3.2. Spatial–Temporal Analysis of Air Pollution
3.2.1. Temporal Characteristics of Air Pollution
In this paper, four important air pollutants (PM
2.5, CO, O
3 and SO
2) were selected to characterize air pollution in the CHUA.
Figure 7 shows the change trend of air pollution in the CHUA from 2000 to 2022.
During the study, the concentration of PM2.5 exhibited an initial upward trend, followed by a subsequent decline. Since 2006, there have been some cities with PM2.5 concentrations exceeding 90 μg·m−3, such as Xingtai, with PM2.5 concentrations of 97.91 μg·m−3 and 98.23 μg·m−3 in 2006 and 2007, respectively. In 2013, one third of the cities had the highest PM2.5 concentration of 100 μg·m−3, with Hebi and Xingtai having concentrations as high as 110.29 μg·m−3 and 112.02 μg·m−3. Over the past few years, China has undergone rapid industrialization and urbanization, leading to increased energy consumption and pollutant emissions due to the construction of numerous factories and urban expansion. Particularly, the combustion of fossil fuels such as coal has been the primary cause of the rise in PM2.5 concentrations. From 2013 to 2019, the concentration of PM2.5 in each city of the CHUA continued to decline, ranging between 43.68 μg·m−3 and 61.7 μg·m−3, which benefited from the promulgation and implementation of policies such as the Action Plan for Air Pollution Prevention and Control and the Three-year Action Plan for Winning the Blue-Sky Defense. Good results have been achieved in the control of PM2.5. By 2022, Hebi stood out as the only city with a PM2.5 concentration surpassing 50 μg·m−3, while the majority of cities in the Central Plains urban agglomeration maintained concentrations ranging between 40 μg·m−3 and 50 μg·m−3. Notably, the region experienced a marked improvement in PM2.5 pollution levels. This positive trend can be attributed not only to the profound influence of the COVID-19 pandemic’s profound impact on daily life and industrial activities, but also to China’s consistent and sustained commitment to particulate matter prevention and control measures.
From 2000 to 2022, the O
3 column concentration presents a zigzag distribution. As can be seen from
Figure 7d, Handan, Xingtai, Liaocheng and Puyang have higher O
3 column concentrations, while Fuyang, Nanyang and Xinyang have lower O
3 column concentrations. Among them, the O
3 column concentration in 2010 and 2015 was relatively high, and only two cities, Nanyang and Xinyang, had O
3 column concentrations less than 300 DU, and Xingtai had an O
3 column concentration of more than 320 DU. It is likely that Handan, Xingtai, Liaocheng and Puyang may have more industrial enterprises and traffic vehicles, resulting in greater emissions of O₃ precursors such as NOx and VOCs (volatile organic compounds) in these areas, which favor the formation of O₃. In contrast, Fuyang, Nanyang and Xinyang may have relatively fewer industries, leading to less emissions of O₃ precursors.
On the whole, the concentration of SO2 in the CHUA showed an increasing trend. At the same time, Jiaozuo, Jiyuan, Zhengzhou and Xinyang were the cities with the highest concentrations of SO2, while Sanmenxia was the city with the lowest concentration of SO2, ranging from 13.39 μg·m−3 to 29.71 μg·m−3. This is because cities such as Jiaozuo, Jiyuan, Zhengzhou and Xinyang have well-developed industries, especially the rapid development of industries such as coal, power and chemicals, which may have led to significant SO₂ emissions. From 2000 to 2009, the concentration of SO2 increased rapidly from 13.7 μg·m−3–31.97 μg·m−3 to 27.86 μg·m−3–61.27 μg·m−3. The change in the SO2 concentration from 2010 to 2022 was rather tortuous. In 2011, the SO2 concentrations in various cities were the highest they had been in the past two decades, and there were nine cities with SO2 concentrations exceeding 50 μg·m−3, among which Jiaozuo’s SO2 concentration reached 65.6 μg·m−3, which was the city with the highest SO2 concentration. To further reduce SO₂ emissions, it is necessary to adopt more effective measures, such as optimizing energy structure, strengthening industrial pollution control and improving vehicle emission standards.
