• Energy Research
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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.

Developing bioenergy from plant feedstocks is considered an opportunity to reduce greenhouse gas emissions and secure biofuel supply. This study is an assessment of the availability of field crop residues for bioenergy feedstocks in northwest China (NWC) and southwest China (SWC). The amount of field crop residues was calculated by analyzing statistical data on crop acreages and yields at the provincial and county levels in the NWC and SWC regions. Total residue mass varied from 58.1 to 62.0 million tons (Mt) in NWC and from 92.8 to 97.2 Mt in SWC from 2008 to 2010. Field residues accounted for 86 % in NWC and 94 % in SWC of the total residue mass; the process residue mass accounted for 14 and 6 % of the total residue mass in the NWC and SWC, respectively. In the NWC region, wheat, maize, and cotton were the main crops, providing 17.0, 14.0, and 8.1 Mt of the field residue mass, respectively. In the SWCregion, rice, maize, and canola provided 30.6, 15.2, and 9.7 Mt of the total residue mass, respectively. In NWC, maize cob (1.98 Mt) and cotton seed hull (1.93Mt) formed the majority of the process residues. In SWC, rice hull (5.9 Mt), maize cob (3.7 Mt), and sugarcane bagasse (3.2 Mt) were the main contributors. Most crop residues became available from August to September in the NWC region, whereas harvesting was spread over the whole year in the SWC region. Converted to standard coal equivalent (SCE), total residues in the NWC region amounted to 32.6–34.1 Mt SCE, with 30.7 Mt of field residues and 2.7 Mt of process residue mass. In the SWC region, the total residue mass was equivalent to 48.7–50.8 Mt SCE, including 42.5 Mt of field residues and 7.2 Mt of process residues. Total crop residue availability for biofuels amounted to 16.9 and 28.1 Mt of field residues in NWC and SWC, respectively. Considering transport conditions, surplus amounts, residue densities, and harvest timings, Chongqing Municipality and Shaanxi province showed the best conditions for producing biofuel feedstocks.

Livestock production in peri-urban areas constitutes an important sub-sector of the agricultural production system in China, and contributes to environmental degradation and local air borne pollution contributing to smog. As a result, local policies are being implemented to safeguard the environment. However, there has been little attempt to quantify the impact of environmental policies on livestock production structure, spatial distribution and their related greenhouse gases (GHGs) and ammonia (NH3) emissions. Here, we calculated the inventories of GHGs and NH3 emissions for 2010 and 2014 for peri-urban livestock production in Beijing, using reliable spatially explicit data, which was collected from 1748 industrial farms in 2010 and 2351 industrial farms in 2014, including pig, dairy, beef cattle, poultry and sheep farms. Our estimates indicated that total industrial livestock production increased by 17% between 2010 and 2014, even under the more strict environmental protection polices, with farm size decreasing by between 7% and 47%. Up to 50% of the industrial livestock farms have remained in operation, with the rest closing down or being moved to other regions. Following this trend, total GHGs emission decreased from 5.0 to 4.5 Tg CO2-eq between 2010 and 2014. Most of the GHGs emission reduction was due to the lowering of energy related carbon dioxide (CO2) emission in 2014. Total NH3 emission decreased from 102 to 96 Gg between 2010 and 2014, mainly due to more stringent environmental regulations for new and extended farms (increased in farm size), e.g. Discharge standard for pollutants for livestock and poultry breeding. Our study identified that GHGs and NH3 emission hotspots were concentrated in suburban areas (around the city centre and with less agricultural resource and population density) in 2010. However, between 2010 and 2014 these hotspots moved to the exurban plain and mountain area following the closure or sub-division of intensive farms in suburban regions and construction of new and small farms in exurban areas (around the suburban and with more agricultural resource and lower population density). Scenario analysis suggests that total GHGs emission can be reduced by up to 1.0 Tg CO2-eq (23% of total livestock sector emissions) in Beijing, using a combination of modifications of farm type, livestock diet and manure management. The integrated scenario can reduce CH4, N2O and NH3 emissions by 27%, 9% and 35%, compared to the reference scenario. Within this short period of time (5 years), policies have had direct impacts on peri-urban livestock production in Beijing, resulting in marked changes in the structure of different livestock sectors, as well as the GHGs and NH3 emission inventories and their spatial distribution. Our analysis clearly shows that the success of these (and future) polices relies on optimizing spatial management of new livestock production systems. Policy and farmer guidance should focus on optimizing livestock diet and on-farm manure management, industrial production systems and the pig and poultry sectors in peri-urban regions.

