A cohort study of traffic-related air pollution and mortality in Toronto, Ontario, Canada

Meteorological factors and climate change impact on asthma: a systematic review of epidemiological evidence

OBJECTIVE

This systematic review aimed to investigate the epidemiological data about meteorological factors and climate change (CC) impact on asthma.

DATA SOURCES

A search was performed using three databases (Web of Science, Science Direct, and MEDLINE) for all relevant studies published from January 1, 2018, to December 31, 2022.

STUDY SELECTIONS

This systematic review complied with the PRISMA document's requirements, including studies related to meteorological factors and CC impact on asthma. The search included studies published in English or French language, and was based on title, abstract, and complete text. Documents not meeting inclusion requirements were excluded.

RESULTS

We identified 18 studies published in the last five years that were eligible for inclusion in this review. We found that these studies concerned European, Asian, American, and Oceanic cities. Extreme variations in temperature, humidity, wind speed, exceptional incidents like hurricanes, cold and heat waves, and seasonal shifts were strongly correlated with the worsening of asthmatic symptoms, particularly in childhood. In addition, excessive concentrations of air pollutants and aeroallergens were linked to pediatric asthma emergency hospital admissions.

CONCLUSIONS

A significant association between the consequences of CC and asthma in adults particularly in children has been demonstrated. Future research should quantify the impact of global change in climate regarding the aeroallergens' distribution in terms of geography and time. It is also necessary to research the impact of air pollution on asthmatic health, like sulfur dioxide (SO2), nitrogen dioxide (NO2), ozone (O3), and particles having an aerodynamic diameter lower than 2.5 µm (PM2.5).

Long-term exposure to air pollution on cardio-respiratory, and lung cancer mortality: a systematic review and meta-analysis

Air pollution is a major cause of specific deaths worldwide. This review article aimed to investigate the results of cohort studies for air pollution connected with the all-cause, cardio-respiratory, and lung cancer mortality risk by performing a meta-analysis. Relevant cohort studies were searched in electronic databases (PubMed/Medline, Web of Science, and Scopus). We used a random effect model to estimate the pooled relative risks (RRs) and their 95% CIs (confidence intervals) of mortality. The risk of bias for each included study was also assessed by Office of Health Assessment and Translation (OHAT) checklists. We applied statistical tests for heterogeneity and sensitivity analyses. The registration code of this study in PROSPERO was CRD42023422945. A total of 88 cohort studies were eligible and included in the final analysis. The pooled relative risk (RR) per 10 μg/m3 increase of fine particulate matter (PM2.5) was 1.080 (95% CI 1.068-1.092) for all-cause mortality, 1.058 (95% CI 1.055-1.062) for cardiovascular mortality, 1.066 (95%CI 1.034-1.097) for respiratory mortality and 1.118 (95% CI 1.076-1.159) for lung cancer mortality. We observed positive increased associations between exposure to PM2.5, PM10, black carbon (BC), and nitrogen dioxide (NO2) with all-cause, cardiovascular and respiratory diseases, and lung cancer mortality, but the associations were not significant for nitrogen oxides (NOx), sulfur dioxide (SO2) and ozone (O3). The risk of mortality for males and the elderly was higher compared to females and younger age. The pooled effect estimates derived from cohort studies provide substantial evidence of adverse air pollution associations with all-cause, cardiovascular, respiratory, and lung cancer mortality.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40201-024-00900-6.

Long-term NO2 exposure and mortality: A comprehensive meta-analysis

In response to the World Health Organization's (WHO) revised annual mean nitrogen dioxide (NO2) standard from 40 μg/m3 to 10 μg/m3, reflecting the growing evidence linking long-term exposure to ambient NO2 and excess mortality, we conducted a comprehensive meta-analysis incorporating 11 new studies published since the WHO analysis. Our investigation involved a systematic search of three major databases (PubMed, Web of Science, and Scopus) for articles published until July 1, 2022. We employed random effects models to calculate summarized risk ratios (RR) along with 95% confidence intervals (CIs) for overall and subgroup analyses. Sensitivity analyses were conducted to assess result robustness, and publication bias was evaluated using funnel plots and Egger's linear regression. Out of 2799 identified articles, 56 were included in our meta-analysis. The findings indicate a heightened risk of all-cause, cardiovascular, and respiratory mortality associated with long-term exposure to ambient NO2, with pooled RR values of 1.03 (95% CI: 1.02, 1.05), 1.07 (95% CI: 1.04, 1.10), and 1.03 (95% CI: 1.02, 1.05) per 10 μg/m3 increase, respectively. Substantial heterogeneity (I2 = 84%-96%) among studies was observed. Subgroup analysis revealed significantly elevated RR values in Asia and Oceania (p-value <0.05). The aggregated values for all-cause and cardiovascular mortality were slightly larger than those reported in previous studies. Our study emphasizes the imperative to develop more patient cohorts and conduct age-refined analyses to explore the impact of existing chronic diseases on these associations. Further, additional cohorts in Asia and Oceania are essential to fortify evidence in these regions. Lastly, we recommend using fused multi-source data with higher spatiotemporal resolution for individual exposure representation to minimize heterogeneity among studies in future research.

Ultra-high-resolution mapping of ambient fine particulate matter to estimate human exposure in Beijing

With the decreasing regional-transported levels, the health risk assessment derived from fine particulate matter (PM2.5) has become insufficient to reflect the contribution of local source heterogeneity to the exposure differences. Here, we combined the both ultra-high-resolution PM2.5 concentration with population distribution to provide the personal daily PM2.5 internal dose considering the indoor/outdoor exposure difference. A 30-m PM2.5 assimilating method was developed fusing multiple auxiliary predictors, achieving higher accuracy (R2 = 0.78-0.82) than the chemical transport model outputs without any post-simulation data-oriented enhancement (R2 = 0.31-0.64). Weekly difference was identified from hourly mobile signaling data in 30-m resolution population distribution. The population-weighted ambient PM2.5 concentrations range among districts but fail to reflect exposure differences. Derived from the indoor/outdoor ratio, the average indoor PM2.5 concentration was 26.5 μg/m3. The internal dose based on the assimilated indoor/outdoor PM2.5 concentration shows high exposure diversity among sub-groups, and the attributed mortality increased by 24.0% than the coarser unassimilated model.

Long-term exposure to traffic-related air pollution and non-accidental mortality: A systematic review and meta-analysis

BACKGROUND

The health effects of traffic-related air pollution (TRAP) continue to be of important public health interest across the globe. Following its 2010 review, the Health Effects Institute appointed a new expert Panel to systematically evaluate the epidemiological evidence regarding the associations between long-term exposure to TRAP and selected health outcomes. This paper describes the main findings of the systematic review on non-accidental mortality.

METHODS

The Panel used a systematic approach to conduct the review. An extensive search was conducted of literature published between 1980 and 2019. A new exposure framework was developed to determine whether a study was sufficiently specific to TRAP, which included studies beyond the near-roadway environment. We performed random-effects meta-analysis when at least three estimates were available of an association between a specific exposure and outcome. We evaluated confidence in the evidence using a modified Office of Health Assessment and Translation (OHAT) approach, supplemented with a broader narrative synthesis.

RESULTS

Thirty-six cohort studies were included. Virtually all studies adjusted for a large number of individual and area-level covariates-including smoking, body mass index, and individual and area-level socioeconomic status-and were judged at a low or moderate risk for bias. Most studies were conducted in North America and Europe, and a few were based in Asia and Australia. The meta-analytic summary estimates for nitrogen dioxide, elemental carbon and fine particulate matter-pollutants with more than 10 studies-were 1.04 (95% CI 1.01, 1.06), 1.02 (1.00, 1.04) and 1.03 (1.01, 1.05) per 10, 1 and 5 µg/m³, respectively. Effect estimates are interpreted as the relative risk of mortality when the exposure differs with the selected increment. The confidence in the evidence for these pollutants was judged as high, because of upgrades for monotonic exposure-response and consistency across populations. The consistent findings across geographical regions, exposure assessment methods and confounder adjustment resulted in a high confidence rating using a narrative approach as well.

CONCLUSIONS

The overall confidence in the evidence for a positive association between long-term exposure to TRAP and non-accidental mortality was high.

California's early transition to electric vehicles: Observed health and air quality co-benefits

The transition to electric vehicles is projected to have considerable public health co-benefits, but most evidence regarding air quality and health impacts comes from projections rather than real-world data. We evaluated whether population-level respiratory health and air quality co-benefits were already detectable at the relatively low levels of zero-emissions vehicles (ZEVs: battery electric, plug-in hybrid, hydrogen fuel cell vehicle) adoption in California, and evaluated the ZEV adoption gap in underserved communities. We conducted a zip code-level ecologic study relating changes in annual number of ZEVs (nZEV) per 1000 population from 2013 to 2019 to: (i) annual average monitored nitrogen dioxide (NO2) concentrations and (ii) annual age-adjusted asthma-related emergency department (ED) visit rates, while considering educational attainment. The average nZEV increased from 1.4 per 1000 population in 2013 (standard deviation [SD]: 2.1) to 14.7 per 1000 in 2019 (SD: 14.7). ZEV adoption was considerably slower in zip codes with lower educational attainment (p < 0.0001). A within-zip code increase of 20 ZEVs per 1000 was associated with a - 0.41 ppb change in annual average NO2 (95 % confidence interval [CI]:-1.12, 0.29) in an adjusted model. A within-zip code increase of 20 ZEVs per 1000 population was associated with a 3.2 % decrease in annual age-adjusted rate of asthma-related ED visits (95 % CI:-5.4, -0.9). Findings were supported by a variety of sensitivity analyses. Observational data on the early phase ZEV transition in California provided a natural experiment, enabling us to document the first real-world associations between increasing nZEV and changes in air quality and health. Results suggest co-benefits of the early-phase transition to ZEVs but with an adoption gap among populations with lower socioeconomic status which threatens the equitable distribution of possible co-benefits.

