The Nexus of Environmental Protection and Economic Growth in Northern Minority Areas of China Under the Background of Sustainable Climate Policies

Abstract

Exploring the relationship between economic development and environmental protection holds substantial theoretical value for the sustainable progress of minority regions. This paper initially analyzes the overarching mechanisms governing economic growth and climate change challenges in industrial decarbonization toward carbon neutrality. Subsequently, it conducts an empirical analysis utilizing historical economic and environmental data from five provinces to investigate the trajectory of economic development and shifts in environmental quality. The objective of this paper is to flatten the environmental Kuznets curve (EKC) in northwest minority areas, ensuring the continuous enhancement of environmental quality and green transformation in tandem with economic growth, thereby forging a low-pollution pathway for sustainable development. It is observed that an EKC characteristic exists between the economy and the environment in these regions, evolving from discoordination to primary coordination. The environment and economic development in ethnic minority areas of China are progressing slowly, and there is an urgent need for sustainable development reforms. The environment and economic development in ethnic minority areas of China from 2003 to 2022 are progressing slowly, and there is an urgent need for sustainable development reforms. During the economic development process, minimizing environmental pollution should be a fundamental prerequisite, with a focus on industrial ecological advancement, intensifying governmental environmental protection measures, and boosting green technological innovation to strive for a flattening of the EKC and advance a trajectory toward sustainable development.

1. Introduction

Since the Industrial Revolution in Britain in the 18th century, the trajectory of global economic development has involved the significant consumption of natural resources and deterioration of environmental quality, making the balance between economic growth and environmental protection a global issue [1,2]. With increasing attention to climate change and environmental problems, the international community began advocating for a new development concept in the 1970s: sustainable development [3]. This concept emphasizes the coordinated development of economic growth, social progress, and environmental protection, gradually becoming a global consensus [4]. Since the 1990s, scholars have increasingly engaged in quantitative studies of the relationship between the environment and the economy, with the environmental Kuznets curve being one such research method [5,6]. The degree of inequality in wealth distribution initially widens, but with economic growth, income disparities tend to narrow, demonstrating a long-term trajectory of “deterioration followed by improvement” in income inequality, which takes on an inverted U-shape [7]. However, this trend does not manifest uniformly across the different countries [8,9].

In this context, China’s minority areas, particularly northwest minority areas, are increasingly highlighted for their strategic significance in ecological security and as emerging regions for economic development [10]. Following the “deterioration followed by improvement” trajectory regarding the relationship between economic growth and environmental degradation (which may exist), the minority areas are still in the early stages of industrialization (the initial phase of industrial transfer). They cannot continue along the past inverted U-shaped trajectory regarding the relationship between economic growth and potential environmental pollution. Instead, they must first seek a “safety warning line” for economic growth at the onset of industrialization, as illustrated in Figure 1.

The sustainable development of northwest minority areas in China is not only related to local economic welfare and ecological security but is also crucial for achieving sustainable development goals both nationally and globally [11]. Therefore, in-depth research into the interactions among economic growth, environmental protection, and regional sustainable development in this area is of significant importance for formulating effective policies and strategies [12,13]. In this context, this study aims to provide a comprehensive perspective to understand and address the economic and environmental challenges facing northwest minority areas. Through empirical analysis, it explores how these regions can protect the environment while pursuing economic growth and achieving regional sustainable development. This will provide a scientific basis for policymakers, aiding in effectively protecting the environment while promoting economic growth and achieving harmonious coexistence between the socio-economic and natural environments. The marginal contribution of this study lies in analyzing the relationship between the economy and the environment in five ethnic minority areas in China, providing suggestions for the sustainable development of remote areas in China.

2. Literature Review

Regarding the relationship between economic growth and environmental pollution, throughout the historical process of industrialization, the tension between the economy and the environment has been at the core of complex contradictions between humans and the environmental system [14,15]. This contradiction is especially pronounced in minority areas. These areas typically began industrialization later, possess a relatively weak economic foundation, and are hindered by traditional cultural influences, facing numerous obstacles in the popularization and application of technology, resulting in a slow industrialization process and long-term economic lag [16]. This lag exacerbates relative poverty in these regions, leading to dual issues of population growth and ecological fragility [17]. Specifically, population growth not only exacerbates poverty but also places greater pressure on the ecological environment, rendering it increasingly vulnerable. Conversely, a fragile ecological environment further deepens the degree of poverty, forming a vicious cycle [18]. This phenomenon is particularly pronounced in minority areas, where the pursuit of economic growth must also consider the responsibility of protecting a fragile ecological environment [19,20].

