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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.

The country’s unique philosophy is expressed by Bhutan’s Gross National Happiness (GNH) as the guiding principle of development. Bhutan is at a crossroads: It can maintain the current pattern of development—with rising inequality—or develop a vibrant private sector to generate jobs and diversify the economy, building resilience to future external shocks. The overarching priority of this Country Partnership Framework (CPF) is job creation. This CPF presents an integrated framework of WBG support to help Bhutan achieve inclusive and sustainable development through private sector–led job creation.

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.

Nearly three billion people in low- and middle-income countries (LMICs) rely on polluting fuels, resulting in millions of avoidable deaths annually. Polluting fuels also emit short-lived climate forcers and greenhouse gases (GHGs). Liquefied petroleum gas (LPG) and grid-based electricity are scalable alternatives to polluting fuels but have raised climate and health concerns. Here, we compare emissions and climate impacts of a business-as-usual household cooking fuel trajectory to four large-scale transitions to gas and/or grid electricity in 77 LMICs. We account for upstream and end-use emissions from gas and electric cooking, assuming electrical grids evolve according to the 2022 World Energy Outlook’s “Stated Policies” Scenario. We input the emissions into a reduced-complexity climate model to estimate radiative forcing and temperature changes associated with each scenario. We find full transitions to LPG and/or electricity decrease emissions from both well-mixed GHG and short-lived climate forcers, resulting in a roughly 5 millikelvin global temperature reduction by 2040. Transitions to LPG and/or electricity also reduce annual emissions of PM2.5 by over 6 Mt (99%) by 2040, which would substantially lower health risks from Household Air Pollution. Primary input data was collected from the following sources: Baseline household fuel choices - WHO household energy database (https://www.nature.com/articles/s41467-021-26036-x) End-use emissions - US EPA lifecycle assessment of household fuels (https://cfpub.epa.gov/si/si_public_record_report.cfm?dirEntryId=339679&Lab=NRMRL&simplesearch=0&showcriteria=2&sortby=pubDate&timstype=Published+Report&datebeginpublishedpresented) Upstream emissions - Argonne National Labs GREET Model (https://greet.es.anl.gov/index.php) Current and future population estimates - UNECA (http://data.un.org/Explorer.aspx?d=EDATA) Input data was processed by defining household fuel choice scenarios, estimating national household fuel consumption based on these scenarios, and applying fuel-specific emission factors to create country-specific emission pathways. These emission pathways were input into the FaIR model (https://zenodo.org/record/5513022#.Yt_jfHbMLb0) which generated additional data for each scenario including time series of pollution concentrations, radiative forcing, and temperature changes. All data is provided in CSV format. Nothing proprietary is required. 

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 contains terrestrial fluxes of nitrous oxide (N2O), methane (CH4) and ecosystem respiration (carbon dioxide (CO2)) calculated from static chamber measurements in riparian buffers of oil palm plantations on mineral soil, in Riau, Sumatra, Indonesia. Measurements were made monthly, from January 2019 until September 2021, with a break from April 2019 to October 2019 to allow for felling and replanting, and another break from January 2021 to June 2021 due to Covid-19 restrictions. To help to reduce the environmental impact of oil palm plantations, riparian buffers are now required by regulations in many Southeast Asian countries. The experiments were conducted to investigate the impact of greenhouse gas emissions from the riparian buffers. Research was funded through NERC grant NE/R000131/1 Sustainable Use of Natural Resources to Improve Human Health and Support Economic Development (SUNRISE) Greenhouse gas concentrations were measured using static chambers, enclosed for 45 minutes. Multiple regressions (including linear and hierarchical multiple regression) were fitted to calculate the best fit flux, using the RCflux R package, written by Dr Peter Levy (UKCEH).

Variation in food resources can result in dramatic fluctuations in the body condition of animals dependent on those resources. Decreases in body mass can disrupt patterns of energy allocation and impose stress, thereby altering immune function. In this study we investigated links between changes in body mass of captive cane toads (Rhinella marina), their circulating white blood cell populations, and their performance in immune assays. Captive toads that lost weight over a 3-month period had increased levels of monocytes and heterophils and reduced levels of eosinophils. Basophil and lymphocyte levels were unrelated to changes in mass. Because individuals that lost mass had higher heterophil levels but stable lymphocyte levels, the ratio of these cell types was also higher, partially consistent with a stress response. Phagocytic ability of whole blood was higher in toads that lost mass, due to increased circulating levels of phagocytic cells. Other measures of immune performance were unrelated to mass change. These results highlight the challenges faced by invasive species as they expand their range into novel environments which may impose substantial seasonal changes in food availability that were not present in the native range. Individuals facing energy restrictions may shift their immune function towards more economical and general avenues of combating pathogens.

How do rising temperatures affect long-term labor reallocation in developing economies? In this paper, we examine how increases in temperature impact structural transformation and urbanization within Indian districts between 1951 and 2011. We find that rising temperatures are associated with lower shares of workers in non-agriculture, with effects intensifying over a longer time frame. Supporting evidence suggests that local demand effects play an important role: declining agricultural productivity under higher temperatures reduces the demand for non-agricultural goods and services, which subsequently lowers non-agricultural labor demand. Our results illustrate that rising temperatures limit sectoral and rural-urban mobility for isolated households. Districts in India .

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).