Short-term associations between ambient air pollution and emergency department visits for Alzheimer's disease and related dementias

Dementia is a seriously disabling illness with substantial economic and social burdens. Alzheimer's disease and its related dementias (AD/ADRD) constitute about two-thirds of dementias. AD/ADRD patients have a high prevalence of comorbid conditions that are known to be exacerbated by exposure to ambient air pollution. Existing studies mostly focused on the long-term association between air pollution and AD/ADRD morbidity, while very few have investigated short-term associations. This study aims to estimate short-term associations between AD/ADRD emergency department (ED) visits and three common air pollutants: fine particulate matter (PM_2.5), nitrogen dioxide (NO₂), and warm-season ozone.

Methods

For the period 2005 to 2015, we analyzed over 7.5 million AD/ADRD ED visits in five US states (California, Missouri, North Carolina, New Jersey, and New York) using a time-stratified case-crossover design with conditional logistic regression. Daily estimated PM_2.5, NO_2, and warm-season ozone concentrations at 1 km spatial resolution were aggregated to the ZIP code level as exposure.

Results

The most consistent positive association was found for NO₂. Across five states, a 17.1 ppb increase in NO₂ concentration over a 4-day period was associated with a 0.61% (95% confidence interval = 0.27%, 0.95%) increase in AD/ADRD ED visits. For PM_2.5, a positive association with AD/ADRD ED visits was found only in New York (0.64%, 95% confidence interval = 0.26%, 1.01% per 6.3 µg/m³). Associations with warm-season ozone levels were null.

Conclusions

Our results suggest AD/ADRD patients are vulnerable to short-term health effects of ambient air pollution and strategies to lower exposure may reduce morbidity.

Sex-Dependent Responses to Maternal Exposure to PM2.5 in the Offspring

Objective: Particulate matter (PM) with a diameter of 2.5 μm or less (PM_2.5) can cross the blood-placental barrier causing adverse foetal outcomes. However, the impact of maternal exposure to low-levels of PM_2.5 on liver health and the metabolic profile is unclear. This study aimed to investigate hepatic responses to long-term gestational low-dose PM_2.5 exposure, and whether the removal of PM after conception can prevent such effects. Method: Female Balb/c mice (8 weeks) were exposed to PM_2.5 (5 μg/day) for 6 weeks prior to mating, during gestation and lactation to model living in a polluted environment (PM group). In a sub-group, PM_2.5 exposure was stopped post-conception to model mothers moving to areas with clean air (pre-gestation, Pre) group. Livers were studied in 13-week old offspring. Results: Female offspring in both PM and Pre groups had increased liver triglyceride and glycogen levels, glucose intolerance, but reduced serum insulin and insulin resistance. Male offspring from only the Pre group had increased liver and serum triglycerides, increased liver glycogen, glucose intolerance and higher fasting glucose level. Markers of oxidative stress and inflammation were increased in females from PM and Pre groups. There was also a significant sex difference in the hepatic response to PM_2.5 with differential changes in several metabolic markers identified by proteomic analysis. Conclusions: Maternal PM exposure exerted sex-dependent effects on liver health with more severe impacts on females. The removal of PM_2.5 during gestation provided limited protection in the offspring’s metabolism regardless of sex.

Association between exposure level of air pollutants and incidence rate of circulatory disease in residential and industrial areas of South Korea

This study investigated the correlation between the concentration of air pollutants in two metropolitan cities, Seoul and Incheon, located in South Korea with different urban characteristics and the number of patients with circulatory diseases among residents exposed to air pollution. The residential area was selected as Eunpyeong-gu of Seoul Metropolitan City and the industrial area as Jung-gu of Incheon Metropolitan City. The evaluation period is between 2015 and 2016. The relevant data provide by the Korea governmental agency were analysed to derive the purpose of this study. It was confirmed that PM₁₀, PM_2.5, nitrogen dioxide, carbon monoxide, and sulfur dioxide among air pollutants had an increasing impact on the incidence rate of circulatory diseases. The PM_2.5 was positively correlated with the incidence rate of all circulatory diseases in residential area (p < 0.05). The carbon monoxide showed a positive correlation with circulatory system diseases except for hypertension in residential area. (p < 0.05). The sulfur dioxide was positively correlated with all circulatory diseases in both residential and industrial area (p < 0.05). Based on the results obtained from this study, it was found that there are different types of air pollutants that affect circulatory diseases in residential and industrial areas.

Effects of air pollution on human health - Mechanistic evidence suggested by in vitro and in vivo modelling

Airborne particulate matter (PM) comprises both solid and liquid particles, including carbon, sulphates, nitrate, and toxic heavy metals, which can induce oxidative stress and inflammation after inhalation. These changes occur both in the lung and systemically, due to the ability of the small-sized PM (i.e. diameters ≤2.5 μm, PM_2.5) to enter and circulate in the bloodstream. As such, in 2016, airborne PM caused ∼4.2 million premature deaths worldwide. Acute exposure to high levels of airborne PM (eg. during wildfires) can exacerbate pre-existing illnesses leading to hospitalisation, such as in those with asthma and coronary heart disease. Prolonged exposure to PM can increase the risk of non-communicable chronic diseases affecting the brain, lung, heart, liver, and kidney, although the latter is less well studied. Given the breadth of potential disease, it is critical to understand the mechanisms underlying airborne PM exposure-induced disorders. Establishing aetiology in humans is difficult, therefore, in-vitro and in-vivo studies can provide mechanistic insights. We describe acute health effects (e.g. exacerbations of asthma) and long term health effects such as the induction of chronic inflammatory lung disease, and effects outside the lung (e.g. liver and renal change). We will focus on oxidative stress and inflammation as this is the common mechanism of PM-induced disease, which may be used to develop effective treatments to mitigate the adverse health effect of PM exposure.

Low-Concentration Air Pollution and Mortality in American Older Adults: A National Cohort Analysis (2001-2017)

Mounting epidemiological evidence has documented the associations between long-term exposure to multiple air pollutants and increased mortality. There is a pressing need to determine whether risks persist at low concentrations including below current national standards. Air pollution levels have decreased in the United States, and better understanding of the health effects of low-level air pollution is essential for the amendment of National Ambient Air Quality Standards (NAAQS). A nationwide, population-based, open cohort study was conducted to estimate the association between long-term exposure to low-level PM_2.5, NO₂, O₃, and all-cause mortality. The study population included all Medicare enrollees (ages 65 years or older) in the contiguous U.S. from 2001 to 2017. We further defined three low-exposure subcohorts comprised of Medicare enrollees who were always exposed to low-level PM_2.5 (annual mean ≤12-μg/m³), NO₂ (annual mean ≤53-ppb), and O₃ (warm-season mean ≤50-ppb), respectively, over the study period. Of the 68.7-million Medicare enrollees, 33.1% (22.8-million, mean age 75.9 years), 93.8% (64.5-million, mean age 76.2 years), and 65.0% (44.7-million, mean age 75.6 years) were always exposed to low-level annual PM_2.5, annual NO₂, and warm-season O₃ over the study period, respectively. Among the low-exposure cohorts, a 10-μg/m³ increase in PM_2.5, 10-ppb increase in NO₂, and 10-ppb increase in warm-season O₃, were, respectively, associated with an increase in mortality rate ranging between 10 and 13%, 2 and 4%, and 12 and 14% in single-pollutant models, and between 6 and 8%, 1 and 3%, and 9 and 11% in tripollutant models, using three statistical approaches. There was strong evidence of linearity in concentration-response relationships for PM_2.5 and NO₂ at levels below the current NAAQS, suggesting that no safe threshold exists for health-harmful pollution levels. For O₃, the concentration-response relationship shows an increasingly positive association at levels above 40-ppb. In conclusion, exposure to low levels of PM_2.5, NO₂, and warm-season O₃ was associated with an increased risk of all-cause mortality.

Observations and Parameterization of the Effects of Barrier Height and Source-to-Barrier Distance on Concentrations Downwind of a Roadway

New results are presented from wind tunnel studies performed at the United States Environmental Protection Agency (U.S. EPA), which include cases with solid roadside barriers of varying heights and cases with varying distances between the line source (roadway) and a 6-m-tall barrier. The Source-to-Barrier Distance cases include seven lanes of traffic with each lane acting as an independent source of continuous emissions along a line (i.e., line source). A mixed-wake algorithm that accounts for barrier effects within a steady-state air dispersion model was updated based on the recent wind tunnel studies. To study the effects of a solid roadside barrier, varying barrier heights and varying distances between the line source and barrier were modeled with the U.S. EPA regulatory air dispersion model AERMOD (v. 21112) using the line-source option that includes an experimental barrier option (RLINEXT). The mixed-wake algorithm reproduced the shape of the vertical concentration profiles observed in the wind tunnel data, including the uniform concentration profile from the ground vertically to a height somewhat greater than the height of the barrier. The algorithm responded appropriately to changes in barrier height and source-to-barrier distance, producing greater reductions in ground-level concentrations for taller barriers and for shorter source-to-barrier distances. Additionally, a rule of thumb that approximates the effect of a downwind barrier was formulated by converting an estimated vertical dispersion into an additional travel distance. The wind tunnel results, the update to the mixed-wake algorithm, and a comparison of the two data sets are described in this paper.

