Comparisons of simple and complex methods for quantifying exposure to individual point source air pollution emissions.
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ABSTRACT:
SUBMITTER: Henneman LRF
PROVIDER: S-EPMC7494583 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Recent studies have sought epidemiological evidence of the effectiveness of energy transitions. Such evidence often relies on so-called "natural experiments," wherein environmental and/or health outcomes are assessed before, during, and after the transition of interest. Often, these studies attribute air pollution exposure changes-either modeled or measured-directly to the transition. We formalize a framework for separating the fractions of a given exposure change attributable to meteorological variability and emissions changes. Using this framework, we quantify relative impacts of wind variability and emissions changes from coal-fired power plants on exposure to SO2 emissions across the United States under three unique combinations of spatial-temporal and source scales. We find that the large emissions reductions achieved by United States coal-fired power plants after 2005 dominated population exposure changes. In each of the three case studies, however, we identified periods and regions in which meteorology dampened or accentuated differences in total exposure relative to exposure change expected from emissions reductions alone. The results evidence a need for separating meteorology-induced variability in exposure when attributing health impacts to specific energy transitions.
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Project description:BACKGROUND: Long-term exposures to particulate matter air pollution (PM2.5 and PM10) and high traffic load have been associated with markers of systemic inflammation. Epidemiological investigations have focused primarily on total PM, which represents a mixture of pollutants originating from different sources. OBJECTIVE: We investigated associations between source-specific PM and high-sensitive C-reactive protein (hs-CRP), an independent predictor of cardiovascular disease. METHODS: We used data from the first (2000-2003) and second examination (2006-2008) of the Heinz Nixdorf Recall study, a prospective population-based German cohort of initially 4,814 participants (45-75 years of age). We estimated residential long-term exposure to local traffic- and industry-specific fine particulate matter (PM2.5) at participants' residences using a chemistry transport model. We used a linear mixed model with a random participant intercept to estimate associations of source-specific PM and natural log-transformed hs-CRP, controlling for age, sex, education, body mass index, low- and high-density lipoprotein cholesterol, smoking variables, physical activity, season, humidity, and city (8,204 total observations). RESULTS: A 1-?g/m3 increase in total PM2.5 was associated with a 4.53% increase in hs-CRP concentration (95% CI: 2.76, 6.33%). hs-CRP was 17.89% (95% CI: 7.66, 29.09%) and 7.96% (95% CI: 3.45, 12.67%) higher in association with 1-?g/m3 increases in traffic- and industry-specific PM2.5, respectively. RESULTS for PM10 were similar. CONCLUSIONS: Long-term exposure to local traffic-specific PM (PM2.5, PM10) was more strongly associated with systemic inflammation than total PM. Associations of local industry-specific PM were slightly stronger but not significantly different from associations with total PM.
| S-EPMC4080540 | biostudies-literature
Project description:Exposure to ozone and fine particulate matter (PM2.5) can cause adverse health effects, including premature mortality due to cardiopulmonary diseases and lung cancer. Recent studies quantify global air pollution mortality but not the contribution of different emissions sectors, or they focus on a specific sector.We estimated the global mortality burden of anthropogenic ozone and PM2.5, and the impact of five emissions sectors, using a global chemical transport model at a finer horizontal resolution (0.67° × 0.5°) than previous studies.We performed simulations for 2005 using the Model for Ozone and Related Chemical Tracers, version 4 (MOZART-4), zeroing out all anthropogenic emissions and emissions from specific sectors (All Transportation, Land Transportation, Energy, Industry, and Residential and Commercial). We estimated premature mortality using a log-linear concentration-response function for ozone and an integrated exposure-response model for PM2.5.We estimated 2.23 (95% CI: 1.04, 3.33) million deaths/year related to anthropogenic PM2.5, with the highest mortality in East Asia (48%). The Residential and Commercial sector had the greatest impact globally-675 (95% CI: 428, 899) thousand deaths/year-and in most regions. Land Transportation dominated in North America (32% of total anthropogenic PM2.5 mortality), and it had nearly the same impact (24%) as Residential and Commercial (27%) in Europe. Anthropogenic ozone was associated with 493 (95% CI: 122, 989) thousand deaths/year, with the Land Transportation sector having the greatest impact globally (16%).The contributions of emissions sectors to ambient air pollution-related mortality differ among regions, suggesting region-specific air pollution control strategies. Global sector-specific actions targeting Land Transportation (ozone) and Residential and Commercial (PM2.5) sectors would particularly benefit human health. Citation: Silva RA, Adelman Z, Fry MM, West JJ. 2016. The impact of individual anthropogenic emissions sectors on the global burden of human mortality due to ambient air pollution. Environ Health Perspect 124:1776-1784;?http://dx.doi.org/10.1289/EHP177.
