Pollution characteristics of aromatic hydrocarbons in the groundwater of China

Identification and quantification of low concentration phenol and toluene in groundwater by fluorescence spectroscopy with Gaussian feature extraction

Groundwater, a vital freshwater resource, faces increasing contamination risks from chemical industrial parks discharging hazardous compounds such as phenol and toluene. Detecting these pollutants at low concentrations is essential to ensure water quality and protect against long-term hazards. A method combining fluorescence spectroscopy and Gaussian feature extraction is proposed for the identification and quantification of phenol and toluene in groundwater. Fluorescence excitation-emission matrix (EEM) spectra of phenol and toluene are first measured, followed by feature extraction using a Gaussian function. The extracted features are then employed for qualitative identification and quantitative determination via support vector machine (SVM) and partial least squares (PLS) regression, respectively. For qualitative identification, Gaussian feature extraction is compared with original feature and PCA-based feature extraction methods. For quantification, it is compared with peak picking and PCA-based feature extraction methods. The results show that after Gaussian feature extraction, the performance is significantly improved. The identification accuracy for single-component samples reached 95.24 %, while for mixture samples, the accuracy was 90 %. In quantitative analysis of mixture samples, the average relative error for phenol concentrations of 2 µg/L or higher and toluene concentrations of 600 µg/L was controlled around 10 %, while for phenol concentrations at 1 µg/L, the relative error was about 30 %. This approach enhances both identification and quantification performance, providing a reliable tool for the early detection and quantification of low-concentration contaminants in groundwater, with great potential for environmental protection.

Hydrochemistry characteristics and genesis of shallow groundwater in diverse industrial agglomeration areas in typical alluvial plain of the Yellow River

The groundwater environment in the middle and upper reaches of the Yellow River in China has attracted extensive attention. But, the hydrochemistry characteristics and genesis of shallow groundwater in diverse industrial agglomeration areas in typical alluvial plain of the Yellow River are still unknown. In this study, geochemical analysis methods, the positive matrix factorisation model, and the geodetector model were used to multidimensional analyze. The results showed that 78 % of the groundwater samples had high-alkalinity-risk and high-salinity-risk, and the water quality was poor and unsuitable for irrigation. "Very poor" and "undrinkable" samples accounted for 26.31 %. The weathering of calcium magnesium minerals and the dissolution of soluble sulfate were important sources of the main chemical components of the groundwater. However, evaporation and concentration gradually dominated from the inclined plain of the piedmont to the alluvial plain of the Yellow River. Domestic and agricultural activities were important sources of nitrogen species (NO3-, NO2-, and NH4+). The presence of Al, Mn, Zn, and Pb was caused by the production activities of various enterprises. The pollution contributors of natural sources, domestic and agricultural activities, industrial production and other sources were 29.49 %, 17.05 %, 31.41 %, and 22.05 %, respectively. Groundwater velocity and enterprise type were the main factors driving groundwater pollution by these four metal substances. The interaction between enterprise type and groundwater velocity had the greatest influence on the concentrations of Al, Mn, and Zn. Moreover, the interaction between enterprise type and the distance from enterprise had the greatest influence on Pb levels. Overall, groundwater pollution in the study area was the result of both natural and human factors. The findings of this study can offer valuable insights and theoretical support for preventing groundwater pollution in other industrial agglomeration areas in the alluvial plain of the Yellow River.

Regulation of the co-transport of toluene and dichloromethane by adsorbed phase humic acid under different hydro-chemical conditions

