Ambient Air Pollutant Concentrations Research Articles

Long-term exposure to low ambient air pollution concentrations and mortality among 28 million people: results from seven large European cohorts within the ELAPSE project

Long-term exposure to ambient air pollution has been associated with premature mortality, but associations at concentrations lower than current annual limit values are uncertain. We analysed associations between low-level air pollution and mortality within the multicentre study Effects of Low-Level Air Pollution: A Study in Europe (ELAPSE). In this multicentre longitudinal study, we analysed seven population-based cohorts of adults (age ≥30 years) within ELAPSE, from Belgium, Denmark, England, the Netherlands, Norway, Rome (Italy), and Switzerland (enrolled in 2000-11; follow-up until 2011-17). Mortality registries were used to extract the underlying cause of death for deceased individuals. Annual average concentrations of fine particulate matter (PM2·5), nitrogen dioxide (NO2), black carbon, and tropospheric warm-season ozone (O3) from Europe-wide land use regression models at 100 m spatial resolution were assigned to baseline residential addresses. We applied cohort-specific Cox proportional hazard models with adjustment for area-level and individual-level covariates to evaluate associations with non-accidental mortality, as the main outcome, and with cardiovascular, non-malignant respiratory, and lung cancer mortality. Subset analyses of participants living at low pollutant concentrations (as per predefined values) and natural splines were used to investigate the concentration-response function. Cohort-specific effect estimates were pooled in a random-effects meta-analysis. We analysed 28 153 138 participants contributing 257 859 621 person-years of observation, during which 3 593 741 deaths from non-accidental causes occurred. We found significant positive associations between non-accidental mortality and PM2·5, NO2, and black carbon, with a hazard ratio (HR) of 1·053 (95% CI 1·021-1·085) per 5 μg/m3 increment in PM2·5, 1·044 (1·019-1·069) per 10 μg/m3 NO2, and 1·039 (1·018-1·059) per 0·5 × 10-5/m black carbon. Associations with PM2·5, NO2, and black carbon were slightly weaker for cardiovascular mortality, similar for non-malignant respiratory mortality, and stronger for lung cancer mortality. Warm-season O3 was negatively associated with both non-accidental and cause-specific mortality. Associations were stronger at low concentrations: HRs for non-accidental mortality at concentrations lower than the WHO 2005 air quality guideline values for PM2·5 (10 μg/m3) and NO2 (40 μg/m3) were 1·078 (1·046-1·111) per 5 μg/m3 PM2·5 and 1·049 (1·024-1·075) per 10 μg/m3 NO2. Similarly, the association between black carbon and non-accidental mortality was highest at low concentrations, with a HR of 1·061 (1·032-1·092) for exposure lower than 1·5× 10-5/m, and 1·081 (0·966-1·210) for exposure lower than 1·0× 10-5/m. Long-term exposure to concentrations of PM2·5 and NO2 lower than current annual limit values was associated with non-accidental, cardiovascular, non-malignant respiratory, and lung cancer mortality in seven large European cohorts. Continuing research on the effects of low concentrations of air pollutants is expected to further inform the process of setting air quality standards in Europe and other global regions. Health Effects Institute.

Associations of long-term exposure to ambient air pollutants with metabolic syndrome: The Wuhan Chronic Disease Cohort Study (WCDCS)

