Effect of air pollution control on life expectancy in the United States: an analysis of 545 U.S. counties for the period from 2000 to 2007

Air pollution and climate change as grand challenges to sustainability

There is a cross-disciplinary link between air pollution, climate crisis, and sustainable lifestyle as they are the most complex struggles of the present century. This review takes an in-depth look at this relationship, considering carbon dioxide emissions primarily from the burning of fossil fuels as the main contributor to global warming and focusing on primary SLCPs such as methane and ground-level ozone. Such pollutants severely alter the climate through the generation of greenhouse gases. The discussion is extensive and includes best practices from conventional pollution control technologies to hi-tech alternatives, including electric vehicles, the use of renewables, and green decentralized solutions. It also addresses policy matters, such as imposing stricter emissions standards, setting stronger environmental regulations, and rethinking some economic measures. Besides that, new developments such as congestion charges, air ionization, solar-assisted cleaning systems, and photocatalytic materials are among the products discussed. These strategies differ in relation to the local conditions and therefore exhibit a varying effectiveness level, but they remain evident as a tool of pollution deterrence. This stresses the importance of holistic and inclusive approach in terms of engineering, policies, stakeholders, and ecological spheres to tackle.

Public Health Relevance of US EPA Air Quality Index Activity Recommendations

Importance

Reducing exposure to fine particulate matter (<2.5 μm [PM2.5]) air pollution improves cardiopulmonary morbidity and mortality. However, the public health relevance of air quality index (AQI) activity guidelines under present-day environmental conditions in the US has not been critically assessed.

Objective

To evaluate the public health relevance of following PM2.5 AQI activity guidance in preventing serious atherosclerotic cardiovascular disease (ASCVD) and pulmonary events among adults in the US.

Design, Setting, and Participants

This cross-sectional modeling study involved the general adult population and sensitive individuals as designated by the US Environmental Protection Agency (EPA), including adults with preexisting ASCVD or lung disease (asthma or chronic obstructive pulmonary disease). The study was conducted between August 1, 2023, and January 31, 2024.

Exposures

Daily AQI strata for PM2.5 and the corresponding activity recommendations.

Main Outcomes and Measures

The main outcome was the number needed to treat (NNT) per day by following activity guidance across daily AQI strata to prevent 1 serious ASCVD or pulmonary event among relevant populations. To calculate PM2.5-induced excess disease event rates per day, estimated baseline disease-specific daily event rates for each group were multiplied by the increase in risks due to PM2.5 levels at each AQI stratum. The number of events prevented per day was calculated by multiplying each excess disease event rate by the percentage in exposure reduction plausibly incurred by following population-specific activity guidance at each AQI level. The NNT is the reciprocal of the number of events prevented.

Results

The NNT to prevent ASCVD events was high for the general population and for patients with ASCVD across all AQI strata. The range of values was comparatively lower to prevent pulmonary events among adults with lung disease. During most days (96%) when activity recommendations were promulgated due to elevated PM2.5 (AQI, 101-200), the NNT to prevent a serious disease event remained very high for the general population (>18 million), patients with ASCVD (approximately 1.6-5 million), and adults with lung disease (approximately 66 000-202 000).

Conclusions and Relevance

These findings suggest that existing PM2.5 AQI activity recommendations are of questionable public health relevance in present-day conditions and merit consideration for updating to improve their potential effectiveness.

Changes in industrial air pollution and the onset of childhood asthma in Quebec, Canada

Ambient air pollution has been associated with asthma onset and exacerbation in children. Whether improvement in air quality due to reduced industrial emissions has resulted in improved health outcomes such as asthma in some localities has usually been assessed indirectly with studies on between-subject comparisons of air pollution from all sources and health outcomes. In this study we directly assessed, within small areas in the province of Quebec (Canada), the influence of changes in local industrial fine particulate matter (PM2.5), nitrogen dioxide (NO2), and sulfur dioxide (SO2) concentrations, on changes in annual asthma onset rates in children (≤12 years old) with a longitudinal ecological design. We identified the yearly number of new cases of childhood asthma in 1282 small areas (census tracts or local community service centers) for the years 2002, 2004, 2005, 2006, and 2015. Annual average concentrations of industrial air pollutants for each of the geographic areas, and three sectors (i.e., pulp and paper mills, petroleum refineries, and metal smelters) were estimated by the Polair3D chemical transport model. Fixed-effects negative binomial models adjusted for household income were used to assess associations; additional adjustments for environmental tobacco smoke, background pollutant concentrations, vegetation coverage, and sociodemographic characteristics were conducted in sensitivity analyses. The incidence rate ratios (IRR) for childhood asthma onset for the interquartile increase in total industrial PM2.5, NO2, and SO2 were 1.016 (95% confidence interval, CI: 1.006-1.026), 1.063 (1.045-1.090), and 1.048 (1.031-1.080), respectively. Positive associations were also found with pollutant concentrations from most individual sectors. Results suggest that changes in industrial pollutant concentrations influence childhood asthma onset rates in small localities.

The Impact of Ambient and Wildfire Air Pollution on Rhinosinusitis and Olfactory Dysfunction

PURPOSE OF REVIEW

With increasing industrialization, exposure to ambient and wildfire air pollution is projected to increase, necessitating further research to elucidate the complex relationship between exposure and sinonasal disease. This review aims to summarize the role of ambient and wildfire air pollution in chronic rhinosinusitis (CRS) and olfactory dysfunction and provide a perspective on gaps in the literature.

RECENT FINDINGS

Based on an emerging body of evidence, exposure to ambient air pollutants is correlated with the development of chronic rhinosinusitis in healthy individuals and increased symptom severity in CRS patients. Studies have also found a robust relationship between long-term exposure to ambient air pollutants and olfactory dysfunction. Ambient air pollution exposure is increasingly recognized to impact the development and sequelae of sinonasal pathophysiology. Given the rising number of wildfire events and worsening impacts of climate change, further study of the impact of wildfire-related air pollution is a crucial emerging field.

Aging, longevity, and the role of environmental stressors: a focus on wildfire smoke and air quality

Aging is a complex biological process involving multiple interacting mechanisms and is being increasingly linked to environmental exposures such as wildfire smoke. In this review, we detail the hallmarks of aging, emphasizing the role of telomere attrition, cellular senescence, epigenetic alterations, proteostasis, genomic instability, and mitochondrial dysfunction, while also exploring integrative hallmarks - altered intercellular communication and stem cell exhaustion. Within each hallmark of aging, our review explores how environmental disasters like wildfires, and their resultant inhaled toxicants, interact with these aging mechanisms. The intersection between aging and environmental exposures, especially high-concentration insults from wildfires, remains under-studied. Preliminary evidence, from our group and others, suggests that inhaled wildfire smoke can accelerate markers of neurological aging and reduce learning capabilities. This is likely mediated by the augmentation of circulatory factors that compromise vascular and blood-brain barrier integrity, induce chronic neuroinflammation, and promote age-associated proteinopathy-related outcomes. Moreover, wildfire smoke may induce a reduced metabolic, senescent cellular phenotype. Future interventions could potentially leverage combined anti-inflammatory and NAD + boosting compounds to counter these effects. This review underscores the critical need to study the intricate interplay between environmental factors and the biological mechanisms of aging to pave the way for effective interventions.

Effect of PM2.5 air pollution on the global burden of lower respiratory infections, 1990-2019: A systematic analysis from the Global Burden of Disease Study 2019

Particulate matter (PM) air pollution is closely related to lower respiratory infections (LRIs). However, the global LRI burden attributable to PM remains unclear. Here, we provide a comprehensive assessment of the PM2.5-attributable LRI burden using data from the Global Burden and Disease Study (GBD) 2019. We found that PM2.5 air pollution contributed to approximately 0.7 million deaths and 37.6 million disability-adjusted life years (DALYs) of LRIs in 2019. The LRI burden attributable to PM2.5 has decreased from 1990 to 2019, with a more pronounced decrease in household PM2.5 than in ambient PM2.5. Unlike the decreasing trend in LRI burden due to household PM2.5 worldwide, nearly one fifth of countries experienced an increase of LRI burden due to ambient PM2.5. The burden was unevenly distributed to less developed countries, mainly in Sub-Saharan Africa. All age groups experienced a decrease in the PM2.5-attributable burden, with the most significant decrease in children younger than 10 years. Notably, individuals aged 20-84 years experienced an increase in the LRI burden attributable to ambient PM2.5. Males had higher burden than females in the elder age and higher SDI regions. This study provided an evidence-based guidance for the prevention of LRIs and control of PM2.5 air pollution.

The contribution of wildfire to PM2.5 trends in the USA

Steady improvements in ambient air quality in the USA over the past several decades, in part a result of public policy1,2, have led to public health benefits1-4. However, recent trends in ambient concentrations of particulate matter with diameters less than 2.5 μm (PM2.5), a pollutant regulated under the Clean Air Act1, have stagnated or begun to reverse throughout much of the USA5. Here we use a combination of ground- and satellite-based air pollution data from 2000 to 2022 to quantify the contribution of wildfire smoke to these PM2.5 trends. We find that since at least 2016, wildfire smoke has influenced trends in average annual PM2.5 concentrations in nearly three-quarters of states in the contiguous USA, eroding about 25% of previous multi-decadal progress in reducing PM2.5 concentrations on average in those states, equivalent to 4 years of air quality progress, and more than 50% in many western states. Smoke influence on trends in the number of days with extreme PM2.5 concentrations is detectable by 2011, but the influence can be detected primarily in western and mid-western states. Wildfire-driven increases in ambient PM2.5 concentrations are unregulated under current air pollution law6 and, in the absence of further interventions, we show that the contribution of wildfire to regional and national air quality trends is likely to grow as the climate continues to warm.

