Predictive Model of Avian Electrocution Risk on Overhead Power Lines

Electrocution on overhead power structures negatively affects avian populations in diverse ecosystems worldwide, contributes to the endangerment of raptor populations in Europe and Africa, and is a major driver of legal action against electric utilities in North America. We investigated factors associated with avian electrocutions so poles that are likely to electrocute a bird can be identified and retrofitted prior to causing avian mortality. We used historical data from southern California to identify patterns of avian electrocution by voltage, month, and year to identify species most often killed by electrocution in our study area and to develop a predictive model that compared poles where an avian electrocution was known to have occurred (electrocution poles) with poles where no known electrocution occurred (comparison poles). We chose variables that could be quantified by personnel with little training in ornithology or electric systems. Electrocutions were more common at distribution voltages (≤33 kV) and during breeding seasons and were more commonly reported after a retrofitting program began. Red‐tailed Hawks (Buteo jamaicensis) (n = 265) and American Crows (Corvus brachyrhynchos) (n = 258) were the most commonly electrocuted species. In the predictive model, 4 of 14 candidate variables were required to distinguish electrocution poles from comparison poles: number of jumpers (short wires connecting energized equipment), number of primary conductors, presence of grounding, and presence of unforested unpaved areas as the dominant nearby land cover. When tested against a sample of poles not used to build the model, our model distributed poles relatively normally across electrocution‐risk values and identified the average risk as higher for electrocution poles relative to comparison poles. Our model can be used to reduce avian electrocutions through proactive identification and targeting of high‐risk poles for retrofitting. Modelo Predictivo del Riesgo de Electrocución de Aves en Líneas Eléctricas Elevadas     

基于GM-SVR的小样本条件下化工设备可靠性预测

为了准确预测化工设备可靠性趋势，针对化工设备失效寿命数据为小样本的情形，基于灰色估计法与支持向量回归机在小样本数据处理中的优势，建立了失效寿命时间服从三参数威布尔分布的化工设备可靠性模型；结合GM（1，1）和SVR对模型进行参数估计，在压缩机可靠性分析中进行了实例应用，对比分析了最小二乘法、灰色估计法和GM-SVR的估计效果。研究结果表明:GM-SVR对威布尔分布参数的估计精度明显优于最小二乘法和灰色估计法，可以有效地应用于化工设备失效数据为小样本时的可靠性预测。     

Credibility and advocacy in conservation science

Conservation policy sits at the nexus of natural science and politics. On the one hand, conservation scientists strive to maintain scientific credibility by emphasizing that their research findings are the result of disinterested observations of reality. On the other hand, conservation scientists are committed to conservation even if they do not advocate a particular policy. The professional conservation literature offers guidance on negotiating the relationship between scientific objectivity and political advocacy without damaging conservation science's credibility. The value of this guidance, however, may be restricted by limited recognition of credibility's multidimensionality and emergent nature: it emerges through perceptions of expertise, goodwill, and trustworthiness. We used content analysis of the literature to determine how credibility is framed in conservation science as it relates to apparent contradictions between science and advocacy. Credibility typically was framed as a static entity lacking dimensionality. Authors identified expertise or trustworthiness as important, but rarely mentioned goodwill. They usually did not identify expertise, goodwill, or trustworthiness as dimensions of credibility or recognize interactions among these 3 dimensions of credibility. This oversimplification may limit the ability of conservation scientists to contribute to biodiversity conservation. Accounting for the emergent quality and multidimensionality of credibility should enable conservation scientists to advance biodiversity conservation more effectively.     

基于移动监测和土地利用回归模型的上海市近地面黑碳浓度空间模拟

黑碳(BC)是大气污染物的重要组成部分,对空气质量与人类生活健康产生重要的影响.本研究采用移动样带手段开展上海市近地面BC浓度监测,分析其基本统计特征和空间分异性.在此基础上,利用土地利用回归模型(LUR),探讨人口密度、经济产值和交通道路网密度等因素对上海市近地面BC浓度空间分异的影响.结果表明上海市近地面BC平均浓度为(9.86±8.68)μg·m~(-3),空间差异明显,郊区[(10.47±2.04)μg·m~(-3)]比市中心地区[(7.93±2.79)μg·m~(-3)]高32.03%(2.54μg·m~(-3)).气象要素(风速和相对湿度)和交通道路变量(路网长度、省道距离、高速距离等)显著影响上海市近地面BC浓度(r为0.5~0.7,P0.01).基于气象和交通道路变量的LUR模型能较好模拟上海近地面BC浓度(调整后R2为0.62~0.75,交叉验证R2为0.54~0.69,RMSE为0.15~0.20μg·m~(-3)),其中100 m和5 km缓冲距离的LUR模型相对较优,在一定程度上表明上海市近地面BC浓度主要受气象要素和交通源的影响.本研究有利于加深对上海市BC浓度空间分布格局及其影响因素的客观认识,可为模拟和预测BC对人类活动和自然环境的响应机制提供科学依据和理论支撑.     

供水管网铁释放的影响因素相对重要性分析

供水管网的铁释放问题近年来日益受到关注.影响供水管网铁释放的因素众多,本研究选取了pH、溶解氧(DO)、碱度(Alk)、硬度、氯离子(Cl~-)、硫酸根(SO_4~(2-))、温度(T)和水力停留时间(HRT)这8个影响因素,利用逐步回归和偏相关分析,建立了铁释放的非线性幂指数模型,并用标准化回归系数和偏相关系数比较了这些因素的相对重要性.结果表明,铁释放模型拟合效果良好;用标准化回归系数衡量影响因素相对重要性时,SO_4~(2-)、HRT、Cl~-和T是相对重要的因素,相对重要性排序为SO_4~(2-)≈HRTCl~-T;用偏相关系数衡量时,HRT、SO_4~(2-)、Alk、Cl~-和T是相对重要的因素,排序为HRTSO_4~(2-)AlkCl~-T.综合两种系数的分析结果,HRT、SO_4~(2-)和Cl~-是本研究条件下相对重要的因素,T和Alk的相对重要性视实际情况变动.     

