Experimental Characterization of Atmospheric Diffusion in Complex Terrain with Land-Sea Interactions

The body of information presented in this paper is directed to scientists working in atmospheric dispersion research and model development. Two years of field measurements in the coastal area of Bilbao in northern Spain show that the diffusion behavior in this complex terrain can be classified into several well defined patterns, which correspond to certain meteorological conditions. The approach taken has been the systematic use of SO₂ remote sensors (COSPEC) and ground level monitors in moving platforms which are used to follow and document the flow of the air mass. Results to date show that complex reentry cycles can occur and that synoptically different flows may be indistinguishable by wind sensors at ground level (affected by channeling), and yet result in totally different observed pollution levels by a fixed monitoring network (affected by topographical effects). These results are being used to parameterize the cause-effect relationships and guide the modeling efforts in this area of complex terrain.     

Field intercomparison of precipitation measurements performed within the framework of the Pan European Intensive Monitoring Program of EU/ICP Forest

A 6-month field intercomparison study on precipitation measurements was performed at Schagerbrug near the west coast in the Netherlands. Twenty bulk sampling systems and two wet-only samplers were evaluated on accuracy, sampling strategy and performance under field conditions. Bulk precipitation fluxes of NO3-, NH4+, H+ and Kjeldahl-N generally could be determined with a greater accuracy than bulk precipitation fluxes of SO4(2-), Na+, Cl-, Mg2+, Ca2+, Alkalinity and H+. Bulk precipitation fluxes of K+ generally had the lowest accuracy. Only 20% of the sampling systems differed less than 10% from the best estimate, whereas most systems (60%) differed more than 20% from the best estimate. The inaccuracy induced by the sampling system appeared to be much larger than that resulting from the analysis of the samples by different laboratories as determined by ring-tests.     

Field intercomparison of throughfall measurements performed within the framework of the Pan European intensive monitoring program of EU/ICP Forest

A 6-month field intercomparison study on throughfall measurements was performed at Speulder forest near the west coast in The Netherlands. Twenty throughfall sampling systems were evaluated on accuracy, sampling strategy and performance under field conditions. Throughfall fluxes of NO3-, K+ and Kjeldahl-N generally could be determined with a larger accuracy than fluxes of SO4(2-), NH4+, Na+, Cl-, Mg2+, Ca2+, and alkalinity. Throughfall fluxes of H+ generally had the lowest accuracy. Only 20% of the sampling systems differed more than 20% from the best estimate, whereas 45% of the systems stayed within a 10% range from the best estimate. The difference from the best estimate was mainly caused by aspects related to sampling strategy, like, for example, collecting area, sampler placement. The inaccuracy induced by the sampling system appeared to be much larger than that resulting from the analysis of the samples by different laboratory as determined by ring-tests. The field intercomparison described in this article gave a good insight in the different aspects contributing to the overall accuracy of the measurements. However, performing a future field intercomparison is recommended for throughfall and stemflow in order to also take in account other aspects that might influence the performance of the different measurement systems (e.g. tree species, climate zone, summer/winter period).     

Evaluation of the measurement uncertainty in automated long-term sampling of PCDD/PCDFs

