Long-term exposure to ambient PM2.5 and impacts on health in Rome, Italy

Temporal characteristics and health effects related to NO2, O3, and SO2 in an urban area of Iran

This study reports on temporal variations of NO2, O3, and SO2 pollutants and their related health effects in urban air of Khorramabad, Iran using AirQ 2.2.3 software. Based on data between 2015 and 2021, hourly NO2, O3, and SO2 concentrations increase starting at 6:00 a.m. local time until 9:00 p.m., 3:00 p.m., and 7:00 p.m. local time, respectively, before gradually decreasing. The highest monthly NO2, O3, and SO2 concentrations are observed in October, August, and September, respectively. Annual median NO2, O3, and SO2 concentrations range between 17 ppb and 38.8 ppb, 17.5 ppb-36.6 ppb, and ∼14 ppb-30.8 ppb, respectively. Two to 93 days and 17-156 days between 2015 and 2021 exhibit daily concentrations of NO2 and SO2 ≤ WHO AQGs, respectively, while 187-294 days have 8-h maximum O3 concentrations ≤ WHO AQGs. The mean excess mortality ascribed to respiratory mortality, cardiovascular mortality, hospital admissions for COPD, and acute myocardial infraction are 121, 603, 39, and 145 during 2015-2021, respectively. O3 is found to exert more significant health effects compared to SO2 and NO2, resulting in higher cardiovascular mortality. The gradual increase in NO2 and possibly O3 over the study period is suspected to be due to economic sanctions, while SO2 decreased due to regulatory activity. Sustainable control strategies such as improving fuel quality, promoting public transportation and vehicle retirement, applying subsidies for purchase of electric vehicles, and application of European emission standards on automobiles can help decrease target pollutant levels in ambient air of cities in developing countries.

Evaluating the mortality and health rate caused by the PM2.5 pollutant in the air of several important Iranian cities and evaluating the effect of variables with a linear time series model

All over the world, the level of special air pollutants that have the potential to cause diseases is increasing. Although the relationship between exposure to air pollutants and mortality has been proven, the health risk assessment and prediction of these pollutants have a therapeutic role in protecting public health, and need more research. The purpose of this research is to evaluate the ill-health caused by PM2.5 pollution using AirQ + software and to evaluate the different effects on PM2.5 with time series linear modeling by R software version 4.1.3 in the cities of Arak, Esfahan, Ahvaz, Tabriz, Shiraz, Karaj and Mashhad during 2019-2020. The pollutant hours, meteorology, population and mortality information were calculated by the Environmental Protection Organization, Meteorological Organization, Statistics Organization and Statistics and Information Technology Center of the Ministry of Health, Treatment and Medical Education for 24 h of PM2.5 pollution with Excel software. In addition, having 24 h of PM2.5 pollutants and meteorology is used to the effect of variables on PM2.5 concentration. The results showed that the highest and lowest number of deaths due to natural deaths, ischemic heart disease (IHD), lung cancer (LC), chronic obstructive pulmonary disease (COPD), acute lower respiratory infection (ALRI) and stroke in The effect of disease with PM2.5 pollutant in Ahvaz and Arak cities was 7.39-12.32%, 14.6-17.29%, 16.48-8.39%, 10.43-18.91%, 12.21-22.79% and 14.6-18.54 % respectively. Another result of this research was the high mortality of the disease compared to the mortality of the nose. The analysis of the results showed that by reducing the pollutants in the cities of Karaj and Shiraz, there is a significant reduction in mortality and linear modeling provides a suitable method for air management planning.

Size-segregated characteristics of water-soluble oxidative potential in urban Xiamen: Potential driving factors and implications for human health

Oxidative potential (OP), defined as the ability of particulate matter (PM) to generate reactive oxygen species (ROS), has been considered as a potential health-related metric for PM. Particles with different sizes have different OP and deposition efficiencies in the respiratory tract and pose different health risks. In this study, size-segregated PM samples were collected at a coastal urban site in Xiamen, a port city in southeastern China, between August 2020 and September 2021. The water-soluble constituents, including inorganic ions, elements and organic carbon, were determined. Total volume-normalized OP based on the dithiothreitol assay was highest in spring (0.241 ± 0.033 nmol min-1 m-3) and lowest in summer (0.073 ± 0.006 nmol min-1 m-3). OP had a biomodal distribution with peaks at 0.25-0.44 μm and 1.0-1.4 μm in spring, summer, and winter and a unimodal pattern with peak at 0.25-0.44 μm in fall, which were different from the patterns of redox-active species. Variations in the seasonality of fine and coarse mode OP and their correlations with water-soluble constituents showed that the size distribution patterns of OP could be attributed to the combined effects of the size distributions of transition metals and redox-active organics and the interactions between them which varied with emissions, meteorological conditions and atmospheric processes. Respiratory tract deposition model indicated that the deposited OP and the toxic elements accounted for 47.9 % and 36.8 % of their measured concentrations, respectively. The highest OP doses and the excess lifetime carcinogenic risk (ELCR) were found in the head airway (>70 %). However, the size distributions of OP deposition and ELCR in the respiratory tract were different, with 63.9 % and 49.4 % of deposited ELCR and OP, respectively, coming from PM2.5. Therefore, attention must be paid to coarse particles from non-exhaust emissions and road dust resuspension.

