Spatial Distribution Of Contaminants Research Articles

Distributed Estimation of Fields Using a Sensor Network with Quantized Measurements.

In this paper, the problem of estimating a scalar field (e.g., the spatial distribution of contaminants in an area) using a sensor network is considered. The sensors are assumed to have quantized measurements. We consider distributed estimation algorithms where each sensor forms its own estimate of the field, with sensors able to share information locally with its neighbours. Two schemes are proposed, called, respectively, measurement diffusion and estimate diffusion. In the measurement diffusion scheme, each sensor broadcasts to its neighbours the latest received measurements of every sensor in the network, while in the estimate diffusion scheme, each sensor will broadcast local estimates and Hessians to its neighbours. Information received from its neighbours will then be iteratively combined at each sensor to form the field estimates. Time-varying scalar fields can also be estimated using both the measurement diffusion and estimate diffusion schemes. Numerical studies illustrate the performance of the proposed algorithms, in particular demonstrating steady state performance close to that of centralized estimation.

The toxic legacy of artisanal and informal mining: XRF and gis analysis of soil contamination by Hg, Pb and As in the Secocha annex, Camaná, Peru

Hg, used as the main input in the gold amalgamation process in artisanal mining, along with lead Pb and As present in the toxic waste resulting from mining activity, cause serious effects on the environment and human health, as it occurs in the Secocha annex (Camaná, Peru). The objectives of the present study were to determine the concentrations of Hg, Pb, and As in the soil of the Secocha annex, evaluate the level of contamination of the site, determine the spatial distribution of contamination and the concentrations of the evaluated elements, and determine the origin of these contaminants. To achieve these objectives, satellite imagery, field sampling, X-ray fluorescence techniques, soil quality environmental regulations, geo-accumulation indices (Igeo), and geographic information system techniques were used. The results revealed maximum concentrations of 350 and 176.6 mg/kg for Hg and Pb, respectively. Of the 72 soil samples collected, the concentrations of Hg located within the urban/industrial area, where gold recovery activities are carried out, exceeded environmental regulations to a greater extent. In turn, the calculated Igeo revealed extreme soil contamination (5 < Igeo) due to the presence of Hg in most of the study area (95%), followed by moderate to heavy contamination (2 < Igeo < 3) due to the presence of Pb and As (0.5 and 5%, respectively). To reduce contamination and the concentrations of the evaluated elements, it is recommended to carry out studies to reuse inputs, change gold processing methodologies, and/or relocate the generated waste.

Conditional generative adversarial networks for groundwater contamination characterization and source identification

Accurate characterization of sources and spatial distribution of contamination remains crucial in groundwater survey and remediation efforts. Nevertheless, conventional geo-statistical methods, like kriging, usually produce overly smooth concentration fields that violate the transport physics. Furthermore, the identification of contaminant sources based on kriging methods may be misleading. As a deep learning approach, Generative adversarial networks (GANs) is being increasingly employed to extract patterns and insights from intricate geospatial data. The conditional variant of GANs (CGANs), can reconstruct complete spatial data from sparse point observations. In this study, we propose a deep learning framework with CGANs for the purpose of groundwater contamination characterization and source identification. In ensure compliance with the principles of transport physics, we use a numerical transport model as the underlying prior model for training the CGANs. Through the adaptation of network architecture, the generator transforms low-dimensional random variables and observation data into concentration images, while the discriminator is responsible for extracting source information from these images. The developed framework is tested through two numerical cases with channelized random hydraulic conductivity fields, which pose a challenge due to the complexity of the concentration fields. The results demonstrate that the proposed method can give accurate results for both contaminant characterization and source identification in groundwater. CGANs excel in reconstructing concentration fields compared to traditional interpolation methods such as Kriging and inverse distance weighting (IDW). Additionally, CGANs offer the capability to estimate uncertainty and exhibit a certain level of error robustness.