The transport behavior of combined organic pollutants in soil and groundwater has attracted significant attention in recent years. Research on the influence of humic acid (HA) on organic pollutant transport behavior mainly focuses on the study of the mobile phase HA, with less research on the adsorbed phase HA, especially regarding its interaction with combined pollutants. To enhance understanding of the regulation of co-transport and retention of combined pollutants by adsorbed phase HA, in this study, tests were conducted to investigate how toluene (TOL) and dichloromethane (DCM) are transported in the presence of adsorbed phase HA at different pH levels and ionic strengths. As the proportions of HA-coated sand increased, so did its adsorption capacity for TOL and DCM, which can be attributed to adsorbed phase HA providing more adsorption sites compared to plain sand, thereby reducing the transport potential of the pollutants. The presence of both TOL and DCM facilitated their mutual transportation due to competitive adsorption controlled by the adsorbed phase HA content in the porous medium. Furthermore, it was observed that pH levels influenced the transport behavior of TOL and DCM when adsorbed phase HA was present since adsorbed phase HA transformation into mobile phase was regulated by pH levels. The transport patterns can be effectively simulated using the chemical nonequilibrium two-site sorption model in HYDRUS-1D, accurately reflecting the retardation coefficients and transport distances based on model parameters. This work sheds new light on the regulatory role of adsorbed phase HA in TOL and DCM transport under diverse hydrochemical conditions, with implications for accurately depicting the behavior of combined pollutants, optimizing the remediation strategies and improving remediation efficiency in contaminated sites.

Development of an effective QSAR-based hazard threshold prediction model for the ecological risk assessment of aromatic hydrocarbon compounds

The insufficient hazard thresholds of specific individual aromatic hydrocarbon compounds (AHCs) with diverse structures limit their ecological risk assessment. Thus, herein, quantitative structure-activity relationship (QSAR) models for estimating the hazard threshold of AHCs were developed based on the hazardous concentration for 5% of species (HC5) determined using the optimal species sensitivity distribution models and on the molecular descriptors calculated via the PADEL software and ORCA software. Results revealed that the optimal QSAR model, which involved eight descriptors, namely, Zagreb, GATS2m, VR3_Dzs, AATSC2s, GATS2c, ATSC2i, ω, and Vm, displayed excellent performance, as reflected by an optimal goodness of fit (R2adj = 0.918), robustness (Q2LOO = 0.869), and external prediction ability (Q2F1 = 0.760, Q2F2 = 0.782, and Q2F3 = 0.774). The hazard thresholds estimated using the optimal QSAR model were approximately close to the published water quality criteria developed by different countries and regions. The quantitative structure-toxicity relationship demonstrated that the molecular descriptors associated with electrophilicity and topological and electrotopological properties were important factors that affected the risks of AHCs. A new and reliable approach to estimate the hazard threshold of ecological risk assessment for various aromatic hydrocarbon pollutants was provided in this study, which can be widely popularised to similar contaminants with diverse structures.

Prioritization of organic contaminants in China's groundwater based on national-scale monitoring data and their persistence, bioaccumulation, and toxicity

There has been increasing concern regarding the adverse environmental and health effects of organic pollutants. A list of priority control organic pollutants (PCOPs) can provide regulatory frameworks for the use and monitoring of organic compounds in the environment. In this study, 20,010 groundwater samples were collected from 15 "first level" groundwater resource zones in China. Fifty (50) organic compounds were analyzed based on their prevalence, occurrence, and physicochemical properties (persistence, bioaccumulation, and toxicity). Results showed that 16 PCOPs, including 12 pesticides, 3 aromatic hydrocarbons (AHs), and 1 phthalate ester, were recognized. Pesticides and AHs accounted for 75 % and 18.75 % of the high-priority pollutants, respectively. There were significant differences in PCOPs between confined and phreatic groundwater. Higher concentrations of pesticides were mainly detected in phreatic groundwater. PCOPs detected in samples from the 15 groundwater resource zones were mainly pesticides and AHs. The groundwater data indicate that the organic compounds detected in the Yellow River Basin (YRB), Yangtze River Basin (YZB), Liaohe River Basin (LRB), and Songhua River Basin (SRB) are mainly categorized as Q1 (high priority) and Q2 (medium priority) pollutants based on the contaminants ranking system in China. The findings from this study offer a snapshot of the wide distribution of PCOPs in the surveyed regions, and are expected to establishing treatment and prevention measures at both the regional and national levels in China.

