Estimation of the effects PM2.5, NO2, O3 pollutants on the health of Shahrekord residents based on AirQ+ software during (2012-2018)

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.

Air pollution status and attributable health effects across the state of West Bengal, India, during 2016-2021

Air pollution is one of the most significant threats to human safety due to its detrimental health consequences worldwide. This study examines the air pollution levels in 22 districts of West Bengal from 2016 to 2021, using data from 81 stations operated by the West Bengal Pollution Control Board (WBPCB). The study assesses the short- and long-term impacts of particulate matter (PM) on human health. The highest annual variation of PM10 was noted in 2016 (106.99 ± 34.17 μg/m3), and the lowest was reported in 2020 (88.02 ± 13.61 μg/m3), whereas the highest annual variations of NO2 (μg/m3) were found in 2016 (35.17 ± 13.55 μg/m3), and lowest in 2019 (29.72 ± 13.08 μg/m3). Similarly, the SO2 level was lower (5.35 μg/m3) in 2017 and higher in 2020 (7.78 μg/m3). In the state, Bardhaman, Bankura, Kolkata, and Howrah recorded the highest PM10 concentrations. The monthly and seasonal variations of pollution showed higher in December, January, and February (winter season) and lowest observed in June, July, and August (rainy season). The southern part of West Bengal state has recorded higher pollution levels than the northern part. The short- and long-term health impact assessment due to particulate matter shows that the estimated number of attributable cases (ENACs) for incidence of chronic bronchitis in adults and prevalence of bronchitis in children were 305,234 and 14,652 respectively. The long-term impact of PM2.5 on human health ENACs for mortality due to chronic obstructive pulmonary disease for adults, acute lower respiratory infections in children aged 0-5, lung cancer, and stroke for adults were 21,303, 12,477, 25,064, 94,406, and 86,272 respectively. This outcome assists decision-makers and stakeholders in effectively addressing the air pollution and health risk concerns within the specified area.

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.

Assessing the effectiveness of artificial neural networks (ANN) and multiple linear regressions (MLR) in forcasting AQI and PM10 and evaluating health impacts through AirQ+ (case study: Tehran)

Air pollution is one of the major concerns for the population and the environment due to its hazardous effects. PM10 has affected significant scientific and regulatory interest because of its strong correlation with chronic health such as respiratory illnesses, lung cancer, and asthma. Forcasting air quality and assessing the health impacts of the air pollutants like particulate matter is crucial for protecting public health.This study incorporated weather, traffic, green space information, and time parameters, to forcst the AQI and PM10. Traffic data plays a critical role in predicting air pollution, as it significantly influences them. Therefore, including traffic data in the ANN model is necessary and valuable. Green spaces also affect air quality, and their inclusion in neural network models can improve predictive accuracy. The key factors influencing the AQI are the two-day lag time, the proximity of a park to the AQI monitoring station, the average distance between each park and AQI monitoring stations, and the air temperature. In addition, the average distance between each park, the number of parks, seasonal variations, and the total number of vehicles are the primary determinants affecting PM10.The straightforward effective Multilayer Perceptron Artificial Neural Network (MLP-ANN) demonstrated correlation coefficients (R) of 0.82 and 0.93 when forcasting AQI and PM10, respectively. This study also used the forcasted PM10 values from the ANN model to assess the health effects of elevated air pollution. The results indicate that elevated levels of PM10 can increase the likelihood of respiratory symptoms. Among children, there is a higher prevalence of bronchitis, while among adults, the incidence of chronic bronchitis is higher. It was estimated that the attributable proportions for children and adults were 6.87% and 9.72%, respectively. These results underscore the importance of monitoring air quality and taking action to reduce pollution to safeguard public health.

