Air Quality Guidelines Research Articles

Cognitive Benefits of Reducing Indoor Particulate Matter Exposure During Sleep: New Evidence from a Randomized, Double-blind Crossover Trial.

There is increasing evidence that particulate matter (PM) pollution may adversely impact cognition. Considering that sleep is critical for cognitive health and occupies about one-third of human life, understanding the cognitive effects of indoor PM exposure during sleep and the potential cognitive benefits of reducing such exposure is crucial, yet currently unknown. This randomized, double-blind crossover intervention trial was conducted among 80 college students with real and sham PM filtration in their dormitories. Real-time indoor PM levels and nocturnal sleep parameters were monitored, followed by quantification of serum neurotransmitter metabolites and cognitive assessments in the mornings. We found that PM exposure during sleep, particularly PM1 and PM2.5, affected immediate and delayed memory, executive function, and global cognition. Reducing PM exposure during sleep resulted in improvements in multiple cognitive domains, with a 0.21 (95% CI: 0.05, 0.36) increase in global cognitive z-score, in which increased sleep oxygen saturation (SpO2) and alterations in dopamine metabolism and histidine metabolism played important roles. Notably, even when indoor PM2.5 levels were below the WHO air quality guidelines, further reducing PM exposure could still improve sleep SpO2 and neurotransmitter metabolism. This study provides a promising strategy to mitigate indoor PM-induced cognitive impairment.

Ambient air pollution, urban green space and childhood overweight and obesity: A health impact assessment for Barcelona, Spain

BackgroundThe burden of childhood overweight and obesity attributable to ambient air pollution and a lack of urban green spaces (UGS) remains unknown. This study aimed to estimate the attributable cases of childhood overweight and obesity due to air pollution and insufficient UGS exposure in Barcelona, Spain. MethodsWe applied a quantitative health impact assessment approach. We collected childhood overweight and obesity prevalence levels and exposure data from 69 spatial basic health zones in Barcelona. We estimated particulate matter (PM2.5) and nitrogen dioxide (NO2) levels using land use regression models, normalized difference vegetation index (NDVI) levels using remote sensing and percentage of green area (%GA) using land use. We estimated relative risks, population attributable fractions, and preventable overweight/obesity cases in children under following scenarios: Compliance of World Health Organization (WHO) air quality guidelines (AQGs) for (1) PM2.5 and (2) NO2; achieving (3) city-target NDVI levels and (4) 25% green area (%GA) recommendations. The analyses were stratified by socioeconomic deprivation index (in quintiles). Uncertainty was quantified using Monte Carlos simulations. ResultsCompliance of WHO AQGs could prevent 0.4% [253 (95%CI, −604; 1086)] and 4.2% [3000 (95%CI, 1009; 4943)] of childhood overweight/obesity cases due to excess PM2.5 and NO2 levels in Barcelona, respectively. Compliance of NDVI and %GA targeted levels could prevent 6% [4094 (95%CI, 1698; 6379)] and 10% [6853 (95%CI, 1440; 12779)] of childhood overweight/obesity cases respectively. The preventable burdens of childhood overweight/obesity cases were slightly higher in middle-class socioeconomic areas due to the higher adverse exposure levels at baseline (high air pollution, less UGS). DiscussionCompliance with WHO AQGs and achieving UGS targets can reduce childhood overweight and obesity levels in Barcelona, and potentially in other locations as well. This underscores the need for policies that foster healthier urban environments of high environmental quality in order to protect child health.

Reconstruction of PM2.5 Concentrations in East Asia on the Basis of a Wide–Deep Ensemble Machine Learning Framework and Estimation of the Potential Exposure Level from 1981 to 2020

