
| |  | |  | |
| Assessment of Personal and Community-Level Exposures to Particulate Matter among Children with Asthma in Detroit, Michigan, as Part of Community Action Against Asthma (CAAA) Gerald J. Keeler,1 J. Timothy Dvonch,1 Fuyuen
Y. Yip,1 Edith A. Parker,2 Barbara A. Israel,2
Frank J. Marsik,1 Masako Morishita,1 James A.
Barres,1 Thomas G. Robins,1 Wilma Brakefield-Caldwell,3
and Mathew Sam4 1Department of Environmental Health Sciences, 2Department
of Health Behavior and Health Education, University of Michigan, Ann
Arbor, Michigan, USA; 3Community Action Against Asthma, Detroit,
Michigan, USA; 4Detroit Health Department, Division of Environmental
Health, Detroit, Michigan, USA
Abstract We report on the research conducted by the Community Action Against Asthma (CAAA) in Detroit, Michigan, to evaluate personal and community-level exposures to particulate matter (PM) among children with asthma living in an urban environment. CAAA is a community-based participatory research collaboration among academia, health agencies, and community-based organizations. CAAA investigates the effects of environmental exposures on the residents of Detroit through a participatory process that engages participants from the affected communities in all aspects of the design and conduct of the research ; disseminates the results to all parties involved ; and uses the research results to design, in collaboration with all partners, interventions to reduce the identified environmental exposures. The CAAA PM exposure assessment includes four seasonal measurement campaigns each year that are conducted for a 2-week duration each season. In each seasonal measurement period, daily ambient measurements of PM2.5 and PM10 (particulate matter with a mass median aerodynamic diameter less than 2.5 µm and 10 µm, respectively) are collected at two elementary schools in the eastside and southwest communities of Detroit. Concurrently, indoor measurements of PM2.5 and PM10 are made at the schools as well as inside the homes of a subset of 20 children with asthma. Daily personal exposure measurements of PM10 are also collected for these 20 children with asthma. Results from the first five seasonal assessment periods reveal that mean personal PM10 (68.4 ± 39.2 µg/m3) and indoor home PM10 (52.2 ± 30.6 µg/m3) exposures are significantly greater (p < 0.05) than the outdoor PM10 concentrations (25.8 ± 11.8 µg/m3) . The same was also found for PM2.5 (indoor PM2.5 = 34.4 ± 21.7 µg/m3 ; outdoor PM2.5 = 15.6 ± 8.2 µg/m3) . In addition, significant differences (p < 0.05) in community-level exposure to both PM10 and PM2.5 are observed between the two Detroit communities (southwest PM10 = 28.9 ± 14.4 µg/m3, PM2.5 = 17.0 ± 9.3 µg/m3 ; eastside PM10 = 23.8 ± 12.1 µg/m3, PM2.5 = 15.5 ± 9.0 µg/m3) . The increased levels in the southwest Detroit community are likely due to the proximity to heavy industrial pollutant point sources and interstate motorways. Trace element characterization of filter samples collected over the 2-year period will allow a more complete assessment of the PM components. When combined with other project measures, including concurrent seasonal twice-daily peak expiratory flow and forced expiratory volume at 1 sec and daily asthma symptom and medication dairies for 300 children with asthma living in the two Detroit communities, these data will allow not only investigations into the sources of PM in the Detroit airshed with regard to PM exposure assessment but also the role of air pollutants in exacerbation of childhood asthma. Key words: ambient PM, childhood asthma, community-based participatory research, particulate matter, personal exposure, urban air quality. Environ Health Perspect 110(suppl 2) :173-181 (2002) . http://ehpnet1.niehs.nih.gov/docs/2002/suppl-2/173-181keeler/abstract.html |
|
|
 |
This article is part of the monograph Advancing Environmental Justice
through Community-Based Participatory Research.
Address correspondence to G.J. Keeler, University of Michigan, Air Quality
Laboratory, Dept. of Environmental Health Sciences, 109 South Observatory
St., Ann Arbor, MI 48109-2029 USA. Telephone: (734) 936-1836. Fax: (734) 936-7283.
E-mail: jkeeler@umich.edu
The Michigan Center for the Environment and Children's Health (MCECH) is
funded by the National Institute of Environmental Health Sciences (grant 1-P01-ES09589-01)
and the U.S. Environmental Protection Agency (grant R826710-01). Informed
consent was obtained from study participants prior to all data collection
described in this manuscript.
The authors acknowledge the tremendous efforts of E. Snedeker and R. Currie
at Maybury Elementary School and R. Johnson and E. Sheppard at Keith Elementary
School. We also thank K. Edgren, M. Salinas, M. Lyon, M. Lynam, and K. Quintal
for their efforts in carrying out the field work aspects of this research.
We also thank the anonymous reviewers for their suggestions that led to significant
improvements in this manuscript.
Received 13 August 2001; accepted 19 February 2002.
Introduction
Background on Asthma Prevalence, Causation, and Aggravation
Asthma is the most common chronic disease of childhood in the developed world,
affecting approximately 5 million children under 18 years of age in the United
States (1,2). From 1982 to 1994, the prevalence rate of pediatric asthma
(under age 18) in the United States increased by 61% (1). The mortality
rate from asthma for persons 19 years of age and under increased by 78% from
1980 to 1993 (1). Asthma is particularly prevalent among urban populations
and minority populations (3-5). The national trends in the increase
in asthma are visible in Detroit, where a 1993-1994 study found that 17.4%
of the 230 children in the sample had a physician diagnosis of asthma (6)
and where pediatric hospital admissions for asthma among African American children
has escalated (from 11.6% of pediatric hospital admissions in 1986 to 17.5%
in 1989). Data from the Michigan Department of Community Health show childhood
asthma hospitalization rates in Detroit were more than twice the statewide average
during the period from 1991 to 1996 (75.5 ± 1.4 per 10,000 children under
18 years of age for Detroit vs. 30.1 ± 0.3 per 10,000 for Michigan). Furthermore,
pediatric asthma hospitalization rates, while stable throughout the rest of
Michigan, continue to rise in Detroit (84.3 ± 3.3 per 10,000 in Detroit
in 1997 vs. 30.7 ± 0.7 per 10,000 in Michigan) (7).
The causation and aggravation of pediatric asthma is complex and multifactorial
and includes genetic disposition, demographic variables, psychosocial stressors,
and environmental exposures (8-14). Considerable research
evidence suggests that both indoor and outdoor environmental exposures may be
involved in the worldwide increase in asthma (15-25). Some
of the strongest associations have been found with indoor allergens such as
dust mite and cockroach in children sensitized to that particular allergen (24-32).
