High Concentrations Of Air Pollutants Research Articles

Direct current cardioversion and the impact of short-term exposure to air pollution: a report from the nationwide EP-PARTICLES study

Abstract Background Air pollution and atrial fibrillation (AF) represent significant public health challenges, impacting global health considerably. Numerous studies have focused on areas with high or very high air pollution concentrations, our study examines a unique area in Poland characterized by low to moderate air pollution levels. Our research also addresses a commonly overlooked in research type of pollution - Polish smog. Due to its composition rich in particulate matter and the conditions in which it is formed - is characterized by extremely adverse health effects. Aim To explore the correlation between short-term air pollution exposure and the incidence of acute direct current cardioversion (DCC) for AF treatment. Methods The study area encompassed three voivodeships from Eastern Poland at the NUTS-2 level, with a population of 5,429,378 individuals. Data on hospitalizations from 2011 to 2020 were obtained from the National Health Fund. We combined air pollution and weather condition data from both ground monitoring stations and satellite observations. Emergency visits for AF and DCC were identified using ICD-9 and ICD-10 codes. For a national perspective, we applied meta-analytical strategies to the municipality-specific outcomes. The results are presented as percentage increases in admissions (% IR) with 95% confidence intervals (95%CI). Results Over the decade, 190,454 hospitalizations for AF were reported with a standardized hospitalization rate (SHR) of 358 per 100,000/year (SD=113) and 30,291 DCC admissions (SHR=56.9 [SD]=26). The mean age for AF vs. DCC cohort was 69.6 (SD=11.2) vs. 68.7 (SD=10.4) years, with females representing 56.1% (N=106,822) of AF cases vs. 46.1% (N=13,953) of DCC admissions (P<0.001). Each 10 µg/m3 increase in PM2.5, PM10, and NO2 concentration on the exposure day led to 1.6% (1.1%–2.1%), 1% (0.8%–1.6%), and 1.8% (1.1%–2.6%) increases in acute AF admissions, respectively, with effects lasting up to 6 days. Women and older individuals were more vulnerable to AF episodes induced by air pollution (P<0.001). A 10 µg/m3 increase in PM2.5 on the day of admission increased DCC admissions by 1.5% (0.1%–2.9%, P=0.04), with effects persisting for up to 3 days. The impact of PM10 was time-delayed: 1.3% (0.2%–2.4%, P=0.02) for LAG1 (i.e. one day after exposure), and 1.1% (0.1%–2.2%, P=0.4) for LAG2. No significant effects of gaseous pollutants on DCC (SO2, NO2, and BaP) were observed, nor any differences in the effects by age or sex. Exposure-response functions show steeper slopes of the PM2.5 associations in the lower ranges of exposures, far below air quality norms set by the World Health Organization. Conclusions Air pollution acts as a triggering factor for acute AF hospitalizations and DCC. The differential impact of air pollution on AF events between groups highlights that women and older individuals are particularly vulnerable. Air pollution exposure should be considered into AF management and prevention strategies.Pooled exposure–response function: % inc

Time series analysis of the interaction between ambient temperature and air pollution on hospitalizations for AECOPD in Ganzhou, China

This study aimed to investigate the univariate and bivariate effects of ambient temperature and air pollutants on 57,251 inpatients with AECOPD (Acute Exacerbation of Chronic Obstructive Pulmonary Disease) in Ganzhou from January 1, 2016, to December 31, 2019. We categorized the daily mean temperature and air pollutant variables based on the exposure–response curve of the Distributed Lag Non-Linear Model. Poisson regression model was used for interaction and stratification analysis. The Relative Excess Risk due to Interaction (RERI) with 95% confidence intervals (95% CI) between daily mean temperature (Tmean) and air pollutants including NO2, PM2.5, and PM10 were − 0.428 (95% CI − 0.637, − 0.218), -− 0.227 (95% CI − 0.293, − 0.161), and − 0.119 (95% CI − 0.159, − 0.079). Further stratification analysis showed the relative risk (RR) (95% CI) of high NO2 (> 33 μg/m3) at low Tmean (≤ 28 °C) was 1.119 (95% CI 1.096, 1.142). Low temperatures with high PM10 in men and high PM2.5 in women were associated with a higher risk of AECOPD hospitalization. The results indicate a higher risk of hospitalization for AECOPD when there is with high concentrations of air pollution at low temperatures.