Satellite observations are widely used to estimate the concentrations of surface air pollutants, but the temporal coverage of these datasets is relatively short. To overcome this limitation, we propose a wide–deep ensemble machine learning framework to reconstruct the fine particulate matter (PM2.5) dataset of east Asia (EA) over the past four decades (1981–2020). The results indicate that the framework effectively leveraged the advantages of satellite observations (higher accuracy) and model-based estimations (longer temporal coverage) of surface air pollutants. The reconstructed PM2.5 concentrations agreed well with the ground measurements, with coefficient of determination (R2) and root-mean-square error (RMSE) values of 0.99 and 1.38 μg·m−3, respectively, which outperformed the satellite-based PM2.5 estimates. As more ground measurements were incorporated into the model for training, the average RMSE in Japan and the Korean Peninsula decreased to 0.83 and 1.50 μg·m−3, respectively. Simultaneously, on the basis of the reconstructed datasets, we investigated the exposure level to PM2.5 in EA from 1981 to 2020. Since 2000, the increase in anthropogenic emissions has substantially worsened the air quality in EA, and nearly 50% of the population resided in areas where the annual average PM2.5 concentrations exceeded 50 μg·m−3 from 2009–2010. Despite the implementation of various mitigation strategies by local authorities to lower the ambient PM2.5 concentrations, the entire exposure level in EA is still implausible to meet the WHO air quality guidelines. In addition, population aging and climate change have the potential to increase PM2.5 exposure risk in the future. For policy-makers in EA, it is essential to consider the effects of these factors and develop more effective mitigation strategies that aim to lessen the health impact associated with PM2.5 exposure.

Clearing the Air to Address Pollution's Cardiovascular Health Crisis.

Air pollution is a critical global health issue that significantly impacts cardiovascular health. The air pollutant PM2.5 (particulate matter with a diameter of 2.5 micrometres or less) has been positioned as a leading environmental risk factor for morbidity and mortality, especially from cardiovascular diseases (CVDs). Using data from the World Health Organization (WHO), Global Health Observatory, and the United Nations Environment Programme, we explored global trends in air pollution, with a focus on PM2.5 levels, the implications for cardiovascular health, and the policy measures aimed at reducing their impact. Despite progress in reducing pollution levels in high-income countries, global trends show a limited annual reduction in PM2.5 concentration. The analysis highlights disparities between regions, with low- and middle-income countries bearing the brunt of air pollution-related CVDs. In 2019 alone, ambient air pollution was responsible for approximately 4.2 million deaths worldwide. Of these, 70% were caused by CVDs, with approximately 1.9 million deaths from ischemic heart disease and 900,000 deaths from stroke. Policy gaps remain a challenge, with many countries lacking adequate legally binding air quality standards. We recommend the adoption of WHO air quality guidelines, enhanced monitoring of air pollution levels, and increased investment in interdisciplinary research to understand the full scope of air pollution's effects on cardiovascular health. Addressing the global cardiovascular crisis linked to air pollution will require coordinated efforts from policymakers, healthcare systems, and global health organisations.

Assessment of Mortality Attributable to Air Pollution in the Urban Area of Pisa (Central Italy) Characterized by Multi-Source Exposures

Air pollution is one of the main risk factors for human health. The aim of this study was to provide an Integrated Environmental and Health Impact Assessment (IEHIA) tool to estimate the impacts on both environment and human health in Pisa municipality (central Italy). For each pollutant considered (PM2.5, PM10, and NO2), both Population-Weighted Exposure (PWE) and Attributable Deaths (ADs) were calculated considering the difference between the PWE and the latest air quality guidelines suggested by the World Health Organization. The PWEs were 16.1 µg/m3, 24.9 µg/m3, and 25.9 µg/m3 for PM2.5, PM10, and NO2, respectively. The ADs from natural causes due to exposure to PM2.5, PM10, and NO2 were 63, 29, and 51, respectively. The AD distribution was mainly concentrated in urban areas for particulate matter and in urban and suburban areas for NO2. The results highlighted significantly higher levels of air pollution than the reference levels, with a percentage of ADs from natural causes of approximately 6% of the total mortality in Pisa. IEHIA offers support for environmental and health policies and territorial planning. The authors recommend the adoption of prevention measures aimed at mitigating air pollution in critical areas, with a consequent reduction in avoidable mortality.

