The Ecological Footprint and Allocation of Guangxi Beibu Gulf Urban Agglomeration

Abstract

To understand the allocation efficiency and fairness of natural capital in the Guangxi Beibu Gulf urban agglomeration, its ecological footprint from 2007 to 2020 was calculated based on the emergy ecological footprint (EEF) model, and the 10,000 Yuan GDP and Gini coefficient were introduced. The results show that (1) in the past 14 years, the per capita ecological footprint of the urban agglomeration slowly increased, the ecological pressure index rapidly increased with an average annual growth rate of 6.55%, and the regional ecological safety showed an unsafe trend. (2) The regional ecological footprint was mainly based on cultivated land, construction land and fossil energy land, of which the latter two significantly increased. For construction land, the average annual per capita growth rate in the central city of Nanning and the coastal cities (Fangchenggang, Beihai and Qinzhou) exceeded 10%, ranging from 11.39%–25.70%. For fossil energy land, the annual average per capita growth rate in Fangchenggang and Chongzuo exceeded 10%, at 19.64% and 11.40%, respectively. During urbanization, increasing population density leads to increased regional consumption of electricity and energy, thus affecting the regional ecological security. (3) The resource utilization efficiency improved annually, and the resource allocation was generally fair. Nanning and Beihai had high economic contributions and low ecological carrying capacities, Qinzhou and Chongzuo had low economic contributions and high ecological carrying capacities, and Yulin and Fangchenggang had low economic contributions and low ecological carrying capacities. These results clarify the differences among cities in the development of the Guangxi Beibu Gulf urban agglomeration, improve the efficiency of natural resource allocation, and provide a reference for the achievement of regional sustainable development.

1. Introduction

With the rapid development of the economy and the increase in the urban population, natural resource consumption has accelerated, resulting in the demand for resources exceeding the ecological carrying capacity of the earth; this imbalance is the main cause of global warming, water pollution, and land desertification [1]. According to the 2019 annual report of the Global Footprint Network, due to unsustainable production and consumption, 1.75 earths are required to maintain the world’s current living and development level, and more than 80% of the world’s population lives in countries with ecological deficits. The sustainable development of the regional ecology and economy based on the rational utilization of ecological resources has become a future development trend [2].

Urban areas have high concentrations of industrial and economic activities, they also have extremely important and sensitive environmental resources and corresponding environmental problems. The sustainable development of a region depends not only on the efforts of individual cities but also on the mutual cooperation among cities in the region [3,4]. In particular, the negative externalities caused by the unfair allocation of resources will lead to the continued transfer of pollution between regions, consequently affecting regional sustainable development. Yang et al. [5] established a fairness evaluation framework for natural resource consumption in urban agglomerations, reflecting the fairness of natural resource consumption with the ecological service value coefficient; their results show that unfair consumption of natural resources leads to a decline in ecosystem service capacity. Latera P et al. [6] have indicated that the unfairness of ecological occupation leads to the vulnerability of the ecological environment system. Therefore, the issue of fairness and allocation efficiency between economic maximization and consumed resources can be discussed through the Gini coefficient of resources and the environment [5,6,7,8].

Resource distribution fairness and allocation efficiency are core socioeconomic concepts [9,10]. With the acceleration of urbanization, the consumption of natural resources and the occupation of ecological environments also increase, and the fairness and efficiency of the allocation between ecological capital (i.e., natural resources and ecological environments) and human-made capital has gained scientific attention [11,12,13]. Generally, the return of ecological capital is represented by the ecological footprint, eco-productive land area calculated by the net primary productivity (NPP) [14], emergy ecological footprint (EEF) [15,16], carbon footprint (CF) [17] or pollutant emissions (production) in the process of resource consumption [15,18], while the return of human-made capital is mainly reflected by the gross domestic product (GDP), city development index or ecological capacity [14,19].

China is undertaking a national strategy of new urbanization and ecological civilization construction. Urban agglomeration is the main form of urbanization and is an important platform to drive sustained economic growth, promote the coordinated development of regions, and participate in international cooperation and competition. China has successively approved 11 national-level urban agglomerations, including urban agglomerations in the middle reaches of the Yangtze River, Yangtze River Delta, Beibu Gulf, and Guangdong–Hong Kong–Macao Greater Bay Area [20], and there are still eight urban agglomerations to be approved [21]. The construction of urban agglomerations has effectively promoted the development of the regional economy, but the synergistic problem between ecological capital and human-made capital has become increasingly apparent. In building an urbanization pattern, we must take into account the fairness and efficiency of resource consumption and economic maximization and consciously integrate economic and social development with ecological progress.

Therefore, by using the ecological footprint model and its improvements, researchers have conducted studies on the spatiotemporal evolution and influencing factors of the ecological footprint of urban agglomerations, ecological security assessment, and the equity of the ecological footprint and economic development. In terms of fairness and the efficiency of resource allocation, the research has mainly focused on the provincial scale or more mature urban agglomerations [22]. Few studies have focused on new or economically weak urban agglomerations. However, new urban agglomerations have more abundant natural endowments, and their economic development relies more on natural capital, so it is particularly important to build a synergistic urban pattern between them. This study focused on the Beibu Gulf urban agglomeration in Guangxi, which is connected with the frontier of the Association of Southeast Asian Nations (ASEAN), as a case study. First, based on the emergy ecological footprint model, the ecological carrying capacity and ecological footprint of six cities in the region from 2007 to 2020 were calculated. Second, the evolution characteristics and distribution differences of the ecological capital in the Guangxi Beibu Gulf urban agglomeration were analyzed. And third, the evolution trend of fairness and efficiency between the regional ecological capital consumption and capital allocation was clarified. Our study provides a reference for the effective allocation of local resources and the coordinated and sustainable development of the economy, society and ecology.

