Air pollution and visitation at U.S. national parks.
Ontology highlight
ABSTRACT:
SUBMITTER: Keiser D
PROVIDER: S-EPMC6051738 | biostudies-literature | 2018 Jul
REPOSITORIES: biostudies-literature
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Project description:Seasonal snowpack, lichens, and lake sediment cores were collected from fourteen lake catchments in eight western U.S. National Parks and analyzed for sixteen polycyclic aromatic hydrocarbons (PAHs) to determine their current and historical deposition, as well as to identify their potential sources. Seasonal snowpack was measured to determine the current wintertime atmospheric PAH deposition; lichens were measured to determine the long-term, year around deposition; and the temporal PAH deposition trends were reconstructed using lake sediment cores dated using (210)Pb and (137)Cs. The fourteen remote lake catchments ranged from low-latitude catchments (36.6 degrees N) at high elevation (2900 masl) in Sequoia National Park, CA to high-latitude catchments (68.4 degrees N) at low elevation (427 masl) in the Alaskan Arctic. Over 75% of the catchments demonstrated statistically significant temporal trends in SigmaPAH sediment flux, depending on catchment proximity to source regions and topographic barriers. The SigmaPAH concentrations and fluxes in seasonal snowpack, lichens, and surficial sediment were 3.6 to 60,000 times greater in the Snyder Lake catchment of Glacier National Park than the other 13 lake catchments. The PAH ratios measured in snow, lichen, and sediment were used to identify a local aluminum smelter as a major source of PAHs to the Snyder Lake catchment. These results suggest that topographic barriers influence the atmospheric transport and deposition of PAHs in high-elevation ecosystems and that PAH sources to these national park ecosystems range from local point sources to diffuse regional and global sources.
| S-EPMC2898559 | biostudies-literature
Project description:Climate change will affect not only natural and cultural resources within protected areas but also tourism and visitation patterns. The U.S. National Park Service systematically collects data regarding its 270+ million annual recreation visits, and therefore provides an opportunity to examine how human visitation may respond to climate change from the tropics to the polar regions. To assess the relationship between climate and park visitation, we evaluated historical monthly mean air temperature and visitation data (1979-2013) at 340 parks and projected potential future visitation (2041-2060) based on two warming-climate scenarios and two visitation-growth scenarios. For the entire park system a third-order polynomial temperature model explained 69% of the variation in historical visitation trends. Visitation generally increased with increasing average monthly temperature, but decreased strongly with temperatures > 25°C. Linear to polynomial monthly temperature models also explained historical visitation at individual parks (R2 0.12-0.99, mean = 0.79, median = 0.87). Future visitation at almost all parks (95%) may change based on historical temperature, historical visitation, and future temperature projections. Warming-mediated increases in potential visitation are projected for most months in most parks (67-77% of months; range across future scenarios), resulting in future increases in total annual visits across the park system (8-23%) and expansion of the visitation season at individual parks (13-31 days). Although very warm months at some parks may see decreases in future visitation, this potential change represents a relatively small proportion of visitation across the national park system. A changing climate is likely to have cascading and complex effects on protected area visitation, management, and local economies. Results suggest that protected areas and neighboring communities that develop adaptation strategies for these changes may be able to both capitalize on opportunities and minimize detriment related to changing visitation.
| S-EPMC4470629 | biostudies-literature
Project description:Fifty-six seasonal snowpack samples were collected at remote alpine, subarctic, and arctic sites in eight Western U.S. national parks during three consecutive years (2003-2005). Four current-use pesticides (CUPs) (dacthal (DCPA), chlorpyrifos, endosulfans, and gamma-hexachlorocyclohexane (HCH)) and four historic-use pesticides (HUPs) (dieldrin, alpha-HCH, chlordanes, and hexachlorobenzene (HCB)) were commonly measured at all sites, during all years. The mean coefficient of variation for pesticide concentrations was 15% for site replicate samples, 41% for intrapark replicate samples, and 59% for interannual replicate samples. The relative pesticide concentration profiles were consistent from year to year but unique for individual parks, indicating a regional source effect. HUP concentrations were well-correlated with regional cropland intensity when the effect of temperature on snow-air partitioning was considered. The mass of individual CUPs used in regions located one-day upwind of the parks was calculated using air mass back trajectories, and this was used to explain the distribution of CUPs among the parks. The percent of the snowpack pesticide concentration due to regional transport was high (>75%) for the majority of pesticides in all parks. These results suggest that the majority of pesticide contamination in U.S. national parks is due to regional pesticide use in North America.
