Introduction

Resource scarcity and waste siege are posing serious challenges to global municipal waste management and environmental governance [1, 2]. In the context of global low-carbon and green transformations, achieving sustainable waste management is a critical issue that urgently needs to be addressed [3, 4]. The zero waste (ZW) strategy was developed to alleviate the environmental burden and resource depletion caused by solid waste [5]. The core of ZW lies in promoting responsible production and consumption patterns, as well as resource reuse and efficient recycling, striving to avoid waste incineration and arbitrary discharge, thereby maximizing the efficiency of natural resource utilization and minimizing negative impacts on the ecological environment [6-8]. Looking back at history, Canberra, Australia, set an example in 1995 and became the world’s first city to implement the ZW strategy, leading a global environmental trend. Since then, many countries, organizations, and enterprises have responded and devoted themselves to ZW practices [2, 9]. The zero waste city (ZWC), a cutting-edge concept of sustainable urban development, has become a goal pursued in many countries [10, 11]. ZWC is not only an important measure to promote collaborative efficiency in reducing pollution and carbon emissions but also the main way to achieve the high-quality development of a green economy. Therefore, to curb solid waste problems from the source and promote the construction of an environmentally friendly society, it is urgent to conduct a more in-depth exploration of ZWC.

As the second-largest economy in the world, China is facing serious waste pollution problems due to industrialization and urbanization in the past few decades [12]. It is estimated that China adds more than 10 billion tons of solid waste annually, with a total storage volume of about 70 billion tons [13]. The various problems caused by solid waste, such as high generation intensity, low resource utilization, and illegal dumping incidents, urgently need to be addressed [14]. The Ministry of Ecology and Environment of China issued the “Work Plan of the ZWC Pilot Program” in 2018, which marked the launch of the ZWC strategy. Sixteen local authorities and districts were identified as ZWC pilot areas in 2019 and were broadened to 113 cities in 2022 [15, 16]. These policy initiatives demonstrate China’s strong commitment to ZW management. Exploring Chinese ZWC is of great importance to addressing the waste pollution problem in China and the implementation of ZW strategies in other developing countries.

Zero waste performance (ZWP) refers to the evaluation of the effectiveness achieved in reducing solid waste at the source, utilizing resources, and harmless disposal through the implementation of a series of measures and policies in the process of building a ZWC. Understanding ZWP is not only one of the main tasks of ZWC construction but also provides theoretical support for subsequent policy decisions [17]. The differences in economic structure and resource endowment may cause different demands for solid waste disposal, resulting in discrepancies in waste management [13]. Exploring the regional gaps in ZWP is of practical significance for the balanced promotion of ZWC construction. Moreover, capturing the evolutionary trends of ZWP is critical to the further expansion of ZWC pilots in the future. Therefore, it is necessary to evaluate ZWP in China and to analyze its regional differences and evolutionary trends.

Previous studies related to the measurement of ZWP can be divided into two categories. One is to measure the effectiveness of waste management through a series of specific indicators, such as per capita waste generation, diversion ratio, collection efficiency, and recovery rate, as a single quantitative standard [18]. Some scholars have criticized this outcome-oriented assessment approach for failing to adequately reflect the complexity and dynamics of the waste management process [19]. Zaman and Lehmann [20] pointed out that even achieving a 100% diversion rate does not necessarily mean achieving the goal of ZW. The second is to use comprehensive evaluation indicators to measure ZWP. For example, the “zero waste index” was proposed by Zaman and Lehmann [17]. This tool can measure ZWC performance based on the substitution potential of recycled, renewable resources for virgin resources and has been applied in several case studies [21]. Cong et al. [22] used the undesirable super-efficiency model to assess the efficiency of ZWC constructions. Zaman [23] constructed an evaluation index system for ZWP from four dimensions: socio-cultural, managerial, economic, and environmental.

There are two types of studies related to ZWP evaluation objects. One type of study evaluated ZWP at the regional level. For example, Han et al. [13] investigated the performance of ZWC in 31 provinces in China from 2010 to 2019 and explored influencing factors in terms of economy, technology, resource endowment, and education. Peng et al. [24] studied the influence of environmental protection investment and green innovation on solid waste management capacity in 30 provinces in China. The other type of study looked at the city level. From the perspective of the “water-energy-food” system, a framework for the assessment of ZWC was constructed by Zhang et al. [25], and the similarities and differences between China (Beijing, Shanghai, and the Greater Bay Area city cluster) and other countries (San Francisco, New York, and Tokyo) were compared. Taking Xuzhou City as an example, Wen et al. [26] explored the construction status and barrier factors of mining-based ZWCs in China.

