Glass Fibers and Their Use as Filter Media

Typical air quality effect levels of photochemical oxidants on specific plant substrates are illustrated. These include ambient oxidant exposure data measured as “total oxidant” as well as laboratory exposures to individual pure oxidants, ozone, or PAN compounds, since these oxidants are identified in photochemical smog. New terms, “PaNs” and “PAN-type” oxidant, have been proffered for purposes of clarification of the terminology. PAN-type oxidant more precisely defines the phytotoxicant complex causing silvering or bronzing of the lower leaf surfaces in lieu of the older term “oxidant.” Due to the recognition of several oxidizing phytotoxicants in recent years, it is recommended that the term oxidant be reserved for use as a generic term. A tabular classification of the oxidizing phytotoxicants found in community photochemical smog and the specific syndromes produced is provided.     

Why geodiversity matters in valuing nature's stage

Geodiversity—the variability of Earth's surface materials, forms, and physical processes—is an integral part of nature and crucial for sustaining ecosystems and their services. It provides the substrates, landform mosaics, and dynamic physical processes for habitat development and maintenance. By determining the heterogeneity of the physical environment in conjunction with climate interactions, geodiversity has a crucial influence on biodiversity across a wide range of scales. From a literature review, we identified the diverse values of geodiversity; examined examples of the dependencies of biodiversity on geodiversity at a site‐specific scale (for geosites <1 km² in area); and evaluated various human‐induced threats to geosites and geodiversity. We found that geosites are important to biodiversity because they often support rare or unique biota adapted to distinctive environmental conditions or create a diversity of microenvironments that enhance species richness. Conservation of geodiversity in the face of a range of threats is critical both for effective management of nature's stage and for its own particular values. This requires approaches to nature conservation that integrate climate, biodiversity, and geodiversity at all spatial scales.     

Advances in science and applications of air pollution monitoring: A case study on oil sands monitoring targeting ecosystem protection

The potential environmental impact of air pollutants emitted from the oil sands industry in Alberta, Canada, has received considerable attention. The mining and processing of bitumen to produce synthetic crude oil, and the waste products associated with this activity, lead to significant emissions of gaseous and particle air pollutants. Deposition of pollutants occurs locally (i.e., near the sources) and also potentially at distances downwind, depending upon each pollutant’s chemical and physical properties and meteorological conditions. The Joint Oil Sands Monitoring Program (JOSM) was initiated in 2012 by the Government of Canada and the Province of Alberta to enhance or improve monitoring of pollutants and their potential impacts. In support of JOSM, Environment and Climate Change Canada (ECCC) undertook a significant research effort via three components: the Air, Water, and Wildlife components, which were implemented to better estimate baseline conditions related to levels of pollutants in the air and water, amounts of deposition, and exposures experienced by the biota. The criteria air contaminants (e.g., nitrogen oxides [NO_x], sulfur dioxide [SO₂], volatile organic compounds [VOCs], particulate matter with an aerodynamic diameter <2.5 μm [PM_2.5]) and their secondary atmospheric products were of interest, as well as toxic compounds, particularly polycyclic aromatic compounds (PACs), trace metals, and mercury (Hg). This critical review discusses the challenges of assessing ecosystem impacts and summarizes the major results of these efforts through approximately 2018. Focus is on the emissions to the air and the findings from the Air Component of the ECCC research and linkages to observations of contaminant levels in the surface waters in the region, in aquatic species, as well as in terrestrial and avian species. The existing evidence of impact on these species is briefly discussed, as is the potential for some of them to serve as sentinel species for the ongoing monitoring needed to better understand potential effects, their potential causes, and to detect future changes. Quantification of the atmospheric emissions of multiple pollutants needs to be improved, as does an understanding of the processes influencing fugitive emissions and local and regional deposition patterns. The influence of multiple stressors on biota exposure and response, from natural bitumen and forest fires to climate change, complicates the current ability to attribute effects to air emissions from the industry. However, there is growing evidence of the impact of current levels of PACs on some species, pointing to the need to improve the ability to predict PAC exposures and the key emission source involved. Although this critical review attempts to integrate some of the findings across the components, in terms of ECCC activities, increased coordination or integration of air, water, and wildlife research would enhance deeper scientific understanding. Improved understanding is needed in order to guide the development of long-term monitoring strategies that could most efficiently inform a future adaptive management approach to oil sands environmental monitoring and prevention of impacts.

