Evaluation of Water–Carbon–Ecological Footprint and Its Spatial–Temporal Changes in the North China Plain

Abstract

The North China Plain (NCP) serves as the main grain production land in China, functioning as a critical region for ensuring China’s food security. To address the multifaceted challenges confronting food security in the NCP, the study embarked on a comprehensive analysis of the synergistic interactions between agricultural water usage, carbon emissions, and ecosystem health. By proposing footprint family indicators and using the bottom-up IPCC coefficient approach, this study quantitatively evaluates the spatial–temporal changes of water–carbon–ecological footprints in NCP from 2003 to 2020. Furthermore, a coupling coordination degree model that focuses on the coordination of water–carbon–ecological footprints is established. The findings are as follows: (1) The total water footprint in the NCP showed a striking increasing trend with an increase of 1.52 × 10¹¹ m³, and the carbon footprint increased by 1.27 × 10⁹ t, with significant ecological impacts. (2) The NCP’s ecological footprint exhibited an “M”-shaped trend. The land structure maintained stable with negligible changes in the proportion of ecological footprints. (3) The coupling degree between the footprints of water, carbon, and ecology in the NCP is high, revealing a noteworthy interaction effect. This research can provide data support for effective resources allocation and sustainable social–economic development, offering reasonable insights for China to formulate more scientific policies of green transition in land use and ecological civilization construction.

1. Introduction

The importance of sustainable development in addressing environmental and social issues has been widely recognized [1]. In response to global resource consumption challenges, as highlighted by the 2012 United Nations Conference on Sustainable Development (“Rio+20”), developing more sustainable consumption and production (SCP) practices is a key component of the sustainable development agenda [2]. The goal is to reduce environmental impacts and implement integrated policies that promote resource efficiency and sustainable consumption, aiming for a more sustainable future at both urban and broader levels. This requires considering the synergies between various related areas, such as water and carbon. Therefore, to gain a comprehensive understanding of the connections between these sectors, the environmental footprint proposed by scholars can be seen as an important conceptual tool for achieving sustainable development [3].

The concept of the footprint originated as a measure of the physical area of land occupied by an entity, that is, the imprint it leaves upon the land [4]. However, the definition has since been broadened to “an indicator of human pressure on the environment [5]”. This notion was initially coined from the ecological footprint, which was introduced by Rees in 1992 [4]. The ecological footprint draws a correlation between human society and the natural environment by quantifying the biologically productive land area required [6]. As the inaugural comprehensive footprint indicator, the ecological footprint serves to gauge the degree of environmental degradation resulting from human activities. It aids individuals in comprehending the direct and indirect consequences of their actions on the planet [7]. Over the years, the ecological footprint has gained considerable traction and popularity within environmental discourse. The ecological footprint is predominantly determined utilizing the global hectare (gha) approach, which was first introduced by Wackernagel [8]. Jaibumrung et al. [9] applied this method to calculate the ecological footprint of rice production in Thailand, which incorporates GHG emissions, water, and land demand into productive land use, thus contributing to the understanding of resource utilization and resource reduction analysis. Lee et al. [10] conducted a comprehensive analysis of Taiwan’s ecological footprint from 2000 to 2018, charting its long-term trajectory. In response to certain limitations of the global hectare (gha) method, such as its failure to account for regional heterogeneity, recent studies have suggested alternative approaches [11]. These include the use of national hectares (nha), provincial hectares, or local hectares as substitutes for the global hectare method. The national hectare method offers several advantages over its counterparts. It provides a more precise assessment of the ecological status of regions at the sub-national level compared to the global hectare method. Additionally, it facilitates the horizontal comparison of ecological status across different regions at the national scale, as opposed to the provincial or local hectare methods [12]. For instance, Zhang et al. [13] applied the nha method to calculate the ecological footprint of Shaanxi Province and enhanced the assessment of its three-dimensional ecological footprint. This approach was instrumental in evaluating the ecological security patterns within the province. Furthermore, Li et al. [14] developed an ecological footprint accounting system based on the national hectare method and conducted a thorough analysis of natural resource consumption across 31 provinces in China over the period from 2000 to 2018.