Meteorological, chemical and biological evaluation of the coupled chemistry-climate WRF-Chem model from regional to urban scale. An impact-oriented application for human health

Extreme climatic conditions, like heat waves or cold spells, associated to high concentrations of air pollutants are responsible for a broad range of effects on human health. Consequently, in the recent years, the question on how urban and peri-urban forests may improve both air quality and surface climate conditions at city-scale is receiving growing attention by scientists and policymakers, with previous studies demonstrating how nature-based solutions (NBS) may contribute to reduce the risk of population to be exposed to high pollutant levels and heat stress, preventing, thus, premature mortality. In this study we present a new modeling framework designed to simulate air quality and meteorological conditions from regional to urban scale, allowing thus to assess the impacts of both air pollution and heat stress on human health at urban level. To assess the model reliability, we evaluated the model's performances in reproducing several relevant meteorological, chemical, and biological variables. Results show how our modeling system can reliably reproduce the main meteorological, chemical, and biological variables over our study areas, thus this tool can be used to estimate the impact of air pollution and heat stress on human health. As an example of application, we show how common heat stress and air pollutant indices used for human health protection change when computed from regional to urban scale for the cities of Florence (Italy) and Aix en Provence (France).

Differentiated impact of low-exhaust-emission vehicles on NO2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$_\ ext {2}$$\\end{document} and particle concentrations in the Paris region

Higher concentrations of air pollutants, such as nitrogen dioxide (NO2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$_\ ext {2}$$\\end{document}) and particulate matter (PM), are observed in streets compared to the urban background. These concentrations could be predominantly attributed to road traffic, which remains an important source despite relentless efforts. In this study, performed over the Paris area, the impacts of the evolution of the fleet composition on urban air quality down to the street scale is assessed with two scenarios assuming the introduction of very-low-emission vehicles. Exhaust emission factors for these vehicles are based on the improvement of engine and after-treatment technologies, leading to factors lower than those proposed for the European emission standard Euro 7. Using the year 2014 as the baseline, very-low-emission vehicles are introduced up to the year 2030 for the Paris region. NO2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$_\ ext {2}$$\\end{document} emissions are thus reduced by 68 % in streets, and concentrations by 53 %. However, PM concentration reduction is limited to 18 % in streets as non-exhaust emissions from tyre and brake wear and road abrasion are preponderant. PM emissions from non-exhaust sources represent 59 % of the total road-traffic emission of PM in 2014 and 89 % in 2030. Non-regulated pollutant concentrations are also reduced, by 42 % for black carbon and 30 % for organic matter. Considering only very-low-emission and electric vehicles in the fleet further reduce NO2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$_\ ext {2}$$\\end{document} emissions and concentrations by 99.5 % and 80 % respectively. PM concentrations are only reduced by 22 %. This study highlights the high reduction potential of NO2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$_\ ext {2}$$\\end{document} concentrations with very-low-emission and electric vehicles, because of reduction of exhaust emissions. However, difficulties remain to reduce PM concentrations in urban areas, with the large majority of PM traffic emissions coming from non-exhaust sources.

Built Environment, Natural Environment, and Mental Health.

Mental health disorders have become a global problem, garnering considerable attention. However, the root causes of deteriorating mental health remain poorly understood, with existing literature predominantly concentrating on socioeconomic conditions and psychological factors. This study uses multi-linear and geographically weighted regressions (GWR) to examine the associations between built and natural environmental attributes and the prevalence of depression in US counties. The findings reveal that job sprawl and land mixed use are highly correlated with a lower risk of depression. Additionally, the presence of green spaces, especially in urban area, is associated with improved mental health. Conversely, higher concentrations of air pollutants, such as PM2.5 and CO, along with increased precipitation, are linked to elevated depression rates. When considering spatial correlation through GWR, the impact of population density and social capital on mental health displays substantial spatial heterogeneity. Further analysis, focused on two high depression risk clustering regions (northwestern and southeastern counties), reveals nuanced determinants. In northwestern counties, depression rates are more influenced by factors like precipitation and socioeconomic conditions, including unemployment and income segregation. In southeastern counties, population demographic characteristics, particularly racial composition, are associated with high depression prevalence, followed by built environment factors. Interestingly, job growth and crime rates only emerge as significant factors in the context of high depression risks in southeastern counties. This study underscores the robust linkages and spatial variations between built and natural environments and mental health, emphasizing the need for effective depression treatment to incorporate these multifaceted factors.

