Simulation of population-based commuter exposure to NO2 using different air pollution models

We simulated commuter routes and long-term exposure to traffic-related air pollution during commute in a representative population sample in Basel (Switzerland), and evaluated three air pollution models with different spatial resolution for estimating commute exposures to nitrogen dioxide (NO2) as a marker of long-term exposure to traffic-related air pollution. Our approach includes spatially and temporally resolved data on actual commuter routes, travel modes and three air pollution models. Annual mean NO2 commuter exposures were similar between models. However, we found more within-city and within-subject variability in annual mean (±SD) NO2 commuter exposure with a high resolution dispersion model (40 ± 7 µg m−3, range: 21–61) than with a dispersion model with a lower resolution (39 ± 5 µg m−3; range: 24–51), and a land use regression model (41 ± 5 µg m−3; range: 24–54). Highest median cumulative exposures were calculated along motorized transport and bicycle routes, and the lowest for walking. For estimating commuter exposure within a city and being interested also in small-scale variability between roads, a model with a high resolution is recommended. For larger scale epidemiological health assessment studies, models with a coarser spatial resolution are likely sufficient, especially when study areas include suburban and rural areas

Estimates of CO2 from fires in the United States: implications for carbon management

<p>Abstract</p> <p>Background</p> <p>Fires emit significant amounts of CO₂to the atmosphere. These emissions, however, are highly variable in both space and time. Additionally, CO₂emissions estimates from fires are very uncertain. The combination of high spatial and temporal variability and substantial uncertainty associated with fire CO₂emissions can be problematic to efforts to develop remote sensing, monitoring, and inverse modeling techniques to quantify carbon fluxes at the continental scale. Policy and carbon management decisions based on atmospheric sampling/modeling techniques must account for the impact of fire CO₂emissions; a task that may prove very difficult for the foreseeable future. This paper addresses the variability of CO₂emissions from fires across the US, how these emissions compare to anthropogenic emissions of CO₂and Net Primary Productivity, and the potential implications for monitoring programs and policy development.</p> <p>Results</p> <p>Average annual CO₂emissions from fires in the lower 48 (LOWER48) states from 2002–2006 are estimated to be 213 (± 50 std. dev.) Tg CO₂yr^-1and 80 (± 89 std. dev.) Tg CO₂yr^-1in Alaska. These estimates have significant interannual and spatial variability. Needleleaf forests in the Southeastern US and the Western US are the dominant source regions for US fire CO₂emissions. Very high emission years typically coincide with droughts, and climatic variability is a major driver of the high interannual and spatial variation in fire emissions. The amount of CO₂emitted from fires in the US is equivalent to 4–6% of anthropogenic emissions at the continental scale and, at the state-level, fire emissions of CO₂can, in some cases, exceed annual emissions of CO₂from fossil fuel usage.</p> <p>Conclusion</p> <p>The CO₂released from fires, overall, is a small fraction of the estimated average annual Net Primary Productivity and, unlike fossil fuel CO₂emissions, the pulsed emissions of CO₂during fires are partially counterbalanced by uptake of CO₂by regrowing vegetation in the decades following fire. Changes in fire severity and frequency can, however, lead to net changes in atmospheric CO₂and the short-term impacts of fire emissions on monitoring, modeling, and carbon management policy are substantial.</p

The relevance of commuter and work/school exposure in an epidemiological study on traffic-related air pollution

