Heavy metal pollution of soils and risk assessment in Houston, Texas following Hurricane Harvey

Isotopic insights and integrated analysis for heavy metal levels, ecological risks, and source apportionment in river sediments of the Qinghai-Tibet Plateau

The research was carried out to examine the pollution characteristics, ecological risk, and origins of seven heavy metals (Hg, As, Pb, Cu, Cd, Zn, and Ni) in 51 sediment samples gathered from 8 rivers located on the Qinghai-Tibet Plateau (QTP) in China. The contents of Hg and Cd were 5.0 and 1.1 times higher than their background values, respectively. The mean levels of other measured heavy metals were below those found naturally in the local soil. The enrichment factor showed that the study area exhibited significantly enriched Hg with 70.6% sampling sites. The Cd contents at 19.6% of sampling sites were moderately enriched. The other sampling sites were at a less enriched level. The sediments of all the rivers had a medium level of potential ecological risk. Hg was the major ecological risk factor in all sampling sites, followed by Cd. The findings from the positive matrix factorization (PMF) analysis shown agricultural activities, industrial activities, traffic emissions, and parent material were the major sources. The upper, middle, and low reaches of the Quanji river had different Hg isotope compositions, while sediments near the middle reaches were similar to the δ202Hg of the industrial source. At the upstream sampling sites, the Hg isotope content was very close to the background level. The results of this research can establish a strong scientific sound to improve the safety of the natural circumstances of rivers on the QTP.

Using L. minor and C. elegans to assess the ecotoxicity of real-life contaminated soil samples and their remediation by clay- and carbon-based sorbents

Toxic substances, such as polycyclic aromatic hydrocarbons (PAHs) and heavy metals, can accumulate in soil, posing a risk to human health and the environment. To reduce the risk of exposure, rapid identification and remediation of potentially hazardous soils is necessary. Adsorption of contaminants by activated carbons and clay materials is commonly utilized to decrease the bioavailability of chemicals in soil and environmental toxicity in vitro, and this study aims to determine their efficacy in real-life soil samples. Two ecotoxicological models (Lemna minor and Caenorhabditis elegans) were used to test residential soil samples, known to contain an average of 5.3, 262, and 9.6 ppm of PAHs, lead, and mercury, for potential toxicity. Toxicity testing of these soils indicated that 86% and 58% of soils caused ≤50% inhibition of growth and survival of L. minor and C. elegans, respectively. Importantly, 3 soil samples caused ≥90% inhibition of growth in both models, and the toxicity was positively correlated with levels of heavy metals. These toxic soil samples were prioritized for remediation using activated carbon and SM-Tyrosine sorbents, which have been shown to immobilize PAHs and heavy metals, respectively. The inclusion of low levels of SM-Tyrosine protected the growth and survival of L. minor and C. elegans by 83% and 78%, respectively from the polluted soil samples while activated carbon offered no significant protection. These results also indicated that heavy metals were the driver of toxicity in the samples. Results from this study demonstrate that adsorption technologies are effective strategies for remediating complex, real-life soil samples contaminated with hazardous pollutants and protecting natural soil and groundwater resources and habitats. The results highlight the applicability of these ecotoxicological models as rapid screening tools for monitoring soil quality and verifying the efficacy of remediation practices.

Characteristics and pollution risks of potentially toxic elements and nematode community structure on farm soil near coal mines

As one of the most important coal-producing provinces of China, Shanxi Province has been concerned about soil potentially toxic elements (PTEs) contamination in recent years. The study aimed to determine the status and sources of PTEs contamination and evaluate the quality of the soil ecology. This study investigated the degree of 13 PTEs contamination. The sources and contributions of PTEs were traced by the absolute principal component score followed by a multiple linear regression model (APCS-MLR). And the status of the soil ecosystem was verified by evaluating the soil nematode community around the coal mining areas in Jinzhong. The results showed that the mean PTEs concentration of 5 trace elements were higher than the background values of Shanxi, and safe to considerable was indicated by the pollution and ecological risk values. Soil Hg was the most contaminated element, followed by Cd. The distribution of PTEs was determined by coal mining activities (44.72%) followed by agricultural practice (32.37%) and coal transportation (21.37%). The nematode genera Acrobeloides (4.01%), Aphelenchus (20.30%), Meloidogyne (11.95%) and Aporcelaimus (2.74%) could be regarded as bioindicators of soil PTEs contamination by their tolerance. Concentrations of soil Cr, Mn, Ti and Cd showed remarkable influences on the total nematode abundance, maturity index, enrichment index, structural index, Shannon-Wiener diversity index and Pielou index of soil nematode. It is an appropriate method to evaluate the status of soil PTEs contamination combining the response of a single nematode genus and the nematode community evaluation index.