Delayed effects of air pollution on public bike-sharing system use in Seoul, South Korea: A time series analysis

Background:As a complementary means to urban public transit systems, public bike-sharing provides a green and active mode of sustainable mobility, while reducing carbon-dioxide emissions and promoting health. There has been increasing interest in factors affecting bike-sharing usage, but little is known about the effect of ambient air pollution. Method:To assess the short-term impact of daily exposure to multiple air pollutants (PM2.5, PM10, NO2, and O3) on the public bike-sharing system (PBS) usage in Seoul, South Korea (2018–2021), we applied a quasi-Poisson generalized linear model combined with a distributed lag nonlinear model (DLNM). The model was adjusted for day of the week, holiday, temperature, relative humidity, and long-term trend. We also conducted stratification analyses to examine the potential effect modification by age group, seasonality, and COVID-19. Results:We found that there was a negative association between daily ambient air pollution and the PBS usage level at a single lag day 1 (i.e., air quality a day before the event) across all four pollutants. Our results suggest that days with high levels of air pollutants (at 95th percentile) are associated with a 0.91% (0.86% to 0.96%) for PM2.5, 0.89% (0.85% to 0.94%) for PM10, 0.87% (0.82% to 0.91%) for O3, and 0.92% (0.87% to 0.98%) for NO2, reduction in cycling behavior in the next day compared to days with low levels of pollutants (at 25th percentile). No evidence of effect modification was found by seasonality, age nor the COVID-19 pandemic for any of the four pollutants. Conclusions:Our findings suggest that high concentrations of ambient air pollution are associated with decreased rates of PBS usage on the subsequent day regardless of the type of air pollutant measured.

Effects of extreme meteorological factors and high air pollutant concentrations on the incidence of hand, foot and mouth disease in Jining, China.

The evidence on the effects of extreme meteorological conditions and high air pollution levels on incidence of hand, foot and mouth disease (HFMD) is limited. Moreover, results of the available studies are inconsistent. Further investigations are imperative to elucidate the specific issue. Data on the daily cases of HFMD, meteorological factors and air pollution were obtained from 2017 to 2022 in Jining City. We employed distributed lag nonlinear model (DLNM) incorporated with Poisson regression to explore the impacts of extreme meteorological conditions and air pollution on HFMD incidence. We found that there were nonlinear relationships between temperature, wind speed, PM2.5, SO2, O3 and HFMD. The cumulative risk of extreme high temperature was higher at the 95th percentile (P95th) than at the 90th percentile(P90th), and the RR values for both reached their maximum at 10-day lag (P95th RR = 1.880 (1.261-2.804), P90th RR = 1.787 (1.244-2.569)), the hazardous effect of extreme low temperatures on HFMD is faster than that of extreme high temperatures. The cumulative effect of extreme low wind speeds reached its maximum at 14-day lag (P95th RR = 1.702 (1.389-2.085), P90th RR = 1.498(1.283-1.750)). The cumulative effect of PM2.5 concentration at the P90th was largest at 14-day lag (RR = 1.637 (1.069-2.506)), and the cumulative effect at the P95th was largest at 10-day lag (RR = 1.569 (1.021-2.411)). High SO2 concentration at the P95th at 14-day lag was associated with higher risk for HFMD (RR: 1.425 (1.001-2.030)). Our findings suggest that high temperature, low wind speed, and high concentrations of PM2.5 and SO2 are associated with an increased risk of HFMD. This study not only adds insights to the understanding of the impact of extreme meteorological conditions and high levels of air pollutants on HFMD incidence but also holds practical significance for the development and enhancement of an early warning system for HFMD.

