Taking away David’s sling*: environmental justice and land-use conflict in extractive resource development

Exploring cases of gas and coal extraction in Australia and the U.S.A., this paper considers instances in which legal and political frameworks have been used to prioritise development interests and minimise opportunities for community objection. Two case studies illustrate the role of law and the influence of politics on environmental conflict, conflict resolution, and participation in decision-making associated with resource extraction. A range of barriers to meaningful community participation in land-use decision-making are exposed by combining legal and non-legal concepts of equity and justice with ideologies of democracy and representation. These include asymmetry in information and resources available to parties; instances of misrecognition of weaker participants; and examples of malrecognition, where community attempts to engage democratic rights of public participation were thwarted by the strategic and deliberate actions of both industry and government. This paper illustrates the limits of current legal approaches to addressing land-use conflict and contributes to the developing scholarship of environmental justice as an analytic framework for addressing complex environmental and social justice issues.     

Impact of Length of Dataset on Streamflow Calibration Parameters and Performance of APEX Model

Due to resource constraints, long‐term monitoring data for calibration and validation of hydrologic and water quality models are rare. As a result, most models are calibrated and, if possible, validated using limited measured data. However, little research has been done to determine the impact of length of available calibration data on model parameterization and performance. The main objective of this study was to evaluate the impact of length of calibration data (LCD) on parameterization and performance of the Agricultural Policy Environmental eXtender model for predicting daily, monthly, and annual streamflow. Long‐term (1984‐2015) measured daily streamflow data from Rock Creek watershed, an agricultural watershed in northern Ohio, were used for this study. Data were divided into five Short (5‐year), two Medium (15‐year), and one Long (25‐year) streamflow calibration data scenarios. All LCD scenarios were calibrated and validated at three time steps: daily, monthly, and annual. Results showed LCD affected the ability of the model to accurately capture temporal variability in simulated streamflow. However, overall average streamflow, water budgets, and crop yields were simulated reasonably well for all LCD scenarios.     

Climate adaptation of food value chains: the implications of varying consumer acceptance

Despite there being considerable research and knowledge surrounding the risks of climate change on agricultural productivity, fewer studies have examined risks from a whole-of-chain perspective (i.e. from producer to consumer) and the perceptions of consumers about the climate adaptation strategies of food businesses. This paper presents the findings of a survey of 1532 Australian consumers and how they might respond to a food company’s climate adaptation strategy. Three respondent archetypes, ‘Eco-warriors’ (n = 557), ‘Undecideds’ (n = 600) and ‘Abdicators’ (n = 375), were identified based on their perceptions of risks associated with climate change and their attitudes towards climate adaptation. Further analysis was carried out to understand how each group of respondents would respond to adaptation strategies employed by food companies. Based on the findings of this study, two main challenges are presented for food value chains: (1) translating consumer needs and preferences to niche opportunities arising from adaptation and (2) understanding how best to communicate adaptation benefits based on varying attitudes and information needs. By addressing these challenges, synergies between adaptation goals and competitive strategies in food value chains may be achieved.     

Exploring future agricultural development and biodiversity in Uganda,Rwanda and Burundi: a spatially explicit scenario-based assessment

Regional Environmental Change - Competition for land is increasing as a consequence of the growing demands for food and other commodities and the need to conserve biodiversity and ecosystem...     

Modeling spatio-temporal wildfire ignition point patterns

We analyze and model the structure of spatio-temporal wildfire ignitions in the St. Johns River Water Management District in northeastern Florida. Previous studies, based on the K-function and an assumption of homogeneity, have shown that wildfire events occur in clusters. We revisit this analysis based on an inhomogeneous K-function and argue that clustering is less important than initially thought. We also use K-cross functions to study multitype point patterns, both under homogeneity and inhomogeneity assumptions, and reach similar conclusions as above regarding the amount of clustering. Of particular interest is our finding that prescribed burns seem not to reduce significantly the occurrence of wildfires in the current or subsequent year over this large geographical region. Finally, we describe various point pattern models for the location of wildfires and investigate their adequacy by means of recent residual diagnostics.

Networks,Agency and (De)stabilization: The Issue of Navigation on the River Wye,UK

This paper assesses the way in which an actor network presiding over the management of the River Wye has stabilized through accepting a particular view on the issue of navigation. The paper provides an account of how the network was challenged by a dissonant actor who, through reviving an old company, developed a counter network. It is argued that network stabilization is a form of consensus-building and it is contended that the way in which an issue is defined is crucial in terms of the successful enrolment of actors. The paper illustrates some of the conflicts and complexities encountered in resource planning, suggesting that research of this nature should trace actors back through time as well as through space if dynamics between actors involved in rural planning and management are to be effectively understood.     

Monitoring organic contaminants in eggs of glaucous and glaucous-winged gulls (Larus hyperboreus and Larus glaucescens) from Alaska

Gull eggs have been used to monitor contaminants in many parts of the world. The Seabird Tissue Archival and Monitoring Project (STAMP) is a long-term program designed to track trends in pollutants in northern marine environments using seabird eggs. Glaucous and glaucous-winged gull (Larus hyperboreus and Larus glaucescens) eggs collected in 2005 from seven Alaskan colonies were analyzed for organic contaminants. Concentrations ranged from below detection limits to 322 ng g⁻¹ wet mass in one egg for 4,4′-DDE and differed among the samples collected in the Gulf of Alaska and Bering and Chukchi Seas. Chick growth and survival rates may be affected by the contaminant levels found in the eggs, but the eggs should be safe for human consumption if they are eaten in small quantities. STAMP plans to continue collecting and banking gull eggs for future real-time and retrospective analyses.     

