Pollution Vulnerability Research Articles

Assessing pollution vulnerability in groundwater: A case study of Kala Shah Kaku industrial complex

ABSTRACT Various factors, such as industrialization, population growth, and urbanization, have caused water quality and availability to decline worldwide, resulting in water crises in many regions and millions of annual deaths from water-related diseases. The study aimed to assess the groundwater quality in Kala Shah Kaku, an industrial area in central Punjab, Pakistan. Groundwater samples from six locations were analyzed for physical and chemical parameters and heavy metals. The results revealed that Kala Shah Kaku's groundwater is unsuitable for drinking due to exceeding the physical and chemical parameters range. The study identified industrial effluents from nearby industries as the primary source of pollution in the area's groundwater. These findings emphasize the urgent need for remedial measures to address industrial pollution and protect groundwater resources in Kala Shah Kaku.

Integrated assessment of groundwater pollution vulnerability in Goulmima: a comparative analysis of DRASTIC and GOD methods

Integrated assessment of groundwater pollution vulnerability in Goulmima: a comparative analysis of DRASTIC and GOD methods

Assessment of Air Pollution Vulnerability and its impact in Jaipur city

AIR POLLUTION • Contamination of the indoor or outdoor environment by any chemical, physical or biological agent that modifies the natural characteristics , concentration . • Industrial pollution accounts for 51% of pollution, followed by automobile pollution (27%), agricultural burning (17%), and miscellaneous causes (5%) comprising CO (Carbon Monoxide), Sox (Oxides of Sulphur), Ozone, NOx (Oxides of Nitrogen), Unburnt hydrocarbons, PM (Particulate matters).Other pollutants released are C4H6 (Butadiene), Photochemical oxidants, aldehydes, lead etc. • According to a recent research,13 cities were listed in to of the most polluted 20 cities of the with the worst yearly levels of air pollution are in India, And at least 140 million people there breathe air that is 10 times or more over the WHO acceptable limit

Groundwater pollution vulnerability assessment using a modified DRASTIC model in Ho Chi Minh City, Vietnam

AbstractThe Pleistocene aquifer serves as a vital water source for various activities in Ho Chi Minh City, Vietnam, including concentrated and individual exploitation. In the present study, the DRASTIC (D, depth of water; R, net recharge; A, aquifer media; S, soil media; T, topography; I, impact of vadose zone; C, hydraulic conductivity) model was used to evaluate the groundwater sensitivity of the study area. To analyse Ho Chi Minh City's Upper‐Middle Pleistocene aquifer vulnerability, the analytic hierarchy process (AHP) method was used to optimize the DRASTIC score and include land use (LU) characteristics. Four distinct weights were used: DRASTIC, modified DRASTIC‐LU, AHP‐DRASTIC and modified AHP‐DRASTIC‐LU. This study identified low, moderate and high vulnerability for 12%, 55% and 33% of the DRASTIC‐LU index values, respectively. The AHP‐DRASTIC index classifies 61%, 26% and 13% of sites as low, moderate and highly vulnerable, respectively. The study reveals that 52%, 30% and 18% of the area are vulnerable to the modified AHP‐DRASTIC‐LU index classes. The most sensitive factors are shallow aquifer roofs, recharge and LU. The real‐world accuracy of the DRASTIC models was tested using 106 groundwater nitrate concentrations. The modified AHP‐DRASTIC‐LU is the most accurate and appropriate model for the current research region.

Evaluation of the vulnerability and pathways of groundwater pollution in the Zanjanrud river basin by an integrated modeling approach

Evaluation of the vulnerability and pathways of groundwater pollution in the Zanjanrud river basin by an integrated modeling approach

Development of a national antibiotic multimetric index for identifying watersheds vulnerable to antibiotic pollution

