Abstract

Residential carbon dioxide emissions can be divided into a direct component caused by consumers via direct energy usage and an indirect component caused by consumers buying and using products to meet their needs, with a higher proportion caused by the latter. Based on Beijing panel data for 1993–2012, an economic boom period in China, indirect carbon dioxide emissions were separately calculated for urban and rural households using the consumer lifestyle approach (CLA) model. Then, an extended stochastic impact by regression on population, affluence, and technology (STIRPAT) model was used to analyze the influence from two aspects, social economy, and land use, with high precision. Results indicate that indirect CO2 emissions in Beijing households display a rising trend in urban areas but a slight decrease in rural areas. Technology influences and forest land are, respectively, the most important aspects of the social economy and land use. Higher population and urbanization resulted in enhanced emissions in both urban and rural areas. The Engel coefficient presented a negative correlation with indirect CO2 emissions for both rural and urban areas. Compared with urban areas, the per capita net income of rural areas restrained consumption. The consumption structure of urban residents was more biased toward the tertiary industry than that of rural residents. Although technical progress has proceeded, it cannot offset urban residents’ indirect CO2 emissions caused by the large amount and rapid growth of consumption. Regarding land use, urban construction land net primary productivity (NPP) was high and not an important factor contributing to indirect CO2 emissions. Forest and lawn primarily served a recreational function and exhibited a positive impact. Water and cultivated land offered insufficient production and thus had a negative influence. For rural residents, lawn and cultivated land production is self-sufficient. Forests offer a carbon sequence effect, and construction land expansion increased the proportion of developed area, offering a scale effect that resulted in reduced carbon emissions. Based on the results, alternative carbon emission reduction policies have been proposed for each tested influence aspect to reduce emissions, including policies for optimizing industrialization quality, constructing a medium-density city, increasing space efficiency, encouraging sustainable consumption behavior, and increasing the efficiency of energy utilization.

Highlights

  • With socio-economic development and a sharp increase in population, energy consumption is increasing worldwide

  • The results show that the consumption structure of urban residents was more biased toward the tertiary industry than that of rural residents

  • Studies in Finland and Thailand show urbanization is not strongly related with CO2 emissions, and the indirect CO2 emission produced by urban residents is slightly less than those of rural people [15,58]

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Summary

Introduction

With socio-economic development and a sharp increase in population, energy consumption is increasing worldwide. These two methods are more suitable for micro-scale calculation, like a household or a community, but not for macro-scale, like estimating household CO2 emissions in whole Beijing because the data volume would be significant and the calculation would be extremely complex Compared with these two methods, Sustainability 2019, 11, 6563 the CLA method, which uses more accessible data, is commonly used to calculate indirect energy consumption and carbon emissions and was applied in this study [23,24]. This research is expected to improve the analyses of the comprehensive influence of indirect CO2 emissions from households in other metropolises during rapid economic booms and the realization of energy conservation and emission reduction goals

Study Area
The CLA Model
The STIRPAT Model
Urban and Rural Household’s Indirect CO2 Emissions
The Influence of Different Land Uses
Findings
Conclusions and Recommendations
Full Text
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