Particulate mater with 10 μm or less in diameter PM 10 ) is known to have adverse efects on human health and the environment. For countries commited to reducing PM 10 emissions, it is essential to have models that accurately estimate and predict PM 10 concentrations for reporting and monitoring purposes. In this chapter, a broad overview of recent empirical statistical and machine learning techniques for modelling PM 10 is presented. This includes the instrumentation used to measure particulate mater, data preprocessing, the selection of explanatory variables and modelling methods. Key features of some PM 10 prediction models developed in the last 10 years are described, and current work modelling and predicting PM 10 trends in New Zealand a remote country of islands in the South Paciic Ocean are examined. In conclusion, the issues and challenges faced when modelling PM 10 are discussed and suggestions for future avenues of investigation, which could improve the precision of PM 10 prediction and estimation models are presented.

No abstract

No abstract

According to the roadmap designed by the European Commission (2011), it has become mandatory for the European countries to promote renewable sources to provide their required energy by 2050 (Babonneau et al., 2016; Read et al., 2016). The main goal for this switch from fossil fuels to renewable energy sources, is to mitigate the release of CO2 into the atmosphere (Crotogino et al., 2010; Türkseven Doğrusoy and Serin, 2015; Reuß et al., 2017). However, the utilization of the renewable energy sources (RES) is Centre for Research on Settlements and Urbanism Journal of Settlements and Spatial Planning J o u r n a l h o m e p a g e: http://jssp.reviste.ubbcluj.ro One of the consequences of rapid global population growth is the increase in the energy demand. Currently, the main source of energy for various applications is fossil fuels, which are not renewable and their utilization at large scales have caused a number of environmental issues such as global warming. Hydrogen is one of the main renewable energy sources; however, its utilization has not yet been sufficiently commercialized due to some existing technical issues. For large-scale underground Hydrogen storage facilities, selecting the most suitable setup location is accounted to be a crucial factor in order to use Hydrogen as a promising and environmentally friendly energy carrier. This study aims to develop an expert judgment approach for the prioritization of criteria involving site selection of large-scale Hydrogen storage facilities to support development of modern cities and industries. In this regard, Fuzzy-Delphi methodology was used to prioritize the criteria and sub-criteria, which seemed to be most relevant for the underground Hydrogen storage site selection process. A comprehensive screening was performed in the literature and eighteen criteria from technical, economic, health, safety and environment (HST) and social points of view were extracted. A professional questionnaire was designed for the criteria prioritization and SPSS 25.0 was employed to analyse the achieved results. According to the gained results, the most important sub-criteria were identified as legal restrictions, reservoir permeability and porosity, and regional risks. Also, the findings demonstrated that HSE and technical issues of sustainability for the site selection of H2 underground storage were more underscored in comparison to economic and social criteria. It is concluded that more in-depth studies are still needed to cover more aspects of sustainability regarding site selection for underground gas storages with special focus on social dimensions.

No abstract

No abstract

In recent decades, the pace of industrialization has caused an number of environmental problems. A considerable increase in the global energy demand is one of the most important problems in today’s world. In fact, fossil fuels are the main source of energy triggering the release of huge amounts of greenhouse gases into the atmosphere. Many efforts have been made by researchers to come up with different strategies to mitigate the global consequences of greenhouse gas emissions such as global warming. One of these strategies is to reduce the amount of greenhouse gas emited into the atmosphere. This study aims to select the appropriate sites for carbon dioxide underground storage facilities. The selection of the best sites for CO2 underground storage is very important from various perspectives of sustainable development to accelerate the commercialization of such facilities. In this regard, fuzzy-Delphi methodology was used to prioritize the most important criteria in the CO2 storage process. Nineteen sub-criteria were selected in the technical, health, safety and environmental (HSE), economic and social categories. Specialist questionnaires were prepared, considering all relevant scientific and technical aspects, and experts in the field were invited to participate in the survey. The results were analyzed using SPSS 25.0. According to results, Geology and Lithology, Caprock Permeability, Social Acceptance, Depth, Reservoir Permeability, and Porosity were determined as the highest priorities. Based on the results achieved, it can be concluded that technical criteria are of the highest importance in the site selection of underground carbon dioxide site selection facilities.

No abstract