Air Pollution Studies Research Articles

Role of epidemiology in the EU policy formulation of chemicals

Abstract Over the past 50 years, the European Union has built a robust legal framework for managing chemicals. This framework balances the benefits of using chemicals for societal well-being and economic prosperity with the need to protect human health and the environment from potential risks. As part of the EU’s Zero Pollution ambition in the context of the Green Deal, the European Commission adopted in 2020 the Chemicals Strategy for Sustainability, with the aim to better protect human health and the environment from harmful chemicals, while boosting innovation by promoting the use of safer and more sustainable chemicals. Assessing quantitative health impacts within the EC Better Regulation guidance typically involves indicators measuring the environmental burden of disease (EBD), providing a useful mean for legislators to evaluate the benefits of policy actions both in terms of health gains and cost. While such analyses are common in air pollution studies, challenges arise in the chemical legislation area, particularly in non-occupational settings, where the population is exposed to low concentrations of many chemicals through multiple exposure routes. In such contexts, the intrinsic complexities linked to exposure characterization and to the assessment of causality between the exposure and the health outcome may hinder the estimation of benefits of legislative actions. Debates may arise regarding the reliability of the underlying epidemiological studies, making challenging for policymakers to ascertain the robustness and generalizability of the findings of such analyses. Our work provides a summary and analysis of recent case studies in the context of chemicals. We focus on how epidemiological evidence was used in conducting EBD analyses in supporting better formulation of EU polices of chemicals. Speakers/Panelists Marleen Bekker Wageningen University & Research, Wageningen, Netherlands

Preliminary Study of Air Pollution and Adverse Pregnancy Outcomes: A Mendelian Randomization Study

The chief aim of this research is to investigate the causality of air pollutants and adverse pregnancy outcomes. Two-sample Mendelian randomization was conducted, employing genetic variants connected with air pollution as instrumental variables. Sixteen adverse pregnancy outcomes were extracted as the main outcome measures from the genome-wide association study (GWAS). The inverse-variance weighted (IVW) method was conducted as the primary analysis method. This study found that there were causal association between NO2 and pre-eclampsia (weighted median: OR = 1.30, 95% CI = [1.03–1.64], p = 0.029) and between PM2.5 and placental abruption (IVW: OR = 10.94, 95% CI = [1.28–93.45], p = 0.029). There were potential causal relationships between NO2 and gestational hypertension (IVW: OR = 1.14, 95% CI = [0.99–1.30], p = 0.060); NO2 and placental abruption (IVW: OR = 1.97, 95% CI = [0.90–4.28], p = 0.089); NOx and fetal growth restriction (IVW: OR = 0.06, 95% CI = [0.99–1.12], p = 0.089); PM2.5 and slow fetal growth and fetal malnutrition (MR–Egger: OR = 54,240.95, 95% CI = [2.08–1,411,757,729.46], p = 0.059); PM10 and hyperemesis gravidarum (MR–Egger: OR = 0.12, 95% CI = [0.02–0.97], p = 0.086); PM10 and preterm birth (weighted median: OR = 1.60, 95% CI = [0.95–2.70], p = 0.075); and PM10 and spontaneous abortion (weighted median: OR = 1.60, 95% CI = [0.95–2.70], p = 0.075). There was no pleiotropy, but there was some heterogeneity. In conclusion, air pollution has a causal effect on several adverse pregnancy outcomes.

Comparative Study of Air Pollution with Ayurveda and its Management

Background Environmental pollution is increasing day by day and imposing severe and irreversible damage to the world. Air pollution is one of the biggest threats for the environment and affecting humans, animals, crops, cities, forests, aquatic ecosystems. Environmental Toxicology is the science concerned with study of harmful effects of various chemical, biological and physical agents on living organisms. In Ayurveda Charakacharya has briefly described the environmental health in chapter named Janpadodhvansaniyavimanam. Ayurveda has a dedicated branch called Agadatantra which deals with the toxicological aspects of living entities of environment. Aims and objectives We aim to relate and validate this knowledge pertaining to the air pollution. Material and method the references available regarding the air pollution in classical texts were studied and compared with the available information in the contemporary medical literatures. Signs of air pollution given in the text compared and studied with signs of Air pollution. Discussion Ayurveda terms of Vikrut and Prakrut Vayu described in Granthas are found to be relatable with contemporary findings. Conclusion Air pollution described in Ayurveda are very precise and explanatory. Management of air pollution with this ancient science are the new open windows for healthy air breathing for every living organism.

