A GIS-based approach to determining optimal location for decentralized inner city smart filters: Toward net zero cities.

Climate change has already begun to take visible effect globally in recent years. Given the climate change paradox and urbanization trends, cities' success would not only depend on smartness and sustainability, but also resilience to all forthcoming economic, environmental, or behavioral changes. Numerous technologies have surfaced and proved effective in CO2 removal from the local environment. However, the optimal placement of these smart filters is a complex task and require logical and strategic decision-making. Determining the optimal location is one of the key factors for establishing a network of smart air filters. This study used a GIS-based suitability analysis for identifying optimal locations for smart filters based on pollution hotspots (population and spatial proximity to industry, commercial centers, roads, high-traffic areas, and intersections). The spatial analysis involves the determination and preparation of input layers, ranking layers, assigning weights to each criterion, and generation of a suitability map. The sites with a higher suitability score (7 or above) are optimum sites for air filters. The sites are spatially distributed over different regions. The findings revealed that GIS-based suitability analysis can be an effective technique for placing smart filters within an urban environment. These findings can help decision-makers to prioritize the location considering environmental constraints. The proposed solution aims to pave the way for fostering resilient, smart, and sustainable cities through a community sensing platform targeting hotspots within spatial variations.

The development of a grey relational analysis-based composite index for environmental sustainability assessment: Towards a net-zero emissions strategy in Saudi Arabia.

Climate change and environmental sustainability assessment are essential in city planning, design, and smart city advancement. Despite Saudi Arabia's high global greenhouse gas (GHG) emissions ranking, a comprehensive review of extant studies revealed insufficient tools enhancing the policymaking and comprehension of climate change and environmental performance. This paper developed a hybrid green city index (GCI) and grey relational analysis (GRA) composite index for appraising national environmental sustainability via a robust, efficient, effective, and replicable grading process. The index is designed based on two primary considerations. The first is the selection of quality underlying indicators/categories, while the second is the adoption of GRA for conducting the normalization, weighting and aggregation process. These two considerations influenced the proposed composite index, which was later applied to Saudi Arabia as a study area. The results revealed that the environmental sustainability of Saudi Arabia is not significant, with the most outstanding of 0.3127 for 2010. At the category level, the favourable environmental sustainability ranking is between the 2010 and 2012 assessment period, with a gradual decline till 2018. This study's findings are unique as no studies within the context of Saudi Arabia and the Gulf region have utilized this study's research approach. Although not all indicators of the proposed index were used in the study area, this study's methodology and outcomes have the beneficial impact of assisting Saudi Arabia's decision-makers across the cities in monitoring the status and progress of implementing its net zero carbon emissions by 2060.

Analysis of the implementation of urban computing in smart cities: A framework for the transformation of Saudi cities.

Smart city development is gaining widespread acceptance as a means of mitigating urban development problems. However, the implementation of smart cities faces challenges, especially in developing countries. Urban computing is regarded as an enabler of innovation and smart city development. This study explores the adoption of urban computing to address the smart city and urban development problems of Saudi cities. Using a systematic review, this study highlights the trends and influential contributions of urban computing to smart city research. It identifies the urban computing framework and uses the framework to analyze the use of urban computing in Saudi cities to promote smart city development and sustainability. While Saudi Arabia has taken notable steps in urban computing, especially in providing services, further steps need to be taken to achieve the transformation into smart sustainable cities.

Spatial and temporal variations of satellite-derived multi-year particulate data of Saudi Arabia: an exploratory analysis.

The effects of concentrations of fine particulate matter on urban populations have been gaining attention because fine particulate matter exposes the urban populace to health risks such as respiratory and cardiovascular diseases. Satellite-derived data, using aerosol optical depth (AOD), have been adopted to improve the monitoring of fine particulate matter. One of such data sources is the global multi-year PM2.5 data (2001-2010) released by the Center for International Earth Science Information Network (CIESIN). This paper explores the satellite-derived PM2.5 data of Saudi Arabia to highlight the trend of PM2.5 concentrations. It also examines the changes in PM2.5 concentrations in some urbanized areas of Saudi Arabia. Concentrations in major cities like Riyadh, Dammam, Jeddah, Makkah, Madinah and the industrial cities of Yanbu and Jubail are analyzed using cluster analysis. The health risks due to exposure of the populace are highlighted by using the World Health Organization (WHO) standard and targets. The results show a trend of increasing concentrations of PM2.5 in urban areas. Significant clusters of high values are found in the eastern and south-western part of the country. There is a need to explore this topic using images with higher spatial resolution and validate the data with ground observations to improve the analysis.