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Economic sustainability of China's growth from the perspective of its resource and environmental supply system: National scale modeling and policy analysis

  • NIU Fangqu , 1, 2 ,
  • JIANG Yanpeng 3
  • 1. Key Laboratory of Regional Sustainable Development Modeling, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China
  • 2. Collaborative Innovation Center for Geopolitical Setting of Southwest China and Borderland Development, Kunming 650500, China
  • 3. Institute for Global Innovation and Development, Center for Modern Chinese City Studies, School of Urban and Regional Science, East China Normal University, Shanghai 200062, China

Niu Fangqu (1979‒), PhD and Associate Professor, specialized in urban and regional sustainable development modeling. E-mail:

Received date: 2020-10-14

  Accepted date: 2020-12-20

  Online published: 2021-10-25

Supported by

National Natural Science Foundation of China(42071153)

Priority Research Program of Chinese Academy of Sciences(XDA20080000)


Since the implementation of the economic reform and opening up policy in 1978, China has miraculously created long-term high-speed economic growth, but has also had to face the problem of excessive consumption of resources as well as an intensification of environmental pollution. As a result, China is now facing a slowdown in development. China must maintain a certain speed of development to realize its goal of being a powerful nation, and becoming a developed country by 2050. To this end, China is facing a transformation of its economic development. There is a need to agree on an expected economic growth rate, along with the corresponding development modes or means of regulation in the medium- and long-term periods. This study developed a systematic-dynamic model to simulate the coupling relationship between economic growth, development modes, and the environmental supply system, and explored the possible options for future economic growth as well as the resource use and environmental protection requirements (the main factors). The results showed that to achieve the development goal of becoming a developed country by 2050, while maintaining a good ecological environment, the suitable growth rate for China's economy is 3.8%-6.3%. Within this range, a growth rate of 3.8%-4.4% was found to be relatively safe, while a growth rate of 4.4%-6.3% required further technical progress. This study provides an early warning in regard to China's environmental and development status. The study was a response to the “Future Earth” framework document and, in terms of development speed, it developed a theoretical system for the determination of resource and environmental carrying capacity (RECC).

Cite this article

NIU Fangqu , JIANG Yanpeng . Economic sustainability of China's growth from the perspective of its resource and environmental supply system: National scale modeling and policy analysis[J]. Journal of Geographical Sciences, 2021 , 31(8) : 1171 -1186 . DOI: 10.1007/s11442-021-1891-3