Implications: Quantification of atmospheric emissions for multiple pollutants needs to be improved, and reporting mechanisms and standards could be adapted to facilitate such improvements, including periodic validation, particularly where uncertainties are the largest. Understanding of baseline conditions in the air, water and biota has improved significantly; ongoing enhanced monitoring, building on this progress, will help improve ecosystem protection measures in the oil sands region. Sentinel species have been identified that could be used to identify and characterize potential impacts of wildlife exposure, both locally and regionally. Polycyclic aromatic compounds are identified as having an impact on aquatic and terrestrial wildlife at current concentration levels although the significance of these impacts and attribution to emissions from oil sands development requires further assessment. Given the improvement in high resolution air quality prediction models, these should be a valuable tool to future environmental assessments and cumulative environment impact assessments.     

Determination of the source areas contributing to regionally high warm season PM2.5 in eastern North America

An ensemble-trajectory analysis technique known as Quantitative Transport Bias Analysis was applied to determine which geographic areas systematically contributed to above- and below-average fine particle mass (PM2.5) over eastern North America. Six-hour average measurements from 12 rural or suburban locations in eastern North America collected using a tapered element oscillating microbalance were individually associated with corresponding 3-day back-trajectories for the warm seasons (May-September) of 2000 and 2001. Much of the populated areas of northeastern North America were implicated in the build-up of PM2.5 to above-average concentrations. The finer structure of the Quantitative Transport Bias Analysis pattern indicated that transport from the Ohio River Valley, particularly the eastern portion of this area, was most often associated with the highest PM2.5 concentrations. In addition, air masses originating over a relatively large area from southeast Ohio to the western part of Virginia and the western Kentucky to central Tennessee area tended to result in relatively high PM2.5 concentrations over northeastern North America. These observation-based findings were consistent with the spatial distribution of the main sulfur dioxide emissions sources and the major oxides of nitrogen point sources.     

Incorporating known sources of uncertainty to determine precautionary harvests of saltwater crocodiles.

It has been demonstrated repeatedly that the degree to which regulation operates and the magnitude of environmental variation in an exploited population will together dictate the type of sustainable harvest achievable. Yet typically, harvest models fail to incorporate uncertainty in the underlying dynamics of the target population by assuming a particular (unknown) form of endogenous control. We use a novel approach to estimate the sustainable yield of saltwater crocodile (Crocodylus porosus) populations from major river systems in the Northern Territory, Australia, as an example of a system with high uncertainty. We used multimodel inference to incorporate three levels of uncertainty in yield estimation: (1) uncertainty in the choice of the underlying model(s) used to describe population dynamics, (2) the error associated with the precision and bias of model parameter estimation, and (3) environmental fluctuation (process error). We demonstrate varying strength of evidence for density regulation (1.3-96.7%) for crocodiles among 19 river systems by applying a continuum of five dynamical models (density-independent with and without drift and three alternative density-dependent models) to time series of density estimates. Evidence for density dependence increased with the number of yearly transitions over which each river system was monitored. Deterministic proportional maximum sustainable yield (PMSY) models varied widely among river systems (0.042-0.611), and there was strong evidence for an increasing PMSY as support for density dependence rose. However, there was also a large discrepancy between PMSY values and those produced by the full stochastic simulation projection incorporating all forms of uncertainty, which can be explained by the contribution of process error to estimates of sustainable harvest. We also determined that a fixed-quota harvest strategy (up to 0.2K, where K is the carrying capacity) reduces population size much more rapidly than proportional harvest (the latter strategy requiring temporal monitoring of population size to adjust harvest quotas) and greatly inflates the risk of resource depletion. Using an iconic species recovering from recent extreme overexploitation to examine the potential for renewed sustainable harvest, we have demonstrated that incorporating major forms of uncertainty into a single quantitative framework provides a robust approach to modeling the dynamics of exploited populations.     

