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We provide a dataset from a household survey in Mpanda region in Western Tanzania (N = 137) that was conducted in 2011. Household heads (or replacements) were interviewed. The topics addressed covered a broad range of socio-economic data and including, among others, household information (number of household members, age, sex, religion etc.), agricultural production (e.g. crops produced and livestock owned) including number and size of plots, income generation, energy access and owned assets.

Climate disasters affect human security and development, moreso in fragile and conflict-affected contexts where population’ capacities to cope with climate change are compromised. Responses to such crises lie at the nexus of humanitarian assistance, development, and peacebuilding. Yet, there are still too few integrated programmatic responses coordinating peacebuilding and climate actions to ensure a progressive human development. This research develops a multi-scalar model to help actors identify thematic areas to inform synergistic efforts and programs at different scales to better coordinate their actions. Findings suggest that climate action and peacebuilding sectors can coordinate actions around climate and conflict risk assessments, the management of land and water resources, ecosystem restoration, nature-based climate adaptation, climate and conflict smart agriculture, natural resources governance, and sustainable market development. These collaborative efforts have the potential to generate co-benefits, such as increased social cohesion and livelihood creation.

The PRIMAP-hist Socio-Eco dataset combines several published datasets to create a comprehensive set of population and Gross domestic product (GDP) pathways for every country covering the years 1850 to 2017, and all UNFCCC (United Nations Framework Convention on Climate Change) member states, as well as most non-UNFCCC territories. The data has no sector resolution. List of datasets included in this data publication: (1) PMHSOCIOECO21_GDP_26-Jul-2019.csv: contains the GDP data for all countries(2) PMHSOCIOECO21_Population_26-Jul-2019.csv: contains the population data for all countries(3) PRIMAP-hist_SocioEco_data_description.pdf: including CHANGELOG(all files are also included in the .zip folder) When using this dataset or one of its updates, please cite the DOI of the precise version of the dataset. Please consider also citing the relevant original sources when using the PRIMAP-hist Socio-Eco dataset. See the full citations in the References section further below. A data description article is in preparation. Until it is published we refer to the description article of the PRIMAP-hist emissions time series for the methodology used. SOURCES: - UN World Population Prospects 2019 (UN2019)- World Bank World Development Indicators 2019 (July) (WDI2019B). We use the *NY.GDP.MKTP.PP.KD* variable for GDP.- Penn World Table version 9.1 (PWT91). We use the *cgdpe* variable for GDP (Robert and Feenstra, 2019; Feenstra et al., 2015)- Maddison Project Database 2018 (MPD2018). We use the *cgdppc* variable for GDP (Bolt et al,, 2018)- Anthropogenic land use estimates for the Holocene – HYDE 3.2 (HYDE32)(Klein Goldewijk, 2017)- Continuous national gross domestic product (GDP) time series for 195 countries: past observations (1850–2005) harmonized with future projections according to the Shared Socio-economic Pathways (2006–2100) (Geiger2018, Geiger and Frieler, 2018)Full references are available in the data description document. Methods:Country resolved data is combined from different sources using the PRIMAP emissions module (Nabel et. al., 2011). It is supplemented with growth rates from regionally resolved sources and numerical extrapolations.

Using survey information of 150 randomly selected households across 21 villages of the forest-rich district of Swat, Pakistan, this study assessed households’ decision-making behaviors in depending on income from nearby forested land using socio-economic attributes. The evidence from the study may aid in making the existing policies be better targeted toward families that depend on the forest for income. Descriptive statistics and econometric techniques such as logit and tobit were used to analyze the data. Respondent households obtained the highest share of their income from off-farm activities (37%) and least from forest activities (16%). Fuelwood constitutes the biggest share (66%) of forest income, followed by medical plants (20%) and fodder (13%). We found that households with more physical assets, more family members working in off-farm jobs, and households earning more income from off-farm jobs were significantly and negatively associated with households’ decision to depend on forest income and total income obtained. We also found that households with less distance to the market and membership to joint forest management committees (JFMCs) were significantly and negatively associated with households’ total income obtained. However, household size was significantly and positively related to households’ decision of forest dependency. The study recommends the creation of off-farm opportunities and inclusion of local people in the management of forests through establishment of JFMCs, particularly for large and poor families.

Although Africa's share in the global energy system is only small today, ongoing population growth and economic development imply that this can change significantly. Here, we discuss long-term energy-system developments in Africa using results of a recent model inter-comparison study on global climate policy. We focus on Africa's role in the wider global energy system and in global climate mitigation. The results show a considerable spread in model outcomes, emphasizing the large uncertainty regarding Africa's energy future. Without climate policy, Africa's share in global energy-related CO2 emissions is projected to increase to 3-23% by 2100. Emissions become significant on a global scale only after 2050. In none of the model projections the international ambition to provide universal modern energy access by 2030 is achieved. Furthermore, although the continent is currently a large net exporter of oil and natural gas, towards 2050 the model projections emphasize that Africa needs most of its resources for its rapidly growing domestic demand. However, the projected rapid expansion of their energy system also implies that Africa gains importance in global mitigation action. An important challenge is to align the increasing investments in the energy system with climate policy and potential revenues from international carbon trading.

Supporting adaptation to climate change in poor vulnerable countries is an ethical and legal obligation that arises from the very uneven distribution of responsibility for and vulnerability to climate change. A fair global regime for adaptation funding is needed where contributions are determined by the economic capability of countries and by their responsibility for climate change. Payments from the fund would depend on the biophysical and socio-economic vulnerability of countries, and developing countries would need to have a strong voice in all decisions. Recent estimates of the adaptation needs of developing countries are in the range of US $70–100 billion per year for the public sector. Adaptation funding needs to be additional to the current and promised level of official development assistance. Because of the strong links between adaptation and general development co-operation, a broad definition of eligible adaptation measures should initially be used. Co-funding of measures with large co-benefits independent of climate change appears justified in the case of recipient countries with sufficient capability. Climate-sensitive sectors where adaptation is particularly urgent include water supply, agriculture, coastal protection, and disaster risk management. Where adaptation in situ is not effectively possible, support needs to be provided for the managed relocation of affected populations. Industrialised countries need to quickly provide substantial financial resources for adaptation in poor countries to support urgently needed adaptation measures and to rebuild trust in the international climate negotiations.

The main aim of this paper is to demonstrate that clusters can support the sustainable development of rural areas through the creation of shared value. This is done via the close exam-ination of six different cases of rural clusters in Greece, Italy, Germany, Poland, Denmark, and Sweden. Qualitative as well as quantitative data were taken from the clusters, which demonstrated that their main business approaches naturally coincided with the creation of economic, social, and environmental benefits for the local communities in which they operated. The case clusters were created in a top-down manner, aimed at boosting regional R&D activities and making the local economy more competitive and more sustainable. However, private initiative took over and al-lowed these clusters to flourish because meeting the regions’ economic, social, and environmental needs successfully coincided with the target of the clusters’ own development and profitability. The results show that clusters, with their potential for shared value creation, can constitute a powerful engine for the revitalisation and development of rural areas, addressing the significant challenges which they are currently facing.