Haynes Air Data Summary in Marietta.docx Personal air sampling in Marietta.pdf

Hello Chuck,

In response to your request, I’m forwarding you a summary of the Marietta CARES ambient air

monitoring data. I’m including Florence Fulk from EPA’s Office of Research and Development here in

Cincinnati on this email as during a recent sabbatical, she generated several of the air data plots.

I’m also forwarding the personal air sampling paper that was recently published. It contains the air

sampling methods.

Please let me know if additional information would be useful.

All the best,

E ri n

EYL4I,l’sJ. /Vl.e57, DYP, MS

Assistant Professor

Clinical and Translational Research Program, Director

Division of Epidemiology and BiostatisticsDepartment of Environmental HealthUniversity of Cincinnati, College of Medicine

3223 Eden Aye, P0 Box 670056

Cincinnati, OH 45267-0056

PH: 513-558-5427FX: 513-558-4838

UNIVERSITY Of

Cincinnati
Hi Erin,

It was good to talk with you today. As I mentioned, we are interested in obtaining the ambient air

monitoring data at Marietta College, or a summary of those data, and results of your exposure and health

research. Could you please share that information with us as it becomes available.

Let me know if you have questions.

Thanks.

Chuck

Phone: 919-541-7912
Marietta Community Actively Researching Exposure Study

PI: Erin N. Haynes, DrPH, MS

Personal and Stationary Air Data

Funded by NIH/NIEHS 1R01ES016531-01

Stationary and Personal Air Methods used by the Marietta CARES Research Study

Taken from:

Haynes, Erin N., Ryan, Patrick, Chen, Aimin, Brown D., Kuhnell, P, Wittberg D, Terrell, M., Reponen T. 

Assessment of Personal Exposure to Manganese in Children Living Near a Ferromanganese Refinery. 

Sci of Total Environ. 2012 Jun 15;427-428:19-25. Epub 2012 May 1.

Stationary Air Sampling. A stationary air sampler was positioned on the rooftop of a Marietta College 

building approximately 8 kilometers from EMI. The site was selected based on its high population density 

within the catchment area. Positioning the stationary air monitor in the highest population density area within 

the community provided an exposure scenario experienced by the anticipated majority of the study 

participants. Stationary samples were collected using Harvard-type PM2.5 impactors (MS&T Area Sampler; Air 

Diagnostics, Inc, Harrison, ME) with a high volume sampling pump, calibrated to 10 liters per minute (LPM) ± 

0.5 LPM. The sampler was equipped with a sampler ring, a Whatman support pad to prevent filter blow out, 

and a 37 mm pre-weighed Teflon membrane filter (2 μm pore size; SKC Inc., Eighty-Four, PA) to collect 

airborne particles smaller than 2.5 μm. The sampling times were 48 hours ±2 hours. Three 48-hour samples 

were collected each week. Stationary air sampling was conducted over a 2-year time frame from October 

2008 – September 2010. Only the results from the stationary air sampling during the time of the personal air 

sampling are used in these analyses. 

Personal air sampling. Personal air samples were collected using a Personal Modular Impactor, PMI 

coarse (SKC Inc.). The PMI coarse sampler is a two stage impactor, capable of sampling for PM2.5, PM2.5-10, or 

both. The PMI coarse sampler was selected to minimize the bounce of large particles on the PM2.5 filter by 

using an oiled impaction plate on the PM2.5-10 stage instead of a collection filter. 

Air pumps and battery packs were placed in a backpack, with a short Tygon® tube to connect the PMI 

sampler to the air sampling pump. The pumps were calibrated to 3 LPM ±0.1 LPM. The PMI sampler was 

equipped with the same type of Teflon filters used for outdoor sampling. The air sampling technician 

demonstrated how to wear the backpack and the sampler. The technician instructed to keep the air sampler 
near the child’s breathing zone during times when the child could not comfortably wear the backpack, for 

instance during sleep the equipment could be laid on a nightstand. The sampling time was 48 hours ± 2 hours 

and the sampler remained in or near the child’s breathing zone for the duration of the sampling time. All 

personal samples were collected during the Spring season of two consecutive years: April-June, 2009 and 

March–June, 2010. 

During a home visit with the participating families, a study team member conducted a brief 

questionnaire to determine the child’s potential exposure to particle sources during the sampling period. 

Questions included the child’s exposure to cigarette smoke, use of heating and cooking devices, candle use, 

and time sampling setup was not with subject or was outside of the Marietta area. Throughout the 48 hour 

period, parents of participants filled out an activity log to indicate the activities of the child during the sampling 

period and to identify when and if the sampling device was not with the child during the sampling period. 

