Concorde Emissions at Dulles International Airport: Results of Measurements

Hamilton, Ontario is an industrial city with a population of 300,000 which is situated at the western end of Lake Ontario. Canada’s two largest iron and steel mills are located here; the city historically has had relatively poor air quality, which has improved markedly in the last 25 years. Concern about the health effects of current air quality recently led us to carry out an epidemiological study of the effects of air pollution on the respiratory health of over 3500 school children. Respiratory health was measured by pulmonary function testing of each child, and by an assessment of each child’s respiratory symptoms via a questionnaire administered to the parents. Previous studies had shown that other environmental factors (e.g. parental smoking, parental cough, socioeconomic level, housing, and gas cooking) might also affect respiratory health, and thus “confound” any potential relationships between health and air pollution. The questionnaire also collected information on many of these confounding factors. For the purposes of initial analysis, the city was divided Into five areas in which differences In air quality were expected. In general, factors which have been associated with poor respiratory health were observed to be more prevalent in areas of poorer air quality.     

Ammonia modeling for assessing potential toxicity to fish species in the Rio Grande, 1989-2002.

Increasing volumes of treated and untreated human sewage discharged into rivers around the world are likely to be leading to high aquatic concentrations of toxic, unionized ammonia (NH3), with negative impacts on species and ecosystems. Tools and approaches are needed for assessing the dynamics of NH3. This paper describes a modeling approach for first-order assessment of potential NH3 toxicity in urban rivers. In this study daily dissolved NH3 concentrations in the Rio Grande of central New Mexico, USA, at the city of Albuquerque's treated sewage outfall were modeled for 1989-2002. Data for ammonium (NH4+) concentrations in the sewage and data for discharge, temperature, and pH for both sewage effluent and the river were used. We used State of New Mexico acute and chronic NH3- N concentration values (0.30 and 0.05 mg/L NH3-N, respectively) and other reported standards as benchmarks for determining NH3 toxicity in the river and for assessing potential impact on population dynamics for fish species. A critical species of concern is the Rio Grande silvery minnow (Hybognathus amarus), an endangered species in the river near Albuquerque. Results show that NH3 concentrations matched or exceeded acute levels 13%, 3%, and 4% of the time in 1989, 1991, and 1992, respectively. Modeled NH3 concentrations matched or exceeded chronic values 97%, 74%, 78%, and 11% of the time in 1989, 1991, 1992, and 1997, respectively. Exceedences ranged from 0% to 1% in later years after enhancements to the wastewater treatment plant. Modeled NH3 concentrations may differ from actual concentrations because of NH3 and NH4+ loss terms and additive terms such as mixing processes, volatilization, nitrification, sorbtion, and NH4+ uptake. We conclude that NH3 toxicity must be considered seriously for its potential ecological impacts on the Rio Grande and as a mechanism contributing to the decline of the Rio Grande fish community in general and the Rio Grande silvery minnow specifically. Conclusions drawn for the Rio Grande suggest that NH3 concentrations may be high in rivers around the world where alkaline pH values are prevalent and sewage treatment capabilities are poorly developed or absent.     

Estimating Fugitive Emissions of Volatile Compounds from Equipment Leaks

This paper is directed to those concerned with estimating releases to the air of volatile compounds from equipment component leaks. We compared emission rates for equipment component leaks using EPA’s Average Emission Factor Method, Leak/No-Leak Emission Factor Method, and Stratified Emission Factor Method. The latter two methods may be used if there are concentration measurements about the components. An organic vapor analyzer was applied with the appropriate response factor to measure the concentrations around each equipment component using EPA Method 21. We analyzed this data to determine mass emission rates. Results show that the Average Emission Factor Method substantially overstates the emission rates calculated using these other two methods. We conclude that use of Method 21 concentration measurements with the Leak/No Leak or Stratified Emission Factor Method may increase the accuracy and reduce significantly the estimated releases to the air of volatile compounds from equipment component leaks for many facilities.     

Cross-sectional survey methods to assess retrospectively mortality in humanitarian emergencies

Since the rates and causes of mortality are critical indicators of the overall health of a population, it is important to evaluate mortality even where no complete vital statistics reporting exists. Such settings include humanitarian emergencies. Experience in cross-sectional survey methods to assess retrospectively crude, age-specific, and maternal mortality in stable settings has been gained over the past 40 years, and methods appropriate to humanitarian emergencies have been developed. In humanitarian emergencies, crude and age-specific mortality can be gauged using methods based on the enumeration of individuals resident in randomly selected households—frequently referred to as a household census. Under-five mortality can also be assessed through a modified prior birth history method in which a representative sample of reproductive-aged women are questioned about dates of child births and deaths. Maternal mortality can be appraised via the initial identification of maternal deaths in the study population and a subsequent investigation to determine the cause of each death.     