Improved surveillance of antibiotics and antibiotic resistance (AR) throughout the environment is an important aspect of the prevention and control of threats posed to human and ecological health. In response to field investigations often limited by resources and time, this study aims to develop a systematic approach to assess watershed vulnerability to antibiotic pollution and AR by integrating modeling and field studies. The national antibiotic pollution vulnerability index was developed to identify watersheds most impacted by antibiotic sources. The index incorporates multiple metrics representing antibiotic pollution driven by both agricultural activities and municipal wastewater (i.e. outpatient antibiotic prescriptions, wastewater treatment plant effluent flow, stream order and dilution factor of effluent-receiving streams, manure application, and animal facilities), alongside climate change indicators (i.e., temperature, precipitation, and runoff). The pollution index was applied at a state level in North Carolina to identify the most-impacted watersheds and inform site selection for targeted field study quantifying azithromycin, ciprofloxacin, sulfamethoxazole, and trimethoprim concentrations. Modeled-informed sites in NC demonstrated the highest reported concentrations of azithromycin, trimethoprim, and sulfamethoxazole compared to previous NC studies, confirming the index effectiveness in identifying watersheds with higher antibiotic concentrations. At the national scale, watersheds relatively more vulnerable to antibiotic pollution are predominantly located in the Midwest, South, and Northeast regions of the U.S., with Iowa and Indiana being the most impacted states. Climate change is expected to exacerbate watershed vulnerability to agriculture-driven AR in the Midwest and Northeast due to an increase in precipitation and mean temperature coupled with intense agricultural activities. In addition, due to climate change-induced reductions in precipitation and runoff, watersheds in the Midwest, Mid-Atlantic, and South Central are dominantly at higher risk of effluent-driven AR occurrences. We have disseminated the developed indices as open-source online tools to aid in prioritizing strategies to mitigate AR occurrence across the U.S.

APPORT DE LA GEOMATIQUE ALA DELIMITATION DES PERIMETRES DE PROTECTION AUTOUR DE LA PRISE DEAUPOUR LALIMENTATION EN EAU POTABLE SUR LA RIVIERE ME A KONGOFON (SUD EST DE LA COTE DIVOIRE)

The quality of the Me Rivers water is threatened by sources of pollution generated in the region without any measures being taken to protect this resource.So, to reduce the risk of pollution of this water resource, this study aims to delimit the protection perimeters around the water intake on the river.The methodological approach consisted firstly in assessing the vulnerability of the resource through the weighting and combination of five selected parameters, and then in determining the protection perimeters on the basis of the pre-established vulnerability map and data from previous studies.The pollution vulnerability map obtained reveals five classes of vulnerability around the water intake, with a dominance of the high class estimated at 29.44% of the watershed. Three protection perimeters have been defined. The immediate protection perimeter has a 200 m radius around the water intake and covers areas with a strong influence on the rivers vulnerability to pollution over a surface area of 1.97 km2.The close protection perimeter, covering a 1000 m radius, was delimited from the immediate protection perimeter. It covers an area of 43.7 km2 and takes into account the rivers low, medium and very high vulnerability classes, following the direction of water flow in the Me watershed.The remote protection perimeter covers a large part of the watershed, with an area of 1,480 Km2. It covers the rest of the catchments highly vulnerable areas and adjoins the close protection perimeter.The defined protection perimeters can serve as a guide for sustainable management and protection of river quality.

APPORT DE LA GEOMATIQUE ALA DELIMITATION DES PERIMETRES DE PROTECTION AUTOUR DE LA PRISE DEAUPOUR LALIMENTATION EN EAU POTABLE SUR LA RIVIERE ME A KONGOFON (SUD-EST DE LA COTE DIVOIRE)

The quality of the Me Rivers water is threatened by sources of pollution generated in the region without any measures being taken to protect this resource.So, to reduce the risk of pollution of this water resource, this study aims to delimit the protection perimeters around the water intake on the river.The methodological approach consisted firstly in assessing the vulnerability of the resource through the weighting and combination of five selected parameters, and then in determining the protection perimeters on the basis of the pre-established vulnerability map and data from previous studies.The pollution vulnerability map obtained reveals five classes of vulnerability around the water intake, with a dominance of the high class estimated at 29.44% of the watershed. Three protection perimeters have been defined. The immediate protection perimeter has a 200 m radius around the water intake and covers areas with a strong influence on the rivers vulnerability to pollution over a surface area of 1.97 km2.The close protection perimeter, covering a 1000 m radius, was delimited from the immediate protection perimeter. It covers an area of 43.7 km2 and takes into account the rivers low, medium and very high vulnerability classes, following the direction of water flow in the Me watershed.The remote protection perimeter covers a large part of the watershed, with an area of 1,480 Km2. It covers the rest of the catchments highly vulnerable areas and adjoins the close protection perimeter.The defined protection perimeters can serve as a guide for sustainable management and protection of river quality.

