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.     

Song as an attractant for male and female European starlings,and the influence of song complexity on their response

Summary We tested the hypothesis that song attracts females and repels males in the European starling. We broadcast recorded song from speakers attached to nestboxes, while paired boxes with silent speakers served as controls. As predicted, females were attracted to the song boxes. Contrary to prediction, males were also attracted to the `song' boxes. Singing by male starlings may be costly because it attracts competitors for limited nesting sites, but the cost cannot be avoided due to the need to attract a mate. In a second experiment simple song (composed of 20 different phrase types) and complex song (40 phrase types) were played simultaneously. More males were captured at boxes where simple song was played. Song complexity may function as an indicator of male quality and be used by male starlings to assess potential competitors.     

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.     

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.     

Parameter values to model the soil ingestion pathway

Soil ingestion is an important exposure pathway for contaminants that are not otherwise very mobile in the environment. Health of both humans and animals can be affected. This paper summarizes the literature and recommends models and probabilistic parameter values for risk assessment applications. Models of the pathway require estimates of the amounts of soil ingested, the concentration of contaminants relative to the original soil, and the bioavailability in the gut of the contaminants ingested with soil. Using a lead-contaminated sandbox as an example, the modelling recommendations suggest that a child typically may consume 50 mg d^–1 of the sandbox soil, the soil ingested will have a tenfold higher lead concentration than the original soil, and the lead will be as bioavailable as if ingested as inorganic lead in water.The Canadian Government right to retain a non-exclusive, royalty free licence in and to any copyright is acknowledged.     

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.