Multiple Contamination Sources Research Articles

Identification of Multiple Surface Water Contamination Sources Based on UV–Vis Spectral Unmixing with Turbidity Adaptiveness

Identification of Multiple Surface Water Contamination Sources Based on UV–Vis Spectral Unmixing with Turbidity Adaptiveness

Landscapes of risk: A comparative analysis of landscape metrics for the ecotoxicological assessment of pesticide risk to bees

Abstract Pesticide use in agricultural landscapes creates environmental contamination that is heterogenous in space and time. Mobile organisms, such as bees, are exposed to multiple contamination sources when visiting patches that vary in the amount, timing and toxicity of pesticides used. Yet, environmental risk assessments (ERA) typically fail to consider this heterogeneity, in part because of the complexities of estimating exposure to different pesticides, and subsequent risk at organism‐relevant scales. We use pesticide assays of 269 bee‐collected pollen samples to understand the spatiotemporal variability of risk across a network of 41 field sites in southern Sweden. Observed bee pesticide risk is calculated based on compound‐specific residue quantifications in pollen and standardized toxicity data. We then compare the ability of three classes of landscape‐scale variables to predict this risk: (1) landscape composition and configuration metrics, (2) landscape load based on national pesticide use data and (3) predictions from a newly developed bee pesticide exposure model. Based on use data, 10 crops account for 81% of the total risk. We detected 49 pesticide compounds in bee‐collected pollen. Although herbicides and fungicides constitute the bulk of detected pesticides, both in frequency and amount quantified, unsurprisingly, insecticides contribute the most to risk. Landscape composition and configuration metrics did not predict observed pesticide risk, and interactions with bee species indicate taxa‐dependency in predictions. Landscape load predicted observed risk consistently between taxa. Risk estimates from our exposure model were strongly predictive but only when considering realized risk (i.e., risk estimates based on prior pesticide use information). Synthesis and applications. Predicting pesticide risk based on landscape patterns could enable landscape‐scale ERA. However, simple metrics of landscape pattern, such as proportion of agricultural land, are not sufficient. We found that risk observed in bee‐collected pollen was best predicted when integrating spatialized pesticide use in the pesticide exposure model, underscoring the importance of such data for research, monitoring and mitigation. Further, we propose a guidance framework for future landscape ecotoxicological risk analyses that clarifies data needs relative to risk prediction goals.

Evidence of transboundary movement of chemicals from Mexico to the U.S. in Tijuana River Estuary sediments

The Tijuana River Estuary (TRE) has been a public health hazard and point of contention between the United States and Mexico for decades, with sources of pollution on both sides of the border. The goal of our study is to determine the presence and dynamics of chemical contamination in the TRE. We sampled sediment from four TRE locations in the U.S. during stable dry conditions and immediately after a wet weather period. Organic chemicals were initially screened with non-targeted analysis using gas chromatography high-resolution mass spectrometry (GC/HRMS) that tentatively identified 6978 chemicals in the NIST 20 database. These tentative identifications were filtered using the USEPA CompTox database to guide quantitative targeted analysis at detection limits below 1 ng/g dry weight sediment. Quantitative targeted analysis of 152 organic pollutants and 18 inorganic elements via GC/HRMS revealed generally higher concentrations of contaminants in dry weather sediments compared to wet weather sediments. The highest concentrations of all chemical classes were detected at the site closest to the U.S.-Mexico border, followed by an urban area near Imperial Beach, California, U.S. All sites exhibited a mixture of petrogenic and pyrogenic polycyclic aromatic hydrocarbons (PAHs). Current-use pesticides were dominated by pyrethroid insecticides and the thiocarbamate herbicide s-Ethyl dipropylthiocarbamate (EPTC), while the U.S.-banned organochlorine pesticides were dominated by chlordanes, dieldrin, and dichlorodiphenyltrichloroethane (DDT) and its degradation byproducts. Polychlorinated biphenyl (PCB) concentrations were greatest at the site closest to the U.S.-Mexico border but in the low nanogram-per-gram range. Phthalates were only found at the same site, with relatively high concentrations of bis(2-ethylhexyl) phthalate. This study provides positive identification and quantitative concentrations for organic pollutants in TRE sediments. Our data suggest that there are multiple sources of chemical contamination in the estuary, including possible transboundary movement of pollutants from Mexico.

