汽油清净性快速检测方法与监管方案研究

车用汽油清净性与汽车尾气污染物排放水平、燃油经济性等密切相关。为提高汽油清净性检测效率、提升相关职能部门的监管能力,提出了一种车载移动式多通道汽油清净性快速模拟检测方法（简称多通道快速模拟检测法）。与我国法规推荐的汽油机进气阀沉积物模拟试验方法（简称快速模拟检测法）相比,多通道快速模拟检测法的单个油样检测总耗时降低77.8%,多个油样检测总耗时降低94.4%,检验用油量减少约80%,成本降低约90%;多通道快速模拟检测法与快速模拟检测法具有较好的相关性（皮尔逊相关系数为0.4~0.8）,可用于汽油清净性的快速检测。最后,提出了汽油清净性的现场监管检测方案。

     

基于节点流量校核的供水管网爆管定位研究

针对目前基于节点压力变化定位供水管网爆管的方法,当供水管网中泵切换时,导致定位爆管位置存在误报的问题,提出了基于节点流量校核的管网爆管定位方法.利用奇异矩阵法推导出节点流量灵敏度矩阵,采取奇异矩阵中的最优搜索向量计算方法找到节点流量变化位置,确定爆管管道.首先,将该方法应用于一个小管网,阐述基于节点流量校核的管网爆管定...     

加油站油气回收系统VOCs泄漏FID现场检测方法及效果分析

油气回收系统密闭点VOCs泄漏质量分数值是衡量加油站是否存在超标排放的重要指标。为提高加油站VOCs泄漏检测的时效性、代表性与准确性,采用FID现场检测方法对郑州市某加油站油气回收系统进行了检测,全方位对比分析了实验室气相色谱法与现场检测法的检测时效性、准确性,提出了密闭区域检测及质量保证和控制建议,并根据实际检测数据分析了易泄漏点。结果表明：采用FID现场检测方法对油气回收系统密闭点进行检测,能使检测成本降低90%,检测效率提高 15 倍;在现场检测前完成仪器的校准、响应时间的测定与精密度的验证工作,可使VOCs最大质量分数偏差维持在5%以下,这进一步验证了FID现场检测方法测量的准确度;油气回收系统泄漏点的确定及现场检测流程和步骤的优化,可有效提高检测数据的代表性;检测设备的定期校准,可确保FID示值相对误差在±10％范围内,响应时间不超过30 s,从而为检测质量控制提供保障;为确保泄漏点完好,结合实际检测工作,应采用液位仪自动计量技术,加强设备的维护保养并设置加油枪气液比为1.05～1.15。综上所述,在保证FID的准确性与稳定性的前提下,采用FID现场检测方法对油气回收系统VOCs泄漏质量分数进行检测具有时效性强、准确度高、数据代表性强等优势。本研究结果可为加油站采用FID现场检测油气回收系统VOCs泄漏的质量分数提供参考。     

Effectiveness of Scat‐Detection Dogs in Determining Species Presence in a Tropical Savanna Landscape

Abstract: Most protected areas are too small to sustain populations of wide‐ranging mammals; thus, identification and conservation of high‐quality habitat for those animals outside parks is often a high priority, particularly for regions where extensive land conversion is occurring. This is the case in the vicinity of Emas National Park, a small protected area in the Brazilian Cerrado. Over the last 40 years the native vegetation surrounding the park has been converted to agriculture, but the region still supports virtually all of the animals native to the area. We determined the effectiveness of scat‐detection dogs in detecting presence of five species of mammals threatened with extinction by habitat loss: maned wolf (Chrysocyon brachyurus), puma (Puma concolor), jaguar (Panthera onca), giant anteater (Myrmecophaga tridactyla), and giant armadillo (Priodontes maximus). The probability of scat detection varied among the five species and among survey quadrats of different size, but was consistent across team, season, and year. The probability of occurrence, determined from the presence of scat, in a randomly selected site within the study area ranged from 0.14 for jaguars, which occur primarily in the forested areas of the park, to 0.91 for maned wolves, the most widely distributed species in our study area. Most occurrences of giant armadillos in the park were in open grasslands, but in the agricultural matrix they tended to occur in riparian woodlands. At least one target species occurred in every survey quadrat, and giant armadillos, jaguars, and maned wolves were more likely to be present in quadrats located inside than outside the park. The effort required for detection of scats was highest for the two felids. We were able to detect the presence for each of five wide‐ranging species inside and outside the park and to assign occurrence probabilities to specific survey sites. Thus, scat dogs provide an effective survey tool for rare species even when accurate detection likelihoods are required. We believe the way we used scat‐detection dogs to determine the presence of species can be applied to the detection of other mammalian species in other ecosystems.     

Cluster detection using Bayes factors from overparameterized cluster models

In this paper, we consider the use of a partition model to estimate regional disease rates and to detect spatial clusters. Formal inference regarding the number of partitions (or clusters) can be obtained with a reversible jump Markov chain Monte Carlo algorithm. As an alternative, we consider the ability of models with a fixed, but overly large, number of partitions to estimate regional disease rates and to provide informal inferences about the number and locations of clusters using local Bayes factors. We illustrate and compare these two approaches using data on leukemia incidence in upstate New York and data on breast cancer incidence in Wisconsin.     