Spatial Distribution of Contaminants in Glacial Streams and River Tributaries in the Ecologically Sensitive Regions of Gilgit Baltistan, Pakistan

Spatial Distribution of Contaminants in Glacial Streams and River Tributaries in the Ecologically Sensitive Regions of Gilgit Baltistan, Pakistan

Resource conundrum in Mongolia: Soil contamination from coal and copper–molybdenum mining

AbstractSoil contamination and the resulting ecological disturbances are a common phenomenon in mining areas, including the vicinities of the largest and oldest open‐pit mining areas in Mongolia. In this work, the potential ecological risk index (RI), Nemerow integrated pollution index (PIN), and Geoaccumulation index (Igeo) were used to estimate the level of soil contamination with Ni, Cu, Zn, As, Cr, and Pb in the top layer of the soils around Baganuur coal mine and Erdenet copper–molybdenum mine. Three different analytical methods were used: portable X‐ray fluorescence (pXRF) for the first assessment of samples, and stationary X‐ray fluorescence and Inductively Coupled Plasma Optical Emission Spectroscopy for the confirmation of results in the laboratory. Even though general contamination levels in both study areas were relatively low, some potentially toxic elements were found at contents several times higher than the maximum permissible level (MPL) according to the national standard of Mongolia. In the Baganuur area, Zn was up to 2.8 and As was up to 3.00 times higher, while in the Erdenet area, As was up to 2.4, Cr was up to 1.7, Cu was up to 8.1, and Zn was up to 1.2 times higher than MPL of the national standard in the vicinity to the mining and industrial area. The estimation of the pXRF measurement had generally similar results to the other two laboratory methods based on spatial distributions of heavy metal content. Among the different geochemical indices, the PIN showed a more accurately distinguished spatial distribution of contamination. For example, highly contaminated areas were found in the vicinity of the open pit, the tailings pond and the industrial area based on PIN results: 3.6%–4.9% of the total area in Baganuur and 3.1%–4.9% of the total area in Erdenet. The identified pollution levels emphasize the essential need for soil rehabilitation in mining areas, a key factor for Mongolia's economic development and environmental stability. In addition, the lack of documented soil rehabilitation initiatives underscores the pressing need for enhanced environmental responsibility in the country's expanding mining sector.

Assessment of spatial distribution of lead in soils around an active military shooting range

Abstract In this study, the extent of Pb contamination around an active military shooting range is re-assessed to ascertain current contamination status comparatively to data’s reported 20 years ago. This is because lead bullet disintegration and mobility takes several years and extensively affects levels of soil-Pb contamination. A total of 120 topsoil samples were collected within the impact area (front) and non-impact area (back) for Pb determination. High concentrations of Pb were found at impact berm both front (28940±2996 μg/g) and back (775±128 μg/g). Spatial distribution of contamination reflects the distances from berm. Soil-Pb contamination around non-impact area was notable at back berm through to 100 m distance with significant difference in Pb, Cr, Ni and Zn levels. Concentration of Pb at berm was observed to have increase five-fold over a period of about twenty years from previous study with accumulation factor of about 1000. Principal component analysis PCA indicated 67 % of total metal load of range soil was majorly from impact areas of the berm. The correspondence analysis relay plot shows pollution order of Pb > Ni > Cd > Cr > Zn > Cu. This confirms soil contamination especially around the impact area, i.e. impact berm and firing lines and non-impact area at 0 m, 10 m, 50 m and 100 m. Environmental consequence of high soil-Pb levels within the range especially non-impact areas utilized for farming activities will leave much to desire. Hence, extensive and continuous monitoring is needed. However, remediation through appropriate soil washing technique could reduce Pb levels and improve soil condition regardless of age.

