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The Importance of Air and Air Quality

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Annotated Bibliography

Kuiper, J. Lazaro, and Chang, Young-Soo. 2003. Assessing Human health and Environment Impacts of Air Pollutants presented at the Twenty-third Annual ESRI User Conference, San Diego, CA

In this article, the authors gave information on air pollutants caused by humans and described the impact that air pollutants play on human health depending on the distance, time and the dose. The authors explained that an air pollutant that is transported and deposited near its source has minimal impacts to the receptor and on air quality unless the dose (toxicity) is high and the receptor is among the sensitive group of humans. If the (pollutants have to travel a relatively long distance and/or the pollutants have been airborne for long time then the impacts to the receptor will be high as the pollutants are likely to react with other pollutants that can cause the toxicity of the dose to be higher than when it was closer to the receptor.

The 1990 amendment to the Clean Air Act (CAA) includes federal assistance and leadership to help state and local governments implement programs to prevent and control air pollution. Locations that have higher criteria air pollutants based on the National Ambient Air Quality Standards (NAAQS) are consider non-attainment area and the state is responsible to fill the State Implementation Plans (SIP) for the area to attain the NAAQS at the earliest practical date. With the SIP, businesses are given an opportunity to reduce their emission and present a voluntary reduction before the specified date instead of being fined. In addition, the 1990 CAA included the Clean Air Act Permit Program (CAPP) that demands more from significant pollution emitters and introduces market-based flexible programs to clean up pollutants efficiently and economically. The CAA strengthens the EPA power to fine violators and revoke the permit of repeated violators. (www.access.gp.gov/nara/cfr/waisdx.02/40cfr51_02.html Accessed November 2007)

Monitoring the six criteria pollutants have seen emission reduction by 25 percent as a result of the CAA, but at the same time half of US citizens still live in non-attainment area for one or more of the six criteria pollutants. Monitoring air quality directly is very expensive compared to air quality modeling when an acceptable level of accuracy is set. The authors presented several models such as Health-consequence Assessment models, Screening models and Large-Eddy simulation and computational fluid Dynamics models that can be used in assessing future impacts of various pollutants under various hypothetical accidental release scenarios and presented certain examples that will best fit each model along with pros and cons of these models. In addition, the uses of GIS with these models were presented and suggestions in selecting the right model based on the question(s) to be answered.

The authors presented several projects example in which GIS was used along with the air quality models used to answer question of compliance with national and state air quality standards, accidents analysis and risk assessment and environmental justice questions. For further information on their work with GIS and Environmental assessment can be found at this site http://www.ead.anl.gov.

Levy, J. I., Houseman, E. A., Spengler, J. D. Loh, P. and Ryan, L. 2001 Fine Particulate Matter and Polycyclic Aromatic Hydrocarbon Concentration Patterns in Roxbury, Massachusetts: A community-based GIS Analysis. Environmental Health Perspectives 109:4, 341- 47

The prevalence of asthma in the United States has increased substantially and the residents in the Dudley Square area of Roxbury, Massachusetts have been concerned about respiratory health problems in their community. Roxbury hospitalization rates were 9.8 per 1000 compared with Boston and the whole state - 4.2 and 2.1 respectively. Asthma prevalence was higher for lower socioeconomic status families and children. Those who lived in a zip code with 20 percent of the population below poverty level are 7.6 times more likely to have asthma than those who lived in a zip code with 10 percent of the population below poverty level according to a cross-sectional analysis of Boston families conducted by the authors. Although the authors did not identify the areas in Roxbury, all the zip codes in Roxbury fall within the higher poverty category. A small scale survey conducted by the youth interns with the Roxbury Environmental Empowerment Project (REEP) found 24 percent asthma prevalence in Dudley Square. Other studies have linked respiratory symptoms and diseases to traffic flow and proximity to the main roads; the survey conducted by the local schoolchildren of Dudley Square found that residents perceived traffic flow to be the primary source of air pollution in their community. Dudley Square used to house an elevated train station but in 1980 the trains were rerouted and elevated tracks removed and the train terminal was changed to a bus terminal. The Alternatives for Community and Environment (ACE) survey found that 15 bus and truck depots are located within a 1.5 mile radius of Dudley Square garaging more than 1,150 diesel vehicles including one-half of the Massachusetts Bay Transportation Authority bus fleet. From all the preliminary surveys and all community meetings, ACE determined that air pollution from traffic was a major concern of residents and also a link to asthma and other respiratory diseases. The authors used a pilot modeling to help Dudley Square residents determine the air pollution patterns in their neighborhood and evaluate the potential contributions of diesel buses and other vehicles. The authors main goal was to develop an approach applicable for epidemiologic assessments of traffic-related respiratory symptoms that will allow them to determine personal exposure and determine the role of specific pollutants (Particulate matter (PM) and polycyclic aromatic hydrocarbon (PAHs)) or sources.

