固定源硫酸雾国内外采样方法优劣分析

固定污染源硫酸雾的国标采样方法为滤筒法，但对其采样效率研究较少。在调研国内外标准方法及相关文献的基础上，通过大量实样测定，对国标采样法进行改进：在内装滤筒的烟尘采样管后串联一个冲击式吸收瓶，此改进方法弥补了国标漏测气态硫酸雾的缺陷，采样效率达到99％以上，国标法仅为改进法的47％～68％。将国标改进法与USEPA采样法进行比对，结果表明，由于中国环境本底颗粒物浓度较高，硫酸雾易吸附于颗粒物上，致使USEPA采样效率仅为国标改进法的2?4％～12％。     

污染源废气中二噁英监测采样应注意的几个问题

解析废气中二噁英监测采样的现状及不足,针对生活垃圾焚烧炉(炉排炉)、蓄热式焚烧炉(RTO)和危险废物焚烧炉(回转窑)3种不同类型焚烧炉,考察了采样过程中烟道类型、采样时间和采样时间间隔不同对二噁英监测的影响。结果表明,在水平烟道和垂直烟道采样测得二噁英排放浓度水平相当,有垂直烟道时,优先在垂直烟道采样;间隔采样和连续采样二噁英测定结果基本一致,为了便于操作,建议均采用连续采样方式;采样时间上,生活垃圾焚烧炉应保证超过1 h,蓄热式焚烧炉以2 h左右为宜;间歇投料危险废物焚烧炉应尽量满足2 h以上,条件不许可时,可通过增加采样流量缩短采样时间保证采样量,并在危险废物完全燃烧前结束采样工作。     

Effect of imperfect detectability on adaptive and conventional sampling: simulated sampling of freshwater mussels in the upper Mississippi River

Adaptive sampling designs are recommended where, as is typical with freshwater mussels, the outcome of interest is rare and clustered. However, the performance of adaptive designs has not been investigated when outcomes are not only rare and clustered but also imperfectly detected. We address this combination of challenges using data simulated to mimic properties of freshwater mussels from a reach of the upper Mississippi River. Simulations were conducted under a range of sample sizes and detection probabilities. Under perfect detection, efficiency of the adaptive sampling design increased relative to the conventional design as sample size increased and as density decreased. Also, the probability of sampling occupied habitat was four times higher for adaptive than conventional sampling of the lowest density population examined. However, imperfect detection resulted in substantial biases in sample means and variances under both adaptive sampling and conventional designs. The efficiency of adaptive sampling declined with decreasing detectability. Also, the probability of encountering an occupied unit during adaptive sampling, relative to conventional sampling declined with decreasing detectability. Thus, the potential gains in the application of adaptive sampling to rare and clustered populations relative to conventional sampling are reduced when detection is imperfect. The results highlight the need to increase or estimate detection to improve performance of conventional and adaptive sampling designs.     

Evaluating performance of stormwater sampling approaches using a dynamic watershed model

Accurate quantification of stormwater pollutant levels is essential for estimating overall contaminant discharge to receiving waters. Numerous sampling approaches exist that attempt to balance accuracy against the costs associated with the sampling method. This study employs a novel and practical approach of evaluating the accuracy of different stormwater monitoring methodologies using stormflows and constituent concentrations produced by a fully validated continuous simulation watershed model. A major advantage of using a watershed model to simulate pollutant concentrations is that a large number of storms representing a broad range of conditions can be applied in testing the various sampling approaches. Seventy-eight distinct methodologies were evaluated by "virtual samplings" of 166 simulated storms of varying size, intensity and duration, representing 14 years of storms in Ballona Creek near Los Angeles, California. The 78 methods can be grouped into four general strategies: volume-paced compositing, time-paced compositing, pollutograph sampling, and microsampling. The performances of each sampling strategy was evaluated by comparing the (1) median relative error between the virtually sampled and the true modeled event mean concentration (EMC) of each storm (accuracy), (2) median absolute deviation about the median or "MAD" of the relative error or (precision), and (3) the percentage of storms where sampling methods were within 10% of the true EMC (combined measures of accuracy and precision). Finally, costs associated with site setup, sampling, and laboratory analysis were estimated for each method. Pollutograph sampling consistently outperformed the other three methods both in terms of accuracy and precision, but was the most costly method evaluated. Time-paced sampling consistently underestimated while volume-paced sampling over estimated the storm EMCs. Microsampling performance approached that of pollutograph sampling at a substantial cost savings. The most efficient method for routine stormwater monitoring in terms of a balance between performance and cost was volume-paced microsampling, with variable sample pacing to ensure that the entirety of the storm was captured. Pollutograph sampling is recommended if the data are to be used for detailed analysis of runoff dynamics.     

