Search Results (19)

In light of the global raw material crisis and the ongoing degradation of the natural environment, this study provides a significant contribution to the advancement of the circular economy in the construction sector. The authors conducted a comprehensive analysis of the feasibility of using waste sands originating from wastewater treatment plants as substitutes for natural fine aggregates in concrete mixtures. The investigation included the evaluation of the physicochemical, environmental, and mechanical properties of the analyzed waste sands. The results demonstrate a high application potential for sewer cleaning sand (SC), which, in its current form, can be used in non-structural applications. The key advantages of the sand that was examined include a high sand-equivalent value (98.2%), low contents of impurities (LOI < 1.5%), and a favorable chemical composition. Leaching tests for harmful substances, including heavy metals, for both the sand and the mortar samples, did not indicate any significant environmental risk. One principal conclusion of the study is the identification of the possibility of closing the waste life cycle at the wastewater treatment plant stage, which could significantly contribute to the reduction of landfilled waste volumes and operational costs. Full article

Tree root intrusion can cause failures of underground sewer pipes and thus represent a major water asset management issue. If tree root intrusion is not detected early, this may lead to the interruption of wastewater services and high costs of repair to the pipeline. The objectives of this review are to assess the existing maintenance strategies, explore suitable strategies for Australia and similar settings around the world, and identify possible factors and predictive tools. Maintenance strategies can be divided into two categories: reactive and proactive approaches. The current reactive approaches are (1) mechanical techniques to clean the root mass in pipe networks and (2) chemical techniques to remove the root mass and control future growth. The literature suggests that the reactive approaches often provide only partial solutions. The proactive approaches, guided by a predictive model of tree root intrusion and its related factors, showed the potential to improve maintenance and limit the risk of the damage from re-occurring. Predictive models could help to evaluate the risk of planting trees in different conditions and minimise the damage of tree root intrusion after further multifactor investigations. Full article

Aiming to solve the problem of clearing obstacles in narrow and complex sewers, this paper introduces a visually assisted Sewer Cleaning Robot (SCR) for cleaning sewers with diameters ranging from 280 to 780 mm. The main work is carried out as follows: (a) A mobile platform is equipped with a pressing mechanism to press against the pipe walls in different diameters. The arm uses high-load linear actuator structures, enhancing load capacity while maintaining stability. (b) A Detection–Localization–Cleaning mode is proposed for cleaning obstacles. The YOLO detection model is used to identify six types of sewer defects. Target defects are then localized using monocular vision based on edge detection within defect bounding boxes. Finally, cutting is performed according to the localized defect positions. The feasibility of SCR in cleaning operations is validated through a series of experiments conducted under simulated pipeline conditions. These experiments evaluate its mobility, visual detection, and localization capabilities, as well as its ability to clear hard obstacles. This paper provides technical reserves for replacing human labor that use vision algorithms to assist in cleaning tasks within sewers. Full article

Machine learning techniques have progressively emerged as important and reliable tools that, when combined with machine condition monitoring, can diagnose faults with even superior performance than other condition-based monitoring approaches. Furthermore, statistical or model-based approaches are often not applicable in industrial environments with a high degree of customization of equipment and machines. Structures such as bolted joints are a key part of the industry; therefore, monitoring their health is critical to maintaining structural integrity. Despite this, there has been little research on the detection of bolt loosening in rotating joints. In this study, vibration-based detection of bolt loosening in a rotating joint of a custom sewer cleaning vehicle transmission was performed using support vector machines (SVM). Different failures were analyzed for various vehicle operating conditions. Several classifiers were trained to evaluate the influence of the number and location of accelerometers used and to determine the best approach between specific models for each operating condition or a single model for all cases. The results showed that using a single SVM model with data from four accelerometers mounted both upstream and downstream of the bolted joint resulted in more reliable fault detection, with an overall accuracy of 92.4%. Full article

