The current article reviews the state of art of the perfluoroalkyl and polyfluoroalkyl substances (PFASs) compounds and provides an overview of PFASs occurrence in the environment, wildlife, and humans. This study reviews the issues concerning PFASs exposure and potential risks generated with a focus on PFAS occurrence and transformation in various media, discusses their physicochemical characterization and treatment technologies, before discussing the potential human exposure routes. The various toxicological impacts to human health are also discussed. The article pays particular attention to the complexity and challenging issue of regulating PFAS compounds due to the arising uncertainty and lack of epidemiological evidence encountered. The variation in PFAS regulatory values across the globe can be easily addressed due to the influence of multiple scientific, technical, and social factors. The varied toxicology and the insufficient definition of PFAS exposure rate are among the main factors contributing to this discrepancy. The lack of proven standard approaches for examining PFAS in surface water, groundwater, wastewater, or solids adds more technical complexity. Although it is agreed that PFASs pose potential health risks in various media, the link between the extent of PFAS exposure and the significance of PFAS risk remain among the evolving research areas. There is a growing need to address the correlation between the frequency and the likelihood of human exposure to PFAS and the possible health risks encountered. Although USEPA (United States Environmental Protection Agency) recommends the 70 ng/L lifetime health advisory in drinking water for both perfluorooctane sulfonate (PFO) perfluorooctanoic acid (PFOA), which is similar to the Australian regulations, the German Ministry of Health proposed a health-based guidance of maximum of 300 ng/L for the combination of PFOA and PFOS. Moreover, there are significant discrepancies among the US states where the water guideline levels for the different states ranged from 13 to 1000 ng L⁻¹ for PFOA and/or PFOS. The current review highlighted the significance of the future research required to fill in the knowledge gap in PFAS toxicology and to better understand this through real field data and long-term monitoring programs.

There is a growing need for more sustainable wastewater treatment technologies to provide non-conventional water sources. Constructed Wetland systems (CW) are viewed as a low-cost treatment technology with proven treatment efficiency. CWS can treat a variety of contaminants using low energy and natural systems by altering various design parameters. There are two configuration types of constructed wetlands: vertical (VF) and horizontal flow CW (HF). Both configurations have been widely adopted in both large and pilot scale studies with proven records of reasonable wastewater treatment efficiency. The current article reviews the recent development of CW technology and highlights the main achievements and successful applications for wastewater treatment at various locations. The review has indicated that a considerable removal efficiency is attained while using engineered CW systems with variable treatment rates for various pollutants. The treatment efficiency is a function of various parameters including wastewater type, scale dimensions, applied plant and the retention time. The review compared the treatment efficiency for both VF and HF and has revealed that various removal rates of BOD, COD, TSS, TN, TP and NH₄ was attained using both configurations. Yet, the removal efficiency in the case of VF was slightly higher compared with the HF with an average treatment level of 77% and 68% was achieved in both systems, respectively. The review revealed that the CW is an effective and sustainable technology for wastewater treatment with the initial influent level, microbial biofilm, detention time, plant species and configuration among the most dominating parameters that are directly controlling the removal rates.

This study aims to estimate the carbon footprint and relative uncertainties for design components of conventional and geopolymer concrete. All the design components of alkaline-activated geopolymer concrete, such as fly ash, ground granulated blast furnace slag, sodium hydroxide (NaOH), sodium silicate (Na₂SiO₃), superplasticizer, and others, are assessed to reflect the actual scenarios of the carbon footprint. The conjugate application of the life cycle assessment (LCA) tool SimPro 9.4 and @RISK Monte Carlo simulation justifies the variations in carbon emissions rather than a specific determined value for concrete binders, precursors, and filler materials. A reduction of 43% in carbon emissions has been observed by replacing cement with alkali-activated binders. However, the associative uncertainties of chemical admixtures reveal that even a slight increase may cause significant environmental damage rather than its benefit. Pearson correlations of carbon footprint with three admixtures, namely sodium silicate (r = 0.80), sodium hydroxide (r = 0.52), and superplasticizer (r = 0.19), indicate that the shift from cement to alkaline activation needs additional precaution for excessive use. Therefore, a suitable method of manufacturing chemical activators utilizing renewable energy sources may ensure long-term sustainability.