Even sampling designs generation by charges repulsion simulation

Evenly distributed sampling design is generally considered as an efficient sampling design. It is widely used in sampling for the environmental survey. In this paper, we present a novel method for generating N evenly distributed samples within a given irregular polygon via simulating the movements of some ideal homogeneous point charges. Initially, charges are randomly put into the sampling region; then, they are freed and held orderly; and after enough runs, the charges will finally reach a stable state with all of them having a zero resultant force and velocity; and so they distribute evenly within the region. Their layout can thus be considered as an evenly distributed sampling design. The main advantages of this method are: (1) it is easy to understand and implement; (2) it is efficient in both running and generating better designs. Analysis and experimental results indicate that this method is an efficient and robust method for generating even sampling designs for 2D polygonal sampling region.     

Assessment of sampling and analytical uncertainty of trace element contents in arable field soils

Assessment of trace element contents in soils is required in Germany (and other countries) before sewage sludge application on arable soils. The reliability of measured element contents is affected by measurement uncertainty, which consists of components due to (1) sampling, (2) laboratory repeatability (intra-lab) and (3) reproducibility (between-lab). A complete characterization of average trace element contents in field soils should encompass the uncertainty of all these components. The objectives of this study were to elucidate the magnitude and relative proportions of uncertainty components for the metals As, B, Cd, Co, Cr, Mo, Ni, Pb, Tl and Zn in three arable fields of different field-scale heterogeneity, based on a collaborative trial (CT) (standardized procedure) and two sampling proficiency tests (PT) (individual sampling procedure). To obtain reference values and estimates of field-scale heterogeneity, a detailed reference sampling was conducted. Components of uncertainty (sampling person, sampling repetition, laboratory) were estimated by variance component analysis, whereas reproducibility uncertainty was estimated using results from numerous laboratory proficiency tests. Sampling uncertainty in general increased with field-scale heterogeneity; however, total uncertainty was mostly dominated by (total) laboratory uncertainty. Reproducibility analytical uncertainty was on average by a factor of about 3 higher than repeatability uncertainty. Therefore, analysis within one single laboratory and, for heterogeneous fields, a reduction of sampling uncertainty (for instance by larger numbers of sample increments and/or a denser coverage of the field area) would be most effective to reduce total uncertainty. On the other hand, when only intra-laboratory analytical uncertainty was considered, total sampling uncertainty on average prevailed over analytical uncertainty by a factor of 2. Both sampling and laboratory repeatability uncertainty were highly variable depending not only on the analyte but also on the field and the sampling trial. Comparison of PT with CT sampling suggests that standardization of sampling protocols reduces sampling uncertainty, especially for fields of low heterogeneity.     

