Long-term effects of air pollutants on deaths in a semi-urban city in Northwestern Turkey: a time series analysis

To examine the associations between daily variations of coarse Particulate Matter(PM10) and/or sulfur dioxide(SO2) and mortality. The Poisson Generalized Linear Model(GLM) was employed to analyze the relationship between ambient air pollutants such as PM10 and SO2 and mortality. For each 10 μg/m3 increase in PM10, the overall mortality risk was found to be 1.022-fold high on the previous-eighth-day(lag 7) (RR, 95%CI:1.002-1.042) in the unadjusted model; 1.031-fold high in men (RR, 95%CI:1.005-1.058); 1.024-fold high in those aged 65 and over (RR, 95%CI:1.001-1.048). Also, the risk of death in men was 1.028-fold high in the model adjusted on the previous- eighth-day(lag 7) (RR, 95%CI:1.002-1.055). Mortality risk was found to be 1.088-fold high in 10 μg/m3 increase in SO2 under 65 years in males in the previous-third-day(lag 2) in the unadjusted model, and the risk of death was found to be 1.086-fold (RR, 95%CI:1.007-1.164) high in males in the adjusted model.   .

An overview of atmospheric aerosol and their effects on human health

Epidemiologic investigations have previously been published in more than 200 papers, and several studies have examined the impacts of particle air pollution on health. The main conclusions now being made about the epidemiological evidence of particle pollution-induced health impacts are discussed in this article. Although there is no universal agreement, most reviewers conclude that particulate air pollution, particularly excellent combustion-cause contamination prevalent in many municipal and manufacturing environments, is a significant risk for cardiopulmonary sickness and mortality. Most epidemiological research has concentrated on the impacts of acute exposure, although the total public health implications of chronic acquaintance's outcome may be more extraordinarily significant. According to some reviewers, prolonged, repeated exposure raises the risk of cardiorespiratory death and chronic respiratory illness. A more general (but still universal) agreement is that short-term particle pollution exposure has been shown to aggravate pre-existing pulmonary and cardiovascular diseases and increase the number of community members who become sick, require medical treatment, or die. Several in-depth studies conducted in the global and Indian regions are addressed.

Downregulation of TAZ elicits a mitochondrial redox imbalance and ferroptosis in lung epithelial cells exposed to diesel exhaust particles

Mitochondrial dysfunction was reported to be involved in the development of lung diseases including chronic obstructive pulmonary disease (COPD). However, molecular regulation underlying metabolic disorders in the airway epithelia exposed to air pollution remains unclear. In the present study, lung bronchial epithelial BEAS-2B and alveolar epithelial A549 cells were treated with diesel exhaust particles (DEPs), the primary representative of ambient particle matter. This treatment elicited cell death accompanied by induction of lipid reactive oxygen species (ROS) production and ferroptosis. Lipidomics analyses revealed that DEPs increased glycerophospholipid contents. Accordingly, DEPs upregulated expression of the electron transport chain (ETC) complex and induced mitochondrial ROS production. Mechanistically, DEP exposure downregulated the Hippo transducer transcriptional co-activator with PDZ-binding motif (TAZ), which was further identified to be crucial for the ferroptosis-associated antioxidant system, including glutathione peroxidase 4 (GPX4), the glutamate-cysteine ligase catalytic subunit (GCLC), and glutathione-disulfide reductase (GSR). Moreover, immunohistochemistry confirmed downregulation of GPX4 and upregulation of lipid peroxidation in the bronchial epithelium of COPD patients and Sprague-Dawley rats exposed to air pollution. Finally, proteomics analyses confirmed alterations of ETC-related proteins in bronchoalveolar lavage from COPD patients compared to healthy subjects. Together, our study discovered that involvement of mitochondrial redox dysregulation plays a vital role in pulmonary epithelial cell destruction after exposure to air pollution.

