Evaluation and determination of soil remediation schemes using a modified AHP model and its application in a contaminated coking plant

Strain and Electric Field Engineering of G-ZnO/SnXY (X, Y = S, Se) S-Scheme Heterostructures for Photocatalyst and Electronic Device Applications: A Hybrid DFT Calculation

Using hybrid density functional theory calculations, we systematically study the biaxial strain and electric field modulated electronic properties of g-ZnO/SnS2, g-ZnO/SnSe2, and g-ZnO/SnSSe S-scheme van der Waals heterostructures (vdWHs). g-ZnO/SnS2 and g-ZnO/SnSSe are found to be promising photocatalysts for water splitting with high solar-to-hydrogen efficiencies, even under acidic, alkaline, and high-stress conditions. The strain effect on the bandgaps of g-ZnO/SnXY is explained in detail according to the correlation between geometry structure and orbital hybridization of SnXY, which could help understand the strain-induced band structure evolutions in other SnXY (X, Y = S, Se)-based vdWHs. It is surprising that under an external electric field, g-ZnO/SnS2, g-ZnO/SnSe2, and g-ZnO/SnSSe can offer the occupied nearly free-electron (NFE) states. In many materials, NFE states are usually unoccupied and is not conducive to the charge transport. The NFE state in g-ZnO/SnSe2 is the most sensitive to the electric field and might be promising electron transport channel in nanoelectronic devices. g-ZnO/SnSe2 might also have application potential in gas sensors and high-temperature superconductors.

An interpolation method incorporating the pollution diffusion characteristics for soil heavy metals - taking a coke plant as an example

The existing spatial interpolation methods in the prediction of soil heavy metal distribution are generally based on spatial auto correlation theory, rarely considering the pollution patterns. By contrast, in polluted sites, heavy metals have a strong heterogeneity even within a very small area, which is not exactly in line with auto correlation theory. This contradiction may lead to inaccuracy in spatial prediction. Atmospheric diffusion and deposition are one of the main sources of soil heavy metal pollution caused by coal-related production activities. To improve the prediction accuracy, the diffusion patterns of pollutants were considered in this paper by integrating Geodetector, Co-Kriging (COK), and partition interpolation. Geodetector was used to identify the main driving factors of soil pollution, based on which, the main driving factors were used as covariates introduced into the interpolation method (COK). Specifically, the amount of particulate matter deposition obtained by a pollutant diffusion model (AERMOD) was used as a covariate. For comparison, the distances to quenching, coke oven, and ammonium sulfate section were also used as covariates. Compared with the Ordinary Kriging method, the method COK-AERMOD established here decreased the root mean square error values of As (2.05 reduced to 1.89), Cd (0.18 reduced to 0.16), Cr (19.07 reduced to 12.97), Cu (6.92 reduced to 4.72), Hg (0.32 reduced to 0.28), Ni (16.92 reduced to 16.10), Pb (18.29 reduced to 16.62), and Zn (159.68 reduced to 153.66). This method in this paper is informative for the interpolation of soil elements in contaminated areas with known pollution source and diffusion patterns.

Whole-Process Risk Management of Soil Amendments for Remediation of Heavy Metals in Agricultural Soil-A Review

Reducing the mobility and bioavailability of heavy metals in soils by adding exogenous materials is a technology for remediating soils contaminated with heavy metals. Unlike industrial sites, the use of such techniques in agricultural soils requires consideration of not only reducing the mobility of heavy metals but also avoiding adverse effects on soil fertility and the growth of plants. Due to the uncertainty of the stability of amendments applied to agricultural soil, the application of amendments in farmland soil is controversial. This article reviewed the field studies in which amendments were used to immobilize heavy metals, and identified the potential environmental impacts of all aspects of soil amendment usage, including production and processing, transportation, storage, application to soil, long-term stability, and plant absorption. Results of the study indicated that after identifying the environmental risks of the whole process of the application of improvers in agricultural fields, it is necessary to classify the risks according to their characteristics, and design differentiated risk control measures for the safe application of this type of technology.