Since the publication of the first version of European standard EN-1948 in 1996, long-term sampling equipment has been improved to a high standard for the sampling and analysis of polychlorodibenzo-p-dioxin (PCDD)/polychlorodibenzofuran (PCDF) emissions from industrial sources. The current automated PCDD/PCDF sampling systems enable to extend the measurement time from 6–8 h to 15–30 days in order to have data values better representative of the real pollutant emission of the plant in the long period. EN-1948:2006 is still the European technical reference standard for the determination of PCDD/PCDF from stationary source emissions. In this paper, a methodology to estimate the measurement uncertainty of long-term automated sampling is presented. The methodology has been tested on a set of high concentration sampling data resulting from a specific experience; it is proposed with the intent that it is to be applied on further similar studies and generalized. A comparison between short-term sampling data resulting from manual and automated parallel measurements has been considered also in order to verify the feasibility and usefulness of automated systems and to establish correlations between results of the two methods to use a manual method for calibration of automatic long-term one. The uncertainty components of the manual method are analyzed, following the requirements of EN-1948-3:2006, allowing to have a preliminary evaluation of the corresponding uncertainty components of the automated system. Then, a comparison between experimental data coming from parallel sampling campaigns carried out in short- and long-term sampling periods is realized. Long-term sampling is more reliable to monitor PCDD/PCDF emissions than occasional short-term sampling. Automated sampling systems can assure very useful emission data both in short and long sampling periods. Despite this, due to the different application of the long-term sampling systems, the automated results could not be directly compared with manual results, not even in terms of measurement uncertainty. This investigation focuses on both uncertainty and repeatability of the automated sampling method. The standard 20988, developed by Internarional Organization of Standardization (ISO) can be used to estimate the measurement uncertainty. The results confirm that the uncertainties of manual and automated methods are comparable. At the same time, it is not appropriate to consider the manual method as a reference for the evaluation of the uncertainty of the automated sampling system, due to the high variability of both systems.     

A passive flux denuder for evaluating emissions of ammonia at a dairy farm

Passive samplers have been shown to be an inexpensive alternative to direct sampling. Diffusion denuders have been developed to measure the concentration of species such as ammonia (NH3), which is in equilibrium with particulate ammonium nitrate. Conventional denuder sampling has required active sampling that inherently requires air pumps and, therefore, electrical power. To estimate emissions of NH3 from a fugitive source would require an array of active samplers and meteorological measurements to estimate the flux. A recently developed fabric denuder was configured in an open tube to passively sample NH3 flux. Passive and active samplers were collocated at a dairy farm at the California State University, Fresno, Agricultural Research Facility. During this comparison study, NH3 flux measurements were made at the dairy farm lagoon before and after the lagoon underwent acidification. Comparisons were made of the flux measurements obtained directly from the passive flux denuder and those calculated from an active filter pack sampler and wind velocity. The results show significant correlation between the two methods, although a correction factor needed to be applied to directly compare the two techniques. This passive sampling approach significantly reduces the cost and complexity of sampling and has the potential to economically develop a larger inventory base for ambient NH3 emissions.     

Estimation of uncertainty arising from different soil sampling devices: the use of variogram parameters

In the frame of the international SOILSAMP project, funded and coordinated by the National Environmental Protection Agency of Italy (APAT), uncertainties due to field soil sampling were assessed. Three different sampling devices were applied in an agricultural area using the same sampling protocol. Cr, Sc and Zn mass fractions in the collected soil samples were measured by k(0)-instrumental neutron activation analysis (k(0)-INAA). For each element-device combination the experimental variograms were calculated using geostatistical tools. The variogram parameters were used to estimate the standard uncertainty arising from sampling. The sampling component represents the dominant contribution of the measurement uncertainty with a sampling uncertainty to measurement uncertainty ratio ranging between 0.6 and 0.9. The approach based on the use of variogram parameters leads to uncertainty values of the sampling component in agreement with those estimated by replicate sampling approach.     

Simultaneous sampling of gas- and aerosol-phase TDI with a triple filter system

A new triple filter system sampler/model is proposed for the precise and accurate simultaneous sampling and determination of gas- and aerosol-phase 2,4-toluene diisocyanate (TDI). The system consists of two front Teflon filters for sampling aerosol-phase TDI and a final coated glass fiber filter to collect gas-phase TDI. The aerosol-phase TDI is collected on the first Teflon filter, while the second Teflon filter is used to estimate gaseous TDI adsorbed by the first. According to the gas adsorption test of two Teflon filters in series, the TDI gas adsorption fraction of the two filters is almost the same. Results of the evaporation test using pure TDI aerosols collected on the Teflon filter show that significant evaporation of the compound does not occur during sampling. These two findings allow the use of a model to estimate accurate gas- and aerosol-phase TDI concentrations. The comparison test with an annular denuder shows that the triple filter system can minimize the TDI sampling bias between the dual filter and the annular denuder systems.     