Assessing the impact of air pollution on short-term hospital visits for respiratory diseases in Lampang, a city heavily affected by biomass burning in Mainland Southeast Asia: Sex and age considerations

Mainland Southeast Asia has long been confronted with severe air pollution issues caused by open biomass burning. The analysis is conducted from January 2014 to December 2017 in Lampang located in central of Mainland Southeast Asia. The analysis of air pollution revealed significant exceedances of the PM10 (32%) and O3 (29%) air quality guidelines set by the World Health Organization. The major source of PM10 in Lampang is biomass burning, accounting for 97%, and it also experiences a high respiratory disease incidence of 7,276.61 per 100,000 population. A time-series analysis was conducted using generalized linear models based on Poisson regression, considering various lag times, to assess the relative risk (RR) among all age groups (0–14 years, 15–64 years, ≥65 years) and genders. A 10 μg/m3 increase in PM10 and O3 was associated with statistically significant percentage increases at lag 0. Specifically, there was a 0.65% (95% CI: 0.38–0.92) increase in respiratory diseases for PM10 and a 0.72% (95% CI: 0.43–1.01) increase for O3. The impact of PM10 and O3 significantly affects respiratory diseases in children, adults, and the elderly. Elderly males and females both experience the highest impact of PM10, whereas the greatest impact of O3 is observed in elderly males and adult females. Biomass burning is a major source that should be controlled to reduce the health risk of people. Protecting vulnerable groups like adult females, elderly males, and elderly females from high air pollution concentrations is crucial, especially with many countries experiencing an aging demographic shift.

Impact of air pollution: tourists’ decision making behaviour during rural tourism

In recent years, the increasingly severe air pollution has not only posed a threat to residents’ health but also had a significant influence on tourists’ travel decision making behaviours. This study utilised empirical dynamic model–long short-term memory model to predict air pollutant concentrations in Xidi Village, China, and investigated their impact on tourists’ travel decisions. According to the results, there is a negative correlation between air quality and air quality index (AQI). The lowest AQIs were recorded in May and August 2022, with visitor numbers reaching 12 305 and 11 705, respectively. During the period from May to October, except for ozone (O3), which reached a maximum concentration of 157 μg/m3, all other pollutant concentrations remained at low levels. According to the predictions of the model, Xidi Village often experiences high concentrations of air pollutants during the spring and winter seasons, leading to hazy weather. This information provides accurate air quality data for tourists, helping them avoid periods of severe pollution at their travel destinations and reducing travel risks.

Quantifying the indirect effects of different air pollutants on crop yields in North China Plain

High concentrations of air pollutants could affect crop yield directly via influencing crop physiology and indirectly via regulating climate conditions. How multiple air pollutants affect crop yields directly and indirectly remains elusive in the North China Plain (NCP), which is the hotspot of air pollution and crop production. Here, we construct data-driven models to quantify the indirect effects of four major air pollutants on the yields of winter wheat and summer maize through modulating climate variations in the NCP during 2005–2020. Our results show that wheat has a greater negative sensitivity to absorbing aerosol optical thickness (AAOD), ozone concentration (O3), sulfur dioxide concentration (SO2) and nitrogen dioxide concentration (NO2) than maize. The indirect effects of AAOD, O3 and SO2 in November and O3 in April control wheat yield variation, while the indirect effects of AAOD and O3 in June, O3 and SO2 in July, O3 and NO2 in August, and O3 in September dominate maize yield variation. Our results emphasize the indirect effects of air pollutants on crop yield via regulating climate variations, which has great implications for improving our understanding of air pollution-climate-crop interactions and guiding targeted adaptation and mitigation efforts.

