Water environmental stress, rebound effect, and economic growth of China’s textile industry

Decoupling method

The decoupling elasticity between water environmental stress and economic growth of TI can be expressed as follows: (1) $$D\text{=}\frac{\text{\%}\mathrm{\Delta }W}{\text{\%}\mathrm{\Delta }P}\text{=}\frac{\left(W^T-W^{T-1}\right)/W^{T-1}}{\left(P^T-P^{T-1}\right)/P^{T-1}}\text{=}\frac{W^T/W^{T-1}-1}{P^T/P^{T-1}-1}$$

In Eq. (1), D is the decoupling elasticity of wastewater discharge, W is the water environmental stress from TI, W^T, and W^T−1 are the discharge volumes for years T and T−1, respectively, P is the economical indicator, and P^T and P^T−1 are the output values for years T and T−1, respectively. Thus, the decoupling elasticity D is determined by using the ratio of change rate between water environmental stress (%ΔW) and industrial output value (%ΔP). The calculation of decoupling elasticity is a non-dimensional process.

The decoupling relationship under the elastic index method can be further sub-divided into eight levels based on the relationship between decoupling and coupling (Tapio, 2005). Changes in water environmental stress and economic growth can be divided into coupling, decoupling, and negative decoupling. A more detailed segmentation falls within the range of ±20% of $\%\mathrm{\Delta }W/\%\mathrm{\Delta }P\text{\hspace{0.17em}=\hspace{0.17em}1}$, which is still regarded as elastic coupling. The positive or negative growth from the variable itself is expressed as an expansion of coupling and recessive coupling. A concrete classification of decoupling degree is shown in Fig. 1. According to the definition, strong decoupling represents the most favorable decoupling state and strong negative decoupling represents the least favorable decoupling state. Under the condition of weak decoupling, the economic growth rate is still faster than the increasing speed of water environmental stress, so it also indicates a relative good decoupling status as compared with other states.

LMDI decomposition method

The decomposition method is an analytic procedure to explore the potential structure of target variables and study the mechanism of object action. Index decomposition analysis (IDA) is one of the main research methods to break down influencing factors. The basic idea of the IDA method is to upward trace the change of the target variable, decompose the variable into several combinations of influencing factors, and analyze the contribution degree of different factors to determine highly contributing factors objectively (Xu & Liu, 2014).

The Divisia index method introduced by Divisia is one of the most commonly used exponential decomposition methods. Hulten (1973) elaborated and described the method in detail and applied the exponential decomposition method for the study of energy issues. The multiplication and addition forms of the arithmetic mean of the Divisia index method has been proposed (Boyd et al., 1987; Boyd, Hanson & Sterner, 1988). Ang & Pandiyan (1997) presented a modified Divisia decomposition method, the logarithmic mean Divisia exponential decomposition method (LMDI), which eliminated the residual terms in the decomposition to avoid the arbitrariness of parameter estimation and enhance the credibility of the results. A logarithmic operation could not calculate zero and negative values (Ang & Liu, 2007; Ang & Zhang, 2000), making the Divisia decomposition method can be used for any case analysis.

The LMDI decomposition method is widely used in the analysis of influencing factors, and the multiplication and addition forms of LMDI can be converted by formulas. Compared with multiplication decomposition, it is easier to analyze the decomposition results through addition decomposition. Therefore, the addition form is used to construct the decomposition model. The equation is expressed as follows: (2) $$W\text{=}{\displaystyle \sum _{i=1}\left(\frac{W_i}{{\text{IP}}_i}\times \frac{{\text{IP}}_i}{\text{IP}}\times \text{IP}\right)}={\displaystyle \sum _{i=1}\left({\text{DI}}_i\times S\times \text{IS}\right)}$$ The variables in Eq. (2) are defined in Table 1.

