Dynamic Correlation between Industry Greenization Development and Ecological Balance in China

Abstract

By estimating the changing of industry greenization development and ecological balance in China from 2000 to 2017, this paper aims to study the dynamic correlation between industry and ecology in recent years. We focus on the conservation of resources in industry greenization development—if fewer resources are consumed under the same technical conditions as the base period, it means progress in green industrial development. The green proportion of industrial value-added is measured in a quantitative way to gauge the effect and level of industry greenization development in 2000–2017. Meanwhile, the changing impacts on China’s ecological balance imposed by ecological footprint and bearing capacity in 2000–2017 is calculated, and their relation is analyzed using the co-integration approach and PLS method. The results show that industry greenization development and ecological balance are in negative correlation in China, meaning our ecological balance is somewhat mitigated while we strongly practice and promote green industrial development.

1. Introduction

In 2010, China surpassed Japan to become the world’s second largest economy with a GDP of USD 5878.6 billion. However, the rapid economic development of China in recent years has been accompanied by increasingly severe environmental problems. How to transit from the economic model of low efficiency and pollution to the economic mode of high efficiency, energy saving, and environmental protection is a pressing issue that awaits addressing.

Industrial development is closely related to economic development as its foundation. In other words, to coordinate economic, social, resource, and ecological development, we need to start with industry, change its structure, steer it to a green path, and then develop the green economy. As ecological resource is a vital link in industrial development, their inherent connection is what we should think carefully about. The report of the 18th National Congress of the Communist Party of China made in November 2012 initiated the Five-sphere Integrated Plan to comprehensively promote economic, political, cultural, social, and ecological development. How has the policy of “ecological development” affected the green development and ecological balance of China?

Therefore, this paper focuses on resource conservation in green industrial development and gives a comprehensive evaluation of China’s industry greenization development in the 21st century by measuring its effects in monetary terms. We also measure the ecological balance of China with the ecological footprint method proposed by Wackernagel [1]. By comparing the growth rate of industry greenization development and ecological balance and analyzing their relation, this paper evaluates their dynamic correlation and hopes to provide the theoretical basis for China’s next-step industrial restructuring and ecological development.

2. Literature Review

2.1. Green Industrial Development

Studies of green development trace back to 1962, when American biologist Rachel Carson published The Silent Spring, in which she proposed that that the use of chemicals and fertilizers harmed the human being and the environment. He called on people to reflect on the environmental damages caused by economic and technological development [2]. Ten years later, the Club of Rome, a private academic organization, published a research report titled The Limits to Growth, which warned the world to pay close attention to the relation between human and environmental and resource consumption [3]. As more scholars and international organizations studied the relation between economic growth and resource, environment, and sustainability, they have proposed a string of concepts such as “green economy”, “green growth”, and “green development”, and have made systematic descriptions and studies of the economy-ecology relation. In the past decade, in particular, concepts regarding economic growth, green economy, and green development have flourished around the world, and green industrial policies are drawing extensive attention and being adopted by countries to achieve green development. The United Nations Industrial Development Organization (UNIDO) has established an indicator system for industry greenization development in Asia that encompasses such aspects as natural resource, environment, and greenhouse gases (GHG) emission [4]. The indicator system for green economy launched by United Nations Environment Programme (UNEP) measures the development of green economy on the three fronts of economic transition, resource efficiency, and social benefits [5]. The Organization for Economic Co-operation and Development (OECD) has set up a PSR-based low-carbon economy evaluation system, which is comprised of such aspects as human activities, ecological balance, environmental quality, and natural resources [6]. Many foreign scholars have studied industrial greening from the perspective of indicator system or input–output ratio. For instance, Styles et al. established an evaluation system of 22 indicators, including CO₂ emission and SO₂ emission, to measure the environmental emission index and evaluate the development status of plant protection industry in Ireland [7]. Charles R. Hall gave an in-depth evaluation on the flourishing green spillover effects of relevant industries in the US with the input-output method [8]. Martin Jänicke, by analyzing the OECD-proposed “green growth” and based on industrial data of countries like Germany, Japan, and China, proposed that we need to improve the resource productivity, such as through better energy-saving technologies (e.g., renewable energy, energy efficiency, and recycling) and economize the environment and resources to achieve sustainable growth [9]. Domestic studies of industrial greening generally take the connotations of green development, such as resource conservation, environmental protection, and sustainable growth, as those of industrial greening. For instance, Zhong Maochu believed that “environmental industry” and “industrial greening” are limited adaptation on the industrial level to “ecological biocapacity”. He proposed an “eco-environmental consumption” quota system to measure industrial greening and promoted environmental protection industry as a way to boost industrial greening [10]. Most scholars have evaluated industry greenization development by establishing the indicator system or comprehensive index for it or calculating its total factor productivity (TFP). Different scholars have, from different perspectives, built clearly layered greening evaluation indicator systems, covering a full range of dimensions such as economy, society, ecology, environment, and resource [11,12,13,14]. Although there is no unified definition of the connotations of industrial greening, studies so far have all measured and evaluated it from different angles and discovered its structural or technical problems in this process. Suggestions on improvement are then put forth to boost the upgrade of industrial structure or improvement of productive efficiency, hence the sustainable economic development.

