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This study investigated three research questions. Is there any correlation among income level, household size, and energy use among households of a city in a developing country? What gaps exist between energy saving behavior and practices of households? What is the current local awareness and level of use of renewable energy? These questions were addressed though a quantitative and qualitative approach with a survey using a Likert scale and yes/no answers. A random sampling technique was used to survey a total of 1150 household of 46 communities of six districts of Xiamen city of China. This data, in addition to the descriptive statistics, were analyzed through a Chi square test, Mann-Whitney test, and regression analysis. Results revealed that the energy supply mix of all the communities predominantly consisted of electricity (74%). Surprisingly results of this study are contradictory to the sustainable energy goals of China-2020. There was no source of renewable energy in the energy supply mix. Statistical significant relationship was found between income and energy use whereas there was a significant difference between household size and energy use. Households are using mostly non-efficient devices. No energy conservation and renewable energy awareness programs have been initiated by the government. Respondents are very willing to conserve energy and pay for renewable energy sources provided such initiatives have government support and programs that have a reward system. Recommendations include that local-scale policy makers should launch campaigns about energy saving awareness to shrink the gap between awareness and practice. • Quantification of gaps between energy conservation knowledge and behavior among high-income households of Xiamen city. • 1150 households, 46 communities and six districts are analyzed for energy emission and renewable energy adaptation. • A significant correlation was found among income, household size, and energy use. • There is dire need to shrink the gap between energy-saving awareness and action. [ABSTRACT FROM AUTHOR]

Fossil fuel energy consumption is still dominant, supporting economic development and influencing environmental and climate change, both immediately and over time (e.g., carbon emissions). In this study, the concept of using fossil fuel energy (or fossil energy–based sources) as the anchor for determining carbon responsibility was proposed, which can more directly and adequately quantify and reflect the environmental responsibility of each stage of the energy economic system and further advance research on the extension of responsibility allocation to the front and back ends. Two key parameters, the primary energy consumption responsibility conversion factor and the value-added allocation factor, were introduced to couple both the energy and economic systems around carbon responsibility allocation and to complete the tracking and calculation of primary energy consumption responsibility in the entire energy supply chain. The relevant calculation data were used to map the responsibility using Sankey diagrams. Based on these parameters, we selected the Chinese energy supply system from 2002 to 2020 as a case study, calculated the allocation profile of primary energy consumption responsibility in the energy supply chain, and analyzed the evolution and allocation of primary energy consumption responsibility in the economic/residential sectors, final commodities, and final use categories. The results showed that energy-intensive industries (e.g., smelting and pressing of metals and manufacturing of chemicals) and energy-intensive products (e.g., construction commodities) are still important carrier sectors and commodities of primary energy consumption responsibility in China. Gross fixed capital formation remains the largest expenditure category of primary energy consumption responsibility. However, with the development and transformation of the national economy, the distribution of primary energy consumption responsibilities among the various stages of the energy system had subtly changed. The mapping structure of PECREE allocation Sankey diagram. [Display omitted] [ABSTRACT FROM AUTHOR]