Exposure to Primary Air Pollutants Generated by Highway Traffic and Daily Mortality Risk in Near-Road Communities: A Case-Crossover Study

Most epidemiologic studies fail to capture the impact of spatiotemporal fluctuations in traffic on exposure to traffic-related air pollutants in the near-road population. Using a case-crossover design and the Research LINE source (R-LINE) dispersion model with spatiotemporally resolved highway traffic data, we quantified associations between primary pollutants generated by highway traffic-particulate matter with an aerodynamic diameter less than or equal to 2.5 μm (PM2.5), oxides of nitrogen (NOx), and black carbon (BC)-and daily nonaccidental, respiratory, cardiovascular, and cerebrovascular mortality among persons who had resided within 1 km (0.6 mile) of major highways in the Puget Sound area of Washington State between 2009 and 2013. We estimated these associations using conditional logistic regression, adjusting for time-varying covariates. Although highly resolved modeled concentrations of PM2.5, NOx, and BC from highway traffic in the hours before death were used, we found no evidence of an association between mortality and the preceding 24-hour average PM2.5 exposure (odds ratio = 0.99, 95% confidence interval: 0.96, 1.02) or exposure during shorter averaging periods. This work did not support the hypothesis that mortality risk was meaningfully higher with greater exposures to PM2.5, NOx, and BC from highways in near-road populations, though we did incorporate a novel approach to estimate exposure to traffic-generated air pollution based on detailed traffic congestion data.

Toxicity screening of air extracts representing different source sectors in the Greater Toronto and Hamilton areas: In vitro oxidative stress, pro-inflammatory response, and toxicogenomic analysis

In the present study, the suitability and sensitivity of different in vitro toxicity endpoints were determined to evaluate and distinguish the specific contributions of polycyclic aromatic carbon (PAC) mixtures from various sites in Toronto (Canada), to pulmonary toxicity. Air samples were collected for two-month periods from April 2014 to March 2015 from one location, and from August 2016 to August 2017 from multiple locations reflecting different geographical areas in Toronto, and the Greater Toronto Area, with varying source emissions including background, traffic, urban, industrial and residential sites. Relative concentrations of PACs and their derivatives in these air samples were characterised. In vitro cytotoxicity, pro-inflammatory, and oxidative stress assays were employed to assess the acute pulmonary effects of urban-air-derived air pollutants. In addition, global transcriptional profiling was utilized to understand how these chemical mixtures exert their harmful effects. Lastly, the transcriptomic data and the chemical profiles for each site and season were used to relate the biological response back to individual constituents. Site-specific responses could not be derived; however, the Spring season was identified as the most responsive through benchmark concentration analysis. A combination of correlational analysis and principal component analysis revealed that nitrated and oxygenated polycyclic aromatic hydrocarbons (PAHs) drive the response at lower concentrations while specific PAHs drive the response at the highest concentration tested. Unsubstituted PAHs are the current targets for analysis as priority pollutants. The present study highlights the importance of by-products of PAH degradation in the assessment of risk. The study also demonstrates the usefulness of in vitro toxicity assays to derive meaningful data in support of risk assessment.

The Relationship Between Ambient Air Pollution and Hospitalizations for Gout in a Humid Subtropical Region of China

Objective

Gout is a chronic disease caused by the deposition of sodium urate (MSU) crystals. Available data on the association between environmental hazards and gout are scarce. The present study was present to investigate the relationship between short-term exposure to air pollution and hospitalizations for acute gout from 2016 to 2020 in Anqing City, China.

Methods

Daily records of hospital admissions for acute gout in Anqing from 1 January 2016 to 31 December 2020 were retrieved from the tertiary first-class hospitals in Anqing. Air pollutants and meteorological data were obtained from the China Environmental Monitoring Station and China Meteorological Data Service Center respectively. We used a time-series analysis to explore the association between air pollution (NO₂, O₃, and CO) and hospitalizations for acute gout, and conducted stratified analyses by gender, age and season.

Results

We observed an association between NO₂ and hospitalizations for gout (lag 0, relative risk (RR):1.022, 95% confidence interval (CI):1.004-1.041). For every 1 mg/m³ increase in CO concentration, hospitalizations for gout increased by 3.9% (lag 11 days, RR=1.039, 95% CI: 1.004-1.076). Intriguingly, there was a negative association between O₃ and hospitalizations for gout (lag0, RR=0.986, 95% CI: 0.976-0.996). Stratified analyses showed that exposure to high levels of NO₂ was considered to be more vulnerable to gout in cold season.

Conclusion

Our study showed that short-term exposure to NO₂ and CO has a significant effect on hospitalizations for acute gout.

Assessing the intra-urban variability of nitrogen oxides and ozone across a highly heterogeneous urban area

High-resolution air quality maps are critical towards assessing and understanding exposures to elevated air pollution in dense urban areas. However, these surfaces are rarely available in low- and middle-income countries that suffer from some of the highest air pollution levels worldwide. In this study, we make use of land use regressions (LURs) to generate annual and seasonal, high-resolution nitrogen dioxide (NO₂), nitrogen oxides (NO_x), and ozone (O₃) exposure surfaces for the Greater Beirut Area (GBA) in Lebanon. NO₂, NO_x and O₃ concentrations were monitored using passive samplers that were deployed at 55 pre-defined monitoring locations. The average annual concentrations of NO₂, NO_x, and O₃ across the GBA were 36.0, 89.7, and 26.9 ppb, respectively. Overall, the performance of the generated models was appropriate, with low biases, high model robustness, and acceptable R² values that ranged between 0.66 and 0.73 for NO₂, 0.56 and 0.60 for NO_x, and 0.54 and 0.65 for O₃. Traffic-related emissions as well as the operation of a fossil-fuel power plant were found to be the main contributors to the measured NO₂ and NO_x levels in the GBA, whereas they acted as sinks for O₃ concentrations. No seasonally significant differences were found for the NO₂ and NO_x pollution surfaces; as their seasonal and annual models were largely similar (Pearson's r > 0.85 for both pollutants). On the other hand, seasonal O₃ pollution surfaces were significantly different. The model results showed that around 99% of the population of the GBA were exposed to NO₂ levels that exceeded the World Health Organization defined annual standard.

Does Industrial Agglomeration or Foreign Direct Investment Matter for Environment Pollution of Public Health? Evidence From China

This article focuses on the interaction between China's industrial agglomeration, foreign direct investment (FDI) and environmental pollution of public health in the past 15 years. By conducting theoretical and empirical research, we try to reveal the relationship and mechanism between the economic growth and public health from the perspective of environmental pollution. By constructing an embedded theoretical model of industrial agglomeration and FDI, this article combines other environmental pollution influencing factors, expounds the impact mechanism of industrial agglomeration on environmental pollution. Based on the provincial-level panel data of China on environmental pollution and industrial agglomeration, the empirical test is carried out through the threshold panel regression model. According to the results, industrial agglomeration can significantly rectify the regional environmental pollution, thereby benefiting public health. FDI has a phased impact on the relationship between industrial agglomeration and environmental pollution. Specifically, when the level of FDI is low, the positive improvement effect of industrial agglomeration on environmental pollution is relatively strong. This is mainly because industrial agglomeration can promote economic growth, technological progress, and enhance environmental awareness. When the level of FDI exceeds the first threshold and continues to rise, the positive improvement effect of industrial agglomeration is maximized. Before the level of FDI exceeds the second threshold, this effect gradually weakens. The population concentration and excessive expansion of city scale brought about by industrial agglomeration will lead to the increase of regional resource and energy consumption, thus aggravating environmental pollution. The policy implication is that while the government and enterprises are vigorously increasing the level of foreign investment, they must pay equal attention to economic growth and public health, and the level of industrial agglomeration should match the level of foreign investment so as to give full play to the positive improvement effect of industrial agglomeration on environmental pollution, and realize the coordinated development of the regional economy, environment and population health.

Health Cost Estimation of Traffic-Related Air Pollution and Assessing the Pollution Reduction Potential of Zero-Emission Vehicles in Toronto, Canada

Fossil fuel vehicles, emitting air toxics into the atmosphere, impose a heavy burden on the economy through additional health care expenses and ecological degradation. Air pollution is responsible for millions of deaths and chronic and acute health problems every year, such as asthma and chronic obstructive pulmonary disease. The fossil-fuel-based transportation system releases tons of toxic gases into the atmosphere putting human health at risk, especially in urban areas. This analysis aims to determine the economic burden of environmental and health impacts caused by Highway 401 traffic. Due to the high volume of vehicles driving on the Toronto Highway 401 corridor, there is an annual release of 3771 tonnes of carbon dioxide equivalent (CO2e). These emissions are mainly emitted onsite through the combustion of gasoline and diesel fuel. The integration of electric and hydrogen vehicles shows maximum reductions of 405–476 g CO2e per vehicle-kilometer. Besides these carbon dioxide emissions, there is also a large amount of hazardous air pollutants. To examine the impact of air pollution on human health, the mass and concentrations of criteria pollutants of PM2.5 and NOx emitted by passenger vehicles and commercial trucks on Highway 401 were determined using the MOVES2014b software. Then, an air dispersion model (AERMOD) was used to find the concentration of different pollutants at the receptor’s location. The increased risk of health issues was calculated using hazard ratios from literature. Finally, the health cost of air pollution from Highway 401 traffic was estimated to be CAD 416 million per year using the value of statistical life, which is significantly higher than the climate change costs of CAD 55 million per year due to air pollution.