To break this cycle, in ethnic minority areas, comprehensive measures must be taken. In researching the economic growth, environmental protection, and regional sustainable development of the northwest minority areas of China, numerous scholars have proposed various viewpoints and research findings, including but not limited to promoting technological innovation, improving resource utilization efficiency, strengthening environmental protection, and developing a low-carbon economy [21]. Some studies suggest that economic growth often comes at the expense of the environment. However, increasing evidence indicates that, particularly through the role of digitalization, a win–win situation for both economic growth and environmental protection can be achieved [11]. Existing scholars have confirmed that technological innovation significantly contributes to economic growth in minority areas [22]. Green finance can mitigate the adverse environmental impacts of natural resource rents on carbon emissions, providing a policy reference for achieving coordination between environmental protection and development in northwest minority areas [23]. Additionally, other scholars have proposed a data mining analysis of human resources’ impact on economic development in minority areas [24], indicating a significant positive relationship between human capital and economic development in the northwest. Some scholars also argue that China’s ESG practices significantly enhance high-quality development of enterprises, particularly affecting green total factor productivity, exhibiting a U-shaped relationship [25].

Regarding specific policy implementation effect evaluations, through empirical analysis of the vertical management reform of China’s environmental protection agencies, environmental regulations significantly reduced carbon emissions from industrial enterprises, indicating that the implementation of environmental regulations can promote environmental protection [8], albeit through passive methods such as reducing production, limiting enterprise entry, and increasing the failure rate of enterprises. Other studies have shown that green foreign direct investment (FDI) significantly alleviates local air pollution and poverty issues, providing positive guidance for attracting green investment in the northwest [26]. Research conducted by other scholars has also demonstrated that implementing strict environmental regulatory policies can effectively promote energy poverty alleviation, providing policy references for minority areas to find a balance between environmental protection and economic development [27,28,29]. Through these measures, sustainable economic development in minority areas can be promoted while protecting and improving the ecological environment, thus achieving a harmonious coexistence between socio-economic and natural environments.

In summary, comprehensive measures including technological innovation, improving resource efficiency, strengthening environmental protection, and reforming educational culture can effectively address the dual issues of economic lag and environmental fragility in minority areas, achieving sustainable economic development and ecological protection [21]. Due to later industrialization, weak economic foundations, and the influence of traditional cultural thoughts, the northwest minority areas of China face numerous obstacles to the popularization and application of technology, leading to slow economic growth that lags significantly behind the national average. However, through the reasonable design and implementation of policy, high-quality economic development can be achieved while protecting the environment [30]. This study will further explore how to achieve an optimal balance between environmental protection and economic growth in this region, providing more specific suggestions and schemes for policymakers. Based on the above literature analysis, the EKC curve in ethnic minority areas of China may present an inverted N-shaped pattern.

3. Empirical Model Design

3.1. Model

This paper employs panel data to construct the environmental Kuznets curve (EKC) model for the northwest minority areas of China, aiming to elucidate the relationship between environmental protection and economic growth in these areas. The parameters of the EKC model primarily utilize polynomial models with one to three orders of per capita GDP as explanatory variables, along with logarithmic polynomial models. To avoid potential biases in understanding the curve and the inflection point due to reliance on a single estimation method, this study conducts fitting analyses using both classical logarithmic quadratic and cubic equations based on the mechanisms of economic growth and environmental protection in the northwest minority areas. This approach is intended to explore the relationship between environmental protection and economic growth, and to determine whether the EKC exhibits the characteristic inverted U-shape based on the significance and sign characteristics of the regression coefficients.

