Plastics, often known as synthetic polymers, have become an essential workhorse element in the contemporary marketplace due to their availability in a wide range of forms and adaptability. Despite its many advantages, the present plastic business has problems that are becoming more obvious by the day. Between 2000 and 2019, global waste plastic production more than quadrupled to 460 million metric tonnes. Only 9% is recycled, 12% is burned, and the rest is disposed of in the waste stream. As per the Down to Earth 2018 figures, India consumes over 16.4 million metric tonnes of plastic. In that, single-use plastics are made up of nearly 43% and were disposed of in landfills. Recycling possibilities include converting waste into raw materials for industry, producing fuel, and using it as construction material. Since buildings are intended to last for several decades, adding such waste materials into them helps to extend their life. It is thus conceivable to reduce both the amount of plastic waste put in landfills and the amount of natural resources mined for the production of conventional materials. This comprehensive review intends to logically analyze the findings of numerous researchers who introduced waste plastic in various forms (flakes, fibers, pellets, granules, pellets, and molten forms) into different building materials. This article supports the discussion of using waste plastic for sustainable building by offering details regarding the physical, mechanical, and durability strength properties of building materials containing various forms of plastic waste. The review analysis indicates that adding plastic waste, regardless of shape or particle size, tends to reduce the workability and mechanical properties of the resulting material. However, introducing plastic particles in small amounts, such as 2%–20%, helps to obtain threshold strength properties. The study also suggests that the addition of smaller particles with irregular forms helps to obtain better results than larger particles with uniform shapes and smooth surfaces.

The ecological integrity of several freshwater ecosystems has been disrupted by the rapid and unrestrained accumulation of toxic heavy metals (HMs) from various sources. Changes in land use and land cover, in the form of urbanization and industrialization, have significantly affected the surface-water quality of freshwater ecosystems by causing an upsurge in pollutant loads. In addition, agricultural runoff has contributed to the decrease in water quality. Almost 70% of India's surface-water resources have become polluted owing to the discharge of untreated sewage and industrial effluents, according to a recent report by the Central Water Commission (CWC) of India, with 42 rivers containing at least two HMs in concentrations above the permissible limit. The aquatic biota inhabiting contaminated sites can accumulate HMs from the surface water. In high concentrations, these HMs can damage biotic components, predominantly by triggering oxidative stress and becoming bioaccumulated in different trophic levels of freshwater ecosystems. Heavy metal contamination in the aquatic environment can also cause direct potential hazards to humans, mostly through their consumption of fish and waterfowl. Thus, it is recommended that the untreated wastewater discharge from industry, agricultural fields, and households be curtail to improve surface-water quality. In this systematic review, we investigated the probable sources of the HMs, the HM contamination in the important rivers and wetlands of India, the effects of HM toxicity on freshwater food chains, and potential remediation measures. The findings of the present study will improve our knowledge about the spectrum of HM toxicity and the effects of HM contamination on the biota in freshwater bodies throughout India, and will also aid policymakers in building strategic and sustainable freshwater management plans around the globe.

Climate change (CC) is considered one of the most critical threats to human lives and activities due to dramatic increases in the frequency and severity of droughts and floods under global warming. To alleviate such impacts, many studies on CC adaptation strategies in water management have emerged. This review covers 131 relevant studies published over the past two decades. It aims to robustly synthesize the applied strategies/techniques and identify findings and gaps. In addition, a bibliometric analysis is performed to describe the co-citation network and statistical characteristics of the reviewed papers and identify the related research clusters. A typical procedure for CC adaptation studies is proposed based on previous studies. It is found that systems reoperation was preferred for CC adaptation in water resources management, specifically by updating the reservoir operation curves using optimization algorithms. However, low impact development (LID) measures were favored in storm drainage and flood mitigation systems. As for future relevant research, the main recommendations are integrating environmental, social, and economic aspects in evaluating CC adaptation strategies and incorporating land use and land cover (LULC) and water demand changes in CC adaptation studies. This state-of-the-art review represents essential information for improving CC adaptation strategies in water management.

Drought and population growth, especially in the western United States, are propelling a need for more efficient irrigation. Smart irrigation controllers, which interface with soil moisture, evapotranspiration (ET), or weather sensors, have been promoted as a demand-side management tool for this purpose. This paper reviews the body of research on residential smart irrigation controllers and their effectiveness. We find that smart irrigation controllers consistently reduce water demand by 15% among general users and more than 40% among indulgent users. Gaps in research include studies addressing peak demand reduction, centralized communication, data verifiability, and human factors of landscape management. Future work may develop techniques for coordinating networks of smart irrigation controllers to enable greater shifting and shaving of discretionary irrigation demands, similar to what is already happening in the electric grid, thereby creating an integrated water distribution system (IWDS). An IWDS may utilize smart irrigation controllers as direct load control devices at customer end points and interface with advanced metering infrastructure (AMI) and supervisory control and data acquisition (SCADA) systems at a central location to create more effective demand-side management (DSM) strategies for water conservation.

Weather-based irrigation controllers (WBICs) have become the prevalent smart controllers used for residential irrigation scheduling. They are easy to install, have smartphone control, are easy to program, utilize local real-time weather data, prevent operating the irrigation system during rain or other adverse weather events, adjust watering schedules and duration seasonally, conserve water, and reduce water billing costs. In addition to the ease of use and benefits at the residential user level, smart irrigation controllers have the potential to provide the water utility with controls to buffer or shift peak irrigation demands. This buffering and shifting of peak demands have the potential to lower energy costs, decrease the carbon footprint, and delay costly infrastructure upgrades. With technological advancements and the proliferation of smart controllers, the future for water utilities will become more similar to the electrical grid industry. The smart controllers and technology will enable the development of the IWDS. The IWDS will allow the water utility to utilize data from AMI meters, SCADA systems, smart irrigation controllers, artificial intelligence, and other smart technology to operate more effectively and efficiently.

Wearable sensing devices (WSDs) have enormous promise for monitoring construction worker safety. They can track workers and send safety-related information in real time, allowing for more effective and preventative decision making. WSDs are particularly useful on construction sites since they can track workers’ health, safety, and activity levels, among other metrics that could help optimize their daily tasks. WSDs may also assist workers in recognizing health-related safety risks (such as physical fatigue) and taking appropriate action to mitigate them. The data produced by these WSDs, however, is highly noisy and contaminated with artifacts that could have been introduced by the surroundings, the experimental apparatus, or the subject’s physiological state. These artifacts are very strong and frequently found during field experiments. So, when there is a lot of artifacts, the signal quality drops. Recently, artifacts removal has been greatly enhanced by developments in signal processing, which has vastly enhanced the performance. Thus, the proposed review aimed to provide an in-depth analysis of the approaches currently used to analyze data and remove artifacts from physiological signals obtained via WSDs during construction-related tasks. First, this study provides an overview of the physiological signals that are likely to be recorded from construction workers to monitor their health and safety. Second, this review identifies the most prevalent artifacts that have the most detrimental effect on the utility of the signals. Third, a comprehensive review of existing artifact-removal approaches were presented. Fourth, each identified artifact detection and removal approach was analyzed for its strengths and weaknesses. Finally, in conclusion, this review provides a few suggestions for future research for improving the quality of captured physiological signals for monitoring the health and safety of construction workers using artifact removal approaches.