The contribution of the exposome to the burden of cardiovascular disease

Large epidemiological and health impact assessment studies at the global scale, such as the Global Burden of Disease project, indicate that chronic non-communicable diseases, such as atherosclerosis and diabetes mellitus, caused almost two-thirds of the annual global deaths in 2020. By 2030, 77% of all deaths are expected to be caused by non-communicable diseases. Although this increase is mainly due to the ageing of the general population in Western societies, other reasons include the increasing effects of soil, water, air and noise pollution on health, together with the effects of other environmental risk factors such as climate change, unhealthy city designs (including lack of green spaces), unhealthy lifestyle habits and psychosocial stress. The exposome concept was established in 2005 as a new strategy to study the effect of the environment on health. The exposome describes the harmful biochemical and metabolic changes that occur in our body owing to the totality of different environmental exposures throughout the life course, which ultimately lead to adverse health effects and premature deaths. In this Review, we describe the exposome concept with a focus on environmental physical and chemical exposures and their effects on the burden of cardiovascular disease. We discuss selected exposome studies and highlight the relevance of the exposome concept for future health research as well as preventive medicine. We also discuss the challenges and limitations of exposome studies.

High performance filtration membranes from electrospun poly (3-hydroxybutyrate)-based fiber membranes for fine particulate protection

PM2.5 (particulate matter with a size of <2.5 μm) pollution has become a critical issue owing to its adverse health effects, including bronchitis, pneumonopathy, and cardiovascular diseases. Globally, around 8.9 million premature casualties related to exposure to PM2.5 were reported. Face masks are the only option that may restrict exposure to PM2.5. In this study, a PM2.5 dust filter was developed via the electrospinning technique using the poly (3-hydroxybutyrate) (PHB) biopolymer. Smooth and continuous fibers without beads were formed. The PHB membrane was further characterized, and the effects of the polymer solution concentration, applied voltage, and needle-to-collector distance were analyzed via the design of experiments technique, with three factors and three levels. The concentration of the polymer solution had the most significant effect on the fiber size and the porosity. The fiber diameter increased with increasing concentration, but decreases the porosity. The sample with a fiber diameter of ∼600 nm exhibited a higher PM2.5 filtration efficiency than the samples with a diameter of 900 nm, according to an ASTM F2299-based test. The PHB fiber mats fabricated at a concentration of 10%w/v, applied voltage of 15 kV, and needle tip-to-collector distance of 20 cm exhibited a high filtration efficiency of 95% and a pressure drop of <5 mmH2O/cm2. The tensile strength of the developed membranes ranged from 2.4 to 5.01 MPa, higher than those of the mask filters available in the market. Therefore, the prepared electrospun PHB fiber mats have great potential for the manufacture of PM2.5 filtration membranes.

Associations Between Gender Gaps in Life Expectancy, Air Pollution, and Urbanization: A Global Assessment With Bayesian Spatiotemporal Modeling

Objectives: It's evident that women have a longer life expectancy than men. This study investigates the spatiotemporal trends of gender gaps in life expectancy (GGLE). It demonstrates the spatiotemporal difference of the influence factors of population-weighted air pollution (pwPM_2.5) and urbanization on GGLE. Methods: Panel data on GGLE and influencing factors from 134 countries from 1960 to 2018 are collected. The Bayesian spatiotemporal model is performed. Results: The results show an obvious spatial heterogeneity worldwide with a continuously increasing trend of GGLE. Bayesian spatiotemporal regression reveals a significant positive relationship between pwPM_2.5, urbanization, and GGLE with the spatial random effects. Further, the regression coefficients present obvious geographic disparities across space worldwide. Conclusion: In sum, social-economic development and air quality improvement should be considered comprehensively in global policy to make a fair chance for both genders to maximize their health gains.

Effect of air pollution on disease burden, mortality, and life expectancy in North Africa and the Middle East: a systematic analysis for the Global Burden of Disease Study 2019

BACKGROUND

Air pollution is the sixth highest risk factor for attributable disability-adjusted life-years (DALYs) in North Africa and the Middle East, but the relative importance of different subtypes of air pollution and any potential differences in their health effects by population demographics or country-level socioeconomic factors have not been fully explored. The objective of this study was to investigate the effect of high ambient particulate matter less than 2·5 μm in size (PM) and ambient ozone air pollution on disease burden, mortality, and life expectancy in 21 countries in the North Africa and the Middle East super-region from 1990 to 2019 using the Global Burden of Diseases, Injuries, and Risk Factors (GBD) Study estimates.

METHODS

The study data were derived from GBD 2019, examining data from 1999 to 2019 in North Africa and the Middle East. In this study, the types of air pollution investigated included PM pollution and ambient ozone pollution. PM pollution itself was categorised as household air pollution from solid fuels and ambient PM pollution. The burden attributable to each risk factor, directly or indirectly, was incorporated in the population attributable fraction to estimate the total attributable deaths and DALYs. The summary exposure value (SEV) as the relative risk-weighted prevalence of exposure was extracted to compare the distribution of excess risk times the exposure level in a population where everyone is at maximum risk and ranges from zero (no excess risk exists in a population) to 100 (highest risk). The effect of air pollution on life expectancy was estimated via a cause-deleted life table analysis.

FINDINGS

The age-standardised DALYs rate attributable to air pollution declined by 44·5%, from 4884·2 (95% uncertainty interval 4381·5-5555·4) to 2710·4 (2317·3-3125·6) per 100 000 from 1990 to 2019. Afghanistan (6992·3, 5627·7-8482·7), Yemen (4212·4, 3241·3-5418·1), and Egypt (4034·8, 3027·7-5138·6) had the highest age-standardised DALYs rates attributable to air pollution in 2019 per 100 000, whereas Türkiye (1329·2, 1033·7-1654·7), Jordan (1447·3, 1154·2-1758·5), and Iran (1603·0, 1404·7-1813·8) had the lowest rates. During the study period, the age-standardised SEV of air pollution (PM and ambient ozone in total) decreased by 10·9% (5·8-17·7%) in the super-region, whereas the SEV of ambient ozone pollution alone increased by 7·7% (0·7-14·3%). Among the components of PM pollution, the SEV of ambient PM pollution increased by 40·1% (25·2-63·7%); however, the SEV of household air pollution from solid fuels decreased by 70·6% (64·1-77·0%). Among the investigated types of air pollution, 98·9% of the DALYs from air pollution in the super-region were attributable to PM pollution. If air pollution had been lowered to the theoretical minimum risk exposure levels for 2019, then the average life expectancy would have been 1·6 years higher.

INTERPRETATION

The burden attributable to air pollution substantially decreased in the study period across the super-region as a whole. Most of the burden from air pollution is attributed to PM pollution, the exposure to which has substantially increased in the past three decades. Interventions and policies that reduce population exposure to PM pollution could potentially increase the average life expectancy in the super-region. This finding calls for concerted efforts from governments and public health authorities in the super-region to tackle air pollution as an important threat to population health.

FUNDING

Bill & Melinda Gates Foundation.

PM2.5-related neonatal encephalopathy due to birth asphyxia and trauma: a global burden study from 1990 to 2019

Long-term exposure to fine particulate matter (PM_2.5) may increase the risk of neonatal encephalopathy due to birth asphyxia and trauma. However, little is known about the trends of PM_2.5-related neonatal encephalopathy burden under different levels of social and economic development. We studied the burden of PM_2.5-related neonatal encephalopathy due to birth asphyxia and trauma measured by the age-standardized mortality rate (ASMR) and the age-standardized disability-adjusted life years rate (ASDR), and its trends with the socio-demographic index (SDI) in 192 countries and regions from 1990 to 2019. This is a retrospective study using the Global Burden of Disease Study 2019 (GBD2019) database. The age-standardized mortality rate (ASMR) and age-standardized disability-adjusted life years rate (ASDR) are used to measure the burden of PM_2.5-related neonatal encephalopathy in different countries and regions. The mortality rate (per 100 thousand) is used to evaluate the differences of PM_2.5-related neonatal encephalopathy burden in sex and age. The annual percentage changes (APCs) and the average annual percentage changes (AAPCs) are used to reflect the trends of PM_2.5-related neonatal encephalopathy burden over years (1990-2019) and are calculated using a Joinpoint model. The relationship of the socio-demographic index with the ASMR and ASDR is calculated using Gaussian process regression. In summary, the global burden of PM_2.5-related neonatal encephalopathy increased since 1990, especially in boys, early neonates, and regions with low-middle SDI. Globally, the ASMR and ASDR of PM_2.5-related neonatal encephalopathy burden in 2019 were 0.59 (95% CI: 0.40, 0.83) per 100,000 people and 52.59 (95% CI: 35.33, 73.67) per 100,000 people, respectively. From 1990 to 2019, the ASMR and ASDR of PM_2.5-related neonatal encephalopathy increased by 44.39% and 44.19%, respectively. The global average annual percentage changes of ASMR and ASDR were 1.3 (95% CI: 1.0, 1.6). The relationship between the socio-demographic index and the burden of PM_2.5-related neonatal encephalopathy presented negative correlation when the socio-demographic index was more than 0.60. Middle, high-middle, and high SDI regions had decreasing trends of PM_2.5-related neonatal encephalopathy, of which the AAPCs for both ASMR and ASDR ranged from - 0.3 to - 3.1. Besides improving the progress in national policy and the coverage rate of maternal and neonatal health care and facility-based delivery, air pollution control may also be a better way for countries with large and increasing amounts of exposure to PM_2.5 pollution to reduce neonatal encephalopathy. And our results also suggest that low and low-middle SDI countries should appropriately pay more attention to early newborns and boys.