2. Materials and Methods

2.1. Study Area

The Beibu Gulf urban agglomeration was officially established in 2017 and is located in the western coastal region of China. As a national-level urban agglomeration, it has geographical advantages, can tap regional characteristics, and can build a livable and business-friendly, blue bay urban agglomeration serving the ASEAN community and Southwest, Central South and South China. Among the national agglomerations, the Guangxi Beibu Gulf urban agglomeration (Nanning, Chongzuo, Qinzhou, Fangchenggang, Beihai and Yulin, Figure 1) is located in the center of the Beibu Gulf economic circle, and its unique location consists of both land and sea. It is an important region for the economic development of Guangxi, the most convenient passage to the sea in Southwest China, and an important bridge for communication between China and the ASEAN community. At present, the overall economic foundation of the Guangxi Beibu Gulf urban agglomeration is still relatively weak [23,24,25]. However, the urban agglomeration is rich in resources, with dozens of national nature reserves, such as the Shiwan Mountain, Beilun Estuary, mangroves, and coral reefs. In 2020, the forest cover of the urban agglomeration was as high as 54.4%, the sea water quality was high in 95.5% of the nearshore area, and the proportion of days with good ambient air quality was as high as 98.7%. The main focus of the area’s development was the protection of natural ecology while it underwent economic development and to seek a path toward the coordinated development of both regional resources and the economy [26].

2.2. Data Sources

The data were obtained from the Nanning, Chongzuo, Qinzhou, Fangchenggang, Beihai, Yulin and Guangxi Statistical Yearbooks from 2008 to 2021. The output of grain, sugarcane, oil, vegetables, fruits, wood, meat, eggs, milk, aquacultural products, the total amount of energy consumption above the scale, and the electricity consumption of the entire population were selected to calculate the ecological footprint. First, since there are no statistical data on the total energy consumption of the entire population broken down by a specific type of energy in the almanac of each city, the energy consumption of the industrial enterprises at the city scale is used as the indicator of the electricity consumption of the entire population. Second, because cities do not have the basic conditions and supervision mechanisms required to calculate detailed statistics, the completeness and continuity of the data are seriously insufficient, and trade adjustment cannot be calculated. Therefore, the output of crops, forest products, livestock products and aquacultural products were used to replace consumption in the calculation of the ecological footprint of biological resources [27].

2.3. Methods

2.3.1. Emergy Ecological Footprint Model

• 1.. Ecological carrying capacity. Zhao et al. [28,29] improved the ecological footprint model according to the emergy analysis theory of Odum [30], a famous American ecologist, and proposed the emergy ecological footprint model. Ecological carrying capacity refers to the bioproductive land area that the earth can provide for the development of human society by its resource regeneration capacity and environmental absorption and transformation capacities [2]. The regional ecological carrying capacity [31] mainly uses solar energy, wind energy, the chemical and potential energy of rainwater, the rotational energy of the earth and tidal energy. The first four different conversion forms belonging to the same energy type need to use only the maximum value. The sum of the above-mentioned maximum value, the rotational energy value of the earth and the tidal energy value is taken as the total energy value of the ecological carrying capacity. The calculation formula of the ecological carrying capacity is:

  (1)$\mathrm{EC}=\raisebox{1ex}{$\mathrm{E}$}\!\left/ \!\raisebox{-1ex}{$\mathrm{P}$}\right.$

  where EC is the ecological carrying capacity (hm²) of the study area; E represents the solar energy value of renewable resources (sej); and P represents the global average emergy density, 3.14 × 10¹⁴ sej/hm². The sunshine hours, average altitude and regional area of the six cities in the Guangxi Beibu Gulf urban agglomeration were obtained from the Guangxi Statistical Yearbook. To account for the biodiversity protection area, 12% of the modified ecological carrying capacity should be deducted from the calculation of the ecological carrying capacity [13].

• 2.. Ecological footprint. The emergy ecological footprint uses the emergy values of various consumption rates in production and daily life to calculate the consumption emergy values of all kinds of biologically productive lands to obtain the total emergy ecological footprint. The calculation formula is as follows:

  (2)$\mathrm{EF}={{\displaystyle \sum }}_{i=1}^n{A}_i={{\displaystyle \sum }}_{i=1}^n\left(C_i/P_i\right)$

  where EF is the emergy ecological footprint (hm²) of the study area; i indicates the resource type; A_i represents the emergy ecological footprint of the ith resource; C_i represents the emergy value of the ith resource; and P_i represents the average emergy density of Guangxi Beibu Gulf urban agglomeration from 2007 to 2020, which is 2.425 × 10¹⁵ sej/hm².

• 3.. Ecological tension index (ET). The ecological pressure index refers to the ratio of the ecological footprint to the ecological carrying capacity, reflecting the intensity of human interference in the regional ecosystem [32]. The calculation formula is as follows:

  (3)$\mathrm{ET}=\mathrm{EF}/\mathrm{EC}$

  where ET is the ecological stress index of the study area, EF is the ecological footprint, and EC is the ecological carrying capacity. The classification standard of the ET is shown in Table 1 [1,2].