植物根系分泌物研究方法评述

根系分泌物是植物与土壤微环境进行物质、能量和信息交流的重要媒介,对根系分泌物数量、种类的研究是植物营养、化感作用、环境修复等研究领域的重要内容。目前,根系分泌物研究中应用的收集方法主要有溶液培收集、土培收集、基质培收集和连续性根系分泌物收集系统等;分离纯化方法主要有树脂法、衍生化与萃取法、层析法和分子膜与超速离心法;检测方法有生物活性测定方法和仪器分析方法。文章结合实例综合论述了这些根系分泌物收集、分离纯化以及测定的方法,为研究者找到合适的根系分泌物研究方法提供参考。     

A field experiment characterizing variable detection rates during plant surveys

Surveys aimed at finding threatened and invasive species can be challenging due to individual rarity and low and variable individual detection rates. Detection rate in plant surveys typically varies due to differences among observers, among the individual plants being surveyed (targets), and across background environments. Interactions among these 3 components may occur but are rarely estimated due to limited replication and control during data collection. We conducted an experiment to investigate sources of variation in detection of 2 Pilosella species that are invasive and sparsely distributed in the Alpine National Park, Australia. These species are superficially similar in appearance to other yellow-flowered plants occurring in this landscape. We controlled the presence and color of flowers on target Pilosella plants and controlled their placement in plots, which were selected for their variation in cover of non-target yellow flowers and dominant vegetation type. Observers mimicked Pilosella surveys in the plots and reported 1 categorical and 4 quantitative indicators of their survey experience level. We applied survival analysis to detection data to model the influence of both controlled and uncontrolled variables on detection rate. Orange- and yellow-flowering Pilosella in grass- and heath-dominated vegetation were detected at a higher rate than nonflowering Pilosella. However, this detection gain diminished as the cover of other co-occurring yellow-flowering species increased. Recent experience with Pilosella surveys improved detection rate. Detection experiments are a direct and accessible means of understanding detection processes and interpreting survey data for threatened and invasive species. Our detection findings have been used for survey planning and can inform progress toward eradication. Interaction of target and background characteristics determined detection rate, which enhanced predictions in the Pilosella eradication program and demonstrated the difficulty of transferring detection findings into untested environments.     

Ti-Si-Ox脱硝催化剂载体的组分优化及其性能研究

采用挤出成型法制备系列Ti-Si-Ox复合氧化物催化剂载体,研究了Ti-Si-Ox催化剂载体组分配比、酸量、比表面积与脱硝性能和抗压强度的关系。采用XRD、Raman spectra、N2-BET、Py-IR以及XPS等表征技术对催化剂载体进行表征。结果表明：Ti/Si元素摩尔比为9∶1时Ti0.9Si0.1Ox催化剂载体的轴向抗压强度适中且脱硝催化活性最高;在5 000 h-1空速条件下,催化剂载体最高脱硝活性在400 ℃时达到99.0%且起燃温度降至260 ℃;另外,Ti0.9Si0.1Ox催化剂载体的比表面积为75.4 m2·g-1,介孔最可几分布为8.1 nm,轴向抗压强度为1.4 MPa,符合工业应用条件,即Ti-Si-Ox载体具有较好的工业应用前景。     

北京市黑臭水体治理的动态遥感监测及影响因素分析

为及时、准确掌握黑臭水体治理进展,基于“北京二号”影像数据和同期的野外综合水体实测数据,采用深度学习算法对黑臭水体进行识别,并引入地理探测器对黑臭水体影响因素进行定量分析。结果表明：基于Faster R-CNN算法的黑臭水体遥感识别,总准确率达到90%左右,短时间内(5~33 h)即可完成北京市建成区黑臭水体的筛查工作;在空间维度上,黑臭水体主要分布在中心城区以外,并在通州区、朝阳区和大兴区较为集中;在时间维度上,专项治理期间(2015—2018年)内,黑臭水体的数量和长度总体趋势都是递减的,但偶尔也有反黑现象;2018年底,在全市建成区范围内,已全面消除黑臭现象;在一年内,第1季度水体环境最好,第2季度次之,第3季度最差,从第4季度开始好转;在北京市大兴区,土壤全氮量(贡献率为32.07%)和周边养殖场排污(贡献率为27.04%)是黑臭水体形成的主要影响因素,高程(贡献率为8%)、土壤类型(贡献率为7.6%)和土地利用类型(贡献率为6.1%)的贡献率较弱。由此可以看出,基于Faster R-CNN算法识别影像中的黑臭水体识别准确率高,可及时、准确地监测城市黑臭水体治理情况,使用地理探测器可定量分析并确定各影响因素的贡献率。本研究成果可为城市黑臭水体的动态监测和治理提供有力的技术支撑。