To evaluate the spatial and temporal patterns in transportation-related pollutants in Dudley Square, a geographic information system (GIS) approach was used. Normally, research of this type requires a relatively dense network of monitors placed in randomly selected and representative locations with specific information collected. In this study the authors have used portable monitors to collect data because of the limited sampling instruments available (2 for PAHs and one for PM2.5) In addition, the authors wanted it to be community based, and local high school students were involved in helping with the research. These students carried portable monitors on the streets in a 1-mile radius around a large bus terminal at different times of the day to create GIS map of concentrations and gather data on sites that could predict ambient concentrations. With this method, the students were able to cover the same locations multiple times and the researchers were able to calculate spatial concentration patterns rather than temporal variability while estimating covariate effects in different settings to strengthen their confidence in their regression findings. In July and August of 1999, different instruments were used to collect the various informations (PM2.5, PAHs, temperature and humidity). In addition, students collected information on frequency of bus activity on the road, general level of traffic, road classification as proxy for the overall volume of traffic and later students verified their work on bus frequency on the road against the bus schedule. The authors collected information on road classification for all roads covered by the mobile instruments as a proxy for the overall volume of traffic by extracting the information from United States Census TIGER data for Suffolk County, Massachusetts. All data collected were geocoded in ArcView. ArcView was used to find the distance between each mobile measurement and hypothesized fixed source to test whether a concentration gradient existed from the Dudley Square bus terminal.

PAH and PM2.5 were higher on bus traffic routes when detailed site characteristics were gathered. Both pollutants were higher during morning rush hours and on weekdays, and PAH concentration was higher near the bus terminal with higher relative humidity. The results indicate that there are significant predictors of PAH concentrations in spatial model and insignificant predictors of PAH concentrations in temporal model when dealing with the bus routes. Although there are limitations to this study, the authors demonstrated the efficacy of a GIS and LME regression approach in characterizing air pollution patterns in an urban area with limited resources.

Kunzli, N. and Tager, I. B.2000. Long Term health Effects of Particulate and Other Ambient Air Pollution: Research Can Progress Faster If We Want It To. Environmental Health Perspectives 108:10, 915-18.

The authors stated that research advisory boards have emphasized the need for study of long term health effects of outdoor air pollution on both sides of the Atlantic. But most of the research conducted has focused primarily on short-term effects through controlled exposure studies and a variety of epidemiologic study designs, although there are a few longitudinal studies and cross-sectional studies that have evaluated the potential long-term health effects. Furthermore, the authors stated that knowledge of long-term health effects is needed to better estimate the public health impact of air pollution and the benefit of air pollution control. There are several challenges to ambient air research and to name a couple: research setting and lack of disease specificity. Research setting is a very challenging one since outdoor air pollution is ever-present; lifetime exposures are relatively homogeneously distributed across large areas and are influenced by outside air quality unlike occupational or behavioral risk factors. In addition, fine particles can move indoors which increases the homogeneity of personal long-term exposure to PM2.5 from outside sources between participants of the same geographic area. As a result, long-term air pollution effects have been restricted to a limited number of study sites. There is no specific disease from air pollution; therefore, air pollution has to be considered a component cause for multifactorial health results. For this reason along with improvement in air quality, population sizes need to be large to estimate long-term effects with reasonable precision. With these criteria - long follow-up and large population size, funding agencies are not attracted to long-term research but prefer short time frames with limited funding budgets; as a result only a handful of research studies in this area are long-term. The authors only know of two studies in United States (US) which have reached fifteen years of follow-up time and the Swiss study - Swiss Study on Air Pollution and Lung Disease in Adults (SAPALDIA) that is currently funded.

