Remediation Technologies of Contaminated Sites in China: Application and Spatial Clustering Characteristics

Abstract

Screening remediation technologies through the lens of green, low-carbon, and sustainable development is crucial for contaminated land management. To better understand the applicability of remediation technologies, this paper explored their application in China based on a survey of 643 cases. By employing coupled analysis and local spatial autocorrelation methods, this study reveals the alignment between remediation technologies and pollutants, along with their spatial distribution and clustering patterns. Specifically, the four primary remediation technologies identified were cement kiln co-processing (CKCP), chemical oxidation/reduction (CO/CR), thermal desorption (TR), and solidification and stabilization (S/S), collectively accounting for over 90% of the cases. Additionally, our findings indicated significant variation in how different pollutants respond to remediation technologies, largely attributable to the characteristics of the pollutants. We observed High–High clustering patterns for CKCP, CO/CR, TR, and S/S. These were predominantly found in Jiangsu, Chongqing, Shandong, and Guizhou for CKCP and CO/CR and in Hebei, Jiangsu, Shanghai, and Chongqing for CO/CR. TR exhibited a High–High clustering in Shanghai, as did S/S. This research contributes to reducing the economic and resource costs associated with the trial-and-error of screening contaminated soil remediation technologies, offering valuable scientific and technological guidance for contaminated land regulation.

1. Introduction

Land contamination is an urgent global environmental concern due to rapid industrialization and urbanization [1]. The complex chemical mixtures spilled and leaked from industrial waste, chemical plant remnants, metal smelting, and mining pose threats to human health and the environment, hindering sustainable land use [2]. In 2023, public data from China’s government procurement and provincial and city-shared resource networks revealed the initiation of 4568 soil and groundwater remediation projects, with investments of around 22.909 billion RMB (renminbi, the official currency of China) [3]. Thus, remediation has become a critical national task in China, emphasizing the urgent need for efficient practices.

In response, governments and environmental regulators worldwide are dedicated to adopting green, low-carbon strategies for sustainable land remediation [4,5]. A broad spectrum of soil remediation technologies exists, exemplified by the United States Superfund’s application of nearly 30 technologies across 1468 contaminated sites. From the perspective of disposal sites, the remediation technologies of contaminated sites include in situ remediation technologies and ex situ remediation technologies, including physical remediation technologies, chemical remediation technologies, bioremediation technologies, and physicochemical remediation technologies from the perspective of remediation principles. However, selecting suitable technologies for contaminated site remediation remains challenging, given the complexity of site conditions, diverse contaminants, global soil variety, and varying remediation standards [6].

Hence, the option of remediation technologies for contaminated sites depends on the site characteristics, socio-economic background, and regulatory systems [7,8]. Consequently, adopting suitable technologies is crucial for minimizing remediation costs and enhancing efficiency. This complexity has necessitated diverse research methods, such as bibliometric analysis, mathematical modeling, optimization algorithms, and technology assessments [9]. The research content mainly focused on identifying the development trend of contaminated site remediation technologies, effectiveness evaluation, environmental impact and economic evaluation, technology innovation and optimization, case studies, and field trials [6,10,11]. Relevant studies have been conducted to clarify the trends and removal techniques of environmental pollutants, analyze the global research and application trends of phytoremediation techniques, and discuss the properties of ultrasound-assisted degradation of organic pollutants [12,13]. Song et al. comprehensively evaluated the effectiveness of in situ remediation of soils and sediments contaminated with organic pollutants and heavy metals (HMs) from an environmental perspective [14]. Some scholars reviewed the life cycle assessment of soil remediation technologies and assessed the environmental and socio-economic sustainability of remediation strategies for large-scale contaminated sites in China [15,16]. Xu et al. modified zero-valent iron (ZVI) with sodium carboxymethyl cellulose (CMC) to investigate the feasibility of using a new class of stabilized ZVI nanoparticles for in situ reductive immobilization of Cr(VI) in water and sandy loam soils [17]. These studies involved the development and optimization of the technology and a comprehensive consideration of the environmental, economic, social, and policy aspects of implementing the technology.

