Springer Science and Business Media LLC

In the Beijing-Tianjin-Hebei (BTH) urban agglomeration, the atmospheric particulate matter (PM) pollution has become exacerbated year by year. In an attempt to understand the current condition of aerosol particulate pollution in the BTH region, the temporal and spatial distribution, future trend changes, and potential source areas of absorbing aerosols in the BTH region from 2005 to 2019 were analyzed based on Ozone Monitoring Instrument/Aura Near UV Aerosol Optical Depth and Single Scattering Albedo 1-orbit L2 Swath 13 × 24 km V003 (OMAERUV) daily product data; besides, relevant influencing factors were explored in this study. As per the analysis of results, the ultraviolet aerosol index (UVAI) increased by 3.03% in the time series from 2005 to 2019. Spatially, the absorbing aerosol in the North China Plain was always maintained in a high-value area, and the15-year average annual UVAI value has been as high as 0.45. In the monthly time series, a “V” shape started from January. The peak value of seasonal characteristics reached the highest in winter, followed by autumn and spring, and the lowest in summer. The external potential sources in the BTH region are mainly sand and dust sources generated in the northwest, while those of absorbing aerosols are mainly carbon sources in spring, with the lowest external absorbing aerosols in summer. The potential sources of absorbing aerosols in autumn are relatively complicated. The potential sources of absorbing aerosols are mainly sand and dust sources in the north. The time series of absorbing aerosols mainly showed an anti-continuous rise, and 54.23% of absorbing aerosols indicated an upward trend that would occur in the future. The relationship between absorbing aerosols and PM2.5 is mutual conversion. According to the path coefficient, industrial production activities are important sources of atmospheric absorbing aerosols, and precipitation can reduce the content of absorbing aerosols in the atmosphere caused by industrial production.

The emergence of coronavirus disease 2019 (COVID-19) has become a worldwide pandemic after its first outbreak in Wuhan, China. However, it remains unclear whether COVID-19 death is linked to ambient air pollutants or meteorological conditions. We collected the daily COVID-19 death number, air quality index (AQI), ambient air pollutant concentrations, and meteorological variables data of Wuhan between Jan 25 and April 7, 2020. The Pearson and Poisson regression models were used accordingly to understand the association between COVID-19 deaths and each risk factor. The daily COVID-19 deaths were positively correlated with AQI (slope = 0.4 ± 0.09, R2 = 0.24, p < 0.01). Detailedly, PM2.5 was the only pollutant exhibiting a positive association (relative risk (RR) = 1.079, 95%CI 1.071–1.086, p < 0.01) with COVID-19 deaths. The PM10, SO2, and CO were all also significantly associated with COVID-19 deaths, but in negative pattern (p < 0.01). Among them, PM10 and CO had the highest and lowest RR, which equaled to 0.952 (95%CI 0.945–0.959) and 0.177 (95%CI 0.131–0.24), respectively. Additionally, temperature was inversely associated with COVID-19 deaths (RR = 0.861, 95%CI 0.851–0.872, p < 0.01). Contrarily, diurnal temperature range was positively associated with COVID-19 deaths (RR = 1.014, 95%CI 1.003–1.025, p < 0.05). The data suggested that PM2.5 and diurnal temperature range are tightly associated with increased COVID-19 deaths.

Clean air is a fundamental requirement for the existence of life on earth. However, with the rapid rate of economic development, globalization, and increasing energy demand, large amount of emissions and waste are generated, leading to severe air pollution. This paper surveys the literature to provide an overview of the impact of air pollution on various aspects of human life. The impact is categorized broadly into health and socio-economic aspects and further subcategorized into multiple dimensions of health and socio-economic consequences. The survey reveals that the impact of air pollution is comprehensive, ranging from chronic to life-threatening diseases, and from malfunctioning of specific organ systems to subjective well-being. Additionally, evidence of the impact of air pollution on unexpected dimensions such as housing prices, larger economy, academic outcomes, and more is uncovered, leaving no doubt on the need to address this problem with the attention of the highest order. This evidence can be used to trigger more research and give policy-makers a starting point for clean-air campaigns. Merely highlighting the seriousness of the issue is not enough, and hence the paper also surveys the broader literature to identify interventions for clean air developed by public and private stakeholders across the world. While none of them may be ripe for blind duplication, this paper aims to provide decision-makers and researchers a bouquet of solutions to choose from while developing clean air programs and research agenda.

On 4th August 2020, drastic explosions occurred at the port of Beirut, Lebanon. These explosions released an extensive amount of toxic gases and caused atmospheric damages along with terrestrial and marine disturbances. In the current study, the impact of the incident on both local and regional air quality was assessed by ALOHA and HYSPLIT models. The ALOHA results estimated the concentrations of NO2 and NO and their exposure times for two specific densely populated locations in the high-risk zone. The concentrations of outdoor NO2 exceeded the AEGL-3 tier in Borj Hammoud, and Jdeideh after 8, and 10 min of the explosion, respectively. The HYSPLIT results showed the movement of NOx cloud eastwards, reaching Syria, and turned southwards, affecting Iraq, Jordon, Saudi Arabia, Kuwait, Iran, and then moved to central Asia through Turkmenistan. The air quality station at Khorramabad, Iran, could observe a small peak during the NOx toxic cloud arrival time on 6th August 2020 at 13:00 UTC. Besides the Mediterranean Sea, the Caspian Sea, the Persian Gulf, and the Gulf of Oman were also affected by the toxic clouds. Damascus is in the high impacted zone with around 105 kg NO2 deposition. Fragile marine environments are also disturbed. The Persian Gulf, with more than 80% of its area, under low impacted zone was receiving 10 µgm−2. Results drag the attention to the associated risk of old factories to the environment. Therefore, it is necessary to have regular safety monitoring in industrial zones and neighboring to eliminate future incidents.