Correction methods for organic carbon artifacts when using quartz-fiber filters in large particulate matter monitoring networks: the regression method and other options

Sampling and handling artifacts can bias filter-based measurements of particulate organic carbon (OC). Several measurement-based methods for OC artifact reduction and/or estimation are currently used in research-grade field studies. OC frequently is not artifact-corrected in large routine sampling networks (e.g., U.S. Environmental Protection Agency (EPA)'s Chemical Speciation Network). In some cases, the OC artifact has been corrected using a regression method (RM) for artifact estimation. In this method, the gamma-intercept of the regression of the OC concentration on the fine particle (PM2.5) mass concentration is taken to be an estimate of the average OC sampling artifact (net of positive and negative artifacts). This paper discusses options for artifact correction in large routine sampling networks. Specifically, the goals are to (1) articulate the assumptions and limitations inherent to the RM, (2) describe other artifact correction approaches, and (3) suggest a cost-effective method for artifact correction in large monitoring networks. The RM assumes a linear relationship between measured OC and PM mass: a constant slope (OC mass fraction) and a constant intercept (RM artifact estimate). These assumptions are not always valid. Additionally, outliers and other individual data points can have a large influence on the RM artifact estimates. The RM yields results within the range of measurement-based methods for some datasets and not for others. Given that the adsorption of organic gases increases with atmospheric concentrations of organics, subtraction of an average artifact from all samples (e.g., across multiple sites) will underestimate OC for lower-concentration samples (e.g., clean sites) and overestimate OC for higher-concentration samples (e.g., polluted sites). For relatively accurate, simple, and cost-effective artifact OC estimation in large networks, the authors suggest backup filter sampling on at least 10% of sampling days at all sites with artifact correction on a sample-by-sample basis as described herein.     

A Passive Flux Denuder for Evaluating Emissions of Ammonia at a Dairy Farm

Abstract

Passive samplers have been shown to be an inexpensive alternative to direct sampling. Diffusion denuders have been developed to measure the concentration of species such as ammonia (NH₃), which is in equilibrium with particulate ammonium nitrate. Conventional denuder sampling that inherently requires air pumps and, therefore, electrical power. To estimate emissions of NH₃ from a fugitive source would require an array of active samplers and meteorological measurements to estimate the flux. A recently developed fabric denuder was configured in an open tube to passively sample NH₃ flux. Passive and active samplers were collocated at a dairy farm at the California State University, Fresno, Agricultural Research Facility. During this comparison study, NH₃ flux measurements were made at the dairy farm lagoon before and after the lagoon underwent acidification. Comparisons were made of the flux measurements obtained directly from the passive flux denuder and those calculated from an active filter pack sampler and wind velocity. The results show significant correlation between the two methods, although a correction factor needed to be applied to directly compare the two techniques. This passive sampling approach significantly reduces the cost and complexity of sampling and has the potential to economically develop a larger inventory base for ambient NH₃ emissions.     

Simultaneous Sampling of Gas- and Aerosol-Phase TDI with a Triple Filter System

Abstract

A new triple filter system sampler/model is proposed for the precise and accurate simultaneous sampling and determination of gas- and aerosol-phase 2,4-toluene diisocyanate (TDI). The system consists of two front Teflon filters for sampling aerosol-phase TDI and a final coated glass fiber filter to collect gas-phase TDI. The aerosol-phase TDI is collected on the first Teflon filter, while the second Teflon filter is used to estimate gaseous TDI adsorbed by the first. According to the gas adsorption test of two Teflon filters in series, the TDI gas adsorption fraction of the two filters is almost the same. Results of the evaporation test using pure TDI aerosols collected on the Teflon filter show that significant evaporation of the compound does not occur during sampling. These two findings allow the use of a model to estimate accurate gasand aerosol-phase TDI concentrations. The comparison test with an annular denuder shows that the triple filter system can minimize the TDI sampling bias between the dual filter and the annular denuder systems.     