1 Introduction

Socioeconomic development is generally accompanied by resource consumption and environmental pollution. For a developing country seeking economic development, such as China, there are often problems in coordinating economic development with environmental pollution. Since the implementation of China's economic reform and open up policy in 1978, the miracle of rapid economic growth has, unexpectedly, lasted for nearly 40 years. According to the China Statistical Yearbook 2018, the GDP has increased by almost 10% annually for most of this period (NBSC, 2018a). However, such rapid economic growth has also given rise to a series of negative effects, such as excessive consumption of resources, environmental pollution, and even acute social conflicts, that have penetrated into the ecological and environmental system (Zhou and Zhou, 2017). To escape the “middle-income trap”, sustaining rapid economic growth over a long-term period is essential, in particular with reference to China's social stability and national security. Correspondingly, the Chinese central government has set a target to build a modernized and powerful nation-state by 2050. This modernization is anticipated to be accompanied by urbanization and industrialization (Kendall, 2007). Related to this target, from a policy and academic perspective, socioeconomic transformation is urgently needed and will have marked significance. The central government has therefore taken political measures to achieve this (i.e., stabilized economic growth and adjusted industrial structure). This study therefore addressed two interrelated research questions: (1) what is the appropriate rate of future economic growth in China? and (2) what development pathways should be adopted to attain the policy-making goal?
There are multiple factors that affect and even determine economic growth. They include the supply of resources, the security of land and water resources, the carrying capacity of the ecological and environmental system, and the growth potential and development mode of industry (Meadows et al., 1972). Considering the limited supply of these factors over short- and long-term periods, the prediction of the supply of these factors should be considered a component in the policy-making process with regard to national and regional development.
Several substantial geographic studies have investigated the relationships between economic systems, resources, and the environment (Gibbs and O'Neill, 2016; Jiang et al., 2017). In the early studies, causality was widely employed to explain the relationships between the geographic environment and the state of national development, resulting in the research field of geographic determinism (Huib and Chris, 2009; James and Aadland, 2011). In recent decades, the interplay between these two systems has been recognized and studied by academic communities (Fan and Qian, 2004; Zhao et al., 2011; Lanouar and Zouhair, 2017; Shan et al., 2017). In light of this theoretical reorientation, international scientists, economists, and educators gathered in Rome, in 1972, to jointly publish The Limits of Growth: The Report of the Club of Rome on Human Dilemmas. This book profoundly explained the principles underlying different systems, including population growth, food production, industrial development, resource consumption, and environmental pollution. These principles were integrated to evaluate the carrying capacity of the Earth, with the subject matter reminding humans to adjust their development methods and lifestyles to enable harmony between humans and the environment (Meadows et al., 1972). In 1992 and 2014, the second and third editions were published, which provided a more detailed and systematic analysis, while showing that human development has greatly surpassed the carrying capacity of the Earth's ecosystems (i.e., the emergence of the phenomenon of “overshoot”). In February 2012, the International Future Earth Transition Team developed a framework of Future Earth: Global Sustainability Research, arguing that human activities would trigger a dramatic and irreversible transformation of the Earth (FETT, 2012; Lu, 2014). In addition, this team initiated a comprehensive study that incorporated the environment, resources, and sustainable development, with the intention of providing policy guidance to governments. In terms of the research methodology, many methodological innovations have been initiated, such as the well-known population theory (Malthus, 1798), ecological footprint (Rees, 1992; Wackernagel and Rees, 1996; Sutton et al., 2012), energy value (Odum, 1988; Lou et al., 2015), and net primary production (NPP) (Vitousek et al., 1986; Thebault et al., 2008).
Chinese geographical research has proactively responded to these initiatives by fully committing to the exploration of the “human-land relationship” and its impact on development (Zhang and Liu, 2004; Zhou, 2015; Li et al., 2016; He and Shao, 2018). Studies of China's regional development originated in the mid to late 1970s. In the 1980s to 1990s, studies of regional development were only undertaken by economic geographers, and therefore interdisciplinary studies across the natural sciences and humanities are rare. Subsequently, the Chinese central government issued the “China's Agenda 21st” in 1994, which led to a surge of research in the field of sustainable development (SCC, 1994). The majority of the conventional literature has focused on the basic principles of regional sustainable development, as well as relevant strategies and plans (Wen et al., 1999; Liu and Chen, 2002; Jia and Liu, 2003; Chen, 2009). In the early stages of the 21st century, researchers studied the underlying mechanism between the elements of environment and development, with the primary research agenda being the “Assessment of Resource and Environmental Carrying Capacity” (Mao and Yu, 2001; Zhang et al., 2009; Li et al., 2012; Wang et al., 2014; Wei et al., 2014; Zheng et al., 2015; Peng et al., 2016; Fan et al., 2017; Zhou and Zhou, 2017). These studies, which produced both substantial literature and governmental policies, provided support to the sustainable development decision-making process. Several researchers have meticulously revisited these studies when considering the RECC systems in the past 100 years (Feng et al., 2017). However, there is little available literature regarding territorial practices that would enable the pathways and underlying mechanisms of sustainable development to be ascertained. In addition, researchers have downplayed the relationship between economic development and the environment, and have not agreed on how to determine a reasonable economic growth rate in different stages of development. The emergence of many such practical problems illustrates that the current research lacks foresight, and there is a need for research that focuses on the development mode and speed to be conducted across different disciplines.
The remainder of this article consists of five sections. The second section provides a simple introduction and quantifies the interactions between economic growth, resources, and the environment to uncover the trends of extensive development in China and the associated problems. We argue that China's RECC is not sufficient to achieve the government's development target if the present development mode, i.e., extensive development, is continued. The next section presents the detailed components of the proposed model (i.e., China model [CM]). This model links various important factors that determine the quality of economic growth and uses them in an assessment of development speed and mode. In the fourth section, several scenarios are simulated on the basis of possible strategies pertaining to China's socioeconomic transformation and development. These are used to explore the appropriate development speeds and modes, and thus provide references and a basis for the formulation of Chinese transformation and development strategies. The fifth section presents a detailed discussion that is followed by a concluding section that summarizes the major findings of this study and its theoretical implications for sustainable development and socioeconomic policy-making in China.