A spatiotemporal study on contamination and bioaccumulation of heavy metals in sediment and cyprinid fish (Capoeta razii) from Telar River, Iran

The concentrations of heavy metals (Cr, Cd, Ni, and Pb) were investigated in sediment and cyprinid fish (Capoeta razii) from Telar River, Iran in spring, summer, and autumn. Mean concentration of metals in fish and sediment over the seasonal sampling was as follows: Cr > Ni > Pb > Cd. Metal deposition in sediment was higher than their bioaccumulation in fish tissue. Unlike sedimentary metals, the tissue-content of Pb and Cr varied seasonally. Enrichment Factor (EF) values of Cr and Ni showed partial enrichment, implicating the role of anthropogenic inputs, while Pb was derived from natural weathering. When considering Pollution Load Index (PLI), an uneven temporal and spatial distribution of contamination was observed in sediment with moderate contamination level in spring and summer and no pollution in autumn. Tissue-contents of Pb, Cr, and Cd were below permissible limits while a higher risk level of Ni was noted for human consumption.

Spatial distribution of selenium and other potentially toxic elements surrounding mountaintop coal mines in the Elk Valley, British Columbia, Canada

Despite the extensive use of mountaintop coal mining in the Elk Valley, British Columbia, Canada's largest metallurgical coal-producing region, little is known about the transport and deposition of fugitive dust emissions within its mountain landscape. This study aimed to assess the extent and spatial distribution of selenium and other potentially toxic elements (PTEs) near the town of Sparwood originating from fugitive dust emitted from two mountaintop coal mines. To achieve these objectives concentrations of 47 elements within moss tissues of Hylocomium splendens, Pleurozium schreberi, and Ptilium crista-castrensis were analyzed from 19 locations between May 29 to June 1, 2022. Contamination factors were then calculated to identify areas of contamination, along with generalized additive models to assess the relationship between selenium and the mines. Finally, Pearson correlation coefficients were calculated between selenium and other PTEs to determine which exhibited similar behaviour. This study found that selenium concentrations are a function of proximity to mountaintop mines, and the region's topographic features and prevailing wind patterns play a role in the transport and deposition of fugitive dust. Contamination is highest immediately surrounding mines and decreases at increasing distances, with the region's steep mountain ridges shielding the deposition of some fugitive dust when acting as a geographic barrier between adjacent valleys. Furthermore, silver, germanium, nickel, uranium, vanadium, and zirconium were identified as other PTEs of concern. The implications of this study are significant as it demonstrated the extent and spatial distribution of contaminants originating from fugitive dust emissions surrounding mountaintop mines and some of the controls to its distribution in mountain regions. As Canada and other mining jurisdictions look to expand critical mineral development, it will be important for proper risk assessment and mitigation in mountain regions to limit community and environmental exposure to contaminants within fugitive dust.

Monitoring of Spatio-Temporal Dynamics of Air Pollution in Enugu Urban using Remote Sensing and GIS

Ambient air pollution is widely acknowledged to be the worst type of environmental pollution. The amount of air pollution varies from time to time and from region to region. The spatiotemporal distribution of air pollutants in the city of Enugu was investigated in this study. Due to the high concentration of industrial clusters, heavy traffic and increasing population density in the study area, notable places were purposely sampled during the hours of 8a.m. and 4p.m. A portable gas analyzer, the Aerocet-531 Met One Instrument, Drager X-am 5000, was used to quantify the amounts of PM2.5, PM10, CO, SO2, and NO2. The GPS coordinates of the sampling spots were recorded using the portable Germin-300 Global Positioning System (GPS) device analyzer, which aided in the data processing to create spatial interpolation maps in ArcMap. GIS and remote sensing methods were utilized to analyze the spatial distribution of contaminants using satellite images. ArcGIS and Erdas Imagine were used to analyze the identification of pollution sources, the geographical distribution of pollutants in connection to land use and the epidemiological scope of pollutants from sources. The approaches employed to get the findings included image categorization, proximity, intersection, and interpolation. It was determined that there was a correlation between the landuse density and the levels of NO2, SO2, CO, PM2.5, and PM10. Within 100m – 400m of major roadways, correlation values were highest, indicating a high risk of vulnerability in this area. The maximum values for PM2.5 and PM10 were 1.78μg/m3 and 205μg/m3 respectively during the dry season and 2.13μg/m3 and 184μg/m3 during the wet weather. Similarly, the minimum values for PM2.5 and PM10 are 0.25μg/m3 and 161μg/m3 respectively during the dry season and 0.45μg/m3 and 132μg/m3 during the wet weather. The study further shows that the range values of SO2, NO2, and CO during the dry season are between 0.71 to 1.98ppb, 0.72 to 1.96ppb and 9.21 to 18.04ppb respectively while ranges of 0.45 to 1.73ppb, 0.31 to 0.89ppb, and 7.94 to 12.56ppb were recorded during the wet season. The study concluded that the high levels of PM2.5, PM10, SO2, NO2, and CO in the study area monitored especially in the dry season may present a potential public health risk. Sequel to this, it is advised that the study area should reduce their exposure in light of this, especially during the dry season.

