Reservoir water quality: a case from Jordan

Jordan relies heavily on reservoirs building and development to cope with water supply challenges, where monitoring and assessment of reservoir water quality are critically important for the sustainable use of these water supplies. Mujib Dam is an important water supply source in central western Jordan. Evaluation of water quality parameters and their spatial distributions (vertical and horizontal) showed near-neutral pH values with nearly similar values from surface to bottom. The vertical profile of DO and TDS in the dammed reservoir showed slight decreasing trends with increasing depth. Although Ca, Mg, Na, and K concentrations varied slightly with depths, their variations showed no trends. Similarly, the vertical and horizontal distribution patterns of Cl, SO₄, HCO₃, NO₃, and PO₄ in Mujib reservoir water showed insignificant variations in surface water layer and relatively unchanged values or decreasing trends through the water column. Higher values of TN have been observed, especially in the western part, suggesting that agricultural activities and livestock farming in the upstream catchment are impacting water quality. Results revealed that weathering and dissolution of rocks are the major source of water chemistry. The majority of trace metal levels (Cd, Cr, Cu, Fe, Mn, Pb, Zn, Co, Ni, Sr, and B) in water showed relatively similar surface and bottom values. The concentrations of COD and BOD₅ in surface water were relatively low with higher concentrations observed in the northwestern corner, coincided with higher levels of chlorophyll a. The average ratio of TN to TP in surface water suggests that phosphorus is the limiting factor for the algal blooms, whereas the average chlorophyll a level in surface water indicates oligo-mesotrophic water.     

Estimation of soil specific surface area using some mechanical properties of soil by artificial neural networks

Soil specific surface area (SSA) is an important property of soil. Depending on the measurement techniques, determination of the SSA is costly and time consuming. Hence, a limited number of studies have been conducted to predict the SSA from the soil variables. In this study, the soil samples were taken from the literature. Fractal parameters (FP) were calculated by the model of Bird et al. (European Journal of Soil Science 51, 55–63, 2000) used as the input variables to predict the SSA. Some studies have been carried out on the prediction capability of the different parameters using the artificial neural networks (ANNs). The ANNs were further used and 20 models were developed to investigate the value of input variables to predict the SSA. The results showed that the PTF13 (RMSE?=?0.13) and PTF18 (RMSE?=?0.13) with the input variables of particle-size distribution and Atterberg limits revealed better performance than the other PTFs (in the training step). It is because of the fact that free swelling index (FSI) and Atterberg limits were closely correlated to the soil clay mineralogy as one of the important factors controlling the SSA. In general, this results demonstrated that the PTF9 with the variables of sand, clay, plastic limit (PL), liquid limit (LL), and FSI showed the best (RMSE?=?0.37) results in the estimation of the SSA. In conclusion, there was not a strong correlation between the soil mechanical properties and SSA but also ANNs were a suitable method to predict the SSA from the soil variables.     

FIA-coupled spectrophotometric method for determination of Cr (VI) traces in natural waters: application of in-line dissolution of 1,5-diphenylcarbazide after heat treatment and activated alumina as adsorbent for preconcentration

This work proposes the quantification of Cr (VI) ions in natural waters in trace level, using activated alumina (Al₂O₃) as preconcentration support, controlled in-line dissolution of the solidified chromophore diphenylcarbazide after heat treatment and spectrophotometric detection. The manifold ensures high sensitivity of analytical response, good repeatability, and stability. In this work, optimization of experimental conditions of a flow injection system was chosen as the parameters for greater sensitivity and better selectivity. The selected optimized conditions were 0.30 mol L^?1 for H₂SO₄ concentration, system flow rate as 0.40 mL min^?1, sample injection volume of 192.50 μL, 2 min for preconcentration time, and 0.10 mol L^?1 for eluent concentration. The analytical curves obtained for real sample analysis show linear range from 0.192 to 0.961 μM, linear correlation coefficient R?=?0.9997 and LOD?=?0.024 μM. The preconcentration factor of about four times was obtained through the passage of 800 μL of a standard solution containing 0.961 μM of Cr (VI) through mini-column of preconcentration followed by elution at 192.5 μL of NH₄OH 0.1 mol L^?1 solution. The solid chromogenic reagent presented high durability (weeks in daily use with mass of 0.0993 g) and good reproducibility in analytical signal. The reactivation of the mini-column of alumina should be executed after ten injections of eluent, using 800 μL of HCl 0.02 mol L^?1 solution in flow through the same. Each cycle of injection and elution of the sample takes about 5 min on the proposed terms. Despite the length of each cycle still be high, low concentrations can be detected using a technique of relatively low cost. This is due in part, the association dissolution of the chromogenic reagent directly in the line and the preconcentration step. Another important factor is the economy of reagent chromogenic, low generation of reject contributing to better quality of the environment, and the high potential for applications to work in field.     