| S-EPMC2919226 | biostudies-other
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:BackgroundLimited evidence links air pollution exposure to chronic cough and sputum production. Few reports have investigated the association between long-term exposure to air pollution and classically defined chronic bronchitis.ObjectivesOur objective was to estimate the association between long-term exposure to particulate matter (diameter <10??m, PM10; <2.5?m, PM2.5), nitrogen dioxide (NO2), and both incident and prevalent chronic bronchitis.MethodsWe estimated annual average PM2.5, PM10, and NO2 concentrations using a national land-use regression model with spatial smoothing at home addresses of participants in a prospective nationwide U.S. cohort study of sisters of women with breast cancer. Incident chronic bronchitis and prevalent chronic bronchitis, cough and phlegm, were assessed by questionnaires.ResultsAmong 47,357 individuals with complete data, 1,383 had prevalent chronic bronchitis at baseline, and 647 incident cases occurred over 5.7-y average follow-up. No associations with incident chronic bronchitis were observed. Prevalent chronic bronchitis was associated with PM10 [adjusted odds ratio (aOR) per interquartile range (IQR) difference (5.8??g/m3)=1.07; 95% confidence interval (CI): 1.01, 1.13]. In never-smokers, PM2.5 was associated with prevalent chronic bronchitis (aOR=1.18 per IQR difference; 95% CI: 1.04, 1.34), and NO2 was associated with prevalent chronic bronchitis (aOR=1.10; 95%?CI=1.01,?1.20), cough (aOR=1.10; 95% CI: 1.05, 1.16), and phlegm (aOR=1.07; 95% CI: 1.01, 1.14); interaction p-values (nonsmokers vs. smokers) <0.05.ConclusionsPM10 exposure was related to chronic bronchitis prevalence. Among never-smokers, PM2.5 and NO2 exposure was associated with chronic bronchitis and component symptoms. Results may have policy ramifications for PM10 regulation by providing evidence for respiratory health effects related to long-term PM10 exposure. https://doi.org/10.1289/EHP2199.
| S-EPMC6066337 | biostudies-literature
Project description:In the last decade, a number of quantitative epidemiological studies of specific diseases have been done in developing countries that for the first time allow estimation of the total burden of disease (mortality and morbidity) attributable to use of solid fuels in adult women and young children, who jointly receive the highest exposures because of their household roles. Few such studies are available as yet for adult men or children over 5 years. This paper evaluates the existing epidemiological studies and applies the resulting risks to the more than three-quarters of all Indian households dependent on such fuels. Allowance is made for the existence of improved stoves with chimneys and other factors that may lower exposures. Attributable risks are calculated in reference to the demographic conditions and patterns of each disease in India. Sufficient evidence is available to estimate risks most confidently for acute respiratory infections (ARI), chronic obstructive pulmonary disease (COPD), and lung cancer. Estimates for tuberculosis (TB), asthma, and blindness are of intermediate confidence. Estimates for heart disease have the lowest confidence. Insufficient quantitative evidence is currently available to estimate the impact of adverse pregnancy outcomes (e.g., low birthweight and stillbirth). The resulting conservative estimates indicate that some 400-550 thousand premature deaths can be attributed annually to use of biomass fuels in these population groups. Using a disability-adjusted lost life-year approach, the total is 4-6% of the Indian national burden of disease, placing indoor air pollution as a major risk factor in the country.
| S-EPMC27217 | biostudies-literature
Project description:As our results suggested that metformin acts to limit mitochondrial ROS and calcium-mediated activation of IL-6, we reasoned it would likely affect other processes in alveolar macrophages triggered by exposure to particulate matter (PM). Therefore, we treated mice with metformin in the drinking water for 24 hours before we instilled PM intratracheally. We then flow-sorted alveolar macrophages from whole lung homogenates 24 hours later for transcriptomic analysis (RNA-Seq).