Geostatistical analysis of arsenic contamination in soil and comparison of interpolation techniques in Nadia district of Bengal, India

The contamination of soil and water with arsenic directly or indirectly affects millions of people, particularly in Southeast Asia. Efficiently managing contaminated sites cost-effectively requires an understanding of the spatial distribution of contamination in soil. In this study, different interpolation methods, including Ordinary Kriging (OK), Inverse Distance Weighted (IDW), Radial Basis Function (RBF), and Empirical Bayesian Kriging (EBK), were evaluated in the Bengal region to determine their effectiveness in predicting the Olsen extractable As content in the soil. The study found that the mean Olsen extractable content in soil was 1.45 mg kg-1 , with a range of 0.48 to 3.57 mg kg-1 . Geostatistical analysis showed that the northern side of Nadia had relatively high contamination, while the southern side had relatively lower contamination. The Root Mean Square Error (RMSE) values of the different interpolation methods ranged from 0.52 to 0.54, with corresponding mean cross-validation (CV) values ranging from -0.005 to 0.008. The predicted minimum and maximum values of as-in soil were in close agreement with the measured values for IDW interpolation, followed by OK, RBF, and EBK. The study found that IDW consistently provided the most precise predictions of pollution in the soil throughout space. These findings have significant implications for managing contamination in the Nadia West Bengal and other regions facing similar challenges.

APPARATUS FOR LOCALIZATION AND DOSIMETRY OF WOUNDS WITH RADIOACTIVE CONTAMINATION.

Disasters involving radioactive materials are one of the most dangerous accidents a living organism can be exposed to. Individuals and first responders are in risk during accidents or interventions, due to radioactive debris impact, due to the use of depleted uranium ammunition or a malevolent act against individuals. Moreover, radioactive contamination of wounds causes internal exposure in the body and standard decontamination procedures cannot be applied. In order to deal with such situations, we are developing a measurement system consisting of a robotic arm, an array of various detectors and a corresponding methodology, which allows quantifying timely the spatial distribution of contamination and the radiation dose for the adequate medical response. The aim of this publication is to the present current status of the development of the described apparatus.

Seawater intrusion decreases the metal toxicity but increases the ecological risk and degree of treatment for coastal groundwater: An Indian perspective

Contaminant vulnerability in the critical zones like groundwater (GW)-seawater (SW) continuum along the entire Gujarat coast was investigated for the first time through an extensive water monitoring survey. The prime focus of the study was to evaluate whether or not: i) seawater intrusion induced metal load translates to toxicity; ii) in the coastal groundwater, metal distribution follows the pattern of other geogenic and anthropogenic contaminants like NO3- and F-; and iii) what future lies ahead pertaining to metal fate in association with saturation conditions of the coastal aquifers. The spatial distribution of contaminants depicts that the Gulf of Khambhat area is highly contaminated. Ecological risk assessment (ERA) indicates that the Gujarat coast is experiencing a high ecological risk compared to the southeast coast of India. Investigation results revealed that metals, pH, NO3, and CO3 are more vulnerable at the SW-GW mixing interface. An increase in pH is reflected in fewer ionic species of metals in the GW. Salinity ingress due to seawater intrusion (SWI) reduces the toxicities of all trace metals except Cu, attributed to the increase of Ca in GW, leading to dissociation of CuCO3. Reactive species are dominant for Zn and Cd; and M-CO3 ligands are dominant for Cu and Pb owing to the undersaturation of dolomite and calcite in the aquifer system. SWI tends to increase the metal load but the toxicity of metals varies with the density of industries, anthropogenic activities, changes in the mixing-induced saturation conditions, and intensive salt production across the coast. Multivariate analysis confirmed that the hydrogeochemical processes change due to GW-SW mixing and dictates over natural weathering. The ecological risk index (ERI) for the Arabian sea is experiencing moderate (300 ≥ ERI>150) to high ecological risk (ERI >600). Children population is likely to encounter a high health risk through ingestion and dermal exposure than adults. Overall, the study emphasizes the complexity of toxicity-related health impacts on coastal communities and suggests the dire need for frequent water monitoring along the coastal areas for quick realization of sustainable development goals.