Source Apportionment of Heavy Metals Based on Multiple Approaches for a Proposed Subway Line in the Southeast Industrial District of Beijing, China

Apportioning the sources of heavy metals (HMs) in soil is of great importance for pollution control. A total of 64 soil samples from 13 sample points at depths of 0-21 m were collected along a proposed subway line in the southeast industrial district of Beijing. The concentrations, distribution characteristics, and sources of eight HMs were investigated. The results showed that the concentrations of Hg, Cd, Cu, Pb, As, and Zn in the topsoil (0-2 m) exceeded the Beijing soil background values. Three sources were identified and their respective contribution rates calculated for each of the HMs using multiple approaches, including correlation analysis (CA), top enrichment factor (TEF), principal component analysis (PCA), and positive matrix factor (PMF) methods. As (63.11%), Cr (61.67%), and Ni (70.80%) mainly originated from natural sources; Hg (97.0%) was dominated by fossil fuel combustion and atmospheric deposition sources; and Zn (72.80%), Pb (69.75%), Cu (65.36%) and Cd (53.08%) were related to traffic sources. Multiple approaches were demonstrated to be effective for HM source apportionment in soil, whilst the results using PMF were clearer and more complete. This work could provide evidence for the selection of reasonable methods to deal with soils excavated during subway construction, avoiding the over-remediation of the soils with heavy metals coming from natural sources.

A Comprehensive Evaluation System for the Stabilization Effect of Heavy Metal-Contaminated Soil Based on Analytic Hierarchy Process

Stabilization technology is widely used in the remediation of heavy metal-contaminated farmland soil. However, the evaluation method for the remediation effect is not satisfactory. To scientifically evaluate the remediation effect, this study constructed a comprehensive evaluation system by bibliometric analysis and an analytic hierarchy process (AHP). Ultimately, 16 indicators were selected from three aspects of the soil, crops, and amendment. The 16 indicators are divided into three groups, namely indicators I that can be evaluated according to the national standards of China, indicators II that can be evaluated according to the classification management of farmland and Indicators III that are the dynamic change indicators without an evaluation criterion. Comprehensive scores for 16 indicators were calculated using three response models, respectively. According to the difference between the scores before and after the remediation, the remediation effect is divided into five levels, which are excellent, good, qualified, poor, and very poor. This study provides a theoretical basis and insightful information for a farmland pollution remediation and a sustainable utilization.

Development of a Multi-Criteria Decision-Making Approach for Evaluating the Comprehensive Application of Herbaceous Peony at Low Latitudes

The growing region of herbaceous peony (Paeonia lactiflora) has been severely constrained due to the intensification of global warming and extreme weather events, especially at low latitudes. Assessing and selecting stress-tolerant and high-quality peony germplasm is essential for maintaining the normal growth and application of peonies under adverse conditions. This study proposed a modified multi-criteria decision-making (MCDM) model for assessing peonies adapted to low-latitude climates based on our previous study. This model is low-cost, timesaving and suitable for screening the adapted peony germplasm under hot and humid climates. The evaluation was conducted through the analytic hierarchy process (AHP), three major criteria, including adaptability-related, ornamental feature-related and growth habits-related criteria, and eighteen sub-criteria were proposed and constructed in this study. The model was validated on fifteen herbaceous peonies cultivars from different latitudes. The results showed that 'Meiju', 'Hang Baishao', 'Hongpan Tuojin' and 'Bo Baishao' were assessed as Level I, which have strong growth adaptability and high ornamental values, and were recommended for promotion and application at low latitudes. The reliability and stability of the MCDM model were further confirmed by measuring the chlorophyll fluorescence of the selected adaptive cultivars 'Meiju' and 'Hang Baishao' and one maladaptive cultivar 'Zhuguang'. This study could provide a reference for the introduction, breeding and application of perennials under everchanging unfavorable climatic conditions.

Coupling of multi-hydrochemical and statistical methods for identifying apparent background levels of major components and anthropogenic anomalous activities in shallow groundwater of the Liujiang Basin, China