Groundwater pollution risk, health effects and sustainable management of halocarbons in typical industrial parks

As important chemical raw materials and organic solvents, halogenated hydrocarbons not only play an important role in economic development, but are also the main source of environmental pollution. This study proposed an improved groundwater risk assessment model system, aimed at identifying and treating contaminants at leak sites. Groundwater ubiquity score (GUS) was used to evaluate the leachability of organic pollutants. The entropy-weighted water quality index (EWQI) method was used to assess the comprehensive quality of groundwater at the site. An improved groundwater health risk assessment model was constructed to analyze the health risks of groundwater. The sources of organic pollutants were identified based on the positive matrix factorization (PMF) model. Self-organizing mapping (SOM) and the K-means algorithm were integrated to classify and manage pollution source areas. The results showed that groundwater in the study area was strongly affected by human activities. The pollution source was located in a factory near S05. Different organic pollutants were highly leachable and had high potential to contaminate surrounding groundwater. 1,2-dichloropropane and 1,2,3-trichloropropane caused the largest range of contamination. The groundwater pollution index in the study area was high, and 72% of the monitoring points were non-drinkable. Both the carcinogenic and non-carcinogenic indexes of groundwater far exceeded the international standard limits and had a great impact on human health. 1,2,3-trichloropropane and 1,2-dichloropropane were major non-carcinogenic risk factors. The leakage of pollutants and pesticide solvents were the main causes of groundwater pollution. Cluster areas III and II were areas with significant pollution impacts and needed to be monitored intensively. Most areas were cluster I, with relatively low risk. This study can provide technical support for groundwater pollution risk assessment and management in similar industrial parks.

Investigation on molecular characteristics of organic compounds during a full-scale landfill leachate treatment process based on non-targeted analysis

In this study, a new methodology for evaluating full-scale landfill leachate treatment processes by non-targeted analysis using comprehensive two-dimensional gas chromatography quadrupole time-of-flight mass spectrometry (GC × GC-QTOF-MS) was proposed. The method revealed the chemical complexity of organic compounds in landfill leachate samples at the molecular level and evaluated the removal efficiency of the anaerobic-anoxic-oxic (A2O) - membrane bioreactor (MBR) - nanofiltration (NF) treatment process in conjunction with multi-level classification of organic compounds. Results showed that the results of non-targeted analysis combined with multi-level classification of organic compounds had a significant correlation with the conventional water quality parameters and can be used to evaluate the treatment process. A total of 2508 organic compounds were detected in 6 samples. 17 emerging contaminants (ECs) with known potentially hazards were detected, including Diisobutyl Phthalate (DIBP), which is toxic to male reproduction and development, and 4-Tert-Butylphenol, which causes endocrine disruption in animals. The removal rate of organic compounds by this full-scale landfill leachate treatment processes reached 79.14%. The anaerobic tank played a crucial role with 64.98% contribution. For compounds, the removal rate of heterocyclics was as high as 94.67%, and the removal rate of aliphatics was poor, only 63.49%. This treatment process had almost perfect removal effect on the steroids in alicyclics and phenols in aromatics, but poor treatment effect on saturated alkanes in aliphatics and naphthenes in alicyclics. This study provides a methodology for accurate assessment of the molecular level of treatment processes, new insights for process optimization in waste treatment plants, and data support for the detection of emerging contaminants. The environmental hazards of landfill leachate can be further evaluated in the future in conjunction with ecotoxicity assessment studies.