The variation in the CO concentration is different among the cities in the CHUA. The CO concentrations in Handan, Anyang and Hebi were higher, the CO concentrations continued to increase from 2000 to 2009, and the concentrations in 2009 were 1.97 mg·m−3, 1.62 mg·m−3 and 1.48 mg·m−3, respectively, while the concentrations did not change much after 2010. The concentrations of CO in Sanmenxia, Xinyang, Luoyang and Nanyang were always at low levels, ranging from 0.18 mg·m−3 to 0.4 mg·m−3. In addition, the concentrations of CO in Huaibei and Bozhou increased suddenly in 2012 and 2014, and the concentration distribution was 1.35 mg·m−3, 1.16 mg·m−3, 1.2 mg·m−3 and 1.18 mg·m−3. It is possible that these two cities experienced rapid industrial development or changes in the energy structure during these specific years, leading to a sudden increase in CO emissions. Alternatively, they may have encountered unfavorable climate conditions during certain periods, which made it difficult for pollutants to disperse.
3.2.2. Spatial Distribution Characteristics of Air Pollution
The spatial distribution characteristics of the four kinds of air pollutants are shown in
Figure 8. From 2000 to 2015, the distribution of PM
2.5 showed obvious aggregation characteristics, and the cities along Xingtai, Handan and Zhengzhou had high concentrations of PM
2.5. As an international big city, Zhengzhou’s high-density population, dense traffic network and developed economic conditions will make the PM
2.5 concentration continue to rise. Handan and Xingtai, as resource-based heavy industry cities, will inevitably bring more pollution, accelerate industrial transformation and upgrading, eliminate backward production capacity and develop more high-end industries, which will be important reasons for Handan and Xingtai to reduce their PM
2.5 concentrations. By 2022, the PM
2.5 concentration within the CHUA had noticeably improved, as evidenced by the fact that only Hebi exceeded the threshold of 50 μg·m
−3, while the remaining cities boasted low PM
2.5 levels.
The O3 column concentration showed a significant step distribution, increasing from south to north. In 2000 and 2005, only Handan, Xingtai and Liaocheng had O3 column concentrations exceeding the standard value (300 DU). In 2010 and 2015, most cities in the northern part of the CHUA had higher O3 column concentrations. After several years of consistent improvement, in 2022, none of the cities within the CHUA recorded O3 column concentrations surpassing 320 DU. The regions with elevated concentrations remained concentrated predominantly in the central and northern areas, while the southern region exhibited O3 column concentrations that fell within the range of 290 DU to 300 DU. This phenomenon should be related to the urbanization process in different regions, meteorological conditions, precursor emissions and the policy measures implemented in various cities.
The distribution of SO
2 concentrations reveals pronounced clustering patterns, with notably higher levels observed in Zhengzhou and its adjoining cities. In contrast, lower concentrations are prevalent in the southwestern and southern regions. A notable aspect, as evident from
Figure 8, is that despite the implementation of numerous national air pollution prevention and control measures, the SO
2 levels have not demonstrated a discernible decline. It is worth mentioning that only in 2022 did Shangqiu, Huaibei and neighboring cities witness a reduction in their SO
2 concentrations. Henceforth, it is imperative to accord greater attention to SO
2 in our ongoing efforts to mitigate atmospheric pollution.
During the period from 2000 to 2015, the CHAU exhibited distinct spatial distribution characteristics in terms of CO. The high-value areas of CO were primarily concentrated in Handan, Anyang and their surrounding cities. These regions, due to factors such as industrial development, dense traffic and energy utilization structures, experienced relatively high CO emissions. In contrast, the southwestern region emerged as an area with relatively low CO concentrations within the CHUA. This could be attributed to the regional industrial structure, traffic conditions and the implementation of environmental protection measures. However, by 2022, the spatial distribution pattern of CO had undergone significant changes. The high-value areas originally concentrated around Handan and Anyang began to spread towards the southeast and northwest, forming a bipolar distribution characteristic of “southeast–northwest”. This shift may have been influenced by various factors such as regional economic and social development disparities, climate change and the enforcement of environmental protection policies. Notably, cities in the western region experienced an upward trend in CO concentrations during this period. This could be attributed to the increasing traffic and industrial activities in the western region driven by economic growth and urbanization, leading to an increase in CO emissions. Conversely, cities in the southeastern region witnessed a decline in CO concentrations, potentially linked to the strengthened efforts in air pollution control and the optimization of energy structures in recent years.