2.3.2. Allocation Efficiency of Resource Utilization

The indicator of biological productive area consumed per 10,000 yuan (RMB), namely, the ecological footprint per 10,000 RMB of GDP (W), is used to reflect the allocation efficiency of regional resource utilization [33]. The calculation formula is:

(4)$\mathrm{W}=\mathrm{EF}/\mathrm{GDP}$

The smaller the value of W is, the higher the allocation efficiency of resource use in the region, and the larger W is, the lower the allocation efficiency of resource use.

2.3.3. Fairness of Resource Utilization Configuration

The Gini coefficient is a measure of the disparity in income distribution among the residents of a country or region. The coefficient is between [0, 1], and the smaller the value is, the more equitable the distribution; otherwise, the larger the gap between the rich and the poor [27]. The actual distribution between the emergy ecological footprint and the emergy ecological carrying capacity and between the emergy ecological footprint and the GDP were calculated, and the matching degree between ecological capital and ecological carrying capacity and economic growth in the Guangxi Beibu Gulf urban agglomeration was analyzed to determine the ecological carrying capacity and economic contribution Gini coefficients. Finally, the comprehensive Gini coefficient, ecological carrying capacity coefficient and economic contribution coefficient were used to evaluate resource fairness and allocation efficiency [34].

(5)$\mathrm{Gini}=1-{\displaystyle \sum }_{i=1}^n\left(X_i-X_{i-1}\right)\left(Y_i+Y_{i-1}\right)$

where X_i is the cumulative percentage of the fairness evaluation index (such as the ecological carrying capacity and GDP) of the ith city (district) and Y_i is the cumulative percentage of the emergy ecological footprint of the ith city (district). When i = 1, (X_i−1,Y_i−1) is regarded as (0,0). According to the Gini coefficient level in economics, the classification standard is determined [22]; that is, Gini ≤ 0.2 means highly balanced, 0.2 < Gini ≤0.3 means relatively balanced, 0.3 < Gini ≤0.4 means relatively reasonable balance, 0.4 < Gini ≤ 0.5 indicates a moderate imbalance, and Gini > 0.5 indicates a high imbalance. When considering the impact of ecological carrying capacity and economic contribution on ecological footprint equity, the calculation formula of the comprehensive Gini coefficient is as follows:

(6)$\mathrm{G}={{\displaystyle \sum }}_{\mathrm{k}=1}^{\mathrm{m}}\left(R_k\times {\mathrm{Gini}}_{\mathrm{k}}\right)$

where ${\mathrm{Gini}}_{\mathrm{k}}$ represents the K fairness evaluation index and the corresponding index weight coefficient. K = 1, 2 refers to the influence of ecological carrying capacity and economic contribution on the comprehensive Gini coefficient. The fairness of the ecological carrying capacity and the economic contribution to the ecological footprint is determined by the expert scoring method. R₁ and R₂ are 0.4 and 0.6, respectively [27].

The ecological support coefficient (ESC) is the ratio between the proportion of the ecological footprint and the proportion of the ecological carrying capacity of each city. The ESC refers to the ecological footprint of each city, which measures whether a certain proportion of ecological resources needs to contribute a corresponding proportion to the ecological carrying capacity, to describe the matching degree between the ecological footprint and the ecological carrying capacity [35].

(7)$\mathrm{ESC}=\frac{E{F}_i}{EF}/\frac{E{C}_i}{EC}$

where EF_i and EC_i represent the ecological footprint and ecological carrying capacity of each city, respectively, and EF and EC represent the total ecological footprint and ecological carrying capacity of the urban agglomeration, respectively. If ESC > 1, it indicates that the city has a low ecological carrying capacity and negative externality. In contrast, if ESC < 1, the city has a high ecological carrying capacity and positive externality [36].

The economic contribution coefficient (ECC) is a measure of the relationship between the resource occupancy and economic contribution among cities, which is equal to the ratio of the proportion of the ecological footprint to the economic contribution rate [22]. The proportion of the ecological footprint is the percentage of each city’s ecological footprint to the ecological footprint of the urban agglomeration, and the economic contribution rate is the percentage of each city’s GDP to the GDP of the urban agglomeration. The calculation formula is:

(8)$\mathrm{ECC}=\frac{E{F}_i}{EF}/\frac{GD{P}_i}{GDP}$

where EF_i and GDP_i represent the ecological footprint and GDP of each city, respectively, and EF and GDP represent the ecological footprint and GDP of the urban agglomeration, respectively. When ECC > 1, it indicates that the city has high resource losses and relatively low economic benefits. When ECC < 1, it indicates that the proportion of the ecological footprint of the city is less than the economic contribution rate, that is, it has low resource losses and high economic benefits [13,27].