Exposure to environmental tobacco smoke, both in utero (15,19)
and during childhood (17,18,20), also appears to play an important
role in asthma causation and aggravation. Additionally, exposures to indoor
sources of fuel combustion have significant associations with exacerbations
of asthma (33,34). These may be sources of nitrogen dioxide, which
can potentiate airway reactivity in persons with asthma (20). Increased
ambient levels of respirable particulates (35-39) and ozone (35,40-46)
have been reported to precipitate symptoms of asthma (35-37,39)
and to increase emergency department visits and hospitalizations for asthma
(38-41,43-46). Studies in the United States and Europe
report an association between increased morbidity and mortality and ambient
particulate matter (PM) concentrations at levels currently below the U.S. National
Ambient Air Quality Standard (NAAQS) (47-49). Highly sensitive
subpopulations, including children and persons with asthma, are at increased
risk (50,51). Exposure to PM and copollutants in the ambient environment
may provide the critical factor in increased morbidity and mortality in these
individuals in urban centers (50,51).
Air quality fluctuates considerably in the city of Detroit. Given that areas
of Wayne County, including portions of Detroit, have been designated as nonattainment
areas under the NAAQS for PM10 as recently as 1995, there is reason
to believe that residents of these communities may be exposed to levels of respirable
particulates that can exacerbate respiratory illnesses. Although the Wayne County
area was redesignated as being in attainment for the PM10 (particulate
matter with a mass median aerodynamic diameter less than 10 µm) standard
in October 1996, more recent data suggest that local levels of PM2.5 (particulate
matter with a mass median aerodynamic diameter less than 2.5 µm) may exceed
the proposed 1997 U.S. Environmental Protection Agency (U.S. EPA) standards
for PM of that size (52).
Background on Environmental Justice and Community-Based Participatory Research
Environmental justice is defined as "the fair treatment and meaningful involvement
of all people regardless of race, ethnicity, income, and national origin or
educational level with respect to the development, implementation, and enforcement
of environmental laws, regulations, and policies" (53) and is based on
the increasing number of findings that environmental stressors (e.g., air, water,
and land pollution) are disproportionately distributed among communities of
color and low-income communities (54-57). For example, Wernette
and Nieves (58) found that the percentage of persons living in nonattainment
air quality areas is considerably higher for Hispanic and African American populations
than for White populations, with the greatest percentage being for Hispanic
populations. Furthermore, the worst air pollution problems in the United States
are most often found in urban areas in which a large number of communities of
color reside (59). Because of this growing empirical evidence,
the Committee on Environmental Justice (60) has made three recommendations
for environmental and public health research: a) improve the knowledge
base through the conduct of research, using improved methodologies for examining
environmental etiologies of disease; b) engage participants from the
affected communities in all aspects of the design and conduct of the research;
and c) disseminate the results of the research to all parties involved.
In addition to these developments in the environmental justice field, there
have been increasing calls for more participatory and comprehensive approaches
to research and public health practice (61) to address the social and
environmental determinants of health and disease, most visible in the health
disparities between rich and poor, White and non-White, urban and nonurban (55,62-65).
One such approach, community-based participatory research (CBPR), emphasizes
the participation, influence, and control of nonacademic researchers in the
process of creating knowledge and change (61). CBPR is a collaborative
research approach that equitably involves all partners in contributing their
expertise and sharing ownership and responsibilities to enhance understanding
of a given phenomenon, and to translate the knowledge gained into interventions
and policies to improve the health and quality of life of community members
(61).
Environmental Exposure Assessment: Community Action Against Asthma
All exposure assessment data collection for this project takes place through
Community Action Against Asthma (CAAA), a field-based CBPR project. The overall
goal of CAAA is to gain an increased understanding of the environmental and
psychosocial triggers for asthma in children's homes and neighborhoods and to
reduce those triggers through household- and neighborhood-level interventions.
CAAA conducts research that follows suggested guidelines of the Committee on
Environmental Justice (60). That is, CAAA conducts research on the effects
of environmental exposures among the residents of Detroit through a participatory
process that engages participants from the affected communities in all aspects
of the design and conduct of the research; disseminates the results to all parties
involved; and uses the research results to design, in collaboration with all
partners, interventions to reduce the identified environmental exposures. To
ensure this happens, all strategies and plans for data collection and intervention
activities are carried out in accordance with the principles of CBPR (61)
and are thus formulated and approved by the CAAA Steering Committee. The committee
comprises representatives from the Michigan Center for the Environment and Children'ns
Health (MCECH). The center was established in 1998 and is a community-based
participatory research initiative investigating the influence of environmental
factors on childhood asthma. MCECH involves collaboration among the University
of Michigan Schools of Public Health and Medicine, the Detroit Health Department,
the Michigan Department of Agriculture, Plant and Pest Management Division,
and nine community-based organizations in Detroit (Butzel Family Center, Community
Health and Social Services Center, Detroiters Working for Environmental Justice,
Detroit Hispanic Development Corporation, Friends of Parkside, Kettering/Butzel
Health Initiative, Latino Family Services, United Community Housing Coalition,
and Warren/Conner Development Coalition), and Henry Ford Health System.
The CAAA project is being conducted in neighborhoods on the east side and
in the southwest portion of Detroit. The two areas were selected initially as
part of the Detroit Community-Academic Urban Research Center (66),
with which the MCECH is affiliated, on the basis of statistics highly relevant
to general child and family health (e.g., high infant mortality rates, high
proportion of households living below the poverty level); evidence of community
strengths and efforts to address health problems; and preexisting relationships
among some of the partners involved. The east side of Detroit is predominantly
African American (more than 90%) (67), has a large number of single-family
dwellings, and contains a major interstate highway and some manufacturing plants.
Southwest Detroit is the part of the city where the largest percentage of Latinos
reside [approximately 40% Latino, 50% African American, and 10% White (67)]
and has historically contained most of the industrial facilities of Detroit.
This industry, including iron/steel manufacturing, coke ovens, chemical plants,
refineries, sewage sludge incineration, and coal-fired utilities, is located
in and around Zug Island, an industrial complex along the Detroit River (Figure
1). In addition, southwest Detroit experiences heavy car and truck traffic because
of both the presence of two major interstates and the entrance/exit of the Ambassador
Bridge, the international border crossing that connects Detroit to Windsor,
Canada.
 |
| Figure 1. Map
of Detroit, Michigan, illustrating community boundaries and air monitoring
sites (filled circles) used for CAAA. |
The environmental exposure assessment portion of CAAA has as its primary objectives
a) to provide ambient (community-level), microenvironmental (inside schools
and homes), and personal monitoring data needed for the investigatation of the
relationships between exposure metrics and activity patterns of children with
asthma living in an urban community; b) to investigate whether seasonal
and daily fluctuations in ambient air pollution and indoor air contaminants
are predictive of fluctuations in asthma disease status; c) to identify
the components of outdoor and indoor air that are associated with increased
risk for asthma in the urban communities involved; and d) to provide
data needed for the investigation of the relationship of specific interventions
at the household and neighborhood level with measurable decreases in exposure
to contaminants and associated improvements in disease status. CAAA is somewhat
unique in its focus on exploring the combined effects of ambient indoor and
outdoor air contaminants on fluctuations in asthma, and by doing so, uses a
CBPR approach that follows suggested guidelines of the Committee on Environmental
Justice (60). The PM exposure assessment measures and methodologies
for CAAA, described in detail in the following sections, include measures of
both indoor and outdoor air quality, primarily PM and ozone. Our objectives
here are to describe the exposure assessment methodologies of CAAA and to present
results and preliminary findings from PM exposure assessment for the first year
of data collection. Because the exposure assessment activities of CAAA are tightly
linked to the intervention activities of the project, the need for credible
scientific data specific to achieve cleaner environments for children with asthma
cannot be understated. The data collected in the urban neighborhoods must stand
up to rigorous and critical review by the scientific community before it can
be used to evaluate environmental risks. The collection of quality measurement
data with partner involvement leads to more relevant exposure data for the study
of children in urban neighborhoods and provides immediate knowledge and understanding
of the outcomes and results of the combined environmental health analysis to
the communities.