How does manufacturing haze pollution decrease in China: a decomposition study of structural model based on general equilibrium framework

Based on the annual mean PM_2.5 concentration data of 30 provinces and cities in China from 2006 to 2020, this paper constructs a structural model of manufacturing haze pollution, expounds the main mechanisms affecting haze pollution, then statistically decomposes the main factors affecting the change of pollution emissions, and examines the direct and indirect impact paths of the change of haze pollution emissions in China. The study found that (1) the inhibitory effects of latent variables on manufacturing haze pollution is from strong to weak in order: industrial structure upgrading, environmental regulation, trade opening, productivity improvement, and economic scale expansion, while the optimal path for the indirect effect of exogenous latent variables on haze pollution is to rely on environmental regulation and opening up to achieve the improvement of productivity, so as to achieve the purpose of reducing haze pollution. (2) The analysis based on the PVAR model found that industrial structure adjustment is the key factor of haze decline in both the short and long term. Environmental regulation has an obvious effect on haze control in the short term, but in the long run, it still needs to rely on industrial structure adjustment, production efficiency improvement, and trade opening to achieve the goal of reducing haze. (3) There is an inverted U-shaped nonlinear relationship between output scale and environmental regulation. In addition, trade openness has a long-term effect on productivity. Technology spillovers from opening up can reduce haze pollution in the long run by improving productivity. (4) The environmental regulation policy in the central region is characterized by "race to the bottom," while the eastern region shows the characteristic of "race to the top" in the policy game of improving productivity and optimizing the industrial structure. Therefore, haze control requires an appropriate intensity of environmental regulation to reduce the proportion of high pollution and high energy consumption industries. Make full use of the international cooperation platform of the "the Belt and Road Initiative" and the pilot free trade zone to promote substantive cooperation between Chinese enterprises and developed countries in the field of environmental protection technology, increase investment in research and development of clean equipment and cleaner production technology, improve productivity, help China's green manufacturing, and contribute Chinese wisdom and Chinese solutions to global environmental governance and climate change.

Evaluation of Health Economic Loss Due to Particulate Matter Pollution in the Seoul Subway, South Korea

Evaluating an illness's economic impact is critical for developing and executing appropriate policies. South Korea has mandatory national health insurance in the form of NHIS that provides propitious conditions for assessing the national financial burden of illnesses. The purpose of our study is to provide a comprehensive assessment of the economic impact of PM_2.5 exposure in the subway and a comparative analysis of cause-specific mortality outcomes based on the prevalent health-risk assessment of the health effect endpoints (chronic obstructive pulmonary disease (COPD), asthma, and ischemic heart disease (IHD)). We used the National Health Insurance database to calculate the healthcare services provided to health-effect endpoints, with at least one primary diagnosis in 2019. Direct costs associated with health aid or medicine, treatment, and indirect costs (calculated based on the productivity loss in health effect endpoint patients, transportation, and caregivers, including morbidity and mortality costs) were both considered. The total cost for the exposed population for these endpoints was estimated to be USD 437 million per year. Medical costs were the largest component (22.08%), followed by loss of productivity and premature death (15.93%) and other costs such as transport and caregiver costs (11.46%). The total incurred costs (per 1000 persons) were accounted to be USD 0.1771 million, USD 0.42 million, and USD 0.8678 million for COPD, Asthma, and IHD, respectively. Given that the economic burden will rise as the prevalence of these diseases rises, it is vital to adopt effective preventative and management methods strategies aimed at the appropriate population.

The impacts of reduction in ambient fine particulate (PM2.5) air pollution on life expectancy in Taiwan

Fine particulate matter, particles less than 2.5 um in diameter (PM_2.5), is an important environmental human health factor to consider. The long- and short-term influence of PM_2.5 on health has been extensively studied in relation to many health outcomes, although few investigations examined the consequences of chronic ambient PM_2.5 on life expectancy, which constitutes an important gauge of public human health status. Therefore, the aim of this study was to investigate the effects of reducing ambient PM_2.5 levels in Taiwan on life expectancy there from 2000 to 2020. Officially reported island-wide annually average concentrations of ambient PM_2.5, county-level life expectancies, and demographic and socioeconomic and proxy variable were collected for the prevalence of smoking from various national public agencies and organizations, since variables these might potentially confound life expectancy results. The relationship between changes in ambient PM_2.5 levels and life expectancy were determined using linear regression. Data demonstrated that counties with greater reductions in ambient PM_2.5 concentrations were associated with higher life expectancies. Adjusting for alterations in demographic and socioeconomic variables and proxy parameter, the prevalence of smoking data from a multiple regression model, it was found that a 0.3-year rise in life expectancy was noted for each 10 ug/m³ decrease in PM_2.5 in those counties. Our findings show that reducing ambient PM_2.5 levels play an important role for prolongation of life expectancy in Taiwan.

Heterogeneity in Disparities in Life Expectancy Across US Metropolitan Areas

BACKGROUND

Life expectancy in the United States has declined since 2014 but characterization of disparities within and across metropolitan areas of the country is lacking.

METHODS

Using census tract-level life expectancy from the 2010 to 2015 US Small-area Life Expectancy Estimates Project, we calculate 10 measures of total and income-based disparities in life expectancy at birth, age 25, and age 65 within and across 377 metropolitan statistical areas (MSAs) of the United States.

RESULTS

We found wide heterogeneity in disparities in life expectancy at birth across MSAs and regions: MSAs in the West show the narrowest disparities (absolute disparity: 8.7 years, relative disparity: 1.1), while MSAs in the South (absolute disparity: 9.1 years, relative disparity: 1.1) and Midwest (absolute disparity: 9.8 years, relative disparity: 1.1) have the widest life expectancy disparities. We also observed greater variability in life expectancy across MSAs for lower income census tracts (coefficient of variation [CoV] 3.7 for first vs. tenth decile of income) than for higher income census tracts (CoV 2.3). Finally, we found that a series of MSA-level variables, including larger MSAs and greater proportion college graduates, predicted wider life expectancy disparities for all age groups.

CONCLUSIONS

Sociodemographic and policy factors likely help explain variation in life expectancy disparities within and across metro areas.

Visualization and Analysis of Air Pollution and Human Health Based on Cluster Analysis: A Bibliometric Review from 2001 to 2021

Bibliometric techniques and social network analysis are employed in this study to evaluate 14,955 papers on air pollution and health that were published from 2001 to 2021. To track the research hotspots, the principle of machine learning is applied in this study to divide 10,212 records of keywords into 96 clusters through OmniViz software. Our findings highlight strong research interests and the practical need to control air pollution to improve human health, as evidenced by an annual growth rate of over 15.8% in the related publications. The cluster analysis showed that clusters C22 (exposure, model, mortality) and C8 (health, environment, risk) are the most popular topics in this field of research. Furthermore, we develop co-occurrence networks based on the cluster analysis results in which a more specific keyword classification was obtained. These key areas include: "Air pollutant source", "Exposure-Response relationship", "Public & Occupational Health", and so on. Future research hotspots are analyzed through characteristics of the cluster groups, including the advancement of health risk assessment techniques, an interdisciplinary approach to quantifying human exposure to air pollution, and strategies in health risk assessment.

Methods for assessing the impact of PM2.5 concentration on mortality while controlling for socio-economic factors

Even though industrial development has brought vast improvements to our daily lives, it carries with it negative effects such as adverse health outcomes caused by PM_2.5 and other pollutants. The negative externalities and external costs might occur when property rights are not properly defined, which means that if no one holds a property right on the atmosphere and the quality of air, there is no appropriate mechanism to prevent a further expansion of negative effects. An economic burden of pollution related to premature morbidity and mortality in individual countries can account for 5–14% of GDP (World Bank, 2021). In 2019, the worldwide health cost of mortality and morbidity caused by exposure to PM_2.5 concentration was $8.1 trillion, which is equivalent to 6.1 percent of the global gross domestic product (GDP) (World Bank estimate). Policymakers require evidence-based results that clearly show the impact that air pollution has on the economy and society, in order to be able to establish the proper regulations and ensure their successful implementation. The purpose of this long term study is to provide methods for assessing the negative effects of PM_2.5 concentration on PM_2.5-related mortality using panel data structure and demonstrate how socio-economic factors affect this relation. This study employed advanced econometric techniques to analyse the long-term impact of PM_2.5 on human health, while controlling for socio economic indicators. This study has demonstrated significant effects of socio-economic, health risk and system and governance variables on the relation between PM_2.5 ​concentration and PM_2.5-related mortality.

Importance of Punctual Monitoring to Evaluate the Health Effects of Airborne Particulate Matter

Particulate matter (PM) pollution is one of the major public health problems worldwide, given the high mortality attributable to exposure to PM pollution and the high pathogenicity that is found above all in the respiratory, cardiovascular, and neurological systems. The main sources of PM pollution are the daily use of fuels (wood, coal, organic residues) in appliances without emissions abatement systems, industrial emissions, and vehicular traffic. This review aims to investigate the causes of PM pollution and classify the different types of dust based on their size. The health effects of exposure to PM will also be discussed. Particular attention is paid to the measurement method, which is unsuitable in the risk assessment process, as the evaluation of the average PM compared to the evaluation of PM with punctual monitoring significantly underestimates the health risk induced by the achievement of high PM values, even for limited periods of time.