2 Brief analysis of Chinese economic growth

In 2017, China's population was 1.39 billion, and the GDP was 12.3 trillion USD (National Bureau of Statistics of China, 2018a). Figure 1 shows that China's population and GDP have experienced continuous growth since the economic reform and open up policy was initiated in 1978, with the GDP growth rate being significantly higher than the population growth rate. This indicates that the per capita GDP has experienced continuous growth. The annual average GDP growth rate from 1978 to 2011 was 10%; however, it slightly declined after 2011. In 2017, China's economic growth rate was 6.9%, and per capita GDP was 8573.7 USD, which represented the middle-income level according to the international standards formulated by the World Bank (WB, 2017a). There has been a substantial linear increase in population from 1978 to 2017. Before 2015 the population grew at an annual average rate of 12.6 million, but after 2015 the annual average growth rate experienced a slight decline to 7.50 million, which corresponded with the release of the “second-child” policy.( China implemented “Family Planning” in 1978, which required a couple to have only one child. Since 2015, couples have been permitted to give birth to two children, through a system known as the “second-child” policy.) With the continuation of the current economic and population growth, per capita GDP will reach 12,800 USD in 2023, meeting the high-income level of developed countries.
Figure 1 Economic and population growth in China
Urbanization and industrialization are two important pillars of a modern state. Inspired by modernized capitalist countries, such as the USA, the UK, Japan, and Germany, the urbanization rate (i.e., percentage of total population living in urban areas) of a modern country should exceed 75% and the proportion of tertiary industry within the industrial structure should be higher than 60% (WB, 2017b, 2019). According to the China Statistical Yearbook 2018, China's urbanization rate has increased from 17.92% in 1978 to 58.52% in 2017, which is a growth of 1.03 percentage points per year. The proportion of tertiary industry has risen from 24.6% in 1978 to 51.6% in 2017, with an annual average growth of 0.69 percentage points. At this rate, China will complete the industrial upgrading process in 2030, with tertiary production accounting for 60% of total GDP, while an urbanization rate of 75% will be achieved after 2033.
The total water resource in China in 2017 was 2876.12 billion m3. The total water consumption was 604.34 billion m3 (21%), and the per capita water consumption was 435.91 m3 (NBSC, 2018a). Generally speaking, a region is deemed to be short of water if the total water consumption exceeds 20% of its total regional water resources. The water supply will be relatively severely constrained once water consumption exceeds 40%. The worst-case scenario is that more than 70% of the water resource is consumed (Wada et al., 2011; Hoekstra et al., 2012). Based on the current water consumption rate, China has entered the stage of water shortage. With the projected trends in economic growth and water consumption required, the water supply will become relatively severely constrained in 2028.
Chemical oxygen demand (COD) is an important indicator of water quality. According to statistical data, the national COD discharge in 2017 was 10.22 million tons (NBSC, 2018a). Based on China's environmental quality standards for surface water, i.e., the Class I and Class II water COD content (≤15 mg/L), the COD residual capacity would become overloaded at a national discharge of 32.92 million tons. Based on the current COD discharge intensity, the capacity of the water environment will become overloaded in 2039.
In terms of land resource utilization, the total area of built-up land in 2020 is planned to reach 40,719,300 ha (NDRC, 2016). In 2017, the total area of built-up land was 39,574,100 ha, i.e., 1,415,200 ha short of the planned total for 2020. From 2012 to 2017, the annual average growth of built-up land was 529,400 ha. At that speed the limitation for built-up land will be met in 2021. Therefore, it can be inferred that the planned area of built-up land will meet the land use requirements in 2020.
In terms of energy consumption, the total energy consumption of China was around 4358.2 million tons of standard coal in 2017. Energy consumption is derived from the use of both imported and locally extracted resources, and all energy sources (i.e., coal, oil, and natural gas) need to be evaluated. The total consumption of the three energy sources in 2017 was 3861.76 million tons of standard coal, of which, the domestic extracted was 2979.90 million tons of standard coal. The total proven reserves of the three energy sources are around 187,298.9 million tons of standard coal. From 2007 to 2017, China's energy production elasticity coefficient (i.e., the ratio of the annual growth rate of energy production to the annual growth rate of the national economy) was 0.45. Therefore, the growth rate of energy extraction is 3.11%, which corresponds to an economic growth rate of 6.9%. At this consumption rate, China's three common energy sources will be exhausted in 2052.
The extensive development process described above is comprehensively characterized in Figure 2. It indicates that China will enter the ranks of developed countries before 2050, but it will experience both excessive water consumption and serious environmental pollution that could bring it to the verge of energy exhaustion. The resource and environmental supply system is inadequate to support the current extensive growth mode. Therefore, identifying an appropriate growth rate and mode of development is of great significance, both theoretically and empirically.
Figure 2 The projected trend of China's extensive development

3 Data collection and research methodology

3.1 Data collection

The study area was Chinese mainland, which consists of 28 provincial-level administrative regions and four municipalities that are under direct jurisdiction of the central government. The data used was collected from the China Statistical Yearbook 2018 (NBSC, 2018a), the China Energy Statistical Yearbook 2017 (NBSC, 2017), the China City Statistical Yearbook 2018 (NBSC, 2018b), China Urban Construction Statistical Yearbook 2018 (MOHURD, 2018), and the China Environmental Statistics Yearbook 2015 and 2017 (NBSC and MEPC, 2015, 2017). The specific data or parameters used are explained in the following sections.

3.2 Research methodology

Systematic-dynamics (SD) model is an approach that has been widely used to simulate the behavior of real world nonlinear complex systems (Zhou and Zhou, 2017). The system of human-land/social economy-environment is a complicated dynamic system, with multiple interacting elements. The SD model has also been widely used in RECC evaluation (Zhang et al., 2014; Yang et al., 2015; Zhou and Zhou, 2017), and its simulation results have been good. To address the research questions, an SD model (i.e., CM) was developed to simulate the interaction between socio-economic, resource, and environmental factors, and determine the appropriate development speed and mode. The Vensim DSS was adopted as a CM platform. The base year of the simulation was set to 2017 and it made annual predictions through to 2050. The CM consists of multiple components, including population, economy, water resource, energy, and land use components. These components are connected to each other, as explained in the following text.

3.2.1 Population component

The population component was included to predict the demographic trends, urban population growth, and urbanization processes/degree based on historical changes. The total population in a large country, such as China, is strongly affected by fertility-related policies and willingness to give birth. According to a previous analysis, the population in China has been growing linearly. After the implementation of the “second-child” policy, the population has grown at an annual average rate of 7.5 million, i.e., less than the annual rate of 12.6 million before 2015. This indicates that Chinese people's willingness to bear children is declining. This study used the World Bank's forecast of China's population growth, which predicts that China's population will reach a peak of 1.417 billion in 2028. The urbanization rate reached 58.52% in 2017. This indicates that to attain an urbanization rate of 75% by 2050, the urbanization rate needs to increase at a rate of 0.50 percentage points per year.