Patterns and drivers of atmospheric inorganic nitrogen deposition in Northeast Asia

Elevated nitrogen (N) deposition due to intensified emissions of NH3 and NOx is a global problem with profound consequences on living organisms and the environment. Although N emission rates are currently considered to be high in East Asia, reports on the current N deposition level and composition are still limited, especially in northeastern China, where official N deposition monitoring sites are unavailable. This limits our understanding of the spatio-temporal N deposition patterns and their influencing factors at regional to continental scales. Here, we used data collected mostly during 2019 at 38 sites, comprising 7 sites in northeastern China and 31 EANET (Acid Deposition Monitoring Network in East Asia) sites in middle and east Russia, Mongolia, central and southern China, South Korea and Japan to explore the spatial-seasonal variations and drivers of ammonium and nitrate deposition across the Northeast Asia. Total bulk inorganic N (TIN) deposition was 3.7-24.5 kg N ha-1 yr-1 and NH4+-N/NO3--N ratio in the TIN was 0.8-2.8 in northeastern China. The bulk/wet TIN deposition averaged 7.5 kg N ha-1 yr-1 (predominantly in the form of ammonium-N: NH4+-N/NO3--N = 1.4) over the Northeast Asia region, with the highest rates being observed in northeastern China (11.6), as well as central and southern China (10.7), followed by east Russia, South Korea and Japan (5.6), and the lowest in middle Russia and Mongolia (1.5). This regional bulk/wet TIN deposition level is about twice of the wet TIN deposition level in Europe and the United States. The TIN deposition in summer and spring was 45-467% higher than in autumn and winter. Out of the ten land uses considered, only agricultural and urban land uses significantly positively correlated with NH4+-N and NO3--N deposition rates across all monitored sites. This study suggests that the ongoing agricultural and urban expansions are likely to enhance N deposition and its associated effects across global ecosystems.

Assessing the effect of COVID-19 pandemic on air quality change and human health outcomes in a capital city, southwestern Iran

The aimsof this study were to assess the spatial variation of PM2.5, NO2, and O3 between 2019 (before) and 2020 (during COVID-19 pandemic); and calculation the health outcomes of exposure to these pollutants. The daily PM2.5, NO2, and O3 concentrations were applied to assess health effects by relative risk, and baseline incidence. The annual PM2.5 and NO2 mean concentrations exceeded the WHO guideline values, while O3 did not exceed. The restrictive measures associated to COVID-19 led to reduction at the annual means of PM2.5 and NO2 by -25.5% and -23.1%, respectively, while the annual mean of O3 increased by +7.9%. The number of M-CVD and M-RD (-25.6%, -26.1%) related to PM2.5 exposure, and HA-COPD and HA-RD >65 years old (-21% and -3.84%) related to NO2 exposure were reduced in 2020, and O3 exposure-related M-CVD (+30.1%) and HA-RD >65 years old (+23.4%) increased compared to the previous year 2019.

Machine learning model to predict vehicle electrification impacts on urban air quality and related human health effects

Air pollution is a prevailing environmental problem in cities worldwide. The future vehicle electrification (VE), which in Europe will be importantly fostered by the ban of thermal engines from 2035, is expected to have an important effect on urban air quality. Machine learning models represent an optimal tool for predicting changes in air pollutants concentrations in the context of future VE. For the city of Valencia (Spain), a XGBoost (eXtreme Gradient Boosting package) model was used in combination with SHAP (SHapley Additive exPlanations) analysis, both to investigate the importance of different factors explaining air pollution concentrations and predicting the effect of different levels of VE. The model was trained with 5 years of data including the COVID-19 lockdown period in 2020, in which mobility was strongly reduced resulting in unprecedent changes in air pollution concentrations. The interannual meteorological variability of 10 years was also considered in the analyses. For a 70% VE, the model predicted: 1) improvements in nitrogen dioxide pollution (-34% to -55% change in annual mean concentrations, for the different air quality stations), 2) a very limited effect on particulate matter concentrations (-1 to -4% change in annual means of PM_2.5 and PM₁₀), 3) heterogeneous responses in ground-level ozone concentrations (-2% to +12% change in the annual means of the daily maximum 8-h average concentrations). Even at a high VE increase of 70%, the 2021 World Health Organization Air Quality Guidelines will be exceeded for all pollutants in some stations. VE has a potentially important impact in terms of reducing NO₂-associated premature mortality, but complementary strategies for reducing traffic and controlling all different air pollution sources should also be implemented to protect human health.