Furthermore, the intricate and systemic nature of site remediation necessitates a detailed analysis of how contaminants interact with remediation technologies, which is crucial for refining and enhancing the remediation process [18]. For instance, chemical reduction technology mainly applies to treating non-volatile organic pollutants, with their effectiveness hinging on pollutant properties and environmental conditions [7,19]. We will provide a helpful perspective showing the degree of match between various remediation technologies and specific pollutants. Moreover, spatial autocorrelation analysis, a critical tool in soil remediation, is used in various applications such as priority setting, health risk assessment, and source prevention and control [20,21,22]. However, in the context of remediation technologies for contaminated sites, spatial factors are often overlooked despite their importance. The local indicator of spatial association (LISA) provides a statistical method for detecting local spatial autocorrelation in spatial datasets. It can reveal clustering tendencies in spatial data on a regional scale. Significant geographical disparities in remediation technology implementation arise due to variations in economic development, infrastructure, and policy across regions [23]. Elucidating how remediation technology fosters stability and sustainable practices highlighted the resource value of contaminated site remediation. Using LISA allowed us to explore the spatial distribution and aggregation patterns of remediation technologies across regions. This, in turn, facilitated horizontal comparisons of remediation strategies within regions. These comparisons were crucial for resource allocation and environmental policy formulation, ensuring region-specific application strategies.

Being a prominent industrial nation, China is renowned for its extensive inventory of contaminated sites in need of remediation. Accordingly, to acquire a more comprehensive insight into the application of remediation technologies within China, we conducted a study encompassing 643 contaminated sites. The primary objectives of this study were to evaluate the prevailing practices and technologies utilized for site remediation, investigate the spatial clustering patterns linked to these practices, and elucidate the varied remediation methods implemented across different regions of China. This study offers crucial insights into the sustainable management of contaminated lands in China. It helps to enhance the understanding of specific remediation technologies’ efficiency across various geographic regions, thereby helping to reduce ambiguity and costs associated with remediation projects and providing valuable scientific and technical guidance for policymakers and professionals.

2. Materials and Methods

2.1. Data Collection

The research aims to gather literature and case studies related to soil remediation technologies for contaminated sites. We conducted searches using the keywords “soil pollution” and “remediation technology” across multiple databases and platforms, including China Knowledge, Baidu Search, and the Soil Environment Information Publication Platform for Construction Land Use (http://www.spers.cn (accessed on 31 August 2023)). We gathered pertinent data from diverse sources, such as academic papers, investigation and assessment reports, and open project declarations.

2.2. Data Collation and Cleaning

To minimize random data errors and enhance the relevance and reliability of our conclusions, we established specific selection criteria for literature and cases. These criteria included: (1) the study area being a polluted site in China; (2) the presence of potential risks and pollutants of concern at the site; (3) the literature and cases containing information about the site’s location and remediation technologies; and (4) the presence of documented and extractable relevant data in the literature and cases. Applying these criteria, we identified 643 compelling remediation cases. Subsequently, we employed SPSS v26.0 (Chicago, IL, USA) to process and statistically analyze the gathered remediation control cases for polluted sites in China across multiple dimensions. Additionally, we utilized Origin 9.0 software to generate pie charts and stacking diagrams. These visuals enabled us to analyze and visualize soil remediation technology in polluted sites in China. These visualizations facilitated the comprehension of the relationship between remediation technology and pollutants, offering a distinct visual representation of the impact of remediation technology use.

2.3. Local Spatial Autocorrelation

Local spatial autocorrelation analysis is an effective means of exploring local spatial aggregation of categorical features, used to explore the degree of spatial variation and significance of the frequency of application of remediation techniques in neighboring provinces, primarily measured by the local Moran’s I statistic and LISA [24]. The local Moran’s I calculation method is as follows:

$$I_L=\frac{n\times (x_i-\stackrel{-}{x}\left)\sum _{j=1}^n{w}_{i,j}\right(x_j-\stackrel{-}{x})}{\sum _{i=1}^n\sum _{j=1}^n{w}_{i,j}\times {\sum }_{i=1}^n{(x_i-x_j)}^2}$$