Natural background levels (NBLs) is a prerequisite for distinguishing anthropogenic groundwater pollution and judging the evolution of groundwater quality. However, due to regional differences of hydrogeochemitry and water-rock interaction, coupled with long-term anthropogenic activities, it is no longer accurate to assess NBLs with only statistical methods or without considering human impact. Herein, multi-hydrochemical and statistical methods were examined to identify apparent background levels and anthropogenic anomalous activities of shallow groundwater by selecting Liujiang Basin as a study area. The results showed that the differences in hydrochemical characteristics among each hydrogeological unit (HU) fully illustrated the necessity of rationally dividing HU for background value identification. The application of the concept of apparent background levels (ABLs), that is, incorporating normal human activities into the background levels, efficiently solved the problem of being unable to obtain pristine NBLs due to long-term human activities. The coupling of Hydrochemistry and Grubbs' test (Hydro-Grubbs) was confirmed as the optimal method in identifying and eliminating anthropogenic groundwater anomalies, performing sufficiently superiority when compared with purely statistical methods. It is mainly because the Hydro-Grubbs method not only considers the discreteness of the data itself, but also considers the internal connection and evolution process of the hydrochemical compositions. For the eliminated abnormal points, 91.0-93.6% of which have been effectively explained by pollution percentage index and the impact of coal mining, industrial activities, residents, agricultural activities, and septic tanks leakage, proving the rationality and reliability of Hydro-Grubbs method and ABLs evaluation result. This finding will assist in accurately identifying anthropogenic pollution on a regional scale and guiding future efforts to protect groundwater resources.

DynSus: Dynamic sustainability assessment in groundwater remediation practice

Decision-making processes for clean-up of contaminated sites are often highly complex and inherently uncertain. It depends not only on hydrological and biogeochemical site variability, but also on the associated health, environmental, economic, and social impacts of taking, or not taking, action. These variabilities suggest that a dynamic framework is required for promoting sustainable remediation. For this, the decision support system DynSus is presented here for integrating a predeveloped contaminant fate and transport model with a sustainability assessment tool. Implemented within a system dynamics framework, the new tool uses model simulations to provide remediation scenario analysis and handling of uncertainty in various data. DynSus was applied to a site in south Sweden, contaminated with pentachlorophenol (PCP). Simulation scenarios were developed to enable a comparison between alternative remediation strategies and combinations of these. Such comparisons are provided for selected sustainability indicators and remediation performance (in terms of concentration at the recipient). This leads to identifying the most critical variables to ensure that sustainable solutions are chosen. Simulation results indicated that although passive practices, e.g., monitored natural attenuation, were more sustainable at first (5-7 years after beginning remediation measures), they failed to compete with more active practices, e.g., bioremediation, over the entire life cycle of the project (from the beginning of remedial action to achieving the target concentration at the recipient). In addition, statistical tools (clustering and genetic algorithms) were used to further assess the available hydrogeochemical data. Taken together, the results reaffirmed the suitability of the simple analytical framework that was implemented in the contaminant transport model. DynSus outcomes could therefore enable site managers to evaluate different scenarios more quickly and effectively for life cycle sustainability in such a complex and multidimensional problem.

Prediction Performance Comparison of Risk Management and Control Mode in Regional Sites Based on Decision Tree and Neural Network

The traditional risk management and control mode (RMCM) in regional sites has the defects of low efficiency, high cost, and lack of systematism. Trying to resolve these defects and explore the application possibility of machine learning, a characteristic dataset for RMCM in regional sites was established. Three decision tree (DT) algorithms (CHAID, EXHAUSTIVE CHAID, and CART) and two artificial neural network (ANN) algorithms [back propagation (BP) and radial basis function (RBF)] were implemented to predict RMCM in regional sites. The results showed that in the aspects of accuracy (ACC), precision (PRE), recall ratio (REC), and F₁ value, CART–DT was superior to CHAID–DT and EXHAUSTIVE CHAID–DT (E-CHAID–DT); and BP–ANN was superior to RBF–ANN. However, CART–DT was inferior to BP–ANN in ACC, PRE, REC, and F₁ value. BP–ANN model is good at non-linear mapping, and it has a flexible network structure and a low risk of over-fitting. The case study of a typical county demonstration area confirmed the extensibility of the method, and the method has great potential in RMCM prediction in regional sites in the future.

Vertical profile and assessment of soil pollution from a typical coking plant by suspect screening and non-target screening using GC/QTOF-MS

