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A study was designed to investigate the chemical coagulation process for the treatment of the potato food industry wastewater of the “Chipsy factory” located at Abi‐Sier, Egypt. The chemical coagulants used in the study include alum, ferric chloride, calcium chloride, ferric sulphate and Nalco as polymer. Variable doses of these coagulants were examined to determine the optimum dose. Results obtained showed that chemical treatment (coagulation, flocculation, followed by sedimentation) was efficient to reduce the chemical oxygen demand (COD), total suspended solids (TSS) and turbidity significantly. Remarkable variation of the removal efficiency depends on the type of coagulant. Ferric chloride and ferric sulphate were more efficient than calcium chloride. Combination of Nalco with each of the studied coagulants improved the removal efficiency remarkably. Reduction of 91‐94 per cent of turbidity, 93‐97 per cent of COD, and 94‐97 per cent of the TSS was achieved with these combinations.

Examines the effect of pollution along the agriculture highway between Cairo and Alexandria. Different samples of water, soil and plants (clover) were collected from nine variable locations along this highway. Results obtained revealed that the influence of lead precipitating from the atmosphere directly reflects the lead content of soil. Concentration of metals so far did not show any great significant effect.

The removal of nickel and mercury from drinking water, using powdered activated carbon (PAC) and granular activated carbon (GAC) was studied intensively. The water studied was artificially contaminated by Ni and Hg to yield 2mg/l each. Both batch and continuous systems were tested. The time needed to maintain equilibrium and the adsorption isotherm were determined by the batch system. The results obtained were found to be confirmed with Freundlich’s equation, rather than Langmuir or BET. When the PAC was used, the values 1/n and K were 1.59 and 1.02 for Ni and 1.21 and 1.91 for Hg. Relatively similar results were obtained when the GAC was examined. This indicated the stronger adsorbability of mercury compared to nickel. When investigating the continuous system at different contact times the results indicated that increasing the contact time increased the metal : carbon removal efficiency. The overall results showed that the breakthrough points for either Ni or Hg reflected their adsorption isotherms as indicated by k values. Concludes that the addition of an activated carbon filter is recommended for the treatment of drinking water contaminated by heavy metals.

Pot experiments were conducted to study the effects of different levels of Cobalt (Co), on the growth and on the chemical constituents of peanut plants. Co was added to soil at concentrations of 0, 25, 50, 100, 200 and 400mg Co/kg soil. Dry matter accumulation, chlorophyll content, catalase activity, total proteins and free amino acids content, carbohydrates and sugars and mineral contents were determined in roots, stems and leaves of the plant. Results showed that soil polluted with higher rates of Co depressed plant growth in terms of dry matter production. However, the relatively low levels of Co increased the dry matter accumulation. The results obtained indicated high accumulation of Co in plant, although the level of Co in the soil was added in relatively low concentrations. On the other hand, plant chemical constituents exhibited different responses according to plant organ and Co application rate. In addition, the interaction effect both Co and Ni on the mineral content of peanuts was investigated.

Describes a study carried out to evaluate the accumulation of heavy metals by two different vascular aquatic plants in the artificial wetlands which were constructed for the treatment of municipal wastewater in Berlin, Germany. The studied plants were Pharagmites australis and Schoenoplectus lacustris. The investigated metals were: Zn, Cr, Cu, Fe, Cd, Ni and Pb. The translocation of such metals in the plant roots, stems and leaves was also determined. The level of metals in the influent and effluent of the wastewater, as well as the sludge, was investigated. The concentration factor of each metal by plants and sludge was further studied. Results revealed that P. australis has a higher tendency for the accumulation of metals than S. Lacustris. The level of metals was higher in roots, followed by leaves, then stems. Metals were more concentrated in the sludge than in the plants. Further study showed that the levels of metals in plants grown in the artificial wetlands were higher than in those grown in a “controlled” area. Concludes that vascular plants can act as scavengers of metals from the municipal wastewater while still maintaining a healthy status.

In line with global initiatives, the state of Kerala in southern India is actively working towards formalizing its informal solid waste management (SWM) sector. Despite this, there is a dearth of studies on formalization processes, particularly focusing on the conditions of workers within this sector. This study addresses the gap by examining the challenges faced by women workers operating within the formalized framework of Kerala’s SWM sector. It aimed to investigate challenges faced by grassroots women workers in Kerala’s SWM sector during its transition from informal to formal, identifying gaps in the process through their experiences. Using a qualitative methodology, the research gathered data from 10 women workers in the SWM sector in Kozhikode, Kerala, who were part of the Haritha Karma Sena (green task force). Thematic analysis of in-depth interviews revealed two major challenges faced by these women. Firstly, there was a negative societal perception towards them, and secondly, there was a lack of appropriate state response to their needs and requirements. These challenges were attributed to gaps and pitfalls in the formalization process, leading to a lowered socio-economic status for the women, increased vulnerability to health hazards, and societal stigma. The findings underscore the need for significant improvements in the formalization process of Kerala’s waste management sector. The study advocates for targeted policy interventions to enhance the working conditions of SWM workers, emphasizing the importance of expediting and streamlining the formalization process. This, in turn, would contribute to the overall effectiveness of the SWM system in the state.

