Air conditioning and source-specific particles as modifiers of the effect of PM(10) on hospital admissions for heart and lung disease

Silibinin Mitigates Vanadium-induced Lung Injury via the TLR4/MAPK/NF-κB Pathway in Mice

BACKGROUND/AIM

Silibinin, has been investigated for its potential benefits and mechanisms in addressing vanadium pentoxide (V2O5)-induced pulmonary inflammation. This study explored the anti-inflammatory activity of silibinin and elucidate the mechanisms by which it operates in a mouse model of vanadium-induced lung injury.

MATERIALS AND METHODS

Eight-week-old male BALB/c mice were exposed to V2O5 to induce lung injury. Mice were pretreated with silibinin at doses of 50 mg/kg and 100 mg/kg. Histological analyses were performed to assess cell viability and infiltration of inflammatory cells. The expression of pro-inflammatory cytokines (TNF-α, IL-6, IL-1β) and activation of the MAPK and NF-[Formula: see text]B signaling pathways, as well as the NLRP3 inflammasome, were evaluated using real-time PCR, western blot analysis, and immunohistochemistry. Whole blood analysis was conducted to measure white blood cell counts.

RESULTS

Silibinin treatment significantly improved cell viability, reduced inflammatory cell infiltration, and decreased the expression of pro-inflammatory cytokines in V2O5-induced lung injury. It also notably suppressed the activation of the MAPK and NF-[Formula: see text]B signaling pathways, along with a marked reduction in NLRP3 inflammasome expression levels in lung tissues. Additionally, silibinin-treated groups exhibited a significant decrease in white blood cell counts, including neutrophils, lymphocytes, and eosinophils.

CONCLUSION

These findings underscore the potent anti-inflammatory effects of silibinin in mice with V2O5-induced lung inflammation, highlighting its therapeutic potential. The study not only confirms the efficacy of silibinin in mitigating inflammatory responses but also provides a foundational understanding of its role in modulating key inflammatory pathways, paving the way for future therapeutic strategies against pulmonary inflammation induced by environmental pollutants.

Personal Strategies to Reduce the Cardiovascular Impacts of Environmental Exposures

Ubiquitous environmental exposures increase cardiovascular disease risk via diverse mechanisms. This review examines personal strategies to minimize this risk. With regard to fine particulate air pollution exposure, evidence exists to recommend the use of portable air cleaners and avoidance of outdoor activity during periods of poor air quality. Other evidence may support physical activity, dietary modification, omega-3 fatty acid supplementation, and indoor and in-vehicle air conditioning as viable strategies to minimize adverse health effects. There is currently insufficient data to recommend specific personal approaches to reduce the adverse cardiovascular effects of noise pollution. Public health advisories for periods of extreme heat or cold should be observed, with limited evidence supporting a warm ambient home temperature and physical activity as strategies to limit the cardiovascular harms of temperature extremes. Perfluoroalkyl and polyfluoroalkyl substance exposure can be reduced by avoiding contact with perfluoroalkyl and polyfluoroalkyl substance-containing materials; blood or plasma donation and cholestyramine may reduce total body stores of perfluoroalkyl and polyfluoroalkyl substances. However, the cardiovascular impact of these interventions has not been examined. Limited utilization of pesticides and safe handling during use should be encouraged. Finally, vasculotoxic metal exposure can be decreased by using portable air cleaners, home water filtration, and awareness of potential contaminants in ground spices. Chelation therapy reduces physiological stores of vasculotoxic metals and may be effective for the secondary prevention of cardiovascular disease.

A review of air pollution as a driver of cardiovascular disease risk across the diabetes spectrum

The prevalence of diabetes is estimated to reach almost 630 million cases worldwide by the year 2045; of current and projected cases, over 90% are type 2 diabetes. Air pollution exposure has been implicated in the onset and progression of diabetes. Increased exposure to fine particulate matter air pollution (PM2.5) is associated with increases in blood glucose and glycated hemoglobin (HbA1c) across the glycemic spectrum, including normoglycemia, prediabetes, and all forms of diabetes. Air pollution exposure is a driver of cardiovascular disease onset and exacerbation and can increase cardiovascular risk among those with diabetes. In this review, we summarize the literature describing the relationships between air pollution exposure, diabetes and cardiovascular disease, highlighting how airborne pollutants can disrupt glucose homeostasis. We discuss how air pollution and diabetes, via shared mechanisms leading to endothelial dysfunction, drive increased cardiovascular disease risk. We identify portable air cleaners as potentially useful tools to prevent adverse cardiovascular outcomes due to air pollution exposure across the diabetes spectrum, while emphasizing the need for further study in this particular population. Given the enormity of the health and financial impacts of air pollution exposure on patients with diabetes, a greater understanding of the interventions to reduce cardiovascular risk in this population is needed.

Protecting Cardiovascular Health From Wildfire Smoke

Wildfire smoke is a rapidly growing threat to global cardiovascular health. We review the literature linking wildfire smoke exposures to cardiovascular effects. We find substantial evidence that short-term exposures are associated with key cardiovascular outcomes, including mortality, hospitalization, and acute coronary syndrome. Wildfire smoke exposures will continue to increase over the majority of Earth's surface. For example, the United States alone has experienced a 5-fold increase in annual area burned since 1972, with 82 million individuals estimated to be exposed to wildfire smoke by midcentury. The associated rise in excess morbidity and mortality constitutes a growing global public health crisis. Fortunately, the effect of wildfire smoke on cardiovascular health is modifiable at the individual and population levels through specific interventions. Health systems therefore have an opportunity to help safeguard patients from smoke exposures. We provide a roadmap of evidence-based interventions to reduce risk and protect cardiovascular health. Key interventions include preparing health systems for smoke events; identifying and educating vulnerable patients; reducing outdoor activities; creating cleaner air environments; using air filtration devices and personal respirators; and aggressive management of chronic diseases and traditional risk factors. Further research is needed to test the efficacy of interventions on reducing cardiovascular outcomes.

Short-term health effects from outdoor exposure to biomass burning emissions: A review

Biomass burning (BB) including forest, bush, prescribed fires, agricultural fires, residential wood combustion, and power generation has long been known to affect climate, air quality and human health. With this work we supply a systematic review on the health effects of BB emissions in the framework of the WHO activities on air pollution. We performed a literature search of online databases (PubMed, ISI, and Scopus) from year 1980 up to 2020. A total of 81 papers were considered as relevant for mortality and morbidity effects. High risk of bias was related with poor estimation of BB exposure and lack of adjustment for important confounders. PM10 and PM2.5 concentrations originating from BB were associated with all-cause mortality: the meta-analytical estimate was equal to 1.31% (95% CI 0.71, 1.71) and 1.92% (95% CI -1.19, 5.03) increased mortality per each 10 μg m^-3 increase of PM10 and PM2.5, respectively. Regarding cardiovascular mortality 8 studies reported quantitative estimates. For smoky days and for each 10 μg m^-3 increase in PM2.5 concentrations, the risk of cardiovascular mortality increased by 4.45% (95% CI 0.96, 7.95) and by 3.30% (95% CI -1.97, 8.57), respectively. Fourteen studies evaluated whether respiratory morbidity was adversely related to PM2.5 (9 studies) or PM10 (5 studies) originating from BB. All found positive associations. The pooled effect estimates were 4.10% (95% CI 2.86, 5.34) and 4.83% (95% CI 0.06, 9.60) increased risk of total respiratory admissions/emergency visits, per 10 μg m^-3 increases in PM2.5 and PM10, respectively. Regarding cardiovascular morbidity, sixteen studies evaluated whether this was adversely related to PM2.5 (10 studies) or PM10 (6 studies) originating from BB. They found both positive and negative results, with summary estimates equal to 3.68% (95% CI -1.73, 9.09) and 0.93% (95% CI -0.18, 2.05) increased risk of total cardiovascular admissions/emergency visits, per 10 μg m^-3 increases in PM2.5 and PM10, respectively. To conclude, a significant number of studies indicate that BB exposure is associated with all-cause and cardiovascular mortality and respiratory morbidity.