The authors are proposing a new way in assessing the long-term health effects with small size population and less time by using GIS modeling and environmental epidemiology to reach similar goals. The authors proposed that population comes from the whole US instead of a finite number of study areas with clusters of people sharing similar long-term exposure. Monitoring data have restricted some researchers from selecting subjects from few study sites but with modeling this can be resolved. Models can either be based on concentration or emission data; a good example is the European study of the Swiss part because the researchers were able to derive the annual mean concentration of PM10 for each square kilometer across Switzerland with the use of emission registry data. According to the authors, there is no long-term air pollution epidemiology study that has applied such exposure maps to impute exposure even though the use of GIS and environmental epidemiology has been well accounted for in the literature. The authors went on to name a variety of application and users of GIS exposure data - Risk Assessors (Puybonnieux-Texier, and Schneider, and Sommer et al) and Monitoring Optimization (ESF, and HEI). Furthermore, the authors stated that there are existing data available such as the Nurses Health Study, The Physicians Health Study that can be used with one caution that these studies do not have exposure maps and cities without the particulate data should not be included in the analyses. This "piggy-back" approach should be intensified and modified to meet the research question on hand; thereby, giving opportunity to use long-term outdoor air pollution data has all the attributes needed to conduct the research.

Although the authors approached solving the problem of long-term research and large population with limited finances by using GIS, they acknowledge that there are certain requirements that need to be rectified to be able to use previous cohort studies that have attributes that can be used to conduct long-term effects of outdoor air pollution. For example: (1) cohort studies are not centralized or standardized, therefore the first step is to establish identification criteria such as minimum number of participants and duration of follow-up, specificity of measured health outcomes and potential confounders. (2) Monitoring station characteristics and a list of the responsible agencies (3) Interdisciplinary research community, monitoring agencies and policy makers collaborate to make this happen. For the authors, the biggest obstacle will be the collaboration of the interdisciplinary research community where there are no traditions for transdisciplinary collaboration and funding structure.

Lindley, S. J. and Crabbe H. 2004 What Lies beneath? - Issues in the Representation of Air Quality Management Data for Public Consumption Science of the Total Environment 334-335; 307-325

In the United Kingdom (UK) and European Union (EU), local authorities are now required to involve the general public with the local air quality management (AQM). AQM is a spatial activity that involved the public from the beginning by assessing the nature and extent of the air quality problems, developing appropriate policy responses and monitoring progress to the achieved goals. Maps associated with AQM are useful ways to communicate complex information which can aid comprehension and can be highly attractive too. GIS has the capability of both functional and analytical aspects that can produce compelling results but care should be considered during analysis and representation of information as this could influence the interpretation and conclusion. GIS graphic outputs tend to mask the uncertainty found in the input and output. Despite this drawback, the authors stated that the advantages of using GIS in AQM outweigh the negatives - more repetitive data generation activities for ongoing review and assessment; scenarios can be evaluated and policy options proposed for generated scenarios; communicate results to the public; increase public participation in decision making; a variety of spatial analysis techniques can assess compliance with air quality objectives (AQOs). In addition, GIS can ease the use of interactive searches with other software packages but the difference between the details of air-quality-related data and clarity of information representation is the primary conflict between researchers, and policy makers and the public. It is necessary to choose the appropriate selection of analysis techniques and representation methods or the interpretation result may be skewed and may have significant implication such as setting new emission controls.

