Identification Of Pollution Sources Research Articles

Identification of pollution sources in river based on particle swarm optimization

Identification of pollution sources in river based on particle swarm optimization

Prevalence, Distribution, and Genotypes of Adenovirus and Norovirus in the Puzi River and Its Tributaries and the Surrounding Areas in Taiwan.

This study investigated the prevalence, distribution, and genotypes of adenoviruses (AdVs) and noroviruses (NoVs) in the Puzi River and surrounding areas in Taiwan. The viruses in the water samples were isolated using the membrane filtration method and the viral nucleic acids were extracted. The RNA of NoVs was reverse‐transcribed into complementary DNA using reverse transcriptase‐polymerase chain reaction. AdVs and NoVs were detected using nested PCR. Genotyping and phylogenetic analyses were performed to identify the various viral genotypes in the water samples. Human adenovirus (HAdVs) and porcine adenovirus (PAdVs) were the predominant genotypes in the water samples. The prevalence of F species HAdVs serotype 41 (79.2%) and C species PAdVs serotype 5 (18.1%) was higher than that of other serotypes. Among NoVs, genogroup GII was more prevalent than GI. In particular, GII.4 (21.2%) and GII.17 (18.2%) were the predominant genotypes, which was consistent with the clinical findings. The prevalence of both AdVs and NoVs was higher in the winter than spring, summer and autumn seasons. AdVs and NoVs detection results were statistically analyzed by investigating their association with water quality indicators. The results revealed that the presence of AdVs was significantly correlated with the heterotrophic bacterial count, total coliform Escherichia coli, turbidity, salinity, and dissolved oxygen. Meanwhile, the presence of NoVs was only significantly correlated with temperature, pH, and dissolved oxygen. Microbial pollution sources may include urban runoff and discharge of water from livestock farms situated near the river and tributaries within this region of Taiwan. Future studies should include comparisons of the presence of AdVs and NoVs in these known pollution sources and water quality monitoring of these watersheds, as this will allow potential identification of pollution sources. Additionally, remediation strategies must be developed to minimize viral contamination in the river ecosystem.

Pollution zoning on the southern shores of the Caspian Sea by measuring metals in Rutilus kutum tissue.

The aim of this study was to bio monitor the status of heavy metals on the southern shores of the Caspian Sea by determining the concentration of these metals in the tissue of Rutilus kutum. Sampling of kidney tissue, liver, muscle, skin, and gonad of this fish was performed in 5 sites. Sampling was performed in Anzali, Kiashahr, Astara, Farahabad, and Bandar Torkaman from September 2017 to January 2018. In this study, the concentration of elements in different tissues was determined. Contamination zonation was determined by the concentration of metals in fish tissues. The highest amount of Pb accumulation (0.73ppb) was determined in Astara and Anzali regions and in liver tissue. The highest amount of Cd (0.23ppb) was reported in Astara region and in fish liver. Zoning showed that the concentration of most elements in the west of the Caspian Sea is higher than in the east; in other words, the west of the Caspian Sea is more polluted than the east. Existence of polluting sources such as ports, customs, agricultural lands, and tourism industry are important factors of pollution in these areas. Annual biological monitoring along with accurate identification of pollutant sources can help reduce this pollution, especially in the western part of the Caspian Sea. This study showed that the use of zoning technique in environmental studies as an effective management tool can be very useful in providing appropriate ways to identify and control sources and pollutants in the coast.

The implementation of genetic algorithm for the identification of DNAPL sources

Contamination caused by dense non-aqueous phase liquids (DNAPLs) is a serious peril to the groundwater supply quality. The DNAPLs are largely undetected and yet are likely to be a significant factor limiting site remediation. It is necessary to identify the sources of pollution and control pollution in the early stage. The primary objective of this research was to investigate the pollution source and intensity of migrating DNAPLs. This objective was accomplished through the combination of genetic algorithm (GA) and T2VOC numerical experimental simulation. This study considers two synthetic cases of numerical modeling based on the T2VOC from the TOUGH2 code family to assess and evaluate the efficacity of the algorithm. The first case identified concurrently the intensity as well as the location of the one unknown contaminated water source. The second case distinguished various contaminated water sources. For the single source pollution identification, the estimation of intensity error was 0.08%, and the error of GA at second and third true value calculation was 0.05% and 0.03%, respectively, achieving the goal of pollution identification accurately. While for the multiple sources, the deviation of intensity was ranging between 1.02 and 5.65%, the results suggested that source No.2 was mainly responsible for the leakage, and source No.3 adopted the secondary responsibility among others. These two cases suggested that GA established by optimal search strategy could be adopted for effective identification of DNAPL pollution sources. This study provides information that could facilitate the development and implementation of innovative remediation strategies.