Specifically, we construct an economic model that closely connects the per capita gross domestic product (GDP) of northwest minority areas with environmental protection indicators. The model is as follows:

$${\mathrm{E}}_{\mathrm{i}\mathrm{t}}=a_0+a_1{ln\mathrm{y}}_{\mathrm{i}\mathrm{t}}+a_2{ln{y}_{it}}^2+a_3{ln{y}_{it}}^3+ 𝛼4𝑋𝑖𝑡+𝛽𝑖+{\mathsf{\mu }}_t+{\mathsf{\gamma }}_t+{\epsilon }_{it}.$$

(1)

In this model, ${\mathrm{E}}_{\mathrm{i}\mathrm{t}}$ represents the air quality, water quality, and total government environmental protection investment for region i at time t. $y_{it}$ denotes the per capita GDP of region i at time t, while $a_0{, a}_1, a_2, a_3,$ and $a_4$ are parameters of the model, which can take both positive and negative values. The logarithmic forms of these variables help us capture the nonlinear relationship between economic growth and environmental protection. Xit is a vector of control variables that may influence both economic growth and environmental protection, such as education levels and infrastructure development. A₀ is the constant term, and a₀, a₁, a₂, a₃, and a₄ are the regression coefficients. The terms βi and ${\mathsf{\mu }}_t$ represent city fixed effects and year fixed effects, respectively, which control for unobservable heterogeneity between different cities, as well as for macroeconomic policies and other external factors that change over time. ${\mathsf{\gamma }}_t$ is the time trend term, capturing the effects of factors such as technological progress that may lead to improvements in environmental quality over time, thereby controlling for the overall positive trend in air and water quality resulting from continuous advancements in technology. ${\epsilon }_{it}$ is the random error term, which includes unobserved random factors in the model.

The different values of the estimated parameters will determine the nature of the curve relationship between environmental quality and economic growth: if $a_1$ = 0, $a_2$ = 0, $a_3$ = 0, there is no correlation between environmental quality and economic growth. If $a_1$ ≠ 0, $a_2$ = 0, and $a_3$ = 0, there exists a linear relationship represented by a straight line. If $a_2$ ≠ 0 and $a_3$ = 0, a nonlinear quadratic relationship arises. When $a_2$ > 0, the curve is U-shaped, and when $a_2$ < 0, the curve is shaped like the inverted “N”. If $a_3$ ≠ 0, a nonlinear cubic relationship emerges, when $a_3$ > 0, the curve takes an N-shape, and when $a_3$ < 0, the shape of the curve is inverted “N”.

3.1.1. Explanatory Variable

Regarding economic growth, this study, adopting the method outlined by Lu et al. [31], selects the per capita GDP of the northwest minority provinces as a measure of economic growth, as per capita GDP better reflects changes in the level of real economic development.

3.1.2. Dependent Variable

The main indicators chosen for assessing regional sustainable development in this study include economic growth indicators and environmental statistical indicators. Specifically, the environmental indicators include air quality, water quality, and total government investment in environmental protection. The environmental investment metric is represented by the total investment in pollution control. The scoring systems for air quality and water quality indicators are detailed in

Table 1. Environmental quality evaluation index system.

Primary Indicator	Secondary Indicator	Unit	Indicator Attribute
Air Quality (air)	Total Emission of Sulfur Dioxide	10,000 tons	Negative
	Industrial Waste Gas Emission Volume	100 million standard cubic meters	Negative
	Number of Industrial Waste Gas Treatment Facilities	Sets	Positive
	Operating Costs of Industrial Waste Gas Treatment Facilities	CNY 10,000	Positive
Water Quality (water)	Total Industrial Wastewater Emission	100 million tons	Negative
	Industrial Chemical Oxygen Demand Emission	10,000 tons	Negative
	Industrial Ammonia Nitrogen Emission	10,000 tons	Negative
	Investment in Completed Industrial Wastewater Pollution Control Projects	CNY 10,000	Positive
Government Environmental Protection Investment (enin)	Total Investment in Pollution Control	CNY 10,000	Positive

, and the entropy method is employed to calculate the scores for air quality and water quality.

To assess the randomness and disorder of an event, one can also determine the level of dispersion of a particular indicator [32]. After constructing the environmental quality evaluation indicator system, issues arise due to the lack of uniformity in the dimensional characteristics and the significant differences in values among various indicators, resulting in a lack of comparability both between and within the indicators. Therefore, it is necessary to use the entropy method to standardize all raw data to eliminate the impact of dimensions and differences. The specific calculation steps are as follows: let there be k years, n provinces, and m evaluation indicators, with $X_{\mathsf{\theta }\mathrm{i}\mathrm{j}}$ representing the value of the j indicator for province i in year θ. The standardization for positive and negative indicators is detailed in Equations (1) and (2).