Exposure during transport and at non-residential locations is ignored in most epidemiological studies of traffic-related air pollution. We investigated the impact of separately estimating NO2 long-term outdoor exposures at home, work/school, and while commuting on the association between this marker of exposure and potential health outcomes. We used spatially and temporally resolved commuter route data and model-based NO2 estimates of a population sample in Basel, Switzerland, to assign individual NO2-exposure estimates of increasing complexity, namely (1) home outdoor concentration; (2) time-weighted home and work/school concentrations; and (3) time-weighted concentration incorporating home, work/school and commute. On the basis of their covariance structure, we estimated the expectable relative differences in the regression slopes between a quantitative health outcome and our measures of individual NO2 exposure using a standard measurement error model. The traditional use of home outdoor NO2 alone indicated a 12% (95% Cl: 11-14%) underestimation of related health effects as compared with integrating both home and work/school outdoor concentrations. Mean contribution of commuting to total weekly exposure was small (3.2%; range 0.1-13.5%). Thus, ignoring commute in the total population may not significantly underestimate health effects as compared with the model combining home and work/school. For individuals commuting between Basel-City and Basel-Country, ignoring commute may produce, however, a significant attenuation bias of 4% (95% Cl: 4-5%). Our results illustrate the importance of including work/school locations in assessments of long-term exposures to traffic-related air pollutants such as NO2. Information on individuals' commuting behavior may further improve exposure estimates, especially for subjects having lengthy commutes along major transportation routes

Spatial and temporal variability of ultrafine particles, NO2, PM2.5, PM2.5 absorbance, PM10 and PMcoarse in Swiss study areas

Exposure to outdoor air pollutants remains an important concern in Europe, as limit values for NO2 and PM10 continue to be exceeded. Few studies have addressed the long-term spatial contrasts in PM2.5, PM absorbance, PM coarse coarse and especially ultrafine particles. This scarcity of data hampers the possibility to conduct epidemiological studies, assessing the health relevance of these markers of potentially harmful pollutants. Air pollution measurements were performed in eight geographically distinct areas of the Swiss Study on Air Pollution and Lung and Heart Diseases in Adults (SAPALDIA) in Switzerland. NO2 was measured in all eight areas at 40 sites per area, and PM2.5, PM2.5 absorbance, PM10 and ultrafine particles (particle number concentration (PNC) and lung deposited surface area (LDSA)) were measured in 4 of these areas, at a subset of 20 out of 40 sites. Each site was sampled three times during different seasons of the year, using the same equipment, sampling protocols and the same central facilities for analysis of samples. We assessed the spatial variability between areas and between individual sites, as well as pollution contrasts between the seasons and correlations between different pollutants. Within-area spatial contrasts (defined as the ratio between the 90th and 10th percentile) were highest for NO2 (3.14), moderate for PMcoarse (2.19), PNC (2.00) and PM2.5 absorbance (1.94), and lowest for LDSA (1.63), PM2.5 (1.50) and PM10 (1.46). Concentrations in the larger cities were generally higher than in smaller towns and rural and alpine areas, and were higher in the winter than in the summer and intermediate seasons, for all pollutants. Between-area differences accounted for more variation than within-area differences for all pollutants except NO2 and PMcoarse. Despite substantial within-area contrasts for PNC and LDSA, 74.7% and 83.3% of the spatial variance was attributed to between-area variability, respectively. Coefficients of determination between long-term adjusted pollutants were high (R-2>0.70) between NO2, PM2.5 absorbance, PNC and LDSA and between PM2.5 and PM10. The measurement of spatial patterns for this large range of outdoor air pollutants will contribute to a highly standardized estimation of individual long-term exposure levels for SAPALDIA cohort participants. (C) 2015 Elsevier Ltd. All rights reserved

Adult lung function and long-term air pollution exposure. ESCAPE: a multicentre cohort study and meta-analysis.

The chronic impact of ambient air pollutants on lung function in adults is not fully understood. The objective of this study was to investigate the association of long-term exposure to ambient air pollution with lung function in adult participants from five cohorts in the European Study of Cohorts for Air Pollution Effects (ESCAPE). Residential exposure to nitrogen oxides (NO2, NOx) and particulate matter (PM) was modelled and traffic indicators were assessed in a standardised manner. The spirometric parameters forced expiratory volume in 1 s (FEV1) and forced vital capacity (FVC) from 7613 subjects were considered as outcomes. Cohort-specific results were combined using meta-analysis. We did not observe an association of air pollution with longitudinal change in lung function, but we observed that a 10 μg·m-3 increase in NO2 exposure was associated with lower levels of FEV1 (-14.0 mL, 95%CI -25.8- -2.1) and FVC (-14.9 mL, 95% CI -28.7- -1.1). An increase of 10 μg·m-3 in PM10, but not other PM metrics (PM2.5, coarse fraction of PM, PM absorbance), was associated with a lower level of FEV1 (-44.6 mL, 95% CI -85.4- -3.8) and FVC (-59.0 mL, 95% CI -112.3- -5.6). The associations were particularly strong in obese persons. This study adds to the evidence for an adverse association of ambient air pollution with lung function in adults at very low levels in Europe

Arterial blood pressure and long-term exposure to traffic-related air pollution: an analysis in the European Study of Cohorts for Air Pollution Effects (ESCAPE).

