Benzene homologues contaminants in a former herbicide factory site: distribution, attenuation, risk, and remediation implication

An Analysis of the Spatial Characteristics and Transport Fluxes of BTEX in Soil and Atmospheric Phases at a Decommissioned Steel Mill Site in China with a Long History

BTEX (benzene, toluene, ethylbenzene, and xylene), as characteristic pollutants in chemical plant sites, are widely present in the environment and pose a serious threat to the health and safety of nearby residents. Studying the spatial distribution characteristics and transport fluxes of BTEX in soil and air at contaminated sites and the health risks they pose to humans is of great significance for fine pollution control and environmental management. This study took a typical decommissioned steel plant as a case study. A total of 23 soil and air samples were collected from different locations to investigate the spatial distribution characteristics of BTEX in soil and air. The transport and fate of BTEX in soil and air were evaluated using the fugacity model, and finally, a human health risk assessment was conducted. The results indicate a relatively severe level of benzene pollution in both soil and air. The maximum exceedance factor of benzene in soil samples is 31.5, with the concentration exceedance depth at 1.5 m. The maximum concentration of benzene in air samples is 4.98 μg·m-3. Benzene, at 5.9% of the site, shows a low flux with negative values, while other components at various locations all exhibit a trend of transport from the soil phase to the atmospheric phase. Benzene is the pollutant that contributes the most to the transport flux from soil to air within the site. The coking area and sewage treatment area are key areas within the steel mill where BTEX accumulate easily in the soil. The non-carcinogenic risk values of the individual components of BTEX in the soil are below the acceptable risk level. However, the carcinogenic risk value of benzene in the children's exposure scenario exceeds the carcinogenic risk level of 10-6. The carcinogenic risk range of various components of BTEX in the air is 2.63 × 10-6~3.88 × 10-5, with 28.6% of the locations exceeding the threshold of 10-6. The range of the total HI (hazard index) is 2.08 × 10-4~1.81 × 10-1, all of which is below the safety threshold of 1. The results of this study will provide scientific support for the fine pollution control and environmental management of industrial contaminated sites with BTEX as their typical pollutants.

Target and non-target analysis of organochlorine pesticides and their transformation products in an agrochemical-contaminated area

Organochlorine pesticides show biological toxicity and their degradation typically takes many years. Previous studies of agrochemical-contaminated areas have mainly focused on limited target compounds, and emerging pollutants in soil have been overlooked. In this study, we collected soil samples from an abandoned agrochemical-contaminated area. Target analysis and non-target suspect screening by gas chromatography coupled with time-of-flight mass spectrometry were combined for qualitative and quantitative analysis of organochlorine pollutants. Target analysis showed that dichlorodiphenyltrichloroethane (DDT), dichlorodiphenyldichloroethylene (DDE), and dichlorodiphenyldichloroethane (DDD) were the main pollutants. With concentrations between 3.96 × 10⁶ and 1.38 × 10⁷ ng/g, these compounds posed significant health risks at the contaminated site. Non-target suspect screening identified 126 organochlorine compounds, most of which were chlorinated hydrocarbons and 90% of the compounds contained a benzene ring structure. The possible transformation pathways of DDT were inferred from proven pathways and the compounds identified by non-target suspect screening that had similar structures to DDT. This study will be useful for studies of the degradation mechanism of DDT. Semi-quantitative and hierarchical cluster analysis of compounds in soil showed that the distribution of contaminants in soil was influenced by the types of pollution sources and distance to them. Twenty-two contaminants were found in the soil at relatively high concentrations. The toxicities of 17 of these compounds are currently not known. These results improve our understanding of the environmental behavior of organochlorine contaminants in soil and are useful for further risk assessments of agrochemical-contaminated areas.

Three-dimensional distribution characteristics of multiple pollutants in the soil at a steelworks mega-site based on multi-source information

Soil pollution at steelworks mega-sites has become a severe environmental issue worldwide. However, due to the complex production processes and hydrogeology, the soil pollution distribution at steelworks is still unclear. This study scientifically cognized the distribution characteristics of polycyclic aromatic hydrocarbons (PAHs), volatile organic compounds (VOCs), and heavy metals (HMs) at a steelworks mega-site based on multi-source information. Specifically, firstly, 3D distribution and spatial autocorrelation of pollutants were obtained by interpolation model and local indicators of spatial associations (LISA), respectively. Secondly, the characteristics of horizontal distribution, vertical distribution, and spatial autocorrelations of pollutants were identified by combining multi-source information such as production processes, soil layers, and properties of pollutants. Horizontal distribution showed that soil pollution in steelworks mainly occurred in the front end of the steel process chain. Over 47% of PAHs and VOCs pollution area were distributed in coking plants and over 69% of HMs in stockyards. Vertical distribution indicated that HMs, PAHs, and VOCs were enriched in the fill, silt, and clay layers, respectively. Spatial autocorrelation of pollutants was positively correlated with their mobility. This study clarified the soil pollution characteristics at steelworks mega-sites, which can support the investigation and remediation of steelworks mega-sites.