3. Results

3.1. Spatial and Temporal Variation in the Ecological Footprint of the Guangxi Beibu Gulf Urban Agglomeration

3.1.1. Temporal Variation in the Ecological Footprint

The total, composition and per capita ecological footprints of the Guangxi Beibu Gulf urban agglomeration from 2007 to 2020 are shown in Figure 2. As shown in the figure, the ecological footprint increased overall, with an average annual growth rate of 4.86%. The average value of the ecological footprint per capita increased from 1.30 hm²/cap to 3.05 hm²/cap, this value was higher than the global average (2.84 hm²/cap) [37], indicating that the regional sustainable development level is under pressure. The ecological footprints of different biologically productive lands were successively based on cultivated land, construction land, fossil energy land, woodland, grassland, and water area, while cultivated land, construction land and fossil energy land comprised the main kinds of ecological footprints. Among these different land types, forestland, construction land and energy land grew rapidly, with annual average growth rates of 13.53%, 13.35% and 7.18%, respectively. After 2015 in particular, the ecological footprint of regional cultivated land slowly declined, while that of construction land, forestland and fossil energy land significantly increased. The sequential increases in the construction land footprint and fossil energy land footprint were mainly caused by the increase in energy and electricity consumption that was driven by economic development and urbanization, which also reflects that under the background of the new urbanization strategy, the urbanization level and degree of economic activity of the Guangxi Beibei Gulf urban agglomeration have been greatly improved [15]. The increased woodland footprint indicates an increase in forest product production, reflecting the trend of industrial ecological transformation and improvement in ecological footprint diversity, while a slight decrease in the cultivated land footprint indicates that urbanization development has crowded out cultivated land resources to a certain extent [21].

3.1.2. Spatial Variation in the Ecological Footprint

The total ecological footprint and per capita value of the six cities from 2007 to 2020 are shown in Figure 3 and Figure 4. The annual average value of the total ecological footprint was in the order of Nanning > Yulin > Qinzhou > Chongzuo > Fangchenggang > Beihai, with corresponding proportions of 31.92%, 24.72%, 16.24%, 9.52%, 8.92% and 8.67%, respectively. The annual average value of the per capita ecological footprint was Fangchenggang > Beihai > Nanning > Qinzhou > Chongzuo > Yulin, and the corresponding values were 3.79, 2.06, 1.76, 1.65, 1.56, and 1.43 hm²/cap, respectively. The average annual increase rates were 12.43%, 4.36%, 4.89%, 4.17%, and 6.77%, respectively. In the past 14 years, the per capita ecological footprint of Fangchenggang has remained in first place due to its smaller population, while the per capita ecological footprint gap of Nanning, Qinzhou, Beihai, Chongzuo and Yulin gradually narrowed from 2007 to 2010, and the gap could be clearly divided into three gradients after 2010, namely, Beihai, Nanning–Qinzhou–Chongzuo and Yulin. According to Figure 4, the ecological footprint of all the cities in 2007 was mainly based on cultivated land. Subsequently, there was a decrease in cultivated land, while construction land and fossil energy land significantly increased in each city. The average annual growth rates of construction land per capita in Nanning, Fangchenggang and Beihai reached 25.70%, 15.26%, 14.17% and 11.39%, respectively; the annual average growth rates of forestland per capita in Nanning, Qinzhou, Beihai, Chongzuo, Fangchenggang and Yulin were 13.23%, 10.93%, 16.59%, 19.84% 11.63% and 12.97%, respectively; and the average annual growth rates of fossil energy land per capita in Fangchenggang and Chongzuo were 19.64% and 11.40%, respectively.

3.1.3. Spatial and Temporal Variation in the Ecological Tension Index

The ecological tension index of the six cities in the Guangxi Beibu Gulf urban agglomeration from 2007 to 2020 is shown in Figure 5. The ET of the urban agglomeration is, on the whole, increasing, the annual average growth rate is 6.55%, the value has exceeded 1 since 2009, and the whole region is currently close to being in an unsafe state (ET is 1.851). The ET of the cities has basically increased since 2008, especially the ET of Beihai, which has significantly increased. The average value of ET was ranked as Chongzuo < Fangchenggang < Qinzhou < Nanning < Yulin < Beihai, with corresponding values of 0.557, 0.946, 1.111, 1.382, 1.714 and 2.103. The ecological safety of Chongzuo is secure; Fangchenggang, Qinzhou and Nanning are less secure; Yulin is in an unsafe state; and Beihai is in an extremely unsafe state.

3.2. Efficiency and Equity of Ecological Footprint Allocation

3.2.1. Variation in the Ecological Footprint per 10,000 RMB of GDP

The ecological footprint per 10,000 RMB of GDP in the Guangxi Beibu Gulf urban agglomeration from 2007 to 2020 is shown in Figure 6. The ecological footprint of the urban agglomeration per 10,000 RMB of GDP has a general downward trend, decreasing from 1.02 hm²/per 10,000 RMB of GDP in 2007 to 0.48 hm²/per 10,000 RMB of GDP in 2017 and increasing slightly from 2018 to 2020 to 0.51 hm²/per 10,000 RMB of GDP in 2020. The average ecological footprint per 10,000 RMB of GDP over the 14 years was 0.65 hm²/per 10,000 RMB of GDP, and the average annual reduction rate was 5.06%.

In terms of the distribution of the ecological footprint per 10,000 RMB of GDP in each city, the average value of the ecological footprint per 10,000 RMB of GDP over the 14 years was ranked from small to large as Nanning < Beihai < Chongzuo < Fangchenggang < Qinzhou < Yulin, and the corresponding values were 0.50, 0.52, 0.70, 0.72, 0.86 and 0.90 hm²/per 10,000 RMB of GDP, respectively. Only Nanning and Beihai had lower values than the whole urban agglomeration, so their resource allocation efficiencies were higher. Qinzhou and Yulin had obviously higher values than the whole agglomeration, and their resource allocation efficiencies were low. Fangchenggang and Chongzuo had slightly higher values than those of the whole urban agglomeration, and their allocation efficiency dropped abruptly from 2017 to 2020 with the lowest resource allocation efficiencies.