Estimating sampling frequency in pollen exposure assessment over time

A time series model was fitted to the pollen concentration data collected in the Greater Cincinnati area for the Cincinnati Childhood Allergy and Air Pollution Study (CCAAPS). A traditional time series analysis and temporal variogram approach were applied to the regularly spaced databases (collected in 2003) and irregularly spaced ones (collected in 2002), respectively. The aim was to evaluate the effect of the sampling frequency on the sampling precision in terms of inverse of standard error of the overall level of mean value across time. The presence of high autocorrelation in the data was confirmed and indicated some degree of temporal redundancy in the pollen concentration data. Therefore, it was suggested that sampling frequency could be reduced from once a day to once every several days without a major loss of sampling precision of the overall mean over time. Considering the trade-offs between sampling frequency and the possibility of sampling bias increasing with larger sampling interval, we recommend that the sampling interval should take values from 3 to 5 days for the pollen monitoring program, if the goal is to track the long-term average.     

Optimising the sampling effort in riparian surveys

Riparian condition is commonly measured as part of stream health monitoring programs as riparian vegetation provides an intricate linkage between the terrestrial and aquatic ecosystems. Field surveys of a riparian zone provide comprehensive riparian attribute data but can be considerably intensive and onerous on resources and workers. Our objective was to assess the impact of reducing the sampling effort on the variation in key riparian health indicators. Subsequently, we developed a non-parametric approach to calculate an information retained (IR) statistic for comparing several constrained systematic sampling schemes to the original survey. The IR statistic is used to select a scheme that reduces the time taken to undertake riparian surveys (and thus potentially the costs) whilst maximising the IR from the original survey. Approximate bootstrap confidence intervals were calculated to improve the inferential capability of the IR statistic. The approach is demonstrated using riparian vegetation indicators collected as part of an aquatic ecosystem health monitoring program in Queensland, Australia. Of the nine alternative sampling designs considered, the sampling design that reduced the sampling intensity per site by sixfold without significantly comprising the quality of the IR, results in halving the time taken to complete a riparian survey at a site. This approach could also be applied to reducing sampling effort involved in monitoring other ecosystem health indicators, where an intensive systematic sampling scheme was initially employed.     

Groundwater monitoring plans at small-scale sites--an innovative spatial and temporal methodology

An innovative methodology for improving existing groundwater monitoring plans at small-scale sites is presented. The methodology consists of three stand-alone methods: a spatial redundancy reduction method, a well-siting method for adding new sampling locations, and a sampling frequency determination method. The spatial redundancy reduction method eliminates redundant wells through an optimization process that minimizes the errors in plume delineation and the average plume concentration estimation. The well-siting method locates possible new sampling points for an inadequately delineated plume via regression analysis of plume centerline concentrations and estimation of plume dispersivity values. The sampling frequency determination method recommends the future frequency of sampling for each sampling location based on the direction, magnitude, and uncertainty of the concentration trend derived from representative historical concentration data. Although the methodology is designed for small-scale sites, it can be easily adopted for large-scale site applications. The proposed methodology is applied to a small petroleum hydrocarbon-contaminated site with a network of 12 monitoring wells to demonstrate its effectiveness and validity.     

Continuous, intermittent and passive sampling of airborne VOCs

Long sampling periods are often advantageous or required for measuring air quality and characterizing exposures. However, sampling periods exceeding 8 to 24 h using thermally desorbable adsorbent tube (TDT) samplers for the measurement of airborne volatile organic compounds (VOCs) face several challenges, including maintaining stable and low flow rates, and avoiding breakthrough of the adsorbent. These problems may be avoided using intermittent sampling; however, the literature contains few if any reports that have evaluated this technique in environmental, occupational or other applications. The purpose of this study is to evaluate continuous, intermittent and passive sampling methods using both laboratory and real-world tests. Laboratory tests compared continuous and intermittent (active) samplers in a controlled dynamic test gas generation system. Field tests used side-by-side active and passive samplers in an office, home workshop and four smokers' homes. All samples were analyzed for a wide range of VOCs by GC-MS. In most instances, intermittent sampling yielded better reproducibility (duplicate precision of 10 +/- 6%) than continuous low-flow sampling (18 +/- 5%), in part due to difficulty maintaining low flows. Concentrations obtained using intermittent sampling agreed with those for continuous sampling, with downward biases resulting primarily from errors in flow rate measurements. In the field, more VOC species were detected using active rather than passive sampling. Passive measurements were 12% lower than continuous measurements, a difference attributed to declining uptake rates at higher concentrations over the 3 to 4 d sampling period. Overall, most measurements obtained using the three sampling methods agreed within 20% for a wide range of concentrations (0.1 to 230 microg m(-3)). Both passive and intermittent sampling approaches are suitable for long sampling periods, but intermittent sampling provides greater flexibility with respect to sampling period, and permits the use of multi-bed adsorbents that can capture a wider range of VOCs.     

