No abstract

The reuse of greywater has several advantages, including reduced freshwater extraction from rivers, aquifers, and groundwater; reduced need for desalination; less environmental impact from septic tanks and water treatment plants; decreased energy consumption; and reduced chemical pollution. The main objectives of this review study are to assess the technical attributes, ecological impacts, and cost-efficiency of Moving Bed Biofilm Reactor (MBBR) water treatment technology compared to similar available technology for small to medium-sized, decentralized applications in residential and commercial settings such as home gardening, sanitation, and landfills. Previous studies indicate that hybrid technologies such as MBBR are the most promising methods for the total removal of contaminants in wastewater in a decentralized setting. However, the initial capital cost of this technology for small and medium-scale domestic applications worldwide is high and so is a limiting factor in the expansion of its utilization. Expansion of domestic use of such Decentralized Wastewater Treatment Systems (DWTS) could increase the economies of scale and therefore reduce the initial capital costs for this useful water treatment. For the MBBR system, Chemical Oxygen Demand (COD) removal efficiency was found to be 70%, Total Suspended Solids (TSS) removal was found to be 97%, and turbidity removal was 98%

The catastrophic implication of harmful algal bloom (HAB) events in the Arabian Gulf is a strong indication that the study of the spatiotemporal distribution of chlorophyll-a and its relationship with other variables is critical. This study analyzes the relationship between chlorophyll-a (Chl-a) and sea surface temperature (SST) and their trends in the Arabian Gulf and the Gulf of Oman along the United Arab Emirates coast. Additionally, the relationship between bathymetry and Chl-a and SST was examined. The MODIS Aqua product with a resolution of 1 × 1 km2 was employed for both chlorophyll-a and SST covering a timeframe from 2003 to 2019. The highest concentration of chlorophyll-a was seen in the Strait of Hormuz with an average of 2.8 mg m−3, which is 1.1 mg m−3 higher than the average for the entire study area. Three-quarters of the study area showed a significant correlation between the Chl-a and SST. The shallow (deep) areas showed a strong positive (negative) correlation between the Chl-a and SST. The results indicate the presence of trends for both variables across most of the study area. SST significantly increased in more than two-thirds of the study area in the summer with no significant trends detected in the winter.

Urban quality of life (UQoL) study is very important for many applications such as services distribution, urban planning, and socioeconomic analysis. The objective of this study is to create an urban quality of life index map for Al Ain city in the United Arab Emirates (UAE). The research aligns with the United Nations Sustainable Development Goals number ten (reduce inequalities) and eleven (sustainable cities and communities). In this study, remote sensing images and GIS vector datasets were used to extract biophysical and infrastructure facility indicators. The biophysical indicators are normalized difference vegetation index (NDVI), normalized difference water index (NDWI), modified normalized difference water index (MNDWI), soil adjusted vegetation index (SAVI), enhanced normalized difference impervious surfaces index (ENDISI), normalized difference built-up index (NDBI), land surface temperature (LST), slope, and land use land cover (LULC). In addition, infrastructure facility indicators such as distances to main roads, parks, schools, and hospitals were obtained. Additional infrastructure facility variables namely built-up to green area and build-up to bare soil area ratio were extracted from the LULC map. Machine learning was used to classify satellite images and generate LULC map. Random Forest (RF) was found as the best machine learning classifier for this study. The overall classification and Kappa hat accuracy was 95.3 and 0.92, respectively. Both biophysical and infrastructure facility indicators were integrated using principal component analysis (PCA). The PCA analysis identified four components that explain 75% of the variance among the indicators. The four factors were interpreted as the effect of LULC, infrastructure facility, ecological, and slope. Finally, the components were assigned weights based on the percentage of variance they explained and developed the UQoL map. Overall, the result showed that greenness has a greater effect on the spatial pattern of UQoL in Al Ain city. The study could be of a value to policy makers in urban planning and socioeconomic departments.

The authors investigate the perceptions, preferences, and valuation of university students in the United Arab Emirates (UAE) regarding the potential to adopt electric vehicles (EVs) for personal transport by surveying a diverse sample of 664 students from the seven emirates (the capital Abu Dhabi, Ajman, Dubai, Fujairah, Ras Al Khaimah, Sharjah and Umm Al Quwain). Details were elicited about social, economic, and environmental factors that influence the potential to adopt EVs for personal transport, perceived advantages of EVs over gasoline automobiles, and knowledge about EVs. The authors employed the SPSS software platform to categorize various factors according to age and gender. Respondents reported a wide variety of perspectives about EVs including environmental benefits and functional drawbacks. Findings show that participant perceptions, preferences, and valuation about EVs are influenced by a multiplicity of social, economic, and environmental factors. Neglect of these factors will undermine the potential to shift preferences toward greater adoption of emerging sustainable transport technologies.