An overview of other scholars’ studies of industrial greening and green industries leads to the conclusion that unlike the traditional mode of industrial development, industry greenization development is a green economic growth mode that is aimed at reducing resource consumption, raising resource efficiency, protecting and ameliorating the ecology, and achieving sustainable development of the human society. Green economy is the fundamental path to sustainability and ecological economy. The traditional industrial development mode, which only stresses the increase of economic aggregate, not only neglects environmental protection and development, but also destroys the sound environmental status while ignoring the fact that resources are limited and wastes are recyclable. If we take environmental damage and inefficient resource utilization as the opportunity cost of economic development in the future, then the subject of industry greenization development studies how to maximize industrial and economic benefits with minimal opportunity cost.

On the basis of the aforementioned studies, this paper aims to establish a simple and operable method to measure the effects of industry greenization development to make it calculable and measurable. Focused on resource conservation, we equate the decrease of resource consumption on equal technical conditions to progress in green development. Meanwhile, we valuate the decreased resource consumption and quantify the green proportion in industrial added values to measure the effect and level of industrial greening in general.

2.2. Ecological Balance

Ecological pressure can be measured by comparing the ecological footprint and ecological biocapacity in a country or region. It signifies whether the region’s ecological capacity is enough to accommodate the human demands upon nature [15]. An ecological deficit appears when ecological footprint exceeds ecological biocapacity, which means the region’s development mode is relatively unsustainable. The larger the disparity, the higher the ecological balance. An ecological surplus appears when ecological biocapacity exceeds ecological footprint, which means the region’s ecological capacity is enough to accommodate the human demands, and its development mode is relatively sustainable without ecological balance for the moment.

When proposing the concept and calculating method of ecological footprint, Wackernagel measured the 1997 ecological footprint of 52 countries and regions worldwide [16], which showed 35 of them in ecological deficit, namely their ecological footprint exceeded ecological biocapacity. It must be noted that according to Wackernagel’s calculations, the per capita ecological footprint of China in 1997 was 1.2 hm² and the per capita ecological biocapacity was only 0.8 hm², resulting in a per capita ecological deficit of 0.4 hm². This implies that China needed 1.5 times its territory to meet the human demand for natural resources back then.

The theories about ecological footprint were first brought to China by Zhang Zhiqiang in 2000. He introduced Wackernagel’s theories and calculating methods and defined ecological footprint as follows: The ecological footprint of any known population (either an individual, a city, or a country) refers to the total ecologically productive area and water resources needed to produce all the resources consumed by and to absorb all the wastes generated by said population [17,18].

The Global Footprint Network (GFN) was created in 2003 on the basis of Wackernagel’s ecological footprint theory. By opening ecological footprint accounts for the more than 180 countries and regions around the world, the network provides the standardized calculations of their ecological footprint consistently as a useful reference for their own accounting. In the meantime, the World Wildlife Fund for Nature (WWF) has been working with GFN since 2000 to release the biennial Living Planet Report that evaluates and analyzes such topics as change of species, environmental protection, and ecological footprint. The organization has also been issuing the biennial China Ecological Footprint Report since 2008, which has been updated to 2014.

2.3. Relation between Industry Greenization Development and Ecological Balance

Resources and economic growth are interdependent from the economic perspective. On the one hand, economic growth depends on resources; on the other hand, economic growth is the premise for the depth and breadth of resource exploitation and utilization as factors like the economic growth rate, economic quality, and economic structure decide the scale of resource exploitation and resource efficiency. However, resource is simultaneously a driver of and a limitation on economic development, as rapid economic development is sure to cause more resource demand, resource shortage, and environmental deterioration. As an important and common method of quantitative study that evaluates the sustainable utilization of natural resources in a country or region, ecological footprint essentially measures the balance between the ecological productive capacity of various types of land and the human consumption of its resources. It is adopted by some researchers as a resource and environmental indicator in the empirical study of the relation between regional resources and environment and economic development. Research institutes and scholars around the world have calculated the ecological footprint in different countries, including China, to varying degrees, and their results all point to a close relation between ecological footprint and economic development [19,20]. There is a high level of correlation between the change of ecological footprint and economic development, and economic development is an important driver of ecological footprint changes [21].

As the principal carrier of human economic activities, industry is the bond between the economic system and the eco-environmental system [22] and its development is bound to exert significant impacts on the eco-environment. As industry evolves in complexity and sophistication, the way, scale, and nature of human demand on the environment has changed significantly. From agriculture to industry to service industry, the industrial development, while creating immense productive forces, has also seriously damaged the ecological system. In particular, industrial expansion comes side by side with the consumption of large quantities of energy and water resources, polluting the environment [23] and damaging the eco-balance. Quite a number of scholars studied the relation between industrial structure and ecological footprint to analyze how to mitigate ecological balance by transforming the industrial development mode. Fu Chun et al. conducted a co-integration analysis of the ecological footprint, economic aggregate, and the three industries in the round-Poyang Lake area. On that basis, they proposed to comprehensively consider the different impacts of primary, secondary, and tertiary industries on ecological footprint, establish a resource-saving and environment-friendly industrial system, and promote the coordinated and sustainable development of economic industries and ecological biocapacity in the region [24]. Through an analysis of the relation between industrial structure and ecological footprint in China Yunnan Province, Yang Xiaoyan et al. found that the rapid development of the three industries have significant effects on the change of ecological footprint and its components, with the tertiary industry playing a special role in mitigating regional ecological footprint [25].

