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Abstract In this study, we investigate the driving forces behind the changes in residential energy consumption (REC) in China’s urban and rural areas over the 2001–2012 period. Based on the logarithmic mean Divisia index method, the REC changes are decomposed into seven driving forces, which are climate change, energy price, energy expenditure mix, energy cost share (in total expenditure), expenditure share (in income), per capita income and population effects. According to the results, climate effect due to increasing days with abnormal temperature, energy cost share effect characterized by more expenditure to be paid for energy use, income effect describing constant income growth in the residential sector definitely increase REC in both urban and rural areas. In contrast, energy prices and energy expenditure mix effects negatively contribute to the REC increase, respectively because of the increase in energy prices and the transition from the low-priced energy to high-priced energy. Expenditure share and population effects play opposite roles in urban and rural areas, and the reasons and implications are analysed in depth.

Current economic instruments aimed at climate change mitigation focus mainly on CO(2) emissions, but efficient climate mitigation needs to focus on other greenhouse gases as well as CO(2). This study investigates the distributional effects of climate change taxes on households belonging to different income and lifestyle groups; and it compares the effects of a CO(2) tax with a multiple GHG tax in the UK in terms of cost efficiency and distributional effects. Results show that a multi GHG tax is more efficient than a CO(2) tax due to lower marginal abatement costs, and that both taxes are regressive, with lower income households paying a relatively larger share of their income for the taxes than higher income households. A shift from a CO(2) tax to a GHG tax will reduce and shift the tax burden between consumption categories such as from energy-intensive products to food products. Consumers have different abilities to respond to the tax and change their behavior due to their own socio-economic attributes as well as the physical environment such as the age of the housing stock, location, and the availability of infrastructure. The housing-related carbon emissions are the largest component of the CO(2) tax payments for low income groups and arguments could be made for compensation of income losses and reduction of fuel poverty through further government intervention.

While park-people conflicts have received worldwide attention, the extent of illegal resource extraction and the relationship with communities' livelihoods has gained little attention in the literature. Thus this paper investigates the impact of socio-economic factors involved in illegal fuel wood and fodder extraction at Bardia National Park in Nepal. Household questionnaires, key-informant interviews and focus groups were conducted to identify different plant species used by households and explore the causes and mode of resource extraction in three buffer zone villages in the park. Altogether 50 different plants were identified by villagers that were used regularly for different livelihood purposes. Almost half of the respondents met their needs by illegally and regularly extracting resources from the park. Incentive schemes in the form of development projects were important but not sufficient in meeting the basic needs of households' especially for such daily items such as fuel wood and fodder. The results described in this paper showed that proximity and access to resources either in the national park, the buffer zone community forest or the government forest, and impact on the livelihoods significantly influenced the likelihood of illegal resource extraction activities. Villages that differed in terms of their location to the resource base, the provision of alternative resources and influence of these on their livelihoods showed significant differences in terms of their patterns of resource extraction and use of these resources. As resource use options, resource interest, and resource extraction patterns were different between villages and dependent on circumstances specific to villages, site-specific management strategies were necessary and more influential than the enforcement of 'one-size fits all' policies. It is suggested that park management plans should be flexible and adaptive enough to meet site-specific contexts and to endear wider support from local communities.

Recently, in the economics literature, several papers have put forward arguments for using a declining discount rate in social-cost benefit analysis. This paper examines the impact of employing a declining discount rate on the social cost of carbon-the marginal social damage from a ton of emitted carbon. Six declining discounting schemes are implemented in the FUND 2.8 integrated assessment model, including the recent amendments to the Green Book of HM Treasury (Treasury, H.M., 2003. The Greenbook: Appraisal and Evaluation in Central Government. TSO, London). We find that using a declining schedule of discount rates increases the social cost of carbon estimate by as little as 10% or by as much as a factor of 40, depending upon the scenario selected. Although the range of plausible estimates is large, using declining discounting schemes in FUND 2.8 in most cases does not yield values at the £70/tC level suggested by UK DEFRA [Clarkson, R., Deyes, K., 2002. Estimating the social cost of carbon emissions. Government Economic Service Working Paper. HM Treasury, London]. Indeed, only at the higher end of the values of social cost of carbon found here would many climate change related policies - such as the Kyoto Protocol - pass a cost-benefit analysis. This conclusion, however, does not necessarily undermine the ethical and political economic reasons for supporting international collective action on climate change. © 2006 Elsevier Ltd. All rights reserved.