Analysis of Air Sampling Filters. Teflon filters for personal and stationary outdoor samples were 

analyzed for particle mass gravimetrically and for Mn in the PM2.5 fraction using a Thermo X Series II 

inductively coupled plasma mass spectrometer (ICP-MS) by a commercial laboratory (Research Triangle 

Institute, NC). Results were reported in μg/m3 (PM2.5 mass) and ng/m3 (Mn). Ten percent (10%) of the samples 

were laboratory blanks and another 10% were field blanks to protect the validity of the sample results. The 

detection limits were 4.1 μg/sample for PM2.5 mass and 2.5 ng/sample for Mn. 
Table 1. Stationary and Personal Air Sampling for Manganese an PM2.5 during the Two Spring Personal Air 

Sampling Periods

Stationary Air Sampling Personal Air Sampling

March-May 

2009

March-June 

2010

March-May 

2009

March-June 

2010

Mn (ng/m3)

GM (St. Dev.) 5.45 (2.71) 10.33 (3.48) 7.31 (2.23) 9.03 (2.28)

95% C.I. 4.12-6.77 9.04-11.61 6.33-8.28 7.97-10.08

PM2.5 (μg/m3)

GM (St. Dev.) 7.10 (2.62) 11.73 (1.16) 15.84 (1.42) 18.17 (1.81)

95% C.I. 5.81-8.38 11.31-12.16 15.22-16.47 17.34-19.01
Monthly averages for Marietta and Cambridge were plotted. The number of filters used for each month’s 

average sample data point is outlined in the table below.

Marietta Cambridge

10/08 5 0

11/08 12 3

12/08 13 0

1/09 13 4

2/09 9 0

3/09 13 0

4/09 10 0

5/09 7 3

6/09 10 0

7/09 13 0

8/09 9 3

9/09 9 0

10/09 13 0

11/09 13 3

12/09 13 0

1/10 13 0

2/10 12 3

3/10 13 0

4/10 8 0

5/10 10 3

6/10 13 0

7/10 13 0

8/10 13 3

9/10 13 0

10/10 2 0
Monthly Mn concentration in Marietta and Cambridge

Monthly Pm2.5 Concentration in Marietta and Cambridge

All samples listed for 2008-2010 with 50 ng/m3 reference value, Blue dots are Cambridge, black dots are Marietta

0

5

10

15

20

25

30

35

40

06/08 12/08 07/09 01/10 08/10 02/11

Mn Concentration (ng/m3)

Marietta

Cambridge

0

2

4

6

8

10

12

14

16

18

20

06/08 12/08 07/09 01/10 08/10 02/11

PM2.5 Concentration (μg/m3)

Marietta

Cambridge
The line represents the current EPA reference for ambient air Mn of 50 ng/m3

.
Cumulative Distribution for Marietta
Assessment of personal exposure to manganese in children living near a

ferromanganese refinery

Erin N. Haynes a,

⁎, Pat Ryan a

, Aimin Chen a, David Brown b, Sandy Roda a, Pierce Kuhnell a, Dawn Wittberg c,

Matthew Terrell a

, Tiina Reponen a

a College of Medicine, Department of Environmental Health, University of Cincinnati, United States

b Marietta College, Department of Biology and Environmental Sciences, United States

c Neighbors for Clean Air, Marietta Ohio, United States

article info abstract

Article history:

Received 5 October 2011

Received in revised form 20 February 2012

Accepted 14 March 2012

Available online 1 May 2012

Keywords:

Personal air sampling

Manganese

Particulate matter

Exposure

Air pollution

Children

Airborne exposure to manganese (Mn) can result in neurologic effects. Stationary air sampling is the traditional

technique to assess Mn exposure for communities, yet may not accurately reflect children's personal exposure.

The goal of the study was to characterize personal exposure to Mn and PM2.5 in a cohort of children ages

7–9 years residing near a ferromanganese refinery.

A subset of children living in non-smoking households ages 7–9 enrolled in the Marietta Community Actively

Researching Exposure Study during March–June 2009 and 2010 were invited to participate. Blood and hair

were collected and analyzed for Mn. Participants wore a PM2.5 sampler (Personal Modular Impactor) for 48 h.

TWD was based on time spent at home and school and the distance of each from the refinery. Stationary outdoor

air sampling was conducted 8 km from the refinery using a Harvard-type PM2.5 impactor. The relationship

between personal Mn exposure and TWD was examined by multiple regression adjusting for stationary air

Mn concentration, wind speed and direction, and precipitation.

Complete personal air sampling data were collected on 38 children. TWD ranged from 4.7 km to 28.5 km with a

mean distance of 11.1 (4.7 sd) km. Mn concentration in personal air samples ranged from 1.5 ng/m3 to 54.5 ng/m3

(geometric mean, 8.1 ng/m3). TWD was a significant predictor of natural log personal air Mn concentration (lnMn)

with an associated decrease of 0.075 lnMn for each km TWD (pb0.05, 95% CI −0.13 to −0.01). Personal Mn

exposures were positively associated with stationary air Mn levels and inversely associated with wind speed.

A child's location (home and school) relative to the refinery is a significant predictor of personal Mn exposure.

Wind speed is also an important contributor to personal Mn exposure.

© 2012 Elsevier B.V. All rights reserved.