Assessment of groundwater vulnerability to pollution using DRASTIC and the SI methods: case of the alluvial aquifer in Tadjenanet-Chelghoum laid (East Algeria)

The region of Chelghoum Laid - Tadjenanet is located in the east of Algeria in the high southern plains of Setif, characterized by a highly vulnerable shallow alluvial aquifer. The vulnerability of groundwater to pollutants is a relative concept, not measurable or dimensional. The nature, quality, and reliability of used data used have a major impact on the correctness of its assessment. Its classification is usually based on the estimation of many more or less essential factors, such as the characteristics of soil and unsaturated zone, the saturated zone, the recharge , the topography and the hydraulic conductivity. The vulnerability of the aquifer to pollution was investigated using two intrinsic vulnerability methods: DRASTIC and susceptibility index (SI). SI method is an adaptation of the DRASTIC specifically design for nitrate-based pollution. The parameters used as input data are, among others, the depth of the groundwater, the soil type, the topographic slope and the groundwater recharge. The validity of the two methods for assessing the vulnerability to nitrates was established by comparing the distribution of these elements in groundwater with the distribution of the various vulnerability classes. GIS techniques were used to implement these methods. Vulnerability maps created using the DRASTIC and SI method’s depict the potential for pollutants to penetrate and spread in these locations depending on the terrain encountered on the surface and the depth of the aquifer. The comparison revealed that the SI technique is the most accurate in the studied alluvial aquifer. The establishment of the pollution vulnerability map highlighted an area of great vulnerability in the center of the plain, reflected by the fragility of the soil and the shallow depth of the water. While the average vulnerability areas are in the center, and east at the periphery of Wadi Rhumel, the rest of the field is slightly vulnerable. The vulnerability and contamination risk maps created for this study are valuable tools for environmental planning and can be used for predictive management of groundwater resources. This case study suggests that the approach may be applicable to other areas as part of efforts to target groundwater management efforts.

Data mining to aquifer vulnerability assessment

The vulnerability map of aquifer pollution is a part of the early warning system to prevent the deterioration of groundwater quality. The weighted index overlay methods are commonly used to map aquifer vulnerability, but they have a series of drawbacks, indicating the need to apply alternative methods that introduce the least number of a priori considerations in the parameters processing and allow a more accurate interpretation of the final results. The purpose of this study is to use data mining techniques for cluster analysis to evaluate the vulnerability of groundwater pollution in the Almondarez Vento Karst Basin in Havana Province, Cuba, and compare the results with those obtained using the RISK method, which is a weighted index overlay method to study karstic aquifers. The variables selected to apply this unsupervised classification technique were: aquifer lithology, topographic slope of the terrain, soil attenuation index to pollutants, fault density per km2 and presence of direct infiltration zones. The cluster analysis achieved greater spatial discrimination and definition of areas with different degrees of vulnerability, demonstrating its high resolution power.

Application of GIS‐based DRASTIC model and its validation with Solute Transport Model in the assessment of groundwater vulnerability index: A case study from coal mining region of India

AbstractThe intensive Coal mining in Dhanbad, India, is crucial for contaminating the groundwater resources. The present work aims to estimate the vulnerability of aquifers to contamination with the aid of a GIS‐based DRASTIC approach. This is finally validated by comparing the concentration of the contaminant computed by the Solute Transport Model. Using the soil moisture flow and pollutant transport model, an effort is made to validate the vulnerability of groundwater pollution. The vulnerability maps showed that some of this region's western southwest, and northern part lies in the highly vulnerable region. The major influential parameters in the present study for mapping the vulnerability are shallow depth to groundwater, higher net recharge and more permeable vadose zone. Furthermore, the surrounding mining activities are highly accountable for depleting groundwater superiority in the present research area. These vulnerability maps can be later on effectively used for environmental development and managing future water resources. The Solute Transport Model does not compute vulnerability; instead, it computes the concentration of the contaminant.

Vulnerability assessment of soil cadmium with adsorption–desorption coupling model

The transfer rate and extent of cadmium (Cd) to groundwater and plants were controlled by soil adsorption and desorption processes, which directly affect agro-environment safety. Cd mobility shift is critical for the correct assessment of pollution vulnerability in different soil types. But the existing experimental methods and traditional quantitative prediction models are time-consuming and have a small scope of adaptation. In this paper, a coupling model of soil Cd adsorption and desorption was developed based on quantitative retention factors to explore the sensitivity of soil environmental factors for Cd pollution and quantify the spatial distribution pattern of Cd pollution vulnerability in highly heterogeneous soils in China. Results showed that: (1) The type of background electrolyte affected Cd adsorption and desorption capacity in soil solution. The performances of the single background electrolyte models (NaNO3, CaCl2, NaCl, KNO3) are better than the mixed background electrolyte model. (2) The contribution values of adsorption and desorption models were compared by sensitivity analysis. (3) Vulnerable areas of soil Cd pollution with higher risk than expected were selected by using the adsorption–desorption coupling model in China, including Tibet Autonomous Region, Xinjiang Uygur Autonomous Region, northwestern Sichuan Province, southeastern Qinghai Province, Guangdong Province, Guangxi Province, and Yunnan Province. Our adsorption–desorption coupling model can be used as an assessment tool expressing the soil Cd pollution vulnerability based on the available state of Cd, which is expected to provide the quantitative scientific basis for the formulation of Cd quality standard systems and soil remediation measures for regional soil environment protection.