Valorised polypropylene waste based reversible sensor for copper ion detection in blood and water

Heavy metals and plastic pollutants are the two most disastrous challenges to the environment requiring immediate actions. In this work, a techno-commercially feasible approach to address both challenges is presented, where a waste polypropylene (PP) based reversible sensor is produced to selectively detect copper ions (Cu2+) in blood and water from different sources. The waste PP-based sensor was fabricated in the form of an emulsion-templated porous scaffold decorated with benzothiazolinium spiropyran (BTS), which produced a reddish colour upon exposure to Cu2+. The presence of Cu2+ was checked by naked eye, UV-Vis spectroscopy, and DC (Direct Current) probe station by measuring the current where the sensor's performance remained unaffected while analysing blood, water from different sources, and acidic or basic environment. The sensor exhibited 1.3 ppm as the limit of detection value in agreement with the WHO recommendations. The reversible nature of the sensor was determined by cyclic exposure of the sensor towards visible light turning it from coloured to colourless within 5 min and regenerated the sensor for the subsequent analysis. The reversibility of the sensor through exchange between Cu2+- Cu+ was confirmed by XPS analysis. A resettable and multi-readout INHIBIT logic gate was proposed for the sensor using Cu2+ and visible light as the inputs and colour change, reflectance band and current as the output. The cost-effective sensor enabled rapid detection of the presence of Cu2+ in both water and complex biological samples such as blood. While the approach developed in this study provides a unique opportunity to address the environmental burden of plastic waste management, it also allows for the possible valorization of plastics for use in enormous value-added applications.

Unseen Risk: Mapping Contamination Hazards to Enhance Risk Perception in Galena Park, Texas

As extreme weather events have become more frequently observed in recent decades, concerns about exposure to potential flood risk have increased, especially in underserved and socially vulnerable communities. Galena Park, Texas, is a socially vulnerable community that also confronts escalated physical vulnerabilities due to existing flood risks from Buffalo Bayou and the Houston Ship Channel as well as proximity to industrial facilities that emit chemical pollution. To better understand the underlying risks that Galena Park is facing, this research assesses and visualizes the existing contamination hazards associated with the chemical facilities within Galena Park. Through this process, we (1) compute the environmental, health, and physical hazards associated with industrial facilities, (2) spatially geocode the points of contamination sources and flood exposure, and (3) increase awareness of existing risk by visualizing and distributing related information using an ArcGIS Dashboard. The results indicate that there are 169 points of location from 127 industrial facilities, and 24 points were inducing potential chemicals. In total, 126 chemicals have potential physical, health, and environmental hazards. On average, each facility has 2.4 chemicals that could cause potential hazards with a range of zero to 57 chemicals. When examining the specific physical, health, and environmental risks associated with the chemicals, on average each facility has 14.6 types of risks associated with it. This includes, on average, 9.8 types of health hazards, 1.53 physical hazards, and 2.3 environmental hazards per facility. When analyzing the spatial relationship between the chemical exposure and the current flood risk using the Dashboard, it is noticeable that most of the industrial facilities are located in the south of Galena Park, near Buffalo Bayou, where a variety of industrial facilities are clustered. Through this study, we spatially mapped the existing risks in Galena Park that are not readily available to the community and risks that are not currently tangible or visible. The utility of ArcGIS Dashboards affords the opportunity to translate massive databases into digestible knowledge that can be shared and utilized within the community. This study also takes another step toward building community resilience by providing knowledge that can be used to prepare for and respond to disasters. Visualizing unseen risks and promoting awareness can enhance risk perception when supported by scientific knowledge. Further investigation is necessary to enhance preparedness behaviors, identify proper evacuation techniques and routes, and build community networks to comprehensively promote resilience to multi-hazard circumstances.