3.2.2. Variation in the Gini Coefficient

The ecological carrying capacity, economic contribution and comprehensive Gini coefficients of the Guangxi Beibu Gulf urban agglomeration from 2007 to 2020 are shown in Table 2. The three Gini coefficients were all less than 0.30, indicating that the overall ecological demand of the urban agglomeration was well matched with the ecological carrying capacity and economic growth. The comprehensive Gini coefficient decreased from 2007 to 2015 and showed a slight increase from 2015 to 2020, indicating that the equity of ecological capital demand and ecological carrying capacity first increased and then decreased. The Gini coefficient of ecological carrying capacity decreased rapidly from 2007 to 2009, remained relatively stable from 2009 to 2014, fluctuated and increased from 2015 to 2017, and then stabilized. The economic contribution Gini coefficient declined rapidly from 2007 to 2008, remained relatively stable from 2008 to 2017, and continued to grow after 2017, showing a U-shaped distribution.

3.2.3. Variation in the Ecological Carrying Capacity and Economic Contribution Coefficient

The ecological carrying capacity and economic contribution coefficients of the Guangxi Beibu Gulf urban agglomeration from 2007 to 2020 are shown in Table 3 and Figure 7. During the 14 years, the ECC values of Nanning, Chongzuo, Qinzhou, Beihai and Yulin remained relatively stable and fluctuated little, while the ECC values of Fangchenggang increased year by year, and the coefficient of variation was 0.52. The ESC values of Chongzuo and Qinzhou were relatively stable and fluctuated little. The ESC values of Nanning and Yulin showed a central fluctuation, while the ESC values of Fangchenggang and Beihai showed increasing fluctuation, with coefficients of variation of 0.27 and 0.33, respectively.

According to the multiyear average of the two coefficients (Figure 7) and formulas (7)–(8), the economic contribution coefficients of Nanning and Beihai were less than 1, and their ecological carrying capacity coefficients were greater than 1. Nanning and Beihai had high economic contributions and low ecological carrying capacities. These two cities can achieve high economic returns with low resource losses per economic unit, but they have low ecological carrying capacities. The economic contribution coefficients of Chongzuo and Qinzhou were greater than 1, and their ecological carrying capacity coefficients were less than 1. While Chongzuo and Qinzhou have low economic contributions and high ecological carrying capacities, they also have high resource losses and relatively low economic returns. The economic contribution and ecological carrying capacity coefficients of Yulin and Fangchenggang were both greater than 1. Yulin and Fangchenggang have low economic contributions and low ecological carrying capacities, hence they have high resource losses, relatively low economic returns, and low ecological carrying capacities.

4. Discussion

4.1. Characteristics of the Ecological Footprint

4.1.1. General Characteristics

The ecological footprint of the Guangxi Beibu Gulf urban agglomeration can be divided into three periods, namely, the period of increase from 2007 to 2013 (average annual growth rate: 6.67%), the plateau period from 2014 to 2015 (average annual growth rate: 1.13%), and the second increase period from 2016 to 2020 (average annual growth rate: 3.64%). The increase period corresponds to the establishment of the Guangxi Beibu Gulf Economic Zone in 2007, which entered a period of rapid urbanization development. The plateau period corresponds to the 18th National Congress of the Communist Party of China in November 2012, during which the construction of a socialist ecological civilization in China was clearly proposed, making ecological progress a strategic priority and striving to build a beautiful China. Therefore, the urban agglomeration was in a period of industrial structure optimization and adjustment from 2014 to 2015, and its ecological footprint did not significantly increase. The second increase period corresponds to the Development Plan of the Beibu Gulf Urban Agglomeration that was officially approved by the country in February 2017 [38]. Guangxi insisted on promoting development through opening up and green development and aimed to build the Guangxi Beibu Gulf as a blue bay urban agglomeration with a beautiful ecological environment, a vibrant economy and a good quality of life. Therefore, the urban agglomeration mainly promoted high-quality growth with green development and eliminated outdated thermal power plants, cement plants, boilers, motors and other high-energy plants, mines and equipment from 2016 to 2020, and the increase in its ecological footprint slowed down [39]. These results are consistent with relevant studies. The government’s policy guidelines have an obvious regulating effect on the ecological footprint and ensure the appropriate use of natural resources [40,41].