Air pollution burden of disease over highly populated states in the Middle East

Background

Recent epidemiological research has proven that air pollution triggers the risk of morbidity and mortality due to respiratory and cardiovascular-related diseases. More specifically, fine particulate matter with a diameter of <2.5 μm (PM2.5) can penetrate deeply into the lung and bloodstream, causing critical adverse effects on human health.

Objective

It is found that there is inadequate published research related to the health impact of ambient air pollution in the Middle East region. Some states are well studied, while others are not. This work aims to evaluate the health impact of long-term exposure to PM2.5 in the nine most populated countries in the Middle East region, with a total population of about 363 million (in 2012).

Methods

In this study, the human health impacts in terms of total mortality and the estimated attributable proportion (AP) due to long-term exposure to ambient PM2.5 were estimated using the World Health Organization method and software (AirQ+).

Results

In 2012, the annual median PM2.5 concentrations ranged from 34 μg/m3 in Turkey and Syria to 108 μg/m3 in Saudi Arabia. The total estimated mortalities in the nine most populated countries in the Middle East due to long-term exposure to fine particulate matter was about 152,925 (half of which were residents in Egypt). Moreover, the relative risk (RR) was the highest for Saudi Arabia at 1.8031 and the lowest for Turkey and Syria at a value of 1.1553. The highest AP (central value) was 44.5% in Saudi Arabia, while the lowest was 13.4% in Turkey and Syria.

Conclusions

The results indicate a significant impact of air pollution due to long-term exposure to fine particles resulting in early mortality. This urges the collaboration between the governments and different sectors to adopt stringent regulations to control the anthropogenic sources related to traffic and industrial emissions in the Middle East in order to reduce the health burden of air pollution.

A, Nagendra SMS. Trends, Extreme Events and Long-term Health Impacts of Particulate Matter in a Southern Indian Industrial Area

The present study uses various statistical tools to understand the behaviour of PM_2.5 and PM₁₀ in the Kanjikode industrial area of Southern India. Annual PM_2.5 and PM₁₀ average concentrations in 2018-2020 were three times more than the World Health Organization-specified standards (5 and 15 µg m^-3). The statistical distribution analysis suggested well-fitted lognormal and gamma distributions of 24-h average PM_2.5 concentrations and gamma distributions of 24-h average PM₁₀ concentrations. Trend analysis observed a notable monotonic increasing trend for 24-h average PM_2.5 concentrations with an increasing magnitude of 0.43 µg m^-3 per annum. A downward trend was found for 24-h average PM₁₀ concentrations, with a decreasing magnitude of 0.2 µg m^-3 per year. Extreme event analysis of PM_2.5 and PM₁₀ has provided the highest concentration levels expected in the coming 10 years, 193 and 165 µg m^-3, respectively, higher than the Indian National Ambient Air Quality Standards and considered a public health threat. The health risk assessment by AirQ + emphasized that more than 15, 34, and 27 premature deaths caused by total mortality in 2018, 2019, and 2020 could have been prevented if PM_2.5 concentrations in the Kanjikode industrial area did not exceed 10 μg m^-3. Statistical analysis and health risk assessment suggested adopting various constructive and multipronged approaches to reduce pollution levels and develop a health risk management plan in the industrial region.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11270-023-06302-y.

Ambient PM2.5 and O3 pollution and health impacts in Iranian megacity

The main objectives of this study were to (i) assess variation within fine particles (PM_2.5) and tropospheric ozone (O₃) time series in Khorramabad (Iran) between 2019 (before) and 2020 (during COVID-19 pandemic); (ii) assess relationship between PM_2.5 and O₃, the PM_2.5/O₃ ratio, and energy consumption; and (iii) estimate the health effects of exposure to ambient PM_2.5 and O₃. From hourly PM_2.5 and O₃ concentrations, we applied both linear-log and integrated exposure-response functions, city-specific relative risk, and baseline incidence values to estimate the health effects over time. A significant correlation was found between PM_2.5 and O₃ (r =-0.46 in 2019, r =-0.55 in 2020, p < 0.05). The number of premature deaths for all non-accidental causes (27.5 and 24.6), ischemic heart disease (7.3 and 6.3), chronic obstructive pulmonary disease (17 and 19.2), and lung cancer (9.2 and 6.25) attributed to ambient PM_2.5 exposure and for respiratory diseases (4.7 and 5.4) for exposure to O₃ above 10 µg m^-3 for people older than 30-year-old were obtained in 2019 and 2020. The number of years of life lost declined by 11.6% in 2020 and exposure to PM_2.5 reduced the life expectancy by 0.58 and 0.45 years, respectively in 2019 and 2020. Compared to 2019, the restrictive measures associated to COVID-19 pandemic led to reduction in PM_2.5 (-25.5%) and an increase of O₃ concentration (+ 8.0%) in Khorramabad.