Assessment using CFD of the wind direction on the air discharges caused by natural ventilation of a poultry house

Air inside poultry houses must be removed on a regular basis to prevent excess of heat, particles and noxious gases that can imperil animals. To cope with this issue, natural ventilation could be an effective method when assisted by accurate predictions. This study investigates air discharges caused by natural ventilation of a poultry house by means of a three-dimensional computational fluid dynamics (CFD) model. It solves the governing equations of momentum, heat and mass transport, radiative transfers and animal-generated heat. Wind directions of 0°, 36° and 56° (0° corresponds to a wind blowing perpendicular to the ridgeline) were investigated; the CFD model predictions achieved a RMSE of 1.2 °C and 0.6 g[H₂O] kg^?1 [dry air] for internal temperature and absolute humidity, respectively, when air blew with an angle of 36°. Air renewal rates (ARR) were 39.5 (±?1.9), 34.9 (±?2.2) and 33.6 (±?1.7) volumes of the building per hour, when air blew at 0°, 36° and 56°, respectively. Such ARR predictions served to know how the gases contained in air would likely spread downstream from the building in order to define regions of potentially high gas concentration that could endanger neighbouring habitable facilities.     

Water quality index for agricultural systems in Northwest Uruguay

Agricultural systems have experienced rapid expansion and intensification in the last several decades. In Uruguay, since the beginning of 2000, the most common cropping systems have included soybeans. Currently, this crop is expanding towards lowlands traditionally occupied by rice in rotation with pastures. However, the environmental effects of agricultural intensification and diversification are not well known. Thus, some indices have been proposed to quantify the changes in agricultural production systems and assess water quality. The main goal of this study was to develop a water quality index (WQI) to assess the impacts of the diversification of rice production systems in northwest Uruguay. The study was carried out in an agricultural basin where other summer crops have been incorporated in the rice-pasture sequence. Agriculture intensification and crop diversification indices were calculated using information provided by farmers. Water samples were collected downstream of the production area before crop sowing and after crop harvest (2008–2009 to 2010–2011 and 2016–2017 to 2017–2018). Biochemical oxygen demand, nitrates, total phosphorus, fecal coliforms, and total suspended solids were the variables that mainly explained the effects of the agricultural activities on water quality. The proposed water quality index included these unweighted variables, which allowed for the pre-sowing and post-harvest to be differentiated, as well as the degree of diversification. Therefore, the proposed WQI constitutes a tool that can be used to evaluate the water quality in an agricultural basin. Likewise, it can be used to select agricultural sequences that generate the least possible impacts on the associated water resources.     

Bioremediation of tannery effluent by Cr- and salt-tolerant bacterial strains

Microorganisms have great potential to control environmental pollution, particularly industrial sources of water pollution. Currently, leather industry is regarded as the most polluting and suffering from negative impacts due to the pollution it adds to the environment. Chromium, one of the hazardous pollutants discharged from tanneries, is highly toxic and carcinogenic in nature. Effective treatment of tannery effluent is a dire need of the era as a part of environmental management. Among all the wastewater treatment technologies, bioremediation is the most effective and environment-friendly tool to manage the water pollution. The present study evaluated the potential of 11 previously isolated bacterial strains, tolerant to high concentrations of salts and Cr for the bioremediation of tannery effluent. Among all the tested strains, Enterobacter sp. HU38, Microbacterium arborescens HU33, and Pantoea stewartii ASI11 were found most effective in reducing biological oxygen demand (BOD), chemical oxygen demand (COD), total dissolved solids (TDS), total suspended solids (TSS), and chromium (Cr) 70, 63, 57, 87, and 54%, respectively, of tannery effluent and proliferated well under highly toxic conditions, at 9 days of incubation. The pollutant removal efficacy of these bacterial strains can be improved by extending the incubation period or by increasing the amount of inoculum.     