It is clear that scholars have begun to combine ecological footprint with social and economic indicators, but no one has analyzed the relation between industry greenization development with ecological footprint yet, not to mention a comparative analysis of their growth rate. The excessively high resource and environmental price for economic growth is a major issue to be addressed through ecological development in China. Industrial greening seeks to reduce resource consumption and improve resource efficiency, but can it achieve the goal of protecting and improving the eco-environment in the end? Is there less ecological balance when industry greenization development flourishes? This paper aims to measure the national situation of industry greenization development by establishing an evaluation system for its effects and also measure the changing trend of national ecological balance. By studying whether there is a dynamic relation between the effects and ecological balance, we can determine whether industry greenization development has positive effects on mitigating ecological balance.

3. Methodology

3.1. Method of Calculating the Effects of Green Industrial Development

In evaluating the effects of green industrial development, this paper draws on the concept of GDP and uses three input-related indicators, namely energy input, water input, and electricity input. There are two considerations for the evaluation method. First, industrial greening is a complex process. There are scholars who, in view of the specific links of industrial production, advocate productive technology innovation in order to transform the original industry into an environmentally friendly one that conserves resources and has little or no environmental pollution. For example, Su Liyang put forth the “green production” concept that focused on “green industrial production” and established a “industry greenization development performance index” that looked at the resource and environmental performance during industrial production. He aimed to demonstrate the delinking of industrial development from resource and environmental consumption as well as the general progress and level of green industrial production [26]. Some scholars deal with the whole industrial chain, covering the input of raw materials, production, packaging, sales, use of products by users, and post-scrapping disposal, to comprehensively analyze whether an industry meets the requirement for resource conservation, non-pollution, and high efficiency. Yang Guang, for instance, established a greenness measuring system for the whole low-carbon industrial chain, and proposed to measure the whole-chain greenness with internal and external industrial indicators such as the greenness of equipment and facilities used and the degree of logistics development [27]. In this article, the author only constructs the index system from the theoretical aspect but does not carry out the empirical research. Other scholars analyzed industrial development with the input-output method. Wang Xuliang et al. analyzed the green TFP of 14 sub-service-sectors using data about the input and “good” or “bad” output of sub-sectors under China’s service industry in 2004–2014 [28]. The output end is rather complex, including the output of tangible materials, output of intangible services, as well as solid waste, hazardous gas, and other pollutants. Such complexity makes it hard to measure, particularly the output data of primary and tertiary industries.

That is why this paper takes the input end rather than output as the entry point, and measures industry greenization development with the decrease of resource consumption at the input end. Second, the resource input in Chinese industries mostly refers to energy and water input, so this paper adopts the three indicators of energy, water, and electricity input. Electricity input is adopted mainly because this paper measures the green development situation of the whole industry and energy consumption is highly relevant to electricity consumption. Energy consumption is the weighted summation of the consumption of different types of energy, and electricity consumption represents the consumption of electricity resources. Electricity can be mass-produced and transmitted over a long distance. It is convenient to use and easy to control, being the cleanest end-use energy [29]. Therefore, compared with other energies, the use of electricity has notable effect on energy conservation and environmental amelioration. The development of various industries is closely related to electricity. The correlation coefficient between the electricity use of secondary industry and the value added of its output value is as high as 0.994, and that of the tertiary industry is 0.995 [30], but each industry differs in energy and electricity consumption. In the secondary industry, industry consumes a large amount of energy; in the tertiary industry, raw coal and crude oil take up only a small part of energy consumption while electricity takes up a large part. Therefore, discussing energy consumption and electricity consumption separately can help us more accurately analyze how the change in input leads to change in resource consumption in different industries. This paper deducts electricity consumption from total energy consumption by adopting a reference coefficient of standard coal conversion, so that we can separately analyze the change in the electricity-excluded energy consumption.

Specifically, based on the industrial value-added during the base period (2000) and the corresponding energy, water, and electricity consumption intensity, we may use the industrial value-added over the years to estimate the expected level of energy, water, and electricity consumption during the calculation period (2001–2017) as well as the disparity between it and the actual level of consumption. Whether the result is positive or negative indicates whether the industry has pursued green development. The gap and the size of the monetized value reflect how green the industry has turned. The monetized value as a proportion of the value-added for the years shows the outcome of the industries’ green development.