Therefore, the amount of change in discharge between two years ΔW can be expressed as follows: (3) $$\mathrm{\Delta }W\text{=}{\displaystyle \sum _{i=1}\left(\mathrm{\Delta }{W}_{{\text{DI}}_i}\text{+}\mathrm{\Delta }{W}_S\text{+}\mathrm{\Delta }{W}_{\text{IS}}\right)}\text{=}\mathrm{\Delta }{W}_{\text{DI}}\text{+}\mathrm{\Delta }{W}_S\text{+}\mathrm{\Delta }{W}_{\text{IS}}$$ ΔW_DI, ΔW_S, and ΔW_IS represent the changes in water environmental stress caused by discharge intensity, industrial structure, and industrial scale, respectively. T is chosen as the time contrast argument. The logarithmic average weighting of each factor provides the following equations. (4) $$\mathrm{\Delta }{W}_{\text{DI}}\text{=}{\displaystyle \sum _{i=1}\mathrm{\Delta }{\text{DI}}_i}={\displaystyle \sum _{i=1}\frac{W^T-W^{T-1}}{\text{ln}{W}^T-\text{ln}{W}^{T-1}}\times \text{ln}\frac{{\text{DI}}_i{}^T}{{\text{DI}}_i{}^{T-1}}}$$ (5) $$\mathrm{\Delta }{W}_S\text{=}{\displaystyle \sum _{i=1}\mathrm{\Delta }{S}_i}\text{=}{\displaystyle \sum _{i=1}\frac{W^T-W^{T-1}}{\text{ln}{W}^T-\text{ln}{W}^{T-1}}\times \text{ln}\frac{S_i{}^T}{S_i{}^{T-1}}}$$ (6) $$\mathrm{\Delta }{W}_{\text{IS}}\text{=}{\displaystyle \sum _{i=1}\mathrm{\Delta }{\text{IS}}_i}\text{=}{\displaystyle \sum _{i=1}\frac{W^T-W^{T-1}}{\text{ln}{W}^T-\text{ln}{W}^{T-1}}\times \text{ln}\frac{{\text{IS}}_i{}^T}{{\text{IS}}_i{}^{T-1}}}$$

For year T, the contribution of the sub-sector i is calculated as follows. (7) $$\mathrm{\Delta }{W}_{{\text{DI}}_t}\text{=}\mathrm{\Delta }{\text{DI}}_i\text{=}\frac{W^T-W^{T-1}}{\text{ln}{W}^T-\text{ln}{W}^{T-1}}\times \text{ln}\frac{{\text{DI}}_i{}^T}{{\text{DI}}_i{}^{T-1}}$$ (8) $$\mathrm{\Delta }{W}_{S_t}\text{=}\mathrm{\Delta }{S}_i\text{=}\frac{W^T-W^{T-1}}{\text{ln}{W}^T-\text{ln}{W}^{T-1}}\times \text{ln}\frac{S_i{}^T}{S_i{}^{T-1}}$$ (9) $$\mathrm{\Delta }{W}_{{\text{IS}}_t}\text{=}\mathrm{\Delta }{\text{IS}}_i\text{=}\frac{W^T-W^{T-1}}{\text{ln}{W}^T-\text{ln}{W}^{T-1}}\times \text{ln}\frac{{\text{IS}}_i{}^T}{{\text{IS}}_i{}^{T-1}}$$

Decrement and rebound effects

The principle of decrement requires less material, energy, or resource investment to achieve a desired target in production or consumption. In an ecological environment studying area, decrement effect refers to the total amount of environmental stress that declines while the economic output is maintained with improved environmental efficiency. In the decomposition of water environmental stress, the reduction in the water environmental stress brought by the discharge intensity factor and the industrial structure factor is the decrement effect (ΔW_RD). The formula is expressed as follows. (10) $$\mathrm{\Delta }{W}_{\text{RD}}\text{=}\mathrm{\Delta }{W}_{\text{IS}}-\mathrm{\Delta }W\text{\hspace{0.17em}=\hspace{0.17em}}\mathrm{\Delta }{W}_{\text{IS}}-\left(\mathrm{\Delta }{W}_{\text{DI}}\text{+}\mathrm{\Delta }{W}_S\text{\hspace{0.17em}+\hspace{0.17em}}\mathrm{\Delta }{W}_{\text{IS}}\right)\text{\hspace{0.17em}=\hspace{0.17em}}-\mathrm{\Delta }{W}_{\text{DI}}-\mathrm{\Delta }{W}_S$$

