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Summary: Motivation: Communities across the global south use their rich indigenous and local knowledge (ILK) to predict weather events and climate hazards. ILK may assist efforts to address climate change challenges in Africa and make subsequent decisions regarding climate adaptation. Purpose: The article documents evidence of the ILK's potential in reducing vulnerability to climate change and/or improving the resilience of communities. The study also reflects on major barriers that hinder the improved mainstreaming of ILK into adaptation strategies. Methods and approach: The present study uses two main methods: a literature review and a presentation of case studies from a sample of African countries where ILK informs adaptation options, including indigenous land‐tenure practices and weather prediction. The selected case studies highlight the historical legacy of ILK and its effectiveness in reducing vulnerability and the impacts of climate change. Findings The results indicate that, despite being acknowledged as a valuable resource for climate adaptation, current national adaptation policies on the African continent still show serious gaps in effectively integrating ILK systems within the legal frameworks to reduce vulnerability. Policy implications: ILK should be better integrated with modern climate change adaptation strategies to anticipate more effective responses. Both rural communities and relevant government agencies should complement the use of ILK with climate change strategies, so as to maximize its contribution to the effective implementation of climate change policies. [ABSTRACT FROM AUTHOR]

In sub-Saharan Africa, mass rural-urban migration negatively affectthe agriculture sector that accounts for about 23% of the GDP and employs over 60% of the population. Together with a rapidly changing climate, unplanned urbanization poses serious threats to Africa's agriculture sector with the risk of chronic food shortages in the future. To stem this tide, it is imperative to systematically assess the unplanned urbanization trend from a socio-economic perspective and distill the broader implication for sustainable urban farming within the context of climate change in the region. The potentials of digitalization as a tool for transformative adaptation to climate change and enabler of sustainable development in different domains, including agriculture, are beginning to emerge. However, most studies are based on data from Asia, Europe, North America, and Oceania. There is minimal documentation of current applications and prospects of digitalization for sustainable agricultural practices in Africa, particularly in an increasingly urbanized era. Thus, this study addresses this need by evaluating the potentials of digitalization to enable sustainable farming in the face of unprecedented climate change constraints in Africa and minimize the negative impacts of urbanization on agriculture. Through a desk research approach, the present study explores the challenges to digital farming in Africa despite its successful implementation in the global North. Drawing lessons from successful case-studies worldwide, we suggest possible pathways to overcome the challenges and implement localized digitalization approaches to strengthen preventive action against climate risks, enhance disaster preparedness, and aid effective planning and management of agriculture practices. Integrating agriculture into the city via digital urban farming is crucial for long-term food security and creating appealing clean-tech jobs for a large number of new immigrants, thereby supporting African cities' resilience and sustainable development. [ABSTRACT FROM AUTHOR]

Many cities across the world are facing many problems climate change poses to their populations, communities and infrastructure. These vary from increased exposures to floods, to discomfort due to urban heat, depending on their geographical locations and settings. However, even though some cities have a greater ability to cope with climate change challenges, many struggle to do so, particularly in cities in developing countries. In addition, there is a shortage of international studies which examine the links between climate change adaptation and cities, and which at the same time draw some successful examples of good practice, which may assist future efforts. This paper is an attempt to address this information need. The aim of this paper is to analyse the extent to which cities in a sample of developing countries are attempting to pursue climate change adaptation and the problems which hinder this process. Its goal is to showcase examples of initiatives and good practice in transformative adaptation, which may be replicable elsewhere. To this purpose, the paper describes some trends related to climate change in a set of cities in developing countries across different continents, including one of the smallest capital cities (Georgetown, Guyana) and Shanghai, one the world's most populous cities. In particular, it analyses their degree of vulnerability, how they manage to cope with climate change impacts, and the policies being implemented to aid adaptation. It also suggests the use of transformative approaches which may be adopted, in order to assist them in their efforts towards investments in low-carbon and climate-resilient infrastructure, thereby maximizing investments in urban areas and trying to address their related poverty issues. This paper addresses a gap in the international literature on the problems many cities in developing countries face, in trying to adapt to a changing climate. Unlabelled Image • Studies on adaptation challenges in developing cities are scarce. • Ageing and failing infrastructure limit cities' resilience. • There is a positive relationship between cities' income level and adaptation capacity. • Large population is not a barrier per se to a city's adaptation capacity. • Most cities lack local-level climate policies and programmes. [ABSTRACT FROM AUTHOR]