Spatio-temporal variations of indoor air quality in a university library

The present study aims to assess the air quality status in the central library of Indian Institute of Technology Roorkee, India. Pollutants concentrations (i.e. PM₁₀, PM_2.5, PM₁ and TVOC) and comfort parameters i.e. CO₂, temperature and relative humidity were monitored across all floors of the library. Air quality was found to vary significantly (P < 0.05) among the different floors of the library. The average concentration of PM₁₀, PM_2.5 and PM₁ was found to be highest at the first floor. On the other hand, the highest concentration of TVOC (51.7 ± 30 ppb) and CO₂ (838.4 ± 99 ppm) was observed at the ground floor. Pollutant concentration was higher in the morning hours. The indoor pollutants were found positively correlated with each other except relative humidity. Indoor to outdoor ratio for PM₁, TVOC and CO₂ was found to be greater than 1, which indicate a substantial contribution from indoor sources. Exceedance of WHO guidelines was observed for the daily average PM_2.5 concentration.Abbreviation: IAQ: indoor air quality; ASHRAE: American Society of Heating, Refrigerating, and Air-Conditioning Engineers; WHO: World Health Organization; PM: particulate matter; VOC: volatile organic carbon; CO₂: carbon dioxide; TVOC: Total volatile organic compound; RH: relative humidity; HVAC: heating ventilation and air-conditioning; PID: Photo Ionization Detector; PTFE: Polytetrafluoroethylene; NDIR: Non-dispersive infra-red.

Estimating climate change-related impacts on outdoor air pollution infiltration

BACKGROUND

Rising temperatures due to climate change are expected to impact human adaptive response, including changes to home cooling and ventilation patterns. These changes may affect air pollution exposures via alteration in residential air exchange rates, affecting indoor infiltration of outdoor particles. We conducted a field study examining associations between particle infiltration and temperature to inform future studies of air pollution health effects.

METHODS

We measured indoor fine particulate matter (PM_2.5) in Atlanta in 60 homes (810 sampling-days). Indoor-outdoor sulfur ratios were used to estimate particle infiltration, using central site outdoor sulfur concentrations. Linear and mixed-effects models were used to examine particle infiltration ratio-temperature relationships, based on which we incorporated projected meteorological values (Representative Concentration Pathways intermediate scenario RCP 4.5) to estimate particle infiltration ratios in 20-year future (2046-2065) and past (1981-2000) scenarios.

RESULTS

The mean particle infiltration ratio in Atlanta was 0.70 ± 0.30, with a 0.21 lower ratio in summer compared to transition seasons (spring, fall). Particle infiltration ratios were 0.19 lower in houses using heating, ventilation, and air conditioning (HVAC) systems compared to those not using HVAC. We observed significant associations between particle infiltration ratios and both linear and quadratic models of ambient temperature for homes using natural ventilation and those using HVAC. Future temperature was projected to increase by 2.1 °C in Atlanta, which corresponds to an increase of 0.023 (3.9%) in particle infiltration ratios during cooler months and a decrease of 0.037 (6.2%) during warmer months.

DISCUSSION

We estimated notable changes in particle infiltration ratio in Atlanta for different 20-year periods, with differential seasonal patterns. Moreover, when stratified by HVAC usage, increases in future ambient temperature due to climate change were projected to enhance seasonal differences in PM_2.5 infiltration in Atlanta. These analyses can help minimize exposure misclassification in epidemiologic studies of PM_2.5, and provide a better understanding of the potential influence of climate change on PM_2.5 health effects.

Air Pollution and Emergency Hospital Admissions—Evidences from Lisbon Metropolitan Area, Portugal

The relevance of air pollution in the public health agenda has recently been reinforced—it is known that exposure to it has negative effects in the health of individuals, especially in big cities and metropolitan areas. In this article we observed the evolution of air pollutants (CO, NO, NO2, O3, PM10) emissions and we confront them with health vulnerabilities related to respiratory and circulatory diseases (all circulatory diseases, cardiac diseases, cerebrovascular disease, ischemic heart disease, all respiratory diseases, chronic lower respiratory diseases, acute upper respiratory infections). The study is supported in two databases, one of air pollutants and the other of emergency hospital admissions, in the 2005–2015 period, applied to the Lisbon Metropolitan Area. The analysis was conducted through Ordinary Least Squares (OLS) regression, while also using semi-elasticity to quantify associations. Results showed positive associations between air pollutants and admissions, tendentially higher in respiratory diseases, with CO and O3 having the highest number of associations, and the senior age group being the most impacted. We concluded that O3 is a good predictor for the under-15 age group and PM10 for the over-64 age group; also, there seems to exist a distinction between the urban city core and its suburban areas in air pollution and its relation to emergency hospital admissions.

Immunopathological features of air pollution and its impact on inflammatory airway diseases (IAD)

Air pollution causes significant morbidity and mortality in patients with inflammatory airway diseases (IAD) such as allergic rhinitis (AR), chronic rhinosinusitis (CRS), asthma, and chronic obstructive pulmonary disease (COPD). Oxidative stress in patients with IAD can induce eosinophilic inflammation in the airways, augment atopic allergic sensitization, and increase susceptibility to infection. We reviewed emerging data depicting the involvement of oxidative stress in IAD patients. We evaluated biomarkers, outcome measures and immunopathological alterations across the airway mucosal barrier following exposure, particularly when accentuated by an infectious insult.

How Did Distribution Patterns of Particulate Matter Air Pollution (PM2.5 and PM10) Change in China during the COVID-19 Outbreak: A Spatiotemporal Investigation at Chinese City-Level

Due to the suspension of traffic mobility and industrial activities during the COVID-19, particulate matter (PM) pollution has decreased in China. However, rarely have research studies discussed the spatiotemporal pattern of this change and related influencing factors at city-scale across the nation. In this research, the clustering patterns of the decline rates of PM_2.5 and PM₁₀ during the period from 20 January to 8 April in 2020, compared with the same period of 2019, were investigated using spatial autocorrelation analysis. Four meteorological factors and two socioeconomic factors, i.e., the decline of intra-city mobility intensity (dIMI) representing the effect of traffic mobility and the decline rates of the secondary industrial output values (drSIOV), were adopted in the regression analysis. Then, multi-scale geographically weighted regression (MGWR), a model allowing the particular processing scale for each independent variable, was applied for investigating the relationship between PM pollution reductions and influencing factors. For comparison, ordinary least square (OLS) regression and the classic geographically weighted regression (GWR) were also performed. The research found that there were 16% and 20% reduction of PM_2.5 and PM₁₀ concentration across China and significant PM pollution mitigation in central, east, and south regions of China. As for the regression analysis results, MGWR outperformed the other two models, with R² of 0.711 and 0.732 for PM_2.5 and PM₁₀, respectively. The results of MGWR revealed that the two socioeconomic factors had more significant impacts than meteorological factors. It showed that the reduction of traffic mobility caused more relative declines of PM_2.5 in east China (e.g., cities in Jiangsu), while it caused more relative declines of PM₁₀ in central China (e.g., cities in Henan). The reduction of industrial operation had a strong relationship with the PM₁₀ drop in northeast China. The results are crucial for understanding how the decline pattern of PM pollution varied spatially during the COVID-19 outbreak, and it also provides a good reference for air pollution control in the future.

Investigation of the PM2.5, NO2 and O3 I/O ratios for office and school microenvironments

Differentiation of the exposure to PM_2.5 (particulate matter less than 2.5 μm in aerodynamic diameter), NO₂ and O₃ i.e. pollutants of outdoor origin, due to the occupation of office and school microenvironments, was investigated through the quantification of the respective Indoor to Outdoor (I/O) ratios, in simple statistical terms. For that cause, indoor and outdoor observation data were retrieved from the HEALS EDMS database, and more specifically the data from the OFFICAIR and the SINPHONIE EU projects. The I/O ratios were produced and were statistically analyzed in order to be able to study the influence of the indoor environment against the pollutants coming from outdoors. The present statistical approach highlighted also the differences of I/O ratios between the two studied microenvironments for each pollutant. For exposure estimation to the above-mentioned pollutants, the probability and cumulative distribution function (pdf/cdf) empirical approximations led to the conclusion that for offices the I/O ratios of PM_2.5 follow a normal distribution, while NO₂ and O₃ a gamma distribution. Respectively, for schools the I/O ratios of all pollutants follow a lognormal distribution.