BackgroundEvidence on the associations between long-term exposure to ambient air pollutants (including particle with aerodynamic diameter ≤10 μm (PM10), particle with aerodynamic diameter ≤2.5 μm (PM2.5), ozone (O3), nitrogen dioxide (NO2), and sulfur dioxide (SO2)) and prevalence of metabolic syndrome (MetS) remains inconclusive. This study aimed to determine the associations based on a case-control study nested in the Wuhan Chronic Disease Cohort study (WCDCS), a population-based study with baseline survey in 2019. MethodsA total of 10,253 residents living in Wuhan were recruited. The 3-year average concentrations of main pollutants (PM10, PM2.5, O3, NO2, and SO2) at residences prior to the survey date were estimated to evaluate the long-term exposures. The generalized linear mixed models were used to investigate the changes in MetS prevalence by an IQR increases in each air pollutant exposure concentrations. Interaction effects between air pollutants and demographic, lifestyle, and dietary factors on MetS were evaluated by including an interactive item in the main model. ResultsThe prevalence of MetS in Wuhan was 9.8%, and the 3-year exposure concentrations of PM10, PM2.5, O3, NO2, and SO2 were 84.1 μg/m3, 50.5 μg/m3, 55.7 μg/m3, 46.0 μg/m3, and 9.4 μg/m3, respectively. Higher PM10, PM2.5 and O3 exposure concentrations were associated with an elevated MetS prevalence (e.g. an IQR increase in PM2.5, OR = 1.193, 95% confidence intervals (95%CIs): 1.028, 1.385; for O3, OR = 1.074, 95%CIs: 1.025, 1.124), whereas NO2, and SO2 were negatively or insignificant correlated with odds of Mets (e.g. an IQR increase in NO2, OR = 0.865, 95%CIs: 0.795, 0.941). Males, smokers, alcohol drinkers and individuals who intake fruits occasionally exposure to PM10 and PM2.5 were found had a higher risk of developing MetS. ConclusionsLong-term exposure to higher concentrations of ambient air pollutants may elevate the prevalence of MetS in populations in Central China. Susceptible individuals especially those with unhealthy lifestyles had a higher risk for MetS.

Associations of solid fuel use and ambient air pollution with estimated 10-year atherosclerotic cardiovascular disease risk.

Although exposure to ambient air pollution (AAP) increases the risk for arteriosclerotic cardiovascular disease (ASCVD), evidence on the association of solid fuel use with ASCVD and its association modified by ambient air pollution remains limited. A total of 16,779 adults were derived from the Henan Rural Cohort Study. Concentrations of ambient air pollutants (PM1, PM2.5, PM10, and NO2) were estimated by a spatiotemporal model based on satellites data. Solid fuel use was assessed by a self-reported questionnaire. The associations of solid fuel use with high 10-year ASCVD risk and the modified association by exposure to air pollutants were explored using logistic regression models. There were positive associations of AAP exposure with high 10-year ASCVD risk among individuals with self-cooking. The joint associations between high AAP exposures and solid fuel use with high 10-year ASCVD risk were found. Compared to clean fuel user with low PM2.5 exposure, the odds ratios (ORs) and 95% confidence intervals (CIs) of high 10-year ASCVD risk was 1.25 (1.09, 1.42) for solid fuel user with low PM2.5 exposure, 1.93 (1.75, 2.12) for clean fuel user with high PM2.5 exposure, and 3.08 (2.67, 3.54) for solid fuel user with high PM2.5 exposure, respectively. Their additive effect on high 10-year ASCVD risk was observed (relative excess risk due to interaction (RERI): 0.90 (95%CI: 0.50, 1.30), attributable proportion due to interaction (AP): 0.29 (95%CI: 0.19, 0.40), and synergy index (SI): 1.77 (95%CI: 1.38, 2.26)). This study showed a synergistic effect of AAP and household air pollution reflected by solid fuel use on high 10-year ASCVD risk, suggesting that reducing solid cooking fuels and controlling air pollution may have a joint effect on public health improvement.

Invited Perspective: Moving from Characterizing to Addressing Racial/Ethnic Disparities in Air Pollution Exposure.

Invited Perspective: Moving from Characterizing to Addressing Racial/Ethnic Disparities in Air Pollution Exposure.

Ambient air pollution associated with lower academic achievement among US children: A nationwide panel study of school districts.

Ambient air pollution is an important environmental exposure and has been linked with impaired cognitive function. Few studies have investigated its impact on children's academic performance on a nationwide level. We hypothesize that higher ambient air pollution concentrations will be associated with lower average academic test scores. We investigated three prevalent ambient air pollutants: PM2.5, NO2 and ozone, and their associations with the average academic test scores, at the Geographic School District (GSD) level, of the third to eighth grade students in the United States from 2010 to 2016. We applied multivariate linear regression and controlled for urbanicity, socioeconomic status, student racial/ethnic compositions, and individual intercepts for each district-grade level and each year. We found that an interquartile range increase in PM2.5 concentrations was associated with a 0.007 (95% confidence interval: 0.005, 0.009) SD lower average math test scores, and a 0.004 (95% confidence interval: 0.002, 0.005) SD lower average English language/arts test scores. Similar associations were observed for NO2 and ozone on math, and for NO2 on English language/arts. The magnitudes of these associations are equivalent to the effects of short-term reductions of thousands of dollars in district median household income. The reductions in test scores were larger for GSDs with higher socioeconomic status, though most associations remained negative at all socioeconomic levels. Our results show that ambient air pollution within a GSD is associated with lower academic performance among children. Further improving air quality may benefit children's overall academic achievement and socioeconomic attainment across the lifespan.