Building upon the concept of the ecological footprint, the carbon and water footprints have been sequentially introduced as complementary indicators. The carbon footprint, when defined in land-based terms [15], refers to the amount of land necessary for sequestering carbon dioxide emissions and is also recognized as the “energy footprint” [16]. In the context of carbon footprint accounting, the Intergovernmental Panel on Climate Change (IPCC) method has gained international recognition and is widely utilized for estimating carbon emissions [17]. Dong et al. [18] employed the IPCC coefficient method to calculate the carbon footprint of the Tibetan region, thereby assessing the ecological sustainability of the area’s urban centers. Their findings revealed that the distribution of sub-footprints within the city was both spatially distributed and uneven. Similarly, Huo et al. [19] quantified the carbon emissions of the North and Northeast China plains. They conducted an in-depth assessment of the carbon footprints associated with two distinct agroecosystems in the North China Plain: wheat and maize irrigation systems as well as maize rainfed systems in the Northeast Plain. Arjen Y. Hoekstra [20] introduced the water footprint indicator in 2002. The calculation of the water footprint is mainly divided into the bottom-up approach and the top-down approach. The top-down approach takes the perspective of product production and equals the WF of the region plus the virtual net water inflow (outflow). The bottom-up approach calculates WF from a consumption perspective, including the demand for precipitation in agricultural production, the demand for surface and groundwater resources, and the demand for water resources to adsorb pollutants. Since the top-down approach relies on trade data, it is more suitable for WF studies at the provincial or national level. In contrast, the bottom-up approach is well suited for WF accounting on a regional scale [21]. Sturla et al. [22] assessed the regional economic pressure on global water resources based on bottom-up water footprint accounting combined with input-output modeling. Taking Lanzhou city as the study area, Li et al. [23] established an evaluation index system and comprehensively evaluated the status of water resources utilization while using the water footprint method and the Tapio decoupling model to measure the decoupling status of water resources utilization and economic development from 2002 to 2021.

As research on single footprint indicators has gradually progressed, it has been argued that there are limitations to relying on a single indicator to summarize the pressures on the environment caused by human activities [3]. In response, Galli et al. [24] introduced the “Footprint Family”, conceptualizing it as “a suite of indicators grounded in a consumption-based approach, designed to monitor the human impact on the environment”. The development of the Footprint Family aimed to deliver a more holistic representation of the environmental pressures associated with human endeavors. Nawab et al. [25] evaluated the energy–water relationship between trading regions and Shanghai in domestic and international trade, concluding that “Shanghai is a net importer of energy and water flow”. Liu et al. [26] quantified water and energy footprints and evaluated the water–energy relationship between the Beijing–Tianjin–Hebei region, providing suggestions for water and energy conservation to achieve regional sustainable development. Zhang et al. [27] introduces an innovative water–energy (WE) nexus assessment framework which was designed to delineate and analyze the interconnections among various economic sectors. Through an examination of the carbon footprints of Asian emerging economies under two distinct scenarios—one involving the use of renewable energy and the other non-renewable energy—Saqib [28] highlighted the imperative for these economies to prioritize the adoption of renewable energy sources and to enhance energy efficiency as strategies for mitigating their carbon footprints. Nathaniel, S. P. [29] explored the impact of energy use, urbanization, trade, and economic growth on the environment through ecological footprint indicators, and found that urbanization, economic growth, and energy consumption exacerbate environmental degradation over the long term, while trade also worsens the environment. Steen-Olsen et al. [30] calculated the water, carbon, and ecological footprints of the 27 member countries of the European Union using input-output analysis to gain a more comprehensive understanding of the environmental pressure caused by EU consumption activities on the planet. Ridoutt et al. [31] evaluated greenhouse gas emissions, water use impacts, and other related environmental burdens of the beef production system in southern Australia. Čuček et al. [32] developed a multi-objective dimensionality reduction method that can calculate a comprehensive index from water, carbon, and ecological footprint indicators, which has been applied in the biomass energy supply chain. The North China Plain (NCP) is the second largest plain in China, with abundant arable land resources, making it an important grain-producing region in our country [33]. However, the per capita available water resources in the North China region (910 m³/yr) are much lower than those in the South China region (3180 m³/yr) and also lower than the recommended global water resource pressure baseline (1700 m³/yr), making it a severely water-scarce region [34]. In recent years, due to the increasing population density and rapid urbanization process in the NCP, carbon emissions have increased, groundwater levels have significantly declined, water pollution has become severe, and the ecological environment has been seriously damaged. Therefore, in order to ensure national food security and achieve the social goal of carbon peaking, it is crucial to develop reasonable water-saving measures for the NCP. It is necessary to conduct research on the changes in water–carbon–ecological footprints and their coupling relationships in this region, assess the region’s resource and environmental pressures, address climate change and water scarcity issues in the North China region, formulate rational regional development strategies, and achieve sustainable and coordinated development of the ecological environment in the NCP.