Biochar and Cd Alter the Degradation and Transport of Kasugamycin in Soil and Spinach

Biochar has been widely studied to reduce multiple contaminant sources in one matrix (e.g., several heavy metals in soils), yet less attention has been paid to accelerating pesticide degradation while in the presence of any heavy metals, such as when kasugamycin (KSM) and cadmium (Cd) are both present in soil. While KSM has low toxicity compared to other pesticides, it can be a potential health risk when applied to vegetable crops, especially when KSM is used or overapplied to achieve rapid reductions in insect and disease pressure. The degradation behavior of KSM (2 kg ha−1) in the presence of Cd (20 mg kg−1) and biochar (5% by wt.) when growing spinach (Spinacia oleracea) was studied. The biochar increased spinach shoot and root biomass by 51.0–54.8% and 24.4–39.0%, respectively, compared to the KSM treatment only. Compared to the treatments that did not receive biochar, the biochar application increased the KSM degradation in the soil by 8.4–68.4% and, subsequently, less KSM was absorbed by the spinach roots (18.0–48.4%) and shoots (33.0–33.2%). The KSM degradation rate, as a function of soil depth, was enhanced in the presence of Cd. The biochar also effectively decreased the KSM concentration with soil depth, reducing downward KSM migration. The KSM degradation, increased by the biochar, led to smaller organic moieties and some macromolecular organic phases. In soils that are contaminated with Cd and where vegetables are raised, biochar may be used as an environmentally friendly proponent for increasing KSM degradation, reducing KSM downward transport and, thus, protecting environmental and human health.

Predicting the impact and duration of persistent and mobile organic compounds in groundwater systems using a contaminant mass discharge approach

This study investigated methods for predicting the duration and impact on groundwater quality from persistent and mobile organic compounds (PMOCs) at a drinking water well field affected by multiple contaminant sources. The fungicide metabolite N,N-dimethylsulfamide (DMS), which frequently occurs above the Danish groundwater quality criterion (0.1 μg/L), was used as an example. By combining contaminant mass discharge (CMD) estimations, modeling, and groundwater dating, a number of important discoveries were made. The current center of contaminant mass was located near the source area. The CMD at the well field was predicted to peak in 2040, and an effect from the investigated sources on groundwater quality could be expected until the end of the 21st century. A discrepancy in the current CMD at the well field and the estimated arrival time from the studied source area suggested an additional pesticide source, which has not yet been thoroughly investigated. The presence of the unknown source was supported by model simulations, producing an improved mass balance after inclusion of a contaminant source closer to the well field.The approach applied here was capable of predicting the duration and impact of DMS contamination at a well field at catchment scale. It furthermore shows potential for identification and quantification of the contribution from individual sources, and is also applicable for other PMOCs. Predicting the duration of the release and impact of contaminant sources on abstraction wells is highly valuable for water resources management and authorities responsible for contaminant risk assessment, remediation, and long-term planning at water utilities.

Exploring VA presence in groundwater of densely populated livestock farming watersheds: Sources, seasonal dynamics and geospatial relationships