(1)

where $I_L$ is the local Moran’s I; n denotes the number of provinces and municipalities; x_i and x_j are the attribute values of locations i and j; $\overline{x}$ is the average of the attribute values of all i and j; w_ij denotes the weight assigned to each raster measurement cell. A binary symmetric spatial weight matrix W is usually used to express the regional proximity relationship of n locations. If j is one of the four cells directly adjacent to i, then w_i,j is 1. If it is any other cell or the cell has no data, then w_i,j is 0.

$$W=\left[\begin{array}{ccc}{W}_{11}& \cdots & W_{1n}\\ ⋮& & ⋮\\ W_{n1}& \cdots & W_{nn}\end{array}\right]$$

(2)

Meanwhile, the significance of the $I_L$ obtained from the calculation was tested using the Z-distribution with the test formula:

$$Z_I=\frac{I-E\left(I\right)}{\sqrt{\mathrm{V}\mathrm{a}\mathrm{r}I}}$$

(3)

$$E\left(I\right)=-\frac{1}{n-1}$$

(4)

$$\mathrm{V}\mathrm{a}\mathrm{r}\left(I\right)=E\left(I^2\right)-E^2\left(I\right)$$

(5)

where $E\left(I\right)$ and $\mathrm{V}\mathrm{a}\mathrm{r}\left(I\right)$ are the expected values of $I_L$ and the variance of $I_L$. The LISA maps obtained from the local Moran’s I can be classified into five cluster types [25]. High–High (or Low–Low) indicates a spatial positive correlation between having a high (low) application frequency and its neighboring area also having a high (low) application frequency. High–Low and Low–High regions are spatially negatively correlated. High–Low indicates that a province with a higher frequency of application is surrounded by provinces with a lower frequency of application. Low–High indicates that a province with a lower frequency of application is surrounded by provinces with a lower frequency of application.

The data on the practice of remediation technologies for contaminated sites in China were visualized in terms of spatial distribution by ArcGIS v10.5 (Esri, Redlands, CA, USA). We further selected widely recognized and representative remediation technologies—cement kiln coprocessing (CKCP), chemical oxidization/reduction (CO/CR), thermal desorption (TR), and solidification and stabilization (S/S)—and conducted univariate spatial correlation analyses with GeoDa v1.8 (Chicago, IL, USA) to examine their spatial aggregation patterns.

3. Results and Discussion

3.1. Application Status of Remediation Technologies for Contaminated Soils

Since the remediation of contaminated sites has attracted attention for decades, many practitioners have explored a variety of remediation technologies through their joint efforts [26]. The appropriate remediation techniques have a positive impact on saving remediation costs and improving remediation efficiency. Among the 643 remediation cases we collected, more than half of the contaminated sites use ex situ remediation techniques (approximately 88.04%), compared to 52 contaminated sites using in situ remediation techniques, which accounted for about 7.23%. It was worth noting that 34 contaminated sites applied both in situ and ex situ remediation techniques, all of which were characterized by the presence of multiple contaminants (Figure S1). Ex situ remediation techniques are usually more economically expensive and environmentally hazardous than in situ remediation techniques [27]. More application of ex situ remediation technologies is obviously against the green and sustainable development of remediation technologies for contaminated sites. Hence, it is necessary to promote the development of in situ remediation technologies to realize more efficient remediation.

We further identified 10 remediation techniques with different remediation principles from the collected cases, and the application frequency of which amounted to 2035 times (Table S1). As shown in Figure 1, the four main remediation technologies of contaminated sites were, in descending order, CKCP, CO/CR, TR, and S/S, with the application frequency ratios of 43.88%, 22.75%, 13.46%, and 13.22%, respectively, and the total of which exceeded 90%. Analysis of 643 historical cases highlighted the usage patterns of 10 remediation technologies, with cement kiln coprocessing (CKCP) emerging as the most common approach. CKCP can achieve harmless disposal by relying on existing cement equipment. Moreover, the green transformation of the cement industry and the implementation of relevant policies have further promoted the growth of the industry capacity of CKCP technology [28]. As for the other three technologies used more frequently, their commonalities were easy handling, technical maturity, and high efficiency. Incineration remediation (IR) was one of the least used remediation technologies [29]. Due to the prone to dioxin generation, the application of IR in China has been significantly reduced in recent years. Soil vapor extraction (SVE) was likewise less used because it was adopted from abroad and is still in the experimental stage.

