Cumulative impact assessment in environmental planning: A coastal wetland watershed example

Several theoretical, analytical, and institutional difficulties have impeded the development and application of the assessment of cumulative environmental impacts. Watershed development on coastal wetlands offers an ideal context for evaluating the land disturbance target approach to cumulative impact assessment. A model land use planning system involving a time series approach was developed for Elkhorn Slough in California. The approach included four major components: evaluation of erosion susceptibility, measurement of land disturbance, establishment of a land disturbance target, and a comparison of existing and target land disturbance values. Further research is needed to test the transferability of the approach in a wide range of coastal watersheds and to verify the applicability of the methods to other cumulative impact problems.     

Analysing the sensitivity behaviour of two hydrology models

Recently, the New Morris Method has been presented as an effective sensitivity analysis tool for mathematical models. The New Morris Method estimates the sensitivity of an output parameter to a given set of input parameters (first-order effects) and the extent these parameters interact with each other (second-order effects). This method requires the specification of two parameters (runs and resolution) that control the sampling of the output parameter to determine its sensitivity to various inputs. The criteria for these parameters have been set on the analysis of a well-behaved analytical function (see Cropp and Braddock, Reliab. Eng. Syst. Saf. 78:77–83, 2002), which may not be applicable to other physical models that describe complex processes. This paper will investigate the appropriateness of the criteria from (Cropp and Braddock, 2002) and hence the effectiveness of the New Morris Method to determine the sensitivity behaviour of two hydrologic models: the Soil Erosion and Deposition System and Griffith University Representation of Urban Hydrology. In the first case, this paper will separately analyse the sensitivity of an output parameter on a set of input parameters (first- and second-order effects) for each model and discuss the physical meaning of these sensitivities. This will be followed by an investigation into the sampling criteria by exploring the convergence of the sensitivity behaviour for each model as the sampling of the parameter space is increased. By comparing these trends to the convergence behaviour from Cropp and Braddock (2002), we will determine how well the New Morris Method estimates the sensitivity for each model and whether the sampling criteria are appropriate for these models. It will be shown that the New Morris Method can provide additional insight into the functioning of these models, and that, under a different metric, the sensitivity behaviour of these models does converge confirming the sampling criteria set by Cropp and Braddock.     

Analysis of pollutant levels in central Hong Kong applying neural network method with particle swarm optimization

Air pollution has emerged as an imminent issue in modernsociety. Prediction of pollutant levels is an importantresearch topic in atmospheric environment today. For fulfillingsuch prediction, the use of neural network (NN), and inparticular the multi-layer perceptrons, has presented to be acost-effective technique superior to traditional statisticalmethods. But their training, usually with back-propagation (BP)algorithm or other gradient algorithms, is often with certaindrawbacks, such as: 1) very slow convergence, and 2) easilygetting stuck in a local minimum. In this paper, a newlydeveloped method, particle swarm optimization (PSO) model, isadopted to train perceptrons, to predict pollutant levels, andas a result, a PSO-based neural network approach is presented. The approach is demonstrated to be feasible and effective bypredicting some real air-quality problems.     

Multi-objective, decision-based assessment of a water quality monitoring network in a river system

Water quality monitoring network design has historically tended to use experience, intuition and subjective judgement in locating monitoring stations. Better design procedures to optimize monitoring systems need to simultaneously identify significant planning objectives and consider a number of social, economic and environmental constraints. The consideration of multiple objectives may require further decision analysis to determine the preference weights associated with the objectives to aid in the decision-making process. This may require the application of an optimization study to extract such information from decision makers or experts and to evaluate the overall effectiveness of locating strategies. This paper assesses the optimal expansion and relocation strategies of a water quality monitoring network using a two-stage analysis. The first stage focuses on the information retrieval of preference weights with respect to the designated planning objectives. With the aid of a pre-emptive goal programming model, data analysis is applied to obtain the essential information from the questionnaire outputs. The second stage then utilizes a weighted multi-objective optimization approach to search for the optimal locating strategies of the monitoring stations in the river basin. Practical implementation is illustrated by a case study in the Kao-Ping River Basin, south Taiwan.     

Optimal and suboptimal control of anaerobic digesters

Anaerobic digester failure due to entry of inhibitors or sudden changes in the feed substrate concentration may be encompassed beneficially by applying optimal control theory. An almost proportional relationship between the dilution rate and the methane production rate leads to a simple suboptimal control law with only minor loss in performance, after the occurrence of the above mentioned events.     