Antibiotics are an indispensable component of the livestock industry and are released into the environment through various pathways during livestock rearing processes. Among various environmental mediums, groundwater holds significant importance as it serves as a crucial resource for potable water supply and agricultural practices. However, the persistent use of antibiotic-contaminated groundwater can lead to prolonged exposure to these agents in human and ecological systems, thereby engendering serious apprehensions, including the emergence of antibiotic-resistant bacterial strains. Therefore, in this study, the concentration of antibiotics in groundwater within densely populated livestock farming areas was analyzed using UHPLC-q-orbitrap HRMS combined with online solid-phase extraction. The measured cumulative concentrations of antibiotics in the groundwater samples collected from the surveyed areas ranged from 15.8 ng L─1 to 1530.0 ng L─1. The residual antibiotics obtained from the surveyed region exhibited significant seasonal variation, with higher concentrations observed during summer. This seasonal pattern is attributed to the combined effects of agricultural activities and climatic factors. The concentrations of antibiotics in the investigated area demonstrated associations between the composition of livestock species and the density of livestock farming facilities. Specifically, veterinary-specific antibiotics (sulfaquinoxaline [SQX] and clopidol [CLO]), commonly employed in poultry farming, were found to be more prominent in the area with a high concentration of poultry farming facilities. In regions characterized by a dense poultry farm presence, the highest concentrations of SQX and CLO were founded at 135.7 ng L─1 and 178.6 ng L─1, respectively. In contrast, areas without any farms exhibited lower concentrations, measuring 39.9 ng L─1 for SQX and 10.1 ng L─1 for CLO. Similarly, antibiotics primarily used in swine farming showed a strong correlation with the presence of large-scale swine farming operations. In the case of sulfamethazine, which is commonly used in pig farming, concentrations exceeding 500 ng L─1 were observed in groundwater samples collected near large-scale swine farming facilities. These observations suggest that antibiotics are introduced into groundwater through the discharge of wastewater and excreta from livestock farming facilities. Consequently, this study establishes that regional variations in antibiotic concentrations within groundwater are influenced by factors such as local usage patterns, the scale and types of livestock farming, and the prevailing climatic conditions. In order to elucidate the precise associations between multiple sources of contamination, including livestock farming facilities, and to enhance our understanding of their spatial correlations, there appears to be a need for research focused on spatial correlation analysis.

Assessment of multiple fecal contamination sources in surface waters using environmental mitochondrial DNA metabarcoding

Waterborne diseases are transmitted to humans through the fecal contamination of water, where homeothermic species are the main reservoir. Fecal indicator bacteria (FIB) are often used to determine the occurrence of fecal contamination. However, FIB cannot provide the source of fecal contamination. Furthermore, as fecal inputs and contamination could originate from multiple sources (e.g., human, livestock, wildlife), multiple source tracking markers are required to identify fecal sources. From a previous study, we developed a mitochondrial DNA (mtDNA) metabarcoding approach to assess the presence of multiple homeotherms in four surface waters. Here, we have broadened our approach by sampling 86 surface water samples from the L'Assomption River and Ville-Marie watersheds (Province of Quebec, Canada). Fecal coliform levels were higher than the expected sanitary recommendations for recreational water (> 200 CFU/100 mL) in 73 % samples. The occurrence of mtDNA from human, livestock, domestic animals, wild mammals and wild birds was found in 40–88 % of the samples. Multivariate analyses showed significant covariations between homeothermic taxa and fecal coliforms, enterococci, β-D-glucuronidase, conductivity, the human-specific Bacteroidales Hf183 genetic marker, and the human population, in the watersheds of L'Assomption River (p = 0.001) and Ville-Marie (p = 0.015) (Province of Quebec, Canada). Through the application of Bayes Theorem, it was determined that fecal coliforms co-occurred with the detection of bovine, beaver, robin and chicken mtDNA in 100 % of cases in the L'Assomption River watershed, and human mtDNA co-occurred with fecal coliforms in 93 % and 76 % of cases in L'Assomption River watershed and Ville-Marie sub-catchment, respectively. This study suggests that fecal contamination could be the result of multiple species, among which some wild animals may contribute to fecal inputs in surface waters, resulting in potential risk to human health. This reinforces the necessity of using the mtDNA metabarcoding method to monitor multi-animal species.

Preliminary assessment of a degraded river in the Niger Delta, Nigeria using physico-chemical characteristics and water quality index

Surface water degradation is increasingly becoming a national issue in Nigeria as it affects the suitability of water for its various uses. The preliminary study of the physicochemical parameters and water quality index of the Orogodo River was conducted to ascertain the extent of degradation from multiple sources of contamination. Water samples were collected from four sites that were impacted by various anthropogenic activities along the Orogodo River in Delta State during the months of February (number of samples = 16) and September (number of samples = 16) 2020. The water samples were analyzed using standard methods. The results of the physicochemical analysis using ANOVA showed significant differences (P<0.05) only in biochemical oxygen demand and turbidity across the four sites. The biochemical oxygen demand (3.05±2.47) and turbidity (8.35±5.162) at site 3 espectively that is a major abattoir discharge point were above the Nigeria Standard for Drinking Water Quality acceptable limits for drinking water and could portend harm to water users and ecosystem integrity. The water quality index analysis revealed that sites 1 and 4 showed good water quality and those of sites 2 and 3 showed poor water quality. The study demonstrated that water quality index analysis and physicochemical characteristics were critical factors in evaluating the deteriorating conditions of the Orogodo River. Periodic monitoring of the river quality and integrity is vital as the river water will require extensive treatment for safe usage.