| S-EPMC5089880 | biostudies-other
Project description:Psychosocial and environmental stress exposures across the life course have been shown to be relevant in the development of cardiovascular disease (CVD). Assessing more than one stressor from different domains (e.g., individual and neighborhood) and across the life course moves us towards a more integrated picture of how stress affects health and well-being. Furthermore, these individual and neighborhood psychosocial stressors act on biologic pathways, including immune function and inflammatory response, which are also impacted by ubiquitous environmental exposures such as air pollution. The objective of this study is to evaluate the interaction between psychosocial stressors, at both the individual and neighborhood level, and air pollution on CVD. This study used data from the 2009-2011 Behavioral Risk Factor Surveillance System (BRFSS) from Washington State. Adverse childhood experiences (ACEs) measured at the individual level, and neighborhood deprivation index (NDI) measured at the zip code level, were the psychosocial stressors of interest. Exposures to three air pollutants-particulate matter (both PM2.5 and PM10) and nitrogen dioxide (NO?)-were also calculated at the zip code level. Outcome measures included several self-reported CVD-related health conditions. Both multiplicative and additive interaction quantified using the relative excess risk due to interaction (RERI), were evaluated. This study included 32,151 participants in 502 unique zip codes. Multiplicative and positive additive interactions were observed between ACEs and PM10 for diabetes, in models adjusted for NDI. The prevalence of diabetes was 1.58 (95% CI: 1.40, 1.79) times higher among those with both high ACEs and high PM10 compared to those with low ACEs and low PM10 (p-value = 0.04 for interaction on the multiplicative scale). Interaction was also observed between neighborhood-level stressors (NDI) and air pollution (NO?) for the stroke and diabetes outcomes on both multiplicative and additive scales. Modest interaction was observed between NDI and air pollution, supporting prior literature on the importance of neighborhood-level stressors in cardiovascular health and reinforcing the importance of NDI on air pollution health effects. ACEs may exert health effects through selection into disadvantaged neighborhoods and more work is needed to understand the accumulation of risk in multiple domains across the life course.
| S-EPMC5877017 | biostudies-literature
Project description:This study is the first of its kind to utilize longitudinal, nationally representative panel data from the United States to assess the relationship between exposure to air pollution and reports of psychological distress. Using annual-average measures of air pollution in respondents' census blocks of residence we find that over the period 1999-2011 particulate matter 2.5 is significantly associated with increased psychological distress; this association remains even after controlling for a robust set of demographic, socioeconomic, and health-related covariates. This study suggests that public health efforts to reduce the personal and societal costs of mental illness should consider addressing not only individual characteristics and factors in the social environment, but also underexplored facets of the physical environment such as air pollution.