Potential roles of air pollutants on the induction and aggravation of rheumatoid arthritis: From cell to bedside studies

Rheumatoid arthritis (RA) is an involving chronic systemic inflammatory disease which mainly affects the joints. Several factors including genetic, environment and infections have been acknowledged as being involved in the pathogenesis and aggravation of RA. Air pollution, particularly particulate matter is widely recognized as a cause of health problems. This review is to summarize and discuss the association between air pollutants and the development or the aggravation of RA based on evidence from in vitro, in vivo and clinical studies. The results from the review found that air pollutants can stimulate immunological processes and stimulate inflammatory mediators and autoantibodies productions, both in intro and in vivo studies. In addition, air pollutants can induce RA and aggravate RA disease activity. Unfortunately, there also are some discrepancies in the results, which might be due to the type cell line and the concentration of air pollutants used in the in vitro and in vivo studies, as well as the concentration and duration of exposure in human studies. These findings suggest that future studies focused on elucidating these mechanisms using advanced techniques and identifying reliable biomarkers to assess individual susceptibility and disease activity should be carried out. Longitudinal studies, intervention strategies, and policy implications also should be explored. A comprehensive understanding on these association will facilitate targeted approaches for prevention and management of air pollutant-induced RA and improve health outcome.

A novel statistical-dynamical method for a seasonal forecast of particular matter in South Korea

Societal concerns about air quality in East Asia are still growing despite country-level efforts to reduce air pollution emissions. In coping with this growing concern, the government and the public demand a longer‑lead forecast of air quality to ensure sufficient response time until society prepares for countermeasures such as a temporary reduction of specific emission sources. Here we propose a novel method that produces skillful seasonal forecasting of wintertime (December to February) PM₁₀ concentration over South Korea. The method is based on the idea that climate condition and air quality have co-variability in the seasonal time scales and that the state-of-art seasonal prediction model will benefit air quality forecasting. More specifically, a linear regression model is constructed to link observed winter PM₁₀ concentration and climate variables where the predicted climate variables were furnished from NCEP CFSv2 forecast initialized during autumn. In this case, climate variables were selected as predictors of the model because they are not only physically related to air quality but also 'predictable' in CFS hindcast. Through analysis of retrospective forecasts of 20 winters for the period 2001-2020, we found this model shows statistically significant skill for the seasonal forecast of wintertime PM₁₀ concentration.

Phyto-cleaning of particulate matter from polluted air by woody plant species in the near-desert city of Jodhpur (India) and the role of heme oxygenase in their response to PM stress conditions

Particulate matter (PM) is one of the most dangerous pollutants in the air. Urban vegetation, especially trees and shrubs, accumulates PM and reduces its concentration in ambient air. The aim of this study was to examine 10 tree and shrub species common for the Indian city of Jodhpur (Rajasthan) located on the edge of the Thar Desert and determine (1) the accumulation of surface and in-wax PM (both in three different size fractions), (2) the amount of epicuticular waxes on foliage, (3) the concentrations of heavy metals (Cd and Cu) on/in the leaves of the examined species, and (4) the level of heme oxygenase enzyme in leaves that accumulate PM and heavy metals. Among the investigated species, Ficus religiosa L. and Cordia myxa L. accumulated the greatest amount of total PM. F. religiosa is a tall tree with a lush, large crown and leaves with wavy edge, convex veins, and long petioles, while C. myxa have hairy leaves with convex veins. The lowest PM accumulation was recorded for drought-resistant Salvadora persica L. and Azadirachta indica A. Juss., which is probably due to their adaptation to growing conditions. Heavy metals (Cu and Cd) were found in the leaves of almost every examined species. The accumulation of heavy metals (especially Cu) was positively correlated with the amount of PM deposited on the foliage. A new finding of this study indicated a potentially important role of HO in the plants' response to PM-induced stress. The correlation between HO and PM was stronger than that between HO and HMs. The results obtained in this study emphasise the role of plants in cleaning polluted air in conditions where there are very high concentrations of PM.