Cumulative environmental risk assessment of metals and polycyclic aromatic hydrocarbons from ship activities in ports

Marine environmental risk assessments rarely consider the cumulative risk from multiple contaminants and sources. Ships give rise to a range of contaminants, originating from different onboard sources, resulting in contaminant loads to the marine environment. Here, the Ship Traffic Emission Assessment Model (STEAM), in combination with the hydrodynamic and chemical fate model MAMPEC, was used to calculate loads and predicted environmental concentrations (PECs) of metals and polycyclic aromatic hydrocarbons, in four ports. PECs were compared to the predicted no effect concentrations (PNEC) to assess environmental risk from the different onboard sources, both separately and cumulatively. The results show that three out of four ports were subject to unacceptable risk. This study highlights the importance of accounting for multiple contaminant sources when assessing the marine environmental risks of shipping and challenges the suitability of the proposed new international guidelines on how to assess risk of scrubber water discharge.

Sources and spatiotemporal distribution characteristics of nitrogen and phosphorus loads in the Haihe River Basin, China

Water quality monitoring stations are crucial for detecting excess pollutants in river sections, but identifying the causes of these exceedances can be challenging, especially in heavily polluted rivers with multiple contamination sources. To address this issue, we used the SWAT model to simulate pollution loads from various sources in the Haihe River Basin, analyzing the spatiotemporal distribution of pollutants from seven nitrogen/phosphorus sources in sub-basins. Our results show that crop production is the primary contributor to nitrogen and phosphorus loads in the Haihe River Basin, with the highest loads occurring in summer, followed by fall, spring, and winter. However, industries, atmospheric deposition, and municipal sewage treatment plants have a greater downstream impact on nitrogen/phosphorus contributions due to land use changes. The study highlights the need for targeted prevention and control policies based on the primary sources of pollution loads in different regions.

Prediction of 1,4-Dioxane Migration in Groundwater and Evaluation of Remediation Measures in an Illegal Dumping Site Using a 2D-Numerical Model

Illegal dumping sites are usually characterized by complex contamination situations due to the presence of multiple contamination sources. To improve the efficiency of illegal waste dumping site remediation, this study developed a numerical model considering the effects of groundwater levels and hydraulic gradient changes on remediation operations. Using this model, the most likely sources of contamination for 1,4-dioxane at an illegal waste site in Iwate Prefecture, Japan, were successfully identified (including location, amount, and time of occurrence) by reproducing historical monitoring data (from 2010 to 2022) through history matching, and future contaminant migration in groundwater was predicted. In addition, based on quantitative evaluations of the remediation measures, we found that some remediation measures, such as impermeable wall construction, while having some effects on the control of contamination spreading, may accelerate the migration of contaminants off-site due to the change of hydraulic gradient. Therefore, remediation procedures should be more carefully considered for illegal dumping sites based on an understanding of the distribution of contamination sources and hydraulic gradient evolutions.

Sources and historical records of metal(loid)s in river sediments from an agricultural tributary of Tuojiang river: Evidence from geochemical analyses and Pb isotope