Assessment of Kitchen Air Pollution: Health Implications for the Residents of Ilorin South, Nigeria

Indoor air quality is essential, so its quality cannot be compromised. Hence, this research assessed indoor gaseous air pollutant concentrations from sources in thirty-three residential kitchens within the 4-zone of Ilorin-South Local Government, Kwara, Nigeria. The work focused on SO2, NO2, and CO emission concentration quantification, determination of the air quality index (AQI), estimation of health assessment risk, and deduced their health implications on the residents. The concentrations of NO2 and SO2 were determined by the Saltzman method using a Gilair-3 air sampler, while the concentration of CO was determined using an MSA Altair-5x multigas detector. Three types of eleven kitchen environments each (kitchens where liquefied petroleum gas (LPG), charcoal, and firewood were used as fuel sources) were considered. The concentrations of NO2, SO2, and CO were higher in kitchens that used charcoal and firewood. The major health risks were deduced in percentages from the questionnaire administered, where headaches had the highest percentage (20.7). The model indicated that the concentrations of the pollutants in the evening, irrespective of the sampling points, were higher than those in the morning. Firewood contributed significantly more than charcoal and LPG ( $p<0.05$ ). The results of the health assessment risk showed that the risk estimated for normal exposure to the pollutants in all the households studied revealed a hazard quotient of <1.0 except for SO2 from firewood for infants and children = 1.09. The AQI results showed the worst health conditions for households that used firewood (0.103–4.760 ppm NO2; 0.327–0.647 ppm SO2; and 12.30–57.83 ppm CO). The study concluded that the use of LPG should be preferred as a source of fuel for cooking.

Assessing and Validating the Ability of Machine Learning to Handle Unrefined Particle Air Pollution Mobile Monitoring Data Randomly, Spatially, and Spatiotemporally

Many epidemiological studies have evaluated the accuracy of machine learning models in predicting levels of particulate number (PN) and black carbon (BC) pollutant concentrations. However, few studies have investigated the ability of machine learning to predict the pollutant concentration with using unrefined mobile measurement data and explore the reliability of the prediction models. Additionally, researchers are moving away from using fixed-site data in favor of using mobile monitoring data in a variety of locations to develop hourly empirical models of particulate air pollution. This study compared the differences between long-term (daily average) and short-term (hourly average and 1 s unrefined data) model performance in three different classes of cross validation: randomly, spatially, and spatially temporally. This study used secondary data describing BC and PN pollutant levels in the rural location of Blacksburg (VA). Our results show that the model based on unrefined data was able to detect the pollutant hot spot areas with similar accuracy compared to the aggregated model. Moreover, the performance was found to improve when temporal data added to the model: the 10-fold MAE for the BC and PN were 0.44 μg/m³ and 3391 pt/cm³, respectively, for the unrefined data (one second data) model. The findings detailed here will add to the literature on the correlation between data (pre)processing and the efficacy of machine learning models in predicting pollution levels while also enhancing our understanding of more reliable validation strategies.

The Association between the Burden of PM2.5-Related Neonatal Preterm Birth and Socio-Demographic Index from 1990 to 2019: A Global Burden Study

BACKGROUND

Preterm birth (PTB) leads to short-term and long-term adverse effects on newborns. Exposure to fine particulate matter (PM_2.5) was positively related to PTB. However, the global annual average PM_2.5 was three times than the recommended value in 1998-2014. Socio-demographic index (SDI) is a new indicator that comprehensively reflects the overall development level of a country, partly because of "the epidemiological transition". Among other countries with higher and similar SDI levels, policy makers have the opportunity to learn from their successful experiences and avoid their mistakes by identifying whether their burdens of disease are higher or lower than the expected. However, it is unclear about the trends of the burden of PM_2.5-related preterm birth in different countries and different levels of SDI regions. Additionally, the relationship between the SDI and the burden in 1990-2019 is also unclear.

METHODS

This was a retrospective study based on the Global Burden of Disease Study 2019 (GBD2019) database from 1990 to 2019. The burden of PM_2.5-related PTB was measured by the age-standardized mortality rate (ASMR), age-standardized disability-adjusted life years rate (ASDR), mortality rate, and the disability-adjusted life years (DALYs). The annual percentage changes (APCs) and the average annual percentage changes (AAPCs) were used to reflect the trends over the past 30 years, which were calculated using a joinpoint model. The relationships between the ASMR, ASDR, and SDI were calculated using a Gaussian process regression.

FINDINGS

In 2019, the entire burden of PM_2.5-related PTB was relatively high, where the ASMR and the ASDR were 0.76 and 67.71, increasing by 7.04% and 7.12%, respectively. It mainly concentrated on early neonates, boys, and on low-middle SDI regions. The increase in the burden of PM_2.5-related PTB in low and low-middle SDI regions is slightly higher than the decrease in other SDI regions. In 2019, the burden varied greatly among different levels of SDI regions where ASMRs varied from 0.13 in high SDI regions to 1.19 in low-middle regions. The relationship between the expected value of the burden of PM_2.5-related PTB and SDI presented an inverted U-shape, and it reached the maximum when SDI is around 0.50. The burdens in four regions (South Asia, North Africa and the Middle East, western sub-Saharan Africa, and southern sub-Saharan Africa) were much higher than the mean value. Boys bore more burden that girls. The sex ratio (boys:girls) of the burden showed a dramatically increasing trend in low SDI regions and a decreasing trend in middle SDI regions and high-middle SDI regions. These differences reflect the huge inequality among regions, countries, ages, and sex in the burden of PM_2.5-related PTB.

CONCLUSION

The overall burden of PM_2.5-related PTB in 2019 was relatively high, mainly concentrated on early neonates, boys, and on low-middle SDI regions. It showed an increasing trend in low-middle and low SDI regions. The association between the burden and the SDI presented an inverted U-shape. It is very necessary to promulgate policies to prevent and control air pollution in countries with large and increasing exposure to PM_2.5 pollution because it does not need action at an individual level. Focusing on public educational interventions, public and professional policies, and improving accessibility of prenatal care are other feasible ways for low and low-middle SDI countries. Policy makers should also appropriately allocate medical resources to boys and early newborns.

Non-linear relations between life expectancy, socio-economic, and air pollution factors: a global assessment with spatial disparities

Influential factors of socio-economic and air pollution on life expectancy (LE) show complexity. The investigations of non-linear functions of LE, socio-economic, and air pollution factors have not been largely conducted, and spatial and temporal differences of the linear or non-linear relations between LE and the influential factors have been obscured across countries in the world. In this study, the non-linear relations between LE and factors of per capita gross national income (GNI_pc), urban population rate (UPR), and fine-particulate (PM_2.5) were estimated from 2000 to 2015 by using a generalized additive model (GAM). The collected data included the 219 countries and regions with sufficient data and covers the period 2000-2015. The results demonstrate that at the global level, the GNI_pc plays a stable and significant non-linear role in LE, while the non-linear relationships between UPR, PM_2.5, and LE are not significant. The temporal variation was further investigated that the non-linear effect of PM_2.5 on LE is gradually strengthened, and the non-linear effect of UPR on LE shows a weakened trend. However, GNI_pc always plays a significantly non-linear role in the LE level. Furthermore, the spatial difference in the non-linear relations among different continents is detected. In sum, it cannot be ignored the non-linear effects of socio-economic and air pollution factors on LE at a global scale and across different continents.

Health and Human Wellbeing in China: Do Environmental Issues and Social Change Matter?

How to mitigate greenhouse gas emission and achieve human development remain major sustainability issues, particularly in China. Empirical research on the effects of climate warming and social change on human health and wellbeing is quite fragmented. This study examines the impact of environmental issues and social changes on health and human wellbeing using a time series data of China from 1991 to 2020. Findings show that environmental issues have a negative impact on health and human wellbeing in long run. While the internet is a form of social change that tends to improve health and human wellbeing in the long run. FDI exerts a positive effect on human health, but it does not improve wellbeing in the long run. In contrast, financial development does not improve human health but it has a significant positive impact on wellbeing in the long run. Our empirical insights have important implications for achieving human wellbeing through the pursuit of environmental sustainability and social change.

Air Pollution, Socioeconomic Status, and Age-Specific Mortality Risk in the United States

IMPORTANCE

Prior studies on the association between fine particulate matter with diameters 2.5 μm or smaller (PM2.5) and probability of death have not applied multilevel analysis disaggregating data for US census tract, states, and counties, nor tested its interaction by socioeconomic status (SES). Such an approach could provide a more refined identification and targeting of populations exposed to increased risk from PM2.5.

OBJECTIVE

To assess the association between PM2.5 and age-specific mortality risk (ASMR) using disaggregated data at the census tract level and evaluate such association according to census tract SES.

DESIGN, SETTING, AND PARTICIPANTS

This nationwide cross-sectional study used a linkage of 3 different data sets. ASMR for the period of 2010 to 2015 was obtained from the National Center for Health Statistic, SES data covering a period from 2006 to 2016 came from the American Community Survey, and mean PM2.5 exposure levels from 2010 to 2015 were derived from well-validated atmospheric chemistry and machine learning models. Data were analyzed in April 2021.

EXPOSURES

The main exploratory variable was mean census tract-level long-term exposure to PM2.5 from 2010 to 2015.

MAIN OUTCOMES AND MEASURES

The primary outcome was census tract-level ASMR. Multilevel models were used to quantify the geographic variation in ASMR at levels of census tract, county, and state. Additional analysis explored the interaction of SES in the association of ASMR with PM2.5 exposure.

