Modeling rhizofiltration: heavy-metal uptake by plant roots

The discovery of phytoaccumulation potential of plant species has led to its application for remediation of heavy-metal-contaminated soil and wastewater, which is termed as phytoextraction/rhizofiltration. For prediction, analysis, planning and cost-effective design of such systems, mathematical models not only are used as a screening tool but also provide optimal parameters like harvesting time, irrigation schedule, etc. Several laboratory and field scale studies have been carried out in the past, and mathematical expressions have been developed by various researchers for different phenomena like metal adsorption in soil, plant root growth with time, moisture and metal uptake by plant root, moisture movement in unsaturated zone, soil moisture relationship, etc. The complete design of any such phytoremediation program would require the knowledge of behavior of heavy-metal movement in soil, water and plant root system. In this paper, a model for simulating heavy-metal dynamics in soil, water and plant root system is developed and discussed. The governing non-linear partial differential equation is solved numerically by implicit finite difference method using Picard's iterative technique, and the formulation has been illustrated using a characteristic example. The source code is written in MATLAB.     

A ten channel fibre-optic device for distributed sensing of underground hydrocarbon leakage

With millions of fuel storage tanks and oil pipelines installed around the world, there is inevitably frequent leakage of potentially hazardous hydrocarbons. As many of these installations are below ground, it can often be many years before the extent of the leak is discovered. We have previously reported the development of a sensor for the detection of such subterranean leaks, using infrared reflectometry to interrogate a hydrocarbon sensitive membrane. However, a single sensor cannot provide any information about the flow rate or direction of the leak. This paper describes the extension of the technology to a multi-channel distributed sensing system, using optical fibres capable of distributing the sensors over large subterranean areas. Results are reported from the evaluation of the device, which consisted of monitoring the movement of different hydrocarbons (gasoline, diesel and insulating oil) through a vertical sand-filled vessel.     

Detecting and characterising sources of persistent organic pollutants (PAHs and PCBs) in surface sediments of an industrialized area (harbour of Trieste, northern Adriatic Sea)

A sediment sampling based on a two-dimensional mapping was performed in the harbour of Trieste (northern Adriatic Sea), considering 28 sites exposed to pollutant inputs from harbour and industrial activities. Polycyclic aromatic hydrocarbons (PAHs) and polychlorinated biphenyls (PCBs) were determined in surface sediments, because these very persistent pollutants seem to be responsible for the depletion of benthic populations observed in this area. The correlation matrix indicates that PAHs and PCBs are non-correlated, and probably have different sources. Both cluster analysis performed on the sampling sites and graphical drawing of the PAH sediment contents make it possible to locate along the shoreline a band of more polluted sediments, clustered around a site facing a steelmaking factory, to be considered as the main source point for PAHs. The evaluation of phenanthrene to anthracene (P/AN) and fluoranthene to pyrene (FL/PY) ratios permits the assessment of the pyrolytic, industrial origin of these PAHs, rejecting a second possible source of hydrocarbons (i.e., an oil-pipeline terminal, situated near the steelmaking factory). Graphical drawing of the total PCB iso-concentrations reveals a different source-point for this other category of very persistent pollutants.     

Accuracy and traceability in environmental monitoring--pitfalls in methylmercury determinations as a case study

The concepts of accuracy and traceability as applied to environmental analysis are still prone to misunderstandings. While accuracy refers to the closeness of analytical values to "true values" (trueness) and among various repetitions (precision), the term traceability implies a link of data obtained to established references through an unbroken chain of comparisons all with stated uncertainties. These misunderstandings, possibly occurring among the analytical community, may have consequences on environmental data interpretation. Recent discussions in the field of environmental speciation analysis illustrated that accuracy and traceability issues are still not firmly established within the environmental chemistry community. This paper discusses this issue, taking methylmercury as a case study.     