Solving the mysteries of Lahore smog: the fifth season in the country

South Asian smog is an annually recurring air pollution event that is characterized by high concentrations of air pollutants, low visibility, and severe socio-economic disruptions. It is most frequently observed across the north-western parts of the Indo-Gangetic Plains (IGP). Since 2016, it has become so frequent and pervasive that they are colloquially referred to as “the fifth season” in the region. During this season populations residing in this area including cities such as Lahore, Amritsar, Faisalabad, Multan, Delhi etc. are exposed to hazardous levels of air pollution. This study attempts to understand the reasons for the recent increase in the intensity and frequency of intense air pollution episodes by utilizing ground-based and satellite observations. Time-series analysis, seasonal and annual variations in PM2.5 and AOD were carried out. Satellite data of UVAAI, CO, and fire count were used to determine the fire incidences and aerosol characterization. The results indicate that during the last decade, there has been an increase in air pollution sources while crop residue burning, and motor vehicles have greatly contributed to the increased frequency and intensity of such events. The meteorological and topographical data analysis revealed that the IGP provides ample cloud-condensation nuclei and optimum conditions for the accumulations of pollutants, especially in the post-monsoon and winter periods. The Mann-Kendall test was performed to confirm the annual and seasonal trends of PM2.5. The major cities of South Asia such as Lahore, Delhi, Kathmandu, and Dhaka have recently shown a decreasing trend with respect to annual AOD. However, an increase has been observed for the period of post-monsoon especially for cities of Lahore and Delhi. To distinguish potential sources of air pollutants during extreme smog episodes in the region, Analytical Hierarchy Process (AHP) was conducted to estimate the most contributing factors to the annual smog episodes. According to the data, the transboundary pollution resulting from open-field agriculture fires has been assigned moderate importance over vehicular emissions. A HYSPLIT trajectory model coupled with ground observations and satellite data shows that the agricultural fires do have a profound impact on the air quality of the region. It highlights the importance of transboundary pollution and cooperation among cities, regions, and countries across the shared airshed of the Indo-Gangetic Plains.

A seven-year-based characterization of aerosol light scattering properties at a rural central European site

Our study investigates the temporal variability of aerosol light scattering properties measured at three wavelengths (total scattering coefficient, backscattering coefficient, Ångström scattering exponent, hemispheric backscattering ratio and asymmetry parameter) at the rural background site of the National Atmospheric Observatory Košetice over a period of over seven years (2012–2019). The influence of fog and cloudiness on aerosol light scattering properties (ASP), together with their comparison to particle number size distribution was also investigated. The overall medians of total scattering (σsp) and backscattering coefficient (σbsp), hemispheric backscattering ratio (b) and asymmetry parameter (g) measured at 550 nm and Ångström scattering exponent (SAE_450/700) were 35.20 Mm−1, 5.07 Mm−1, 0.14 and 0.57 and 1.82, respectively. σsp and g decreased by 2.05 Mm−1/year, and 0.009/year, respectively, whereas b increased by 0.004/year. The selected aerosol properties were strongly correlated with particle number, mass, area and volume concentrations in the 200–800 nm mode. A decrease in SAE_450/700 implies a shift towards larger particle sizes, and evolutions in b and g suggest a higher backscattering portion to total scattering. The highest σsp and σbsp levels were observed in the cold seasons together with higher concentrations of air pollutants (carbonaceous aerosol, SO2 and NOx). This could be explained by enhanced emissions from human activities such as domestic heating combined with the higher stability of the atmosphere (poor atmospheric dispersion). In the summer, decreases in particle size and higher rates of backscatter fraction were attributed to secondary organic aerosol (SOA) formation. The accumulation mode showed the strongest aerosol scattering potential, with SAE_450/700 values < 2. Aerosol light scattering was significantly higher during overcast and foggy days compared to fine, cloudy, partly cloudy and no-fog days, possibly due to the particle hygroscopic growth under high relative humidity (shift of particle size towards larger sizes), which in turn can lead to a lower aerosol backscattering fraction. Source identification linked the changes in ASP to the synoptic situation over Europe rather than to specific sources of pollution.

Comorbid asthma is associated with rhinitis severity in children exposed to air pollutants.

