Optimal estimation for global ground-level fine particulate matter concentrations

We develop an optimal estimation (OE) algorithm based on top-of-atmosphere reflectances observed by the MODIS satellite instrument to retrieve near-surface fine particulatematter (PM2.5). The GEOS-Chem chemical transport model is used to provide prior information for the Aerosol Optical Depth (AOD) retrieval and to relate total column AOD to PM2.5. We adjust the shape of the GEOS-Chem relative vertical extinction profiles by comparison with lidar retrievals from the CALIOP satellite instrument. Surface reflectance relationships used in the OE algorithm are indexed by land type. Error quantities needed for this OE algorithm are inferred by comparison with AOD observations taken by a worldwide network of sun photometers (AERONET) and extended globally based upon aerosol speciation and cross correlation for simulated values, and upon land type for observational values. Significant agreement in PM2.5 is found over North America for 2005 (slope = 0.89; r = 0.82; 1-σ error = 1 μg/m3 + 27%), with improved coverage and correlation relative to previous work for the same region and time period, although certain subregions, such as the San Joaquin Valley of California are better represented by previous estimates. Independently derived error estimates of the OE PM2.5 values at in situ locations over North America (of ±(2.5 μg/m3 + 31%) and Europe of ±(3.5 μg/m3 + 30%) are corroborated by comparison with in situ observations, although globally (error estimates of (3.0 μg/m3 + 35%), may be underestimated. Global population-weighted PM2.5 at 50% relative humidity is estimated as 27.8 μg/m3 at 0.1° × 0.1° resolution

Improved estimate of the policy-relevant background ozone in the United States using the GEOS-Chem global model with 1/2° × 2/3° horizontal resolution over North America

The policy-relevant background (PRB) ozone is defined by the US Environmental Protection Agency (EPA) as the surface ozone concentration that would be present over the US in the absence of North American anthropogenic emissions. It is intended to provide a baseline for risk and exposure assessments used in setting the National Ambient Air Quality Standard (NAAQS). We present here three-year statistics (2006–2008) of PRB ozone over the US calculated using the GEOS-Chem global 3-D model of atmospheric composition with 1/2° × 2/3° horizontal resolution over North America and adjacent oceans (2° × 2.5° for the rest of the world). We also provide estimates of the US background (no anthropogenic US emissions) and natural background (no anthropogenic emissions worldwide and pre-industrial methane). Our work improves on previous GEOS-Chem PRB estimates through the use of higher model resolution, 3-year statistics, better representation of stratospheric influence, and updated emissions. PRB is particularly high in the intermountain West due to high elevation, arid terrain, and large-scale subsidence. We present for this region a detailed model evaluation showing that the model is successful in reproducing ozone exceedances up to 70 ppbv. However, the model cannot reproduce PRB-relevant exceptional events associated with wildfires or stratospheric intrusions. The mean PRB estimates for spring–summer are 27 ± 8 ppbv at low-altitude sites and 40 ± 7 ppbv at high-altitude sites. Differences between the PRB simulation and the natural simulation indicate a mean enhancement from intercontinental pollution and anthropogenic methane of 9 ppbv at low-altitude sites and 13 ppbv at high-altitude sites. The PRB is higher than average when ozone exceeds 60 ppbv, particularly in the intermountain West. Our PRB estimates are on average 4 ppbv higher than previous GEOS-Chem studies and we attribute this to higher lighting, increasing Asian emissions, and improved model resolution. Whereas previous studies found no occurrences of PRB exceeding 60 ppbv, we find here some occurrences in the intermountain West. The annual 4th-highest PRB values in the intermountain West are typically 50–60 ppbv, as compared to 35–45 ppbv in the East or on the West Coast. Such high PRB values in the intermountain West suggest that special consideration of this region may be needed if the ozone NAAQS is decreased to a value in the 60–70 ppbv range.Earth and Planetary SciencesEngineering and Applied Science

Spatiotemporal Variations in Ambient Ultrafine Particles and the Incidence of Childhood Asthma.

