1. Introduction
Coal mining in Portugal was a significant economic activity until the closure of the last mine in 1994. This activity resulted in environmental liabilities as multiple industrial facilities are currently abandoned, with mine drainage discharges in the hydrographic systems and large amounts of mining residues stored.
Coal mining can release hazardous elements at potentially harmful levels to the environment, causing soil and water contamination, land degradation and ecological deterioration [
1,
2,
3,
4,
5]. In Portugal, as in many other countries, the abandoned mining areas constitute a contamination focus [
6,
7,
8,
9,
10,
11].
The management of this type of risk of contamination represents an obstacle to the development of any region since such abandoned mines can cause environmental issues and decrease the health conditions of the surrounding areas. Consequently, the analysis of the environmental susceptibility of abandoned coal waste piles has become an important tool in their planning and management.
Several studies applied Multiple Criteria Decision Making (MCDM) methods to evaluate the risk of abandoned waste piles in several contexts. For instance, Alamanos and Papaioannou [
12] presented an approach combining Geographical Information System (GIS) with multi-criteria analysis (MCA) to evaluate wetland effectiveness using multiple factors (geomorphological, climatological, hydrological and land use), in Grand River (Ontario, Canada). Qiaoxiu et al. [
13] used a Fuzzy Analytic Hierarchy Process (FAHP) combined with a mathematic model based on Logarithmic Fuzzy Preference Programming (LFPP) method to estimate and rank several factors (environmental, human, management and technological, and equipment factors) to implement a management model and guide the safety managers in the mining process, in China. Choi et al. [
14] performed a combination of factor analysis and fuzzy relations with GIS software to determine vulnerable locations to coal mine subsidence in Taebaek City, Korea. Rehman et al. [
15] combined several methods, including fuzzy logic to analyze the mining subsidence susceptibility in Raniganj coalfield (India) using site-specific parameters. Dai et al. [
16] used AHP to combine several factors to determine the risk of coal-floor water inrush in the Hacheng mine area, part of the southeastern margin of Ordos Basin in Shaanxi Province (China). Sahin et al. [
17] also used AHP combined with GIS to investigate possible places of air pollution in four districts of Igdir city (Turkey). Chabok et al. (2020) used FAHP to select the optimum location for municipal solid waste in Ahvaz (Iran), combining environmental and socio-economic criteria. AHP has also been used with success for susceptibility modeling of landslide risk in North Macedonia [
18]. From the literature consulted, it can be concluded that the use of GIS combined with MCDM evaluation could provide a better understanding and a strong and efficient database, and it can constitute a guide for policymakers and experts.
São Pedro da Cova (Porto, Portugal) coal waste pile has been studied in recent years because it has been self-burning since 2005 after being ignited by a forest wildfire. Due to its great importance, one international scientific research project named ECOAL (Ecological Management of Coal Waste Piles in Combustion) was implemented, aiming at the remote, multi-point, and continuous monitoring of gas emissions and combustion temperature in the self-burning coal waste pile using advanced optical fiber sensing technology [
19]. The results allowed the study of the dynamic and evolution of the combustion process. A more recent project, named CoalMine, that started in 2018, aimed to characterize and quantify the environmental impacts caused by the self-burning of the coal waste pile, including the potential environmental impacts on ecosystems, including soils, waters, and human health (
https://www.fc.up.pt/coalmine/, accessed on 22 July 2022). Previous studies proved to be of prime importance the environmental monitoring of the São Pedro da Cova coal waste pile, and as well as that, the identification of potential environmental impacts of the surrounding areas is of extreme relevance, including soils and waters [
2,
3,
19,
20,
21,
22,
23,
24,
25,
26,
27]. Taking this into consideration, there is a great interest in the environmental susceptibility mapping of the São Pedro da Cova coal waste pile considering the contamination of the surrounding areas.
