Predicting Chronic Fine and Coarse Particulate Exposures Using Spatiotemporal Models for the Northeastern and Midwestern United States

Background: Chronic epidemiologic studies of particulate matter (PM) are limited by the lack of monitoring data, relying instead on citywide ambient concentrations to estimate exposures. This method ignores within-city spatial gradients and restricts studies to areas with nearby monitoring data. This lack of data is particularly restrictive for fine particles (PM with aerodynamic diameter < 2.5 μm; PM2.5) and coarse particles (PM with aerodynamic diameter 2.5–10 μm; PM10–2.5), for which monitoring is limited before 1999. To address these limitations, we developed spatiotemporal models to predict monthly outdoor PM2.5 and PM10–2.5 concentrations for the northeastern and midwestern United States. Methods: For PM2.5, we developed models for two periods: 1988–1998 and 1999–2002. Both models included smooth spatial and regression terms of geographic information system-based and meteorologic predictors. To compensate for sparse monitoring data, the pre-1999 model also included predicted PM10 (PM with aerodynamic diameter < 10 μm) and extinction coefficients (km−1). PM10–2.5 levels were estimated as the difference in monthly predicted PM10 and PM2.5, with predicted PM10 from our previously developed PM10 model. Results: Predictive performance for PM2.5 was strong (cross-validation R2 = 0.77 and 0.69 for post-1999 and pre-1999 PM2.5 models, respectively) with high precision (2.2 and 2.7 μg/m3, respectively). Models performed well irrespective of population density and season. Predictive performance for PM10–2.5 was weaker (cross-validation R2 = 0.39) with lower precision (5.5 μg/m3). PM10–2.5 levels exhibited greater local spatial variability than PM10 or PM2.5, suggesting that PM2.5 measurements at ambient monitoring sites are more representative for surrounding populations than for PM10 and especially PM10–2.5. Conclusions: We provide semiempirical models to predict spatially and temporally resolved long-term average outdoor concentrations of PM2.5 and PM10–2.5 for estimating exposures of populations living in the northeastern and midwestern United States

Protected area targets post-2020

The ten-year Strategic Plan for Biodiversity, made up of 20 Aichi Biodiversity Targets, is coming to an end and it is therefore timely to assess their appropriateness so as to provide scientific support on the development of an improved post-2020 framework. Here we focus on Aichi Target 11, concerned with conserving protected areas and other effective area-based conservation measures by 2020. We identify four broad problems with Aichi Target 11 that have led to perverse outcomes and an inability for nations to account for true conservation progress. We propose a formulation for a target for site-based conservation beyond 2020 aimed at overcoming them: ‘The value of all key biodiversity areas and other sites of global significance for biodiversity is documented and retained through protected areas and other effective area-based conservation measures’

Short-term Air Pollution Levels and Blood Pressure in Older Women

Background: Evidence of associations between daily variation in air pollution and blood pressure (BP) is varied and few prior longitudinal studies adjusted for calendar time. Methods: We studied 143,658 postmenopausal women 50 to 79 years of age from the Women's Health Initiative (1993-2005). We estimated daily atmospheric particulate matter (PM) (in three size fractions: PM2.5, PM2.5-10, and PM10) and nitrogen dioxide (NO2) concentrations at participants' residential addresses using validated lognormal kriging models. We used linear mixed-effects models to estimate the association between air pollution concentrations and repeated measures of systolic and diastolic BP (SBP, DBP) adjusting for confounders and calendar time. Results: Short-term PM2.5and NO2were each positively associated with DBP {0.10 mmHg [95% confidence interval (CI): 0.04, 0.15]; 0.13 mmHg (95% CI: 0.09, 0.18), respectively} for interquartile range changes in lag 3-5 day PM2.5and NO2. Short-term NO2was negatively associated with SBP [-0.21 mmHg (95%CI: -0.30, -0.13)]. In two-pollutant models, the NO2-DBP association was slightly stronger, but for PM2.5was attenuated to null, compared with single-pollutant models. Associations between short-term NO2and DBP were more pronounced among those with higher body mass index, lower neighborhood socioeconomic position, and diabetes. When long-term (annual) and lag 3-5 day PM2.5were in the same model, associations with long-term PM2.5were stronger than for lag 3-5 day. Conclusions: We observed that short-term PM2.5and NO2levels were associated with increased DBP, although two-pollutant model results suggest NO2was more likely responsible for observed associations. Long-term PM2.5effects were larger than short-term

Confounding and exposure measurement error in air pollution epidemiology

Studies in air pollution epidemiology may suffer from some specific forms of confounding and exposure measurement error. This contribution discusses these, mostly in the framework of cohort studies. Evaluation of potential confounding is critical in studies of the health effects of air pollution. The association between long-term exposure to ambient air pollution and mortality has been investigated using cohort studies in which subjects are followed over time with respect to their vital status. In such studies, control for individual-level confounders such as smoking is important, as is control for area-level confounders such as neighborhood socio-economic status. In addition, there may be spatial dependencies in the survival data that need to be addressed. These issues are illustrated using the American Cancer Society Cancer Prevention II cohort. Exposure measurement error is a challenge in epidemiology because inference about health effects can be incorrect when the measured or predicted exposure used in the analysis is different from the underlying true exposure. Air pollution epidemiology rarely if ever uses personal measurements of exposure for reasons of cost and feasibility. Exposure measurement error in air pollution epidemiology comes in various dominant forms, which are different for time-series and cohort studies. The challenges are reviewed and a number of suggested solutions are discussed for both study domains

