气体中雾状物质的采样效率探讨

发生增塑剂 DEP雾 ,粒径主要分布在 0 .48～ 3 .4μm。使用不同容积、不同类型的吸收瓶 (管 )在不同的采样条件下进行 DEP雾样品采集 ,将采样效率和采样过程发生的现象进行比较 ,选择出合适的采样方法和采样条件     

标准气与空气样品同路同效输送的新型采样总管集成技术

经过近20年的发展,监测部门面对日益严峻的环境压力及其对环境监测数据要求的日益严格,要求大气自动监测QA/QC体系必须更加完善。针对传统采样总管标准气不能实现与空气样品同路同效输送的问题进行探讨,并研发出一套实现标准气与空气样品同路同效输送的新型采样总管集成技术。     

地表水总磷测定中现场前处理方式及分析方法比对研究

针对目前地表水总磷测定中样品采集和分析过程普遍存在的技术问题,选取多泥沙河流(长江、黄河)、感潮河段(浙闽片区)、湖库(太湖流域) 3类典型水体的多个点位,以及代表一般河流(除多泥沙河流和感潮河段以外的河流)水体的点位为研究对象,探讨不同现场前处理方式和分析方法对总磷测定结果的影响。结果表明:现场前处理方式是影响总磷测定结果的主要因素,总磷浓度与浊度呈正相关。对于地表水采样,建议一般河流(沉降30 min后,浊度50 NTU)采用沉降30 min的现场前处理方式,泥沙含量大的水体(沉降30 min后,浊度≥50 NTU)采用4000 r/min离心2 min的现场前处理方式,多藻类湖库水体采用63μm筛过滤的现场前处理方式。可通过浊度色度补偿消除实验室比色干扰。     

土壤环境监测基础点位布设思路与方法

为适应新形势下土壤环境保护工作重点任务和要求,"十三五"期间,中国亟需构建布局合理、功能完备的土壤环境监测网,确定国控监测点位,以说清全国土壤环境质量整体状况、潜在风险状况及变化趋势。通过梳理欧美等发达国家和地区的做法和经验,针对国内土壤环境的实际情况,开展布点尺度和点位优化方法研究,提出了国家尺度上适宜布点尺度,建立了统一的历史点位优化筛选规则,在此基础上,形成了点位的布设思路、原则和方法,并给出了阶段性的布设结果,最后提出了后续进一步完善的方向。     

固定污染源废气中磷酸雾测定方法研究

目前,对固定污染源废气中磷酸雾的检测并无统一的方法,相关含磷污染物的控制指标主要是磷化氢、单质磷以及五氧化二磷。在调研国内外分析方法及相关文献的基础上,通过对几种典型含磷污染源的实样测试,提出了固定污染源废气中磷酸雾的检测方法。结果表明,使用石英滤筒捕集固定污染源废气中的磷酸雾,采样效率可达98%以上。捕集到的总磷酸雾不仅包含磷酸,还包含磷酸盐以及含磷氧化物等,是一项综合指标。该指标能够反映含磷污染物的排放特征,可为未来此类污染物的排放控制提供依据。     

西安市某工业园夏季VOCs浓度特征及O3、SOA生成潜势

2020年7月30日—10月10日对西安市某工业园区大气中的70种VOCs开展了为期73 d的VOCs手工采样监测,分析了上、下风向2个点位VOCs浓度组成特征、O₃生成潜势和SOA生成潜势,并运用PMF进一步分析该区域VOCs的主要来源。结果显示:监测期间工业园区平均VOCs浓度为203.50μg/m³,以甲醛和乙醛为主的醛酮类(148.37μg/m³)是主要污染物,占TVOC浓度的57%～84%,其次是烷烃。通过上、下风向VOCs成分比较发现,醛酮类为高污染时段特征污染物,工业园区平均OFP为969.66μg/m³,醛酮类对O₃生成的贡献最大,占TOFP的80%～97%,其次是烯烃。工业园区平均SOAFP为0.50μg/m³,芳香烃对SOA生成的贡献最大,占TSOAFP的48%～98%,其次是烷烃。PMF源解析得到5个因子,分别为工业源、溶剂涂料、燃烧源、移动源及其他源,贡献率分别占35.2%、20.4%、18.3%、12.8%、13.3%,解析显示该...     