Modeling and optimization study on degradation of organic contaminants using nZVI activated persulfate based on response surface methodology and artificial neural network: a case study of benzene as the model pollutant

Due to the complicated transport and reactive behavior of organic contamination in groundwater, the development of mathematical models to aid field remediation planning and implementation attracts increasing attentions. In this study, the approach coupling response surface methodology (RSM), artificial neural networks (ANN), and kinetic models was implemented to model the degradation effects of nano-zero-valent iron (nZVI) activated persulfate (PS) systems on benzene, a common organic pollutant in groundwater. The proposed model was applied to optimize the process parameters in order to help predict the effects of multiple factors on benzene degradation rate. Meanwhile, the chemical oxidation kinetics was developed based on batch experiments under the optimized reaction conditions to predict the temporal degradation of benzene. The results indicated that benzene (0.25 mmol) would be theoretically completely oxidized in 1.45 mM PS with the PS/nZVI molar ratio of 4:1 at pH 3.9°C and 21.9 C. The RSM model predicted well the effects of the four factors on benzene degradation rate (R2 = 0.948), and the ANN with a hidden layer structure of [8-8] performed better compared to the RSM (R2 = 0.980). In addition, the involved benzene degradation systems fit well with the Type-2 and Type-3 pseudo-second order (PSO) kinetic models with R2 > 0.999. It suggested that the proposed statistical and kinetic-based modeling approach is promising support for predicting the chemical oxidation performance of organic contaminants in groundwater under the influence of multiple factors.

Spatiotemporal characteristics and dynamic risk assessment of a multi-solvents abandoned pesticide-contaminated site with a long history, in China

With the development of the economy and the adjustment of urban planning and layout, abandoned pesticide sites are widely distributed in major and medium cities in China. Groundwater pollution of a large number of abandoned pesticide-contaminated sites has caused great potential risks to human health. Up to now, few relevant studies concerned the spatiotemporal variation of risks exposure to multi-pollutants in groundwater using probabilistic methods. In our study, the spatiotemporal characteristics of organics contamination and corresponding health risks in the groundwater of a closed pesticide site were systematically assessed. A total of 152 pollutants were targeted for monitoring over a time span up to five years (i.e., June 2016-June 2020). BTEX, phenols, chlorinated aliphatic hydrocarbons, and chlorinated aromatic hydrocarbons were the main contaminants. The metadata was subjected to health risk assessments using the deterministic and probabilistic methods for four age groups, and the results showed that the risks were highly unacceptable. Both methods showed that children (0-5 years old) and adults (19-70 years old) were the age groups with the highest carcinogenic and non-carcinogenic risks, respectively. Compared with inhalation and dermal contact, oral ingestion was the predominant exposure pathway that contributed 98.41%-99.69% of overall health risks. Spatiotemporal analysis further revealed that the overall risks first increased then decreased within five years. The risk contributions of different pollutants were also found to vary substantially with time, indicating that dynamic risk assessment is necessary. Compared with the probabilistic method, the deterministic approach relatively overestimated the true risks of OPs. The results provide a scientific basis and practical experience for scientific management and governance of abandoned pesticide sites.

Anaerobic mineralization of toluene by enriched soil-free consortia with solid-phase humin as a terminal electron acceptor

The anaerobic biodegradation of toluene proceeds very slowly owing to limited electron acceptors in contaminated aquifer. The liquid reagents traditionally used to enhance this process readily migrate away from the contaminated site, and continuous addition would cause secondary pollution. In our previous study, the reduced solid-phase humic substances (humin), which are redox active, were found to act as electron donors to promote the microbial reactions. Here, we provide new evidence that humin can promote the anaerobic biodegradation of toluene as a terminal electron acceptor. When inoculating nitrate-reducing (NR) and iron-reducing (IR) consortia with toluene degradation activities, the average toluene degradation rates reached 21.20 ± 1.18 μmol/(L·d) and 15.43 ± 0.41 μmol/(L·d) in the presence of a sediment humin (HMcj), and 94.69% ± 4.26% and 93.20% ± 3.73% of the electrons released from toluene oxidation to CO₂ could be recovered by the reduction of HMcj, respectively. Spectroscopy analyses revealed that quinone moieties and nitrogen-containing moieties may be the electron-accepting groups of HMcj. Based on 16S rRNA sequencing, Cellulomonas spp. were the possible functional bacteria in the culture with NR consortium as the inoculum, while Azospira spp., Cellulomonas spp. and Bacillus spp. were the possible functional bacteria in the culture with IR consortium as the inoculum. Further Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt) analyses indicated that toluene oxidation and extracellular electron transfer functions were more abundant in HMcj amended cultures, suggesting a possible enhancement mechanism by HMcj. Additionally, experiments using natural groundwater illustrated that toluene degradation was highly dependent on its concentration, HMcj dosage, pH, and salinity. The study of a column filled with HMcj-coated quartz sand demonstrated a desirable level of toluene degradation in a continuous-flow mode without the presence of other electron acceptors. This study provided an effective and green approach for the remediation of the toluene-contaminated groundwater.