Upstream oil and gas production and ambient air pollution in California

BackgroundPrior studies have found that residential proximity to upstream oil and gas production is associated with increased risk of adverse health outcomes. Emissions of ambient air pollutants from oil and gas wells in the preproduction and production stages have been proposed as conferring risk of adverse health effects, but the extent of air pollutant emissions and resulting nearby pollution concentrations from wells is not clear. ObjectivesWe examined the effects of upstream oil and gas preproduction (count of drilling sites) and production (total volume of oil and gas) activities on concentrations of five ambient air pollutants in California. MethodsWe obtained data on approximately 1 million daily observations from 314 monitors in the EPA Air Quality System, 2006-2019, including daily concentrations of five routinely monitored ambient air pollutants: PM2.5, CO, NO2, O3, and VOCs. We obtained data on preproduction and production operations from Enverus and the California Geographic Energy Management Division (CalGEM) for all wells in the state. For each monitor and each day, we assessed exposure to upwind preproduction wells and total oil and gas production volume within 10 km. We used a panel regression approach in the analysis and fit adjusted fixed effects linear regression models for each pollutant, controlling for geographic, seasonal, temporal, and meteorological factors. ResultsWe observed higher concentrations of PM2.5 and CO at monitors within 3 km of preproduction wells, NO2 at monitors at 1-2 km, and O3 at 2-4 km from the wells. Monitors with proximity to increased production volume observed higher concentrations of PM2.5, NO2, and VOCs within 1 km and higher O3 concentrations at 1-2 km. Results were robust to sensitivity analyses. ConclusionAdjusting for geographic, meteorological, seasonal, and time-trending factors, we observed higher concentrations of ambient air pollutants at air quality monitors in proximity to preproduction wells within 4 km and producing wells within 2 km.

Air pollution and emergency department visits for urticaria

BACKGROUND AND AIM: The objective of this work was to investigate correlations between air pollution and emergency department (ED) visits for urticaria in Toronto, Canada. METHODS: The National Ambulatory Care Reporting System database was used to draw the diagnosed ED visits. The L50 section of the International Classification of Disease 10th Revision was used to extract ED visits whose primary causes of visit was urticaria-related conditions. Statistical models (Poisson regression) using daily counts of ED visits were created for urticaria, ambient air pollution concentrations, and weather factors. We considered two air quality health indexes and six ambient air pollutants for exposure: fine particulate matter PM2.5, O3, CO, NO2, SO2, and maximum 8-hour average ozone. RESULTS:A total of 176 statistically significant (P-Value 0.05) positive correlations were identified over the 14 day lag period. For ozone,74 positive correlations were observed with the following relative risks (RR) for one interquartile range (IQR=12.8 ppb) increase: RR=1.361 (95% confidence interval: 1.302, 1.404), 1.359 (1.299, 1.401), 1.351 (1.281, 1.404) in the warm season (April-September), lag 0, and RR=1.019 (1.013, 1.025), 1.023 (1.016, 1.030), 1.014 (1.007, 1.021), lag 1, in the cold period (October-March), for all, females, and males, respectively. 10, 45 and 45 positive correlations were also obtained for sulfur dioxide, fine particulate matter, and daily maximum 8-hour average ozone concentrations, respectively. CONCLUSIONS:The results indicate that urban ambient air pollution could influence the rates of ED visits for urticaria. Ambient ozone was determined as the main environmental factor contributing to these associations. KEYWORDS: Ozone, Traffic-related, Short-term exposure, Allergies