夏季太湖CDOM光学特性空间差异及其来源解析

为进一步探究夏季太湖CDOM（有色溶解性有机质）光学特性在空间分布上的差异性与其来源的关系,对其紫外-可见吸收及三维荧光光谱特性进行了分析研究,在此基础上进一步分析了CDOM吸尘系数及其荧光组分（C1、C2、C3、C4）强度和各水质参数间的相关性.结合主成分分析法探讨了CDOM的来源以及与各参数指标[ρ（DOC）除外]之间的来源关系.结果表明:CDOM吸收系数α（355）、S值（光谱斜率）变化范围分别为3.27~8.27 m-1和0.011~0.021 nm-1;太湖西部、北部及南部湖区CDOM丰度较大,S值较低,受陆源输入的影响较为明显.CDOM的三维荧光光谱揭示其中含有两种类蛋白质组分C1和C2以及类腐殖质组分C3和C4,并且以类蛋白质组分为主.此外,大部分采样点的荧光指数（FI）为1.70~2.01,自生源指数（BIX）大于1,腐殖化指数（HIX）小于0.6,r_（T/C）（荧光峰T与荧光峰C荧光强度比值）小于2,表明夏季太湖CDOM内源特性相对强烈.研究显示,除ρ（DOC）外,CDOM与其他水质参数在第一主成分上（贡献率为90.8%）均存在显著相关关系,说明各水质参数的来源存在相似性,并且受生物自生源影响更为显著.      

基于污泥掺烧的某生活垃圾焚烧厂烟道气、飞灰及炉渣中的二(口恶)英特征

以我国南方某生活垃圾焚烧厂掺烧10%市政污泥的生活垃圾为研究对象,对前/后口废气、飞灰、炉渣及用于掺烧的污泥中17种二(口恶)英的含量进行了测定,并分析了其指纹分布特征.结合焚烧工况及处理设施,从生成机理角度探讨了二(口恶)英的排放特征、毒性当量浓度主成分特征及主要单体的排放因子线性关系.结果表明：掺烧10%的市政污泥后,废气中二(口恶)英的去除率为99.4%,低于国家排放标准;固体废物中二(口恶)英含量为飞灰 > 炉渣 > 污泥.这说明采用高温焚烧和"活性炭喷射+布袋除尘"装置不会影响掺烧10%污泥的达标排放.指纹分布特征表明,前口废气以1,2,3,4,6,7,8-HpCDF和OCDD为主,后口废气以OCDD和OCDF为主;飞灰、炉渣及污泥中的主要单体为OCDD、1,2,3,4,6,7,8-HpCDD、OCDF、1,2,3,4,6,7,8-HpCDF.主成分分析显示,前口废气和飞灰中的二(口恶)英毒性分布特征相似;炉渣和污泥的毒性分布特征相似;后口废气有自身的特征.这说明在相同工况条件下,经同一设施处理的废物中二(口恶)英排放特征相似.排放因子分析表明,2,3,4,7,8-PeCDF和1,2,3,6,7,8-HxCDF、1,2,3,6,7,8-HxCDD和1,2,3,7,8,9-HxCDD与总毒性排放因子具有较强的线性关系,且呋喃类（PCDFs）强于二(口恶)英类（PCDDs）.     

基于主成分分析法的陕北地区可持续发展对比研究

基于可持续发展基本理论,选取60项指标建立陕北地区可持续发展评价指标体系,采用软件SPSS(19.0)进行主成分分析,分别对延安市、榆林市2000—2014年的可持续发展水平、可持续发展潜力和可持续发展协调度进行动态对比分析。结果表明延安市、榆林市发展基本趋于一致:可持续发展水平较高,但可持续发展潜力明显不足,可持续发展协调度较低;制约其可持续发展的主要因素在于资源发展动力不足、产业结构单一、环境的恶化及治理的低效。     

基于神经网络的碳排放预测及影响因素分析

基于新疆1995—2014年农业生产碳排放源,建立碳排放关系数据库。应用广义神经网络(generalized regression neural network,GRNN)构建了排放量预测模型,结合平均影响值(mean impact value,MIV)方法对碳排放影响因素进行量化。结果表明:1)GRNN模型预测碳排放的平均绝对百分误差和拟合优度分别为2.7860%和0.8720;2)新疆人口、人均GDP、农业贡献值、农机总动力和农户固定资产投资等因素对农业生产碳排放的影响程度分别为0.6210、0.2377、0.3698、0.8500和0.1000。该成果可为新疆碳排放总量分析和影响因素量化方面提供参考。     

基于GIS和LUR模型的西安市PM2.5浓度空间分布模拟研究

基于地理信息系统GIS和土地利用回归LUR模型,模拟西安市PM2.5浓度空间动态分布,结果表明:与PM2.5浓度相关性最高的分别为缓冲区为2 km的水域面积、人口密度和距离水域距离,R 2分别为0.501,0.393和0.280;与PM2.5浓度相关性最低的分别为缓冲区为4 km的水域面积、未利用地面积和耕地面积,R 2分别为0.039、0.021和0.017.未考虑风速建立的LUR模型多元回归的相关系数为0.856,R 2为0.733,考虑风速的相关系数为0.892,R 2为0.796,表明风速对于污染物的分布影响较大,LUR模型模拟效果较好.模拟的PM2.5年均浓度高风险区分布于中部,中风险区分布于中西部,低风险区分布于东南部和西部.