3.3. Synergies between Carbon Emissions and Air Pollution
3.3.1. Coupling Coordination Degree Timing Characteristics
From 2000 to 2022, the coupling coordination degree of CEAP in the CHUA exhibited an upward trend, indicating a continuous strengthening of their coordination levels (
Figure 9).
In 2000 and 2005, the carbon emissions and air pollution of most cities experienced an uncoordinated state. During this period, most cities failed to effectively control carbon emissions and air pollution while pursuing economic growth, resulting in a low level of coordination between the two. In 2005, the coupling coordination degree of Anyang was the highest, which was 0.632, belonging to the primary coordination state. On the contrary, in 2005, Pingdingshan’s coupling coordination degree was extremely low, indicating a state of severe imbalance. This suggested that Pingdingshan faced significant challenges in promoting coordinated CEAP, necessitating the adoption of more proactive and effective measures for improvement.
In 2010, significant progress was achieved in the coordinated management of carbon emissions and air pollution in the CHUA. That year, 90% of the cities within the CHUA achieved a coordinated state in terms of carbon emissions and air pollution. Worth mentioning are the cities of Zhengzhou, Luoyang, Anyang, Hebi and Jiyuan, which attained good coordination with coupling coordination degrees of 0.835, 0.894, 0.894, 0.807 and 0.803, respectively. These results indicate their exceptional performance in managing carbon emissions and air pollution. Compared to previous years, the level of coordination in these cities has improved markedly. Notably, Luoyang’s coupling coordination degree increased by an impressive 140% during this period. The successful experience of Luoyang not only provides valuable lessons for other cities but also sets a model for promoting the synergistic governance of carbon emissions and air pollution across the entire CHUA and beyond.
In 2015, 80% of the cities in the CHUA were in a state of coordination, among which the coupling coordination degrees of Anyang and Jiyuan reached 0.902 and 0.927. The reason was that the implementation of the Action Plan for Air Pollution Prevention and Control in 2013 improved the synergies in CEAP. However, despite the positive progress made by most cities in coordinated governance, the performance of some cities was still unsatisfactory. For example, in 2015, the coupling coordination degree of Sanmenxia dropped to 0.166, indicating a severe imbalance. This suggests that Sanmenxia needs to take more proactive and effective measures to promote the synergistic effect of CEAP.
In 2022, a remarkable 87% of cities demonstrated a state of sync, illustrative of a widespread trend towards effective coordination. Within this group, six cities stood out as exemplars, boasting a coupling coordination degree that surpassed 0.8. Liaocheng, in particular, excelled with an exceptional coupling coordination degree of 0.98. This notable achievement represented a substantial leap forward, reflecting an improvement of 0.458 over its 2015 levels and firmly placing the city in a state of excellent coordination. Contrastingly, Bozhou found itself in the primary stages of the coordination, with a coupling coordination degree of 0.619. While this might seem modest in comparison, it is important to highlight the city’s impressive growth trajectory. Since 2015, the coupling coordination degree of Bozhou has increased by 77%. Meanwhile, Zhoukou also deserves recognition for its impressive turnaround. Its coupling coordination degree has increased by 75%, successfully transforming from being on the verge of coordination to achieving intermediate coordination. To elevate the regional coupling coordination to a higher level and achieve more harmonious and efficient development, we can provide strong support for high-quality regional development by rationally planning land use, adjusting urban layouts, promoting the application of clean energy and facilitating industrial upgrading.
3.3.2. Spatial Pattern of Coupling Coordination Degree
There is significant spatial heterogeneity in the coupling coordination degree of CEAP from 2000 to 2022, and the spatial characteristics of the coordination degree level are shown in
Figure 10.