A multitechnique approach for the identification of multiple contamination sources near a polluted industrial site

AbstractDegraded land requires rapid and suitable remedial actions, thus appropriate and fast methodological approaches for estimating the spatial distribution of contaminants are needed. In this context, a methodological approach combining isotopic measurements, heavy metals concentrations mapping, X‐ray diffraction, and cluster analysis, was applied to characterize a polluted industrial site where the contamination due to improper waste disposal could have spread also into the surrounding fields. This approach was applied to a set of representative topsoil (from 15 to 30 cm depth) and subsoil (from 130 to 150 cm depth) samples, selected either inside or outside the contaminated site. The X‐ray diffraction analysis highlighted that only the mineralogy of the subsoil below the buried waste was noticeably altered, while the concentration mapping highlighted that the levels of several heavy metals on the edge of the contaminated site, at both depths, were very similar to those found in the samples from the outside. Based on these findings, Pb was used as a tracer for heavy metal pollution by its stable isotopes' analysis. The cluster analysis of the isotopic measurements revealed that only the contamination detected inside the industrial site could be attributed to the pollutants migration from the buried waste. Conversely, the contaminants concentrations found in the topsoil samples taken outside the site could be ascribed to contamination sources other than the polluted waste present inside the site.

Spatial distribution of contaminants and water quality assessment using an indexical approach, Astore River basin, Western Himalayas, Northern Pakistan

Astore River is an important tributary located in the Upper Indus River Basin, Western Himalayas, Northern Pakistan. This study aimed at assessing water quality of the river for domestic, drinking, and irrigation purposes. Astore river (n = 40) samples were collected and analyzed for a set of 17 physicochemical parameters. Water quality index (WQI), corrosion, scaling tendencies, and irrigation water quality indices were used for its grading and statistical analyses for the source apportionment of contaminants. Results indicated that turbidity, fluoride, and nitrate (NO3) values surpassed the safe limits in 60%, 2.5%, and 2.5% of samples. WQI revealed that only 19.5% of samples were classified in poor and very poor water quality classes due to turbidity and NO3. Irrigation and corrosion indices of the river showed its suitability for agriculture and corrosive tendency. The dominant hydro-chemical facies were Ca-Mg/Cl-SO4 and results suggested that natural sources play a role in shaping hydrochemistry.

Use of Geographically Weighted Regression (GWR) to Reveal Spatially Varying Relationships between Cd Accumulation and Soil Properties at Field Scale