Africa is one of the most vulnerable regions in respect of climate change. As the African continent struggles to adapt to climate change, a variety of measures are being pursued to alleviate the resultant pressures on people, properties and their livelihoods in several African cities. Collectively, they show that climate change adaptation in Africa is not as hopeless as widely claimed, and that there are some promising prospects. The literature shows a deficiency on studies which examine the extent to which climate change adaptation is being pursued in African cities. This paper addresses this need, and outlines some of the most important climate threats (e.g. increasing temperatures, droughts, sea level rise, sea and river flooding) and synergic non-climate factors, as well as recent progress made in respect of implementing climate change adaptation in African cities. Rather than adopt a general description of trends, this research focuses on concrete case studies from six major cities across the central, western, and eastern regions of the African continent (Douala, Lagos City, Dar-es-Salaam, Accra, Addis Ababa and Mombasa). The vulnerability and adaptive capacity status of the studied cities are discussed. Difficulties and challenges encountered in implementing adaptation policies in these areas are also highlighted. Furthermore, some successful examples of climate change adaptation initiatives in the surveyed cities are provided. Finally, the paper outlines some of the policy measures which can be implemented towards strengthening the capacity of African cities to adapt to a changing climate. [ABSTRACT FROM AUTHOR]

Climate change is generally known to impact ozone concentration globally. However, the intensity varies across regions and countries. Therefore, local studies are essential to accurately assess the correlation of climate change and ozone concentration in different countries. This study investigates the effects of climatic variables on ozone concentration in Malaysia in order to understand the nexus between climate change and ozone concentration. The selected data was obtained from ten (10) air monitoring stations strategically mounted in urban-industrial and residential areas with significant emissions of pollutants. Correlation analysis and four machine learning algorithms (random forest, decision tree regression, linear regression, and support vector regression) were used to analyze ozone and meteorological dataset in the study area. The analysis was carried out during the southwest monsoon due to the rise of ozone in the dry season. The results show a very strong correlation between temperature and ozone. Wind speed also exhibits a moderate to strong correlation with ozone, while relative humidity is negatively correlated. The highest correlation values were obtained at Bukit Rambai, Nilai, Jaya II Perai, Ipoh, Klang and Petaling Jaya. These locations have high industries and are well urbanized. The four machine learning algorithms exhibit high predictive performances, generally ascertaining the predictive accuracy of the climatic variables. The random forest outperformed other algorithms with a very high R2 of 0.970, low RMSE of 2.737 and MAE of 1.824, followed by linear regression, support vector regression and decision tree regression, respectively. This study's outcome indicates a linkage between temperature and wind speed with ozone concentration in the study area. An increase of these variables will likely increase the ozone concentration posing threats to lives and the environment. Therefore, this study provides data-driven insights for decision-makers and other stakeholders in ensuring good air quality for sustainable cities and communities. It also serves as a guide for the government for necessary climate actions to reduce the effect of climate change on air pollution and enabling sustainable cities in accordance with the UN's SDGs 13 and 11, respectively. • Climate change has the potential to influence air pollution. • Temperature is an essential factor for ozone pollution. • Wind serves as a medium for transboundary pollution. • Random forest outperformed the other machine learning algorithms for surface ozone prediction. • Industrialized and urbanized areas are hotspots for bad air quality. [ABSTRACT FROM AUTHOR]

