4.3.1. Comparison with Prior Studies
The overreliance on socioeconomic regulation measures (e.g., improving energy sustainability and optimizing industrial technology), while ignoring the optimization of urban form, could significantly hinder the achievement of the “carbon peaking” target [
2,
4,
58]. Although a number of studies have investigated the internal mechanisms of urban form on greenhouse gas emissions, few have incorporated these findings into carbon emission forecasting. To address this deficiency, we proposed a new carbon emission forecasting model that simultaneously considers the influences of socioeconomic environment and urban form. The outcomes suggested that urban form has profound effects on carbon emissions. Compared with the baseline model, which considers only conventional socioeconomic factors, the incorporation of urban form factors can enhance the rationality of carbon emission forecasting.
A number of studies have focused on improving the accuracy of carbon emission forecasting, primarily through the optimization of algorithms. For example, Ren et al. [
24] proposed CSO-FLN, while Chen et al. [
52] put forward TPE-BP, and Wan et al. [
83] presented DIGM (1, N). While these studies have made notable contributions to improving accuracy, the models they constructed generally consider only socioeconomic variables. These studies have suggested the optimization of industrial and energy consumption structures as a significant strategy for mitigating carbon emissions. In contrast to previous studies, this study proposed a novel carbon emission forecasting framework that considers the joint influence of urban form and socioeconomic development. This could enhance the rationality of carbon emission forecasting. In addition to a more comprehensive consideration of the independent variables, another advantage of this study is the capacity to forecast carbon emissions at the municipal level while maintaining a high goodness-of-fit level. Despite the finding that Model II demonstrated an excellent fit for most cities, it is important to acknowledge that individual cases with large errors, particularly in Zhuhai, where the MAPE exceeded 20%, indicate that Model II falls short in adequately capturing the unique driving mechanisms of carbon emissions in Zhuhai City. In future research, we can attempt to apply more complex and advanced carbon emission forecasting models to explore whether we can further improve the accuracy of carbon emission forecasting results that take urban form into account.
The outcomes of the scenario forecasting indicated that Guangdong Province cannot fulfill its “carbon peak” in 2030 if the status quo or an extensive socioeconomic development pattern is adopted. This finding is in line with the conclusion of Ren and Long [
24]. A low-carbon development pattern is a crucial pathway for Guangdong Province to fulfill the planned “carbon peak”. In summary, it is recommended to control the pace of economic and population growth and optimize industrial technology and energy sustainability to limit the increase in carbon emissions. This finding was also in agreement with the outcome of previous studies [
77,
84,
85].
Despite the importance of carbon emission reduction measures from a socioeconomic perspective, steady economic growth remains a fundamental goal for many developing countries and regions [
36,
86]. Consequently, the implementation of carbon emission mitigation measures will be more challenging when economic growth is a priority. Furthermore, the significant reliance on fossil fuels in these regions poses a challenge to the implementation of energy efficiency measures intended to reduce greenhouse gas emissions through the restructuring of the energy sector [
5,
87]. In this regard, rational urban design represents a promising approach to reducing carbon emissions [
4,
38,
43]. The findings of this study indicate that carbon emissions will most likely increase if the urban form is not optimized.
In consideration of the typical and representative urbanization development pattern of Guangdong Province, the framework proposed in this study for forecasting carbon emissions by considering the joint influence of urban form and socioeconomic development can be extended to other regions. Specifically, the following three types of typical regions are applicable to this framework. Firstly, the developed coastal city clusters represented by the Yangtze River Delta exhibit similarities with Guangdong Province in that they are facing environmental pressures brought about by high-density urbanization; secondly, the major urban belts in the newly industrialized regions of Southeast Asia are exhibiting characteristics of urban expansion and industrial agglomeration that bear a strong resemblance to those of Guangdong Province’s development at the beginning of the twenty-first century. These regions have experienced significant foreign investment in the manufacturing sector and rapid expansion of built-up areas. This framework is also applicable to the core economic zones of emerging economies (e.g., Brazil, India), which also need to rationalize urban sprawl and develop low-carbon economic development plans to control carbon growth. The adaptability of the framework’s parameters and the ease with which data can be acquired contribute to its application advantage.
In order to further validate the universality of the model constructed in this study, the existing framework was followed to model carbon emissions in Jiangsu Province, China, which has an urbanization level comparable to that of Guangdong Province. Specifically, two groups of carbon emissions forecasting models were constructed: the baseline group and the improved group (
Table 7). These were achieved by selecting indicators of the same type and year. The findings indicated that the carbon emissions forecasting model, which considered the joint influence of urban form and socioeconomic development, exhibited an enhanced fit. Furthermore, the model’s fitting accuracy is comparable to that of Model II. These outcomes confirmed the validity and replicability of the framework proposed in this study.