In 2000, the coupling degree between urban CEAP in the CHUA generally exhibited a state of imbalance. More alarmingly, a staggering 36% of cities were in a state of severe imbalance. Eleven cities, including Nanyang, Liaocheng and Yuncheng, were among them, indicating an urgent need to address their environmental issues. These cities face multiple challenges stemming from unreasonable industrial structures, leading to high carbon emissions, inefficient energy utilization resulting in resource waste and the inadequate implementation of environmental policies causing lags in environmental governance. It is imperative for these cities to take decisive measures to accelerate the transformation of their economic development mode, optimize their industrial structure, improve energy efficiency and strengthen the implementation of environmental policies to achieve coordinated management of carbon emissions and air pollution. Only by doing so can they gradually overcome the predicament of severe imbalance and embark on a green and sustainable development path.
In 2005, although some progress was achieved in the coordination, the overall picture remained concerning. While the number of cities experiencing serious and moderate incoordination had receded compared to prior years, a staggering 83% of cities still struggled with incoordination. Notably, Xinyang and Pingdingshan stood out with particularly serious incoordination, exhibiting coordination degrees of merely 0.134 and 0.135, respectively. This incoordination state will have a profound impact on the development of the city. However, there are also some cities that have made positive progress in coordination. Anyang, Nanyang, Sanmenxia, Jiyuan, Hebi and Jiaozuo were among the first cities to initiate coordination, with coordination degrees ranging from 0.505 to 0.632. Despite these positive developments, there is still considerable room for improvement. These cities need to continue their efforts, further refine their collaborative governance mechanisms, enhance the level of coordination and make greater contributions to the sustainable development of the CHUA.
In 2010, the coordination level between CEAP showed a general upward trend. Among them, 23% of cities achieved good coordination, with Anyang and Luoyang attaining a coupling coordination degree of 0.894, ranking first in the CHUA. This significant achievement was the result of active efforts made by these two cities in optimizing the industrial structure, improving their energy efficiency and implementing environmental protection measures. However, despite the overall improvement in coordination within the CHUA, some cities still performed poorly in coordinating carbon emissions and air pollution. For example, Handan, Yuncheng and Bozhou remained in a state of imbalance. These cities’ economic development mainly relied on extensive development models, with relatively homogenous industrial structures dominated by traditional industries with high energy consumption and emissions. Simultaneously, these cities lagged behind in industrial transformation, with slow progress in developing emerging and green industries, being unable to effectively compensate for the environmental impact of traditional industries. This development model not only caused severe environmental damage but also constrained the long-term healthy development of the cities.
In 2015, 24 cities were in a coordinated state, with Anyang and Jiyuan achieving high-quality coordination levels. However, this coordinated state was not a ubiquitous phenomenon across all cities in the CHUA. Taking Handan City as an example, it was in intermediate coordination in 2010 but transitioned to primary coordination by 2015. This indicates that despite making some progress in environmental protection and sustainable development, Handan still needs to continue its efforts. To further enhance its coordination level, Handan must conduct a more in-depth analysis of its existing issues and take targeted measures for improvement. Meanwhile, the coordination statuses of some cities experienced significant declines. During this period, four cities shifted to a state of imbalance: Changzhi, Zhoukou, Luohe and Sanmenxia. Among them, Changzhi, Zhoukou and Luohe were at intermediate levels of imbalance, while Sanmenxia’s imbalance was more severe, reaching a state of severe imbalance. These changes serve as a reminder that maintaining a coordinated level between carbon emissions and air pollution is not easy and requires continuous effort and exploration of suitable development paths by each city.
