Fenton法和类Fenton法降解土壤中的二苯砷酸

本文对Fenton法与类Fenton法降解土壤中的二苯砷酸(diphenylarsinic acid,DPAA)进行了研究.考察了H2O2投加量和催化剂种类(Fe2+/Fe3+)对红壤及黑土中DPAA降解效果的影响,并采用高效液相色谱-质谱联用法(HPLC-MS/MS)对降解中间产物进行了初步鉴定.结果显示,针对红壤与黑土分别采用类Fenton法与Fenton法,在H2O2投加浓度为1 mol·L-1,含铁催化剂浓度为0.25 mol·L-1,土水比为1∶3,反应时间为1h的条件下,红壤及黑土中DPAA的降解率均可达到65%以上.HPLC-MS/MS的分析结果表明,DPAA可脱苯环形成降解产物苯砷酸(phenylarsinic acid,PAA),而PAA进一步氧化生成无机砷,这可能是Fenton/类Fenton法降解DPAA的途径之一.     

江西钨矿周边土壤重金属生态风险评价:不同评价方法的比较

对江西省大余县某钨矿区周边的农田土壤进行调查分析,并采用不同的方法对土壤进行评价,结果表明,土壤As、Pb、Zn、Cu和Ni的含量范围分别为15.33—154.65 mg·kg-1、156.29—346.98 mg·kg-1、47.73—277.72 mg·kg-1、19.06—210.24 mg·kg-1和12.00—35.11 mg·kg-1,一些土壤样点的As、Pb、Zn和Cu含量已超过国家土壤环境质量二级标准.利用地累积指数法对土壤进行评价,结果表明土壤均受到As、Pb、Zn、Cu和Ni不同程度的污染;根据CPI(综合污染指数)评价标准,65.7%的土壤处于污染状态;利用TCLP法对土壤生态风险进行评价,结果显示所有土壤并未受到重金属的污染,以内梅罗综合污染指数法对土壤进行综合评价,结果表明该农田土壤重金属生态风险处于安全范围;以潜在生态危害指数法评价,发现Pb、As和Cu达到或超过中等生态风险的样点分别占37.14%、25.72%和2.86%,其他重金属污染风险均属轻微以下.不同评价方法得出的评价结果有差异,人们在评价重金属污染土壤时要根据评价的目的慎重选择合适的评价方法.     

药品和个人护理用品在固体基底中的检测方法和分布现状

药品和个人护理用品(Pharmaceuticals and personal care products,PPCPs)在环境中广泛存在,威胁生态环境和人类健康,受到越来越多的关注.本文综述了固体基底中PPCPs的检测方法,总结了国内外污泥、土壤、沉积物等基底中PPCPs的污染现状,并对PPCPs的进一步研究进行了展望.结果表明,PPCPs的检测方法朝多样化和趋优化的方向发展.污泥样品中PPCPs种类多、浓度高(μg·kg-1—mg·kg-1),土壤和沉积物中虽然浓度不高,但是总量不可小觑.目前,固体基底中的PPCPs还需要更全面和更广泛的研究.     

Chemopreventive effects of ellagic acid against genotoxicity induced by benzo(a)pyrene

Benzo(a)pyrene (B(a)P) is a commonly used indicator for polycyclic aromatic hydrocarbons (PAHs) contamination. The use of certain phytochemicals and some polyphenolic compounds proved to be effective in blocking PAH-induced effects. The aim of the present study was to examine the possible inhibitory effects of ellagic acid (EA), present in berries and nuts, against B(a)P-mediated toxicity using in vitro and in vivo test systems. In vitro method included the Ames test, using Salmonella typhimurium tester strain TA100. In vivo experiments were based on mouse bone marrow micronucleus (MN) assay and immunoblotting. EA produced a decrease in the number of revertant colonies against B(a)P in the Ames assay. Further, there was a reduction in the mean number of micronucleated polychromatic erythrocytes in the presence of EA in the co-treatment protocol of the MN test. Western blotting results showed downregulation of CYP450 isoform CYP1A1 which prevented bioactivation of B(a)P. Thus, the present study demonstrates antimutagenic role played by EA against the mutagenic activity of B(a)P in both in vitro and in vivo systems.     

