Factors associated with driving under the influence of alcohol

Objective: This study examined the risk factors of driving under the influence of alcohol (DUI) among drivers of specific vehicle categories (DSC). On the basis of this research, the variables related to DUI and involvement in traffic crashes were defined. The analysis was conducted for car drivers, bicyclists, motorcyclists, bus drivers, and truck drivers.

Method: The research sample included drivers involved in traffic crashes on the territory of Serbia in 2016 (60,666). Two types of analyses were conducted in this study. Logistic regression established the correlation between DUI and DSC and the The Technique for Order of Preference by Similarity to Ideal Solution (Multi-criteria decision making) method was applied to consider the scoring and explore the potential for the prevalence of DUI on the basis of 2 data sets (DUI and non DUI).

Results: The study results showed that driver error and male drivers were the 2 most significant risk factors for DUI, with the highest scores and potential for prevalence. The nonuse of restraint systems, driver experience, and driver age are the factors with a significant prediction of involvement in an accident and an insignificant prediction of DUI.

Conclusions: Following the development of the logistic prediction models for DUI drivers, testing of the model was conducted for 3 control driver groups: Car, motorcycle, and bicycle. The prediction model with a probability greater than 50% showed that 77% of car drivers were under the influence of alcohol. Similarly, the prediction percentage for motorcyclists and bicyclists amounted to 71 and 67%, respectively. The recommendation of the study is that drivers whose DUI probability is above 50% should be potentially suspected of DUI. The results of this study can help to understand the problem of DUI among specific driver categories and detect DUI drivers, with the aim of creating successful traffic safety policy.     

建筑安全风险因素分级排序的风险矩阵法

为减少风险分级排序时产生的风险结,在引入施工安全事故频率的基础上,采用单元格细化和Borda序值法改进原有的风险矩阵法。改进后的方法使得风险等级数量增加,风险结数量减少。将该方法应用于脚手架工程的风险因素的分级与排序,风险等级分为6级,且实现了12个因素的明确排序。     

Characterization and control of odorous gases at a landfill site: a case study in Hangzhou, China

Municipal solid waste (MSW) landfills are one of the major sources of offensive odors potentially creating annoyance in adjacent communities. At the end of May 2007, an odor pollution incident occurred at the Tianziling landfill site, Hangzhou, China, where the residents lodged complaints about the intense odor from the landfill, which drew a significant attention from the government. In this study, ambient air monitoring was conducted at the Tianziling landfill site. The main odor composition of the gas samples collected on June 1st 2007 and the reduction of various odorous gases from the samples collected on June 1st 2009 due to the applied odor control techniques were determined using gas chromatography-mass spectrometry (GC-MS). In addition, variations of primary odorous gaseous (NH₃ and H₂S) concentrations at different locations in the landfill site from July 2007 to June 2009 were also investigated by using classical spectrophotometric methods. Results showed that a total of 68 volatile compounds were identified among which H₂S (56.58-579.84 μg/m³) and NH₃ (520-4460 μg/m³) were the notable odor components contributing to 4.47-10.92% and 83.91-93.94% of total concentrations, respectively. Similar spatial and temporal shifts of H₂S and NH₃ concentrations were observed and were significantly affected by environmental factors including temperature, air pressure and wind direction. Odor pollution was worse when high temperature, high humidity, low air pressure, and southeast, northeast or east wind appeared. Moreover, the environmental sampling points of the dumping area and the leachate treatment plant were found to be the main odor sources at the Tianziling landfill site. The odor control technologies used in this project had a good mitigating effect on the primary odorous compounds. This study provides long-term valuable information concerning the characteristics and control of odors at landfill sites in a long run.     

湖北省棉花生产变化影响因子研究

利用灰色关联分析方法,探讨了湖北省近50多年来棉花生产的总体变化趋势及影响湖北省棉花总产量的各项因子。结果表明,棉花单产是影响湖北省棉花总产量的首要因子,播种面积对棉花总产的影响仅次于单产,其制约作用呈上升趋势;自然因素对棉花总产量的影响不断下降;有效灌溉面积对湖北省棉花总产量有逐步增强的制约趋势;农业机械总动力、农业用电量以及化肥施用量对湖北省棉花总产也有着重要的影响。     

我国水污染治理行业2012年发展综述

综述了2012年我国水污染治理行业发展状况及发展环境;阐述并评价了行业市场运营、行业骨干企业经营、行业技术创新发展的状况;分析了行业目前的市场热点及发展趋势。     

影响富营养化水体沉水植物修复的生态因子探讨

日益严重的水体富营养化现象,不仅降低了它的使用功能,也使水生态系统日趋退化,从而制约了当地社会经济的可持续发展。利用组建或重建沉水植物技术净化水质或进行水体生态修复是一种有效的生态工程措施。本文综述了光照、pH、营养盐、重金属、悬浮颗粒物及着生藻类等生态因子对沉水植物修复的影响和修复时应注意的问题。     

非点源污染模型中土壤侵蚀因子研究进展

非点源污染模型是进行非点源污染模拟研究的重要手段,而土壤侵蚀模型是非点源污染模型的基础,土壤侵蚀因子的研究是土壤侵蚀模型的重要基础。本文对国内外主要土壤侵蚀因子研究的成果进行了概述,并指出在今后相当一段时期内,土壤侵蚀因子的研究仍是土壤侵蚀模型研究的重要工作。     

