Elsevier

Journal of Cleaner Production

Volume 33, September 2012, Pages 50-59
Journal of Cleaner Production

Embedded carbon footprint of Chinese urban households: structure and changes

https://doi.org/10.1016/j.jclepro.2012.05.018Get rights and content

Abstract

Reducing environmental pressure is a major concern for China but despite the improvements in energy efficiency, its gross carbon dioxide (CO2) emissions have maintained an upward trend, consistent with the Jevons Paradox. A fundamental shift is thus needed at all levels, including the household.

This paper explores the embedded carbon footprint (ECF) of Chinese urban households associated with activities, such as food, personal transport, communications, education, recreation, health and hygiene. It uses an input–output model for carbon emissions and 2003–2009 urban household data. The results show that the total ECF emission intensity increases when an individual's consumption is higher than 10,000 Yuan (¥). Structural changes are further observed with consumption expenditure above ¥10,000: food, clothing and other survival-oriented emissions intensities as well as education, health and development-oriented emissions intensities reduce; transport, recreation, housing and enjoyment-oriented emissions intensities increase or remain stable and the total emissions intensity increases. Currently per capita consumption expenditure of Chinese urban residents exceeds ¥10,000 and as income continues to rise, China will remain on a high-carbon track. There is a need for better policies, management and behavioural change and the study provides some policy suggestions, including a carbon quota system to guide individual consumption.

Highlights

► A new methodology is proposed to study the embedded carbon footprint of households. ► A study of Chinese urban households' embedded carbon footprint (ECF) is conducted. ► The changes in the households' ECF as they relate to increasing income are discussed. ► Policy recommendations are formulated, including a potential carbon quota system.

Introduction

It is well known that increase in consumption is the main factor behind the serious environmental deterioration across the globe, including constantly growing greenhouse gas (GHG) emissions (Lenzen and Shauna, 2001). Technological improvements in energy efficiency, for example, have not decreased energy use (which is predominantly fossil fuel based) as per capita consumption has continued to grow (Rood et al., 2003). Strong concerns are currently being raised about the increase of wealth in developing countries, such as China and India, which is likely to aggravate the ecological situation even further (Pearce, 2008). In fact, China is already the top GHG emitter, largely caused by the production sector of its economy, but what are we to expect as the country's population becomes richer?

Since the 1990s it has been increasingly acknowledged that reducing household carbon emissions can be a starting point for developing strategies aimed at environmental protection (Boxall, 2006). In Canada, for example, households are estimated to generate 45% of the country's GHG emissions (Statistics Canada, 2011). Household carbon dioxide (CO2) emissions however are largely associated with the provision of certain functional needs, such as shelter, food or recreation (Druckman and Jackson, 2009). The carbon footprint of a household is represented not only through the direct consumption of energy, petrol and gas but also in the carbon embedded in the products it uses or consumes. Driving a car or heating a home, for example is direct generators of CO2 emissions, while purchasing goods and services, such as television sets, furniture, food or holidays contributes to GHG emissions indirectly through the embedded carbon emissions of production, distribution and disposal (Kerkhof et al., 2009).

Without having a clear understanding as to what a household consumes, what carbon emissions this generates and what are the likely changes to be expected, it is impossible to see a shift in consumer behaviour towards a sustainable society. This is particularly the case for China's growing and fast urbanising economy contributing to improving household consumption levels. A good description of the impacts of the components of urban consumption can also inform policy making by government as well as industry when it comes to the development and adoption of cleaner products.

This paper is focussed exclusively on CO2 emissions as the primary indicator of negative environmental externalities. The main aim of the study is to provide an overview of the embedded carbon footprint (ECF) of Chinese urban households and the specific objectives are: (1) to develop a methodology to analyse the ECF; (2) to apply the developed methodology to analyse data on Chinese urban households; (3) to understand emerging trends in the Chinese households ECF in relation to changing income levels and (4) to put forward policy recommendations that can potentially encourage a reduction in the carbon footprint.

The paper is organised as follows. Section 2 reviews the existing literature related to this topic. The methodologies adopted for the analysis are introduced in Section 3 and the trends in ECF are presented in Section 4. In the concluding Section 5, we synthesise the salient findings and comment on their relevance for policy makers. Finally, this paper puts forward the personal carbon quota concept as a new path for the realisation of the Porter Hypothesis which claims that environmental regulation can induce efficiency and encourage innovation producing a win–win situation for increased social welfare and net commercial benefits for private companies (Porter and van der Linde, 1995).

Section snippets

Household-embedded carbon footprint

The use of fossil energy resources remains one of the main sources of CO2 emissions (IPCC, 2007). According to China's Statistical Bureau (NBSC, 2010), fossil fuels accounted for 92.2% of the total energy consumption in China in 2009. As the country remains heavily dependent on this energy source, its contribution to the increase in the on-going atmospheric concentration of CO2 and its corollary of climate change continues to grow. Rapid urbanisation has been associated with increases in both

Methodology and data sources

The use of different methodologies to assess a carbon footprint is likely to result in different estimation outcomes (Plassmann et al., 2010; Dias and Arroja, 2012). In the case of the embedded carbon footprint, there have been at least two alternative approaches for its estimation. One is based on estimating the “apparent consumption” of each type of energy resource, along the line of the methodology proposed by Wackernagel and Rees (1996) and its later development. The other, proposed by

Trends in China's carbon dioxide emissions

The importance of being able to estimate the Chinese urban household embedded carbon footprint can be understood within the context of China's constantly raising total CO2 emissions. Despite a small decrease between 1997 and 2000, the overall trend is upwards (see Fig. 1). In fact, the 2005 level was 48% higher than that in 1995. Between 1995 and 2002, due to the economies of scale achieved through the replacement of small energy generation units with large ones, CO2 emissions decreased at a

Conclusion

The Chinese urban households are no longer satisfied with the provision of basic needs and are fast adopting Western lifestyles (Hubacek et al., 2009) which have significant implications for their overall ecological footprint. This study sheds some light on how their embedded carbon footprint evolves with the increasing levels of household income.

The above analysis shows that the ECF structure is stable. The food and housing ECFs are dominant when consumption expenditure is below the ¥6000

Acknowledgements

The first and the last author acknowledge the assistance from the National Natural Science Foundation of China (project 71171183: Measurement of Carbon Footprint and Its Evolution Mechanism Based on Consumer Behaviors and project 71172213: Hybrid Governance and Performance Evaluation of Regional Innovation System). The second, third and fourth authors acknowledge the financial help of the Australian Research Council. We also want to thank the subject editor and four anonymous reviewers' whose

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