3.2.2 Economic component

This is an important component because economic growth directly determines the level of per capita income, resource consumption, and environmental pollution. The processes of economic growth and industrial structure change are simulated in this component. In CM, the economic growth rate and industrial structure are adjustable parameters within the simulation process. Essentially, these parameters are determined to identify the appropriate mode and rate of development. The GDP in every year is initially predicted on the basis of a certain growth rate. The per capita GDP is then calculated by combining the predicted GDP with the population forecast. Primary production has accounted for a stable proportion of China's industrial structure over the past few decades, with an average value of 7.9%. The CM considers the proportion of primary production to remain stable, and therefore uses this value. In 2017, the proportion of tertiary production in China's industrial structure accounted for 51.6% of the total. If the industrial upgrading process is completed in 2050, and the proportion of tertiary production reaches 60% as planned, the proportion of tertiary production will increase by an average of 0.25 percentage points per year. The proportion of secondary production is therefore calculated in accordance with the proportions of primary and tertiary industries.

3.2.3 Water resource component

The water resource component is used to simulate changes in total water use, which includes production water and domestic water. According to 2017 statistical data, the total water resources in China were around 2,876 billion m3. The primary consumption, secondary industrial consumption, and domestic water consumption (including tertiary production) were 376.64, 127.7, and 83.8 billion m3, respectively. The GDP values of primary and secondary production were 6546 and 33,462 billion yuan, respectively, and the population was 1.39 billion (NBSC, 2018a). The intensity of water consumption pertaining to both production and domestic uses can therefore be calculated, with the intensities of the primary and secondary production being 0.385 and 0.026 m3 per USD, respectively. The intensity of the domestic water consumption was calculated to be 60 m3 per capita. In addition, ecological water accounted for 2.8% of the total water consumption in 2017, and CM therefore allocates the same proportion of water for ecological usage. Finally, the total water consumption for every year in the future is predicted via the integration of the primary, secondary, domestic, and ecological water consumptions, which is given by formula (1):
where w is the total water consumption, rpri and rter are the ratios of primary and tertiary production to total GDP, pop is population, and weco is ecological water consumption.

3.2.4 Environment component

The environment component is used to simulate changes in the water environment. Water quality is affected by several factors, with the widely-used COD parameter adopted in this study to simulate changes of water quality alongside economic development. Considering the Class I and Class II water quality standards, the total COD capacity of the national water resource is 43.114 million tons. To maintain good water quality, the total COD discharge ttlCOD cannot exceed the upper limit of the water environmental capacity. The intensity of production and domestic pollutant discharges of each industrial sector were obtained from economic and pollutant discharge data (NBSC, 2018a; NBSC and MEPC, 2017). The primary industry discharge intensity was calculated to be 4550 tons per billion USD, the secondary industry discharge intensity was 260 tons per billon USD, and the domestic discharge intensity was 0.0053 tons per capita. Based on these values, the ttlCOD in each year can be determined in formula (2):
where ttlCOD is the total COD discharge from industrial production and domestic sources, rpri and rsec are the proportion of primary and secondary production, respectively, and pop is total population.

3.2.5 Energy component

The energy component is used to calculate energy consumption, which includes industrial and domestic consumptions. The China Statistical Yearbook 2018 shows that China's total energy consumption in 2017 was 449 million tons of standard coal (NBSC, 2018a). Energy consumption intensity by industrial sector can be calculated in accordance with the energy consumption and GDP. The primary industry energy consumption intensity was calculated to be 0.0871 million tons per billion USD, secondary industry energy consumption intensity was 0.6767 million tons per billion USD, and the energy consumption intensity of tertiary industry was 0.131 million tons per billion USD. Residential energy consumption intensity was calculated based on domestic energy consumption and population, and was determined to be 0.39 tons per capita. Accordingly, based on projected economic and population growth, the total energy consumption for each year can be calculated by summing industrial and residential energy consumption, which is given by formula (3):
where E is the total energy consumption, GDPp, GDPS, and GDPt are the GDP of the primary, secondary, and tertiary industry, respectively, and pop is population.
Socioeconomic development is limited by the total amount of the available energy, which is generated from both local and imported resources. The total consumption of local energy generated through common energy sources (i.e., coal, oil, and natural gas) was 2979.90 million tons of standard coal in 2017, which accounted for 66.4% of the total energy consumption. The total proven reserves of the three common energy types are around 187,298.9 million tons of standard coal. The amount of these energy sources that remain is the total reserves minus the total annual consumption, which is calculated using formula (4):
${{E}_{a}}={{E}_{three\_ttl}}-\underset{i}{\mathop \sum }\,({{E}_{i}}*66.4%)$
where Ea is the amount of energy resource that remains, Ethree_ttl is the total amount of the three types of common energy, and Ei is the energy consumption of year i. The total economic volume and population that the remaining reserves can support will be calculated through formulas (3-4).

3.2.6 Land use component

The land use component is used to depict the growth of built-up land. The Urban Construction Statistical Yearbook shows that the area of urban built-up land in 2018, including residential land, industrial land, and tertiary industry land was around 55,155.47 km2 (MOHURD, 2018). Combining GDP within industry and population, the intensity of built-up land consumption was calculated: the industrial land consumption intensity was 2.652 km2 per billion USD, the tertiary industry land consumption intensity was 0.864 km2 per billion USD, and the residential land consumption intensity was 20,870 km2 per billion people. Based on this data, the increase in the area of land needed for industrial development and population growth can be calculated from formula (5):
$\Delta Lan{{d}_{c}}=\Delta GD{{P}_{s}}*2.652+\Delta GD{{P}_{t}}*0.864+\Delta Urban\_pop*20870$
where ΔLandc is the total amount of new built-up land, ∆GDPS and ∆GDPt are the respective increases in secondary and tertiary GDP, and ΔUrban_pop is the growth of urban population. The area of land used for residential and industrial purpose will continue to increase, but the total amount should not exceed the total amount of planned built-up land, i.e., 40.7193 million ha for 2020.

