Regional disparities in decoupling economic growth and steel stocks: Forty years of provincial evidence in China

Highlights

• Decoupling analysis between economic growth and steel stocks in China on provincial scale is conducted.

• Steel stocks show no clear signs of saturation or flatten off pattern although the growth rate decline recently.

• An EKC-like pattern is found between steel stocks and economic growth.

• Steel stocks productivity is increasing on provincial scale although regional disparity is substantial.

• Steel stocks are relative decoupling from economic growth, still far away from absolute decoupling.

Abstract

Human-made material stocks promote the economic prosperity, while the consumption, maintenance, and operation of them have led to adverse environmental impacts. Decoupling materials stocks from economic growth is a key strategy for relieving environmental pressures and achieving sustainable development. China's unprecedented development offers a unique opportunity for uncovering the relationship between in-use stocks and economic growth. In this study, we analyzed the regional disparity of in-use steel stocks estimated by bottom-up accounting method during 1978–2018 in 31 provinces in mainland China, explored the stocks productivity on provincial and regional scale, and conducted a decoupling analysis of in-use steel stocks with economic growth. The results showed that there was a huge disparity among the provincial total steel stocks, per-capita steel stocks, and stocks density. Some provinces, e.g. Beijing, Tianjin, and Shanghai, that had the highest stocks density had comparatively lower per-capita steel stocks and total steel stocks, indicating higher share of in-use steel stocks and lower material intensive economic structure. In-use steel stocks in China showed no clear signs of saturation or flatten off pattern although their growth rate declined recently. An increase in steel stocks productivity was found during 1978–2018, which means relative decoupling of in-use steel stocks from economic growth, but still far away from absolute decoupling. The dematerialization pattern revealed in this study deepens our understanding of material-economy interactions. Policy implications for dematerialization transition should focus on developing compact cities, prolonging the lifespan of products, and advancing technological development.

Introduction

The Anthropocene marks a new chapter in the geological era where human activity dominates the development of global ecosystems (Sterner et al., 2019), and the “Great Acceleration” marked by expansion in human population and development of novel materials has witnessed the remarkable influence of human activity (Lewis and Maslin, 2015). The process of modern urbanization and industrialization in the 20th century have converted large quantities of natural resources into a variety of manufactured capital in the form of extensively built infrastructure, industrial facilities, and transportation equipment, to enable human's modern life and support the economic development (Graedel and Cao, 2010; Graedel et al., 2015; Krausmann et al., 2017; Roberts, 1996). Globally, the manufactured capital, as the entire physical man-made stocks, expanded greatly and the growth was fastest in the three decades after World War Ⅱ (WWⅡ) at 4% per annum (Krausmann et al., 2017), while the global gross domestic product (GDP) grew at a similar pace (World Bank, 2018). With increasing population and living standards in developing countries, and “western lifestyles” in developed countries, the size of manufactured capital will continue to grow, and the waste and emissions resulted from their production, maintenance, and operation have been reaching or exceeding crucial ecological limits (Foley et al., 2011; Rockstrom et al., 2009).

The Sustainable Development Goals (SDGs) adopted by the UN General Assembly (2015), brought a renewed focus on a long-standing challenge: the potential for material throughput and environmental impact to decouple absolutely from economic growth. Essential to meeting this challenge is how to regulate the manufactured capital to reduce its environmental and resource impacts while maintaining its function for human well-being (Gielen et al., 2016; Tu et al., 2019), since the manufactured capital requires a socially organized continuous flows of materials and energy from and to the environment when providing services and shelter for human. Compared with extensive efforts devoted to analyzing the decoupling of economic growth from environmental impacts (Schandl et al., 2016; Shuai et al., 2019; Wu et al., 2019), decoupling of economic growth from manufactured capital has thus far received relatively little attention in sustainability science (Weisz et al., 2015).