• AI and DT are helpful in climate change teaching, research and SDGs implementation. • AI contributes to climate change adaptation similar to climate-smart technologies. • AI is a game-changer towards innovative solutions to pressing climate change threats. • AI is extensively applied to increase climate change adaptation in both Americas. • AI contributes to climate resilience and the post-COVID-19 recovery process. • DTs enhance governance and policy coherence in climate change adaptation. Artificial Intelligence (AI) is believed to have a significant potential use in tackling climate change. This paper explores the connections between AI and climate change research as a whole and its usefulness in climate change adaptation efforts in particular. Using a systematic review of the literature on applications of AI for climate change adaptation and a questionnaire survey of a multinational and interdisciplinary team of climate change researchers, this paper shows the various means via which AI can support research on climate change in diverse regions, and contribute to efforts towards climate change adaptation. The surveyed articles are classified under nine areas, e.g., Global/Earth Related; Water-related Issues and agriculture, 95% of which are related to adaptation. The areas that have attracted the most studies about AI applications are water-related management issues (38%). In terms of the survey results, the most robust agreements were noted concerning the capacity of digitisation and AI to strengthen governance practices and afford policy coherence in climate change. Evidence gathered in the study suggests that, provided that due care is taken, the use of AI can provide a welcome support to global efforts to better understand and handle the many challenges associated with a changing climate. [ABSTRACT FROM AUTHOR]

Air pollution is a global geo-hazard with significant implications, including deterioration of health and premature death. Climatic variables such as temperature, rainfall, wind, and humidity impact air pollution by affecting the strength, transportation, and dispersion of pollutants in the atmosphere. Emerging data science tools, particularly Machine Learning (ML) big data analytics, are being utilized to predict air pollution intensity and frequency under varying climatic conditions for effective mitigation plans. However, comprehensive documentation of these digitalization approaches and outcomes in terms of correlating future air pollution with climate change remains scant. This study addresses this gap by systematically reviewing pertinent literature on climate change and air pollution studies. We also investigated the potentials of integrated spatial data science for spatial modelling and identifying cities vulnerable to air pollution hazards. Our findings show that climatic factors and seasonal variations are critical predictors of air quality in urban areas. A strong correlation exists between climate change and air quality, and air quality in urbanized regions is projected to deteriorate with climate change in the future. Therefore, climatic variables remain essential factors for the prediction of air quality. Also, air pollutants tend to have higher concentration in the warm season, making the consideration of seasonal changes crucial in air quality management. The study also revealed that machine learning algorithms such as random forest, gradient boosting machine, and classification and regression trees (CART) accurately predict air pollution hazard when integrated with spatial models. The detailed review of literature undertaken in this study provides a strong basis for the conclusion that the integration of spatial techniques and machine learning has the potential to improve air pollution prediction outcome and aid appropriate intervention initiatives by the stakeholders. Thus, emerging geospatial intelligence technologies and digital innovations particularly Artificial intelligence, machine learning and big data analytics that underpin the fourth industrial revolution (IR 4.0) can enhance existing early warning mechanisms and support a prompt and effective response to climate-change-induced air pollution, thereby fostering sustainable cities and societies. [Display omitted] • Climatic variables can adversely impact air pollution. • Rapid change in the climate can lead to rise or fall of atmospheric pollutants. • Machine learning has the capability to predict future air pollution hazard. • IR 4.0 technologies are reliable tools to ensure urban sustainability. [ABSTRACT FROM AUTHOR]

This study develops an oil spill environmental vulnerability model for predicting and mapping the oil slick trajectory pattern in Kota Tinggi, Malaysia. The impact of seasonal variations on the vulnerability of the coastal resources to oil spill was modelled by estimating the quantity of coastal resources affected across three climatic seasons (northeast monsoon, southwest monsoon and pre-monsoon). Twelve 100 m3 (10,000 splots) medium oil spill scenarios were simulated using General National Oceanic and Atmospheric Administration Operational Oil Modeling Environment (GNOME) model. The output was integrated with coastal resources, comprising biological, socio-economic and physical shoreline features. Results revealed that the speed of an oil slick (40.8 m per minute) is higher during the pre-monsoon period in a southwestern direction and lower during the northeast monsoon (36.9 m per minute). Evaporation, floating and spreading are the major weathering processes identified in this study, with approximately 70% of the slick reaching the shoreline or remaining in the water column during the first 24 h (h) of the spill. Oil spill impacts were most severe during the southwest monsoon, and physical shoreline resources are the most vulnerable to oil spill in the study area. The study concluded that variation in climatic seasons significantly influence the vulnerability of coastal resources to marine oil spill. Image 1 • Oil spill coastal sensitivity maps were developed considering climatic variations. • GNOME model was used for the prediction of the oil spill trajectory. • Geographical Information System Kernel density spatial analysis tool is significant for the development of vulnerability map. • The novel coastal environmental vulnerability maps are particularly useful for decision making in a changing climate. [ABSTRACT FROM AUTHOR]