Ambient air pollution and academic achievements among US children: a panel study

BACKGROUND AND AIM: Ambient air pollution is an important environmental exposure, and children are especially vulnerable to its neurotoxic effects. Prior studies have associated early childhood exposures to air pollution with poor performances in cognitive and academic tests. No existing study has tested such associations on a nationwide level. We hypothesize that higher ambient air pollution concentrations in a Geographic Schol District (GSD) in the year prior to the state testing window will be associated with lower average academic test scores at the district level. METHODS: We investigate three prevalent ambient air pollutants: PM2.5, NO2 and ozone, and their association with the academic test scores of all students in grades 3 to 8 in the United States at the GSD level from 2010 to 2016. We applied multivariate linear regression and controlled for urbanicity, socioeconomic status, student racial compositions, GSD-grade fixed effects and year fixed effects. The two-way fixed effects model resembles a generalized difference-in-difference approach in a panel data setting. The results can be interpreted causally if certain assumptions are met. RESULTS:We found that a 1 μg/m3 increase in ambient PM2.5 was associated with a 0.00246 standard deviation (95% CI: 0.00173, 0.00320) lower average Math test score. Similar associations were found for NO2 (0.00049 per ppb, 95% CI: 0.00020, 0.00079) and ozone (0.00146 per ppm, 95% CI: 0.00111, 0.00180). For English language/arts (ELA), a 1 μg/m3 (ppb) increase in ambient PM2.5 (0.00141, 95% CI: 0.00083, 0.00199) and NO2 (0.00161, 95% CI: 0.00138, 0.00185) were associated with lower average test scores. The reductions in both Math and ELA test scores were larger for GSDs with higher socioeconomic status. CONCLUSIONS:Our results show that ambient air pollution is associate with lower academic performances among children. Further improving air quality may benefit children’s academic achievements and career in the long run. KEYWORDS: Air pollution, Neurodevelopmental outcomes, Oxides of nitrogen, Ozone, Particulate matter

Ambient air pollution exposures and functional decline in a sample of non-demented community-dwelling older adults in Northern Manhattan

BACKGROUND AND AIM: A growing body of evidence has linked air pollution exposures to indicators of unhealthy aging. The effects of air pollution on functional performance in older adults remain poorly understood. We investigated cross-sectional and longitudinal associations between air pollution exposures and functional performance. METHODS: From an available pool of 2182 participants enrolled in the Washington Heights-Inwood Aging Project from 1999-2002, 1884 individuals of Hispanic, Non-Hispanic White, or Non-Hispanic Black race-ethnicity who had valid addresses, no diagnosis of probable dementia at study intake, and were not missing data in the outcome measure of interest were selected. Inverse probability of censoring weighted linear mixed-effects models were used to investigate the associations between residential ambient air pollutant concentrations (fine particulate matter [PM2.5] and nitrogen dioxide [NO2]) at baseline and functional performance as measured by an extended Instrumental Activities of Daily living scale (IADL-x), adjusting for potential confounders. RESULTS:Participants were followed for a maximum of six study visits, with a median follow-up time of 4.28 years. Higher concentrations of pollutant exposures were associated with lower IADL-x scores at baseline and steeper rates of decline in IADL-x scores over time. In adjusted models, a one IQR increase in PM2.5 was associated with a 0.275 standard deviation SD (95 % CI: -0.356, -0.194) lower IADL-x score at baseline and an additional 0.031 SD (95% CI: -0.048, -0.013) decline per year of follow-up. A one IQR increase in NO2 was associated with a 0.133 SD (95 % CI: -0.180, -0.086) lower IADL-x score at baseline and an additional 0.035 SD (95% CI: -0.046, -0.024) decline per year of follow-up. CONCLUSIONS:These results contribute to the body of evidence on the deleterious effects of air pollution on healthy aging and point to opportunities for future research on potential pathways linking air pollution exposures to functional decline. KEYWORDS: air pollution, functional performance, aging.

Effects of exposure to surrounding green, air pollution and traffic noise with non-accidental and cause-specific mortality in the Dutch national cohort

BackgroundEveryday people are exposed to multiple environmental factors, such as surrounding green, air pollution and traffic noise. These exposures are generally spatially correlated. Hence, when estimating associations of surrounding green, air pollution or traffic noise with health outcomes, the other exposures should be taken into account. The aim of this study was to evaluate associations of long-term residential exposure to surrounding green, air pollution and traffic noise with mortality.MethodsWe followed approximately 10.5 million adults (aged ≥ 30 years) living in the Netherlands from 1 January 2013 until 31 December 2018. We used Cox proportional hazard models to evaluate associations of residential surrounding green (including the average Normalized Difference Vegetation Index (NDVI) in buffers of 300 and 1000 m), annual average ambient air pollutant concentrations [including particulate matter (PM2.5), nitrogen dioxide (NO2)] and traffic noise with non-accidental and cause-specific mortality, adjusting for potential confounders.ResultsIn single-exposure models, surrounding green was negatively associated with all mortality outcomes, while air pollution was positively associated with all outcomes. In two-exposure models, associations of surrounding green and air pollution attenuated but remained. For respiratory mortality, in a two-exposure model with NO2 and NDVI 300 m, the HR of NO2 was 1.040 (95%CI: 1.022, 1.059) per IQR increase (8.3 µg/m3) and the HR of NDVI 300 m was 0.964 (95%CI: 0.952, 0.976) per IQR increase (0.14). Road-traffic noise was positively associated with lung cancer mortality only, also after adjustment for air pollution or surrounding green.ConclusionsLower surrounding green and higher air pollution were associated with a higher risk of non-accidental and cause-specific mortality. Studies including only one of these correlated exposures may overestimate the associations with mortality of that exposure.

