崇明北湖叶绿素a浓度与环境因子的GAM回归分析

以崇明北湖为例,采用广义加性模型(GAM)对该湖的叶绿素a浓度与相关环境因子进行分析.结果表明,叶绿素a浓度与总氮、总磷和水温之间存在较好的非线性关系(P<0.05),叶绿素a浓度与总磷之间的关系先为单调递增,当总磷浓度达到0.12mg/L时,变为单调递减;不同总氮浓度区间上,总氮对叶绿素a浓度的影响不同,氮浓度为0.6~1.8mg/L时,对叶绿素a浓度的影响不大;水温在24~26℃时,叶绿素a浓度最高.叶绿素a浓度与氮磷比之间也存在较好的非线性关系(P<0.1),氮限制时,叶绿素浓度与氮磷比呈反比;磷限制时,叶绿素a浓度随着氮磷比单调递减.     

沙尘天气PM10对多种心血管疾病日门诊人数的影响

为研究沙尘天气大气可吸入颗粒物(PM10)与心血管系统疾病每日门诊人数的联系,采用半参数广义相加泊松回归模型(GAM),在排除了混杂因素如季节趋势、日历效应、气象因素和时间长期趋势等作用的前提下,分析2004年3月1日~5月31日沙尘暴频发区——甘肃省武威市大气PM10与多种心血管疾病每日门诊相对危险度(RR)的关系.结果表明,PM10与男、女总心血管系统疾病门诊RR均在滞后第2d(lag2)的联系有统计学意义.PM10分别在lag3和lag4对男、女性风湿性心脏病门诊RR的影响有统计学意义; PM10(lag2)与男性高血压门诊RR的联系有统计学意义.PM10在lag2对男性缺血性心血管疾病门诊RR的影响有统计学意义;PM10对男、女性心律失常以及充血性心力衰竭门诊RR的影响均无统计学意义.在调整了SO2和/或NO2后,PM10对男、女性心血管系统疾病门诊RR的作用有所下降,但在统计学上仍有意义.然而在分别调整了其他污染物后,SO2和NO2变得无统计学意义.沙尘天气PM10浓度分类模型分析表明,从正常清洁天、轻度污染天到扬沙天气、沙尘暴天气,随着PM10浓度水平的增大,心血管系统疾病(缺血性心血管疾病、充血性心力衰竭、心律失常、高血压、风湿性心脏病)门诊RR也随之增高,呈现一定的剂量效应关系.沙尘天气可吸入颗粒物可引起暴露居民多种心血管系统疾病(缺血性心血管疾病、充血性心力衰竭、心律失常、高血压、风湿性心脏病)门诊人数增多,且均呈现滞后效应. PM10浓度与心血管系统疾病门诊RR表现为一定的剂量效应关系.PM10浓度与沙尘天气强度有密切关系, 随着PM10浓度与沙尘天气强度的增大,暴露居民心血管系统多种疾病日门诊RR也增大,具体为:正常清洁天＜轻度污染天＜扬沙天＜沙尘暴天.     

Emergy algebra: Improving matrix methods for calculating transformities

Transformity is one of the core concepts in Energy Systems Theory and it is fundamental to the calculation of emergy. Accurate evaluation of transformities and other emergy per unit values is essential for the broad acceptance, application and further development of emergy methods. Since the rules for the calculation of emergy are different from those for energy, particular calculation methods and models have been developed for use in the emergy analysis of networks, but double counting errors still occur because of errors in applying these rules when estimating the emergies of feedbacks and co-products. In this paper, configurations of network energy flows were classified into seven types based on commonly occurring combinations of feedbacks, splits, and co-products. A method of structuring the network equations for each type using the rules of emergy algebra, which we called “preconditioning” prior to calculating transformities, was developed to avoid double counting errors in determining the emergy basis for energy flows in the network. The results obtained from previous approaches, the Track Summing Method, the Minimum Eigenvalue Model and the Linear Optimization Model, were reviewed in detail by evaluating a hypothetical system, which included several types of interactions and two inputs. A Matrix Model was introduced to simplify the calculation of transformities and it was also tested using the same hypothetical system. In addition, the Matrix Model was applied to two real case studies, which previously had been analyzed using the existing method and models. Comparison of the three case studies showed that if the preconditioning step to structure the equations was missing, double counting would lead to large errors in the transformity estimates, up to 275 percent for complex flows with feedback and co-product interactions. After preconditioning, the same results were obtained from all methods and models. The Matrix Model reduces the complexity of the Track Summing Method for the analysis of complex systems, and offers a more direct and understandable link between the network diagram and the matrix algebra, compared with the Minimum Eigenvalue Model or the Linear Optimization Model.     

长江流域能源利用效率研究

考察长江流域四川、重庆、湖南、湖北 、江西、安徽、浙江、江苏、上海七省二市能源利用效率,比较分析其差异以及原因,寻求提高能源利用效率的途径。首先定义能源利用效率为能源通过要素优化配置产生的技术效率,然后利用数据包络DEA和全要素效率SFA方法进行测度,最后通过比较拉氏指数与迪氏指数的优劣,采用迪氏指数法对能源利用效率影响因素进行分解。计算出七省二市及六部门1997~2006年GDP能耗、能源技术效率和能源利用效率,并分析了结构调整、技术进步和制度进化对能源效率的影响程度。研究表明：（1）结构调整是提高能源利用效率的有力措施;（2）技术进步和制度进化是提高能源利用效率的关键;（3）能源利用效率研究方法应尽量统一并不断改进.     

