Pollution Intensity Research Articles

Small and medium-sized banks and pollution emissions from industrial enterprises

Drawing upon the theory of comparative advantage of small and medium-sized banks, this paper employs pollution data from industrial enterprises in China spanning 2000 to 2014. Utilizing the establishment of urban commercial bank branches in counties as a quasi-natural experiment, we investigate the impact of the development of small and medium-sized banks on industrial enterprises' pollutant emissions and the underlying mechanisms of this effect. Our findings reveal that the establishment of urban commercial bank branches in counties significantly reduces wastewater and sulfur dioxide emissions from enterprises, a result that remains robust across various tests. Further heterogeneity analyses show that this pollution reduction effect is more pronounced for small and medium-sized, more finance-constrained, start-up firms, and firms located in areas with low carbon pilots and higher levels of marketisation. The analysis of the impact mechanism suggests that the establishment of urban commercial banks achieves this reduction by increasing enterprise output, thereby diluting pollution intensity, and fostering green technological innovation, which enhances pollution treatment capabilities. Additionally, our research highlights that government intervention significantly influences the pollution reduction effect of urban commercial banks and the mode of this influence.

PM2.5 reduces the daytime/nighttime urban heat island intensity over mainland China

PM2.5 pollution severely threatens people's living environment and health, significantly affect urban heat island (UHI). In this study, in-situ observed data were combined with satellite data via refined pollution intensity classification methods, and the relationships between PM2.5 and canopy/surface UHI (CUHI/SUHI) were analyzed. PM2.5 reduced the UHI in nearly all the environments, with more pronounced effects during clear-sky daytime and winter (-0.33 °C for the SUHI) and less pronounced effects at all-sky nights and in summer. For the former, PM2.5 primarily diminishes the UHI intensity (UHII) by weakening incident radiation; this radiative forcing effect is exacerbated by the combination of PM2.5 and high humidity, which is further amplified by winter pollution peaks. At night, the UHII primarily influenced by the initial temperature conditions during the day. Less intake of surface energy on high-pollution days, which in turn affects longwave radiation from the surface/canopy at night. Additionally, PM2.5 has been found to significantly influence UHI through its interaction with potential influential factors and its filtering effect (different PM2.5 levels correspond to varying conditions of these factors). This study with new insights into the impact of PM2.5 on UHI could aid in the design of strategies to improve urban heat and pollution environments.

Shields against pollution: phytoremediation and impact of particulate matter on trees at Wigry National Park, Poland

This study examines the impact of airborne particulate matter (PM) and associated trace elements (TEs) on deciduous and coniferous trees at the edge of Wigry National Park in northeast Poland, focusing on pollution levels and the potential for phytoremediation. Researchers measured PM concentrations in the air and on the leaves of Picea abies, Quercus robur, and Corylus avellana, along with photosynthetic indicators (Fv/Fm ratio and performance index). The study found significant differences in pollution intensity across areas with varying levels of human activity. P. abies, an evergreen species, accumulated the highest PM levels (>200 μg/cm2), while Q. robur had the highest accumulation among deciduous trees (>50 μg/cm2). Trace elements such as Fe, Cu, Zn, Sr, and Cd were detected, with C. avellana being the most efficient in accumulating Cd (up to 7.5 mg/kg). The accumulation of pollutants correlated with reduced photosynthetic efficiency in trees closest to pollution sources. The findings suggest that strategically planting specific tree species can help mitigate air pollution in national parks and protect sensitive vegetation. Future research should explore the long-term effects of PM on forest health and the role of different species in phytoremediation.

Bottom-up discrete systematic modelling for analysis and prediction of future trends for land-sea environmental pollution systems