Short-term exposure to air pollution and biomarkers of cardiovascular effect: A repeated measures study

To help understand the pathophysiologic mechanisms linking air pollutants and cardiovascular disease (CVD), we employed a repeated measures design to investigate the associations of four short-term air pollution exposures - particulate matter less than 2.5 μm in diameter (PM_2.5), nitrogen dioxide (NO₂), ozone (O₃) and sulfur dioxide (SO₂), with two blood markers involved in vascular effects of oxidative stress, soluble lectin-like oxidized LDL receptor-1 (sLOX-1) and nitrite, using data from the Multi-Ethnic Study of Atherosclerosis (MESA). Seven hundred and forty participants with plasma sLOX-1 and nitrite measurements at three exams between 2002 and 2007 were included. Daily PM_2.5, NO₂, O₃ and SO₂ zero to seven days prior to blood draw were estimated from central monitors in six MESA regions, pre-adjusted using site-specific splines of meteorology and temporal trends, and an indicator for day of the week. Unconstrained distributed lag generalized estimating equations were used to estimate net effects over eight days with adjustment for sociodemographic and behavioral factors. The results showed that higher short-term concentrations of PM_2.5, but not other pollutants, were associated with increased sLOX-1 analyzed both as a continuous outcome (percent change per interquartile increase: 16.36%, 95%CI: 0.1-35.26%) and dichotomized at the median (odds ratio per interquartile increase: 1.21, 95%CI: 1.01-1.44). The findings were not meaningfully changed after adjustment for additional covariates or in several sensitivity analyses. Pollutant concentrations were not associated with nitrite levels. This study extends earlier experimental findings of increased sLOX-1 levels following PM inhalation to a much larger population and at ambient concentrations. In light of its known mechanistic role in promoting vascular disease, sLOX-1 may be a suitable translational biomarker linking air pollutant exposures and cardiovascular outcomes.

Cable-car measurements of vertical aerosol profiles impacted by mountain-valley breezes in Lushan Mountain, East China

In-situ field observations of vertical aerosol profiles for one month in complex terrain (Lushan Mountain, China) were carried out using a cable car, which resolved detailed vertical distributions of mountain aerosols with low-cost operation. Cable-car observations were conducted during the early morning and late afternoon, when mountain and valley winds dominated, respectively. The diurnal aerosol variations at the top and foot of Lushan Mountain were analyzed based on environmental and meteorological stations. The observations indicated that the mountain-valley breezes notably impacted the mountain-area aerosol distribution under weak weather conditions. More uniform aerosol profiles for the afternoon than the morning, with their decreasing rates of PM_2.5 (particles with diameters less than 2.5 μm) were 1.64 and 2.28 μg m^-3/100 m, respectively. The PM_2.5/PM₁₀ ratio at the mountain top increased from 0.69 to 0.81, and that at the mountain base decreased from 0.75 to 0.70 from morning to afternoon. The PM_2.5 concentration decreased in and around Lushan Mountain from daytime to nighttime, with the impacted diameter of the 300-m topography line being smaller than ~5 km, while the concentration increased in Jiujiang City. The relative decreasing rate of PM_2.5 was higher at the mountain top site (~20%) than at the base site (~2%) from daytime to nighttime. Moreover, uniform aerosol profiles could have been caused by regional transport through a relatively strong low-level synoptic flow (~5 m s^-1) and the mountain's dynamic lifting effect.

