顺序暴露场景下四环素和砷对斑马鱼的联合毒性效应

在一些不连续生产的工业活动、畜禽养殖等间歇性排放废水的场景中,水环境中的盐酸四环素（Tetracycline,TET）和砷（Arsenic,As）可能会产生区别于单一或复合暴露的顺序暴露场景,从而导致复杂的生物毒性.本研究通过分析模式生物斑马鱼的表型数据（肥满度）、病理损伤（H&E染色实验）及氧化损伤（丙二醛和还原型谷胱甘肽含量）,探究顺序暴露方式下TET和As（Ⅲ）的联合毒性效应.结果表明：50 μg·L^-1 TET可造成肝脏和肠道的病理学损伤,并进一步诱导氧化损伤.100 μg·L^-1 As（Ⅲ）可造成肝脏炎性细胞浸润及肝脏和肠道的氧化损伤.连续暴露TET和As（Ⅲ）导致斑马鱼肥满度降低,且氧化损伤明显加剧,这可能与TET损伤了抗氧化防御系统有关.值得注意的是,TET暴露后设置2周的恢复期,可减轻As（Ⅲ）对斑马鱼肝脏和肠道的损伤,其机理可能与生物对污染物的适应及交叉抗性相关.本研究的实验结果可为评估TET和As（Ⅲ）的联合毒性效应提供新的视角.     

基于TRACEr的管制员差错风险量化分析

为准确辨识管制员(ATCO)的人为差错风险,量化预测不同认知领域的差错发生概率,根据认知差错回溯与预测分析(TRACEr)中的认知功能框架定义管制差错类型,分析心理差错机制的致因因素,将其作为根节点建立空中交通管理(ATM)不安全事件的贝叶斯网络;引入加权距离计算网络节点的条件概率,分析我国近10年的空管人误数据,以挖掘差错风险因素。研究结果表明:管制员的人为差错产生于各个认知领域,由此导致的不安全事件发生概率为0.040 7;警觉性失效、未充分学习、忽略危险、沟通误解和信息传输不清晰是主要风险因素,产生判断差错和信息传输差错的概率较大。     

基于CREAM和贝叶斯网络的空管人误概率预测方法

针对研究管制人因可靠性时存在的模糊性和片面性问题,采用认知可靠性与失误分析方法（CREAM）中的扩展预测法,计算10项管制通用任务的人误概率;在此基础上,以管制行为形成因子作为根节点构建贝叶斯网络,建立其与情景控制模式的不确定关系模型,对管制员在多任务中的人误概率进行预测。研究结果表明:在由相同评判者给出行为形成因子影响效应的前提下,由CREAM扩展预测法和构建贝叶斯网络的方法预测得到的多数任务的人误概率差异较大,从方法的客观性、合理性和适用性角度分析,贝叶斯网络在研究该问题时更具优势。     

基于人工神经网络的气体泄爆最大超压预测研究

为解决传统经验公式在预测气体泄爆中最大超压出现时的较大偏差或过于保守的问题,提出使用人工神经网络预测气体泄爆最大超压。基于124组实验数据,采用BP与RBF神经网络,通过优化算法计算与迭代循环对泄爆样本中的影响因素进行降维与选择,并确定2类神经网络本身在学习与计算气体泄爆样本时的相关参数。结果表明:PCA（主成分分析法）在当前样本条件下的降维效果较差,而通过迭代对比确认气体泄爆样本中的5类特征全部保留时神经网络的训练模拟效果最好;通过对124组实验数据进行随机挑选训练集与测试集的训练模拟结果发现,神经网络对气体泄爆中最大超压的预测效果较好;通过对比Molkov提出的和经Fakandu等改进的NFPA 68经验公式以及2类神经网络的预测结果表明,神经网络相比于传统气体泄爆经验公式具有明显优势。     

Bioaccumulation and elimination of avermectin B1a in the earthworms (Eisenia fetida)