A novel meteorological method to classify wintertime cold-air pool events

Cold-air pools (CAPs) are common in mountain valleys throughout the world (e.g., western North America, Himalayas, Alps, etc.) during winter months. Weak surface winds, cold temperatures, high humidity, and snow cover presence are common characteristics of CAPs, and in populated areas there is an increase in air pollution concentrations. Previous methods for identifying CAP events and determining their strength often rely on a combination of, radiosonde data, air pollution concentrations, and/or surface meteorological datasets. Ambient air pollution concentrations vary by location based on the local emissions sources and continually change due to regulations and human activity patterns, therefore they are unreliable for consistent CAP quantification. Here, the bulk atmospheric stability is calculated as the valley heat deficit (VHD) using radiosonde data for 12 locations in the western U.S. over 16 winters. A new CAP classification method is developed and compared to three existing CAP classification methods. Results indicate that the new method agrees well with existing approaches but provides a more robust CAP classification because it is solely based on meteorology and not air quality. For all locations, 00Z (afternoon/early evening) radiosondes account for roughly 8–41% of all CAP occurrences (12Z and 00Z), independent of the method used. Meaning that the stable boundary layer persists throughout the daytime in these cases often leading to persistent CAP events (PCAP). While PCAP length varies across locations, they are a similar order of magnitude because synoptic conditions that span the entire western U.S. govern CAP onset and PCAP length. Additionally, several locations (e.g., Reno, Elko, Spokane, Riverton, and Grand Junction) release radiosondes from a site located at an elevation above the valley floor, often underestimating the bulk atmospheric stability by more than 30%. A method to incorporate surface station data in the bulk atmospheric stability calculation is given to reduce this underestimation.

The effects of indoor and outdoor air pollution on the prevalence of adults' respiratory diseases in four Chinese cities: a comparison between 2017-2018 and 1993-1996.

BackgroundOver the past decades, both ambient and household air pollution have changed in several aspects, including the emission sources and the concentrations of pollutants, in many Chinese cities. It is unknown whether these changes are associated with changes in health conditions, especially given changes in other factors due to rapid economic growth.MethodsTwo cross-sectional surveys were conducted in two periods spanning more than twenty years (1993–1996 vs. 2017–2018) in four Chinese cities of Chongqing, Wuhan, Lanzhou, and Guangzhou. Data were collected regarding adults’ respiratory disease, smoking status, education, occupation, and household characteristics. Ambient air pollution data were obtained for each study. We first used logistic regression models to construct the district-specific adjusted disease prevalences. In the second stage, first-difference regression models were employed to examine whether the change in respiratory diseases prevalences was associated with the change in outdoor air pollution and indoor air pollution surrogates.ResultsA total of 7,557 and 9,974 households were participating in Period 1 (1993–1996) and Period 2 (2017–2018), respectively. Compared to Period 1, we found substantial reductions in the ambient air pollution concentrations, and a suggestive improvement in cooking-related indoor air pollution in Period 2. We observed decreases in the district-specific covariate-adjusted prevalences of both asthma and chronic bronchitis among participants, with an average reduction of 3.6% (range: 0.0% to 24.3%). From Period 1 to Period 2, one percent decrease in the proportion of cooking with coal was associated with a 19.0% (95% CI, 0.96–37.04%) decrease in the prevalence of males’ chronic bronchitis and a 1.86% (0.69–3.04%) increase in the prevalence of females’ asthma. Little evidence was observed regarding the potential health benefits associated with the decreases in ambient air pollution levels.ConclusionsThe substantial reduction in household use of coal for cooking might be an important contributor to the decrease in adults’ respiratory disease prevalence from 1993–1996 to 2017–2019 in four Chinese cities. Changes in this indoor air pollution source, along with other risk factors for respiratory diseases, may have masked respiratory health benefits associated with reductions in outdoor air pollution levels.

