Nielsenthomsen7872

Geosynthetic clay liners (GCL) are increasingly being used as a major component of barrier systems replacing compacted clay liners due to their very low permeability and speed of installation. Researchers and practitioners have identified the critical role of the GCL overlap that presents constant challenges encountered in maintaining the designed hydraulic conductivity. This study presents a series of flow box tests conducted to evaluate and improve understanding of the combined effect of each of the four contributing factors, namely, overlap width, supplemental bentonite applied at the overlap, the overburden confining stress, and the hydraulic head acting on the GCL overlap. The findings reveal that the overlap width is the most significant parameter affecting the design hydraulic conductivity. The application of a minimum overburden stress to maintain the designed hydraulic performance is also recognised as important. The effect of confinement due to higher hydraulic heads is of interest to practitioners. read more The supplemental bentonite has the least effect on the GCL overlap hydraulic performance even though it enhances the function of the overlap seam. This knowledge addresses the inadequacy of published GCL overlap experimental data comparing the effect of different factors affecting its hydraulic performance. It also assists industry practitioners to design and specify the overlap criterion for a specific application depending on the product specifications and site conditions. The results of this research will help minimise failures of liner systems in barrier applications such as landfills, mines, tailing dams substantially to reduce the potential risk of groundwater contamination.Mammal herbivores, and specially deer, can cause severe damages to agriculture, producing economic losses. Repellents based on odor, visual and/or taste stimuli have been tested to minimize these damages, but their global effectiveness has not been quantified. A systematic literature review on the use of repellents to reduce damage by deer was carried out, and an evaluation of the effectiveness of different repellents and application methods was performed. A Beta regression was employed considering the percentage of vegetation unbrowsed at the end of the essay as the response variable. A total of 246 essays testing ten different repellents and 236 essays testing four different application methods were extracted from 58 articles. Odor-based repellents, such as those including "meat and blood" and "urine, hair and feces of predators", were found to be the most effective to reduce damage. Non-lethal methods, such as repellents, could be valuable tools to manage this human-wildlife conflict.As an important new tool for ecological poverty alleviation, carbon trading compensation is combining ecological protection with rural poverty alleviation. This paper evaluates the poverty alleviation impact of China's pilot carbon emissions trading schemes (ETS) at the provincial level before and after the program, which was implemented from 2007 to 2017. Specifically, we measure poverty alleviation in terms of rural residential income growth and rural job creation. By exploiting the quasi-experimental variation in whether provinces were affected by this pilot ETS policy, our analysis finds that the ETS policy resulted in increases in rural residential income and employment. We find the estimated effects correspond to an increase of approximately 752.6 yuan in annual rural residential income and 2.35% in the ratio of rural employed population to the total employed population, accounting for 9.5% of the rural residents' income and 7.11% of the rural employment, specifically. The results imply that the implementation of ETS is beneficial to income growth and job creation for rural areas of China, which mean the ETS policy may be conducive to poverty alleviation in affected provinces.The concentrative isolation of metal traces from aqueous solutions is of vital importance for environmental and industrial processes. Developing reliable systems of nanoscale that can be fine-tuned to effectively isolate these metals remains an intriguing aim which can potentially beget economic benefits and mitigate major environmental concerns. Here we demonstrate a conceptual metal extraction system where magnetic multi-wall carbon nanotubes (M-MWCNTs) are surface-equipped with a molecular network of polyethylenimine (PEI) to serve as a reusable nano-ionic exchanger, referred to as "M-MWCNTs-PEI". The designed nano-ionic exchanger forms readily stable suspensions with the metal-bearing aqueous solutions eliminating the need for vigorous agitation. Besides, it can be magnetically manipulated and separated in/from the solution. To exemplify its potential for the isolation of metal traces, the M-MWCNTs-PEI was tested with the uranium trace ions in aqueous media. The M-MWCNTs-PEI featured distinct sorption capacity of ~488 mg/g at pH 6, with moderate, but stable, binding affinity toward uranium ions. As such, excellent isolation performance is demonstrated while bound uranium ions are effectively concentrated and recovered from the interfacial PEI molecular network. This was efficiently achieved by exposing the loaded M-MWCNTs-PEI to solutions of small volumes and specific chemistry. Such combined qualities of large capacity and reusability have not been observed with the previously reported ion exchange systems. Altogether, our observations here demonstrate how functional systems of nanoscale can be adapted for industrial applications while this concept can be extended to address other important resources such as rare-earth and lanthanide