The ecological footprint of the six cities was mainly based on their cultivated land, construction land and energy land ecological footprints, among which the annual growth rate of the ecological footprint of the construction land, woodland and energy land was high, while the ecological footprint of the cultivated land showed a slight downwards trend. First, during the early stage of the new urbanization strategy, the Guangxi Beibu Gulf urban agglomeration expanded its demand for construction land and energy land. However,, clean energy power generation significantly increased, improving the environmental benefits and ecological footprint of urban agglomerations [2,3,4,5,40]. According to Guangxi official statistics, the average annual growth rate of power consumption in Guangxi was 4.48% from 2011 to 2017, and the average annual growth rate rose to 12.01% from 2017 to 2020, mainly for industrial electricity demand. From 2011 to 2015, Guangxi was dominated by thermal power (50%) and hydropower (40%). From 2015 to 2020, it was still dominated by thermal power and hydropower, but nuclear power and wind power were developed, and their proportions gradually increased. By 2020, Guangxi’s thermal power accounted for 54.74%, hydropower accounted for 30.53%, and nuclear power and wind power accounted for 14.74% of its total power output [42]. Furthermore, the change in the ecological footprint of cultivated land and forestland is also consistent with previous research results [43]. Due to multiple factors, such as terrain, economy and human intervention, part of the cultivated land in Guangxi was converted into forestland comprising economic forests, such as eucalyptus, sugarcane and fruit trees, in Qinzhou, Chongzuo and Fangchenggang.

4.1.2. Spatial Characteristics

Due to the imbalance of resource endowment, society and economy, the ecological footprint of the Guangxi Beibu Gulf urban agglomeration also has significant spatial heterogeneity. As the core city of the Beibu Gulf urban agglomeration, Nanning has been built into a modern ASEAN metropolis on the Beibu Gulf [21]. Its annual average GDP and population account for 42.44% and 31.41%, respectively, of the total urban agglomeration, ranking first in the urban agglomeration. Yulin is the machinery manufacturing base of the Beibu Gulf in Guangxi and is the world leader in diesel engine manufacturing technology [22]. Its annual average GDP and population account for 17.75% and 29.84%, respectively, of the total urban agglomeration, ranking second. The two cities are characterized by rapid industrialization and urbanization and high ecological resource consumption, resulting in large ecological footprints. Most urban agglomeration ecological footprints are affected by these same factors [16,44]. Qinzhou’s annual average GDP and population account for 12.42% and 16.95%, respectively, of the total urban agglomeration, ranking third, and its corresponding ecological footprint is also the third largest. The annual average GDP and population of Chongzuo account for 8.71% and 10.58%, respectively, of the total urban agglomeration. Although Chongzuo has a low economic level, its total ecological footprint is also the fourth largest, influenced by the resource consumption of traditional pillar industries such as sugar manufacturing, the manganese, cement and chemical industries [45] and a slightly higher population. The annual average GDP and population of Beihai account for 11.43% and 7.22%, respectively, of the total urban agglomeration. Beihai is one of the first coastal open cities in China and the most famous tourist resort in the Beibu Gulf of Guangxi, with tourism, which consumes relatively few resources [23], as its main industry, so that its total ecological footprint ranks fifth. The annual average GDP and population of Fangchenggang account for 7.36% and 4.01%, respectively, of the total urban agglomeration, and are the lowest in the urban agglomeration Similarly, its total ecological footprint ranks the smallest. However, since 2012, the coastal industry of Fangchenggang has introduced industries with high energy consumption rates, such as the steel and petrochemical industries, making its ecological footprint increase by the most significant margin.

4.1.3. Characteristics of Ecological Pressure

At present, the ET of China’s mega urban agglomerations has exceeded 2; these areas include the Beijing–Tianjin–Hebei, Pearl River Delta, Yangtze River Delta, Yellow River Delta, and Guanzhong urban agglomerations [44,46,47]. However, the ET of the Guangxi Beibu Gulf urban agglomeration is also not in a safe state, though the human disturbance intensity of its regional ecosystem is relatively low.

Chongzuo accounts for 24.06% of the land area of the urban agglomeration. At the same time, because it has national protected areas, such as the White-headed Langr Nature Reserve and Nonggang Nature Reserve, as ecological security barriers, its cultivated land and woodland areas account for 26.33% and 60.75%, respectively, of the city’s land area. Its rich cultivated land and woodland resources, relatively large land area, and suitable climate give it a high ecological carrying capacity [22]. In addition, it has a low ecological footprint and good ecological security.

Qinzhou and Fangchenggang are coastal cities that account for 14.88% and 8.56%, respectively, of the land area of the urban agglomeration, and forestland accounts for 58.96% and 62.93% of these cities’ land areas, respectively. At the same time, Qinzhou also has the largest inland sea in China, the Maowei Sea, and abundant forestland and marine resources make its ecological carrying capacity higher [48]. However, its high ecological footprint makes its ecosystem status slightly unsafe.

Nanning accounts for 30.35% of the urban agglomeration’s land area. The cultivated land and forestland areas account for 21.72% and 56.15% of the city’s land area, respectively, and it is known as the Green City of China. Yulin accounts for 17.57% of the land area of the urban agglomeration, cultivated land and forestland areas account for 15.08% and 58.45% of the city’s land area, respectively, and its modern agriculture and industry are relatively developed. Both Nanning and Yulin have relatively large land areas, rich woodland resources, typical subtropical monsoon climates, and good ecological carrying capacities. However, due to their high ecological footprint, their ecological security status shows risk, especially in Yulin.

Beihai is rich in marine resources [23], but the cultivated land and forestland areas account for only 37.22% and 30.51% of the city’s land area, respectively. Its forestland resources are small, which makes its ecological carrying capacity poor and leads to prominent ecological pressure.