1. Introduction

Manganese (Mn) is an essential dietary element biologically utilized

for numerous physiologic processes as a constituent of enzymes and an

activator of other enzymes (Nielsen, 1999), such as Mn superoxide

dismutase (MnSOD), a principal antioxidant enzyme of mitochondria

(Leach and Harris, 1997). Mn enzymes are also involved in bone development (Keen and Zidenberg-Cherr, 1996), wound healing (Shetlar and

Shetlar, 1994), and the metabolism of carbohydrates, amino acids, and

cholesterol (Institute of Medicine, 2001). Upon ingestion, Mn is subject

to tight homeostatic control (Papavasiliou et al., 1966). Inhaled Mn,

however, can bypass biliary excretion mechanisms and directly enter

the systemic circulation (Davis, 1998, 1999; Keen et al., 1999). Inhaled

Mn exposure may have a dose-related continuum of nervous system

dysfunction, and the lowest level linked with neurotoxicity is unknown

(Mergler et al., 1999). At the high end of exposure (>1 mg/m3

), Mn can

result in Manganism, an extrapyramidal movement disorder similar to,

but clinically distinguishable from, Parkinson's disease (Aschner et al.,

2005; Huang et al., 1993; Pal et al., 1999). At concentrations near or

below the reference concentration (RfC) of 50 ng/m3 established by

the U.S. Environmental Protection Agency (EPA, 2009), Mn neurotoxicity includes effects on neuropsychological and motor functions

(Mergler et al., 1999), postural stability (Hudnell, 1999; Standridge et

al., 2008; Hernández-Bonilla et al., 2011), and increased risk for physician diagnosis of Parkinson's disease (Finkelstein and Jerrett, 2007).

Children and infants may be particularly susceptible for the neurotoxic

effects of environmental ambient Mn exposure due to the development

of the brain and central nervous system and the ability of ambient Mn to

cross the blood–brain barrier and accumulate in the brain (Elder et al.,

2006; Aschner, 1999, 2000, 2006). In utero exposure to environmental

Mn has also been associated with decreased neurocognitive and neuromotor functions in children (Takser et al., 2004).

Science of the Total Environment 427–428 (2012) 19–25

⁎ Corresponding author at: University of Cincinnati, MED-Environmental Health,

Kettering G32A, P. O. Box 670056, Cincinnati, OH 45267, United States. Tel.: +1 513

558 5427; fax: +1 513 558 4838.

E-mail address: erin.haynes@uc.edu (E.N. Haynes).

0048-9697/$ – see front matter © 2012 Elsevier B.V. All rights reserved.

doi:10.1016/j.scitotenv.2012.03.037

Contents lists available at SciVerse ScienceDirect

Science of the Total Environment

journal homepage: www.elsevier.com/locate/scitotenv
Mn is frequently a component of ambient particulate matter (PM),

a complex mixture of acids, organic chemicals, metals and soil or dust

particles. The coarse fraction (PM2.5–10) is often dominated by crustal

materials (e.g., windblown dust, resuspension of road dust, demolition of buildings), whereas the particles in fine (PM2.5) and ultrafine

(PM0.1) fractions are mostly formed through combustion processes

including metal refining. Fine and ultrafine particles have been associated with adverse health effects (Schwartz et al., 1996; Pope et al.,

2009) which can be attributed to the properties of these particles including size, surface area, and composition.

Eramet Marietta, Inc. (EMI), a ferromanganese refinery in operation

since 1952 (Eramet Marietta [Internet], 2011) is located in Marietta,

Ohio, a rural Appalachian American community situated along the

Ohio River. The refinery has reported their fugitive Mn emissions to

the EPA varying from 580,213 lb/year in 1999 to 101,503 lb/year in

2009 (EPA, 2011). An academic–community partnership was developed

(Haynes et al., 2011) between the University of Cincinnati and the

community to conduct an epidemiologic investigation of the neurobehavioral effects of Mn on children, the Marietta Community Actively

Researching Exposure Study (CARES). The purpose of this study was

to address, in part, one of the community-driven concerns of the “microenvironments” of children residing near the refinery by examining

personal exposure to PM2.5 and its constituents in a subset of the cohort.

Traditionally, exposure to particulate matter and Mn, in particular,

in the ambient environment is measured by stationary outdoor air

monitoring; however, outdoor stationary monitors may not be representative of personal exposures for several reasons. Stationary monitors are typically placed in locations far above the typical breathing

zone, i.e., rooftops, and humans spend the majority of their time indoors (Klepeis, 2001). Furthermore, personal exposures are often

higher than shown by microenvironmental measurements in indoor

or outdoor air because of so-called “personal cloud” effect, caused by

closer proximity to pollution sources or particle resuspension due to

human activity (Wallace, 2000). Thus, the goal of our study was to characterize personal exposure to Mn and PM2.5 in a cohort of children ages

7–9 years residing near a ferromanganese refinery.

2. Methods

2.1. Study population

Children ages 7, 8, and 9 years were recruited for participation in

the personal air sampling through their enrollment in CARES. Eligibility for CARES includes children ages 7–9 who have resided in the

Marietta area throughout their life and their biological mother having

resided in the area during pregnancy with the child. Children were

recruited for participation in CARES through recruitment letters sent

home through schools, radio and newspaper ads, and fliers. Children

enrolled in CARES from Marietta were selected to participate in the

personal air sampling study if they were reported to be residing in a

non-smoking household. The study was approved by the Institutional

Review Board of the University of Cincinnati and all participants

signed an informed consent and assent.