BACKGROUND: Long-term exposure to air pollution has been hypothesized to elevate arterial blood pressure (BP). The existing evidence is scarce and country specific. OBJECTIVES: We investigated the cross-sectional association of long-term traffic-related air pollution with BP and prevalent hypertension in European populations. METHODS: We analyzed 15 population-based cohorts, participating in the European Study of Cohorts for Air Pollution Effects (ESCAPE). We modeled residential exposure to particulate matter and nitrogen oxides with land use regression using a uniform protocol. We assessed traffic exposure with traffic indicator variables. We analyzed systolic and diastolic BP in participants medicated and nonmedicated with BP-lowering medication (BPLM) separately, adjusting for personal and area-level risk factors and environmental noise. Prevalent hypertension was defined as ≥ 140 mmHg systolic BP, or ≥ 90 mmHg diastolic BP, or intake of BPLM. We combined cohort-specific results using random-effects meta-analysis. RESULTS: In the main meta-analysis of 113,926 participants, traffic load on major roads within 100 m of the residence was associated with increased systolic and diastolic BP in nonmedicated participants [0.35 mmHg (95% CI: 0.02, 0.68) and 0.22 mmHg (95% CI: 0.04, 0.40) per 4,000,000 vehicles × m/day, respectively]. The estimated odds ratio (OR) for prevalent hypertension was 1.05 (95% CI: 0.99, 1.11) per 4,000,000 vehicles × m/day. Modeled air pollutants and BP were not clearly associated. CONCLUSIONS: In this first comprehensive meta-analysis of European population-based cohorts, we observed a weak positive association of high residential traffic exposure with BP in nonmedicated participants, and an elevated OR for prevalent hypertension. The relationship of modeled air pollutants with BP was inconsistent

Arterial blood pressure and long-term exposure to traffic-related air pollution: an analysis in the European study of cohorts for air pollution effects (ESCAPE)

Background: Long-term exposure to air pollution has been hypothesized to elevate arterial blood pressure (BP). The existing evidence is scarce and country specific. Objectives: We investigated the cross-sectional association of long-term traffic-related air pollution with BP and prevalent hypertension in European populations. Methods: We analyzed 15 population-based cohorts, participating in the European Study of Cohorts for Air Pollution Effects (ESCAPE). We modeled residential exposure to particulate matter and nitrogen oxides with land use regression using a uniform protocol. We assessed traffic exposure with traffic indicator variables. We analyzed systolic and diastolic BP in participants medicated and nonmedicated with BP-lowering medication (BPLM) separately, adjusting for personal and area-level risk factors and environmental noise. Prevalent hypertension was defined as ≥ 140 mmHg systolic BP, or ≥ 90 mmHg diastolic BP, or intake of BPLM. We combined cohort-specific results using random-effects meta-analysis. Results: In the main meta-analysis of 113,926 participants, traffic load on major roads within 100 m of the residence was associated with increased systolic and diastolic BP in nonmedicated participants [0.35 mmHg (95% CI: 0.02, 0.68) and 0.22 mmHg (95% CI: 0.04, 0.40) per 4,000,000 vehicles × m/day, respectively]. The estimated odds ratio (OR) for prevalent hypertension was 1.05 (95% CI: 0.99, 1.11) per 4,000,000 vehicles × m/day. Modeled air pollutants and BP were not clearly associated. Conclusions: In this first comprehensive meta-analysis of European population-based cohorts, we observed a weak positive association of high residential traffic exposure with BP in nonmedicated participants, and an elevated OR for prevalent hypertension. The relationship of modeled air pollutants with BP was inconsistent