Source identification of pollution and health risks to metals in household indoor and outdoor dust: A cross-sectional study in a typical mining town, China

Dust is regarded as an important pathway of heavy metal(loid)s to the human body. Health risks posed by metal(loid)s from household dust are of particular concern. However, the contamination and sources of heavy metal(loid)s in household dust environments, as well as source identification of health risks related to heavy metal(loid)s from household dust for vulnerable populations such as children, have not been thoroughly studied in China, particularly for the areas involved with industrial activities such as ore mining. Thus, a cross-sectional study was conducted in a rural area famous for Pb/Zn ore mining, to assess the pollution sources and health risks of heavy metal(loid)s from household indoor and outdoor dust and to identify the contribution of household dust to the health risks for children. The results indicated that household environment was heavily contaminated by metal(loid)s, which were mainly attributed to mining activity. Meanwhile, the indoor/outdoor ratio and the redundancy analysis indicated that there were other pollution sources in indoor environments such as coal combustion, materials for interior building and decoration. Vapor inhalation was the main exposure pathway for Hg, while ingestion was the predominant pathway for other metal(loid)s. Although the cancer risks were relatively low, the HIt from household indoor and outdoor dust (2.19) was about twice the acceptable limit (1) and was primarily from Pb (64.52%) and As (23.42%). Outdoor dust was a larger contributor to the HI of Sb, As, Cr, Cd, Zn and Pb, which accounted for 51.37%, 58.63%, 52.14%, 59.66%, 52.87% and 64.47%, respectively, and the HIt was mainly from outdoor dust (60.76%). These results indicated that non-cancer health risks were largely from outdoor dust exposure, and strengthened the notion that concern should be given to the potential health risks from metal(loid)s in household dust both originating from mining activity and indoor environmental sources.

Integrated Surface-Groundwater Modelling of Nitrate Concentration in Mediterranean Rivers, the Júcar River Basin District, Spain

High nutrient discharge from groundwater (GW) into surface water (SW) have multiple undesirable effects on river water quality. With the aim to estimate the impact of anthropic pressures and river–aquifer interactions on nitrate status in SW, this study integrates two hydrological simulation and water quality models. PATRICAL models SW–GW interactions and RREA models streamflow changes due to human activity. The models were applied to the Júcar River Basin District (RBD), where 33% of the aquifers have a concentration above 50 mg NO3−/L. As a result, there is a direct linear correlation between the nitrate concentration in rivers and aquifers (Júcar r2 = 0.9, and Turia r2 = 0.8), since in these Mediterranean basins, the main amount of river flows comes from groundwater discharge. The concentration of nitrates in rivers and GW tends to increase downstream of the district, where artificial surfaces and agriculture are concentrated. The total NO3− load to Júcar RBD rivers was estimated at 10,202 tN/year (239 kg/km2/year), from which 99% is generated by diffuse pollution, and 3378 tN/year (79 kg/km2/year) is discharged into the Mediterranean Sea. Changes in nitrate concentration in the RBD rivers are strongly related to the source of irrigation water, river–aquifer interactions, and flow regulation. The models used in this paper allow the identification of pollution sources, the forecasting of nitrate concentration in surface and groundwater, and the evaluation of the efficiency of measures to prevent water degradation, among other applications.