Methods
Assessment of Personal Exposures to Indoor and Outdoor Air Pollutants
The implementation of this study was made possible by the CBPR approach used
in the assessment of environmental exposures of children with asthma living
in two communities in Detroit. The CAAA Steering Committee played an active
role in the implementation decisions for the exposure assessment aspects of
the project. They actively participated in the identification, hiring, and training
of community outreach workers, called Community Environmental Specialists (CES),
who performed the household assessments and the personal exposure monitoring
activities. A Steering Committee hiring subcommittee was formed to oversee the
selection of the CES, including development of job descriptions, interviewing,
and ultimate hiring of the four CES. The Steering Committee also approved the
content and format of the CES training curriculum, and some Steering Committee
members participated as trainers in some of the CES training sessions. In addition,
as described below, the Steering Committee participated in the design of the
recruitment process for the families participating in the intensive exposure
assessment aspects of the research.
The CAAA project includes participation of 300 children, 7-11 years of
age, who were diagnosed with moderate to severe asthma through a mailed screening
questionnaire. These families reside in one of two Detroit communities, eastside
or southwest (Figure 1). As part of a community-level environmental exposure
assessment, air quality measurements are performed at fixed monitoring locations
within each of the communities. Four times each year, a 2-week seasonal field
intensive data collection is conducted so that investigators can assess both
levels of exposure as well as asthma health status of all 300 participants.
Twice-daily measures of pulmonary function include peak expiratory flow (PEF)
and forced expiratory volume at 1 sec (FEV1). Additional measures
of the children's health status include diaries of daily asthma symptoms and
medications. During the seasonal assessments, daily measures of PM2.5,
PM10, and ozone are made at each of the two community locations on
the rooftops of two elementary schools. In addition, daily measures of PM2.5
and PM10 are also made indoors in school classrooms to characterize
indoor penetration of outdoor pollutants.
Indoor levels of PM2.5 and PM10 are also monitored daily
in the homes of 20 study participants during each seasonal assessment. As mentioned
previously, the Steering Committee was actively involved in the recruitment
process for these 20 households. The original recruitment process proposed by
the academic partners involved contacting these potential 20 households via
telephone and letter to ask them to participate. On the basis of input from
the community members on the Steering Committee, the recruitment process was
redesigned to include visits to the potential families by a community member
of the Steering Committee, who volunteered to visit each of the 20 households.
During these visits, the member further explained the purpose of the exposure
assessment equipment (including photographs of the equipment) to the families
so they would better understand what their participation in the intensive household
exposure monitoring would entail.
In addition to indoor measurements in their home, these children also wear
a personal exposure monitor (PEM) each day for characterization of their exposure
to PM10. The rationale for this seasonal measurement approach considered
the expected daily variability in PM exposure as well as issues related to retention
and participation of families. It was determined that a seasonal assessment
period of 2 weeks, taking into account the synoptic meteorology of southeast
Michigan and regional air pollution transport patterns, would be of sufficient
duration to introduce and characterize variation in PM exposure for analysis
with health outcome measures. At the same time, a seasonal assessment period
of 2 weeks (in each season for 2 years) was determined to be the maximum duration
for obtaining adequate retention of and participation by the 300 CAAA families
involved.
Community-level exposure assessment. Ambient air quality measurements
are performed at two sampling locations established for this study. Community-level
exposure measurements are made on the rooftops (inlet heights approximately
5-6 m above ground) of Keith and Maybury Elementary Schools, located in
the eastside and southwest Detroit communities, respectively (monitoring sites
denoted by filled circles in Figure 1). Filter-based measurements of PM2.5
and PM10 are made daily during seasonal exposure assessment field
intensives (each 2 weeks in duration) at each sampling location. All PM samples
collected are nominally 24 hr in duration. Measurements are made using both
2-µm pore, 47-mm Teflon (PTFE) membrane filters (Pall, Ann Arbor, MI) and
prebaked 47-mm quartz fiber filters (Pall). Vacuum pump systems are used to
draw air through the sample at a nominal flow rate of 16.7 L/min using Teflon-coated
aluminum cyclone inlets (University Research Glassware, Chapel Hill, NC). The
volume of air drawn through each sampling train is determined using a dry test
meter (DTM; Schlumberger, Owenton, KY) placed inline between the vacuum pump
and the sample. The DTMs are calibrated both before and after being deployed
into the field against a laboratory spirometer (Warren E. Collins, Inc., Boston,
MA), which is a primary calibration standard. In addition, flow determinations
are made at the beginning and end of each sampling period using a calibrated
rotameter (Matheson Inc., Montgomeryville, PA) to ensure that the flow rate
is set correctly.
Teflon filters are also collected daily during seasonal measurement intensives
using a dichotomous sequential air sampler, Partisol-Plus Model 2025 (Rupprecht
and Patashnick, Inc., Albany, NY), for subsequent chemical and elemental characterization
of fine and coarse particles. As opposed to the standard cyclone inlets, which
collect all particles less than the defined size cut, the dichotomous configuration
permits the differentiated mass determination and chemical composition of the
fine (<2.5 µm aerodynamic diameter) and coarse (2.5-10 µm)
particles contained in PM10, which can aid in further source identification.
The sequential dichotomous sampler also maintains sampling flow rates of 16.7
L/min using integrated volumetric flow controllers.
Semicontinuous PM determinations are made at each of the fixed ambient monitoring
locations using a tapered element oscillating microbalance (TEOM) ambient particulate
monitor Series 1400a (Rupprecht and Patashnick, Inc.) operated at 40oC
and equipped with a sharp-cut cyclone (SCC) inlet (BGI Inc., Waltham, MA). These
inlets provide a sharper particle size cut at 2.5 µm relative to standard
cyclone inlets. Similar to the dichotomous sequential samplers described above,
the TEOM also operates at a sampling flow rate of 16.7 L/min while incorporating
volumetric flow control. In contrast to the standard filter-based measures described
above, which provide a sample media suitable for subsequent chemical characterization,
the primary function of the TEOM is to determine PM mass. The great advantage
of the TEOM is its ability to characterize PM concentrations in near real time
(30-min intervals for this study), as opposed to the 24-hr integrated values
obtained using the standard filter-based methods. The 30-min fine-mass data
provided by the TEOM allow one to better assess short-term pollutant episodes
and to determine contributions from local sources, which can impact the community
on very short time frames. In contrast to the daily PM measurements performed
only during the seasonal assessment periods, the TEOMs operate continuously
year-round.
