富集采样法监测空气和废气样品时采样体积的确定方法

讨论了富集采样法监测空气和废气样品时确定采样体积的主要因素，给出了富集采样法监测空气和废气样品时采样体积的确定方法和实例。     

广西典型自然保护区监管天地一体化技术应用探究

基于遥感影像、无人机航摄与移动核查技术,构建了集自然保护区"一张图"、图斑任务管理、移动核查为一体的天地一体化自然保护区人类活动监管系统,并以防城金花茶国家级自然保护区为例,进行试点监测监管研究。结果表明,利用监管系统可提高自然保护区监管时效性,有效解决监管盲区。对防城金花茶国家级自然保护区的人类活动进行监测评价,该保护区有工矿用地、农田、居民点、道路、其他人工设施等5类,以农田、居民点、普通道路为主,人类活动影响一般。     

Uncertainty Assessment of Voc Emissions from Paint in the Netherlands Using the Nusap System

We demonstrate an innovative approach to uncertainty assessment known as the NUSAP system, to assess qualitative and quantitative uncertainty for the case of emissions of volatile organic compounds (VOC) from paint in The Netherlands. Using expert elicitation, we identified key sources of error, critical assumptions, and bias in the monitoring process. We assessed pedigree and probabilistic uncertainty of all input quantities. We used four pedigree criteria to assess the strength of the knowledge base: proxy representation, empirical basis, methodological rigour and degree of validation. Using Monte Carlo analysis, we assessed sensitivity and propagation of uncertainty. Results for sensitivity and pedigree were combined in a NUSAP Diagnostic Diagram, which effectively highlighted the assumption for VOC percentage of imported paint as the weakest spot in the monitoring of VOC emissions. We conclude that NUSAP facilitates systematic scrutinization of method and underlying assumptions and structures creative thinking on sources of error and bias. It provides a means to prioritise uncertainties and focus research efforts on the potentially most problematic parameters and assumptions, at the same time identifying specific weaknesses in the knowledge base. With NUSAP, nuances of meaning about quantities can be conveyed concisely and clearly, to a degree that is not possible with statistic methods only.     

Sampling of Sparse Species with Probability Proportional to Prediction

In this article, a 3P sampling (Probability Proportional to Prediction) approach is presented for surveying sparse species connected to certain types of substrates. The method uses the surveyors judgement of the probability of finding the species on a substrate as the base for selection of substrates for species inventories. The method is presented together with estimators, variances and variance estimators. The method is first presented for sampling based on all substrates in a study area and then as a subsampling technique in a two-stage design in which plots or strips are selected in a first stage. The presented approach was evaluated as a subsampling technique in a strip survey of calicioid lichen species associated with coarse broadleaf trees. In comparison with a simple random subsampling without replacement, 3P subsampling was in one study area found to be an improvement with 30–55% in terms of standard errors. The improvement was more modest in the other study area, only between 10–16%. The strip survey with 3P subsampling was more cost-efficient than a strip survey without subsampling except in one case. Based on the results in the test, 3P sampling seems to have a potential for sampling sparse species.     

A method to combine non-probability sample data with probability sample data in estimating spatial means of environmental variables

In estimating spatial means of environmental variables of a region from datacollected by convenience or purposive sampling, validity of the results canbe ensured by collecting additional data through probability sampling. Theprecision of the estimator that uses the probability sample can beincreased by interpolating the values at the nonprobability sample points tothe probability sample points, and using these interpolated values as anauxiliary variable in the difference or regression estimator. Theseestimators are (approximately) unbiased, even when the nonprobability sampleis severely biased such as in preferential samples. The gain in precisioncompared to the estimator in combination with Simple Random Samplingis controlled by the correlation between the target variable andinterpolated variable. This correlation is determined by the size (density)and spatial coverage of the nonprobability sample, and the spatialcontinuity of the target variable. In a case study the average ratio of thevariances of the simple regression estimator and estimator was 0.68for preferential samples of size 150 with moderate spatial clustering, and0.80 for preferential samples of similar size with strong spatialclustering. In the latter case the simple regression estimator wassubstantially more precise than the simple difference estimator.     