2.2. Stationary air sampling

A stationary air sampler was positioned on the rooftop of a Marietta

College building approximately 8 km from EMI. The site was selected

based on its high population density within the catchment area. Positioning the stationary air monitor in the highest population density

area within the community provided an exposure scenario experienced

by the anticipated majority of the study participants. Stationary samples were collected using Harvard-type PM2.5 impactors (MS&T Area

Sampler; Air Diagnostics, Inc, Harrison, ME) with a high volume sampling pump, calibrated to 10 L per minute (LPM)±0.5 LPM. The sampler was equipped with a sampler ring, a Whatman support pad to

prevent filter blow out, and a 37 mm pre-weighed Teflon membrane

filter (2 μm pore size; SKC Inc., Eighty-Four, PA) to collect airborne particles smaller than 2.5 μm. The sampling times were 48 h±2 h. Three

48-hour samples were collected each week. Stationary air sampling

was conducted over a 2-year time frame from October 2008–September

2010. Only the results from the stationary air sampling during the time

of the personal air sampling are used in these analyses.

2.3. Personal air sampling

Personal air samples were collected using a Personal Modular Impactor, PMI coarse (SKC Inc.). The PMI coarse sampler is a two stage impactor,

capable of sampling for PM2.5, PM2.5–10, or both. The PMI coarse sampler

was selected to minimize the bounce of large particles on the PM2.5 filter

by using an oiled impaction plate on the PM2.5–10 stage instead of a collection filter.

Air pumps and battery packs were placed in a backpack, with a short

Tygon® tube to connect the PMI sampler to the air sampling pump.

The pumps were calibrated to 3 LPM±0.1 LPM. The PMI sampler was

equipped with the same type of Teflon filters used for outdoor sampling. The air sampling technician demonstrated how to wear the backpack and the sampler. The technician instructed to keep the air sampler

near the child's breathing zone during times when the child could not

comfortably wear the backpack, for instance during sleep the equipment could be laid on a nightstand. The sampling time was 48 h±2 h

and the sampler remained in or near the child's breathing zone for the

duration of the sampling time. All personal samples were collected

during the Spring season of two consecutive years: April–June, 2009

and March–June, 2010.

During a home visit with the participating families, a study team

member conducted a brief questionnaire to determine the child's

potential exposure to particle sources during the sampling period.

Questions included the child's exposure to cigarette smoke, use of

heating and cooking devices, candle use, and time sampling setup was

not with subject or was outside of the Marietta area. Throughout the

48-hour period, parents of participants filled out an activity log to

indicate the activities of the child during the sampling period and to

identify when and if the sampling device was not with the child during

the sampling period.

2.4. Analysis of air sampling filters

Teflon filters for personal and stationary outdoor samples were analyzed for particle mass gravimetrically and for Mn in the PM2.5 fraction

using a Thermo X Series II inductively coupled plasma mass spectrometer (ICP-MS) by a commercial laboratory (Research Triangle Institute,

NC). Results were reported in μg/m3 (PM2.5 mass) and ng/m3 (Mn).

Ten percent (10%) of the samples were laboratory blanks and another

10% were field blanks to protect the validity of the sample results. The

detection limits were 4.1 μg/sample for PM2.5 mass and 2.5 ng/sample

for Mn.

2.5. Time weighted distance (TWD)

TWD was calculated based on time spent at home (TimeHome) and

school (TimeSchool) and the distance of each (DistanceHome and

DistanceSchool) from the ferromanganese refinery divided by the child's

total sampling time (48±2 h). The TWD was calculated using the following equation:

TWD 1⁄4 TimeHome DistanceHome ð Þþ TimeSchool DistanceSchool ð Þ

Total Time Sampled : ð1Þ

20 E.N. Haynes et al. / Science of the Total Environment 427–428 (2012) 19–25
2.6. Wind index

In order to account for the influence of wind direction on sampled

concentrations of Mn, a continuous measure of the location of the

child's home relative to the wind direction during the 48 h of sampling and the location of the primary Mn emission source, EMI, Inc.

was derived. This measure, referred to as the wind index, was

calculated as

Wind Index 1⁄4

1− Cos AngleHomePlant−AngleWind  

2 ð2Þ

where AngleHomePlant is the Euclidean direction of the Mn point source

from the child's home and AngleWind is the average wind direction

during the 48-hour sampling period obtained from the National

Climatic Data Center climate data from the Parkersburg, West Virginia

at the Mid-Ohio Valley Airport. The cosine transformation allows for a

rescaling of the difference in the home angle to the Mn point source

and wind direction to a scale with a range of 0 to 1. Hence, a home

directly upwind of the Mn point source during sampling will have a

wind index variable of 0 and homes directly downwind a value of 1.