In fact, the methodologies for accounting footprint indicators have undergone considerable advancement. Nevertheless, a review of the existing literature reveals that, as constituent components of the ecological footprint, the water footprint and carbon footprint are frequently investigated within the frameworks of water–ecological footprint coupling or carbon–ecological footprint coupling, among other similar binary indicator couplings. To date, there has been limited exploration into the tripartite coupling of water, carbon, and ecological footprints, with further research in this area yet to be extensively conducted. Concurrently, the majority of research endeavors have been undertaken at either the national or provincial levels in a generalized fashion, with a notable absence of studies that specifically target the primary food-producing regions. Therefore, in this study, we use a bottom-up approach to calculate the water footprint of the NCP, the IPCC coefficient method to calculate the carbon footprint, and the national hectare method to calculate the ecological footprint. Finally, we analyze the trends in water footprint, carbon footprint, and ecological footprint of the NCP from 2003 to 2020. Based on this, we use a coupled coordination model to reveal the coupling relationship between water, carbon, and ecological footprints in the NCP, aiming to establish a robust scientific basis for the judicious allocation of regional resources and to foster sustainable development within the resource–environmental sector. Additionally, this project endeavors to furnish actionable recommendations designed to enhance the sustainable use of land in the North China Plain (NCP).

2. Materials

2.1. Study Area

The NCP lies in eastern China, bordered by the Yanshan Mountains to the north, the Dabie Mountains to the south, and the Bohai Sea and Yellow River to the east. It is the second-largest plain in China with a flat terrain and low elevation. It has a warm temperate monsoon climate, distinct seasons, and concurrent rain and heat, which makes it an important grain-producing area in China. Meanwhile, it is rich in mineral resource endowments, making it also a crucial industrial area. However, due to excessive exploitation and pollution of water resources in the economic development process, the NCP is a severely water-scarce area accounting for only 3.72% of the total national water resources. Therefore, five provinces of the NCP (including Anhui, Hebei, Henan, Jiangsu, and Shandong) were selected as study areas for assessing the water, carbon, and ecological footprints. The geographical location of the study area is shown in Figure 1.

2.2. Data Sources

The data used in this study included three parts. In the part for the water footprint, industrial water requirement, residential water consumption, and ecology water requirement were provided by the China Statistical Yearbook on Environment. Production of agricultural and animal products was provided by the China Rural Statistical Yearbook and the China Agriculture Statistical Report. Virtual water volume per unit yield of crop and animal products was based on Hoekstra and Chapagain’s research [35]. The value of import and export trade and gross regional product was provided by the China Statistical Yearbook. In the part for the carbon footprint, energy consumption data were provided by the China Energy Statistical Yearbook. Land use data were provided by the China Rural Statistical Yearbook and the China Agriculture Statistical Report. The coefficient of carbon emission was provided by the Guidelines for the Preparation of Provincial Greenhouse Gas Inventories (trial). In the part for the ecological footprint, production of biological products was provided by the China Statistical Yearbook, the China Rural Statistical Yearbook, and the China Agriculture Statistical Report. The national average production of biological products was provided by the China Statistical Yearbook and the FAOSTAT database. The land equivalence factor was based on Liu and Li’s research [36].

3. Methodology

3.1. Calculation of Water Footprint

In this study, a bottom-up approach [20,37,38] is used to calculate the water footprint of the NCP with the following formula:

$$WF=IWF+EWF$$

(1)

$$IWF={WU}_A+{WU}_I+{WU}_D+{WU}_E-{VWE}_{dom}$$

(2)

$$EWF=VWI-{VW}_{i-e}$$

(3)

where $IWF$ represents the internal water footprint, which refers to the total water resources needed for the products and services consumed by the local population within the region; $EWF$ represents the external water footprint, which is the total amount of virtual water imported from external regions. ${WU}_A,{ WU}_I, { WU}_D, {\mathrm{a}\mathrm{n}\mathrm{d} WU}_E$, represent the water demand for regional agricultural production (including crop water demand and animal water demand), industrial production water demand, residential water consumption, and ecological water demand, respectively. ${VWE}_{dom}$ represents the virtual water exported from this region. $VWI$ represents the virtual water imported from outside the region, and ${VW}_{i-e}$ represents the virtual water of imported products exported to other countries or regions.

Our study cites the research results of Hoekstra and Chapagain [35] using the virtual water footprint of agricultural and animal products calculated by them to calculate the water requirements for regional agricultural production. The formula for calculating the virtual water footprint exported from the local area to other regions is as follows:

$${VWE}_{dom}={\displaystyle \frac{ET}{TP}}\times TPWC$$

(4)

where $ET$ stands for export trade value, $TP$ stands for gross product, and $TPWC$ stands for total water consumption for production.

The external water footprint is calculated using an indirect method with reference to the treatment of exported virtual water. The formula is as follows:

$$EWF=VWI={\displaystyle \frac{IT}{TP}}\times TPWC$$

(5)

where $IT$ represents the value of import trade.

