the question of which conventional source type(s) best characterizes aircraft activities across the four modes of LTO cycle, unanswered. Currently, the publicly released version of FAA’s Aviation Environmental Design Tool (version 3e) models aircraft emissions as a set of AREA sources for all flight segments. A research version of AEDT allows users to model aircraft sources—both fixed wing and rotorcraft—as a series of VOLUME sources in AERMOD. However, both source treatments do not account for plume rise of aircraft jet exhaust. This paper compares AERMOD’s performance in describing SO₂ concentrations associated with airport sources by comparing model results from the two source options during the summer campaign of the Air Quality Source Apportionment study conducted at the Los Angeles International Airport. We conclude that both VOLUME source and AREA treatments overestimate the highest observed SO₂ concentrations despite not accounting for background sources. The VOLUME source option reduces this overestimation by using a higher initial plume spread than the AREA option does, and through the inclusion of meander. Our results suggest the need to include the plume rise of jet exhaust when using AERMOD for airport air quality studies.

Coal-fired power plants (CFPPs) account for > 70% of electricity generation in India, but < 5% of facilities have installed technologies for sulfur dioxide (SO₂) and nitrogen oxide (NO_X) removal. Emissions of these pollutants lead to the formation of fine particulate matter (PM_2.5) and an increased risk of premature mortality for exposed populations. Here, we use a nested version of the GEOS-Chem global chemical transport model (0.5° × 0.625° resolution) for India to estimate reductions in PM_2.5 concentrations that could have been achieved by implementing existing emission control technologies like flue-gas desulfurization (FGD) and/or selective catalytic reduction (SCR). We quantify the associated burden of disease using the integrated exposure response (IER) and global exposure mortality model (GEMM) functions and compare the costs of premature mortality to those for FGD installation. Model simulations for 2010 suggest installation of FGD would have reduced mean annual PM_2.5 concentrations across India by 8%, compared to 3% with SCR installation, and 11% with both FGD and SCR. A 7–28% reduction in PM_2.5 was simulated for local communities closest to CFPPs (same model grid cell), leading to up to 17% reduction in annual premature mortality. Overall, more than 0.21–0.48 million premature deaths would have been avoided over a 10-year period if FGD had been implemented on all CFPPs, compared to 0.09–0.21 million with SCR and 0.22–0.72 million with both FGD and SCR. Benefits associated with such actions are approximately $18.1–$604 billion USD per year, which is equivalent to ~ 0.44 to 10% of India’s GDP. These results suggest that monetary benefits from avoided premature mortality far outweigh the capital and operational costs of FGD and/or SCR installation of $19.5 billion and/or $32.8 billion per year, respectively. This information is essential because the high costs of installation and operation are often given as reasons for delaying installation and commissioning. We conclude that policy actions to control air pollution from CFPPs are economically justifiable.

We investigate the performance of two widely used chemistry-transport models (CTMs) with different chemical mechanisms in reproducing the ambient maximum daily 8-h average ozone (MDA8 O(_{3})) burden over Central Europe. We explore a base case setup with boundary conditions (BC) for meteorology from the ERA-Interim reanalysis and chemical BC from CAM-Chem as well as effects of alterations in these BC based on global model fields. Our results show that changes in meteorological BC strongly affect the correlation with observations but only marginally affect the model biases, while changes in chemical BC increase model biases while correlation patterns remain largely unchanged. Furthermore, our study highlights that CTM choice (and choice of chemical mechanism) has a similar or even larger impact on MDA8 O(_{3}) levels as the impact of altered BC. In summary, our study calls for a multi-model strategy combining different CTM and BC combinations to explore the bandwidth of MDA8 O(_{3}) distributions and thus uncertainty in hindcasts and future projections, in analogy to climate studies considering ensemble simulations under the same anthropogenic emissions but with slightly different initial conditions.

Volatile organic compounds (VOCs) are a class of ubiquitous substances that are present in outdoor and indoor air. They are emitted by a wide range of sources and can penetrate and accumulate specifically in indoor environments. Concern is growing among the scientific community regarding the potential health impacts of exposure to a high concentration of VOCs in indoor spaces. Due to their still-developing respiratory and immune systems, children may be the most fragile subjects in this regard, and therefore, the study of indoor air quality in schools is of the utmost importance. In this work, the concentrations of total volatile organic compounds (TVOCs) and of 20 specific compounds belonging to this class were determined in a school in Squinzano, a town in the province of Lecce (Apulia region, southern Italy). Sampling was carried out in indoor (classrooms and bathrooms) and outdoor (terrace) areas using passive diffusive samplers for VOCs and photoionization detectors for TVOCs. Average concentrations of both TVOC (303 ± 47 µg m⁻³) and individual VOCs (< 0.5 µg m⁻³) were below levels of concern; however, specific indoor sources such as cleaning activities and student occupancy were responsible for peaks in TVOC concentrations above harmless levels for children and school staff. The data were then compared to the ones obtained in a similar study conducted in a school in Galatina, another town of the Apulia region, highlighting the impact of the surrounding outdoor environment on the indoor profile of VOCs.