3.2.7 China model

The above components were integrated to construct an SD model (i.e., CM) that simulated China's development process, as shown in Figure 3. The core elements of every module are dark-colored. The input parameters of the CM include population, GDP, industrial structure, the resource consumption intensity of various industries and populations, pollutant discharge intensity, population and GDP growth rate, and other control parameters. The outputs are the remaining built-up land, the remaining water resources, the remaining environmental capacity, and the remaining energy reserves in each year in the future. In CM, changes in GDP, population, and industrial structure will lead to changes in the simulation results. Any changes in the intensities of resource consumption and pollutant discharge will also lead to changes in the simulation results. Using CM, the appropriate rate and mode of development to accomplish the development goal can be obtained.
Figure 3 The SD model: China model

4 Scenario setting and results

With the overall aim of China becoming a developed country by 2050, different development scenarios were established to examine the impact of the different rates and modes of development upon the resource and environmental supply system. An appropriate rate and mode of development were determined. The standards required to meet the conditions of a developed country were set as follows: the resource and environmental supply system must be in good condition, there must be a high-income, and the country must be modernized. As discussed above, modernization was defined by an urbanization rate of above 75% and a tertiary production ratio of more than 60%.

4.1 Scenario 1

This scenario was created to determine the maximum rate of development that can be adopted to ensure the continuation of current levels of technological advancement. Essentially it asks, if the current intensities of resource consumption and pollutant discharge remain unchanged, what is the maximum rate of economic growth that can be adopted to enable China to become a developed country by 2050, without the resource environment overloading? As we determined earlier, to establish an urbanization rate of 75% and an industrial structure with more than 60% of the industry being tertiary production, the minimum annual growth rate of urbanization and tertiary production needs to be 0.50 and 0.25 percentage points, respectively. Compared with the current situation, the rate of urbanization and industrial transformation will both decrease slightly. The CM simulation results showed that to maintain the supply of resources and environmental protection without overloading them by 2050, the maximum economic growth rate that can be adopted is 3.8%, which will enable China to reach a per capita GDP of 12,650 USD in 2027, and so become a high-income country. This means that within this scenario, with an annual economic growth rate of 3.8%, China will become a developed country while maintaining a strong resource and environmental supply system.

4.2 Scenario 2

With reference to the level of technological development in the USA, this scenario set an optimistic pace of development. Based on scenario 1, scenario 2 was further developed by improving the level of technological progress. In general, technological progress will contribute to an enhanced efficiency of resource utilization as well as the decrease of pollutant discharge. However, it is difficult to quantify technological progress. Existing data suggests that resource consumption and pollutant discharge in the USA have been relatively stable in recent years. In 2015, the intensity of water consumption in the USA was 0.029 billion m3 per billion USD (Dieter et al., 2018; USGS, 2019), which represents only 60% of the intensity of water consumption in China. In 2050, for China to reach the same level of water consumption as the USA, the intensity of water consumption needs to decline annually by 1.22 percentage points from the 2017 level. Energy consumption within the USA in 2017 was 0.01647 million tons of standard coal per billion USD of GDP (Statista, 2018), which represents 45% of the intensity of energy consumption in China. If the energy consumption intensity in China is to reach that level in 2050, it needs to decrease annually by 1.67% percentage points. Because pollutant discharge is directly linked to energy consumption, the rate of improvement in pollutant discharge was set to be equivalent to the rate of energy consumption. Thus, the CM simulation results revealed that the maximum economic growth rate could be 6.3%, which ensured that the resource and environmental supply system in China would not be overloaded by 2050. Under this growth rate, China will become a high-income country in 2023. In summary, based on the optimistic belief that China's level of technological development in 2050 will reach the current level of the USA, the maximum economic growth could be maintained at 6.3% to ensure that China achieves its target of becoming a developed country by 2050 without overloading the resource and environmental supply system.