Synthesis of Harvard Environmental Protection Agency (EPA) Center studies on traffic-related particulate pollution and cardiovascular outcomes in the Greater Boston Area

The association between particulate pollution and cardiovascular morbidity and mortality is well established. While the cardiovascular effects of nationally regulated criteria pollutants (e.g., fine particulate matter [PM_2.5] and nitrogen dioxide) have been well documented, there are fewer studies on particulate pollutants that are more specific for traffic, such as black carbon (BC) and particle number (PN). In this paper, we synthesized studies conducted in the Greater Boston Area on cardiovascular health effects of traffic exposure, specifically defined by BC or PN exposure or proximity to major roadways. Large cohort studies demonstrate that exposure to traffic-related particles adversely affect cardiac autonomic function, increase systemic cytokine-mediated inflammation and pro-thrombotic activity, and elevate the risk of hypertension and ischemic stroke. Key patterns emerged when directly comparing studies with overlapping exposure metrics and population cohorts. Most notably, cardiovascular risk estimates of PN and BC exposures were larger in magnitude or more often statistically significant compared to those of PM_2.5 exposures. Across multiple exposure metrics (e.g., short-term vs. long-term; observed vs. modeled) and different population cohorts (e.g., elderly, individuals with co-morbidities, young healthy individuals), there is compelling evidence that BC and PN represent traffic-related particles that are especially harmful to cardiovascular health. Further research is needed to validate these findings in other geographic locations, characterize exposure errors associated with using monitored and modeled traffic pollutant levels, and elucidate pathophysiological mechanisms underlying the cardiovascular effects of traffic-related particulate pollutants. Implications: Traffic emissions are an important source of particles harmful to cardiovascular health. Traffic-related particles, specifically BC and PN, adversely affect cardiac autonomic function, increase systemic inflammation and thrombotic activity, elevate BP, and increase the risk of ischemic stroke. There is evidence that BC and PN are associated with greater cardiovascular risk compared to PM_2.5. Further research is needed to elucidate other health effects of traffic-related particles and assess the feasibility of regulating BC and PN or their regional and local sources.

Human exposure factors as potential determinants of the heterogeneity in city-specific associations between PM2.5 and mortality

Multi-city population-based epidemiological studies of short-term fine particulate matter (PM_2.5) exposures and mortality have observed heterogeneity in risk estimates between cities. Factors affecting exposures, such as pollutant infiltration, which are not captured by central-site monitoring data, can differ between communities potentially explaining some of this heterogeneity. This analysis evaluates exposure factors as potential determinants of the heterogeneity in 312 core-based statistical areas (CBSA)-specific associations between PM_2.5 and mortality using inverse variance weighted linear regression. Exposure factor variables were created based on data on housing characteristics, commuting patterns, heating fuel usage, and climatic factors from national surveys. When survey data were not available, air conditioning (AC) prevalence was predicted utilizing machine learning techniques. Across all CBSAs, there was a 0.95% (Interquartile range (IQR) of 2.25) increase in non-accidental mortality per 10 µg/m³ increase in PM_2.5 and significant heterogeneity between CBSAs. CBSAs with larger homes, more heating degree days, a higher percentage of home heating with oil had significantly (p < 0.05) higher health effect estimates, while cities with more gas heating had significantly lower health effect estimates. While univariate models did not explain much of heterogeneity in health effect estimates (R² < 1%), multivariate models began to explain some of the observed heterogeneity (R² = 13%).

Exploration of the heterogeneous effect of climate change on ozone concentration in an urban environment

Ozone is a significant causative agent of mortality in cities. Urban environments are expressly vulnerable to global warming because of the extensive emission of air pollutants with urban heat island effect enhancing much rapidly the ozone concentration than in the less urbanized regions. This effect previously was not studied in local scale. It was hypothesized that climate change will cause heterogenic increase of ozone concentration in the different parts of the cities. To study this effect, the near-surface ozone concentration of 10 points of a Hungarian city was measured and modeled. At first step, the local correlations between solar radiation, air temperature, relative humidity and the near surface ozone concentrations at 3 m height were determined, specifying the local ozone-producing conditions. Then, based on the scenario of the Intergovernmental Panel on Climate Change 5th assessment report, the future seasonal near-surface ozone concentrations were modeled. Based on the model, it was determined that climate change will result in a heterogenic increase of near-surface ozone concentration.

Estimation of health benefits from air quality improvement using the MODIS AOD dataset in Seoul, Korea

BACKGROUND

Exposure to fine particles in the atmosphere can adversely affect health and even lead to premature death. Recently, South Korea has attracted attention because of its rapid increase in the concentration of Particulate Matter (PM).

OBJECTIVES

We estimated the economic benefits of reducing PM₁₀ in Seoul, South Korea, based on MODerate-resolution Imaging Spectroradiometer (MODIS) Aerosol Optical Depth (AOD). Based on the retrieved PM₁₀ data, we estimated its effects on overall health in each district of Seoul, Korea between 2014 and 2015.

METHODS

The relationships between MODIS AOD and ground-based PM₁₀ data were identified in different seasons in South Korea between 2012 and 2013 using the linear regression model. The health benefits were estimated by the Benefits Mapping and Analysis Program (Benmap) using the scenarios from the World Health Organization (WHO).

RESULTS

The correlation between MODIS AOD and PM₁₀ concentration differed with the season. There was a higher correlation between MODIS AOD and PM₁₀ concentration in winter (R = 0.57) than there was in other seasons. Based on the MODIS AOD, the average annual PM₁₀ concentration in Seoul was higher in 2014 than it was in 2015, at values of 45.7 μg/m³, and 41.6 μg/m³, respectively. The greatest economic benefit of reducing PM₁₀ concentration (WHO annual standard of 20 μg/m³) was in 2014. This benefit was estimated to be 7022 (95% CI: 599, 20496), 2617 (95% CI: 216, 7750), and 1328 (95% CI: -159, 4679) billion KRW for all-cause, cardiovascular, and respiratory mortalities in 2014 and 2015, respectively.

CONCLUSIONS

These results demonstrate that, despite considerable improvements in air quality in recent decades, there is still a need for countermeasures to prevent economic loss due to air pollution in Seoul.

The Shape of the Concentration-Response Association between Fine Particulate Matter Pollution and Human Mortality in Beijing, China, and Its Implications for Health Impact Assessment

BACKGROUND

Studies found approximately linear short-term associations between particulate matter (PM) and mortality in Western communities. However, in China, where the urban PM levels are typically considerably higher than in Western communities, some studies suggest nonlinearity in this association. Health impact assessments (HIA) of PM in China have generally not incorporated nonlinearity in the concentration-response (C-R) association, which could result in large discrepancies in estimates of excess deaths if the true association is nonlinear.

OBJECTIVES

We investigated nonlinearity in the C-R associations between with PM with aerodynamic diameter [Formula: see text] ([Formula: see text]) and mortality in Beijing, China, and the sensitivity of HIA to linearity assumptions.

METHODS

We modeled the C-R association between [Formula: see text] and cause-specific mortality in Beijing, China (2009-2012), using generalized linear models (GLM). [Formula: see text] was included through either linear, piecewise-linear, or spline functions to investigate evidence of nonlinearity. To determine the sensitivity of HIA to linearity assumptions, we estimated [Formula: see text]-attributable deaths using both linear- and nonlinear-based C-R associations between [Formula: see text] and mortality.

RESULTS

We found some evidence that, for nonaccidental and circulatory mortality, the shape of the C-R association was relatively flat at lower concentrations of [Formula: see text], but then had a positive slope at higher concentrations, indicating nonlinearity. Conversely, the shape for respiratory mortality was positive and linear at lower concentrations of [Formula: see text], but then leveled off at the higher concentrations. Estimates of excess deaths attributable to short-term [Formula: see text] exposure were, in some cases, very sensitive to the linearity assumption in the association, but in other cases robust to this assumption.

CONCLUSIONS

Our results demonstrate some evidence of nonlinearity in [Formula: see text]-mortality associations and that an assumption of linearity in this association can influence HIAs, highlighting the importance of understanding potential nonlinearity in the [Formula: see text]-mortality association at the high concentrations of [Formula: see text] in developing megacities like Beijing. https://doi.org/10.1289/EHP4464.

Spatial variation in the effects of air pollution on cardiovascular mortality in Beijing, China

Due to lack of data from multiple air quality monitoring stations, studies about spatial association between concentrations of ambient pollutants and mortality in China are rare. To investigate the spatial variation of association between concentrations of particulate matter less than 10 μm in aerodynamic diameter (PM₁₀) and nitrogen dioxide (NO₂) and cardiovascular mortality in Beijing, China, we collected data including daily deaths, concentrations of PM₁₀ and NO₂, and meteorological factors from January 1, 2009, to December 31, 2010, in all 16 districts of Beijing. Generalized additive model (GAM) and generalized additive mixed model (GAMM) were used to examine the citywide and district-specific effects of PM₁₀ and NO₂ on cardiovascular mortality. The citywide effect derived from GAMM was lower than that derived from GAM and the strongest effects were identified for 2-day moving average lag 0-1. For every 10 μg/m³ increases in concentrations of PM₁₀ and NO₂, the corresponding daily cardiovascular mortality increases in 0.31% (95%CI 0.15%, 0.46%) and 1.63% (95%CI 1.11%, 2.13%), respectively. The death risk associated with air pollutants varied across different geographic districts in Beijing. We found spatially varied adverse effects of air pollution on cardiovascular deaths in Beijing. But there was insufficient evidence to show the significant spatial heterogeneity in mortality effects of PM₁₀ and NO₂ in this study.

