Developing Effective Decision Support for the Application of “Gentle” Remediation Options: The GREENLAND Project

Gentle remediation options (GRO) are risk management strategies/technologies that result in a net gain (or at least no gross reduction) in soil function as well as risk management. They encompass a number of technologies, including the use of plant (phyto‐), fungi (myco‐), and/or bacteria‐based methods, with or without chemical soil additives or amendments, for reducing contaminant transfer to local receptors by in situ stabilization, or extraction, transformation, or degradation of contaminants. Despite offering strong benefits in terms of risk management, deployment costs, and sustainability for a range of site problems, the application of GRO as practical on‐site remedial solutions is still in its relative infancy, particularly for metal(loid)‐contaminated sites. A key barrier to wider adoption of GRO relates to general uncertainties and lack of stakeholder confidence in (and indeed knowledge of) the feasibility or reliability of GRO as practical risk management solutions. The GREENLAND project has therefore developed a simple and transparent decision support framework for promoting the appropriate use of gentle remediation options and encouraging participation of stakeholders, supplemented by a set of specific design aids for use when GRO appear to be a viable option. The framework is presented as a three phased model or Decision Support Tool (DST), in the form of a Microsoft Excel‐based workbook, designed to inform decision‐making and options appraisal during the selection of remedial approaches for contaminated sites. The DST acts as a simple decision support and stakeholder engagement tool for the application of GRO, providing a context for GRO application (particularly where soft end‐use of remediated land is envisaged), quick reference tables (including an economic cost calculator), and supporting information and technical guidance drawing on practical examples of effective GRO application at trace metal(loid) contaminated sites across Europe. This article introduces the decision support framework. ©2015 Wiley Periodicals, Inc.     

Feasibility study of preparation and certification of reference materials for nitrogen dioxide and sulfur dioxide in diffusive samplers

This paper presents the results of a feasability study for the preparation and certification of reference materials (RMs) for nitrogen dioxide (NO(2)) and sulfur dioxide (SO(2)) in diffusive samplers. RMs for NO(2) were prepared by exposure to gas mixtures in a chamber while the RMs for SO(2) were prepared by liquid spiking. Certification of RMs for NO(2) was found feasible with a certified uncertainty of 5.8% and a proposed shelf life of 5 years. The uncertainty was calculated with contribution from the homogeneity of preparation, stability and transport of the CRMs and from an external verification of the certified value. To reach 5.8% of uncertainty, the contribution of the differences between the results of analysis by ion chromatography and colorimetry must be eliminated. It is proposed to solve this by pre-extracting the samplers with water before analysis. The results of this study indicate that the samplers are stable for at least two years before and after exposure when stored in a refrigerator. By contrast, the certification of RMs for SO(2) was found to not be feasible due to instability problems. This instability was attributed to reaction of sulfate on the walls of the samplers. Alternatively, the preparation of RMs by simultaneous exposure to SO(2) and NO(2) has been tested. Satisfying homogeneities has been reached both for NO(2) and SO(2).     

Canopy Spectra and Remote Sensing of Ashe Juniper and Associated Vegetation

A study was conducted in central Texas to determine the potential of using remote sensing technology to distinguish Ashe juniper (Juniperus ashei Buchholz) infestations on rangelands. Plant canopy reflectance measurements showed that Ashe juniper had lower near-infrared reflectance than other associated woody plant species and lower visible reflectance than mixed herbaceous species in spring and summer. Ashe juniper could be distinguished on color-infrared aerial photographs acquired in March, April, June, and August and on QuickBird false color satellite imagery obtained in June, where it had a distinct dark reddish-brown tonal response. Unsupervised classification techniques were used to classify aerial photographic and satellite imagery of study sites. An accuracy assessment performed on a computer classified map of a photographic image showed that Ashe juniper had producer's and user's accuracies of 100% and 92.9%, respectively, whereas an accuracy assessment performed on a classified map of a satellite image of the same site showed that Ashe juniper had producer's and user's accuracies of 94.1% and 88.1%, respectively. Accuracy assessments performed on classified maps of satellite images of two additional study sites showed that Ashe juniper had producer's and user's accuracies that ranged from 87.1% to 96.4%. These results indicate that both color-infrared photography and false color satellite imagery can be used successfully for distinguishing Ashe juniper infestations.     