Modeling of atmospheric particulate matters via artificial intelligence methods

Nowadays, pollutants continue to be released into the atmosphere in increasing amounts with each passing day. Some of them may turn into more harmful forms by accumulating in different layers of the atmosphere at different times and can be transported to other regions with atmospheric events. Particulate matter (PM) is one of the most important air pollutants in the atmosphere, and it can be released into the atmosphere by natural and anthropogenic processes or can be formed in the atmosphere as a result of chemical reactions. In this study, it was aimed to predict PM₁₀ and PM_2.5 components measured in an industrial zone selected by adaptive neuro-fuzzy inference system (ANFIS), support vector regression (SVR), classification and regression trees (CART), random forest (RF), k-nearest neighbor (KNN), and extreme learning machine (ELM) methods. To this end, in the first stage of the study, the dataset consisting of air pollutants and meteorological data was created, the temporal and qualitative evaluation of these data was performed, and the PM (PM₁₀ and PM_2.5) components were modeled using the "R" software environment by artificial intelligence methods. The ANFIS model was more successful in predicting the PM₁₀ (R² = 0.95, RMSE = 5.87, MAE = 4.75) and PM_2.5 (R² = 0.97, RMSE = 3.05, MAE = 2.18) values in comparison with other methods. As a result of the study, it was clearly observed that the ANFIS model could be used in the prediction of air pollutants.

Long-term exposure to air-pollution and COVID-19 mortality in England: A hierarchical spatial analysis

Recent studies suggested a link between long-term exposure to air-pollution and COVID-19 mortality. However, due to their ecological design based on large spatial units, they neglect the strong localised air-pollution patterns, and potentially lead to inadequate confounding adjustment. We investigated the effect of long-term exposure to NO2 and PM2.5 on COVID-19 mortality in England using high geographical resolution. In this nationwide cross-sectional study in England, we included 38,573 COVID-19 deaths up to June 30, 2020 at the Lower Layer Super Output Area level (n = 32,844 small areas). We retrieved averaged NO2 and PM2.5 concentration during 2014-2018 from the Pollution Climate Mapping. We used Bayesian hierarchical models to quantify the effect of air-pollution while adjusting for a series of confounding and spatial autocorrelation. We find a 0.5% (95% credible interval: -0.2%, 1.2%) and 1.4% (95% CrI: -2.1%, 5.1%) increase in COVID-19 mortality risk for every 1 μg/m3 increase in NO2 and PM2.5 respectively, after adjusting for confounding and spatial autocorrelation. This corresponds to a posterior probability of a positive effect equal to 0.93 and 0.78 respectively. The spatial relative risk at LSOA level revealed strong patterns, similar for the different pollutants. This potentially captures the spread of the disease during the first wave of the epidemic. Our study provides some evidence of an effect of long-term NO2 exposure on COVID-19 mortality, while the effect of PM2.5 remains more uncertain.

Unexpected air quality impacts from implementation of green infrastructure in urban environments: A Kansas City case study

Green infrastructure (GI) implementation can benefit an urban environment by reducing the impacts of urban stormwater on aquatic ecosystems and human health. However, few studies have systematically analyzed the biophysical effects on regional meteorology and air quality that are triggered by changes in the urban vegetative coverage. In this study we use a state-of-the-art high-resolution air quality model to simulate the effects of a hypothetically feasible vegetation-focused GI implementation scenario in Kansas City, MO/KS on regional meteorology and air quality. Full year simulations are conducted for both the base case and GI land use scenarios using two different land surface models (LSMs) schemes inside the meteorological model. While the magnitudes of the changes in air quality due to the GI implementation differ using the two LSMs, the model outputs consistently showed increases in summertime PM_2.5 (1.1 μg m^-3, approximately 10% increase using NOAH LSM), which occurred mostly during the night and arose from the primary components, due to the cooler surface temperatures and the decreased planetary boundary layer height (PBLH). Both the maximum daily 8-hour average ozone and 1 h daily maximum O₃ during summertime, decreased over the downtown areas (maximum decreases of 0.9 and 1.4 ppbv respectively). The largest ozone decreases were simulated to happen during the night, mainly caused by the titration effect of increased NO_x concentration from the lower PBLH. These results highlight the region-specific non-linear process feedback from GI on regional air quality, and further demonstrate the need for comprehensive coupled meteorological-air quality modeling systems and necessity of accurate land surface model for studying these impacts.