Additional ambient measurements made at each of the community monitoring sites
include ozone and meteorological variables. Ozone, identified in previous studies
to be a lung irritant, is monitored continuously at each of the sites and is
logged as 30-min average values (Dasibi Environmental, Glendale, CA). Because
ozone is a secondary pollutant typically present in Michigan at high levels
only during the warm months, ozone measurements are made from April through
October during each year of the study. Standard U.S. EPA protocols are used
for calibration of all continuous instruments deployed in the field for this
study. Standard meteorological variables including temperature, atmospheric
pressure, relative humidity, wind speed, and wind direction (R. M. Young Co.,
Traverse, City, MI) are recorded in 30-min intervals at each of the sites. Meteorological
variables are collected at a height of 4 m above the school rooftop, and all
pollutant inlets are at a height of approximately 2 m above the rooftop.
Indoor and personal pollutant exposure assessment. Indoor PM
levels are measured inside classrooms at the two elementary schools that serve
as fixed outdoor monitoring sites, as well as inside the homes of 20 Detroit
families participating in CAAA. Indoor measurements of PM2.5 and
PM10 are made concurrently with the outdoor measures on a daily basis
during each seasonal assessment to provide a measure of indoor penetration of
outdoor pollutants as well as provide insight into indoor sources of PM. Similar
to the outdoor sample collection methodologies, indoor PM measurements are made
with both Teflon and prebaked quartz filter media and use Teflon-coated aluminum
cyclone sample inlets at a nominal flow rate of 16.7 L/min. Sample flow rates
are set using calibrated rotameters as described above. Indoor sample inlets
are set at an approximate height of 1 m, a typical height of the breathing zone
of children 7-11 years of age. Indoor samples are collected using pump
systems designed and fabricated at the University of Michigan Air Quality Laboratory
(UMAQL). These pump systems use linear, free-piston vacuum pumps, needle valves,
and timers to provide accurately regulated air flow for PM sample collection.
Acoustically insulated wood cases, designed for operation in the classroom and
home environments, house the pumps, thus minimizing pump noise during sampling
periods. Special attention was given to details such as noise and size of the
equipment through close communication with our community partners and participating
families.
Of the 300 total participants, 20 children who have indoor PM exposure measurements
performed in their homes also participate in personal exposure monitoring for
PM10. PEMs (MSP Corp., Minneapolis, MN) are worn by 10 children during
the first week of each seasonal assessment, then by 10 other children during
the second week. The PEM system includes a small battery-powered pump (Gilian
Inc., West Cladwell, NJ). The commercially available nickel-cadmium rechargeable
batteries typically used with these pumps can provide only enough power for
an 8-hr sampling duration (for workplace exposure applications). However, because
the CAAA wanted to quantify PM exposure for full 24-hr sample periods, the UMAQL
developed a custom battery pack using AA-size alkaline batteries that ensured
pump power for sample durations of 24 hr or more. Sample flow rates for the
PEMs are set at 2 L/min using a built-in rotameter calibrated with a Gilian
Gilibrator (Gilian Inc.). The personal samples are collected using 2-µm
pore, 37-mm Teflon (PTFE) membrane filters (Pall) in a PM10 filter
inlet cassette. The pump and battery pack assembly is carried in a small child's
backpack, while the inlet is connected via a short piece of Tygon tubing to
the child's breathing zone. The PEM is carried with the child throughout the
course of each day both indoors and outdoors, including home, school, auto.
While the child sleeps the PEM is placed on a nearby nightstand or equivalent.
The child also records hourly activities in a daily activity log kept during
all sample collection periods.
Laboratory analyses. All filters collected as part of CAAA for
PM characterization are prepared and analyzed at the UMAQL. All gravimetric
determinations of Teflon filters are made using a microbalance (Mettler MT-5;
Mettler Toledo, Columbus, OH) in a temperature/humidity-controlled environment.
All sample handling, processing, and analysis takes place in a Class 100 ultra-clean
laboratory uniquely suited for ultra-trace element analysis with an emphasis
on environmental determinations. Measures including field blanks, filter-lot
blanks, laboratory blanks, replicate analyses, and externally certified standard
weights are incorporated into all gravimetric analyses for quality assurance
(QA) and quality control (QC) purposes. The detection limit for mass determination,
calculated as 3 times the standard deviation of seven replicate filter measures,
is 5.1 µg. This corresponds to a concentration detection limit of 1.8 µg/m3
for a 24-hr personal sample collected at 2 L/min.
Upon completion of gravimetric analysis, PM samples collected on Teflon filters
are analyzed for trace element composition. Teflon sample filters are wetted
with 150 µL ethanol before extraction in 20 mL 10% HNO3 and
sonication for 48 hr in an ultrasonic bath. Samples are then diluted with Milli-Q
water (Millipore, Bedford, MA) to 4% volume/volume solutions prior to passive
acid digestion for 1 month. The extracts are then analyzed for a suite of elements
by high-resolution inductively coupled plasma-mass spectrometry (ICP-MS;
Finnigan MAT ELEMENT2 (Thermo Finnigan, San Jose, CA) similar to that previously
described (68,69). This analysis method also incorporates daily
QA/QC measures such as field blanks, acid blanks, laboratory blanks, replicate
analyses, and external standards certified by the National Institute of Standards
and Technology (NIST) (e.g., NIST SRM 1643c).
PM samples collected on quartz filters are analyzed for carbonaceous aerosols
at the UMAQL using a thermal-optical analyzer (Sunset Labs, Forest Grove, OR).
The speciation of organic carbon (OC) and elemental carbon (EC) is accomplished
through gradient heating and continuous monitoring of filter transmittance with
flame ionization detection. This method has been previously described (70,71)
and also includes the equivalent QA/QC measures described above for gravimetric
and trace element determinations.
Results
Method Comparisons for Particulate Matter Collection: Samplers and Inlets
Automated samplers for ambient PM collection, although ideally suited to fixed-site
outdoor air monitoring efforts, tend to be prohibitively large, costly, and
immobile for indoor home and personal exposure monitoring. To circumvent these
problems, customized manual sampling techniques were developed for CAAA that
allow these types of exposure monitoring to be conducted. Because it is necessary
to use different sampling systems and approaches to quantify PM levels in each
of the microenvironments (i.e., indoor, outdoor, personal), a sampler methods
comparison is performed to characterize any inherent differences in sampler
performance for PM collection. This is essential because different sampler inlets
and monitors are used in each of the microenvironments sampled. Results are
presented below for sampler intercomparisons conducted during the first year
of CAAA exposure assessment.
Personal exposure monitors versus standard cyclone inlets for PM10.