An Adaptive Toolkit for Projecting the Impact of Green Infrastructure Provisions on Stormwater Runoff and Pollutant Load-A Case Study on the City of Galena Park, Texas, USA

The implementation of green infrastructure in retrofit projects to reduce flooding and pollution is a significant challenge in space- constrained and overly developed communities which also have complex underground utility systems. To overcome this challenge, the authors have developed an adaptive green infrastructure toolkit that can be tailored by both on-ground spatial size and underground depth of obstruction. This study aims to assess the effectiveness of this toolkit in mitigating flooding and non-point source pollutants by demonstrating the case of the city of Galena Park, Texas, USA, which has suffered from severe flooding as well as on-ground and underground space constraint issues. We first applied the toolkit to create a master plan for Galena Park and evaluated the effect of the plan by using the Delft3D-FM (Flexible Mesh) flood model alongside the Long-Term Hydrologic Impact Assessment (L-THIA) model. The results demonstrate progressive reductions in stormwater runoff and NPS pollutants across different phases. These findings highlight the toolkit's effectiveness in improving water management and pollution control, providing valuable empirical evidences for similar communities facing similar challenges.

First-principle study on the stability of Cd passivates in soil

The stable existence of heavy metals in soil under natural conditions is the core issue in heavy metal pollution solidification and remediation technology. However, the existing research is limited to soil passivation tests of different materials or biochar adsorption tests and cannot reveal the internal mechanism of functional groups of different compounds in soil passivation. This paper takes the common heavy metal ion Cd²⁺ as an example to analyze the stability of the combination of heavy metal ions and common ion groups in soil. The stability and existing form of Cd are analyzed by using first-principle calculations, and the free energy, band structure, and partial density of states of CdCO₃, CdSO₄, CdCl₂, and CdSiO₃ are computed. The stability of Cd binding to common anions in soil is determined. Results show the descending order of structural stability of cadmium compounds is CdSiO₃, CdSO₄, CdCO₃, and CdCl₂. SO₄^2- and SiO₃^2- can be used as preferred functional groups for cadmium pollution passivation. Anhydrous sodium sulfate and sodium silicate are promising passivators.

A review of common natural disasters as analogs for asteroid impact effects and cascading hazards

Modern civilization has no collective experience with possible wide-ranging effects from a medium-sized asteroid impactor. Currently, modeling efforts that predict initial effects from a meteor impact or airburst provide needed information for initial preparation and evacuation plans, but longer-term cascading hazards are not typically considered. However, more common natural disasters, such as volcanic eruptions, earthquakes, wildfires, dust storms, and hurricanes, are likely analogs that can provide the scope and scale of these potential effects. These events, especially the larger events with cascading effects, are key for understanding the scope and complexity of mitigation, relief, and recovery efforts for a medium-sized asteroid impact event. This paper reviews the initial and cascading effects of these natural hazards, describes the state of the art for modeling these hazards, and discusses the relevance of these hazards to expected long-term effects of an asteroid impact. Emergency managers, resource managers and planners, and research scientists involved in mitigation and recovery efforts would likely derive significant benefit from a framework linking multiple hazard models to provide a seamless sequence of related forecasts.