Dust is a main source of different indoor contaminants, such as polychlorinated biphenyls (PCBs) generally applied in buildings. This study is the first report on the levels of PCBs in the indoor dust of Bushehr port, Iran. PCBs were evaluated in 30 dust samples collected from homes, offices, and stores. A total of 10 PCB congeners were found in dust samples. The mean levels of PCBs in homes, offices, and stores were 3.46, 0.51, and 1.28 ng/g, respectively. PCB52 and 31 in homes with values of 0.78 and 0.31 ng/g had the highest levels of PCB congeners. Also, no significant difference was detected among the PCB contents of buildings with different applications in Bushehr. Furthermore, PCBs in indoor dust showed acceptable cancer risk (CR) for different age groups. Most CR was observed for infants and toddlers at homes and stores thorough dust ingestion as the main exposure route to PCBs in dust. Based on the results of this research, exposure to PCBs in indoor buildings may cause a high risk for people of different ages.

The introduction of Tier 3 light-duty vehicles with reduced emissions began in New York State (NYS) in 2017, with required compliance by 2025. We hypothesized that improved air quality during the early implementation of Tier 3 (2017–2019) would result in reduced rates of hospitalizations and emergency department (ED) visits for respiratory infection associated with increased PM_2.5 compared to 2014–2016 (pre-Tier 3). Using data on adult patients hospitalized or having an ED visit for influenza, upper respiratory infection, culture-negative pneumonia, or respiratory bacterial infection, living within 15 miles of six air quality monitoring sites in NY, and a case-crossover design and conditional logistic regression, we estimated the rates of respiratory infection hospitalizations and ED visits associated with increased ambient PM_2.5 concentrations in the previous 0–6 days and each week thereafter up to 1 month. Interquartile range (IQR) increases in PM_2.5 in the previous 6 days were associated with 4.6% (95% CI: − 0.5, 10.1) and 11.9% (95% CI = 6.1, 18.0) increased rates of influenza hospitalizations in 2014–2016 and 2017–2019, respectively. This pattern of larger relative rates in 2017–2019 observed at all lag times was only present in males hospitalized for influenza but not other infections or in females. The rates of respiratory infection visits associated with increased PM_2.5 were generally not reduced in this early Tier 3 implementation period compared to 2014–2016. Limited fleet penetration of Tier 3 vehicles and differences in particle deposition, infection type, and sex by period may all have contributed to this lack of improvement.

Metagenomics is a novel genomic tool employed to accurately study the composition of microbial communities in their ecological environments, including mass transport systems. Despite the potential significance of these sites as sources of exposure, the pathogenic microbiomes in these constructed settings remain unexplored. In this study, high-throughput sequencing was utilized to identify the microbiota obtained from the Metropolitan Transport of Shanghai (MTS) during the spring and summer. A diverse range of microbiota, especially pathogens, and models for mapping diversity and environmental variables were analyzed using the metagenomic techniques. The results indicate that bacteria accounted for 95.26% of the categorized genes in the 108 aerosol samples analyzed during the spring and summer, with the remaining 4.73% attributed to eukaryotes, viruses, and archaea. We successfully identified 86 microorganisms that align with the National Microbiology Data Center's List of Pathogenic Microorganisms, uncovering unique characteristics of various species with potential health implications throughout across seasons. Additionally, the distribution and diversity of the microbiota were significantly influenced by temperature, humidity, season, and time of day. The study's findings establish a framework for investigating and evaluating potential public health risks, offering early warning of biosecurity concerns related to these built environments. They also provide a comprehensive and unbiased perspective on the characteristics of microbial communities and potential pathogens in urban metros. Environmental and public health experts will find this investigation into the pathogenic microbiomes found in aerosol samples compelling.

The surge in urbanization and industrialization is majorly contributing to ambient air pollution, predominantly in terms of particulate emissions. Human health is highly susceptible to the particles suspended in the air due to their lightweight and small size (≤ 2.5 μm), called atmospheric aerosols. In India, insufficient ground-based instruments hinder continuous aerosol monitoring. However, remote sensing offers earth imagery for in-depth analysis of air quality and weather parameters. In the present study, an attempt is made to retrieve the high-resolution (30 m) AOT using Landsat 8 Operational Land Imager (L8-OLI) imagery for Pune, Maharashtra, from the years 2014 to 2021. For the atmospheric corrections and better spatiotemporal resolution, the dark target spectrum-based Image Corrections for Atmospheric Effects (iCOR) algorithm was executed. The year 2021 showed the highest mean AOT value at the Pashan location (18.537° N, 73.805° E) in Pune, India. Also, seasonal analysis (winter and summer) indicates that the mean AOT in the winter gradually increases every year. The AOT retrieved using L8-OLI with iCOR and AOT retrieved from Aerosol Robotic Network (AERONET) in situ monitoring station (± 30 min) at 440 nm showed R² = 0.76, r = 0.83, and RMSE = 0.1012. From this, it is summarized that for L8-OLI images, the iCOR algorithm performs well for the atmospheric correction by retrieving AOT at high spatial resolution with minimum cloud cover.