With the growing need for industrial waste management, CKCP emerged as a popular method for treating both organic and some inorganic wastes during the latter half of the twentieth century. Contaminant stability, kiln temperature, and waste pretreatment methods influence CKCP’s final disposal efficiency. With increasing demand for treating hard-to-degrade organic pollutants, CO/CR has become widely used. Key factors include the choice of oxidizing agent, pollutant’s chemical nature, and reaction conditions (such as pH and temperature). Since the 1980s, TR has treated soils contaminated by volatile organic compounds (VOCs), with key factors being treatment temperature, soil type, moisture content, and system sealing efficiency. S/S techniques have been applied to treat HM-contaminated soils and hazardous wastes, with the additive type and proportion, contaminant type and concentration, and final mass’s physicochemical stability as the main factors. Case study results suggest that frequently used remediation technologies have been proven effective and reliable. However, as each contaminated site is unique, choosing the most suitable remediation technology demands a comprehensive assessment and comparison. This includes considering technology effectiveness, economic costs, environmental impact, social and policy factors, and adaptability to ensure alignment with both immediate needs and long-term sustainability goals.

Although the remediation technologies of contaminated sites have developed rapidly in China, there were still a lot of limitations, especially in the context of the carbon peaking and carbon neutrality goals proposed by China [30]. According to the latest version of USEPA’s Superfund Remedy Report, the average ratio of in situ remediation technologies in 2018–2020 was approximately 55.77%. In situ remediation technologies have remained the preferred remediation technologies for contaminated sites at present [31]. As for China, the application rate of in situ remediation technologies was lower. Mainstream remediation technologies, such as CKCP and S/S, still have secondary pollution problems, while SVE, BR, and other technologies have better application prospects due to their environmental friendliness. Furthermore, it is imperative to develop low-energy-consuming equipment and green remediation materials and to promote the widespread application of in situ remediation technologies such as S/S and CO/CR. Therefore, it is of great necessity to integrate low-carbon emission reduction into the practice of contaminated site remediation and then focus on in situ remediation and risk control.

3.2. Coupling Characteristics between Contaminants and Remediation Technologies

The chemical and physical properties of target contaminants at contaminated sites determine their environmental behavior and remediation strategies. These sites address a wide range of contaminants, encompassing 40 common pollutants (Table S2). Due to their stability and bioaccumulation, these substances pose a long-term threat to human health. HMs can accumulate in the food chain, affecting the health of plants, animals, and humans. For example, mercury can cause neurological damage, while lead may result in blood and nervous system disorders [32]. Polycyclic aromatic hydrocarbons (PAHs), benzene compounds, and pesticides persist and are challenging to degrade, leading to their long-lasting presence in the environment and contributing to soil contamination [33]. Organic pollutants in the environment exhibit behaviors such as transport, adsorption, and biodegradation, which are influenced by soil properties. A thorough understanding of these contaminants’ properties is vital for choosing suitable remediation technologies. Distinct contaminant characteristics require precise and efficient remediation technologies to guarantee environmental safety and health.

Various remediation technologies were analyzed and coupled for different target pollutants at contaminated sites (Figure 2). Selecting the appropriate remediation technologies is crucial for successful remediation due to variations in the chemical properties and existing forms of pollutants. We observed distinct responses from different pollutant types to remediation technologies.

For HMs, three to six primary remediation technologies were employed, with application percentages as follows: CKCP > S/S > SW > CO/CR > EL > BR > TR. CKCP, S/S, and SW were key remediation technologies for HM pollution, owing to the non-degradable nature of HMs. It is worth noting that CKCP was applied to more than 40% of Hg, Cu, Cr(VI), As, Cd, Ni, Co, and V. Except for Cd, Co, and V, the other seven HMs were less frequently treated with CO/CR. Remediation of Pb and Sb primarily used S/S. Interestingly, TR was exclusively employed for As among HMs. The type and species of HMs significantly influence their environmental behavior, resulting in the need for various remediation techniques [34]. CKCP utilizes high temperatures to bind HMs within the cement matrix, thereby reducing their bioavailability and mitigating environmental risks. TR employs high temperatures to volatilize and eliminate soil contaminants, proving especially effective for As removal.