For positive indicators,

$$X_{ij}={\displaystyle \frac{X_{ij}-min\left(X_{ij}\right)}{max\left(X_{ij}\right)-min\left(X_{ij}\right)}}.$$

(2)

For negative indicators,

$$X_{ij}={\displaystyle \frac{max\left(X_{ij}\right)-X_{ij}}{max\left(X_{ij}\right)-min\left(X_{ij}\right)}}.$$

(3)

Calculate indicator weights as follows:

$$P_{ij}={\displaystyle \frac{X_{ij}}{{\sum }_{i=1}^m{X}_{ij}}}.$$

(4)

Calculate the information entropy as follows:

$$e_j=-\mathrm{k}{\sum }_{i=1}^m{P}_{ij}ln\left(P_{ij}\right).$$

(5)

Calculate the coefficient of variation as follows:

$$g_j=1-e_j.$$

(6)

Calculate weights as follows:

$$W_j={\displaystyle \frac{g_j}{{\sum }_{j=1}^n{g}_j}}.$$

(7)

Calculate the final comprehensive score to derive scores for water and air quality as follows:

$$F_i=\sum _{j=1}^n{W}_j{X}_{ij}.$$

(8)

3.1.3. Control Variable

Based on existing research [33,34], several factors, including technological level, industrial structure, urbanization rate, population size, and environmental regulation, have significant impacts on environmental pollution. Therefore, the following control variables are introduced. (i) Technological level (tech): this is represented by the number of practical patents granted, which serves as an indicator of the technological advancement in the region. (ii) Urbanization rate (urba): this is measured as the proportion of the urban population to the total population, reflecting the level of urbanization in the area. (iii) Population size (popu): this is characterized by the number of permanent residents in the region and is included in the model to account for demographic influences. (iv) Environmental regulation (enre): this is measured by the proportion of investment in industrial pollution control relative to the industrial added value, indicating the intensity of environmental regulation in the industrial sector. (v) Industrial structure (inst): the advancement of industrial structure is represented by an index that reflects the sophistication of the industrial structure. This index emphasizes the overall relationship between different industries by assigning different weights to the primary, secondary, and tertiary sectors. The specific calculation formula for the industrial structure index is as follows:

$$\mathrm{inst}={\sum }_{\mathrm{i}=1}^3\mathrm{i}\ast {\displaystyle \frac{{\mathrm{Y}}_i}{\mathrm{Y}}} (\mathrm{i} = 1, 2, 3).$$

(9)

In this context, Y represents the gross domestic product (GDP) of the region, while ${\mathrm{Y}}_i$ denotes the output value of the i-th industry in that region. Logarithmic transformation of the data facilitates the attainment of a stationary time series without affecting the inherent characteristics of the data. It also helps to mitigate extreme fluctuations and eliminate potential heteroscedasticity. Therefore, the logarithmic transformation is applied to per capita GDP, the number of utility model patents granted, the proportion of urban population, and the number of permanent residents.

3.1.4. Data Source

In this study, panel data from five northwest minority provinces from 2003 to 2022 are selected as the foundational data to measure economic growth and environmental pollution. All data are sourced from the China Statistical Yearbook, China Environmental Statistical Yearbook, China Urban Statistical Yearbook, China Regional Statistical Yearbook, and various regional statistical yearbooks. Missing data are supplemented using interpolation methods. To avoid significant fluctuations in the data and eliminate potential heteroscedasticity, logarithmic transformations are applied to specific datasets, including per capita GDP, the number of practical patents granted, the proportion of the urban population, and the number of permanent residents. From the descriptive statistics of the variables, it can be concluded that the distribution of each variable is average and falls within the ideal range (

Table 2. Descriptive statistics of main variables.