Air Pollution and Mortality in the Elderly in Kerman, Iran

Background: Today, air pollution is a major issue in the world, particularly in metropolitan areas. Objectives: Accordingly, this study aimed to investigate the relation between air pollution and mortality in the elderly in Kerman City. Methods: This ecological study was conducted using 2006 - 2013 mortality data inquired from the Deputy of Health of Kerman University of Medical Sciences. The data on cardiovascular and respiratory mortality, as well as death due to trauma, diabetes, and other diseases that happened in men and women aged 60 and higher were extracted. Air pollution data (CO, SO2, O3, NO, NO2, NOx, and PM10) for the same time frame were inquired from the Environmental Protection Agency of Kerman Province. Negative binomial regression was used to evaluate the relation between air pollutants and mortality using STATA13 software. Results: During the study period, a total of 14,793 deaths occurred in elderly men and women in Kerman City. Cardiovascular diseases were the leading cause of death. The results of multivariate analysis of air pollutants indicated that NO was directly and significantly related to the total number of deaths in the elderly, and increase in sulfur dioxide, ozone and NO was significantly related to increased mortality among elderly women. Carbon monoxide was significantly related to cardiovascular death of the elderly. But air pollutants did not show any significant effect on respiratory-, trauma-, and diabetes-related deaths. Conclusions: Our findings indicate that there is a significant relation between air pollution and mortality in the elderly. Accordingly, a warning system is suggested to reduce the elderly’s commuting on highly air polluted days.

Long-term exposure to nitrogen dioxide and mortality: A systematic review and meta-analysis

BACKGROUND

Ambient air pollution is among the greatest environmental risks to human health. However, little is known about the health effects of nitrogen dioxide (NO₂), a traffic-related air pollutant. Herein, we aimed to conduct a meta-analysis to investigate the long-term effects of NO₂ on mortality.

METHODS

We conducted a systematic search for studies that were published up to February 2020 and performed a meta-analysis of all available epidemiologic studies evaluating the associations between long-term exposure to NO₂ with all-cause, cardiovascular, and respiratory mortality. Overall pooled effect estimates as well as subgroup-specific pooled estimates (e.g. location, exposure assessment method, exposure metric, study population, age at recruitment, and key confounder adjustment) and 95% confidence intervals were calculated using random-effects models. Risk of bias assessment was accessed by following WHO global air quality guidelines. Publication bias was accessed by visually inspecting funnel plot and Egger's liner regression was used to test of asymmetry.

RESULTS

Our search initially retrieved 1349 unique studies, of which 34 studies met the inclusion criteria. The pooled hazard ratio (HR) for all-cause mortality was 1.06 (95%CI: 1.04-1.08, n = 28 studies, I² = 98.6%) per 10 ppb increase in annual NO₂ concentrations. The pooled HRs for cardiovascular and respiratory mortality per 10 ppb increment were 1.11 (95%CI: 1.07-1.16, n = 20 studies, I² = 99.2%) and 1.05 (95%CI: 1.02-1.08, n = 17 studies, I² = 94.6%), respectively. The sensitivity analysis pooling estimates from multi-pollutant models suggest an independent effect of NO₂ on mortality. Funnel plots indicate that there is no evidence for publication bias in our study.

CONCLUSION

We provide robust epidemiological evidence that long-term exposure to NO₂, a proxy for traffic-sourced air pollutants, is associated with a higher risk of all-cause, cardiovascular, and respiratory mortality that might be independent of other common air pollutants.

The impact of long- and short-term exposure to different ambient air pollutants on cognitive function in China

In the field of environmental health, the impact of air pollution on people's cognitive function is receiving increasing attention. Various air pollution exposures and different exposure periods result in different degrees of damage to cognition. This paper first used CFPS cognitive tests to evaluate the cognitive function of 15,163 adults in 25 provinces of China. Next, based on the geographical location of the population, the kriging interpolation method was applied to evaluate the different exposure periods for various air pollutants (PM_2.5, NO₂ and O₃). Air pollution exposures lasting 3 years and more were referred to in this paper as long-term exposures, while those lasting<3 years were short-term exposures. This paper used an ordinary least squares (OLS) regression model to explore the differential effects of various air pollutant exposures and discussed the impact of long- and short-term exposure to pollutants. Subsequently, Moran's index was used to test the spatial connection for cognitive function, and the spatial error model was used for analysis in the spatial autoregressive model. This research also conducted a heterogeneity study on the justice of air pollutant exposure among people with different characteristics. The population was classified according to cognitive function and geographic location using OLS regression and quantile regression, and a propensity score matching (PSM) model was used for cross-validation to explore whether people with different characteristics and attributes were differentially exposed to air pollution. We found that there were significant negative relationships between air pollutant exposure and cognitive function, especially PM_2.5 exposure and long-term exposure. In addition, air pollution had significantly different impacts on cognition based on the different characteristics and attributes of the person exposed. This study helps by analyzing the socioeconomic factors that affect the level of exposure and suggests that groups who are vulnerable to environmental pollution should be protected and the occurrence of injustice reduced. The study also provides a reference for the distribution of pollution sources and the allocation of health resources, which can be useful for population distribution planning.

Particulate Matter, an Intrauterine Toxin Affecting Foetal Development and Beyond

Air pollution is the 9th cause of the overall disease burden globally. The solid component in the polluted air, particulate matters (PMs) with a diameter of 2.5 μm or smaller (PM_2.5) possess a significant health risk to several organ systems. PM_2.5 has also been shown to cross the blood–placental barrier and circulate in foetal blood. Therefore, it is considered an intrauterine environmental toxin. Exposure to PM_2.5 during the perinatal period, when the foetus is particularly susceptible to developmental defects, has been shown to reduce birth weight and cause preterm birth, with an increase in adult disease susceptibility in the offspring. However, few studies have thoroughly studied the health outcome of foetuses due to intrauterine exposure and the underlying mechanisms. This perspective summarises currently available evidence, which suggests that intrauterine exposure to PM_2.5 promotes oxidative stress and inflammation in a similar manner as occurs in response to direct PM exposure. Oxidative stress and inflammation are likely to be the common mechanisms underlying the dysfunction of multiple systems, offering potential targets for preventative strategies in pregnant mothers for an optimal foetal outcome.

Characterizing long-term NO2 concentration surfaces across a large metropolitan area through spatiotemporal land use regression modelling of mobile measurements

A spatiotemporal land use regression (LUR) model optimized to predict nitrogen dioxide (NO₂) concentrations obtained from on-road, mobile measurements collected in 2015-16 was independently evaluated using concentrations observed at multiple sites across Toronto, Canada, obtained more than ten years earlier. This spatiotemporal LUR modelling approach improves upon estimates of historical NO₂ concentrations derived from the previously used method of back-extrapolation. The optimal spatiotemporal LUR model (R² = 0.71 for prediction of NO₂ data in 2002 and 2004) uses daily average NO₂ concentrations observed at multiple long-term monitoring sites and hourly average wind speed recorded at a single site, along with spatial predictors based on geographical information system data, to estimate NO₂ levels for time periods outside of those used for model development. While the model tended to underestimate samplers located close to the roadway, it showed great accuracy when estimating samplers located beyond 100 m which are probably more relevant for exposure at residences. This study shows that spatiotemporal LUR models developed from strategic, multi-day (30 days in 3 different months) mobile measurements can enhance LUR model's ability to estimate long-term, intra-urban NO₂ patterns. Furthermore, the mobile sampling strategy enabled this new LUR model to cover a larger domain of Toronto and outlying suburban communities, thereby increasing the potential population for future epidemiological studies.

Association between traffic-related air pollution and hospital readmissions for rheumatoid arthritis in Hefei, China: A time-series study

Air pollution is an important risk factor for autoimmune diseases, but its association with the recurrence of rheumatoid arthritis (RA) remains unclear so far. This study aimed to investigate the short-term association between traffic-related air pollutants and hospital readmissions for RA in Hefei, China. Data on daily hospital readmissions for RA and traffic-related air pollutants, including particulate matter (PM_2.5 and PM₁₀), nitrogen dioxide (NO₂), and carbon monoxide (CO), from 2014 to 2018 were retrieved. A time-series approach using generalized linear regression model was employed. The analysis was further stratified by sex, age and season. A total of 1153 readmissions for RA were reported during the study period. A significant association between high-concentration PM_2.5 (90th percentile) and RA readmissions was observed on lag1 (relative risk (RR) = 1.09, 95% confidence interval (CI): 1.01-1.19) and lasted until lag3 (RR = 1.06, 95%CI: 1.01-1.12). From lag2 to lag5, high-concentration NO₂ (90th percentile) was associated with increased risk of RA readmissions, with the highest RR observed at lag 4 (1.11, 95%CI: 1.05-1.17). Stratified analyses indicated that females and the elderly appeared to be more vulnerable to high-concentration PM_2.5 and NO₂ exposure. High-concentration PM_2.5 and NO₂ in cold seasons were consistently significantly associated with increased risk of RA readmissions. Exposure to high-concentration PM_2.5 and NO₂ was associated with increased risk of RA readmissions. Protective measures against the exposure to high-concentration PM_2.5 and NO₂ should be taken to reduce the recurrence risk in RA patients, especially in females, the elderly and during cold seasons.

Long-term exposure to NO2 and O3 and all-cause and respiratory mortality: A systematic review and meta-analysis

BACKGROUND

WHO has published several volumes of Global Air Quality Guidelines to provide guidance on the health risks associated with exposure to outdoor air pollution. As new scientific evidence is generated, air quality guidelines need to be periodically revised and, where necessary, updated.