Multi-Domain Environmental Quality of Indoor Mixed-Use Open Spaces and Insights into Healthy Living—A Quarantine Hotel Case Study

In the post-pandemic context, data-driven design interventions that can endow architectural spaces with mixed-use and open characteristics that are adaptable and environmentally resilient are increasingly important. Ubiquitous semi-public architecture, such as hotel buildings, plays a crucial role in public health emergencies. Many hotels adopt mixed-use and open room spatial layouts, integrating diverse daily functions into a single tiny space, fostering flexible utilization and micro-scale space sharing; however, these also introduce potential health risks. This study offers a comprehensive evaluation of the indoor environmental quality (IEQ) of a hotel room space and discusses feasible intervention strategies for healthier renovation and rehabilitation. Taking a hotel in Shenzhen as a case, a multi-domain environmental assessment was conducted during the COVID-19 quarantine period in the summer of 2022. The study examines the health risks inherent in the hotel’s guest room and the varying patterns of IEQ factors across the hotel’s domains, including volatile organic compound concentrations, physical environmental parameters, and heat stress indices. The results illustrate diverse change trends in the chemical, physical, and heat stress factors present in the tested quarantined hotel room space throughout a typical summer day. Although most of the examined environmental factors meet local and global standards, some problems draw attention. In particular, the PM2.5 concentration was generally observed to be above the World Health Organization (WHO) air quality guideline (AQG) standards, and the interior lighting did not meet required standards most of the time. Moreover, correlation and multiple regression analyses uncover significant influence by physical environmental conditions on the concentrations of chemical pollutants in the hotel room. The study preliminarily identifies that higher relative humidity could lead to a lower concentration of CO2 while a higher PM2.5 concentration. Wet bulb globe temperature (WBGT) was observed to positively affect CO2 concentration. Further, the results suggest that even with relatively rigorous initial adjustment and re-renovation, multi-domain environmental quality in air-conditioned quarantine hotel rooms should be monitored and ameliorated from time to time. Overall, this study offers a scientific foundation for healthier upgrades of existing hotel buildings as well as provides insights into achieving environmental resilience in newly constructed hotel buildings for the post-pandemic era.

Benefits of hypothetical air pollution reduction interventions on NCDs in Belgium

Abstract Background The adverse health impact of air pollution on non-communicable diseases (NCDs) is well documented, yet methodological tools for assessing the potential health benefits of interventions are lacking. This study uses a parametric g-computation approach to evaluate the impact of hypothetical interventions targeting long-term air pollution exposure on reducing NCDs prevalence in Belgium, using data from three national Health Interview Surveys (BHIS 2008-2013-2018). Methods BHIS data (n = 27,536) were linked to environmental data at participants’ residential addresses. A g-computation approach was used to calculate the potential impact fractions of air quality interventions on several NCDs. Regression models were adjusted for socio-economic, environmental and lifestyle factors. The scenarios involved reducing individual long-term air pollution exposure to WHO air quality guideline levels, followed by investigating dose-response functions through various percentage reductions in air pollution exposure. Results Significant associations were found between air pollution and asthma, stroke, and multimorbidity. Adhering to WHO air quality guidelines would substantially reduce stroke risk in Belgium by 0.87% (95% CI:0.38; 1.35) for PM2.5 and 0.32% (95% CI:-0.05; 0.70) for NO2, preventing 63% and 22% of cases, respectively. For asthma, risk reduction was 1.43% (95% CI:-0.53; 3.4) for PM2.5 and 0.83% (95% CI: 0.01; 1.63) for NO2, preventing 27% and 16% of cases, respectively. For multimorbidity, risk reduction was 3.20 % (95% CI: -1.75; 8.16) for PM2.5 and 0.43% (95% CI:-2.03; 2.90) for NO2, preventing 7% and 0.4% of cases, respectively. Results revealed a clear dose-response association between air pollution reduction and the prevalence of stroke, asthma, and multimorbidity in Belgium. Conclusions This study demonstrates that air pollution reduction interventions could effectively decrease the prevalence of asthma, stroke, and multimorbidity in Belgium. Key messages • Air pollution reduction interventions could effectively decrease the prevalence of asthma, stroke, and multimorbidity in Belgium. • The g-computation approach to assess PIF of interventions represents a straightforward approach for drawing causal inferences from observational data.