Emission profile of 18 carbonyl compounds,CO, CO2, and NOx emitted by a diesel engine fuelled with diesel and ternary blends containing diesel,ethanol and biodiesel or vegetable oils

The impact of vehicular emissions on air depends, among other factors, on the composition of fuel and the technology used to build the engines. The reduction of vehicular emissions requires changes in the fuel composition, and improving the technologies used in the manufacturing of engines and for the after-treatment of gases. In general, improvements to diesel engines have targeted not only emission reductions, but also reductions in fuel consumption. However, changes in the fuel composition have been shown to be a more rapid and effective alternative to reduce pollution. Some factors should been taken into consideration when searching for an alternative fuel to be used in diesel engines, such as emissions, fuel stability, availability and its distribution, as well as its effects on the engine durability. In this work, 45 fuel blends were prepared and their stability was evaluated. The following mixtures (v/v/v) were stable for the 90-day period and were used in the emission study: diesel/ethanol – 90/10%, diesel/ethanol/soybean biodiesel – 80/15/5%, diesel/ethanol/castor biodiesel – 80/15/5%, diesel/ethanol/residual biodiesel – 80/15/5%, diesel/ethanol/soybean oil – 90/7/3%, and diesel/ethanol/castor oil – 90/7/3%. The diesel/ethanol fuel showed higher reduction of NO_x emission at a lower load (2 kW) when compared with pure diesel. The other fuels showed a decrease of NO_x emissions in the ranges of 6.9–75% and 4–85% at 1800 rpm and 2000 rpm, respectively. The combustion efficiencies of the diesel can be enhanced by the addition of the oxygenate fuels, like ethanol and biodiesel/vegetable oil, resulting in a more complete combustion in terms of NO_x emission. In the case of CO₂ the decreases were in the ranges of 5–24% and 4–6% at 1800 rpm and 2000 rpm, respectively. Meanwhile, no differences were observed in CO emission. The carbonyl compounds (CC) studied were formaldehyde, acetaldehyde, propionaldehyde, acrolein, acetone, crotonaldehyde, butyraldehyde, butanone, benzaldehyde, isovaleraldehyde, valeraldehyde, o-toluenaldehyde, m-toluenaldehyde, p-toluenaldehyde, hexaldehyde, octaldehyde, 2,5-dimethylbenzaldehyde, and decaldehyde. Among them, formaldehyde, acetaldehyde, acetone, and propionaldehyde showed the highest emission concentrations. When ternary blend contains vegetable oil, there is a strong tendency to increase the emissions of the high weight CC and decrease the emissions of the low weight CC. The highest concentration of acrolein was observed when the fuel contains diesel, ethanol and biodiesel. With the exception of NO_x, the use of ternary blended fuels resulted on the increase in the emission rates of the studied compounds.     

Back-extrapolation of estimates of exposure from current land-use regression models

Land use regression has been used in epidemiologic studies to estimate long-term exposure to air pollution within cities. The models are often developed toward the end of the study using recent air pollution data. Given that there may be spatially-dependent temporal trends in urban air pollution and that there is interest for epidemiologists in assessing period-specific exposures, especially early-life exposure, methods are required to extrapolate these models back in time. We present herein three new methods to back-extrapolate land use regression models. During three two-week periods in 2005–2006, we monitored nitrogen dioxide (NO₂) at about 130 locations in Montreal, Quebec, and then developed a land-use regression (LUR) model. Our three extrapolation methods entailed multiplying the predicted concentrations of NO₂ by the ratio of past estimates of concentrations from fixed-site monitors, such that they reflected the change in the spatial structure of NO₂ from measurements at fixed-site monitors. The specific methods depended on the availability of land use and traffic-related data, and we back-extrapolated the LUR model to 10 and 20 years into the past. We then applied these estimates to residential information from subjects enrolled in a case–control study of postmenopausal breast cancer that was conducted in 1996.Observed and predicted concentrations of NO₂ in Montreal decreased and were correlated in time. The estimated concentrations using the three extrapolation methods had similar distributions, except that one method yielded slightly lower values. The spatial distributions varied slightly between methods. In the analysis of the breast cancer study, the odds ratios were insensitive to the method but varied with time: for a 5 ppb increase in NO₂ using the 2006 LUR the odds ratio (OR) was about 1.4 and the ORs in predicted past concentrations of NO₂ varied (OR～1.2 for 1985 and OR～1.3–1.5 for 1996). Thus, the ORs per unit exposure increased with time as the range and variance of the spatial distributions decreased, and this is due partly to the regression coefficient being approximately inversely proportional to the variance of exposure. Changing spatial variability complicates interpretation and this may have important implications for the management of risk. Further studies are needed to estimate the accuracy of the different methods.