In 2022, three cities emerged as exemplars of excellent coordination, namely Handan, Liaocheng and Zhengzhou. Cities such as Xingtai and Heze also demonstrated a relatively high degree of coupling coordination, which enhances environmental quality, generates economic and social benefits for the cities and fosters a mutually beneficial outcome. However, we should also recognize that some cities still face challenges in coordinating carbon emissions and air pollution. Cities such as Hebi, Xinxiang and Jiyuan are on the verge of imbalance, indicating that they still face certain challenges and difficulties in carbon emission control and air pollution governance. These cities need to conduct in-depth analyses of the root causes of the problems and take practical and effective measures to address them, such as addressing unreasonable industrial structures, improving energy efficiency and strengthening the implementation of environmental protection measures. By doing so, they can achieve coordinated governance of carbon emissions and air pollution at an earlier data.
3.4. Analysis of Driving Factors of Synergistic Benefit
To further investigate the spatial differences and influencing mechanisms underlying the synergistic benefits of CEAP, this paper selected industrial transformation, industrial structure, per capita GDP, level of external openness, population density, urban green coverage, energy consumption, NDVI, temperature and precipitation as influencing factors. The MGWR model was employed to delve into the underlying mechanism of its impact on the synergy of benefits in the CHUA. The descriptive statistical results are shown in
Table 5. There exists a notable spatial heterogeneity in the impact of PTI, VSI, POP, PGDP, GCR, OPEN, ECO and PRE on the co-benefits of CEAP in the CHUA. While the effects of TEM and NDVI on the synergy of CEAR did not show significant differences, the regression coefficients were around 0.093 and 0.210, respectively, and fluctuated in a small range. This indicates that the effects of TEM and NDVI are positive, and as the temperature rises and vegetation coverage increases, the synergy of CEAR may also improve accordingly.
Regression coefficients with spatial heterogeneity were visually analyzed (
Figure 11). The PTI to the synergistic benefit of CEAP is negative (
Figure 11a), mainly in the central and western regions, and the regression coefficient ranges from −0.820 to −0.238, indicating that industrial transformation has an inhibitory effect on the synergistic benefit. Specifically, the performances of Jiyuan, Luohe, Anyang, Hebi, Nanyang, Luoyang and Shangqiu are particularly prominent, with absolute values of regression coefficients greater than 0.670. In particular, the regression coefficient of Hebi reaches −0.820, indicating that whenever industrial transformation increases by 1%, the coupling coordination degree of Shangqiu decreases by 0.820%. This undoubtedly reminds us that we must be more cautious in promoting industrial transformation. Industrial transformation is a complex process that requires technological support such as clean energy technologies and energy-saving technologies. Firstly, the introduction of new technologies and equipment necessitates significant financial investment, often with a long return period. Secondly, during the adjustment of the industrial structure, it is necessary to consider the interconnectedness and dependence between different industries, as well as the regional differences between areas. All these factors can affect the synergistic benefits of reducing CEAP.
The impact of VSI on synergistic benefits varies in different cities (
Figure 11b), not only in terms of direction, but also in magnitude. For Sanmenxia and Yuncheng, the impact of the industrial structure on synergistic benefits exhibits a significant negative correlation, with regression coefficients of −1.553 and −1.304, respectively. This means that as the industrial structure is adjusted, the coordinated governance effect of CEAP in these cities not only fails to improve, but actually shows a downward trend. This is because these cities are primarily dominated by traditional industrial structures, often centered around high-energy consumption and high-emission industries such as coal, oil, steel and cement. These industries generate significant amounts of carbon emissions and air pollution during their production processes, thereby affecting the realization of synergistic benefits. However, Huaibei, Bozhou and Suchou are different. The impact of the industrial structure on synergistic benefits exhibits a significant positive correlation, with regression coefficients ranging from 1.110 to 1.467. This indicates that changes in the industrial structure can promote the coordination of CEAP. This phenomenon may be related to the level of urban development. More developed cities with more advanced industrial structures and technological levels can take more effective measures to address environmental issues such as CEAP. In contrast, less developed cities may face greater challenges in environmental governance due to relatively backward industrial structures and limited technological levels.