Six remediation technologies were used for VOCs, with the following application percentages: CKCP > CO/CR > TR > MSA > BR > SVE. The primary technologies for VOC remediation were CKCP, CO/CR, and TR. CKCP was notably used in over 40% of cases for pollutants like 1,2-DCA, TCE, and others. CO/CR was most frequently used for CB remediation. SVE was employed across various contaminants, including BE, CF, and TCE. SVE is acknowledged as a cost-effective technique and is frequently utilized to remediate soils with unsaturated VOC contamination [35].

For SVOCs, various remediation technologies are employed in order of application frequency: CKCP, CO/CR, TR, BR, MSA, SW, IR, and EL. The primary remediation technologies for SVOCs were CKCP, CO/CR, and TR. It is worth noting that CKCP was applied in over 40% of cases for contaminants like NPH, AN, DBA, IP, CH, and BkF. CO/CR was employed in over 40% of cases for AN, BaP, and NB. In the remediation of BaP, BaA, BbF, and DBA, all seven alternative technologies, except EL, were used.

OPCs only involve three remediation technologies, with their application frequencies ranking: CKCP, TR, CO/CR. Significantly, CKCP represented over 40% of the applications for all seven identified pesticide pollutants.

Regarding TPH remediation technologies, the application frequencies were as follows, in descending order: CKCP, CO/CR, TR, SW, and EL. Among these technologies, CKCP comprised 50.46% of applications, followed by CO/CR at 40.37%.

Our study demonstrated the diverse preferences in choosing remediation technologies for various pollutants during land remediation. Certain contaminants, including V, HCB, and CTT, favored specific remediation technologies, while others, such as Cu, BaP, As, and IP, used a mix of techniques. Specific remediation strategies may be chosen for TCE based on its chemical stability or toxicity characteristics [36]. Remediation technology selection depended on the contaminant’s characteristics, cost, effectiveness, and feasibility.

Regarding pollutants treated, CKCP, CO/CR, and TR addressed 40, 37, and 30 pollutants, respectively. SW addressed 16 pollutants, while S/S addressed 10. MSA, EL, IR, and SVE each treated fewer than 10 pollutants. Based on the analysis above, CKCP emerges as the most prevalent method, frequently applied to a wide range of contaminants, with the highest overall utilization rate and extensive applicability. CO/CR and TR were also frequently used as remediation technologies. Methods like S/S and SW, though less common, played crucial roles in specific cases. IR, though limited in the types of pollutants it addresses, remained essential for certain contaminants. EL was primarily employed for Cr (VI), which may indicate specialization in remediating certain pollutant types. This analysis provided a comprehensive perspective on the scope and significance of various remediation techniques for addressing diverse contaminants. The varied strategies in remediation practices mirror the intricacies and tailored requirements of site remediation endeavors.

3.3. Spatial Distribution of Remediation Technologies

Successful remediation strategies need to consider the influence of factors such as geography, industrial development level, economy, and environmental sustainability on technology selection, as well as the chemical and physical properties of pollutants. Therefore, it is crucial to identify interprovincial distribution patterns of remediation technologies and the spatial clustering characteristics of critical technologies. This identification helps in recognizing effective remediation approaches, drawing lessons, and preventing pollution.

Figure 3a illustrates the geographical distribution pattern of various remediation technologies. Chongqing, Shanghai, Jiangsu, Guizhou, and Zhejiang exhibited more frequent use of remediation technologies compared to other regions, which were previously focal points for remediating and treating polluted sites in China [37]. Remediation technology usage remained infrequent in Fujian, Gansu, Yunnan, and Jilin, possibly due to their smaller industrial scale and less severe environmental pollution issues compared to other provinces [38]. Consequently, variations in the burden of site remediation, economic conditions, and resource allocations among provinces may influence the selection of remediation technologies.