2.7. Biological collection and analysis

2.7.1. Blood

Venipuncture samples were collected by trained phlebotomists

using a 23 gauge butterfly needle and vacutainer cuff or needle and

syringe. Proper preparation and blood collection techniques were

employed to ensure that samples were not contaminated. Blood collection equipment and supplies were tested to be trace-metal free

and were stored and set up in a manner that kept them free of dust

and contaminants. Blood collection tubes were placed in a small bag

after the box was opened to protect the tops from being contaminated.

Kimwipes®, a lint free cloth, was used to cover the tubes, place blood

collection supplies on, or used whenever needed to protect equipment

from contamination.

The blood puncture area at the site of the antecubital vein was

prepared by briskly scrubbing the area twice with alcohol pads in a

circular fashion from inside to outside, and wiping the area with a

gauze sponge following each scrub. After a 5 second air drying time

the needle was inserted into the vein and blood either aspirated

into a syringe or vacutainer tube depending on the collection method

best for the subject. A purple top tube with EDTA anticoagulant was

filled for each participant. Immediately after collection the tubes

were inverted several times and placed covered on an orbital mixer

for several minutes.

Whole blood for Mn analysis was refrigerated until shipped at

least monthly to the New York State Department of Health's (NYSDOH) Wadsworth Center, Health Research, Inc. Albany Division. The

Laboratory of Inorganic and Nuclear Chemistry under the direction

of Dr. Patrick Parsons conducted the analyses of the whole blood for

Mn by Graphite Furnace Atomic Absorption Spectroscopy (GFAAS).

A Perkin-Elmer Model 5100ZL Atomic Absorption Spectrometer

with Zeeman background correction and equipped with an AS-70

Auto-sampler was used for the analysis of the samples. The instrument was operated using a hollow cathode lamp at the 279.5 nm

line along with a slit width of 0.2 nm. Blood was diluted 1 to 9 with

an aqueous solution of 0.015% Mg(NO3)2 6H2O, 0.1% Triton® X-100,

and 0.2% HNO3. Using the auto-sampler twenty (20) μL of the diluent

was deposited into a graphite tube onto an L'vov platform. The diluent

of each sample was analyzed twice. The Method Detection Limit

(MDL), defined as three times the standard deviation of twenty separate runs of a low Mn concentration blood, was 1.5 μg/L for blood Mn.

Quality control consisted of incorporating numerous secondary blood

reference materials into daily analytical runs. There are no certified

reference materials currently available for blood Mn (Praamsma et al.,

2011).

2.7.2. Hair

Hair samples were obtained from children using ceramic scissors

cleaned with alcohol. Samples were taken from the occipital region,

cut close to the scalp, and deposited in clean, white envelopes. Approximately 20 strands of hair were isolated and cut. For children with very

short hair, samples were taken from several areas of the head and collected directly into the envelope. Hair was analyzed for Mn concentrations (μg/g) at the Channing Trace Metals Laboratory, Brigham and

Women's Hospital, Harvard School of Public Health (Boston, MA)

using methods previously described (Wright et al., 2006).

Briefly, hair samples were cleaned in 10 mL of 1% Triton X-100 solution for 15 min, followed by repeated rinsing with distilled deionized

water, and drying at 70 °C for 24 h. Subsequently, the samples were

digested with 1 mL concentrated nitric acid for 24 h and diluted to

5 mL with deionized water. Acid-digested samples were analyzed

using inductively coupled plasma-mass spectrometry (ICP-MS) (Elan

DRC II, Perkin Elmer, Norwalk, CT). Analysis of Mn was performed

using indium as the internal standard. Recovery of the analysis of

quality control standard by this procedure is 90–110%, and the coefficient of variation of the within-day analysis was b10%. Samples were

measured by the instrument five times and the average of the five replicates is reported for each child. The average method detection limit

was 1.63 ng/g.

2.8. Data analysis

The distribution of stationary and personal air Mn exposures was

examined and natural log transformation was used to reach normality (lnsMn and lnpMn for stationary and personal Mn respectively). Geometric means, geometric standard deviations, and 95% confidence

intervals were used to describe the air Mn data. The Mn and PM2.5

concentrations of stationary and personal samplings were compared

between the two testing years (2009 and 2010). Multiple linear regression models were used to examine the personal air Mn concentrations as a function of TWD, stationary air Mn concentration, wind

speed and direction, and average precipitation. Separate regression

models were used to examine the association between personal Mn

concentration and blood and hair Mn. All data analyses were performed using SAS 9.2 (SAS Institute Inc., Cary, NC), and a significance

level of 0.05.

Study data were collected and managed using REDCap electronic

data capture tools hosted at the University of Cincinnati. REDCap (Research Electronic Data Capture) is a secure, web-based application

designed to support data capture for research studies, providing: 1)

an intuitive interface for validated data entry; 2) audit trails for tracking data manipulation and export procedures; 3) automated export

procedures for seamless data downloads to common statistical packages; and 4) procedures for importing data from external sources

(Harris et al., 2009).