Trace Metals in Soot and PM2.5 from Heavy-Fuel-Oil Combustion in a Marine Engine

Heavy fuel oil (HFO) particulate matter (PM) emitted by marine engines is known to contain toxic heavy metals, including vanadium (V) and nickel (Ni). The toxicity of such metals will depend on the their chemical state, size distribution, and mixing state. Using online soot-particle aerosol mass spectrometry (SP-AMS), we quantified the mass of five metals (V, Ni, Fe, Na, and Ba) in HFO-PM soot particles produced by a marine diesel research engine. The in-soot metal concentrations were compared to in-PM2.5 measurements by inductively coupled plasma-optical emission spectroscopy (ICP-OES). We found that <3% of total PM2.5 metals was associated with soot particles, which may still be sufficient to influence in-cylinder soot burnout rates. Since these metals were most likely present as oxides, whereas studies on lower-temperature boilers report a predominance of sulfates, this result implies that the toxicity of HFO PM depends on its combustion conditions. Finally, we observed a 4-to-25-fold enhancement in the ratio V:Ni in soot particles versus PM2.5, indicating an enrichment of V in soot due to its lower nucleation/condensation temperature. As this enrichment mechanism is not dependent on soot formation, V is expected to be generally enriched within smaller HFO-PM particles from marine engines, enhancing its toxicity.

The spatial variation in the effects of air pollution on cardiovascular mortality in Beijing, China

Owing to lack of data from multiple air quality monitoring stations, studies about spatial association between concentrations of ambient pollutants and mortality in China are rare. To investigate the spatial variation of association between concentrations of particulate matter less than 10 μm in aerodynamic diameter (PM₁₀), nitrogen dioxide (NO₂) and carbon monoxide (CO) and cardiovascular mortality in Beijing, China, we collected data including daily deaths, concentrations of PM₁₀, NO₂ and CO, and meteorological factors from 1 January 2009 to 31 December 2010 in all 16 districts of Beijing. Generalized additive model (GAM) and generalized additive mixed model (GAMM) were used to examine the citywide and district-specific effects of PM₁₀, NO₂ and CO on cardiovascular mortality. The citywide effect derived from GAMM was lower than that derived from GAM, and the strongest effects were identified for 2-day moving average lag 0-1. The interquartile increases in concentrations of PM₁₀, NO₂ and CO were associated with 2.46 (95% confidence interval (CI), 1.22-3.72), 4.11 (95%CI, 2.82-5.42) and 2.23 (95%CI, 1.14-3.33) percentage increases in daily cardiovascular mortality by GAMM, respectively. The relative risk of each district compared with reference district was generally statistically significant. The death risk associated with air pollutants varies across different geographic districts in Beijing. The data indicate that the risk is high in suburban areas and rural counties. We found significant and spatially varied adverse effects of air pollution on cardiovascular deaths across the rural and urban areas in Beijing.

Effects of air pollution on hospital visits for pneumonia in children: a two-year analysis from China

Although the effect of air pollution on respiratory health has been identified, few studies can be available to evaluate the association of air pollution with hospital visits for children's pneumonia in China. To explore whether high concentrations of air pollutants (including PM_2.5, PM₁₀, NO₂, and SO₂) are related to hospital visits for pneumonia in children, we conducted a population-based time-series study in Ningbo, China, from January 1st, 2014 to November 1st, 2015. We used a generalized additive Poisson regression model to calculate risk ratios and 95% confidence intervals for the associations of air pollutants and hospital visits for pneumonia in children and found that these four pollutants were associated with the increased hospital visits for pneumonia in children (1.3% for PM2.5, 1.0% for PM10, 2.9% for NO₂, 5.0% for SO₂ per 10-μg/m³ increase in PM2.5, PM10, NO₂, and SO₂, respectively). Stronger associations were observed in the cold seasons and among children under 5 years.

Global Associations between Air Pollutants and Chronic Obstructive Pulmonary Disease Hospitalizations. A Systematic Review

RATIONALE

Exacerbations are key events in chronic obstructive pulmonary disease (COPD), affecting lung function decline and quality of life. The effect of exposure to different air pollutants on COPD exacerbations is not clear.

OBJECTIVES

To carry out a systematic review, examining associations between air pollutants and hospital admissions for COPD exacerbations.

METHODS

MEDLINE, Embase, BIOSIS, Science Citation Index, and the Air Pollution Epidemiology Database were searched for publications published between 1980 and September 2015. Inclusion criteria were focused on studies presenting solely a COPD outcome defined by hospital admissions and a measure of gaseous air pollutants and particle fractions. The association between each pollutant and COPD admissions was investigated in metaanalyses using random effects models. Analyses were stratified by geographical clusters for investigation of the consistency of the evidence worldwide.

MEASUREMENTS AND MAIN RESULTS

Forty-six studies were included, and results for all the pollutants under investigation showed marginal positive associations; however, the number of included studies was small, the studies had high heterogeneity, and there was evidence of small-study bias. Geographical clustering of the effects of pollution on COPD hospital admissions was evident and reduced heterogeneity significantly.

CONCLUSIONS

The most consistent association was between a 1-mg/m³ increase in carbon monoxide level and COPD-related admissions (odds ratio, 1.02; 95% confidence interval, 1.01-1.03). The heterogeneity was moderate, and there was a consistent positive association in both Europe and North America, although levels were clearly below World Health Organization guideline values. There is mixed evidence on the effects of environmental pollution on COPD exacerbations. Limitations of previous studies included the low spatiotemporal resolution of pollutants, inadequate control for confounding factors, and the use of aggregated health data that ignored personal characteristics. The need for more targeted exposure estimates in a large number of geographical locations is evident.

Health risk associated with airborne particulate matter and its components in Jeddah, Saudi Arabia

Samples of PM_2.5 and PM₁₀ have been collected in all of four seasons at seven sites within the city of Jeddah, Saudi Arabia. The samples have been analysed for a range of trace elements. There is a large loading of wind-blown dust and the majority of elements are predominantly associated with coarse particles. Enrichment factors, however, show that some elements are markedly enriched above crustal abundance. Using mean data for the PM_2.5 and PM₁₀ fractions from each of the seven sampling sites, health risks have been estimated for particulate matter mass, the elements Cr, Mn, Ni, Pb, As, Cd and V measured in this study, and polycyclic aromatic hydrocarbons using data from an earlier study within Jeddah. Cancer risks are calculated from mean airborne concentrations and cancer slope factors for the carcinogenic metals and PAH, but the cancer risks are relatively modest compared to the lifetime risk of mortality due to PM_2.5 exposure. The risks associated with exposure to V and Mn are considered to be small, while concentrations of cadmium far exceed the European Union Limit Value and World Health Organisation guideline. Cadmium shows a very high crustal enrichment factor but is present predominantly in the coarse particle fraction suggesting that local soils and surface dusts are unusually enriched in Cd relative to the global average. Using national data for mortality rates, the excess mortality due to PM_2.5 exposure has been calculated and amounts to over 1100 deaths annually for the city of Jeddah.

PM2.5 and Mortality in 207 US Cities: Modification by Temperature and City Characteristics

BACKGROUND

The reported estimated effects between long-term PM2.5 exposures and mortality vary spatially. We assessed whether community-level variables, including socioeconomic status indicators and temperature, modify this association.

METHODS

We used data from >35 million Medicare enrollees from 207 US cities (2000-2010). For each city, we calculated annual PM2.5 averages, measured at ambient central monitoring sites. We used a variation of a causal modeling approach and fitted city-specific Cox models, which we then pooled using a random effects meta-regression. In this second stage, we assessed whether temperature and city-level variables, including smoking and obesity rates, poverty, education and greenness, modify the long-term PM2.5-mortality association.

RESULTS

We found an association between long-term PM2.5 and survival (hazard ratio = 1.2; 95% confidence interval [CI]: 1.1, 1.3 per 10 μg/m increase in the annual PM2.5 average concentrations). We observed elevated estimates in the Southeastern, South and Northwestern US (hazard ratio = 1.9; 95% CI: 1.7, 2.2, and 1.4; 95% CI: 1.2, 1.7, and 1.4; 95% CI: 1.1, 1.9, respectively). We observed a higher association between long-term PM2.5 exposure and mortality in warmer cities. Furthermore, we observed increasing estimates with increasing obesity rates, %residents and families in poverty, %black residents and %population without a high school degree, and lower effects with increasing median household income and %white residents.

