Estimating non-native plant richness with a species-accumulation model along roads

Monitoring non-native plant richness is important for biodiversity conservation and scientific research. The species-area model (SA model) has been used frequently to estimate the total species richness within a region. However, the conventional SA model may not provide robust estimations of non-native plant richness because the ecological processes associated with the accumulation of exotic and native plants may differ. Because roads strongly dictate the distributions of exotic plants, we propose a species-accumulation model along roads (SR model), rather than an SA model, to estimate the non-native plant richness within a region. Using 270 simulated data sets, we compared the differences in performance between the SR and SA models. A decision tree based on prediction accuracy was created to guide model application, which was validated using field data from 3 national nature reserves in 3 different provinces in China. The SR model significantly outperformed the SA model when non-native species were restricted to the roadsides and the proportion of uncommon exotic species was small. More importantly, the SR model accurately estimated the non-native plant richness in all field sites with an error of <1 species per site. We believe our new model meets the practical need to efficiently and robustly estimate non-native plant richness, which may facilitate effective biodiversity conservations and promote research on non-native plant invasion and vegetation dynamics.     

Driving difficulties as reported by older drivers with mild cognitive impairment and without neurological impairment

Objective: Considerable evidence indicates that medical conditions prevalent among older individuals lead to impairments in visual, cognitive, or psychomotor functions needed to drive safely. The purpose of this study was to explore the factors determining driving difficulties as seen from the viewpoint of 30 older drivers with mild cognitive impairment (MCI) and 30 age-matched controls without cognitive impairment.

Methods: Perceptions of driving difficulties from both groups were examined using data from an extensive questionnaire. Samples of drivers diagnosed with MCI and age-matched controls were asked to report the frequency with which they experienced driving difficulties due to functional deficits and knowledge of new traffic rules and traffic signs.

Results: The analysis revealed that 2 factors underlie MCI perceptions of driving difficulties, representing (1) difficulties associated with late detection combined with slowed response to relevant targets in the peripheral field of view and (2) difficulties associated with divided attention between tasks requiring switching from automatic to conscious processing particularly of long duration. The analysis for healthy controls revealed 3 factors representing (1) difficulties in estimating speed and distance of approaching vehicles in complex (attention-dividing) high-information-load conditions; (2) difficulties in moving head, neck, and feet; and (3) difficulties in switching from automatic responses to needing to use cognitive processing in new or unexpected situations.

Conclusions: Though both group analyses show difficulties with switching from automatic to decision making, the difficulties are different. For the control group, the difficulty in switching involves switching in new or unexpected situations associated with high-information-load conditions, whereas this switching difficulty for the MCI group is associated with divided attention between easier tasks requiring switching. These findings underline the ability of older drivers (with MCI and without cognitive impairment) to indicate probable impairments in various driving skills. The patterns of difficulties perceived by the MCI group and the age-matched healthy control group are indicative of demanding driving situations that may merit special attention for road designers and road safety engineers. They may also be considered in the design of older drivers’ fitness to drive evaluations, training programs, and/or vehicle technologies that provide for older driver assistance.     

基于换乘人耐受限的对向公交换乘生存距离模型研究

为揭示对向公交换乘距离与换乘乘客横穿道路的相互关系,约请272名受试者,完成城市公交汽车换乘试验。基于换乘试验统计出横穿马路人数,采用非参数估计方法估计换乘乘客的最大忍耐换乘距离,利用SPSS软件,构建拟合程度最高的对向换乘生存距离二次项函数模型,并对模型的有效性进行验证。结果表明,违规过街行人数随公交换乘距离的增大而增多;生存率随换乘距离的增大呈现"缓慢减小-迅速减小-平缓减小"的变化趋势,换乘距离增加至126 m后,越来越多的乘客难以接受这样的距离;换乘距离相同时,男性相比女性更容易横穿马路;根据构建的对向公交换乘生存距离模型,85%的换乘乘客可接受的换乘距离为124 m,50%的换乘乘客可接受的换乘距离为174 m。     

PMF和PCA/MLR法解析上海市高架道路地表径流中多环芳烃的来源

以上海市内环高架道路径流中的多环芳烃(PAHs)为研究对象,于2012年7~9月,实测了8场降雨的道路径流中的PAHs,了解了城市交通干道径流中PAHs的污染状况,并采用正定矩阵因子分解(PMF)和主成分分析/多元线性回归(PCA/MLR)两种模型对径流中的PAHs进行源解析.因子分析表明,径流中Σ16 PAHs的浓度范围为1.585~7.523μg·L-1,两种模型对于PAHs的来源有较为一致的判定.交通源为高架道路地表径流中PAHs的主要来源,PMF和PCA/MLR得到的源贡献率分别为37.7%和44.3%,其余3种来源石油源、燃气源和其他源,PMF得到的源贡献率依次为21.9%、26.4%、14.0%;与之对应,PCA/MLR得到的源贡献率依次为28.9%、18.3%、8.5%.PMF和PCA/MLR模型的计算值与实测值拟合较好,相关系数分别为0.961和0.997.     