There is a growing global interest in preserving transportation infrastructure. This necessitates routine evaluation and timely maintenance of road networks. The effectiveness of pavement management systems (PMSs) heavily relies on accurate pavement deterioration models. However, there are limited comparative studies on modeling approaches for rural roads in arid climatic conditions using the same datasets for training and testing. This study compares three approaches for developing a pavement condition index (PCI) model as a function of pavement age: classical regression, machine learning, and deep learning. The PCI is a pavement management index widely adopted by many road agencies. A dataset on pavement age and distress was collected over a twenty-year period to develop reliable predictive models. The results demonstrate that the regression model, machine learning model, and the deep learning model achieved a coefficient of determination ($R^2$) of 0.973, 0.975, and 0.978, respectively. While these values are technically equal, the average bias for the deep learning model (1.14) was significantly lower than that of the other two models, signaling its superiority. Additionally, the trend predicted by the deep learning model showed more distinct phases of PCI deterioration with age than the machine learning model. The latter exhibited a wider range of PCI deterioration rates over time compared to the regression model. The deep learning model outperforms a recently developed regression model for a similar region. These findings highlight the potential of using deep learning to estimate pavement surface conditions accurately and its efficacy in capturing the PCI-age relationship.

Coupled human and natural systems (CHANS) represent dialectic interaction between human and nature subsystems. This dynamic interaction involves a prominent level of complexity stemming from the uncertain interrelation between the systems and the incorporated subsystems. The complexity within CHANS includes reciprocal effects, nonlinearity, uncertainties, and heterogeneity. Although many researchers have highlighted the significance of understanding the nature of the coupling effect, most of the prevailing literature emphasises either human or natural systems separately, while considering the other as exogenous, despite evaluating the reciprocal and complex interrelations. The current review utilises the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA). It focuses on synthesising the prevailing literature on the CHANS framework in several disciplines, focusing on the approach, findings, limitations, and implications. The review comprises 56 relevant articles, found through Endnote and Covidence database searches. The findings identify the dominant complexity character as reciprocal effects and feedback loops, confirming the complex interactions between human and natural systems. Furthermore, the review provides evidence surrounding the significance of developing an analytical framework that can better explain the complex connections between humans and nature, as it provides a comprehensive understanding of CHANS and their potential impacts.

Poorly developed regions in the Gaza Strip, Palestine, face significant risks to public safety, the environment, and stormwater infrastructure due to soil erosion and deposition. This study is the first of its kind to investigate soil erosion in this area. A revised universal soil loss equation (RUSLE) model was utilized and validated using field measurements of accumulated sediments at three major stormwater detention basins from 2014 to 2020. High-resolution maps were created to capture the urbanization effect and to further improve the future prediction of urbanization. The findings revealed that the highest potential for sediment generation in the Gaza governorate occurred over the slopes of the eastern ridge, which drain toward the city center. Sediment generation ranged from 1784 to 4281 ton/ha for the years of 2018 and 2020, respectively. The average sediment delivery ratio (SDR) was calculated to be 0.00134. The estimations for sediment export ranged from 0 to 135.3 ton/ha for the year 2020, with an average of 0.0737 ton/ha. The urban areas exhibited the least sediment export rate; however, the model revealed abnormal behavior for a dataset of the field measurements which was ascribed to the impact of destruction/reconstruction activities in the corresponded watersheds that followed the war in 2014. This conducted research stands as a pioneering effort in quantifying and cartographically representing sediment erosion potential within the Gaza Strip. Thus, it serves as an indispensable point of reference for future researchers in terms of the employed parameterization and calibration methodology. Furthermore, it holds distinct significance as an unparalleled resource for experts and stakeholders who are invested in comprehending the ramifications of erosion on urban landscapes and drainage systems.