Differences in particle collection efficiency for PM10 measured with
the PEMs and standard cyclone inlets were investigated over two seasonal assessment
periods in each of the indoor classroom sampling locations. These filters were
collected concurrently each day for 2 weeks during each seasonal assessment.
Figure 2 shows the results of this method intercomparison. Regression of the
PEM data against the cyclone data yields a slope of 1.05, with r2
of 0.91 (n = 18). Figure 2 illustrates that the two methods are very
comparable for collection of PM10 over a wide concentration range
(5-75 µg/m3), as the mean percent difference between the
two methods is 17.1%.
 |
Figure 2.
Sample inlet method intercomparison between PEM inlets and standard
cyclone inlets for PM10 conducted inside community school
classrooms (n = 18).
|
Standard cyclone inlets versus sequential dichotomous samplers for PM2.5
and PM10. The collection efficiency for PM2.5
and PM10 was investigated by side-by-side measurements performed
daily with the standard cyclone inlets and the sequential dichotomous samplers
over three seasonal assessment periods at each of the community monitoring sites.
Figure 3 illustrates that the two methods are not statistically different from
each other for collection of PM10 (fine and coarse filter combined
for dichotomous sampler) over a range of 5-50 µg/m3. The
mean percent difference between the two methods was 10.6% (n = 56). However,
differences in particle collection efficiency for fine and coarse fraction determinations
were observed between the two methods, as illustrated in Figures 4 and 5. For
determination of PM2.5, the standard cyclone inlets resulted in significantly
higher concentrations (p < 0.05 average of 19.0% higher) than the
dichotomous sampler, as seen in Figure 4. This difference is likely due to the
sharper particle size cut at 2.5 µm provided by the dichotomous sampler
inlet. In contrast, the standard cyclone inlets were found to be significantly
lower (p < 0.05 average of 28.3% lower) than the dichotomous samplers
for determination of the coarse particle fraction (PM2.5-10),
as seen in Figure 5. This, again, is due to the sharper size cut at 2.5 µm
provided by the dichotomous sampler, as the coarse particle fraction for the
standard cyclones is determined by subtracting the PM2.5 sampler
value from the PM10 sampler value. These characterized methodological
differences will be of paramount importance in ultimately gaining a quantitative
understanding of true differences in personal exposures among the various microenvironments.
 |
Figure 3.
Sample inlet method intercomparison between sequential dichotomous samplers
and standard cyclone inlets for PM10 conducted at ambient
community monitoring sites (n = 56).
|
 |
Figure 4.
Sample inlet method intercomparison between sequential dichotomous samplers
and standard cyclone inlets for fine fraction particulate (PM2.5)
conducted at ambient community monitoring sites (n = 56).
|
 |
Figure 5.
Sample inlet method intercomparison between sequential dichotomous samplers
and standard cyclone inlets for coarse fraction particulate (PM2.5-10)
conducted at ambient community monitoring sites (n = 56).
|
Standard cyclone inlets versus continuous TEOM instruments with sharp-cut
cyclones for PM2.5. Differences in PM2.5 concentrations
measured with the standard cyclone inlets and the continuous TEOM instruments
equipped with SCC were investigated. Data from both outdoor community monitoring
sites collected during the four seasonal assessment periods were used. These
data expand upon the results previously presented for the first two seasonal
assessment periods (71). The standard cyclone inlets resulted
in significantly higher PM2.5 (p < 0.05 average of 14.1%
higher, n = 104) than the PM2.5 measured with the TEOM equipped
with SCC inlet at the two monitoring sites for the autumn, spring, and summer
assessment periods. This is likely because of the sharper particle size cut
obtained with the SCC inlet, as previous characterization studies using the
standard cyclones and the TEOM equipped with a standard cyclone show the two
methods to be in good agreement (72). The effects of the SCC inlet
are relatively consistent in the spring, summer, and autumn seasonal assessment
data. However, the TEOM PM2.5 is much lower on average (27%, n
= 19) than the standard cyclones PM2.5 during the winter assessment.
This relatively large difference during the winter season is primarily driven
by TEOM sampling bias encountered during the winter season related to the instrument's
internal filter temperature set point with regard to loss of semivolatile nitrate
and organic compounds from the filter, as previously discussed by Dvonch et
al. (72). Novel approaches to modify the TEOM monitor and characterize
the performance of this instrument have recently been reported (73).
Particulate Matter Exposure Assessment
Particulate matter characterization at community schools. Meteorological
measurements of wind speed, wind direction, temperature, pressure, and relative
humidity were performed at each school. Table 1 provides an overview of the
meteorological results for the first year of data collection and provides other
air quality indicators measured at the sites. The meteorological conditions
observed during the intensive assessment periods fell within the climatological
norms for Detroit for year 1 of the study, except winter 2000, which was on
average slightly above the climatological mean temperature. Included in the
table are the mean and maximum 1-hr ozone concentration, the maximum 1-hr PM2.5
concentration measured with the TEOM, the maximum daily PM concentrations measured
during each season, and the mean concentrations measured both indoors and outdoors
at the two community schools in each season. Results from the first five seasonal
campaigns (October 1999-October 2000) indicate daily PM2.5 levels
averaged 17.0 ± 9.3 µg/m3 and 15.5 ± 9.0 µg/m3
at the southwest Detroit and east Detroit sites, respectively. Daily PM10
for the same measurement periods resulted in 28.9 ± 14.4 µg/m3
and 23.8 ± 12.1 µg/m3 at the two sites, respectively. Levels
of both PM2.5 and PM10 are significantly higher at the
southwest Detroit site relative to the east Detroit site. Although levels of
both PM10 and PM2.5 had large daily variability in both
communities, even larger variations (over 100 µg/m3) in PM2.5
were observed with the TEOM on shorter temporal scales (30 min) (Figure 6).
 |
Figure 6.
Continuous (30-min integrated) PM2.5 measured with a TEOM
at the southwest Detroit ambient community monitoring site on 23 September
2000.
|
Indoor PM levels are very sensitive to infiltration rates that tend to be
higher for smaller particles. Both the community schools studied, Keith and
Maybury, have no air conditioning, and the levels of PM indoors varied dramatically
and proportionately with the outdoor levels when the school windows were opened.
As seen in Table 1, the indoor classroom PM levels more closely follow the outdoor
PM levels during the spring, summer, and fall seasons when the outdoor temperatures
are generally higher. In contrast, classroom PM levels are well below ambient
during the winter season.
Personal and home indoor particulate matter characterization.
The most difficult measurement to perform is the personal exposure measurement.