广州地区孕妇羊水中PCBs暴露水平初步研究

随机采集广州地区非职业PCBs(polychlorinated biphenyls,多氯联苯)暴露单胎孕妇分娩时羊水,分析羊水中PCBs浓度水平;结合孕妇临床资料(年龄、孕周、身体质量指数(body mass index,BMI))以及孕妇居住环境信息等,阐明了广州地区非职业暴露孕妇羊水PCBs蓄积的影响因素。结果表明,∑33PCBs浓度为15.91-324.38 ng·g-1,平均值为114.34±83.52 ng·g-1,中值为84.8 5ng·g-1;其中十氯含量最低,平均浓度为2.66±3.46 ng·g-1,中值为1.47 ng·g-1;六氯PCBs含量最高,平均浓度为28.79±33.84 ng·g-1,中值为17.48 ng·g-1。样本中有31种PCBs同分异构体在孕妇羊水中检出,分别为PCB 8、28、30、49、52、70、74、77、82、87、99、101、105、114、118、126、128、138、153、156、158、166、169、170、179、180、183、187、189、198和209;羊水主要的PCBs暴露以五氯PCBs、六氯PCBs和七氯PCBs为主,主要的同分异构体为PCB 138(4.73%)、179(4.15%)、153(3.92%)、183(3.89%)、166(3.77%)、187(3.74%)以及180(3.67%);暴露水平与美国、西班牙、加拿大等地区相比属于严重水平。统计结果显示,年龄、身体质量指数和孕周与PCBs蓄积有显著性正相关关系;工业区居住的孕妇相与非工业区居住孕妇相比,上述统计结果更为显著。     

有机化学品不同温度下(过冷)液体蒸气压预测模型的建立与评价

(过冷)液体蒸气压(PL)是评价化学品在环境中分配、迁移和归趋行为的重要参数。PL具有较强的温度依附性。发展一种能够精确预测不同环境温度下化学品PL的方法,有助于填补化学品生态风险评估的大量数据缺失。本研究收集整理了661种有机化合物在不同温度下(200~830 K)共计10 478个log PL值。在此基础上,采用偏最小二乘(PLS)回归和支持向量机(SVM)方法,构建了PL的线性和非线性预测模型。结果表明:2种模型均具有良好的拟合度、稳健性及预测能力,SVM模型的预测性能略高于PLS模型(PLS:R2adj.tra=0.912,RMSEtra=0.477,Q2ext=0.910;SVM:R2adj.tra=0.997,RMSEtra=0.092,Q2ext=0.967)。机理分析表明,温度是影响PL的主要因素,温度越高,蒸气压越大;其次,X1sol也影响PL大小,X1sol用来描述分子间的色散作用,分子间色散力越小,蒸气压越大;此外,化合物的氢键个数、极性和分子构型等因素也影响PL大小。采用Wiliams plot方法表征了PLS模型应用域。所建立的模型可用来预测烷烃、烯烃、醇、酮、羧酸、苯、酚、联苯、卤代芳香烃、含N化合物及含S化合物在不同温度下的PL数据。     

Multi-objective transportation route optimization for hazardous materials based on GIS

Safety and security are of paramount importance, it is important to optimize and improve the routes of trucks that carry hazardous materials. In this study, we not only ensure the risk in the network, but also consider the transportation cost and the factors such as buildings and emergency facilities around the routes. The Geographic Information System (GIS) is used to quantify the factors on each section in the network. We present an epsilon constrained multi-objective mixed-integer linear programming optimization model to find the robust and stable transportation optimization solutions. At the end, we complete a case analysis of the proposed methodology to determine the motorway segments in Jiangsu province, China and test the above algorithm on the network, which has 144 nodes and 388 sections. The results we get show that the factors of buildings play a very important role in the model, and the multi-objective mixed-integer linear optimization model is reasonable and performs good quality.     