Increased tropospheric ozone levels as a public health issue during COVID-19 lockdown and estimation the related pulmonary diseases

The aims of this study were to i) investigate the variation of tropospheric ozone (O₃) levels during the COVID-19 lockdown; ii) determine the relationships between O₃ concentrations with the number of COVID-19 cases; and iii) estimate the O₃-related health effects in Southwestern Iran (Khorramabad) over the time period 2019-2021. The hourly O₃ data were collected from ground monitoring stations, as well as retrieved from Sentinel-5 satellite data for showing the changes in O₃ levels pre, during, and after lockdown period. The concentration-response function model was applied using relative risk (RR) values and baseline incidence (BI) to assess the O₃-related health effects. Compared to 2019, the annual O₃ mean concentrations increased by 12.2% in 2020 and declined by 3.9% in 2021. The spatiotemporal changes showed a significant O₃ increase during COVID-19 lockdown, and a negative correlation between O₃ levels and the number of COVID-19 cases was found (r = - 0.59, p < 0.05). In 2020, the number of hospital admissions for cardiovascular diseases increased by 4.0 per 10⁵ cases, the mortality for respiratory diseases increased by 0.7 per 10⁵ cases, and the long-term mortality for respiratory diseases increased by 0.9 per 10⁵ cases. Policy decisions are now required to reduce the surface O₃ concentrations and O₃-related health effects in Iran.

COVID-19 Outbreak Related to PM10, PM2.5, Air Temperature and Relative Humidity in Ahvaz, Iran

In this study, we assessed several points related to the incidence of COVID-19 between March 2020 and March 2021 in the Petroleum Hospital of Ahvaz (Iran) by analyzing COVID-19 data from patients referred to the hospital. We found that 57.5% of infected referrals were male, 61.7% of deaths by COVID-19 occurred in subjects over 65 years of age, and only 2.4% of deaths occurred in younger subjects (< 30 years old). Analysis showed that mean PM₁₀ and PM_2.5 concentrations were correlated to the incidence of COVID-19 (r = 0.547, P < 0.05, and r = 0.609, P < 0.05, respectively) and positive chest CT scans (r = 0.597, P < 0.05, and r = 0.541, P < 0.05 respectively). We observed that a high daily air temperature (30–51 °C) and a high relative humidity (60–97%) led to a significant reduction in the daily incidence of COVID-19. The highest number of positive chest CT scans were obtained in June 2020 and March 2021 for daily air temperature ranging from 38 °C and 49 °C and 11 °C and 15 °C, respectively. A negative correlation was detected between COVID-19 cases and air temperature (r =  − 0.320, P < 0.05) and relative humidity (r =  − 0.384, P < 0.05). In Ahvaz, a daily air temperature of 10–28 °C and relative humidity of 19–40% are suitable for the spread of coronavirus. The highest correlation with the number of COVID-19 cases was found at lag3 (r = 0.42) and at lag0 with a positive chest CT scan (r = 0.56). For air temperature and relative humidity, the highest correlations were found at day 0 (lag0). During lockdown (22 March to 21 April 2020), a reduction was observed for PM₁₀ (29.6%), PM_2.5 (36.9%) and the Air Quality Index (33.3%) when compared to the previous month. During the pandemic period (2020–2021), the annual mean concentrations of PM₁₀ (27.3%) and PM_2.5 (17.8%) were reduced compared to the 2015–2019 period.

"pySewage": a hybrid approach to predict the number of SARS-CoV-2-infected people from wastewater in Brazil

It is well known that the new coronavirus pandemic has global environmental, public health, and economic implications. In this sense, this study aims to monitor SARS-CoV-2 in the largest wastewater treatment plant of Goiânia, which processes wastewater from more than 700,000 inhabitants, and to correlate the molecular and clinical data collected. Influent and effluent samples were collected at Dr. Helio de Seixo Britto's wastewater treatment plant from January to August 2021. Viral concentration was performed with polyethylene glycol before viral RNA extraction. Real-time qPCR (N1 and N2 gene assays) was performed to detect and quantify the viral RNA present in the samples. The results showed that 43.63% of the samples were positive. There is no significant difference between the detection of primers N1 (mean 3.23 log10 genome copies/L, std 0.23) and N2 (mean 2.95 log10 genome copies/L, std 0.29); also, there is no significant difference between the detection of influent and effluent samples. Our molecular data revealed a positive correlation with clinical data, and infection prevalence was higher than clinical data. In addition, we developed a user-friendly web application to predict the number of infected people based on the detection of viral load present in wastewater samples and may be applied as a public policy strategy for monitoring ongoing outbreaks.