Addressing the challenge of marine environmental pollution requires accurate forecasting systems, yet current methods relying on artificial intelligence and big data face limitations due to insufficient and inconsistent marine data. This paper proposes an integrated bottom-up prediction system featuring a grey modeling module and an optimization module. The grey modeling module introduces a novel nonlinear nested systematic grey model, which employs multi-structure discretization to capture intricate and variable system changes by leveraging the dual nonlinearity of cumulative generated sequences and time trends. Nested solutions minimize prediction errors through discrete recursive equations with underlying-upper structures. The optimization module utilizes an efficient bio-inspired meta-heuristic algorithm, the Coati Optimization Algorithm, which balances global and local search strategies. The accuracy and robustness of the proposed model are enhanced by optimizing its nonlinear parameters through comparative analysis with other algorithms and conducting a sensitivity analysis on the number of iterations. The proposed prediction system is validated in representative Chinese provinces (Zhejiang, Shandong, and Hainan), demonstrating high prediction accuracy for both land-based and marine environmental pollution systems, with mean absolute percentage errors below 8% in both training and test sets. Projections indicate that by 2030, land-based source pollution intensities in these provinces will decrease by approximately 5.71%, 0.16%, and 1.64%, respectively, while marine pollution indices are expected to decline by 3.28%, 4.86%, and 2.89%. This study provides a valuable predictive tool for addressing the complexity, variability, and uncertainty of marine environmental pollution, while contributing to the promotion of land-sea integration and the protection of marine ecosystems.

LES of blockage of thermal radiation to the pool surface in large double pool fires.

Thermal radiation blockage to the pool surface plays a major role in assessing the fire growth and heat feedback to the pool surface and thereby intensity of pollution to the environment. In this work, large eddy fire simulations are performed to quantify the thermal radiation blockage to the pool surface of 0.6 m n-heptane double pool fires (DPF). The interspace between the two pools is varied from 0 to 0.6 m. The results of the air entrainment show that the considered double pool configuration is radiation dominated irrespective of the separation distances between the pools. The predicted heat feedbacks are in good agreement with the experimental results. A radiation influencing zone (RIZ) is introduced based on the percentage of the radiation contribution from the flame. RIZ is directly proportional to the flame height. Based on the opacity through the RIZ, the thermal radiation blockage is calculated. The blockage of radiation from standalone fire to double fire increased to 20%. The calculated radiative heat flux to the pool surface is in good agreement with the reported measurements. In addition, the maximum deviation between calculated and measured heat fluxes of the studied DPF is 6.8%. Further, the accuracy of the present methodology is shown better than the reported literature estimations.

Composition of the Low Molecular Weight Metabolome of Potamogeton perfoliatus (Potamogetonaceae) as an Indicator of the Transformation of the Ecological State of the Littoral Zone

The composition and nature of changes in the low-molecular-weight metabolome (NM) of Potamogeton perfoliatus L., growing in 6 biotopes of Lake Ladoga with different types of the anthropogenic load has been analyzed. According to the research results, it was found that the total number of low molecular weight organic compounds (LMWOCs) in the P. perfoliatus NM composition is directly dependent on anthropogenic load, which is well marked by the development of cyanobacteria. The greater the intensity of pollution or eutrophication of waters, or the higher the number of cyanobacteria, the lower the total number of LMWOCs and their concentration. A strongly pronounced dependence of the total concentrations of groups of NM compounds on the anthropogenic disturbance of the biotope and the concentration of cyanobacteria was revealed. A decrease in the number, relative amount, total concentration of carboxylic acids, number and content of unsaturated fatty acids, and, at the same time, an increase in the composition and content of phenols and the total content of aldehydes and ketones depends on an increase in anthropogenic pressure. The specific composition of NM of pierced pondweed depends on its response to biotic and abiotic factors of the aquatic environment, including anthropogenic ones. The revealed features of the change in the composition of P. perfoliatus NM make it possible to use it as an integral indicator of the anthropogenic impact on the littoral biotopes of water bodies and the deterioration of their ecological state.

Sustainable Urban Development: A Comprehensive Model for Assessing Health Risks from Compounded Pollution in Xi’an

Global climate change and rapid urbanization have brought unprecedented environmental challenges, especially in rapidly expanding cities like Xi’an, posing potential challenges to sustainable development if not accompanied by adequate greenery, thoughtful layouts, and pollution control measures. The increasing frequency and intensity of urban air pollution (e.g., PM2.5, PM10, O3) and extreme climate events (e.g., heatwaves) have heightened health risks for residents. Existing studies mostly focus on single pollution or climate factors, neglecting the compounded effects of these factors. To fill this research gap, this study presents a health risk assessment model, specifically by analyzing the compounded effects of heatwaves and air pollution. By integrating hazard, exposure, and vulnerability factors using the entropy weight–TOPSIS method, the results reveal significant spatial differences in health risks across various regions of Xi’an. The findings provide valuable guidance for urban planners and policymakers to better address environmental hazards, reduce health risks, and promote sustainable urban development.