Computer vision in consideration of automated and robotic systems has come up as a steady and robust platform in sewer maintenance and cleaning tasks. The AI revolution has enhanced the ability of computer vision and is being used to detect problems with underground sewer pipes, such as blockages and damages. A large amount of appropriate, validated, and labeled imagery data is always a key requirement for learning AI-based detection models to generate the desired outcomes. In this paper, a new imagery dataset S-BIRD (Sewer-Blockages Imagery Recognition Dataset) is presented to draw attention to the predominant sewers’ blockages issue caused by grease, plastic and tree roots. The need for the S-BIRD dataset and various parameters such as its strength, performance, consistency and feasibility have been considered and analyzed for real-time detection tasks. The YOLOX object detection model has been trained to prove the consistency and viability of the S-BIRD dataset. It also specified how the presented dataset will be used in an embedded vision-based robotic system to detect and remove sewer blockages in real-time. The outcomes of an individual survey conducted at a typical mid-size city in a developing country, Pune, India, give ground for the necessity of the presented work. Full article

In the face of unstoppable urbanisation, disaster risks are projected to increase, mainly in unplanned areas that usually lack disaster risk reducing infrastructure. In Africa, including South Africa, limited resources and capacity hinder the provision of such infrastructure. The objective of this study was to determine options for promoting disaster risk reducing infrastructure in informal settlements in Giyani Municipality, Limpopo Province, South Africa, a disaster risk-prone area. A case study was conducted to collect primary data from purposively selected experts and the SWOT factors from the Integrated Development Plan Report of 2019/2020. A TOWS analytical hierarchical process was applied to pairwise comparisons of factors to prioritize them using eigenvalues and generate strategic options for promoting disaster risk reduction infrastructure in the informal settlements of Giyani Local Municipality. In the TOWS results, the experts suggested integrating traditional authorities into the municipal development processes, implementing an environmental framework that includes disaster management policies and an integrated waste management plan, and developing innovative technological projects that provide up-to-date spatial planning data to provide disaster risk reducing infrastructure in informal areas. This study concludes that the provision of affordable housing, clean regular piped water, storm and sewer drainage systems, street lighting, accessible routes, solid waste collection, electricity, and healthcare services would reduce a range of disaster risks. Full article

This study aims to model the performance of sewage networks under diverse blockage situations in terms of overflow occurrence using internet-of-things-based technologies in Hong Kong. To this end, a multi-stage methodological approach is employed, starting from collecting required data using smart sensors, utilizing novel data mining techniques, and using a case study simulation. From the results obtained, the following conclusions are drawn: (1) several sites under investigation are imbued with partial blockages, (2) the overall performance of the sewer network has a nonlinear relationship with the blockages in terms of the remaining time to overflow, (3) in cases of complete blockages, the sewer only takes few minutes to reach the manhole cover level that causes the system to experience overflow, and (4) cleaning work significantly improve the performance of the sewage network by 86%. The outcomes of this study provide a solid foundation for the concerned environmental engineers and decision-makers towards reducing the magnitude of sewer overflow and improving different aspects of our environment. Full article

The highly infectious Tomato brown rugose fruit virus (ToBRFV) is a new viral threat to tomato production worldwide. In production, the very easy mechanical transmissibility combined with the high resistance in vitro is of great concern. We tested: (i) whether household cleaning products, commercial agricultural detergents, and an authorized plant protectant are suitable for cleaning contaminated clothing, and (ii) whether infectious viruses remain in the resulting cleaning water. The evaluation of the sanitation effect was performed using bioassays, by counting ToBRFV-associated necrotic local lesions on Nicotiana tabacum cv. Xanthi NN. For this purpose, leaves were mechanically inoculated with treated fabrics and cleaning solutions which would normally be discharged to the sewer system. The detergents Fadex H⁺ (FH) and Menno Hortisept Clean Plus, as well as the disinfectant Menno Florades (MF), led to an almost complete removal of ToBRFV from contaminated fabrics, corresponding to a reduction in local lesions by 99.94–99.96%. In contrast, common household cleaning products (Spee ActivGel (SAG), Vanish Oxi Action Gel (VO) did not effectively remove the pathogen from the fabric, where the reduction was 45.1% and 89.7%, respectively. In particular, cleaning solutions after the use of household cleaners were highly contaminated with ToBRFV. After a 16-h treatment with the disinfectant MF, infectious ToBRFV was no longer present in VO, FH, and MF cleaning solutions, as demonstrated by extensive bioassays. Full article