Key elements of AQM are data intensive and require spatial expression which the authors divide into three groups - information associated with the causes of air pollution, information about current levels of air quality, and information about future potential levels of air quality. Much has been done in determining and justifying health-related air quality standards and ways to inform the public, for example, the UK health-related pollution index found in this website http://www.airquality.co.uk. The information is simple and if the public needs more information, there other links that give more detailed information that the public can connect to, but there is more to be done to track the spatial aspect of the information thereby making the delivery of air quality data personalized in terms of time, space and activities. Careful consideration should be taken in choosing the right method to disseminate data thereby maximizing positive impact and minimizing misinterpretation. The authors used two case study examples to investigate the range and nature of issues associated with spatial data generation and AQM representation with relation to the generation and use of emissions inventory data. Furthermore, the authors illustrate how these issues affect the perception and response of air pollution problems after the data have been distributed to scientific world and then to the policy makers and public.

The use of GIS with AQM is growing and so is the gulf between the historical cartography discipline and the present GIS users and the interpretation and dissemination of information. The authors mentioned the prospects that GIS has created -- more research opportunity and knowledge in air quality field but have also opened unconscious misuse. In addition, very little consideration has been given to spatial error associated with the representation and aggregation of sources data to selected output, and the numerous uncertainties during the process.

Lacan, I., Zhou, J. Y. Liu, Kai-Shen and Waldman, J. 2006 A Geographic Information Systems (GIS) and Spatial Modeling Approach to Assessing Indoor Radon Potential at Local Level Applied Radiation and Isotopes 64:490-96

Radon is considered a human carcinogen. For the past 30 years, studies have indicated an increased risk of lung cancer with high concentration of radon. About 30 percent of non-smoker deaths and 10 percent of all lung-cancer deaths in the US are attributed to indoor-radon exposure. (Muirheal, 1994; Lubin et al, 1995; Samet 1997) The authors stated that indoor radon exposure is assessed using cumulative long-term concentration measurement and if this information is unavailable multivariate models are used to predict the indoor air concentration as a function of the characteristics of the building and its occupants but there are uncertainties in using this method. Geographic information systems (GIS) provide new means of exploring indoor radon at various spatial scales and resolutions, rapid means of generating maps that integrate diverse spatial information and help with visualization of various relationships between radon-potential factors, and for application of spatial statistics, spatial analysis, and comprehensive assessment. The authors used a case study to demonstrate how GIS can be used in assessing indoor-radon potential. Although GIS provides an easy visualization of spatial patterns in a map form, it does not resolve all the problems associated with spatially explicit information to estimate human exposure to indoor radon. 

Huen, K., Gunn, L., Duromod, P., Jeng, M., Scalf, R. and Holland, N. 2006 Application of a Geographic Information System to Exposure Associations between Air Pollution and Micronucleus Frequencies in African American Children and Adults Environmental and Molecular Mutagenesis 47: 236-46

The authors used GIS methods and regional ozone monitoring data to explore how exposure to outdoor air pollution affects cytogenetic damage in African American children and adults from Oakland, California. Several studies have shown a correlation between the effects of traffic pollution and the adverse health effects of outdoor air pollution on children's health. The authors mentioned several studies results from traffic pollution ranging from leukemia, asthma, evidence of genetic damage, and respiratory disorders. Furthermore, the authors cited several studies that have looked for evidence of genetic damage as a result of traffic pollution exposure, and using micronucleus (MN) assay to study the effect of environmental, occupational, genetic and lifestyle factors on genomic stability. Several researchers have stated that low income areas experience greater concentration of ozone and particulate matter than high income areas in California, and according to the authors, children of color were three times more likely to live in areas with high traffic density compared to Caucasian children. Based on this and information obtained from other researchers, the authors suggested that city children live in more high risk environments thereby leaving them more vulnerable to hazardous effects.

Residential and school/daycare addresses were obtained from questionnaire data and a commercial road data layer obtained from Geographic Data Technology (GDT) were geocoded using ArcView GIS software by the authors. GIS methods were applied to create individual measures of traffic-related exposures at residential and school/daycare addresses for each child and this provided a better differentiation between individual exposures to traffic pollution using alternative measures of proximity to major roads. The combination of GIS and cytogenetic methods with regional ozone monitoring data was good choice in determining environmental-exposed populations and the authors think that it will be promising tool for detecting genetic damage in environmentally-exposed populations.