The spatial variation of correlation between Cd accumulation and its impact factors plays an important role in precise management of Cd contaminated farmland. Samples of topsoils (n = 247) were collected from suburban farmland located at the junction of the Yellow River Basin and the Huaihe River Basin in China using a 200 m × 200 m grid system. The total and available contents of Cd (T-Cd and A-Cd) in topsoils were analyzed by ICP-MS, and their spatial distribution was analyzed using kriging interpolation with the GIS technique. Geographically weighted regression (GWR) models were applied to explore the spatial variation and their influencing mechanisms of relationships between major environmental factors (pH, organic matter, available phosphorus (A-P)) and Cd accumulation. Spatial distribution showed that T-Cd, A-Cd and their influencing factors had obvious spatial variability, and high value areas primarily cluster near industrial agglomeration areas and irrigation canals. GWR analysis revealed that relationships between T-Cd, A-Cd and their environmental factors presented obvious spatial heterogeneity. Notably, there was a significant negative correlation between soil pH and T-Cd, A-Cd, but with the increase of pH in soil the correlation decreased. A novel finding of a positive correlation between OM and T-Cd, A-Cd was observed, but significant positive correlation only occurred in the high anthropogenic input area due to the complex effects of organic matter on Cd activity. The influence intensity of pH and OM on T-Cd and A-Cd increases under the strong influence of anthropogenic sources. Additionally, T-Cd and A-Cd were totally positively related to soil A-P, but mostly not significantly, which was attributed to the complexity of the available phosphorus source and the differences in Cd contents in chemical fertilizer. Furthermore, clay content might be an important factor affecting the correlation between Cd and soil properties, considering that the correlation between Cd and pH, SOM, A-P was significantly lower in areas with lower clay particles. This study suggested that GWR was an effective tool to reveal spatially varying relationships at field scale, which provided a new idea to further explore the related influencing factors on spatial distribution of contaminants and to realize precise management of a farmland environment.

Multivariate tools to investigate the spatial contaminant distribution in a highly anthropized area (Gulf of Naples, Italy)

The Gulf of Naples located in a high anthropized coastal area is subjected to an infrastructural intervention for the installation of a submarine power pipeline. In order to evaluate the distribution of contaminants in the seafloor sediments, a preliminary study has been conducted in the area using multivariate techniques. The statistic approach was performed to gain insights on the occurrence of organic and inorganic contaminants within the area, aiming to identify the relevant hot spots. Three geographical sub-areas influenced by different contaminant association were recognized: Torre Annunziata (TA), Capri (CA), and middle offshore (MO). TA and CA resulted marked by a severe contamination pattern due to anthropogenic pressures. In addition, the influence of the depositional basin in governing the contamination trend has been pointed out. The supervised technique PLS_DA resulted to be a powerful tool in addressing the complexity of the huge dataset acquired during the marine survey, highlighting the main trends in the variability of quality indicators, orienting thus the deeper investigations during follow-up monitoring activities.

Upotreba fluorescencije indukovane laserskim zračenjem (LIF) kao metode u Sjedinjenim Američkim Državama

Spatial characterization of the contamination is a fundamental component of any remediation approach. Compared to conventional investigation methods, the laser-induced fluorescence (LIF) is a faster screening tool and provides the detection of hydrocarbon contamination in real-time. This investigation was conducted at a hydrocarbon-contaminated site in Pennsylvania, US. The presence of light nonaqueous-phase liquids (LNAPL) was detected in 6 of 17 LIF borings, with the reference emitter responses ranging between 45% and 225%. The depth of the response was highly accurate and valuable and provided insight into the spatial distribution of contamination. The results indicated that no substantial amount of LNAPL existed along the LIF borings profile, thus excluding this area as a preferential LNAPL migration pathway. The obtained results contributed to the characterization and remediation of this industrial site.

Health risk assessment and spatial distribution of nitrate, nitrite, fluoride, and coliform contaminants in drinking water resources of kazerun, Iran