Collaborative effort for the improvement of a self-burning coal waste pile database is essential during the long-term contamination reduction process. In the São Pedro da Cova coal waste pile, several data were acquired from 2019–2021, through distinct methodologies combined in a multi-approach to estimate the environmental impacts of the waste pile. The information acquired by several techniques, namely in situ campaigns and remote sensing data, through satellite imagery and Unmanned Aerial Vehicle (UAV) sensors, were manipulated and integrated in a GIS open-source application (Coal Mine), developed for QGIS software, focused on describing the spatial distribution of the contaminated area and also characterizing the environmental and health risks [
20].
As a result of the integration in a GIS environment of all the data acquired during the CoalMine project, and to fill a scientific gap, this study aims: (i) to create the susceptibility map of contamination in the areas surrounding the São Pedro da Cova self-burning coal waste pile; and, (ii) to develop the webGIS application incorporating all the information obtained in the project and that can be useful for the residents of São Pedro da Cova and also to the public entities and researchers. Specifically, it is mainly intended to publish and share data acquired between 2019 and 2021, in the São Pedro da Cova self-burning coal waste pile, through a freely available webGIS as open portal data.
As so, the adopted methodology was implemented considering the available data acquired in the field and a webGIS was developed constituting the final product of the project. The result is crucial to understand how the surrounding areas can be negatively affected by the waste pile contaminants.
The next sections are organized as follows:
Section 2 describes the study area, the data inventory maps, and the methodology adopted to estimate the environmental susceptibility mapping in a self-burning coal waste pile using a GIS-based MCDM approach.
Section 3 presents the methodology adopted to design and implement the webGIS, considering the architecture, software, and tools.
Section 4 presents the results and discussion of the obtained environmental susceptibility map and the outcomes in terms of performance, user interface, and utility of the webGIS.
Section 5 presents the conclusions and future work.
3. WebGIS Development
A webGIS application was developed in the context of the project of the São Pedro da Cova coal waste pile (
Figure 7a; [
20]). The webGIS is a user interaction interface that enables easy access and visualization of geographical data. The developed application was based on Python programming language and available to society from
https://gis.up.pt/coalmine (accessed on 20 May 2022). In the frontend, an easy and intuitive graphic interface was created to configure the design of the application. For this, Hyper Text Markup Language (HTML), Cascading Style Sheets (CSS) and JavaScript were used. Bootstrap, a powerful, extensible, and feature-packed frontend toolkit, was also used (
https://getbootstrap.com/, accessed on 30 May 2022) to create buttons, action widgets, among others. As the backend, the database was configured using the PostGIS database, an open-source database that is an extension of the PostgreSQL database [
67]. A server was also used in this study, the Geoserver, an open-source server for sharing geospatial data (
https://geoserver.org/, accessed on 30 January 2022). All the data were hosted in the PostGIS database and connected to Geoserver. Several standard functionalities were implemented: (i) zoom in/out; (ii) measure buttons (m, km, mi); (iii) selection of three different base maps (Google Satellite, Open Street Map (OSM) and Water Color Map) in a radio button; (iv) search button for a specific location; (v) the presentation of the geographical coordinates of the position of the cursor; (vi) a home button to zoom to the layers of the project; (vii) the full-screen view, which extends the canvas to all the screen; (viii) the scale according to the zoom; (ix) a collapsible navigation bar composed of two links (
About and
WebGIS) that allows changing the pages between information about the project (
About) and the webGIS application; and (x) a panel group with scroll action composed by collapsed headings with the years of the project (2019, 2020 and 2021), besides the water and soil samples. In this panel group, when the user clicks on a year, a set of maps appears defined in cards. These cards are composed of the title of the map, the description of the map, an illustrative image, and two horizontal sliders: the top small slider allows us to turn on/off the map on the canvas and the bottom slider (
Opacity) allows applying transparency to the map, giving the possibility to overlap raster files with different information (
Figure 7b).
The maps were generated in raster format, except for water and soil samples, which were created in vector format (points). In these two layers, an additional functionality was applied. At each point, when clicked by the user, a table appears with the information on the hydrogeochemical and soil characterization [
20], along with the geographical coordinates of each point (
Figure 8). In the future, the webGIS will be continuously maintained and updated when new data are collected. In the
About link, all the information about the data and procedures, as well as the contacts, are provided.