Estimating monthly concentrations of ambient key air pollutants in Japan during 2010–2015 for a national-scale birth cohort

Exposure to ambient air pollution is associated with maternal and child health. Some air pollutants exhibit similar behavior in the atmosphere, and some interact with each other; thus, comprehensive assessments of individual air pollutants are required. In this study, we developed national-scale monthly models for six air pollutants (NO, NO2, SO2, O3, PM2.5, and suspended particulate matter (SPM)) to obtain accurate estimates of pollutant concentrations at 1 km × 1 km resolution from 2010 through 2015 for application to the Japan Environment and Children's Study (JECS), which is a large-scale birth cohort study. We developed our models in the land use regression framework using random forests in conjunction with kriging. We evaluated the model performance via 5-fold location-based cross-validation. We successfully predicted monthly NO (r2 = 0.65), NO2 (r2 = 0.84), O3 (r2 = 0.86), PM2.5 (r2 = 0.79), and SPM (r2 = 0.64) concentrations. For SO2, a satisfactory model could not be developed (r2 = 0.45) because of the low SO2 concentrations in Japan. The performance of our models is comparable to those reported in previous studies at similar temporal and spatial scales. The model predictions in conjunction with the JECS will reveal the critical windows of prenatal and infancy exposure to ambient air pollutants, thus contributing to the development of environmental policies on air pollution.

Short-term impact of ambient air pollution exposure on daily clinic visits for patients with urticaria in Kaohsiung, Taiwan

The aim of this study was to investigate associations between daily visit count for patients with urticaria (DVCPU) and short-term changes in ambient air pollutant concentrations. Information of DVCPU with an ICD-9 diagnostic code 708 in out-patient clinic visits was retrieved from the medical records of Kaohsiung Veterans General Hospital from January 1, 2014, to July 31, 2018, as a dependent variable. Ambient air pollutant data were retrieved from the Taiwan Air Quality Monitoring Network database including carbon monoxide (CO), ground-level ozone (O3), particulate matter (PM)10, PM2.5, nitrogen dioxide (NO2), and nitric oxide (NO). Independent variables included one-day weighted 75th percentile values of one kind of air pollutant, meteorological factors (temperature, humidity, wind speed, and rainfall), and weekdays in the same model. Multivariable Poisson regression was used for analysis. DVCPU was significantly positively associated with an increasing level of NO2 on the 1st–3rd lag days (relative risk (RR): 1.02~1.03) and O3 on the 1st and 3rd lag days (RR = 1.002). Men were associated with CO on the visit day and 1st–5th lag days (RR: 1.65~2.06) and PM10 on the 1st (RR = 1.002) and 3rd lag days (RR = 1.003). Women were associated with CO on the 3rd–4th lag days (RR = 1.4) and O3 on the 1st (RR = 1.003) and 5th (RR = 1.004) lag days. The non-elderly (age < 65 years) was associated with O3 on the 1st (RR = 1.003) and 3rd (RR = 1.002) lag days. The elderly (age ≥ 65 years) was associated with CO on the visit day, 1st, 3rd, and 5th lag days (RR: 1.94~4.67), PM2.5, and PM10 on the visit day (RR = 1.01). Ambient air pollutants exposure was an important risk factor for patients with urticaria seeking treatment on certain days among the visit day and lag days.

Development of a Health-Based Index to Identify the Association between Air Pollution and Health Effects in Mexico City

