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.     

Further studies using X-ray fluorescence to sample lead contaminated carpeted surfaces

The sampling of carpeted surfaces to test for lead contamination primarily focuses upon vacuum techniques. Vacuum sampling techniques, however, require time-consuming, expensive laboratory analysis of the dusts obtained and are unable to determine total lead load on the carpet. X-ray fluorescence (XRF) analysis is an on-site, inexpensive, non-destructive, quick technique for predicting metals levels in a variety of media, such as water, soil, filter paper and painted surfaces. A 1992 study of the feasibility of XRF to analyze for lead and soil loadings on carpeted surfaces indicated that XRF can detect lead at a low enough level to warrant further study. This paper expands this earlier study and developes lead and soil loading calibration curves for three different carpet types based upon XRF lead L-beta peak areas and XRF iron and barium K-alpha peak and background areas. Results indicate that variation in the data can be reduced through modifications of the XRF analysis technique, thus reducing the statistically determined detection level, and that carpet type does affect the calibration. Detection levels of approximately 70 mg/m² for lead and 5 g/m² for soil were obtained. Overall, good agreement was found between results of this study and the earlier one. XRF shows excellent potential for quantitative analysis of lead on carpeted surfaces.     

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.     

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.     

Patchy distributions: Optimising sample size

A method for estimating sample size which does not require an a priori definition of desired precision, or the assumption that the population is normally distributed with constant variance, has recently been proposed. This paper discusses this method and presents five modifications which make the method easier to use and reduce the probability of estimating a larger sample size than is actually required. The method is extended and used to estimate the mean abundance of patchily distributed benthic organisms. The technique can be used to guide the design of any environmental sampling programme, be it physical, chemical or biological, where comparisons between times and/or locations are required. Trade-offs between numbers of replicates and numbers of levels/sites are discussed.     

Emissions of gaseous and particulate pollutants in a port and harbour region in India

Ports can generate large quantity of pollutants in the atmosphere due to various activities like loading and unloading,transportation, and construction operations. Determination of the character and quantity of emissions from individual sources is an essential step in any project to control and minimize the emissions.In this study a detailed emission inventory of total suspendedparticulate matter (TSP), particulate matter less than 10 m(PM₁₀), sulfur dioxide (SO₂) and nitrogen oxides (NO_x) for a port and harbour project near Mumbai is compiled. Results show that the total annual average contributions of TSP and PM₁₀ from all the port activitieswere 872 and 221 t yr^-1, respectively. Annual average emissions of gaseous pollutants SO₂ and NO_xwere 56 and 397 t yr^-1, respectively, calculatedby using emission factors for different port activities. The maximum TSP emission (419 t yr ^-1) was from paved roads, while the least (0.4 t yr^-1) was from bulk handling activity. The maximum PM₁₀ emission (123 t yr^-1) was from unpaved roads and minimum (0.2 t yr^-1) from bulk handling operations. Similarly the ratio of TSP and PM₁₀ emission was highest (5.18) from paved roads and least (2.17) from bulk handling operations. Regression relation was derivedfrom existing emission data of TSP and PM₁₀ from variousport activities. Good correlation was observed between TSP andPM₁₀ having regression coefficient >0.8.     

Fate and movement of atrazine, cyanazine, metolachlor and selected degradation products in water resources of the deep Loess Hills of Southwestern Iowa, USA

The environmental fate and movement of herbicides widely used for weed control in corn are assessed for a deep loess soil in southwestern Iowa. Beginning in the early 1980s, the herbicide-based weed control program emphasized the application of atrazine (ATR) or cyanazine (CYN) and metolachlor (MET) for both broadleaf and grass control. Between 1992 and 1995, concentrations of ATR, desethylatrazine (DEA), desisopropylatrazine (DIA), CYN and MET were measured in rainwater, both shallow and deep vadose zone water, and well water. Results show that the frequency of herbicide detections and the range and distribution of occurrences are dependent upon both landscape position and temporal inputs of recharge water from rainfall. Generally, DIA was observed more frequently and in higher mean concentration in well water than DEA, while DEA was observed more frequently than DIA in vadose zone groundwater. A chromatographic analogy is suggested to explain the occurrence patterns observed for both parent herbicide and degradation products within the unsaturated zone water. Analysis of rainwater samples collected during this time also revealed low concentrations of ATR, CYN and MET, with the timing of the detections indicative of non-local transport. Results show that the deep loess soil conducts both water and agricultural chemicals relatively rapidly and as such represents a production system which is vulnerable to contamination of shallow groundwater by herbicide-derived chemicals. Results also illustrate the importance of including major herbicide degradation products in water resource impact assessment studies.     

Assessing land use impacts on flood processes in complex terrain by using GIS and modeling approach

A distributed hydrologic modeling and GIS approach is applied for the assessment of land use impact in the Steinsel sub-basin, Alzette, Grand-Duchy of Luxembourg. The assessment focuses on the runoff contributions from different land use classes and the potential impact of land use changes on runoff generation. The results show that the direct runoff from urban areas is dominant for a flood event compared with runoff from other land use areas in this catchment, and tends to increase for small floods and for the dry season floods, whereas the interflow from forested, pasture and agricultural field areas contributes to the recession flow. Significant variations in flood volume, peak discharge, time to the peak, etc., are found from the model simulation based on the three hypothetical land use change scenarios.     

Application of a checklist for quality assistance in environmental modelling to an energy model

Large, complex energy models present considerable challenges to develop and test. Uncertainty assessments of such models provide only partial guidance on the quality of the results. We have developed a model quality assistance checklist to aid in this purpose. The model checklist provides diagnostic output in the form of a set of pitfalls for the model application. The checklist is applied here to an energy model for the problem of assessing energy use and greenhouse gas emissions. Use of the checklist suggests that results on this issue are contingent on a number of assumptions that are highly value-laden. When these assumptions are held fixed, the model is deemed capable of producing moderately robust results of relevance to climate policy over the longer term. Checklist responses also indicate that a number of details critical to policy choices or outcomes on this issue are not captured in the model, and model results should therefore be supplemented with alternative analyses.