Eu(III)-Functionalized MOF-Based Dual-Emission Ratiometric Sensor Integrated with Logic Gate Operation for Efficient Detection of Hippuric Acid in Urine and Serum

With the introduction of Eu³⁺ ions as the secondary fluorescent signal reporter and sensing active sites, a dual-emission ratiometric sensor of Eu³⁺@NiMOF (Eu³⁺ functional NiMOF) for hippuric acid (HA) detection in urine and serum was fabricated via the postsynthetic encapsulating strategy. Based on the two emission signals at 441 nm (turn-on) and 628 nm (turn-off), the produced Eu³⁺@NiMOF ratiometric sensor provided enhanced sensitivity, higher selectivity, and 9.7 times lower limits of detection (LOD) for the detection of HA (2.38 μM, 0.42 μg·mL^-1) than that of the pristine NiMOF. Considering the high sensitivity and visualization results, further exploration of intelligent applications in the HA sensing process was carried out by constructing a tandem combinational logic gate to improve the practicability and convenience with the help of a smartphone. This work provides a promising approach for developing MOF-based ratiometric sensors to detect biomarkers.

Three-dimensional spatial prediction of Zn in the soil of a former tire manufacturing plant using machine learning and readily attainable multisource auxiliary data

Pollutants in the soil of industrial site are often highly heterogeneously distributed, which brought a challenge to accurately predict their three-dimensional (3D) spatial distributions. Here we attempt to create effective 3D prediction models using machine learning (ML) and readily attainable multisource auxiliary data for improving the prediction accuracy of highly heterogeneous Zn in the soil of a small-size industrial site. Using raw covariates from functional area layout, stratigraphic succession, and electrical resistivity tomography, and derived covariates of the raw covariates as predictors, we created 6 individual and 2 ensemble models for Zn, based on ML algorithms such as k-nearest neighbors, random forest, and extreme gradient boosting, and the stacking approach in ensemble ML. Results showed that the overall 3D spatial patterns of Zn predicted by individual and ensemble ML models, inverse distance weighting (IDW), and ordinary Kriging (OK) were similar, but their predictive performances differed significantly. The ensemble model with raw and derived covariates had the highest accuracy in representing the complex 3D spatial patterns of Zn (R² = 0.45, RMSE = 344.80 mg kg^-1), compared to the accuracies of individual ML models (R² = 0.27-0.44, RMSE = 396.75-348.56 mg kg^-1), OK (R² = 0.33, RMSE = 381.12 mg kg^-1), and IDW interpolation (R² = 0.25, RMSE = 402.94 mg kg^-1). Besides, the prediction accuracy gains of incorporating derived covariates were higher than adopting ensemble ML instead of single ML algorithm. These results highlighted the importance of developing derived covariates whilst adopting ML in predicting the 3D distribution of highly heterogeneous pollutant in the soil of small-size industrial site.

Systematic Review of the Health and Equity Impacts of Remediation and Redevelopment of Contaminated Sites

(1) Background: Globally there is a vast legacy of contaminated sites from past industrial, commercial and military activity, waste disposal, and mineral extraction. This review examined the extent to which the remediation of contaminated sites reduces health risks to new and existing populations. (2) Methods: Standard academic databases were searched for papers that reported on health-related outcomes in humans following remediation and redevelopment of contaminated sites. Title/abstract screening, followed by full-text screening identified sixteen papers that met the eligibility criteria. (3) Results: Most studies were set in the United States of America and reported changes in blood lead concentrations in children, following soil remediation and, in some cases, public health campaigns to reduce exposure. Two further studies examined the impacts of remediation on soil contaminated with chromium and sediments contaminated with polychlorinated biphenyls (PCBs). (4) Conclusions: Overall, the evidence suggests that remediation via removal, capping, and replacing soil, and planting vegetation is effective at reducing concentrations of lead and chromium in blood and urine in children. There is also evidence that sediment dredging can reduce PCB concentrations in umbilical cords in infants. Study designs are relatively weak and some recommendations are provided for those wishing to examine the health impacts of remediation.

Probabilistic human health-risk assessment and influencing factors of aromatic hydrocarbon in groundwater near urban industrial complexes in Northeast China

Organic pollutants are common in the environment, very difficult to remove, and pose a serious threat to human health. Probabilistic risk assessment advances conservative single-point estimation and brings a new perspective to risk assessment. From 2009 to 2019, we monitored the distribution of major pollutants in an industrial park in Northeastern China. The result showed the maximum concentration of benzene reached 73,680 μg/L in 2009, benzo[a]pyrene reached 36.80 ng/L in 2016. These concentrations are significantly above the levels set by Chinese regulatory agencies. The single-factor index increases year by year, and pollutants gradually spread from the pollution leakage source to surrounding areas. A new method was used to quantify the human health risk from groundwater organic pollution accurately, based on the triangular fuzzy numbers coupled with the Monte Carlo simulation. The Monte Carlo simulation was used to simulate the triangular fuzzy numbers. This simplified the operation between the triangular fuzzy numbers and their function successfully and obtained the risk as a set of values. The results indicated that non-carcinogenic risk was negligible in all age groups (children, adolescents, and adults). Conversely, when it comes to carcinogenic risks, adults were about 50-270 times the tolerable level of risk due to long exposure years and wide skin contact areas. Oral ingestion played an essential role in total exposure (>90%) compared to dermal contact. Control of exposure duration and intake should be prioritized when making decisions to reduce risk uncertainty. Monte Carlo simulation-triangular fuzzy numbers can effectively reduce the risk of uncertainty and reflect the complex conditions of the groundwater environment for small amounts of data or inaccurate data.