Environmental and lifestyle factors affect benzene uptake biomonitoring of residents near a petrochemical plant

Background

We monitored urinary benzene excretion to examine factors affecting benzene uptake in a sample of the general population living near a petrochemical plant.

Methods

Our study population included 143 subjects: 33 petrochemical plant workers (W) with low level occupational benzene exposure; 30 residents in a small town 2 km from the plant (2kmR); 26 residents in a second small town located 2 to 4 km from the plant (4kmR); and 54 urban residents 25 km from the plant (25kmR). Exposure to benzene was evaluated by personal air sampling during one work-shift for the W group, and from 8.00 to 20:00 for general population subgroups, and by urinary benzene (BEN-U).

Results

Median airborne benzene exposure was 25, 9, 7 and 6 μg/m³ benzene among the W, 2kmR, 4kmR, and 25kmR subgroups, respectively; the highest level was found among the workers, while there was no significant difference among the other groups. Median BEN-U was 2 to 14-fold higher in smokers compared to non-smokers; among non-smokers BEN-U was the highest in W (median 236 ng/L), and lower in the 2kmR (48 ng/L) and 4kmR (63 ng/L) subgroups than in the 25kmR (120 ng/L) subgroup. A multiple linear regression analysis, explaining up to 73% of BEN-U variability, confirmed that active smoking and airborne benzene most strongly affected BEN-U. Among the non-smoking, non-occupationally exposed study subjects, a positive association was found between BEN-U and the distance of residence from the plant. This association was explained by increased exposure to urban traffic emissions in the study group residing at a greater distance from the plant. Environmental tobacco smoke had a marginally positive role.

Conclusion

Among factors affecting benzene uptake in non-occupationally exposed individuals, urban residence contributes to benzene exposure more than residing in close proximity to a petrochemical plant.     

Urinary methyl tert-butyl ether and benzene as biomarkers of exposure to urban traffic

Methyl tert-butyl ether (MTBE) and benzene are added to gasoline to improve the combustion process and are found in the urban environment as a consequence of vehicular traffic. Herein we evaluate urinary MTBE (MTBE-U) and benzene (BEN-U) as biomarkers of exposure to urban traffic. Milan urban policemen (130 total) were investigated in May, July, October, and December for a total of 171 work shifts. Personal exposure to airborne benzene and carbon monoxide (CO), and atmospheric data, were measured during the work shift, while personal characteristics were collected by a questionnaire. A time/activity diary was completed by each subject during the work shift. Spot urine samples were obtained for the determination of MTBE-U and BEN-U. Median personal exposure to CO and airborne benzene were 3.3 mg/m(3) and 9.6 μg/m(3), respectively; median urinary levels in end-of-shift (ES) samples were 147 ng/L (MTBE-U) and 207 ng/L (BEN-U). The time spent on traffic duty at crossing was about 40% of work time. Multiple linear regression models, taking into account within-subject correlations, were applied to investigate the role of urban pollution, atmospheric conditions, job variables and personal characteristics on the level of biomarkers. MTBE-U was influenced by the month of sampling and positively correlated to the time spent in traffic guarding, CO exposure and atmospheric pressure, while negatively correlated to wind speed (R(2) for total model 0.63, P<0.001). BEN-U was influenced by the month and smoking habit, and positively correlated to urinary creatinine; moreover, an interaction between CO and smoking was found (R(2)=0.62, P<0.001). These results suggest that MTBE-U is a reliable marker for assessing urban traffic exposure, while BEN-U is determined mainly by personal characteristics.     

印染行业清洁生产技术

论述了目前印染行业水污染的现状及原因，指出调整产业结构、应用新工艺、大力提倡节约用水、清沽生产将是印染行业实现可持续发展的必由之路。     

Handling of dioxin measurement data in the presence of non-detectable values: overview of available methods and their application in the Seveso chloracne study

Exposure measurements of concentrations that are non-detectable or near the detection limit (DL) are common in environmental research. Proper statistical treatment of non-detects is critical to avoid bias and unnecessary loss of information. In the present work, we present an overview of possible statistical strategies for handling non-detectable values, including deletion, simple substitution, distributional methods, and distribution-based imputation. Simple substitution methods (e.g., substituting 0, DL/2, DL/ radical2, or DL for the non-detects) are the most commonly applied, even though the EPA Guidance for Data Quality Assessment discouraged their use when the percentage of non-detects is >15%. Distribution-based multiple imputation methods, also known as robust or "fill-in" procedures, may produce dependable results even when 50-70% of the observations are non-detects and can be performed using commonly available statistical software. Any statistical analysis can be conducted on the imputed datasets. Results properly reflect the presence of non-detectable values and produce valid statistical inference. We describe the use of distribution-based multiple imputation in a recent investigation conducted on subjects from the Seveso population exposed to 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD), in which 55.6% of plasma TCDD measurements were non-detects. We suggest that distribution-based multiple imputation be the preferred method to analyze environmental data when substantial proportions of observations are non-detects.     

应用时间-活动模式估计儿童个体NOx暴露水平

将时间-活动模式与微环境空气污染物监测相结合估计儿童个体NO_x暴露水平. 分别在北京和青岛两市各选择3所学校监测校园环境污染物,并在每个学校选择10名儿童监测其家庭居室空气中ρ(NO_x)及个体24 h NO_x暴露水平,同时收集其时间-活动信息,采用时间-活动模式估计儿童的个体暴露水平. 交通工具中的NO_x暴露水平可通过校门口空气中ρ(NO_x)和交通工具的污染水平系数(λ)估计.结果表明:利用时间-活动模式模拟的儿童个体24 h NO_x暴露水平为0.041 mg/m3,与调整后的个体暴露实测水平相关性较好(R0.785,P<0.01),差值为(-0.002　6±0.013　0) mg/m3,二者的差异无统计学意义 (t0.139,P>0.05).表明采用时间-活动模式与微环境空气质量监测结果相结合方法估计的儿童NO_x暴露水平与个体实际暴露水平一致.