The characteristics of nano-micron calcite particles/common bacteria complex and its interfacial interaction

Based on the composite pollution of atmospheric microbial aerosol, this paper selects the calcite/bacteria complex as the research object which was prepared by calcite particles and two common strains of bacteria (Escherichia coli, Staphylococcus aureus) in the solution system. The morphology, particle size, surface potential, and surface groups of the complex were explored by modern analysis and testing methods, with an emphasis on the interfacial interaction between calcite and bacteria. The SEM, TEM, and CLSM results showed that the morphology of the complex could be divided into three types: bacteria adhering to the surface or edge of micro-CaCO₃, bacteria aggregating with nano-CaCO₃, and single nano-CaCO₃ wrapping bacteria. The complex's particle size was about 2.07 ~ 192.4 times larger than the original mineral particles, and the nano-CaCO₃/bacteria complex's particle size variation was caused by the fact that nano-CaCO₃ has agglomeration in solution. The surface potential of the micro-CaCO₃/bacteria complex (isoelectric point pH = 3.0) lies between micro-CaCO₃ and bacteria, while the surface potential of the nano-CaCO₃/bacteria complex (isoelectric point pH = 2.0) approaches the nano-CaCO₃. The complex's surface groups were based primarily on the infrared characteristics of calcite particles, accompanied by the infrared characteristics of bacteria, displaying the interfacial interaction from the protein, polysaccharides, and phosphodiester groups of bacteria. The interfacial action of the micro-CaCO₃/bacteria complex is mainly driven by electrostatic attraction and hydrogen bonding force, while the nano-CaCO₃/bacteria complex is guided by surface complexation and hydrogen bonding force. The increase in the β-fold/α-helix ratio of the calcite/S. aureus complex indicated that the secondary structure of bacterial surface proteins was more stable and the hydrogen bond effect was strong than the calcite/E. coli complex. The findings are expected to provide basic data for the mechanism research of atmospheric composite particles closer to the real environment.

Health Risk Assessment of Exposure to Air Pollutants Exceeding the New WHO Air Quality Guidelines (AQGs) in São Paulo, Brazil

We applied the AirQ+ model to analyze the 2021 data within our study period (15 December 2020 to 17 June 2022) to quantitatively estimate the number of specific health outcomes from long- and short-term exposure to atmospheric pollutants that could be avoided by adopting the new World Health Organization Air Quality Guidelines (WHO AQGs) in São Paulo, Southeastern Brazil. Based on temporal variations, PM_2.5, PM₁₀, NO₂, and O₃ exceeded the 2021 WHO AQGs on up to 54.4% of the days during sampling, mainly in wintertime (June to September 2021). Reducing PM_2.5 values in São Paulo, as recommended by the WHO, could prevent 113 and 24 deaths from lung cancer (LC) and chronic obstructive pulmonary disease (COPD) annually, respectively. Moreover, it could avoid 258 and 163 hospitalizations caused by respiratory (RD) and cardiovascular diseases (CVD) due to PM_2.5 exposure. The results for excess deaths by RD and CVD due to O₃ were 443 and 228, respectively, and 90 RD hospitalizations due to NO₂. Therefore, AirQ+ is a useful tool that enables further elaboration and implementation of air pollution control strategies to reduce and prevent hospital admissions, mortality, and economic costs due to exposure to PM_2.5, O₃, and NO₂ in São Paulo.

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.

Synergistic or Antagonistic Health Effects of Long- and Short-Term Exposure to Ambient NO2 and PM2.5: A Review

Studies on adverse health effects associated with air pollution mostly focus on individual pollutants. However, the air is a complex medium, and thus epidemiological studies face many challenges and limitations in the multipollutant approach. NO₂ and PM_2.5 have been selected as both originating from combustion processes and are considered to be the main pollutants associated with traffic; moreover, both elicit oxidative stress responses. An answer to the question of whether synergistic or antagonistic health effects of combined pollutants are demonstrated by pollutants monitored in ambient air is not explicit. Among the analyzed studies, only a few revealed statistical significance. Exposure to a single pollutant (PM_2.5 or NO₂) was mostly associated with a small increase in non-accidental mortality (HR:1.01-1.03). PM_2.5 increase of <10 µg/m³ adjusted for NO₂ as well as NO₂ adjusted for PM_2.5 resulted in a slightly lower health risk than a single pollutant. In the case of cardiovascular heart disease, mortality evoked by exposure to PM_2.5 or NO₂ adjusted for NO₂ and PM_2.5, respectively, revealed an antagonistic effect on health risk compared to the single pollutant. Both short- and long-term exposure to PM_2.5 or NO₂ adjusted for NO₂ and PM_2.5, respectively, revealed a synergistic effect appearing as higher mortality from respiratory diseases.