Ratios of organic mass to organic carbon in fine particulate matter at urban sites in China and Korea during winter and summer.

This study evaluates the composition and seasonal characteristics of fine particulate matter (PM2.5) during winter and summer through simultaneous measurements conducted at the Gwangju Institute of Science and Technology in South Korea and the Changping campus of Peking University in China. PM2.5 samples were concurrently collected at both sites, and chemical analyses were conducted to quantify various components, including carbonaceous materials, ionic species, and metals. Although the average PM2.5 concentrations were comparable between the two sites, there were distinct differences in the concentrations of major components. Organic indicator compounds were analyzed to discern the contributions of primary and secondary pollution sources. Changping displayed a mix of primary and secondary pollution, characterized by higher concentrations of primary organic carbon (POC) such as polycyclic aromatic hydrocarbons and hopanes, compared to Gwangju. In contrast, Gwangju demonstrated a higher prevalence of secondary organic carbon (SOC), particularly water-soluble organic carbon not related to biomass burning (WSOCnbb) and various polar organic compounds. The organic mass to organic carbon (OM/OC) ratios estimated using the mass balance method revealed significant differences, with Gwangju showing a higher ratio of 2.3 compared to 1.9 at Changping, indicating a greater influence of secondary pollutants at Gwangju. Additionally, both Changping and Gwangju exhibited higher OM/OC ratios in summer (Changping: 2.0, Gwangju: 2.5) compared to winter (Changping: 1.8, Gwangju: 2.2), indicating seasonal differences in organic mass contributions to PM2.5. These findings underscore the importance of accounting for spatial and seasonal variations in air pollution studies and suggest that updating commonly used OM/OC ratios could enhance the reliability of research outcomes.

Air Pollution and Parkinson Disease in a Population-Based Study

The role of air pollution in risk and progression of Parkinson disease (PD) is unclear. To assess whether air pollution is associated with increased risk of PD and clinical characteristics of PD. This population-based case-control study included patients with PD and matched controls from the Rochester Epidemiology Project from 1998 to 2015. Data were analyzed from January to June 2024. Mean annual exposure to particulate matter with a diameter of 2.5 µm or less (PM2.5) from 1998 to 2015 and mean annual exposure to nitrogen dioxide (NO2) from 2000 to 2014. Outcomes of interest were PD risk, all-cause mortality, presence of tremor-predominant vs akinetic rigid PD, and development of dyskinesia. Models were adjusted for age, sex, race and ethnicity, year of index, and urban vs rural residence. A total of 346 patients with PD (median [IQR] age 72 [65-80] years; 216 [62.4%] male) were identified and matched on age and sex with 4813 controls (median [IQR] age, 72 [65-79] years, 2946 [61.2%] male). Greater PM2.5 exposure was associated with increased PD risk, and this risk was greatest after restricting to populations within metropolitan cores (odds ratio [OR], 1.23; 95% CI, 1.11-1.35) for the top quintile of PM2.5 exposure compared with the bottom quintile. Greater NO2 exposure was also associated with increased PD risk when comparing the top quintile with the bottom quintile (OR, 1.13; 95% CI, 1.07-1.19). Air pollution was associated with a 36% increased risk of akinetic rigid presentation (OR per each 1-μg/m3 increase in PM2.5, 1.36; 95% CI, 1.02-1.80). In analyses among patients with PD only, higher PM2.5 exposure was associated with greater risk for developing dyskinesia (HR per 1-μg/m3 increase in PM2.5, 1.42; 95% CI, 1.17-1.73), as was increased NO2 exposure (HR per 1 μg/m3 increase in NO2, 1.13; 95% CI, 1.06-1.19). There was no association between PM2.5 and all-cause mortality among patients with PD. In this case-control study of air pollution and PD, higher levels of PM2.5 and NO2 exposure were associated with increased risk of PD; also, higher levels of PM2.5 exposure were associated with increased risk of developing akinetic rigid PD and dyskinesia compared with patients with PD exposed to lower levels. These findings suggest that reducing air pollution may reduce risk of PD, modify the PD phenotype, and reduce risk of dyskinesia.

