Evaluation and Improvement of a Dry Deposition Model using SO2 and O3 Measurements over a Mixed Forest

A dry deposition model (RDM) for operational application has beenevaluated and modified in the present study. Field measurements of friction velocity and dry deposition velocity of SO₂ andO₃ over a mixed forest have been used to evaluate RDM. It was found that RDM predicts friction velocities very close to measurements and thus it can predict reasonable aerodynamic resistance. RDM overestimated O₃ deposition during dry nighttime conditions and underestimated both O₃ andSO₂deposition for early morning hours. It could not predict the mean diurnal variation in deposition velocity for either O₃ or SO₂ deposition under wet surface conditions. Modifications have been made for O₃ and SO₂ dry deposition based on the comparison of results and based upon additional published data. Compared to an earlier version of RDM, the modified versionpredicts better results for O₃ and SO₂ dry deposition,especially under rain and dew conditions.     

Key role for nuclear energy in global biodiversity conservation

Modern society uses massive amounts of energy. Usage rises as population and affluence increase, and energy production and use often have an impact on biodiversity or natural areas. To avoid a business‐as‐usual dependence on coal, oil, and gas over the coming decades, society must map out a future energy mix that incorporates alternative sources. This exercise can lead to radically different opinions on what a sustainable energy portfolio might entail, so an objective assessment of the relative costs and benefits of different energy sources is required. We evaluated the land use, emissions, climate, and cost implications of 3 published but divergent storylines for future energy production, none of which was optimal for all environmental and economic indicators. Using multicriteria decision‐making analysis, we ranked 7 major electricity‐generation sources (coal, gas, nuclear, biomass, hydro, wind, and solar) based on costs and benefits and tested the sensitivity of the rankings to biases stemming from contrasting philosophical ideals. Irrespective of weightings, nuclear and wind energy had the highest benefit‐to‐cost ratio. Although the environmental movement has historically rejected the nuclear energy option, new‐generation reactor technologies that fully recycle waste and incorporate passive safety systems might resolve their concerns and ought to be more widely understood. Because there is no perfect energy source however, conservation professionals ultimately need to take an evidence‐based approach to consider carefully the integrated effects of energy mixes on biodiversity conservation. Trade‐offs and compromises are inevitable and require advocating energy mixes that minimize net environmental damage. Society cannot afford to risk wholesale failure to address energy‐related biodiversity impacts because of preconceived notions and ideals.     

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.     

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...     

Modelling strategies for the management of the critically endangered Carpentarian rock-rat (Zyzomys palatalis) of northern Australia

The Carpentarian rock-rat (Zyzomys palatalis) is a critically endangered endemic rodent known from only four sandstone gorges in the southeast Gulf of Carpentaria, Northern Territory, Australia. These gorges harbour thickets of monsoon rainforest and broadleaf woodland, surrounded by a Eucalypt savanna matrix. The long-term persistence of Z. palatalis is threatened by altered fire regimes, grazing by feral animals and stock, weed intrusion, and the stochastic hazards associated with small, fragmented populations. To assess the relative importance of these threats and develop practical management options, a population and habitat simulation model was developed, based on the best existing data. Population viability was predicted to be highly sensitive to the frequency of hot, late dry-season fires. Progressive habitat degradation (due predominantly to intense late dry-season fires) is likely to substantially reduce population size and lead to the probable extinction of the species within the next 100 years. The most effective management strategy to counteract this threat would be regular, controlled, fuel reduction burns in the vegetation around the gorge entrances during the early dry season. Establishing a new population (through translocation of captive-bred individuals) would not appreciably reduce extinction risk, but could provide valuable additional data on the impact of threats, if conducted as an adaptive management experiment.     

Factors influencing farmers' concerns regarding bovine tuberculosis in wildlife and livestock around Riding Mountain National Park

Despite intensive efforts over the last century to eradicate bovine tuberculosis (TB) in North America, several hotspots of infected wildlife and livestock remain, raising concerns that the disease will never be eradicated. The stress and frustration for a farmer caused by having a herd test positive for TB or living in an infected region can be substantial. The goal of this study was to investigate the concerns of farmers around Riding Mountain National Park (RMNP) regarding the presence of TB in wildlife and livestock and conduct an exploratory analysis of causal factors. Data were collected from 786 farmers within 50 km of RMNP using a mail-back questionnaire. Overall, farmers indicated a high level of concern toward diseases in both wildlife and cattle relative to other concerns. The spatial variables that had the greatest influence on TB concern were both the distance of farms to the RMNP boundary and distance of farms to previous cases of TB. The most important aspatial factor associated with high TB concern was the frequency with which farmers observed elk on their land. These results underscore the important differences between 'objective' measures of risk, such as epidemiological estimates of disease prevalence, and subjective measures of disease concern, such as risk perception and acceptability of management actions. Written responses suggest that concerns regarding disease may affect how farmers view wildlife on their land and their relationship with neighbouring protected areas. Management activities that reduce the frequency of elk interactions with farms, but also recognize the complex relationship that farmers have with wildlife and protected areas, will be most effective in mitigating farmer concern regarding this important problem.