Soil distribution of fipronil and its metabolites originating from a seed-coated formulation

Seed-coating with the insecticide fipronil has been intensively used in sunflower cultivation to control soil pests such as wireworms. A research project was undertaken to determine the soil distribution of fipronil and of its main phenylpyrazole metabolites. Under agronomic conditions, the quantity of fipronil in the seed-coat (437 microg/seed) decreased continuously during the cultivation period (3.9 microg day(-1) during the first two months; 0.3 microg day(-1) during the next four months). At the end of the cultivation period, 42% of all phenylpyrazole compounds remained in the seed-coat. Fipro nil was poorly mobile in soil, and at the end of the cultivation period it was mostly concentrated in the soil layer close to the seed (3240 microg kg(-1) soil). Starting from the seed-coating, a fipronil concentration gradient was measured in the soil, up to a distance of 11 cm from the seed. Degradation in the soil occurred at a moderate rate, probably due to the fact that water solubilization of the solid active ingredient present in the seed coating was rate limiting. Indeed, after 6 months of cultivation, only 51% of the fipronil seed-coating was found in the soil, about 7% having been absorbed by the sunflower plant, and 42% remaining in the seed coat. The predominant metabolites produced in the soil were sulfone-fipronil, sulfide-fipronil and amide-fipronil, which were produced at average rates of 5 microg kg(-1) soil day(-1), 3 microg kg(-1) soil day(-1), and 0.4 microg kg(-1) soil day(-1), respectively. In contrast, the photoproduct, desulfinyl-fipronil, was barely detected. All phenylpyrazole compounds were poorly mobile, except for the amide derivative, which is devoid of insecticidal activity in marked contrast to the other metabolites. Furthermore, detectable soil contamination was limited to a zone of about 11 cm around the seed.     

Occurrence and fate of pesticides in four contrasting agricultural settings in the United States

Occurrence and fate of 45 pesticides and 40 pesticide degradates were investigated in four contrasting agricultural settings--in Maryland, Nebraska, California, and Washington. Primary crops included corn at all sites, soybeans in Maryland, orchards in California and Washington, and vineyards in Washington. Pesticides and pesticide degradates detected in water samples from all four areas were predominantly from two classes of herbicides--triazines and chloroacetanilides; insecticides and fungicides were not present in the shallow ground water. In most samples, pesticide degradates greatly exceeded the concentrations of parent pesticide. In samples from Nebraska, the parent pesticide atrazine [6-chloro-N-ethyl-N'-(1-methylethyl)-1,3,5-triazine-2,4-diamine] was about the same concentration as the degradate, but in samples from Maryland and California atrazine concentrations were substantially smaller than its degradate. Simazine [6-chloro-N,N'-diethyl-1,3,5-triazine-2,4-diamine], the second most detected triazine, was detected in ground water from Maryland, California, and Washington. Metolachlor [2-chloro-N-(2-ethyl-6-methylphenyl)-N-(2-methoxy-1-methylethyl)acetamide] rarely was detected without its degradates, and when they were detected in the same sample metolachlor always had smaller concentrations. The Root-Zone Water-Quality Model was used to examine the occurrence and fate of metolachlor at the Maryland site. Simulations accurately predicted which metolachlor degradate would be predominant in the unsaturated zone. In analyses of relations among redox indicators and pesticide variance, apparent age, concentrations of dissolved oxygen, and excess nitrogen gas (from denitrification) were important indicators of the presence and concentration of pesticides in these ground water systems.     

Estimates of animal methane emissions

The enteric methane emissions into the atmospheric annually from domestic animals total about 77 Tg. Another 10 to 14 Tg are likely released from animal manure disposal systems. About 95% of global animal enteric methane is from ruminants, a consequence of their large populations, body size and appetites combined with the extensive degree of anaerobic microbial fermentation occurring in their gut. Accurate methane estimates are particularly sensitive to cattle and buffalo census numbers and estimated diet consumption. Since consumption is largely unknown and must be predicted, accuracy is limited often by the information required, i.e., distribution of animals by class, weight and productivity. Fraction of the diet lost as enteric methane mostly falls into the range of 5.5–6.5% of gross energy intake for the world's cattle, sheep and goats. Manure methane emissions are heavily influenced by fraction of disposal by anaerobic lagoon. Non-ruminants, i.e., swine, become major contributors to these emissions.     