Although a number of studies have examined ZWP, there are still some shortcomings. First, previous studies mainly focused on ZWP evaluation at the provincial level, while few assessed ZWP at the city level in China. The rare studies focusing on ZW at the city level are limited to qualitative analysis and lack quantitative analysis, which prevents an overall understanding of China’s city ZWP. Since the construction of a ZWC is city-based, measuring ZWP at the city level can offer a more intuitive understanding of ZWC construction. Second, there is a lack of studies analyzing regional differences in China’s city ZWP and even fewer studies on its evolution trends. That is, the existing studies failed to provide information on the differences and evolution of ZWP in Chinese cities. Exploring regional differences and evolution trends is significant, not only for narrowing the disparity in ZWP but also for further promoting ZWC construction in China and other developing countries.

Based on the above considerations, this paper aims to fill the above research gap by answering the following three questions. (1) What is ZWP at the city level in China?

(2) What are the differences among regions? (3) What are the evolution trends of ZWP? Compared with previous works, the present study has two potential innovations: First, different from previous studies on the evaluation of ZWP at the provincial level, this paper achieves a horizontal comparison at the city level and provides a comprehensive understanding of ZWC construction in China. Second, this study attempts to explore the dynamic evolution and shifting trends of ZWP at the city level in China. This study is one of the first batches of literature to examine the regional differences and dynamic evolution of China’s ZWP. The findings in this paper offer theoretical support and decision-making reference for further expansion of the ZWC pilot. It is of great significance for narrowing the regional differences in China’s ZWP and promoting the construction of ZWC in a balanced manner.

Materials and Methods

Results and Discussion

Overall Evaluation of the ZWP

Fig. 1 reports the trends of ZWP at the city level in China and four major regions from 2010 to 2020. Overall, China’s city ZWP at the city level improved from 0.0892 to 0.2358 during the observation period, with an increase of 10.21% per year on average. From a regional perspective, only the average of waste management in the eastern region is larger than the national mean, while the other three regions have a lower average than that of the country. The results indicated that China’s city ZWP is gradually increasing.

China’s city ZWP gradually increased, which agrees with the result of Han et al. [13]. The improvement in ZWP may be attributed to the Chinese government’s high emphasis on solid waste management. On the one hand, a series of environmental regulatory instruments have been adopted for solid waste pollution prevention and control, with remarkable results. For instance, the extended producer responsibility system has been adopted, and mandatory domestic waste separation has been promoted [27]. On the other hand, residents and enterprises have become aware of environmental protection and actively participate in waste management, promoting waste recycling and resource utilization [28, 29]. Despite the increase in China’s city ZWP, there is still significant room for improvement. This finding is consistent with the opinion of Wen et al. [30]. The construction of ZWC in China is at a preliminary stage and has not yet been implemented nationwide [13], which may be a potential explanation for the relatively low level of China’s city ZWP.

The spatial distribution of ZWP at the city level in China displays the characteristics of “East > Central > West > Northeast”. The eastern region takes the lead in ZWP, which echoes the findings of existing literature [13, 30]. The possible reasons are as follows: First, the eastern region has more efficient solid waste management than other regions and can efficiently convert resource inputs into outputs [31]. Second, the eastern region is economically developed and has invested heavily in waste management (e.g., sanitation vehicles and waste incineration plants), which offers the fundamental guarantee for ZWC construction. The ZWP of the central region gradually approaches the national average, second only to the eastern region, showing a significant catching-up effect. This may be attributed to the “Rise of Central China” strategy, which has led to industrial structure optimization in the central region [32], reduced dependence on natural resources, and curbed solid waste emissions [33, 34]. The western region is prone to solid waste hoarding due to its fragile ecology [13]. In addition, there are many obstacles to solid waste management in the western region, such as more illegal solid waste disposal practices, lower utilization rates, and backward construction of management institutions and teams [35]. In the northeast region, shrinking cities and severe population exodus have led to increased operating share costs for urban infrastructure and a lack of waste collection and transportation facilities [36]. This may hinder the development of ZW management.

Fig. 1.

ZWP at the city level in China and four regions from 2010 to 2020.

The Evolution Trend of ZWP

Time Evolution Trend

Fig. 2 portrays the kernel density curves of China’s city ZWP in 2010, 2013, 2017, and 2020. It can be found that the curve shifted to the right, indicating that China’s city ZWP has improved. The main peak of the curve increased in height and narrowed in width from 2010 to 2020, which means that the aggregation of China’s city ZWP has improved, and its absolute difference has decreased. The obvious right trailing feature was found on the curve in 2010, which weakened in 2020, showing that the difference in China’s city ZWP decreases. The kernel density curves exhibit a double-peaked curve throughout the observation period; that is, the ZWP of most Chinese cities is distributed around two different scores (0.05 and 0.3). This phenomenon can be referred to as the polarization of ZWP in Chinese cities.