燃煤电厂烟气中汞的采集与分析方法

汞的测试技术包括采样和分析两部分,其中汞含量的分析方法已经相对比较成熟,限制测试技术发展的诸多问题主要来源于取样过程。根据不同的取样方式,将现有测试技术分为湿式采样分析法、干式采样分析法以及在线分析技术3种,重点介绍了3种方法的采样原理、系统构成、过程的影响因素以及适用范围。最后针对CVAAS、CVAFS、AES 3种汞含量测定技术在Hg CEMS测试系统中的应用进行了对比介绍。     

Assessing temporal representativeness of water quality monitoring data

The effectiveness of different monitoring methods in detecting temporal changes in water quality depends on the achievable sampling intervals, and how these relate to the extent of temporal variation. However, water quality sampling frequencies are rarely adjusted to the actual variation of the monitoring area. Manual sampling, for example, is often limited by the level of funding and not by the optimal timing to take samples. Restrictions in monitoring methods therefore often determine their ability to estimate the true mean and variance values for a certain time period or season. Consequently, we estimated how different sampling intervals determine the mean and standard deviation in a specific monitoring area by using high frequency data from in situ automated monitoring stations. Raw fluorescence measurements of chlorophyll a for three automated monitoring stations were calibrated by using phycocyanin fluorescence measurements and chlorophyll a analyzed from manual water samples in a laboratory. A moving block bootstrap simulation was then used to estimate the standard errors of the mean and standard deviations for different sample sizes. Our results showed that in a temperate, meso-eutrophic lake, relatively high errors in seasonal statistics can be expected from monthly sampling. Moreover, weekly sampling yielded relatively small accuracy benefits compared to a fortnightly sampling. The presented method for temporal representation analysis can be used as a tool in sampling design by adjusting the sampling interval to suit the actual temporal variation in the monitoring area, in addition to being used for estimating the usefulness of previously collected data.     

被动采样在水体中有机污染监测的应用:以PAHs为例

半透膜采样技术是一种可原位、连续、动态监测水环境中非极性、弱极性有机污染物的被动采样技术,已在国内外发展20余年,但在环境监测中使用很少。从半透膜被动采样特点、采样器构造入手,着重对应用该技术的环节进行剖析,同时涉及被动采样结果及其评价方法。最后以多环芳烃（PAHs）为例,综述了近年来SPMD技术监控水体中非极性、弱极性有机污染物的常用分析技术及其发展。     

A diffusive sampling device for the determination of formaldehyde in air using N-methyl-4-hydrazino-7-nitrobenzofurazan (MNBDH) as reagent

A new method utilizing the diffusive sampling of formaldehyde in air has been developed. Formaldehyde is sampled with the use of a glass fiber filter impregnated with N-methyl-4-hydrazino-7-nitrobenzofurazan (MNBDH) and phosphoric acid. The formaldehyde hydrazone formed is desorbed from the filter with acetonitrile and determined by high-performance liquid chromatography (HPLC) with UV/visible detection at 474 nm. The sampling rate was determined to be 24.7 mL min-1 with a relative standard deviation of 7% for 48 experiments. The measured sampling rates were not dependent on the formaldehyde concentration (0.1-1.0 mg m-3), sampling time (15-482 min) or relative humidity (20-85%). The detection limit was 70 micrograms m-3 for a 15 min sampling period and 2 micrograms m-3 for an 8 h sampling period.     