| S-EPMC6023621 | biostudies-literature
Project description:Understanding the air pollution emission abatement potential and associated control cost is a prerequisite to design cost efficient control policies. In this study, a linear programming algorithm model, International Control Cost Estimate Tool, was updated with cost data for applications of 56 types of end-of-pipe technologies and five types of renewable energy in 10 major sectors namely power generation, industry combustion, cement production, iron and steel production, other industry processes, domestic combustion, transportation, solvent use, livestock rearing, and fertilizer use. The updated model was implemented to estimate the abatement potential and marginal cost of multiple pollutants in China. The total maximum abatement potentials of sulfur dioxide (SO2), nitrogen oxides (NOx), primary particulate matter (PM2.5), non-volatile organic compounds (NMVOCs), and ammonia (NH3) in China were estimated to be 19.2, 20.8, 9.1, 17.2 and 8.6 Mt, respectively, which accounted for 89.7%, 89.9%, 94.6%, 74.0%, and 80.2% of their total emissions in 2014, respectively. The associated control cost of such reductions was estimated as 92.5, 469.7, 75.7, 449.0, and 361.8 billion CNY in SO2, NOx, primary PM2.5, NMVOCs and NH3, respectively. Shandong, Jiangsu, Henan, Zhejiang, and Guangdong provinces exhibited large abatement potentials for all pollutants. Provincial disparity analysis shows that high GDP regions tend to have higher reduction potential and total abatement costs. End-of-pipe technologies tended be a cost-efficient way to control pollution in industries processes (i.e., cement plants, iron and steel plants, lime production, building ceramic production, glass and brick production), whereas such technologies were less cost-effective in fossil fuel-related sectors (i.e., power plants, industry combustion, domestic combustion, and transportation) compared with renewable energy. The abatement potentials and marginal abatement cost curves developed in this study can further be used as a crucial component in an integrated model to design optimized cost-efficient control policies.
| S-EPMC8336370 | biostudies-literature
Project description:Using daily fine particulate matter (PM2.5) composition data from the 2000-2005 U.S. EPA Chemical Speciation Network (CSN) for over 200 sites, we applied multivariate methods to identify and quantify the major fine particulate matter (PM2.5) source components in the U.S. Novel aspects of this work were: (1) the application of factor analysis (FA) to multi-city daily data, drawing upon both spatial and temporal variations of chemical species; and, (2) the exclusion of secondary components (sulfates, nitrates and organic carbon) from the source identification FA to more clearly discern and apportion the PM2.5 mass to primary emission source categories. For the quantification of source-related mass, we considered two approaches based upon the FA results: 1) using single key tracers for sources identified by FA in a mass regression; and, 2) applying Absolute Principal Component Analysis (APCA). In each case, we followed a two-stage mass regression approach, in which secondary components were first apportioned among the identified sources, and then mass was apportioned to the sources and to other secondary mass not explained by the individual sources. The major U.S. PM2.5 source categories identified via FA (and their key elements) were: Metals Industry (Pb, Zn); Crustal/Soil Particles (Ca, Si); Motor Vehicle Traffic (EC, NO2); Steel Industry (Fe, Mn); Coal Combustion (As, Se); Oil Combustion (V, Ni); Salt Particles (Na, Cl) and Biomass Burning (K). Nationwide spatial plots of the source-related PM2.5 impacts were confirmatory of the factor interpretations: ubiquitous sources, such as Traffic and Soil, were found to be spread across the nation, more unique sources (such as Steel and Metals Processing) being highest in select industrialized cities, Biomass Burning was highest in the U.S. Northwest, while Residual Oil combustion was highest in cities in the Northeastern U.S. and in cities with major seaports. The sum of these source contributions and the secondary PM2.5 components agreed well with the U.S. PM2.5 observed during the study period (mean=14.3 ug/m3; R2= 0.91). Apportionment regression analyses using single-element tracers for each source category gave results consistent with the APCA estimates. Comparisons of nearby sites indicated that the PM2.5 mass and the secondary aerosols were most homogenous spatially, while traffic PM2.5 and its tracer, EC, were among the most spatially representative of the source-related components. Comparison of apportionment results to a previous analysis of the 1979-1982 IP Network revealed similar and correlated major U.S. source category factors, albeit at lower levels than in the earlier period, suggesting a consistency in the U.S. spatial patterns of these source-related exposures over time, as well. These results indicate that applying source apportionment methods to the nationwide CSN can be an informative avenue for identifying and quantifying source components for the subsequent estimation of source-specific health effects, potentially contributing to more efficient regulation of PM2.5.
