ALBERT

Description: The present work investigates pollutant removal and the transformation of nitrogen from sewage wastewater using a pilot-scale multi-stage bio-vermifilter system. Over a study period of 48 weeks, the pollutant removal performance of the system was measured and the effects of hydraulic loading rate (HLR) and dry–wet ratio (D/W) were estimated. The relationship between oxygen transfer rate and load of oxygen necessity was calculated and analysed for system optimisation. The method for diluting the isotope δ 15 N-NO 3 − was applied to study nitrogen transfer. Moreover, statistical correlations were analysed to determine the crucial factors which influence nitrogen transfer efficiency. The system removes pollutants efficiently; specifically, the average removal efficiencies are 94.2 % for chemical oxygen demand (COD), 93.3 % for NH 4 + -N, and 58.2 % for total nitrogen (T-N). Lowering HLR and D/W can enhance nitrogen removal. Nitrogen speciation and transformation were examined under an optimised condition with an HLR of 0.36 m day −1 and a D/W of 3. The results of isotope δ 15 N-NO 3 − dilution showed that NO 3 − -N was mainly produced in trickling bio-filter and vermibio-filter (VBF) I. By contrast, NO 3 − -N was mainly reduced in VBF II. Under stable operating conditions and environmental factors, COD/T-N was verified as the crucial factor in nitrogen removal.

Description: This study presents a novel roughness formulation to conceptually account for microtopography and compares it to four existing roughness models from literature. The aim is to increase the grid size for computational efficiency, while capturing subgrid scale effects with the roughness formulation to prevent the loss in accuracy associated with coarse grids. All roughness approaches are implemented in the Hydroinformatics Modeling System and compared with results of a high resolution shallow water model in three test cases: rainfall-runoff on an inclined plane with sine-wave shaped microtopography, flow over an inclined plane with random microtopography and rainfall-runoff in a small natural catchment. Although the high resolution results can not be reproduced exactly by the coarse grid model, e.g. local details of flow processes can not be resolved, overall good agreement between the upscaled models and the high resolution model has been achieved. It is concluded that the accuracy increases with the number of calibration parameters available, however the calibration process becomes more difficult. Using coarser grids results in significant speedup in comparison with the high resolution simulation. In the presented test cases the speedup varies from 20 up to 2520, depending on the size and complexity of the test case and the difference in cell sizes. The proposed roughness formulation generally shows the best agreement with the reference solution, compared to the other models investigated in this study.

Description: To determine the ammonia nitrogen adsorption and release characteristics of surface sediments in Dianchi Lake, 36 surface sediment (0–10 cm) samples were collected in 2013. Results showed that compared with other lakes in China (e.g. Erhai Lake and Taihu Lake), Dianchi Lake had high levels of ammonia nitrogen (NH 4 + –N) adsorption capacity, release rate and release capacity. The ammonia nitrogen release risk of Dianchi sediments was relatively high. Comparison of the equilibrium ammonium concentration ( ENC 0 ) in surface sediments and the ammonium contents in the overlying water of Dianchi Lake indicated that ENC 0 was high for most lake sections. Therefore, the sediments of Dianchi Lake would be a pollution source, and ammonia nitrogen release risk was high because the surface sediments of Dianchi Lake were heavily contaminated with nitrogen. The total nitrogen (TN) and NH 4 + –N contents of the sediments of Dianchi Lake greatly influenced the ammonia nitrogen adsorption–release process. Aside from TN, nitrogen fractions should also be studied when assessing pollutant release risk from lake sediments. NH 4 + –N was the main fraction of nitrogen released from sediments, which was highly significant when evaluating sedimentary release capacity. The sedimentary release capacity and release potential of nitrogen provided important information to assess release risks.

Description: The variability and sensitivity of crop evapotranspiration (ET) measurements at field scale are still poorly understood in the irrigated farmland of arid region in Northwest China. The spatial and temporal dynamics and sensitivity of field ET are fundamental for the scaling up and validation of ET estimates from remote sensing data. In the study, we analysed the dynamics, impact factors and sensitivity of spring wheat ET during the growing season in Northwest China. Results indicated that there was a significant effect of first irrigation event on the spatial and temporary variability of ET. At the tillering-shooting stage (before the first irrigation event), spatial variability of ET was the lowest and gradually increased with crop growth. In some experimental plots, spring wheat ET had a significantly higher temporal stability than other plots except for the tillering-shooting stage. The sample sites with higher temporal stability could be used for long-term monitoring samples and for up scaling of ET measurements. In comparison with LAI and ET 0 , surface soil moisture change ∆ θ 0–20 cm was the most sensitive variable of ET measurements, which could be used as the auxiliary variable to improve the ET accuracy. With the soil moisture measurements, the relative error of ET was 9.4 % with only half the number of ET sampling data.