Health risk assessment of polycyclic aromatic hydrocarbons (PAHs) adsorbed in PM2.5 and PM10 in a region of Arequipa, Peru

The concentrations of PM_2.5 and PM₁₀, as well as those of the PAHs bound to these particles, were quantified at four sites in the region of Arequipa, Peru, during the year 2018. These samples were collected with high volume samplers, and the concentrations of the PAHs were quantified by liquid chromatography (HPLC). The values found for PM_2.5 and PM₁₀ at all the sampling sites in Arequipa exceeded the norms established in Peru (50 μg m^-3 annual average value for PM₁₀ and 25 μg m^-3 annual average value for PM_2.5), with the industrial site presenting the highest values of particulate matter (PM₁₀ max = 235.1 μg m^-3; PM_2.5 max = 218.4 μg m^-3). With respect to seasonality, in the cold season (winter), the concentration of particles was higher compared to the other seasons. Concerning the PAHs, it was found that these had the highest concentrations at the industrial site, followed by the site with high vehicular traffic, with both these sites differing significantly from the rural sites. In addition, at the industrial and high traffic sites, there was a predominance of PAHs with 5 and 6 rings, whereas at the rural sites, PAHs with fewer rings predominated. Finally, the calculated values of lifetime lung cancer risk also revealed a difference between sites with marked emission sources, where irrigation was considered moderate, and the rural sites, where irrigation was considered low. This demonstrated that people living at sites with mobile sources and/or industries had a higher cancer risk compared to the inhabitants of rural sites.

Association between ambient PM2.5 and emergency department visits for psychiatric emergency diseases

Background

Whether or not short-term exposure to particulate matter <2.5 μm in diameter (PM_2.5) increases the risk of psychiatric emergency diseases is unclear.

Methods

The study was performed in a metropolis from January 2015 to December 2016. The exposure was PM_2.5, and the confounders were weather (temperature and humidity) and other pollutants (PM₁₀, SO₂, CO, O₃, and NO₂). The outcomes were emergency department (ED) visits with psychiatric disease codes (F00-F99 in ICD10 codes). General additive models were used for the statistical analysis to calculate the adjusted relative risks (ARRs) and 95% confidence intervals (95% CIs) for the daily number of ED visits with a lag of 1 to 3 days following a 10 μg/m³ increase in PM_2.5.

Results

During the study period, a total of 67,561 ED visits for psychiatric diseases were identified and tested for association with PM_2.5. Daily ED visits for all psychiatric diseases were not associated with PM_2.5 in the model that was not adjusted for other pollutants. The ARR (95% CI) in the model adjusted for SO₂ was 1.011 (1.002–1.021) by 10 μg/m³ of PM_2.5 on Lag 1 for all psychiatric diseases (F00-F99). The ARR (95% CI) in the model adjusted for O₃ was 1.015 (1.003–1.029) by 10 μg/m³ of PM_2.5 on Lag 1 for F40-F49 (Neurotic, stress-related and somatoform disorders).

Conclusion

An increase in PM_2.5 showed a significant association with an increase in ED visits for all psychiatric diseases (F00-F99) and for neurotic, stress-related and somatoform disorders (F40-F49) on lag day 1.

The role of weather conditions and normal level of air pollution in appearance of stroke in the region of Southeast Europe

We investigated correlation between the normal level of air pollution, weather conditions and stroke occurrence in the region of Southeast Europe with a humid continental climate. This retrospective study included 1963 patients, 1712 (87.2%) with ischemic (IS) and 251 (12.8%) with hemorrhagic stroke (HS) admitted to emergency department. The number of patients, values of weather condition (meteorological parameters) [air temperature (°C), atmospheric pressure (kPa), relative humidity (%)] and concentrations of air pollutants [particulate matter (PM₁₀), nitrogen dioxide (NO₂), ozone (O₃)], were recorded and evaluated for each season (spring, summer, autumn, winter) during 2 years (July 2008-June 2010). The highest rate of IS was observed during spring (28.9%) (p = 0.0002) and HS in winter (33.9%) (p = 0.0006). We have found negative Spearman's correlations (after Bonferroni adjustment for the multiple correlations) of the number of males with values of relative humidity (%) (day 0, rho = - 0.15), the total number of strokes (day 2, rho = - 0.12), females (day 2, rho = - 0.12) and IS (day 2, rho = - 0.13) with concentrations of PM₁₀ (µg/m³), as well as negative correlations of the number of females (day 2, rho = - 0.12) and IS (day 2, rho = - 0.12) with concentrations of NO₂ (µg/m³) (for all p < 0.002). In winter, the number of HS (day 0, rho = 0.25, p = 0.001) positively correlated with concentrations of O₃ (µg/m³). The appearance of stroke has seasonal variations, with the highest rates during spring and winter. Positive correlation between the number of HS and values of O₃ requires an additional reduction of the legally permitted pollutants concentrations.