Pollution sources identification, health, and radiological risk assessment of naturally occurring radioisotopes and heavy metals in waste dumpsites in Ijebu-Ode, Ogun State, Southwest Nigeria

This study evaluates human health, pollution, and radiological risk assessment of potentially toxic metals (PTMs) (Pb, Cd, Cr, Ni, and Zn), radioisotopes (238U, 232Th, and 40K) and its associated radiological indices from dumpsite soils in Ogun State, Nigeria, using a calibrated atomic absorption spectrophotometer (AAS) and highly shielded γ-ray spectrometry using NaI(TI) detector. Fourier transform infrared spectrometer (FTIR) complemented by X-ray diffraction (XRD) techniques were used to evaluate the mineralogical composition of the soils. Multivariate statistical analysis was used to apportion the source of PTMs and the radioisotopes. The mean concentration of Pb, Cd, Cr, Ni, and Zn obtained were 22.35, 17.95, 20.83, 19.02, and 75.88 mg kg−1, respectively. The activity concentrations of 238U, 232Th, and 40K ranged from 49.71 ± 16.3 − 314.15 ± 55.2, BDL − 87.54 ± 7.38, and BDL − 3721.3 ± 231.6 Bqkg−1, respectively. The values obtained were above the global average value in most of the samples. According to the four-pollution and ecological risk assessment model, the dumpsite soils are strongly to low polluted and enriched with toxic metals in the order Zn > Cr > Pb > Ni > Cd. The estimated carcinogenic risk of the three carcinogenic PTMs for children and adults were higher than the acceptable limit (1 × 10−6). The results of the PCA and HCA results are consistent with the correlation coefficient analysis which showed that mixed natural, anthropogenic and lithogenic sources mainly from aggregation of lead-containing materials in the waste on the dumpsite, vehicular emission and industrial discharges are the main sources of Pb, Ni, and Cd in the three studied dumpsites. Thus, dumpsite soil poses great threat to health, increased pollution and enhances the radiological risk to the general population via human multiple exposure routes.

Pollution characteristics, spatial distribution, and source identification of heavy metals in road dust in a central eastern city in China: a comprehensive survey.

Road dust enriched with heavy metals (HMs) is detrimental to ecosystems and human health in urban environments. In this study, it is to explore the concentrations, spatial distribution, contaminated levels, and source identification of six HMs (lead (Pb), zinc (Zn), copper (Cu), cobalt (Co), chromium (Cr), and nickel (Ni)) based on 130 road dusts in Xinyang urban area. The results indicated that the contents of Pb, Zn, Cu, and Co were higher than the background values in more than 99% of the samples, and their average concentrations were 15.2, 9.2, 8.6, and 6.3 times the background value, respectively. The spatial distribution of high-value areas for Pb, Zn, Cu, Cr, and Ni was more similar, which was associated with traffic density near major roads and population and settlement patterns. Co was relatively different from the five elements, which was distributed in the areas of residence, commerce, and industry. Furthermore, the investigated HMs were clearly polluted, with Pb, Zn, Cu, and Co indicating high levels of contamination, while Cr and Ni were moderately polluted. The comprehensive pollution of the six HMs was mostly moderate to heavy in this study. Moreover, three sources of HMs designated by correlation analysis (CA) and principal component analysis (PCA) were mixed traffic emissions and industrial waste for Cu and Cr; automotive emissions for Pb, Ni, and Zn; and mixed domestic waste and industrial activities for Co, with contributions of 42.3%, 46.4%, and 11.3% via the principal component analysis-multiple linear regression (PCA-MLR) model. The multi-factor index for pollution assessment combined with source identification is extremely effective and practical for providing reliable data support and a theoretical reference for pollution monitoring and governance.

Research Advances in the Analysis of Nitrate Pollution Sources in a Freshwater Environment Using δ15N-NO3− and δ18O-NO3−

Nitrate is usually the main pollution factor in the river water and groundwater environment because it has the characteristics of stable properties, high solubility and easy migration. In order to ensure the safety of water supply and effectively control nitrate pollution, it is very important to accurately identify the pollution sources of nitrate in freshwater environment. At present, as the most accurate source analysis method, isotope technology is widely used to identify the pollution sources of nitrate in water environment. However, the complexity of nitrate pollution sources and nitrogen migration and transformation in the water environment, coupled with the isotopic fractionation, has changed the nitrogen and oxygen isotopic values of nitrate in the initial water body, resulting in certain limitations in the application of this technology. This review systematically summarized the typical δ15N and δ18O-NO3− ranges of NO3− sources, described the progress in the application of isotope technique to identify nitrate pollution sources in water environment, analyzed the application of isotope technique in identifying the migration and transformation of nitrogen in water environment, and introduced the method of quantitative source apportionment. Lastly, we discussed the deficiency of isotope technique in nitrate pollution source identification and described the future development direction of the pollution source apportionment of nitrate in water environment.