Description: Sediment contamination by heavy metals can result in significant damage to the ecological water environment. Sediment dredging is a useful way to reduce the adverse effects of heavy metal pollution in freshwater. The dredging depth is a key parameter in environmental dredging engineering. In this paper, we propose an innovative method called the critical-risk-depth method for calculating the environmental dredging depth that has been specifically designed for removal of river sediments contaminated by heavy metals. To determine the critical risk depth for dredging, the heavy metal concentrations at different sediment depths and their potential ecological risks must be tested and evaluated. The first step of the method involves analyzing sediments to determine the lateral and vertical distribution of heavy metals. In the next step, Hakanson’s potential ecological risk index is used to assess the ecological risk of heavy metals at different sediment depths. Finally, the recommended environmental dredging depths are calculated based on the potential risk for change in the vertical distribution and the given threshold level for the potential critical risk from heavy metals. We carried out a case study to determine the dredging depth for river sediment in Pinghu. The sediment analysis results show that the contents of Cd, Zn, and Pb are excessive when compared with the local soil background levels. Because of the accumulation effect of heavy metals in sediments, the heavy metal contents tend to decrease with sediment depth, but this trend may change as a result of human activities and other river dredging events. There is a high potential ecological risk level from heavy metal pollution in sediments in the study area, and the recommended environmental dredging depths of the ten rivers range from 35 to 100 cm.

Description: A multi-element geochemical soil survey was performed to assess the geochemical baseline and the environmental impacts of some potentially harmful elements in soils of the Kerman city. In doing so, a total of 175 samples, including residual (5), evaporate (6), silty–clay plain (42), urban (15), archaeological (3), road side (12), runway side (3), rail road side (7), agricultural (34), machinery battery manufacturing station (10), gasoline station (17), machinery paint working station (17) and cemetery (4) soil samples were collected on the 1:50,000 scale map of the Kerman city. The soil samples were analysed by ICP-OES for Ag, As, Bi, Cd, Co, Cr, Cu, Hg, Li, Mo, Ni, Pb, Se, Sn, V, W and Zn. The resulting elemental values in non-contaminated residual soils are similar to that of global background soil level (Salimen et al. Geochemical atlas of Europe. Part 1, Background information, methodology and maps. Finland Geological Survey, p 526, 2006 ; Lindsay Chemical equilibria in soils. Wiley, p 449, 1979 ). However, the soils close to the gasoline stations are enriched in Pb with variations up to 202 mg/kg. Soils developed around the machinery battery manufacturing stations also give a very high concentration of Pb as high as 60,445 mg/kg. The anomalous contents of Pb in soil samples close to the machinery paint working places range from 0.27 to 692 mg/kg. Some high values of Zn up to 1655 mg/kg are related to the agricultural soils in Pistachio gardens. The results highlight that the most anomalous harmful elements include Pb, Sn, Cd, Cu, Zn, Sb, As and Mo, which is supported by their high enrichment factors.

Description: Groundwater resources of karst aquifers within Circum-Mediterranean are a vital natural resource, which have been exploited since the dawn of the Mediterranean civilization. In Greece, carbonate formations are thought to be one of the most important sources for various water uses, that are vital for the country’s economy and development, that is agriculture and water supply. In most cases, they are considered as integral parts of some of the most strategic hydrosystems in Greece, containing surface water and groundwater resources that secure water supply for several anthropogenic activities. This paper provides a review of different aquifer types in Greece (granular and karstic), focusing on karst hydrosystems. It presents their spatial distribution throughout the entire Greek territory, and describes the most important environmental stresses upon them, while it analyzes their importance and role to the country’s water supply. Finally, this study analyzes the river basin of (Central Greece), used as a reference hydrosystem, to prove the ample importance of karst reservoirs in Greece.

Description: Capillary barrier cover systems (CBCSs) are useful and low-cost earthen cover systems for preventing water infiltration and controlling seepage at solid waste landfills. A possible technique to enhance the impermeable properties of CBCSs is to make water repellent grains by mixing the earthen cover material with a hydrophobic agent (HA). In this study, six different grains with different geometries and sizes were used to prepare dry hydrophobized grains by mixing with different contents of oleic acid as a HA. Wet hydrophobized grains were prepared by adjusting the water content ( θ g ; kg kg −1 ) of dry hydrophobized grains. To characterize the water repellency (WR) of dry and wet hydrophobized grains, initial solid-water contact angles ( α i ) were measured using the sessile drop method (SDM). Based on SDM results from the α i –HA content and α i – θ g curves, useful WR indices were introduced as “Area_ dry ” and “Area_ wet ” (areas under the α i –HA content and α i – θ g curves, respectively), “HA_ zica ” and “θ g_zica ” (maximum HA content and θ g at which WR disappears, respectively), and “α i,peak ” and “HA_ αi,peak ” (peak α i in the α i –HA content curve and corresponding HA content to α i,peak , respectively). Pearson correlation analysis was performed to identify correlations between proposed WR indices and basic grain properties. Results showed that WR indices correlated well to d 50 and coefficient of uniformity ( C u ) and regression equations for WR indices were obtained as functions of d 50 and C u ( r 2  〉 0.7).

Description: In the present study, minimax probability machine regression (MPMR) and extreme learning machine (ELM) have been adopted for prediction of seismic liquefaction of soil based on strain energy. Initial effective mean confining pressure ( \( \sigma_{\text{mean}}^{\prime} \) ), initial relative density after consolidation ( D r ), percentage of fines content (FC), coefficient of uniformity ( C u ), and mean grain size ( D 50 ) have been taken as inputs of MPMR and ELM models. MPMR and ELM have been used as regression techniques. The performances of MPMR and ELM have been compared with the artificial neural network. A sensitivity analysis has been carried out to determine the effect of each input. The experimental results demonstrate that proposed methods are robust models for determination seismic liquefaction potential of soil based on strain energy.