浅谈人的不安全行为与安全生产

从行为学、安全系统工程学、心理学的观点,阐述了事故的致因。其中,人的不安全行为是事故发生的主要原因。因此,只有控制人的不安全行为,才能有效地避免人身事故的发生。     

Influence of metal oxides on PCDD/Fs formation from pentachlorophenol

Chlorophenols (ClPhs) are considered as important precursors for PCDD/Fs formation. The influences of series of metal oxides including MgO, Al2O3, CaO, BaO, TiO2, V2O5, MnO2, Fe2O3, Co3O4, CuO, Ag2O, ZnO, HgO, SnO, PbO, La2O3, CeO2, and Eu2O3 on PCDD/Fs formation from pentachlorophenol (PCP) were investigated in a laboratory-scale reactor. The results indicated that most of the above metal oxides have obvious suppressing effects on the total amount of PCDD/Fs formation from precursor PCP except for CuO, ZnO, MnO2, TiO2 and Co3O4 with promotion effects at 280 degrees C for 2 h. Although MgO, Al2O3, Fe2O3, PbO, La2O3 and Eu2O3 could reduce the amount of octachlorinated dibenzo-p-dioxin (OCDD), they promote the formation of more toxic 1,2,3,4,6,7,8-HpCDD at the same time. The total suppressing efficiencies of several metal oxides including CaO, BaO, PbO, Ag2O, HgO and SnO which have lower Z/r (charge to radius ratio) <2 are all over 90%. The theories of generalized acid-base and atomic parameter (Z/r) were used to speculate the effecting mechanisms. The factors including time and temperature on suppressing efficiencies of CaO, BaO and PbO have also been studied in the present paper. The results showed that the total suppressing efficiencies of CaO, BaO and PbO increase with the increase of heated time and temperature.     

Quantitative structure-activity relationships for the inhibition toxicity to root elongation of Cucumis sativus of selected phenols and interspecies correlation with Tetrahymena pyriformis

The comparative toxicities of selected phenols to higher plants Cucumis sativus were measured and the negative logarithm molar concentration of the root elongation median inhibition (IRC50) were derived. Quantitative structure-activity relationships (QSARs) were developed to explore the toxicity influencing factors and for predictive purpose. The toxicity data, fell into two classes: polar narcosis and bio-reactive. For polar narcotic phenols, a highly significant two-parameter QSAR based on 1-octanol/water partition coefficient (logKow) and energy of the lowest unoccupied orbital (E(lumo)) was derived (IRC50 = 0.77 log Kow - 0.39E(lumo) + 2.36 n = 22 r2 = 0.89). The five bio-reactive chemicals proved to show elevated toxicity due to their typical substructure involved diverse reactive mechanisms. In an effort to model all chemicals, a robust multiple-variable QSAR combining logKow, E(lumo) and Qmax, the most negative net atomic charge, was developed (IRC50 = 0.65 logKow - 0.72E(lumo) + 0.23Qmax + 2.81 n = 27 r2 = 0.94), indicating that hydrophobicity, electrophilicity and hydrogen bond interaction contribute mainly to the phytotoxicity. The toxicological data was compared with Tetrahymena pyriformis 2-d population growth inhibition toxicity (IGC50) and excellent interspecies correlations were observed both for the polar narcotics and for five reactive chemicals (for polar narcotics: IRC50 = 0.95IGC50 + 1.07 n = 16 r2 = 0.89; for bio-reactive chemicals: IRC50 = 0.98IGC50 + 2.19 n = 5 r2 = 0.97; and for all: IRC50 = 0.93IGC50 + 1.63 n = 21 r2 = 0.87). This suggested that T pyriformis toxicity could serve as a surrogate of C. sativus toxicity for phenols and interspecies correlation also could be established for reactive chemicals.     

Structure-activity relationships and response-surface analysis of nitroaromatics toxicity to the yeast (Saccharomyces cerevisiae)