Response of environmental factors to attenuation of toluene in vadose zone

Contaminated groundwater migrates in reverse direction under capillary force in vadose zone, and the attenuation process of pollutant adsorption and microbial degradation changes the environment of vadose zone. In this study, the response of toluene to environmental factors during reverse migration and attenuation of toluene from aquifer to vadose zone was studied by column experiment and experimental data analysis. The changes of environmental factors, including potential of hydrogen (pH), dissolved oxygen (DO), and oxidation-reduction potential (ORP), and toluene concentration were monitored by soil column experiment under sterilized and non-sterilized conditions. The 16S rRNA molecular biological detection technology was used to quantitatively analyze the impact of microbial degradation on the environment. Finally, the correlation between environmental factors and concentration in the attenuation process of toluene in the vadose zone was quantitatively studied by Pearson Correlation Coefficient (PCC) and multivariate statistical equation. The results showed that pH was primarily affected by microbial degradation, and DO and ORP were primarily affected by both adsorption and microbial degradation. The attenuation of toluene was divided into two stages: adsorption dominated (0~26 d) and microbial degradation dominated (26~55 d). The degradation amounts of microorganisms at each position in the non-sterilized column from bottom to top were 9.37%, 55.34%, 68.64%, 75.70%, 66.03% and 42.50%. At the same time, the article proposes for the first time that there is an obvious functional relationship between environmental factors (DO, ORP, pH), time (t) and concentration (C_Toluene):C_Toluene=C₀+A100t+Bα+Cβ+D100γ, (α,β,γ are the pH, DO and ORP of capillary water, respectively; A, B, C and D are all undetermined coefficients), R² > 0.95. The results of this study may facilitate the use of simple and easy-to-obtain environmental factors to characterize the dynamic process of pollutant concentration changes.

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.

The Environmental Impact of a Complex Hydrogeological System on Hydrocarbon-Pollutants’ Natural Attenuation: The Case of the Coastal Aquifers in Eleusis, West Attica, Greece

The study area is the Thriassion Plain, an important area, in antiquity, surrounding the famous ancient town of Eleusis, 20 km west of Athens. The modern town and port and the entire area were heavily industrialized (1965–1995) coupled with unregulated urban and agricultural development. The presence of two crude oil refineries and other oil-related industries have strongly impacted the entire environment, including soils, waters and sediments of the broader area. The purpose of this work is to better understand how a multi-layered groundwater system affects the potential underground spread of certain fuel volatile compounds, namely the BTEX (benzene, toluene, ethylbenzene and total xylenes) as well as their attenuation after their direct or indirect release into the aquifer system. The spatial distribution of BTEX in groundwaters show that they were concentrated mainly in four rather restricted locations. Three of them were spotted, as expected, in the close vicinity of known pollution sources (a military airfield and two crude oil refineries). The other one corresponds to an abandoned site with no outstanding pollution sources where wells exist, eventually used for illegal dumping of oily wastes. It is important that the concentrations decrease significantly from autumn to spring. This decline could be characterized as natural attenuation, related to natural dilution phenomena and a flushing out of pollutants discharging through underwater springs to the sea during the rainy period (October to April). This, in turn, could be associated to the specific geological conditions affecting the hydrology, such as the unconsolidated non-permeable deposits and the multi layered formations of the area’s aquifers.