CONCLUSIONS

To the best of our knowledge, this is the first study to assess modification by temperature and community-level characteristics on the long-term PM2.5-survival association. Our findings suggest that living in cities with high temperatures and low socio economic status (SES) is associated with higher effect estimates.

The interactive effects between high temperature and air pollution on mortality: A time-series analysis in Hefei, China

Recent evidence suggests that there may be an interaction between air pollution and heat on mortality, which is pertinent in the context of global climate change. We sought to examine this interaction in Hefei, a hot and polluted Chinese city. We conducted time-series analyses using daily mortality, air pollutant concentration (including particulate matter with aerodynamic diameter <10μm (PM₁₀), sulphur dioxide (SO₂) and nitrogen dioxide (NO₂)), and temperature data from 2008 to 2014. We applied quasi-Poisson regression models with natural cubic splines and examined the interactive effects using temperature-stratified models. Subgroup analyses were conducted by age, gender, and educational levels. We observed consistently stronger associations between air pollutants and mortality at high temperatures than at medium temperatures. These differences were statistically significant for the associations between PM₁₀ and non-accidental mortality and between all pollutants studied and respiratory mortality. Mean percentage increases in non-accidental mortality per 10μg/m³ at high temperatures were 2.40% (95% confidence interval: 0.64 to 4.20) for PM₁₀, 7.77% (0.60 to 15.00) for SO₂, and 6.83% (-1.37 to 15.08) for NO₂. The estimates for PM₁₀ were 3.40% (0.96 to 5.90) in females and 4.21% (1.44 to 7.05) in the illiterate, marking them as more vulnerable. No clear trend was identified by age. We observed an interaction between air pollutants and high temperature on mortality in Hefei, which was stronger in females and the illiterate. This may be due to differences in behaviours affecting personal exposure to high temperatures and has potential policy implications.

Short-term exposures to ambient air pollution and risk of recurrent ischemic stroke

OBJECTIVE

To investigate the association between short-term changes in ambient pollution (particulate matter <2.5µm in aerodynamic diameter (PM_2.5) and ozone (O₃)) and the risk of recurrent ischemic stroke among individuals living in a bi-ethnic community.

METHODS

We identified recurrent ischemic stroke cases from the population-based Brain Attack Surveillance in Corpus Christi (BASIC) project between 2000 and 2012. Associations between PM_2.5 (mean 24-h) and O₃ (maximal 8-h) levels, measured on the previous day, and odds of ischemic stroke were assessed using a time-stratified case-crossover design and modeled using conditional logistic regression.

RESULTS

There were 317 recurrent ischemic strokes after excluding 41 strokes that occurred on days with missing air pollution data. Mean age was 72 years (SD=12) and median time to stroke recurrence was 1.1 years (IQR: 0.2-2.8 years). Median levels of PM_2.5 and O₃ over the study period were 7.7μg/m³ (IQR: 5.6-10.7μg/m³) and 35.2 ppb (IQR: 25.0-46.1 ppb), respectively. We observed no associations between previous-day PM_2.5 and O₃ and odds of recurrent stroke (OR=0.95 per 10µg/m³ of PM_2.5, 95% CI: 0.71-1.28 and OR=0.97 per 10ppb of O₃, 95% CI: 0.87-1.07) after adjusting for ambient temperature and relative humidity. Co-adjustment of both pollutants did not change the results.

CONCLUSION

We found no evidence of associations between previous-day air pollution levels and recurrent ischemic stroke. Research on the influence of air pollutants on risk of stroke recurrence is still in its infancy, and more research is necessary in studies that are adequately powered to understand the relation.

Major air pollutants and risk of COPD exacerbations: a systematic review and meta-analysis

Background

Short-term exposure to major air pollutants (O₃, CO, NO₂, SO₂, PM₁₀, and PM_2.5) has been associated with respiratory risk. However, evidence on the risk of chronic obstructive pulmonary disease (COPD) exacerbations is still limited. The present study aimed at evaluating the associations between short-term exposure to major air pollutants and the risk of COPD exacerbations.

Methods

After a systematic search up until March 30, 2016, in both English and Chinese electronic databases such as PubMed, EMBASE, and CNKI, the pooled relative risks and 95% confidence intervals were estimated by using the random-effects model. In addition, the population-attributable fractions (PAFs) were also calculated, and a subgroup analysis was conducted. Heterogeneity was assessed by I².

Results

In total, 59 studies were included. In the single-pollutant model, the risks of COPD were calculated by each 10 μg/m³ increase in pollutant concentrations, with the exception of CO (100 μg/m³). There was a significant association between short-term exposure and COPD exacerbation risk for all the gaseous and particulate pollutants. The associations were strongest at lag0 and lag3 for gaseous and particulate air pollutants, respectively. The subgroup analysis not only further confirmed the overall adverse effects but also reduced the heterogeneities obviously. When 100% exposure was assumed, PAFs ranged from 0.60% to 4.31%, depending on the pollutants. The adverse health effects of SO₂ and NO₂ exposure were more significant in low-/middle-income countries than in high-income countries: SO₂, relative risk: 1.012 (95% confidence interval: 1.001, 1.023); and NO₂, relative risk: 1.019 (95% confidence interval: 1.014, 1.024).

Conclusion

Short-term exposure to air pollutants increases the burden of risk of COPD acute exacerbations significantly. Controlling ambient air pollution would provide benefits to COPD patients.

Type and Proximity of Green Spaces Are Important for Preventing Cardiovascular Morbidity and Diabetes--A Cross-Sectional Study for Quebec, Canada

This study aimed at determining the role of proximity to specific types of green spaces (GSes) as well as their spatial location in the relationship with the most morbid cardiovascular diseases (CVD) and diabetes. We measured the accessibility to various types of GS and used a cross-sectional approach at census Dissemination Area (DA) levels in the Montreal and Quebec City metropolitan zones for the period 2006–2011. Poisson and negative binomial regression models were fitted to quantify the relationship between distances to specific types of GS and CVD morbidity as well as some risk factors (diabetes and hypertension) while controlling for several social and environmental confounders. GSes that have sports facilities showed a significant relationship to cerebrovascular diseases: the most distant population had an 11% higher prevalence rate ratio (PRR) compared to the nearest, as well as higher diabetes risk (PRR 9%) than the nearest. However, the overall model performance and the understanding of the role of GSes with sport facilities may be substantially achieved with lifestyle factors. Significantly higher prevalence of diabetes and cerebrovascular diseases as well as lower access to GSes equipped with sports facilities were found in suburban areas. GSes can advantageously be used to prevent some CVDs and their risk factors, but there may be a need to reconsider their types and location.

PM2.5 and survival among older adults: effect modification by particulate composition

BACKGROUND

Fine particulate (PM2.5) air pollution has been consistently linked to survival, but reported effect estimates are geographically heterogeneous. Exposure to different types of particle mixtures may explain some of this variation.

METHODS

We used k-means cluster analyses to identify cities with similar pollution profiles, (ie, PM2.5 composition) across the United States. We examined the impact of PM2.5 on survival, and its variation across clusters of cities with similar PM2.5 composition, among Medicare enrollees in 81 US cities (2000-2010). We used time-varying annual PM2.5 averages, measured at ambient central monitoring sites, as the exposure of interest. We ran by-city Cox models, adjusting for individual data on previous cardiopulmonary-related hospitalizations and stratifying by follow-up time, age, gender, and race. This eliminates confounding by factors varying across cities and long-term trends, focusing on year-to-year variations of air pollution around its city-specific mean and trend. We then pooled the city-specific effects using a random effects meta-regression. In this second stage, we also assessed effect modification by cluster membership and estimated cluster-specific PM2.5 effects.

RESULTS

We followed more than 19 million subjects and observed more than 6 million deaths. We found a harmful impact of annual PM2.5 concentrations on survival (hazard ratio = 1.11 [95% confidence interval = 1.01, 1.23] per 10 μg/m). This effect was modified by particulate composition, with higher effects observed in clusters containing high concentrations of nickel, vanadium, and sulfate. For instance, our highest effect estimate was observed in cities with harbors in the Northwest, characterized by high nickel, vanadium, and elemental carbon concentrations (1.9 [1.1, 3.3]). We observed null or negative associations in clusters with high oceanic and crustal particles.

CONCLUSIONS

To the best of our knowledge, this is the first study to examine the association between PM2.5 composition and survival. Our findings indicate that long-term exposure to fuel oil combustion and power plant emissions have the highest impact on survival.

Urban-rural differences in daily time-activity patterns, occupational activity and housing characteristics

BACKGROUND

There is evidence that rural residents experience a health disadvantage compared to urban residents, associated with a greater prevalence of health risk factors and socioeconomic differences. We examined differences between urban and rural Canadians using data from the Canadian Human Activity Pattern Survey (CHAPS) 2.

