Trace metal (Cd,Cu, Pb,Zn) fractionation in urban-industrial soils of Ust-Kamenogorsk (Oskemen), Kazakhstan—implications for the assessment of environmental quality

Ust-Kamenogorsk is one of the largest cities and industrial centers in Kazakhstan. Non-ferrous metallurgy (Zn–Pb smelter) has acted as a predominating industrial branch in the city since late 1940s. The industrial plants are situated directly adjacent to the residential area of the city which creates grievous ecotoxicological hazard. In the present paper, we aimed at assessing the trace metal pollution of top soils in Ust-Kamenogorsk and its potential threats to the local population. The top soils were sampled at 10 sites throughout the city center. We determined the physical and chemical properties of soils as well as the contents of Cd, Cu, Pb, and Zn. In addition, the soil samples were subjected to a five-step sequential extraction to ascertain the fractionation of trace metals. On this basis, we calculated the geoaccumulation index (I_geo) and pollution load index (PLI) and assessed bioavailability of the elements. From our data, it emerged that the soils displayed a strong polymetallic pollution. PLI was as high as 33.4. Throughout the city, the trace metal contents exceeded the geochemical background and allowable values for residential, recreational, and institutional areas. The I_geo obtained were 3.7–6.5 for Cd, 1.5–4.7 for Cu, 2.8–5.7 for Pb, and 2.6–4.6 for Zn. The soils in Ust-Kamenogorsk displayed extremely high contamination with Cd, moderate to strong contamination with Pb and Zn, and low to moderate contamination with Cu. Cd and Pb were found to be the most bioavailable elements. The mobility of trace metals in the soils changed in the order Cd > Pb > Zn > Cu.     

Microbiological and physical–chemical water quality of the rice fields in Sinos River’s basin, Southern Brazil

In this study, we evaluate spatial and temporal variations of the water’s quality used in rice fields. Every 15 days during the different phases of cultivation of the rice—vegetative, reproductive, and maturity—samples were collected from the main irrigation channel, from the surface water in the field, and from the excess-water drainage channel. The differences in the values of 13 variables were analyzed by the analysis of variance system and by the Principal Component Analysis (PCA) technique. The results demonstrate that the values observed for the presence of total coliforms, heat-tolerant coliforms, and pH were higher in the irrigation water and that the calcium and magnesium components were greater in the drainage water. The PCA results indicate that three groups of variance exist and that these three account for 77 % of the observed variances. The first principal component, (39 % of the variances), includes the variables pH, phosphorus, potassium, carbon, and turbidity; the second (28.1 %), calcium, magnesium, and conductivity; while the third accounts for only 9.9 % of the variation and incorporates the variable biological thermotolerant coliforms. The spatial pattern resulting from the distribution of the sampling locations as regards the first two principal components indicates a difference between the irrigation and drainage waters. The variables of the first and third items (except for the turbidity in the second component) reach higher values in the irrigation water, while the variables associated with the second component have higher values in the drainage water. The information provided is important for the analysis of the influence exercised by plantation management decisions on the microbiological, physical, and chemical quality of the water. The results confirm the ability of paddy rice field to filter out some of the chemicals and coliforms from the irrigation water as it passes through the agro ecosystem.     

Water monitoring and treatment for drinking purposes in 2004 tsunami affected area—Ban Nam Khem, Phang Nga, Thailand

University of Brescia and Mahidol University of Bangkok developed a project in Phang Nga province (Thailand), the most damaged by 2004 tsunami. In particular, the study, performed between April and May 2006, dealt with the surface and ground water monitoring in Ban Nam Khem village and the experimental evaluation of possible drinking treatment alternatives. The monitoring highlighted that saline content in the tsunami affected area is decreasing but still very high (conductivity presented values up to 2,600 and 6,230 microS/cm in ground and surface water, respectively); hence, advanced and complicated processes such as reverse osmosis should be adopted to treat such water for drinking purposes. Waiting for ground water salinity to assume acceptable values, activities for the reduction of its organic and microbiological contamination will be started. However, it has to be underlined that the diffusion of drinking water to a greater part of population can be obtained only through the realization of new centralised treatment plants and the improvement of existing ones (serving at the moment about 20% of inhabitants).     

Analysis of long-term water quality for effective river health monitoring in peri-urban landscapes—a case study of the Hawkesbury–Nepean river system in NSW, Australia