The impact of the POP on the synergistic benefits of different cities exhibits significant differences (
Figure 11c). The regression coefficients of Changzhi and Fuyang show a significant negative correlation, with correlation coefficients of −0.292 and −0.182, respectively. In these two cities, the increase in population density is often accompanied by a higher energy demand, and there is often an urban heat island effect that leads to poor air circulation and difficulty in dispersing pollutants. This, to a certain extent, inhibits the synergistic benefits of reducing carbon emissions and air pollution. However, there are also some cities that exhibit completely opposite effects on the impact of population density on the synergistic benefits. For example, the regression coefficients of Hebi, Xinxiang and Kaifeng are between 0.038 and 0.649, showing a significant positive correlation. This may be because while an increase in population size leads to an increase in direct and indirect energy consumption, on the other hand, the agglomeration effect resulting from the population concentration can improve technological levels to a certain extent, enhance resource utilization efficiency and promote the development of circular economy and green industries, thereby facilitating the synergistic benefits of reducing carbon emissions and air pollution.
Except Bozhou, the PGDP has a significant positive impact on the synergistic benefits of CEAP, and this positive promotion effect gradually increases from southwest to northeast (
Figure 11d), with regression coefficients ranging from 0.237 to 2.020. As the level of economic development continues to improve, individuals are demanding newer, greener and higher-quality methods of economic progress. The extensive economic development method is gradually abandoned, and the government and enterprises prefer to adopt sustainable development strategies, focusing on the balance between economic growth and environmental protection. Through promoting clean energy, strengthening energy conservation and emission reduction and developing a circular economy and other measures, these regions have effectively controlled the growth rate of CEAP while maintaining rapid economic growth.
The contribution of GCR to the synergistic benefits of CEAR in different cities cannot be ignored (
Figure 11e). For example, the regression coefficients of Changzhi, Liaocheng, Huaibei and other cities are between 4.280 and 8.979. This is because green vegetation can absorb substances such as CO
2 and PM2.5 in the air, inhibiting the synergistic benefits of carbon emissions and air pollution through the direct absorption and storage of carbon dioxide, the improvement of the urban heat island effect, the filtration and adsorption of air pollutants, and the provision of ecological services. However, the impact of GCR on other cities is completely different. For Xingtai and Kaifeng, the regression coefficients of GCR are −10.656 and −9.981, respectively, indicating a strong inhibitory effect. Due to the limited capacity of green vegetation to absorb pollution, pollution in most cities has already exceeded the upper limit for pollution reduction. It is far from enough to rely solely on expanding the green space to improve CEAP, and it may even have a counterproductive effect.
The impact of OPEN on the synergistic benefits of CEAR showed a negative correlation, with an average regression coefficient of −1.024 (
Figure 11f). This indicates that for every 1% increase in the level of opening up, the coordination of CEAP decreased by 0.133%. This is due to the fact that some regions prioritize economic development and opening up to the outside world, neglecting environmental protection factors. They undertake the transfer of high-energy-consuming, high-emission and highly polluting industries from other countries or regions and are unable to fully absorb and apply environmental protection technologies and clean energy technologies, thus inhibiting the synergistic benefits of CEAP.
Except Bengbu, the contribution of ECO to the synergistic benefits of CEAP in the CHUA is undoubtedly positive, with regression coefficients ranging between 0 and 1.850 (
Figure 11g). This may be because the energy consumption of cities mainly comes from conventional energy sources like coal, whose combustion generates significant amounts of carbon dioxide and other atmospheric pollutants, leading to a simultaneous increase in CEAP. At the same time, the industrial structure of these cities is relatively traditional, with a relatively large proportion of high-energy-consuming, high-emitting and highly polluting industries. This is also an important reason for the positive contribution to the synergistic benefits of CEAP in terms of overall energy consumption.
The impact of PRE on the synergistic benefits of CEAR is mainly concentrated in the affected cities in the northeast, showing a significant negative correlation, with regression coefficients ranging from −0.118 to −0.1094 (
Figure 11h). Specifically, rainfall may affect activities such as transportation and industrial production, ultimately resulting in elevated carbon emissions. During the process of rainfall, chemical substances such as nitrogen oxides and sulfur dioxide are released, forming fine particulate matter such as sulfuric acid mist and nitric acid mist, which leads to a deterioration of air quality. This affects the synergistic benefits of carbon emissions and air pollution.