The kernel density curves of the four regions in 2010, 2013, 2017, and 2020 are reported, which shows the evolutionary trend of city ZWP in four regions (Fig. 3). For the eastern region, the main peak height rises, and the peak width narrows from 2010 to 2020, illustrating a downward trend in the absolute gap of ZWP in the eastern region. The right trailing feature gradually weakened, indicating a decrease in the difference in the eastern region. The double peak evolved into a single peak, implying a weakening polarization in the eastern region.

Fig. 2.

Kernel density curve of China’s city ZWP.

Fig. 3.

Kernel density curve of city ZWP in the four regions.

Table 4.

Global Moran’s I of China’s city ZWP.

Year	Moran’s I	E(I)	Sd(I)	Z-vale	P-value
2010	0.132	-0.006	0.064	2.151	0.032
2011	0.122	-0.006	0.064	1.986	0.047
2012	0.167	-0.006	0.064	2.692	0.007
2013	0.222	-0.006	0.064	3.532	0.000
2014	0.231	-0.006	0.065	3.676	0.000
2015	0.235	-0.006	0.065	3.737	0.000
2016	0.268	-0.006	0.065	4.251	0.000
2017	0.277	-0.006	0.065	4.392	0.000
2018	0.247	-0.006	0.064	3.923	0.000
2019	0.247	-0.006	0.064	3.928	0.000
2020	0.215	-0.006	0.064	3.449	0.001

Unlike the eastern region, the other three regions have been showing an obvious double-peak feature, which indicates that there has been a polarization of ZWP in the other three regions from 2010 to 2020. In the western region, for example, the ZWP of Chongqing, Chengdu, and Xi’an reached 0.37 or above in 2020, while 18 cities have not yet reached 0.07. It can be seen that there is a huge difference in ZWP. The cities with higher ZWP usually belong to provincial capitals or municipalities directly under the central government. This finding coincides with the result of Zhao et al. [38], who found that Taiyuan, the capital city in Shanxi Province, had a higher level of ZWP than other non-capital cities.

Spatial Evolution Trend

The spatial correlation of ZWP at the city level in China was verified, and the results are shown in Table 4. Moran’s I was significant (p<0.05) and fluctuated between 0.122 and 0.277, which means that the spatial correlation of China’s city ZWP is significantly positive.

Based on the quartiles of the level of ZWP, all sample cities were classified into four states, namely, S1, S2, S3, and S4, which represent the city’s ZWP from poor to good. The transfer probability matrices are shown in Table 5. The results of the conventional Markov chain show that the likelihood that S1, S2, S3, and S4 will remain the same in the next year is 72.81%, 67.27%, 78.22%, and 90.84%, respectively. The relatively high probabilities on the diagonal of the transfer matrix demonstrate the strong stability of ZWP at the city level in China under the condition that the sample city is seen as an independent unit. The probabilities of S1, S2, and S3 shifting upward are 27.19%, 17.38%, and 19.2%, respectively. The probabilities of a downward shift for S2, S3, and S4 are 15.25%, 2.58%, and 9.16%, respectively. It can be seen that the likelihood of upward transfer is generally higher than the likelihood of downward transfer, suggesting that the ZWP at the city level in China displays an improving trend.

Table 5 indicates that the spatial Markov transfer matrix has the following features: First, the probabilities on the diagonal are higher than the probabilities on the non-diagonal, which means China’s city ZWP remains stable when considering the effect of adjacent cities. Second, the shifting probabilities are concentrated near the diagonal, indicating that the shift of ZWP occurs mainly in adjacent states, and it is hard to make the jump to transition in a short time. Third, the state transfer of China’s city ZWP has a spatial spillover effect. That is, the lower the ZWP in the neighboring cities, the greater the transferring probability of the city to a lower state; the higher the ZWP in the neighboring cities, the greater the transferring probability of the city to a better state. For instance, the transfer likelihood of S3 to S2 is 2.11%, while the corresponding transfer probability increases to 10.34% when adjacent to S1. The probability of S1 shifting to S2 is 22.27%, but the corresponding transfer probability increases to 26.67% when adjacent to S4.