Many studies have been performed that have attempted to characterize the personal
exposure of people using various sampling techniques. Table 2 shows the average
PM10 concentrations by season measured with the PEMs worn by the
20 children with asthma participating in this portion of the study. On average,
for all four seasons in collection year 2000, personal exposures to PM10
were 68.4 ± 39.2 µg/m3, or 2.7 times higher than the levels
of PM10 measured outdoors at the community level for the same periods
(25.8 ± 11.8 µg/m3). However, personal PM10
levels were not significantly higher than indoor PM10 levels measured
in homes during the same periods (52.2 ± 30.6 µg/m3). The
PM levels in this study are similar in magnitude to levels of indoor home PM2.5
and PM10 and personal PM10 measured in previous studies
for children in urban locations (74-77). Although children living
in homes with at least one smoker tended to have higher PM exposures than children
living in nonsmoking homes, this was not always the case. Personal exposures
for individual children were 2-3 times higher than the indoor or outdoor
concentrations measured concurrently, regardless of their household smoking
status. However, indoor levels of PM (both PM10 and PM2.5)
in homes of children with asthma living in a smoking household were statistically
higher than indoor levels of PM in nonsmoking households. As seen in Table 2,
the levels of PM were, on average, about twice as high in the smoking homes
compared with those in the nonsmoking homes.
Discussion and Future Work
The first year results suggest that the levels of fine PM in the two Detroit
communities will exceed the proposed annual NAAQS for PM2.5 of 15
µg/m3. The influence of local sources on both PM2.5
and PM10 was clearly observed in the year 1 data. Outdoor levels
of PM in both size fractions were found to be significantly greater in the southwest
community than in the eastside community and also appear to drive the indoor
PM levels in both the schools and homes to be higher as well. The increased
levels in southwest Detroit, where the coarse particle fraction (PM2.5-10)
makes up nearly 40% of the total PM10, are likely due to the proximity
of the southwest community to the heavy industry on and around Zug Island, as
well as the proximity to interstate motorways and the entrance to the Ambassador
Bridge leading to Windsor, Canada (Figure 1). The bridge from Detroit to Windsor
is the most traveled international border crossing between the two countries.
Because of local traffic patterns, truck routes take all bridge-bound traffic
through the southwest Detroit community. This results in a continuous queue
of diesel truck traffic through the community. Preliminary analysis of data
collected during the summer of 2000 at Maybury Elementary School suggests that
traffic contributes a significant fraction of the PM measured at this site with
a majority of the measured PM in the submicron size range.
While outdoor PM levels across the city may not meet the new NAAQS for PM2.5,
indoor levels of PM in nonsmoking homes are typically 1.5-2 times higher
than the outdoor PM levels. Smoking continues to be a major contributor to the
PM levels measured indoors, as well as contributing to the personal PM exposures
of children with asthma. Whereas a child's exposure to secondhand smoke can
voluntarily be reduced through education and intervention, exposure to such
things as diesel emissions and other industrial emissions can only be remedied
through effective policy decisions and through emissions control programs. Previous
studies have attempted to find associations of higher incidences of asthma with
specific sources such as traffic patterns and density. One study found evidence
that children with asthma living near busy roads may have an increased risk
of repeated medical care visits, compared with children with asthma living near
lower traffic densities (78). Thus, identifying the sources of
the PM exposure must be a high priority for children living in industrialized
urban areas like Detroit.
Comprehensive elemental characterization (trace metals, EC, OC) of all filter
samples over the 2-year collection period will provide a more complete assessment
of the PM components. A detailed source apportionment of the elevated PM exposures
measured for the children with asthma in each microenvironment can then be performed.
For example, tracer species of specific source types can be used within a receptor-modeling
framework to identify the major sources contributing to PM in each community.
Furthermore, daily diaries and activity patterns will be linked with the exposure
metrics to determine the relationship between children's exposure to PM and
their daily activities and to determine the effects of these exposures on their
respiratory health.
The second-year data collection activities will expand upon the measurements
performed in year 1 by making microenvironmental measurements only when the
children are present in the microenvironment, e.g., 8 a.m. to 4 p.m. for measurements
in the school classrooms. Additional measurements will be made to more fully
characterize the size distributions of the ambient PM, including the ultrafine
particles, as well as provide for a more complete chemical characterization
of the PM to which the children with asthma living in these communities are
exposed. Furthermore, continuous EC measurements, using an aethalometer, will
be performed in the southwest community to specifically address exposure to
diesel emissions. When combined with other project metrics including twice-daily
seasonal PEF and FEV1 measurements and daily asthma symptom and medication
dairies for 300 children with asthma, and daily characterization of PM personal
exposure and PM indoor home exposure for a subset of 20 of the children, the
chemical and elemental data will allow investigations not only into the sources
of PM in the Detroit airshed with regard to PM exposure assessment but also
into the role of air pollutants in exacerbation of childhood asthma.
There is considerable research evidence indicating an association between
indoor and outdoor environmental exposures and childhood asthma (15-25)
and that such exposures are particularly concentrated in urban, low-income communities
of color (50,51,54-59). The results presented here are consistent
with these findings and point to the need to better understand and address the
sources of both indoor and outdoor pollutants. In keeping with the recommendations
of the Committee on Environmental Justice (60), the CAAA project
is involving community partners in collecting, analyzing, interpreting, and
disseminating the results of this research as well as in developing, implementing,
and evaluating household-, community-, and policy-level strategies aimed at
reducing these exposures and improving the health of children and their families
in Detroit. Interventions to reduce exposures based upon sound scientific data
and relevant exposure metrics is a key to the CAAA approach for implementing
these strategies. |
|
 |
| [References Listed in PubMed] References and Notes
1. American Lung Association. Epidemiology and Statistics
Unit, Trends in Asthma Morbidity and Mortality. 1998. Available: http://www.lungusa.org/data/asthma
[accessed April 1997].
2. Mannino DM, Homa DM, Pertowski CA, Ashizawa A, Nixon
LL, Johnson CA, Ball LB, Jack E, Kang D. Surveillance of asthma - United States,
1960-1995. Morb Mortal Wkly Rep, CDC Surveill Summ 47(SS-1):1-28 (1998).
3. Eggleston PA. Urban children and asthma: morbidity
and mortality. Immunol Allergy Clin N Am 18(1):75-84 (1998).
4. Gergen PJ, Mullally DI, Evans R. National survey of
prevalence of asthma among children in the United States 1976 to 1980. Pediatrics
8:1-7 (1988).
5. Nelson DA, Johnson CC, Divine GW, Strauchman C, Joseph
CL, Ownby DR. Ethnic differences in the prevalence of asthma in middle class
children. Ann Allergy Asthma Immunol 78:21-26 (1997).
6. Joseph CLM, Foxman B, Leickly FE, Peterson E, Ownby
D. Prevalence of undiagnosed asthma in urban school children. J Pediatr 129(5):735-742
(1996).
7. Michigan Department of Community Health. 1997. Health
Statistics Report. Michigan Department of Community Health. Available: http://www.ndnh.state.mi.us
[accessed April 1997].
8. Bates DV. Observations on asthma. Environ Health Perspect
103(suppl 6):243-247 (1995).
9. Beggs PJ, Curson PH. An integrated environmental asthma
model. Arch Environ Health 50(2): 87-94 (1995).
10. Crater SSE, Platts-Mills TA. Searching for the cause
of the increase in asthma. Curr Opin Pediatr 10(6):594-599 1998.
