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

CITATION: Aina, Y.A., Van der Merwe, J.H. & Alshuwaikhat, H.M. 2014. Spatial and temporal variations of satellite-derived multi-year particulate data of Saudi Arabia: An exploratory analysis. International Journal of Environmental Research and Public Health, 11(11):11152-11166, doi:10.3390/ijerph111111152.The original publication is available at www.mdpi.com/journal/ijerphThe 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.http://www.mdpi.com/1660-4601/11/11/11152Publisher's versio

Framing Electric Mobility for Urban Sustainability in a Circular Economy Context: An Overview of the Literature

The development of electro-mobility is one of the centerpieces of European country attempts to reduce carbon emissions and increase the quality of life in cities. The goals of reducing emissions from the transport sector and phasing out fossil-fueled vehicles in (urban) transport by 2050 present unrivaled opportunities to foster electro-mobility. This paper provides a comprehensive review of the literature and provides a detailed analysis of the current development of electro-mobility in Europe, assessing social, economic, and environmental aspects under a circular economy (CE) context. It also examines the existing challenges and suggests ways of addressing them towards improving the environmental performance of electro-mobility and the urban quality of life. The paper argues that a narrow technology-only agenda in electro-mobility will be less successful without the imperative of the CE, including not just materials and resources but also energy, to unlock the medium-term co-benefits of de-carbonization of both the transport as well as the building and energy sectors. The paper critically reviews some of the anticipated future developments that may guide the growth of this rapidly growing field into a CE

Design Thinking for Sustainable Development: a bibliometric analysis and case study research

This paper describes the role of Design Thinking (DT) in the context of sustainable development (SD), based on a perceived research need to identify the features which may characterise its deployment, and identify ways via which it may be optimised, especially in the implementation of the United Nations Sustainable Development Goals (UN SDGs). The main goal of this study is to examine the connection between DT and SD and showcase examples of what has been done to deploy it, using real-case situations. From a methodological perspective, the paper deploys a set of two methods: bibliometric analysis and case studies. Among other findings, the paper shows that DT can be used to help implement the UN SDGs by providing an approach that emphasises human-centred design. This includes identifying problems, creating user-friendly solutions, and testing them in order to ensure that they are effective. Also, by using DT, companies, organisations, and governments can create low-cost, high-impact, and sustainable solutions to help achieve SDGs such as SDG8, SDG9, SDG12, and SDG13, among others. Overall, DT provides a framework for combining creative and analytical reasoning, specific mindsets, and diverse hands-on tools and techniques to improve critical thinking abilities towards sustainability challenges. The novelty of the paper relies on the fact that the combined use of the two methods allowed the identification of some useful features of DT, which may facilitate its deployment in sustainability contexts. This may assist future studies since it provides a theoretical basis for the field

SUSTAINABLE PLANNING: THE NEED FOR STRATEGIC ENVIRONMENTAL ASSESSMENT-BASED MUNICIPAL PLANNING IN SAUDI ARABIA

The Saudi government has made some efforts in incorporating the principles of sustainable development into the planning process by establishing a framework for considering environmental consequences of development activities. The framework is guided by the General Environmental Code. The Ministerial Committee on the Environment (MCE) coordinates the environmental assessment of plans, policies and programmes prior to approval. However, the framework tends to focus on plans and programmes at the national level with little or no explicit provision for ensuring the assessment of municipal plans, policies and programmes. This paper evaluates the integration of environmental assessment into the municipal planning process and the plan documents. The findings indicate that the implementation of environmental assessment at the municipal planning level is minimal. Inadequate institutional framework and lack of effective environment assessment legislation are the main barriers to the implementation. Overall, the assessment shows that there is the need to improve sustainability planning practice in the Kingdom.Strategic environmental assessment, master plan, sustainable planning, sustainability indicators, Saudi Arabia

The Development of a GIS-Based Model for Campus Environmental Sustainability Assessment

Sustainability indicators and assessments are vital in promoting campus sustainability. Despite the plethora of indicator frameworks, campus sustainability assessment in developing countries encounters many challenges including lack of, or restricted access to, data and difficulties in measuring indicators. There is also a limited application of Geographical Information Systems (GIS) in campus environmental sustainability assessment, although campus operations have spatial dimensions. This article proposes a GIS-based model for environmental sustainability assessment of campus operations and demonstrates its usefulness using King Fahd University of Petroleum and Minerals, Saudi Arabia. The model applies spatial analysis techniques, including inverse distance weighted (IDW) interpolation, to statistically assess the various campus operational activities by using land use data to estimate greenhouse gas emissions from energy use, water consumption, solid waste, and transportation. The integration of spatial dimension in the model facilitates the collection and measurement of spatially related indicators, helps identify hotspots of campus operations, and provides better visualization of the existing condition and future scenario of campus environmental sustainability status. This model can assist decision-makers to construct strategies for improving the overall environmental sustainability of university campuses. The paper concludes by highlighting how the model can address some challenges of campus sustainability assessment in developing countries

Evaluation of different combinations of palm kernel cake - and cotton seed cake - based diets on the performance of West African Dwarf goats