Health impacts quantification attributed to ambient particulate matter in the nearest Iranian city to the main dust source

Urban air contamination is one of the ten most dangerous parameters for human health, which causes cardiovascular disease, respiratory, metabolic diseases, and decreased lung function. Air Q is a reliable software for studying the impacts of atmospheric contaminants on human health, and today, it is widely used in the environment. The purpose of this research was to quantify the mortality and morbidity rates that corresponded to ambient particulate matter (PM) in Rigan City. To perform this, the Air Q software was used. The findings reflected that the yearly mean values of PM₁₀ and PM_2.5 are 264.83 and 50.45 μg/m³. The findings indicated that the PM₁₀ and PM_2.5 content in Rigan was above standard levels described by WHO. The total number of deaths, cardiovascular deaths, and respiratory deaths due to PM in Rigan were estimated as 70.3, 45.8, and 10.7 persons, respectively. Hospital admissions for cardiovascular and respiratory diseases correlated to PM₁₀ were estimated at 154.2 and 59 persons, respectively. Acute myocardial infarction associated with PM_2.5 was 2.7 persons. Overall, the data in this study may be helpful to national and regional policymakers who are responsible for managing and preventing atmospheric contamination and assessing the costs of health risks.

Using Bayesian networks for environmental health risk assessment

The study investigated the potential relationships between air pollution, socio-economy, and proven pathologies (e.g., respiratory, cardiovascular) within an industrial area in Southern France (Etang de Berre), gathering steel industries, oil refineries, shipping, road traffic and experiencing a Mediterranean climate. A total of 178 variables were simultaneously integrated within a Bayesian model at intra-urban scale. Various unsupervised and supervised algorithms (maximum spanning tree, tree-augmented naive classifier) as well as sensitivity analyses were used to better understand the links between all variables, and highlighted correlations between population exposure to air pollutants and some pathologies. Adverse health effects (bronchus and lung cancers for 15-65 years old people) were observed for hydrofluoric acid at low background concentration (<0.003 μg m^-3) while exposure to particulate cadmium (0.210-0.250 μg m^-3) disrupts insulin metabolism for people over 65 years-old leading to diabetes. Bronchus and lung cancers for people over 65 years-old occurred at low background SO₂ concentration (6 μg m^-3) below European limit values. When benzo[k]fluoranthene exceeded 0.672 μg m^-3, we observed a high number of hospital admissions for respiratory diseases for 15-65 years-old people. The study also revealed the important influence of socio-economy (e.g., single-parent family, people with no qualification at 15 years-old) on pathologies (e.g., cardiovascular diseases). Finally, a diffuse polychlorinated biphenyl (PCB) pollution was observed in the study area and can potentially cause lung cancers.

Particulate Matter in an Urban–Industrial Environment: Comparing Data of Dispersion Modeling with Tree Leaves Deposition

Particulate matter represents a serious hazard to human health, and air quality models contribute to the understanding of its dispersion. This study describes particulate matter with a ≤10 μm diameter (PM10) dynamics in an urban–industrial area, through the comparison of three datasets: modeled (TAPM—The Air Pollution Model), measured concentration (environmental control stations—ECS), and leaf deposition values. Results showed a good agreement between ECS and TAPM data. A steel plant area was used as a PM10 emissions reference source, in relation to the four sampling areas, and a distance/wind-based factor was introduced (Steel Factor, SF). Through SF, the three datasets were compared. The SF was able to describe the PM10 dispersion values for ECS and leaf deposition (r2 = 0.61–0.94 for ECS; r2 = 0.45–0.70 for leaf); no relationship was found for TAPM results. Differences between measured and modeled data can be due to discrepancies in one district and explained by a lack of PM10 inventory for the steel plant emissions. The study suggests the use of TAPM as a suitable tool for PM10 modeling at the urban scale. Moreover, tree leaves are a low-cost tool to evaluate the urban environmental quality, by providing information on whether and when data from leaf deposition can be used as a proxy for air pollution concentration. Further studies to include the re-suspension of particles as a PM10 source within emission inventories are suggested.