The study of rebound effects originates from energy economics (Khazzoom, 1980); Vehmas, Luukkanen & Kaivo-Oja (2004) extended the rebound effect to the field of environment and suggested that the resulting improvements in ecological efficiency are offset by the increase in population and the richness of living brought by such ecological improvement; an increase in ecological efficiency aggravated the environmental damage. The study of the relationship between the ecological environment and economic development should consider the issue of sustainable development (Vehmas, Luukkanen & Kaivo-Oja, 2007) given that expanding an economic scale increases environmental stress and its total amount. The formula of rebound effect (ΔW_RB) is expressed as follows. ΔW_RB and ΔW are equal in numerical value. (11) $$\mathrm{\Delta }{W}_{\text{RB}}\text{=}\mathrm{\Delta }{W}_{\text{IS}}-W_{\text{RD}}\text{=}\mathrm{\Delta }{W}_{\text{IS}}\text{\hspace{0.17em}+\hspace{0.17em}}\mathrm{\Delta }{W}_{\text{DI}}\text{\hspace{0.17em}+\hspace{0.17em}}\mathrm{\Delta }{W}_S$$

Data

According to China’s “Industrial Classification for National Economic Activities” (GB/T 4754-2017), the TI is divided into the manufacture of textile (MT), the manufacture of textile wearing and apparel (MTWA), and manufacture of chemical fibers (MCF) in this study. Therefore, the data from the TI’s industrial output value and the total wastewater discharge are the sum of the three sub-sectors. The National Bureau of Statistics of China and the Ministry of Environmental Protection of China provided the data. The sample analysis period is from 2001 to 2014. This paper uses the gross industrial product as the economic output value (the constant price in 2014) in the analytical model, and the total wastewater discharged is the wastewater discharge volume. Data from 2001 to 2005 are derived from the China Environment Yearbook (2002–2006) (Ministry of Environmental Protection of the People’s Republic of China, 1998–2006); the data are recorded in the China Environmental Statistical Annual Report (2006–2014) with the same statistical caliber (Ministry of Environmental Protection of the People’s Republic of China, 2006–2014).

Wastewater and COD discharge of TI and sub-sectors

From 2001 to 2014, China’s TI and sub-sectors’ total wastewater discharge are shown in Fig. 2A. The total amount of wastewater in China’s TI increases first and then decreases. An upward fluctuating trend was observed during 2001–2011, which increased from 1,923.93 Mt in 2001 to 3,021.08 Mt in 2011 with an average annual growth rate of 4.62%. Wastewater discharge decreased from 2012 to 2014, and the discharge volume was 2,537.68 Mt in 2014. MT’s wastewater discharge trends in the sub-sector are basically consistent with TI’s wastewater discharge trends. The total amount of wastewater discharged from MT is the largest, followed by that from MCF and MTWA. The total discharge of MT’s wastewater rose from 2001 to 2010. The total wastewater discharge from MT accounted for 64.04% in 2001 and 81.92% in 2012. MTWA’s wastewater was the smallest in proportion and variation amplitude. MCF’s wastewater discharge proportion was in the middle position among three sub-sectors, and its overall trend was declining, which accounted for the highest in 2014 (7.01%) and the lowest in 2001 (1.94%).

Figure 2B shows the COD discharge of China’s TI and sub-sectors during 2001–2014. The COD discharge can be divided into three stages. From 2001 to 2007, the COD discharge of the TI showed an upward trend as a whole, from 0.41 Mt in 2001 to 0.46 Mt in 2007, with an average annual growth rate of 2.17%. The TI’s COD discharge was in a volatile trend from 2007 to 2011. The COD discharge in 2011 was 0.46 Mt, which was flat with that amount in 2007. The COD discharge began to decline steadily since 2011. The discharged COD quantity was 0.40 Mt in 2014, which was reduced by 13.83% compared to 2011. MT is the major source of the TI’s COD discharge. From 2001 to 2007, MT’s COD discharge showed an upward trend. MT accounted for the largest COD discharge proportion in 2007 (74.78%) and the least proportion in 2013 (59.27%). MTWA has the least discharge volume and proportion of TI’s COD. The proportion was all between 5.02% (2005) and 1.30% (2001). MCF’s COD discharge proportion was between MT and MTWA, whose proportion was highest in 2001 (38.51%) and lowest in 2007 (21.32%).