Structural equation model of the influence of noise annoyance on miners’ unsafe behavior in coal mines

Miners' unsafe behavior (UB) is the main cause of coal mine accidents. Previous research has suggested that excessive noise in tunnels impacts miners' temperaments and safe production behavior. To explore the influence of noise on UB, four different dimensions of noise annoyance were identified: cognitive, emotional, communication, and physical mechanism annoyance. The coal mine noise annoyance scale, miners' unsafe behavior intention (UBI) scale, and miners’ UB scale were developed according to different dimensions. In the first survey, a total of 200 questionnaires were distributed in the two coal mines, and 193 valid questionnaires were recovered. Exploratory factor analysis was conducted, and invalid items were removed according to the analysis results to form the final scale. Then, 500 final scales were distributed in two Chinese coal mines, and 482 valid questionnaires were collected. Confirmatory factor analysis was conducted by collating the data of the second questionnaire. Based upon the structural equation model (SEM), the SEM of the influence of noise annoyance degree on UB and the path analysis with latent variable path analysis with the latent variables (PA-LVs) mediating model of the effect of UBI on UB were established, and the path coefficients with fitting data of the model were analyzed. The results indicated that the four dimensions of coal mine noise annoyance had a strong positive impact on UB, which was reduced by less noise annoyance. In addition, the Bootstrap method was used to verify the mediating method among the four dimensions of noise annoyance, cognitive annoyance, emotional annoyance, with communication annoyance indirectly affecting UB through UBI. The research results provide theoretical support for reducing the UB of miners and improving coal mine safety levels.     

Experimental and theoretical research on the inhibition performance of ethanol gasoline/air explosion by C6F12O

The safety issue of ethanol gasoline and the methods to control or weaken its explosion have attracted attention. To clarify the effect of C₆F₁₂O (perfluoro(2-methyl-3-pentanone)) on the explosion of ethanol gasoline-air mixtures and intrinsic mechanism, the explosion overpressure and flame propagation behavior under different equivalence ratios (φ = 0.6–0.8) and C₆F₁₂O concentrations (χ_inh = 0–4.0%) were experimentally obtained. The detailed inhibitor reaction process was also obtained by CHEMKIN based on a new assembly kinetic mechanism. The results show that the effects of C₆F₁₂O on the explosion characteristics of ethanol gasoline varied with χ_inh and φ. For rich flames, C₆F₁₂O is more effective than and heptafluoropropane (C₃HF₇) and nitrogen (N₂) in suppressing explosions; for lean and equivalence ratio flames, the addition of C₆F₁₂O may result in more severe explosions. The decrease in chemical reactivity is mainly because the mole fractions of OH and H radicals and the proportion of paths H radicals involved decrease after adding C₆F₁₂O, and R1500: CF₃COF + H = CF₃CO + HF, R965: CF₂:O + H = CF:O + HF, R863: CF₃ + H = CF₂ + HF are main suppressing reactions.     

基于BERT-BILSTM-CRF模型的电力行业事故文本智能分析*

为解决电力行业事故报告文本较长、语义复杂,难以进行有效文本识别问题,提出1种以BERT作为底层的预训练模型,并设计1种双重注意力机制编码器,结合BILSTM-CRF深度挖掘事故文本语义特征,从而实现文本智能分析。首先构建电力词典,通过对BERT预训练,进行BIO标注,然后引入BILSTM-CRF模型实现对文本标签智能分类,最后将该模型与现行其他4种深度学习模型进行对比。研究结果表明:该模型智能识别精确率、召回率及F1值(查准率)均达到约97%,较其他4种模型中效果最好的模型分别提高0.02,0.03,0.02。研究结果可为电力行业事故报告文本分析提供1种新思路。