Variable	Sample Size	Mean Value	Minimum Value	Maximum Value	Standard Deviation
lnpgdp	100	10.2003	8.6170	11.4770	0.4680
water	100	0.4992	0.2614	0.8581	0.1175
air	100	0.3262	0.1693	0.8078	0.1226
lnenin	100	13.2987	10.8781	15.5424	1.3135
lntech	100	7.1933	3.4012	9.9977	2.6858
inst	100	2.3158	2.1600	2.4307	0.0604
lnurba	100	3.8736	3.3098	4.2283	0.0463
lnpopu	100	7.2432	6.2804	7.8813	0.4693
enre	100	0.0078	0.0002	0.04764	0.0070

).

4. Results

4.1. Analysis of Environmental Quality Characteristics

The increase in the concentration of greenhouse gases and pollutants emitted by production activities in the air changes the radiation balance of the atmospheric system, causing the temperature to rise and accelerating the speed of the water cycle. At the same time, pollutants in the water environment also participate in the process of the water cycle, which has a negative impact on climate change and environmental quality. Specifically, western minority areas in China, including the Xinjiang Uyghur Autonomous Region, Inner Mongolia Autonomous Region, Gansu Province, Ningxia Hui Autonomous Region, and Qinghai Province, account for 42% of the total land area of China. This area is home to a large population of ethnic minorities and holds a crucial geographic position within China. However, due to adjustments in the industrial structure of the northwest region, particularly the development of electricity, ferrous metal smelting, and other inorganic chemical industries, there has been a significant increase in coal usage. This surge has been a major contributing factor to the exacerbation of air pollution and the continuous rise in greenhouse gas emissions. Additionally, the increased use of coal in northwest minority areas dictates the upward trend in greenhouse gases in this region. Insufficient end-of-pipe treatment facilities, along with a severe lag in the installation capacity for industrial waste gas treatment facilities and inadequate investment in subsequent pollution control measures, are significant contributors to the migration of air pollution phenomena toward the northwest. The fragile ecological environment, characterized by arid and low-rainfall conditions in the northwest, exacerbates the deterioration of air quality and climate change, further worsening the local ecological state. This vulnerable ecological environment reduces the carrying capacity of the regional ecosystem, significantly intensifying the impact of natural disasters. The low treatment rate of domestic sewage, combined with the weak economic foundation of northwest minority areas and the slow development of urban infrastructure, results in serious delays in the construction of urban drainage networks and sewage treatment facilities. The urban wastewater treatment rate is below 10%, well below the national average [35].

Figure 2 illustrates the dynamic changes and trends in environmental indicators across northwest minority areas. From the figure, it can be observed that the air quality score in the Xinjiang Uyghur Autonomous Region fluctuates in conjunction with government environmental protection investment, both experiencing a trend of rising and then falling. However, by 2022, both government investment and air quality were slightly higher than levels observed in 2003. Water quality demonstrates significant fluctuations, with the 2022 water quality score being lower than that in 2003, indicating that efforts of controlling water pollution have not been effective. In the Inner Mongolia Autonomous Region, investments in environmental pollution show an initial increase followed by a decrease. Meanwhile, the scores of water and air quality demonstrate a fluctuating upward trend, indicating significant improvements in water and air pollution control efforts. Gansu Province has relatively low government expenditure on environmental protection, which peaked in 2013 before gradually declining. The water quality fluctuates but is generally better than the air quality due to the province’s reliance on coal as a primary energy source, resulting in substantial emissions from coal combustion that poses high treatment difficulties and costs [36]. The Ningxia Hui Autonomous Region exhibits low levels of government environmental protection investment, with an initial increase followed by a decline, peaking in 2016. From 2003 to 2015, the trend in air quality changes aligned with changes in environmental protection investment, while from 2016 to 2022, the two displayed opposing trends. The water quality score fluctuates between 0.2 and 0.9. In Qinghai Province, both air and water quality, as well as government environmental protection investment, show little fluctuation over time and remain at relatively low levels. This is attributed to the location of Qinghai Province in the northeastern part of the Tibetan Plateau, where the ecological environment is extremely fragile and the energy and raw materials industries occupy a large share of the industrial structure, resulting in high energy consumption [37].