The impact of asthma on the severity of rhinitis when children with allergic rhinitis (AR) are exposed to air pollutants has not been studied. Children with AR (65 with asthma, 208 without asthma), aged 6-13 years, were recruited from a hospital in Taichung, Taiwan, between 2007 and 2011. Correlations between Pediatric-Rhinoconjunctivitis-Quality-of-Life score, nasal peak expiratory flow, and air pollutants were compared. With the same age, research time, and form the same city, children with AR (660 with asthma, 3174 without asthma) were selected from a database. Correlations between clinical visit times for AR and air pollutants were compared. In male children with AR and asthma, both clinical and database studies revealed a correlation between higher rhinitis discomfort (quality-of-life score), higher visit times for AR, and higher PM10, PM2.5, NO2, NMHC concentrations. Correlations between higher nasal inflammation/obstruction (lower expiratory flow) and higher air pollutant concentrations were observed in male children with AR and asthma. In children with AR, comorbid asthma was associated with increased rhinitis severity when they were exposed to air pollutants, and the association was only noted in males. Increased nasal obstruction/inflammation from exposure to air pollutants may be the mechanisms underlying this association. The influence of asthma on the severity of rhinitis when children with allergic rhinitis (AR) are exposed to air pollutants has not been studied. In children with AR, the correlation between higher rhinitis discomfort, higher number of clinical visits for AR, and higher PM10, PM2.5, NO2, NMHC concentrations were only noted in those who also had asthma. The correlation was only noted in male. Comorbid asthma was associated with higher rhinitis severity when children with AR are exposed to air pollutants The association was only noted in male.

A DYNAMIC SPATIAL FILTERING APPROACH TO MITIGATE UNDERESTIMATION BIAS IN FIELD CALIBRATED LOW-COST SENSOR AIR POLLUTION DATA.

Low-cost air pollution sensors, offering hyper-local characterization of pollutant concentrations, are becoming increasingly prevalent in environmental and public health research. However, low-cost air pollution data can be noisy, biased by environmental conditions, and usually need to be field-calibrated by collocating low-cost sensors with reference-grade instruments. We show, theoretically and empirically, that the common procedure of regression-based calibration using collocated data systematically underestimates high air pollution concentrations, which are critical to diagnose from a health perspective. Current calibration practices also often fail to utilize the spatial correlation in pollutant concentrations. We propose a novel spatial filtering approach to collocation-based calibration of low-cost networks that mitigates the underestimation issue by using an inverse regression. The inverse-regression also allows for incorporating spatial correlations by a second-stage model for the true pollutant concentrations using a conditional Gaussian Process. Our approach works with one or more collocated sites in the network and is dynamic, leveraging spatial correlation with the latest available reference data. Through extensive simulations, we demonstrate how the spatial filtering substantially improves estimation of pollutant concentrations, and measures peak concentrations with greater accuracy. We apply the methodology for calibration of a low-cost PM2.5 network in Baltimore, Maryland, and diagnose air pollution peaks that are missed by the regression-calibration.

Exposure to Multiple Air Pollutants and the Risk of Fractures: A Large Prospective Population-Based Study.

Atmospheric chemistry studies suggest air pollution impedes ultraviolet B photons and thus reduces cutaneous vitamin D3 synthesis. Biological evidence shows that inhaled pollutants disrupt circulating 25-hydroxyvitamin D (25[OH]D) metabolism and ultimately impact bone health. The hypothesis is that higher air pollution concentrations are associated with a higher risk of fractures, mediated by lower circulating 25(OH)D. The study included participants of the UK Biobank who were free of fracture history at enrollment (2006 to 2010) and analyzed their environmental exposure data (2007 to 2010). Air pollution measurements included the annual averages of air particulate matter (PM2.5 , PM2.5-10 , and PM10 ), nitrogen oxides (NO2 and NOx ), and a composite air pollution score. Multivariable Cox proportional hazard models were used to assess the associations of the individual pollutants and the score with fracture risks. Mediation analyses were conducted to assess the underlying role of serum 25(OH)D in such associations. Among 446,395 participants with a median of 8-year follow-up, 12,288 incident fractures were documented. Participants living in places with the highest quintile of air pollution score had a 15.3% increased risk of fractures (hazard ratio [95%CI]: 1.15[1.09,1.22]) compared to those in the lowest, and 5.49% of this association was mediated through serum 25(OH)D (pmediation < 0.05). Pollutant-specific hazard of top-to-bottom quintiles was 16% for PM2.5 , 4% for PM2.5-10 , 5% for PM10 , 20% for NO2 , and 17% for NOx , with a 4% to 6% mediation effect of serum 25(OH)D concentrations. The associations of the air pollution score with fracture risks were weaker among female participants, those who drank less alcohol, and consumed more fresh fruit than their counterparts (pinteraction < 0.05). © 2023 American Society for Bone and Mineral Research (ASBMR).