Optimal emission control and identification of an unknown pollution source

The advection-diffusion-reaction equation is used for describing the dispersion of a quasi-passive contaminant from industrial point sources in a limited area. The conditions established on the open boundary ensure that the problem is correct in the sense of Hadamard, that is, its solution exists, is unique, and is stable to initial perturbations. The Lagrange identity is used to construct the adjoint operator and formulate an adjoint problem. Equivalent direct and adjoint estimates are derived to assess the concentration of the pollutant at monitoring sites of the area. Formulas obtained on the basis of adjoint estimates are useful in analysing the sensitivity of the model to both variations in the intensity of pollution sources and variations in the initial distribution of the pollutant concentration in the area. New optimal emission control strategies based on using the adjoint estimates are developed in order to prevent violations of existing sanitary standards by timely reduction of emission rates of operating sources. Optimal control here lies in minimizing these reductions. In addition, this control is primarily aimed at reducing the intensity of emissions from sources that most pollute the monitoring site. Also, new methods are proposed for identifying the main parameters of an unknown point source that arose as a result of a dangerous incident (accident, explosion, etc.). These methods allow determining the location and intensity of a constant or non-stationary point source, as well as the moment of emission of a pollutant in the case of an instantaneous point source. This helps to quickly assess the scale of the incident and its consequences. Numerical results show the effectiveness of the methods.

Participatory process in environmental monitoring design: examples from the Port of Limassol

Sea transport and seaborne trade have increased significantly in the past few decades. As sea traffic hubs, ports have high risks because of the limitation in manoeuvrability, number of vessels, and land-based port activities. In the coastal city of Limassol, water and air pollution has been anecdotally attributed to port activities. The STEAM project (Sea Traffic Management in the Eastern Mediterranean, INTEGRATED/0916/0063, [1]) aims to set up a monitoring plan to aid in the identification and mitigation of pollution sources. The project followed a participatory process, where port stakeholders and scientists were consulted and included in the ideation, design and implementation process. This participatory process developed a greater sense of stakeholder ownership in the environmental monitoring programs and facilitated their adoption. According to the consultation process, air and water quality are the most important factors to monitor. Five static and one mobile multi-sensor monitoring stations make up the air quality monitoring design for the Port of Limassol. Three air quality stations were installed within the port area along with two stations near the anchorage area. Two environmental data buoys and two oil detectors make up the water quality monitoring stations. The oil detectors will be placed within the port. One environmental data buoy will be placed downstream of the port, while the second buoy will be placed between the port entrance, the Limassol Marina and the anchorage area.

Determination of load capacity of BOD pollutant in Cisadane River with Qual2kw model & its effect on DO parameters

The research to determine the carrying capacity of pollutant loads in the middle to downstream Cisadane River segment started from Jl. Teuku Umar, Tangerang and ends at Muara Tanjung Burung, Tangerang Regency with a research time starting from March – June 2021. Increased land-use change due to human and industrial activities so that population growth and limited residential land make watersheds a target for land conversion. The purpose of this study is to identify sources of pollutants that have the potential to contaminate the Cisadane River in the middle to downstream segments, analyze water quality and pollutant load capacity, the Cisadane River in the middle to downstream segments along 34 km. The method used for identification of pollutant sources is carried out by conducting field surveys, water quality analysis is carried out by SNI and compared with quality standards according to Peraturan Pemerintah No. 22 of 2021, as well as analysis of the Pollutant Load Capacity (PLC) BOD and DO using the QUAL2Kw model. The results of identifying potential pollutant sources in the middle to a downstream segment of the Cisadane River are dominated by settlements, agriculture, industry, and other domestic activities, namely restaurants and stalls. The results of water quality analysis for BOD parameters ranged from 2.51 mg/L - 5.1 mg/L, and DO range from 5.4 mg/L – 7,2 mg/L. BOD parameters from all points 1-2 meet the quality standard class 2 (3 mg/L) & points 4-6 do not meet the quality standard. The DO parameter is still in good condition because the more significant the DO value, the waters are in good condition. The high levels of BOD in the Cisadane River are influenced by domestic waste that enters the river, and the land is dominated by built-up spaces as settlements, schools, hotels and malls. Land use around the river is very influential on the load of pollutants that enter the river. The lowest DTBP of the Cisadane River for BOD is 22497,9 kg/day, and the highest is 33201,6 kg/day. The decrease in the concentration of BOD load must be lowered in the Cisadane River by 29% - 42%.