An experiment was carried out using 15 West African Dwarf goats (8 - 10kg body weight) to investigate the comparative performance of the animals when different combinations of palm kernel cake and cotton seed cake were contained in their diets. Results indicated that 40% palm kernel cake (zero cotton seed cake) in the diets significantly induced better feed utilization for gain (100g/d) and feed conversion ratio (3.70), least total dry matter intake (4.8% body weight) and least water consumption (40ml/ w0.75 kg; P>0.05) than other combinations. The least crude protein (15.5%) and the highest metabolizable energy (8.37MJ/kg) diet (40% PKC) provoked the fastest growth rate (100g/d) in the animals. Concentrate intake was higher in all the treatments than grass intake. The blood glucose, total blood protein, blood urea nitrogen and cost per kg body weight (18.3, 13.3, 31.0mg/dl and N33.8 (0.4 US dollar), respectively) were significantly lower in goats fed sole palm kernel cake based diets than those fed combinations of palm kernel cake and cottonseed cake. It is concluded that palm kernel cake alone (without any combination with cottonseed cake) is adequate as protein source in compounding protein supplements for West African Dwarf goats for profitable performance.Keywords: Palm kernel cake, cotton seed cake, goats, performance

The influence of urban form on the spatiotemporal variations in land surface temperature in an arid coastal city

This article explores using satellite images to monitor spatiotemporal variations in temperature related to urban form. Land surface temperatures (LST) were estimated from Landsat images (1986–2016) and the land cover and urban form LST were extracted by using samples representing different urban forms/cover types. A transect of 20 km was taken across the city to derive the LST across the different land cover types. Urban heat island index and statistical analysis were carried out to understand the influence of urban form and cover on changes in surface temperature. The results are compared with temperature regimes of an industrial city (Yanbu) to depict differences in the two cities. The analysis of variance (ANOVA) shows variations, at 0.01 level of significance, in the LST values of the city centre, high-rise, low-density, vegetation, desert and industrial land-use types. The outcome of the study is valuable for decision-makers in achieving sustainable urban development

A ticket to where? Dwindling snow cover impacts the winter tourism sector as a consequence of climate change

https://v2.sherpa.ac.uk/id/publication/11372Climate change affects human activities, including tourism across various sectors and time frames. The winter tourism industry, dependent on low temperatures, faces significant impacts. This paper reviews the implications of climate change on winter tourism, emphasising challenges for activities like skiing and snowboarding, which rely on consistent snowfall and low temperatures. As the climate changes, these once taken-for-granted conditions are no longer as commonplace. Through a comprehensive review supported by up-to-date satellite imagery, this paper presents evidence suggesting that the reliability of winter snow is decreasing, with findings revealing a progressive reduction in snow levels associated with temperature and precipitation changes in some regions. The analysis underscores the need for concerted efforts by stakeholders who must recognize the reality of diminishing snow availability and work towards understanding the specific changes in snow patterns. This should involve multi-risk and multi-instrument assessments, including ongoing satellite data monitoring to track snow cover changes. The practical implications for sports activities and the tourism industry reliant on snow involve addressing challenges by diversifying offerings. This includes developing alternative winter tourism activities less dependent on snow, such as winter hiking, nature walks, or cultural experiences.info:eu-repo/semantics/publishedVersio

Assessing the suitability of GlobeLand30 for land cover mapping and sustainable development in Malaysia using error matrix and unbiased area Estimation

Global Land Cover (GLC) maps have been extensively used as background data for numerous applications such as land-use planning, climate change monitoring, and urban planning. While countries in Europe and North America have greatly developed land cover maps, several developing countries in Asia and Africa lack such vital data sources. GlobeLand30’s 30 m resolution dataset has the potential to meet the mapping needs of these developing regions. However, differences in accuracy of the dataset between countries can be significant making it unsuitable to adopt regional accuracy directly for assessing individual country’s accuracy level. Therefore, it is critical to develop reliable localized assessments. This research assesses the accuracy of GlobeLand30 for Malaysia using multiple evaluation approaches. Seven classes of land cover data were evaluated using 197 samples in the country. An overall accuracy of 63.45% and 65.70% was obtained from the Error Matrix using sample counts and the new unbiased area estimator respectively. We conclude that the overall accuracy of GlobeLand30 in tropical developing countries like Malaysia is generally lower than the accuracy in developed countries and arid developing countries thereby requiring significant improvement for optimal use. However, despite the errors due largely to misclassification, the GlobeLand 30 data has the potential to complement other LULC data to estimate and monitor vital land-use changes in Malaysia and the ASEAN region in general for sustainable development

Assessment of data mining, multi-criteria decision making and fuzzy-computing techniques for spatial flood susceptibility mapping: a comparative study

This study develops an Adaboost-GIS model for flood susceptibility mapping and evaluates its relative performance by undertaking a comparative assessment of the machine learning model with Multi-Criteria Decision Making (MCDM) and soft computing models integrated with GIS. An Analytic Hierarchy Process (AHP), Analytic Network Process (ANP), Fuzzy-AHP, Fuzzy-ANP and AdaBoost machine learning models were developed and integrated with GIS to classify the susceptibility of the study area. Out of 70 sample validation locations, Adaboost’s performance was the best with a 95.72% similarity match with very high and high susceptibility locations followed by F-ANP, ANP, F-AHP and AHP with 95.65%, 92.75%, 81.42% and 77.14% similarity matches, respectively. It also had the highest AUC (0.864). Thus, the Adaboost machine learning, Fuzzy computing and conventional MCDM models can be adopted by stakeholders for accurately assessing flood susceptibility, thereby fostering safe and resilient cities