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.     

Application of cryofocusing hydride generation and atomic fluorescence detection for dissolved mercury species determination in natural water samples

The concentration levels of mercury (Hg) species in natural water samples are usually low. Consequently, accurate analysis with low detection limits is still a major problem. In this work, a method was applied for the simultaneous direct determination of dissolved mercury species in water samples by on-line hydride generation (HG), cryogenic trapping (CT), gas chromatography (GC) and detection by atomic fluorescence spectrometry (AFS). The suitability of the method for real samples with different organic matter and chloride contents was evaluated by recovery experiments in synthetic and natural spiked water samples. The HG method was compared with other current available methods for mercury analysis with respect to the different fraction of mercury analysed, i.e. 'reactive', 'reducible' or total. HG derivatization and SnCl2 reduction (with and without previous oxidation with BrCl) were applied to synthetic and natural (spiked and non-spiked) water samples. The influence of chloride and dissolved organic matter concentrations was studied. The results suggest that the HG procedure is suitable for the simultaneous determination of Hg2+ and MeHg+ in surface water samples. Inorganic mercury analysed by HG (i.e. reducible) is close to the total inorganic mercury.     

Laboratory-polluted soils: a methodological approach to establish equilibrium conditions for different metal chemical forms in soils

An approach based on the number of extractions performed over time was applied to study the time necessary to attain equilibrium conditions between the different chemical forms present in two natural soils laboratory-loaded with heavy metals (Cu(II), Pb(II), Zn(II)). The influence of some soil parameters, such as pH value, cation exchange capacity and organic matter content, on the equilibrium time was evidenced both by the different nature of the soils and by the treatment of soils with paper mill sludge. Equilibrium conditions were determined by studying the metal partitioning in the soil on a case by case basis. The behaviour of the three metals was not the same, and the conditions of equilibrium among the different chemical forms were the result of the amount of heavy metals added as well as of the nature of the soil.     

Working backwards to move forwards: Graph-based connectivity metrics for reserve network selection

In this paper we apply graph theory in a reserve selection exercise to explore the tradeoffs between maintaining connectivity and minimizing the total area of a protected area network. Rather than focus on a single organism, we used a multi-species approach and looked at the tradeoff curves for organisms with varying dispersal abilities. We first generated the tradeoff curves using a graph-based metric to determine the importance of individual patches for maintaining connectivity. We then performed an analogous set of analyses using patch size as a surrogate measure of importance.     

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.     

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.     

Effect of Humic Acid on the Bioavailability of γ-Hexachlorocyclohexane in Marsilea Minuta (L.)

Effect of various concentrations of humic acid (0.2 to 1%) on thebioavailability of -HCH in vegetative clones of theaquatic fern Marsilea minuta was studied in a staticexperimental bioassay system on different photoperiods. Additionof humic acid showed the reduction in the bioavailability of-HCH in all the photoperiods (72 hr light to 144 hrlight) at the interval of 16 hr light (L) and 8 hr dark (D) inboth aerial and submerged portion as compared to controlindicating its protective role in toxicity.     

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.