北京市典型道路扬尘化学组分特征及年际变化

选择北京市具有代表性道路,于2004年9月和2013年5月进行采样,利用再悬浮设备制备道路扬尘PM₁₀与PM_2.5样品,并进行化学组分分析,建立了2004年和2013年北京市道路扬尘PM₁₀与PM_2.5源成分谱,以分析和探讨北京市道路扬尘化学组分特征及其组分年际变化.结果表明,北京市道路扬尘PM₁₀与PM_2.5源成分谱中的化学组分特征均为Ca、Si、有机碳（organic carbon,OC）、Al、Fe、K、Mg、SO₄^2-和元素碳（element carbon,EC）,其在道路扬尘中的含量之和分别为：2004年PM₁₀为46.7303%、PM_2.5为56.9198%和2013年PM_2.5为38.7478%;占全部被测组分的比例分别为95.9%、94.3%和94.7%.2004年道路扬尘中,环路Si、Al的含量显著低于其他道路类型,受到的土壤风沙尘影响最小;建筑水泥尘特征元素Ca主干道含量最高,高速五环进京口含量最低;EC在高速五环进京口的含量显著高于其他道路类型.而2013年PM_2.5中被测组分总含量及Si、Al、Ca的含量次干道均显著低于其他道路类型.2013年与2004年相比,北京市道路扬尘PM_2.5中除SO₄^2-含量略上升了2.0%外,其余组分含量下降显著,Ca、Si、OC、Al、Fe、K、EC和NO₃^-下降幅度分别为45.1%、31.5%、17.5%、20.3%、55.6%、33.3%、30.0%和50.3%.结果表明,［NO₃^-］/［SO₄^2-］比值不能准确反映固定源和移动源相对贡献大小的变化.［OC］/［EC］比值,2004年PM₁₀为9.77±3.88,PM_2.5为9.36±3.25,2013年PM_2.5为14.41±10.41,北京市道路扬尘存在二次有机碳（secondary organic carbon,SOC）,且SOC是道路扬尘PM₁₀与PM_2.5的重要组成部分.不同城市道路扬尘及同一城市不同粒径的道路扬尘成分谱相似度不高,应建立相应的成分谱并适时更新.     

新疆天山天池景区道路土壤磁学特征及其环境意义

为验证利用环境磁学方法监测旅游景区道路土壤污染的可行性,以新疆天山天池景区为研究区,采集不同道路土壤样品72件,并对其进行系统的磁学特征分析.结果表明:景区道路土壤样品磁性矿物含量适中,以亚铁磁性矿物(磁铁矿)为主,同时伴有少量不完全反铁磁性矿物;土壤磁性颗粒以多畴(MD)和稳定单畴(SSD)粗颗粒为主,且含有少量超顺磁性细颗粒(SP);从双因素方差分析结果看,不同位置道路土壤样品的磁性参数(χ_(LF)、SIRM、SOFT、χ_(FD)、SIRM/χ_(LF))和距离道路不同距离土壤样品的磁性参数(χ_(LF)、SIRM、SOFT、S_(-ratio))之间均存在显著性差异;景区旅游交通流量和距离道路远近、自然成土过程等人为和自然因素是影响景区道路土壤磁性特征变化的关键因素.     

城市路面径流重金属排放规律及初期效应研究

在西安市城市主干道南二环太白立交高架段设置路面径流采样点,采用降雨-产流-产污同步观测的试验方法,对2014年7月—2015年8月的6场降雨径流事件进行采样,监测径流过程中Cu、Pb、Zn、Cr、Ni、Cd的浓度变化,并研究其污染排放规律及初期冲刷效应。结果表明:路面径流污染排放规律与降雨特征及污染物赋存状态密切相关,溶解态重金属浓度均在径流初期达到峰值;颗粒态重金属浓度峰值出现时间略滞后于雨强峰值;重金属总量初期冲刷程度的强弱和溶解态重金属的差异较大,重金属总量初期冲刷程度越强,溶解态重金属反而越弱。     

高原环境对军用越野汽车的影响及对策研究

目的研究高原环境对军用越野汽车性能的影响,提出提高军用越野汽车高原环境适应性的技术措施。方法简要介绍高原地区的气候和地理环境条件特点,通过高原实地试验分析高原环境条件对军用越野汽车动力性能、经济性能、起动性能、热平衡和制动等性能的影响规律和影响机理。结果针对军用越野汽车的动力系统、底盘系统和驾驶室人-机环境等,提出了采用高压共轨燃油喷射、可调高增压、低气压低温起动、热平衡控制、四轮转向、悬架增强、辅助制动、轮胎中央充放气以及驾驶室高原人-机工程等提高军用越野汽车高原环境适应性的技术对策和建议。结论为提高军用越野汽车高原环境适应性提供了指导。     

农村村落地表灰尘磁化率特征及环境意义——以商丘市毛堌堆镇为例

通过对商丘市毛堌堆镇若干村落地表灰尘磁化率进行测试,对比自然村落和集聚村落地表灰尘磁化率、集聚村落与城市地表灰尘磁化率,以及探究集聚村落内部地表灰尘磁化率差异,定量研究农村村落的地表灰尘磁化率特征。结果表明:灰尘磁化率(Xlf)变幅为50.12×10~(-8)~266.97×10~(-8) m~3/kg,平均值为115.51×10~(-8) m~3/kg;频率磁化率(Xfd%)变幅为0.93%~5.97%,平均值为2.73%;磁化率与频率磁化率呈负相关关系,表明地表灰尘磁化率升高主要受人为活动影响;集聚村落地表灰尘磁化率大于自然村落但小于城市;集聚村落中心地表灰尘磁化率大于外围;灰尘磁化率值与村落规模呈正相关。农村地表灰尘磁化率可以揭示各农村村落地表灰尘污染状况。     

地形数据对高架复合道路噪声预测结果的影响研究

在噪声预测中除了合理设置噪声源强等参数外,是否选取了合理的地形数据反映沿线地貌对声环境的影响,也会涉及到预测结果的可靠性和真实性.本次利用Noisesystem模型对某市拟建高架复合道路的声环境影响情况进行模拟,对比有无地形数据的垂向线接收点预测结果,其最大差值为5.98 dB.这表明有无地形数据对噪声预测结果影响很大,在实际高架复合道路项目中应充分考虑地形对声环境的影响.