Clarifying the sources and historical variation of metal(loid)s in agricultural river sediments is vital for watershed contamination control and environmental improvements. In this study, a systematical geochemical investigation of Pb isotopic characteristics and the spatial-temporal distribution of metal(loid)s abundances was conducted to delineate the origins of metal(loid)s (Cd, Zn, Cu, Pb, Cr, and As) in sediments from an agricultural river, Sichuan Province, Southwest China. The results showed significant enrichment of Cd and Zn in the whole watershed, with substantial anthropogenic contributions of 86.1% and 63.1% for the surface sediments, and 79.1% and 67.9% for the core sediments, respectively. As was mainly derived from natural sources. Cu, Cr, and Pb were originated from the mixing sources of natural and anthropogenic processes. The anthropogenic origin of Cd, Zn, and Cu in the watershed was closely correlated with agricultural activities. The profile of EF-Cd and EF-Zn displayed an increasing trend from the 1960s–1990s, and then kept a high value, which was consistent with the development of national agricultural activities. Pb isotopic signatures suggested multiple sources of the anthropogenic Pb contamination, including industrial/sewage discharge, coal combustion, and vehicle exhaust. The average anthropogenic 206Pb/207Pb ratio (1.1585) approximated that of local aerosols (1.1660), suggesting aerosol deposition was a crucial pathway of anthropogenic Pb input to sediment. Furthermore, the anthropogenic Pb percentages (mean of 52.3 ± 10.3%) from the EF approach were in line with that from the Pb isotopic method (mean of 45.5 ± 13.3%) for sediments under intense anthropogenic impacts.

PCBs, PCNs, and PCDD/Fs in Soil around an Industrial Park in Northwest China: Levels, Source Apportionment, and Human Health Risk.

The concentrations of polychlorinated biphenyls (PCBs), polychlorinated naphthalenes (PCNs), and polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/Fs) were determined in soil samples collected around an industrial park in Northwest China, to investigate the potential impacts of park emissions on the surrounding environment. The total concentration ranges of PCBs, PCNs, and PCDD/Fs in the soil samples were in 13.2-1240, 141-832, and 3.60-156 pg/g, respectively. The spatial distribution and congener patterns of PCBs, PCNs, and PCCD/Fs indicated that there might be multiple contamination sources in the study area, so source apportionments of PCBs, PCNs, and PCCD/Fs were performed by a positive matrix factorization model based on the concentrations of all target congeners together. The results revealed that these highly chlorinated congeners (CB-209, CN-75, and OCDF) might be derived from phthalocyanine pigments, the legacy of Halowax 1051 and 2,4-D products, which together contributed nearly half of the total concentration of target compounds (44.5%). In addition to highly chlorinated congeners, the local industrial thermal processes were mainly responsible for the contamination of PCBs, PCNs, and PCDD/Fs in the surrounding soil. The total carcinogenic risk of PCBs, PCNs, and PCDD/Fs in a few soil samples (0.22 × 10-6, 0.32 × 10-6, and 0.40 × 10-6) approached the threshold of potential carcinogenic risk (1.0 × 10-6). Since these pollutants can continuously accumulate in the soil, the contamination of PCBs, PCNs, and PCDD/Fs in surrounding soil deserves continuous attention.

Explaining the persistence of hazardous chemicals in the Doce River (Brazil) by multiple sources of contamination and a major environmental disaster

High concentrations of hazardous chemicals may be introduced into aquatic ecosystems during episodes of acute and chronic environmental contamination. This study aimed to quantify inorganic and organic contaminants along the Doce River Basin (DRB), evaluate spatial and temporal variations of their concentrations, and their associations with the respective potential anthropogenic sources, considering the cumulative effects of a tailing dam rupture event. Multivariate analysis indicated that higher levels of trace elements in the Upper DRB were related to its proximity to the mining activities in this region, while organic contaminants such as PAHs are probably introduced by industrial effluents and urban centers along the DRB. In addition, seasonal variation showed to be an important factor influencing the distribution of chemicals, with wet season increasing levels of trace elements in the water. Despite the contribution of natural geological features in the Upper DRB, it becomes clearer that intense mineral exploitation for decades, combined with the dam failure disaster are responsible for the increased levels and spread of these inorganic contaminants along the DRB. Furthermore, other sources of organic contaminants contribute to this contamination scenario, resulting in complex mixtures of chemicals and increasing the ecological risks in the region.

