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In Cameroon, as in other countries of the Congo basin region, policy processes and activities related to climate change have been hitherto geared mostly towards mitigation and related questions, with limited concern about adaptation issues. However, the increasing vulnerability of Cameroon to climate variability and change makes adaptation significant to its national climate-change policy. Nonetheless, it remains a challenge to make both adaptation and mitigation occupy the same policy space in Cameroon. This paper builds partly on studies carried out in two community forest carbon initiatives in the southern rainforest of Cameroon. It also argues, supported by existing literature on adaptation and mitigation, that mitigation activities have the potential to produce adaptation outcomes; a situation which avoids duplication of efforts and waste of financial and technical resources, if synergetic options are anticipated and planned. However, whether such integrated approaches succeed and are subsequently reflected in national-level climate policy depends on how actors across different sectors and at different levels engage and carry out their roles. The paper discusses these roles and how they can support each other in pursuing integrated initiatives – a context which is vital for Cameroon.

Purpose This study aims to consider environmental sustainability, a global challenge under the preview of sustainable development goals, highlighting the significance of knowledge economy in attaining sustainable aggregate demand behavior globally. For this purpose, 155 countries that have data available from 1995 to 2021 were selected. The purpose of selecting these countries is to test the global responsibility of the knowledge economy to attain environmental sustainability. Design/methodology/approach Results are estimated with the help of panel quantile regression. The empirical existence of aggregate demand-based environmental Kuznets curve (EKC) was tested using non-linear tests. Moreover, principal component analysis has been incorporated to construct the knowledge economy index. Findings U-shaped aggregate demand-based EKC at global level is validated. However, environmental deterioration increases with an additional escalation after US$497.945m in aggregate demand. As a determinant, the knowledge economy is reducing CO2 emissions. The knowledge economy has played a significant role in global responsibility, shifting the EKC downward and extending the CO2 reduction phase for every selected country. Further, urbanization, energy intensity, financial development and trade openness significantly deteriorate the environmental quality. Originality/value This study contains the empirical existence of aggregate demand-based EKC. The role of the knowledge economy is examined through an index which is calculated by using four pillars of the knowledge economy (technology, innovations, education and institutions). This study is based on a combined panel of all the countries for which the data was available.

This dataset currently consists of a single excel file which contains the Scottish Social Accounting Matrix for 2013, with households being disaggregated into quintiles based on their weekly income. The dataset has been used to study the impact of Energy Efficient Scotland programme and associated work that explored how the anticipated impacts may change due to Brexit

This chapter focuses on the evaluation of adaptive capacities of community-level human systems related to agriculture and food security. It highlights findings regarding approaches and domains to monitor and evaluate behavioral changes from CGIAR’s research program on climate change, agriculture and food security (CCAFS). This program, implemented in five West African countries, is intended to enhance adaptive capacities in agriculture management of natural resources and food systems. In support of participatory action research on climate-smart agriculture, a monitoring and evaluation plan was designed with the participation of all stakeholders to track changes in behavior of the participating community members. Individuals’ and groups’ stories of changes were collected using most significant change tools. The collected stories of changes were substantiated through field visits and triangulation techniques. Frequencies of the occurrence of characteristics of behavioral changes in the stories were estimated. The results show that smallholder farmers in the intervention areas adopted various characteristics of behavior change grouped into five domains: knowledge, practices, access to assets, partnership and organization. These characteristics can help efforts to construct quantitative indicators of climate change adaptation at local level. Further, the results suggest that application of behavioral change theories can facilitate the development of climate change adaptation indicators that are complementary to indicators of development outcomes. We conclude that collecting stories on behavioral changes can contribute to biophysical adaptation monitoring and evaluation.

Although the United Nations’ Sustainable Development Goals (SDGs) advocate, through SDG 4 and SDG 10, equitable quality education and the reduction of inequalities within and between countries, respectively, few studies have examined how inequalities in regional sustainability influence higher education. Therefore, this study aims to examine the relationship between regional sustainability and higher education in China using fixed-effects panel modelling. A systematic force framework showing how regional sustainability drives higher education was constructed from economic, social, and environmental perspectives, and the endogeneity in the process of how regional sustainability affects higher education was explored by introducing one-year lagged values as instrumental variables. Our results show that regional sustainability has a significant impact on higher educational attainment in China, with differing effects in the eastern, central, and western regions, respectively. In central China, economic sustainability plays a significant positive role in higher educational attainment; in the western region, economic and social sustainability have stronger positive effects, while environmental sustainability has significantly negative effects. In terms of policy implications, our findings can be used to support regional development policies to promote regional higher education.