The acute toxicity, bioaccumulation, and elimination of avermectin B1a (AVM B1a) in earthworm (Eisenia fetida) were investigated in different exposure systems. The LC50 of AVM B1a on earthworms were 24.1 mg/kg and 17.1 mg/kg, respectively, for 7 and 14 days in artificial soil. The LC50 tested by the filter paper for 2 days was 4.63 microg/cm2. The earthworms were cultivated in artificial soil containing 0.6 mg/kg and 3.0 mg/kg AVM B1a, respectively for bioaccumulation experiments. The AVM B1a residues in earthworms were determined with HPLC-fluorescence method. The results showed that AVM B1a was taken up from the concentrated artificial soil by the earthworms and the steady-state levels were reached after 9-18 days of exposure. On the 18th day, the final concentrations of AVM B1a in the earthworms treated with two different dosages were 107 ng/g and 165 ng/g, respectively; there were not significantly accumulation. About 80.0% and 94.8% of the accumulated AVM B1a were eliminated respectively in two groups within 1 day after they were exposed to AVM B1a-free soil, but a trace amount of AVM B1a was found for a relative long time in earthworms.     

Influence of methanol on retention of hydrophobic organic chemicals in soil leaching column chromatography

The influence of methanol in methanol-water mixed eluents on the capacity factor (k'), an important parameter which could depict leaching potential of hydrophobic organic chemicals (HOCs) in soil leaching column chromatography (SLCC), was investigated. Two reference soils, GSE 17201 obtained from Bayer Landwirtschaftszentrum, Monheim, Germany and SP 14696 from LUFA, Spencer, Germany, were used as packing materials in soil columns, and isocratic elution with methanol-water mixtures at different volume fractions of methanol (phi) were tested. Short-term exposure of the column (packed with the GSE 17201 soil) to the eluents increased solute retention by a certain (23% log-unit) degree evaluated through a correlation with the retention on the same soil column but unpreconditioned by methanol-containing eluents. Long-term exposure of soil columns to the eluents did not influence the solute retention. A log-linear equation, log k' = log k'(w) - S(phi), could well and generally describe the retention of HOCs in SLCC. For the compounds of homologous series, logk'(w) had good linear relationship with S, indicating the hydrophobic partition mechanism existing in the retention process.     

Air quality and health benefits from potential coal power plant closures in Texas

As power production from renewable energy and natural gas grows, closures of some coal-fired power plants in Texas become increasingly likely. In this study, the potential effects of such closures on air quality and human health were analyzed by linking a regional photochemical model with a health impacts assessment tool. The impacts varied significantly across 13 of the state’s largest coal-fired power plants, sometimes by more than an order of magnitude, even after normalizing by generation. While some power plants had negligible impacts on concentrations at important monitors, average impacts up to 0.5 parts per billion (ppb) and 0.2 µg/m³ and maximum impacts up to 3.3 ppb and 0.9 µg/m³ were seen for ozone and fine particulate matter (PM_2.5), respectively. Individual power plants impacted average visibility by up to 0.25 deciviews in Class I Areas. Health impacts arose mostly from PM_2.5 and were an order of magnitude higher for plants that lack scrubbers for SO₂. Rankings of health impacts were largely consistent across the base model results and two reduced form models. Carbon dioxide emissions were relatively uniform, ranging from 1.00 to 1.26 short tons/MWh, and can be monetized based on a social cost of carbon. Despite all of these unpaid externalities, estimated direct costs of each power plant exceeded wholesale power prices in 2016.

Implications: While their CO₂ emission rates are fairly similar, sharply different NO_x and SO₂ emission rates and spatial factors cause coal-fired power plants to vary by an order of magnitude in their impacts on ozone, particulate matter, and associated health and visibility outcomes. On a monetized basis, the air pollution health impacts often exceed the value of the electricity generated and are of similar magnitude to climate impacts. This suggests that both air pollution and climate should be considered if externalities are used to inform decision making about power-plant dispatch and retirement.     

医疗废物中有机质的热解动力学研究

在空气气氛下，对医疗废物中几种有代表性的有机质进行非等温热解实验。分析实验结果发现，热解失重曲线与N2气氛下不同，出现多个DTG峰。利用Freeman—CarroⅡ法求出了各有机质的表观动力学参数，并建立了能较好反映各物料失重过程的表观多步反应动力学模型。针对混合物料无法直接求出表观动力学参数，建立了多组分反应动力学模型。