11. Grant EN, Wagner R, Weiss KB. Observations on emerging
patterns of asthma in our society. J Allergy Clin Immunol 104(2):S1-S9 (1999).
12. Morgan WJ, Martinez FD. Risk factors for developing
wheezing and asthma in childhood. Pediatr Clin N Am 39:1185-1203 (1999).
13. Sears MR. Epidemiology of childhood asthma. Lancet
350:1015-1020 (1997).
14. Weiss KB, Gerger PJ, Crain EF. Inner-city asthma:
the epidemiology of an emerging US public health concern. Chest 101(6):362s-367s
(1992).
15. Barber K, Mussin E, Taylor DK. Fetal exposure to involuntary
maternal smoking and childhood respiratory disease. Anna Allergy Asthma Immunol
76:427-430 (1996).
16. Cuijpers CEJ, Swaen G, Wesseling G, Sturmans F, Wouters
EF. Adverse-effects of the indoor environment on respiratory health in primary-school
children. Environ Res 68(1):11-23 (1995).
17. Forastiere F, Corbo GM, Michelozzi P, Pistelli R,
Agabiti N, Brancato G, Ciappi G, Perucci CA. Effects of environment and passive
smoking on the respiratory health of children. Int J Epidemiol 21:67-73 (1992).
18. Goren AI, Hellmann S. Respiratory conditions among
schoolchildren and their relationship to environmental tobacco smoke and other
combustion products. Arch Environ Health 50(2):112-118 (1995).
19. Hu FB, Persky V, Flay BR, Zelli A, Cooksey J, Richardson
J. Prevalence of asthma and wheezing in public schoolchildren: association with
maternal smoking during pregnancy. Ann Allergy Asthma Immunol 79:80-84 (1997).
20. Infante-Rivard C. Childhood asthma and indoor environmental
risk factors. Am J Epidemiol 137:834-844 (1993).
21. Leaderer BP, Beckett WA. Epidemiologic evidence of
an association between air quality and asthma. J Pharmacy Pharmacol 49(3):39-44
(1997).
22. Newman-Taylor A. Environmental determinants of asthma.
Lancet 345(8945):296-299 (1995).
23 Ostro BD, Lipsett MJ, Mann JK, Wiener MB, Selner J.
Indoor air pollution and asthma: results from a panel study. Am J Respir Crit
Care Med 149:1400-1406 (1994).
24. Platts-Mills TAE, Sporik RB, Chapman MD, Heumann PW.
The role of indoor allergens in asthma. Allergy 50:5-12 (1995).
25. Silvestri M, Oddera S, Rossi GA, Crimi P. Sensitization
to airborne allergens in children with respiratory symptoms. Ann Allergy Asthma
Immunol 76:239-244 (1996).
26. Arruda K, Rizzo MC, Chapman MD, Fernandex-Caldas E,
Baggio D, Platts-Mills TAE, Naspit CK. Exposure and sensitization to dust mite
allergens among asthmatic children in Sao Paulo, Brazil. Clin Exp Allergy J
21:433-439 (1991).
27. Charpin D, Birnbaum J, Haddi E, Genard G, Lanteaume
A, Toumi M, Faraj F, Van der Brempt X, Vervloet D. Altitude and allergy to house
dust mites: a paradigm of the influence of environmental exposure on allergic
sensitization. Am Rev Respir Dis 143:983-986 (1991).
28. Platts-Mills TAE, Chapman MD. Dust mites: immunology,
allergic disease, and environmental control. J Allergy Clin Immunol 80:755-775
(1987).
29. Platts-Mills TAE, Thomas WR, Aalberse RC, Vervoloet
D, Chapman MD. Dust mite allergens and asthma: report of a 2nd international
workshop. J Allergy Clin Immunol 89:1046-1060 (1992).
30. Rosenstreich DL, Eggleston PA, Kattan M, Baker D,
Slavin RG, Gergen P, Mitchell H. McNiff-Mortimer K, Lynn H, Ownby D, Malveaux
F. The role of cockroach allergy and exposure to cockroach allergen in causing
morbidity among inner-city children with asthma. N Engl J Med 336:1356-1363
(1997).
31. Sporik R, Holgate ST, Platts-Mills TAE, Cogswell J.
Exposure to house dust mite allergen (der p I) and the development of asthma
in childhood: a prospective study. N Engl J Med 323:502-507 (1990).
32. Sporik RB, Chapman MD, Platts-Mills TAE. House dust
mite exposure as a cause of asthma. Clin Exp Allergy J 22:897-906 (1992).
33 Ogston SA, Florey CV, Walker CH. The Tayside infant
morbidity and mortality study: effect on health using gas for cooking. Br Med
J 290:957-960 (1985).
34. Neas LN, Dockery DW, Ware JH, Spengler JD, Speizer
FE, Ferris BG Jr. Association of indoor nitrogen dioxide with respiratory symptoms
and pulmonary function in children. Am J Epidemiol 134:204-219 (1991).
35. Abbey DE, Petersen F, Milis PK, Beeson WL. Long-term
ambient concentrations of total suspended particulates, ozone, and sulfur dioxide
and respiratory symptoms in a nonsmoking population. Arch Environ Health 48:33-46
(1993).
36. Koenig JQ, Larson TV, Hanley QS, Rebolledo V, Dumler
K, Checkoway H, Wang SZ, Lin D, Pierson WE. Pulmonary function changes in children
associated with fine particulate matter. Environ Res 63:26-38 (1993).
37. Pope CA, Dockery DW, Spengler JD, Raizenne ME. Respiratory
health and PM10 pollution. A daily time series analysis. Am Rev Respir
Dis 144:668-674 (1991).
38. Schwartz J, Siater D, Larson TV, Pierson WE, Koenig
JQ. Particulate air pollution and hospital emergency room visits for asthma
in Seattle. Am Rev Respir Dis 147:826-831 (1993).
39. Walters S, Griffiths RK, Ayres JG. Temporal association
between hospital admissions for asthma in Birmingham and ambient levels of sulphur
dioxide and smoke. Thorax 49:133-140 (1994).
40. Cody RP, Weisei CP, Birnbaum G, Lioy PJ. The effects
of ozone associated with summertime photochemical smog on the frequency of asthma
visits to hospital emergency departments. Environ Res 58:184-194 (1992).
41. Kesten S, Szaiai J, Dzyngei B. Air quality and the
frequency of emergency room visits for asthma. Ann Allergy Asthma Immunol 74:269-273
(1995).
42. Ostro BD, Lipsett Mi, Mann JK, Braxton-Olwens H, White
MC. Air Pollution and asthma exacerbations among African-American children in
Los Angeles. Inhal Toxicol 7:711-722 (1995).
43. Ponka A. Asthma and low level air pollution in Helsinki.
Arch Environ Health 46:262-270 (1991).
44. Romieu I, Meneses F, Sienra-Monge JJ, Huerta J, Ruiz
Velasco S, White MC, Etzel RA, Hernandez-Avila M. Effects of urban air pollutants
on emergency visits for childhood asthma in Mexico City. Am J Epidemiol 141:546-553
(1995).
