Biotic and abiotic degradation of illicit drugs, their precursor, and by-products in soil

This study presents the first systematic information on the degradation patterns of clandestine drug laboratory chemicals in soil. The persistence of five compounds - parent drugs (methamphetamine, 3,4-methylenedioxymethamphetamine (MDMA)), precursor (pseudoephedrine), and synthetic by-products N-formylmethylamphetamine and 1-benzyl-3-methylnaphthalene) - were investigated in laboratory scale for 1 year in three different South Australian soils both under non-sterile and sterile conditions. The results of the degradation study indicated that 1-benzyl-3-methylnaphthalene and methamphetamine persist for a long time in soil compared to MDMA and pseudoephedrine; N-formylmethylamphetamine exhibits intermediate persistence. The role of biotic versus abiotic soil processes on the degradation of target compounds was also varied significantly for different soils as well as with the progress in incubation period. The degradation of methamphetamine and 1-benzyl-3-methylnaphthalene can be considered as predominantly biotic as no measureable changes in concentrations were recorded in the sterile soils within a 1 year period. The results of the present work will help forensic and environmental scientists to precisely determine the environmental impact of chemicals associated with clandestine drug manufacturing laboratories.     

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.     

Future landfill emissions and the effect of final cover installation--a case study

Municipal solid waste (MSW) landfills are potential long-term sources of emissions. Hence, they need to be managed after closure until they do not pose a threat to humans or the environment. The case study on the Breitenau MSW landfill was performed to evaluate future emission levels for this site and to illustrate the effect of final cover installation with respect to long-term environmental risks. The methodology was based on a comprehensive assessment of the state of the landfill and included analysis of monitoring data, investigations of landfilled waste, and an evaluation of containment systems. A model to estimate future emission levels was established and site-specific predictions of leachate emissions were presented based on scenario analysis. The results are used to evaluate the future pollution potential of the landfill and to compare different aftercare concepts in view of long-term emissions. As some leachable substances became available for water flow during cover construction due to a change in the water flow pattern of the waste, a substantial increase in leachate concentrations could be observed at the site (e.g. concentrations of chloride increased from 200 to 800 mg/l and of ammonia-nitrogen from 140 to about 500 mg/l). A period of intensive flushing before the final cover installation could have reduced the amount of leachable substances within the landfill body and rapidly decreased the leachate concentrations to 11 mg Cl/l and 79 mg NH₄-N/l within 50 years. Contrarily, the minimization of water infiltration is associated with leachate concentrations in a high range for centuries (above 400 mg Cl/l and 200 mg NH₄-N/l) with low concomitant annual emission loads (below 12 kg/year of Cl or 9 kg/year of NH₄-N, respectively). However, an expected gradual decrease of barrier efficiency over time would be associated with higher emission loads of 50 kg of chloride and 30 kg of ammonia-nitrogen at the maximum, but a faster decrease of leachate concentration levels.     

Spatial and seasonal variations in atrazine and metolachlor surface water concentrations in Ontario (Canada) using ELISA

Concerns regarding the impacts of pesticides on aquatic species and drinking water sources have increased demands on water quality monitoring programs; however the costs of sample analysis can be prohibitive. In this study we investigated enzyme-linked immunosorbent assay (ELISA) as a cost-effective, high through-put method for measuring pesticide concentrations in surface waters. Seven hundred and thirty-nine samples from 158 locations throughout Ontario were analysed for atrazine and metolachlor from April to October 2007. Concentrations ranged from <0.1 to 3.91 μg L⁻¹ (median = 0.12 μg L⁻¹) for atrazine and from <0.1 to 1.83 μg L⁻¹ (median = 0.09 μg L⁻¹) for metolachlor. Peak concentrations occurred in late spring/early summer, in rural agricultural locations, and decreased over the remainder of the growing season for both herbicides. About 3% of the samples that had ELISA results occurring above the limit of quantification (0.10 μg L⁻¹) were evaluated against gas chromatography-mass spectrometry (GC-MS). Linear regression analysis revealed a R² value of 0.88 and 0.39, for atrazine and metolachlor, respectively. ELISA tended to overestimate concentrations for atrazine and metolachlor, most likely because the ELISA kits also detect their metabolites. Atrazine data suggest that ELISA may be used complementary with GC-MS analysis to enhance the spatial and temporal resolution of a water quality monitoring study. The commercially available metolachlor ELISA kit requires further investigation. ELISA may be used to detect atrazine and metolachlor in surface water samples, but it is not recommended as a quantitative replacement for traditional analytical methods.     