Calibration of the Chemcatcher passive sampler for monitoring selected polar and semi-polar pesticides in surface water

Passive sampling is a powerful method for continuous pollution monitoring, but calibration experiments are still needed to generate sampling rates in order to estimate water concentrations for polar compounds. We calibrated the Chemcatcher device with an uncovered SDB-XC Empore disk as receiving phase for 12 polar and semi-polar pesticides in aquatic environments in flow-through tank experiments at two water flow velocities (0.135 m/s and 0.4 m/s). In the 14-day period of exposure the uptake of test substances in the sampler remained linear, and all derived sampling rates R(s) were in the range of 0.1 to 0.5 L/day. By additionally monitoring the release of two preloaded polar pesticides from the SDB-XC disks over time, very high variation in release kinetics was found, which calls into question the applicability of performance reference compounds. Our study expands the applicability of the Chemcatcher for monitoring trace concentrations of pesticides with frequent occurrence in water.     

Pesticide residues in products of plant origin in the European Union

The results of a co-ordinated monitoring programme for pesticide residues in the European Union and Norway carried out in 1996 and 1997 are presented. The aim of this programme is to work towards a system, which makes it possible to estimate actual dietary pesticide intake for the population of the European Union. Based on a statistically dérived sampling plan and within the limited number of pesticides/commodities analysed, the most critical pesticides (benomyl group and dithiocarbamates) and commodities (mandarine and lettuce) were identified. In case of detected non-compliances, repeated sampling and, if necessary, enforcement actions are to be taken by national authorities. The programme will be continued in the next years.     

Intrasite sampling of Hong Kong soils contaminated by Caesium-137

Previous measurements of soil contamination by Caesium-137 (137Cs) in Hong Kong have been used both to estimate background levels prior to the construction of the Guangdong Nuclear Power Station (GNPS) at Daya Bay and to evaluate health hazards arising from the radionuclide. These measurements are reviewed and contrasted with recent advances in understanding of 137Cs distribution in soil. Preliminary research findings are used to illustrate the microscale variability of 137Cs in the Hong Kong environment and to suggest intrasite sampling methods for establishing suitable reference values.     

Sampling duration calculations

Routine air quality monitoring produces filter samples that, when analyzed, yield the total amount of the aerosol present in the volume of air drawn by the pump in the monitoring device during the given sampling period. From this we obtain an average concentration of the aerosol for the given duration. The samples are therefore really aggregate samples. A natural question then is "what is the effect of the duration of aggregation on the accuracy and precision of the estimate of the quantity of interest?" The answer depends on a number of factors, such as the quantity that is being estimated: a mean, or an extreme value, or some other quantity; the nature of the measurement error--additive versus multiplicative; the costs of laboratory analyses, and so on. In this paper, we investigate these issues when the interest is in estimating the mean concentration of a specified aerosol species over a fixed time period. In particular, we propose a method for determining a sampling duration that will yield the "best estimate" of the mean concentration for a given cost whenever appropriate statistical assumptions hold.     

Distribution of pesticide residues in soil and uncertainty of sampling

Pesticide residues were determined in about 120 soil cores taken randomly from the top 15 cm layer of two sunflower fields about 30 days after preemergence herbicide treatments. Samples were extracted with acetone-ethyl acetate mixture and the residues were determined with GC-TSD. Residues of dimethenamid, pendimethalin, and prometryn ranged from 0.005 to 2.97 mg/kg. Their relative standard deviations (CV) were between 0.66 and 1.13. The relative frequency distributions of residues in soil cores were very similar to those observed in root and tuber vegetables grown in pesticide treated soils. Based on all available information, a typical CV of 1.00 was estimated for pesticide residues in primary soil samples (soil cores). The corresponding expectable relative uncertainty of sampling is 20% when composite samples of size 25 are taken. To obtain a reliable estimate of the average residues in the top 15 cm layer of soil of a field up to 8 independent replicate random samples should be taken. To obtain better estimate of the actual residue level of the sampled filed would be marginal if larger number of samples were taken.     