Based on the dynamic changes in environmental indicators from 2003 to 2022, it can be observed that the air quality in the five northwest minority areas has gradually improved, with air quality scores experiencing a fluctuating upward trend. The water quality scores for Xinjiang Uyghur Autonomous Region, Inner Mongolia Autonomous Region, Gansu Province, and Ningxia Hui Autonomous Region demonstrate significant fluctuations. In 2022, the air quality in Xinjiang Uyghur Autonomous Region and Qinghai Province decreased compared to 2003, while the air quality levels in the remaining regions improved. In all five minority areas, including Xinjiang, Inner Mongolia, Gansu, Qinghai, and Ningxia, government investments in environmental protection exhibited a trend of initially rising and then declining, peaking around 2015. However, the investment in environmental protection by the governments of the Ningxia Hui Autonomous Region and Qinghai Province is significantly lower than that of the other three regions. On average, across the five northwest minority areas, water quality shows fluctuations while air quality has improved and is on an upward trend. The total government investment in environmental protection has increased and then decreased over this period.

4.2. Results of Empirical Analysis

To analyze the relationship between economic development and environmental pollution, polynomial regression using quadratic or cubic models can be employed. In this study, polynomial models are used to fit the relationships between environmental pollution and per capita GDP. Comparison of model fit and the significance of estimated coefficients reveals that cubic polynomial fitting outperforms quadratic fitting. Thus, a cubic polynomial is selected as the testing model. Statistical analysis of air quality, water quality, total government environmental protection investment, and per capita GDP is conducted using Stata 16, with the results presented in

Table 3. Baseline regression results.

Variables	1	2	3	4	5	6
	Air	Air	Water	Water	Lnenin	Lnenin
lnpgdp	−3.2248 ***	13.3591 ***	−2.6300 **	30.8496 ***	−10.6729 ***	76.7467 **
	−6.4493	−3.1598	−2.2762	−3.0756	−3.0136	−2.4413
lnpgdp2	0.1551 ***	−1.5152 ***	0.1373 **	−3.2347 ***	0.5581 ***	−8.2469 **
	−6.5365	−3.5744	−2.5046	−3.2164	−3.3204	−2.6163
lnpgdp3		0.0560 ***		0.1131 ***		0.2954 ***
		−3.9454		−3.3573		−2.797
inst	0.3252	0.2467	−0.1019	−0.2604	3.6965 **	3.2827 **
	−1.5512	−1.288	−0.2103	−0.5730	−2.4895	−2.305
enre	−0.7187	−0.124	3.8119 *	5.0124 ***	10.5300 *	13.6646 **
	−0.8399	−0.1565	−1.928	−2.6676	−1.7374	−2.3203
lntech	−0.0734 ***	−0.0760 ***	−0.0446	−0.0497	0.2422	0.2288
	−2.8787	−3.2764	−0.7558	−0.9031	−1.3401	−1.3266
lnurba	−0.2865	0.0673	0.6029	1.3171 **	−2.4676	−0.6026
	−1.2395	−0.2945	−1.1287	−2.4308	−1.5072	−0.3548
lnpopu	−0.8978 ***	−0.7105 ***	−0.2346	0.1435	−2.3789 ***	−1.3916 *
	−8.2731	−6.4920	−0.9355	−0.5528	−3.0950	−1.7101
Constant	24.4032 ***	−32.9821 **	12.8638 **	−102.9852 ***	80.2458 ***	−222.2517 **
	−10.1267	−2.2423	−2.3102	−2.9512	−4.7015	−2.0321
Observations	100	100	100	100	100	100
R-squared	0.9395	0.9508	0.6484	0.6984	0.9653	0.9689
Year fe	yes	yes	yes	yes	yes	yes
Prov fe	yes	yes	yes	yes	yes	yes

Notes: significance levels are indicated by *, **, and ***, corresponding to the 10%, 5%, and 1%, respectively.

. All the variables passed the robust test, and the VIF index was below 10 for each.

According to the results in Table 3, the cubic function fit for air quality scores has a high coefficient of determination. The cubic function expression is provided by the following:

$${\mathrm{air}}_{\mathrm{it}}=-32.9821+13.3591{ln\mathrm{y}}_{\mathrm{i}\mathrm{t}}-1.5152{ln{y}_{it}}^2+0.0560{ln{y}_{it}}^3$$

(10)

This indicates that the relationship between air quality scores and per capita GDP is modeled by a cubic polynomial. The coefficients $a_1$ > 0, $a_2$ < 0, $a_3$ > 0 suggest an N-shaped relationship, indicating that higher air quality scores correspond to better air quality and lower environmental pollution. Therefore, it can be inferred that the relationship between air pollution and economic growth exhibits an inverted N-shaped pattern: as the per capita GDP increases, air pollution levels in the northwest minority areas initially decrease, then increase, followed by another decrease, reflecting a sequence of improvement–deterioration–improvement.