2018-10-05 | GSE98731 | GEO
Project description:BackgroundPopulation exposure assessment methods that capture local-scale pollutant variability are needed for large-scale epidemiological studies and surveillance, policy, and regulatory purposes. Currently, such exposure methods are limited.MethodsWe created 2006 national pollutant models for fine particulate matter [PM with aerodynamic diameter ? 2.5 ?m (PM2.5)], nitrogen dioxide (NO2), benzene, ethylbenzene, and 1,3-butadiene from routinely collected fixed-site monitoring data in Canada. In multiple regression models, we incorporated satellite estimates and geographic predictor variables to capture background and regional pollutant variation and used deterministic gradients to capture local-scale variation. The national NO2 and benzene models are evaluated with independent measurements from previous land use regression models that were conducted in seven Canadian cities. National models are applied to census block-face points, each of which represents the location of approximately 89 individuals, to produce estimates of population exposure.ResultsThe national NO2 model explained 73% of the variability in fixed-site monitor concentrations, PM2.5 46%, benzene 62%, ethylbenzene 67%, and 1,3-butadiene 68%. The NO2 model predicted, on average, 43% of the within-city variability in the independent NO2 data compared with 18% when using inverse distance weighting of fixed-site monitoring data. Benzene models performed poorly in predicting within-city benzene variability. Based on our national models, we estimated Canadian ambient annual average population-weighted exposures (in micrograms per cubic meter) of 8.39 for PM2.5, 23.37 for NO2, 1.04 for benzene, 0.63 for ethylbenzene, and 0.09 for 1,3-butadiene.ConclusionsThe national pollutant models created here improve exposure assessment compared with traditional monitor-based approaches by capturing both regional and local-scale pollution variation. Applying national models to routinely collected population location data can extend land use modeling techniques to population exposure assessment and to informing surveillance, policy, and regulation.
| S-EPMC3237350 | biostudies-literature
Project description:Exposure to fine particulate matter (PM2.5) from fuel combustion significantly contributes to global and US mortality. Traditional control strategies typically reduce emissions for specific air pollutants and sectors to maintain pollutant concentrations below standards. Here we directly set national PM2.5 mortality cost reduction targets within a global human-earth system model with US state-level energy systems, in scenarios to 2050, to identify endogenously the control actions, sectors, and locations that most cost-effectively reduce PM2.5 mortality. We show that substantial health benefits can be cost-effectively achieved by electrifying sources with high primary PM2.5 emission intensities, including industrial coal, building biomass, and industrial liquids. More stringent PM2.5 reduction targets expedite the phaseout of high emission intensity sources, leading to larger declines in major pollutant emissions, but very limited co-benefits in reducing CO2 emissions. Control strategies limiting health damages achieve the greatest emission reductions in the East North Central and Middle Atlantic states.
| S-EPMC7031358 | biostudies-literature
Project description:The concentrations of trace elements in feather moss Pleurozium schreberi (Brid.) Mitt. were used to indicate the relative levels of air pollution by trace elements in Polish national parks. Pleurozium schreberi was collected from nine national parks. The highest concentrations were recorded in the moss samples from the southern and most industrialised part of the country; the lowest from northern and north-eastern Poland. A comparison of data obtained from Polish national parks in the 1970s and 1990s showed a significant decrease in the concentrations of heavy metals. In the linear covariability estimation, the t quantile approach was used for multi-element comparison. A number of positive covariabilities were observed. This is a result of anthropogenic activity and the geochemical characteristics of the local environment, including crust composition to which soil composition is related. The statistical approach of t quantile to study common relationships between element concentrations can be used in the interpretation of biomonitoring research results in similar studies.
| S-EPMC7578132 | biostudies-literature