First, we need to calculate the monetary value of energy indicator, as shown in the equation below:

$$GM{V}_{Ti}=\left(TE{C}_{Ri}-GD{P}_{Ri}\times TE{I}_0\right)P_{T0}$$

(1)

In this equation, $GM{V}_{Ti}$ stands for the monetary value of energy indicator, $TE{C}_{Ri}$ stands for actual total energy consumption, and $GD{P}_{Ri}$ the actual GDP, all during the calculation period, while $TE{I}_0$ stands for energy intensity and $P_{T0}$ the unit price of standard coal, both in the base period. This paper adopts the 2000 average unit price of standard coal [31]. The energy input indicator is energy consumption, and the data are from the energy statistical yearbook and provincial statistical yearbooks. With the help of the reference coefficient of energy-to-standard-coal conversion, we deduct electricity consumption from the energy consumption to separately analyze the change in the electricity-excluded energy consumption.

Second, we need to calculate the monetary value of electricity indicator, as shown in the equation below:

$$GM{V}_{Ei}=\left(E{C}_{Ri}-GD{P}_{Ri}\times E{I}_0\right)P_{E0}$$

(2)

In this equation, $GM{V}_{Ei}$ stands for the monetary value of electricity indicator, $E{C}_{Ri}$ stands for actual total electricity consumption, and $GD{P}_{Ri}$ the actual GDP, all during the calculation period, while $E{I}_0$ stands for electricity intensity and $P_{E0}$ the average electricity price, both in the base period. The electricity input indicator is electricity consumption, and the data of electricity consumption and sale price is from the energy statistical yearbook and provincial statistical yearbooks. As residential electricity use accounts for only a small part of total electricity consumption and it includes electricity use by the tertiary industry, electricity consumption is taken to represent the total industrial electricity consumption.

Next we need to calculate the monetary value of water resource indicator, as shown in the equation below:

$$GM{V}_{Wi}=\left(W{C}_{Ri}-GD{P}_{Ri}\times W{I}_0\right)P_{W0}$$

(3)

In this equation, $GM{V}_{Wi}$ stands for the monetary value of water resource indicator, $W{C}_{Ri}$ stands for actual total water consumption, and $GD{P}_{Ri}$ the actual GDP, all during the calculation period, while $W{I}_0$ stands for water intensity and $P_{W0}$ the water price for industrial and commercial use, both during the base period. The water input indicator is total water consumption, of which the data come from the local water resource bulletins. Since domestic water use includes water consumption by tertiary industry and construction industry and residential water use accounts for a small proportion, total water consumption is adopted to represent the total industrial water consumption.

At last, we need to add up the monetary values of all three indicators, as shown in the equation below:

$$GM{V}_i=GM{V}_{Ti}+GM{V}_{Ei}+GM{V}_{Wi}$$

(4)

In the summation above, a negative $GM{V}_i$ means the actual input of energy, water resource, and electricity is less than expected, which implies better effects of industry greenization development than in the base period. Likewise, a positive $GM{V}_i$ means the actual input is larger than expected, implying worse effects of industry greenization development than in the base period.

3.2. Method of Calculating Ecological Balance

3.2.1. Calculation of Ecological Footprint

Based on a comprehensive analysis of the actual situation and the availability of data, Wackernagel designed six types of ecologically productive land in his theoretical mode, namely arable land, forest land, grassland, water areas, construction land, and fossil energy land (only for ecological footprint), which have been used by most scholars in later studies.

Per capita ecological footprint is calculated as follows:

$$ef=\frac{EF}{N}=\frac{1}{N}\times {\displaystyle \sum }_{j=1}^6\left(r_j\times a{a}_j\right)$$

(5)

In this equation, $N$ stands for the size of population of a country or region, $ef$ stands for per capita ecological footprint, $r_j$ is equivalence factor, and $a{a}_j$ is the area of the jth type of ecologically productive land.

$$a{a}_j={{\displaystyle \sum }}_{i=1}^n\left(C_i/P_i\right)$$

(6)

Here, $C_i$ means the per capita annual consumption of the ith product and $P_i$ is the average productive capacity of the ith product.

The consumption data cover grain, beans, potato, cotton, peanut, rapeseed, sesame, bast fiber, sugarcane, beet, tobacco, tea leaves, poultry eggs, pork, timber, rubber, bancoul nut, fruits (apple, banana, citrus, melons, etc.), beef, mutton, dairy, woolen products, aquatic products, construction land, land for electric utilities, coal, petroleum, and natural gas.

Per capita ecological biocapacity is calculated as follows:

$$bc=\frac{BC}{N}=\frac{1}{N}\times {\displaystyle \sum }_{j=1}^5\left(a_j\times r_j\times y_j\right)$$

(7)

In this equation, $N$ stands for the number of people, $bc$ stands for per capita ecological biocapacity, $a_j$ the per capita annual occupation of the jth type of ecologically productive land, $r_j$ is equivalence factor, and $y_j$ is yield factor, which differs in each country and region given their different land quality and yield rate. It must be noted that regulations on environmental protection demand that 12% of land area should be deducted from ecological biocapacity to protect bio-diversity, so the result from the equation above should be multiplied by 0.88 to get a country or region’s final ecological biocapacity.

