**1. Introduction**

Owing to rapid industrialization, urbanization, population growth, and a lack of environmental awareness, environmental degradation and pollution problems have emerged [1,2] among which soil heavy metal pollution has become a global environmental dilemma [3,4]. It has been reported that approximately 20% of soil in the world is contaminated, with over 10 million contaminated sites covering more than 20 million hectares of land, more than 50% of which are contaminated with harmful heavy metals [5]. Approximately 600,000 ha of soil in the United States has been contaminated with heavy metals [4]. Approximately 470,000 ha of agricultural soil in Japan has been contaminated with heavy metals [6]. In China, farmland per capita is less than half of the world average, but the total area of farmland contaminated by heavy metals is nearly 20 Mha, accounting for nearly 19.4% of the total farmland [7].

Soil heavy metal pollution brings food security threats and serious economic losses. The combined impact of heavy metal pollution on the global economy is estimated to exceed \$10 billion annually [5,8]. A survey supported by the European Commission estimates that the social loss caused by soil pollution is approximately 17.3 billion euros per year [8]. In

**Citation:** Yan, Y.; Wang, L.; Yang, J. The Willingness and Technology Preferences of Farmers and Their Influencing Factors for Soil Remediation. *Land* **2022**, *11*, 1821. https://doi.org/10.3390/ land11101821

Academic Editor: Purushothaman Chirakkuzhyil Abhilash

Received: 18 September 2022 Accepted: 16 October 2022 Published: 17 October 2022

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**Copyright:** © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

China, nearly 12 million tons of grain are polluted by heavy metals every year [9]. Therefore, actions must be taken to remediate contaminated soil. The second and third Sustainable Development Goals (SDGs) for 2030, adopted by the United Nations General Assembly, also articulate the need to mitigate food threats [10]. China attaches great importance to the environmental quality of its agricultural soils. In May 2016, the Soil Pollution Prevention and Control Action Plan was issued, and 200 pilot demonstrations for contaminated soil were conducted. From 2016 to 2021, approximately 38 billion yuan was invested in the field of soil pollution prevention and control. In 2020, there were 668 ongoing soil remediation projects nationwide of which 42.4% were agricultural soil remediation projects.

For heavy metal-contaminated agricultural soil, the remediation mechanisms are based on two basic principles: one is to reduce the concentration of heavy metals in the soil and completely remove the pollutants and the other is to use engineering technology to transform the pollutants to less harmful forms [11–14]. Phytoextraction (phytoremediation) and passivation are the most widely used representative technologies for engineering applications based on the above two remediation principles. Phytoextraction is one of the most promising phytoremediation technologies, which uses the root system of (hyper)accumulators to uptake contaminants from the soil and transfer them to aboveground biomass for accumulation, achieving complete removal of contaminants through gradual harvesting of the aboveground biomass [11,15]. Passivation remediation, also known as chemical stabilization, is a technology that reduces the toxicity and biological effectiveness of heavy metal contaminants in the soil environment by adding exogenous passivators to contaminated soil and converting heavy metals to non-activated, less toxic forms through surface complexation, chemical precipitation, ion exchange, adsorption, and so on [16,17]. However, the remediation of contaminated farmland involves arable land utilization not only in terms of technology [18,19] but also in terms of the behavior of farmers on micro level.

Although contaminated agricultural soil remediation projects are collective actions led by the government, farmers are the closest stakeholders to farmland contamination and the executors of remediation projects. If farmers perceive the remediation technologies to be detrimental to their interests, this may hinder effective implementation of the project, which will be a major uncertainty factor in solving the hidden dangers of food safety, especially for agricultural countries with small per capita arable land. It turns out that a gap exists between farmers' behaviors and policy expectations [20]. Therefore, it is necessary to study how to encourage farmers to actively participate in soil remediation, and farmers' willingness to participate in remediation and their preference for remediation technologies are important factors that should be considered in the formulation of sustainable soil remediation policies.

The study of issues related to farmland from farmers' behaviors and attitudes has become an important research perspective [21,22]. Research shows that with the application of various technologies, farmers' attitudes are increasingly determining the success of land use policies and that research on farmers' attitudes can contribute to policy innovation and practical guidance on many land use issues [21,23,24]. Various studies have examined farmers' behaviors and attitudes under certain policies and explored the factors that influence farmers' decision-making behaviors [19–21,23,25]. The main factors that may influence farmers' behaviors can be divided in household head characteristics, household production characteristics, and technical characteristics [20,26,27]. On the issue of farmland soil pollution, Zhou et al. [19] studied the spontaneous adaption behaviors of farmers in the mining area, such as abandoning farming and adjusting crops, and their results showed that a low level of adaptation perception for which technology was the most important limiting factor followed by money limited the adaptation behaviors of farmers; Yu et al. [28] investigated farmers' comprehensive assessment of the policy of remediation during fallow, such as planting green manure and biological adsorption, and found that it was positively influenced by the cognition of government implementation, the cognition of policy function and the evaluation of value perception. However, phytoremediation and passivation are

the two most commonly used techniques for heavy metal-contaminated farmland. There is still a lack of research on farmers' attitudes towards different soil remediation technologies, the constraints restricting farmers' participation in different technologies remain unclear.

