A Variance Estimator for Constrained Estimates of Change in Relative Categorical Frequencies

Consistent estimators of change and state becomes an issue when sample data come from a mix of permanent and temporary observation units. A joint maximum likelihood estimator of state and change creates estimates of state that depend on antecedent viz. posterior survey results and may differ from estimates of state derived from a single-date analysis of the sample data. A constrained estimator of change in relative categorical frequencies that eliminates this potential inconsistency is proposed and a model based estimator of their sampling variance is developed. The performance of the constrained estimator is quantified against six criteria and a joint maximum likelihood estimator in simulated sampling from 15 populations with three combinations of permanent and temporary samples, four to six categorical class attributes, and constant size between sampling dates. Bias of the constrained estimators was negligible but larger than for joint maximum likelihood estimators. Mean absolute deviations and variances of constrained estimators were generally at par with the joint estimators. Constrained estimators of root mean square errors and achieved coverage of nominal confidence intervals of constrained estimators were occasionally better. A generalized variance function for the constrained estimates of change is provided as a computational shortcut.     

Development of monitoring technology for airborne particulate matter

Particulate matter suspended in the air has adverse effects onhuman health. Its level of concentration is an important parameter in evaluating the degree of hazard it poses to the atmosphere. Conventional methods used in measuring particulatematter are often filter-based, which indicates some disadvantagesbecause such a base requires labor and time. In this study, to achieve real-time measurements, a new electrical method was developed for measuring PM10 and PM2.5 concentrations. The basicprinciple is to electrically charge particles passing through thePM inlet using a corona charger and measure the currents createdby charged particles to obtain the number concentration of particulate matter. A new type inlet based on the particle cupimpactor configuration was designed and its performance was evaluated. A unipolar diffusion charger was developed and thecharger's efficiency was determined experimentally in terms ofPn, which represents the penetration through the charger,P, times the average charge number acquired by a particle,n, for different particle sizes. The correlation was constructed between the PM10 (or the PM2.5) mass concentrationsand the electrical currents due to particles, which were chargedby the diffusion charger.     

Chlorinated Hydrocarbons in Livers of American Mink (Mustela vison) and River Otter (Lutra canadensis) from the Columbia and Fraser River Basins, 1990–1992

We investigated chlorinated hydrocarbon contaminants in aquatic mustelid species on the Fraser and Columbia Rivers of northwestern North America. Carcasses of river otter (Lutra canadensis) (N=24) and mink (Mustela vison) (N=34) were obtained from commercial trappers during the winters of 1990–91 and 1991–92. Pooled liver samples were analyzed for organochlorine pesticides, polychlorinated biphenyls (PCBs), including non-ortho congeners, polychlorinated dibenzo-p-dioxins (PCDDs) and dibenzofurans (PCDFs). Most samples contained detectable concentrations of DDE, PCBs, although there was substantial variability in patterns and trends among neighboring samples. Concentrations of DDE were in some mink and several otter samples from the lower Columbia River elevated (to 4700 g/kg wet weight); excluding one mink sample from the Wenatchee area, mean DDE levels generally decreased between 1978–79 and 1990–92. PCBs were present in all samples. PCB concentrations in otter livers collected from the lower Columbia were ten-fold lower than measured a decade previously; nevertheless, a sample taken near Portland had a mean concentration of 1500 g/kg, within a range of concentrations associated with reproductive effects in captive mink. Concentrations of 2,3,7,8-TCDD and TCDF were generally below detection limits, except for one otter collected near a pulp mill at Castlegar, on the upper Columbia, with 11 ng TCDD/kg in liver. Elevated concentrations of higher chlorinated PCDD/Fs, probably resulting from use of chlorophenolic wood preservatives, were found in both species; one otter sample from the lower Columbia had 2200 ng OCDD/kg. International TCDD toxic equivalent levels in mink (31 ng/kg) and otter (93 ng/kg) from the lower Columbia River approached toxicity thresholds for effects on reproduction in ranch mink.     

State estimation in wastewater engineering: Application to an anaerobic process

The use of an extended Kalman filter for state estimation in biological wastewater treatment processes is discussed. The application of the technique requires an adequate mechanistic dynamic model and the identification and modelling of the major sources of stochastic disturbances in the process. The filter allows the on-line tracking of process variables which are not directly measurable. The use of an extended Kalman filter is illustrated through a simulated application to a high rate anaerobic wastewater treatment process.     

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.     

Tree species in relation to soil moisture regime in northwestern Ontario,Canada

Selected data on site, vegetation cover, and soil, including soil moisture regime (SMR), were collected from 2 167 field plots in northwestern Ontario, Canada. SMR provides an estimate of an averaged, annualized soil moisture supply throughout a complete vegetation cycle. SMR is based upon a relative scale that subjectively ranks sites from , 0, and 1 through 9 along a soil moisture continuum which relates to a dry to wet gradient. SMR may be generally correlated to tree growth, stand composition, degree of competition, nutrient availability and overall site quality.This paper reports on relationships between SMR and major tree species. Results highlight relationships between SMR class and the broad ecological ranges of several tree species. In northwestern Ontario, the determination of SMR can help resource managers to better understand the ecology of boreal sites.     

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.     

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.     

Characterization and removal of odors from refuse material

Odorous gases emitted from refuse wastes were scrubbed through activated carbon columns until odor breakthrough occured. Refuse air samples were collected at the influent and effluent ports of the columns for analysis on a gas chromatograph-mass spectrometric system and for odor determination by dynamic olfactometry. Chromatographic profiles of the gases emitted from refuse material were obtained and volatiles identified included carboxylic acids and some sulphur compounds. Organoleptic tests with a dynamic olfactometer revealed that the odor concentration of refuse air averaged about 50 sou m^–3. The adsorption capacities of four commercial grades of activated carbon for refuse odor were evaluated and compared. Results indicated that chemically impregnated activated carbons that are commonly used for odor control at sewerage facilities were less cost effective than non-chemically impregnated carbons.