Inhibition of growth of the yeast Saccharomyces cerevisiae (Cmiz, the minimum concentration that produced a clear inhibition zone within 12 h) for 24 nitroaromatic compounds was investigated and a quantitative structure-activity relationship (QSAR) developed based on hydrophobicity expressed as the l-octanol/water partition coefficient in logarithm form, log K(ow), electrophilicity based on the energy of the lowest unoccupied orbital (E(lumo)). All nitrobenzene derivatives exhibited enhanced reactive toxicity than baseline. The toxicities of mono-nitrobenzenes and di-nitrobenzenes were elicited by different mechanisms of toxic action. For mono-nitro-derivatives, both significant log K(ow) based and strong E(lumo)-dependent relationships were observed indicating that their toxicities were affected both by the penetration process and the interaction with target sites of interaction. The toxicities of di-nitrobenzenes were greater than mono-nitrobenzenes and no log K(ow)-dependent but highly significant E(lumo)-based relationship was obtained. This suggests that toxicity of di-nitrobenzenes was highly electrophilic and involved mainly their in vivo electrophilic interaction with biomacromolecules. In an effort to model the elevated toxicity of all nitrobenzenes, a response-surface analysis was performed and this resulted in a highly predictive two-variable QSAR without reference to their exact mechanisms (Cmiz = 0.41 log K(ow) - 0.89 E(lumo) - 0.46, r2 = 0.87, Q2 = 0.86, n = 24).     

基于CMIP5多模式集合预估东海和南海21世纪海平面高度变化

人类活动引起的当代气候变暖已导致全球海平面显著上升,在21世纪全球气候继续变暖的背景下,东南沿海海平面的升高将对区域环境及社会可持续发展带来巨大挑战,但目前对未来区域海平面变化的预估尚存在较大的不确定性。本文基于筛选的国际耦合模式比较计划第5阶段（CMIP5）的10个模拟性能较好的气候模式输出结果,通过多模式集合预估了未来温室气体三种排放情景下21世纪东海和南海区域海平面高度的趋势变化,并分析了不同影响因子的贡献。通过计算海水热比容、盐比容和动力因子对海平面高度的影响,并在考虑冰川冰盖消融等因子的订正后,发现：21世纪东海和南海海平面高度都呈现连续上升趋势,东海和南海地区上升幅度略小于全球平均,南海上升幅度略大于东海。在温室气体低（RCP2.6）、中（RCP4.5）和高（RCP8.5）排放情景下,21世纪后期（2081—2100年）较前期（2006—2025年）东海/南海平均海平面分别上升0.26 [0.01—0.55] m/0.29 [0.05—0.55] m、0.38 [0.10—0.66] m/0.40 [0.14—0.67] m和0.52[0.15—0.89] m/0.52[0.23—0.83] m（方括号内为相应的不确定性范围）。随着温室气体排放的升高,海平面上升幅度也增大,东海海平面上升区由东南向西北扩展,南海海平面上升区由东北向西南扩展。统计分析还表明：在不同排放情景下,不同影响因子对海平面变化的贡献也不一样,随着排放强度从低到高变化,海洋比容加动力因子的相对贡献从28%—34%升高至46%—47%,而冰川冰盖消融等其他因子的相对贡献从 66%—72%降低至53%—54%。     

成都市PM2.5中无机组分与硝酸盐氮氧同位素变化特征

2013年1月12日～2013年1月23日和2014年8月10日～2014年8月21日在成都市城东成都理工大学校园内按昼夜采集PM_(2.5)样品,分析了PM_(2.5)样品的质量浓度、9种水溶性无机离子含量和硝酸盐的δ~(15)N和δ~(18)O。结果表明,采样期间成都市PM_(2.5)冬、夏季的质量浓度分别为161～677μg/m~3(360±118μg/m~3)和87～137μg/m~3(92±18μg/m~3),冬季超标2～9倍,属于重度污染,夏季超标1～2倍,属于轻度污染; SO_4~(2-)、NO_3~-和NH_4~+(SNA)的质量浓度占总水溶性无机离子和PM_(2.5)质量浓度的比值冬夏季分别为72%±14. 3%和65%±9. 2%,21. 1%±2. 5%和30. 3%±6. 9%,是主要的无机离子组分。结合离子相关性分析,SNA的存在形式在白天以(NH_4)_2SO_4或NH_4HSO_4为主,部分以NH_4NO_3的形式存在,而在夜间则以NH_4NO_3为主,部分以(NH_4)_2SO_4或NH_4HSO_4形式存在。成都市PM_(2.5)中硝酸盐的δ~(15)N和δ~(18)O呈冬季高、夏季低的特征。冬季,硝酸盐来源于燃煤和机动车尾气;夏季,硝酸盐来源于机动车尾气、燃煤和农业土壤释放,根据其[NO_3~-]/[SO_4~(2-)]值说明成都市冬夏季均以固定污染源(燃煤)为主,移动污染源(机动车尾气)为辅。成都市冬季大气颗粒物中硝酸盐主要由NO_x经O_3氧化形成,夏季主要经·OH氧化形成硝酸盐或N_2O_5水解生成硝酸盐。     