The equation for the water quality score in relation to per capita GDP is expressed as follows:

$${\mathrm{water}}_{\mathrm{it}}=-102.9852+30.8496{ln\mathrm{y}}_{\mathrm{i}\mathrm{t}}-3.2347{ln{y}_{it}}^2+0.1131{ln{y}_{it}}^3$$

(11)

Similarly, the coefficients $a_1$ > 0, $a_2$ < 0, $a_3$ > 0 indicate that water pollution also follows an inverted N-shaped relationship with economic growth. As the per capita GDP increases, water pollution levels in the northwest minority areas show a trend of initial decrease, followed by an increase, and then a final decrease, again reflecting an “N” shape. The appearance of such curves suggests that in the early stages of economic growth, both air and water pollution decline as the per capita GDP rises. This phase of economic growth may stem from the development of agriculture, services, and other sectors, or policy factors that have minimal impact on the air and water environments. After the first turning point, the level of environmental pollution in the northwest minority areas begins to rise with increasing per capita GDP, and declines again after reaching the second turning point. The transition from worsening to improving environmental quality, following the environmental Kuznets curve (EKC) pattern, is attributed to the ongoing implementation of circular economy development concepts and a series of pollution control measures. Additionally, the growth of the tertiary sector has contributed to reducing air pollution levels in the northwest minority areas to a certain extent. The right side of the first turning point indirectly reflects an inverted U-shaped curve, partially aligning with the EKC hypothesis.

The relationship between government investment in environmental protection and economic growth is as follows:

$${\mathrm{l}\mathrm{n}\mathrm{e}\mathrm{n}\mathrm{i}\mathrm{n}}_{\mathrm{i}\mathrm{t}}=-222.2517+76.7467{ln\mathrm{y}}_{\mathrm{i}\mathrm{t}}-8.2469{ln{y}_{it}}^2+0.2954{ln{y}_{it}}^3.$$

(12)

The coefficients $a_1$ > 0, $a_2$ < 0, $a_3$ > 0 indicate an N-shaped relationship between total government environmental protection investment and economic growth. As the per capita GDP increases, the total government investment in environmental protection initially rises, then declines, and subsequently increases again. This suggests that as the economy develops, government environmental protection investments are continuously increased. However, at a certain stage of economic development, environmental investments may decrease. In the long term, after reaching a turning point, the government will place greater emphasis on environmental protection and increase investment in this area. At a certain stage of economic development, increasing government environmental investment may help improve environmental quality. However, beyond a certain level, excessive environmental investment could negatively impact economic growth. Additionally, considering the changing marginal effects of environmental investments, the positive effects on economic growth from increased environmental investments will gradually diminish until reaching a critical point, beyond which further environmental investments may suppress economic growth. Therefore, policymakers need to seek a balance between environmental protection and economic growth.

5. Conclusions and Policy Recommendations

5.1. Conclusions

This study selects data from northwest minority areas in China from 2003 to 2022 and conducts an empirical analysis of the relationship between economic growth and environmental pollution based on the environmental Kuznets curve theory, hypothesizing a cubic polynomial relationship. The limitation of this article is that it specifically discusses several ethnic minority regions in China, rather than covering the entire Chinese region. However, the environmental and economic issues in these regions are representative and worthy of study. The relationship between the climate and the environment in these regions demonstrates the patterns of China’s climate and environment. By analyzing these patterns, we can strike a balance between environmental protection and economic development, achieve the simultaneous realization of environmental protection and economic growth, and ultimately achieve sustainable development. This will contribute to China’s experience in global sustainable development. The findings indicate the following:

(i) Existence of EKC characteristics: There is an EKC characteristic in the relationship between the economy and the environment in northwest minority areas, transitioning from dis-coordination to initial coordination. However, it also demonstrates that environmental governance cannot be delayed until economic development is achieved, and pollution will not automatically improve following the EKC model. The occurrence of the EKC turning point necessitates proactive measures to completely eliminate the outdated practice of trading environmental quality for economic profit. We must adhere to an intensive development path to achieve a win–win situation of coordinated economic and environmental development.