Decoupling wastewater and COD discharge from the output value of TI

The decoupling results of water environmental stress and the economic growth in the TI from 2002 to 2014 are shown in Table 2. For the decoupling relations between wastewater discharge and economic growth, good overall decoupling status was observed, in which weak decoupling accounted for nine years (2003–2011), strong decoupling for three years (2002, 2013–2014), and recessive decoupling for one year (2012). The decoupling status behaves even better for COD, with six years for weak decoupling (2004–2007, 2009, 2011), six years for strong decoupling (2002–2003, 2008, 2010, 2013–2014), and one year for recessive decoupling (2012).

The decoupling state of China’s TI was in good condition as a whole from 2002 to 2014 because China promulgated environmental binding policies that promote the change in TI’s economic growth mode. Textile enterprises invested abundant financial, manpower, and material resources for environmental protection equipment and traditional production technology transformation, and investment in advanced technology and equipment increased. Furthermore, the industry technical level greatly improved through the upgrade of equipment manufacturing technology and the introduction of international advanced technology and equipment.

China’s State Council issued the “The notice to issue the 12th Five-Year Plan of environmental protection” in December 2011 (China’s MIIT [2011] No. 42) (Central People’s Government of the People’s Republic of China, 2011). The plan put forward new requirements for pollutant emission in high-polluting industries and raised adjustment strategies to speed up the elimination of backward production capacity. Faced with increasingly stringent environmental requirements, many textile enterprises failed to meet production capacity standards, and they were ordered to stop production or shut their business down. The requirements impacted the TI’s production capacity, and recessive decoupling occurred in both wastewater and COD in 2012.

The TI’s economic growth and water environmental stress in 2013–2014 showed a strong decoupling state, indicating a well implementation in China’s environmental policy. The State Council of China issued “The implementation of the most stringent water resources management system and assessment methods” in 2013 (China’s MIIT [2013] No. 2) (The Central People’s Government of the People’s Republic of China, 2013) to strengthen the red line management of the water function area’s limited pollution and strictly control the total amount of sewage into rivers and lakes. Therefore, in 2013, the TI’s wastewater discharge and COD were 2,550.43 Mt and 0.43 Mt, respectively, which was reduced by 124.79 and 0.11 Mt, respectively, from 2012. Thus, the emission reduction effect is remarkable. The economic development of the TI increased, and the water environmental per unit of output decreased. Thus, the decoupling effect was evident. The TI’s water environmental stress in 2014 continued to decline, wastewater discharge and COD discharge were reduced 0.50% and 7.29%, respectively, compared with that in 2013. The reduction effect in COD is more significant.

On the whole, the decoupling state between discharged COD and economic growth is holding better than the decoupling state between wastewater discharge and economic growth. In order to control COD discharge and reduce water environmental stress, the state has set COD discharge restriction standards and they have achieved great effect. In contrast, the decoupling of wastewater discharge has not reached a desired decoupling state. A large amount of wastewater discharge shows that the water consumption is large and the reuse technology in wastewater is not advanced. The in-depth analysis of the influencing factors of wastewater discharge is of great significance for reducing wastewater discharge.

Decoupling wastewater discharge from the output value of three sub-sectors

The results of the decoupling elasticity of the three sub-sectors of China’s TI from 2002 to 2014 are shown in Tables 3–5.

Table 3 indicates that MT’s decoupling state is unstable during the study years and that weak negative decoupling occurred in 2012. MT showed expansive negative decoupling in 2002 and 2007, strong decoupling in 2011 and 2013, and recessive decoupling in 2014. The remaining nine years were for weak decoupling (2003–2006, 2008–2010). From 2002 to 2011, enterprises and entrepreneurs enhanced their environmental protection awareness. National environmental policies were remarkable tightened, along with a zero emission system on the export of textiles and raw materials. Moreover, customers’ needs of environmental healthy textile products increased. All these are the main reasons underlying the good decoupling during this period. In 2012, “Textile Dyeing and Finishing Industrial Water Pollutant Discharge Standard” (GB4287-2012) was issued by China’s Ministry of Environmental Protection, which requires textile printing and dyeing enterprises’ direct discharge of COD concentration dropped to 100 mg/L or less, and the indirect emissions dropped down to 200 mg/L or less (previously 500 mg/L). Enterprises and industrial parks during this period must heavily invest in building sewage treatment plants or improving the processing capacity of existing wastewater treatment facilities, which resulted in wastes of manpower, material, land, and funds. The majority of China’s textile printing and dyeing enterprises are small- and medium-sized; these enterprises lacked the technology and funds, and their pretreatment facilities barely met the emission requirements, making some enterprises’ bankruptcy and decline in total production (Ma, Wang & Li, 2017). The worldwide financial crisis has led to a shrinking of demand in the textile market, which would have an impact on the export of China’s textile products. Highly stringent environmental protection measures further diminished total textile production in 2014. For instance, Zhejiang Province, where nearly 60% of China’s textile printing and dyeing production capacities are located, carried out “A total of five water treatment” action, which mainly caused recessive decoupling (Ministry of Environmental Protection of the People’s Republic of China, 2014).