Epigenome-wide association study of ambient air pollution in a racially and ethnically diverse population of smokers: The Multiethnic Cohort Study

Epigenome-wide association study of ambient air pollution in a racially and ethnically diverse population of smokers: The Multiethnic Cohort Study

PM2.5 and cognition changes in six US metropolitan areas: The Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air)

PM2.5 and cognition changes in six US metropolitan areas: The Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air)

Household Air Pollution and Postpartum Blood Pressure in the Ghana Randomized Air Pollution and Health Study

Household Air Pollution and Postpartum Blood Pressure in the Ghana Randomized Air Pollution and Health Study

The Impact of Human Activities on Air Pollution in the Fallujah City, Al-Anbar Province – West Iraq

Air pollutant field study and laboratory sample analyses revealed that most of the air pollutants in Fallujah City come from various human activities. These activities: Factories, Bakeries, Private electric generators, etc represent the major sources of gaseous and particulate pollutants. Those emissions have affected the air quality of the air in study areas. This research aimed to identify air pollutant concentrations, and their effects, and develop immediate solutions to reduce their health and environmental impacts. Air pollutant measurements were taken for four sites, with each site having generators and bakeries, another five sites representing industrial activities, and another site representing the residential areas. These measurements which included total suspended particles (TSP), PM10, PM2.5, nitrogen dioxide (NO2), sulphate dioxide (SO2), methane (CH4) and (CO) were conducted in the winter and summer seasons. The plaster and asphalt factories and industrial district locations recorded the highest concentrations of particle pollutants (TSP, PM10, and PM2.5) and gases (NO2, SO2, CH4, and CO). It was also observed that there was an increase in the concentrations of total suspended particles, in addition to some gases measured at the sites of bread ovens and private electric generators, especially in the summer. Most of the sites recorded values higher than the local environmental allowable limits. The high concentrations of air pollutants measured at the study sites are due to the increased demand for electrical energy and the use of private electrical generators to compensate for the lack of electrical energy emitted by high air pollutants. In addition to the emissions of cement, plaster, and asphalt factories and the large quantities of suspended particles they release into the atmosphere resulting from crushing operations and loading operations for raw materials, in addition to the polluting gases they release resulting from the use of black oil, as well as the use of black oil as fuel in the bakeries, which leads to an increase in pollutant concentrations will, therefore, negatively affect air quality.

The impact of digital inclusive finance on environmental pollution: A case study of air pollution.

This study delves into the impact of digital inclusive finance on environmental pollution, with a specific focus on air pollution. Utilizing data from 265 Chinese cities, advanced econometric methods such as the bi-directional fixed effects model, threshold model, spatial Durbin model, and multi-period difference-in-differences model are employed, incorporating a variety of control variables. The empirical findings indicate that digital inclusive finance significantly reduces air pollution. This mechanism chiefly operates through enhancing public environmental consciousness and fostering green technological innovation. The study also uncovers the spatial spillover effect and non-linear characteristics of digital inclusive finance on air pollution, along with its interactive effects with specific policies (e.g., smart city pilot policies and the "major protection, no major development" initiative). Moreover, heterogeneity analysis reveals regional variations in the environmental effects of digital inclusive finance. These insights provide a novel perspective on the relationship between financial technology and environmental protection and offer crucial guidance for policymaking.

Epigenome-wide association study of fluoride exposure during early adolescence and DNA methylation among U.S. children

Exposure to fluoride in early childhood has been associated with altered cognition, intelligence, attention, and neurobehavior. Fluoride-related neurodevelopment effects have been shown to vary by sex and very little is known about the mechanistic processes involved. There is limited research on how fluoride exposure impacts the epigenome, potentially leading to changes in DNA methylation of specific genes regulating key developmental processes. In the Cincinnati Childhood Allergy and Air Pollution Study (CCAAPS), urine samples were analyzed using a microdiffusion method to determine childhood urinary fluoride adjusted for specific gravity (CUFsg) concentrations. Whole blood DNA methylation was assessed using the Infinium MethylationEPIC BeadChip 850 k Array. In a cross-sectional analysis, we interrogated epigenome-wide DNA methylation at 775,141 CpG loci across the methylome in relation to CUFsg concentrations in 272 early adolescents at age 12 years. Among all participants, higher concentrations of CUF were associated with differential methylation of one CpG (p < 6 × 10−8) located in the gene body of GBF1 (cg25435255). Among females, higher concentrations of CUFsg were associated with differential methylation of 7 CpGs; only three CpGs were differentially methylated among males with no overlap of significant CpGs observed among females. Secondary analyses revealed several differentially methylated regions (DMRs) and CpG loci mapping to genes with key roles in psychiatric outcomes, social interaction, and cognition, as well as immunologic and metabolic phenotypes. While fluoride exposure may impact the epigenome during early adolescence, the functional consequences of these changes are unclear warranting further investigation.