RESULTS

Data from 67 148 census tracts nested in 3087 counties and 50 states were analyzed. The association between exposure to PM2.5 and ASMR varied substantially across census tracts. The magnitude of such association also varied across age groups, being higher among adults and older adults. Census tracts accounted for most of the total geographic variation in mortality risk (range, 77.0%-94.2%). ASMR was higher in deciles with greater PM2.5 concentration. For example, ASMR for age 75 to 84 years was 54.6 per 1000 population higher in the decile with the second-highest PM2.5 concentration than in the decile with the lowest PM2.5 concentration. The ASMR, PM2.5 concentrations, and magnitude of the association between both were higher in the census tracts with the lowest SES.

CONCLUSIONS AND RELEVANCE

This cross-sectional study found that census tracts with lower SES presented higher PM2.5 concentrations. ASMR and air pollution varied substantially across census tracts. There was an association between air pollution and ASMR across all age groups in the United States. These findings suggest that equitable public policies aimed at improving air quality are needed and important to increase life expectancy.

Long-Term Exposure to Fine Particulate Matter and the Deterioration of Estimated Glomerular Filtration Rate: A Cohort Study in Patients With Pre-End-Stage Renal Disease

Limited literature has explored the effect of air pollutants on chronic kidney disease (CKD) progression, especially for patients with pre-end-stage renal disease (pre-ESRD). In this study, we reported the linear and nonlinear relationships of air pollutants of particles with diameter <2.5 μm (PM2.5) and nitrogen dioxide (NO2) with estimated glomerular filtration rate (eGFR) deterioration after adjusting for smoking status and other traditional clinical factors. This study adopted a retrospective cohort of patients with stage 3b to stage 5 CKD (N = 11,479) from Taichung Veterans General Hospital during January 2006 to December 2020. The eGFR deterioration was defined as a decline in eGFR > 5 ml/min/1.73 m2/year. Hybrid kriging/land-use regression models were used to estimate the individual exposure levels of PM2.5 and NO2. The relationships of air pollutants with eGFR deterioration were evaluated using Cox proportional hazard models. After adjusting for smoking status, baseline eGFR stages, and other traditional clinical factors, the risk of eGFR deterioration was found to increase with increasing PM2.5 and NO2 level (p < 0.0001 and p = 0.041, respectively), especially for those exposed to PM2.5 ≥ 31.44 μg/m3 or NO2 ≥ 15.00 ppb. Similar results were also found in the two-pollutant models. Nonlinear dose-response relationships of eGFR deterioration were observed for concentrations of 26.11 μg/m3 for PM2.5 and 15.06 ppb for NO2. In conclusion, linear and nonlinear associations between PM2.5 and NO2 levels and the incidence risk of eGFR deterioration were observed in patients with pre-ESRD.

Cloud-Based Decision Support System for Air Quality Management

Air quality is important for the protection of human health, the environment and our cultural heritage and it is an issue that will acquire increased significance in the future due to the adverse effects of climate change. Thus, it is important to not simply monitor air quality, but to make information immediately available to those responsible for monitoring the networks, to policy/decision makers, but also to the general population. Moreover, the development of information technologies over the last couple of decades has allowed the proliferation of real-time pollution monitoring. The work presented herein concerns the development of an effective way of monitoring environmental parameters using dedicated software. It offers a complete suite of applications that support environmental data collection management and reporting for air quality and associated meteorology. It combines modern technologies for the proper monitoring of air quality networks, which can consist of one or more measuring stations. Innovatively, it also focuses on how to effectively present the relevant information, utilizing modern technologies, such as cloud and mobile applications, to network engineers, policy/decision managers, and to the general public at large. It also has the capability of notifying appropriate personnel in the event of failures, overruns or abnormal values. The system, in its current configuration, handles information from six networks that include over 55 air pollution monitoring stations that are located throughout Greece. This practical application has shown that the system can achieve high data availability rates, even higher than 99% during the year.

Assessing Trade-Offs and Optimal Ranges of Density for Life Expectancy and 12 Causes of Mortality in Metro Vancouver, Canada, 1990-2016

Background: Understanding and managing the impacts of population growth and densification are important steps for sustainable development. This study sought to evaluate the health trade-offs associated with increasing densification and to identify the optimal balance of neighbourhood densification for health. Methods: We linked population density with a 27-year mortality dataset in Metro Vancouver that includes census-tract levels of life expectancy (LE), cause-specific mortalities, and area-level deprivation. We applied two methods: (1) difference-in-differences (DID) models to study the impacts of densification changes from the early 1990s on changes in mortality over a 27-year period; and (2) smoothed cubic splines to identify thresholds of densification at which mortality rates accelerated. Results: At densities above ~9400 persons per km², LE began to decrease more rapidly. By cause, densification was linked to decreased mortality for major causes of mortality in the region, such as cardiovascular diseases, neoplasms, and diabetes. Greater inequality with increasing density was observed for causes such as human immunodeficiency virus and acquired immunodeficiency syndrome (HIV/AIDS), sexually transmitted infections, and self-harm and interpersonal violence. Conclusions: Areas with higher population densities generally have lower rates of mortality from the major causes, but these environments are also associated with higher relative inequality from largely preventable causes of death.

Estimating Associations Between Annual Concentrations of Particulate Matter and Mortality in the United States, Using Data Linkage and Bayesian Maximum Entropy

BACKGROUND

Exposure to fine particulate matter (PM2.5) is an established risk factor for human mortality. However, previous US studies have been limited to select cities or regions or to population subsets (e.g., older adults).

METHODS

Here, we demonstrate how to use the novel geostatistical method Bayesian maximum entropy to obtain estimates of PM2.5 concentrations in all contiguous US counties, 2000-2016. We then demonstrate how one could use these estimates in a traditional epidemiologic analysis examining the association between PM2.5 and rates of all-cause, cardiovascular, respiratory, and (as a negative control outcome) accidental mortality.

RESULTS

We estimated that, for a 1 log(μg/m3) increase in PM2.5 concentration, the conditional all-cause mortality incidence rate ratio (IRR) was 1.029 (95% confidence interval [CI]: 1.006, 1.053). This implies that the rate of all-cause mortality at 10 µg/m3 would be 1.020 times the rate at 5 µg/m3. IRRs were larger for cardiovascular mortality than for all-cause mortality in all gender and race-ethnicity groups. We observed larger IRRs for all-cause, nonaccidental, and respiratory mortality in Black non-Hispanic Americans than White non-Hispanic Americans. However, our negative control analysis indicated the possibility for unmeasured confounding.

CONCLUSION

We used a novel method that allowed us to estimate PM2.5 concentrations in all contiguous US counties and obtained estimates of the association between PM2.5 and mortality comparable to previous studies. Our analysis provides one example of how Bayesian maximum entropy could be used in epidemiologic analyses; future work could explore other ways to use this approach to inform important public health questions.

Projecting Lifetime Health Outcomes and Costs Associated with the Ambient Fine Particulate Matter Exposure among Adult Women in Korea

We sought to estimate the lifetime healthcare costs and outcomes associated with the exposure to the escalated concentration of fine particulate matter (particle size < 2.5 μm, PM2.5) among adult Korean women. We adapted a previously developed Markov model, and a hypothetical cohort composed of Korean women was exposed to either a standard (15 μg/m3) or increased (25 μg/m3) concentration of PM2.5. The time horizon of the analysis was 60 years, and the cycle length was 1 year. The outcomes were presented as direct healthcare costs and quality-adjusted life years (QALYs), and costs were discounted annually at 5%. Deterministic and probabilistic sensitivity analyses were performed. The model estimated that when the exposure concentration was increased by 10 μg/m3, the lifetime healthcare cost increased by USD 9309, which is an 11.3% increase compared to the standard concentration group. Women exposed to a higher concentration of PM2.5 were predicted to live 30.64 QALYs, compared to 32.08 QALYs for women who were exposed to the standard concentration of PM2.5. The tendency of a higher cost and shorter QALYs at increased exposure was consistent across a broad range of sensitivity analyses. The negative impact of PM2.5 was higher on cost than on QALYs and accelerated as the exposure time increased, emphasizing the importance of early intervention.

Establishing A Sustainable Low-Cost Air Quality Monitoring Setup: A Survey of the State-of-the-Art

Low-cost sensors (LCS) are becoming popular for air quality monitoring (AQM). They promise high spatial and temporal resolutions at low-cost. In addition, citizen science applications such as personal exposure monitoring can be implemented effortlessly. However, the reliability of the data is questionable due to various error sources involved in the LCS measurement. Furthermore, sensor performance drift over time is another issue. Hence, the adoption of LCS by regulatory agencies is still evolving. Several studies have been conducted to improve the performance of low-cost sensors. This article summarizes the existing studies on the state-of-the-art of LCS for AQM. We conceptualize a step by step procedure to establish a sustainable AQM setup with LCS that can produce reliable data. The selection of sensors, calibration and evaluation, hardware setup, evaluation metrics and inferences, and end user-specific applications are various stages in the LCS-based AQM setup we propose. We present a critical analysis at every step of the AQM setup to obtain reliable data from the low-cost measurement. Finally, we conclude this study with future scope to improve the availability of air quality data.