45. Thurston GD, Ito K, Kinney PL, Lippmann M. A multi-year
study of air pollution and respiratory hospital admissions in three New York
State metropolitan areas: results for 1988 and 1989 summers. J Expos Anal Environ
Epidemiol 2:429-450 (1992).
46. White MC, Etzei RA, Wilcox WD, Lloyd C. Exacerbations
of childhood asthma and ozone pollution in Atlanta. Environ Res 65(1):56-68
(1994).
47. Schwartz J. Air Pollution and hospital admissions
for the elderly in Detroit, Michigan. Am J Respir Crit Care Med 150:648-655
(1994).
48. Schwartz J. Short term fluctuations in air pollution
and hospital admissions of the elderly for respiratory diseases. Thorax 50:531-538
(1995).
49. Dockery DW, Pope CA. Acute respiratory effects of
particulate air pollution. Annu Rev Public Health 15:107-136 (1994).
50. Schwartz J. Particulate air pollution and chronic
respiratory disease. Environ Res 62:7-13 (1993).
51. U.S. EPA. Air Quality Criteria for Particulate Matter.
EPA/600/P-95/001aF-001cF. Washington, DC:U.S. Environmental Protection Agency,
April 1996.
52. Gildemeister AG. Urban Atmospheric Mercury: The Impact
of Local Sources on Deposition and Ambient Concentration Assessing in Detroit,
Michigan [PhD Dissertation]. Ann Arbor, MI:University of Michigan, 2001.
53. U.S. EPA. Final Guidance for Incorporating Environmental
Justice Concerns in EPA's NEPA Compliance Analyses. Washington, DC:U.S. Government
Printing Office, 1998. Available:http://es.epa.gov/oeca/
ofa/ejepa.html [accessed April 1997].
54. Bryant B, Mohai P. Race and the Incidence of Environmental
Hazards: A Time for Discourse. Boulder, CO:Westview Press, 1992.
55. Bullard RD, ed. Unequal Protection: Environmental
Justice and Communities of Color. San Francisco:Sierra Club Books, 1994.
56. Bullard RD. Solid waste sites and the Black Houston
community. Sociol Inq 53:273-288 (1993).
57. Commission for Racial Justice. Toxic Waste and Race
in the United States: A National Report on the Racial and Socio-Economic Characteristics
of Communities with Hazardous Waste Sites. New York:United Church of Christ,
1987
58. Wernette DR, Nieves LA. Breathing polluted air. EPA
J 18(1):16-17 (1992).
59. American Lung Association. Minorities and Air Pollution
Fact Sheets. New York:American Lung Association, 1998.
60. Committee on Environmental Justice. Toward Environmental
Justice: Executive Summary. Washington, DC:National Academy Press, 1999.
61. Israel BA, Schulz AJ, Parker EA, Becker AB. Review
of community-based research: assessing partnership approaches to improve public
health. Annu Rev Public Health 19:173-202 (1998).
62. Krieger N. Epidemiology and the web of causation:
has anyone seen the spider? Soc Sci Med 39(7):887-903 (1994).
63. Krieger N, Rowley DL, Herman AA, Avery B, Phillips
MT. Racism, sexism, and social class: implications for studies of health, disease,
and well-being. Am J Prev Med 9(6):82-122 (1993).
64. Williams DR, Collins C. US socioeconomic and racial
differences in health: patterns and explanations. Annu Rev Sociol 21:349-386
(1995).
65. House JS, Williams DR. Understanding and reducing
socioeconomic and racial/ethnic disparities in health, www.nap.edu/openbook/0309071755/html/82.html
[accessed April 1997].
66. Israel BA, Lichtenstein R, Lantz P, McGranaghan R,
Allen A, Guzman R, Softley D, Maciak B. The Detroit Community-Academic Urban
Research Center: lessons learned in the development, implementation and evaluation
of a community-based participatory research partnership. J Public Health Manage
Practice 7(5)1-19 (2001).
67. U.S. Census Bureau. Available: http://www.census.gov
[accessed April 1997]/
68. Long SE, Martin TD. Method 200.8. In: Methods for
the Determination of Metals in Environmental Samples. Environmental Monitoring
Systems Laboratory, Office of Research and Development. Boca Raton, FL:CRC Press,
1992.
69. Dvonch JT, Graney JR, Marsik FJ, Keeler GJ, Stevens
RK. An investigation of source-receptor relationships for mercury in south Florida
using event precipitation data. Sci Total Environ 213:95-108 (1998).
70. Cassinelli ME, O'Connor PF, eds. NIOSH Method 5040,
In: NIOSH Manual of Analytical Methods, 4th ed., 2nd Supplement [Supplement
to DHHS (NIOSH) Publ no. 94-113]. Cincinnati, OH:National Institute for Occupational
Safety and Health, 1998.
71. Huntzicker JJ, Johnson RL, Shah JJ, Cary RA. Analysis
of organic and elemental carbon in ambient aerosol by a thermal-optical method.
In: Particulate Carbon: Atmospheric Life Cycle (Wolff GT, Klimisch RL, eds).
New York:Plenum Press,1982;79-88.
72. Dvonch JT, Marsik FJ, Keeler GJ, Robins TG, Yip F,
Morishita M. Field comparison of PM2.5 TEOM and PM2.5
manual filter-based measurement methods in urban atmospheres. J Aerosol Sci
31(suppl 1):S190-S191 (2000).
73. Eatough DJ, Eatough NL, Obeidi F, Pang Y, Modey W,
Long R. Continuous determination of PM2.5 mass, including semi-volatile
species. Aerosol Sci Technol 34:1-8 (2001).
74. Ozkaynak H, Xue J, Spengler J, Wallace LA, Pellizari
E, Jenkins P. Personal exposure to airborne particles and metals: results from
the particle TEAM study in Riverside, California. J Expos Anal Environ Epidemiol
6(1):57-78 (1996).
75. Janssen N, Hoek G, Harssema H, Brunekreef B. Childhood
exposure to PM10: relation between personal, classroom, and outdoor
concentrations. Occup Environ Med 54:888-894 (1997).
76. Brauer M, Hruba F, Mihalikova E, Fabianova E, Miskovic
P, Plzikova A, Lendacka M, Vandenberg J, Cullen A. Personal exposure to particles
in Banska Bystrica, Slovakia. J Expos Anal Environ Epidemiol 10:478-487 (2000).
77. Wheeler AJ, Williams I, Beaumont RA, Hamilton RS.
Characterisation of particulate matter sampled during a study of children's
personal exposure to airborne particulate matter in a UK urban environment.
Environ Monit Assess 65:69-77 (2000).
78. McConnel R, Berhane K, Gilliland F, London SJ, Voa
H, Avol E, Gauderman WJ, Margolis HG, Lurmann F, Thomas DC, Peters JM. Air pollution
and bronitic symptoms in southern California children with asthma. Environ Health
Perspect 9:757-767 (1999).
Last Updated: March 28, 2002 |
|
 |
|
| |