OBJECTIVES

The aims of the study were 1) to summarise the available evidence on the effect of long-term exposure to ozone (O3) and nitrogen dioxide (NO2) on mortality; 2) and to assess concentration response functions (CRF), their shape and the minimum level of exposures measured in studies to support WHO's update of the global air quality guidelines.

DATA SOURCES

We conducted a systematic literature search of the Medline, Embase and Web of Science databases following a protocol proposed by WHO and applied Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) guidelines for reporting our results.

STUDY ELIGIBILITY CRITERIA

Cohort studies in human populations (including sub-groups at risk) exposed to long-term concentrations of NO2 and O3. Outcomes assessed were all-cause, respiratory, Chronic Obstructive Pulmonary Disease (COPD) and Acute Lower Respiratory Infection (ALRI) mortality.

STUDY APPRAISAL AND SYNTHESIS METHODS

Studies included in the meta-analyses were assessed using a new Risk of Bias instrument developed by a group of experts convened by WHO. Study results are presented in forest plots and quantitative meta-analyses were conducted using random effects models. The certainty of evidence was assessed using a newly developed adaptation of GRADE.

RESULTS

The review identified 2068 studies of which 95 were subject to full-text review with 45 meeting the inclusion criteria. An update in September 2018 identified 159 studies with 1 meeting the inclusion criteria. Of the 46 included studies, 41 reported results for NO2 and 20 for O3. The majority of studies were from the USA and Europe with the remainder from Canada, China and Japan. Forty-two studies reported results for all-cause mortality and 22 for respiratory mortality. Associations for NO2 and mortality were positive; random-effects summary relative risks (RR) were 1.02 (95% CI: 1.01, 1.04), 1.03 (1.00, 1.05), 1.03 (1.01, 1.04) and 1.06 (1.02, 1.10) per 10 μg/m3 for all-cause (24 cohorts), respiratory (15 cohorts), COPD (9 cohorts) and ALRI (5 cohorts) mortality respectively. The review identified high levels of heterogeneity for all causes of death except COPD. A small number of studies investigated the shape of the concentration-response relationship and generally found little evidence to reject the assumption of linearity across the concentration range. Studies of O3 using annual metrics showed the associations with all-cause and respiratory mortality were 0.97 (0.93, 1.02) and 0.99 (0.89, 1.11) per 10 μg/m3 respectively. For studies using peak O3 metrics, the association with all-cause mortality was 1.01 (1.00, 1.02) and for respiratory mortality 1.02 (0.99, 1.05), each per 10 μg/m3. The review identified high levels of heterogeneity. Few studies investigated the shape of the concentration-response relationship. Certainty in the associations (adapted GRADE) with mortality was rated low to moderate for each exposure-outcome pair, except for NO2 and COPD mortality which was rated high.

LIMITATIONS

The substantial heterogeneity for most outcomes in the review requires explanation. The evidence base is limited in terms of the geographical spread of the study populations and, for some outcomes, the small number of independent cohorts for meta-analysis precludes meaningful meta-regression to explore causes of heterogeneity. Relatively few studies assessed specifically the shape of the CRF or multi-pollutant models.

CONCLUSIONS

The short-comings in the existing literature base makes determining the precise nature (magnitude and linearity) of the associations challenging. Certainty of evidence assessments were moderate or low for both NO2 and O3 for all causes of mortality except for NO2 and COPD mortality where the certainty of the evidence was judged as high.

Cluster Analysis of Inhalant Allergens in South Korea: A Computational Model of Allergic Sensitization

Objectives.

Sensitization to specific inhalant allergens is a major risk factor for the development of atopic diseases, which impose a major socioeconomic burden and significantly diminish quality of life. However, patterns of inhalant allergic sensitization have yet to be precisely described. Therefore, to enhance the understanding of aeroallergens, we performed a cluster analysis of inhalant allergic sensitization using a computational model.

Methods.

Skin prick data were collected from 7,504 individuals. A positive skin prick response was defined as an allergen-to-histamine wheal ratio ≥1. To identify the clustering of inhalant allergic sensitization, we performed computational analysis using the four-parameter unified-Richards model.

Results.

Hierarchical cluster analysis grouped inhalant allergens into three clusters based on the Davies-Bouldin index (0.528): cluster 1 (Dermatophagoides pteronyssinus and Dermatophagoides farinae), cluster 2 (mugwort, cockroach, oak, birch, cat, and dog), and cluster 3 (Alternaria tenus, ragweed, Candida albicans, Kentucky grass, and meadow grass). Computational modeling revealed that each allergen cluster had a different trajectory over the lifespan. Cluster 1 showed a high level (>50%) of sensitization at an early age (before 19 years), followed by a sharp decrease in sensitization. Cluster 2 showed a moderate level (10%–20%) of sensitization before 29 years of age, followed by a steady decrease in sensitization. However, cluster 3 revealed a low level (<10%) of sensitization at all ages.

Conclusion.

Computational modeling suggests that allergic sensitization consists of three clusters with distinct patterns at different ages. The results of this study will be helpful to allergists in managing patients with atopic diseases.

Temporal trends in associations between ozone and circulatory mortality in age and sex in Canada during 1984-2012

BACKGROUND

Considerable research has been conducted on the association between ground-level ozone (ozone) and various causes of mortality, but the relationships by age and sex (biological) have been inconsistent, and temporal trends remain unexplored.

OBJECTIVES

The study goals are to investigate the adverse health effects of short-term exposure to ozone on circulatory mortality by age and sex, and to examine trends in annual health effects.

METHODS

Daily ozone, temperature, and circulatory mortality counts (ICD I00-I99) were collected for 24 urban cities for 29 years (1984-2012). Associations between ozone and circulatory mortality were estimated using generalized additive Poisson models for season (warm vs. cold), age [base (≥1) vs. seniors (>65)], and sex, accounting for confounders (calendar-time, temperature, day of the week). City-specific estimates were pooled to represent national associations through Bayesian hierarchical models.

RESULTS

While the cold season returned insignificant estimates, the warm season showed statistically significant associations: a 10 ppb increase in ozone was associated with 0.7% increase in circulatory mortality with a 95% posterior interval of 0.2%, 1.1%. One-day lagged ozone in the warm season showed little age differences [0.7% (0.23%, 1.12%) vs. 0.8% (0.22%, 1.27%)], but visible sex differences: females were at a higher circulatory mortality risk than males [1.1% (0.31%, 1.71%) vs. 0.3% (-0.46%, 0.98%)]. Annual estimates suggest overall up-down temporal changes; a slightly increasing trend until 2002-2004, and a generally decreasing trend thereafter.

CONCLUSION

This study found noticeable sex-related differences in circulatory mortality attributable to short-term exposure to ozone. Further research is warranted to understand whether sex alone, or unknown interactions with other factors derived the differences, and to clarify the specific biological mechanisms underlying differences in risk estimates between females and males.

Attributable Risk to Assess the Health Impact of Air Pollution: Advances, Controversies, State of the Art and Future Needs

Despite the increased attention given to the health impact assessment of air pollution and to the strategies to control it in both scientific literature and concrete interventions, the results of the implementations, especially those involving traffic, have not always been satisfactory and there is still disagreement about the most appropriate interventions and the methods to assess their effectiveness. This state-of-the-art article reviews the recent interpretation of the concepts that concern the impact assessment, and compares old and new measurements of attributable risk and attributable fraction. It also summarizes the ongoing discussion about the designs and methods for assessing the air pollution impact with particular attention to improvements due to spatio-temporal analysis and other new approaches, such as studying short term effects in cohorts, and the still discussed methods of predicting the values of attributable risk (AR). Finally, the study presents the more recent analytic perspectives and the methods for directly assessing the effects of not yet implemented interventions on air quality and health, in accordance with the suggestion in the strategic plan 2020-2025 from the Health Effect Institute.

Interaction between neighborhood walkability and traffic-related air pollution on hypertension and diabetes: The CANHEART cohort

BACKGROUND

Living in unwalkable neighborhoods has been associated with heightened risk for diabetes and hypertension. However, highly walkable environments may have higher concentrations of traffic-related air pollution, which may contribute to increased cardiovascular disease risk. We therefore aimed to assess how walkability and traffic-related air pollution jointly affect risk for hypertension and diabetes.

METHODS

We used a cross-sectional, population-based sample of individuals aged 40-74 years residing in selected large urban centres in Ontario, Canada on January 1, 2008, assembled from administrative databases. Walkability and traffic-related air pollution (NO₂) were assessed using validated tools and linked to individuals based on neighborhood of residence. Logistic regression was used to estimate adjusted associations between exposures and diagnoses of hypertension or diabetes accounting for potential confounders.

RESULTS

Overall, 2,496,458 individuals were included in our analyses. Low walkability was associated with higher odds of hypertension (lowest vs. highest quintile OR = 1.34, 95% CI: 1.32, 1.37) and diabetes (lowest vs. highest quintile OR = 1.25, 95% CI: 1.22, 1.29), while NO₂ exhibited similar trends (hypertension: OR = 1.09 per 10 p.p.b., 95% CI: 1.08, 1.10; diabetes: OR = 1.16, 95% CI: 1.14, 1.17). Significant interactions were identified between walkability and NO₂ on risk for hypertension (p < 0.0001 and diabetes (p < 0.0001). At higher levels of pollution (40 p.p.b.), differences in the probability of hypertension (lowest vs. highest walkability quintile: 0.26 vs. 0.25) or diabetes (lowest vs. highest walkability quintile: 0.15 vs. 0.15) between highly walkable and unwalkable neighborhoods were diminished, compared to differences observed at lower levels of pollution (5 p.p.b.) (hypertension, lowest vs. highest walkability quintile: 0.21 vs. 0.13; diabetes, lowest vs. highest walkability quintile: 0.09 vs. 0.06).

