Surfactant-enhanced anoxic degradation of polycyclic aromatic hydrocarbons (PAHs) in aged subsurface soil at high temperature (60 °C).

Thermally enhanced anoxic biodegradation is emerging as a promising method for removing PAHs from subsurface soil. However, some PAHs still remain in soil following remediation with thermally enhanced anoxic degradation due to low bioavailability of these residual PAHs. The effects of five surfactants (Tween 80, TX 100, Brij 30, SDS, and SDBS) on the desorption of PAHs, anoxic degradation of PAHs, and native bacteria in soil at high temperature (60 °C) were evaluated in this study.

Polycyclic aromatic hydrocarbon removal from subsurface soil mediated by bacteria and archaea under methanogenic conditions: Performance and mechanisms.

In situ anoxic bioremediation is an easy-to-use technology to remediate polycyclic aromatic hydrocarbon (PAH)-contaminated soil. Degradation of PAHs mediated by soil bacteria and archaea using CO as the electron acceptor is an important process for eliminating PAHs under methanogenic conditions; however, knowledge of the performance and mechanisms involved is poorly unveiled. In this study, the effectiveness and efficiency of NaHCO (CO) as an electron acceptor to stimulate the degradation of PAHs by bacteria and archaea in highly contaminated soil were investigated.

Insights into the effects of Fenton oxidation on PAH removal and indigenous bacteria in aged subsurface soil.

Combined chemical oxidation and bioremediation is a promising method of treating polycyclic aromatic hydrocarbon (PAH) contaminated soil, wherein indigenous soil bacteria play a critical role in the subsequent biodegradation of PAHs after the depletion of the oxidant. In this study, different Fenton conditions were applied by varying either the oxidation mode (conventional Fenton (CF), Fenton-like (LF), modified Fenton (MF), and graded modified Fenton (GMF)) or the HO dosage (0%, 3%, 6%, and 10% (v/v)) to treat PAH contaminated soil. The results revealed that when equal dosages of HO are applied, PAHs are significantly removed following oxidation treatment, and the removal percentages obeyed the following sequence: CF > GMF > MF > LF.

Effectiveness of predicting the spatial distributions of target contaminants of a coking plant based on their related pollutants.

The prediction accuracy of the spatial distribution of soil pollutants at a site is relatively low. Related pollutants can be used as auxiliary variables to improve the prediction accuracy. However, little relevant research has been conducted on site soil pollution.

An effective method for determining the optimal sampling scale based on the purposes of soil pollution investigations and the factors influencing the pollutants.

There is a lack of a systematic method for determining the optimal sampling scale based on the purposes of soil pollution investigations (purpose) and the factors influencing of pollutants, which could affect the accuracy of determining pollution scope of the pollution. Therefore, in this study, both the purpose and the influencing factors were considered to determine the optimal sampling scale. The conclusions were obtained through geostatistical and spatial analysis.

Quantitative analysis of the main sources of pollutants in the soils around key areas based on the positive matrix factorization method.

Quantitative identification of the main sources of heavy metals and polycyclic aromatic hydrocarbons (PAHs) in soils around multiple types of key areas is of great significance for blocking pollution sources. However, there is a lack of more comprehensive relevant research. In this study, Beijing was taken as the research area and four main sources were identified using the positive matrix factorization (PMF) method.

Effectiveness of predicting spatial contaminant distributions at industrial sites using partitioned interpolation method.

Soil pollution at industrial sites is an important issue in China and in most other regions of the world. The accurate prediction of the spatial distribution of pollutants at contaminated industrial sites is a requirement for the development of most soil remediation strategies, and is commonly performed using spatial interpolation methods. However, significant and abrupt variations in the spatial distribution of pollutants decrease prediction accuracy.

Removal of polycyclic aromatic hydrocarbons (PAHs) and the response of indigenous bacteria in highly contaminated aged soil after persulfate oxidation.

Integrated chemical-biological treatment is a promising alternative to remove PAHs from contaminated soil, wherein indigenous bacteria is the key factor for the biodegradation of residual PAHs after the application of chemical oxidation. However, systematical study on the impact of persulfate (PS) oxidation on indigenous bacteria as well as PAHs removal is still scarce. In this study, the influences of different PS dosages (1%, 3%, 6%, and 10% [w/w]), as well as various activation methods (native iron, HO, alkaline, ferrous iron, and heat) on PAHs removal and indigenous bacteria in highly contaminated aged soil were investigated.

Comparison of common spatial interpolation methods for analyzing pollutant spatial distributions at contaminated sites.