Table 4 shows that, except for 2003–2004, 2007, and 2011, MTWA’s growth rate of wastewater is less than that of its output value. MTWA showed expansive negative decoupling in 2003, 2004, and 2011; strong decoupling in 2005, 2009, and 2012; expansive coupling in 2002; strong negative decoupling in 2007; recessive decoupling in 2010; and weak decoupling in the remaining four years (2006, 2008, and 2013–2014). Compared with the other two sub-sectors, the main reason for the bad decoupling condition of MTWA is that its production process determines that the consumption of water resources is not high; thus, wastewater discharge is relatively minimal. A large part of MTWA’s wastewater discharge was from the working water of labor and the process water of basic equipment. China’s accession to the WTO from 2001 to 2005 contributed to the increase in MTWA’s scale of exports. MTWA’s labor-intensive characteristics require considerable labor for production activities, which is the main reason for the increase in wastewater emissions. The rapid growth of MTWA and foreign export trade (Ministry of Industry and Information Technology of the People’s Republic of China, 2016a) from 2006 to 2014 increased wastewater discharge. However, MTWA’s wastewater discharge during this period changed minimally because the Chinese MTWA experienced an evolution process from the original equipment manufacture to the original design manufacture and the original brand manufacture. This increased level of technology inhibited wastewater emissions.

Table 5 shows MCF’s recessive decoupling in 2003, 2009, and 2012; weak decoupling in 2005 and 2006; and expansive negative decoupling in 2014. The remaining seven years were strong decoupling (2002, 2004, 2007–2008, 2010–2011, 2013). MCF achieved more years with strong decoupling state compared with the other two sub-sectors. However, this ideal decoupling state is not continuous but alternative, which indicates that the state is unstable. During the “11th Five-Year” period (2006–2010), MCF eliminated more than 3 million tons of backward production capacity, and water consumption per ton and wastewater discharge decreased by 25.7% and 25%, respectively, compared with those in 2005; the production of chemical fiber in 2010 was 30.9 million tons, which accounted for over 60% of the world’s total production (Ministry of Industry and Information Technology of the People’s Republic of China, 2012). The “Adjustment and revitalization plan of TI” (Central People’s Government of the People’s Republic of China, 2009) put forward new requirements on the TI’s industrial structure and wastewater discharge from 2009 to 2011; the plan proposed to accelerate the elimination of backward production capacity of MCF and high demand forced MCF to optimize industrial capacity and technology innovation. The decoupling status of MCF fluctuated during the “12th Five-Year Plan” period (2011–2015). This fluctuation is primarily attributed to the constraints on resources and environment that brought challenges, and the contradictions of inner structural and among products, scale, and application that remained prominent (Ministry of Industry and Information Technology of the People’s Republic of China, 2017).

Analysis of factors influencing wastewater discharge

Decomposition analysis of the wastewater discharge in TI

The decomposition contribution results and the factors’ effect figure of China’s TI wastewater discharge from 2002 to 2014 are shown in Fig. 3. A positive value indicates that the factor has a positive effect on wastewater discharge, which means that the factor promotes wastewater discharge. A negative value means that the factor has a negative correlation to wastewater discharge, that is, wastewater discharge is suppressed.