Burden and economic impact of PM2.5 exposure on Acute Myocardial Infarction in Portugal, 2011-2021

Abstract Background Air pollution, specifically particulate matter with a diameter of 2.5 micrometers (PM2.5), is the primary environmental health risk in Europe. Exposure to PM2.5 increases the risk of cardiovascular diseases, including AMI, resulting in high direct costs associated with in-patient treatment. This study aims to estimate the avoidable and attributable disease and economic burden of AMI due to ambient PM2.5 exposure in Portugal between 2011 and 2021. Methods National databases were used to assess the annual number of hospitalisations and deaths due to AMI between 2011 and 2021. The annual mean costs were calculated using a direct cost analysis (bottom-up micro-costing) to assess the direct economic burden of AMI. In turn, these cases and associated costs were multiplied by the respective morbidity and mortality population attributable fraction (PAF) to estimate the number of hospital admissions and deaths, and their associated costs attributable to ambient PM2.5 exposure. For 2019 and 2021, an alternative scenario of exposure was considered (2021 WHO Air Quality Guidelines), and the avoidable morbidity and mortality costs were determined using the potential impact fraction (PIF). Results Between 2011 and 2021, there were 130,447 hospitalisations and 47,968 deaths due to AMI, with 4.79% and 28.90%, respectively, attributable to ambient PM2.5 exposure. This translates to a direct economic burden of morbidity of more than 44 million euros and mortality of almost 195 million euros. If the proposed scenario guidelines were met, 279 cases and 448 deaths would have been avoided in 2019, resulting in a savings of almost 9.7 million euros. In 2021, 93 cases and 355 deaths would have been avoided, with approximately 4 million euros saved. Conclusions Exposure to ambient PM2.5 significantly contributes to AMI cases and deaths in Portugal, imposing a significant economic burden. These findings highlight the urgent need for measures to improve air quality. Key messages • PM2.5 pollution in Portugal drives AMI cases and fatalities, entailing significant economic costs. • Adhering to WHO air quality guidelines promises substantial reductions in AMI incidence and save millions annually in healthcare expenditure.

Estimating risk using the novel Particulate Matters years index (ePM-years index). A report from the nationwide EP-PARTICLES study

Abstract Background Air pollution is the largest environmental risk factor, especially for cardiovascular disease (CVD). In this study, we present an original concept of estimating the risk associated with exposure to air pollution: the Particulate Matters years index (ePM-years index). Objective To assess the predictive performance of the ePM-years index. Methods The ePM-years index is an indicator of hypothetical exposure to air pollution. It is estimated by multiplying the number of years spent in a given environment by the difference between the average annual PM2.5 concentration and the allowed level of pollution given by World Health Organization (WHO) guidelines (Figure 1). We collected data from 2011 to 2020 on mortality and hospitalizations from National Health Fund and the Central Statistical Office in Poland, respectively. For further analysis, we used an age-standardized rate (SR), established on the European Standard Population structure. The source of air pollution data was GEM-AQ air quality modeling system. All data were connected with TERYT codes, all analyses were conducted at the county level (LAU-1) and then aggregated to the voivodeship level (NUTS-2). Poisson regression models were used to estimate associations between CVD mortality, ePM-years, and population level social and health status. We also estimated the attributable fraction of CVD mortality due to air pollution using AirQ+ methodology from the WHO. Results We recorded 4,010,531 deaths including 1,669,464 (41.6%) deaths due to CVD with a median age of 78.16 (SD=12.54), and 53.4% of females (N=914,932). Current smokers amounted to 29.9% (23.4%-33.2%). The main causes of death were coronary artery disease [405,268 (24.3%)] and heart failure [376,592 (22.6%)]. The mean Gross Domestic Product (GDP) per capita was 9644 EUR (7517-12,048), and the mean yearly PM2.5 concentration was 23.3 (SD=6.3) μg/m3, corresponding with the mean ePM-index 35.8 (21.5-66.6) in analysed time. The SR for CVD mortality was 500.3 (min. 461.9 – max. 604.5), the SR hospitalization rates were as follows: hypertension 312 (299-342), diabetes 90 (78.9-95.9), and HF 557.9 (310-728.4). There was an association of the ePM-years index with CVD mortality (shown as increase per 10 ePM-years): In Model 1 adjusted for GDP, risk ratio (RR) 1.023 (95% confidence interval (CI): 1.002-1.044); in Model 2 adjusted for comorbidities, RR=1.025 (95%CI: 1.004-1.046); in Model 3 adjusted for GDP, comorbidities and weather conditions RR=1.027 (95%CI: 1.005-1.049). We estimated that 16.2% (N=324,460) [95%CI: 12.54% -17.9%] of CVD deaths were attributable to PM2.5 exposure, using the WHO's air quality guideline as the reference. Conclusions The ePM-years index may be used as a tool for risk stratification for patients and incorporated into CVD outcomes prediction models. The index can help with planning of appropriate primary and secondary prevention schemes related to long-term pollution exposure.