美国EPA地表水质监测与评估的点位设计介绍

介绍了美国EPA地表水质监测与评估的点位设计。首先,指导性文件《基本水质监测方案》中的环境监测计划要求建立1个不少于1 000个点位的国家地表水质环境监测网,并提出了点位设计的标准,包括4点基本要求和针对每一类水域的具体要求。其次,另一指导性文件《准备州综合水质评估(305b报告)和电子升级:报告内容的准则》提出了1种新的对水质的综合性评估技术,要求在传统的判断点位设计的基础上增加概率统计点位设计方法。最后,全国一致的概率统计点位设计是相当有效的获知全国范围的水质情况及变化趋势的方法,EPA完全支持通过这种概率统计点位设计的方法来评估更多的水质状况。概率统计点位设计是EPA地表水质监测与评估的点位设计的发展趋势。     

Assessment of vehicular pollution in Kolkata, India, using CALINE 4 model

Michigan water quality standards for public bathing beaches require local health departments to collect and analyze a minimum of three water samples for Escherichia coli during each sampling event. The geometric mean number of E. coli colonies is then compared to the 300 colonies per 100 ml standard to determine compliance. This article compares the results of the currently mandated procedure to a composite sampling method, whereby the three samples are mixed in equal volumes and analyzed once. This effectively replaces the geometric mean of the individual sample results with an arithmetic mean. Although arithmetic means are more affected by outliers, this sensitivity to high concentrations is more health conservative than the geometric mean. During the 2007 sampling season, nine bathing beaches were monitored once each week. Three individual point samples and a composite sample were analyzed for each sampling event. No statistically significant differences in bacteria concentrations were found between composite sample analysis and the arithmetic mean of individual point sample analyses. No violations were detected in the 2007 sampling season, so using historical data, a retrospective analysis was performed on samples gathered at nine bathing beaches in Kalamazoo County, Michigan during the years 2001–2007. The arithmetic mean of the three samples taken at each site served as a surrogate composite sample. The benefits of compositing the three samples were investigated assuming a 2/3 reduction in analytical costs. In the traditional sampling method, three individual samples were obtained and analyzed once in every 3-week period during the summer season, whereas compositing was simulated by taking the arithmetic mean of each week’s results. The results of this retrospective cost analysis indicates that ten to 14 violations would have been missed using the less frequent traditional sampling and analysis methodology. Composite sampling is a cost-saving alternative to traditional sampling techniques that can be more protective of public health, particularly when the savings are applied to increased numbers of samples in time or space.     

Comparison of 24 h averaged VOC monitoring results for residential indoor and outdoor air using Carbopack X-filled diffusive samplers and active sampling--a pilot study

Analytical results obtained by thermal desorption GC/MS for 24 h diffusive sampling of 11 volatile organic compounds (VOCs) are compared with results of time-averaged active sampling at a known constant flow rate. Air samples were collected with co-located duplicate diffusive sampling tubes and one passivated canister. A total of eight multiple-component sampling events took place at fixed positions inside and outside three private homes. Subsequently, a known amount of sample air was transferred from the canister to an adsorbent tube for analysis by thermal desorption GC/MS. Results for the 11 most prevalent compounds--Freon 11, 1,3-butadiene, benzene, toluene, tetrachloroethene, ethylbenzene, m,p-xylene, o-xylene, 4-ethyltoluene, 1,3,5-trimethylbenzene, and p-dichlorobenzene--show that the ratio of average study values (diffusive sampling to active sampling) is 0.92 with 0.70 and 1.14 extreme ratios. Absolute percent difference for duplicate samples using diffusive sampling was <10% for the four most prevalent compounds. Agreement between the two sampling approaches indicates that the prediction of approximately constant diffusive sampling rates based on previous laboratory studies is valid under the field conditions.     

