Effect of methyl mercuric chloride treatment on haematological characteristics and erythrocyte morphology of Swiss mice

Effects of methyl mercuric chloride (MMC) on the blood parameters of Swiss mice (Mus musculus) were studied. The mice received an initial dose of MMC (24 mg kg(-1) body wt) as intraperitoneal injection followed by a second similar dose on the 14th day of the first dose administration. Significant (p < or = 0.001) decreases in haemoglobin content, red blood cell (RBC) count and haematocrit value were observed in the MMC injected mice when compared to the control mice. The effect of the second dose was severe, after which no significant recovery in the values of these parameters was observed. The result also showed a high degree of mercury accumulation in the blood of the MMC exposed mice. Interesting features were marked in the erythrocyte morphology of the exposed mice. An initial shrinkage followed by swelling of the cells was observed after each injection. The outline of the exposed cells was irregular with beak like or small finger like projections. Rupturing and disintegration of the erythrocyte membrane, leading to erythrolysis, were also noticed.     

Effect of shore position and environmental metal levels on body metal burdens in the barnacle, Elminius modestus

Body (thorax and prosoma) weight, shell growth, and Zn, Cu, Fe, Mn and Ca levels were measured in artificially settled Elminius modestus over a 14-month period following transfer to high, mid and low tide positions in the uncontaminated Menai Strait and two mid tide sites within a Zn and Cu polluted bay on the North West coast of Anglesey. Barnacles showed higher mortality and slower growth at the upper shore position than at any other site. There was no evidence of Zn and Cu regulation by the bodies or shells, and both seemed to reflect environmental levels. Body metal levels were lowest in early winter and the highest second year values were found in January (Zn), March (Cu, Fe) or May (Ca). Higher shore barnacles contained larger concentrations of Zn than mid or low tide animals. Differences in feeding activity and the amount of testes may account for these variations. Reciprocal transplants between polluted and 'clean' sites indicate that body Cu and Zn accumulation and loss was very rapid. Spatial and temporal changes in shell metal levels closely mirror that of the body.     

Air Pollution in Singapore: Its Multielemental Aspect as Measured by Nuclear Analytical Techniques

Aerosol samples were collected in 1994 in Singapore on two occasions: once in June during the normal meteorological conditions and later in October during a long haze period caused by the heavy forest fire in Indonesia. Filtration and impaction collection methods were used simultaneously so that detailed elemental analysis of bulk as well as of different size fractions could be performed. Accelerator based nuclear analytical techniques such as Particle Induced X-Ray Emission (PIXE), Rutherford Backscattering (RBS) and Nuclear Microscopy (NM) were used for analysis. These techniques are fast, truly multielemental and perfectly suited for routine analysis of a large number of aerosol samples. Typically all samples were analysed for the following 24 elements: Na, Mg, Al, Si, P, S, Cl, K, Ca, Ti, V, Mn, Cr, Fe, Co, Ni, Cu, Zn, Ga, As, Br, Rb, Sr and Pb. Detection limits for bulk analysis were generally below ng/m3 and for single particle analysis absolute detectable mass was approximately 10-17 g. Additionally, trace elements such as Cd, Sn, Sb and Ba whose characteristic X-ray lines were normally "obscured" by the lines of other more abundant elements, were detected when analysing by nuclear microscope in single particle mode.Judging by the average concentrations of lead and sulphur which are good indicators of industrial component of air pollution the situation in Singapore is satisfactory. Pb was typically found in concentrations of 5 to 50 ng/m3 and sulphur in concentrations of 1 to 2 µg/m3. These concentrations are well below limits set by the World Health Organisation (1500 ng/m3 and 40 µg/m3, respectively). On the other hand during the haze period the average concentrations of elements like S, K, Ti, V, Mn, Ni, As and Pb were found to be 3 to 6 times higher than usual. Results are presented and discussed.     

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.     

Suspended particulates and bioaerosols emitted from an agricultural non-point source

Suspended particulate and bioaerosol levels were measured at three sites downwind of an agricultural non-point source during the wheat harvesting season. Suspended particulates were detected at mean values ranging from 10000 to 2420 micrograms m-3 at distances of from 20 to 60 m downwind of the source, respectively. Airborne viable bacterial counts were recorded at mean values ranging between 10(4) and 10(6) colony forming units (cfu) m-3, whereas, Gram negative (Gram -ve) bacteria varied between 10(3) and 10(5) cfu m-3. Fungi levels were detected at mean values varying between 10(5) and 10(6) cfu m-3. However, streptomycetes were found at lower counts than those recorded for viable bacteria and fungi. Total viable bacteria, Gram -ve bacteria, fungi and streptomycetes associated hay fragments were determined at mean values of 1.5 x 10(6), 1.6 x 10(3), 2.2 x 10(4) and 6 x 10(3) cfu g-1 of hay, respectively. Cladosporium, white and red yeasts as well as Alternaria were the predominant airborne fungi, whereas, Alternaria was the dominant species associated with hay fragments. Pseudomonas, Acinetobacter and Enterobacteriaceae were the dominant Gram -ve bacteria. The most common fungal genera, such as Cladosporium and Fusarium (minor short axis), as well as Streptomyces species have an aerodynamic diameter (dae) of less than 5 microns, which can penetrate and deposit in the alveoli. Farmers and nearby residents are exposed to high levels of organic dust and bioaerosols during the wheat harvesting season. This may cause health problems in exposed persons based on toxic or allergic reactions.     

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.