The environmental protection agency's research program on total human exposure

Ott, Wayne R.; Wallace, Lance; Mage, David T.; Akland, Gerald; Lewis, Robert W.; Sauls, Harold B.; Rodes, Charles; Kleffman, David; Kuroda, Donna; Morehouse, Karen

doi:10.1016/0160-4120(86)90064-4

Cited by 19 publications

(4 citation statements)

References 26 publications

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“…Though a CSF could have been used for the MESH study, in general, few health-based values (such as a RfD, CSF, reference concentration or BEI) are available to put biomonitoring results into context [ 5 ]. A Transparent, Bi-directional Discussion about Risk Assessment with Communities—Current knowledge of exposure and dose is limited for most contaminants of concern and since the human health risk model is sequential, the lack of accurate information can severely weaken the ability to assess risk and protect human health [ 68 ]. These data gaps are more pronounced in children’s exposure assessment (e.g., [ 69 ]).…”

Section: Discussionmentioning

confidence: 99%

Improving Environmental Health Literacy and Justice through Environmental Exposure Results Communication

Ramírez‐Andreotta

Brody

Lothrop

et al. 2016

IJERPH

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Understanding the short- and long-term impacts of a biomonitoring and exposure project and reporting personal results back to study participants is critical for guiding future efforts, especially in the context of environmental justice. The purpose of this study was to evaluate learning outcomes from environmental communication efforts and whether environmental health literacy goals were met in an environmental justice community. We conducted 14 interviews with parents who had participated in the University of Arizona’s Metals Exposure Study in Homes and analyzed their responses using NVivo, a qualitative data management and analysis program. Key findings were that participants used the data to cope with their challenging circumstances, the majority of participants described changing their families’ household behaviors, and participants reported specific interventions to reduce family exposures. The strength of this study is that it provides insight into what people learn and gain from such results communication efforts, what participants want to know, and what type of additional information participants need to advance their environmental health literacy. This information can help improve future report back efforts and advance environmental health and justice.

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Section: Discussionmentioning

confidence: 99%

Improving Environmental Health Literacy and Justice through Environmental Exposure Results Communication

Ramírez‐Andreotta

Brody

Lothrop

et al. 2016

IJERPH

View full text Add to dashboard Cite

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“…Concentrations measured at fixed monitoring sites or concentration surrogates (such as nearby traffic counts) are used to derive exposures at the residence locations (Huang and Batterman 2000 ; Meng et al 2007 ; von Klot et al 2009 ). Although this is a relatively simple and generalizable approach that can be applied in the context of available data, it is recognized that human activity patterns may be particularly important for explaining exposure variation (Klepeis et al 2001 ; National Center for Environmental Assessment et al 2011 ; Ott et al 1986 ). Hence, exposure error and misclassification are concerns, with potential outcomes of inaccurate health and environmental impact assessments and policy interventions (Huang and Batterman 2000 ; Krzyzanowski 1997 ; Özkaynak et al 1986 ; Sheppard et al 2012 ; Thomas et al 1993 ; Zeger et al 2000 ).…”

Section: Introductionmentioning

confidence: 99%

Impacts of travel activity and urbanicity on exposures to ambient oxides of nitrogen and on exposure disparities