Towards healthy and energy-efficient buildings in the context of Egypt: Modelling demand-controlled ventilation to improve the indoor air quality in a generic office space in Cairo

Cairo is characterised by high concentrations of ambient air pollutants, especially air particulate matter of diameter less than 2.5 micrometre (PM2.5). Many studies have emphasized the impact of PM2.5 on people’s health and wellbeing including a World Bank report that has attributed 12% of the total annual deaths in Cairo to the exposure to ambient PM2.5. On one hand. improving the energy efficiency of buildings may involve implementing energy efficiency measures that aim to achieve indoor thermal comfort by maximizing the use of natural ventilation and minimizing mechanical air-conditioning. However, while natural ventilation can help reduce CO2 levels, it can also potentially lead to an increase in indoor PM2.5 levels. This study aims to investigate the impact of multiple air filtration scenarios on the energy consumption and the indoor air quality for a shoebox model that aims to represent generic offices Cairo. The study uses EnergyPlus simulations that leverage an Energy Management System script to model the demand-controlled ventilation, apply air filters when required, and simulate the increase in energy use due to the relevant pressure drops in the air system. The results for the scenarios investigated in the study highlighted that air filters can reduce the average indoor PM2.5 levels by nearly 40% during occupancy hours while causing an estimated increase of around 2-7% in the total operational energy. Given data and assumptions relevant to the study context, it was found that filtering the recirculated air while minimizing the introduction outdoor fresh air can be sufficient to minimize indoor PM2.5 levels.

Spatiotemporal association between air pollution and stroke mortality in South Korea

BackgroundAir pollutant concentrations in South Korea vary greatly by region and time. To assess temporal and spatial associations of stroke subtypes with long-term air pollution effects on stroke mortality, we studied ischemic stroke (IS), intracerebral hemorrhage (ICH), and subarachnoid hemorrhage (SAH). MethodsThis was an observational study conducted in South Korea from 2001–2018. Concentrations of carbon monoxide (CO), nitrogen dioxide (NO2), sulfur dioxide (SO2), and particulate matter ≤10 µm in diameter (PM10) were determined from 332 stations. Average air pollutant concentrations in each district were determined by distance-weighted linear interpolation. The nationwide stroke mortality rates in 249 districts were obtained from the Korean Statistical Information Service. Time intervals were divided into three consecutive 6-year periods: 2001–2006, 2007–2012, and 2013–2018. ResultsThe concentrations of air pollutants gradually decreased from 2001–2018, along with decreases in IS and ICH mortality rates. However, mortality rates associated with SAH remained constant. From 2001–2006, NO2 (adjusted odds ratio [aOR]:1.13, 95% confidence interval: 1.08–1.19), SO2 (aOR: 1.10, 1.07–1.13), and PM10 (aOR: 1.12, 1.06–1.18) concentrations were associated with IS mortality, and SO2 (aOR: 1.07, 1.02–1.13) and PM10 (aOR:1.11,1.06–1.22) concentrations were associated with SAH-associated mortality. Air pollution was no longer associated with stroke mortality from 2007 onward, as the air pollution concentration continued to decline. Throughout the entire 18-year period, ICH-associated mortality was not associated with air pollution. ConclusionsConsidering temporal and spatial trends, high concentrations of air pollutants were most likely to be associated with IS mortality. Our results strengthen the existing evidence of the deleterious effects of air pollution on IS mortality.

Relative contributions of ambient air and internal sources to multiple air pollutants in public transportation modes

