Integration of modeling,monitoring and laboratory observation to determine reasons for air quality violations

An attempt was made to explain ambient air quality violations in the vicinity of industrial plants. Micrometeorology, diffusion calculaations, ambient readings, and plant engineering data are all taken into consideration to ascertain whether the plant is or is not the principal offender.Scrutiny of hi-vol filters using scanning electron microscopy for particle size analysis and particle chemical make-up as an assessment technique is also described.Case histories using the above analytical techniques are discussed.Presented at the 16th National Conference on Energy and the Environment, May 23, 1979     

The occurrence of acid precipitation on the west coast of the United States

Compilation of published and unpublished data shows acid precipitation to be more widespread in the Pacific coastal states than is generally recognized. Although information is scattered and discontinuous, precipitation is definitely acidic in the Los Angeles Basin and north-central california, and in the Puget Sound region in Washington. Acid rain occurrences have been observed in western and eastern Oregon, but data are inadequate for regional generalization. New stations currently being established in Washington and Oregon, largely in resposnse to the recently renewed activity of Mount St. Helens, will greatly facilitate assessment of precipitation acidity in the Northwest.     

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.     

唐山市空气中SO2与TSP污染状况分析

分析了唐山市从1988年至1992年大气中SO2和TSP的污染状况和变化规律，取得对该市环境管理的科学依据。     

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.     

Ammonia uptake by plants

The paper considers the methodology and results of experimental determination of dry deposition and ammonia uptake by isolated plant leaves. Analytical expressions are proposed which allow a transition from rates obtained in an isolated chamber to dry ammonia deposition by standing crops leaves.     

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.