Forensic Analytical Approach for Hydrocarbon Fingerprinting in Soil Vapor Samplings: Example of a Residential Neighborhood in Brazil

Conventional analytical methods determine the concentration of compounds used to estimate the presence of environmental contamination capable of posing risk to human and ecological receptors (Murphy and Morrison, 2007). While these target analytes help regulators and environmental professional identify and manage potentially harmful conditions, these compounds can be generated by many natural and anthropogenic (man-made) sources and conventional methods alone fail to compositionally differentiate subsurface sources of contamination in complex environments (Morrison, 2000; Wang and Fingas, 2003; Gouvêa et al, 2019; Douglas et al, 2007). This case study demonstrates the advantage of using both conventional and forensic testing methods to accurately identify the source(s) of volatile hydrocarbon contamination in soil vapor samples for the development of an accurate conceptual site model in a neighbourhood near industrial facilities in Rio de Janeiro State, Brazil. The goal of this study was to differentiate potential impacts from a local steelmaking plant from fugitive hydrocarbons associated with more generic human activity in urban settings. This case study demonstrated the advantage of constructing chemical fingerprints from conventional volatile organic compound (VOC) method TO 15 and a forensic volatile hydrocarbon method using an enhanced version of method TO 15 (PIANO). The chemical fingerprints of vapor samples collected from subsurface soil gas and sewers were analysed and compared to laboratory reference samples. These data determined that the VOCs detected in neighbourhood soil vapor samples were associated with fugitive petroleum products migrating in the sewer pipelines and not with the steelmaking wastes emplaced near the residential area. This article discusses the forensic data and chemical signatures that support these findings, and the use of environmental forensic techniques to evaluate environmental data associated with complex scenarios, involving multiple contamination sources.

Inverse estimation of multiple contaminant sources in three-dimensional heterogeneous aquifers with variable-density flows

Groundwater contamination is an exacerbating global issue that severely threatens human health. Subsurface remediation thus has gained increased interest in recent years. To effectively remediate subsurface contaminated sites, one needs to identify the locations of contaminant sources and characterize contaminant spreading. Groundwater contamination is often driven by multiple contaminant sources, making source identification problems challenging. Further, when the densities of dissolved contaminants and ambient groundwater differ, the resultant variable-density flows add complexity to the task of source identification. However, most previous studies are limited to a single source identification in a two-dimensional aquifer. This study presents a novel inversion method based on ensemble smoothing that identifies the locations of multiple contaminant sources in three-dimensional heterogeneous aquifer systems. A new covariance localization algorithm based on a clustering method is integrated into the inversion method, which improves the accuracy of multi-source identification. Using the proposed inversion framework, we successfully estimate the locations of multiple contaminant sources and three-dimensional permeability fields utilizing pressure and concentration data from monitoring wells. Further, we investigate and elucidate the effects of aquifer heterogeneity and variable-density flows on multiple source identification. We find that variable-density flow increases the data information contents and thus improves the inversion accuracy. This is the first-time demonstration of the effects of variable-density flow on the inversion accuracy of multi-source identification in three-dimensional heterogeneous aquifer systems.

An Effective and Efficient Method for Identification of Contamination Sources in Water Distribution Systems Based on Manual Grab‐Sampling

AbstractMost of the contamination source localization methods for water distribution systems (WDSs) assume the availability of accurate water quality models and multi‐parameter online sensors, which are often out of reach of many water utilities. To address this, a novel manual grab‐sampling method (MGSM) is developed to effectively and efficiently locate continuous contamination sources in a WDS using a dynamic and cyclical sampling strategy. The grab samples are collected at a pre‐specified number of hydrants by the corresponding teams followed by laboratory tests. The MGSM optimizes the sampling plan at each cycle by making the probability of contamination source(s) in each sub‐network as equal as possible, where sub‐networks are determined by the selected hydrants and current flow pipe directions. The CS's size is reduced at each cycle by exploiting sample testing results obtained in the previous cycle until there are no further hydrants to sample from. Two real‐world WDSs are used to demonstrate the effectiveness of the proposed MGSM. The results obtained show that the MGSM can significantly reduce the spatial range of the CS (to about 5% of the entire WDS) for a range of scenarios including multiple contamination sources and pipe flow direction changes. We found that an optimal number of sampling teams exists for a given WDS, representing a balanced trade‐off between detection efficiency and sampling/testing budgets. Due to its relative simplicity, the proposed MGSM can be used in engineering practice straightaway and it represents a viable alternative to the methods associated with water quality models and sensors.