Assessing spatial variability of ambient nitrogen dioxide in Montréal, Canada, with a land-use regression model

The purpose of this study was to derive a land-use regression model to estimate on a geographical basis ambient concentrations of nitrogen dioxide (NO2) in Montreal, Quebec, Canada. These estimates of concentrations of NO2 will be subsequently used to assess exposure in epidemiologic studies on the health effects of traffic-related air pollution. In May 2003, NO2 was measured for 14 consecutive days at 67 sites across the city using Ogawa passive diffusion samplers. Concentrations ranged from 4.9 to 21.2 ppb (median 11.8 ppb). Linear regression analysis was used to assess the association between logarithmic concentrations of NO2 and land-use variables derived using the ESRI Arc 8 geographic information system. In univariate analyses, NO2 was negatively associated with the area of open space and positively associated with traffic count on nearest highway, the length of highways within any radius from 100 to 750 m, the length of major roads within 750 m, and population density within 2000 m. Industrial land-use and the length of minor roads showed-no association with NO2. In multiple regression analyses, distance from the nearest highway, traffic count on the nearest highway, length of highways and major roads within 100 m, and population density showed significant associations with NO2; the best-fitting regression model had a R2 of 0.54. These analyses confirm the value of land-use regression modeling to assign exposures in large-scale epidemiologic studies.     

Prehistoric Decline in Freshwater Mussels Coincident with the Advent of Maize Agriculture

Abstract:  During late prehistory, high population densities and intensive agricultural practices of Native American societies had profound effects on the pre-Columbian landscape. The degree to which Native American land use affected aquatic ecosystems is unknown. Freshwater mussels are particularly sensitive harbingers of modern-day ecosystem deterioration. We used data from prehistoric Native American shell middens to examine prehistoric trends in abundance of freshwater mussels of the genus Epioblasma in North America during the last 5000 years. The relative abundance of Epioblasma declined steadily during this period, a result that could be explained either by an increase in human impacts to streams or by long-term climatic changes unrelated to human activities. The rate of decline of Epioblasma increased significantly, however, after the advent of large-scale maize agriculture in the southeastern United States about 1000 years before the present. Our results suggest that human land-use activities in prehistory caused changes in freshwater mussel communities that were lower in magnitude but similar in direction to changes caused by recent activities.     

How should surface elevation table data be analyzed? A comparison of several commonly used analysis methods and one newly proposed approach

Environmental and Ecological Statistics - The use of surface elevation table (SET) instruments to monitor elevation changes at low elevation coastal locations has steadily increased in recent...     

Relationships among Isolated Wetland Size, Hydroperiod, and Amphibian Species Richness: Implications for Wetland Regulations

Abstract: Wetland development within the United States is regulated primarily by size. Decisions concerning wetland destruction or conservation are therefore based in part on three inherent assumptions: (1) small wetlands contain water for short portions of the year; (2) small wetlands support few species; and (3) species found in small wetlands are also found in larger wetlands. We tested these assumptions using data on wetland size, relative hydroperiod (drying scores), and relative species richness of amphibians in depression wetlands of the southeastern United States. We found a significant (p = 0.03) but weak (r² = 0.05) relationship between hydroperiod and wetland size and no relationship (p = 0.48) between amphibian species richness and wetland size. Furthermore, synthetic models of lentic communities predict that short-hydroperiod wetlands support a unique group of species. Empirical investigations support this prediction. Our results indicate that hydroperiod length should be included as a primary criterion in wetland regulations. We advocate a landscape approach to wetlands regulation, focused in part on conserving a diversity of wetlands that represent the entire hydroperiod gradient.