Effects of elevated CO2 concentration on the polyamine levels of field-grown soybean at three O3 regimes

Effects of increased ozone (O3) and carbon dioxide (CO2) on polyamine levels were determined in soybean (Glycine max L. Merr. cv. Clark) grown in open-top field chambers. The chamber treatments consisted of three O3 regimes equal to charcoal filtered (CF), non-filtered (NF), and non-filtered plus 40 nl litre(-1) O3 and CO2 treatments equal to 350, 400 and 500 microl litre(-1) for a total of nine treatments. Leaf samples were taken at three different times during the growing season. Examination of growth and physiological characteristics, such as photosynthesis, stomatal resistance, and shoot weight, revealed that increasing CO2 ameliorated the deleterious effects of increased O3. Results from the initial harvest, at the pre-flowering growth stage (23 days of treatment), showed that increasing O3 at ambient CO2 caused increases in putrescine (Put) and spermidine (Spd) of up to six-fold. These effects were lessened with increased CO2. Elevated CO2 increased polyamines in plants treated with CF air, but had no effect in the presence of ambient or enhanced O3 levels. Leaves harvested during peak flowering (37 days of treatment) showed O3-induced increases in Put and Spd at ambient CO2 concentrations. However, increased CO2 levels inhibited this response by blocking the O3-induced polyamine increase. Leaves harvested during the pod fill stage (57 days of treatment) showed no significant O3 or CO2 effects on polyamine levels. Our results demonstrate that current ambient O3 levels induce the accumulation of Put and Spd early in the growing season and that further increases in O3 could result in even greater polyamine increases. These results are consistent with a possible antiozonant function for polyamines. The ability of increased CO2 to protect soybeans from O3 damage, however, does not appear to involve polyamine accumulation.     

Disappearance of bromopropylate residues in artichokes, strawberries and beans

Residues of Bromopropylate were determine in artichokes, strawberries and beans after foliar spray of acaricide at two rates. The rates used were 1 g/l formulated product (normal recommended) and 1.5 g/l. The residue levels of bromopropylate in the three crops after 14 days were lower than 0.7 ppm and did not exceed the Maximum Residual Level (MRL) recommended by FAO. In the artichokes and strawberries, the total concentration of residues decreased by 50% of the initial level after 2-3 days. Only trace levels of the bromopropylate residues (less than 0.01 ppm) were detected in the "hearts" of the artichokes. Bromopropylate residues in the green beans were also less than 0.8 ppm after the first day of foliar spraying. The kinetic of degradation occurred in two different steps. In the first step (4-6 days) the dissipation of bromopropylate was faster whereas in the second step (7-14 days) the loss of residues was much slower.     

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.     

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.     

Speciation of arsenic using solid phase extraction cartridges

Various solid phase extraction (SPE) cartridges were investigated for speciation of arsenite [As(III)], arsenate [As(v)], monomethylarsonic acid (MMA) and dimethylarsinic acid (DMA). Cartridges containing different types of sorbent materials were tested for arsenic retention and elution characteristics. Alumina cartridges were found to completely retain all the four target arsenic species, and are suitable for removal and preconcentration purposes. For speciation analysis, different arsenic species were separated on the basis of their selective retention on and elution from specific cartridges. DMA was retained on a resin-based strong cation exchange cartridge and eluted with 1.0 M HCl. MMA and As(v) were both retained on a silica-based strong anion exchange cartridge and sequentially eluted with 60 mM acetic acid (for MMA) and 1.0 M HCl [for As(v)]. As(III) was not retained on either cartridge and remained in solution. Arsenic species in solution and those eluted from the cartridges were subsequently quantified by using flow injection with hydride generation atomic fluorescence spectrometry (FI-HGAFS) and hydride generation atomic absorption spectrometry (FI-HGAAS). A detection limit of 0.05 microg L(-1) arsenic in water sample was achieved using HGAFS. An application of the method was demonstrated at a drinking water treatment facility. As(III) and As(v) species were determined in water at various stages of treatment. The method is suitable for routine determination of trace levels of arsenic in drinking water to comply with more stringent environmental regulations.     

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.