Delineating and identifying risk zones of soil heavy metal pollution in an industrialized region using machine learning

The ability to control the risk of soil heavy metal pollution is limited by the inability to accurately depict their spatial distributions and to reasonably delineate the risk zones. To overcome this limitation and develop machine learning methods, a hybrid data-driven method supported by random forest (RF) and fuzzy c-means with the aid of inverse distance weighted interpolation was proposed to delineate and further identify risk zones of soil heavy metal pollution on the basis of 577 soil samples and 12 environmental covariates. The results indicated that, compared to multiple linear regression, RF had a better prediction performance for As, Cd, Cr, Cu, Hg, Ni, Pb, and Zn, with the corresponding R² values of 0.86, 0.85, 0.78, 0.85, 0.84, 0.78, 0.79 and 0.76, respectively. The relative concentrations (predicted concentrations divided by risk screening values) of Cd (17.69), Cr (1.38), Hg (0.31), Pb (6.52), and Zn (8.24) were relatively high in the north central part of the study area. There were large differences in the key influencing factors and their contributions among the eight heavy metals. Overall, industrial enterprises (21.60% for As), soil pH (31.60% for Cd), and population (15.50% for Cr) were the key influencing factors for the heavy metals in soil. Four risk zones, including one high risk zone, one medium risk zone, and two low risk zones were delineated and identified based on the characteristics of the eight heavy metals and their influencing factors, and accordingly discriminated risk control strategies were developed. In the high risk zone, it will be necessary to strictly control the discharge of heavy metals from the various industrial enterprises and mines by the adoption of cleaner production practices, centralizedly treat the domestic wastes from residents, substantially reduce the irrigation of polluted river water, and positively remediate the Cd, Cr, and Ni-polluted soil.

Contamination Assessment and Potential Human Health Risks of Heavy Metals in Urban Soils from Grand Forks, North Dakota, USA

Heavy metal (HM) pollution of soil is an increasingly serious problem worldwide. The current study assessed the metal levels and ecological and human health risk associated with HMs in Grand Forks urban soils. A total 40 composite surface soil samples were investigated for Mn, Fe, Co, Ni, Cu, Zn, As, Pb, Hg, Cr, Cd and Tl using microwave-assisted HNO3-HCl acid digestion and inductively coupled plasma mass spectrometry (ICP-MS) analysis. The enrichment factor (EF), contamination factor (CF), geoaccumulation index (Igeo), ecological risk and potential ecological risk index were used for ecological risk assessment. The park soils revealed the following decreasing trend for metal levels: Fe > Mn > Zn > Cr > Ni > Cu > Pb > As > Co > Cd > Tl > Hg. Based on mean levels, all the studied HMs except As and Cr were lower than guideline limits set by international agencies. Principal component analysis (PCA) indicated that Mn, Fe, Co, Ni, Cu, Zn, As, Cd, Pb, Cr and Tl may originate from natural sources, while Hg, Pb, As and Cd may come from anthropogenic/mixed sources. The Igeo results showed that the soil was moderately polluted by As and Cd and, based on EF results, As and Cd exhibited significant enrichment. The contamination factor analysis revealed that Zn and Pb showed moderate contamination, Hg exhibited low to moderate contamination and As and Cd showed high contamination in the soil. Comparatively higher risk was noted for children over adults and, overall, As was the major contributor (>50%), followed by Cr (>13%), in the non-carcinogenic risk assessment. Carcinogenic risk assessment revealed that As and Cr pose significant risks to the populations associated with this urban soil. Lastly, this study showed that the soil was moderately contaminated by As, Cd, Pb and Hg and should be regularly monitored for metal contamination.

Distribution, accumulation, migration and risk assessment of trace elements in peanut-soil system

Trace elements contamination is mainly originated from industrial emission, sewage irrigation and pesticides, and poses a threat to the environment and human health. This study analyzed the trace element pollutants in peanut-soil systems, the enrichment and translocation capacity of peanut to trace elements, and the potential risk of trace elements to environment and human health. The results indicated that Cd and Ni in peanut kernels exceeded the standard limits in 2019, and the exceeding rate were 9% and 31%, respectively. Cd in 8% of soil samples and As in 98% of soil samples exceeded the risk screening value of trace elements. The concentration of trace elements in peanuts was related to varieties and planting regions. In addition, there was a significant positive correlation between the concentration of Cd in peanut kernel and its concentration in soil. Compared with other trace elements, peanut kernels had stronger ability to enrich and transport Cd, Cu, and Zn, the BFs were 0.45, 0.51 and 0.47, respectively. After oil extraction, trace elements were mainly concentrated in peanut meal, and only 0.25% of Cd was in oil. The RI of trace elements was less than 150, indicating that the study area was under low degree of ecological risk. However, As and Cd might pose moderate risk to environment. Trace elements in soil and peanut could not cause non-carcinogenic and carcinogenic risks to human, but the HI and CR value of As (0.59 and 9.54 × 10^-5) in soil and CR_ing value of Cd (9.25 × 10^-7) in peanut were close to the critical value. We conclude that Cd pollution in peanut kernel, and Cd and As pollution in soil should be monitored to enter into the food chain or environment and to avoid the possible health hazards and environment risks.