Source identification of surface water pollution using multivariate statistics combined with physicochemical and socioeconomic parameters

Accurate identification of potential contamination sources of river water is a basis for effective pollution control and sustainable water management. Pollution source identification based on physicochemical-parameters-only method may lead to uncertainty and subjectivity. In this study along with hydrochemistry parameters (HPs), socioeconomic parameters (SPs) were considered as an auxiliary in multivariate statistics to achieve a comprehensive assessment on pollution sources with accurate estimates of source identification and apportionment. Fifteen physicochemical parameters were combined with twelve socioeconomic parameters in multivariate statistics to quantitatively assess potential pollution sources and their contributions to river water pollution. Multivariate statistics in the study included regression analysis, principal component analysis (PCA), and absolute principal component score-multiple linear regression (APCS-MLR). Regression analysis between hydro-chemical parameters and socioeconomic parameters indicated that industrial and population growths were the main factors related to ammonium nitrogen (NH4+-N), total nitrogen (TN) contamination, while total phosphorus (TP) was more correlated with domestic discharge and poultry breeding. Based on the results of PCA, four latent factors were extracted for hydrochemistry parameters (HPs) and socioeconomics parameters (SPs), accounting for 68.59% and 82.40% of the total variance, respectively. With integrating the PCA results of the two parameter groups, pollution sources were ranked as industrial effluents > rural wastewater > municipal sewage > phytoplankton growth and agricultural cultivation. Source apportionment in APCS-MLR revealed that industrial wastewater and rural wastewater averagely contributed 35.68% and 25.08% of pollution, respectively, followed by municipal sewage (18.73%) and phytoplankton pollution (15.13%) with relatively small percentage of unrecognized source. It is concluded that socioeconomic parameters assisting hydrochemistry parameters in multivariate statistics can improve the accuracy and certainty of pollution source identification, supporting decision makers to formulate strategies on protection of river water quality.

Identification of heavy metal pollution sources and its associated risk assessment in an industrial town using the K-means clustering technique

This study intends to (i) identify the potential sources of heavy metal (HM) pollution in an industrial town situated in the northwestern part of Iran and (ii) and assess whether the pollution levels discharged by HMs are significant. A suite of geochemical samples collected from the topsoil horizon of the study area were analyzed for HMs, namely Cr, Ni, Co, Cu, V, Zn, Mn, and Pb, to attain the objectives mentioned above. Compositional data analysis (CODA) techniques were employed for pinpointing the potential source of HM pollution. Initially, the centered log-ratio (clr) transformation was applied to the dataset containing raw values of chemically analyzed soil samples to address the data closure problem. Multifractal moving average interpolation was then applied to the clr-transformed data to model the spatial distribution of HMs in the study area. Maps of the spatial distribution of HMs in the study area were further classified by the concentration-area (C-A) fractal technique for identifying the potential hotspots of HM pollution in the area. It was followed by using the K-means clustering technique for classifying samples into distinct classes. This method was selected for geochemical pattern recognition owing to its simplicity and robustness in identifying subtle patterns embedded in geochemical data. The above hybrid methodology points to three anthropogenic sources discharging HM pollution into the area: leather factories, brickworks, and highways. Finally, pollution indices, namely the geo-accumulation index, pollution load index, and potential ecological risk, revealed that the elevated levels of Ni, Cr, and Co can pose serious impediments to the soil quality of the study area.

Revealing heavy metal correlations with water quality and tracking its latent factors by canonical correlation analysis and structural equation modeling in Dongjianghu Lake.