3.2. Calculation of Carbon Footprint

In this study, the IPCC method [39,40] is used to measure the carbon footprint of the NCP, and the specific calculation formula is as follows [41,42]:

$$F=F_h+F_t$$

(6)

$$F_h=\sum E_i\times V_i\times H_i\times B_i\times {10}^{-3}\times {\displaystyle \frac{44}{12}}$$

(7)

$$F_t=G\times M+T\times N+\left(S\times O+P\times Q\right)+K\times R+A\times U$$

(8)

where $F$ represents the total carbon footprint of the region, $F_h$ represents the carbon footprint generated by fossil energy consumption, and $F_t$ represents the carbon footprint generated during land use. $E_i$ is the consumption amount of the $i$-th type of energy (t), $V_i$ is the average lower heating value of the $i$-th type of energy (TJ/Gg, 1 Gg = 10³ t), $H_i$ is the default carbon content of the $i$-th type of energy (kg/GJ), and $B_i$ is the default oxidation rate of the $i$-th type of energy. $G, T, S, P, K, \mathrm{a}\mathrm{n}\mathrm{d} A$ represent the amounts of fertilizer use, pesticide use, crop planting area, agricultural machinery power use, irrigation area, and agricultural film used in the agricultural cultivation process. $M, N, O, Q, R, \mathrm{a}\mathrm{n}\mathrm{d} U$ are the corresponding conversion coefficients. Among them, $M \mathrm{a}\mathrm{n}\mathrm{d} N$ are referenced from the Oak Ridge National Laboratory, with values of 0.8956 and 4.9341 kg/kg, respectively. $O, Q, R,\mathrm{a}\mathrm{n}\mathrm{d} U$ are referenced from the Institute of Resource, Ecosystem and Environment of Agriculture (IREEA) at Nanjing Agricultural University with values of 16.47 kg/hm², 0.18 kg/kW, 266.48 kg/hm², and 5.18 kg/hm², respectively.

The carbon emission factors for various energy sources are constructed based on the General Principles for Calculating Comprehensive Energy Consumption and the Guidelines for the Preparation of Provincial Greenhouse Gas Inventories (trial) as shown in

Table 1. Carbon emission factors for fossil energy.

Name of Energy Source	Average Low-Level Calorific Value (TJ/Gg)	Carbon Content Per Unit Calorific Value (tC/TJ)	Carbon Oxidation Rate (%)
Coke	28.470	29.42	93
Crude Oil	41.868	20.08	98
Petrol	43.124	18.90	98
Gasoline	43.124	19.60	98
Diesel Oil	42.705	20.20	98
Bunker Fuel	41.868	21.10	98
Liquefied Petroleum Gas	50.242	17.20	98
Petroleum	38.979	15.32	99

.

3.3. Calculation of the Ecological Footprint

This study uses the national hectare method to calculate the ecological footprint of the NCP. The specific calculation formula is as follows [43,44]:

$$EF=\sum _{i=1}^4[r_i\times \sum _j({\displaystyle \frac{c_j}{{ep}_j}})]$$

(9)

where $EF$ represents the ecological footprint of the region, $j$ represents the type of accounting project. Since this study has already calculated the carbon footprint of energy consumption, in order to avoid repetition, the ecological footprint calculation process selects agricultural products, livestock products, aquatic products, and forest products for accounting. The term $r_i$ represents the equilibrium factor of the $i$-th type of land, including arable land, grassland, water area, and forest land. The term $j$ represents the type of accounting project, including agricultural products, livestock products, aquatic products, and forest products. Based on the availability of data from statistical yearbooks, biological productive land types and corresponding account product types (as shown in

Table 2. Types of product accounting and biologically productive land divisions in the NCP.

Biologically Productive Land Types	Account Product Type
Arable land	Agricultural production	Grain, cotton, oilseeds, vegetables, tobacco, hemp, pork, poultry and eggs
Grassland	Livestock products	Beef, lamb, dairy
Woodland	Forest products	Fruits, tea, oilseeds
Watershed	Fishery products	Fishery products

) are identified. The term $c_j$ represents the total production of the $j$-th type of biological resource; the term ep_j represents the national average yield of the $j$-th type of accounting project. Referring to the calculation results of Liu [36], the equilibrium factors for arable land, grassland, water area, and forest land are 1.74, 0.44, 0.35, and 1.41, respectively.

3.4. Coupling Coordination Analysis of Water–Carbon–Ecological Footprint

In order to eliminate the influence of metric units and positive and negative effects, the calculated water, carbon, and ecological footprint data of the NCP were standardized using the method of standardization of extreme deviation, and the calculation formulas are shown below [45,46,47].

$$x=\left\{\begin{array}{c}{\displaystyle \frac{x_i-x_{min}}{x_{max}-x_{min}}}, Positive indicators\\ {\displaystyle \frac{x_{max}-x_i}{x_{max}-x_{min}}},Negative indicators\end{array}\right.$$

(10)

where $x$ is the normalized value, $x_{max}$ is the maximum value of the sample data, $x_{min}$ is the minimum value of the sample data and $x_i$ is the untreated value.