Organochlorine contaminants in seabird eggs from the Pacific coast of Canada, 1971–1986

Eggs were collected from seven seabird species at colonies on the British Columbia coast from 1983 to 1986 and analyzed for organochlorine contaminants. Total PCB levels (wet weight) were highest in double-crested cormorants (Phalacrocorax auritus) from the Fraser estuary (2.91 mg kg^-1) and the Strait of Georgia (3.79 mg kg^-1). Highest DDE levels were in fork-tailed storm-petrels (Oceanodroma furcata) from the Queen Charlotte Islands (1.68 mg kg^-1). Organochlorine levels were generally lower in eggs from the mid 1980s than in those collected in the early 1970s. Organochlorine levels in Pacific alcids and hydrobatids foraging in offshore locations were compared to those in the same or ecologically similar species from the Canadian Atlantic coast. DDT- and HCH-related compounds were higher in Pacific populations while levels of dieldrin, oxychlordane, and HCB were generally lower. With the exception of -HCH, levels of all measured organochlorines were lower in cormorants breeding in the Fraser River estuary than in cormorants from the St. Lawrence River estuary on the Atlantic coast.     

Water quality test based on dielectrophoretic measurements of fresh water algae Selenastrum capricornutum

A method is described whereby dielectrophoresis of algal cells is used to perform rapid water quality analysis, specifically detecting the presence of CuSO4. The dielectric collection spectrum of the fresh water alga Selenastrum capricornutum was determined for a range of concentrations of CuSO4 from 25 mg L(-1) to 0.25 mg L(-1) for exposure times of 15 min and 18 h. In all cases increasing the concentration of CuSO4 reduced cell collection, but a step reduction was observed in collection between 2 mg L(-1) and 5 mg L(-1). This method has potential for forming a rapid, low-cost test for water quality with broad specificity and significantly reduced analysis time compared to current methods.     

Determination of biomass burning emission factors: Methods and results

Biomass burning, in a broad sense, encompasses different burning practices, including open and confined burnings, and different types of vegetation. Emission factors of gaseous or particulate trace compounds are directly dependent both on the fuel type and the combustion process. Emission factors are generally calculated by stoichiometric considerations using the carbon mass balance method, applied either to combustion chamber experiments or to field experiments based on ground-level measurements or aircraft sampling in smoke plumes. There have been a number of experimental studies in the last 10 years to investigate wildfires in tropical, temperate, or boreal regions. This article presents an overview of measurement methods and experimental data on emission factors of reactive or radiatively active trace compounds, including trace gases and particles. It focuses on fires in tropical regions, that is, forest and savanna fires, agricultural burns, charcoal production, use of fuelwood, and charcoal combustion.     

Factor analysis of trace-element data from tree-bark samples in The Netherlands

Monte Carlo-assisted factor analysis has been applied to a data set of 20 trace-element concentrations in tree-bark samples obtained from 123 locations in The Netherlands, with the aim to investigate the suitability of bark as a biomonitor for air pollution. A Monte Carlo approach was used to give more insight to the uncertainties and significance levels of the factor analysis results. Notwith-standing a rather strong influence of soil material on the concentration levels, factor analysis enabled the identification of five significant pollution source types, all of which corresponded with source types found in an earlier biomonitoring study in The Netherlands using epiphytic lichens. A more detailed comparison with the lichen results showed a remarkable difference in lead concentrations between bark and lichen. It was concluded that bark can be successfully employed as a biomonitor for air pollution. The power of factor analysis to adequately determine the soil contribution may render extensive sample washing procedures superfluous.     

Characterizing soils for hazardous waste site assessments

This paper provides a review and justification of the minimum data needed to characterize soils for hazardous waste site assessments and to comply with the Comprehensive Environmental Response, Compensation and Liability Act (CERCLA). Scientists and managers within the regulatory agency and the liable party need to know what are the important soil characteristics needed to make decisions about risk assessment, what areas need remediation and what remediation options are available. If all parties involved in characterizing a hazardous waste site can agree on the required soils data set prior to starting a site investigation, data can be collected in a more efficient and less costly manner. Having the proper data will aid in reaching decisions on how to address concerns at, and close-out, hazardous waste sites.This paper was prepared to address two specific concerns related to soil characterization for CERCLA remedial response. The first concern is the applicability of traditional soil classification methods to CERCLA soil characterization. The second is the identification of soil characterization data type required for CERCLA risk assessment and analysis of remedial alternatives. These concerns are related, in that the Data Quality Objective (DQO) process addresses both. The DQO process was developed in part to assist CERCLA decision-makers in identifying the data types, data quality, and data quantity required to support decisions that must be made during the remedial investigation/feasibility study (RI/FS) process. Data Quality Objectives for Remedial Response Activities: Development Process (US EPA, 1987a) is a guidebook on developing DQOs. This process as it relates to CERCLA soil characterization is discussed in the Data Quality Objective Section of this paper.