In terms of remediation technology allocation, notable differences exist in the types of technologies employed and the predominant choices made by different provinces (Figure 3b). Chongqing, Guizhou, Jiangsu, and Beijing relied heavily on CKCP. In contrast, provinces and cities such as Shanghai, Guangdong, Guangxi, and Jiangxi did not employ CKCP. Instead, Shanghai utilized a higher proportion of CO/CR, and Guangdong favored S/S. TR was more prevalent in Jiangsu, Zhejiang, and Liaoning. S/S found widespread use across several provinces, with Zhejiang, Hunan, and Shanghai being notable adopters. SW exhibited a concentrated presence, with 78.20% of its applications occurring in Shanghai (Table S3). These remediation technologies are generally known for their capacity to address a wide range of contaminants swiftly and efficiently. This aligns with the characteristics of China’s remediation industry, which deals with large volumes, urgent tasks, and limited investment in industry development.

3.4. Spatial Autocorrelation Analysis of Remediation Technologies

Widely used and representative methods were selected to investigate the spatial clustering patterns and influencing mechanisms of CKCP, CO/CR, TR, and S/S, and the results are shown in Figure 4. We found that these four typical remediation technologies have different spatial characteristics; as we mentioned before, the choice of remediation technologies is related to regional pollution, economic, and social characteristics (Figure S2).

CKCP was one of the most widely used remediation technologies, whose High–High cluster distribution was mainly concentrated in Jiangsu, Chongqing, Shandong, and Guizhou, while Low–Low cluster distribution was mainly in Guangdong and Gansu (Figure 4a). Additionally, relevant literature mentions successful disposal projects in Chongqing, Jiangsu, and Beijing [39]. CKCP was initially applied in the remediation of pesticide-contaminated soil at the Songjiazhuang subway station. Since the issuance of the Soil Pollution Prevention and Control Action Plan and the Technical Policy for Co-disposal of Solid Waste in Cement Kilns in 2016, CKCP has been extensively utilized as an efficient method for waste treatment and resource recovery in highly contaminated areas. Furthermore, the distribution of CKCP was influenced by industrial layout and infrastructure, primarily favoring regions with a higher concentration of cement plants. Chinese cement manufacturing firms are predominantly situated in Eastern China, particularly in Jiangsu and Shandong. The local government in Chongqing has actively promoted CKCP adoption, driven by national policies that offer support and financial incentives, including hazardous waste recognition rules and exemption policies. In contrast, Guizhou had fewer cement plants but exhibited a notable concentration of cement kiln technology. This suggested that collaboration between Chongqing and Guizhou across regions, along with the transfer of Chongqing’s technology to other areas, could facilitate the cooperative progress of regional remediation and contaminated site treatment.

CO/CR has the advantages of complete remediation, lower cost, and faster construction preparation than other technologies, with high-density distribution in Hebei, Jiangsu, Shanghai, and Chongqing (Figure 4b). It has been reported that the application of CO/CR was spread widely in economically developed areas, such as coastal and riverine areas in the central and eastern parts of China, since the depth of the groundwater here was relatively shallow, and the synergistic remediation of soil and groundwater was required [40]. Chemical redox reactions usually require relatively well-developed mass transfer, and groundwater has better electron transfer conditions than soil. Differently, our research also pointed out that CO/CR was a commonly used remediation technology for contaminated sites in Chongqing. HM-TPH complex pollution was an important characteristic of the contaminated sites in Chongqing, and 82.5% of the site soils in Chongqing were alkaline, which facilitated the stabilization of most of the HM pollutants [41]. Although CO/CR has been applied more frequently in Chongqing, Hubei, the neighboring province, had relatively few applications of this technology. The application of CO/CR was not only strongly influenced by changes in humic acid content, reducing metal content, soil permeability, and pH but might also be driven by local policies. Hubei Province is rich in mineral resources, and for the treatment of tailings, a pond is more often used in S/S or other remediation technologies. In addition, our study pointed out that Gansu Province showed a Low–Low cluster distribution, which might be closely related to the relatively poor conductivity of local soil.

