Estimation of Ambient PM2.5 Concentrations in Maryland and Verification by Measured Values

Abstract

In 1997, Maryland had no available ambient Federal Reference Method data on particulate matter less than 2.5 μm in aerodynamic diameter (PM_2.5), but did have annual ambient data for PM smaller than 10 μm (PM₁₀) at 24 sites. The PM₁₀ data were analyzed in conjunction with local annual and seasonal zip-code-level emission inventories and with speciated PM_2.5 data from four nearby monitors in the IMPROVE network (located in the national parks, wildlife refuges, and wilderness areas) in an effort to estimate annual average and seasonal high PM_2.5 concentrations at the 24 PM₁₀ monitor sites operating from 1992 to 1996. All seasonal high concentrations were estimated to be below the 24-hr PM_2.5 National Ambient Air Quality Standards (NAAQS) at the sites operating in Maryland between 1992 and 1996. The estimates also indicated that 12 monitor sites might exceed the 3-year annual average PM_2.5 NAAQS of 15 ug/m³, but Maryland’s air quality shows signs that it has been improving since 1992. The estimates also were compared with actual measurements after the PM_2.5 monitor network was installed. The estimates were adequate for describing the chemical composition of the PM_2.5, forecasting compliance status with the 24-hr and annual standards, and determining the spatial variations in PM_2.5 across central Maryland.     

Analysis of Trace Metal Particulates in Atmospheric Samples Using X-Ray Fluorescence

Trace metals collected on filter paper by a hi-volume air sampler for 24 hours were analyzed using the X-ray fluorescence method. A gamma ray exciting source (²⁴¹Am) and a bremsstrahlung exciting source (¹⁴⁷Pm) were both used to produce the X-rays, the latter being more efficient. For the samples collected in Dayton, several metals were detected, viz.: Ti, Fe, Cu, Zn, Pb, Cd, and Sn. Elements in the periodic table between Ti and Cs were seen to have a sensitivity limit of 0.5 micrograms/m³ of air.     

Analysis of Mosses and Soils for Quantifying Heavy Metal Concentrations in Sicily: A Multivariate and Spatial Analytical Approach

- DOI: http://dx.doi.org/10.1065/espr2006.01.006 Background The use of vegetal organisms as indicators of contamination of the environment is partially replacing traditional monitoring techniques. Amongst the vegetal organisms available, mosses appear to be good bioindicators and are used for monitoring anthropogenic and natural fall-out on soils. This study has two objectives: the evaluation of the concentrations of heavy metals in soils and mosses of the Sicily Region, in Italy and the identification of the origin of fall-out of heavy metals. Methods Mosses and the surface soil were sampled at 28 sites, only the youngest segments of Hylocomium splendens and Hypnum cupressiforme, corresponding to the plant tissues produced during the last 3 years, were taken. The elements Cd, Cu, Ni, Pb and Zn were analysed by ICP-MS and Hg by AAS. Statistical analysis was by PCA and spatial representation by GIS. Results and Discussion In the mosses sampled in Sicily, the highest concentrations of Cd were found around the cities of Palermo and Messina. The highest concentrations of Hg were recorded in the northern part of the island between Trapani and Messina, similar to the distribution of Cu. Different areas with the highest concentrations of Ni were found near the south coast, in the vicinity of Palermo and around the Volcano Etna. The highest concentrations of Pb were found in the south-west coast near Agrigento, where important chemical plants and petroleum refineries are located. Except for a few locations, Zn fall-out was found to be evenly distributed throughout Sicily. Conclusion The sites where the concentrations of heavy metals cause greatest concern have been revealed by the PCA analysis and portrayed using GIS. Also of some concern is the diffuse and anthropogenic origin of Hg and Cd. The combined approach of using soil and mosses, together with pedological interpretation and application of multivariate statistical techniques has provided valuable insight into the environmental aspects of heavy metal deposition in a region of southern Europe. Recommendations and Outlook Further insight into the deposition of heavy metals will require more detailed sampling of soils and mosses in both new and previous study areas. This needs to be complemented by detailed pedological investigations in the study areas. Future research programmes will address these issues.     

Workplace and Environmental Air Contaminant Concentrations Measured by Open Path Fourier Transform Infrared Spectroscopy: A Statistical Process Control Technique to Detect Changes from Normal Operating Conditions

Open path Fourier transform infrared (OP-FTIR) spectroscopy is a new air monitoring technique that can be used to measure concentrations of air contaminants in real or near-real time. OP-FTIR spectroscopy has been used to monitor workplace gas and vapor exposures, emissions from hazardous waste sites, and to track emissions along fence lines. This paper discusses a statistical process control technique that can be used with air monitoring data collected with an OP-FTIR spectrometer to detect departures from normal operating conditions in the workplace or along a fence line. Time series data, produced by plotting consecutive air sample concentrations in time, were analyzed. Autocorrelation in the time series data was removed by fitting dynamic models. Control charts were used with the residuals of the model fit data to determine if departures from defined normal operating conditions could be rapidly detected. Shewhart and exponentially weighted moving average (EWMA) control charts were evaluated for use with data collected under different room air flow and mixing conditions.

Under rapidly changing conditions the Shewhart control chart was able to detect a leak in a simulated process area. The EWMA control chart was found to be more sensitive to drifts and slowly changing concentrations in air monitoring data. The time series and statistical process control techniques were also applied to data obtained during a field study at a chemical plant. A production area of an acrylonitrile, 1,3-butadiene, and styrene (ABS) polymer process was monitored in near-real time. Decision logics based on the time series and statistical process control technique introduced suggest several applications in workplace and environmental monitoring. These applications might include signaling of an alarm or warning, increasing levels of worker respiratory protection, or evacuation of a community, when gas and vapor concentrations are determined to be out-of-control.