CONCLUSIONS

Walkability and traffic-related air pollution interact to jointly predict risk for hypertension and diabetes. Although walkable neighborhoods appear to have beneficial effects, they may accentuate the harmful effects of air pollution on cardiovascular risk factors.

Characteristics of cohort studies of long-term exposure to PM2.5: a systematic review

This study systematically reviewed all the cohort studies investigating the relationship between long-term exposure to PM_2.5 and any health outcome until February 2018. We searched ISI Web of Knowledge, Pubmed, and Scopus databases for peer-reviewed journal research articles published in English. We only extracted the results of the single-pollutant main analysis of each study, excluding the effect modifications and sensitivity analyses. Out of the initial 9523 articles, 203 articles were ultimately included for analysis. Based on the different characteristics of studies such as study design, outcome, exposure assessment method, and statistical model, we calculated the number and relative frequency of analyses with statistically significant and insignificant results. Most of the studies were prospective (84.8%), assessed both genders (66.5%), and focused on a specific age range (86.8%). Most of the articles (78.1%) had used modeling techniques for exposure assessment of cohorts' participants. Among the total of 317 health outcomes, the most investigated outcomes include mortality due to cardiovascular disease (6.19%), all causes (5.48%), lung cancer (4.00%), ischemic heart disease (3.50%), and non-accidental causes (3.50%). The percentage of analyses with statistically significant results were higher among studies that used prospective design, mortality as the outcome, fixed stations as exposure assessment method, hazard ratio as risk measure, and no covariate adjustment. We can somehow conclude that the choice of right characteristics for cohort studies can make a difference in their results.

The influence of spatial patterning on modeling PM2.5 constituents in Eastern Massachusetts

Geostatistical exposure methods for air pollution have inherent uncertainties, resulting in varying levels of exposure misclassification. In this study, we propose that areas representing clusters of PM_2.5 elements are potential predictor variables to be included in spatial models for particle composition. The inclusion of these clusters may minimize the exposure misclassification. We evaluated the influence of spatial patterning on modeling of 10 components of ambient PM_2.5, which included Al, Cu, Fe, K, Ni, Pb, S, Ti, V, and Zn. This study was performed in three stages. First, we applied a hybrid approach (combination of Empirical Bayesian Kriging and land use regression) to estimate spatial variability for each one of the 10 components of ambient PM_2.5. In this stage, we accounted for numerous predictors representing land use, transportation, demographic, and geographical characteristics. In the second stage, we applied the same hybrid approach adding clusters of each PM_2.5 component to the set of predictor variables. The clusters here were estimated by a multivariate clustering approach based on k means. Finally, in the last stage, we compared the estimates obtained from the model without clusters (first stage) and the model with clusters (second stage). Overall, our findings suggest significant influence of spatial clusters on modeling some PM_2.5 components. We observed that the clusters may affect the error of the prediction values and especially the proportion of explained variance for most of the PM_2.5 constituents evaluated in this study. The model with cluster presented a better performance for all PM_2.5 components, except for Pb, which the R² value decreased 8.51% when we included the clusters in the analysis; and for V, which the R² value did not change with the clusters. Models for Cu and Fe explained the highest concentration variance. The R² value for the model without cluster was 0.55 for both pollutants. When we accounted for clusters, R² value increased 13 and 7% for Cu (R² = 0.62) and Fe (R² = 0.59), respectively. The models for K and S presented the lowest performance for both models with and without cluster (although the model with cluster improved substantially the R² values). Better knowledge of the influence of spatial patterns on air pollution modeling should be of interest to policy makers to devise future strategies to improve human exposure assessment to air particulates while controlling for spatial patterns of ambient PM_2.5 elemental concentration.

Polycyclic aromatic compounds in urban air and associated inhalation cancer risks: A case study targeting distinct source sectors

Passive air sampling was conducted in Toronto and the Greater Toronto Area from 2016 to 2017 for 6 periods, in order to investigate ambient levels of polycyclic aromatic compounds (PACs) associated with different source types. The selected sampling sites (n = 8) cover geographical areas with varying source emissions including background, traffic, urban, industrial and residential sites. Passive air samples were analyzed for PACs which include PAHs, alkylated PAHs (alk-PAHs), dibenzothiophene and alkylated dibenzothiophenes (DBTs) and results for PAHs were used to calculate inhalation cancer risks using different approaches. The samples were also characterized for PAH derivatives including nitrated PAHs (NPAHs) and oxygenated PAHs (OPAHs). Concentrations of Σalk-PAHs and DBTs, which are known to be enriched in fossil fuels, as well as ΣNPAHs, were highest at a traffic site (MECP) located adjacent to the 18-lane Highway 401 that runs across Toronto. Except for an industrial site (HH/BU), PAC compositions were similar across the sampling sites with Σalk-PAHs being the most abundant class of PACs suggesting traffic emission was a major contributor to PACs in the atmosphere of Toronto. The industrial site exhibited a distinct chemical composition with ΣPAHs dominating over Σalk-PAHs and with elevated levels of fluoranthene, 9-nitroanthracene, and 9,10-anthraquinone, which likely reflects emissions from nearby industrial sources. MECP and HH/BU exhibited higher lifetime excess inhalation cancer risks indicating an association with traffic and industrial sources. The importance of the traffic sector as a source of PACs to ambient air is further supported by strong correlations of the ΣPAHs, Σalk-PAHs, DBTs, and ΣOPAHs with NO_x. This study highlights the importance of traffic as an emission source of PACs to urban air and the relevance of PAC classes other than just unsubstituted PAHs that are important but currently not included in air quality guidelines or for assessing inhalation cancer risks.

Evaluation of predictive capabilities of ordinary geostatistical interpolation, hybrid interpolation, and machine learning methods for estimating PM2.5 constituents over space

Numerous modeling approaches to estimate concentrations of PM_2.5 components have been developed to derive better exposures for health studies, including geostatistical interpolation approaches, land use regression models and, models based on remote sensing technology. Recently, there have been some efforts to develop models based on machine learning algorithms. Each one of these exposure assessment methods has inherent uncertainties resulting in varying levels of exposure misclassification. To date, only a few studies have attempted to systematically compare exposure estimates from different PM_2.5 constituent models. Our research addresses this gap, by comparing the predictive capabilities of ordinary geostatistical interpolation (Ordinary Kriging - OK), hybrid interpolation (combination of Empirical Bayesian Kriging and land use regression), and machine learning techniques (forest-based regression) for estimating PM_2.5 constituents in Eastern Massachusetts in the United States. We compared the estimates of 10 ambient PM_2.5 components, which included Al, Cu, Fe, K, Ni, Pb, S, Ti, V, and Zn. The OK model performed poorest for all PM_2.5 components, with an R² under 0.30. The hybrid model presented a slight improvement, especially for Cu and Fe, for which the R² value increased to 0.62 and 0.59, respectively. These elements presented the highest R² value from the hybrid model. The forest model presented the best performance, with R² values higher than 0.7 for most of the particle components, including Cu, Fe, Ni, Pb, Ti, and V. Same as observed with the hybrid model, the forest model for Cu and Fe explained the highest concentration variance, with a R² value equal to 0.88 and 0.92, respectively. The forest model for K, S, and Zn performed poorest with an R² value of 0.54, 0.37, and 0.44, respectively. The results presented here can be useful for the environmental health community to more accurately estimate PM_2.5 constituents over space.

Effects of short-term exposure to particulate matter air pollution on cognitive performance

This paper assesses the effect of short-term exposure to particulate matter (PM) air pollution on human cognitive performance via a double cross over experimental design. Two distinct experiments were performed, both of which exposed subjects to low and high concentrations of PM. Firstly, subjects completed a series of cognitive tests after being exposed to low ambient indoor PM concentrations and elevated PM concentrations generated via candle burning, which is a well-known source of PM. Secondly, a different cohort underwent cognitive tests after being exposed to low ambient indoor PM concentrations and elevated ambient outdoor PM concentrations via commuting on or next to roads. Three tests were used to assess cognitive performance: Mini-Mental State Examination (MMSE), the Stroop Color and Word test, and Ruff 2 & 7 test. The results from the MMSE test showed a statistically robust decline in cognitive function after exposure to both the candle burning and outdoor commuting compared to ambient indoor conditions. The similarity in the results between the two experiments suggests that PM exposure is the cause of the short-term cognitive decline observed in both. The outdoor commuting experiment also showed a statistically significant short-term cognitive decline in automatic detection speed from the Ruff 2 and 7 selective attention test. The other cognitive tests, for both the candle and commuting experiments, showed no statistically significant difference between the high and low PM exposure conditions. The findings from this study are potentially far reaching; they suggest that elevated PM pollution levels significantly affect short term cognition. This implies average human cognitive ability will vary from city to city and country to country as a function of PM air pollution exposure.

Regional Cooperative Pollution Control and Residents' Health Expenditures: Empirical Evidence from China

BACKGROUND

Environmental pollution seriously damages not only the ecosystem but also the well-being of residents. There is an association between air pollution and residential health expenditures. The aim of this study was to identify the association between pollution control and residents' health expenditures.