A 10-year assessment of ambient fine particles and related health endpoints in a large Mediterranean city

Fine particles i.e., with an aerodynamic diameter lower than 2.5 μm (PM_2.5) have potentially the most significant effects on human health compared to other air pollutants. The main objectives of this study were to i) investigate the temporal variations of ambient PM_2.5 in Marseille (Southern France), where air pollution is again a major public health issue, and ii) estimate their short-term health effects and annual trend (Mann-Kendall test) over a 10-year period from 2010 to 2019. In Marseille, the main sources of PM_2.5 could be related to road traffic, industrial complexes, and oil refineries surrounded the city. The number of premature deaths and hospital admissions attributable to ambient PM_2.5 exposure for non-accidental causes, cardiovascular and respiratory diseases were estimated by using in-situ air quality data, city-specific relative risk values and baseline incidence. Despite significant reduction of PM_2.5 (- 0.80 μg m^-3 year^-1), Marseille citizens were exposed to PM_2.5 levels exceeding the World Health Organization (WHO) Air Quality Guideline for human health protection (10 μg m^-3) during entire study period. Exposure to ambient PM_2.5 substantially contributed to mortality and hospital admissions: 871 deaths for non-accidental causes, 515 deaths for cardiovascular diseases, 47 deaths for respiratory diseases, as well as 1034 hospital admissions for cardiovascular diseases and 834 for respiratory diseases were reported between 2010 and 2019. Compliance with WHO annual limit values can result in substantial socio-economic benefits by preventing premature deaths and hospital admissions. For instance, based on the value of a statistical life and average cost of a hospital admission, the associated benefit for healthcare would have been €131 million in 2019. Between 2010 and 2019, the number of PM_2.5-related non-accidental deaths decreased by 1.15 per 10⁵ inhabitants annually. Compared to 2010-2019, the restrictive measures associated to COVID-19 pandemic led to a reduction in PM_2.5 of 11% in Marseille, with 2.6 PM_2.5-related deaths averted in 2020.

High health expenditures and low exposure of population to air pollution as critical factors that can reduce fatality rate in COVID-19 pandemic crisis: a global analysis

One of the problems hardly clarified in Coronavirus Disease 2019 (COVID-19) pandemic crisis is to identify factors associated with a lower mortality of COVID-19 between countries to design strategies to cope with future pandemics in society. The study here confronts this problem by developing a global analysis based on more than 160 countries. This paper proposes that Gross Domestic Product (GDP) per capita, healthcare spending and air pollution of nations are critical factors associated with fatality rate of COVID-19. The statistical evidence seems in general to support that countries with a low average COVID-19 fatality rate have high expenditures in health sector >7.5% of GDP, high health expenditures per capita >$2,300 and a lower exposure of population to days exceeding safe levels of particulate matter (PM_2.5). Another relevant finding here is that these countries have lower case fatality rates (CFRs) of COVID-19, regardless a higher percentage of population aged more than 65 years. Overall, then, this study finds that an effective and proactive strategy to reduce the negative impact of future pandemics, driven by novel viral agents, has to be based on a planning of enhancement of healthcare sector and of environmental sustainability that can reduce fatality rate of infectious diseases in society.

Human health risk associated to particulate matter and polycyclic aromatic hydrocarbon levels and their relation with preponderant sources in Gran La Plata, Argentina

Levels of suspended particulate matter (PM) of both fractions PM₁₀ and PM_2.5 in ambient air were monitored in three areas of Gran La Plata: industrial, urban, and residential (2017-2019). Associated polycyclic aromatic hydrocarbons (PAHs) and nitropolycyclic aromatic hydrocarbons (NPAHs) to PM were also determined and possible emission sources were identified. Assessment of health risk to PM exposure and associated compounds was realized. Results showed a decrease in levels of PM₁₀ in each area along the period studied, especially in the industrial area. Decreases in PM_2.5 levels were also observed in urban and residential areas over the years, although the trend is not as marked as with PM₁₀ levels. Then, PM_2.5 levels in the industrial area have remained practically constant. The 89% of both PM₁₀ and PM_2.5 annual mean exceeds the WHO reference values. The presence of most of the 16 US EPA priority PAHs studied was found with a detection frequency greater than 60% and it was possible to identify the importance of the contributions of vehicular emissions as predominant sources of PAH emission. From the calculations of the risk of contracting cancer throughout life (LCR), in the case of adults, the US EPA limits were not complied in the industrial and urban areas and in both fractions of PM. From the evaluation of the burden of disease (EBD), the calculated relative risks of mortality were very similar for the studied districts, being the relative risk in La Plata slightly lower, about 3-5%, than those in Berisso and Ensenada.