Beautifying urban environment: Smart city construction and sustainable pollution control in China

Faced with the environmental pollution challenges brought by urbanization, smart city construction (SCC) offers a practical and viable pathway for environmental protection. This study treats China's SCC policy as a quasi-natural experiment, utilizing balanced panel data from 285 cities across the country spanning from 2003 to 2019. Through the multi-period Difference-in-Differences (DID) model, the influence of smart city initiatives on urban pollution emissions is systematically examined. Results demonstrate that SCC effectively control urban pollution emissions, leading to a 1.46% decrease in pollution levels in pilot cities. These findings are robust to various tests, including parallel trends analysis, placebo tests, Propensity Score Matching (PSM)-DID, alternative pollution calculation methods, pollution intensity adjustments, control for other policy interferences, and sample adjustments, alongside endogeneity tests using instrumental variables. SCC achieves pollution control through mechanisms that enhance urban technological innovation, facilitate industrial restructuring, and talent agglomeration and financial agglomeration. Heterogeneity analysis reveals a more pronounced impact in the eastern area, large cities, higher administrative levels, cities with superior digital infrastructure, and those with higher human capital levels and pollution severity. This research explores a practical approach towards achieving sustainable pollution control by optimizing technology, industrial structure, and human resources.

The Characteristics and Traceability Analysis of the Overflow Pollution During the Flood Season in an Urban Area

The issue of combined sewer overflow (CSO) triggered by rainfall has become a significant obstacle to the improvement of water environment quality. This study conducted a long-term monitoring of three types of rainwater outlets, i.e., combined sewer overflows (Test-CSO), separated sewer outlets (Test-SSO), and partially separated sewer outlets (Test-PSSO), to reveal the characteristics of overflow pollution and trace its sources by monitoring the pollutants from different underlying surfaces across various urban functional areas. The results showed that the major pollutants in overflow events exhibited the following order: COD ≥ TSS > TN > TAN > TP. Rainwater elevated COD and TSS in the Test-CSO, while reducing nitrogen and phosphorus concentrations by dilution. The Test-PSSO experienced varying degrees of overflow pollution, primarily due to the sewer sediment. A negative relationship between the rainfall and peak time of overflow pollution was observed. The traceability analysis indicated the overall pollution intensity exhibited the following order: residential areas > industrial parks > commercial areas. In addition to commercial areas, the pollution intensity across underlying surfaces generally exhibited the following order: roofs > roads > grasslands. The roof runoff was an important source of pollutants for overflow pollution, and TSS and COD were the major contributors. Notably, grasslands had a buffering effect on pollutants and pH.

Environmental taxes, offshoring and welfare: The effects of environmental damage and pollution intensity

We analyze the effects of domestic environmental damage and pollution intensity on a monopolist final good producer’s incentive for offshoring a critical intermediate good. Contrary to the usual pollution haven hypothesis, we find that a higher domestic environmental damage, which creates a higher domestic environmental tax, may decrease the incentive for offshoring. This trend is enhanced by a higher pollution intensity of the final good production. Hence, a lower pollution intensity of the final good production may increase offshoring and pollution leakage. Offshoring in our analysis can be excessive or insufficient from the point of view of the domestic country.

Characteristics of iron-sulfur metabolism and acid-producing microorganisms in groundwater contaminated by acid mine drainage in closed coal mines

The generation of acid mine drainage (AMD) from mining activities poses significant challenges to humanity due to its intense pollution and difficult management. Despite the hostile conditions presented by AMD, a plethora of microorganisms thrive in this environment. In this study, we employ metagenomic techniques and microbial diversity analysis to systematically categorize microorganisms. Specifically, we identify Sulfur-iron metabolizing microorganisms associated with AMD, encompassing 6 phyla and 1149 genera. Functional predictions and pathogenicity analyses are conducted on this microbial community. Furthermore, we specifically emphasize the study of acid-producing microorganisms. This research marks the first discussion on the scope and structure of acid-producing microorganisms., comprising 1 phylum, 39 genera, and 1393 species. Our research outcomes comprehensively depict the microbial diversity in AMD, unveiling their influence on the physicochemical properties of AMD pollution. This study contributes valuable insights to addressing environmental challenges arising from AMD and aids in its remediation.

