Integrating Environmental and Socio-Economic Indicators of a Linked Catchment–Coastal System Using Variable Environmental Intensity

Can we develop land use policy that balances the conflicting views of stakeholders in a catchment while moving toward long term sustainability? Adaptive management provides a strategy for this whereby measures of catchment performance are compared against performance goals in order to progressively improve policy. However, the feedback loop of adaptive management is often slow and irreversible impacts may result before policy has been adapted. In contrast, integrated modelling of future land use policy provides rapid feedback and potentially improves the chance of avoiding unwanted collapse events. Replacing measures of catchment performance with modelled catchment performance has usually required the dynamic linking of many models, both biophysical and socio-economic—and this requires much effort in software development. As an alternative, we propose the use of variable environmental intensity (defined as the ratio of environmental impact over economic output) in a loose coupling of models to provide a sufficient level of integration while avoiding significant effort required for software development. This model construct was applied to the Motueka Catchment of New Zealand where several biophysical (riverine water quantity, sediment, E. coli faecal bacteria, trout numbers, nitrogen transport, marine productivity) models, a socio-economic (gross output, gross margin, job numbers) model, and an agent-based model were linked. An extreme set of land use scenarios (historic, present, and intensive) were applied to this modelling framework. Results suggest that the catchment is presently in a near optimal land use configuration that is unlikely to benefit from further intensification. This would quickly put stress on water quantity (at low flow) and water quality (E. coli). To date, this model evaluation is based on a theoretical test that explores the logical implications of intensification at an unlikely extreme in order to assess the implications of likely growth trajectories from present use. While this has largely been a desktop exercise, it would also be possible to use this framework to model and explore the biophysical and economic impacts of individual or collective catchment visions. We are currently investigating the use of the model in this type of application.     

An ecological perspective on nanomaterial impacts in the environment

Growing concerns over the potential for unintended, adverse consequences of engineered nanoparticles (ENPs) in the environment have generated new research initiatives focused on understanding the ecological effects of ENPs. Almost nothing is currently known about the fate and transport of ENPs in environmental waters, soils, and sediments or about the biological impacts of ENPs in natural environments, and the bulk of modern nanotoxicogical research is focused on highly controlled laboratory studies with single species in simple media. In this paper, we provide an ecological perspective on the current state of knowledge regarding the likely environmental impacts of nanomaterials and propose a strategy for making rapid progress in new research in ecological nanoscience.     

The Analysis of Airborne Sulfate

This report reviews the current state of analytical methodology for sulfate in airborne particles. Methods for determination of total aerosol sulfate and total soluble sulfate are assessed. A more detailed review of the relatively new techniques for quantitative speciation of airborne sulfate then follows. Size distribution methodology and filter sampling difficulties relating to the collection of airborne sulfate-containing particles are enumerated. Experiments are suggested which use new, improved, and potentially applicable sulfate speciation techniques to obtain a better understanding of the generation, transport, transformation and removal processes that, in turn, determine the identity and concentrations of sulfate species in ambient air.     

Characterization of Particulates from Power Plants

The emphasis on participate control from industrial processes has been shifted recently towards fine particulates, having diameters less than 3 microns. There exists an urgent need for more scientific information of fine particle characterization.^1,2 Coal and oil fired power plants are among the largest anthropogenic point sources of particulate matter.³ Limited knowledge is available on particle size distribution and trace metal composition in power plant emissions.^4-7 The morphological properties of particle emissions have been largely neglected. In this report we present some information on particle characteristics for an oil-fired and coal-fired power plant.     

An Intelligent Emissions Controller for Fuel Lean Gas Reburn in Coal-Fired Power Plants

ABSTRACT

The application of artificial intelligence techniques for performance optimization of the fuel lean gas reburn (FLGR) system is investigated. A multilayer, feedforward artificial neural network is applied to model static nonlinear relationships between the distribution of injected natural gas into the upper region of the furnace of a coal-fired boiler and the corresponding oxides of nitrogen (NO_x) emissions exiting the furnace. Based on this model, optimal distributions of injected gas are determined such that the largest NO_x reduction is achieved for each value of total injected gas. This optimization is accomplished through the development of a new optimization method based on neural networks. This new optimal control algorithm, which can be used as an alternative generic tool for solving multidimensional nonlinear constrained optimization problems, is described and its results are successfully validated against an off-the-shelf tool for solving mathematical programming problems. Encouraging results obtained using plant data from one of Commonwealth Edison's coal-fired electric power plants demonstrate the feasibility of the overall approach.

Preliminary results show that the use of this intelligent controller will also enable the determination of the most cost-effective operating conditions of the FLGR system by considering, along with the optimal distribution of the injected gas, the cost differential between natural gas and coal and the open-market price of NO_x emission credits. Further study, however, is necessary, including the construction of a more comprehensive database, needed to develop high-fidelity process models and to add carbon monoxide (CO) emissions to the model of the gas reburn system.     