3.2.2. Calculation of Ecological Balance

Per capita ecological balance is calculated as follows:

$$eb=bc-ef$$

(8)

A negative result means ecological deficit, which implies that the region’s development mode is relatively unsustainable. The larger the disparity, the higher the ecological balance. A positive result means an ecological surplus, which implies that the region’s ecological capacity is enough to accommodate human demands, and its development mode is relatively sustainable without ecological balance for the moment.

3.2.3. Source of Data

The calculations of ecological balance in this paper come from the China Statistical Yearbook, China Energy Statistical Yearbook, China Rural Statistical Yearbook, and National Footprint Accounts of previous years as well as from WWF and GFN.

4. Analysis of Results

4.1. Analysis on the Calculation Results of Industry Greenization Development

We evaluate the national industrial development in 2000–2017 with monetary calculations. First we need to address the nominal value added. Assume that the technological level remains unchanged, then the annual consumption of energy, water, and electricity should be equivalent to the total production of the same year. However, nominal value added cannot accurately reflect the real production scale and level as it is affected by price in the current year, so we calculate the actual GDP of 2000–2017 with 2000 constant price, so as to accurately measure the actual production scale. The actual GDP added value in each year is shown in

Table 1. Conversion of actual added value 2000–2017 (2000 constant price) (GDP index comes from the website of National Bureau of Statistics).

National	Nominal Value Added (RMB100 Million)	GDP Index (Previous Year = 1)	Actual Value Added (RMB100 Million)
2000	100,280.10	1.00	100,280.10
2001	110,863.10	1.08	108,603.35
2002	121,717.40	1.09	118,486.25
2003	137,422.00	1.10	130,334.88
2004	161,840.20	1.10	143,498.70
2005	187,318.90	1.11	159,857.55
2006	219,438.50	1.13	180,159.46
2007	270,232.30	1.14	205,742.11
2008	319,515.50	1.10	225,699.09
2009	349,081.40	1.09	246,914.80
2010	413,030.30	1.11	273,087.77
2011	489,300.60	1.10	299,031.11
2012	540,367.40	1.08	322,654.57
2013	595,244.40	1.08	347,821.63
2014	643,974.00	1.07	373,212.61
2015	689,052.10	1.07	398,964.28
2016	743,585.50	1.07	425,694.88
2017	827,121.70	1.07	455,067.83

.

Given the actual GDP in each calculation period and the energy intensity, water intensity, and electricity intensity in the base period of 2000, we use Equations (1) to (4) to come to the monetary calculations of indicators signifying the effects of industry greenization development of 2000–2017.

Table 2. Monetary calculations of indicators signifying the effects of green industrial development.

China	$\mathit{G}\mathit{M}{\mathit{V}}_{\mathit{T}\mathit{i}}$ (RMB100 Million)	$\mathit{G}\mathit{M}{\mathit{V}}_{\mathit{E}\mathit{i}}$ (RMB100 Million)	$\mathit{G}\mathit{M}{\mathit{V}}_{\mathit{W}\mathit{i}}$ (RMB100 Million)	$\mathit{G}\mathit{M}{\mathit{V}}_{\mathit{i}}$ (RMB100 Million)
2000	0.00	0.00	0.00	0.00
2001	−116.56	17.28	−772.94	−872.22
2002	−145.44	166.50	−1996.85	−1975.80
2003	133.57	613.13	−3649.75	−2903.06
2004	529.75	1085.15	−4638.30	−3023.40
2005	725.70	1395.91	−6261.56	−4139.95
2006	541.82	1766.75	−8163.56	−5855.00
2007	117.19	2043.54	−10,921.17	−8760.43
2008	−487.64	1700.34	−12,926.75	−11,714.06
2009	−968.65	1555.49	−15,142.55	−14,555.71
2010	−1462.48	2114.05	−17,898.68	−17,247.10
2011	−1893.70	2751.18	−20,572.83	−19,715.35
2012	−2498.14	2585.13	−23,093.82	−23,006.84
2013	−3242.12	3012.17	−25,770.06	−26,000.02
2014	−4094.01	2516.11	−28,731.05	−30,308.95
2015	−5091.90	1781.28	−31,537.99	−34,848.61
2016	−6136.65	1654.70	−34,594.87	−39,076.82
2017	−7069.30	1484.51	−37,809.06	−43,393.85

Note: A positive value (+) means the actual input is larger than expected, implying the effects of industry greenization development declined from 2000; a negative value (−) means the actual input is less than expected, implying the effects of industry greenization development improved from 2000.

shows the monetary value of the disparity in energy, electricity, and water consumption from 2001 to 2017 as well as the total monetary value $GM{V}_i$, with 2000 being the base period. According to this calculating method, disparity = actual input-expected input. A positive disparity (+) means the actual consumption of energy, water, and electricity is more than expected. In other words, the anticipated input under 2000’s technological level is less than the actual input, which can be interpreted as that industry greenization development did not improve in 2001–2017, and it might have even fallen back. We therefore may hold that the effects of industry greenization development declined in that period. On the other hand, a negative disparity (−) means the actual consumption of energy, water, and electricity is less than expected. In other words, the anticipated input under 2000’s technological level is more than the actual input, which can be interpreted as that industry greenization development improved in 2001–2017, and we may hold that its effects improved.