4. Results and Discussion
As previously mentioned, the evaluation of the contamination that affects the surrounding areas of São Pedro da Cova’s self-burning coal waste pile considered five parameters: (i) the waste pile, (ii) runoff areas, (iii) downstream drainage, (iv) the distance from the waste pile, and (v) the NDVI index. The factors were ranked and weighted based on their importance. The most important factors were the waste pile itself, the runoff, and the downstream drainage. The least important was the distance to the coal mine and the presence of vegetation. To produce the final susceptibility map, two methods were tested: the AHP method and the Fuzzy-AHP. The AHP method was applied through the pairwise comparison matrix (
Table 6). The matrix was applied to assess the class ratings in each parameter and to estimate the final weights for each parameter. The values of the CR were less than 10%, which is in accordance with the consistency defined by the pairwise comparison [
50]. To obtain the final susceptibility map (
Figure 9a), the WOM method was used (Equation (3)) in GIS software (QGIS open-source software), where the assignment of the rankings was performed to each factor and then each of them was multiplied by the respective weight. The final susceptibility map values range from 0 to 1 and indicate an increasing degree of susceptibility.
In the second approach, the fuzzy logic technique, which has been widely used in environmental risk assessment [
13,
14], was applied to standardize the criteria layers. In this study, the fuzzy logic was applied to the distance to waste pile, NDVI map, and downstream drainage map. Areas near to the waste pile have a higher susceptibility to contamination, as well as the areas in the downstream drainage system near the waste pile. Otherwise, areas with low NDVI values have a higher susceptibility to contamination due to soil instability and wind transport of pollutants. Finally, to obtain the susceptibility map (
Figure 9b), the WOM method was applied (Equation (3)). Values ranging from 0 to 1 were assigned, where areas with values close to 1 are more susceptible to contamination than areas with values close to 0. The final maps were divided into five classes using “Natural Breaks” method from ArcGIS software.
The evaluation of the results obtained was performed through the generation of the AUC curve, which is a statistical technique used by researchers to validate predictive results. As in
Figure 10, the ROC curve is always above the reference line with the value of 0.5, with an AUC score of 0.813 indicating very good and accurate performance of the AHP approach. Fuzzy-AHP also indicates a very good value (0.800), despite the odd shape of the ROC curve. The obtained AUC scores indicate that the proposed models are suitable for susceptibility mapping.
As expected, in both methods, the zones more susceptible to mine contamination were identified over the waste pile and in the immediate surrounding areas affected by the runoff. These areas were classified as presenting very high and high susceptibility to mine contamination and are mostly dominated by forest use and there is no urban overlap. The contamination susceptibility ranged from high to moderate along the closest segment of the drainage network from the waste pile and the mine effluents discharge; along these segments there is evidence for agricultural practices and therefore a growing concern with the eventual usage of poor-quality water for irrigation purposes. The following segments downstream decrease to low susceptibility as there is a significant dilution on pollutants concentration caused by tributary water input to the drainage lines.
A concentric area with approximately 1 km surrounding the waste pile is classified as moderate susceptibility as a reflex of contaminants deposition from the waste pile by areal dissemination. This area affects both urban, agricultural areas and forest.
To validate the results, the LULC maps were generated for the study zone, and the COSSim was used (
Figure 11). Comparing both maps and considering that the LULC map aggregates the classes from COSSim, from visual interpretation it can be concluded that the maps are coherent. The waste pile location is mainly characterized by vegetation (mainly eucalyptus) and bare soil zones. It can also be observed that the urban areas are very close to the waste pile.
The influence of urban contamination in the areas adjacent to the waste pile cannot be neglected. As previously mentioned in Teodoro et al. [
20], there are multiple types of contamination sources contributing differently to the concentration of PTEs and other elements registered in soils that surround the mine. The samples located in urban areas upstream of the mine demonstrated a moderate increase in PTEs (As, Pb, Mo, Cu, Zn, Co, Ni and Ag). These values can influence the results obtained, suggesting that the contamination in the urban area can have different sources (external to the waste pile).