Changes in Streambed Composition in Salmonid Spawning Habitat of the Elwha River during Dam Removal

One uncertainty associated with large dam removal is the level of downstream sediment deposition and associated short‐term biological effects, particularly on salmonid spawning habitat. Recent studies report downstream sediment deposition following dam removal is influenced by proximity to the source and river transport capacity. The impacts of dam removal sediment releases are difficult to generalize due to the relatively small number of dam removals completed, the variation in release strategies, and the physical nature of systems. Changes to sediment deposition and associated streambed composition in the Elwha River, Washington State, were monitored prior to (2010‐2011) and during (2012‐2014) the simultaneous removal of two large dams (32 and 64 m). Changes in the surface layer substrate composition during dam removal varied by year and channel type. Riffles in floodplain channels downstream of the dams fined and remained sand dominated throughout the study period, and exceeded levels known to be detrimental to incubating salmonids. Mainstem riffles tended to fine to gravel, but appear to be trending toward cobble after the majority of the sediment was released and transported through system. Thus, salmonid spawning habitats in the mainstem appear to have been minimally impacted while those in floodplain channels appear to have been severely impacted during dam removal.     

A global assessment of chromium pollution using sperm whales (Physeter macrocephalus) as an indicator species

Chromium (Cr) is a well-known human carcinogen and a potential reproductive toxicant, but its contribution to ocean pollution is poorly understood. The aim of this study was to provide a global baseline for Cr as a marine pollutant using the sperm whale (Physeter macrocephalus) as an indicator species. Biopsies were collected from free-ranging whales around the globe during the voyage of the research vessel The Odyssey. Total Cr levels were measured in 361 sperm whales collected from 16 regions around the globe detectable levels ranged from 0.9 to 122.6 μg Cr g tissue⁻¹ with a global mean of 8.8 ± 0.9 μg g⁻¹. Two whales had undetectable levels. The highest levels were found in sperm whales sampled in the waters near the Islands of Kiribati in the Pacific (mean = 44.3 ± 14.4) and the Seychelles in the Indian Ocean (mean = 19.5 ± 5.4 μg g⁻¹). The lowest mean levels were found in whales near the Canary Islands (mean = 3.7 ± 0.8 μg g⁻¹) and off of the coast of Sri Lanka (mean = 3.3 ± 0.4 μg g⁻¹). The global mean Cr level in whale skin was 28-times higher than mean Cr skin levels in humans without occupational exposure. The whale levels were more similar to levels only observed previously in human lung tissue from workers who died of Cr-induced lung cancer. We conclude that Cr pollution in the marine environment is significant and that further study is urgently needed.     

Earthworm ecotoxicological assessments of pesticides used to treat seeds under tropical conditions

Ecotoxicological laboratory tests (lower-tier tests) are fundamental tools for assessing the toxicity of pesticides to soil organisms. In this study, using these tests under tropical conditions, we quantified the impact of the insecticides imidacloprid, fipronil, and thiametoxam, and the fungicides captan and carboxin + thiram, all of which are used in the chemical treatment of crop seeds, on the survival, reproduction, and behavior of Eisenia andrei (Oligochaeta). With the exception of imidacloprid, none of the pesticides tested caused mortality in E. andrei in artificial soils. The LC₅₀ of imidacloprid was estimated as 25.53 mg active ingredient kg^?1 of dry soil. Earthworm reproduction rates were reduced by imidacloprid (EC₅₀ = 4.07 mg kg^?1), fipronil (EC₂₀ = 23.16 mg kg^?1), carboxin + thiram (EC₅₀ = 56.38 mg kg^?1), captan (EC₅₀ = 334.84 mg kg^?1), and thiametoxam (EC₅₀ = 791.99 mg kg^?1). Avoidance behavior was observed in the presence of imidacloprid (AC₅₀ = 0.11 mg kg^?1), captan (AC₅₀ = 33.54 mg kg^?1), carboxin + thiram (AC₅₀ = 60.32 mg kg^?1), and thiametoxam (AC₅₀ = >20 mg kg^?1). Earthworms showed a preference for soils with the insecticide fipronil. Imidacloprid was the most toxic of the substances tested for E. andrei. The avoidance test was the most sensitive test for most pesticides studied, but results varied between pesticides. These results offer new insights on the toxicity of pesticides used to treat seeds in tropical regions. However, they should be complemented with higher-tier tests in order to reduce the uncertainties in risk assessment.     

Influence of Landscape Variability on Atmospheric Dispersion

Using idealized distributions of surface moisture, it is shown that with a significant synoptic prevailing flow over these regions of surface variability, dispersion is generally enhanced over heterogeneous surfaces as compared to horizontally homogeneous conditions. The importance of the heterogeneity becomes less, however, as the large scale wind speed increases and/or the spatial scale of the heterogeneities become less. This work also clearly demonstrates that the use of Gaussian regulatory models in areas of landscape variability is inappropriate.