The database presents the scenario results of an exploratory research, carried out at the International Institute for Applied Systems Analysis (IIASA): the Low Energy Demand (LED) study (Grubler et al. 2018). The LED scenario explored how far transformative changes that combine technological changes, end-use efficiency, and new business models for energy service provision can lead for lowering energy demand, and how these changes could drive deep decarbonisation in the long-term. The scenario development methodology included a bottom-up analysis of how currently existing, though often embryonic, social, institutional, and technological trends could become mainstream with resulting step-changes in efficiency and resulting lowered energy demand. The bottom-up demand estimations were then further explored for their supply side and emissions and climate implications with a top-down modeling framework drawing on the Shared Socioeconomic Pathways (SSP) framework (Riahi et al. 2017). The results show that global final energy demands can be drastically reduced in 2050, to around 245 EJ/yr, or 40% lower than today, whilst significantly expanding human welfare and reducing global development inequalities. According to the knowledge of the authors, LED is the lowest long-term global energy demand scenario ever published. The LED scenario meets the 1.5°C climate target in 2100 without overshoot and keeps the global mean temperature increase below 1.5°C with a probability of more than 60%, without requiring controversial negative emission technologies, such as bioenergy with carbon capture and storage (BECCS), that figure prominently in the emission scenario literature (Rogelj et al. 2015, Anderson and Peters 2016, Creutzig et al. 2016, Smith et al. 2016). Furthermore, the beneficial impacts of the LED scenario on a range of other sustainable development goals are also shown, demonstrating that efficiency of energy services provision plays a critical role in reaching low-energy futures without compromising increased living standards in the Global South, while at the same time reducing adverse social and environmental impacts of climate mitigation strategies that focus predominantly on large-scale supply-side transformations. The research is published in a peer-reviewed article in Nature Energy (Grubler et al. 2018) with ample supplementary information. Water consumption and withdrawal data are published in Parkinson et al. (2018). The data is available for download from the LED Database. The content of the LED database and any derived analysis may only be used for non-commercial scientific publications, articles, educational purposes, figures and data tables provided that the source reference pursuant to section 'Required citation' is included and all relevant publications are correctly cited. Partial reproductions of the database content may be stored in online repositories, if this is necessary to comply with a journal's data archiving and access requirements. Such reproductions must be limited to the scope of the manuscript in question, and must include a hyperlink to the source database hosted at https://db1.ene.iiasa.ac.at/LEDDB and the download date from the source database. However, any wholesale duplication, translation, reworking, processing, arrangement, transformation, or reproduction through the internet or any other channels, of the https://db1.ene.iiasa.ac.at/LEDDEB for commercial or non-commercial purposes is not permitted without the explicit written approval of IIASA.

South Africa is likely to experience higher temperatures and less rainfall as a result of climate change. Resulting changes in regional water endowments and soil moisture will affect the productivity of cropland, leading to changes in food production and international trade patterns. High population growth elsewhere in Africa and Asia will put further pressure on natural resources and food security in South Africa. Based on four climate change scenarios from two general circulation models (CSIRO and MIROC) and two IPCC SRES emission scenarios (A1B, B1), this study assesses the potential impacts of climate change on global agriculture and explores two alternative adaptation scenarios for South Africa. The analysis uses an updated GTAP-W model, which distinguishes between rainfed and irrigated agriculture and implements water as an explicit factor of production for irrigated agriculture. For South Africa to adapt to the adverse consequences of global climate change, it would require yield improvements of more than 20 percent over baseline investments in agricultural research and development. A doubling of irrigation development, on the other hand, will not be sufficient to reverse adverse impacts from climate change in the country.

China contributes 23 % of global carbon emissions, of which 26 % originate from the household sector. Due to vast variations in both climatic conditions and the affordability and accessibility of fuels, household carbon emissions (HCEs) differ significantly across China. This study compares HCEs (per person) from urban and rural regions in northern China with their counterparts in southern China. Annual macroeconomic data for the study period 2005 to 2012 were obtained from Chinese government sources, whereas the direct HCEs for different types of fossil fuels were obtained using the IPCC reference approach, and indirect HCEs were calculated by input-output analysis. Results suggest that HCEs from urban areas are higher than those from rural areas. Regardless of the regions, there is a similarity in per person HCEs in urban areas, but the rural areas of northern China had significantly higher HCEs than those from southern China. The reasons for the similarity between urban areas and differences between rural areas and the percentage share of direct and indirect HCEs from different sources are discussed. Similarly, the reasons and solutions to why decarbonising policies are working in urban areas but not in rural areas are discussed.

The rapid development of traditional agriculture in China was achieved at the expense of high energy consumption and investments. However, the global green development trend made it necessary for the country to transform its agricultural energy utilization. Energy efficiency changes are affected by many factors, particularly industrial agglomeration. In recent years, the Chinese government has introduced a series of policies, including setting major producing regions for grains and advantageous regions for characteristic agricultural product. These have caused significant changes to the spatial layout of the agriculture industry. However, there is still a lack of research on the impact of these changes on agricultural energy efficiency (AEE). In this study, panel data of 30 Chinese provinces from 2000 to 2016 were entered into stochastic frontier models to measure the country's AEE at the provincial level. A series of spatial econometric models were also used to analyze the impact of agricultural industrial agglomeration on China's AEE. The results indicated that the country's AEE exhibited obvious spatial gradients and correlations. After controlling the impacts of spatial correlation and other factors in the models, agricultural industrial agglomeration was found to have an overall positive impact on China's AEE. In the future, policies should be formulated to increase AEE by establishing agricultural functional areas, strengthening the innovation and sharing of green development technologies at the farm level, and promoting the optimization of energy structures in agricultural and rural areas.