Opinion: How will advances in aerosol science inform our understanding of the health impacts of outdoor particulate pollution?

Abstract. Air pollution, characterized by high levels of particulate matter (PM), poses the greatest environmental threat to human health, causing an estimated 7 million deaths annually and accounting for 5 % of the global gross domestic product (GDP). While the health impacts of PM are influenced by the toxicity of its individual chemical constituents, the mortality burden of PM is solely based on its total mass concentration. This is because of a lack of large-scale, high-resolution data on PM chemical composition, needed for epidemiological assessments. Identifying which PM constituents are harmful to health has been the “holy grail” of atmospheric science since the landmark 1993 study on six US cities established a definitive link between PM and mortality. Ever since, atmospheric scientists have focused on understanding aerosol composition, emission sources, and formation pathways, while longitudinal epidemiological studies have required individual-level exposure data, employing land use regression models for the prediction of exposures at fine resolutions. In this opinion article, we argue that the time has come to shift the focus towards incorporating PM chemical composition into epidemiological health assessments, laying the foundation for the development of new regulatory metrics. This shift will enable the creation of targeted guidelines and subsequent regulations, prioritizing mitigation efforts against the most harmful anthropogenic emissions. Central to this shift is the availability of global, long-term, high-resolution data on PM chemical composition that are obtained through field observations and modelling outputs. In the article, we underscore key milestones within aerosol science that have been integral for advancing this foundational shift. Specifically, we examine emerging modelling tools for estimating exposure to individual PM components, present the type of ambient observations needed for model developments, identify key gaps in our fundamental understanding of emissions and their atmospheric transformation, and propose advancing cross-disciplinary collaboration between aerosol scientists and epidemiologists to understand the health impacts of individual PM components. We contend that aerosol science has now reached a pivotal moment in elucidating the differential health impacts of PM components, representing a first step towards their incorporation into air quality guidelines.

How ambient NO2 impacts the mortality burden of ischemic heart disease in Portugal (2011-2021)?

Abstract Background Air pollution is a major environmental risk to human health, contributing to premature death and disease. Nitrogen dioxide (NO2) is a pollutant of significant public health concern, associated with increased risks of all-cause mortality, particularly in cardiovascular and respiratory deaths. In 2021, NO2 exposure exceeding the World Health Organization Air Quality Guidelines resulted in 69,000 deaths in the European Union. This study aims to estimate the impact of ambient NO2 exposure on ischemic heart disease (IHD) in Portugal, from 2011 to 2021, estimated in years of life lost (YLL). Methods Data on ambient NO2 levels were obtained from the Portuguese Environment Agency’s online database QualAr. Only monitoring stations that reported valid data for at least 75% of the time in a year were considered. The number of IHD mortality cases from 2011 to 2021 was sourced from Statistics Portugal. The burden of IHD attributed to NO2 exposure was estimated in YLL for the Portuguese population aged 25 years and older, categorized by five-years age groups, regions of mainland Portugal and sex, using the population attributable fraction (PAF). Results Between 2011 and 2021, mainland Portugal experienced a declining trend in NO2 mean levels, with occasional fluctuations. Regarding IHD YLL attributed to NO2 exposure, the same trend was followed with an overall decline over the study period. In total, 94,843.75 (95% CI 53,408.35-134,766.17) IHD YLL were attributed to NO2 exposure, with an estimated number of IHD YLLs higher for males than for females. Conclusions These findings underscore the significant impact of air pollution on human health. Despite an overall reduction in YLL across mainland Portugal, persistent health effects emphasize the need to reduce NO2 concentrations, with informed decision-making being crucial to mitigate these impacts and protect public health. Key messages • Ambient NO2 exposure significantly impacts ischemic heart disease mortality in Portugal. • These estimates underscore the necessity of well-informed decision-making to safeguard public health.