我国华北地区湿地生态需水量研究探讨与应用实例

我国华北地区湿地通常处于缺水状态.当湿地分别为"资源型缺水"和"水质型缺水"时,目前常用的几种生态需水量估算方法的适用范围是不同的.水量平衡法是较通用的方法;而水量损失法和最低水位法主要适用于资源型缺水;物质平衡法和逐年环境改良法则主要应用于污染型缺水的情况.针对不同的情况可以选取相应的估算方法.本文应用不同估算方法,对河北保定白洋淀湿地和北京顺义杨镇湿地的生态需水量进行了估算,通过估算结果间的比较,反映出白洋淀湿地面临的污染问题更严重,而杨镇湿地更亟需解决的是资源型缺水问题,使其补偿措施更有针对性,能更好地协调人与湿地生态环境问的关系.     

Effects of white‐nose syndrome on regional population patterns of 3 hibernating bat species

Hibernating bats have undergone severe recent declines across the eastern United States, but the cause of these regional‐scale declines has not been systematically evaluated. We assessed the influence of white‐nose syndrome (an emerging bat disease caused by the fungus Pseudogymnoascus destructans, formerly Geomyces destructans) on large‐scale, long‐term population patterns in the little brown myotis (Myotis lucifugus), the northern myotis (Myotis septentrionalis), and the tricolored bat (Perimyotis subflavus). We modeled population trajectories for each species on the basis of an extensive data set of winter hibernacula counts of more than 1 million individual bats from a 4‐state region over 13 years and with data on locations of hibernacula and first detections of white‐nose syndrome at each hibernaculum. We used generalized additive mixed models to determine population change relative to expectations, that is, how population trajectories differed with a colony's infection status, how trajectories differed with distance from the point of introduction of white‐nose syndrome, and whether declines were concordant with first local observation of the disease. Population trajectories in all species met at least one of the 3 expectations, but none met all 3. Our results suggest, therefore, that white‐nose syndrome has affected regional populations differently than was previously understood and has not been the sole cause of declines. Specifically, our results suggest that in some areas and species, threats other than white‐nose syndrome are also contributing to population declines, declines linked to white‐nose syndrome have spread across large geographic areas with unexpected speed, and the disease or other threats led to declines in bat populations for years prior to disease detection. Effective conservation will require further research to mitigate impacts of white‐nose syndrome, renewed attention to other threats to bats, and improved surveillance efforts to ensure early detection of white‐nose syndrome.     

Comparison of some atmospheric chemical modeling schemes

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轴流通风机A声级估算的探讨

本文导出了轴流风机整机噪声的估算公式,经验证估算值在风机额定工况和部分调速范围运转时符合实际。同时对不同估算公式进行了分析。     

Removal process estimation of population size for a population with a known sex ratio

A removal model for estimating population size which uses the known population sex ratio is studied. A maximum likelihood estimate and an optimal martingale estimate of the population size are proposed. Their standard errors and large sample properties are obtained. Simulation studies are reported, and the performance of the proposed estimators are compared with the standard maximum likelihood estimator which ignores the sex ratio information. An example on a capture study of deer mice is given.     

Identifying factors affecting the safety of mid-block bicycle lanes considering mixed 2-wheeled traffic flow

Objective: Electric bikes (e-bikes) have been one of the fastest growing trip modes in Southeast Asia over the past 2 decades. The increasing popularity of e-bikes raised some safety concerns regarding urban transport systems. The primary objective of this study was to identify whether and how the generalized linear regression model (GLM) could be used to relate cyclists' safety with various contributing factors when riding in a mid-block bike lane. The types of 2-wheeled vehicles in the study included bicycle-style electric bicycles (BSEBs), scooter-style electric bicycles (SSEBs), and regular bicycles (RBs).

Methods: Traffic conflict technology was applied as a surrogate measure to evaluate the safety of 2-wheeled vehicles. The safety performance model was developed by adopting a generalized linear regression model for relating the frequency of rear-end conflicts between e-bikes and regular bikes to the operating speeds of BSEBs, SSEBs, and RBs in mid-block bike lanes.

Results: The frequency of rear-end conflicts between e-bikes and bikes increased with an increase in the operating speeds of e-bikes and the volume of e-bikes and bikes and decreased with an increase in the width of bike lanes. The large speed difference between e-bikes and bikes increased the frequency of rear-end conflicts between e-bikes and bikes in mid-block bike lanes. A 1% increase in the average operating speed of e-bikes would increase the expected number of rear-end conflicts between e-bikes and bikes by 1.48%. A 1% increase in the speed difference between e-bikes and bikes would increase the expected number of rear-end conflicts between e-bikes/bikes by 0.16%.

Conclusions: The conflict frequency in mid-block bike lanes can be modeled using generalized linear regression models. The factors that significantly affected the frequency of rear-end conflicts included the operating speeds of e-bikes, the speed difference between e-bikes and regular bikes, the volume of e-bikes, the volume of bikes, and the width of bike lanes. The safety performance model can help better understand the causes of crash occurrences in mid-block bike lanes.