Combined Effect of Hot Weather and Outdoor Air Pollution on Respiratory Health: Literature Review

Association between short-term exposure to ambient air pollution and respiratory health is well documented. At the same time, it is widely known that extreme weather events intrinsically exacerbate air pollution impact. Particularly, hot weather and extreme temperatures during heat waves (HW) significantly affect human health, increasing risks of respiratory mortality and morbidity. Concurrently, a synergistic effect of air pollution and high temperatures can be combined with weather–air pollution interaction during wildfires. The purpose of the current review is to summarize literature on interplay of hot weather, air pollution, and respiratory health consequences worldwide, with the ultimate goal of identifying the most dangerous pollution agents and vulnerable population groups. A literature search was conducted using electronic databases Web of Science, Pubmed, Science Direct, and Scopus, focusing only on peer-reviewed journal articles published in English from 2000 to 2021. The main findings demonstrate that the increased level of PM10 and O3 results in significantly higher rates of respiratory and cardiopulmonary mortality. Increments in PM2.5 and PM10, O3, CO, and NO2 concentrations during high temperature episodes are dramatically associated with higher admissions to hospital in patients with chronic obstructive pulmonary disease, daily hospital emergency transports for asthma, acute and chronic bronchitis, and premature mortality caused by respiratory disease. Excessive respiratory health risk is more pronounced in elderly cohorts and small children. Both heat waves and outdoor air pollution are synergistically linked and are expected to be more serious in the future due to greater climate instability, being a crucial threat to global public health that requires the responsible involvement of researchers at all levels. Sustainable urban planning and smart city design could significantly reduce both urban heat islands effect and air pollution.

The associations of air pollution and socioeconomic factors with esophageal cancer in China based on a spatiotemporal analysis

Rapid urbanization and industrialization in China have incurred serious air pollution and consequent health concerns. In this study, we examined the modifying effects of urbanization and socioeconomic factors on the association between PM_2.5 and incidence of esophageal cancer (EC) in 2000-2015 using spatiotemporal techniques and a quasi-Poisson generalized linear model. The results showed a downward trend of EC and high-risk areas aggregated in North China and Huai River Basin. In addition, a stronger association between PM_2.5 and incidence was observed in low urbanization group, and the association was stronger for females than males. When exposure time-windows were adjusted as 0, 5, 10, 15 years, the incidence risk increased by 2.48% (95% CI: 2.23%, 2.73%), 2.20% (95% CI: 1.91%, 2.49%), 2.18% (95% CI%: 1.92%, 2.43%), 1.87% (95% CI%:1.64, 2.10%) for males, respectively and 4.03% (95% CI: 3.63%, 4.43%), 2.20% (95% CI: 1.91%, 2.49%), 3.97% (95% CI: 3.54%, 4.41%), 3.06% (95% CI: 2.71%, 3.41%) for females, respectively. The findings indicated people in low urbanization group faced with a stronger EC risk caused by PM_2.5, which contributes to a more comprehensive understanding of combating EC challenges related to PM_2.5 pollution.

The Historical Trend of Air Pollution and Its Impact on Human Health in Campania Region (Italy)

The Campania region covers an area of about 13,590 km2 with 5.8 million residents. The area suffers from several environmental issues due to urbanization, the presence of industries, wastewater treatment, and solid waste management concerns. Air pollution is one of the most relevant environmental troubles in the Campania region, frequently exceeding the limit values established by European directives. In this paper, airborne pollutant concentration data measured by the regional air quality network from 2003 to 2019 are collected to individuate the historical trends of nitrogen dioxide (NO2), coarse and fine particulate matter with aerodynamic diameters smaller than 10 μm (PM10) and 2.5 μm (PM2.5), and ozone (O3) through the analysis of the number of exceedances of limit values per year and the annual average concentration. Information on spatial variability and the effect of the receptor category is obtained by lumping together data belonging to the same province or category. To obtain information on the general air quality rather than on single pollutants, the European Air Quality Index (EU-AQI) is also evaluated. A special focus is dedicated to the effect of deep street canyons on air quality, since they are very common in the urban areas in Campania. Finally, the impact of air pollution from 2003 to 2019 on human health is also analyzed using the software AIRQ+.