3. Results

A total of 48 children participated in the personal air sampling

study. Equipment failures, i.e., air pump stopped during the sampling

period, resulted in exclusion of 10 (20.8%) participants from the data

analysis. Thus, complete personal air sampling data were collected on

38 children living within a 28.5 km radius of the ferromanganese refinery (Fig. 1). All children were 7 (21%), 8 (39%), or 9 (39%) years old,

and 66% (n= 25) of the participating children were female. The majority of the participants were Caucasian (95%, n= 36), 1 was African

American (3%), and 1 was Native American (3%) (Table 1).

Although families were excluded based on report of a smoking

family member, three (8%) participating families reported having a

E.N. Haynes et al. / Science of the Total Environment 427–428 (2012) 19–25 21
family member smoking in the home during the personal air sampling for 1–2 h. Two (5%) children reported spending more than 3 h

during the 48-hour sampling period outside of the Marietta area

(Table 1). The majority (n= 29, 76%) remained in the Marietta area

during the sampling period. The personal air sampling monitor

remained with 28 (74%) of the children during the entire sampling

period, whereas 7 children (18%) did not have the monitor for

1–2 h, and 2 children (5%) reportedly did not have the monitor for

3–4h(Table 1).

Mean blood Mn concentration in the personal air sampling cohort

was 9.5 μg/L ranging from 5 μg/L to 14.4 μg/L. Mean hair Mn concentration was 0.47 μg/g and ranged from 0.085 μg/g to 1.25 μg/g. Hair

Mn and blood Mn were not significantly correlated in this sample,

with correlation coefficient of 0.26, p= 0.15. In multiple linear regression model adjusting for age, sex, and daily dietary Mn intake, hair

Mn was only slightly higher in persons with high blood Mn with an

estimate of 0.05 μg/g increase in hair Mn per 1 μg/L blood Mn (95%

CI: −0.001 to 0.095, p= 0.06). Approximately 58% (22/38) of the

children had their blood and hair collected within 14 days of their

participation in the personal air sampling component of the study.

Personal air Mn concentration varied between the 2009 and 2010

during Spring sampling periods (Table 2). The personal air Mn

appeared to be higher in 2010, but the variation did not reach

statistical significance. The stationary air Mn also demonstrated similar trend, but again no statistical significance was found between

2009 and 2010. Differences between stationary and personal air Mn

concentrations were not significant in both 2009 and 2010.

PM2.5 concentration was consistently higher in the personal air filters than in the stationary air filters (pb0.05 for both 2009 and 2010).

The stationary air PM2.5 concentration was slightly higher in 2010

than in 2009, with borderline significance (p= 0.06).

When combining the sampling periods for those with personal air

sampling (n=38), the geometric mean (GM) personal air Mn was

8.1 ng/m3, and the GM stationary air Mn was 11 ng/m3 (Table 3). The

mean stationary PM2.5 was 10.8 μg/m3, and the GM personal PM2.5

was 16.9 μg/m3. The TWD ranged from 4.7 km to 28.5 km with a mean

distance of 11.1 km (4.7 km sd) from the ferromanganese refinery

(Table 3). During the entire sampling period, wind speed averaged

8.1 km/h and ranged from 2.6 to approximately 15 km/h, and it rained

an average of 0.43 cm (sd 0.54 cm; range 0–2.25 cm). The amount of

time the participating children spent outdoors ranged from 0% to 45%

with an average of 14% (sd12%).

Based on the multiple regression model, personal air Mn concentration (pMN) was positively associated with stationary Mn concentration and inversely associated TWD and wind speed (Table 4). For

each km increase in TWD, i.e., further far from the stationary source,

Fig. 1. Map of personal air sampling participants, schools, and the stationary air sampling site.

22 E.N. Haynes et al. / Science of the Total Environment 427–428 (2012) 19–25
the lnpMn was decreased by −0.075 (95% CI: −0.13, −0.01). This was

roughly translated to about 8% decrease (1-e−0.075) in original personal air Mn concentrations by each km TWD. Neither age nor gender

was associated with personal air Mn concentration.

Using separate multiple regression models, neither blood Mn nor hair

Mn was associated with the stationary or personal air Mn concentrations

or TWD (data not shown); however, there was a positive trend in blood

Mn by personal air Mn concentration, although this was not significant

(Fig. 2). After repeating the analysis with only those children (n=22)

whose blood and hair were collected within 14 days of the personal air

sampling, there remained no statistically significant association between

personal air Mn and blood or hair Mn.

4. Discussion

This is to our knowledge the first study of children's personal exposure to ambient Mn and its relationship with biological markers of exposure. The results of this analysis demonstrate that in this rural

Appalachian community personal exposure to Mn is significantly associated with children's proximity to a ferromanganese refinery. Ambient

background concentrations of Mn and wind speed were also significantly associated with personal Mn exposure. Biological markers of exposure including concentrations of Mn in blood and hair, however,

were not associated with either sampled personal Mn exposure or the

child's time-weighted distance from the ferromanganese facility. This

can potentially be explained by the small number of children participating in the personal air sampling (n=38).