Health risks from air pollution continue to be a major concern for residents in Mexico City. These health burdens could be partially alleviated through individual avoidance behavior if accurate information regarding the daily health risks of multiple pollutants became available. A split sample approach was used in this study to create and validate a multi-pollutant, health-based air quality index. Poisson generalized linear models were used to assess the impacts of ambient air pollution (i.e., fine particulate matter (PM2.5), nitrogen dioxide (NO2), and ground-level ozone (O3)) on a total of 610,982 daily emergency department (ED) visits for respiratory disease obtained from 40 facilities in the metropolitan area of Mexico City from 2010 to 2015. Increased risk of respiratory ED visits was observed for interquartile increases in the 4-day average concentrations of PM2.5 (Risk Ratio (RR) 1.03, 95% CI 1.01–1.04), O3 (RR 1.03, 95% CI 1.01–1.05), and to a lesser extent NO2 (RR 1.01, 95% CI 0.99–1.02). An additive, multi-pollutant index was created using coefficients for these three pollutants. Positive associations of index values with daily respiratory ED visits was observed among children (ages 2–17) and adults (ages 18+). The use of previously unavailable daily health records enabled an assessment of short-term ambient air pollution concentrations on respiratory morbidity in Mexico City and the creation of a health-based air quality index, which is now currently in use in Mexico City.

SPATIAL DISTRIBUTED LAG DATA FUSION FOR ESTIMATING AMBIENT AIR POLLUTION.

We introduce spatial (DLfuse) and spatiotemporal (DLfuseST) distributed lag data fusion methods for predicting point-level ambient air pollution concentrations, using, as input, gridded average pollution estimates from a deterministic numerical air quality model. The methods incorporate predictive information from grid cells surrounding the prediction location of interest and are shown to collapse to existing downscaling approaches when this information adds no benefit. The spatial lagged parameters are allowed to vary spatially/spatiotemporally to accommodate the setting where surrounding geographic information is useful in one area/time but not in another. We apply the new methods to predict ambient concentrations of eight-hour maximum ozone and 24-hour average PM2.5 at unobserved spatial locations and times, and compare the predictions with those from several state-of-the-art data fusion approaches. Results show that DLfuse and DLfuseST often provide improved model fit and predictive accuracy when the lagged information is shown to be beneficial. Code to apply the methods is available in the R package DLfuse.

Sources of PM2.5-bound water soluble ions at EMEP’s Auchencorth Moss (UK) supersite revealed by 3D-Concentration Weighted Trajectory (CWT) model

The Concentration Weighted Trajectory (CWT) model is a well-known tool which combines the residence time (trajectory points) of air masses over specific regions with ambient concentrations of air pollutants, aiming to identify potential long range transport impacts. An upgraded 3D-version of CWT model (3D-CWT), investigating not only the geographical origin of the exogenous emissions but also the altitudinal layers in which the transport occurs, was developed and coupled with PM2.5-bound concentrations of water soluble ions (nss- SO4−2 (non-sea salt sulfates), NO3−, Cl−, NH4+, Na+, Mg+2, Ca+2 and K+) for the years 2017–2018, derived by the Auchencorth Moss supersite in Southeast Scotland, United Kingdom (UK). The 3D-CWT model was implemented in two distinct altitudinal layers above ground level (0 m ≤ Layer 1 < 1000 m, 1000 m ≤ Layer 2 < 2000 m), because few trajectory points exceeded the 2000 m limit. Transport of Secondary Inorganic Aerosols (SIA) from South – Southeast England were detected in both vertical layers, affecting SO4−2, NO3−, and NH4+ levels, whilst SIA intrusions from Northwest Europe were detected in Layer 2. Sea salt particle transport from North Atlantic and the North Sea, comprising Cl−, Na+ and Mg+2, were detected in both layers whilst K+ contributions from Southeast England were also detected in both layers, suggesting also impacts from biomass burning. Moreover particle transport of a crustal origin, marked by Ca+2 enhancement, mainly occurred in layer 1 and included soil/dust resuspension from areas around the station and infrequent dust intrusions from the Sahara desert.

Ambient air pollution and emergency department visits in Toronto, Canada

To investigate the acute impact of various air pollutants on various disease groups in the urban area of the city of Toronto, Canada. Statistical models were developed to estimate the relative risk of an emergency department visit associated with ambient air pollution concentration levels. These models were generated for 8 air pollutants (lagged from 0 to 14 days) and for 18 strata (based on sex, age group, and season). Twelve disease groups extracted from the International Classification of Diseases 10th Revision (ICD-10) were used as health classifications in the models. The qualitative results were collected in matrices composed of 18 rows (strata) and 15 columns (lags) for each air pollutant and the 12 health classifications. The matrix cells were assigned a value of 1 if the association was positively statistically significant; otherwise, they were assigned to a value of 0. The constructed matrices were totalized separately for each air pollutant. The resulting matrices show qualitative associations for grouped diseases, air pollutants, and their corresponding lagged concentrations and indicate the frequency of statistically significant positive associations. The results are presented in colour-gradient matrices with the number of associations for every combination of patient strata, pollutant, and lag in corresponding cells. The highest number of the associations was 8 (of 12 possible) obtained for the same day exposure to carbon monoxide, nitrogen dioxide, and days with elevated air quality health index (AQHI) values. For carbon monoxide, the number of the associations decreases with the increasing lags. For this air pollutant, there were almost no associations after 8 days of lag. In the case of nitrogen dioxide, the associations persist even for longer lags. The numerical values obtained from the models are provided for every pollutant. The constructed matrices are a useful tool to analyze the impact of ambient air pollution concentrations on public health.