Air pollution and general practitioner access and utilization: a population based study in Sarnia, 'Chemical Valley,' Ontario

<p>Abstract</p> <p>Background</p> <p>Health impacts of poor environmental quality have been identified in studies around the world and in Canada. While many of the studies have identified associations between air pollution and mortality or morbidity, few have focused on the role of health care as a potential moderator of impacts. This study assessed the determinants of health care access and utilization in the context of ambient air pollution in Sarnia, Ontario, Canada.</p> <p>Methods</p> <p>Residents of Sarnia participated in a Community Health Study administered by phone, while several ambient air pollutants including nitrogen dioxide (NO₂), sulphur dioxide (SO₂) and the volatile organic compounds benzene, toluene, ethylbenzene, mp- and o-xylene (BTEX) were monitored across the city. Land Use Regression models were used to estimate individual exposures to the measured pollutants and logistic regression models were utilized to assess the relative influence of environmental, socioeconomic and health related covariates on general practitioner access and utilization outcomes.</p> <p>Results</p> <p>The results show that general practitioner use increased with levels of exposure to nitrogen dioxide (NO₂- Odds Ratio [OR]: 1.16, <it>p </it>< 0.05) and sulphur dioxide (SO₂- OR: 1.61, <it>p </it>< 0.05). Low household income was a stronger predictor of having no family doctor in areas exposed to high concentrations of NO₂and SO₂. Respondents without regular care living in high pollution areas were also more likely to report travelling or waiting for care in excess of 20 minutes (OR: 3.28, <it>p </it>< 0.05) than their low exposure counterparts (OR: 1.11, <it>p </it>> 0.05).</p> <p>Conclusions</p> <p>This study provides evidence for inequitable health care access and utilization in Sarnia, with particular relevance to its situation as a sentinel high exposure environment. Levels of exposure to pollution appears to influence utilization of health care services, but poor access to primary health care services additionally burden certain groups in Sarnia, Ontario, Canada.</p

NEOTROPICAL XENARTHRANS: a data set of occurrence of xenarthran species in the Neotropics

Xenarthrans – anteaters, sloths, and armadillos – have essential functions for ecosystem maintenance, such as insect control and nutrient cycling, playing key roles as ecosystem engineers. Because of habitat loss and fragmentation, hunting pressure, and conflicts with 24 domestic dogs, these species have been threatened locally, regionally, or even across their full distribution ranges. The Neotropics harbor 21 species of armadillos, ten anteaters, and six sloths. Our dataset includes the families Chlamyphoridae (13), Dasypodidae (7), Myrmecophagidae (3), Bradypodidae (4), and Megalonychidae (2). We have no occurrence data on Dasypus pilosus (Dasypodidae). Regarding Cyclopedidae, until recently, only one species was recognized, but new genetic studies have revealed that the group is represented by seven species. In this data-paper, we compiled a total of 42,528 records of 31 species, represented by occurrence and quantitative data, totaling 24,847 unique georeferenced records. The geographic range is from the south of the USA, Mexico, and Caribbean countries at the northern portion of the Neotropics, to its austral distribution in Argentina, Paraguay, Chile, and Uruguay. Regarding anteaters, Myrmecophaga tridactyla has the most records (n=5,941), and Cyclopes sp. has the fewest (n=240). The armadillo species with the most data is Dasypus novemcinctus (n=11,588), and the least recorded for Calyptophractus retusus (n=33). With regards to sloth species, Bradypus variegatus has the most records (n=962), and Bradypus pygmaeus has the fewest (n=12). Our main objective with Neotropical Xenarthrans is to make occurrence and quantitative data available to facilitate more ecological research, particularly if we integrate the xenarthran data with other datasets of Neotropical Series which will become available very soon (i.e. Neotropical Carnivores, Neotropical Invasive Mammals, and Neotropical Hunters and Dogs). Therefore, studies on trophic cascades, hunting pressure, habitat loss, fragmentation effects, species invasion, and climate change effects will be possible with the Neotropical Xenarthrans dataset

Sustainability Agenda for the Pantanal Wetland: Perspectives on a Collaborative Interface for Science, Policy, and Decision-Making.

Building bridges between environmental and political agendas is essential nowadays in face of the increasing human pressure on natural environments, including wetlands. Wetlands provide critical ecosystem services for humanity and can generate a considerable direct or indirect income to the local communities. To meet many of the sustainable development goals, we need to move our trajectory from the current environmental destructive development to a wiser wetland use. The current article contain a proposed agenda for the Pantanal aiming the improvement of public policy for conservation in the Pantanal, one of the largest, most diverse, and continuous inland wetland in the world. We suggest and discuss a list of 11 essential interfaces between science, policy, and development in region linked to the proposed agenda. We believe that a functional science network can booster the collaborative capability to generate creative ideas and solutions to address the big challenges faced by the Pantanal wetland