Wastewater has significant potential as a source of clean energy. This energy can be used both within external sewer networks and on the scale of individual residential buildings, and the use of shower heat exchangers appears to be the most reasonable solution. However, in the case of Poland, the problem is still the unwillingness of society to use this type of solution, caused mainly by the lack of space for the installation of vertical drain water heat recovery (DWHR) units and the low efficiency of horizontal units. In response to this issue, the efficiency of a new compact shower heat exchanger designed to be mounted below the shower tray, as well as its linear counterpart, was investigated under various operating conditions. In addition, the financial efficiency of using the compact DWHR unit with average water consumption for showering was evaluated. For this purpose, discount methods were used to estimate the financial efficiency of investments. The study showed that the compact shower heat exchanger has higher efficiency than its linear counterpart. Depending on the temperature of cold water and the flow rate of both media through the heat exchanger, it achieves efficiencies ranging from 22.43% to 31.82%, while the efficiency of the linear DWHR unit did not exceed 23.03% in the study. The financial analysis showed that its use is particularly beneficial when the building uses an electric hot water heater. The investment’s sensitivity to changes in the independent variables is small in this case, even with low water consumption per shower. The only exceptions are investment outlays. Therefore, the compact DWHR unit is a clean energy device, which in many cases is financially viable. Full article

Waste from street cleaning is usually of a fine fraction below 10 mm and varies greatly in both quantity and composition. It may be composed of chlorides, especially for that resulting during winter due to the use of street de-icing agents. Chlorides can cause the salinization of surface water and groundwater, and the salinization of soils, which in turn lead to the deterioration of water purity and a decrease in biodiversity of aquatic organisms, changes in microbiological structure, and increases in toxicity of metals. Therefore, it is very important to determine the level of salinity in stored waste and its impact on the environment. The present study was conducted in a city of about 55,000 inhabitants. The highest chloride concentrations were observed after winter in waste from street and sidewalk cleaning around the sewer gullies, amounting to 1468 mg/dm³. The lowest chloride concentration in this waste occurred in summer and amounted to 35 mg/dm³. The multi-criteria analysis indicated that the most beneficial form of street cleaning and, thus, of reductions in chloride concentration in the waste from street cleaning, would be sweeping and daily washing. The objective of this research was to determine the amount of chlorides in sweepings on an annual basis in order to determine the potential risks associated with their impact on select aspects of the environment and to evaluate the frequency of necessary cleaning for city streets, considering the effects. The methodology used was a multi-criteria evaluation, which as a decision analysis, allowed us to determine the frequency of cleaning and washing of streets, in such a way that an ecological effect is achieved with simultaneous economic efficiency. Full article

Dry-weather flows in urban channels and streams, often termed “urban drool”, represent an important source of urban surface water impairment, particularly in semi-arid environments. Urban drool is a combination of year-round flows in urban channels, natural streams, and storm-sewer systems (runoff from irrigation return flow, car washes, street cleaning, leakage of groundwater or wastewater into streams or storm sewers, etc.). The purpose of this study was to better understand the extent and sources of urban drool pollution in Denver, Colorado by identifying relationships between urban catchment characteristics and pollutants. Water-quality samples were taken throughout Denver at urban drainage points that were representative of a variety of urban characteristics. Samples were analyzed for total suspended solids (TSS), coliforms, Escherichia Coli (E. coli), nutrients (nitrate, phosphorus, and potassium), dissolved and total organic carbon, and dissolved and total recoverable metals. Results from this study were as follows: (1) most contaminants (nitrate, phosphorus, arsenic, iron, manganese, nickel, selenium, and zinc) were concluded to be primarily loaded from shallow groundwater; (2) anthropogenic effects likely exacerbated groundwater pollutant concentrations and contributions to surface water; (3) nitrate, nickel, and manganese may be partially contributed by industrial inputs; (4) medical marijuana cultivation sites were identified as a potential source of nutrient and zinc pollution; (5) E. coli was a ubiquitous contaminant in all urban waterways; (6) erosion of contaminated urban soils, presumably from construction, was found to significantly increase concentrations of TSS, total phosphorus, and total metals. Increasing urbanization and predicted drier climates suggest that dry-weather flows will become more important to manage; the results from this study provide insight on dry-weather water quality management for the City and County of Denver. Full article

