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Most of the climate change models for South Africa predict a reduction in freshwater availability by 2050, which implies that water availability for sectoral production activities is expected to decline. This decline has an impact on sectoral output, value added and households’ welfare. Using a computable general equilibrium approach, this study investigates the possible impact of global change on households’ welfare. The simulation results show that water scarcity due to global change can potentially lead to a general deterioration in households’ welfare. The poor households, whose incomes are adversely impacted, are the most vulnerable to the consequences of the impact of global change on water resources in South Africa. This vulnerability can only be reduced if welfare policies that maintain food consumption levels for the least and low-income households are implemented

Society faces the double challenge of increasing biomass production to meet the future demands for food, materials and bioenergy, while addressing negative impacts of current (and future) land use. In the discourse, land use change (LUC) has often been considered as negative, referring to impacts of deforestation and expansion of biomass plantations. However, strategic establishment of suitable perennial production systems in agricultural landscapes can mitigate environmental impacts of current crop production, while providing biomass for the bioeconomy. Here, we explore the potential for such “beneficial LUC” in EU28. First, we map and quantify the degree of accumulated soil organic carbon losses, soil loss by wind and water erosion, nitrogen emissions to water, and recurring floods, in ∼81.000 individual landscapes in EU28. We then estimate the effectiveness in mitigating these impacts through establishment of perennial plants, in each landscape. The results indicate that there is a substantial potential for effective impact mitigation. Depending on criteria selection, 10–46% of the land used for annual crop production in EU28 is located in landscapes that could be considered priority areas for beneficial LUC. These areas are scattered all over Europe, but there are notable “hot-spots” where priority areas are concentrated, e.g., large parts of Denmark, western UK, The Po valley in Italy, and the Danube basin. While some policy developments support beneficial LUC, implementation could benefit from attempts to realize synergies between different Sustainable Development Goals, e.g., “Zero hunger”, “Clean water and sanitation”, “Affordable and Clean Energy”, “Climate Action”, and “Life on Land”. I studien har vi utforskat potentialen för fördelaktig markanvändningsförändring genom strategisk perennialisering i Europa. Miljöproblematiken i fler än 81,000 individuella landskap har kvantifierats och potentialen att lindra miljöproblematik med hjälp av strategisk etablering av perenna grödor har uppskattats i varje enskilt landskap. För mer information, se engelsk beskrivning.

We analyze past and anticipated future trends in crop yields, per capita consumption, and population to estimate agricultural land requirements globally by 2050 and 2100. Assuming “business as usual,” higher-income countries are expected to show little or no net growth in cropland by the end of the century, even in the face of moderate climate change. In contrast, in lower-income countries, we project that land requirements will grow dramatically, and climate change will likely double this expansion. Although economic growth is often considered to work in opposition to conservation, accelerating economic development in lower-income countries, which would help alleviate poverty and increase standards of living, would also greatly reduce potential cropland expansion in lower-income countries, even with climate change, owing to slower population growth and improved crop yields that more than offset increased per capita consumption. Combining economic development in low-income countries with reduced consumption in high-income countries could dramatically shrink global cropland requirements by the year 2100 even with moderate climate change. Such a remarkable reduction in cropland area would have enormous benefits for both biodiversity and global climate change.  All of the data files are analyzed using R.

This dataset contains the underlying data for the following publication: Li, R., Perdana, S., Vielle, M. (2021), Potential integration of Chinese and European emissions trading market: welfare distribution analysis, Mitigation and Adaptation Strategies for Global Change, 26:22 https://doi.org/10.1007/s11027-021-09960-7.

{"references": ["Hannah Ritchie, Max Roser, Edouard Mathieu, Bobbie Macdonald and Pablo Rosado - Data on CO2 and Greenhouse Gas Emissions by Our World in Data https://github.com/owid/co2-data#data-on-co2-and-greenhouse-gas-emissions-by-our-world-in-data", "Our World in Data, Cumulative CO2 emissions, 2020 https://ourworldindata.org/grapher/cumulative-co-emissions", "GDP, PPP (constant 2017 international $) - World Bank, International Comparison Program, World Bank | World Development Indicators database, World Bank | Eurostat-OECD PPP Programme", "Cumulative CO2 Emissions of International Transport \u2013 Joseph Nowarski, DOI:10.5281/zenodo.7114110", "Dataset Cumulative CO2 Emissions of International Transport \u2013 Joseph Nowarski, DOI:10.5281/zenodo.7114087", "Dataset Global Warming Forecast using Acceleration Factors - Joseph Nowarski, DOI:10.5281/zenodo.7151890", "CO2 Emission per GDP Forecast 2020-2100 - Joseph Nowarski, DOI:10.5281/zenodo.7264413"]} The dataset includes Business as Usual (BAU) forecast of world global CO2 emissions per GDP (Cp$) for 2020-2100. The CO2 emission forecast is from the publication “Dataset Global Warming Forecast using Acceleration Factors” [6]. According to this publication, the CO2 emissions without international transport will change from 33,803 MtCO2/y in 2020 to 70,191 MtCO2/y in 2100, a 108% increase. The GDP forecast applies a parabolic trendline of the last 30 years. According to this calculation, the world GDP will change from 126.3 MM$/y in 2020 to 728.1 MM$/y in 2100, a 476% increase. CO2 emissions per GDP (Cp$) are calculated by dividing the CO2 emissions per year by the GDP in the same year. The world 0.000268 tCO2/$GDP Cp$ in 2020 will decrease by 64% in 2100 to 0.000096 tCO2/$GDP.

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.

‘Productive Uses of Energy and gender in the Street Food Sector’, is a title of our four year project which is part of the DFID funded ENERGIA Gender and Energy Research programme. This research focuses on male and female owned micro enterprises preparing and selling food in Rwanda, Senegal and South Africa. This sector provides livelihoods for many women and men in these countries and this project provides the gender and energy nexus analysis. One of the primary goals of this project is to influence energy policy making and implementation in the focus countries.

This is a repository of global and regional human population data collected from: the databases of scenarios assessed by the Intergovernmental Panel on Climate Change (Sixth Assessment Report, Special Report on 1.5 C; Fifth Assessment Report), multi-national databases of population projections (World Bank, International Database, United Nation population projections), and other very long-term population projections (Resources for the Future). More specifically, it contains: - in `other_pop_data` folder files from World Bank, the International Database from the US Census, and from IHME - in the `SSP` folder, the Shared Socioeconomic Pathways, as in the version 2.0 downloaded from IIASA and as in the version 3.0 downloaded from IIASA workspace - in the `UN` folder, the demographic projections from UN - `IAMstat.xlsx`, an overview file of the metadata accompanying the scenarios present in the IPCC databases - `RFF.csv`, an overview file containing the population projections obtained by Resources For the Future '- the remaining `.csv` files with names `AR6#`, `AR5#`, `IAMC15#` contain the IPCC scenarios assessed by the IPCC for preparing the IPCC assessment reports. They can be downloaded from AR5, SR 1.5, and AR6 This data in intended to be downloaded for use together with the package downloadable here. The dataset was used as a supporting material for the paper "Underestimating demographic uncertainties in the synthesis process of the IPCC" accepted on npj Climate Action (DOI : 10.1038/s44168-024-00152-y).