A comprehensive workflow for suspect screening and non-target screening with gas chromatography coupled with quadrupole time-of-flight mass spectrometry (GC/QTOF-MS) was used to characterize the pollution characteristics of soil samples in a typical coking plant in China. Suspect screening confirmed 57 chemicals including PAHs, alkyl PAHs, and phthalates contained in high-resolution personal compound database and library (PCDL). Non-target screening detected 88 chemicals from soil samples in the NIST 17 library. A total of 122 chemicals were screened in soil samples, and many of them were of emerging concern. Their presence in the soil obtained from coking operations has been underestimated, such as the oxygenated PAHs (naphtho[2,1-b]furan and 9H-fluoren-9-one), and the alkyl biphenyls compounds (4,4'-dimethylbiphenyl, 3,3'-dimethylbiphenyl, 4-methyl-1,1'-biphenyl and 2,2',5,5'-tetramethyl-1,1'-biphenyl). Toxicity assays by luminescent bacteria proved that the extracts from soil samples at different depths showed varying toxicity to V. qinghaiensis sp.-Q67. Soil extracts from a depth of 20-40 cm exhibited the greatest toxicity to luminescent bacteria compared with the other six-layered soil samples, which was correlated with the number of detectable pollutants and total organic carbon content. This study provided a screening method for suspect and non-target contaminants in urban industrial soil sites, which was important in identifying localized contamination sources.

Informing remediation of benzene contamination in drinking water distribution systems through multi-criteria decision analysis

When contamination incidents occur in drinking water distribution systems, utilities need to select the remediation technologies most suited to their system-specific conditions and the contaminants of concern. Technology selection often involves balancing competing priorities. Multi-Criteria Decision Analysis (MCDA) is a promising approach that has been used extensively in other industries but not yet in drinking water system remediation. This paper discusses development of a computer-based tool that allows practitioners to leverage the Analytical Hierarchy Process (AHP), a well-established method of MCDA, to select remediation technologies based on their effectiveness and their compatibility with the practitioner's project objectives. This paper focuses on benzene, a contaminant implicated for many years in contamination incidents following spills and, more recently, wildfires.

Super-stable mineralization effect of layered double hydroxides for heavy metals: Application in soil remediation and perspective

Agriculture soil plays a crucial role in sustainable development of human society. Unfortunately, soil quality is continuing degradation due to industrial and agricultural activities. Among them, agriculture soil contamination by heavy metals has become a serious threat to global food safety and human health. Because of low-cost, easy to implement, and fast effects, in situ chemical stabilization strategy has drawn great attention in soil remediation fields. However, since heavy metals are not removed from soil, it is still a great challenge to develop the cost-effective stabilizers with strong and long-term immobilization ability. Layered double hydroxides (LDHs) have been extensively applied in environmental fields owing to their unique structure. Very recently, LDHs have been used as amendment in in situ soil remediation for immobilization of heavy metals, exhibiting excellent long-term stability in practice application through trapping heavy metal ions into the lattice of LDHs layer. Given that the super-stable mineralization effect of LDHs for heavy metals, we summarize the structure of LDHs, key points of super-stable mineralization, practical challenges, and potential applications in other heavy metals pollution scenarios in this article, wishing that could provide new strategies and insights into rational designing of amendments for soil remediation.

Systematic and bibliographic review of sustainability indicators for contaminated site remediation: Comparison between China and western nations

Sustainable remediation, which promotes the use of more sustainable practices during environmental clean-up activities, is an area of intense international development. While numerous indicators related to sustainable remediation assessment have been utilized and published in related academic literature, they are difficult to unify and vary in emphasis between countries. Following literature retrieval from CNKI, Springer, ScienceDirect, and Wiley Online databases, we present a systematic and bibliometric analysis of relevant national and international literature to define the most frequently considered indicators of sustainability, which play important roles in selecting remediation technologies or site management methods from a sustainability perspective. Following the application of co-occurrence analysis and social network analysis, the results indicate that 1) environmental criteria are most commonly used in evaluating remediation technologies, with significantly less emphasis on social criteria in Chinese publications in particular; 2) with an increasing number of publications in the last 20 years, sustainable remediation has gone through an initial stage, rising stage, and burst or wider adoption stage, characterized by a transformation of the research theme from a predominantly risk-based management approach to a sustainability-based one, with risk management as an underpinning principle; 3) health, resource, cost, and time are the most widely used indicators in terms of social, environmental, economic, and technical criteria, respectively; 4) clear differences exist between China and other nations, particularly in the frequency of usage of each indicator, the application of social criteria, and preferred stakeholders. Nevertheless, China has made significant progress and now makes increasing contributions to sustainable remediation at an international level.