4.3 Scenario 3

This scenario was also based on scenario 1 but considered the optimal speed for development in relation to what was considered the likely pace of technological development in China. To determine the pace of technological development in this scenario, reports from the National Information Center were consulted, indicating that the pace of Chinese technological progress has increased annually by 0.42% since 2000 (NICC, 2016). Based on this result, we assumed that the intensity of resource consumption and pollutant discharge in China would decrease annually at a rate of 0.42%. In terms of urbanization and transformation of the industrial structure, we set the same change process as used in the previous scenarios. The CM simulation results showed that the maximum annual growth rate could be 4.4%, which would mean China will become a high-income country in 2026. Therefore, in this scenario, with an annual economic growth rate of 4.4%, China could become a developed country by 2050 without overloading the resource and environmental supply system.
The parameters used in these three scenarios are listed in Table 1. To summarize, to achieve modernization by 2050, the minimum annual growth rate of urbanization and tertiary industry development should be 0.50 and 0.25 percentage points, respectively. In terms of the economic growth rate, given its current level of technological development, China can adopt a maximum economic growth rate of 3.8%. If we are optimistic and believe that the level of technological development will continue to advance and reach the current level of the USA by 2050, the maximum economic growth rate that can be adopted is 6.3%. However, with reference to China's technological progress in the past two decades, an economic growth rate of 4.4% is more likely. Thus, it can be concluded that the future economic growth rate in China will range from 3.8% to 6.3%. Within this range, 3.8% to 4.4% is considered a safe pace of development, while a growth rate within 4.4% to 6.3% would require further technical advances. To reduce the impact of socioeconomic development on the resource and environmental supply system, the rate of economic growth could be reduced. Additionally, socioeconomic growth could also increase if the level of technological development is sufficient.
Table 1 Parameters of the three development scenarios
Parameter categories Parameters Current
Scenario 1 Scenario 2 Scenario 3
Population and urbanization Population growth rate
(10,000 people/year)
750 World Bank forecast World Bank
World Bank
Urbanization growth rate
(percentage point/year)
1.03 0.5 0.50 0.50
Industry and economy Rate of change in the proportion of tertiary production
(percentage point/year)
0.69 0.25 0.25 0.25
Economic growth rate (%) 6.9 3.8 6.3 4.4
Water resource Water consumption intensity
of primary industry (m3/USD)
0.385 0.385 Annual decrease of 1.22 percentage points Annual
of 0.42%
Water consumption intensity of secondary industry (m3/USD) 0.026 0.026 Annual decrease of 1.22 percentage points Annual
of 0.42%
Domestic water consumption intensity (m3/USD per capita) 60 60 Annual decrease of 1.22 percentage points Annual
of 0.42%
Water environment COD discharge intensity of
primary industry
(tons/billion USD)
4550 4550 Annual decrease of 1.67 percentage points Annual
of 0.42%
COD discharge intensity of secondary industry
(tons/billion USD)
260 260 Annual decrease of 1.67 percentage points Annual
of 0.42%
Domestic COD discharge
intensity (tons per capita)
0.0053 0.0053 Annual decrease of 1.67 percentage points Annual
of 0.42%
Energy Energy consumption intensity
of primary industry
(million tons/billion USD)
0.0871 0.0871 Annual decrease of 1.67 percentage points Annual
of 0.42%
Energy consumption intensity
of secondary industry
(million tons/billion USD)
0.6767 0.6767 Annual decrease of 1.67 percentage points Annual
of 0.42%
Energy consumption intensity
of tertiary industry
(million tons/billion USD)
0.131 0.131 Annual decrease of 1.67 percentage points Annual
of 0.42%
Domestic energy consumption
(tons per capita)
0.39 0.39 Annual decrease of 1.67 percentage points Annual
of 0.42%
Land use Industrial land consumption intensity (km2/billion USD) 2.652 2.652 2.652 2.652
Tertiary land use intensity
(km2/billion USD)
0.864 0.864 0.864 0.864
Residential land use intensity
(km2/billion people)
20870 20870 20870 20870

5 Discussion

With regard to the validity or reliability of the model, there were several factors that require further discussion, e.g. mobility of resources, industrial structure, and study scales.

5.1 Mobility of resources

Many resources can be moved across regions through market flows, and can therefore be obtained from both local and imported supplies. By focusing on the carrying capacity of local resources, this study evaluated the intensity of consumption of local resources by the socio-economic system. Therefore, the simulation results are of great significance to the current socio-economic system. Changes in the socio-economic system may increase the proportion of imports in the local market, while reducing the intensity of consumption of local resources. Therefore, to improve the accuracy and reliability of the simulation results, it is necessary to further consider the trends of the dependence of the socio-economic system on external resources. The advantage of this model lies in its horizontal comparison among different development scenarios, rather than the absolute forecast values.

5.2 Industrial structure and land use

This study simulated the interaction among the development pathways of the three major industries, population growth, and the resource and environmental supply system at the national scale. However, resource consumption and environmental effects vary across different industries, as well as the internal sectors within a particular industry. To provide more explanatory industrial adjustment decisions, a microscopic simulation must be conducted on the basis of sub-sectors. This study did not take into account any changes in land use intensity in the proposed scenarios. The relationships between land use and economic activities are complicated. With economic growth, the demands for land do not increase proportionally. Therefore, further study is required to refine the relationship between economic activity and land use, which will enable changes in land demand with socioeconomic development to be predicted.

5.3 Spatial and temporal scales

In terms of their spatial scale, population and industries are generally not evenly distributed across various land areas due to the geographical conditions. Therefore, even if all the socioeconomic impacts of development are within an acceptable range at the national level, some regions with high socio-economic densities may encounter an overload. To achieve decision support for the sustainable development of sub-regions, studies at the regional level are urgently needed. In addition, this study did not consider long-term development; therefore, the simulation results did not identify the rate and mode of development that should apply after 2050. This study only attempted to determine the preferred rate and mode of development for achieving the development goal by 2050. For long-term development, in the wake of likely technological progress the RECC will be further enhanced. The China model can be used to test different development scenarios and provide a reference for decision-making, rather than make decisions for us. The relative distribution of the model results is more significant than the absolute values.