Mixed Contaminants: Occurrence, Interactions, Toxicity, Detection, and Remediation

The ever-increasing rate of pollution has attracted considerable interest in research. Several anthropogenic activities have diminished soil, air, and water quality and have led to complex chemical pollutants. This review aims to provide a clear idea about the latest and most prevalent pollutants such as heavy metals, PAHs, pesticides, hydrocarbons, and pharmaceuticals—their occurrence in various complex mixtures and how several environmental factors influence their interaction. The mechanism adopted by these contaminants to form the complex mixtures leading to the rise of a new class of contaminants, and thus resulting in severe threats to human health and the environment, has also been exhibited. Additionally, this review provides an in-depth idea of various in vivo, in vitro, and trending biomarkers used for risk assessment and identifies the occurrence of mixed contaminants even at very minute concentrations. Much importance has been given to remediation technologies to understand our current position in handling these contaminants and how the technologies can be improved. This paper aims to create awareness among readers about the most ubiquitous contaminants and how simple ways can be adopted to tackle the same.

Geo-Accumulation Index of Manganese in Soils Due to Flooding in Boac and Mogpog Rivers, Marinduque, Philippines with Mining Disaster Exposure

This paper presents the effects of flooding on the accumulation of manganese (Mn) in soils within proximity of the Boac and Mogpog rivers in Marinduque of The Philippines. Marinduque, an island province in the Philippines, experienced two catastrophic tailings storage facility (TSF) failures in the 1990s that released sulfide-rich tailings into the two major rivers. The Philippines experiences 21–23 typhoons every year, 11 of which pass thru Marinduque that causing inundation of floodplain areas in the province. A flood hazard map developed using LiDAR DEM was utilized for the Boac and Mogpog rivers for an accurate representation of flooding events. A portable X-ray fluorescence spectrometer (pXRF) and a Hannah multi-parameter device were used for the on-site analyses of Mn concentration and water physico-chemical properties, respectively. Spatial grid mapping with zonal statistics was employed for a comprehensive analysis of all the data collected and processed. Correlation analysis was carried out on Mn concentrations in soil and surface water, electrical conductivity (EC), total dissolved solids (TDS), pH, temperature, curve number (CN), and flood heights. The curve number indicates the runoff response characteristic of the Mogpog-Boac River basin. The results show that 40% of the total floodplain area of Boac and Mogpog were subjected to high hazards with flood heights above 1.5 m. The Mn content of soils had a statistically significant moderate positive correlation with flood height (r = 0.458) and a moderate negative correlation with pH (r = −0.438). This condition suggested that more extensive flooding promotes Mn contamination of floodplain soils in the two rivers, the source of which includes the mobilization of Mn-bearing silt, sediments, and mine drainage from the abandoned mine pits and TSFs. There is also a strong negative correlation between pH and Mn concentrations in surface water, a relationship attributed to the solubilization of Mn-bearing precipitates based on geochemical modeling results. Using Muller’s geo-accumulation index, 77.5% of the total floodplain of the two rivers was identified as “moderately contaminated” with an average Mn soil content of 3.4% by weight (34,000 mg/kg). The Mn contamination map of floodplain soils in the Mogpog and Boac rivers described in this study could guide relevant regional, national, and local government agencies in planning appropriate intervention, mitigation, remediation, and rehabilitation strategies to limit human exposure to highly contaminated areas.