A critical review of decision support systems for brownfield redevelopment

Over the past two decades, many decision support systems (DSSs) have been developed to support decision makers and facilitate the planning and redevelopment process of brownfields. Existing systems are however often siloed in their approach and do not fully capture the complexity of brownfield sites from a sustainable development point of view. This critical review provides an insight into the development and implementation of DSSs, published and emerging, together with assessment of their strengths, limitations and opportunities for future integration. Brownfields DSS applications include: remediation technology selection; and land use planning; and risk assessment. The results of this review lead the authors to identify four opportunities to improve brownfield DSSs: (i) increased use of qualitative socioeconomic criteria, particularly costs and economic variables, (ii) decision-support during the early stages of brownfield redevelopment, (iii) the integration of predictive modelling methods, and (iv) improvements of user interfaces and modern web-based functionalities.

INSIDE-T: A Groundwater Contamination Transport Model for Sustainability Assessment in Remediation Practice

Current sustainability assessment (SA) tools to help deal with contaminated groundwater sites are inherently subjective and hardly applied. One reason may be lack of proper tools for addressing contaminant spread which are basically objective. To fill this gap, there is a need for contaminant transport models that provide site managers with needed room for applying their judgments and considerations about the efficiency of each remediation method based on their experiences in similar cases. INSIDE-T uses trend analysis and inverse modeling to estimate transport parameters. It then simulates contaminant transport both with and without the inclusion of remedial actions in a transparent way. The sustainability of each remedy measure can then be quantified based on the underlying SA tool (INSIDE). INSIDE-T was applied to a site in south Sweden, contaminated with pentachlorophenol. Simulation scenarios were developed to enable comparison between various remediation strategies and combinations of these. The application indicated that natural attenuation was not a viable option within the timeframe of interest. Although pump-and-treat combined with a permeable reactive barrier was found to be just as effective as bioremediation after five years, it received a much lower sustainability score overall. INSIDE-T outcomes enable site managers to test and evaluate different scenarios, a necessity in participatory decision-making practices such as remediation projects.

Algorithm for Selecting Best Available Techniques in Polish Coking Plants Supporting Multi-Criteria Investment Decisions in European Environmental Conditions

The tightened approach of the European Commission to the issue of meeting the levels of pollutant emissions to the environment, inextricably connected with the level of technology used, is a serious financial challenge for many European coke producers, therefore the main aim of the article is to develop an algorithm of conduct that allows a selection of the best available emission abatement techniques from the coking plant in conditions with multiple emission sources, taking into account technological, environmental, and economic criteria. This algorithm can be used as a universal tool supporting production managers in planning investments limiting the environmental impact of the coking plant in the most economically advantageous way, while using BAT techniques. In the development of the algorithm, a multi-criteria analysis and a scenario method were used, as well as a number of typical methods for measuring and reducing the level of emissions in the coke production process. Its demonstration and verification were carried out within ten investment scenarios prepared for a selected coking plant. The presented method of selecting the optimal scenario is universal and allows for a flexible selection of weights for the criteria depending on the needs and limits of the investor at a given time or to long term plans to adapt to the increasingly tightening environmental requirements. This method can also be used in discussions with the authorities issuing integrated permits as regards the deadlines for adapting to legal requirements.

INSIDE: An efficient guide for sustainable remediation practice in addressing contaminated soil and groundwater

Modeling criteria interaction in decision-making problems is complex and often neglected. In complicated problems, like contaminated site remediation projects, independency of involved criteria is not a realistic assumption. INfluence based deciSIon guiDE (INSIDE) is a methodology that enables sustainable decision making and management in contaminated site remediation practice. Unlike most previous decision-support methods, INSIDE considers realistic interactions among all involved criteria. The method not only gives a one-time best option for choosing a remediation method for the project at hand, but also a management plan for further improvements of the system. INSIDE recognizes economic, environmental, social, and technological considerations for the most sustainable practice. Eight criteria are defined based on these aspects and they can be interrelated. This means that a criterion, e.g., remediation time, does not need to belong to any pre-defined category such as economic, environmental, social, or technical, but can interact with other criteria. This allows for a system with many degrees of freedom that is more realistic for practical problem-solving. In INSIDE, the DEcision MAking Trial and Evaluation Laboratory (DEMATEL) and Analytic Network Process (ANP) techniques are combined for assigning weights to criteria and scoring of remediation alternatives, respectively. Thus, the proposed methodology gives a managerial cone of influence versus importance for all involved criteria in the system. The method is applied to a data-scarce case study in Iran to prioritize between remediation methods for a contaminated groundwater aquifer. The results show that human health risk and environmental impacts are more influential than other evaluated criteria. The suggested methodology should be further tested on a variety of actual remediation problems for additional evaluation.