| S-EPMC3951912 | biostudies-literature
Project description:With increasing population, rapid urbanization, and increased migration to cities, the local impacts of increasing transportation and industrial-related air pollution are of growing concern worldwide. Elevated air pollution concentrations near these types of sources have been linked to adverse health effects including acute and chronic respiratory and cardiovascular diseases. Mobile monitoring has proven to be a useful technique to characterize spatial variability of air pollution in urban areas and pollution concentration gradients from specific sources. A study was conducted in the Kansas City, Kansas (USA) metropolitan area using mobile monitoring to characterize the spatial variability and gradients of air pollutants to identify the contribution of multiple sources on community-level air quality in a complex urban environment. Measurements focused on nitrogen dioxide (NO2), black carbon (BC), and ultrafine particulate matter (UFP). Mobile monitoring showed that median concentrations of these pollutants ranged by up to a factor of three between the communities, with individual measurements ranging over an order of magnitude within the community. Evaluating these air quality measurements with wind direction data highlighted the influence of specific and combinations of air pollution sources on these elevated concentrations, which can provide valuable information to environmental and public health officials in prioritizing and implementing cost-effect air quality management strategies to reduce exposures for urban populations.
| S-EPMC7882077 | biostudies-literature
Project description:BACKGROUND:Early-life exposure to traffic-related air pollution exacerbates childhood asthma, but it is unclear what role it plays in asthma development. METHODS:The association between exposure to primary mobile source pollutants during pregnancy and during infancy and asthma incidence by ages 2 through 6 was examined in the Kaiser Air Pollution and Pediatric Asthma Study, a racially diverse birth cohort of 24,608 children born between 2000 and 2010 and insured by Kaiser Permanente Georgia. We estimated concentrations of mobile source fine particulate matter (PM2.5, µg/m), nitrogen oxides (NOX, ppb), and carbon monoxide (CO, ppm) at the maternal and child residence using a Research LINE source dispersion model for near-surface releases. Asthma was defined using diagnoses and medication dispensings from medical records. We used binomial generalized linear regression to model the impact of exposure continuously and by quintiles on asthma risk. RESULTS:Controlling for covariates and modeling log-transformed exposure, a 2.7-fold increase in first year of life PM2.5 was associated with an absolute 4.1% (95% confidence interval, 1.6%, 6.6%) increase in risk of asthma by age 5. Quintile analysis showed an increase in risk from the first to second quintile, but similar risk across quintiles 2-5. Risk differences increased with follow-up age. Results were similar for NOX and CO and for exposure during pregnancy and the first year of life owing to high correlation. CONCLUSIONS:Results provide limited evidence for an association of early-life mobile source air pollution with childhood asthma incidence with a steeper concentration-response relationship observed at lower levels of exposure.
| S-EPMC5718963 | biostudies-literature
Project description:Independent estimates of fossil fuel CO2 (CO2ff) emissions are key to ensuring that emission reductions and regulations are effective and provide needed transparency and trust. Point source emissions are a key target because a small number of power plants represent a large portion of total global emissions. Currently, emission rates are known only from self-reported data. Atmospheric observations have the potential to meet the need for independent evaluation, but useful results from this method have been elusive, due to challenges in distinguishing CO2ff emissions from the large and varying CO2 background and in relating atmospheric observations to emission flux rates with high accuracy. Here we use time-integrated observations of the radiocarbon content of CO2 ((14)CO2) to quantify the recently added CO2ff mole fraction at surface sites surrounding a point source. We demonstrate that both fast-growing plant material (grass) and CO2 collected by absorption into sodium hydroxide solution provide excellent time-integrated records of atmospheric (14)CO2 These time-integrated samples allow us to evaluate emissions over a period of days to weeks with only a modest number of measurements. Applying the same time integration in an atmospheric transport model eliminates the need to resolve highly variable short-term turbulence. Together these techniques allow us to independently evaluate point source CO2ff emission rates from atmospheric observations with uncertainties of better than 10%. This uncertainty represents an improvement by a factor of 2 over current bottom-up inventory estimates and previous atmospheric observation estimates and allows reliable independent evaluation of emissions.
| S-EPMC5027441 | biostudies-literature