Acute effects of short-term exposure to ambient air pollution on reproductive hormones in young males of the MARHCS study in China

Air pollution, which is associated with male reproductive health. However, it is unknown the acute effects of ambient air pollutants exposure on male reproductive hormones. The current study, we measured serum levels of reproductive hormone in 2030 blood samples gathered from The Male Reproductive Health in Chongqing College Students (MARHCS) cohort study. We derived a full coverage of ambient air pollutant (PM10, PM2.5, SO2, NO2, CO and O3) concentrations by employing machine learning algorithms, and used a mixed-effect model to estimate single-day and cumulative effects of air pollutants exposure on serum reproductive hormones. Our results showed that (1) PM10 and PM2.5 concentrations were positively associated with estradiol (E2) in both single and cumulative lag days, but were negatively associated with the ratio of Testosterone/E2 (the T/E2 ratio). NO2 was positively associated with estradiol at lag day 2 (95% CI: 0.290, 0.881; corrected P = 0.048) and lag 0–2 days (95% CI: 0.523, 1.337; corrected P = 0.003), with progesterone (P) at lag day 2 and lag day 3 (corrected P < 0.05). There was also a positive association between CO exposure and progesterone at lag day 2. (2) SO2 was inversely associated with E2 at lag day 3, 4 and lag 0–4 days, and progesterone at lag day 0, 1, 2 and lag 0–1, 0–2, 0–4 days, but positively associated with the T/E2 ratio at lag day 3, 4 and lag 0–4 days (corrected P < 0.05). O3 exposure was negatively associated with E2 at lag day 3 (95% CI: −0.216, −0.074, corrected P = 0.03). (3) No significant associations were found between the cumulative daily average air pollutant exposure of CO, O3 and hormone outcomes. This study suggests that short-term exposure to air pollutants may thus alter reproductive hormone levels, especially on serum estradiol, progesterone levels and the T/E2 ratio.

Air pollution and emergency department visits for urticaria

Abstract Introduction. This study investigates associations between air pollution and emergency department (ED) visits for urticaria in Toronto, Canada. Aim. To verify the hypothesis that urticaria are related to air pollution. Material and methods. The National Ambulatory Care Reporting System database is used to draw the daily ED visits. The L50 section of the International Classification of Disease 10th Revision is applied to extract ED visits whose primary causes was urticaria-related skin condition. Statistical models (condition Poisson regression) using daily counts of ED visits are constructed for urticaria (health response) with ambient air pollution concentrations and weather factors as independent variable. Two air quality health indexes and six ambient air pollutants: fine particulate matter PM2.5, O3, CO, NO2, SO2, and maximum 8-hour average ozone are considered as an exposure. Results. A total of 176 statistically significant (P-Value &lt;0.05) positive correlations were identified over the 15 day lag period (0-14 days). For daily average of ambient ozone, 74 positive correlations were observed with the following relative risks (RR) for a one interquartile range (IQR=12.8 ppb) increase: RR=1.361 (95% confidence interval: 1.302, 1.404), 1.359 (1.299, 1.401), 1.351 (1.281, 1.404) in the warm season (April-September), lag 0, and RR=1.019 (1.013, 1.025), 1.023 (1.016, 1.030), 1.014 (1.007, 1.021), lag 1, in the cold period (October-March), for all, females, and males, respectively. 10, 45 and 45 positive correlations were also obtained for sulfur dioxide, fine particulate matter, and daily maximum 8-hour average ozone concentrations, respectively. Conclusions. The results indicate that urban ambient air pollution could influence the numbers of ED visits for urticaria. Ambient ozone was determined as the main environmental factor contributing to these associations.