南海水域不同深度非光合微生物的固碳潜能及其对不同电子供体的响应

通过对南海水域多个区域不同深度的海水分别以H2、Na2S2O3、Na NO2为电子供体经过一定时间的驯化培养后,测定其中非光合微生物的固碳潜力,并统计南海水域不同深度非光合微生物在不同电子供体条件下固碳潜力的差异性,最后结合不同深度海水的主要固碳基因丰度差异,分析南海水域不同深度海洋非光合微生物在不同电子供体条件下固碳潜能差异的原因.结果发现以Na NO2为电子供体时,海洋非光合微生物固碳能力普遍较低,各深度之间没有显著差异;以H2为电子供体时,表层海水中的非光合微生物的固碳潜力显著高于深层海水中的;而以Na2S2O3为电子供体时,深层海水中的非光合微生物的固碳潜力显著高于表层海水中的.基因分析结果表明,固碳基因cbb L在表层海水中的丰度高于深层海水,而cbb M基因在深层海水中的丰度高于表层海水.硫细菌大多以拥有cbb M基因为主,而氢细菌大多以拥有cbb L基因为主.因此不同海洋深度非光合微生物对不同电子供体响应的差异性可能和优势菌群结构的差异有关.海洋表层和深层溶解氧、无机碳含量的差异是导致菌群结构差异,乃至固碳潜力差异的重要原因.     

氢燃料电池汽车动力系统生命周期评价及关键参数对比

发展氢燃料电池汽车被认为是解决能源安全和环境污染问题的理想解决方案之一,为量化探究氢燃料电池汽车动力系统的化石能源消耗和排放情况,运用GaBi软件建模,以新能源汽车相关技术路线为参考,构建我国氢燃料电池汽车动力系统的数据清单并对其全生命周期化石能源消耗和全球变暖潜值情况进行定量评价计算和预测分析,对不同类型的双极板、不同能量控制策略和不同制氢方式对环境的影响分别进行了对比研究,并对关键数据进行了不确定分析.结果表明,预计到2030年我国每台氢燃料电池汽车动力系统生命周期的化石能源消耗量（ADP_f）、全球变暖潜值（GWP,以CO₂ eq计）和酸化潜值（AP,以SO₂ eq计）分别为1.35×10⁵ MJ、9108 kg和15.79 kg.动力系统生产制造阶段的化石能源消耗和全球变暖潜值均高于使用阶段,主要原因是燃料电池堆栈和储氢罐的制造过程.金属双极板、石墨复合双极板和石墨双极板的制造工艺中石墨复合双极板的综合环境效益最好.能量控制策略的优化会使得氢能消耗降低,当氢能消耗降低22.8%时,动力系统的生命周期化石能源消耗和全球变暖潜值分别降低10.4%和8.3%.相比于甲烷蒸气重整制氢,基于混合电网电解水制氢的动力系统生命周期全球变暖潜值高出53.7%[KG-*6],而基于水电电解水制氢降低39.6%.降低动力系统生命周期化石能源消耗和全球变暖潜值的措施包括优化能量控制策略降低氢能消耗、规模化发展可再生能源发电电解水制氢产业和聚焦突破燃料电池堆栈关键技术实现性能提升.     

太子河河岸带土地利用类型与硅藻群落结构的关系

为了评价河岸带土地利用对河流硅藻群落的影响,于2012年5月对太子河河岸带4种主要土地利用类型(森林用地、森林耕作用地、耕地、城镇建设用地)下38个采样点的硅藻群落和水环境特征进行采样分析. 结果表明:森林用地的指示种为膨大桥弯藻(Cymbella turgida)、优美桥弯藻(C. delicatula)、弧形峨眉藻(Ceratoneis arcus)、Gomphonema trancatum等寡污指示种;耕地的指示种为颗粒直链藻(M. granulate)、库津小环藻(Cyclotella kuetzingiana)、线形菱形藻(N. linearis)、尖布纹藻(Gyrosigma acuminatum)等污染指示种. 聚类分析结果显示,相同土地利用类型区域内,硅藻群落结构特征较为相似. 典范对应分析显示,ρ(COD_Mn)、ρ(SS)(SS为悬浮物)和ρ(TDS)(TDS为总溶解固体)是影响硅藻群落结构特征的主要水环境因子. 不同土地利用类型区域内硅藻群落结构特征差异显著,其中,森林用地内硅藻生物指数(17.98)和硅藻属数量(17.33个)最高,Shannon-Wiener多样性指数(2.22)和Pielou均匀度指数(0.54)最低;耕地内Shannon-Wiener多样性指数和Pielou均匀度指数平均值最高,分别为3.37和0.82;城镇建设用地内物种丰富度(11.00)、硅藻生物指数(9.20)和硅藻平均密度(0.71×104 L-1)最低. 研究显示,不同土地利用类型通过对水环境因子的影响进而影响硅藻群落的变化,其中城镇建设用地面积所占比例较高的河流水环境质量和硅藻群落状况最差;太子河河岸带土地利用类型对河流硅藻群落结构影响显著,并表现出明显的空间异质性.