Nigeria is one of the most vulnerable countries to climate change (CC) impact. Thus, there is a need to mitigate emission and implement strategies to adapt to the impacts of CC. This study is a review of publications on CC mitigation and/or adaptation in Nigeria. The aims are as follows: to identify commonly adopted climate change adaptation strategies (CCAS) and their determinants; and to identify the climate change mitigation strategies (CCMS) that are widely deployed to reduce emissions in Nigeria. Relevant keywords were used to search for publications in Scopus and Google Scholar. Our dataset shows that from 1999 to the present, there has been an exponential growth in the number of publications on CCAS and CCMS. In total, 75.2% of the papers were on CCAS, 19.6% were on CCMS and 5.2% combined CCAS and CCMS. Many of the papers on CCMS were on ‘Energy’ and ‘Agriculture’. Other sectors identified from the included studies pertinent to mitigation in Nigeria included ‘forestry’, ‘waste management’, ‘industry’ and others. Most (80.7%) of the CCAS papers were related to ‘Agriculture’, showing the most important sector where CC-adaptive capacity is required in Nigeria. In all, 45% of the papers on CCAS were on ‘Social’ adaptation, followed by ‘Structural measures’ (42%), with the smallest amount being on ‘Institutional’ measures (13%). The relatively fewer number of papers on institutional CCAS highlights the need for more research. This is because institutional measures which include policies, legal and fiscal support are important to build resilience to climate change impact. The greatest determinant influencing the adoption of CCAS is ‘Education’. A higher number of publications on ‘Agriculture’ for both CCMS and CCAS underscores the importance of the sector and the need to develop its mitigation and adaptive capacity strategies. Our results and findings were also compared and discussed in line with similar works on CCMS and CCAS in Africa.

Nigeria is among the countries highly vulnerable to climate change impact. Thus, there has been growing emphasis on the pursuit of decarbonization and net-zero (net-zero transition) strategies. The aim of this work is to review major concepts in research publications associated with climate change mitigation in Nigeria. The literature search was conducted on the Scopus database using relevant keyword operators. Mixed methods were adopted to conduct bibliometric, text mining and content analysis. Bibliometric software (VOSviewer) was used. The research objectives were to identify how net-zero transition research has evolved in Nigeria; their important research themes and trends in Nigeria, and potential directions for future research on achieving them in Nigeria. The results show that the number of publications in the field has been increasing, with 87% of the articles included in the dataset published between 2016 and 2024. Through data clustering, eight clusters of articles were identified, namely (i) the renewable energy, economic growth and emission reduction nexus (ii) energy transition in the Nigerian power system, (iii) policy drivers (socio-technical and economic) for a cleaner energy system, (iv) energy transition governance, (v) hybrid renewable energy systems, (vi) low-carbon transition, (vii) energy efficiency and low-carbon growth and others. By checking through the keywords used by authors, it appears that the most popular keywords are carbon neutrality, hydrogen, biomass, circular economy, and electric vehicles. These keywords further highlight areas of research interests. Some of the potential future directions identified include the need for effective research communication and strong cooperation between academia and relevant CC policy-making bodies to translate scientific research into evidence-based policies and actionable frameworks; tiered subsidies or tax rebates to low-income households to promote CC mitigating technologies and align CC objectives with social equity; and others. Although this work focuses solely on Nigeria, the country shares similar characteristics with many sub-Saharan African countries, and some others in the global South. Accordingly, the findings will be relevant to those areas, with some unique adaptations.

Artificial intelligence (AI) is increasingly being used today to provide solutions to many environmental problems. This is because of AI’s capability over empirical measurement and conventional computational techniques. This work therefore aim to review publications on AI applications in environmental research field. Literature was search for in Scopus database using Boolean-keyword operators. Among others, the study objectives include identifying evolution of the publications on AI within environmental research domain; their research themes and trends. Mixed-methods (qualitative and quantitative analysis) was adopted for the study, and they comprise bibliometric, text-mining and content analysis. 797 suitable publications were included in the study. Result shows 83% of the included publications in our dataset were published between 2018 and 2024. By checking through authors’ keywords, it appears that recent and popular research interest is being paid to areas such as industry 4.0, smart cities, thermal comfort, circular economy, environmental monitoring, carbon emissions and others. Text-mining of the dataset shows that most frequently used ML technique is Artificial Neural network (ANN), followed by Support Vector Machine (SVM). Text-mining also identified three major themes from the publications on AI within environmental research. They are (i) ecological decision support system (DSS), for detection, prediction and analysis of changes in ecological aspects for evidence-based decisions; (ii) sustainability transitions, illustrated by circular economy, industry 4.0, sustainable supply chains, and (iii) pollution monitoring/-***- and treatment. Eleven major research themes were also identified from bibliographic coupling of the publications within the dataset. The study results could provide a basis for future areas of interests within environmental research.