Examines the fate of heavy metals in sewage water and the sludge produced. Investigates the level of metals before and after the use of chemical coagulants as well as throughout every process of the plant. Results reveal that the present upgrading of the plant has a remarkable improvement in the performance of the sewage treatment. Concludes that such upgrading of the plant reduces sewage tax because of the improvement in performance. In addition, the hydrolysis of the pre‐treated sludge can improve the de‐nitrified process and therefore can save energy, while the application of lime can be a substitution for enlarging the plant itself.

There have been numerous efforts to tackle the problem of accumulated construction and demolition wastes worldwide. In this regard, this study develops a model for identifying the optimum fleet required for waste transportation. The proposed model is validated through a case study from the construction sector in New Cairo, Egypt.

Various fleet combinations are assessed against the time, cost, energy and emissions generated from waste transportation. Genetic algorithm optimization is performed to select the near-optimum solutions. Complex proportional assessment and operational competitiveness rating analysis decision-making techniques are applied to rank Pareto frontier solutions. These rankings are aggregated using an ensemble approach based on the half-quadratic theory. Finally, a sensitivity analysis is implemented to determine the most sensitive attribute.

The results reveal that the optimum fleet required for construction and demolition wastes (CDW) transportation consists of one wheel loader of bucket capacity 2.5 cubic meters and nine trucks of capacity 22 cubic meters. Furthermore, consensus index and trust level of 0.999 are obtained for the final ranking. This indicates that there is a high level of agreement between the rankings. Moreover, the most sensitive criterion (i.e. energy) is identified using a sensitivity analysis.

This study proposes an efficient and effective construction and demolition waste transportation strategy that will lead to economic gains and protect the environment. It aims to select the optimum fleet required for waste transportation based on economic, social and environmental aspects. The usefulness of this study is establishing a consensual decision through the aggregation of conflicting decision makers' preferences in waste transportation and management.

Presents the findings of a study conducted to examine the efficiency of the combined anaerobic‐aerobic reactors for the treatment of three different tannery industrial wastewaters, focusing on the fate of chromium and other associated metals. Examines elimination rates of such metals with respect to each successive treatment process. Discusses the correlation between the chemical characteristics of the wastewater influent and effluent along with the level of heavy metals in such wastewater and the produced sludge. Confirms that the use of such sludge in agriculture should be restricted and recommends the recovery of Cr from the tanning sludge.

An abundance of techniques has been presented so forth for waste classification but, they deliver inefficient results with low accuracy. Their achievement on various repositories is different and also, there is insufficiency of high-scale databases for training. The purpose of the study is to provide high security.

In this research, optimization-assisted federated learning (FL) is introduced for thermoplastic waste segregation and classification. The deep learning (DL) network trained by Archimedes Henry gas solubility optimization (AHGSO) is used for the classification of plastic and resin types. The deep quantum neural networks (DQNN) is used for first-level classification and the deep max-out network (DMN) is employed for second-level classification. This developed AHGSO is obtained by blending the features of Archimedes optimization algorithm (AOA) and Henry gas solubility optimization (HGSO). The entities included in this approach are nodes and servers. Local training is carried out depending on local data and updations to the server are performed. Then, the model is aggregated at the server. Thereafter, each node downloads the global model and the update training is executed depending on the downloaded global and the local model till it achieves the satisfied condition. Finally, local update and aggregation at the server is altered based on the average method. The Data tag suite (DATS_2022) dataset is used for multilevel thermoplastic waste segregation and classification.

By using the DQNN in first-level classification the designed optimization-assisted FL has gained an accuracy of 0.930, mean average precision (MAP) of 0.933, false positive rate (FPR) of 0.213, loss function of 0.211, mean square error (MSE) of 0.328 and root mean square error (RMSE) of 0.572. In the second level classification, by using DMN the accuracy, MAP, FPR, loss function, MSE and RMSE are 0.932, 0.935, 0.093, 0.068, 0.303 and 0.551.

The multilevel thermoplastic waste segregation and classification using the proposed model is accurate and improves the effectiveness of the classification.