6 Conclusions

The long-term rapid growth of China's economy has led to an excessive consumption of resources and an increasingly damaged environment. However, to achieve modernization and become a high-income country, China needs to maintain a certain speed of development. The country is therefore confronted with the demands of both environmental improvement and stable development. Researchers and the policy-makers face challenges related to the appropriate rate of economic growth and mode of development. This study developed a systematic-dynamic model (i.e., CM) for simulating the interactions among economic development, urbanization, industrial structure, and the resource and environmental supply system, which also identified the appropriate growth speed and development mode. This study makes a contribution to domestic sustainable development research in China, and provides an important response to the “Future Earth” framework document initiative.
The results showed that to achieve the development goal of becoming a developed country by 2050 or earlier, while maintaining an acceptable eco-environment, it is necessary for China to adopt an economic growth rate of 3.8% to 6.3%. This was determined on the premise that technological progress will improve the efficiency of resource utilization as well as reduce pollutant discharge. While growth speeds of 3.8% to 4.4% were found to be safe rates, a growth rate of 4.4% to 6.3% would require advances in technological progress. Therefore, while a lower growth rate could be adopted to reduce the pressure on resource and environmental supply systems, a higher growth rate could be adopted only with advances in technological progress. Different development scenarios can be compared and analyzed through model proposed, and better development modes can be identified to support decision-making. This study developed a theoretical system of RECC, with respect to a suitable rate of economic growth. It provides a reference for studies of economic growth and resource and environmental supply systems, and the results will be of great value to the theoretical development and practices.
This study provides a baseline and a useful model, but the analysis still needs to be deepened and developed. The basic scenarios are set in accordance with China's development goals; however, socio-economic development is actually influenced by more factors than the factors considered in CM. Therefore, the model needs to incorporate more socio-economic, resource, and environmental elements. A detailed application of this research needs to be conducted on the basis of a subdivided industrial structure and a study area to support the future adjustment of industrial structure, industrial spatial optimization, resource use, and environmental management.
Chen S Y, 2009. Energy consumption, CO2 discharge and sustainable development in Chinese industry. Economic Research Journal, (4):41-55. (in Chinese)

Dieter C A, Maupin M A, Caldwell R R et al., 2018. Estimated use of water in the United States in 2015: U.S. Geological Survey Circular, 1441,65p.

Fan J, Qian Q L, 2004. A comparative-study on the interactive relations between economic development and resource-environment in China's eastern coastal areas. Journal of Natural Resources, 19(1):96-105. (in Chinese)

Fan J, Zhou K, Wang Y F, 2017. Basic points and progress in technical methods of early-warning of the national resource and environmental carrying capacity (V2016). Progress in Geography, 36(3):266-276. (in Chinese)

Feng Z M, Yang Y Z, Yan H M et al., 2017. A review of resources and environment carrying capacity research since the 20th century: From theory to practice. Resources Science, 39(3):379-395. (in Chinese)

Future Earth Transition Team FETT, 2012. Future Earth: Research for global sustainability: A framework document. accessed in Dec. 2019.

Gibbs D, O'Neill K, 2016. Future green economies and regional development: A research agenda. Regional Studies, 51(1):161-173.


He S W, Shao X, 2018. Spatial clustering and coupling coordination of population-land-economic urbanization in Beijing-Tianjin-Hebei region. Economic Geography, 38(1):95-102. (in Chinese)


Hoekstra A Y, Mekonnen M M, Chapagain A K et al., 2012. Global monthly water scarcity: Blue water footprints versus blue water availability. Plos One, 7(2):e32688.


Huib E, Chris P, 2009. Determinism/environmental determinism. International Encyclopedia of Human Geography, 29(3):102-110.

James A, Aadland D, 2011. The curse of natural resources: An empirical investigation of U.S. counties. Resource and Energy Economics, 33(2):440-453.


Jia R X, Liu Y, 2003. China's regional sustainable development status quo and its classification. Geographical Research, 22(5):637-652. (in Chinese)

Jiang L, Bai L, Wu Y M, 2017. Coupling and coordinating degrees of provincial economy, resources and environment in China. Journal of Natural Resources, 32(5):637-652. (in Chinese)

Kendall D, 2007. Sociology in Our Times. Boston: Cengage Learning.

Lanouar C, Zouhair M, 2017. The impact of economic development and social-political factors on ecological footprint: A panel data analysis for 15 MENA countries. Renewable and Sustainable Energy Reviews, 76.

Li T X., Fu Q, Peng S M, 2012. Evaluation of water and soil resources carrying capacity based on DPSIR frame work. Journal of Northeast Agricultural University, 43(8):637-652. (in Chinese)

Li X Y, Yang Y, Liu Y, 2016. Research progress in man-land relationship evolution and its resource-environment base in China. Acta Geographica Sinica, 71(12):2067-2088. (in Chinese)

Liu Y S, Chen B M, 2002. The study framework of land use/cover change based on sustainable development in China. Geographical Research, 21(3):637-652. (in Chinese)

Lou B, Qiu Y H, Ulgiati S, 2015. Energy-based indicators of regional environmental sustainability: A case study in Shanwei, Guangdong, China. Ecological Indicators, 57:637-652.

Lu D D, 2014. The framework document of “Future Earth” and the development of Chinese geographical science: The foresight of Academician HUANG Bingwei's statement. Acta Geographica Sinica, 69(8):1043-1051. (in Chinese)

Malthus T R, 1798. An Essay on the Principle of Population. London: Pickering, 2001.

Mao H Y, Yu D L, 2001. Regional Carrying Capacity in Bohai Rim. Acta Geographica Sinica, 56(3):637-652. (in Chinese)

Meadows D H, Meadows D L, Randers J et al., 1972. The Limits to Growth:A Report for the Club of Rome's Project on the Predicament of Mankind. New York: Universe Books.