Multi-criteria decision analysis of optimal planting for enhancing phytoremediation of trace heavy metals in mining sites under interval residual contaminant concentrations

As one of the most cost-effective and sustainable methods for contaminants' removal, sequestration and/or detoxification, phytoremediation has already captured comprehensive attention worldwide. Nevertheless, the accurate effects of various spatial pattern in enhancing phytoremediation efficiency is not yet clear, especially for the polluted mining areas. This study designed nine planting patterns (monocropping, double intercropping and triple intercropping) of three indigenous plant species (Setaria viridis (L.), Echinochloa crus-galli (L.) and Phragmites australis (Cav.) Trin. ex Steud.) to further explore the effects of plants spatial pattern on phytoremediation efficiency. Considering the uncertainties of the residual contaminants' concentration (RCC) caused by soil anisotropy, permeability and land types, the interval transformation was introduced into the plant uptake model to simulate the remediation efficiency. Then multi-criteria decision analysis (MCDA) were applied to optimal the planting patterns, with the help of criteria of (a) the amount of heavy metal absorption; (b) the concentration of residual contaminant in soil; (c) root tolerance of heavy metals; (d) the total investment cost. Results showed that (1) the highest concentrations of Zn, Cd, and Pb of the polluted area were 7320.02, 14.30, 1650.51 mg kg^-1 (2) During the 180 days simulation, the highest RMSE of residue trace metals in soil are 3.02(Zn), 2.67(Pb), 2.89(Cd), respectively. (3) The result of IMCDA shows that the planting patterns of Setaria viridis, Echinochloa crus-galli and Phragmites australis in alternative a9 (269 mg kg^-1 year^-1) had the highest absorption rate of heavy metals compared with a7 (235 mg kg^-1 year^-1) and a2 (240 mg kg^-1 year^-1). After 20 years of remediation, the simulated RCC in a9 is far below the national standard, and the root toxicity is 0.12 (EC ≤ EC₂₀). In general, the optimal alternative derived from interval residual contaminant concentration can effectively express the dynamic of contaminant distribution and then can be effectively employed to evaluate the sustainable remediation methods.

Analysis of radially convergent tracer test in a two-zone confined aquifer with vertical dispersion effect: Asymmetrical and symmetrical transports

Radially convergent tracer test (RCT) with an extraction well and a tracer injection well is commonly conducted for determining aquifer dispersivity associated with the spreading of contamination plume. A variety of analytical models for RCT have been proposed, but the effects of skin zone and vertical dispersion are rarely explored. In addition, little attention is paid to the validity of those analytical models assuming asymmetrical tracer transport (ATT) as radially symmetrical transport (RST) toward the pumping well. This study develops a new analytical model for RCT subject to the above-mentioned effects in a confined aquifer with a skin zone around the wellbore. The Laplace-domain solution of the model for a continuous or instantaneous input is developed. A finite element solution (FES) for ATT is also developed to verify the Laplace-domain solution based on RST. Results suggest ATT can be regarded as RST in predicting the breakthrough curve (BTC) at the pumping well when four quantitative conditions are met. A lumped dimensionless parameter dominates those two effects on the BTC. Both the FES and Laplace-domain solution agree with monitored concentration data from a field RCT.

GIS Multi-Criteria Analysis by Ordered Weighted Averaging (OWA): Toward an Integrated Citrus Management Strategy

This study proposes a site location assessment model for citrus cropland using multi-criteria evaluation (MCE) and the combination of a set of factors for suitability mapping and delineating the suitable areas for citrus production in Ramsar, Iran. It defines an incorporated method for the suitability mapping of the most appropriate sites for citrus cultivars with an emphasis on the multi-criteria decision analysis (MCDA) process. The combination of geographic information system (GIS) and a modified version of the analytic hierarchy process (AHP) based on the ordered weighted averaging (OWA) technique is also emphasized. The OWA is based on two principles, namely: the weights of relative criterion significance and the order weights. Therefore, the participatory technique was employed to outline the set of standards and the important criterion. The results derived from the GIS–OWA technique indicate that the cultivation of citrus is feasible only in limited areas, which make up 6.7% of the total area near the Caspian Sea. This investigation has shown that the GIS–OWA model can be integrated into MCDA to select the optimal site for citrus production. The present research highlights how multi-criteria in GIS can play a considerable role in decision making for evaluating the suitability of selected sites for citrus production.