Indoor air pollutants, ventilation rate determinants and potential control strategies in Chinese dwellings: A literature review

After nearly twenty years of rapid modernization and urbanization in China, huge achievements have transformed the daily lives of the Chinese people. However, unprecedented environmental consequences in both indoor and outdoor environments have accompanied this progress and have triggered public awareness and demands for improved living standards, especially in residential environments. Indoor pollution data measured for >7000 dwellings (approximately 1/3 were newly decorated and were tested for volatile organic compound (VOC) measurements, while the rest were tested for particles, phthalates and other semi-volatile organic compounds (SVOCs), moisture/mold, inorganic gases and radon) in China within the last ten years were reviewed, summarized and compared with indoor concentration recommendations based on sensory or health end-points. Ubiquitous pollutants that exceed the concentration recommendations, including particulate matter, formaldehyde, benzene and other VOCs, moisture/mold, inorganic gases and radon, were found, indicating a common indoor air quality (IAQ) issue in Chinese dwellings. With very little prevention, oral, inhalation and dermal exposure to those pollutants at unhealthy concentration levels is almost inevitable. CO₂, VOCs, humidity and radon can serve as ventilation determinants, each with different ventilation demands and strategies, at typical occupant densities in China; and particle reduction should be a prerequisite for determining ventilation requirements. Two directional ventilation modes would have profound impacts on improving IAQ for Chinese residences are: 1) natural (or window) ventilation with an air cleaner and 2) mechanical ventilation with an air filtration unit, these two modes were reviewed and compared for their applicability and advantages and disadvantages for reducing human exposure to indoor air pollutants. In general, mode 2 can more reliably ensure good IAQ for occupants; while mode 1 is more applicable due to its low cost and low energy consumption. However, besides a roadmap, substantial efforts are still needed to develop affordable, applicable and general ventilation solutions to improve the IAQ of residential buildings in China.

Does temperature modify the effect of PM10 on mortality? A systematic review and meta-analysis

Large and growing literature has explored whether temperature modified the effect of particular matter (PM) on mortality, but results of the modification effect are inconsistent. In this study, we reviewed information from 29 studies to get the qualitative evidence of the modification effects of temperature on PM to mortality, and the data from 16 of the 29 studies were extracted to conduct a meta-analysis. Temperatures were grouped into three level: "low", "middle" and "high" according to the original studies. The random effect model was used in the meta-analysis with the relative risk (RR) as the measure indicator. The RRs (95% confidence intervals, CIs) for non-accidental death, cardiovascular death and respiratory death per 10 μg/m³ increase in PM₁₀ were 1.004 (1.003, 1.006), 1.005 (1.003,1.007), and 1.005 (1.000,1.010) in the low temperature level, 1.005 (1.004,1.006), 1.005 (1.004,1.007), and 1.008 (1.006, 1.010) in the middle temperature level, and 1.012 (1.010, 1.015), 1.016 (1.010, 1.022) and 1.019 (1.010,1.028) in the high temperature level, respectively. In conclusion, moderate evidence exists that temperature modifies the effect of PM₁₀ on mortality. The effect of PM₁₀ on respiratory death was the greatest, while the effect on non-accidental death was the smallest in the same temperature level. In addition, the effects of PM₁₀ on all the three kinds of mortality were the biggest in the high-temperature level, and the smallest in the low-temperature level.