Exposure to nitrate, nitrite, and fluoride through drinking water consumption, especially in arid and semi-arid regions, has been considered by many researchers. Therefore, the present study aimed to investigate the status of nitrate, nitrite, fluoride, and total coliforms in water supply sources of Kazerun located in Fars province, Iran, determine their spatial distribution, and perform health risk assessment in four age groups (infants, children, teenagers, and adults). In this research, the concentration data of 25 groundwater wells were examined. Then, the spatial distribution of the contaminants was determined using the Arc GIS software (v. 10.5) and their health risk assessment was performed via the standard method of the US Environmental Protection Agency. The maximum concentrations of nitrate, nitrite, and fluoride were 25.5, 0.056, and 0.72 mg/l, respectively and their mean concentrations were 13.5, 0.008, and 0.52 mg/l, respectively. In addition, the mean and maximum concentrations of coliforms were 371.21 and 2694.50 CFU/100 ml, respectively. The total coliforms value was higher than the permissible limit in 60 % of the cases. The highest Chronic Daily Intake (CDI) of the studied contaminants was related to nitrate among children (range: 0.21–1.45, with an average value of 0.77 mg/kg-day). Moreover, the Hazard Quotient (HQ) values were below 1 for all contaminants and in all age groups. The highest HQ value (0.9) belonged to nitrate amongst children. Furthermore, the Hazard Index (HI), as a cumulative effect of HQ, was calculated for all three contaminants and the results showed that it was greater than 1 in 56 % of the cases among children, which was considered a serious risk. The findings revealed no significant relationship between nitrate and nitrite concentrations and total coliforms. Overall, nitrate seemed to play a more critical role in the health risk of the exposed age groups in comparison to nitrite and fluoride. Hence, appropriate managerial measures are recommended to be taken.

SPATIAL DISTRIBUTION, POLLUTION, AND HEALTH RISK ASSESSMENT OF HEAVY METAL IN INDUSTRIAL AREA SOILS OF ULAANBAATAR, MONGOLIA

Abstract. The heavy metal pollution of urban soil of industrial area and its impact on human healths becoming one of the environmental problems in Ulaanbaatar city of Mongolia. The purpose of this study was to determine spatial distribution and health risk of heavy metal pollution in soils surrounding area of leather processing factory and wastewater treatment plants (WWTP) of Ulaanbaatar city. Mapping the spatial distribution of contaminants in soils is the basis of pollution evaluation and risk control. Interpolation methods are extensively applied in the mapping processes to estimate the heavy metal (As, Zn, Pb, Cd, Cr, Cu) concentrations of topsoils. The average concentrations of Cr, Ni, Pb, Zn, Cu and As were 1986.9, 110.5, 111.0, 110.5, 53.5, 16.4 mg/kg, respectively. According to result as the soil pollution index with spatial distribution, a high pollution level for Cr while Zn, Cu and Pb have medium pollution levels. The soil pollution index (PI) values of heavy metals of study areas are, following descending orders Cr > Zn > Cu > Pb > As > Ni. The potential ecological risk of Cr, Cu, Pb, As indicated high ecological risk in the study area. The Hazard index values for almost all the metals were higher than 1, it is indicating a carcinogenic risk for children and adults. The risk index values of two metals (Cr, As) were contribute to a higher risk of development of cancer in humans. Heavy metal contamination can occur when soil particles are swept away from the initial pollution areas by the wind. Therefore, it is necessary to take measures to reduce soil pollution and encourage rehabilitation.

Spatial and temporal distribution of surface water contaminants in the Houston Ship Channel after the Intercontinental Terminal Company Fire.

Background:The fire at the Intercontinental Terminals Company (ITC, Deer Park, La Porte, TX, USA) from March 17-20, 2019 resulted in substantial releases of chemical contaminants to the environment, including the surface waters of the Houston Ship Channel.Objective:To characterize spatial and temporal trends, as well as potential human health risks, from these releases.Methods:Out of 433 substances with available data, seven were selected for analysis: benzene, toluene, ethylbenzene, xylenes, oil & grease, suspended solids, and total petroleum hydrocarbons. Spatial and temporal concentration trends were characterized, and hazard quotients and cancer risks were calculated to estimate the potential for human health impacts from these contaminants.Results:Temporal analysis showed presence of these chemical contaminants in water immediately after the event; their concentrations dissipated substantially within 4 weeks. The spatial distribution of contaminants indicated the highest concentrations in the waterways within about 1km of the ITC. The greatest potential human health risks stemmed from presence of benzene.Significance:A short-term but substantial spike in the concentrations of a number of hazardous contaminants occurred near the incident, with concentrations returning to apparent baseline levels within one month likely due to a combination of volatization, dilution and degradation.