Aliphatic hydrocarbons recovered in vegetables from soils based on their in-situ distribution in various soil humus fractions using a successive extraction method.

Aliphatic hydrocarbons (AHs) are major petroleum contaminants in the environment. In this study, the AHs bound to various soil endogenetic humus fractions were separated through successive extraction. Most of the AHs (46.

Influence of PAH speciation in soils on vegetative uptake of PAHs using successive extraction.

Polycyclic aromatic hydrocarbon (PAH) speciation in soils and the relationship between PAH speciation in soils and the accumulation of PAHs in vegetables have rarely been reported. In this study, the organic solvent extractable PAHs in soils, PAHs that bind to endogenetic soil humus, soil properties, and PAHs in B. chinensis were comprehensively studied.

Consistency between health risks and microbial response mechanism of various petroleum components in a typical wastewater-irrigated farmland.

Various petroleum components possess distinctive migration and toxicity characteristics. Evaluation of contamination levels on the basis of total concentrations of petroleum hydrocarbons in soil and groundwater is limited. Hunpu, a typical wastewater-irrigated area, is located at the southwest of Shenyang City, Liaoning Province, China.

Rainfall Threshold Assessment Corresponding to the Maximum Allowable Turbidity for Source Water.

  This study aims to assess the upstream rainfall thresholds corresponding to the maximum allowable turbidity of source water, using monitoring data and artificial neural network computation. The Taipei Water Source Domain was selected as the study area, and the upstream rainfall records were collected for statistical analysis. Using analysis of variance (ANOVA), the cumulative rainfall records of one-day Ping-lin, two-day Ping-lin, two-day Tong-hou, one-day Guie-shan, and one-day Tai-ping (rainfall in the previous 24 or 48 hours at the named weather stations) were found to be the five most significant parameters for downstream turbidity development.

Establishment of turbidity forecasting model and early-warning system for source water turbidity management using back-propagation artificial neural network algorithm and probability analysis.

The purpose of this study is to establish a turbidity forecasting model as well as an early-warning system for turbidity management using rainfall records as the input variables. The Taipei Water Source Domain was employed as the study area, and ANOVA analysis showed that the accumulative rainfall records of 1-day Ping-lin, 2-day Ping-lin, 2-day Fei-tsui, 2-day Shi-san-gu, 2-day Tai-pin and 2-day Tong-hou were the six most significant parameters for downstream turbidity development. The artificial neural network model was developed and proven capable of predicting the turbidity concentration in the investigated catchment downstream area.

Petroleum contamination of soil and water, and their effects on vegetables by statistically analyzing entire data set.

Aliphatic hydrocarbons have been used to assess total oil concentrations, petroleum sources, and petroleum degradation. In this study, surface soil, groundwater, surface water, and vegetables were collected from the outskirts of Xi'an, the largest city in northwestern China, and the samples were analyzed for aliphatic hydrocarbon contents. The concentrations of n-alkanes were 1.

Effects of pollution sources and soil properties on distribution of polycyclic aromatic hydrocarbons and risk assessment.

In this study, the concentrations of polycyclic aromatic hydrocarbons (PAHs) in soil profiles and the soil properties were analyzed in Hunpu, a typical wastewater irrigation area, northeast of China. The total concentrations of 16 priority control PAHs ranged from 7.88 to 2,231.