Conflict between Population and Urbanization Factors： Impact of Urban Heat Island on Energy Consumption Balance

High density of buildings and population in urban areas increases urban temperature, generally known as the urban heat island. Raised temperature, especially in SUlIuner, alms city centers into unwelcome hot areas, with direct effects on electricity demand and energy consttrnption for cooling buildings and increases the production of carbon dioxide and other pollutants. Therefore, by considering that the energy consumption in the world has been faced with intense crisis, it becomes increasingly important to study the effects of urban heat island on energy constunption in order to improve people＇s environment and decrease energy use in cities. This paper, therefore, is focused on urbanization and population size factors to understand tile influence way of these factors on formation of UHI and energy consumption balance. To achieve this aim, this paper explores literally the conceptual framework of confliction between population and urban structure, which produce UHI intensity and affected energy consumption balance. It is then discussed how these two factors can be affected and give implication to the city, and then, focuses on whether actions should be taken for balancing adaptation and mitigation UHI effects. It will be concluded by making the recommendations for preventive action and provide quality of life.

Artificial Intelligence:A new era for spatial modelling and interpreting climate-induced hazard assessment

The application of Artificial Intelligence in various fields has witnessed tremendous progress in the recent years.The field of geosciences and natural hazard modelling has also benefitted immensely from the introduction of novel algorithms,the availability of large quantities of data,and the increase in computational capacity.The enhancement in algorithms can be largely attributed to the elevated complexity of the network architecture and the heightened level of abstraction found in the network's later layers.As a result,AI models lack transparency and accountability,often being dubbed as"black box"models.Explainable AI(XAI)is emerging as a solution to make AI models more transparent,especially in domains where transparency is essential.Much discussion surrounds the use of XAI for diverse purposes,as researchers explore its applications across various domains.With the growing body of research papers on XAI case studies,it has become increasingly important to address existing gaps in the literature.The current literature lacks a comprehensive understanding of the capabilities,limitations,and practical implications of XAI.This study provides a comprehensive overview of what constitutes XAI,how it is being used and potential applications in hydrometeorological natural hazards.It aims to serve as a useful reference for researchers,practitioners,and stakeholders who are currently using or intending to adopt XAI,thereby contributing to the advancements for wider acceptance of XAI in the future.

Assessing household perception,autonomous adaptation and economic value of adaptation benefits:Evidence from West Coast of Peninsular Malaysia

Climate change is causing sea-level rise,intense and frequent storm surge flooding,and significant shoreline erosion in Malaysian coastal areas.Consequently,coastal properties,infrastructure,and livelihoods are threatened.It has become apparent that adaptation at the household and community level is necessary to offset the adverse impacts of coastal hazards.The community needs to be made aware of the risks,acquire knowledge about adaptation options,and be empowered to take their own actions.Public perception and preference are therefore crucial for design and implementation of effective planning for climate change.Thus,this study assesses households'perception,adaptation measures and empirically estimates willingness to pay and preference for planned adaptation measures to guide policy instruments through public engagement.In Malaysia,ten highly vulnerable coastal areas in the Selangor coast were surveyed at the household level(n=1016)through face-to-face interviews using a structured questionnaire.Regarding households’perception and adaptation methods,most of the households in the highly exposed areas perceived less risk of inundation and sea-level rise threat and adopted less proactive adaptation and limited risk reduction behaviours during the extreme event.The study found that 66.9%of households were willing to pay for planned adaptation measures despite the limited income capabilities and in favour of moderate adaptation(23.9%).The binomial and ordinal regression results indicated that the probability of willingness to pay for planned adaptation measures significantly increases with age,prior exposure to coastal hazards,awareness,risk perception,community participation,being affected by property damage and loss of income due to extreme events.With increased monthly household income and access to telecommunication services,households will probably pay higher for better adaptation measures.A significant amount of perceived yearly adaptation benefits in the coastal districts revealed the economic value of extensive(22,969.50 MYR/5462.43 USD),moderate(21,853.20 MYR/5196.96 USD)and minimal adaptation measures(8022.90 MYR/1907.94 USD)that can be utilised to incentivise coastal adaptation plans.The findings suggest policies to incorporate social values to reduce vulnerability,enhance community resilience,and contribute to the knowledge gap of adaptation research in the coastal areas.