With concerns of energy shortages, China, like the United States, European Union, and other countries, is promoting the development of biofuels. However, China also faces high future demand for food and feed, and so its bioenergy program must try to strike a balance between food and fuel. The goals of this paper are to provide an overview of China's current bioethanol program, identify the potential for using marginal lands for feedstock production, and measure the likely impacts of China's bioethanol development on the nation's future food self-sufficiency. Our results indicate that the potential to use marginal land for bioethanol feedstock production is limited. Applying a modeling approach based on highly disaggregated data by region, our analysis shows that the target of 10 million t of bioethanol by 2020 seems to be a prudent target, causing no major disturbances in China's food security. But the expansion of bioethanol may increase environmental pressures due to the higher levels of fertilizer use. This study shows also that if China were able to cultivate 45% of its required bioethanol feedstock on new marginal land, it would further limit negative effects of the bioethanol program on the domestic and international economy, but at the expense of having to apply another 750 thousand t of fertilizer.

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.

There is increasing attention for the contribution of emerging economies to global innovation, including innovation of renewable energy technologies. The Technological Innovation Systems (TIS) framework presents a list of system functions for the analysis of the development of a technology. It has often been applied to renewable energy technologies, but with a strong focus on advanced economies. In this paper, we elaborate on emerging economy innovation system formation, structured according to TIS functions. Rather than analysing development of the technology, we analyse the development of the Chinese TIS vis-a-vis the global forefront. Key to this notion is that TIS, especially for clean-tech, are transnational phenomena. Lagging TIS depend on the global TIS, whereas leading TIS contribute to its formation. It is concluded that China has reduced its dependence on foreign knowledge and investment, but the outward contribution remains limited. The main challenge to foreign market expansion lies in reforming the domestic TIS to focus on turbine quality rather than cost reduction. Demonstration projects are needed, especially for large capacity and offshore turbine models, in order to build up operational history and get quality certification.

Atmospheric aerosol particles (also known as particulate matter) are central to the cause of the two greatest threats to human security: air pollution (~5 million premature deaths per year) and climate change (~0.5 million per year). Addressing these threats requires an understanding of particulate matter sources responsible for both extreme air pollution immediately affect- ing human health and less extreme levels affecting climate over longer timescales. Here, extraordinary levels of air pollution, with submicrometre aerosol (PM 1 ) mass concentration surpassing 300 µ g m -3 , were observed in a moderately sized European city and are attributed to emissions from residential solid fuel--specifically peat and wood, often promoted as 'slow-renew- able', 'low-carbon' or 'carbon-neutral' biomass. Using sophisticated fingerprinting techniques, we find that consumption of peat and wood in up to 12% and 1% of households, respectively, contributed up to 70% of PM 1 . The results from this approach can better inform emissions reduction policies and help to ensure the most appropriate air pollution sources are targeted. Given the far greater abundance of solid fuels and concomitant emissions required to match the calorific benefit of liquid fuels, even modest increases in the consumption of 'green'-marketed solid fuels will disproportionally increase the frequency of extreme pollution events.

The energy-related CO2 emissions in China have increased dramatically from 3384 to 8333 × 106 t during the last decade. To interpret these drastic changes, we undertake a structural decomposition analysis to decompose the changes in CO2 emissions from 1997 to 2010 into the following six driving forces: emission coefficient, energy intensity, Leontief, sectoral structure, demand allocation (the shares of consumption, investments, and exports in final demand), and final demand effects. The results show that declines in energy intensity had a decrease impact on CO2 emissions during the studied period. Changes in the relative importance of intermediate production in total output (the Leontief effect) contributed to decrease CO2 emissions in the 2000–2002 period and to increase emissions in the other periods. The most important driver behind the steady increase in CO2 emissions is the large increase in final demand. A further analysis at the sectoral level revealed differences and fluctuations between sectors. Energy intensity fell most strongly in the electric power sector and the coking, gas, and petroleum production sector (two energy-intensive sectors). The shift toward exports and investment increased CO2 emissions (demand allocation effect). Part of the increases in CO2 emissions thus stem from production activities for consumption activities elsewhere.