This study also provides the development of a webGIS constituting the client interface, free and open source, so any user can access. The webGIS can be considered as a base to develop and apply the appropriate management and monitoring of the São Pedro da Cova waste pile, providing detailed information acquired in situ and also from different geospatial techniques. In this context, the webGIS developed in this project, besides being a final product for dissemination of the data acquired/generated, has a number of advantages: (i) the access is possible from a web browser with connection to Internet, without costs; (ii) it does not require knowledge about any GIS software or database; (iii) it was developed as a user-friendly interface, with intuitive and simplistic buttons to manipulate, consult and access the information; (iv) a wide range of clients can use the application simultaneously; and (v) the application is open to further development and extension of functionalities and it can be adapted to other regions and other studies. Some limitations were also identified, since in the future more actions and analyses can be implemented in the webGIS. Additionally, it depends on the internet connection because some data have a large size.
5. Conclusions
In this study, AHP and Fuzzy AHP methods were employed to create a susceptibility map to identify the zones that possibly can be affected by contaminants of the São Pedro da Cova coal waste pile. The multiple contamination pathways were considered, including water and air. The adopted approach was never applied in the context of the São Pedro da Cova coal waste pile and since the data were available, this study integrated all of them using MCDM methods to evaluate the contaminant susceptibility in the surrounding areas of the waste pile. The results obtained showed that the contamination susceptibility is higher surrounding the abandoned mine, particularly along the waste piles and the corresponding runoff areas, which can be particularly sensitive. Nearly 2 km of mine drainage along the hydrographic network, sourced by the waste pile and the mining effluents discharge, can also be an object of concern, as these areas are surrounded by agriculture fields that can be flooded with contaminated materials and the water can potentially be used for irrigation. The NDVI parameter did not influenced so much the susceptibility to contamination.
The predictive maps were evaluated using the ROC, which indicates an accuracy of 0.813 (AUC = 0.813) for AHP and 0.800 (AUC = 0.800) for Fuzzy AHP, both indicating a high accuracy. Furthermore, the LULC and COSSim maps were compared and analyzed considering the waste pile.
Regarding the susceptibility analysis performed, although the availability of data is not enough, the results of the AHP and Fuzzy AHP methods suggest that it can be applied to other abandoned mines. To disseminate the results obtained under the CoalMine project, a user-friendly webGIS was developed, allowing us to visualize and combine the data obtained during the project, with respect to terrain analysis and water and soil characterization. Regarding the webGIS developed, the data acquired during the CoalMine project can be disseminated for any user, with tools that can help to analyze and combine the information. With the development of the project, users will take great advantage of a variety of long-term information, which provides critical implications for São Pedro da Cova coal waste pile and can help with management decision-making. The access to more available data and a larger time window would have allowed for a more effective analysis. The chosen parameters were selected in order to model the contamination susceptibility on the immediate area surrounding the São Pedro da Cova mine. For this analysis, in such a restrained area, the focus was on the known contamination sources and the identified dissemination pathways. Other factors such as wind preferential direction, aquifer and underground modelling (pluviometry data, types of geologic substract, hydraulic conductivity), and social-economic parameters, should be addressed in future studies regarding risk modelling in broader areas.
The developed work intends to provide information related to the sites more susceptible to contaminants. This work can help to provide security/control measures for public health and safety, preventing potential exposure of the surrounding community to soils and water channels close to a waste pile. It is important to attract the attention of the inhabitants that live close to the waste pile, so they are aware of the potential contaminants
In the future, the acquisition of more field measurements/data to improve this analysis is foreseen, integrating more factors in the MCDM approaches in order to obtain better outcomes. For instance, socio-demographic factors, to understand who is living close to the waste pile and consequently what kind of populations are more exposed or more vulnerable, and what kind of activities are taking place there, among others.