4.2. Ecological Footprint Allocation

4.2.1. Characteristics of Allocation Efficiency

The ecological footprint per 10,000 RMB of GDP in the Guangxi Beibu Gulf urban agglomeration has continued to decline, indicating that the efficiency of resource utilization has improved overall. During the study period, the annual average growth rates of the per capita GDP and per capita ecological footprint of the Guangxi Beibu Gulf urban agglomeration were 10.51% and 4.86%, respectively. In the process of urbanization, the changes in the proportion of the added value of the tertiary industry and the secondary industry to GDP affect the economic benefits that can be created by the ecological footprint [16], and the annual average growth rate of the per capita GDP was higher than the per capita ecological footprint, which is the main reason for the improvement in allocation efficiency. At the same time, China’s green development, industrial transformation and upgrading policies have been phasing out backwards production technologies in recent years, greatly reducing the consumption of resources and vigorously advocating the use of clean energy, energy conservation and emission reduction [39]. In this context, the increase in the ecological footprint has slowed down. However, the ecological footprints of the cities in the study had a significant positive correlation with per capita GDP and population at the 0.01 significance level, while the per capita GDP had a significant positive correlation with the cultivated land ecological footprint, energy land ecological footprint and construction land ecological footprint at the 0.01 significance level. This also shows that the ecological footprint was closely related to the dependence of the region’s population and economic development on electricity and fossil energy, which is consistent with research results in other urban agglomerations [22,27]. The Beibu Gulf urban agglomeration, as a transregional Gulf urban agglomeration on China’s cultivation and construction lands, has the advantages of a coast, an open border, and ecological development. Therefore, the ecological footprint of the Guangxi Beibu Gulf urban agglomeration still needs to be optimized at the policy and institutional levels in terms ecological footprint control on construction and fossil energy lands and ecological footprint retention and industrial ecological transformation on cultivated land.

4.2.2. Characteristics of Allocation Fairness

The unbalanced development of the regional economy is the objective law of regional economic development [49]. From the perspective of urban agglomeration development processes, targeted regional planning should be scientifically implemented in combination with local resource endowments, markets, technologies, institutional mechanisms and other factors, continuously optimizing and upgrading the industrial structure to achieve regional industrial coordination and avoid homogeneous competition [50]. The results indicate that when an urban agglomeration is characterized by central aggregation, there is a clear siphoning effect of the central city, where the population is concentrated, and the central city is mostly characterized by a high economic contribution and a low ecological carrying capacity [42]. The central city greatly contributes to the economy of the urban agglomeration, but some cities monopolize the ecological resources of other cities for economic development. To improve their ecological carrying capacity contribution, it is necessary to strengthen the implementation of ecological red lines and other policies, create biodiversity protection demonstration projects, build ecological towns and ecological communities, and form an integrated urban and rural ecological network [51]. The category of a low economic contribution and a high ecological carrying capacity is mainly found in cities with low connectivity with the central city, a relatively backwards economy, and a high natural resource endowment and important ecological status. In these cities, industrial green and efficient transformation should be implemented to upgrade their industrial technology by transforming their traditional industries and developing emerging industries by transforming their leading industries to improve their economic contribution [52,53]. In particular, the Guangxi Beibu Gulf urban agglomeration has rich marine resources and geographical conditions, while the industrial structure similarity coefficient of Beihai, Qinzhou and Fangchenggang is more than 0.97, areas which are dominated by the primary industry [54]. The emerging marine industry has not formed a scale yet, and the marine industrial structure needs to be further optimized. The category of a low economic contribution and a low ecological carrying capacity contribution is mainly concentrated in cities with high population densities and high total GDP but low per capita GDP. To achieve a win–win situation between regional development and ecological protection in these cities, a new driving force of ecological utilization industries should be cultivated, the consumption of resources should be reduced, the utilization efficiency of natural resources should be improved, and the ecological environment should be protected by law.

5. Conclusions

The ecological footprint of the Guangxi Beibu Gulf urban agglomeration increased slowly and its ecological pressure index showed an overall upwards trend from 2007 to 2020. However, the resource utilization efficiency of the Guangxi Beibu Gulf urban agglomeration increased year by year, and its resource utilization allocation was generally fair. Among the cities, Nanning and Beihai had high economic contributions and low ecological carrying capacities. Chongzuo and Qinzhou had low economic contributions and high ecological carrying capacities. Yulin and Fangchenggang had low economic contributions and low ecological carrying capacities.

Based on its ecological carrying capacity and economic contribution capacity characteristics, the Guangxi Beibu Gulf urban agglomeration needs to rationally adjust its resource allocation and economic development. First, in terms of resource allocation, the three control lines—the ecological protection red lines, permanent basic farmland and urban development boundary—should be strictly observed, total energy consumption should be limited, clean and low-carbon energy should be vigorously developed, backwards and energy-intensive industries should be eliminated, the ecological environment should be protected, and ecological pressure should be alleviated. Second, in terms of regional economic development, Nanning should be considered core to the further formation of an important growth center for the integration of the three cities of Beihai, Qinzhou and Fangchenggang, and to the development of a maritime economy that relies on its natural resources, reduces the dependence on construction land and fossil energy land, enhances the comprehensive strength and competitiveness of the maritime economy, and builds a modern economic system. Yulin and Chongzuo, as the two cities that are adjacent to Nanning, should further promote the development of a high-quality, advanced equipment manufacturing industry, modern agriculture, light industry and food production, a connection with the construction of the Guangdong–Hong Kong–Macao Greater Bay Area, and the improvement of economic strength and resource utilization efficiency. Chongzuo should cultivate a border processing trade for new economic growth on the basis of green and efficient upgrades of its traditional industries.