物元可拓法用于南京城市绿地土壤重金属污染评价

为合理评价土壤中重金属的污染程度,采用方格网法采集南京城市绿地表层土壤（深度为0~15 cm）样品共计180个,对Cu、Pb、Zn、Cd、Cr等5种重金属和类金属As的质量分数进行测定,引入Hakanson毒性响应系数,用于体现重金属毒理性质;对传统的超标赋权法进行修正,体现重金属潜在危害程度;采用物元可拓模型对其综合污染水平进行评价,并与传统的內梅罗综合污染指数法进行比较.结果表明:通过Hakanson毒性响应系数修正后的重金属权重发生了不同程度的调整,其中Zn、Cr、Cu、Pb和As的权重分别下降了92.9%、85.1%、68.9%、61.5%和23.2%,而毒性高的Cd的权重则上升130.0%,充分体现了重金属毒理性质;物元可拓方法模型评价结果显示,南京城市绿地土壤重金属污染等级值为2.481,处于Ⅲ级（轻度污染）水平,但部分采样点污染值高,处于Ⅳ级（中度污染）水平,通过对研究区的污染值进行空间插值发现,中度污染集中在研究区域的北部交通密集区和西部工业密集区,人为污染严重.研究显示,物元可拓模型的评价结果与内梅罗综合污染指数法的评价结果基本一致,且更为精确,适用于土壤重金属污染的评价.      

Triton X-100对土壤中柴油的解吸特征及影响因素

为考察非离子表面活性剂Triton X-100对土壤中柴油解吸特性及土壤理化性质对其解吸的影响,通过振荡平衡法研究Triton X-100对浙江水稻土、重庆紫壤、江西红壤、海南沙土、青海灰漠土和黑龙江黑土中柴油解吸行为及其影响因素.结果表明,Triton X-100对浙江水稻土、重庆紫壤、江西红壤、海南沙土、青海灰漠土和黑龙江黑土中柴油的解吸均符合先快后慢、最后达到解吸平衡的规律,平衡时解吸量分别1.61、1.85、1.80、2.29、2.01和1.13 mg/g.其解吸动力学过程均符合准二级动力学模型（R2>0.99）;6种典型土壤中柴油的等温解吸特征可较好地用修正的米氏方程模型进行描述（R2>0.92）.Q_max（柴油最大解吸量）介于1.81~2.23 mg/g之间,浙江水稻土、重庆紫壤、江西红壤、海南沙土、青海灰漠土和黑龙江黑土中ρ_max（柴油最大解吸率）分别为73.20%、78.06%、75.63%、90.36%、79.89%和62.92%;土壤各理化性质对Triton X-100解吸土壤中柴油的影响起综合作用,其中土壤w（砂粒）与ρ_max呈显著正相关（R2=0.993 6,P < 0.01）,对Triton X-100解吸柴油的影响最大;而CEC（阳离子交换量）、w（OM）、w（黏粒）均与ρ_max呈显著负相关（P < 0.05）.研究显示,修正的米氏方程可用于描述柴油在土壤-水-表面活性剂Triton X-100系统中的解吸行为,w（砂粒）是影响不同土壤中柴油解吸的关键因子,可为应用Triton X-100修复柴油污染土壤提供理论基础.      

包装废弃物添加脱氯半焦制备SRF的热解及动力学特性

利用热重红外分析仪(TG-FTIR)对包装废弃物添加了4种不同比例脱氯半焦制备而成的固体衍生燃料(SRF)的热解特性及热反应动力学进行了研究分析.研究发现,4种燃料热解过程主要包括4个阶段,其中300~400℃和400~500℃为两个主要失重阶段.前一阶段,SRF-1失重显著高于SRF-2、SRF-3和SRF-4,而后一阶段失重分别呈2、3、4倍增加.4种燃料热解残余量的顺序为SRF-4SRF-3SRF-2SRF-1,即添加了脱氯半焦的燃料热解程度越高.FTIR分析表明,添加了脱氯半焦的SRF燃料第三失重峰处不产生氯代烃.随脱氯半焦添加量的增加,第二失重峰CO2产生的浓度减少;第三失重峰CH4析出浓度增加;第四失重峰CO2析出的浓度增加.采用DEAM分布活化能法得到,转化率α0.3时,SRF-2和SRF-3的活化能均高于SRF-1的活化能,0.3α0.9时(α为0.6时除外),SRF-2、SRF-3和SRF-4 3种燃料的活化能低于SRF-1,且SRF-1的活化能呈升高的趋势,而其他3种燃料呈相反趋势.脱氯半焦的添加有利于SRF燃料的热解.