METHODS

Using the pilot project of the regional cooperative pollution control in 28 cities required by the Chinese government as the quasi-natural experiment setting and the panel data of residents' health expenditures in China from 2014 to 2017, the impact of pollution control on residents' health expenditures was systematically explored through difference-in-difference approach.

RESULTS

Air quality of the 28 cities that adopted the regional cooperative pollution control policy improves significantly, thus indicating that this policy effectively solves the self-interest issue of local governments in pollution control, and residents' health expenditures consequently decrease.

CONCLUSION

This study enriches the paradigm that analyzes the relationship between air pollution and residents' health expenditures and reveals the mechanism through which the regional cooperative pollution control reduces residents' health expenditures.

Community-Based Participatory Research at Jacksonville Florida Superfund Ash Site: Toxicology Training to Improve the Knowledge of the Lay Community

Until the late 1960's, Jacksonville, Florida incinerated its solid waste with the resultant ash deposited in landfills or used to fill flood-prone areas. These filled areas were later developed into parks, school sites and residential areas. Lead in soil at these sites was the major toxicant of concern and driver of clean-up actions. During the period of assessment of lead-levels in soil, there were no established lines of communication between the City and residents of affected neighborhoods resulting in mistrust in the community. To address communication issues, a community-based, culturally sensitive Community Environmental Toxicology Curriculum (CETC) and a short video were developed for community stakeholders to inform them of risks, health effects, remediation processes and preventive measures. Pre-and post-tests were developed to measure knowledge gained from the toxicology training. Learning gains averaged 47% and 24% for the community leaders and residents respectively. Most participants strongly agreed that the community toxicology curriculum was a useful tool for promoting awareness of environmental risks in their community and addressing the gap in trust between residents and agencies involved in site remediation.

Risk of concentrations of major air pollutants on the prevalence of cardiovascular and respiratory diseases in urbanized area of Kuala Lumpur, Malaysia

Rapid urbanisation in Malaysian cities poses risks to the health of residents. This study aims to estimate the relative risk (RR) of major air pollutants on cardiovascular and respiratory hospitalisations in Kuala Lumpur. Daily hospitalisations due to cardiovascular and respiratory diseases from 2010 to 2014 were obtained from the Hospital Canselor Tuanku Muhriz (HCTM). The trace gases, PM₁₀ and weather variables were obtained from the Department of Environment (DOE) Malaysia in consistent with the hospitalisation data. The RR was estimated using a Generalised Additive Model (GAM) based on Poisson regression. A "lag" concept was used where the analysis was segregated into risks of immediate exposure (lag 0) until exposure after 5 days (lag 5). The results showed that the gases could pose significant risks towards cardiovascular and respiratory hospitalisations. However, the RR value of PM₁₀ was not significant in this study. Immediate effects on cardiovascular hospitalisations were observed for NO₂ and O₃ but no immediate effect was found on respiratory hospitalisations. Delayed effects on cardiovascular and respiratory hospitalisations were found with SO₂ and NO₂. The highest RR value was observed at lag 4 for respiratory admissions with SO₂ (RR = 1.123, 95% CI = 1.045-1.207), followed by NO₂ at lag 5 for cardiovascular admissions (RR = 1.025, 95% CI = 1.005-1.046). For the multi-pollutant model, NO₂ at lag 5 showed the highest risks towards cardiovascular hospitalisations after controlling for O₃ 8 h mean lag 1 (RR = 1.026, 95% CI = 1.006-1.047), while SO₂ at lag 4 showed highest risks towards respiratory hospitalisations after controlling for NO₂ lag 3 (RR = 1.132, 95% CI = 1.053-1.216). This study indicated that exposure to trace gases in Kuala Lumpur could lead to both immediate and delayed effects on cardiovascular and respiratory hospitalisations.

Asian Culturally Specific Predictors in a Large-Scale Land Use Regression Model to Predict Spatial-Temporal Variability of Ozone Concentration

This paper developed a land use regression (LUR) model to study the spatial-temporal variability of O₃ concentrations in Taiwan, which has typical Asian cultural characteristics with diverse local emission sources. The Environmental Protection Agency's (EPA) data of O₃ concentrations from 2000 and 2013 were used to develop this model, while observations from 2014 were used as the external data verification to assess model reliability. The distribution of temples, cemeteries, and crematoriums was included for a potential predictor as an Asian culturally specific source for incense and joss money burning. We used stepwise regression for the LUR model development, and applied 10-fold cross-validation and external data for the verification of model reliability. With the overall model R² of 0.74 and a 10-fold cross-validated R² of 0.70, this model presented a mid-high prediction performance level. Moreover, during the stepwise selection procedures, the number of temples, cemeteries, and crematoriums was selected as an important predictor. By using the long-term monitoring data to establish an LUR model with culture specific predictors, this model can better depict O₃ concentration variation in Asian areas.

Exposure to traffic and mortality risk in the 1991-2011 Canadian Census Health and Environment Cohort (CanCHEC)

There is evidence that local traffic density and living near major roads can adversely affect health outcomes. We aimed to assess the relationship between local road length, proximity to primary highways, and cause-specific mortality in the 1991 Canadian Census Health and Environment Cohort (CanCHEC). In this long-term study of 2.6 million people, based on completion of the long-form census in 1991 and followed until 2011, we used annual residential addresses to determine the total length of local roads within 200 m of postal code representative points and the postal code's distance to primary highways. The association between exposure to traffic and cause-specific non-accidental mortality was estimated using Cox proportional hazards models, adjusting for individual covariates and contextual factors, including census division-level proportion in high school, the percentage of recent immigrants, and neighborhood income. We performed sensitivity analyses, including adjustment for exposure to PM_2.5, NO₂, or O₃, restricting to subjects in core urban areas, and spatial variation by climatic zone. The hazard ratio (HR) for all non-accidental mortality associated with an interquartile increase in length of local roads was 1.05 (95% CI 1.04, 1.05), while for an interquartile range increase in proximity to primary highways, the HR was 1.03 (95% CI 1.02, 1.04). HRs by traffic quartile increased with increasing lengths of local roads, as well as with closer proximity to primary highways, for all mortality causes. The associations were stronger within subjects' resident in urban core areas, attenuated by adjustment for PM_2.5, and HRs showed limited spatial variation by climatic zone. In the CanCHEC cohort, exposure to higher road density and proximity to major traffic roads was associated with increased mortality risk from cerebrovascular and cardiovascular disease, ischemic heart disease, COPD, respiratory disease, and lung cancer, with unclear results for diabetes.

Long-term Concentrations of Nitrogen Dioxide and Mortality: A Meta-analysis of Cohort Studies

Supplemental Digital Content is available in the text.

Background:

Concentrations of outdoor nitrogen dioxide (NO₂) have been associated with increased mortality. Hazard ratios (HRs) from cohort studies are used to assess population health impact and burden. We undertook meta-analyses to derive concentration–response functions suitable for such evaluations and assessed their sensitivity to study selection based upon cohort characteristics.

Methods:

We searched online databases and existing reviews for cohort studies published to October 2016 that reported HRs for NO₂ and mortality. We calculated meta-analytic summary estimates using fixed/random-effects models.

Results:

We identified 48 articles analyzing 28 cohorts. Meta-analysis of HRs found positive associations between NO₂ and all cause (1.02 [95% confidence interval (CI): 1.01, 1.03]; prediction interval [PI]: [0.99, 1.06] per 10 µg/m³ increment in NO₂), cardiovascular (1.03 [95% CI: 1.02, 1.05]; PI: [0.98, 1.08]), respiratory (1.03 [95% CI: 1.01, 1.05]; PI: [0.97, 1.10]), and lung cancer mortality (1.05 [95% CI: 1.02, 1.08]; PI: [0.94, 1.17]) with evidence of substantial heterogeneity between studies. In subgroup analysis, summary HRs varied by age at cohort entry, spatial resolution of pollution estimates, and adjustment for smoking and body mass index at the individual level; for some subgroups, the HR was close to unity, with lower confidence limits below 1.

Conclusions:

Given the many uncertainties inherent in the assessment of this evidence base and the sensitivity of health impact calculations to small changes in the magnitude of the HRs, calculation of the impact on health of policies to reduce long-term exposure to NO₂ should use prediction intervals and report ranges of impact rather than focusing upon point estimates.

Exposure to Ambient Ultrafine Particles and Nitrogen Dioxide and Incident Hypertension and Diabetes

BACKGROUND

Previous studies reported that long-term exposure to traffic-related air pollution may increase the incidence of hypertension and diabetes. However, little is known about the associations of ultrafine particles (≤0.1 μm in diameter) with these two conditions.

METHODS

We conducted a population-based cohort study to investigate the associations between exposures to ultrafine particles and nitrogen dioxide (NO2) and the incidence of diabetes and hypertension. Our study population included all Canadian-born residents aged 30 to 100 years who lived in the City of Toronto, Canada, from 1996 to 2012. Outcomes were ascertained using validated province-wide databases. We estimated annual concentrations of ultrafine particles and NO2 using land-use regression models and assigned these estimates to participants' annual postal code addresses during the follow-up period. Using random-effects Cox proportional hazards models, we calculated hazard ratios (HRs) and 95% confidence intervals (CIs) for ultrafine particles and NO2, adjusted for individual- and neighborhood-level covariates. We considered both single- and multipollutant models.