4.3.2. Policy Recommendations for Carbon Emission Reduction
The results of this study suggest that the regulation of socioeconomic development can serve as an important strategy for the mitigation of carbon emissions. Therefore, it is suggested that the focus of socioeconomic development be on the quality of the process rather than its speed. It is essential to optimize the industrial structure, promote the development of industries with low energy consumption, and accelerate the development of high-tech industries and modern service industries. These policies can assist in reducing reliance on high-carbon industries. For example, Shenzhen has been a leader in the transition away from traditional energy-consuming industries, such as iron and steel and chemicals, which have been phased out much earlier in comparison to other cities of a similar population and economic scale, such as Guangzhou. Consequently, Shenzhen has achieved lower carbon emissions. Furthermore, the promotion of energy-saving technologies and equipment is essential for improving energy efficiency, while the accelerated development of clean energy sources (such as wind and solar power) is crucial for reducing reliance on fossil fuels. Specifically, the cities located in the eastern and western parts of Guangdong Province (Zhanjiang, Yangjiang, Shantou, Shanwei, etc.) are characterized by a long continental coastline and abundant wind resources. These regions have the potential to reduce their reliance on traditional energy sources by developing offshore wind farms. Cities in the northern part of Guangdong Province (e.g., Shaoguan, Qingyuan) are characterized by abundant solar radiation and land resources, consequently rendering them highly conducive to the implementation of photovoltaic (PV) projects. In economically less developed regions of Guangdong Province, high energy-consuming industries such as iron and steel, cement, and minerals are significant contributors to the local economy, and their complete elimination in the short term is challenging. Therefore, in order to achieve a balance between economic development and carbon emissions, it is recommended that these regions proactively introduce advanced energy technologies to improve energy efficiency. In addition, the government should formulate stringent emission standards to encourage energy-consuming industries to increase their investment in emission reduction.
As the primary economic development region within Guangdong Province, the Pearl River Delta (PRD) is a typical example for the implementation of carbon reduction initiatives, given its generally high carbon emissions. It is recommended that the cities in the PRD region strengthen exchange and collaboration on low-carbon technologies and management experiences and implement joint emission reduction strategies. For example, it is recommended that a regional low-carbon technology sharing platform be established to facilitate the sharing of the outcomes of low-carbon technological innovations and practices among cities. Furthermore, it is recommended that regional emission reduction targets be formulated jointly in order to improve the efficiency of emission reduction. In addition, the substantial population influx is an important factor contributing to the high carbon emissions observed in the PRD region. In particular, those cities with high population density, such as Guangzhou and Foshan, may exacerbate the carbon emission situation if population growth is not adequately managed.
In addition to the traditional socioeconomic measures for carbon emission reduction, rational urban design can substantially contribute to low-carbon urban development. First, the PLADJ reflects the compactness of land use. Excessive agglomeration of urban land can intensify the heat island problem. This may cause a rise in the use of cooling equipment, which in turn generates higher energy demand and carbon emissions [
58,
88]. Second, the LSI characterizes the shape complexity of urban land. An irregular urban shape may result in the dispersion of urban functional areas. This can further reduce the accessibility of public transport and increase people’s propensity to use private vehicles for transportation [
31,
89]. Consequently, the tendency of urban shape to be more complex increases the energy consumption of people traveling by transport [
23,
25]. Third, the PD reflects the fragmentation of urban land. Our results indicate a negative correlation between PD and carbon emissions. Several studies have suggested that increased urban fragmentation will result in longer commuting distances, thereby increasing carbon emissions [
39,
59]. Nevertheless, other studies have indicated that urban fragmentation may act as a deterrent to the increase in carbon emissions within mixed-use and industrial areas [
32,
90]. For instance, in the cases of Dongguan and Shenzhen, increased urban fragmentation curbs carbon emissions [
54].
Based on the results of this study, a number of recommendations are presented for consideration in future urban planning initiatives. These recommendations are centered on three primary aspects, including urban compactness, urban shape complexity, and urban fragmentation. First, it is necessary to simplify the shape complexity of urban land. By rationally delineating urban functional zones (such as residential, commercial, and industrial), the overlap and mixing of urban functions will be reduced, and the urban structure will become more clearly defined. In addition, it is essential to establish an efficient transportation network and direct the development of urban land towards a more regular configuration. As a result, the accessibility and efficiency of the transportation system will be improved. Furthermore, while the results of this study indicate a positive correlation between urban compactness and carbon emissions, it would be beneficial to increase urban compactness in regions where urban land is more dispersed. This is because a compact urban form typically implies a more efficient use of infrastructure [
1,
33]. Nevertheless, in regions where urban land is excessively compact, a polycentric urban form should be developed. For example, the construction of satellite cities by Guangzhou and Foshan could serve to disperse the population and industries from the primary urban areas. This strategy is expected to reduce inter-regional commuting and increase green space, thereby mitigating traffic congestion and the heat island effect [
27,
36]. In the case of cities such as Dongguan and Shenzhen, where mixed-use and industrial areas are concentrated, it is recommended to moderately increase the fragmentation of urban land to reduce carbon emissions. Specifically, feasible measures include the establishment of a decentralized green space system and a network of ventilation corridors. These measures are expected to enhance carbon sink capacity and mitigate the urban heat island effect.
The aforementioned policy implications and recommendations are considered credible prior to 2035, as the scenario parameters were strictly established in accordance with the stipulations of the “Strategy Profile”. The scenario parameters for the period after 2040 were determined through trend extrapolation. In this case, the applicability of these recommendations depends on the alignment between future and current development trends, including policy continuity, socioeconomic stability, and technological development. If inconsistencies are identified, updated data will be required for further analysis. It is recommended that policymakers consider the forecasting results after 2040 as risk warnings rather than precise references for planning. This is especially important given that the forecasting horizon exceeds the time span of the sample.
In summary, the marginal contribution of this study lies in the development of a novel framework for carbon emission forecasting, which integrates urban form factors with socioeconomic factors. This framework addresses a specific knowledge gap in the field of carbon emission forecasting by incorporating the impact of urban form. Through an empirical case study in Guangdong Province, we have validated the effectiveness of the framework and also identified significant advantages in terms of forecasting accuracy. The carbon emission forecasting method proposed by this study is highly applicable, especially in regions experiencing rapid socioeconomic growth and urban expansion. These regions will encounter considerable carbon emission challenges if rational planning for urban forms is not implemented. In this regard, the new findings of our study could inform the promotion of low-carbon management policies and urban design.