In terms of spatial evolution, the state of China’s city ZWP is relatively stable and usually shifts between adjacent states. As mentioned by Li and Li [39], realizing a “Zero Waste Society” requires long-term and arduous efforts. Moreover, the evolution of China’s city ZWP has spatial spillover effects. The probability of the city transforming to higher levels of ZWP increases when neighboring cities have higher levels. The probability of the city evolving to lower levels of ZWP increases when adjacent to cities with lower levels. This finding is similar to the results of previous studies. The positive spatial correlation of solid waste emissions was revealed in the study of Guo and Liu [21]. Peng et al. [24] found that the spatial correlation of solid waste management capacity is significant, and the impact of green innovation and environmental investment on solid waste management capacity has a positive spatial spillover effect. The cities with high levels of ZWP may play a demonstration role by transmitting advanced solid waste disposal technologies and management models to surrounding areas, which in turn will lead to ZWP in neighboring cities.

Table 5.

The Markov transfer probability matrix of China’s city ZWP.

Type of space	Status at year t	Status at year t+1
		S1	S2	S3	S4
No lag	S1	0.7281	0.2227	0.0364	0.0128
	S2	0.1535	0.6727	0.1445	0.0293
	S3	0.0047	0.0211	0.7822	0.192
	S4	0	0.0051	0.0865	0.9084
S1	S1	0.8261	0.1304	0.029	0.0145
	S2	0.1765	0.6471	0.1569	0.0196
	S3	0	0.1034	0.7241	0.1724
	S4	0	0	0.0435	0.9565
S2	S1	0.721	0.2403	0.0386	0
	S2	0.1696	0.6784	0.1345	0.0175
	S3	0.0244	0.0488	0.7805	0.1463
	S4	0	0.0175	0.0877	0.8947
S3	S1	0.7067	0.2333	0.04	0.02
	S2	0.1263	0.6684	0.1579	0.0474
	S3	0	0.004	0.7968	0.1992
	S4	0	0.0044	0.1135	0.8821
S4	S1	0.6	0.2667	0	0.1333
	S2	0.1935	0.7097	0.0968	0
	S3	0	0.0154	0.7538	0.2308
	S4	0	0	0.0238	0.9762

Conclusions

This paper evaluates China’s city ZWP from 2010 to 2020 and explores its regional differences, sources of differences, and dynamic evolution. The results indicate that China’s city ZWP shows an upward trend from 0.0892 in 2010 to 0.2358 in 2020, but currently, China’s city ZWP is still relatively low. From the regional perspective, China’s city ZWP has the feature of “East>Central>West>Northeast”. The overall regional disparity of ZWP at the city level in China tends to decrease. The overall difference in China’s city ZWP mainly originated from inter-regional differences. The aggregation degree of China’s city ZWP increases, and the absolute difference tends to diminish. The evolutionary characteristics of city ZWP vary in each region. The polarization of ZWP in the eastern region diminishes. On the contrary, the polarization phenomenon becomes severe in the other three regions. There is the club convergence characteristic in China’s city ZWP. Most transfers of China’s city ZWP occur at adjacent types, and it is hard to make the jump shift in the short term. The shifting trends of China’s city ZWP show the spatial spillover effect.

Combining the conclusions derived from this paper, the following policy recommendations are proposed. ZWP can be improved by reducing regional differences, avoiding polarization, and outlining the role of demonstrators. First, regional differences brought about by resource endowment and economic level should be fully recognized. It is important to focus on implementing a diversified, graded, and dynamic ZWC strategy. The urban characteristics of each region can be taken into account to formulate targeted fiscal measures to attract the inflow of talent and high-tech enterprises, stimulate market vitality, and thus promote sustainable waste management. Second, improving ZW construction in third- and fourth-tier cities is crucial to alleviating the polarization phenomenon. The first batch of ZWC pilot cities in China represent different prefecture-level cities. For example, Panjin represents a resource-depleted city; Xining is a representative of an ecologically fragile and economically backward city. Summarizing and disseminating the experience of these pilots may be a good way to improve ZWP in third- and fourth-tier cities in China. Third, the role of high-level cities in leading the surrounding cities should be given full play. The ZWC cluster can be created to achieve contiguous development by publicizing and sharing the lessons learned from waste treatment technologies and management models. Cities with low levels of ZWP should actively introduce advanced waste treatment technologies and break down technical barriers. Industrial cooperation and structure optimization should be strengthened to promote deep integration between industries.

Although this paper provides some insights into promoting ZWP at the city level in China, it still has certain shortcomings. First, due to the limitation of data disclosure and lags in the effects of pilot policies, the study sample only covers 173 cities from 2010 to 2020. Subsequent studies could explore the evolutionary trends in ZWP after 2020, as well as comparative analyses of ZWP before and after the implementation of the pilot policy. Other indicators or alternative data can also be considered to expand the scope of the study sample in the future. Secondly, the regional differences and evolutionary trends of ZWP are focused on in this paper, and there are many other worthy research directions in related fields, such as the relationship between technological innovation and ZWP and spatial spillover effects.