In the above context, with the aim of providing a scientific basis for increasing farmers' willingness to participate in remediation, promoting the implementation of agricultural soil remediation projects, and ensuring food security, our study focuses on answering the following questions: What is the attitude of farmers towards soil remediation and what is their preference for remediation technologies? How can farmers' willingness to participate in soil remediation be increased? How can remediation technologies be further optimized from the perspective of farmers? Therefore, in this study, we conducted face-to-face structured interviews with 553 farmers in 4 contaminated agricultural soil remediation project sites in China to: (i) analyze farmers' willingness to remediate and technical preferences in terms of their individual characteristics, household production characteristics, current status of remediation participation, and technical characteristics; (ii) explore the key factors affecting the popularization and application of soil remediation technologies; and (iii) propose suggestions for optimizing technical parameters for remediation in conjunction with farmers' willingness (Figure 1). It is of great theoretical and practical significance to study in depth farmers' willingness and technical preferences to participate in soil remediation projects and to construct an effective participation mechanism. The results of this study will have important reference significance for the remediation of contaminated soil in agricultural countries with small arable land per capita.

**Figure 1.** Flow chart of the research.

#### **2. Materials and Methods**

#### *2.1. Data Sources*

This study surveyed farmers in four soil remediation project areas in China with different levels of soil contamination, where both phytoremediation and passivation remediation were conducted, to ensure that farmers had knowledge of both remediation techniques. Household questionnaire surveys were conducted from January to September 2019 using random sampling and one-to-one structured interview methods. A total of 553 valid questionnaires were obtained from 98 households in Luancheng District, Shijiazhuang City, Hebei Province (A); 147 households in Mianzhu City, Sichuan Province (B); 190 households in Shimen County, Hunan Province (C); and 118 households in Yangshuo County, Guangxi Province (D) (Figure 2). See Supplementary Table S1 for an overview of the study area.

**Figure 2.** Details of the considered study area.

To ensure the scientific credibility and rationality of the questionnaire, the first draft of the questionnaire was designed through a literature review and expert consultation, which was improved based on the results of a random pre-investigation of 50 farmers in the project area of Shimen County, Hunan Province. The main content of the questionnaire consisted of five parts: basic information about the farmers interviewed (such as gender, age, education), household and production characteristics (including family size, farmland area, income composition), current status of participation in soil remediation (such as farmland area remediated, labor income), satisfaction with current remediation and willingness to remediate in the future, preference for remediation technology, and impact of technical characteristics (see Supplementary Table S2). Among them, farmers' characteristics affect household preferences [29]. Household production characteristics may limit farmers' choices in terms of livelihood strategies, and have received the most attention in recent studies [27,30]. Technology characteristics are farmers' psychological perceptions of different remediation technologies and may influence their rate of adoption of technologies. The participation status is an essential variable and may be an important factor influencing farmers' perceptions of different remediation technologies. To ensure the quality of the survey data, a formal survey was conducted in the form of face-to-face communication between the investigator and respondents, and the investigator filled out the questionnaire.

#### *2.2. Research Methodology*

#### 2.2.1. Descriptive Statistics of Farmer Characteristics and Remediation Intentions

To describe the significance of the differences between the backgrounds (individual and household) of the different surveyed populations and the willingness of farmers to participate in future soil remediation and technology selection, a cross-tabulation function in IBM SPSS Statistics software (version 24.0) was used. The remediation and technical intention (non-participation, passivation, phytoremediation) were taken as columns, and the characteristics of farmers were taken as rows to compare the frequency distribution of two independent samples of the rows and columns. Among the characteristics of farmers, continuous variables, such as farmland and income, were defined and transformed into 5-level categorical variables to represent different levels of population. Based on the chi-square test to determine its significance, the original hypothesis of the cross-tabulation was that the two variables of rows and columns were independent of each other. If the chi-square test statistic was less than the critical value of significance level 0.05, the original hypothesis was overturned, indicating that there was a significant difference in remediation technology intention between different row variables (farmers' characteristics). Supplementary Table S2 presents the descriptive statistics of the sample farmers' characteristics.