Spatiotemporal trends in life expectancy and impacts of economic growth and air pollution in 134 countries: A Bayesian modeling study

Life expectancy (LE) varies across countries in space and time, and economic growth and air pollution are two important influence factors to LE. This study mainly aims to investigate spatiotemporal trends in LE in 134 countries from 1960 to 2016 by using Bayesian spatiotemporal modeling. Further, the relations between per capita gross domestic product (GDP_pc) and population-weighted fine particulate matter (pwPM_2.5) and LE are investigated from a global perspective from 1998 to 2016 by using the Bayesian regression model. The results illustrated the heterogeneity of spatiotemporal trends in LE globally. Specifically, Africa and South-East Asia show much lower LE levels, and the Americas, European, and Western Pacific exhibit a relatively higher LE level compared to the overall level. The countries with low overall levels of LE show a relatively stronger upward trend than the overall upward trend and vice versa. In addition, this study demonstrates that the spatial differences in effects of influence factors on LE in the six WHO regions in the 134 countries. Africa shows the highest positive regression coefficient of GDP_pc and lowest negative regression coefficient of pwPM_2.5 on LE than other regions in the world. Furthermore, it shows the complexity of the interaction between economic growth and air pollution on LE across six WHO regions. Our findings suggest the public policies to reduce the health damage caused by air pollution, especially in Africa, Eastern Mediterranean, and Europe where the pwPM_2.5 negatively affect the LE benefits from economic growth.

Global burden of COPD attributable to ambient PM2.5 in 204 countries and territories, 1990 to 2019: A systematic analysis for the Global Burden of Disease Study 2019

The global spatiotemporal pattern of the COPD burden attributable to ambient PM2.5 is unknown in the context of the continuing increase in exposure to ambient PM2.5. Data on COPD burden attributable to ambient PM2.5 from 1990 to 2019 were retrieved from the Global Burden of Disease Study 2019. Cases and age-standardized rates of COPD mortality (ASMR) and disability-adjusted life years (ASDR) were estimated by age, sex, region, and country. The estimated annual percentage change (EAPC) was calculated to quantify the secular trends of ASMR and ASDR from 1990 to 2019. Globally, the number of COPD deaths and DALYs attributable to ambient PM2.5 both increased by over 90% from 1990 to 2019, but ASMR and ASDR both slightly decreased, with EAPC of -0.58 (95% CI: -0.72, -0.44) and -0.40 (95% CI: -0.51, -0.29), respectively. Most COPD deaths and DALYs attributable to PM2.5 occurred in the middle sociodemographic index (SDI) region, but the fastest growth of ASMR and ASDR occurred in the low SDI region, with EAPCs of 2.41 (95% CI: 2.23, 2.59) and 2.34 (95% CI: 2.16, 2.52), respectively. East Asia and South Asia were the high-risk areas of COPD deaths and DALYs attributable to PM2.5, among which China and India were the countries with the heaviest burden. COPD deaths and DALYs attributable to PM2.5 mainly occurred in individuals 70-89 years old and 60-84 years old, respectively. The age-specific rates of mortality and DALYs had a rapid increase in low and low-middle SDI regions from 1990 to 2019. The ASMR or ASDR had a reverse V-shaped relationship with SDI. In summary, the ambient PM2.5-attributable COPD burden is socioeconomic- and age-dependent, and it mediates the heterogeneity of spatial and temporal distribution. Low- and middle-income countries endure the highest ambient PM2.5-attributable COPD burden due to the high exposure to PM2.5 and poor availability and affordability of medicines and diagnostic tests.

Health impacts of air pollution exposure from 1990 to 2019 in 43 European countries

Air pollution is the fourth greatest overall risk factor for human health. Despite declining levels in Europe, air pollution still represents a major health and economic burden. We collected data from the Global Burden of Disease Study 2019 regarding overall, as well as ischemic heart disease (IHD), stroke, and tracheal, bronchus and lung cancer-specific disability adjusted life years (DALYs), years of life lost (YLL) and mortality attributable to air pollution for 43 European countries between 1990 and 2019. Concentrations of ambient particulate matter (aPM_2.5), ozone, and household air pollution from solid fuels were obtained from State of Global Air 2020. We analysed changes in air pollution parameters, as well as DALYs, YLL, and mortality related to air pollution, also taking into account gross national income (GNI) and socio-demographic index (SDI). Using a novel calculation, aPM_2.5 ratio (PMR) change and DALY rate ratio (DARR) change were used to assess each country's ability to decrease its aPM_2.5 pollution and DALYs to at least the extent of the European median decrease within the analysed period. Finally, we created a multiple regression model for reliably predicting YLL using aPM_2.5 and household air pollution. The average annual population-weighted aPM_2.5 exposure in Europe in 1990 was 20.8 μg/m³ (95% confidence interval (CI) 18.3-23.2), while in 2019 it was 33.7% lower at 13.8 μg/m³ (95% CI 12.0-15.6). There were in total 368 006 estimated deaths in Europe in 2019 attributable to air pollution, a 42.4% decrease compared to 639 052 in 1990. The majority (90.4%) of all deaths were associated with aPM_2.5. IHD was the primary cause of death making up 44.6% of all deaths attributable to air pollution. The age-standardised DALY rate and YLL rate attributable to air pollution were more than 60% lower in 2019 compared to 1990. There was a strong positive correlation (r = 0.911) between YLL rate and aPM_2.5 pollution in 2019 in Europe. Our multiple regression model predicts that for 10% increase in aPM_2.5, YLL increases by 16.7%. Furthermore, 26 of 43 European countries had a positive DARR change. 31 of 43 European countries had a negative PMR change, thus not keeping up with the European median aPM_2.5 concentration decrease. When categorising countries by SDI and GNI, countries in the higher brackets had significantly lower aPM_2.5 concentration and DALY rate for IHD and stroke. Overall, air pollution levels, air pollution-related morbidity and mortality have decreased considerably in Europe in the last three decades. However, with the growing European population, air pollution remains an important public health and economic issue. Policies targeting air pollution reduction should continue to be strongly enforced to further reduce one of the greatest risk factors for human health.

Effectiveness of road dust suppressants: insights from particulate matter-related health damage

Although dust suppressants are widely applied to control road dust pollution, a consensus on their effectiveness has not been reached. To evaluate the effectiveness of dust suppressants (a calcium-magnesium complex) from health risks and health damage, spraying and sampling activities were conducted at four sites in Beijing. Using inhalation risk model and health damage assessment, health risks of PM_x for three sensitive occupational groups were calculated and converted to life and economic loss. Results revealed that dust suppressants can indeed mitigate PM pollution and its accompanying health risks and health damage in road dust, but at a limited efficiency. By spraying dust suppressants, the total PM-related life loss reduced by 1.60E-02 years and 2.50E-04 years in urban and suburban areas on average, and the total willingness to pay (WTP) values decreased by 120 and 50 US$ for PM_2.5 and PM₁₀, indicating a more considerable environmental gain if dust suppressants were sprayed in additional regions when necessary. Overall, our study demonstrated that the effectiveness of dust suppressants cannot be pictured only by the variations of pollutant concentrations, and indicators with practice and economic value should be more useful for traffic-related pollution management.

Associations of Reduced Ambient PM2.5 Level With Lower Plasma Glucose Concentration and Decreased Risk of Type 2 Diabetes in Adults: A Longitudinal Cohort Study

It remains unknown whether reduced air pollution levels can prevent type 2 diabetes mellitus. In this study, we investigated the associations between dynamic changes in long-term exposure to ambient fine particulate matter, defined as particulate matter with an aerodynamic diameter ≤2.5 μm (PM2.5), and changes in fasting plasma glucose (FPG) levels and incidence of type 2 diabetes. A total of 151,398 adults (ages ≥18 years) were recruited in Taiwan between 2001 and 2014. All participants were followed up for a mean duration of 5.0 years. Change in PM2.5 (ΔPM2.5) was defined as the value at a follow-up visit minus the corresponding value at the immediately preceding visit. The PM2.5 concentration in Taiwan increased during 2002-2004 and began to decrease in 2005. Compared with participants with little or no change in PM2.5 exposure, those with the largest decrease in PM2.5 had a decreased FPG level (β = -0.39, 95% confidence interval: -0.47, -0.32) and lower risk of type 2 diabetes (hazard ratio = 0.86, 95% confidence interval: 0.80, 0.93). The sensitivity analysis and analyses stratified by sex, age, body mass index, smoking, alcohol drinking, and hypertension generally yielded similar results. Improved PM2.5 air quality is associated with a better FPG level and a decreased risk of type 2 diabetes development.

Ambient air pollution and posttransplant outcomes among kidney transplant recipients

Fine particulate matter (PM2.5 ), a common form of air pollution which can induce systemic inflammatory response, is a risk factor for adverse health outcomes. Kidney transplant (KT) recipients are likely vulnerable to PM2.5 due to comorbidity and chronic immunosuppression. We sought to quantify the association between PM2.5 and post-KT outcomes. For adult KT recipients (1/1/2010-12/31/2016) in the Scientific Registry of Transplant Recipients, we estimated annual zip-code level PM2.5 concentrations at the time of KT using NASA's SEDAC Global PM2.5 Grids. We determined the associations between PM2.5 and delayed graft function (DGF) and 1-year acute rejection using logistic regression and death-censored graft failure (DCGF) and mortality using Cox proportional hazard models. All models were adjusted for sociodemographics, recipient, transplant, and ZIP code level confounders. Among 87 233 KT recipients, PM2.5 was associated with increased odds of DGF (OR = 1.59; 95% CI: 1.48-1.71) and 1-year acute rejection (OR = 1.31; 95% CI: 1.17-1.46) and increased risk of all-cause mortality (HR = 1.15; 95% CI: 1.07-1.23) but not DCGF (HR = 1.05; 95% CI: 0.97-1.51). In conclusion, PM2.5 was associated with higher odds of DGF and 1-year acute rejection and elevated risk of mortality among KT recipients. Our study highlights the importance of considering environmental exposure as risk factors for post-KT outcomes.