Rationale: Little is known regarding the impact of ambient ultrafine particles (UFPs; <0.1 μm) on childhood asthma development. Objectives: To examine the association between prenatal and early postnatal life exposure to UFPs and development of childhood asthma. Methods: A total of 160,641 singleton live births occurring in the City of Toronto, Canada between April 1, 2006, and March 31, 2012, were identified from a birth registry. Associations between exposure to ambient air pollutants and childhood asthma incidence (up to age 6) were estimated using random effects Cox proportional hazards models, adjusting for personal- and neighborhood-level covariates. We investigated both single-pollutant and multipollutant models accounting for coexposures to particulate matter ≤2.5 μm in aerodynamic diameter (PM2.5) and NO2. Measurements and Main Results: We identified 27,062 children with incident asthma diagnosis during the follow-up. In adjusted models, second-trimester exposure to UFPs (hazard ratio per interquartile range increase, 1.09; 95% confidence interval, 1.06-1.12) was associated with asthma incidence. In models additionally adjusted for PM2.5 and nitrogen dioxide, UFPs exposure during the second trimester of pregnancy remained positively associated with childhood asthma incidence (hazard ratio per interquartile range increase, 1.05; 95% confidence interval, 1.01-1.09). Conclusions: This is the first study to evaluate the association between perinatal exposure to UFPs and the incidence of childhood asthma. Exposure to UFPs during a critical period of lung development was linked to the onset of asthma in children, independent of PM2.5 and NO2

A Hybrid Approach to Estimating National Scale Spatiotemporal Variability of PM 2.5 in the Contiguous United States

Airborne fine particulate matter exhibits spatiotemporal variability at multiple scales, which presents challenges to estimating exposures for health effects assessment. Here we created an model to predict ambient particulate matter less than 2.5 microns in aerodynamic diameter (PM2.5) across the contiguous United States to be applied to health effects modeling. We developed a hybrid approach combining a land use regression model (LUR) selected with a machine learning method, and Bayesian Maximum Entropy (BME) interpolation of the LUR space-time residuals. The PM2.5 dataset included 104,172 monthly observations at 1,464 monitoring locations with approximately 10% of locations reserved for cross-validation. LUR models were based on remote sensing estimates of PM2.5, land use and traffic indicators. Normalized cross-validated R2 values for LUR were 0.63 and 0.11 with and without remote sensing, respectively, suggesting remote sensing is a strong predictor of ground-level concentrations. In the models including the BME interpolation of the residuals, cross-validated R2 were 0.79 for both configurations; the model without remotely sensed data described more fine-scale variation than the model including remote sensing. Our results suggest that our modeling framework can predict ground-level concentrations of PM2.5 at multiple scales over the contiguous U.S

A national study of the association between traffic-related air pollution and adverse pregnancy outcomes in Canada, 1999–2008

AbstractNumerous studies have examined the association of air pollution with preterm birth and birth weight outcomes. Traffic-related air pollution has also increasingly been identified as an important contributor to adverse health effects of air pollution. We employed a national nitrogen dioxide (NO2) exposure model to examine the association between NO2 and pregnancy outcomes in Canada between 1999 and 2008. National models for NO2 (and particulate matter of median aerodynamic diameter <2.5µm (PM2.5) as a covariate) were developed using ground-based monitoring data, estimates from remote-sensing, land use variables and, for NO2, deterministic gradients relative to road traffic sources. Generalized estimating equations were used to examine associations with preterm birth, term low birth weight (LBW), small for gestational age (SGA) and term birth weight, adjusting for covariates including infant sex, gestational age, maternal age and marital status, parity, urban/rural place of residence, maternal place of birth, season, year of birth and neighbourhood socioeconomic status and per cent visible minority. Associations were reduced considerably after adjustment for individual covariates and neighbourhood per cent visible minority, but remained significant for SGA (odds ratio 1.04, 95%CI 1.02–1.06 per 20ppb NO2) and term birth weight (16.2g reduction, 95% CI 13.6–18.8g per 20ppb NO2). Associations with NO2 were of greater magnitude in a sensitivity analysis using monthly monitoring data, and among births to mothers born in Canada, and in neighbourhoods with higher incomes and a lower proportion of visible minorities. In two pollutant models, associations with NO2 were less sensitive to adjustment for PM2.5 than vice versa, and there was consistent evidence of a dose-response relationship for NO2 but not PM2.5. In this study of approximately 2.5 million Canadian births between 1999 and 2008, we found significant associations of NO2 with SGA and term birth weight which remained significant after adjustment for PM2.5, suggesting that traffic may be a particularly important source with respect to the role of air pollution as a risk factor for adverse pregnancy outcomes

Ambient air pollution and the prevalence of rhinoconjunctivitis in adolescents: A worldwide ecological analysis