• Urbanization will occur in several hazard-prone areas, driving up the potential for climate change induced damages. • Digitalization impacts communities' socio-economic dynamics by using innovative high-tech tools to transform conventional work approaches. • Key Digitalization concepts offer opportunities to aid sustainable adaptation planning in existing and future urban centers. • Digitalization can help minimize the impacts of climate change related shocks and stresses in urban centers. • Technical limitations, funding, infrastructure deficit and social barriers are major challenges to effective digitalization. Digitalization is a key enabler of sustainable development of cities' socio-economic dynamics with the potential to foster climate-friendly urban environments and societies. The advent of the 4th industrial revolution has seen the increased application of digitalization in several fields and at different levels. High-tech digital devices, platforms and environments are increasingly being deployed to enhance productivity, efficiency and sustainability, and improve overall well-being of urban dwellers. Digitalization is projected to further impact cities in future, transform jobs and trigger life-style changes with far-reaching impacts that will ultimately affect cities' resilience and adaptation capacities. While a growing body of research has highlighted the significance of digitalization to climate change mitigation such as reducing GHG and CO 2 emissions, comprehensive evaluations of the potentials of digitalization as an enabler of climate change adaptation remain scarce. This paper addresses this gap by analysing the current trend in digital revolution in relation to climate change adaptation and examines the likely challenges of digitalization. A desk research method was adopted, focusing on core digitalization concepts driving the Fourth Industrial Revolution (IR 4.0). Nine case studies in cities across various continents were selected to assess the potentials of digitalization in addressing climatic hazards and to highlight benefits from implementing digitalization, while considering the social-ecological-technological challenges and tensions around IR 4.0. Our findings reveal the capabilities of digitalization in supporting more effective early warning and emergency response systems, enhancing food and water security, improving power infrastructure performance, enabling citizen engagement and participatory adaptation measures and minimizing the impacts of climatic hazards. Finally, we recommend feasible pathways to overcome present risks and challenges in order to optimize the numerous opportunities offered by digitalization in support of climate change adaptation initiatives. [ABSTRACT FROM AUTHOR]

Climate change is perceived as a major challenge of modern times. Apart from mitigation measures, such as greenhouse gas emission reductions, a further means to tackle it is via the deployment of adaptation policies and responses, which may also help to address the natural hazards associated with it. Despite the importance of adaptation measures, their effectiveness is often limited by a failure to integrate actions addressing both the causes and symptoms of vulnerability. There is evidence that adaptation processes are largely fragmented, incremental, with limited capacity for transformational change. This paper suggests measures through which transformative adaptation may be further deployed to tackle climate challenges in conjunction with efforts that address poverty alleviation. The implications of this paper are two-fold. Firstly, it offers a comprehensive review of the literature on transformative climate change adaptation, outlining its nature and special features. Secondly, it contains a unique set of cases from 20 countries, predominantly from the Global South, mostly affected by climate change, and is one of the largest studies on the topic ever undertaken. The experiences from this paper will support attempts to sustain transformative adaptation and natural hazards control, which are relevant to the many countries suffering from climatic variations. • Examines the concept of transformative adaptation and its adoption in facing climate change adaptation challenges. • Presents cases of climate change adaptation strategies from 20 countries. • Highlights the context-specific nature of climate change adaptation challenges. • Six countries adopted mainly incremental adaptation approach while 14 countries implemented transformative adaptation methods. • Highlights measures for improving the implementation of transformative adaptation to tackle challenges of climate change. [ABSTRACT FROM AUTHOR]