An index to quantify environmental risk of exposure to future epidemics of the COVID-19 and similar viral agents: Theory and practice

In the presence of the novel Coronavirus Disease (COVID-19) and other new viral agents, one of the fundamental problems in science is the evaluation of environmental and social weaknesses of cities/regions to the exposure of infectious diseases for preventing and/or containing new COVID-19 outbreaks and the diffusion of other viral agents that generate a negative impact on public health and economy of countries. The current monitoring of transmission dynamics of infectious diseases is mainly based on reproduction number (R₀) and fatality rates. However, this approach is a real-time monitoring of transmission dynamics for mitigating the numbers of COVID-19 related infected individuals and deaths. Reproduction number does not provide information to cope with future epidemics or pandemics. The main goal of this study is to propose the Index c (as contagions) that quantifies, ex-ante, the environmental risk of exposure of cities/regions to future epidemics of the COVID-19 and similar vital agents. This Index c synthetizes environmental, demographic, climatological and health risk factors of cities/regions that indicate their exposure to infectious diseases. Index c has a range from 1 (environmental and social weakness of urban areas leading to high levels of exposure to infectious diseases) to 0 (environment that reduces the risk of exposure to infectious diseases in society). The statistical evidence here, applied on case study of Italy, seems in general to support the predictive capacity of the Index c as a particularly simple but superior indicator in detecting the global correlation between potential risk of exposure of cities/regions to infectious diseases and actual risk given by infected individuals and deaths of the COVID-19. The Index c can support a proactive environmental strategy to help policymakers to prevent future pandemics similar to the COVID-19.

Investigating a Potential Map of PM2.5 Air Pollution and Risk for Tourist Attractions in Hsinchu County, Taiwan

In the past few years, human health risks caused by fine particulate matters (PM2.5) and other air pollutants have gradually received attention. According to the Disaster Prevention and Protection Act of Taiwan's Government enforced in 2017, "suspended particulate matter" has officially been acknowledged as a disaster-causing hazard. The long-term exposure to high concentrations of air pollutants negatively affects the health of citizens. Therefore, the precise determination of the spatial long-term distribution of hazardous high-level air pollutants can help protect the health and safety of residents. The analysis of spatial information of disaster potentials is an important measure for assessing the risks of possible hazards. However, the spatial disaster-potential characteristics of air pollution have not been comprehensively studied. In addition, the development of air pollution potential maps of various regions would provide valuable information. In this study, Hsinchu County was chosen as an example. In the spatial data analysis, historical PM2.5 concentration data from the Taiwan Environmental Protection Administration (TWEPA) were used to analyze and estimate spatially the air pollution risk potential of PM2.5 in Hsinchu based on a geographic information system (GIS)-based radial basis function (RBF) spatial interpolation method. The probability that PM2.5 concentrations exceed a standard value was analyzed with the exceedance probability method; in addition, the air pollution risk levels of tourist attractions in Hsinchu County were determined. The results show that the air pollution risk levels of the different seasons are quite different. The most severe air pollution levels usually occur in spring and winter, whereas summer exhibits the best air quality. Xinfeng and Hukou Townships have the highest potential for air pollution episodes in Hsinchu County (approximately 18%). Hukou Old Street, which is one of the most important tourist attractions, has a relatively high air pollution risk. The analysis results of this study can be directly applied to other countries worldwide to provide references for tourists, tourism resource management, and air quality management; in addition, the results provide important information on the long-term health risks for local residents in the study area.

Concentrations and mortality due to short- and long-term exposure to PM2.5 in a megacity of Iran (2014-2019)

The present study aimed to survey the spatial and temporal trends of ambient concentration of PM_2.5 and to estimate mortality attributed to short- and long-term exposure to PM_2.5 in Isfahan from March 2014 to March 2019 using the AirQ⁺ software. The hourly concentrations of PM_2.5 were obtained from the Isfahan Department of Environment and Isfahan Air Quality Monitoring Center. Then, the 24-h mean concentration of PM_2.5 for each station was calculated using the Excel software. According to the results, the annual mean concentration of PM_2.5 in 2014-2019 was 29.9-50.9 μg/m³, approximately 3-5 times higher than the WHO guideline (10 μg/m³). The data showed that people of Isfahan in almost 58% to 96% of the days of a year were exposed to PM_2.5 higher than the WHO daily guideline. The concentrations of PM_2.5 in cold months such as October, November, December and January were higher than those in the other months. The zoning of the annual concentrations of PM_2.5 in urban areas showed that the highest PM_2.5 concentrations were related to the northern, northwestern, southern and central areas of the city. On average, from 2014 to 2019, the number of deaths due to natural mortality, lung cancer (LC), chronic obstructive pulmonary disease (COPD), ischemic heart disease (IHD) and stroke associated with ambient PM_2.5 were 948, 16, 18, 281 and 60, respectively. The present study estimated that on average, 14.29% of the total mortality, 17.2% of lung cancer (LC), 15.54% of chronic obstructive pulmonary disease (COPD), 17.12% of ischemic heart disease (IHD) and 14.94% of stroke mortalities were related to long-term exposure to ambient PM_2.5. So provincial managers and politicians must adopt appropriate strategies to control air pollution and reduce the attributable health effects and economic losses.