RESULTS

Each interquartile change in exposure to ultrafine particles was associated with increased risk of incident hypertension (HR = 1.03; 95% CI = 1.02, 1.04) and diabetes (HR = 1.06; 95% CI = 1.05, 1.08) after adjusting for all covariates. These results remained unaltered with further control for fine particulate matter (≤2.5 μm; PM2.5) and NO2. Similarly, NO2 was positively associated with incident diabetes (HR = 1.06; 95% CI = 1.05, 1.07) after controlling for ultrafine particles and PM2.5.

CONCLUSIONS

Exposure to traffic-related air pollution including ultrafine particles and NO2 may increase the risk for incident hypertension and diabetes. See video abstract at, http://links.lww.com/EDE/B337.

Characterization of aerosol nitroaromatic compounds: Validation of an experimental method

The analytical capabilities associated with the use of silylation reactions have been extended to a new class of organic molecules, nitroaromatic compounds (NACs). These compounds are a possible contributor to urban particulate matter of secondary origin which would make them important analytes due to their (1) detrimental health effects, (2) potential to affect aerosol optical properties, and (3) and usefulness for identifying PM2.5 from biomass burning. The technique is based on derivatization of the parent NACs by using N,O-bis-(trimethylsilyl)-trifluoro acetamide, one of the most prevalent derivatization reagent for analyzing hydroxylated molecules, followed by gas chromatography-mass spectrometry using electron ionization (EI) and methane chemical ionization (CI). This method is evaluated for 32 NACs including nitrophenols, methyl-/methoxy-nitrophenols, nitrobenzoic acids, and nitrobenzyl alcohols. Electron ionization spectra were characterized by a high abundance of ions corresponding to [M+ ] or [M+  - 15]. Chemical ionization spectra exhibited high abundance for [M+  + 1], [M+  - 15], and [M+  + 29] ions. Both EI and CI spectra exhibit ions specific to nitro group(s) for [M+  - 31], [M+  - 45], and [M+  - 60]. The strong abundance observed for [M+ ] (EI), [M+  - 15] (EI/CI), or [M+  + 1] (CI) ions is consistent with the high charge stabilizing ability associated with aromatic compounds. The combination of EI and CI ionization offers strong capabilities for detection and identification of NACs. Spectra associated with NACs, containing hydrogen, carbon, oxygen, and nitrogen atoms only, as silylated derivatives show fragment/adduct ions at either (a) odd or (b) even masses that indicate either (a) odd or (b) even number of nitro groups, respectively. Mass spectra associated with silylated NACs exhibited 3 distinct regions where characteristic fragmentation with a specific pattern associated with (1) ─OH and/or ─COOH groups, (2) ─NO2 group(s), and (3) benzene ring(s). These findings were confirmed with applications to chamber aerosol and ambient PM2.5 .

Incidence and mortality risk for respiratory tract cancer in the city of São Paulo, Brazil: Bayesian analysis of the association with traffic density

BACKGROUND

There is evidence that exposure to traffic-related air pollution is related to the incidence of and mortality associated with lung cancer. The aim of this study was to perform a spatial analysis, with a Bayesian approach, to test the hypothesis that high traffic density is associated with increased respiratory tract cancer incidence and mortality risk among individuals over 20 years of age residing in the city of São Paulo, Brazil.

METHODS

We employed data from two different databases: the São Paulo Municipal Population-Based Cancer Registry (2002-2011 cancer incidence data); and the Mortality Database of the São Paulo Municipal Health Department (2002-2013 cancer mortality data). The relationships between the number of cases of respiratory tract cancer in each area analyzed and the standardized covariates-traffic density and the Municipal Human Development Index (MHDI)-were evaluated with a Besag-York-Mollié ecological model with relative risks (RRs) estimates.

RESULTS

Per 1-unit standard-deviation increase in traffic density and in the MHDI, the RR for respiratory tract cancer incidence was 1.07 (95% CI: 1.02-1.13) and 1.25 (95% CI: 1.18-1.32), respectively, whereas the RR for mortality was 1.04 (95% CI: 0.99-1.09) and 1.23 (95% CI: 1.16-1.30), respectively.

CONCLUSION

Our findings support the hypothesis that residing in areas with high traffic density is associated with increased respiratory tract cancer incidence and mortality risk in the city of São Paulo.

The value of using seasonality and meteorological variables to model intra-urban PM2.5 variation

A yearlong air monitoring campaign was conducted to assess the impact of local temperature, relative humidity, and wind speed on the temporal and spatial variability of PM_2.5 in El Paso, Texas. Monitoring was conducted at four sites purposely selected to capture the local traffic variability. Effects of meteorological events on seasonal PM_2.5 variability were identified. For instance, in winter low-wind and low-temperature conditions were associated with high PM_2.5 events that contributed to elevated seasonal PM_2.5 levels. Similarly, in spring, high PM_2.5 events were associated with high-wind and low-relative humidity conditions. Correlation coefficients between meteorological variables and PM_2.5 fluctuated drastically across seasons. Specifically, it was observed that for most sites correlations between PM_2.5 and meteorological variables either changed from positive to negative or dissolved depending on the season. Overall, the results suggest that mixed effects analysis with season and site as fixed factors and meteorological variables as covariates could increase the explanatory value of LUR models for PM_2.5.

Short-term effects of air pollution on respiratory mortality in Ahvaz, Iran

Background: Urban air pollutants may affect respiratory mortality. This study was conducted to investigate this effect in Ahvaz, one of the most polluted cities in the world. Methods: The impact of 7 major air pollutants including O3, PM10, NO2, CO, and SO2 were evaluated on respiratory mortality in different gender and age groups using a quasi-Poisson, second degree polynomial constrained, distributed lag model, with single and cumulative lag structures adjusted by trend, seasonality, temperature, relative humidity, weekdays, and holiday. Data were analyzed using the dlnm package in R x64 3.2.5 software. Significance level was set at less than 0.05. Results: In adjusted models, for each IQR increase of O3 in the total population, the risk ratio (RR) for respiratory deaths in 0 to 14- day lags was, respectively, 1.009 (95% CI:1.001-1.016) and 1.009 (95% CI:1.002-1.017), and it was 1.021 (95% CI: 1.002-1.040) in cumulative 0 to 14- day lags. For PM10, in the total population and in adjusted models after 0 to 14- day lags and in cumulative lags of 0 to 14 for an IQR increase in the mean concentration of PM10, the RR for respiratory deaths increased significantly and was, respectively, 1.027 (95% CI:1.002-1.051), 1.029 (95% CI:1.006-1.052), and 1.065 (95% CI:1.005-1.128). NO2 showed a significant association with respiratory deaths only in the 18 to 60 year- old age group and in 9- day lags (RR= 1.318, 95% CI:1.002-1.733). Finally, the results showed that for an IQR increase in the mean concentration of CO and SO2, the adjusted RR for respiratory deaths in 9- day lags in the total population was, respectively, RR= 1.058 (95% CI:1.008-1.111) and 1.126 (95% CI:1.034-1.220). Conclusion: Air pollution in Ahvaz is probably causing increased respiratory mortality.

Relationship between income and mortality in a Canadian family practice cohort

OBJECTIVE

To examine the relationship between household income and mortality in a primary care cohort while using personal information obtained from clinical records and administrative data linkages to adjust for confounders.

DESIGN

Survey and analysis of data from several administrative databases.

SETTING

Toronto, Ont.

PARTICIPANTS

Patients of an urban academic family practice who were aged between 45 and 74 and who had made at least 3 visits to the clinic between 1996 and 1997.

MAIN OUTCOME MEASURES

Patients' self-reported household income. Patients' personal information obtained from clinical records and linkages to administrative data to adjust for confounders; personal information was used to adjust for health factors as confounders of the relationship between income and mortality risk.

RESULTS

Of the 1064 patients who received surveys, 519 (49%) responded. There was no significant difference in the mortality rate between nonresponders and responders. Mortality rates were lower than those in the general population throughout follow-up. Within the patient cohort, mortality rates were elevated for smokers, those who had not consumed alcohol in the year before the survey, and those who had been diagnosed with diabetes, hypertension, or cancer before the survey. After all adjustments were made, mortality rates were lower among patients in the higher-income categories than among those with lower household incomes.

CONCLUSION

Universal health care does not eliminate income-related differentials in mortality. Differences in health-related behaviour factors are not sufficient to explain the socioeconomic mortality differences within an area. These data suggest that it is not solely personal choice related to health behaviour but that other explanations must be invoked to account for the relationship between lower household income and increased mortality rates.

Climate Change and the Impact on Respiratory and Allergic Disease: 2018

PURPOSE OF REVIEW

The purpose of this paper is to review allergic respiratory disease related to indoor and outdoor exposures and to examine the impact of known and projected changes in climate. The global burden of disease directly attributed to climate change is very difficult to measure and becomes more challenging when the capacity of humans to adapt to these changes is taken into consideration. Allergic respiratory disease, such as asthma, is quite heterogenous, though closely associated with environmental and consequently immunologic interaction. Where is the tipping point?

RECENT FINDINGS

Our climate has been measurably changing for the past 100 years. It may indeed be the most significant health threat of the twenty-first century, and consequently tackling climate change may be the greatest health opportunity. The impacts of climate change on human health are varied and coming more into focus. Direct effects, such as heatwaves, severe weather, drought, and flooding, are apparent and frequently in the news. Indirect or secondary effects, such as changes in ecosystems and the impact on health, are less obvious. It is these changes in ecosystems that may have the greatest impact on allergic and respiratory diseases. This review will explore some ways that climate change, current and predicted, influences respiratory disease. Discussion will focus on changing pollen patterns, damp buildings with increased mold exposure, air pollution, and heat stress.