The calculations show that the effects of industry greenization development in China have kept improving since 2000. Table 2 shows that from 2001 to 2017, the energy indicator is positive in 2003–2007, which means actual energy input is larger than expected and the indicator restricts industrial greening. However, the indicator is negative in all other years. This means that on the national level, actual energy input is less than expected and energy indicator promotes industrial greening. In comparison, electricity indicator is positive all the way from 2001 to 2017, meaning the actual electricity input is larger than expected and the indicator drags down industrial greening. According to China Energy Statistical Yearbook, industrial electricity use takes up a dominant proportion, around 70%, in the total electricity use of the whole society. Entering the 21st century, China has come to a period of rapid industrialization, when industries have a much stronger electricity demand. This, combined with the “coal-to-electricity” transition program launched in 2003, has led to a higher electricity intensity compared with 2000, although the growing intensity subsided later. Therefore, with 2000 as the base period, the actual electricity consumption is larger than expected, indicating much room for improvement regarding the efficiency of industrial electricity use in China. The water indicator has been quite consistent by remaining negative from 2001 to 2017, which means the industrial sector has made substantial progress in water conservation. China enacted the Water Law of the People’s Republic of China in 2002, with a view to achieving rational exploitation, utilization, conservation, and protection of water resources, preventing and controlling water disasters, and realizing water sustainability. It is clear that China has progressed in water conservation of industrial development.

In Table 2, the monetary value of input indicators directly reflects whether the effects of industry greenization development are up or down. We can compare this monetary value with the actual GDP to see the green proportion in the value added of the current year. As shown in Figure 1, the vertical axis stands for the proportion of input indicator’s monetary value in current-year actual GDP (all monetary values are negative, but they are presented in positive to measure the green proportion), which is used to measure the proportion of the green part in the actual GDP, namely the effects of green industrial development.

According to Figure 1, the green proportion in total output kept increasing in 2001–2017 compared to 2000, indicating ever better effects of industry greenization development and China’s substantial progress in this field. To be specific, the green proportion in GDP went through three stages. In the first stage (2001–2003), the green proportion in GDP shot up steadily. In this period, electricity intensity increased compared to 2000, water intensity decreased compared with 2000, while energy intensity decreased first and increased later. In general, green proportion of GDP showed a similar uptrend during the three years. The green proportion of GDP decreased in 2004 compared with 2003 because the actual energy and electricity consumption was larger than expected but actual water consumption less than expected, so the overall proportion of their monetary value was smaller than in 2003. In the second stage (2004–2011), there was a bulge in the changing curve of the green proportion in GDP, which means green proportion continued to increase in this period but at a reduced rate instead of a straight upcurve. In this stage, energy and water intensity decreased compared with 2000 but the degree of decrease slowed down year by year, hence the reduced increase of green proportion. In the third stage (after 2011), the green proportion of GDP displayed a straight upcurve again. In this period, energy and electricity intensity decreased at a higher rate that was very close every year, which resulted in the straight upturn. It is clear that in the first two years of the 2000–2017 period, the energy, electricity, and water input indicators had small greening effects, which only begun to increase later with the promotion of green development concept, technological progress, and other favorable conditions. However, the growth rate of greening effects slowed down due to immature technologies and other factors until after 2012, when the greening effects of the three indicators all increased steadily as the green development concept was widely accepted and technologies were more advanced.

4.2. Analysis of Ecological Balance Measurement Results Ecological Balance

By calculating the per capita ecological biocapacity and per capita ecological footprint separately, we obtain the ecological balance nationwide in 2000–2017, as shown in Figure 2:

An analysis of the calculations shows that China’s per capita ecological footprint increased continuously from 1.9201 hectares to 3.5910 hectares in 2000–2017, up about 87% and averaging about 4.83% per year. Compared with per capita ecological footprint, the per capita ecological biocapacity increased only by a small margin of 7.73%, or 0.0688 hectares in 17 years. The per capita ecological balance remained negative in 2000–2017, implying that the regional development mode in China in recent years has remained in a relatively unsustainable state. Statistics by land type show that the per capita ecological deficit of fossil energy land accounts for more than 90% of total ecological deficit. In general, China has been in ecological deficit since 2000 with ever-rising ecological balance that only began to drop slightly in 2016. If ecological preservation measures are not adopted soon, China is very likely to face insufficient resource supply in its future development.