Decreasing levels of water quality and elevated concentrations of heavy metals in freshwaters can pose global challenges for drinking water sources. Multivariate statistical techniques have been applied on data matrices of water quality and heavy metals for keen characterization of their spatio-temporal variations, exploration of latent factors, and identification of pollution sources. Non-metric multidimensional scaling (nMDS), canonical correlation analysis (CCA), and structural equation modeling (SEM) were employed to process data matrices of the water quality and heavy metals with 14 parameters measured at 13 sampling sites in Dongjianghu Lake in March, June, August, and December 2016. The sampling sites were grouped into three clusters using the nMDS, suggesting that the increasing order of the water quality levels was approximately midstream < downstream < upstream and lake. The CCA of 14 parameters proved that the Escherichia coli, CODMn, TP, TN, TEMP, DO, and pH were the latent factors to distinguish the sampling sites, suggesting that the natural disturbances further influenced the lake and upstream, while the anthropogenic activities further influenced the midstream and downstream. The CCA of the heavy metals exhibited that the CODMn, F-, and E. coli were the latent factors of the Cu, Zn, and As, while the DO and TEMP were the latent factors of the Cd. This indicated that the Cu, As, and Zn were mainly associated with the anthropogenic activities, while the Cd was predominantly relative to the natural conditions. The SEM of the water quality and heavy metals showed that the weights of CODMn (28.64%), NH3-N (14.96%), BOD5 (14.32%), TN (12.88%), and TP (10.18%) were higher than those of the pH (8.37%), DO (7.73%), TEMP (2.58%), and E. coli (0.34%). This indicated that the former exhibited strong influences on the heavy metals than the latter. Moreover, the CODMn and BOD5 were the key factors of the heavy metals, which should be attributed to the no-point sources, especially the exploitation mining and mill tailings. The water quality assessment by the nMDS, CCA, and SEM can determine the status, trend corresponding to its standards, and trace latent factors and identify possible pollution sources. The study could provide a guide for water quality evaluation and pollution control.

Genetic microbial faecal source tracking: rising technology to support future water quality testing and safety management

Recent developments in water resource monitoring have increased the demand for the reliable identification of faecal pollution sources, also defined as microbial (faecal) source tracking (MST). Standardized faecal indicator bacteria (SFIB) enumeration does not directly support MST, as SFIB occur in animal and human sources. The aim of this study was to rigorously evaluate the applicability of host-associated faecal genetic MST markers detected by quantitative PCR (qPCR) at representative Austrian water resources (ground-, surface-, raw and treated wastewater, n = 196 samples) with high importance for the water management sector. Groundwater covered a gradient of non- (i.e., deep wells) to surface influenced resources (i.e., karst and shallow wells). In addition, single faecal excreta from humans as well as representative livestock and wildlife species were collected to evaluate the faecal source-specificity and -sensitivity of the MST assays. Genetic MST marker resistance against UV irradiation was evaluated in on-site ground and wastewater treatment installations. Bacteroides-based human- (HF183II, BacHum), ruminant- (BacR), and pig-associated (Pig2Bac) MST marker qPCR quantification was performed in concert with cultivation of E. coli, intestinal enterococci, and Clostridium perfringens (SFIB diagnostics). The selected MST makers revealed high faecal source identification capacity for the Austrian water compartments and quantitatively reflected the selected faecal pollution gradient. The study also demonstrated that SFIB data can efficiently be combined with MST data to solve previously unanswered questions in water safety monitoring and management (e.g., support pollution source-targeted catchment protection, hazard assessment, and health risk management). Further research and development needs are discussed to exploit the full power of MST technology. In conclusion, this study illustrates the capacity of molecular faecal pollution diagnostics to revolutionize water quality testing in the decades to come.

Revealing Soil and Tree Leaves Deposited Particulate Matter PTE Relationship and Potential Sources in Urban Environment.

Trees play a pivotal role in improving urban environmental quality and provide several ecosystem services including the removal of pollutants from the air, such as particular matter (PM) and potentially toxic elements (PTE). Therefore, understanding the tree PM and PTE capturing potential, also in connection with plant species, is of great concern, especially in urban areas. This study aims to reveal the link between the elemental composition of PM deposited on tree leaves and soils PTE contents, as well as to rank the PM capturing efficiency of 10 different tree species growing under the impact of urban environments. This also allowed us to test the efficiency of PM deposited on tree leaves as a PTE biomonitoring and pollution source identification tool, in the two biggest urban areas of Armenia. Indeed, high contents of PTE are detected in both soil- and leaf-deposited PM from sites characterized by the presence of localized and active pollution sources (i.e., industrial unites, high traffic, etc.), which are identified by specific tracers (such as Mo, Cu, Zn, Pb, and Cd). Among the studied tree species, the highest PM amount per unit leaf area is observed for Platanus orientalis, but elm species are also identified as promising canditates to be considered for their PM removing potential, and need to be included in future more details studies.