Use of modeling to map potentially toxic elements and assess the risk to human health in soils affected by mining activity

Determining the levels and spatial distribution of potentially toxic elements (PTEs) is essential in designing mitigating strategies to remediate contaminated areas. Efficient prediction of PTEs is difficult due to high spatial variability and multiple sources of contamination. The use of machine learning algorithms is an alternative for the improvement of the predictions. Objective of the study was to model the spatial distribution of PTEs in soils surrounding a tailings pile and to assess potential risks to human health. A total set of 116 soil samples was collected to a depth of 0–10 cm. The covariate database was composed of morphometric variables derived from a DEM and the creation of a tailings pile location covariate. The models tested were Cubist (CUB), Random Forest (RF), Support Vector Machine (SVM), and Linear Model (Lm). Based on the best predictive model, maps showing the spatial distribution, pollution and risk to human health were created. The SVM model had the best performance for predicting spatially the soil contents of Pb and Zn, with lower values of mean absolute error (MAE − 744.71; 306.36) and higher values of R2 (0.56; 0.52). It was possible to verify that the mining tailings pile is the main source of Pb and Zn contamination in the study area. The enrichment factor (EF) and the geoaccumulation index (Igeo) of Pb and Zn show that the soils close to the tailings piles are extremely contaminated (Igeo > 5 and EF > 40), and pose risks to human health (Total carcinogenic risk > 1 × 10–6), especially for children. Therefore, new studies must be carried out with the aim of monitoring and rehabilitating the contaminated areas.

FIESTA II. Disentangling Stellar and Instrumental Variability from Exoplanetary Doppler Shifts in the Fourier Domain

The radial velocity (RV) detection of exoplanets is challenged by stellar spectroscopic variability that can mimic the presence of planets and by instrumental instability that can further obscure the detection. Both stellar and instrumental changes can distort the spectral line profiles and be misinterpreted as apparent RV shifts. We present an improved FourIEr phase SpecTrum Analysis (FIESTA, aka ϕESTA) to disentangle apparent velocity shifts due to a line deformation from a true Doppler shift. ϕESTA projects a stellar spectrum’s cross-correlation function (CCF) onto a truncated set of Fourier basis functions. Using the amplitude and phase information from each Fourier mode, we can trace the line variability at different CCF width scales to robustly identify and mitigate multiple sources of RV contamination. For example, in our study of the 3 yr of HARPS-N solar data, ϕESTA reveals the solar rotational effect, the long-term trend due to solar magnetic cycle, instrumental instability, and apparent solar rotation rate changes. Applying a multiple linear regression model on ϕESTA metrics, we reduce the weighted rms noise from 1.89 to 0.98 m s−1. In addition, we observe a ∼3-day lag in the ϕESTA metrics, similar to the findings from previous studies on the bisector inverse slope and FWHM.

Dealing with complex contamination scenarios: using a multi-geochemical approach to assess environmental quality and identify pollution sources in a semi-arid estuary from Brazil.

The Jundiaí-Potengi Estuary (EJP) is located on the semi-arid coast of northeastern Brazil and is influenced by multiple sources of contamination. The sediment quality of EJP was assessed by using a multi-geochemical approach during the dry and wet seasons. Sediments were analyzed for concentrations of nutrients, metals, polycyclic aromatic hydrocarbons (PAHs), pesticides, hormones (natural and synthetic), and sterols. The results were integrated by multivariate methods. The sediment was altered by the presence of contaminants from anthropogenic and natural sources. The middle and lower estuarine areas were considered more degraded in both seasons. In these regions, metals, hormones, sterols, and PAHs were found, indicating that these regions are severely affected by industrial, sanitary and aquaculture effluents, combustion of fossil fuels, and oil spills. The upstream region was contaminated by pesticides. The contamination pattern along the EJP shows the prevalence of local sources which continuously release the chemicals into the estuary. Worse conditions occurred during the rainy season, when the runoff from urban and rural areas is more intense and carries a greater load of contaminants to the EJP.