Impacts of PM2.5 exposure near cement facilities on human health and years of life lost: A case study in Brazil

Cement factories significantly contribute to atmospheric pollution by generating fine particulate matter (PM2.5), which can potentially increase the mortality risk. The lack of information on the health impacts of PM2.5 pollution from cement operations in Brazil prompted this investigation. We used corrected PM2.5 measurements from low-cost sensors from March 2021 to October 2022 in Rio Branco do Sul, city in the southern region of the country and home to Latin America's largest cement plant, to assess exposure data. Disability-adjusted life years (DALY) method was applied to estimate the years of life lost (YLL) and cost estimate due to deaths from non-accidental causes, cardiovascular and respiratory diseases. The total YLL attributable to PM2.5 concentration was estimated by calculating the attributable fraction (AF) through relative risk. We also collected PM2.5 using a Harvard impactor to evaluate health risks from toxic metals components. During the study period, the analysis of chemical characterization of PM2.5 showed enrichment factors for most elements and the possible influence of the calcination process facilities on the PM2.5 levels. The mean concentration of PM2.5 exceeded the annual WHO air quality guideline (AQG) level, accounted for 3.5%, 4.7%, and 4.3% of total YLL from all causes, cardiovascular, and respiratory diseases, which corresponded to 0.23 (95% CI: 0.17–0.26), 0.06 (95% CI: 0.05–0.07) and 0.03 (95% CI: 0.01–0.06) years loss in life expectancy, respectively. An indirect health cost attributable to PM2.5 resulted in US$ 1.4 million, equivalent to about 3.5% of the total local annual health costs in Rio Branco do Sul, underscoring the significant financial burden of PM2.5 exposures. The greatest economic loss was found in the male age group of 40–69 years and among those with cardiovascular disease, rather than those with respiratory disease. Despite this, the carcinogenic and non-carcinogenic risks from inhalation of hazardous elements were within safe ranges. This work demonstrated PurpleAir's potential for air quality and public health applications. Our findings indicate health and economic benefits from reducing PM2.5 levels by adopting WHO air pollution standards. The results can guide policies toward delivering more effective health care.

Long-Term Exposure to Nitrogen Dioxide and Ozone and Mortality: Update of the WHO Air Quality Guidelines Systematic Review and Meta-Analysis

Long-Term Exposure to Nitrogen Dioxide and Ozone and Mortality: Update of the WHO Air Quality Guidelines Systematic Review and Meta-Analysis

Estimating the burden of diseases attributed to PM2.5 using the AirQ + software in Mashhad during 2016–2021

The study used the AirQ + software developed by the World Health Organization (WHO) to evaluate the health impacts associated with long-term exposure to PM2.5 in Mashhad, Iran. For this purpose, we analyzed the daily average concentrations of PM2.5 (with a diameter of 2.5 micrometers or less) registered by the air quality monitoring stations from 2016 to 2021. The levels of PM2.5 surpassed the Air Quality Guidelines (AQG) limit value of 5 µg/m3 (annual value) established by WHO. The findings revealed that the burden of mortality (from all-natural causes) at people above 30 years old associated with PM2.5 exposures was 2093 [95% confidence interval [CI]: 1627–2314] deaths in 2016 and 2750 [95% CI: 2139–3038] deaths in 2021. In general, the attributable mortality from specific causes of deaths (e.g., COPD (chronic obstructive pulmonary diseases), IHD (ischemic heart diseases) and stroke) in people above 25 years old increased between the years, but the mortality from lung cancer was stable at 46 [95% CI: 33–59] deaths in 2016 and 48 [95% CI: 34–61] deaths in 2021. The attributable mortality from ALRI (Acute Lower Respiratory Infection) in children below 5 years old increased between the years. We also found differences in mortality cases from IHD and stroke among the age groups and between the years 2016 and 2021. It was concluded that burden of disease methodologies are suitable tools for regional and national policymakers, who must take decisions to prevent and to control air pollution and to analyze the cost-effectiveness of interventions.