Commuters are often exposed to relatively high air pollutant concentrations in public transport microenvironments (TMEs) because of their proximity to emission sources. Previous studies have mainly focused on assessing the concentrations of air pollutants in TMEs, but few studies have distinguished between the contributions of ambient air and internal sources to the exposure of commuters to air pollutants. The main objective of this study was to quantify the contributions of ambient air and internal sources to the measured particulate matter and gaseous pollutant concentrations in selected TMEs in Hong Kong, a high-rise, high-density city in Asia. A sampling campaign was conducted to measure air pollutant concentrations in TMEs in Hong Kong in July and November 2018 using portable air quality monitors. We measured the concentrations of each pollutant in different TMEs and quantified the infiltration of particulate matter into these TMEs. The double-decker bus had the lowest particulate matter concentrations (mean PM1, PM2.5, and PM10 concentrations of 5.1, 9.5, and 13 μg/m3, respectively), but higher concentrations of CO (0.9 ppm), NO (422 ppb), and NO2 (100 ppb). For all the TMEs, about half of the PM2.5 were PM1 particles. The Mass Transit Railway (MTR) subway system had a PM2.5/PM10 ratio of about 0.90, whereas the PM2.5/PM10 ratio was about 0.60–0.70 for the other TMEs. The MTR had infiltration factor estimates <0.4 for particulate matter, lower than those of the double-decker bus and minibus. The MTR had the highest contribution from internal sources (mean PM1, PM2.5, and PM10 concentrations of 4.6, 13.4, and 15.8 μg/m3, respectively). This study will help citizens to plan commuting routes to reduce their exposure to air pollution and help policy-makers to prioritize effective exposure reduction strategies.

Early life PM2.5 exposure, childhood cognitive ability and mortality between age 11 and 86: A record-linkage life-course study from Scotland

BackgroundLiving in areas with high air pollution concentrations is associated with all-cause and cause-specific mortality. Exposure in sensitive developmental periods might be long-lasting but studies with very long follow-up are rare, and mediating pathways between early life exposure and life-course mortality are not fully understood. MethodsData were drawn from the Scottish Longitudinal Study Birth Cohort of 1936, a representative record-linkage study comprising 5% of the Scottish population born in 1936. Participants had valid age 11 cognitive ability test scores along with linked mortality data until age 86. Fine particle (PM2.5) concentrations estimated with the EMEP4UK atmospheric chemistry transport model were linked to participants’ residential address derived from the National Identity Register in 1939 (age 3). Confounder-adjusted Cox regression estimated associations between PM2.5 and mortality; regression-based causal mediation analysis explored mediation through childhood cognitive ability. ResultsThe final sample consisted of 2734 individuals with 1608 deaths registered during the 1,833,517 person-months at risk follow-up time. Higher early life PM2.5 exposure increased the risk of all-cause mortality (HR = 1.03, 95% CI: 1.01–1.04 per 10 μg m−3 increment), associations were stronger for mortality between age 65 and 86. PM2.5 increased the risk of cancer-related mortality (HR = 1.05, 95% CI: 1.02–1.08), especially for lung cancer among females (HR = 1.11, 95% CI: 1.02–1.21), but not for cardiovascular and respiratory diseases. Higher PM2.5 in early life (≥50 μg m−3) was associated with lower childhood cognitive ability, which, in turn, increased the risk of all-cause mortality and mediated 25% of the total associations. ConclusionsIn our life-course study with 75-year of continuous mortality records, we found that exposure to air pollution in early life was associated with higher mortality in late adulthood, and that childhood cognitive ability partly mediated this relationship. Findings suggest that past air pollution concentrations will likely impact health and longevity for decades to come.

Green strategies for improving urban microclimate and air quality: A case study of an Italian industrial district and facility

Densely built areas are affected by higher air-pollutant concentrations, representing a significant risk to public health. At the same time, urban settlements have a remarkable environmental impact: cities are responsible for 70% of annual carbon emissions while buildings account for 37% of global energy and process emissions. Moreover, people living in urban areas are frequently exposed to extreme micro-climate conditions caused by the urban heat island effect, related to increased external air temperature and peculiarities of the built environment. Given this framework and considering the Sustainable Development Goals, it is necessary to point out some effective and strategical mitigation measures to ameliorate micro-climate conditions, reduce pollutants concentration and enhance building performance. This paper investigates the potential advantages of green roofs as retrofitting solutions and tree planting on several micro-climate parameters and particulate matter concentration, considering an industrial district located in Italy and using ENVI-met software. The influence of the extensive green roof on energy performance is further investigated at the building level recurring to Design Builder energy models. Results showed that an extensive green roof could reduce external air temperature by up to 1.5 °C, outer surface temperature by up to 15 °C and wind speed by 50% at roof level compared to current state conditions. The application of the green roof let also to achieve energy savings of 15% for both the summer and winter seasons. Focusing on the effect on particulate matter, intensive green roof solutions proved to be more efficient in capturing air pollutants.