TR has been applied mainly to the remediation of VOC and SVOC-contaminated sites. Based on our analysis, it only showed a High–High cluster distribution in Shanghai while showing a High–Low distribution in Liaoning, Shanxi, Jiangsu, and Chongqing (Figure 4c). This result was moderately consistent with the distribution of characteristic pollutants in the contaminated sites. Shanghai statistically had the most VOC and SVOC-contaminated sites, followed by Chongqing and Jiangsu in descending order. As for Liaoning and Shanxi, the rich coal resources might be one of the foundation supports for promoting the application of thermal desorption technology. The Low–High cluster distribution of TR was mainly concentrated in Shannxi and Shandong, which indicated that the application of TR was not prominent in these areas. The reasons for this result might be related to the characteristic pollutants and the hydrogeological conditions of the local sites. TR is usually applied to sandy soils rather than clay soils, as high water content tends to lead to soil clumping, and small-sized soil particles have a stronger adsorption effect on contaminants [42]. The areas of High–High cluster distribution did not motivate the development of using TR to remediate in Shaanxi and Shandong, revealing a stronger spatial heterogeneity in the application of TR. TR is characterized by high remediation efficiency, wide application range, and controllable secondary pollution. The Ministry of Ecology and Environment of the People’s Republic of China (MEEPR) has issued and implemented Technical Specifications of Contaminated Soil Remediation Ex-situ Thermal Desorption and Technical Specifications of Contaminated Soil Remediation In-situ Thermal Desorption in April 2021 [43,44]. Although TR has problems with high energy consumption and high carbon emission, it still has good market prospects and application promotion value in the industry background of green and sustainable remediation by taking energy-saving and carbon reduction measures.

The High–High cluster distribution of the applications of S/S was concentrated in the east coast of China, such as Jiangsu, Zhejiang, and Shanghai, and the High–Low cluster distribution was in Hebei, Hunan, and Fujian (Figure 4d). The S/S has been more widely used in Shanghai and, at the same time, had a positive impact on the surrounding areas, such as Jiangsu and Zhejiang; that was why the spatial clustering distribution appeared in Figure 4d. Liaoning and Chongqing showed a High–Low cluster distribution. Obviously, Hebei, Hunan, and Fujian might be a little radiated by the neighboring areas, and their applications of S/S showed a Low–High distribution. MEEPR has issued and implemented Technical Specifications of Contaminated Soil Remediation Solidification/Stabilization [45]. This action may further promote the standardization and widespread application of S/S in the remediation of contaminated sites. It is worth mentioning that Chongqing, Jiangsu, and Shanghai can be regarded as hotspots for the application of the above four remediation technologies. On the one hand, these regions have a large number of contaminated sites with a wide variety of pollutants. On the other hand, these regions are more economically developed, and the management of contaminated sites is more in-depth. The identification of hotspots and spatial cluster distribution of typical remediation technologies can further guide the rational selection of remediation technologies to maximize the benefits and achieve green and sustainable remediation development.

4. Conclusions

We summarized the efforts and strategies of contaminated land remediation in China, emphasizing how the diversity and geographical features of contaminated sites influence remediation technology choices. This paper investigated 643 cases of contaminated site remediation to assess trends in technology development, effectiveness, and environmental impacts and to offer insights for optimizing the remediation process. The most significant categories of remediation technologies that were encountered in contaminated sites, typically as ex situ, were CKCP, CO/CR, TR, and S/S. The varied remediation strategies for target pollutants underscored the complexity of site remediation and the necessity of choosing technologies based on specific situations. Significant variations existed in the choice of remediation technologies across provinces, influenced by factors like industrial scale and environmental pollution. Spatial clustering analysis highlighted the geographical traits of remediation technologies in China. Preferences for these technologies in various regions were shaped by local policies, industrial layouts, and groundwater depths. This multilevel analysis offers a comprehensive view of decision making in remediation, aiming to maximize benefits and promote green, sustainable development.

Choosing appropriate remediation technologies for the diverse contaminated sites in China, based on the specific chemical and physical properties of the contaminants, is essential for remediation success. For instance, CKCP, widely recognized for its application scope and efficiency, is advised for sites contaminated with HMs such as Ni, Pb, Cu, Hg, and Cd. S/S technology, effective in reducing pollutant mobility and bioavailability, is particularly recommended for Pb contamination remediation. SW, which is optimal for sites with loose soil where contaminants are easily extracted, acts as an efficient initial step in contaminant removal. Furthermore, incorporating examples of remediation technologies from across the globe is necessary. This cross-cultural and cross-border research approach is crucial for addressing China’s complex environmental issues and achieving continuous environmental quality improvement and sustainable development.