The coupled water–carbon–ecological footprint model is as follows:

$$C=\sqrt[3]{{\displaystyle \frac{W\times E\times F}{{\left(\frac{W+E+F}{3}\right)}^3}}}$$

(11)

$$T=\alpha \times W+\beta \times E+\gamma \times F$$

(12)

$$D=\sqrt{C\times T}$$

(13)

where $W$, $E$, and $F$ represent the value of the water footprint, the carbon footprint, and the ecological footprint after standardized treatment using the extreme difference method; $C$, $T$, and $D$ are the degree of coupling of the water–carbon–ecological footprint, the comprehensive coordination index, and the degree of coupling coordination, respectively. The terms α, β, and γ are the weight coefficients of the water footprint, the carbon footprint, and the ecological footprint, respectively. In this study, we take α = β = γ = 1/3 and determine the division criteria of the degree of coupling and the degree of coupling coordination, which are shown in

Table 3. Criteria for classifying the degree of coupling coordination.

Interval of Coupling C Values	Degree of Coupling	Interval of D-Values for Coupling Coordination	Degree of Coupling Coordination
(0.0~0.3)	Low-level coupling	(0.0~0.1)	Extreme disorder
		[0.1~0.2)	Severe disorder
		[0.2~0.3)	Moderate disorder
[0.3~0.5)	Antagonistic period	[0.3~0.4)	Mild disorder
		[0.4~0.5)	On the verge of a disorder
[0.5~0.8)	Break-in period	[0.5~0.6)	Sue for coordination
		[0.6~0.7)	Primary coordination
		[0.7~0.8)	Mid-level coordination
[0.8~1.0)	High-level coupling	[0.8~0.9)	Good coordination
		[0.9~1.0)	High-quality coordination

.

4. Results and Discussion

4.1. Characteristics of Changes in Total Water, Carbon and Ecological Footprint in the NCP

The water footprint of the NCP from 2003 to 2020 is shown in Figure 2. It can be seen that the water footprint of the NCP shows a general trend of increasing and then decreasing, and then the growth rate gradually decreases and finally tends to stabilize. Among them, Shandong and Henan have the largest water footprint and the most obvious increase, especially in Henan, with the most significant increase in 2003–2006 from 1049.2 × 10⁸ m³ in 2003 to 1389.43 × 10⁸ m³ in 2006. This is because Shandong and Henan are the major grain-producing provinces in China, with high water demand for agricultural production. Agricultural water use accounts for a large proportion of total water use, so their water use is much higher than that of the other provinces, which also means that there is great potential for agricultural water saving. The total water footprint of all the provinces initially showed an increasing trend, and the growth rate is large, but between 2005 and 2008 the water footprint of different provinces showed a period of a decreasing trend. This is related to the construction of a water-saving society emphasized by Secretary Hu Jintao in 2004. After that, the water footprint of the provinces continues to increase, but the growth rate decreases year by year. After 2015, except for Anhui, the water footprint of each province shows a downward trend, which indicates that the national use of water resources has been more and more widely paid attention to by all sectors of society, and the efficiency of water resource use is gradually improving.

The carbon footprint changes in the NCP from 2003 to 2020 are shown in Figure 3. It can be seen that the total carbon footprint of each province in the NCP shows an overall upward trend. This means that with the development of economy and society, the energy consumption and other behaviors caused by human activities have produced a large amount of carbon emissions, which has caused great pressure on the ecological environment. Among them, Shandong has the largest total carbon footprint and the most obvious increase, which is due to the fact that Shandong is a major manufacturing province in China with a well-developed industrial base. The industrial production process consumes a large amount of energy, resulting in a large amount of carbon emissions. Hebei has a large increase in its total carbon footprint from 2003 to 2012, from 11,700.8 ×10⁴ t in 2003 to 33,085.5 × 10⁴ t, and then the carbon footprint showed a decreasing trend year by year until 2015 when the total carbon footprint began to increase slowly year by year. Anhui’s total carbon footprint is relatively small and the magnitude of change is small. In addition, it can be learned from the figure that since 2012, the total carbon footprint of the provinces in the NCP has shown a decreasing growth rate, and the total carbon footprint of Hebei and Henan have even decreased. This may be related to the “Twelfth Five-Year Plan” triggered by the State Council in 2011 for the first time to control greenhouse gas emissions. Therefore, the state should vigorously launch energy-saving and emission reduction policies and promote clean energy in order to reduce the pressure on carbon emissions.