Estimating the spatial scale of herbicide and soil interactions by nested sampling, hierarchical analysis of variance and residual maximum likelihood

An unbalanced nested sampling design was used to investigate the spatial scale of soil and herbicide interactions at the field scale. A hierarchical analysis of variance based on residual maximum likelihood (REML) was used to analyse the data and provide a first estimate of the variogram. Soil samples were taken at 108 locations at a range of separating distances in a 9 ha field to explore small and medium scale spatial variation. Soil organic matter content, pH, particle size distribution, microbial biomass and the degradation and sorption of the herbicide, isoproturon, were determined for each soil sample. A large proportion of the spatial variation in isoproturon degradation and sorption occurred at sampling intervals less than 60 m, however, the sampling design did not resolve the variation present at scales greater than this. A sampling interval of 20-25 m should ensure that the main spatial structures are identified for isoproturon degradation rate and sorption without too great a loss of information in this field.     

Sampling Duration Calculations

ABSTRACT

Routine air quality monitoring produces filter samples that, when analyzed, yield the total amount of the aerosol present in the volume of air drawn by the pump in the monitoring device during the given sampling period. From this we obtain an average concentration of the aerosol for the given duration. The samples are therefore really aggregate samples. A natural question then is “what is the effect of the duration of aggregation on the accuracy and precision of the estimate of the quantity of interest?” The answer depends on a number of factors, such as the quantity that is being estimated: a mean, or an extreme value, or some other quantity; the nature of the measurement error—additive versus multiplicative; the costs of laboratory analyses, and so on. In this paper, we investigate these issues when the interest is in estimating the mean concentration of a specified aerosol species over a fixed time period. In particular, we propose a method for determining a sampling duration that will yield the “best estimate” of the mean concentration for a given cost whenever appropriate statistical assumptions hold.     

Source estimation methods for atmospheric dispersion

Both forward and backward transport modeling methods are being developed for characterization of sources in atmospheric releases of toxic agents. Forward modeling methods, which describe the atmospheric transport from sources to receptors, use forward-running transport and dispersion models or computational fluid dynamics models which are run many times, and the resulting dispersion field is compared to observations from multiple sensors. Forward modeling methods include Bayesian updating and inference schemes using stochastic Monte Carlo or Markov Chain Monte Carlo sampling techniques. Backward or inverse modeling methods use only one model run in the reverse direction from the receptors to estimate the upwind sources. Inverse modeling methods include adjoint and tangent linear models, Kalman filters, and variational data assimilation, among others.This survey paper discusses these source estimation methods and lists the key references. The need for assessing uncertainties in the characterization of sources using atmospheric transport and dispersion models is emphasized.     

The seasonal cycles and photochemistry of C2–C5 alkanes at Mace Head

Continuous in-situ measurements of NMHCs at Mace Head, Ireland during two full annual cycles from January 2005 to January 2007 were used to investigate NMHC emission sources and transport including dilution and photochemical oxidation. The Mace Head research station is ideally located to sample a wide range of air masses including polluted European transport, clean North Atlantic and Arctic air masses and the ultra-clean, Southern Atlantic air masses. The variety in air mass sampling is used to investigate interaction of emissions, transport, dilution and photochemistry. Variability of long-lived hydrocarbon ratios is used to assess and estimate typical transport times from emission source to the Mace Head receptor. Seasonality in the ratios of isomeric alkane pairs (for butane and pentanes) are used to assess the effects of atmospheric transport and photochemical ageing. Finally, the natural logarithms of NMHC ratios are used to assess photochemical oxidation.     

Note on a Method to Estimate Missing Air Pollution Data

An iterative regression procedure is presented to estimate missing air pollution measurements when the data are measured at two or more sampling stations in the same vicinity. The procedure utilizes the measurements taken at other stations, on neighboring days, and of other pollutants.

The procedure is applied to a set of Philadelphia pollution data with from five to seventeen per cent of the observations missing. The method is tested by comparing the known observed pollutant values, with their estimates given by the procedure. Correlations between the observations and their estimates are uniformly high, ranging from 0.87 to 0.91. These correlations compare favorably with those estimates given by a simple linear interpolation. The magnitude of the correlations suggests that estimates given by this iterative regression procedure may be used where missing observations pccur without fear of undesirable effects on subsequent work. Therefore, this procedure may be a valuable tool in handling the problem of missing observations in air pollution data.