Figure 3A show that wastewater discharge intensity factor is the most important factor inhibiting the increase of wastewater discharge. In 13 years, the contribution of intensity factors are negative, and the average contribution value of −1,699.37 Mt is a comprehensive reflection of various waste reduction measures, such as pollution control technology, clean production, and production equipment. This value shows that intensity factors are negatively correlated to the change in wastewater discharge. Accelerating the upgrade of emission reduction technology and the promotion of clean production can reduce wastewater discharge in the TI. Compared with the other two factors, the fluctuation of the industrial structure is larger, but the influence is minimal, and its promotion or inhibition effect is insignificant. Overall development trend shows that the structure factor plays a promotion and inhibition roles before 2007 and after 2008, respectively. The numerical value shows that the influence of TI’s structure factors on the changes in wastewater discharge is small, and the average contribution value is only −5.71 Mt, which is far less than that of the other two factors. The industrial structure adjustment of China’s TI is insignificant in reducing its wastewater discharge. Industry scale factor is the most important factor to drive wastewater from the TI. The average contribution value is 2,373.61 Mt, and the total contribution value is 30,856.90 Mt. In 2001–2014, China’s TI output value showed an upward trend, which increased from USD 37.25 billion to USD 27.43 trillion in 2014.

Figure 3B present that TI’s decrement effect continued to increase from 150.51 Mt in 2002 to 3,095.03 Mt in 2014, with an average annual growth rate of 28.65%. The rebound effect increased first (2002–2011) and then declined (2012–2014), with the lowest at −18.39 Mt in 2002 and the highest at 1,097.15 Mt in 2011. The existence of rebound effect shows that the total amount of wastewater discharged from the TI is still increasing. It is mainly due to the reason that as the technology improves, on the one hand, wastewater treatment technology is highly promoted and wastewater discharge decreases; on the other hand, technology progress makes the productivity and consumption to raise, which in turn brings an increase in economic output and wastewater discharge. When the increase in discharge due to the expansion of economies offset the decrement effect brought by the improvement of technology, the rebound effect occurs.

Decomposition analysis of wastewater discharge in three sub-sectors

The decomposition results and factor effects of the three sub-sectors’ wastewater discharge from 2002 to 2014 are shown in Figs. 4–6.

Figure 4A illustrates that the contribution value of MT’s intensity factor is negative except in 2002, and the average contribution value is −1,064.17 Mt. An increasing trend is shown with the years of growth. The contribution value reached −2,043.34 Mt in 2014, which indicates discharge intensity factor as the main inhibitor of wastewater discharge. The contribution value of MT’s structure factor is significantly less than that of the other two factors; thus, its impact is small. The scale factor contributes positive values to wastewater discharge, with a large average contribution value of 1,765.19 Mt, and it is the main driving factor of wastewater discharge. Figure 4B illustrates that the decrement effect of the TI shows an overall trend of growth from 57.79 Mt in 2002 to 2,050.15 Mt in 2014, with an average annual growth rate of 34.63%. The rebound effect rose in 2002–2010 from 32.34 to 1,164.96 Mt but began to decline from 1,118.28 Mt in 2011 to 671.71 Mt in 2014.

Figure 5A shows that the intensity and structure factors of MTWA are small in 2002–2014, and the discharge of wastewater is mainly driven by the scale factor. The scale factor rises as a whole from 2.79 Mt in 2002 to 152.73 Mt in 2014, with an average annual growth rate of 39.59%. Figure 5B presents that the decrement effect of MTWA is not evident, with a minimum value of −55.17 Mt in 2004 and a maximum value of 19.54 Mt in 2010. The rebound effect is mainly controlled by the scale effect; the former fluctuated in 2002–2014 and increased from 6.68 Mt in 2002 to 140.53 Mt in 2014.

The contribution values of MCF’s intensity factor are all negative, with an overall contribution of −641.86 Mt during the study period. Thus, intensity factor is the most important factor that restricts the wastewater discharge of MCF. The structure factor has minimal contribution, and its impact on wastewater discharge is not evident. Scale factor shows an upward trend in the sample years, from 39.19 Mt in 2002 to 834.19 Mt in 2014, with an average annual growth rate of 29.03%. This factor is the main incentive for stimulating wastewater discharge. Figure 6B shows that the decrement effect of MCF increases from 96.60 Mt in 2002 to 1,032.68 Mt in 2014, with an average annual growth rate of 21.83%. MCF’s rebound effect is negative, the maximum value is −57.41 Mt in 2002, and the minimum value is −246.77 Mt in 2013. MCF contributes the most to the decrement effect of TI, and it has the least rebound effect among the three sub-sectors.