The changes in the ecological footprint of the NCP from 2003 to 2020 are shown in Figure 4. Clearly, the ecological footprint of the NCP shows an increasing trend in general. Among them, Shandong had the largest ecological footprint from 2003 to 2006, but the growth rate of ecological footprint was slow. The total ecological footprint showed a decreasing trend after 2005 until after 2009, when the total ecological footprint of Shandong began to stabilize and show a decreasing trend. Hebei and Henan had a faster growth rate of the total ecological footprint from 2003 to 2006, and Henan in 2006. In 2006, Henan surpassed Shandong to become the region with the largest ecological footprint in the NCP, reaching 57.6749 million hm². Then the ecological footprint of Henan continued to increase until 2015, when the ecological footprint reached its peak of 61.833 million hm², and then the size of the ecological footprint declined year by year at a faster rate. The ecological footprint of Hebei has shown a slow downward trend since 2006 until 2015, when the ecological footprint declined substantially and then gradually tended to decrease. Hebei showed a slow downward trend from 2006 until 2015, when the ecological footprint declined significantly and then gradually leveled off. Anhui and Jiangsu had smaller and more stable ecological footprints.

4.2. Characterization of Changes in the Composition of the Water, Carbon, and Ecological Footprint

The components of the water footprint of the NCP are shown in Figure 5, and its analysis shows that the water demand for agricultural production in the NCP from 2003 to 2020 accounts for the largest proportion, while the water demand for the ecological environment accounts for the smallest proportion in the composition of the entire water footprint. The water consumption for industrial production shows a trend of increasing, then decreasing, and then increasing again, with an increasing trend from 2003 to 2007, an increasing trend from 2009 to 2020, and a decreasing trend from 2007 to 2009. This may be due to the implementation of the Eleventh Five-Year Plan in 2007 and the construction of a water-saving society in the NCP. The steady rise in residential water consumption means that the standard of living of the population is constantly improving, and the fluctuating rise in ecological water consumption from 2003 to 2015, with a greater increase in the growth rate from 2015 to 2020, indicates that people’s awareness of environmental protection is increasing year by year.

As shown in Figure 6, it can be seen that crude oil accounts for the largest share of carbon emissions in the NCP, while natural gas accounts for the smallest share in the composition of the overall carbon footprint. This shows that the energy consumption in the NCP is dominated by crude oil. As time goes by, the proportion of natural gas gradually increases, which indicates that people’s consumption structure of energy is gradually changing. They are more inclined to use of cleaner energy, which is conducive to China’s future goal of achieving a carbon-peak and carbon-neutral society.

Analyzing Figure 7, it can be seen that the ecological footprint of arable land in the NCP accounts for the largest proportion, while water accounts for the smallest proportion in the composition of the overall ecological footprint. This indicates that arable land is the main component of land resources in the NCP. Therefore, the red line of arable land should be strictly adhered to, and the construction of high-standard farmland should be promoted to improve the quality of arable land in the NCP. Overall, there is little change in the magnitude of the proportion of each type of ecological footprint, which indicates that there is no significant change in the various types of biologically productive land from 2003 to 2020 and that the land structure of the NCP is relatively stable.

4.3. Analysis of the Coupling Coordination Degree of Water–Carbon–Ecological Footprint

According to the model above, the coupling degree, coordination index, and coupling coordination results of the water–carbon–ecological footprint in the NCP from 2003 to 2020 are shown in

Table 4. Comparison of the coupling degree and coupling coordination of water–carbon–ecological footprint in the North China Plain.

Year	Interval of Coupling C Values	Degree of Coupling	Interval of D-Values for Coupling Coordination	Degree of Coupling	Degree of Coupling Coordination
2003	0.336	0.670	0.475	Antagonistic period	On the verge of a disorder
2004	0.950	0.674	0.800	High-level coupling	Good coordination
2005	0.996	0.735	0.856	High-level coupling	Good coordination
2006	0.982	0.790	0.881	High-level coupling	Good coordination
2007	1.000	0.699	0.836	High-level coupling	Good coordination
2008	0.983	0.713	0.837	High-level coupling	Good coordination
2009	0.955	0.647	0.786	High-level coupling	Mid-level coordination
2010	0.936	0.585	0.740	High-level coupling	Mid-level coordination
2011	0.894	0.507	0.673	High-level coupling	Primary coordination
2012	0.821	0.504	0.643	High-level coupling	Primary coordination
2013	0.741	0.429	0.564	Break-in period	Sue for coordination
2014	0.621	0.437	0.521	Break-in period	Sue for coordination
2015	0.512	0.376	0.439	Break-in period	On the verge of a disorder
2016	0.793	0.155	0.351	Break-in period	Mild disorder
2017	0.650	0.120	0.279	Break-in period	Moderate disorder
2018	0.632	0.109	0.262	Break-in period	Moderate disorder
2019	0.433	0.023	0.101	Antagonistic period	Severe disorder
2020	0.159	0.027	0.065	Low-level coupling	Extreme disorder

. It can be seen that the water-–carbon–ecological footprint coupling degree in the NCP has consistently maintained a high level of coupling from 2004 to 2012, indicating a significant interaction between water footprint, carbon footprint, and ecological footprint within the region during this period. However, since 2012, the coupling degree of water–carbon–ecological footprint in the NCP has been continuously decreasing, with a slight rebound in 2016 and followed by a continuous decline, but still remained above the break-in period. Until 2019, the coupling degree of water–carbon–ecological footprint in the NCP significantly decreased to a low level of coupling, indicating that the interaction between water, carbon, and ecological footprints within the region is continuously weakening, which may be related to the decrease in social production capacity and increase in consumption capacity caused by the outbreak of the COVID-19 pandemic in 2019.