A Bayesian-weighted approach to predicting the number of newly discovered rare species

In natural ecological communities, most species are rare and thus susceptible to extinction. Consequently, the prediction and identification of rare species are of enormous value for conservation purposes. How many newly found species will be rare in the next field survey? We took a Bayesian viewpoint and used observed species abundance information in an ecological sample to develop an accurate way to estimate the number of new rare species (e.g., singletons, doubletons, and tripletons) in an additional unknown sample. A similar method has been developed for incidence-based data sets. Five seminumerical tests (3 abundance cases and 2 incidence cases) showed that our proposed Bayesian-weight estimator accurately predicted the number of new rare species with low relative bias and low relative root mean squared error and, accordingly, high accuracy. Finally, we applied the proposed estimator to 6 conservation-directed empirical data sets (3 abundance cases and 3 incidence cases) and found the prediction of new rare species was quite accurate; the 95% CI covered the true observed value very well in most cases. Our estimator performed similarly to or better than an unweighted estimator derived from Chao et al. and performed consistently better than the naïve unweighted estimator. We recommend our Bayesian-weight estimator for conservation applications, although the unweighted estimator of Chao et al. may be better under some circumstances. We provide an R package RSE (r are s pecies e stimation) at https://github.com/ecomol/RSE for implementation of the estimators.     

Use of opportunistic sightings and expert knowledge to predict and compare Whooping Crane stopover habitat

Predicting a species’ distribution can be helpful for evaluating management actions such as critical habitat designations under the U.S. Endangered Species Act or habitat acquisition and rehabilitation. Whooping Cranes (Grus americana) are one of the rarest birds in the world, and conservation and management of habitat is required to ensure their survival. We developed a species distribution model (SDM) that could be used to inform habitat management actions for Whooping Cranes within the state of Nebraska (U.S.A.). We collated 407 opportunistic Whooping Crane group records reported from 1988 to 2012. Most records of Whooping Cranes were contributed by the public; therefore, developing an SDM that accounted for sampling bias was essential because observations at some migration stopover locations may be under represented. An auxiliary data set, required to explore the influence of sampling bias, was derived with expert elicitation. Using our SDM, we compared an intensively managed area in the Central Platte River Valley with the Niobrara National Scenic River in northern Nebraska. Our results suggest, during the peak of migration, Whooping Crane abundance was 262.2 (90% CI 40.2?3144.2) times higher per unit area in the Central Platte River Valley relative to the Niobrara National Scenic River. Although we compared only 2 areas, our model could be used to evaluate any region within the state of Nebraska. Furthermore, our expert‐informed modeling approach could be applied to opportunistic presence‐only data when sampling bias is a concern and expert knowledge is available.     

Spatially Explicit Power Analyses for Occupancy‐Based Monitoring of Wolverine in the U.S. Rocky Mountains

Conservation scientists and resource managers often have to design monitoring programs for species that are rare or patchily distributed across large landscapes. Such programs are frequently expensive and seldom can be conducted by one entity. It is essential that a prospective power analysis be undertaken to ensure stated monitoring goals are feasible. We developed a spatially based simulation program that accounts for natural history, habitat use, and sampling scheme to investigate the power of monitoring protocols to detect trends in population abundance over time with occupancy‐based methods. We analyzed monitoring schemes with different sampling efforts for wolverine (Gulo gulo) populations in 2 areas of the U.S. Rocky Mountains. The relation between occupancy and abundance was nonlinear and depended on landscape, population size, and movement parameters. With current estimates for population size and detection probability in the northern U.S. Rockies, most sampling schemes were only able to detect large declines in abundance in the simulations (i.e., 50% decline over 10 years). For small populations reestablishing in the Southern Rockies, occupancy‐based methods had enough power to detect population trends only when populations were increasing dramatically (e.g., doubling or tripling in 10 years), regardless of sampling effort. In general, increasing the number of cells sampled or the per‐visit detection probability had a much greater effect on power than the number of visits conducted during a survey. Although our results are specific to wolverines, this approach could easily be adapted to other territorial species. Poder de Análisis Espacialmente Explícito para el Monitoreo Basado en Ocupación del Glotón (Gulo gulo) en las Montañas Rocallosas de Estados Unidos     

丹东凤凰山山上与山下降水酸度迥异原因分析

采用分段监测的方法研究了辽宁丹东凤凰山垂直高度上的降水酸度及组分特征,并利用后向气流轨迹与分段离子相关性叠加分析的方法,对山上与山下降水酸度的差异成因进行了分析。结果表明：凤凰山4次降水中,pH值山上均低于山下,总离子浓度山上均低于山下,说明近地面大气污染物对酸雨起到一定的中和作用;山上降水酸度主要受大气远距离传输影响,山下降水酸度受本地源和远距离传输的共同作用。