Assessing long-term effects of gaseous air pollution exposure on mortality in the United States using a variant of difference-in-differences analysis

Long-term mortality effects of particulate air pollution have been investigated in a causal analytic frame, while causal evidence for associations with gaseous air pollutants remains extensively lacking, especially for carbon monoxide (CO) and sulfur dioxide (SO2). In this study, we estimated the causal relationship of long-term exposure to nitrogen dioxide (NO2), CO, SO2, and ozone (O3) with mortality. Utilizing the data from National Morbidity, Mortality, and Air Pollution Study, we applied a variant of difference-in-differences (DID) method with conditional Poisson regression and generalized weighted quantile sum regression (gWQS) to investigate the independent and joint effects. Independent exposures to NO2, CO, and SO2 were causally associated with increased risks of total, nonaccidental, and cardiovascular mortality, while no evident associations with O3 were identified in the entire population. In gWQS analyses, an interquartile range-equivalent increase in mixture exposure was associated with a relative risk of 1.067 (95% confidence interval: 1.010–1.126) for total mortality, 1.067 (1.009–1.128) for nonaccidental mortality, and 1.125 (1.060–1.193) for cardiovascular mortality, where NO2 was identified as the most significant contributor to the overall effect. This nationwide DID analysis provided causal evidence for independent and combined effects of NO2, CO, SO2, and O3 on increased mortality risks among the US general population.

Learned 1D Passive Scalar Advection to Accelerate Chemical Transport Modeling: A Case Study with GEOS-FP Horizontal Wind Fields

Abstract We developed and applied a machine-learned discretization for one-dimensional (1D) horizontal passive scalar advection, which is an operator component common to all chemical transport models (CTMs). Our learned advection scheme resembles a second-order accurate, three-stencil numerical solver but differs from a traditional solver in that coefficients for each equation term are output by a neural network rather than being theoretically derived constants. We subsampled higher-resolution simulation results—resulting in up to 16× larger grid size and 64× larger time step—and trained our neural-network-based scheme to match the subsampled integration data. In this way, we created an operator that has low resolution (in time or space) but can reproduce the behavior of a high-resolution traditional solver. Our model shows high fidelity in reproducing its training dataset (a single 10-day 1D simulation) and is similarly accurate in simulations with unseen initial conditions, wind fields, and grid spacing. In many cases, our learned solver is more accurate than a low-resolution version of the reference solver, but the low-resolution reference solver achieves greater computational speedup (500× acceleration) over the high-resolution simulation than the learned solver is able to (18× acceleration). Surprisingly, our learned 1D scheme—when combined with a splitting technique—can be used to predict 2D advection and is in some cases more stable and accurate than the low-resolution reference solver in 2D. Overall, our results suggest that learned advection operators may offer a higher-accuracy method for accelerating CTM simulations as compared to simply running a traditional integrator at low resolution. Significance Statement Chemical transport modeling (CTM) is an essential tool for studying air pollution. CTM simulations take a long computing time. Modeling pollutant transport (advection) is the second most computationally intensive part of the model. Decreasing the resolution not only reduces the advection computing time but also decreases accuracy. We employed machine learning to reduce the resolution of advection while keeping the accuracy. We verified the robustness of our solver with several generalization testing scenarios. In our 2D simulation, our solver showed up to 100 times faster simulation with fair accuracy. Integrating our approach to existing CTMs will allow broadened participation in the study of air pollution and related solutions.

An Ecological Association Between Air Pollution and Adolescent Obesity Study.

The purposes of this study were to assess the association between exposure to particulate matter (PM 2.5 ) and adolescent obesity and to identify and visualize the world areas where the problems of adolescent obesity and air pollution by fine PM are more severe. This is an ecological study, based on publicly available data from a World Health Organization site. For each increase in air pollution there was an increase in the probability of being in the higher prevalence obesity group (OR = 1.18 (95% CI, 1.06-1.31). High prevalence rates for both adolescent obesity and air pollution by PM 2.5 were identified in several countries, including Venezuela, Algeria, Libya, Saudi Arabia, Iraq, and Oceania islands. Efforts by local authorities and world organizations should be focused on the countries with the highest prevalence rates for both conditions.