Reanalysis of the association between reduction in long-term PM2.5 concentrations and improved life expectancy

BACKGROUND

Much of the current evidence of associations between long-term PM_2.5 and health outcomes relies on national or regional analyses using exposures derived directly from regulatory monitoring data. These findings could be affected by limited spatial coverage of monitoring data, particularly for time periods before spatially extensive monitoring began in the late 1990s. For instance, Pope et al. (2009) showed that between 1980 and 2000 a 10 μg/m³ reduction in PM_2.5 was associated with an average 0.61 year (standard error (SE) = 0.20) longer life expectancy. That analysis used 1979-1983 averages of PM_2.5 across 51 U.S. Metropolitan Statistical Areas (MSAs) computed from about 130 monitoring sites. Our reanalysis re-examines this association using modeled PM_2.5 in order to assess population- or spatially-representative exposure. We hypothesized that modeled PM_2.5 with finer spatial resolution provides more accurate health effect estimates compared to limited monitoring data.

METHODS

We used the same data for life expectancy and confounders, as well as the same analysis models, and investigated the same 211 continental U.S. counties, as Pope et al. (2009). For modeled PM_2.5, we relied on a previously-developed point prediction model based on regulatory monitoring data for 1999-2015 and back-extrapolation to 1979. Using this model, we predicted annual average concentrations at centroids of all 72,271 census tracts and 12,501 25-km national grid cells covering the contiguous U.S., to represent population and space, respectively. We averaged these predictions to the county for the two time periods (1979-1983 and 1999-2000), whereas the original analysis used MSA averages given limited monitoring data. Finally, we estimated regression coefficients for PM_2.5 reduction on life expectancy improvement over the two periods, adjusting for area-level confounders.

RESULTS

A 10 μg/m³ decrease in modeled PM_2.5 based on census tract and national grid predictions was associated with 0.69 (standard error (SE) = 0.31) and 0.81 (0.29) -year increases in life expectancy. These estimates are higher than the estimate of Pope et al. (2009); they also have larger SEs likely because of smaller variability in exposure predictions, a standard property of regression. Two sets of effect estimates, however, had overlapping confidence intervals.

CONCLUSIONS

Our approach for estimating population- and spatially-representative PM_2.5 concentrations based on census tract and national grid predictions, respectively, provided generally consistent findings to the original findings using limited monitoring data. This finding lends additional support to the evidence that reduced fine particulate matter contributes to extended life expectancy.

The Effect of Particulate Matter Reduction by Indoor Air Filter Use on Respiratory Symptoms and Lung Function: A Systematic Review and Meta-analysis

PURPOSE

Exposure to particulate matter (PM) is a key public health issue, but effective intervention has not yet been established. A systematic literature review and meta-analysis has been conducted to assess the relationship between the use of air filters, one of the most commonly studied interventions, and respiratory outcomes in patients with chronic respiratory diseases.

METHODS

We systematically reviewed intervention studies on PM using PubMed, EMBASE, and Cochrane databases up to September 2019. Studies that included data on PM concentration changes and respiratory symptoms or lung function in patients with respiratory diseases were eligible for inclusion. Effect estimates were quantified separately using the random-effects model.

RESULTS

Six studies were included in the quantitative analysis. Air filter use reduced indoor PM2.5 by 11.45 µg/m³ (95% confidence interval [CI], 6.88, 16.01 µg/m³). Air filter use was not associated with improvements in respiratory symptoms in 5 of the 6 studies or significant changes in the predicted forced expiratory volume in one second (FEV1) (mean change, -1.77%; 95% CI, -8.25%, 4.71%). Air filter use was associated with improved peak expiratory flow rate by 5.86 (95% CI, 3.5, 8.19 of standardized difference).

CONCLUSIONS

The findings of this systematic review suggest that air filters may reduce indoor PM and increase peak expiratory rate in asthmatic patients. However, most studies showed no significant effects of air filters on respiratory symptoms or FEV1. Further studies in regions with high-density PM may provide additional information on this issue.

TRIAL REGISTRATION

PROSPERO Identifier: CRD42020156258.

Exposure to Air Pollution in Relation to Risk of Dementia and Related Outcomes: An Updated Systematic Review of the Epidemiological Literature

BACKGROUND

Dementia is a devastating neurologic condition that is common in older adults. We previously reviewed the epidemiological evidence examining the hypothesis that long-term exposure to air pollution affects dementia risk. Since then, the evidence base has expanded rapidly.

OBJECTIVES

With this update, we collectively review new and previously identified epidemiological studies on air pollution and late-life cognitive health, highlighting new developments and critically discussing the merits of the evidence.

METHODS

Using a registered protocol (PROSPERO 2020 CRD42020152943), we updated our literature review to capture studies published through 31 December 2020, extracted data, and conducted a bias assessment.

RESULTS

We identified 66 papers (49 new) for inclusion in this review. Cognitive level remained the most commonly considered outcome, and particulate matter (PM) remained the most commonly considered air pollutant. Since our prior review, exposure estimation methods in this research have improved, and more papers have looked at cognitive change, neuroimaging, and incident cognitive impairment/dementia, though methodological concerns remain common. Many studies continue to rely on administrative records to ascertain dementia, have high potential for selection bias, and adjust for putative mediating factors in primary models. A subset of 35 studies met strict quality criteria. Although high-quality studies of fine particulate matter with aerodynamic diameter ≤ 2.5 μ m (PM 2.5 ) and cognitive decline generally supported an adverse association, other findings related to PM 2.5 and findings related to particulate matter with aerodynamic diameter ≤ 10 μ m (PM 10 , NO 2 , and NO x ) were inconclusive, and too few papers reported findings with ozone to comment on the likely direction of association. Notably, only a few findings on dementia were included for consideration on the basis of quality criteria.

DISCUSSION

Strong conclusions remain elusive, although the weight of the evidence suggests an adverse association between PM 2.5 and cognitive decline. However, we note a continued need to confront methodological challenges in this line of research. https://doi.org/10.1289/EHP8716.

Fear in a Handful of Dust: The Epidemiological, Environmental, and Economic Drivers of Death by PM2.5 Pollution

This study evaluates numerous epidemiological, environmental, and economic factors affecting morbidity and mortality from PM2.5 exposure in the 27 member states of the European Union. This form of air pollution inflicts considerable social and economic damage in addition to loss of life and well-being. This study creates and deploys a comprehensive data pipeline. The first step consists of conventional linear models and supervised machine learning alternatives. Those regression methods do more than predict health outcomes in the EU-27 and relate those predictions to independent variables. Linear regression and its machine learning equivalents also inform unsupervised machine learning methods such as clustering and manifold learning. Lower-dimension manifolds of this dataset's feature space reveal the relationship among EU-27 countries and their success (or failure) in managing PM2.5 morbidity and mortality. Principal component analysis informs further interpretation of variables along economic and health-based lines. A nonlinear environmental Kuznets curve may describe the fuller relationship between economic activity and premature death from PM2.5 exposure. The European Union should bridge the historical, cultural, and economic gaps that impair these countries' collective response to PM2.5 pollution.

Combining machine learning models through multiple data division methods for PM2.5 forecasting in Northern Xinjiang, China

In this study, daily average PM_2.5 forecasting models were developed and applied in the Northern Xinjiang, China, through combining the back propagation artificial neural network (BPANN) and multiple linear regression (MLR) with another BPANN model. The meteorological (daily average precipitation, pressure, relative humidity, temperature, and wind speed, daily maximum wind speed and sunshine hours on the same day) and air pollutant data (daily PM_2.5, PM₁₀, SO₂, CO, NO₂, and O₃ concentrations on the previous day) in January and August of each year from 2015 to 2019 were used as candidate inputs. The optimal member and combining models were evaluated through the leave-one-out cross-validation (LOOCV), fivefold cross-validation, and hold-out methods. Twelve member models with optimal or sub-optimal performance were further used to develop the combining models. The performances of the BPANN and MLR member models were different using three data division methods. The models were evaluated more comprehensively through the LOOCV. The performances of the combining models were generally better than the member models. For both member and combining models, the PM_2.5 forecasting model performance in August was generally better than in January. The correlation coefficient (R) for the validation set of the optimal combination model was about 0.87 in January and 0.946 in August. These results showed that combining linear and nonlinear models through multiple data division methods would be an effective tool to forecast PM_2.5 concentrations.

Respiratory Impacts of Wildland Fire Smoke: Future Challenges and Policy Opportunities. An Official American Thoracic Society Workshop Report

Wildland fires are diminishing air quality on a seasonal and regional basis, raising concerns about respiratory health risks to the public and occupational groups. This American Thoracic Society (ATS) workshop was convened in 2019 to meet the growing health threat of wildland fire smoke. The workshop brought together a multidisciplinary group of 19 experts, including wildland fire managers, public health officials, epidemiologists, toxicologists, and pediatric and adult pulmonologists. The workshop examined the following four major topics: 1) the science of wildland fire incidence and fire management, 2) the respiratory and cardiovascular health effects of wildland fire smoke exposure, 3) communication strategies to address these health risks, and 4) actions to address wildland fire health impacts. Through formal presentations followed by group discussion, workshop participants identified top priorities for fire management, research, communication, and public policy to address health risks of wildland fires. The workshop concluded that short-term exposure to wildland smoke causes acute respiratory health effects, especially among those with asthma and chronic obstructive pulmonary disease. Research is needed to understand long-term health effects of repeated smoke exposures across fire seasons for children, adults, and highly exposed occupational groups (especially firefighters). Other research priorities include fire data collection and modeling, toxicology of different fire fuel sources, and the efficacy of health protective measures to prevent respiratory effects of smoke exposure. The workshop committee recommends a unified federal response to the growing problem of wildland fires, including investment in fire behavior and smoke air quality modeling, research on the health impacts of smoke, and development of robust clinical and public health communication tools.