Low-level exposure to Mn has previously been associated with

adverse child neurodevelopment including measures of intelligence,

hyperactive behavior, memory, and motor function (Riojas-Rodriguez

et al., 2010; Rodriguez-Agudelo et al., 2006; Wright et al., 2006). Similar

to other environmental neurotoxicants, exposure during critical periods

of neurodevelopment, including prenatally and during early-childhood,

is likely to have the greatest health impact. Unlike lead and some other

known neurotoxicants (e.g. second-hand smoke), however, Mn is an essential element necessary for cellular function (Aschner and Aschner,

2005). Inhalation is a particularly significant route of exposure to Mn

as this pathway bypasses homeostatic excretory mechanisms allowing

for direct exposure to the lung and brain via the olfactory nerve

(Dorman et al., 2002; Tjalve et al., 1996). The significance of this study

is underscored by its focus on children, who are considered particularly

Table 1

Characteristics of participating children, their home environment, and biological concentrations of manganese.

Home and child characteristics N (%)

Total 38

Age

7 8 (21)

8 15 (39)

9 15 (39)

Gender

Male 13 (34)

Female 25 (66)

Race

Caucasian 36 (95)

African American 1 (3)

Native American 1 (3)

Current household smoker

No 35 (92)

Yes 3 (8)

Times gas stove used during sampling period

None 20 (53)

Once 3 (8)

Twice or more 15 (39)

Times electric stove used during sampling period

None 23 (61)

Once 8 (21)

Twice or more 7 (18)

Hours gas heat used during sampling period

0–4 32 (84)

More than 4 6 (16)

Hours fireplace used during sampling period

None 36 (95)

2 2 (5)

Hours child near smokers during sampling period

None 36 (95)

1–2 2 (5)

Hours child spent near lit candle or incense during sampling period

None 31 (82)

1 or more 7 (18)

Hours spent outside Marietta area during sampling period

None 29 (76)

1–2 7 (18)

More than 3 2 (5)

Hours sample device was not with child during sampling period

None 28 (74)

1–2 7 (18)

3–4 2 (5)

4 or more 1 (3)

Blood Mn concentration (μg/L) n= 33

Mean (sd) 9.5 (2.4)

Range 5–14.4

Hair Mn concentration (μg/g) n= 38

Mean (sd) 0.47 (0.3)

Range 0.085–1.25

Table 2

Stationary and personal air sampling for manganese and PM2.5 during the two spring

personal air sampling periods.

Stationary air sampling Personal air sampling

April–May

2009

n= 16

March-June

2010

n= 28

April–May

2009

n= 20

March–June

2010

n= 18

Mn (ng/m3)

GM 5.45 10.33 7.31 9.03

95% C.I. of GM 3.15–9.42 6.64–16.05 4.97–10.74 5.92–13.76

PM2.5 (μg/m3)

GM 7.10a,b 11.73c 15.84 18.17

95% C.I. of GM 4.17–12.07 10.09–13.64 13.40–18.74 13.42–24.60

a P= 0.06 when compared with 2010 stationary PM2.5. b Pb0.05 when compared with 2009 personal PM2.5. c Pb0.05 when compared with 2010 personal PM2.5.

Table 3

Characteristics of variables used in multiple regression models.

Variable N Geometric mean Range

Personal Mn (ng/m3) 38 8.1 1.47–54.48

Stationary Mn (ng/m3) 38 11.0 4.53–34.54

Personal PM2.5 (μg/m3) 38 16.9 5.64–58.04

Stationary PM2.5 (μg/m3) 38 10.8 7.06–18.34

Mean (sd)

Time weighted distance (km) 38 11.24 (4.69) 4.72–28.52

Wind index 38 0.46 (0.35) 0.00–1.00

Wind speed (km/h) 38 8.08 (3.15) 2.63–14.97

Average precipitation (cm) 38 0.43 (0.54) 0–2.25

Elevation (m) 38 70.48 (10.13) 56.32–96.61

Percent child spent outdoors 38 14 (12) 0–45

Table 4

Multiple regression model for personal air Mn concentration (ng/m3).

Variable Parameter

estimate

t-Value 95% C.I. p-Value

Intercept 2.84 2.07 0.04–5.64 0.05

Ln stationary Mn (ng/m3) 0.51 0.24 0.3–0.99 0.04

Time weighted distance (km) −0.075 −2.45 −0.13 to −0.01 0.02

Wind index −0.32 −0.85 −1.07–0.44 0.40

Wind speed (km/h) −0.44 −2.21 −0.18 to −0.01 0.03

Average precipitation (cm) −0.44 −1.73 −0.96–0.08 0.09

Age −0.004c −0.02 −0.35–0.34 0.98

Gender −0.03 −0.11 −0.58–0.52 0.91

E.N. Haynes et al. / Science of the Total Environment 427–428 (2012) 19–25 23
vulnerable to environmental neurotoxicants (National Research

Council, 1993; Woodruff et al., 2004; Landrigan and Miodovnik, 2011).