Improving suspended sediment measurements by automatic samplers

Suspended solids either as total suspended solids (TSS) or suspended sediment concentration (SSC) is an integral particulate water quality parameter that is important in assessing particle-bound contaminants. At present, nearly all stormwater runoff quality monitoring is performed with automatic samplers in which the sampling intake is typically installed at the bottom of a storm sewer or channel. This method of sampling often results in a less accurate measurement of suspended sediment and associated pollutants due to the vertical variation in particle concentration caused by particle settling. In this study, the inaccuracies associated with sampling by conventional intakes for automatic samplers have been verified by testing with known suspended sediment concentrations and known particle sizes ranging from approximately 20 μm to 355 μm under various flow rates. Experimental results show that, for samples collected at a typical automatic sampler intake position, the ratio of sampled to feed suspended sediment concentration is up to 6600% without an intake strainer and up to 300% with a strainer. When the sampling intake is modified with multiple sampling tubes and fitted with a wing to provide lift (winged arm sampler intake), the accuracy of sampling improves substantially. With this modification, the differences between sampled and feed suspended sediment concentration were more consistent and the sampled to feed concentration ratio was accurate to within 10% for particle sizes up to 250 μm.     

Development of active and diffusive sampling methods for determination of 3-methoxybutyl acetate in workplace air

Monitoring of the workplace concentration of 3-methoxybutyl acetate (MBA), which is used in printer's ink and thinner for screen-printing and as an organic solvent to dissolve various resins, is important for health reasons. An active and a diffusive sampling method, using a gas chromatograph equipped with a flame ionization detector, were developed for the determination of MBA in workplace air. For the active sampling method using an activated charcoal tube, the overall desorption efficiency was 101%, the overall recovery was 104%, and the recovery after 8 days of storage in a refrigerator was more than 90%. For the diffusive sampling method using the 3M 3500 organic vapor monitor, the MBA sampling rate was 19.89 cm(3) min(-1). The linear range was from 0.01 to 96.00 microg ml(-1), with a correlation coefficient of 0.999, and the detection limits of the active and diffusive samplers were 0.04 and 0.07 microg sample(-1), respectively. The geometric mean of stationary sampling and personal sampling in a screen-printing factory were 12.61 and 16.52 ppm, respectively, indicating that both methods can be used to measure MBA in workplace air.     

Aspiration and sampling efficiencies of the TSP and louvered particulate matter inlets

An experimental system was developed for the rapid measurement of the aspiration/transfer efficiency of aerosol samplers in a wind tunnel. We attempted to measure the aspiration and particle transfer characteristics of two inlets commonly used for sampling airborne Particulate Matter (PM): the 'Total Suspended Particulate' or TSP inlet, and the louvered 'dichotomous sampler inlet' typically used in sampling PM10 or PM2.5. We were able to determine the fraction of the external aerosol that enters the inlet and is transferred through it, and hence is available for collection by a filter, or further size fractionation into PM10 or PM2.5. This 'sampling efficiency' was analysed as a function of dimensionless aerodynamic parameters in order to understand the factors governing inlet performance. We found that for the louvered inlet the sampling efficiency increases as the external wind increases. Under all conditions expected in practical use the louvered inlet aspirates sufficient PM to allow either PM10 or PM2.5 to be selected downstream. The TSP inlet's sampling efficiency decreases with increasing external wind, and the TSP inlet is likely to under-sample the coarse end of the PM10 fraction at moderate and high external winds. As this inlet is generally not used with a downstream size fractionator, changes in sampling efficiency directly affect the measured aerosol concentration. We also investigated whether it is possible to dimensionally scale the PM inlets to operate at either higher or lower flow rates, while preserving the same sampling characteristics as the current full-scale, 16.67 L min(-1) versions. In the case of the louvered inlet, our results indicate that scaling to lower flow rates is possible; scaling to higher flow rates was not tested. For the TSP sampler, the sampling efficiency changes if the sampler is scaled to operate at smaller or larger flow rates, leading to unreliable performance.