(ii) Diversity in EKC shapes: The EKC curve is not a fixed pattern but exhibits various morphological characteristics. Due to differences in pollution indicators and sample data ranges, this study finds that air and water pollution follow an inverted N-shaped trend in relation to economic growth, overall experiencing a process of improvement-deterioration-then improvement. This suggests that in the future, the economy and environment will trend towards coordinated development.

(iii) Complex nature of environmental pollution: Environmental pollution is not merely a negative externality resulting from economic growth but rather a comprehensive issue influenced by multiple factors. The total government investment in environmental protection shows an N-shaped relationship with economic growth, indicating that improving environmental quality may be a long-term process requiring sustained environmental investment and policy support. The efficiency and effectiveness of environmental investments may vary at different stages of economic development, necessitating continuous monitoring and evaluation of environmental policies. Furthermore, control variables such as industrial structure, population size, technological advancement, and government regulation directly or indirectly impact the production or emission of various pollutants.

5.2. Policy Recommendations

Excessive emissions of greenhouse gases and air pollutants from human production activities pose risks to industrial decarbonization efforts toward carbon neutrality. Therefore, economic growth, environmental protection, and sustainable development of resources present significant challenges toward carbon neutrality for the northwest minority areas of China. To enhance the environmental Kuznets curve framework, it is essential to pursue a path that does not exceed the environmental pollution safety line in ecologically fragile areas, diverging from the traditional “high pollution, high growth” ADC-type curve towards a “lower pollution” trajectory akin to a tunnel. The following approaches to meeting the challenges of climate change can be considered for the coordinated development of the economy and environment:

(i) Promote ecological industrial development and innovation-driven upgrades: The development of northwest minority areas relies on resource support and fulfills an important strategic role in the national energy supply. It is crucial to advance the greening, ecological transformation, and circular upgrading of traditional high-pollution industries. This can be achieved by employing new technologies and equipment to enhance quality, efficiency, and reduce emissions in industrial enterprises, thereby establishing a framework for sustainable green development. Actively promoting a shift in industrial development models is necessary to abandon the traditional extensive approach to industrialization, reducing pollution emissions from the outset and controlling pollution growth during industrialization. Moreover, there should be a strong emphasis on developing the modern service industry, highlighting the importance of clean industries in socio-economic development.

(ii) Strengthen government environmental investment and regulations: As one of the main actors in environmental governance, the government should balance economic development with environmental protection based on effective regional planning. It is important to maintain a reasonable proportion of environmental pollution control investment relative to the GDP. Additionally, the government should leverage its administrative power to impose behavioral constraints on pollution-emitting entities, such as industrial enterprises, through the establishment of a pollution discharge property rights system. Legislation should clearly define the responsibilities, obligations, and penalties for polluting entities, with strict supervision and regulation of pollutant discharge processes to address pollution at its source and achieve coordinated economic and ecological development. Implementing corresponding tax reductions and project support policies can enhance the participation of industrial enterprises in pollution reduction efforts, thereby lowering industrial pollutant emissions and improving environmental quality in northwest minority areas.

(iii) Enhance green technology innovation and promote a green energy transition: Empirical results indicate that technological advancement and energy structure significantly influence environmental pollution reduction. Green technology innovation and the greening of the energy structure both have a substantial impact on economic growth. Technological progress, particularly advances aimed at reducing environmental pollution, can effectively improve energy efficiency and promote a green transition in northwest minority areas. This includes accelerating the elimination of outdated production capacity and actively guiding the replacement of traditional energy sources with new energy sources. Given the unique geographical advantages of northwest minority areas, which are rich in natural resources, there is significant potential for the development of renewable energy sources, such as wind and solar energy. Focusing on overcoming technical bottlenecks across the entire renewable energy industry chain, including energy collection, storage, supply, and transportation, is a good way to maintain and expand its competitive advantage in the national energy market to achieve a comprehensive green transformation of economic and social development.