Impacts of Thermal Environments on Health Risk: A Case Study of Harris County, Texas

The loss of green spaces in urbanized areas has triggered a potential thermal risk in the urban environment. While the existing literature has investigated the direct relationship between urban temperatures and health risks, little is known about causal relationships among key components of urban sustainability and health risks, through a pathway involving urban temperature. This study examined the multiple connections between urbanized land use, urban greenery, urban temperatures and health risks in Harris County, Texas. The census tract-level health data from the 500 Cities Project (Centers for Disease Control and Prevention) is used for analysis. Structural equation model analyses showed that the urban temperature played a mediating role in associations between urbanized land use, urban greenery and health risk. Urban vegetation is associated with a decrease in health risks, while urban land use has associations with an increase in health risks. Findings suggest that proactive policies tailored to provide rich urban greenery in a neighborhood can alleviate urban land use effects on health risks.

Reduced Ambient PM2.5 Was Associated with a Decreased Risk of Chronic Kidney Disease: A Longitudinal Cohort Study

Many countries have dedicated to the mitigation of air pollution in the past several decades. However, evidence of beneficial effects of air quality improvement on chronic kidney disease (CKD) remains limited. We thus investigated the effects of dynamic changes (including deterioration and improvement) in air quality on the incidence of CKD in a longitudinal study in Taiwan. During 2001-2016, this study recruited a total of 163,197 Taiwanese residents who received at least two standard physical examinations. The level of fine particle matter (PM_2.5) was estimated using a high-resolution (1 km²) satellite-based spatio-temporal model. We defined changes of PM_2.5 concentrations (ΔPM_2.5) as the difference between the two-year average measurements during follow-up and during the immediately preceding visit. The time-dependent Cox regression model was adopted to evaluate the relationships between ΔPM_2.5 and the incidence of CKD after adjusting for a series of covariates. The concentrations of PM_2.5 in Taiwan peaked around 2004 and began to decrease since 2005. We observed an approximate linear concentration-response relationship of ΔPM_2.5 with CKD incidence. Every 5 μg/m³ decrease in the ambient concentration of PM_2.5 was associated with a 25% reduced risk of CKD development [hazard ratio (HR): 0.75; 95% CI: 0.73, 0.78]. In conclusion, this study demonstrated that the improvement of PM_2.5 air quality might be associated with a lower risk of CKD development. Our findings indicate that reducing air pollution may effectively prevent the development of CKD.

Ambient Air Pollution and Mortality among Older Patients Initiating Maintenance Dialysis

BACKGROUND

Fine particulate matter (particulate matter with diameter <2.5 µm [PM2.5]) is associated with CKD progression and may impact the health of patients living with kidney failure. While older (aged ≥65 years) adults are most vulnerable to the impact of PM2.5, it is unclear whether older patients on dialysis are at elevated risk of mortality when exposed to fine particulate matter.

METHODS

Older adults initiating dialysis (2010-2016) were identified from US Renal Data System (USRDS). PM2.5 concentrations were obtained from NASA's Socioeconomic Data and Application Center (SEDAC) Global Annual PM2.5 Grids. We investigated the association between PM2.5 and all-cause mortality using Cox proportional hazard models with linear splines [knot at the current Environmental Protection Agency (EPA) National Ambient Air Quality Standard for PM2.5 of 12 μg/m3] and robust variance.

RESULTS

For older dialysis patients who resided in areas with high PM2.5, a 10 μg/m3 increase in PM2.5 was associated with 1.16-fold (95% CI: 1.08-1.25) increased risk of mortality; furthermore, those who were female (aHR = 1.26, 95% CI: 1.13-1.42), Black (aHR = 1.31, 95% CI: 1.09-1.59), or had diabetes as a primary cause of kidney failure (aHR = 1.25, 95% CI: 1.13-1.38) were most vulnerable to high PM2.5. While the mortality risk associated with PM2.5 was stronger at higher levels (aHR = 1.19, 95% CI: 1.08-1.32), at lower levels (≤12 μg/m3), PM2.5 was significantly associated with mortality risk (aHR = 1.04, 95% CI: 1.00-1.07) among patients aged ≥75 years (Pslope difference = 0.006).

CONCLUSIONS

Older adults initiating dialysis who resided in ZIP codes with PM2.5 levels >12 μg/m3 are at increased risk of mortality. Those aged >75 were at elevated risk even at levels below the EPA Standard for PM2.5.

Improvement in life expectancy for ischemic heart diseases by achieving daily ambient PM2.5 standards in China

BACKGROUND

The potential impacts of daily ambient fine particulate pollution (PM_2.5) exposure on year of life lost (YLL) due to ischemic heart diseases (IHD) remain uncertain. We aimed to estimate the improvement in IHD-related life expectancy by attaining the daily air quality standards of ambient PM_2.5 in China.

METHODS AND RESULTS

This study was based on daily mortality data covering 96 Chinese cities from 2013 to 2016. Regional- and national-associations between IHD-related YLLs and daily PM_2.5 were estimated by generalized additive models. We further evaluated the IHD-related avoidable YLLs with an assumption that the daily PM_2.5 was below the ambient air quality standards of World Health Organization (WHO) and China, and calculated the improvement of life expectancy by dividing the avoidable YLLs by the overall number of IHD mortality. We totally recorded 1,485,140 IHD deaths from 2013 to 2016. At the national level, we found a positive association between IHD-related YLLs and daily PM_2.5. Per 10 μg/m³ increment of four-day averaged ambient PM_2.5 related to an increase of 0.40 IHD-related YLLs (95% CI: 0.28, 0.51). By achieving the WHO's air quality guideline, we estimated that an averaged number of 1346.94 (95% CI: 932.61, 1761.27) YLLs can be avoided for the IHD deaths in each city. On average, the life expectancy can be improved by 0.15 years (95% CI: 0.11, 0.19) for each death.

CONCLUSIONS

Our study provides a nationwide picture of the life expectancy improvements by reaching the daily PM_2.5 standards in China, indicating that people can live longer in an environment with higher air quality.

2D and 3D Bulk Materials for Environmental Remediation: Air Filtration and Oil/Water Separation

Air and water pollution pose an enormous threat to human health and ecosystems. In particular, particulate matter (PM) and oily wastewater can cause serious environmental and health concerns. Thus, controlling PM and oily wastewater has been a great challenge. Various techniques have been reported to effectively remove PM particles and purify oily wastewater. In this article, we provide a review of the recent advancements in air filtration and oil/water separation using two- and three-dimensional (2D and 3D) bulk materials. Our review covers the advantages, characteristics, limitations, and challenges of air filters and oil/water separators using 2D and 3D bulk materials. In each section, we present representative works in detail and describe the concepts, backgrounds, employed materials, fabrication methods, and characteristics of 2D and 3D bulk material-based air filters and oil/water separators. Finally, the challenges, technical problems, and future research directions are briefly discussed for each section.

Pollution Characteristics of Particulate Matter (PM2.5 and PM10) and Constituent Carbonaceous Aerosols in a South Asian Future Megacity

The future megacity of Faisalabad is of prime interest when considering environmental health because of its bulky population and abundant industrial and anthropogenic sources of coarse particles (PM10) and fine airborne particulate matter (PM2.5). The current study was aimed to investigate the concentration level of PM2.5 and PM10, also the characterization of carbonaceous aerosols including organic carbon (OC), elemental carbon (EC) and total carbon (TC) in PM2.5 and PM10 samples collected from five different sectors (residential, health, commercial, industrial, and vehicular zone). The data presented here are the first of their kind in this sprawling city having industries and agricultural activities side by side. Results of the study revealed that the mass concentration of PM2.5 and PM10 is at an elevated level throughout Faisalabad, with ambient PM2.5 and PM10 points that constantly exceeded the 24-h standards of US-EPA, and National Environment Quality Standards (NEQS) which poses harmful effects on the quality of air and health. The total carbon concentration varied between 21.33 and 206.84 μg/m3, and 26.08 and 211.15 μg/m3 with an average of 119.16 ± 64.91 μg/m3 and 124.71 ± 64.38 μg/m3 for PM2.5 in summer and winter seasons, respectively. For PM10, the concentration of TC varied from 34.52 to 289.21 μg/m3 with an average of 181.50 ± 87.38 μg/m3 (for summer season) and it ranged between 44.04 and 300.02 μg/m3 with an average of 191.04 ± 87.98 μg/m3 (winter season), respectively. No significant difference between particulate concentration and weather parameters was observed. Similarly, results of air quality index (AQI) and pollution index (PI) stated that the air quality of Faisalabad ranges from poor to severely pollute. In terms of AQI, moderate pollution was recorded on sampling sites in the following order; Ittehad Welfare Dispensary > Saleemi Chowk > Kashmir Road > Pepsi Factory, while at Nazria Pakistan Square and Allied Hospital, higher AQI values were recorded. The analysis and results presented in this study can be used by policy-makers to apply rigorous strategies that decrease air pollution and the associated health effects in Faisalabad.