Assessment of uncertainty of NO2 measurements by the chemiluminescence method and discussion of the quality objective of the NO2 European Directive

Hereafter, an assessment of the ability of the chemiluminescence method to measure ambient NO2 with an accuracy within 15%, as requested by the data quality objective of European directive 1999/30/CE, is presented. In general, uncertainty is evaluated using the response to reference materials or by means of inter-comparisons used to determine some statistics like repeatability, reproducibility and calibration bias. These are incomplete approaches and the method of the Guide to the Expression of Uncertainty in Measurement, advised by the Directive, should be preferred. In fact, even if it requires a large data set, it allows the relative influence of all possible sources of uncertainty to be studied. The extent of NO2 uncertainty is mainly dependent on the level of NO. It is decreased by NOx and the correlation between NOx and NO. Furthermore, the uncertainty budget reveals that the contribution of accuracy of calibration standard, linearity, converter efficiency and drift of the analyser between calibration checks to the overall uncertainty is less important than the contribution of interference, mainly humidity and PAN in rural areas. The relative expanded uncertainty of the NO2 hourly average exceeds 30% for NO2 concentrations lower than 40 microg m(-3). Nevertheless, the data quality objective of 15% is reached for 200 microg m(-3), the hourly limit value of the European directive. On the contrary, at the limit value on the annual average, 40 microg m(-3), the data quality objective is not met if NO is higher than 100 microg m(-3). However, the data quality objective could be reached by correcting the measurements with the bias due to interference.     

profiling areas of ground water contamination by pesticides in california: phase ii – evaluation and modification of a statistical model

A well sampling study was conducted to evaluate anempirical approach to classifying areasof land in California as vulnerable to ground watercontamination by pesticides (Troiano et al., 1994). Wells were sampled from sections of land that had noprevious detections of pesticideresidues. The sections had been classified into vulnerablesoil clusters or into a not-classified groupusing a procedure based on Principal Components Analysis(PCA). Grape, citrus, and olive growingareas of Fresno and Tulare Counties were targeted, areas wherepre-emergence herbicide residues hadbeen detected in well water. Overall, herbicide residues weredetected in 75 of 176 sampled wells, ahigh frequency of detection in relation to results fromprevious targeted well sampling studies. Sinceresidues were also detected in the not-classified group, theclassification procedure was modified usingan approach based on Canonical Variates Analysis (CVA). Moresections were classified intovulnerable soil clusters with the CVA approach than with thePCA method. Data from two otherexplanatory variables, depth to ground water and amount ofpesticide used per section, were includedto illustrate how additional information can be incorporatedinto this approach of identifying vulnerable areas.     

a study of the temporal variability of atrazine in private well water. part ii: analysis of data

In 1988, the Iowa Department of Natural Resources, along withthe University of Iowa, conducted the Statewide Rural WellWater Survey, commonly known as SWRL. A total of 686private rural drinking water wells was selected by use of aprobability sample and tested for pesticides and nitrate. A subsetof these wells, the 10% repeat wells, were additionally sampledin October, 1990 and June, 1991. Starting in November, 1991,the University of Iowa, with sponsorship from the United StatesEnvironmental Protection Agency, revisited the 10% repeat wellsto begin a study of the temporal variability of atrazine and nitratein wells. Other wells, which had originally tested positive foratrazine in SWRL but were not in the 10% population, wereadded to the study population. Temporal sampling for a year-long period began in February of 1992 and concluded in Januaryof 1993. All wells were sampled monthly, a subset was sampledweekly, and a second subset was sampled for 14 day consecutiveperiods. Of the 67 wells in the 10% population tested monthly,7 (10.4%) tested positive for atrazine at least once during theyear, and 3 (4%) were positive each of the 12 months. Theaverage concentration in the 7 wells was 0.10 µg/L. Fornitrate, 15 (22%) wells in the 10% repeat population monthlysampling were above the Maximum Contaminant Level of 10 mg/L at least once. This paper, the second of two papers on thisstudy, describes the analysis of data from the survey. The firstpaper (Lorber et al., 1997) reviews the study design, theanalytical methodologies, and development of the data base.     

Use of cluster and principal component analyses to profile areas in California where ground water has been contaminated by pesticides

An empirical approach to profiling areas of ground water contamination by pesticides was devised that did not rely upon determining the level of vulnerability between land areas and that did not assume any particular pathway for ground water contamination. Climatic and soil data were obtained for 1-square mile sections of land in California where pesticide residues had been found in well water samples and the detection was attributed to legal agricultural applications. These sections were designated as known contaminated (KC) sections. Climate and soil data were also obtained for sections which lacked either well sampling data or a positive pesticide detection. These sections were designated as candidate sections. Statistical procedures were used to cluster groups of KC sections first with respect to climate characteristics and then with respect to soil characteristics. Principal components analysis (PCA) was used to construct a statistical profile of soil variables for each cluster of KC sections. A method based on the PCA was developed to compare the similarity of soil profiles derived for each KC section cluster to individual candidate sections. Since the profiling scheme was based only on data from KC sections, candidate sections that did not match any KC cluster profile could only be considered dissimilar to contaminated sections, receiving a status of not-classified. This profiling method is flexible and it can be revised to incorporate updated well sampling information.