Performance analysis of particulate matter priority control algorithm for outdoor Air-Introduced ventilation Cleaner using prediction model

Growing concerns about health risks associated with poor indoor air quality, such as respiratory illnesses and allergies, highlight the need for improved management strategies. This study proposes a novel approach that combines an artificial neural network (ANN)-based indoor PM2.5 prediction model with a PM-priority control algorithm. This combined approach addresses the limitations of traditional methods by enabling proactive control measures based on predictive PM2.5 levels. With increased global attention to indoor air quality following the COVID-19 pandemic and the stringent 2021 WHO air quality guidelines, this research focuses on real-time management of PM2.5 and CO2 concentrations to maintain a healthy indoor environment. Two elementary school classrooms were equipped as living labs to analyze the performance of the developed system. The PM-priority control algorithm uses predictive data to dynamically regulate ventilation and air purification processes. Continuous retraining of the prediction model ensures adaptability to environmental changes by evaluating the algorithm’s efficiency in real time. The findings demonstrate that maintaining PM2.5 levels within comfortable ranges and reducing energy consumption can enhance the sustainability of buildings and improve the health and productivity of occupants. This approach provides a scalable solution applicable to schools and potentially other public buildings, emphasizing the preventive value of enhancing occupant health and productivity.

Role of meteorology and air pollution on fog conditions over Delhi during the peak winter 2024

Severe air pollution and foggy conditions during winter are persistent challenges, pose significant health hazards, and disrupt daily routines worldwide. In this study, we have investigated the conditions favoring the prolonged fog events in Delhi during January 2024 using observations, back trajectories, and reanalysis datasets. Analysis of visibility observations reveals that foggy (54, 121, 139, and 372 half-hours of very dense, dense, moderate, and shallow fog, respectively) conditions persisted in Delhi for 46 % of the time during the study period. The existence of 3–4 days of cold wave to severe cold wave conditions and the lack of passage of strong western disturbances across north and northwest India have also favored the prolonged fog formation. In addition, high relative humidity (>80 %), shallow boundary layer (216 m), stable weather conditions such as the absence of significant surface winds, the existence of cold wave to severe cold wave, temperature inversion (up to 4 °C), poor ventilation, and presence of high particulate matter (PM10: 298 μg/m3 and PM2.5: 182 μg/m3) facilitated the fog formation. Further, analyses reveal a spurt in daily particulate matter (PM10: 603 μg/m3 and PM2.5: 420 μg/m3; 13.4 and 28 times, respectively, exceeded the WHO air quality guideline levels) along with 4.5 h of zero visibility on 14th January. The analysis of particulate matter reveals the dominance of fine particles from nearby regions, which could have originated from the large-scale anthropogenic open biomass burning used for heating activities. The results derived from this study indicate the need for an accurate representation of the local anthropogenic emissions in the atmospheric models to improve the predictability of air quality and fog and provide insights into the need for their control, particularly during such extreme events.

Application of AERMOD dispersion model for assessment PM10 concentrations from mobile sources in Kuala Lumpur Metropolitan City, Malaysia.

Deterioration of air quality in Kuala Lumpur caused by mobile sources and traffic-related activities with interaction with climatic conditions and dispersion in the atmosphere. This study was focused on predicting the averaged 1-h concentration of particulate matter (PM10) that was emitted from private cars in Kuala Lumpur by applying the air dispersion model American Meteorological Society (AMS)/United States Environmental Protection Agency (EPA) Regulatory Model (AERMOD) in 2014. The AERMOD model indicates that private cars in Kuala Lumpur recorded 1-h concentration of PM10 below the Malaysian Ambient Air Quality Guidelines (RMAQG) in 2014. The highest concentration was 59.2µg/m3 in 2014 and mainly concentrated around the city center and highway networks. The highest concentrations are recorded in early morning and late at night, with the highest concentrations at 4 am and 2 am and 48.68µg/m3 and 38.42µg/m3, respectively. Late night to early morning is identified as the dominant time interval for pollutant dispersion. The findings demonstrated that air quality had a significant impact on the 1-h concentration of PM10 emitted from private cars in Kuala Lumpur.

An Improved Air Health Index Based on Short-Term Cardiovascular Effects in Tianjin, China.