The coupling model can only explain the interaction relationship of the water–carbon–ecological footprint in the NCP, and it is also necessary to analyze the degree of coordination of their interactions through coupling coordination. Overall, the coupling coordination of the NCP shows a trend of initially increasing, then stabilizing, and then continuously decreasing. From 2003 to 2006, the coupling coordination of the water–carbon–ecological footprint in the NCP continued to rise, and the degree of coupling coordination improved from being on the verge of imbalance to a good level of coordination. From 2006 to 2014, the coupling coordination of the NCP began to gradually decline, but it remained in a coordinated state. Nevertheless, since 2015, its coupling coordination rapidly decreased, with the degree of coupling coordination reaching an extremely imbalanced state. This indicates that since 2015, with the rapid economic and social development in the NCP, the imbalance of the water–carbon–ecological footprint system has become increasingly severe, and it is urgent to introduce energy conservation, emission reduction, water conservation, and environmental protection policies to achieve sustainable and coordinated development of the ecological environment in the NCP. It also reflects that the epidemic not only poses a serious threat to society, but also to the environment.

The coupling degree, coordination degree, and coupling-coordination degree of the water–carbon–ecological footprint of various provinces in the NCP at different periods are calculated by using the above formula, as shown in Figure 8. From a spatial perspective, the provinces with higher average coupling degrees in the NCP from 2003 to 2020 are Jiangsu, Shandong, and Hebei, with values of 0.851, 0.784, and 0.728, respectively. Jiangsu is in a high-level coupling stage, while Shandong and Hebei are in a stage of adjustment. The average coupling degrees of Anhui and Henan from 2003 to 2020 are 0.706 and 0.675, respectively. The provinces with higher average coupling-coordination degrees in the NCP from 2003 to 2020 are Shandong, Jiangsu, and Anhui. Shandong and Jiangsu are at a primary coordination level, while Anhui is at a barely coordinated level. The differences in coupling-coordination degrees among the other provinces are not significant, and they are all at a barely coordinated level.

From the perspective of the time scale, the coupling degree, the coordination degree, and the coupling-coordination degree of the five provinces in the NCP all show a trend of “initial increase, then decrease”. This indicates that in the early 21st century, the NCP effectively improved the efficiency of water and carbon resource utilization in the production process, and the water-saving and carbon-reducing policies proposed at that time received good responses. However, after 2010, all three indicators show a decreasing trend. This finding aligns with the inference drawn from the metric coupling calculations conducted by Li et al. [48]. While the water footprint and the carbon footprint continue to grow, the ecological footprint is slowly decreasing. This indicates that resource waste in the production process is gradually becoming more serious, which contradicts the goal of developing a sustainable society in China. Clearly, this may also be related to the adjustment of China’s industrial structure. Therefore, how to improve the efficiency of water, carbon, and biological resource utilization, and reduce resource waste within the scope of reasonable adjustment of the industrial structure has become an urgent issue to consider in the current development process.

4.4. Policy Implementation

Building upon the insights provided by the analysis above, the following strategic recommendations are proposed for the NCP to foster an efficient distribution of regional resources and to promote the sustainable development of the ecosystem.

(1)

It is imperative to enhance the agricultural water management capacity in the NCP. The water footprint of the NCP is generally on an increasing trend, with agriculture accounting for the largest share of water demand, which is already more than 50% of the total water demand. Thus, water conservation measures need to be taken during agricultural production, such as encouraging the use of highly efficient irrigation methods such as drip systems and micro-irrigation, or the use of groundwater for sustainable irrigation [49]. Specific attention should be directed towards implementing water-saving measures in Henan and Shandong, where high levels of water consumption for agricultural purposes are particularly pronounced.

(2)

The adoption of clean energy sources to mitigate carbon emissions within the North China Plain represents a critical strategy for environmental conservation. Our study has documented a persistent rise in the carbon footprint of the region, which has escalated from 4.2 × 10⁸ t to 1.69 × 10⁹ t. Notably, coke and crude oil have been major contributors to carbon emissions, accounting for proportions ranging between 32.99% and 43.34% and 31.55% and 40.29%, respectively. By referencing the carbon content per unit of calorific value for each fossil energy source as presented in Table 1, it becomes apparent that LPG (liquefied petroleum gas) and petroleum emit significantly less carbon—17.2 tC/TJ and 15.32 tC/TJ, respectively—than coke (29.42 tC/TJ) and crude oil (20.08 tC/TJ) when generating equivalent calorific value. Consequently, we advocate for the aggressive promotion of clean energy alternatives, such as natural gas, as part of a broader initiative to drive industrial restructuring and foster green production methodologies. These measures are essential for achieving society’s ambitious goals of carbon peaking and carbon neutrality.