Multiple pollution sources unravelled by environmental forensics techniques and multivariate statistics

Industrial sites affected by anthropogenic contamination, both past and present-day, commonly have intricate pollutant patterns, and source discrimination can be thus highly challenging. To this goal, this paper presents a novel approach combining multivariate statistics and environmental forensic techniques. The efficiency of this methodology was exemplified in a severely polluted estuarine area (Avilés, Spain), where factor analysis and clustering were performed to identify sub-areas with distinct geochemical behaviour. Once six clusters were defined and a pollution index applied, forensic tools revealed that the As speciation, Pb isotopes, and PAHs molecular ratios were useful to categorise the cluster groups on the basis of distinct pollution sources: Zn-smelting, coaly particles and waste disposal. Overall, this methodology offers valuable insight into pollution sources identification, which can be extended to comparable scenarios of complexly polluted environmental compartments. The information gathered using this approach is also important for the planning of risk assessment procedures and potential remediation strategies.

Principal component analysis of groundwater sources pollution in Omu-Aran Community, Nigeria

Most developing countries rely on water sources that are usually not protected making them unsafe for drinking. It is imperative to ensure regular assessment and proper monitoring to evaluate their quality and ensure they meet standards before use. This study was aimed at identifying pollution sources of groundwater in the study area of Omu-Aran and assessing the wáter quality under varying temporal conditions. Ninety-six groundwater samples were collected from eight locations during the dry and wet seasons of 2019–2020. These samples were examined for water quality parameters (n = 10) using standard methods. The study adopted the use of principal component analysis (PCA), water quality index (WQI) and independent sample t test to analyze water pollution sources, fully assess water quality and examine temporal variations in the sampling stations respectively. The mean values for measured parameters all fall within the Nigerian Standard Drinking Water Quality guideline values with the exception of pH, nitrite, dissolved oxygen and T. coliform. This pollution was attributed to sewage pollution arising from anthropogenic sources. Water quality decreased during rainy season as compared to the dry season with significant differences (P < 0.05) between these periods except for pH, total hardness and fluoride. WQI ranged from 28.17 to 108.15 which lies on the “good” to “unsuitable for drinking” spectrum. Three latent factors were extracted for both the wet and dry seasons from measured parameters by means of PCA. They explain natural pollution and soil erosion phenomenom due to seasonal changes while organic matter oxidation and mineral dissolution are also identified as factors that affect the water quality in the study area. In conclusion, the study has been able to integrate the use of PCA and WQI to analyse recorded data for pollution source identification and water quality interpretation in the study area. Regular assessment and proper monitoring to evaluate the quality of these sources should be done in order to ensure they meet standards before use. Users should be encouraged to carry out disinfection and ensure their water sources are protected and not left exposed.

Identification and Prioritisation of Mine Pollution Sources in a Temperate Watershed Using Tracer Injection and Synoptic Sampling

Identifying and prioritising mine sites for remediation is challenging due to inherently complex hydrological systems and multiple potential sources of mine pollution dispersed across watersheds. Understanding mine pollution dynamics in wet temperate watersheds is particularly challenging due to substantial variability in precipitation and streamflows, which increase the importance of diffuse sources. A tracer dilution and synoptic sampling experiment was conducted in a mined watershed in Scotland to identify the main sources of mine pollution, the relative importance of point and diffuse sources of pollution, and the potential benefits of mine site remediation to stream water quality. Using high spatial resolution metal loading datasets, the major Zn and Cd source areas were identified as point sources of mine water predominantly located in the upper part of the watershed. In contrast, the main sources of Pb were diffuse sources of mine tailings and wastes located in the lower part of the watershed. In the latter case, mobilisation of Pb occurred primarily from a section of braided wetland and an uncapped tailings area. Importantly, diffuse sources of mine pollution were found to be the dominant source of Pb, and an important source of Zn and Cd, even under steady-state streamflow conditions. Mass balance calculations suggest that treatment of the main mine water sources in the upper watershed and capping of the tailings deposit in the lower watershed could reduce stream trace metal concentrations by approximately 70%. These data support the development of conceptual models of mine pollution dynamics in wet temperate watersheds. These conceptual models are important as they: (1) help prioritise those mine sites and features for remediation that will deliver the most environmental and socio-economic benefit, and; (2) provide a means to quantify the importance of diffuse pollution sources that may increase in importance in the future as a result of changes in precipitation patterns in temperate watersheds.