Whether exposure to outdoor air pollution increases the prevalence of rhinoconjunctivitis in children is unclear. Using data from Phase Three of the International Study of Asthma and Allergies in childhood (ISAAC), we investigated associations of rhinoconjunctivitis prevalence in adolescents with model-based estimates of ozone, and satellite-based estimates of fine (diameter < 2.5 μm) particulate matter (PM2.5) and nitrogen dioxide (NO2). Information on rhinoconjunctivitis (defined as self-reported nose symptoms without a cold or flu accompanied by itchy watery eyes in the past 12 months) was available on 505,400 children aged 13–14 years, in 183 centres in 83 countries. Centre-level prevalence estimates were calculated and linked geographically with estimates of long-term average concentrations of NO2, ozone and PM2.5. Multi-level models were fitted adjusting for population density, climate, sex and gross national income. Information on parental smoking, truck traffic and cooking fuel was available for a restricted set of centres (77 in 36 countries). Between centres within countries, the estimated change in rhinoconjunctivitis prevalence per 100 children was 0.171 (95% confidence interval: − 0.013, 0.354) per 10% increase in PM2.5, 0.096 (− 0.003, 0.195) per 10% increase in NO2 and − 0.186 (− 0.390, 0.018) per 1 ppbV increase in ozone. Between countries, rhinoconjunctivitis prevalence was significantly negatively associated with both ozone and PM2.5. In the restricted dataset, the latter association became less negative following adjustment for parental smoking and open fires for cooking. In conclusion, there were no significant within-country associations of rhinoconjunctivitis prevalence with study pollutants. Negative between-country associations with PM2.5 and ozone require further investigation

Complex relationships between greenness, air pollution, and mortality in a population-based Canadian cohort

Background: Epidemiological studies have consistently demonstrated that exposure to fine particulate matter (PM 2.5 )is associated with increased risks of mortality. To a lesser extent, a series of studies suggest that living in greener areas is associated with reduced risks of mortality. Only a handful of studies have examined the interplay between PM 2.5 , greenness, and mortality. Methods: We investigated the role of residential greenness in modifying associations between long-term exposures to PM 2.5 and non-accidental and cardiovascular mortality in a national cohort of non-immigrant Canadian adults (i.e., the 2001 Canadian Census Health and Environment Cohort). Specifically, we examined associations between satellite-derived estimates of PM 2.5 exposure and mortality across quintiles of greenness measured within 500 m of individual's place of residence during 11 years of follow-up. We adjusted our survival models for many personal and contextual measures of socioeconomic position, and residential mobility data allowed us to characterize annual changes in exposures. Results: Our cohort included approximately 2.4 million individuals at baseline, 194,270 of whom died from non-accidental causes during follow-up. Adjustment for greenness attenuated the association between PM 2.5 and mortality (e.g., hazard ratios (HRs)and 95% confidence intervals (CIs)per interquartile range increase in PM 2.5 in models for non-accidental mortality decreased from 1.065 (95% CI: 1.056–1.075)to 1.041 (95% CI: 1.031–1.050)). The strength of observed associations between PM 2.5 and mortality decreased as greenness increased. This pattern persisted in models restricted to urban residents, in models that considered the combined oxidant capacity of ozone and nitrogen dioxide, and within neighbourhoods characterised by high or low deprivation. We found no increased risk of mortality associated with PM 2.5 among those living in the greenest areas. For example, the HR for cardiovascular mortality among individuals in the least green areas was 1.17 (95% CI: 1.12–1.23)compared to 1.01 (95% CI: 0.97–1.06)among those in the greenest areas. Conclusions: Studies that do not account for greenness may overstate the air pollution impacts on mortality. Residents in deprived neighbourhoods with high greenness benefitted by having more attenuated associations between PM 2.5 and mortality than those living in deprived areas with less greenness. The findings from this study extend our understanding of how living in greener areas may lead to improved health outcomes

Comparison of multiple PM2.5 exposure products for estimating health benefits of emission controls over New York State, USA

Ambient exposure to fine particulate matter (PM2.5) is one of the top global health concerns. We estimate the PM2.5-related health benefits of emission reduction over New York State (NYS) from 2002 to 2012 using seven publicly available PM2.5 products that include information from ground-based observations, remote sensing and chemical transport models. While these PM2.5 products differ in spatial patterns, they show consistent decreases in PM2.5 by 28%–37% from 2002 to 2012. We evaluate these products using two sets of independent ground-based observations from the New York City Community Air Quality Survey (NYCCAS) Program for an urban area, and the Saint Regis Mohawk Tribe Air Quality Program for a remote area. Inclusion of satellite remote sensing improves the representativeness of surface PM2.5 in the remote area. Of the satellite-based products, only the statistical land use regression approach captures some of the spatial variability across New York City measured by NYCCAS. We estimate the PM2.5-related mortality burden by applying an integrated exposure-response function to the different PM2.5 products. The multi-product mean PM2.5-related mortality burden over NYS decreased by 5660 deaths (67%) from 8410 (95% confidence interval (CI): 4570–12 400) deaths in 2002 to 2750 (CI: 700–5790) deaths in 2012. We estimate a 28% uncertainty in the state-level PM2.5 mortality burden due to the choice of PM2.5 products, but such uncertainty is much smaller than the uncertainty (130%) associated with the exposure-response function