5. Analysis of Dynamic Correlation

5.1. Analysis on the Statistical Relationship

We use the following equation to calculate and compare the growth rate of industry greenization development and ecological shortfall, as shown results in Figure 3.

$$V_{i1}=\frac{GM{V}_i-GM{V}_{i-1}}{GM{V}_{i-1}}$$

(9)

$$V_{i2}=\frac{e{b}_i-e{b}_{i-1}}{e{b}_{i-1}}$$

(10)

The graph shows that the GMV growth rate dropped sharply in 2002–2004. The energy and water intensity in 2001–2002 were both less than that in 2000, but the energy intensity in 2003 was higher than in 2000. The dampening effect from energy and electricity indicators on industrial greening led to the much worse effects of industry greenization development than before. However, GMV growth rate gradually climbed up in 2004–2006 before it began to slow down yearly from 2007 to 2017. The growth rate displayed a sharp fall in 2007–2011 but bounced up a little in 2011–2012, then it dropped slightly and went up again in 2013 and has been on the decline after 2014, though at a reduced rate. The growth rate of ecological shortfall is lower than that of industry greenization development in general. To be more specific, the growth rate of ecological shortfall increased slightly from 2002 to 2004 but decreased mildly in 2004–2008, after which it picked up a little and undulated in a limited way from 2009 to 2013. The fact that it remained positive all the time means the ecological shortfall was aggravated every year and ecological deficit was increasingly serious, but a turning point appeared in 2014. After 2014, negative growth rate of ecological shortfall began to appear, which means the shortfall was being mitigated and human activities were doing fewer damages on nature in this period. Overall, the industry greenization development in China is on a positive track. Although its growth rate has slowed down, the greening process is continuing forward, and ecological deficit has consequently been well addressed. By changing the way that production consumes resources, raising productive efficiency and resource efficiency, industry greenization development will eventually protect and improve the environment. China has achieved a lot in industrial greening and ecological protection. In our future development, we need to adhere to green development and practice ecological development, so as to achieve economic sustainability and protect our eco-environment.

5.2. Ecological Balance Granger Causality Test

The idea of co-integration was initiated by Granger, who held that two variables that were in a relation of co-integration would be in a stable relation in the long term; even if there was short-term deviation, an internal mechanism of co-integration would bring the variables back to long-term balance [32].

Ecological footprint can measure the resource and environmental bearing capacity of the ecological system, while co-integration test can directly analyze multiple nonstationary time series and effectively resolve the problem of “spurious regression”. Therefore, we apply the co-integration test to quantify the relation between the effects of industry greenization development and change in ecological footprint and analyze their mutual effects, in the endeavor to provide important references for China to transform its industrial development mode and formulate future development strategies.

A unit root test is first conducted on GMV, the effects of industry greenization development in 2000–2017, and eb, ecological balance, then we conduct the co-integration test and Granger test, as shown in

Table 3. Results of unit root test.

Variables	eb	gmv	Δeb	Δgmv
Test	(c,n,0)	(c,n,0)	(c,n,0)	(c,n,0)
ADF statistics	−2.262 **	−1.117	−1.425 *	−2.573 **
Conclusion	Stationary	Nonstationary	Stationary	Stationary

Note: (1) The test is (c,t,k). Here c and t mean that the unit root test includes constant term and time trend respectively; n means it doesn’t include constant term or time trend; k means lag order. (2) The sign * and ** respectively means that the t statistics of ADF test rejects the null hypothesis at the significance level of 10% and 5% and the series is stationary. (3) Δ means first difference.

.

The results of unit root test show that the ADF test statistics of industrial greening data in the original series is larger than the critical value at 10% significance level, and the null hypothesis with unit root cannot be rejected, which means the original series is a non-stationary time series. However, the Δeb and Δgmv series after first difference rejects the null hypothesis with unit root at the significance level of 10% and 5%, respectively, and the series of first difference is stationary. Both Δef and Δgmv are I (1) series. The results are shown in

Table 4. Results of Granger test.

Null Hypothesis	F Statistics	p Value	Conclusion
Δgmv isn’t the Granger cause of Δeb	14.993	0.001	Null hypothesis is rejected
Δeb isn’t the Granger cause of Δgmv	0.35824	0.836	Null hypothesis is not rejected

.

To further study the dynamic relation between the two series, we conduct the Granger causality test, and the results show that industrial greening is the Granger cause of ecological balance. The higher level of industrial greening resulting from China’s industrial restructuring has mitigated the ecological balance and reduced ecological deficit year by year.

5.3. Ecological Balance Correlation Analysis

The causality test only tests the time sequence of the economic variables. It does not attest to the existence of a real causality, which should be determined by a combination of factors, including theory, experience, and model. The partial least squares (PLS) is adopted to analyze the factors that affect the change of ecological balance. We introduce the proportion of the output value of primary, secondary, and tertiary industries (FV means the proportion of primary industry, SV the proportion of secondary industry, and TV that of tertiary industry) to analyze how industry greenization development affects the change of ecological balance. The PLS analysis is conducted with SIMCA-P 14.1 (Sartorius, Malmö, Sweden).

First of all, a multiple correlation diagnosis of the variables shows a high degree of correlation among them (

Table 5. Correlation coefficient matrix of independent variables.

	LNGMV	FV	SV	TV	LNEB
LNGMV	1	−0.83767	−0.3027	0.649645	0.81156
FV		1	0.431383	−0.81997	−0.97399
SV			1	−0.87013	−0.39278
TV				1	0.781265
LNEB					1

). The absolute value of correlation coefficient between independent variables is mostly above 0.5, which indicates the existence of multicollinearity between them, a problem that can be effectively solved with PLS, thus making the independent variables more explanatory for dependent variables. This proves that it is right for us to adopt the PLS regression method.

