Search

Household fuel-use (HFU) patterns are strongly associated with multiple effects, including air quality, human health, and regional climate change. This paper presents the results from the first Chinese Environmental Exposure-Related Human Activity Patterns Survey (CEERHAPS), carried out among 91,121 households located in 9108 villages, 636 towns, and 159 counties in 31 provinces. Face-to-face interviews were conducted with each participant to obtain information about the type of fuels used for cooking and heating. The main objectives of this paper were to investigate HFU for cooking and heating in China, to validate the World Health Organization (WHO) model, and to help inform local evaluation models. In China, gas and biomass fuels, the dominant energy fuels for cooking, are used by 44.8% and 32.1% of households, respectively. Approximately 34.1% of families have no household heating during the cold season, and 16.7%, 15.6% and 12.8% of households rely on coal, electricity, and biomass, respectively, for household heating when no central heating was available. The proportion of households using solid fuels has generally decreased during the last two decades. Considerable spatial variation was evident in the HFU patterns for both cooking and heating. The data revealed that the predominant fuel for cooking was biomass (47.6%) in rural populations, whereas urban households were more likely to cook with gas (65.8%). In terms of heating, coal (21.4%) and biomass (19.0%) were the main fuels used in rural households, while electricity (23.6%) and coal (10.5%) were more commonly used in urban areas. The overall HFU results for cooking from this study were comparable to those predicted using the WHO model. We also developed models at the provincial level to estimate HFU for cooking and heating in China; it is expected that the model, if confirmed by future studies, could be used for future research on household air pollution, domestic human exposure and burden of disease. [ABSTRACT FROM AUTHOR]

Accurately understanding the real situation of China’s carbon emissions at the provincial level is not only crucial for realizing carbon mitigation in China, but also of great importance for tackling climate change on a global scale. This paper uses detailed energy consumption data subdivided within each fuel type and sector-specific emission factors, to calculate both direct and indirect energy-related CO 2 emissions for China’s provinces, and offers provincially-targeted policy proposals on emission reductions. The results uncover large divergences in calculation of provincial CO 2 emissions between production-based and consumption-based accounting approaches. Considering the large amount of interprovincial CO 2 emission transfers embodied in secondary energy deployment, the consumption-based accounting performs better in reflecting the actual features and responsibilities of carbon emissions in the provinces of China. From the consumption perspective, Shandong, Hebei, Jiangsu, Inner Mongolia, Guangdong, Henan, Liaoning and Shanxi contributed to the majority of China’s carbon emission growth during the period of 1996–2013, while Xinjiang, Sichuan, Anhui, Tianjin and Hunan were playing an increasingly important role. These two groups of provinces should be regarded as the key regions for national emissions abatement. Meanwhile, the energy industry was the top sectoral contributor to CO 2 emissions growth in most provinces, while service and household sectors made increasingly significant impacts on driving up provincial emissions. Together with ongoing efforts in the energy sector, the mitigation of CO 2 emissions in service and household sectors deserves much more attention, especially in the transportation and urban household sectors. Furthermore, the temporal trends of carbon emissions in various provinces, as well as their factor and sectoral driving forces, varied greatly with each other. Therefore, each of the provinces should formulate emission reduction policies according to their own situation, and target the key driving factors and sectors of carbon emissions at the current stage or in the near future. [ABSTRACT FROM AUTHOR]

[Display omitted] • A method for spatiotemporal coordination of multienergy systems is proposed. • Virtual energy storage gain is calculated based on spectral analysis. • The hydropower regulation ability affects the virtual energy storage gain. • The optimal coordination range between multiple energy sources is obtained. Utilizing the spatial heterogeneity and climate periodicity of various available renewable energy sources can enhance the multienergy complementarity, which will further reduce the energy storage demand and contributes to the "virtual energy storage gain." In this paper, we propose a spatiotemporal coordination method based on spectral analysis for a wind-PV-hydropower system that targets the maximum virtual energy storage gain. The complementary effect of hydropower on wind and PV power can be seen as changes in the regulation ability resulting from the hydropower construction development as well as a decreased variance in the total system production output. This method is used to determine the optimal coordination distance of multiple energy sources that are matched over different periods representing typical climate variation. A case study in the Yalong River basin in China obtains the best range of hydropower bundling surrounding wind power and PV power stations under different hydropower construction planning scenarios, and it reveals that increased regulation capacity of hydropower will reduce the optimal coordination distance but can achieve more energy balance if both actual storage and virtual storage is accounted for. This approach can realize energy delivery with the optimal coordination distance to meet intensive and efficient development needs, which can provide guidance and support for the planning and construction of wind-PV-hydropower storage systems. [ABSTRACT FROM AUTHOR]