To construct an improved air health index (AHI) based on cardiovascular years of life lost (YLL) in Tianjin and assess its utility. We derived the exposure-response coefficients from time-series models and calculated the excess YLL (EYLL) for simultaneous exposure to air pollution and non-optimum temperature. The AHI was developed using the EYLL at the WHO 2021 Air Quality Guideline annual mean values and optimum temperature as a reference. We assessed the validity of AHI by comparing the correlations and model fit between the AHI, air quality health index (AQHI), and air quality index (AQI) with cause-specific YLLs. Each inter quartile range (IQR) increase in AHI was associated with 256.31 (95%CI: 183.05, 329.57), 150.34 (95%CI: 108.23, 192.46), 90.41 (95%CI: 64.80, 116.02) and 60.80 (95%CI:33.41, 88.18) person-year increments for non-accidental, cardiovascular, ischaemic, and cerebrovascular YLL, respectively. The AHI, in contrast to the AQHI and AQI, showed the strongest correlations with the risks of cause-specific YLLs, both in the total population and subpopulations. The AHI based on cardiovascular YLL has a greater predictive ability for health risks.

A Systematic Review of Air Pollution Exposure and Brain Structure and Function during Development.

Air pollutants are known neurotoxicants. In this updated systematic review, we evaluate new evidence since our 2019 systematic review on the effect of outdoor air pollution exposure on childhood and adolescent brain structure and function as measured by magnetic resonance imaging (MRI). Using PubMed and Web of Science, we conducted an updated literature search and systematic review of articles published through March 2024, using key terms for air pollution and functional and/or structural MRI. Two raters independently screened all articles using Covidence and implemented the risk of bias instrument for systematic reviews informing the World Health Organization Global Air Quality Guidelines. We identified 222 relevant papers, and 14 new studies met our inclusion criteria. Including six studies from our 2019 review, the 20 publications to date include study populations from the United States, Netherlands, Spain, and United Kingdom. Studies investigated exposure periods spanning pregnancy through early adolescence, and estimated air pollutant exposure levels via personal monitoring, geospatial residential estimates, or school courtyard monitors. Brain MRI occurred when children were on average 6-14.7 years old; however, one study assessed newborns. Several MRI modalities were leveraged, including structural morphology, diffusion tensor imaging, restriction spectrum imaging, arterial spin labeling, magnetic resonance spectroscopy, as well as resting-state and task-based functional MRI. Air pollutants were associated with widespread brain differences, although the magnitude and direction of findings are largely inconsistent, making it difficult to draw strong conclusions. Prenatal and childhood exposure to outdoor air pollution is associated with structural and functional brain variations. Compared to our initial 2019 review, publications doubled-an increase that testifies to the importance of this public health issue. Further research is needed to clarify the effects of developmental timing, along with the downstream implications of outdoor air pollution exposure on children's cognitive and mental health.

Factors Affecting the Indoor Air Quality and Occupants’ Thermal Comfort in Urban Agglomeration Regions in the Hot and Humid Climate of Pakistan

The World Air Quality Index indicates that Pakistan ranks as the third most polluted country, regarding the average (Particulate Matter) PM2.5 concentration, which is 14.2 times higher than the World Health Organization’s annual air quality guideline. It is crucial to implement a program aimed at reducing PM2.5 levels in Pakistan’s urban areas. This review paper highlights the importance of indoor air pollution in urban regions such as Lahore, Faisalabad, Gujranwala, Rawalpindi, and Karachi, while also considering the effects of outdoor air temperature on occupants’ thermal comfort. The study aims to evaluate past methodological approaches to enhance indoor air quality in buildings. The main research question is to address whether there are statistical correlations between the PM2.5 and the operative air temperature and whether other indoor climatic variables have an impact on the thermal comfort assessment in densely built urban agglomeration regions in Pakistan. A systematic review analysis method was employed to investigate the effects of particulate matter (PM2.5), carbon oxides (COx), nitrogen oxides (NOx), sulfur oxides (SOx), and volatile organic compounds (VOCs) on residents’ health. The Preferred Reporting Items for Systematic Reviews and Meta Analyses (PRISMA) protocol guided the identification of key terms and the extraction of cited studies. The literature review incorporated a combination of descriptive research methods to inform the research context regarding both ambient and indoor air quality, providing a theoretical and methodological framework for understanding air pollution and its mitigation in various global contexts. The study found a marginally significant relationship between the PM2.5 operative air temperature and occupants’ overall temperature satisfaction, Ordinal Regression (OR) = 0.958 (95%—Confidence Interval (CI) [0.918, 1.000]), p = 0.050, Nagelkerke − Regression (R2) = 0.042. The study contributes to research on the development of an evidence-based thermal comfort assessment benchmark criteria for the American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE) Global Thermal Comfort Database version 2.1.