Use of water quality index and multivariate statistical techniques for the assessment of spatial variations in water quality of a small river

Rapid urban development has led to a critical negative impact on water bodies flowing in and around urban areas. In the present study, 25 physiochemical and biological parameters have been studied on water samples collected from the entire section of a small river originating and ending within an urban area. This study envisaged to assess the water quality status of river body and explore probable sources of pollution in the river. Weighted arithmetic water quality index (WQI) was employed to evaluate the water quality status of the river. Multivariate statistical techniques namely cluster analysis (CA) and principal component analysis (PCA) were applied to differentiate the sources of variation in water quality and to determine the cause of pollution in the river. WQI values indicated high pollution levels in the studied water body, rendering it unsuitable for any practical purpose. Cluster analysis results showed that the river samples can be divided into four groups. Use of PCA identified four important factors describing the types of pollution in the river, namely (1) mineral and nutrient pollution, (2) heavy metal pollution, (3) organic pollution, and (4) fecal contamination. The deteriorating water quality of the river was demonstrated to originate from wide sources of anthropogenic activities, especially municipal sewage discharge from unplanned housing areas, wastewater discharge from small industrial units, livestock activities, and indiscriminate dumping of solid wastes in the river. Thus, the present study effectively demonstrates the use of WQI and multivariate statistical techniques for gaining simpler and meaningful information about the water quality of a lotic water body as well as to identify of the pollution sources.     

石膏浆液旋流器的分离性能实验研究

通过理论分析及工程经验对石灰石/石膏法烟气脱硫工艺中石膏浆液脱水系统的旋流器进行优化设计,在与工业实际相近的操作条件下,优选出了一根综合性能较好的旋流器。考察了该旋流器的压力、流量与分离效率之间相互关系,与常规石膏浆液旋流器的分级效率进行了比较,确定了最佳操作条件。结果表明,旋流器的进口流量随着进出口压力差的增大而增大,分离效率随着流量增加先上升后下降。在进口硫石膏颗粒平均粒径为24μm,流量为11.8~14.8 m3/h时,分离效率在85%以上,底流出口10μm、15μm以下的颗粒分别占底流出口颗粒总体积的1%、10%左右,起到了很明显的分级浓缩作用,分离性能也优于常规使用的石膏浆液旋流器。     

厌氧氨氧化ASBR中亚硝氮和氨氮降解规律研究

采用生物膜ASBR反应器,研究了厌氧氨氧化反应过程中亚硝氮与氨氮降解速度的变化规律。结果表明,降解过程主要分为2个阶段:速度上升期(0~30 min)和速度下降期(30~150 min)。一阶指数衰减模型的模拟结果表明,20 min以后亚硝氮、氨氮降解速度逐渐减少,亚硝氮降解速度始终高于氨氮降解速度,但是两者差值随时间逐渐减少。     

CPB改性沸石对磷酸盐的吸附-解吸性能研究

采用溴化十六烷基吡啶(CPB)对天然沸石进行改性,并考察了CPB改性沸石对磷酸盐的吸附-解吸性能。结果表明,CPB改性沸石对磷酸盐具备一定的吸附能力,且吸附行为满足Langmuir等温吸附模型;粒径、改性剂投加量、反应温度、pH值及共存阴离子等因素均会影响CPB改性沸石对磷酸盐的吸附能力;减小粒径和降低反应温度均有利于CPB改性沸石对磷酸盐的吸附去除;粒径≤0.18 mm CPB改性沸石吸附磷酸盐较优的改性剂投加量为250 mmol/kg;当溶液的初始pH值位于4~10之间时CPB改性沸石对磷酸盐的吸附能力随pH值的增加而增强;SO42-的存在会明显降低CPB改性沸石对磷酸盐的吸附效率,而提高溶液的pH值有助于消除SO42-存在对CPB改性沸石吸附磷酸盐的负面影响;HCO3-的存在会一定程度上抑制CPB改性沸石对磷酸盐的吸附去除,而提高溶液的pH值无法消除HCO3-存在对CPB改性沸石吸附磷酸盐的负面影响;CPB改性沸石吸附磷酸盐后一定条件下可以重新解吸出来,且随着解吸液SO42-浓度的增加解吸率明显增大。