Author Contributions

Writing draft, J.P. and J.Y.; data curation, J.P., J.Y., X.L., Y.Z. (Yunnan Zou) and R.H.; writing—review and editing, S.L.; methodology, J.Y. and Y.Z. (Yunlan Zhang); Supervision, S.L. and Y.Z (Yunlan Zhang). All authors have read and agreed to the published version of the manuscript.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Acknowledgments

The authors gratefully acknowledge the financial support received from the Department of Education of Guangxi Zhuang Autonomous Region (Funding data: 30 January 2022).

Conflicts of Interest

The authors declare no conflict of interest.

Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Figures and Tables

Figure 1. The location of the Guangxi Beibu Gulf urban agglomeration.

Figure 2. Ecological footprint composition and per capita ecological footprint of the Guangxi Beibu Gulf urban agglomeration from 2007 to 2020.

Figure 3. Ecological footprints and per capita ecological footprints of six cities from 2007 to 2020.

Figure 4. Spatial distribution of the ecological footprint composition and per capita ecological footprint of the Guangxi Beibu Gulf urban agglomeration in 2007, 2014 and 2020.

Figure 5. The ecological tension index of the Guangxi Beibu Gulf urban agglomeration from 2007 to 2020.

Figure 6. Ecological footprint per 10,000 RMB of GDP in the Guangxi Beibu Gulf urban agglomeration from 2007 to 2020.

Figure 7. Evaluation of the ecological support and economic contribution coefficients of the six cities.

Table 1

Classification standard of the ecological pressure index.

Ecological Security Level	Ecological Tension Index (ET)	Ecological Security Status
1	ET < 0.50	Very safe
2	0.50 ≤ ET < 0.80	Safer
3	0.80 ≤ ET < 1.00	Slightly unsafe
4	1.00 ≤ ET < 1.50	Less safe
5	1.50 ≤ ET < 2.00	Not safe
6	ET > 2.00	Extremely unsafe

Table 2

Ecological carrying capacity, economic contribution and comprehensive Gini coefficients of the Guangxi Beibu Gulf urban agglomeration from 2007 to 2020.

Gini CoefficientYear	Ecological Carrying Gini Coefficient	Economic Contribution Gini Coefficient	CompositeGini Coefficient
2007	0.303	0.174	0.225
2008	0.237	0.134	0.175
2009	0.203	0.128	0.158
2010	0.199	0.136	0.161
2011	0.191	0.131	0.155
2012	0.184	0.133	0.153
2013	0.208	0.147	0.171
2014	0.202	0.150	0.171
2015	0.125	0.146	0.137
2016	0.160	0.139	0.148
2017	0.203	0.136	0.163
2018	0.171	0.148	0.157
2019	0.169	0.184	0.178
2020	0.158	0.198	0.182

Table 3

Ecological carrying capacity, economic contribution and comprehensive Gini coefficients of the Guangxi Beibu Gulf urban agglomeration from 2007 to 2020.

CityYear	Nanning		Chongzuo		Qinzhou		Fangchenggang		Beihai		Yulin
	ECC	ESC	ECC	ESC	ECC	ESC	ECC	ESC	ECC	ESC	ECC	ESC
2007	0.687	1.096	1.002	0.386	1.434	0.896	0.836	0.506	1.021	2.297	1.441	1.899
2008	0.816	1.372	1.012	0.419	1.234	0.856	0.883	0.524	0.754	1.360	1.441	1.475
2009	0.805	1.248	1.022	0.459	1.306	0.867	1.008	0.701	0.794	1.431	1.387	1.397
2010	0.821	1.281	1.047	0.440	1.285	0.930	1.090	0.838	0.681	1.476	1.394	1.334
2011	0.793	1.100	1.021	0.460	1.320	0.923	1.297	0.998	0.767	1.539	1.371	1.579
2012	0.793	1.275	1.041	0.487	1.268	0.930	1.565	0.950	0.754	1.569	1.391	1.256
2013	0.780	1.194	1.037	0.464	1.419	0.900	1.632	1.075	0.719	1.461	1.399	1.503
2014	0.762	1.097	1.055	0.429	1.429	0.969	1.868	1.288	0.728	1.489	1.377	1.649
2015	0.747	1.077	1.108	0.481	1.377	1.020	1.930	1.458	0.785	1.658	1.371	1.289
2016	0.756	1.141	1.105	0.509	1.294	0.784	2.215	1.522	0.784	1.859	1.361	1.445
2017	0.768	1.159	1.087	0.541	1.246	0.851	2.287	1.232	0.782	1.774	1.388	1.457
2018	0.751	1.060	0.889	0.425	1.316	0.972	2.735	1.721	0.824	2.243	1.389	1.421
2019	0.679	1.097	1.341	0.431	1.322	1.078	3.503	2.295	0.772	2.117	1.336	1.156
2020	0.662	1.097	1.417	0.497	1.238	0.882	4.304	2.235	0.780	1.802	1.273	1.378
Average value	0.759	1.164	1.085	0.459	1.320	0.918	1.940	1.239	0.782	1.720	1.380	1.446
Coefficient of variation	0.07	0.12	0.13	0.03	0.05	0.06	0.52	0.27	0.10	0.33	0.03	0.09

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