Similar to other studies of children's personal exposure to PM2.5,

our cohort's personal exposure to PM2.5 was elevated in comparison

to concurrent stationary air sampling. This observation, frequently

referred to as a child's ‘personal dust cloud’, is likely a function of

the time–activity patterns of children, including time spent indoors at

home and school, in vehicles, or walking, running or playing resulting

in the resuspension of particles (Ozkaynak et al., 1996; Elgethun et al.,

2003). Interestingly, however, personal exposure to Mn did not follow

this trend across sampling periods. Whereas in the 2009 sampling

period, personal Mn exposure did, on average, exceed Mn concentrations at the stationary sampling site, the results of the 2010 personal

air sampling demonstrated decreased personal Mn exposure compared

to the stationary site. These findings may be a result of differing meteorological conditions, elevation of participant residences, or alterations in

Mn emissions from the facility. In contrast to other studies of personal

PM2.5 exposure, the variability in personal Mn exposure was similar,

and in 2010 less than, the observed variability in stationary air sampling. These results suggest that resuspension of particles is not a significant source of Mn exposure; rather, as seen by the association between

distance to the ferromanganese facility and personal exposure, location

near the industrial point source is likely the most significant source of

personal exposure.

Though the association between personal exposure to ambient Mn

and concentrations of Mn in hair were not statistically significant, we

did observe a borderline relationship between personal exposure and

blood Mn. Whereas hair Mn may reflect longer term exposure, concentrations of Mn in blood are likely to reflect more recent exposures

due to its short half-life (Smith et al., 2007; Zheng et al., 2000). The

relationship between personal Mn exposure and blood Mn is complicated by the large individual variability of blood Mn due to diet, iron

status, and genes involved in iron metabolism (Haynes et al., 2010;

Claus Henn et al., 2011). However, the concentrations of Mn in blood

observed in this study were similar to or greater than other studies of

children with environmental exposure to ambient Mn. For example,

children residing near Mn mining and processing facilities in Mexico

were reported to have a geometric mean Mn blood concentration of

9.71 μg/L (Riojas-Rodriguez et al., 2010). A study of children ages 6–12

residing near a ferromanganese alloy plant in Brazil also reported a

mean blood Mn concentration of 8.2 μg/L.

Hair Mn in this study is at least 10-fold lower than was measured in

similar cross-sectional studies of children in Brazil where mean hair Mn

was 5.8 μg/g ranging from 0.1 to 86.7 μg/g (Menezes-Filho et al., 2011),

in Mexico where the hair Mn ranged from 0.40 to 48 μg/g (HernándezBonilla et al., 2011), and in children exposed to Mn in drinking water in

Canada (Bouchard et al., 2007) where the mean hair Mn was 5.1 μg/g.

Our results, however, more closely approximate the measured Mn in

hair of children residing near a hazardous waste site in Oklahoma

(Wright et al., 2006) where mean hair Mn was 0.47 μg/g ranging from

0.89 to 2.1 μg/g and a study of young adults in Poland (Chojnacka et

al., 2010) where mean hair Mn was 0.73 μg/g. Variation in hair sample

length used and analysis methods may contribute to differences in

hair Mn concentration. Similar to our study, Wright et al. (2006) analyzed their samples by ICP-MS and used the entire hair sample collected,

whereas Menezes-Filho et al. (2011), Bouchard et al. (2007) and

Hernández-Bonilla et al. (2011) used Zeeman Atomic Absorption

Spectroscopy and reported using only the first centimeter or the

amount available. Although human scalp hair has been used for decades

to assess environmental exposure to metals (Kopito et al., 1967;

Hammer et al., 1971; Yamaguchi et al., 1971; Klevay, 1973; MenezesFilho et al., 2011) variation across studies in the location of the hair sample collected, washing procedure, and length of hair analyzed (ATSDR,

2003; Seidel et al., 2001) limit the ability to compare hair Mn across

studies. Thus, inter- and intra-laboratory validations of hair Mn collection, cleaning and analysis are needed.

A potential limitation of the current study is the number of study

subjects. Due to the difficulty associated with personal air sampling in

children, a subset of the overall CARES cohort was enrolled in this

study. The objective of this study, however, was to determine if a surrogate of Mn exposure, time-weighted distance to the ferromanganese

facility, was applicable in the general cohort. An additional limitation

of this study is the lack of residential locations near the industrial

point source of Mn emissions. On average, the time-weighted distance

from the facility was 11.24 km ranging from 4.7 to 28.5 km. However,

due to the population distribution we expect the subset to reflect the

overall exposure in the CARES cohort. We are not able to assess seasonal

differences in personal exposure or long term personal exposure due to

sampling occurring over the course of one season. We did not observe a

significant association between wind direction, as reflected by the wind

index, and personal exposure to manganese. This finding may be due to

the use of wind direction reported at a nearby airport as a surrogate for

wind direction at the participants' homes as the topography of the study

region may result in varying local wind patterns not reflected by the

average regional wind direction.

In conclusion, the findings of this study suggest that the timeweighted average distance from the ferromanganese facility may be

a suitable surrogate of personal exposure to airborne Mn for participants in the CARES cohort.

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