Unveiling Environmental Crime Trends and Intensity in the EU Countries Through a Sustainability Lens

AbstractEnvironmental crime poses a significant threat to global ecosystems, biodiversity, and human well-being, encompassing activities such as pollution, illegal waste disposal, trade in protected species, and natural resource degradation. Understanding the dynamics of these crimes is essential for devising effective mitigation strategies and promoting sustainability at micro, meso, and macro level. The aim of the study is to examine environmental crimes in the EU, focusing on their current trends, patterns, and Intensity, as well as the impact on sustainability across its three dimensions. Fourteen EU countries environmental crime data from 2016 to 2021were analysed to reveal variations and trends. Geographic information systems (GIS) utilized to identify countries with elevated environmental crime rates, emphasizing the need for interventions in pollution control, waste management, and resource conservation. Results indicate high environmental pollution intensity in Italy, Sweden, and Denmark. Moreover, Italy emerges as the epicentre of illegal waste dumping, with notable cases also present in Belgium and France. Additionally, France, Slovakia, and Italy show alarming levels of illegal wildlife trade. Furthermore, France and Sweden exhibit the highest density of natural resource degradation cases. In addition, the study unveiled a positive correlation ($$\:b>0$$) between environmental pollution, trade in protected species, and natural resource degradation with population growth, while waste disposal exhibited a negative correlation ($$\:b<0$$). Moreover, trade in protected species and resource degradation correlated negatively ($$\:b<0$$) with the poverty ratio. Addressing environmental crimes aligns with the pursuit of green justice, recognizing the interconnectedness of environmental, social, and economic factors. The findings offer valuable insights for policymakers, environmentalists, and communities, guiding interventions towards a sustainable and resilient future.

Correlation relationships of processes in the combustion engine in the RDE test

The article presents considerations on the processes taking place in the combustion engine in the in real driving operating conditions of a vehicle performing the RDE (Real Driving Emissions) test. The tests were carried out using a passenger car with a spark-ignition engine. The processes considered in the article were related to the engine operating states, exhaust emissions and fuel consumption, and the vehicle speed, which determines the engine operating conditions. The RDE test were carried out using PEMS (Portable Emissions Measurement System) equipment, and the following variables were recorded: vehicle speed, control, rotational speed, relative torque and relative engine power, emission pollutant intensity of: carbon monoxide, hydrocarbons, nitrogen oxides and carbon dioxide, the intensity of particle number and the fuel consumption intensity. The recorded signals were digitally processed, and the statistical properties of the variables and the mutual relation between the engine operating states were examined. The properties of the measured variables were investigated in the entire RDE test and in its constituent phases: the first, corresponding to vehicle movement in cities, the second – outside cities, and the third – on highways and expressways. The pollutant specific distance emission and the particle number specific distance as well as the specific distance fuel consumption were determined in relation to the average vehicle speed, and based on these results, the exhaust emissions and fuel consumption characteristics were created. Correlational studies of the considered variables were also performed. Pearson's linear correlation coefficients for the measured variables combinations were determined.

Digitalization and Automation and AI: A Theoretical Framework of rethinking the Pollution Haven Hypothesis

This theoretical paper investigates the impact of digitalization, automation, and artificial intelligence (AI) on environmental regulations, specifically through the lens of the Pollution Haven Hypothesis (PHH). It explores how these advancements influence pollution intensity and environmental compliance costs, challenging the traditional understanding of the PHH. Methodology. The study employs a Cobb-Douglas production function to model the relationship between technological innovations and environmental regulations. By integrating digitalization, automation, and AI into the model, the paper examines how these factors affect the economic incentives for firms to relocate to regions with lenient environmental standards. Findings. The analysis reveals that advancements in digitalization and automation reduce pollution intensity and lower the costs of complying with strict environmental standards. As a result, the economic incentive to relocate to pollution havens diminishes. In an open economy, the combination of stringent environmental policies and technological innovations leads to reduced pollution levels and a shift toward cleaner production processes. Practical Implication. The findings suggest that integrating technological innovations into environmental policy can make adherence to stricter regulations more economically viable, thereby weakening the appeal of pollution havens. This has significant implications for global sustainability efforts, as it highlights the potential for technology to support more effective and equitable environmental regulations. Originality. This study introduces a novel perspective by directly linking technological innovations to shifts in capital allocation and the efficacy of environmental policies. It offers a fresh understanding of the PHH in the context of modern advancements, providing new understanding into the relationship between innovation and environmental regulation.