Gurram

Stuart

Pinjari

2014

Air Qual Atmos Health

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Daily exposures to ambient oxides of nitrogen were estimated here for residents of Hillsborough County, FL. The 2009 National Household Travel Survey provided geocoded data on fixed activity locations during each person-day sampled. Routes between activity locations were calculated from transportation network data, assuming the quickest travel path. To estimate daily exposure concentrations for each person-day, the exposure locations were matched with diurnally and spatially varying ambient pollutant concentrations derived from CALPUFF dispersion model results. The social distribution of exposures was analyzed by comparing frequency distributions of grouped daily exposure concentrations and by regression modeling. To investigate exposure error, the activity-based exposure estimates were also compared with estimates derived using residence location alone. The mean daily activity-based exposure concentration for the study sample was 17 μg/m3, with values for individual person-day records ranging from 7.0 to 43 μg/m3. The highest mean exposure concentrations were found for the following groups: black (20 μg/m3), below poverty (18 μg/m3), and urban residence location (22 μg/m3). Urban versus rural residence was associated with the largest increase in exposure concentration in the regression (8.3 μg/m3). Time in nonresidential activities, including travel, was associated with an increase of 0.2 μg/m3 per hour. Time spent travelling and at nonresidential locations contributed an average of 6 and 24 %, respectively, to the daily estimate. A mean error of 3.6 %, with range from −64 to 58 %, was found to result from using residence location alone. Exposure error was highest for those who travel most, but lowest for the sociodemographic subgroups with higher mean exposure concentrations (including blacks and those from below poverty households). This work indicates the importance of urbanicity to social disparities in activity-based air pollution exposures. It also suggests that exposure error due to using residence location may be smaller for more exposed groups.

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“…The exact time of day recorded by the PEM when combined with activity data allowed microenvironmental CO concentrations to be related to human activities, thus providing a complete CO exposure profile of each person carrying the instrument. 13 The lowest detectable level of the PEM was approximately 1 ppm. Readings between 0.5 and 1.5 ppm were rounded to 1 ppm; CO concentration levels smaller than 0.5 ppm were recorded as 0 ppm.…”

Section: Denver Pem Data Basementioning

confidence: 93%

“…There are two "primary" (health-based) CO NAAQS: a 1-hr 40 mg/m 3 (35 ppm) and an 8-hr 10 mg/m 3 (9 ppm). These standards were first promulgated in 1971 (36 FR 8186; April 30, 1971) and were reaffirmed in both 1985 (50 FR 37484; Sept. 13,1985) and 1994 (59 FR 38906; August 1, 1994). As part of its standard review activities, the EPA undertakes an exposure modeling analysis using the pNEM/CO model.…”

Section: Introductionmentioning

confidence: 95%

Evaluation of a Probabilistic Exposure Model Applied to Carbon Monoxide (pNEM/CO) Using Denver Personal Exposure Monitoring Data

Law¹,

Lioy²,

Zelenka³

et al. 1997

Journal of the Air & Waste Management Association

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The probabilistic National Ambient Air Quality Standards (NAAQS) Exposure Model applied to carbon monoxide (pNEM/CO) was developed by the U.S. Environmental Protection Agency (EPA) to estimate frequency distributions of population exposure to carbon monoxide (CO) and the resulting carboxyhemoglobin (COHb) levels. To evaluate pNEM/CO, the model was set up to simulate CO exposure data collected during a Denver Personal Exposure Monitoring Study (PEM) conducted during the winter of 1982-1983. This paper compares computer-simulated exposure distributions obtained by pNEM/CO with the observed cumulative relative frequency distributions of population exposure to CO from 779 people in the Denver PEM study. The subjects were disaggregated into two categories depending upon whether they lived in a home with a gas stove or an electric stove. The observed and predicted population exposure frequency distributions were compared in terms of 1-hr daily maximum exposure (1DME) and 8-hr daily maximum moving average exposure (8DME) for people living in homes with gas stove or an electric stove. For 1DME, the computer-simulated results from pNEM/CO agreed most closely within the range of 6-13 ppm, but overestimated occurrences at low exposure (<6 ppm) and underestimated occurrences at high exposure (>13 ppm). For 8DME, the predicted exposures agreed best with observed exposures in the range of CO concentration between 5.5 and 7 ppm, and over-predicted occurrences below 5.5 ppm and under-predicted occurrences above 7 ppm.

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The environmental protection agency's research program on total human exposure

Cited by 19 publications

References 26 publications

Improving Environmental Health Literacy and Justice through Environmental Exposure Results Communication

Improving Environmental Health Literacy and Justice through Environmental Exposure Results Communication

Impacts of travel activity and urbanicity on exposures to ambient oxides of nitrogen and on exposure disparities

Evaluation of a Probabilistic Exposure Model Applied to Carbon Monoxide (pNEM/CO) Using Denver Personal Exposure Monitoring Data

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