The EU Directive 2018/2001 recognized wastewater as a renewable heat source. Wastewater from domestic, industrial and commercial developments maintains considerable amounts of thermal energy after discharging into the sewer system. It is possible to recover this heat by using technologies like heat exchangers and heat pumps; and to reuse it to satisfy heating demands. This paper presents a review of the literature on wastewater heat recovery (WWHR) and its potential at different scales within the sewer system, including the component level, building level, sewer pipe network level, and wastewater treatment plant (WWTP) level. A systematic review is provided of the benefits and challenges of WWHR across each of these levels taking into consideration technical, economic and environmental aspects. This study analyzes important attributes of WWHR such as temperature and flow dynamics of the sewer system, impacts of WWHR on the environment, and legal regulations involved. Existing gaps in the WWHR field are also identified. It is concluded that WWHR has a significant potential to supply clean energy at a scale ranging from buildings to large communities and districts. Further attention to WWHR is needed from the research community, policymakers and other stakeholders to realize the full potential of this valuable renewable heat source. Full article

The prediction of sediment levels in combined sewer system (CSS) would result in enormous savings in resources for their maintenance as a reduced number of inspections would be needed. In this paper, we benchmark different machine learning (ML) methodologies to improve the maintenance schedules of the sewerage and reduce the number of cleanings using historical sediment level and inspection data of the combined sewer system in the city of Barcelona. Two ML methodologies involve the use of spatial features for sediment prediction at critical sections of the sewer, where the cost of maintenance is high because of the dangerous access; one uses a regression model to predict the sediment level of a section, and the other one a binary classification model to identify whether or not a section needs cleaning. The last ML methodology is a short-term forecast of the possible sediment level in future days to improve the ability of operators to react and solve an imminent sediment level increase. Our study concludes with three different models. The spatial and short-term regression methodologies accomplished the best results with Artificial Neural Networks (ANN) with 0.76 and 0.61 R2 scores, respectively. The classification methodology resulted in a Gradient Boosting (GB) model with an accuracy score of 0.88 and an area under the curve (AUC) of 0.909. Full article

Timely maintenance of sewers is essential to preventing reduced functionality and breakdown of the systems. Due to the high costs associated with inspecting a sewer system, substantial research has focused on sewer deterioration modeling and identification of the most useful features. However, there is a lack of consensus in the findings. This study investigates how the feature importance depends on the definition of bad pipes and how the feature importance changes between utilities with similar data bases. A dataset containing 318,457 pipes from 35 utilities with a condition state (CS) ranging from one to four was used. The dataset was cleaned, and a backward step analysis (BSA) was applied to two ways of binarizing the CS. Additionally, a BSA was applied for each utility with ≥100 pipes in CS four. The results showed that a selective definition of bad pipes reduced the performance and changed the order of which features contributed the most. In each case, either year of construction, age, groundwater, year of rehabilitation, or dimension was the most important feature. On average 6.5 features contributed to the utility-specific models. The feature analysis was sensitive to the inspection strategy, the size of the dataset, and interdependency between the features. Full article

Prehistoric Hellenic civilizations like many other civilizations believed in gods and thought they had influence on the everyday life of the people. During the Bronze Ages the explanations of illness and health problems were based on mythological, divine, or religious (i.e., theocratic) reasoning or explanations. However, during the Classical and the Hellenistic periods, the Greeks clearly differentiated their thinking from all other civilizations by inventing philosophy and empirical science. Drains/sewers, baths and toilets and other sanitary installations reflect the high cultural and technological level of the period; they are also associated with hygienic and medical studies and practical applications. At that time, medicine was mainly based on clinical observations and scientific investigations. Prior to that time, in the Bronze Age, medicine was entirely confined to religious rituals and beliefs. In ancient Greece, medicine was practiced in Asclepieia (or Asklepieia), which were healing sanctuaries which also functioned as medical schools and hospitals. In the Classical Greece period, more than 400 Asclepieia were operating offering their medical services. The basic elements of each Asclepieia included a clean source of water and related infrastructure. At that time Hippocrates, the father of medicine, and his successors wrote a large number of medical texts in which the crucial role of water and sanitation is documented. They also identified numerous medical terms, many of which remain in use today. The Hippocratic treatises also contributed to the scientific evolution which occurred in later centuries, because they sought to explain the causes of observed natural phenomena in a deterministic way rather than on theocratic explanations in use at the time. In this paper, the evolution of hygiene, focusing on water use in ancient Greece is examined. Full article