Electro-Fenton enhanced MBR for fouling alleviation based on MIL-88B-Fe derived carbon membrane with in-situ generated [rad]OH

Porous carbon membrane (PCM) derived from MIL-88B-Fe with the ability of in-situ generation of hydroxyl radical was introduced to electro-enhanced aerobic membrane bioreactor (EMBR) for membrane fouling mitigation and wastewater quality improvement. The resultant PCM obtained with the calcination temperature of 1000 °C owned significant enhancement on hydrophilic and conductive properties, which helped PCM under −1.2 V could completely remove 10 mg/L bovine serum albumin with 2.5 % membrane flux loss rate. During the 76-day operation of EMBR, the extracellular polymeric substances could be suppressed for depositing on the −1.2 V enhanced PCM due to the combined effect of electrostatic barrier and OH oxidation. The pollutant intensity of total cells, polysaccharides and proteins were all reduced on PCM with −1.2 V. After operation, 36.0 % of cake layer pores was blocked in EMBR by total cells, polysaccharides and proteins. However, it was accounted for 69.8 % of the control group. Above results explained why the EMBR owned an always lower transmembrane pressure. Meanwhile, the pollutants removal rates of COD and NH4+-N were as high as 95 % and 98 % with electro-enhanced filtration, respectively, which is attributed to the collaborated effect from electrochemical effect and significantly increased microbial species related to organic pollutants removal, such as Azohydromonas, Thermomonas.

Spatial source, simulating improvement, and short-term health effect of high PM2.5 exposure during mutation event in the key urban agglomeration regions in China

Air quality in China has significantly improved owing to the effective implementation of pollution control measures. However, mutation events caused by short-term spikes in PM2.5 in urban agglomeration regions continue to occur frequently. Identifying the spatial sources and influencing factors, as well as improving the prediction accuracy of high PM2.5 during mutation events, are crucial for public health. In this study, we firstly introduced discrete wavelet transform (DWT) to identify the mutation events with high PM2.5 concentration in the four key urban agglomerations, and evaluated the spatial sources for the polluted scenario using Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model. Additionally, DWT was combined with a widely used artificial neural network (ANN) to improve the prediction accuracy of PM2.5 concentration seven days in advance (seven-day forecast). Results indicated that mutation events commonly occurred in the northern regions during winter time, which were under the control of both short-range transportation of dirty airmass as well as negative meteorology conditions. Compared with the ANN model alone, the average band errors decreased by 9% when using DWT-ANN model. The average correlation coefficient (R) and root mean square error (RMSE) obtained using the DWT-ANN improved by 10% and 12% compared to those obtained using the ANN, indicating the efficiency and accuracy of simulating PM2.5, by combining the DWT and ANN. The short-term mortality during mutation events was then calculated, with the total averted all-cause, cardiovascular, and respiratory deaths in the four regions, being 4751, 2554, and 582 persons, respectively. A declining trend in prevented deaths from 2018 to 2020 demonstrated that the pollution intensity during mutation events gradually decreased owing to the implementation of the Three-Year Action Plan to Win the Blue Sky Defense War. The method proposed in this study can be used by policymakers to take preventive measures in response to a sudden increase in PM2.5, thereby ensuring public health.

Foreign Direct Investment and Technology Licensing in a Polluting Industry

We consider a firm’s incentive for foreign direct investment (FDI) and international technology licensing in a polluting industry. We explain the rationale and the welfare implications of complementarity between FDI and licensing, i.e., the firm’s strategy of “FDI and licensing” (FL), which is empirically relevant but ignored in the literature. When the environmental tax cannot be committed, the firm adopts the licensing strategy if the pollution intensity is not high, and the licensing strategy may create lower consumer surplus and welfare compared to both FDI and FL. However, if the pollution intensity is high, the firm undertakes FL, which provide higher consumer surplus and welfare compared to both licensing and FDI. When the government can commit to the environmental tax, the firm always prefers FL. The host-country welfare is higher but the consumer surplus and world welfare may be lower under the committed tax policy compared to the non-committed tax policy. These results hold under Cournot competition and Stackelberg competition. We further show that FL can be the equilibrium strategy of the foreign firm if there is fixed-fee licensing instead of a two-part tariff licensing, which is considered in the main analysis.