Attributes of reliable long-term landscape-scale studies: Malpractice insurance for landscape ecologists

Monitoring long-term change in forested landscapes is an intimidating challenge with considerable practical, methodological, and theoretical limitations. Current field approaches used to assess vegetation change at the plot-to-stand scales and nationwide forest monitoring programs may not be appropriate at landscape scales. We emphasize that few vegetation monitoring programs (and, thus, study design models) are designed to detect spatial and temporal trends at landscape scales. Based primarily on advice from many sources, and trial and error, we identify 14 attributes of a reliable long-term landscape monitoring program: malpractice insurance for landscape ecologists. The attributes are to: secure long-term funding and commitment; develop flexible goals; refine objectives; pay adequate attention to information management; take an experimental approach to sampling design; obtain peer-review and statistical review of research proposals and publications; avoid bias in selection of long-term plot locations; insure adequate spatial replication; insure adequate temporal replication; synthesize retrospective, experimental, and related studies; blend theoretical and empirical models with the means to validate both; obtain periodic research program evaluation; integrate and synthesize with larger and smaller scale research, inventory, and monitoring programs; and develop an extensive outreach program. Using these 14 attributes as a guide, we describe one approach to assess the potential effect of global change on the vegetation of the Front Range of the Colorado Rockies. This self-evaluation helps identify strengthes and weaknesses in our program, and may serve the same role for other landscape ecologists in other programs.     

Pesticide burden on some insects of economic importance in Lucknow (India)

Some insects of economic importance from Lucknow (India) have been investigated for their pesticide burden. Chlorinated pesticide residues of DDT, BHC and aldrin along with their metabolites and isomers have been detected in crop pollinating insects, honeybees (Apis indica) and butterflies (Danais chrysippus and Eurema sp.) and predators, dragonfly (Platythemis sp.) and wasps (Polistes herebreus). DDT and their metabolites were present in concentrations which varied from 231–796 ng g^–1, followed by BHC (10–60 ng g^–1), and aldrin (0.26–6.68 ng g^–1). This finding is likely to stimulate newer interest in the area of pesticide research and start meaningful investigation to find if bioaccumulated pesticides would have adverse impact on otherwise beneficial potentials of such insects in our ecosystems.     

Environmental and biological monitoring of methyl ethyl ketone (MEK)

This study was conducted to evaluate the usefulness of various biological parameters for monitoring of workers exposed to methyl ethyl ketone (MEK). Fifty male workers from a large magnetic videotape factory participated in this study. Personal air samples were collected using 3M organic vapor monitors and analysed for MEK by gas chromatography with flame ionisation detector (FID). 10 mL of urine; blood (1 mL) and exhaled air were also collected at the end of an 8-hour workshift. The headspace GC method was applied for measurement of urinary and blood MEK. MEK in expired air was analysed directly by using a GC/FID.The correlation coefficients (r) between environmental MEK and all other biological parameters measured show significant positive relationships. The r for environmental MEK and urine MEK was 0.84; for blood 0.73 and for breath 0.64. The correlation coefficients between blood and urine was 0.72; blood and breath was 0.88 and urine and breath 0.60. These findings suggest that measurements of unmetabolised MEK in blood, exhaled air and urine can be used for biological monitoring of MEK exposure. Nevertheless, laboratory methodological assessment is in favour of measuring urinary MEK as it is non-invasive and does not have to be analysed immediately after collection.     

Spectrophotometric determination of ferbam (iron(III) dimethyldithiocarbamate) in commercial sample and wheat grains using 4,7-diphenyl-1,10-phenanthroline after extraction into mesityl oxide

A procedure has been developed for the determination of iron(III) dimethyldithiocarbamate by converting it into iron(II)-bathophenanthroline complex, which is then extracted into mesityl oxide in the presence of potassium perchlorate. The absorbance is then measured at 534 nm against a reagent blank. Beer's law is obeyed over the concentration range 0.5-20 microg ml(-1) in the final solution. The method is sensitive, highly selective and can be used for the determination of ferbam in a commercial sample, and in mixtures with various dithiocarbamates (ziram, zineb, maneb, etc.) and in wheat grains.