Groundwater pollution vulnerability assessment in the Assin municipalities of Ghana using GIS-based DRASTIC and SINTACS methods

Groundwater pollution vulnerability assessment in the Assin municipalities of Ghana using GIS-based DRASTIC and SINTACS methods

Zoning groundwater vulnerability in residential areas around the Terjun landfill using the aplis method

The development of the Medan City area causes an increase in population, increased activity, changes in the use of water catchment land into residential land, one of which is around the Terjun landfill area, Medan Marelan District. This is directly proportional to the increasing need for water. This study aims to determine how much pollution vulnerability in groundwater with the APLIS Method approach (Altitud, Pendiente, Litologia, Infiltration Prefencial, Seule). Zoning of groundwater vulnerability with the APLIS Method results in a low vulnerability class with a classification of >20-40%.

Mapping groundwater vulnerability using drastic method

Preventive management and protection of groundwater were to create a groundwater vulnerability map. This map provided information distribution on the level of vulnerability to groundwater contamination in an area. The impact made considered in making regional decisions to create a sustainable development framework. The DRASTIC method is an instrument for evaluating the vulnerability of groundwater pollution. The DRASTIC methods can use evaluate vulnerabilities of groundwater contamination which seven parameters: the depth of the groundwater table (D), rainPL (R), aquifer media (A), soil texture (S), topography (T), the influence of unsaturated zones (I), and hydraulic conductivity (C). The additional parameter is the use of land resulting from vulnerability. The parameter data will be poured into a map using ArcGIS and analyzed using the DRASTIC rating index. Eight attributes are included in the modified DRASTIC model, including hydraulic conductivity of the aquifer, topography, impact of the vadose zone, depth to water table, net recharge, aquifer media, soil media, and aquifer media. In a GIS system, these layers were combined using the Raster Calculator tool. The modelx was further validated using fifteen groundwater composite samples that were also gathered. Based on the results of the analysis, groundwater vulnerability in Terjun’s landfill from the five parameters, the value of the DRASCTIC index is 137 which indicates the vulnerability of groundwater is at medium/moderate. Aquifers next to floodplain areas are very sensitive, whereas those next to terrace areas are less vulnerable, according to the results. The model's findings confirm that the topography, soil media, and aquifer depth indicated the strongest correlations with vulnerability. A positive association between the vulnerability classes and the three groundwater quality measures electrical conductivity was also found during the validation of the final DRASTIC map. Although the levels of contamination at this time are below acceptable bounds, the possibility of additional contamination cannot be completely eliminated and is really rather plausible.

Novel machine learning algorithms to predict the groundwater vulnerability index to nitrate pollution at two levels of modeling

The accurate mapping and assessment of groundwater vulnerability index are crucial for the preservation of groundwater resources from the possible contamination. In this research, novel intelligent predictive Machine Learning (ML) regression models of k-Neighborhood (KNN), ensemble Extremely Randomized Trees (ERT), and ensemble Bagging regression (BA) at two levels of modeling were utilized to improve DRASTIC-LU model in the Miryang aquifer located in South Korea. The predicted outputs from level 1 (KNN and ERT models) were used as inputs for ensemble bagging (BA) in level 2. The predictive groundwater pollution vulnerability index (GPVI), derived from DRASTIC-LU model was adjusted by NO3–N data and was utilized as the target data of the ML models. Hyperparameters for all models were tuned using a Grid Searching approach to determine the best effective model structures. Various statistical metrics and graphical representations were used to evaluate the superior predictive performance among ML models. Ensemble BA model in level 2 was more precise than standalone KNN and ensemble ERT models in level 1 for predicting GPVI values. Furthermore, the ensemble BA model offered suitable outcomes for the unseen data that could subsequently prevent the overfitting issue in the testing phase. Therefore, ML modeling at two levels could be an excellent approach for the proactive management of groundwater resources against contamination.