Multi-city population-based epidemiological studies have consistently reported a significant association between ambient fine particulate matter (PM2.5) concentrations and daily mortality. However, in these studies heterogeneity between-community effect estimates is often observed but not thoroughly examined, leaving much of the difference in the effects of individual communities inadequately explained. In this study, we evaluated whether community-specific exposure factors play a role in explaining heterogeneity in the associations between ambient PM2.5 concentrations and several causes of mortality in 27 US communities from 1997 to 2002 as reported by Franklin et al. (J Expo Sci Environ Epidemiol 3:279–287, 2007). Using publically available databases, we created factors capturing home ventilation characteristics and commuting patterns. These factors include the normalized leakage, annual and seasonal temperatures, and in-vehicle commuting distances and time. In-vehicle commuting distance and time, and annual, spring, and fall temperatures were significant negative effect modifiers of the relationship between PM2.5 exposure and respiratory and non-accidental mortality. Additionally, cardiovascular mortality PM2.5 effect estimates were negatively modified by in-vehicle commuting distances. We concluded that future multi-community studies of particle health effects should consider these and other determinants of personal–ambient exposure relationships during the epidemiological analysis.

Mineral dust, originating in arid regions, exerts substantial influence on air quality, health, and climate, ranking it among the most impactful aerosols. Its capacity to travel over great distances can significantly impact local air quality. In our study conducted for the year 2021, we made use of unprecedented, simultaneous in situ measurements to assess the total number, mass concentrations, and size distribution of near-surface aerosols at a semi-arid station. Furthermore, we conducted an in-depth examination of dust episodes, drawing upon evidence from in situ measurements of surface aerosol properties and meteorological records. The highest total number concentrations (230.1 ± 60.61 cm−3) were recorded during the winter season, attributed to a combination of factors including low temperatures, high relative humidity, stable wind conditions, and limited dispersion. Our findings reveal a noteworthy correlation: for every 1% increase in the equivalent black carbon mass fraction, the diurnal temperature range rises by 1.73 °C, with a noticeable impact of the weekend effect. During the dust episodes occurring on April 7–10 and June 16–30, we observed a significant increase (> twofold) in various surface parameters, such as number size distribution (NSD), total and coarse mode mass concentrations, effective radius, and scattering coefficient. Particularly striking was the enhancement in NSD during these dust episodes, consistently exceeding twofold for aerosols larger than 1.0 µm and reaching as high as tenfold for aerosols larger than 5.0 µm. In addition to our surface observations, satellite vertical profiles showed a prominent dust elevated layer situated between 2 and 4 km altitude during the dust episodes. These observations were well-aligned with in situ surface data and dust columnar mass flux obtained from re-analysis data. Re-analysis and model data further support our findings, indicating a long-range transport of aerosols from the Middle East and South Asia during the dust episodes.

Nowadays, increasing particulate matter (PM) remains a challenge for environmental and humanity health and increases death statistics. Case studies and experimental observations demonstrated that vegetation coverage and type of plants affect PM and air quality. Condensation of PM2.5 has an impressive effect on deteriorating air quality. Increasing vegetation coverage has a significant impact on reducing PM2.5. However, the requirement percent vegetation cover (PVC) is likewise a shadow for careful analysis to recommend the requirement percent and area of vegetation for different parts of the metropolitan. In this paper, we propose a four-phase intelligent algorithm for investigating PM2.5 and critical situations to detect unhealthy air quality monitoring stations (AQMSs). Our algorithm makes a decision based on fuzzy and neural network methods and recommends the percent density and area of vegetation. Our analysis of the weather condition is event-driven, considering rainfall as an event to examine the situation of each AQMS before and after rainfall. The experiments demonstrate reducing PM2.5 > 150 to PM2.5 < 50 using recommending PVC of approximately 20–74%. We achieved these results by periodically estimating and evaluating weather conditions in the autumn and winter as two critical seasons of the year.

Residential wood combustion is an important contributor to heating-season ambient fine particle concentrations in many regions of North America. We applied a measurement and modeling approach to evaluate the effect of wood combustion on local and regional air quality in a non-urban setting with complex topography—the Adirondacks region of New York State. Spatially resolved topographic, census, property assessment, and emissions survey data were used to model spatial variability of woodsmoke fine particulate matter (PM2.5) emissions across the region. This spatial emissions model was then used to locate fixed-site monitors and to design a mobile-monitoring campaign. Measurements using a dual-wavelength AethalometerTM enabled the discrimination of woodsmoke from other combustion sources. By comparing these Aethalometer measurements with nephelometer measurements of PM2.5 we determined that the majority of the PM2.5 measured in the Adirondacks during calm, cold winter nights came from wood combustion. We used the measurements of spatial variability in woodsmoke PM2.5 concentrations, the spatial emissions estimates, and additional geographic covariates to develop a spatial model of woodsmoke PM2.5. Considering those living in areas in the upper tertile of modeled woodsmoke concentrations as “exposed,” the model estimated that about 20% (~130,000 people) of the population in the study area were exposed to elevated woodsmoke. Further, the model demonstrates that U.S. census information can be combined with additional survey and property assessment data to provide a broadly applicable estimate of woodsmoke spatial patterns and population exposure. This approach is a promising method for screening potential woodsmoke problems, including those areas with complex terrains.