Ministry of Housing and Urban-rural Development of the People's Republic of China MOHURD, 2018. China Urban Construction Statistical Yearbook. Beijing: China Planning Press.

National Bureau of Statistics of China NBSC, Ministry of Environmental Protection of China MEPC, 2015. China Statistical Yearbook on Environment 2015. Beijing: China Statistics Press.

National Bureau of Statistics of China NBSC, Ministry of Environmental Protection of China MEPC, 2017. China Statistical Yearbook on Environment 2017. Beijing: China Statistics Press.

National Bureau of Statistics of China NBSC, 2017. China Energy Statistical Yearbook 2017. Beijing: China Statistics Press.

National Bureau of Statistics of China NBSC, 2018a. China Statistical Yearbook 2018. Beijing: China Statistics Press.

National Bureau of Statistics of China NBSC, 2018b. China City Statistical Yearbook 2018. Beijing: China Statistics Press.

National Development and Reform Commission (NDRC), 2016. Adjustment for National Land Use Master Plan of China (2006-2020). accessed in Dec. 2018.

National Information Center of China NICC, 2016. Measurement and decomposition of China's total factor productivity. accessed in Dec. 2018.

Odum H T, 1988. Self-organization, transformity, and information. Science, 242:1132-1139.


Peng J, Du Y Y, Liu Y X, Hu X X, 2016. How to assess urban development potential in mountain areas? An approach of ecological carrying capacity in the view of coupled human and natural systems. Ecological Indicators, 60:1017-1030.

Rees W E, 1992. Ecological footprints and appropriated carrying capacity: What urban economics leaves out. Environment and Urbanization, 4(2):637-652.

Shan Y, Zheng H R, Guan D B et al., 2017. Energy consumption and CO2 emissions in Tibet and its cities in 2014. Earth's Future, 5(8):637-652.

State Council of China SCC, 1994. China Agenda 21. accessed in Aug. 2018.

Statista, 2018. U.S. Energy consumption. accessed in Jan. 2019.

Sutton P C, Anderson S J, Tuttle B T et al., 2012. The real wealth of nations: mapping and monetizing the human ecological footprint. Ecological Indicators, 16:11-22.

Thebault J, Schraga T S, Cloern J E et al., 2008. Primary production and carrying capacity of former salt ponds after reconnection to San Francisco Bay. Wetlands, 28(3):637-652.

USGS, 2019. Total water use. accessed in Feb, 2019.

Vitousek P M, Ehrlich P R, Ehrlich A H et al., 1986. Human appropriation of the products of photosynthesis. BioScience, 36(6):637-652.

Wackernagel M, Rees B, 1996. Our Ecological Footprint: Reducing Human Impact on the Earth. Gabriola, British Columbia: New Society Publishers.

Wada Y, van Beek L P H, Viviroli D et al., 2011. Global monthly water stress: Water demand and severity of water stress. Water Resources Research, 47:W07518.

Wang S, Xu L, Yang F L et al., 2014. Assessment of water ecological carrying capacity under the two policies in Tieling City on the basis of the integrated system dynamics model. Science of the Total Environment, 472:1070-1081.

Wei C, Guo Z Y, Wu J P et al., 2014. Constructing an assessment indices system to analyze integrated regional carrying capacity in the coastal zones: A case in Nantong. Ocean Coastal Management, 93:51-59.

Wen Y M, Ke X K, Wang F, 1999. Study on assessment system and assessment method of sustainable development of human-earth system. Advance in Earth Sciences, 14(1):51-55. (in Chinese)

World Bank WB, 2017a. New country classifications by income level:2017-2018. accessed in January, 2019.

World Bank WB, 2017b. World Development Indicators: Structure of output. Accessed in January, 2019.

World Bank WB, 2019. Accessed in August, 2019.

Yang J F, Lei K, Khu S T et al., 2015. Assessment of water environmental carrying capacity for sustainable development using a system dynamics model applied to the Tieling of the Liao River Basin, China. Environmental Earth Sciences, 73:5173-5183.


Zhang L, Liu Y, 2004. An analysis on man-land relationship of eastern China. Acta Geographica Sinica, 59(2):637-652. (in Chinese)

Zhang L B, Li X, Li W H et al., 2009. Human carrying capacity research: Dilemma and reasons. Acta Ecologica Sinica, 29(2):637-652. (in Chinese)

Zhang Z, Lu W X, Zhao Y et al., 2014. Development tendency analysis and evaluation of the water ecological carrying capacity in the Siping area of Jilin Province in China based on system dynamics and analytic hierarchy process. Ecological Modelling, 275:9-21.


Zhao X G, Pan Y J, Zhao B et al., 2011. Temporal-spatial evolution of the relationship between resource-environment and economic development in China: A method based on decoupling. Progress in Geography, 30(6):637-652. (in Chinese)

Zheng D F, Zhang Y, Zang Z et al., 2015. Empirical research on carrying capacity of human settlement system in Dalian City, Liaoning Province, China. Chinese Geographical Science, 25(2):637-652.

Zhou X F, 2015. The model of human-earth areal system based on Yinyang of I Ching. Geographical Research, 34(2):637-652. (in Chinese)

Zhou Y J, Zhou J X, 2017. Urban atmospheric environmental capacity and atmospheric environmental carrying capacity constrained by GDP-PM 2.5. Ecological Indicators, 73:637-652.