Accurate prediction of the spatial distribution of pollutants in soils based on applicable interpolation methods is often the basis for soil remediation in contaminated sites. However, the applicable interpolation method has not been determined for contaminated sites due to the complex spatial distribution characteristics and stronger local spatial variability of pollutants. In this research, the prediction accuracies of three interpolation methods (including the different values of their parameters) for the spatial distribution of benzo[b]fluoranthene (BbF) in four soil layers were compared.

Quantitative analysis of the factors influencing spatial distribution of soil heavy metals based on geographical detector.

With the rapid development of modern industry, heavy metals in the soil introduce the risk of serious pollution. To reduce this pollution risk, the following four research questions needed to be addressed: What are the main influencing factors of soil pollution? What is the degree of influence? Do factors operate independently or are they interconnected? Which regions have high pollution risk and should be paid more attention? The study area was in Huanjiang County, with 273 km, and geographical detector proved to be a useful tool to solve these four problems. We found that mine activity and pH value were the primary influencing factors for total and water-soluble heavy metals.

Development of a model to simulate soil heavy metals lateral migration quantity based on SWAT in Huanjiang watershed, China.

Lateral transportation of soil heavy metals in rainfall events could significantly increase the scope of pollution. Therefore, it is necessary to develop a model with high accuracy to simulate the migration quantity of heavy metals. A model for heavy metal migration simulation was developed based on the SWAT (Soil and Water Assessment Tool) model.

Comparing ordinary kriging and inverse distance weighting for soil as pollution in Beijing.

Spatial interpolation method is the basis of soil heavy metal pollution assessment and remediation. The existing evaluation index for interpolation accuracy did not combine with actual situation. The selection of interpolation methods needs to be based on specific research purposes and research object characteristics.

[Screening of the Reduction/Stabilization Reagent for Cr(Ⅵ) Contaminated Soil in a Planting Site and Reaction Process Monitoring].

There are lots of problems in the domestic remediation of Cr (Ⅵ) contaminated soil field,such as lack of the key processing parameters,poor long-term effect and so on.The Cr (Ⅵ) heavy polluted surface soil was sampled from an electroplating site in North-China,and then treated with five different reducing reagents.At the same time,the on-line ORP probes and interval sampling test were chosen to monitor the reaction process,and to explore the reaction rate and effect.

Application of nitrate to enhance biodegradation of gasoline components in soil by indigenous microorganisms under anoxic condition.

Anaerobic/anoxic biodegradation of hydrocarbons offers an attractive approach to the removal of these compounds from polluted environments such as aquifers, aquatic sediments, submerged soils and subsurface soils. The application of nitrate was investigated to accelerate the degradation of gasoline components such as mono-aromatic hydrocarbons and total petroleum hydrocarbons (TPH) in soil by indigenous microorganisms under anoxic condition. The addition of nitrate had little effect on the degradation of mono-aromatic hydrocarbons m- & p-xylene, o-xylene, sec-butylbenzene and 1,2,4-trimethylbenzene, but facilitated the degradation of TPH (C6-C12) and mono-aromatic hydrocarbons toluene and ethylbenzene markedly.

Application of sewage sludge and intermittent aeration strategy to the bioremediation of DDT- and HCH-contaminated soil.

Adding organic amendments to stimulate the biodegradation of pesticides is a subject of ongoing interest. The effect of sewage sludge on the bioremediation of dichlorodiphenyltrichloroethane (DDT) and hexachlorocyclohexane (HCH) contaminated soil was investigated in bench scale experiments, and intermittent aeration strategy was also used in this study to form an anaerobic-aerobic cycle. Bioremediation of DDT and HCH was enhanced with the addition of sewage sludge and the intermittent aeration.

Risk assessment of water quality using Monte Carlo simulation and artificial neural network method.

There is always uncertainty in any water quality risk assessment. A Monte Carlo simulation (MCS) is regarded as a flexible, efficient method for characterizing such uncertainties. However, the required computational effort for MCS-based risk assessment is great, particularly when the number of random variables is large and the complicated water quality models have to be calculated by a computationally expensive numerical method, such as the finite element method (FEM).

Application of zerovalent iron (Fe(0)) to enhance degradation of HCHs and DDX in soil from a former organochlorine pesticides manufacturing plant.

Remediation of pesticide-polluted soil is particularly challenging when pesticides in soil are aged and a mixture of pesticides is present. Application of zerovalent iron (Fe(0)) was investigated to accelerate the degradation of HCHs (alpha-, beta-, gamma- and delta-hexachlorocyclohexane) and DDX (DDT, DDE and DDD) in the soil from a former organochlorine pesticide manufacturing plant. Ultrasonic extraction was used extract the organochlorine pesticides from soil.