METHODS

Data were collected from 1460 respondents in two rural areas (Haldimand-Norfolk, Ontario and Annapolis Valley-Kings County, Nova Scotia) and 3551 respondents in five urban areas (Vancouver, Edmonton, Toronto, Montreal, and Halifax) using a 24-h recall diary and supplementary questionnaires administered using computer-assisted telephone interviews. We evaluated differences in time-activity patterns, occupational activity, and housing characteristics between rural and urban populations using multivariable linear and logistic regression models adjusted for design as well as demographic and socioeconomic covariates. Taylor linearization method and design-adjusted Wald tests were used to test statistical significance.

RESULTS

After adjustment for demographic and socioeconomic covariates, rural children, adults and seniors spent on average 0.7 (p < 0.05), 1.2 (p < 0.001), and 0.9 (p < 0.001) more hours outdoors per day respectively than urban counterparts. 23.1% (95% CI: 19.0-27.2%) of urban and 37.8% (95% CI: 31.2-44.4%) of rural employed populations reported working outdoors and the distributions of job skill level and industry differed significantly (p < 0.001) between urban and rural residents. In particular, 11.4% of rural residents vs. 4.9% of urban residents were employed in unskilled jobs, and 11.5% of rural residents vs. <0.5% of urban residents were employ in primary industry. Rural residents were also more likely than urban residents to report spending time near gas or diesel powered equipment other than vehicles (16.9% vs. 5.2%, p < 0.001), more likely to report wood as a heating fuel (9.8% vs. <0.1%; p < 0.001 for difference in distribution of heating fuels), less likely to have an air conditioner (43.0% vs. 57.2%, p < 0.001), and more likely to smoke (29.1% vs. 19.0 %, p < 0.001). Private wells were the main water source in rural areas (68.6%) in contrast to public water systems (97.6%) in urban areas (p < 0.001). Despite these differences, no differences in self-reported health status were observed between urban and rural residents.

CONCLUSIONS

We identified a number of differences between urban and rural residents, which provide evidence pertinent to the urban-rural health disparity.

The Canadian Healthy Infant Longitudinal Development (CHILD) birth cohort study: assessment of environmental exposures

The Canadian Healthy Infant Longitudinal Development birth cohort was designed to elucidate interactions between environment and genetics underlying development of asthma and allergy. Over 3600 pregnant mothers were recruited from the general population in four provinces with diverse environments. The child is followed to age 5 years, with prospective characterization of diverse exposures during this critical period. Key exposure domains include indoor and outdoor air pollutants, inhalation, ingestion and dermal uptake of chemicals, mold, dampness, biological allergens, pets and pests, housing structure, and living behavior, together with infections, nutrition, psychosocial environment, and medications. Assessments of early life exposures are focused on those linked to inflammatory responses driven by the acquired and innate immune systems. Mothers complete extensive environmental questionnaires including time-activity behavior at recruitment and when the child is 3, 6, 12, 24, 30, 36, 48, and 60 months old. House dust collected during a thorough home assessment at 3-4 months, and biological specimens obtained for multiple exposure-related measurements, are archived for analyses. Geo-locations of homes and daycares and land-use regression for estimating traffic-related air pollution complement time-activity-behavior data to provide comprehensive individual exposure profiles. Several analytical frameworks are proposed to address the many interacting exposure variables and potential issues of co-linearity in this complex data set.

Multi-site time series analysis of acute effects of multiple air pollutants on respiratory mortality: a population-based study in Beijing, China

In large cities in China, the traffic-related air pollution has become the focus of attention, and its adverse effects on health have raised public concerns. We conducted a study to quantify the association between exposure to three major traffic-related pollutants - particulate matter < 10 μm in aerodynamic diameter (PM10), carbon monoxide (CO) and nitrogen dioxide (NO2) and the risk of respiratory mortality in Beijing, China at a daily spatiotemporal resolution. We used the generalized additive models (GAM) with natural splines and principal component regression method to associate air pollutants with daily respiratory mortality, covariates and confounders. The GAM analysis adjusting for the collinearity among pollutants indicated that PM10, CO and NO2 had significant effects on daily respiratory mortality in Beijing. An interquartile range increase in 2-day moving averages concentrations of day 0 and day 1 of PM10, CO and NO2 corresponded to 0.99 [95% confidence interval (CI): 0.30, 1.67], 0.89 (95% CI: 0.27, 1.51) and 0.95 (95% CI: 0.29, 1.61) percent increase in daily respiratory mortality, respectively. The effects were varied across the districts. The strongest effects were found in two rural districts and one suburban district but significant in only one district. In conclusion, high level of several traffic-related air pollutants is associated with an increased risk of respiratory mortality in Beijing over a short-time period. The high risk found in rural areas suggests a potential susceptible sub-population with undiagnosed respiratory diseases in these areas. Although the rural areas have relatively lower air pollution levels, they deserve more attention to respiratory disease prevention and air pollution reduction.

Associations of short-term particle and noise exposures with markers of cardiovascular and respiratory health among highway maintenance workers

BACKGROUND

Highway maintenance workers are constantly and simultaneously exposed to traffic-related particle and noise emissions, both of which have been linked to increased cardiovascular morbidity and mortality in population-based epidemiology studies.

OBJECTIVES

We aimed to investigate short-term health effects related to particle and noise exposure.

METHODS

We monitored 18 maintenance workers, during as many as five 24-hr periods from a total of 50 observation days. We measured their exposure to fine particulate matter (diameter ≤ 2.5 μm; PM2.5), ultrafine particles, and noise, and the cardiopulmonary health end points: blood pressure, proinflammatory and prothrombotic markers in the blood, lung function, and fractional exhaled nitric oxide (FeNO) measured approximately 15 hr after work. Heart rate variability was assessed during a sleep period approximately 10 hr after work.

RESULTS

PM2.5 exposure was significantly associated with C-reactive protein and serum amyloid A, and was negatively associated with tumor necrosis factor α. None of the particle metrics were significantly associated with von Willebrand factor or tissue factor expression. PM2.5 and work noise were associated with markers of increased heart rate variability, and with increased high-frequency and low-frequency power. Systolic and diastolic blood pressure on the following morning were significantly associated with noise exposure after work, and nonsignificantly associated with PM2.5. We observed no significant associations between any of the exposures and lung function or FeNO.

CONCLUSIONS

Our findings suggest that exposure to particles and noise during highway maintenance work might pose a cardiovascular health risk. Actions to reduce these exposures could lead to better health for this population of workers.

Public health and components of particulate matter: the changing assessment of black carbon

In 2012, the WHO classified diesel emissions as carcinogenic, and its European branch suggested creating a public health standard for airborne black carbon (BC). In 2011, EU researchers found that life expectancy could be extended four to nine times by reducing a unit of BC, vs reducing a unit of PM2.5. Only recently could such determinations be made. Steady improvements in research methodologies now enable such judgments. In this Critical Review, we survey epidemiological and toxicological literature regarding carbonaceous combustion emissions, as research methodologies improved over time. Initially, we focus on studies of BC, diesel, and traffic emissions in the Western countries (where daily urban BC emissions are mainly from diesels). We examine effects of other carbonaceous emissions, e.g., residential burning of biomass and coal without controls, mainly in developing countries. Throughout the 1990s, air pollution epidemiology studies rarely included species not routinely monitored. As additional PM2.5. chemical species, including carbonaceous species, became more widely available after 1999, they were gradually included in epidemiological studies. Pollutant species concentrations which more accurately reflected subject exposure also improved models. Natural "interventions"--reductions in emissions concurrent with fuel changes or increased combustion efficiency; introduction of ventilation in highway tunnels; implementation of electronic toll payment systems--demonstrated health benefits of reducing specific carbon emissions. Toxicology studies provided plausible biological mechanisms by which different PM species, e.g, carbonaceous species, may cause harm, aiding interpretation of epidemiological studies. Our review finds that BC from various sources appears to be causally involved in all-cause, lung cancer and cardiovascular mortality, morbidity, and perhaps adverse birth and nervous system effects. We recommend that the US. EPA rubric for judging possible causality of PM25. mass concentrations, be used to assess which PM2.5. species are most harmful to public health.

IMPLICATIONS

Black carbon (BC) and correlated co-emissions appear causally related with all-cause, cardiovascular, and lung cancer mortality, and perhaps with adverse birth outcomes and central nervous system effects. Such findings are recent, since widespread monitoring for BC is also recent. Helpful epidemiological advances (using many health relevant PM2.5 species in models; using better measurements of subject exposure) have also occurred. "Natural intervention" studies also demonstrate harm from partly combusted carbonaceous emissions. Toxicology studies consistently find biological mechanisms explaining how such emissions can cause these adverse outcomes. A consistent mechanism for judging causality for different PM2.5 species is suggested.