Dematerialization, which refers to decoupling economic growth from material use due to improvements in material productivity, was proposed as a core strategy for resource conservation and environmental protection (Cleveland and Ruth, 1998; Der Voet et al., 2004). Although there are debates on how to achieve dematerialization, the Environmental Kuznets Curve (EKC) hypothesis is attractive enough for discussion to continue. It has been found widespread appeal in decoupling analysis research and policy circles (Stern, 2004; Dinda, 2004; Kempbenedict, 2018). Previous studies have shown that the long-term consumption or production of some bulk materials (e.g., aluminum, steel, cement, paper, wood, and ammonia) per dollar of gross national production (GNP), defined as intensity of use (IU), generally followed a bell-shaped curve in industrialized countries (Bringezu et al., 2004; Krausmann et al., 2017; Strout, 1985; Zhang et al., 2017). These findings support the EKC hypothesis for materials, which assumes that IU for a certain material increases in the initial stage of development but tends to fall as income rises and economy matures. The IU hypothesis believes that decoupling can occur after a sufficiently long period.

As more studies regarding material cycles become available, interests in decoupling between stocks and economic growth are growing (Helmut et al., 2017; Krausmann et al., 2017; Zhang et al., 2017). Stocks are the drivers of materials consumption and production that are defined as flows in materials cycles (Krausmann et al., 2017; McMillan et al., 2010; Pauliuk and Müller, 2014; Song et al., 2019). Different with material flows which monitor at the interface of the coupled human-nature system, the stocks directly reflect the material base of an economy (Zhang et al., 2018). A number of studies have investigated the relationship between stocks and economic growth. For example, Fishman et al. (2015) found that economic growth was the driving force for stocks accumulation in Japan, and stocks relatively decoupled from economic growth. Zhang et al. (2017) developed an integrated analytical framework of dematerialization analysis for material flows and stocks, and conducted a case study on evolution of aluminum cycle in the U.S. They found that aluminum flows and stocks decoupled from economic growth in a clear sequential pattern. Zhang et al. (2017) further pointed out that flows and stocks of materials may play distinct roles in generating economic output. Any convenient dematerialization conclusion could be incomplete or even misleading without a complementary understanding of stocks-economy relationship. Furthermore, improving material productivity at stocks level, which can be measured as economic output per unit of stocks, is a fundamental way for improving material efficiency and decoupling resources depletion, and associated environmental pressures from economic growth (Liu et al., 2012; Weisz et al., 2015). These findings suggest that dematerialization and related material productivity analysis should be rooted in solid understanding of stocks (Zhang et al., 2017).

China, as the second largest economy in the world, has experienced rapid economic growth since its economic reform in 1978 (NBS, 2019). The acceleration of urbanization and industrialization was accompanied by massive infrastructure construction, which were largely achieved by massive inputs of resources, have attracted the world's attention (Gregg et al., 2008; Liang et al., 2014; Liu and Diamond, 2005; Wiedmann et al., 2015). Steel is one of the most important construction materials, and China consumed 48.8% of the world total steel in 2018 (World Steel Association, 2019). Steel industry, as a barometer of economic development in China, exerts considerable pressure on the environment (Tang, 2010). Following the global challenges on resources exhaustion and environmental degradation, the question arises whether economic growth actually has decoupled from steel stocks in China. Although growing efforts are devoted to understanding the relationship between steel stocks and economic growth of China (Song et al., 2019), there still exist many knowledge gaps regarding decoupling analysis between steel stocks and economic growth. Considering China's unbalance in regional economic development (Lu et al., 2019), a similar disparity can also be expected for decoupling pattern, which receives limited attention at present.

In this study, we analyzed the regional disparity of steel stocks estimated by bottom-up accounting method during 1978–2018 in 31 provinces in mainland China, evaluated the stocks productivity combined with economic output, and examined the decoupling pattern of steel stocks and economic growth. The following questions were explored:

• How is the disparity of steel stocks accumulation pattern on provincial scale?

• What is the development pattern of stocks productivity?

• Whether the steel stocks have decoupled from economic growth in China?

The rest of this paper is organized as follows: Section 2 introduces the framework of this study and describes the details of quantification method. Section 3 presents the results of the regional disparity of steel stocks, stocks productivity, and decoupling analysis of steel stocks and economic output. Section 4 discusses the implications of our results followed by conclusions in Section 5.