Second, in PLS regression analysis, the variable importance in projection (VIP_j) is usually adopted to measure the explanatory power of each independent variable X_j for dependent variable Y. Generally speaking, independent variables with VIP_j larger than 1 are important, those with VIP_j between 0.5 and 1 are rather important, and those with VIP_j less than 0.5 are unimportant. The results are shown in

Table 6. Variable importance in projection.

Factor	LNGMV	FV	SV	TV
VIPj	1.0457	1.225	0.686	0.966

.

Table 6 shows that all independent variables have VIP larger than 0.5, which means the independent variables chosen by this paper all have good explanatory power for the change of ecological footprint.

At last, we build the PLS model for regression analysis with SIMCA-P14.1. When the three principal components are adopted, the model’s explanatory power for X and Y reaches 93.9% and 95.0%, respectively, and its cross validity for Y is 93.1%. That all three percentages are close to 1 indicates the model’s high degree of precision. We also build the linear regression model and get the following PLS regression equation:

$$EB=-0.0214GMV-0.838FV+0.232SV+0.310TV+33.45$$

(11)

The regression equation shows how industrial development affects ecological balance. First, the value of industry greenization development is in negative correlation with ecological balance. In other words, the larger the monetary value of industrial greening, the smaller the value of ecological balance, which means industry greenization development has mitigated ecological balance and promoted environmental amelioration. Second, the change of industrial structure also exerts considerable effects on ecological balance. China began to shift its industrial structure in 2012, whereby the order of secondary, tertiary and primary industries was gradually switched to tertiary, secondary, and primary industries. In this process, primary industry takes up an ever smaller part whereas secondary and tertiary industries take up a major proportion. This regression equation shows that the proportion of primary industry is in negative correlation with the change of ecological balance, while the proportion of secondary and tertiary industries is in positive relation with the change of ecological balance. This is consistent with China’s reality regarding economic development and environmental changes. The rapid development of secondary and tertiary industries, especially secondary industry, has brought about serious damages to the natural resources and natural environment in China. The rising proportion of secondary and tertiary industries and expanding footprint of human activities have increased ecological balance. We can see that the ecological balance in China began to lessen slightly in 2016, implying that our environment has been improved to some extent thanks to the implementation of the concept of ecological and green development. It is a good beginning, insignificant as it may be. Going forward, industrial transformation and upgrade and green development will push the green economy forward, continue to reduce ecological footprint and pressure, promote sound ecological development, and achieve economic and social sustainability in China.

6. Conclusions

This paper measures the effects of industry greenization development from the perspective of resource conservation and quantifies those effects by calculating the change of resource input under equal technological conditions. Taking 2000 as the base period, the paper calculates the effects of industry greenization development nationwide in 2000–2017 and evaluates China’s achievements in that field over the years. It also calculates the ecological balance in the same period and analyzes the environmental changes that occur during China’s industry greenization development. Based on all of that, we have come to the following conclusions:

First, on the national level, industry greenization development in 2000–2017 could be roughly divided into three stages—the stage of steady rise, the stage of bulge-shaped development, and the stage of mild upcurve. Industry greenization development in China has yielded satisfactory results with better effects every year. We can see that after China officially proposed to build a resource-saving society in 2003, it has energetically implemented the resource-saving policy both in everyday life and in production. It has constantly raised the resource efficiency and productivity through technological progress, upgrade, and renovation, enlarging the green proportion in GDP. The initiative in 2012 to put ecological development in a prominent position has boosted the development of industrial greening.

Second, China has been under mounting ecological balance since 2000, only with a mild decline in 2016. It is facing a serious ecological deficit. To address this situation as soon as possible, we should make great efforts to improve the ecological efficiency, protect the environment, and advance ecological development.

Third, from 2000 to 2017, the growth rate of China’s ecological balance was basically lower than that of its green industrial development, even with a negative growth in 2014. This means the consistent ecological deficit in China has been continuously mitigated with the progress of industrial greening.

Fourth, there is a relation of co-integration between industry greenization development and ecological balance, the former being the Granger cause of the latter’s change. In the meantime, the PLS model shows that industry greenization development has curbed the deterioration of ecological balance. The rapid development of secondary and tertiary industries has expanded human ecological footprint and therefore increased ecological balance, so modifying the impacts imposed by secondary and tertiary industries on the environment is an important direction for achieving sustainable development in the future.

At present, China is still under immense ecological balance, ecological deficit remains serious, and ecological footprint gives no reason for optimism—all these call for continued measures. We should not only raise the use efficiency of various types of land, but should also control energy consumption, lower energy intensity, and increase the share of clean and renewable energies, which is exactly the approach of industry greenization development. Raising energy efficiency will reduce energy loss on the one hand and control the emission of industrial wastes and pollutants on the other, thus promoting industrial greening. Efforts should be made to optimize the industrial structure, control energy consumption and pollution in heavy industries, and strongly promote the development of hi-tech industries featuring low energy consumption and high net values. We should also work for fair and efficient allocation of resources and factors to improve the eco-environment and achieve sustainable development in China.