Toxicological and epidemiological studies of cardiovascular effects of ambient air fine particulate matter (PM2.5) and its chemical components: coherence and public health implications

Recent investigations on PM2.5 constituents' effects in community residents have substantially enhanced our knowledge on the impacts of specific components, especially the HEI-sponsored National Particle Toxicity Component (NPACT) studies at NYU and UW-LRRI that addressed the impact of long-term PM2.5 exposure on cardiovascular disease (CVD) effects. NYU's mouse inhalation studies at five sites showed substantial variations in aortic plaque progression by geographic region that was coherent with the regional variation in annual IHD mortality in the ACS-II cohort, with both the human and mouse responses being primarily attributable to the coal combustion source category. The UW regressions of associations of CVD events and mortality in the WHI cohort, and of CIMT and CAC progression in the MESA cohort, indicated that [Formula: see text] had stronger associations with CVD-related human responses than OC, EC, or Si. The LRRI's mice had CVD-related biomarker responses to [Formula: see text]. NYU also identified components most closely associated with daily hospital admissions (OC, EC, Cu from traffic and Ni and V from residual oil). For daily mortality, they were from coal combustion ([Formula: see text], Se, and As). While the recent NPACT research on PM2.5 components that affect CVD has clearly filled some major knowledge gaps, and helped to define remaining uncertainties, much more knowledge is needed on the effects in other organ systems if we are to identify and characterize the most effective and efficient means for reducing the still considerable adverse health impacts of ambient air PM. More comprehensive speciation data are needed for better definition of human responses.

Clustering cities with similar fine particulate matter exposure characteristics based on residential infiltration and in-vehicle commuting factors

Epidemiological studies have observed between city heterogeneity in PM2.5-mortality risk estimates. These differences could potentially be due to the use of central-site monitors as a surrogate for exposure which do not account for an individual's activities or ambient pollutant infiltration to the indoor environment. Therefore, relying solely on central-site monitoring data introduces exposure error in the epidemiological analysis. The amount of exposure error produced by using the central-site monitoring data may differ by city. The objective of this analysis was to cluster cities with similar exposure distributions based on residential infiltration and in-vehicle commuting characteristics. Factors related to residential infiltration and commuting were developed from the American Housing Survey (AHS) from 2001 to 2005 for 94 Core-Based Statistical Areas (CBSAs). We conducted two separate cluster analyses using a k-means clustering algorithm to cluster CBSAs based on these factors. The first only included residential infiltration factors (i.e. percent of homes with central air conditioning (AC) mean year home was built, and mean home size) while the second incorporated both infiltration and commuting (i.e. mean in-vehicle commuting time and mean in-vehicle commuting distance) factors. Clustering on residential infiltration factors resulted in 5 clusters, with two having distinct exposure distributions. Cluster 1 consisted of cities with older, smaller homes with less central AC while homes in Cluster 2 cities were newer, larger, and more likely to have central AC. Including commuting factors resulted in 10 clusters. Clusters with shorter in-vehicle commuting times had shorter in-vehicle commuting distances. Cities with newer homes also tended to have longer commuting times and distances. This is the first study to employ cluster analysis to group cities based on exposure factors. Identifying cities with similar exposure distributions may help explain city-to-city heterogeneity in PM2.5 mortality risk estimates.

Exposure measurement error in PM2.5 health effects studies: a pooled analysis of eight personal exposure validation studies

BACKGROUND

Exposure measurement error is a concern in long-term PM2.5 health studies using ambient concentrations as exposures. We assessed error magnitude by estimating calibration coefficients as the association between personal PM2.5 exposures from validation studies and typically available surrogate exposures.

METHODS

Daily personal and ambient PM2.5, and when available sulfate, measurements were compiled from nine cities, over 2 to 12 days. True exposure was defined as personal exposure to PM2.5 of ambient origin. Since PM2.5 of ambient origin could only be determined for five cities, personal exposure to total PM2.5 was also considered. Surrogate exposures were estimated as ambient PM2.5 at the nearest monitor or predicted outside subjects' homes. We estimated calibration coefficients by regressing true on surrogate exposures in random effects models.

RESULTS

When monthly-averaged personal PM2.5 of ambient origin was used as the true exposure, calibration coefficients equaled 0.31 (95% CI:0.14, 0.47) for nearest monitor and 0.54 (95% CI:0.42, 0.65) for outdoor home predictions. Between-city heterogeneity was not found for outdoor home PM2.5 for either true exposure. Heterogeneity was significant for nearest monitor PM2.5, for both true exposures, but not after adjusting for city-average motor vehicle number for total personal PM2.5.

CONCLUSIONS

Calibration coefficients were <1, consistent with previously reported chronic health risks using nearest monitor exposures being under-estimated when ambient concentrations are the exposure of interest. Calibration coefficients were closer to 1 for outdoor home predictions, likely reflecting less spatial error. Further research is needed to determine how our findings can be incorporated in future health studies.

Ambient Woodsmoke and Associated Respiratory Emergency Department Visits in Spokane, Washington

Three multivariate receptor algorithms were applied to seven years of chemical speciation data to apportion fine particulate matter to various sources in Spokane, Washington. Source marker compounds were used to assess the associations between atmospheric concentration of these compounds and daily cardiac hospital admissions and/or respiratory emergency department visits. Total carbon and arsenic had high correlations with two different vegetative burning sources and were selected as vegetative burning markers, while zinc and silicon were selected as markers for the motor vehicle and airborne soil sources, respectively. The rate of respiratory emergency department visits increased 2% for a 3.0 microg/m3 interquartile range change in a vegetative burning source marker (1.023, 95% CI 1.009-1.038) at a lag of one day. The other source markers studied were not associated with the health outcomes investigated. Results suggest vegetative burning is associated with acute respiratory events.

Has the short-term effect of black smoke exposure on pneumonia mortality been underestimated because hospitalisation is ignored: findings from a case-crossover study

BACKGROUND

Short-term associations have been demonstrated between air pollution and respiratory mortality including pneumonia. Studies typically estimate exposure based only on place of residence, yet many are in hospital prior to death. This study investigates lag length and tests the hypothesis that the effect of 'black smoke' is greater when restricted to pneumonia deaths in the community - Community Deaths from Pneumonia.

METHODS

A time-stratified case-crossover design using conditional logistic regression estimated the daily percentage increase in risk of pneumonia mortality in relation to 'black smoke' in the preceding 30 days. Cases were pneumonia deaths in Edinburgh 1981-1996. Multiple 'control' periods, were defined using the same weekdays for the same month as the case death. Lag structure was investigated by a stratified lag model with five 6-day periods and by distributed lag models. Hospital admissions data, defined a community death as someone who had not been in hospital in any of the 30 days before death.

RESULTS

Of 14,346 subjects who died from pneumonia, 7,536 were community deaths. Larger estimated increases in risks were seen in the community for all lag periods. Both stratified and distributed lag methods suggested positive effect estimates for 18 days after exposure and negative thereafter; the average percent increase per day across the 18 days was 0.70% (95% C.I. 0.29-1.14) for community subjects and 0.30% (95% C.I. 0.03-0.59) for all subjects.

CONCLUSIONS

Studies which fail to account for hospitalisation may underestimate exposure effects as stronger pollution effects on mortality were evident in community based subjects.

Spatiotemporally resolved air exchange rate as a modifier of acute air pollution-related morbidity in Atlanta

Epidemiological studies frequently use central site concentrations as surrogates of exposure to air pollutants. Variability in air pollutant infiltration due to differential air exchange rates (AERs) is potentially a major factor affecting the relationship between central site concentrations and actual exposure, and may thus influence observed health risk estimates. In this analysis, we examined AER as an effect modifier of associations between several urban air pollutants and corresponding emergency department (ED) visits for asthma and wheeze during a 4-year study period (January 1999-December 2002) for a 186 ZIP code area in metro Atlanta. We found positive associations for the interaction between AER and pollution on asthma ED visits for both carbon monoxide (CO) and nitrogen oxides (NO(x)), indicating significant or near-significant effect modification by AER on the pollutant risk-ratio estimates. In contrast, the interaction term between particulate matter (PM)(2.5) and AER on asthma ED visits was negative and significant. However, alternative distributional tertile analyses showed PM(2.5) and AER epidemiological model results to be similar to those found for NOx and CO (namely, increasing risk ratios (RRs) with increasing AERs when ambient PM(2.5) concentrations were below the highest tertile of their distribution). Despite the fact that ozone (O(3)) was a strong independent predictor of asthma ED visits in our main analysis, we found no O(3)-AER effect modification. To our knowledge, our findings for CO, NOx, and PM(2.5) are the first to provide an indication of short-term (i.e., daily) effect modification of multiple air pollution-related risk associations with daily changes in AER. Although limited to one outcome category in a single large urban locale, the findings suggest that the use of relatively simple and easy-to-derive AER surrogates may reflect intraurban differences in short-term exposures to pollutants of ambient origin.