(3)

Enhancing land utilization efficiency within the North China Plain region is a paramount objective. Our study has identified that the ecological footprint in Henan Province and Shandong Province is comparatively substantial. Notably, the ecological footprint attributed to arable land constitutes the predominant share, underscoring the critical role of arable land as a vital component of the region’s land resources. In light of these findings, there is a compelling need to vigorously advance the construction of high-standard farmland. This initiative aims to elevate the quality of arable land in the North China Plain and to integrate the deployment of sophisticated agricultural technologies. Concurrently, it is observed that the ecological footprints of forests and watersheds contribute only a minor fraction to the overall ecological footprint. This necessitates a strategic approach to the more efficient utilization of land resources in the North China Plain, thereby ensuring the sustainable and harmonized development of natural resources within the region.

Moreover, this research reveals a consecutive annual decline in the water–carbon–ecological footprint coupling coordination degree in the NCP since 2015. Therefore, all sectors of society have a responsibility to consider the impact of the current economic development trajectory on the land resources and environment of the NCP more and more. The initiation and implementation of diverse arrays of energy-saving, emission-reduction, water conservation, and policies related to land conservation and environmental protection are indispensable to prevent more severe degradation occurring in the ecological environment of the NCP.

4.5. Limitations and Future Work

Due to the overlap between the traditional ecological footprint calculation and the carbon footprint calculation, this paper removes fossil energy from the calculation of the ecological footprint, which may have a certain bias on the ecological footprint calculation results. Some of the data are not published officially, which makes it difficult to obtain. This may cause some inaccuracy in the results of water, carbon, and ecological footprint calculations compared with the actual situation. Furthermore, the sustainability of the outcomes presented in this paper under different future scenarios is a matter that warrants investigation and debate in subsequent scholarly inquiries.

5. Conclusions

This study adopts the bottom-up approach to calculate the water footprint of the NCP, the internationally recognized IPCC method to calculate the carbon footprint of the NCP, and the national hectare method to calculate the ecological footprint of the NCP. Based on the calculated water, carbon, and ecological footprint of the NCP from 2003 to 2020, the coupled coordination model is used to reveal the coupled relationship between the water, carbon and ecological footprints of the NCP. The conclusions are as follows:

(1)

The overall trend of the water footprint in the NCP shows an initial increase followed by a decrease, with the growth rate gradually slowing down, and finally tending to stabilize. In 2020, it reached 6.52 × 10¹¹ m³. Shandong and Henan have the largest water footprints, but Henan has the most significant increase, growing by 52.8% compared to 2003. Agricultural water demand (78.6~83.6%) accounts for the largest proportion of water footprint, while the ecological water demand has the smallest proportion in the entire water footprint composition. This indicates that various water uses in the NCP are mainly for agricultural water use, and there is great potential for agricultural water conservation.

(2)

The carbon footprint of the provinces in the NCP shows an overall upward trend, implying that with the rapid economic development, the pressure of carbon emission increases year by year, which has a great impact on the ecological environment. Among them, Shandong has the largest total carbon footprint, with the most significant increase. The emissions in 2020 (7.30 × 10⁸ t) have reached 5.83 times the emissions in 2003 (1.25 × 10⁸ t). The carbon footprints of coke (32.99~43.34%) and crude oil (31.55~40.29%) account for the largest proportion, and energy consumption in the NCP is dominated by coke and crude oil. With the passage of time, the proportion of natural gas is gradually increasing, and people are more and more inclined to use clean energy.

(3)

The total ecological footprint of the NCP is 1.95 × 10⁸~2.24 × 10⁸ hm², which shows an “M”-shaped trend. The ecological footprint of arable land accounts for the largest proportion (61.5~70.1%), while water accounts for the smallest proportion (0.3~0.4%) in the composition of the whole ecological footprint, which indicates that arable land is the most important component of land resources in the NCP. Overall, the magnitude of the ecological footprint of various categories has not changed much, and the land structure of the NCP is relatively stable.

(4)

The coupling degree of water–carbon–ecological footprints in the NCP is high, and the interaction among water, carbon and ecological footprints is more significant. But, the coupling degree in the NCP has begun to decline continuously since 2015. Overall, the coupling coordination degree of the NCP shows a trend of increasing first, then steady, and then a continuous decline. Among the provinces in the NCP, Jiangsu has the highest mean values of coupling degree (0.851) and degree of coupling coordination (0.603) from 2003 to 2020.