Simulating Spatial Pattern and Dynamics of Military Training Impacts for Allocation of Land Repair Using Images

The land management of US Army installations requires information on land conditions and their history for planning future military training activities and allocation of land repair. There is thus a strong need for methodology development to estimate the land conditions and cumulative military training impacts for the purpose of repair and restoration. In this study, we simulated at Fort Riley, USA, spatial patterns and temporal dynamics of military training impacts on land conditions quantified as percent ground cover using an image-aided spatial conditional co-simulation algorithm. Moreover, we estimated the historical percent ground cover as a measure of the cumulative impacts, and then calculated the allocation of land repair and restoration based on both current and historical land conditions. In addition, we developed a loss function method for allocation of land repair and restoration. The results showed: (1) this co-simulation algorithm reproduced spatial and temporal variability of percent ground cover and provided estimates of uncertainties with the correlation coefficients and root mean square errors between the simulated and observed values varying from 0.63 to 0.88 and from 23% to 78%, respectively; (2) with and without the cumulative impacts, the obtained spatial patterns of the land repair categories were similar, but their land areas differed by 5% to 40% in some years; (3) the combination of the loss function with the co-simulation made it possible to estimate and computationally propagate the uncertainties of land conditions into the uncertainties of expected cost loss for misallocation of land repair and restoration; and (4) the loss function, physical threshold, and probability threshold methods led to similar spatial patterns and temporal dynamics of the land repair categories, however, the loss function increased the land area by 5% to 30% for intense and moderate repairs and decreased the area by 5% to 30% for no repairs and light repairs for most of the years. This approach provided the potential to improve and automate the existing land rehabilitation and maintenance (LRAM) system used for the land management of the U.S. Army installations, and it can be applied to the management of other civil lands and environments. In conclusion, this study overcame the important gaps that exist in the methodological development and application for simulating land conditions and cumulative impacts due to human activities, and also in the methods for the allocation of land for repair and restoration.     

Applications of satellite remote sensing data for estimating biogenic emissions in southeastern Texas

The sensitivity of biogenic emission estimates and air quality model predictions to the characterization of land use/land cover (LULC) in southeastern Texas was examined using the Global Biosphere Emissions and Interactions System (GloBEIS) and the Comprehensive Air Quality Model with extensions (CAMx). A LULC database was recently developed for the region based on source imagery collected by the Landsat 7 Enhanced Thematic Mapper-Plus sensor between 1999 and 2003, and field data for land cover classification, species identification and quantification of biomass densities.  Biogenic emissions estimated from the new LULC data set showed good general agreement in their spatial distribution, but were approximately 40% lower than emissions from the LULC data set currently used by the State of Texas, primarily because of differences in the biomass estimates of key species such as Quercus. Predicted ozone mixing ratios using the biogenic emissions produced from the new LULC data set were as much as 26 ppb lower in some areas on some days, depending on meteorological conditions. Satellite data and image classification techniques provide useful tools for mapping and monitoring changes in LULC. However, field validation is necessary to link species and biomass densities to the classification system used for accurate biogenic emissions estimates, especially in areas such as riparian corridors that contain dense spatial coverage of key species.     

Public risk perspectives on the geologic storage of carbon dioxide

Carbon Dioxide Capture and Storage (CCS) technology has the potential to enable large reductions in global greenhouse gas emissions, but one of the unanswered questions about CCS is to what extent it will be accepted by the public. To provide insight regarding risk perception as an important component that will influence the public acceptance of CCS, this study discusses different notions of risk and their varying uses by the public, who generally use a social constructivist risk perspective, and risk experts, who generally use a realist perspective. Previous studies discussing the public acceptance of CCS have relied on survey response data and/or focus groups. This study instead uses the psychometric theory of public risk perception to postulate how the public is likely to respond to efforts to use geologic storage of CO₂, a component of the CCS architecture. Additionally this paper proposes further actions that could favorably impact the public's perception of risk from geologic storage projects. Through the psychometric analysis this study concludes that the risks of geologic storage are likely to eventually be considered no worse than existing fossil fuel energy technologies. However, since geologic storage of CO₂ is a new technology with little operational experience, additional field tests and a demonstrated ability to mitigate problems should they arise will be necessary to improve the public's perception of risk from CCS technologies.