The Hawkesbury–Nepean River (HNR) system in South-Eastern Australia is the main source of water supply for the Sydney Metropolitan area and is one of the more complex river systems due to the influence of urbanisation and other activities in the peri-urban landscape through which it flows. The long-term monitoring of river water quality is likely to suffer from data gaps due to funding cuts, changes in priority and related reasons. Nevertheless, we need to assess river health based on the available information. In this study, we demonstrated how the Factor Analysis (FA), Hierarchical Agglomerative Cluster Analysis (HACA) and Trend Analysis (TA) can be applied to evaluate long-term historic data sets. Six water quality parameters, viz., temperature, chlorophyll-a, dissolved oxygen, oxides of nitrogen, suspended solids and reactive silicates, measured at weekly intervals between 1985 and 2008 at 12 monitoring stations located along the 300 km length of the HNR system were evaluated to understand the human and natural influences on the river system in a peri-urban landscape. The application of FA extracted three latent factors which explained more than 70 % of the total variance of the data and related to the ‘bio-geographical’, ‘natural’ and ‘nutrient pollutant’ dimensions of the HNR system. The bio-geographical and nutrient pollution factors more likely related to the direct influence of changes and activities of peri-urban natures and accounted for approximately 50 % of variability in water quality. The application of HACA indicated two major clusters representing clean and polluted zones of the river. On the spatial scale, one cluster was represented by the upper and lower sections of the river (clean zone) and accounted for approximately 158 km of the river. The other cluster was represented by the middle section (polluted zone) with a length of approximately 98 km. Trend Analysis indicated how the point sources influence river water quality on spatio-temporal scales, taking into account the various effects of nutrient and other pollutant loads from sewerage effluents, agriculture and other point and non-point sources along the river and major tributaries of the HNR. Over the past 26 years, water temperature has significantly increased while suspended solids have significantly decreased (p?<?0.05). The analysis of water quality data through FA, HACA and TA helped to characterise the key sections and cluster the key water quality variables of the HNR system. The insights gained from this study have the potential to improve the effectiveness of river health-monitoring programs in terms of cost, time and effort, particularly in a peri-urban context.     

Trade-off between water pollution prevention,agriculture profit,and farmer practice—an optimization methodology for discussion on land-use adjustment in China

Agricultural decision-making to control nonpoint source (NPS) water pollution may not be efficiently implemented, if there is no appropriate cost-benefit analysis on agricultural management practices. This paper presents an interval-fuzzy linear programming (IFLP) model to deal with the trade-off between agricultural revenue, NPS pollution control, and alternative practices through land adjustment for Wuchuan catchment, a typical agricultural area in Jiulong River watershed, Fujian Province of China. From the results, the lower combination of practice 1, practice 2, practice 3, and practice 7 with the land area of 12.6, 5.2, 145.2, and 85.3 hm², respectively, could reduce NPS pollution load by 10 %. The combination yields an income of 98,580 Chinese Yuan/a. If the pollution reduction is 15 %, the higher combination need practice 1, practice 2, practice 3, practice 5, and practice 7 with the land area of 54.4, 23.6, 18.0, 6.3, and 85.3 hm², respectively. The income of this combination is 915,170 Chinese Yuan/a. The sensitivity analysis of IFLP indicates that the cost-effective practices are ranked as follows: practice 7 > practice 2 > practice 1 > practice 5 > practice 3 > practice 6 > practice 4. In addition, the uncertainties in the agriculture NPS pollution control system could be effectively quantified by the IFLP model. Furthermore, to accomplish a reasonable and applicable project of land-use adjustment, decision-makers could also integrate above solutions with their own experience and other information.     

Community air monitoring for pesticides—part 2: multiresidue determination of pesticides in air by gas chromatography,gas chromatography–mass spectrometry,and liquid chromatography–mass spectrometry

Two multiresidue methods were developed to determine pesticides in air collected in California. Pesticides were trapped using XAD-4 resin and extracted with ethyl acetate. Based on an analytical method from the University of California Davis Trace Analytical Laboratory, pesticides were detected by analyzing the extract by gas chromatography–mass spectrometry (GC-MS) to determine chlorothalonil, chlorthal-dimethyl, cycloate, dicloran, dicofol, EPTC, ethalfluralin, iprodione, mefenoxam, metolachlor, PCNB, permethrin, pronamide, simazine, trifluralin, and vinclozolin. A GC with a flame photometric detector was used to determine chlorpyrifos, chlorpyrifos oxon, diazinon, diazinon oxon, dimethoate, dimethoate oxon, fonophos, fonophos oxon, malathion, malathion oxon, naled, and oxydemeton. Trapping efficiencies ranged from 78 to 92 % for low level (0.5 μg) and 37–104 % for high level (50 and 100 μg) recoveries. Little to no degradation of compounds occurred over 31 days; recoveries ranged from 78 to 113 %. In the California Department of Food and Agriculture (CDFA) method, pesticides were detected by analyzing the extract by GC-MS to determine chlorothalonil, chlorpyrifos, cypermethrin, dichlorvos, dicofol, endosulfan 1, endosulfan sulfate, oxyfluorfen, permethrin, propargite, and trifluralin. A liquid chromatograph coupled to a MS was used to determine azinphos-methyl, chloropyrifos oxon, DEF, diazinon, diazinon oxon, dimethoate, dimethoate oxon, diuron, EPTC, malathion, malathion oxon, metolachlor, molinate, norflurazon, oryzalin, phosmet, propanil, simazine and thiobencarb. Trapping efficiencies for compounds determined by the CDFA method ranged from 10 to 113, 22 to 114, and 56 to 132 % for 10, 5, and 2 μg spikes, respectively. Storage tests yielded 70–170 % recovery for up to 28 days. These multiresidue methods represent flexible, sensitive, accurate, and cost-effective ways to determine residues of various pesticides in ambient air.