Refined ambient PM2.5 exposure surrogates and the risk of myocardial infarction

Using a case-crossover study design and conditional logistic regression, we compared the relative odds of transmural (full-wall) myocardial infarction (MI) calculated using exposure surrogates that account for human activity patterns and the indoor transport of ambient PM(2.5) with those calculated using central-site PM(2.5) concentrations to estimate exposure to PM(2.5) of outdoor origin (exposure to ambient PM(2.5)). Because variability in human activity and indoor PM(2.5) transport contributes exposure error in epidemiologic analyses when central-site concentrations are used as exposure surrogates, we refer to surrogates that account for this variability as "refined" surrogates. As an alternative analysis, we evaluated whether the relative odds of transmural MI associated with increases in ambient PM(2.5) is modified by residential air exchange rate (AER), a variable that influences the fraction of ambient PM(2.5) that penetrates and persists indoors. Use of refined exposure surrogates did not result in larger health effect estimates (ORs=1.10-1.11 with each interquartile range (IQR) increase), narrower confidence intervals, or better model fits compared with the analysis that used central-site PM(2.5). We did observe evidence for heterogeneity in the relative odds of transmural MI with residential AER (effect-modification), with residents of homes with higher AERs having larger ORs than homes in lower AER tertiles. For the level of exposure-estimate refinement considered here, our findings add support to the use of central-site PM(2.5) concentrations for epidemiological studies that use similar case-crossover study designs. In such designs, each subject serves as his or her own matched control. Thus, exposure error related to factors that vary spatially or across subjects should only minimally impact effect estimates. These findings also illustrate that variability in factors that influence the fraction of ambient PM(2.5) in indoor air (e.g., AER) could possibly bias health effect estimates in study designs for which a spatiotemporal comparison of exposure effects across subjects is conducted.

A framework to spatially cluster air pollution monitoring sites in US based on the PM2.5 composition

BACKGROUND

Heterogeneity in the response to PM2.5 is hypothesized to be related to differences in particle composition across monitoring sites which reflect differences in source types as well as climatic and topographic conditions impacting different geographic locations. Identifying spatial patterns in particle composition is a multivariate problem that requires novel methodologies.

OBJECTIVES

Use cluster analysis methods to identify spatial patterns in PM2.5 composition. Verify that the resulting clusters are distinct and informative.

METHODS

109 monitoring sites with 75% reported speciation data during the period 2003-2008 were selected. These sites were categorized based on their average PM2.5 composition over the study period using k-means cluster analysis. The obtained clusters were validated and characterized based on their physico-chemical characteristics, geographic locations, emissions profiles, population density and proximity to major emission sources.

RESULTS

Overall 31 clusters were identified. These include 21 clusters with 2 or more sites which were further grouped into 4 main types using hierarchical clustering. The resulting groupings are chemically meaningful and represent broad differences in emissions. The remaining clusters, encompassing single sites, were characterized based on their particle composition and geographic location.

CONCLUSIONS

The framework presented here provides a novel tool which can be used to identify and further classify sites based on their PM2.5 composition. The solution presented is fairly robust and yielded groupings that were meaningful in the context of air-pollution research.

Respiratory viral infections and effects of meteorological parameters and air pollution in adults with respiratory symptoms admitted to the emergency room

Background

Respiratory viral infections (RVIs) are the most common causes of respiratory infections. The prevalence of respiratory viruses in adults is underestimated. Meteorological variations and air pollution are likely to play a role in these infections.

Objectives

The objectives of this study were to determine the number of emergency visits for influenza-like illness (ILI) and severe acute respiratory infection (SARI) and to evaluate the association between ILI/SARI, RVI prevalence, and meteorological factors/air pollution, in the city of Porto Alegre, Brazil, from November 2008 to October 2010.

Methods

Eleven thousand nine hundred and fifty-three hospitalizations (adults and children) for respiratory symptoms were correlated with meteorological parameters and air pollutants. In a subset of adults, nasopharyngeal aspirates were collected and analyzed through IFI test. The data were analyzed using time-series analysis.

Results

Influenza-like illness and SARI were diagnosed in 3698 (30·9%) and 2063 (17·7%) patients, respectively. Thirty-seven (9·0%) samples were positive by IFI and 93 of 410 (22·7%) were IFI and/or PCR positive. In a multivariate logistic regression model, IFI positivity was statistically associated with absolute humidity, use of air conditioning, and presence of mold in home. Sunshine duration was significantly associated with the frequency of ILI cases. For SARI cases, the variables mean temperature, sunshine duration, relative humidity, and mean concentration of pollutants were singnificant.

Conclusions

At least 22% of infections in adult patients admitted to ER with respiratory complaints were caused by RVI. The correlations among meteorological variables, air pollution, ILI/SARI cases, and respiratory viruses demonstrated the relevance of climate factors as significant underlying contributors to the prevalence of RVI.

Long-term air pollution exposure and cardio- respiratory mortality: a review

Current day concentrations of ambient air pollution have been associated with a range of adverse health effects, particularly mortality and morbidity due to cardiovascular and respiratory diseases. In this review, we summarize the evidence from epidemiological studies on long-term exposure to fine and coarse particles, nitrogen dioxide (NO2) and elemental carbon on mortality from all-causes, cardiovascular disease and respiratory disease. We also summarize the findings on potentially susceptible subgroups across studies. We identified studies through a search in the databases Medline and Scopus and previous reviews until January 2013 and performed a meta-analysis if more than five studies were available for the same exposure metric.

Neighborhood effects on heat deaths: social and environmental predictors of vulnerability in Maricopa County, Arizona

BACKGROUND

Most heat-related deaths occur in cities, and future trends in global climate change and urbanization may amplify this trend. Understanding how neighborhoods affect heat mortality fills an important gap between studies of individual susceptibility to heat and broadly comparative studies of temperature-mortality relationships in cities.

OBJECTIVES

We estimated neighborhood effects of population characteristics and built and natural environments on deaths due to heat exposure in Maricopa County, Arizona (2000-2008).

METHODS

We used 2000 U.S. Census data and remotely sensed vegetation and land surface temperature to construct indicators of neighborhood vulnerability and a geographic information system to map vulnerability and residential addresses of persons who died from heat exposure in 2,081 census block groups. Binary logistic regression and spatial analysis were used to associate deaths with neighborhoods.

RESULTS

Neighborhood scores on three factors-socioeconomic vulnerability, elderly/isolation, and unvegetated area-varied widely throughout the study area. The preferred model (based on fit and parsimony) for predicting the odds of one or more deaths from heat exposure within a census block group included the first two factors and surface temperature in residential neighborhoods, holding population size constant. Spatial analysis identified clusters of neighborhoods with the highest heat vulnerability scores. A large proportion of deaths occurred among people, including homeless persons, who lived in the inner cores of the largest cities and along an industrial corridor.

CONCLUSIONS

Place-based indicators of vulnerability complement analyses of person-level heat risk factors. Surface temperature might be used in Maricopa County to identify the most heat-vulnerable neighborhoods, but more attention to the socioecological complexities of climate adaptation is needed.

Plasma fluorescent oxidation products and short-term occupational particulate exposures

BACKGROUND

Evidence suggests that fine particulate air pollution results in oxidative induced tissue damage.

METHODS

A global fluorescent oxidation products (FLOx) assay (fluorescent intensity (FI) units per milliliter of plasma) was measured in blood samples collected from 236 nonsmoking, Caucasian, male trucking industry workers either prior to, during, or after their work shifts. Occupational exposures to particulate matter (PM)(2.5) were based on job-specific area-level sampling. Generalized linear models were used to determine associations between FLOx levels and PM(2.5) , adjusted for age, time since last meal, alcohol consumption, aspirin, and cholesterol medications.

RESULTS

The mean (standard deviation) level of FLOx was 265.9 FI/ml (96.0). Levels of FLOx were higher among older individuals and lower among those who had consumed alcohol in the past 24 hr. However, no associations were observed between FLOx and PM(2.5) .

CONCLUSIONS

Our results indicate no association between occupational PM(2.5) exposure and this marker of global oxidative stress.