Assessing environmental influences on radon levels: analysis of independent variables

Regression analysis is essential for prediction analysis and variable identification since air pollution studies are complicated by competing suggestions and require careful interpretation. In the existing predictive analysis, estimating indoor radon levels is challenging due to multicollinearity issues and the existing algorithm's assumption of independent predictor variables, making it difficult to accurately assess individual effects. Hence a novel Unsupervised Bayesian Multiple Regression Analysis is used to correctly offer the specific impacts of each predictor variable by taking the complex interactions between factors in the estimation of indoor radon levels. Furthermore, in the variable identification, indoor radon levels are influenced by complex residual distributions, with existing algorithms failing to predict non-Gaussian residuals due to outlier-sensitive least squares estimation. So a novel Quadratic Discriminant Extreme Learning Machine is implemented to overcome this issue, which creates models that are better able to reliably detect the factors driving indoor radon levels and are more robust to non-Gaussian residual distributions. The proposed method demonstrates excellence in predictive analysis and variable identification achieving high coefficient of relation and low MAE.

A study of indoor air pollution caused by disinfection equipment as a consequence of infectious waste management

ABSTRACT Infectious waste disinfection is an essential process in medical waste management that may cause release of some pollutants. In this study, the PAHs concentration at the disinfection was investigated. The change in the release rate of PAHs in two including infectious waste reduction and increasing the segregation ratio was estimated. The results showed that the PAHs concentration was 1172 – 2066 ng/m3. The specific concentration of PAHs was 852 ng/ton of infectious waste in average. The annual emission of the PAHs resulting from infectious waste disinfection is estimated to be 612.6 kg. Reduction of infectious waste caused by redefining infectious waste and increasing the segregation ratio leads to reduction of PAHs concentration by 50%. Increasing the ratio of segregation and redefinition of infectious waste that led to reduced waste loading volume are essential measures that reduce the emissions of pollutants as by-products of disinfection.

Health effects of air pollution on respiratory symptoms: A longitudinal study using digital health sensors

Previous studies of air pollution and respiratory disease often relied on aggregated or lagged acute respiratory disease outcome measures, such as emergency department (ED) visits or hospitalizations, which may lack temporal and spatial resolution. This study investigated the association between daily air pollution exposure and respiratory symptoms among participants with asthma and chronic obstructive pulmonary disease (COPD), using a unique dataset passively collected by digital sensors monitoring inhaled medication use. The aggregated dataset comprised 456,779 short-acting beta-agonist (SABA) puffs across 3,386 people with asthma or COPD, between 2012 and 2019, across the state of California. Each rescue use was assigned space–time air pollution values of nitrogen dioxide (NO2), fine particulate matter with diameter ≤ 2.5 µm (PM2.5) and ozone (O3), derived from highly spatially resolved air pollution surfaces generated for the state of California. Statistical analyses were conducted using linear mixed models and random forest machine learning. Results indicate that daily air pollution exposure is positively associated with an increase in daily SABA use, for individual pollutants and simultaneous exposure to multiple pollutants. The advanced linear mixed model found that a 10-ppb increase in NO2, a 10 μg m−3 increase in PM2.5, and a 30-ppb increase in O3 were respectively associated with incidence rate ratios of SABA use of 1.025 (95 % CI: 1.013–1.038), 1.054 (95 % CI: 1.041–1.068), and 1.161 (95 % CI: 1.127–1.233), equivalent to a respective 2.5 %, 5.4 % and 16 % increase in SABA puffs over the mean. The random forest machine learning approach showed similar results.This study highlights the potential of digital health sensors to provide valuable insights into the daily health impacts of environmental exposures, offering a novel approach to epidemiological research that goes beyond residential address. Further investigation is warranted to explore potential causal relationships and to inform public health strategies for respiratory disease management.

Environmental pollution and extreme weather conditions: insights into the effect on mental health.