Potentially toxic elements of lake and wetland in Northeastern Qinghai-Tibet Plateau: Distribution, potential sources and risk assessment

The accumulation of toxic elements from sediments poses imminent threats to both the environment and humans. The variation of elements in different sedimentary systems within the same watershed is of significant importance for distinguishing the human activities and adopting relevant management strategies. Based on the surface sediment samples from the Lake Keluke and its wetland, the content and grain size of elements were analyzed. The human health risk indicated in the area the potentially toxic elements (PTEs: Cr, Cu, Zn, Cd and Pb) were at no non-carcinogenic risk to adults or children. Except for Cd, the pollution levels of other PTEs were clean, and potential ecological risk with a low level. However, the pollution of Cd implicated a moderate to heavy pollution intensity and a high ecological risk. According to principal component analysis (PCA), and self-organizing maps (SOM), the main sources of PTEs were of the weathering and leaching of bedrocks; transportation and human agriculture activities. The watershed should reduce pollution caused by human activities and implement efficient agricultural practices.

Regression dependence of the number growth dynamics of the biogas plants in Ukraine

The global environmental crisis forces the countries of the world to introduce and use new alternative means of energy production, in particular methods of extraction and processing of biogas to provide energy to the population. Therefore, the determination of the regression dependence, which describes the dynamics of the increase in the number of biogas plants and can be used when forecasting the number of such plants, is an urgent scientific and technical task. The purpose of the research is to determine the regression dependence, which describes the dynamics of the increase in the number of biogas plants and can be used when forecasting the number of such plants, with the aim of increasing the prevalence of the use of renewable energy sources, saving fossil energy sources and simultaneously reducing the intensity of environmental pollution. During the research, the method of regression analysis of the results of one-factor experiments and other paired dependencies was used with the selection of a rational type of function from the sixteen most common options according to the criterion of the maximum value of the correlation coefficient. Regression was carried out on the basis of linearizing transformations, which allow reducing the non-linear dependence to a linear one. The coefficients of the regression equations were determined by the method of least squares using the developed computer program "RegAnalyz", which is protected by a certificate of copyright registration for the work. An adequate regression relationship was obtained, which describes the dynamics of the increase in the number of biogas plants and can be used when forecasting the number of such plants. A graphical dependence was built that describes the dynamics of the increase in the number of biogas plants and allows to visually illustrate this dynamic and show sufficient convergence of theoretical results with actual data. It was established that the increase in the number of biogas plants in Ukraine during 2012-2019 grew according to a hyperbolic dependence.

Assessment of risk intensity in the triffa plain aquifer: Integration of hazard quantification, land use analysis, dynamic vulnerability GCITF, and DRASTIC method

This study aims to assess the level of groundwater pollution risk in the Triffa Plain, stemming from various pollution sources, with a specific focus on agricultural intensification and excessive pesticide use. Data were collected from ABHM (the Moulouya Hydraulic Basin Agency) and ORMVAM (Regional Office of Moulouya Agricultural Development), and a field visit was conducted in July 2023. The study utilized two main methodologies for mapping risk intensity: the COST 620 action and overlaying vulnerability maps with the land use (LU) factor. Vulnerability maps were generated using the original DRASTIC method and the new dynamic vulnerability assessment method, GCITF.The research approach involved comparing the COST 620 risk index (Ri) and the land use risk index (LU) to identify the most suitable method for the study area. Due to challenges in inventorying various point sources of pollution, the study focused on mapping the primary sources of pollution (diffuse, point, and linear). The key findings indicate that the predominant pollution intensity in the region is high, covering 60.66% of the total surface area. These results closely align with those obtained using the European COST 620 approach and the spatial distribution of nitrates. The study demonstrates the reliability of integrating the GCITF method in assessing groundwater contamination risk, highlighting the significant negative impacts of agricultural activities on the Triffa Plain aquifer, primarily due to uncontrolled pesticide and fertilizer use and point sources of pollution.This study suggests that implementing targeted technical solutions for specific pollution sources is crucial for reducing contamination in the Triffa Plain. These pollution risk intensity maps can assist planners and decision-makers in understanding the origin of pollution and identifying necessary actions to minimize contamination risk, contributing to better groundwater management and protection in the region.