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.     

The efficacy of protoporphyrin as a predictive biomarker for lead exposure in canvasback ducks: Effect of sample storage time

We used 363 blood samples collected from wild canvasback dueks (Aythya valisineria) at Catahoula Lake, Louisiana, U.S.A. to evaluate the effect of sample storage time on the efficacy of erythrocytic protoporphyrin as an indicator of lead exposure. The protoporphyrin concentration of each sample was determined by hematofluorometry within 5 min of blood collection and after refrigeration at 4 °C for 24 and 48 h. All samples were analyzed for lead by atomic absorption spectrophotometry. Based on a blood lead concentration of 0.2 ppm wet weight as positive evidence for lead exposure, the protoporphyrin technique resulted in overall error rates of 29%, 20%, and 19% and false negative error rates of 47%, 29% and 25% when hematofluorometric determinations were made on blood at 5 min, 24 h, and 48 h, respectively. False positive error rates were less than 10% for all three measurement times. The accuracy of the 24-h erythrocytic protoporphyrin classification of blood samples as positive or negative for lead exposure was significantly greater than the 5-min classification, but no improvement in accuracy was gained when samples were tested at 48 h. The false negative errors were probably due, at least in part, to the lag time between lead exposure and the increase of blood protoporphyrin concentrations. False negatives resulted in an underestimation of the true number of canvasbacks exposed to lead, indicating that hematofluorometry provides a conservative estimate of lead exposure.The U.S. Government's right to retain a non-exclusive, royalty-free licence in and to any copyright is acknowledgedDeceased     

Cadmium and zinc source assessment in the Sepetiba Bay and basin region

Industrial and weathering inputs of Cd and Zn to the Sepetiba Bay and basin were assessed, based on production parameters obtained from local environment and industry authorities, and literature data. The results are compared with similar evaluations from other coastal regions and field data obtained in measuring Zn and Cd transport by rivers, direct run-off and atmospheric deposition in the region. Cadmium and zinc inputs to the bay increased by three orders of magnitude relative to pre-industrial fluxes and presently reach up to 1.6 and 180 tonnes per year for Cd and Zn, respectively, which represents a large input-to-area ratio, and explains the high concentration of these metals previously reported in the estuarine biota and sediments of Sepetiba Bay. Industrial activities, mainly metallurgical and chemical, comprise 94% and 84% of the total Cd and Zn inputs to the Bay. This figure identifies the point sources as being responsible for the environmental contamination and for regional poisoning risks.     

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.     

Microbiological characteristics in a zero-valent iron reactive barrier

Zero-valent iron (Fe⁰)-based permeable reactive barriertreatment has been generating great interest for passivegroundwater remediation, yet few studies have paid particularattention to the microbial activity and characteristics withinand in the vicinity of the Fe⁰-barrier matrix. The presentstudy was undertaken to evaluate the microbial population andcommunity composition in the reducing zone of influence byFe⁰ corrosion in the barrier at the Oak Ridge Y-12 Plantsite. Both phospholipid fatty acids and DNA analyses were usedto determine the total microbial population and microbialfunctional groups, including sulfate-reducing bacteria,denitrifying bacteria, and methanogens, in groundwater andsoil/iron core samples. A diverse microbial community wasidentified in the strongly reducing Fe⁰ environment despitea relatively high pH condition within the Fe⁰ barrier (up topH 10). In comparison with those found in the backgroundsoil/groundwater samples, the enhanced microbial populationranged from 1 to 3 orders of magnitude and appeared to increase from upgradient of the barrier to downgradient soil. Inaddition, microbial community composition appeared to change overtime, and the bacterial types of microorganismsincreased consistently as the barrier aged. DNA analysisindicated the presence of sulfate-reducing and denitrifyingbacteria in the barrier and its surrounding soil. However, theactivity of methanogens was found to be relatively low,presumably as a result of the competition by sulfate/metal-reducing bacteria and denitrifying bacteria because of the unlimited availability of sulfate and nitrate in the site groundwater. Results of this study provide evidenceof a diverse microbial population within and in the vicinity ofthe iron barrier, although the important roles of microbial activity, either beneficially or detrimentally, on the longevityand enduring efficiency of the Fe⁰ barriers are yet to be evaluated.     

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.     

The analysis of monitoring data with the aid of time-series analysis

Methods derived from time-series analysis are proposed for processing monitoring data. The necessity for the use of these methods is demonstrated. In a case study time-series analysis was applied to assess the impact of the closure of the Grevelingen estuary (S. W. Netherlands) in 1971 on a local wintering population of Oystercatchers (Haematopus ostralegus) in the adjacent Oosterschelde estuary.Communication No. 328 of the Delta Institute for Hydrobiological Research.