Fly Ash as an Ingredient in the Contaminated Soil Stabilization Process

Fly ash is the main by-product of coal combustion characterized by a large specific surface area. In addition to oxides, it also contains unburned coal and trace elements. This study aimed to investigate the possibility of using fly ash from pit-coal combustion (CFA) for the treatment of benzene-contaminated soil (S). The CFA was used as a mixture with Portland cement (PC) (70% PC + 30% CFA). The soil was treated with a PC-CFA mixture in amounts of 40, 60, and 80% of soil mass. During the process, the concentration of benzene was monitored with the flame-ionization detector. Produced monoliths (S+(PC-CFA)x) were tested for compressive strength and capillary water absorption. The experiment confirmed that the PC-CFA mixture limited benzene emission. The highest reduction in benzene concentration (34–39%) was observed for samples treated with the PC-CFA mixture in an amount of 80% (S+(PC-CFA)80). The average compressive strength of monoliths S+(PC-CFA)40, S+(PC-CFA)60, and S+(PC-CFA)80 was 0.57, 4.53, and 6.79 MPa, respectively. The water absorption values were in the range of 15–22% dm.

External Exposure to BTEX, Internal Biomarker Response, and Health Risk Assessment of Nonoccupational Populations near a Coking Plant in Southwest China

Benzene, toluene, ethylbenzene and xylene isomers (BTEX) have raised increasing concern due to their adverse effects on human health. In this study, a coking factory and four communities nearby were selected as the research area. Atmospheric BTEX samples were collected and determined by a preconcentrator GC–MS method. Four biomarkers in the morning urine samples of 174 participants from the communities were measured by LC–MS. The health risks of BTEX exposure via inhalation were estimated. This study aimed to investigate the influence of external BTEX exposure on the internal biomarker levels and quantitatively evaluate the health risk of populations near the coking industry. The results showed that the average total BTEX concentration in residential area was 7.17 ± 7.24 μg m−3. Trans,trans-muconic acid (T,T-MA) was the urinary biomarker with the greatest average level (127 ± 285 μg g−1 crt). Similar spatial trends can be observed between atmospheric benzene concentration and internal biomarker levels. The mean values of the LCR for male and female residents were 2.15 × 10−5 and 2.05 × 10−5, respectively. The results of the risk assessment indicated that special attention was required for the non-occupational residents around the area.

The influence of benzene air pollution on leukemia incidence and mortality rates

The following study identifies areas where adverse conditions related to benzene pollution are concurrent with leukaemia incidence and mortality (C91–C95). Moreover, it determines the similarities between benzene and leukaemia levels, as well and rules defining their co-occurrence. The analysis covered the period of 2015–2017. Data were obtained from Dane.gov.pl (number of leukaemia cases), the Polish National Cancer Registry website (number of deaths), the Local Data Bank of the Central Statistical Office (population data) and the Chief Inspectorate of Environmental Protection and the Air Quality Portal (data on air quality). Based on the conducted analysis, it was concluded that the following poviat towns have an unfavourable epidemic situation related to leukaemia: Kielce (incidence), Rzeszów (incidence), Elbląg (mortality); meanwhile, high leukaemia incidence and mortality co-occurred with high average benzene concentration in 2015–2017 in the following poviat towns: Kielce, Rybnik, Płock and Rzeszów. It was found that leukaemias belonging to the three-character ICD-10 categories C94, C95 and C92 show the highest rate of co-occurrence with benzene concentration. In addition, two main rules for the co-occurrence of benzene pollution and leukaemia were identified. It was also noted that it is necessary to continue the research for a longer time period, especially in the poviat towns of Kielce and Rzeszów.

Box Experiment Study of Thermally Enhanced SVE for Benzene

In order to describe the changes of soil temperature field, air flow field and remediation situation with time during the process of thermally enhanced SVE (soil vapor extraction), a remediation experiment of benzene contaminated soil with single extraction pipe was carried out in a box device. The results showed that the whole temperature of the system was raised to 80 °C in 4 h. 43% of benzene were removed in the first 2% of the extraction time. After 24 h, the repair efficiency was close to 100%. The device can efficiently remove benzene from soil. By continuously monitoring the parameters in the operation process of the system, the spatial distribution of temperature and soil gas pollutant concentration with time was plotted. It showed the benzene concentration distribution in the soil gas was more consistent with the temperature distribution before the start of ventilation, and the concentration of benzene in the soil gas dropped rapidly after ventilation, while the temperature distribution was almost unaffected. In the treatment of soil with a benzene content of 17.8 mg∙kg−1, when the soil gas benzene concentration is the highest at 180 min, the peak value is 11,200 mg∙m−3, and the average concentration is 7629.4 mg∙m−3.

Predicting Benzene Concentration Using Machine Learning and Time Series Algorithms

Benzene is a pollutant which is very harmful to our health, so models are necessary to predict its concentration and relationship with other air pollutants. The data collected by eight stations in Madrid (Spain) over nine years were analyzed using the following regression-based machine learning models: multivariate linear regression (MLR), multivariate adaptive regression splines (MARS), multilayer perceptron neural network (MLP), support vector machines (SVM), autoregressive integrated moving-average (ARIMA) and vector autoregressive moving-average (VARMA) models. Benzene concentration predictions were made from the concentration of four environmental pollutants: nitrogen dioxide (NO2), nitrogen oxides (NOx), particulate matter (PM10) and toluene (C7H8), and the performance measures of the model were studied from the proposed models. In general, regression-based machine learning models are more effective at predicting than time series models.

Determination of Carcinogenic Toluena Detox Mass In Printing Industrial Workers In Surabaya

Background This study aims to calculate the intake of foods rich in CYP2E1 enzymes and glutathione to increase toluene detoxification. Methods The research design used was a cross sectional method. The research location is printing industry in Surabaya, East Java. The number of respondents was 30 workers of the printing industry. The calculated variables included body weight, work duration (years), work frequency per week (days), average workday (hours) of the respondent and benzene concentration. After all variables were obtained, respiration rate and carcinogenic detox benzene food intake per respondent were determined. Results All respondents who were at work showed benzene concentrations below the threshold value (TLV). Foods containing CYP2E1 enzyme included beef liver, salmon and fish oil while food with glutathione included grapes, avocados and asparagus. Conclusion Adequacy levels of CYP2E1 enzymes and glutathione are different and varied. The effective dose required by each respondent depends on body weight, length of work, and toluene concentration at work. In sum, the greater the toluene concentration, the greater the dietary needs which are rich in enzymes and CYP2E1 glutathione. Each respondent can choose benzene detox food depending on their needs and appetite.

Assessment of Traffic Policemen Exposure To Benzene by Using Trans, Trans-Muconic Acid Biomarker in Ahvaz City, Iran

Benzene is known as an environmental and industrial pollutant. One way to check the amount of exposure to benzene is to measure its metabolites in the urine. Trans, Trans-Muconic Acid which is one of its metabolites is also as a biological indicator of exposure to benzene. In this study, the relationship between the amount of this biomarker and the environmental benzene concentration was investigated in two groups of policemen working outdoors in the traffic-congested areas and indoor in the same area. The results showed that the highest amount of benzene was in Salman Farsi Station at 4.44 ppm. At the same time, the biomarker measured in the urine showed 127.20 μg / L, which was the highest amount. In addition, the amount of benzene in the outdoor was approximately 3 times more than indoor and the amount of biomarker measured in outdoor employees was two times more than indoors ones. In general, wherever there was more benzene, the biomarker would also show a higher amount.