GIS-based risk assessment of tropical surface water pollution by integrating hydrogeological and anthropogenic parameters

Surface water pollution is a huge issue worldwide that keeps growing in magnitude and complexity which leads to millions of people don’t have access to clean water resource. Numerous studies on vulnerability, hazard and risk assessment of water pollution had been conducted yet most of them only focused on one of the three risk components. Therefore, the objective of this study was to apply a geospatial approach that integrated hydrogeological and anthropogenic parameters to assess the risk of surface water pollution in Selangor River Basin, Malaysia. Analytical Hierarchy Process (AHP) and Weighted Linear Combination (WLC) were applied in hydrogeological vulnerability assessment. WRASTIC index was used in anthropogenic hazard assessment. The risk map showed that high-risk zones were mainly located in areas where development and agricultural activities are extensive. Conversely, low-risk zones were in areas that were mostly covered by forest with few developments, such as the upstream region. The results also revealed that high and very risk levels were dependent on soil media and presence of land use and anthropogenic activity especially agriculture, industry, and wastewater presence. The risk map also showed that developed area with high hydrogeological vulnerability would have higher risk of pollution compared to areas without any anthropogenic hazard. The risk map can assist stakeholders to identify at risk of pollution. This allows for better decision-making in integrated river basin management.

Application of remote sensing and gis to identify the vulnerability of ground-water pollution in topograhic karst

Karst or limestone is a landscape in the form of unique. Karst or limestone has sensitive properties and is easily dissolved in water so that the karst topography has a subsurface water system in the form of holes that are susceptible to degradation due to the very fast flow of water so that it is easy to pass water underground. The purpose of this study was to determine the level of vulnerability of karst underground water pollution based on remote sensing data and GIS in the Rengel-Tuban Indonesia karst region. This type of research is quantitative research. Data analysis techniques in this study used image interpretation and logistic regression tests. The researched result is known that Remote sensing imagery and GIS as a tool to identify the level of vulnerability of underground water pollution in the karst region. Utilization of remote sensing imagery and GIS is presented as information of vulnerability of underground water pollution, and the study showed that the average area of karst Rengel was classified as vulnerable to pollution. In conclusion that the average area study was classified as vulnerable to pollution, and the Rengel karst hills are in line with local levels of vulnerability and pollution

A new approach to pollution vulnerability assessment in aquifers using K-means analysis

The most used methods to evaluate the vulnerability to contamination of aquifers are based on overlay index maps, such us DRASTIC, GOD and AVI. These methods assign weighting and rating values to hydrogeological characteristics, introducing subjectivity in the evaluation. In this research, a new methodology is proposed to eliminate some of that subjectivity. The methodology evaluates the vulnerability to contamination of a detrital aquifer using K-means cluster analysis with a new set of parameters. The set is composed of some parameters extracted from these methods, as well as other new ones that have a significant influence on the movement of contaminants. Application of the Principal Components Analysis (PCA) technique before using K-means cluster allowed the selection of the most relevant parameters. To validate the methodology, this was applied to a detrital aquifer located at central Spain (the so-called “Aluviales Jarama-Tajuña” aquifer) with a significant agricultural development. To compare the traditional methods of vulnerability assessment with the K-means cluster, nitrate concentration was used as a pollution indicator. Thus, 23 groundwater quality samples were used to correlate (Spearman´s correlation coefficient) the vulnerability values with nitrate concentration to validate the most suitable method. The results showed that GOD and AVI were not appropriate methods to evaluate the vulnerability of the aquifer, because they have negative or very low correlation with nitrate concentration (− 0.5 and 0.01, respectively). This is due to the use of very few variables that do not represent relevant features for the vulnerability assessment. Alternatively, DRASTIC and K-means cluster analysis obtained higher Spearman´s correlation coefficients (0.34 and 0.48, respectively). The relevant features selected by PCA analysis to use in the K-means low-dimensional analysis were depth of groundwater (D), net recharge (R), and land use (L). The new proposed method grouped data in three clusters that represent low vulnerability (35.9% of the study area), moderate (41.4%) and high vulnerability (22.7%). K-means increases the Spearman’s correlation by 14% with respect to the most approximate conventional method (DRASTIC). Therefore, the results obtained confirm the advantage of joint application of PCA and K-Means analysis, which represents a novel approach for the assessment of groundwater vulnerability in detrital aquifers.

Evaluation of Entre-os-Rios Thermal Aquifer Vulnerability Using DRASTIC Index

The “Entre-os-Rios” thermal aquifer has a protection perimeter buffer zone for avoiding water contamination. A vulnerability map was generated, using geographic information systems (GIS) tools and the DRASTIC index, to evaluate the risk of contamination of the perimeter area. The results showed that the protection perimeter buffer zone has an insignificant to moderate risk of pollution, with the DRASTIC index’s values ranging from 47 to 127 points, and an average pollution vulnerability of 79 points. The alluvium-covered land is vulnerable to moderate contamination but is located far from the catchment point. Areas of minimal risk correspond to locations where the granitic massif has not been altered significantly.
 Keywords: geographic information systems, vulnerability map, protection perimeter buffer zone, DRASTIC index