土壤污染调查加密布点优化方法构建及验证

鉴于传统调查布点方法对土壤污染物平均含量的估计精度较高,但对污染区范围的估计精度不能满足修复治理需求的问题,同时,为了准确估计土壤污染区面积及其空间位置,提出了土壤污染详查样点优化方法.在初步调查的基础上,首先利用地统计条件模拟方法预测土壤污染概率,基于污染概率和土壤污染物含量局部空间变异确定加密布点的优先区域,并根据污染物含量的空间变化趋势布设样点,然后根据优化后的土壤污染调查布点方案估计污染区面积和空间位置.最后,以某Cd污染场地为例,验证了布点优化方法的效果.结果表明,土壤污染调查加密布点方法显著提高了污染区面积及其空间位置的估计精度.案例场地土壤Cd污染区面积的预测误差为4.10%,污染区空间位置的精度为86.10%.土壤污染调查布点优化方法在保证土壤污染调查精度的同时,相比于传统调查方法可显著降低土壤污染调查的样本量.     

便携式GC-MS在室内空气VOC监测中的应用

本文采用苏码罐结合动态稀释权配置标准气体系列,建立了便携式GC-MS分析室内空气VOC的定量方法,并对便携式GC-MS和传统实验室GC-MS这两种检测方法进行对比研究。结果发现,便携式GC-MS和传统实验室GC-MS这两种检测方法所得结果并无显著差异。用便携式GC-MS对不同类型室内空气中VOC进行现场监测,操作简便、分析快速、灵敏度高,能够满足室内空气监测的要求。     

空气净化器净化燃香源PM_(2.5)的性能与效果评价

"史上最严"的控烟条例《北京市控制吸烟条例》正式实施,现行空气净化器性能测试中以香烟烟雾作为颗粒物污染源的标准受到挑战;加之燃香源颗粒物净化手段少有讨论。故以室内燃香替代香烟作为PM2.5的污染源,在环境实验舱内通过对市售净化器性能指标CADR进行测试,证明燃香可产生持续且稳定的颗粒物,可以替代香烟作为颗粒物污染源。燃香全程净化效果试验表明:在一根燃香的过程中时,开启净化器可保持采样点全程优质的空气质量;使用两根燃香时,采样点高度差异可导致明显的浓度差异,建议使用中考虑净化器摆放高度。     

Comparison of atmospheric concentrations of currently used pesticides between urban and rural areas during intensive application period in Alsace (France) by using XAD-2® based passive samplers

XAD-2® passive samplers (PAS) have been exposed simultaneously for 14 days on two sites, one rural and one urban, situated in Alsace (East of France) during intensive pesticides application in agriculture (between March and September). PAS have been extracted and analyzed for current-used pesticides and lindane with an analytical method coupling accelerated solvent extraction (ASE), solid-phase microextraction (SPME) and GC/MS/MS. Results show the detection of pesticides is linked to the period of application and spatial and temporal variabilities can be observed with these PAS during the selected sampling period. The spatial and temporal variability is comparable to the one previously observed by comparing data obtained with PAS with data from Hi.-Vol. samplers in an urban area. Sampling rates were calculated for some pesticides and values are comparable to the data already available in the literature. From these sampling rates, concentrations in ng m^?3 of pesticides in PAS have been calculated and are in the same order of magnitude as those obtained with Hi.Vol. sampling during the same period of time.     

Advantages of Volunteer-Based Biodiversity Monitoring in Europe

Abstract:  Without robust and unbiased systems for monitoring, changes in natural systems will remain enigmatic for policy makers, leaving them without a clear idea of the consequences of any environmental policies they might adopt. Generally, biodiversity-monitoring activities are not integrated or evaluated across any large geographic region. The EuMon project conducted the first large-scale evaluation of monitoring practices in Europe through an on-line questionnaire and is reporting on the results of this survey. In September 2007 the EuMon project had documented 395 monitoring schemes for species, which represents a total annual cost of about €4 million, involving more than 46,000 persons devoting over 148,000 person-days/year to biodiversity-monitoring activities. Here we focused on the analysis of variations of monitoring practices across a set of taxonomic groups (birds, amphibians and reptiles, mammals, butterflies, plants, and other insects) and across 5 European countries (France, Germany, Hungary, Lithuania, and Poland). Our results suggest that the overall sampling effort of a scheme is linked with the proportion of volunteers involved in that scheme. Because precision is a function of the number of monitored sites and the number of sites is maximized by volunteer involvement, our results do not support the common belief that volunteer-based schemes are too noisy to be informative. Just the opposite, we believe volunteer-based schemes provide relatively reliable data, with state-of-the-art survey designs or data-analysis methods, and consequently can yield unbiased results. Quality of data collected by volunteers is more likely determined by survey design, analytical methodology, and communication skills within the schemes rather than by volunteer involvement per se.