Aggregation and ecotoxicity of CeO₂ nanoparticles in synthetic and natural waters with variable pH, organic matter concentration and ionic strength

The influence of pH (6.0-9.0), natural organic matter (NOM) (0-10 mg C/L) and ionic strength (IS) (1.7-40 mM) on 14 nm CeO₂ NP aggregation and ecotoxicity towards the alga Pseudokirchneriella subcapitata was assessed following a central composite design. Mean NP aggregate sizes ranged between 200 and 10000 nm. Increasing pH and IS enhanced aggregation, while increasing NOM decreased mean aggregate sizes. The 48 h-E_rC20s ranged between 4.7 and 395.8 mg CeO₂/L. An equation for predicting the 48 h-E_rC20 (48 h-E_rC20 = −1626.4 × (pH) + 109.45 × (pH)² + 116.49 × ([NOM]) − 14.317 × (pH) × ([NOM]) + 6007.2) was developed. In a validation study with natural waters the predicted 48 h-E_rC20 was a factor 1.08-2.57 lower compared to the experimental values.     

Guidance for performing footprint analyses and life‐cycle assessments for the remediation industry

The US Sustainable Remediation Forum (SURF) proposes a nine‐step process for conducting and documenting a footprint analysis and life‐cycle assessment (LCA) for remediation projects. This guidance is designed to assist remediation practitioners in evaluating the impacts resulting from potential remediation activities so that preventable impacts can be mitigated. Each of the nine steps is flexible and scalable to a full range of remediation projects and to the tools used by remediation practitioners for quantifying environmental metrics. Two fictional case studies are presented to demonstrate how the guidance can be implemented for a range of evaluations and tools. Case‐study findings show that greater insight into a study is achieved when the nine steps are followed and additional opportunities are provided to minimize remediation project footprints and create improved sustainable remediation solutions. This guidance promotes a consistent and repeatable process in which all pertinent information is provided in a transparent manner to allow stakeholders to comprehend the intricacies and tradeoffs inherent in a footprint analysis or LCA. For these reasons, SURF recommends that this guidance be used when a footprint analysis or LCA is completed for a remediation project. © 2011 Wiley Periodicals, Inc.     

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.     

Integrating the Social Dimension in Remediation Decision‐Making: State of the Practice and Way Forward

Sustainable remediation guidance, frameworks, and case studies have been published at an international level illustrating established sustainability assessment methodologies and successful implementation. Though the terminology and indicators evaluated may differ, one common theme among international organizations and regulatory bodies is more comprehensive and transparent methods are needed to evaluate the social sphere of sustainable remediation. Based on a literature review and stakeholder input, this paper focused on three main areas: (1) status quo of how the social element of sustainable remediation is assessed among various countries and organizations; (2) methodologies to quantitatively and qualitatively evaluate societal impacts; and (3) findings from this research, including challenges, obstacles, and a path forward. In conclusion, several existing social impact assessment techniques are readily available for use by the remediation community, including rating and scoring system evaluations, enhanced cost benefit analysis, surveys/interviews, social network analysis, and multicriteria decision analysis. In addition, a list of 10 main social indicator categories were developed: health and safety, economic stimulation, stakeholder collaboration, benefits community at large, alleviate undesirable community impacts, equality issues, value of ecosystem services and natural resources, risk‐based land management and remedial solutions, regional and global societal impacts, and contributions to other policies. Evaluation of the social element of remedial activities is not without challenges and knowledge gaps. Identification of obstacles and gaps during the project planning process is essential to defining sustainability objectives and choosing the appropriate tool and methodology to conduct an assessment. Challenges identified include meaningful stakeholder engagement, risk perception of stakeholders, and trade‐offs among the various triple bottom line dimensions. ©2015 Wiley Periodicals, Inc.     

Preventing corruption in humanitarian assistance: perceptions, gaps and challenges

Corruption is a threat to the purpose of humanitarian assistance. Until fairly recently, humanitarian assistance has not been considered an important arena in broader efforts aimed at curbing corruption, and corruption has not always been considered a particularly important concern for humanitarian assistance despite the obviously challenging nature of the context of humanitarian emergencies. Corruption, though, is a threat to humanitarian action because it can prevent assistance from getting to the people who most need it, and because it can potentially undermine public support for such assistance. This paper examines perceptions of corruption and its affects, documents best practices, and outlines gaps in understanding. It suggests recommendations for improving the capacity of humanitarian agencies to prevent and manage the risk of corruption. Agencies have taken steps to combat corruption and improve accountability--downwards and upwards--but scope remains for improvement and for greater sharing of learning and good practice.