The increasing depletion of natural resources, combined with a wider set of pressures on the environment, has, in recent years, highlighted the need for a more efficient use of energy and a development process that involves alternative energy sources. Energy efficiency has received much attention as a solution, implying both monetary and emissions savings. However, the latter may be partially offset by the income and demand effects of the former, both in more efficient sectors and in spreading to the wider economy. This is the problem of rebound effects. Taking Spain as a case study, and introducing an energy-related CGE model that develops the inclusion of renewables, this paper evaluates a combination of efficiency initiatives to deliver both reduced energy use by households and a more sustainable supply of energy. Our findings suggest that a package aimed at improving efficiency in household electricity and petroleum use, combined with a more competitive supply of energy from renewable sources, may be the only way to get reductions in all energy use, and thus benefit the economy. Specifically, we consider how this package may lead to positive economic impacts and associated rebound effects, where the latter are focused on a greener energy supply.

Study PopulationThe target population of the study were women aged 18 years to 69 years from households in Mwea East sub County that have experienced climate change events. As shown in table 3.1 below, the total population of female in Mwea East sub County in this age category was estimated at 38,734 (Kenya National Bureau of Statistics (KNBS)Volume III, table 2.5, (2019).Sample SizeA sample size of 449 respondents was determined as adequate for statistical analysis for the study using an online sample size calculator (calculator.net, 2021). 95% confidence level and 4.6% margin of error was used to calculate the sample size of 449 respondents determining the level of accuracy of the sample from the total estimated population of 38,734 women aged 18-69 years in Mwea East sub County.Data CollectionThe administration of the questionnaire was done by the Principal Investigator (PI) along with the KIIs, which were conducted after the questionnaire had been administered. The questionnaires were administered by 11 data collection assistants who were trained by the researcher. One of the 11 data collectors was the team leader. The researcher collected data in 5 of the households to demonstrate and practice the data collection process. Data AnalysisQuantitative and qualitative data were analyzed and triangulated to validate the findings. The quantitative data was analyzed using a combination of the IBM SPSS techniques including frequencies, cross-tabulations, bivariate statistics, means, correlations and descriptive ratio statistics. Qualitative data from both respondents and key informants’ interviews were documented using filed notes and thematically analyzed. The analysis from both sets of data was then merged to present the results. Study PopulationThe target population of the study were women aged 18 years to 69 years from households in Mwea East sub County that have experienced climate change events. As shown in table 3.1 below, the total population of female in Mwea East sub County in this age category was estimated at 38,734 (Kenya National Bureau of Statistics (KNBS)Volume III, table 2.5, (2019).Sample SizeA sample size of 449 respondents was determined as adequate for statistical analysis for the study using an online sample size calculator (calculator.net, 2021). 95% confidence level and 4.6% margin of error was used to calculate the sample size of 449 respondents determining the level of accuracy of the sample from the total estimated population of 38,734 women aged 18-69 years in Mwea East sub County.Data CollectionThe administration of the questionnaire was done by the Principal Investigator (PI) along with the KIIs, which were conducted after the questionnaire had been administered. The questionnaires were administered by 11 data collection assistants who were trained by the researcher. One of the 11 data collectors was the team leader. The researcher collected data in 5 of the households to demonstrate and practice the data collection process. Data AnalysisQuantitative and qualitative data were analyzed and triangulated to validate the findings. The quantitative data was analyzed using a combination of the IBM SPSS techniques including frequencies, cross-tabulations, bivariate statistics, means, correlations and descriptive ratio statistics. Qualitative data from both respondents and key informants’ interviews were documented using filed notes and thematically analyzed. The analysis from both sets of data was then merged to present the results.

This dataset underpins the study "Synergies and conflicts of energy development and water security in Africa". The study provides insights into energy supply and demand, power generation, investments and total system costs, water consumption and withdrawal as well as carbon dioxide emissions for the African continent. We developed a model to evaluate energy supply and water requirements to cover the energy needs of the African continent during the period 2015-2065. The model was developed using the open-source modeling system for long-term energy planning OSeMOSYS. The objective function is to minimise total energy system costs, rather than, for example, co-optimise the energy and water sectors. Other energy resources were also included in the model except for adding the water analysis, and the dataset was updated based on the latest available information. The OSeMOSYS model developed to conduct the study “Energy projections for African countries”, itself extended from the Electricity Model Base for Africa (TEMBA), was further extended, included exports for all fuels, water loss due to evaporation in hydropower plants and more scenarios examined. Furthermore, the latest available data on the energy system of Africa was also updated. The TEMBA model produces aggregate energy, and detailed power system results in each country in the African continent. The power sector results are also reported with power pool aggregation. The OSeMOSYS model and input data used to produce these results can be found at KTH-dESA/jrc_temba: TEMBA 2.1 (Version v2.1) [Data set]. Zenodo. http://doi.org/10.5281/zenodo.4889373 (Authors: Ioannis Pappis, Vignesh Sridharan, Will Usher, & Mark Howells. (2021). The initial study was funded by the Joint Research Centre of the European Commission (contract number C936531 - JRC/PTT/2018/C.7/0038/NC).