Environmental pollution exposures, including air, soil, water, light, and noise pollution, are critical issues that may implicate adverse mental health outcomes. Extreme weather conditions, such as hurricanes, floods, wildfires, and droughts, may also cause long-term severe concerns. However, the knowledge about possible psychiatric disorders associated with these exposures is currently not well disseminated. In this review, we aim to summarize the current knowledge on the impact of environmental pollution and extreme weather conditions on mental health, focusing on anxiety spectrum disorders, autism spectrum disorders, schizophrenia, and depression. In air pollution studies, increased concentrations of PM2.5, NO2, and SO2 were the most strongly associated with the exacerbation of anxiety, schizophrenia, and depression symptoms. We provide an overview of the suggested underlying pathomechanisms involved. We highlight that the pathogenesis of environmental pollution-related diseases is multifactorial, including increased oxidative stress, systematic inflammation, disruption of the blood-brain barrier, and epigenetic dysregulation. Light pollution and noise pollution were correlated with an increased risk of neurodegenerative disorders, particularly Alzheimer's disease. Moreover, the impact of soil and water pollution is discussed. Such compounds as crude oil, heavy metals, natural gas, agro-chemicals (pesticides, herbicides, and fertilizers), polycyclic or polynuclear aromatic hydrocarbons (PAH), solvents, lead (Pb), and asbestos were associated with detrimental impact on mental health. Extreme weather conditions were linked to depression and anxiety spectrum disorders, namely PTSD. Several policy recommendations and awareness campaigns should be implemented, advocating for the advancement of high-quality urbanization, the mitigation of environmental pollution, and, consequently, the enhancement of residents' mental health.

Characteristics of Anthropogenic Pollution in the Atmospheric Air of South-Western Svalbard (Hornsund, Spring 2019)

The character of atmospheric pollution and its impact on surface waters may vary substantially in space, and hence, we add a potentially important location for the studies of atmospheric air pollution to the map of the High Arctic. We have investigated the anthropogenic particle characteristics and selected persistent organic pollutant concentrations, in a priorly unmonitored location in the Arctic (Svalbard), exposed to a climatic gradient. Single-particle analysis of PM indicates that besides the prevailing natural aerosol particles, anthropogenic ones were present. The likely anthropogenic origin of some particles was established for spherical Fe-rich or aluminosilicate particles formed in high-temperature processes or metal-rich particles of the chemical composition corresponding to industrial products and atypical for natural minerals; soot, tar balls, and secondary sulfate were also likely of anthropogenic origin. Some of the observed anthropogenic particles could only come from remote industrial sources. POP concentrations indicated a background of LRAT, consistent with the ΣPCB concentrations and volatility profile. However, the ΣDDX composition indicating aged sources and an order of magnitude higher concentrations of both ΣDDXs and ΣHCHs than at other High Arctic monitoring stations indicate their potential source in two types of re-emission from secondary sources, i.e., from seawater and snowpack, respectively.

Association of outdoor air and noise pollution with unprovoked seizures and new onset epilepsy: A systematic review and meta-analysis.

Research has indicated that certain environmental exposures may increase the risk of unprovoked seizures and new onset epilepsy. This study aimed to synthesize the literature that has estimated the associations between short- and long-term exposure to outdoor air and noise pollution and the risk of unprovoked seizures and new onset epilepsy. We searched Embase, MEDLINE, Scopus, Web of Science, BIOSIS Previews, Latin American and Caribbean Health Sciences Literature, Proquest Dissertations and Theses, conference abstracts, and the gray literature and conducted citation tracing in June 2023. Observational and ecological studies assessing the associations of air and noise pollution with unprovoked seizures or new onset epilepsy were eligible. One reviewer extracted summary data. Using fixed and random effects models, we calculated the pooled risk ratios (RRs) for the studies assessing the associations between short-term exposure to air pollution and unprovoked seizures. Seventeen studies were included, 16 assessing the association of air pollution with seizures and one with epilepsy. Eight studies were pooled quantitatively. Ozone (O3; RR = .99, 95% confidence interval [CI] = .99-.99) and nitrogen dioxide (NO2) exposure adjusted for particulate matter (RR = 1.02, 95% CI = 1.01-1.02) on the same day, and carbon monoxide (CO) exposure 2 days prior (RR = 1.12, 95% CI = 1.02-1.22), were associated with seizure risk. A single study of air pollution and epilepsy did not report a significant association. The risk of bias and heterogeneity across studies was moderate or high. Short-term exposure to O3, NO2, and CO may affect the risk of seizures; however, the effect estimates for O3 and NO2 were minimal. Additional research should continue to explore these and the associations between outdoor air pollution and epilepsy and between noise pollution and seizures and epilepsy.