elements.In the last decades, the use of magnetic nanocomposites as a catalyst was considered for removal of organic pollutants due to its easy separation. Therefore, initially, TiO2@ZnFe2O4/Pd nanocomposite was prepared and then used in the photodegradation of diclofenac under direct solar irradiation in the batch and continuous systems. The structure, morphology and other specifications of produced nanocatalyst were determined via XRD, VSM, FESEM/EDX, FTIR, GTA, UV-Vis, Zeta potential, XPS and ICP-OES. The effective factors on diclofenac removal via nanophotocatalyst viz. pH, catalyst concentration, initial concentration of diclofenac, and flow rate and column length on diclofenac photodegradation were studied. Based on the results, the optimal rate for pH, catalyst concentration, and initial concentration of diclofenac was 4, 0.03 g/l and 10 mg/l respectively. Pd-coated TiO2@ZnFe2O4 magnetic photocatalyst had higher photocatalytic activity in diclofenac photodegradation in relation to ZnFe2O4 and TiO2@ZnFe2O4 under solar light irradiation. The findings showed that after five recycles, the photocatalytic efficiency did not show much reduction i.e. the removal efficiency from 86.1% in the first cycle reduced only to 71.38% in the last cycle. Likewise, in this study, with flow rate reduction and column length increase diclofenac degradation rate increased.In this work, silver nanoparticles have been synthesized with an average particle size of 35 nm, within 90s, using microwave and Sapindus mukorossi extract as a stabilizing agent. The AgNps were surface immobilized on eggshells (ES) to obtain Ag@ES, which was characterized by UV-Vis, UV-DRS, FT-IR, ICP-OES, TGA-DSC, SEM-EDX, XRD and XPS. Its applicability as an environmental catalyst was evaluated by Cr (VI) adsorption, photocatalytic degradation of methyl orange, eriochrome black-T, methylene blue, rhodamine-B as model dyes and microbial inhibition against Staphylococcus aureus, Escherichia coli and Candida albicans. The results revealed that Ag@ES exhibited maximum adsorption capacity of 93 mg/g for Cr (VI) ion and degradation efficiency of ~90-98% for removing anionic and cationic dyes. Further, it showed a minimum inhibitory concentration of 15.6, 7.8 and 31.2 μg/mL for S. aureus, E. coli and C. albicans respectively. Moreover, the Ag@ES being a heterogeneous catalyst can be regenerated and reused without significant loss in its efficiency.Herein, novel green/facile approach to synthesize spongy defective zinc oxide nanoparticles (ZnONPs) is presented using for the first time pomegranate seeds molasses as a green capping fuel/reducing mediator during an aqueous solution combustion process. The developed ZnONPs is characterized by UV-Vis. Spectrophotometry and fluorimetry, XRD, Raman spectroscopy, SEM, TEM and BET. Interestingly, pomegranate seeds molasses within a viable content of bio-capping molecules reveal a defective nanoporous ZnO NPs of smaller particle size, greater pore size/volume, and higher surface area compared to the bulky non-biogenic ZnONPs. Moreover, the biosynthesized defective ZnONPs showed narrowed band gap and higher absorption of visible photons that breed higher density of hydroxyl radicals (•OH) under Solar-illumination. Even further, the bulk ZnO and the biosynthesized ZnO photocatalysts were examined in photodegrading flumequine (FL) antibiotic. The bulk ZnO gives 41.46% photodegradation efficiency compared to 97.6% for the biosynthesized ZnO. In highly acidic or highly alkaline media, FL photodegradability is greatly retarded. Scavenging experiment infers considerable contribution of holes over electrons in photodegradation reaction. The biosynthesized ZnO shows high durability in FL photodegradation after four reusing cycles. These promising findings highlight new insights for biogenic synthesis of tuned size/controlled morphology semiconductor NPs relevant to environmental remediation applications.Present study has attempted to measure Water Richness (WR) and Wetland Habitat Suitability (WHS) in deltaic environment and assessed their spatial linkages. Water richness exhibits availability of water in wetland and its dynamicity, whereas wetland habitat suitability depicts physical habitat ambiance of a wetland toward vibrant ecosystem. Both the components are very essential and should be measured to explore ecosystem service and environmental heath of a region. For investigating water richness of the wetland six water availability indicating parameters have been chosen and for assessing wetland habitat suitability four additional parameters have been taken into consideration. Four widely used and recognised machine learning algorithms like Reduced Error Pruning (REP) tree, Random forest, Artificial Neural Network (ANN) and Support Vector Machine (SVM) have been employed here in order to develop suitable model at two phases. Results reveal that very high water rich zone is found over 200-215 km2 wetland area followed by high water rich zone over 125-140 km2 wetland area in both the phases. Wetland habitat suitability assessment shows only 100-150 km2 of the wetland having very high suitability and 110-120 km2 of wetland having high suitability. Field investigation and accuracy assessment support the validity and acceptability of the results. Spatial linkage between water richness and habitat suitability demonstrates that 30-40% very high water rich zone represents very high habitat suitability figuring out importance of both the models. Therefore, results recommend that only water richness of the wetlands of the wetlands is not enough to represent the habitat suitability in the densely populated riparian flood plain region.