_{2.5}

Many portable monitors for quantifying mass concentrations of particulate
matter air pollution rely on aerosol light scattering as the measurement method;
however, the relationship between scattered light (what is measured) and aerosol
mass concentration (the metric of interest) is a complex function of the
refractive index, size distribution, and shape of the particles. In this study,
we compared 33-hour personal PM_{2.5} concentrations measured
simultaneously using nephelometry (personal DataRAM pDR-1200) and gravimetric
filter sampling for working adults (44 participants, 249 samples). Nephelometer-
and filter-derived 33-hour average PM_{2.5} concentrations were
correlated (Spearman’s ρ = 0.77); however, the
nephelometer-derived concentration was within 20% of the filter-derived
concentration for only 13% of samples. The nephelometer/filter ratio, which is
used to correct light-scattering measurements to a gravimetric sample, had a
median value of 0.52 and varied by over a factor of three (10^{th}
percentile = 0.35, 90^{th} percentile = 1.1). When 33-hour samples with
>50% of 10-s average nephelometer readings below the nephelometer limit
of detection were removed from the dataset during sensitivity analyses, the
fraction of nephelometer-derived concentrations that were within 20% of the
filter-derived concentration increased to 25%. We also evaluated how much the
accuracy of nephelometer-derived concentrations improved after applying: (1) a
median correction factor derived from a subset of 44 gravimetric samples, (2)
participant-specific correction factors derived from one same from each subject,
and (3) correction factors predicted using linear models based on other
variables recorded during the study. Each approach independently increased the
fraction of nephelometer-derived concentrations that were within 20% of the
filter-derived concentration to approximately 45%. These results illustrate the
challenges with using light scattering (without correction to a concurrent
gravimetric sample) to estimate personal exposure to PM_{2.5} mass among
mobile adults exposed to low daily average concentrations (median = 8
μg·m^{−3} in this study).

Variations in the factor used to correct nephelometer data to a
gravimetric sample present challenges for estimating personal exposure to
PM_{2.5} mass.

Many studies rely on devices that measure light scattering to estimate
concentrations of particulate matter (PM) air pollution (

Epidemiological studies have linked exposure to higher PM mass concentrations
with adverse health outcomes and mass-based air quality standards are used around
the world (

Previous studies reported that measurements recorded by wearable,
research-grade nephelometers (i.e., various models of the personal DataRAM) were
sensitive to relative humidity (RH) and the type of aerosol sampled (

In personal monitoring applications, r^{2} values ranging from 0.48
to 0.86 were reported for 24-hour average PM concentrations measured using personal
DataRAM nephelometers and gravimetric samplers (

Research-grade nephelometers, like the personal DataRAM, often include a
filter cartridge downstream of the light-scattering sensor. Using this arrangement,
the PM concentration reported by the sensor can be corrected to a gravimetric sample
in post-processing. The nephelometer/filter ratio, defined herein as the ratio of
the time-averaged PM_{2.5} concentration derived from nephelometer
measurements to the time-averaged PM_{2.5} concentration derived from a
filter sample (both in μg·m^{−3}), is the factor used
to correct the time-resolved light-scattering measurement to the gravimetric
sample.

Although instruments that measure the particle properties that influence the
gravimetric correction factor (

In this study, the mass of PM_{2.5} measured by a wearable aerosol
nephelometer was compared to integrated filter measurements collected simultaneously
during personal monitoring of working adults exposed to relatively low daily average
PM_{2.5} mass concentrations. We aimed to answer the following
questions: (1) How well do personal PM_{2.5} mass concentrations measured
using a nephelometer agree with personal PM_{2.5} mass concentrations
measured using a gravimetric sample (

Data were collected as part of the Fort Collins Commuter Study (_{2.5} mass, PM_{2.5} black carbon, particle number
concentration, and carbon monoxide) for approximately 33 hours while they went
about their normal daily routine (which included commuting to and from work
either by car or bike). Monitoring began around 3 pm on the day before the
commutes (the “sample date”) and ended around 12 am on the day
after the commutes. Data were collected between September 2012 and February
2014. Each participant was scheduled to complete eight monitoring periods during
a 4- to 12-week period. The study continued throughout all seasons, but efforts
were made to collect all samples for a given participant within a single season.
In total, 377 samples were collected by 45 participants on 107 unique sample
dates.

Each participant was randomly assigned a backpack full of sampling
equipment on each sample date. The sampling equipment in the backpack included a
pDR-1200 nephelometer (Thermo Fisher Scientific, Waltham, MA, USA), which
featured a PM_{2.5} inlet (PEM, SKC, Eighty Four, PA, USA) and a 37-mm
filter on the outlet (PallFlex Fiberfilm T60A20; Pall, Port Washington, NY,
USA). The pDR-1200 used an LED light source with a center wavelength of 880 nm,
detected scattered light over an angle of 50° to 90°, and recorded
data continuously using a 10-second averaging window. Airflow through the
PM_{2.5} inlet was maintained at 4.0
L·min^{−1} using a personal sampling pump (OMNI 400,
Mesa Labs, Lakewood, CO, USA). Airflow through the nephelometer and filter was
maintained at 3.8 L·min^{−1}, while airflow through an
aethalometer (microAeth Model AE51, AethLabs, San Francisco, CA, USA) installed
in parallel with the nephelometer/filter was maintained at 0.2
L·min^{−1}. To determine the mass of fine particulate
black carbon to which the participant was exposed during the sample,
aethalometer black carbon measurements were analyzed and integrated as described
previously (_{2.5} was calculated using the mass accumulated on
the filter as the reference.

Other data collected included particle number concentration (for 128/377
samples; DiSC Mini, Matter Aerosol AG, Wohlen, Switzerland); carbon monoxide
mixing ratio (T15n, Langan Products, San Francisco, CA, USA); GPS location and
movement of the backpack (BT-Q1000XT, QStarz, Taipei, Taiwan); movement and
heart rate of the participant (Actiheart, CamNtech, Cambridge, UK); as well as
the temperature, RH, and light intensity measured on the outside of the backpack
(MSR Electronics, GmbH, Seuzach, Switzerland). The procedures used to collect
these data have been described previously (_{2.5} measurements (taken by the
pDR-1200) to estimate the fraction of the total PM_{2.5} exposure
associated with each microenvironment category.

Hourly ambient PM_{2.5} concentrations in Fort Collins during
the study period (September 2012–February 2014), as measured at EPA
monitoring site 08-069-0009 using a ThermoFisher Scientific 1405-DF TEOM, were
downloaded from the EPA AQS Data Mart (_{2.5} concentration measured using the filter behind the
nephelometer. Ambient temperature and RH data were obtained from the Christman
Field weather station at Colorado State University (

Prior to study initiation, all six pDR-1200 units were sent to the
manufacturer for calibration. The factory calibration aerosol was Society of
Automotive Engineers (SAE) Fine test dust, which has an MMD of 2–3
μm, a geometric standard deviation (GSD) of 2.5, a particle density of
2.60–2.65 g·cm^{−3}, and a refractive index of 1.54
(

Filters were pre- and post-weighed on a balance with 1 μg resolution (MX5, Mettler-Toledo, Columbus, OH, USA). The calibration of the balance was checked each day using a 50 mg calibration weight. Filters were equilibrated in the low-humidity, climate-controlled microbalance laboratory for at least 24 hours before weighing. Pre- and post-sample filter masses were measured in duplicate; if the first and second measurements differed by more than 5 μg, a third measurement was taken. Immediately prior to each measurement, the filter was placed on a Polonium-210 neutralizer (Staticmaster 2U500, NRD Static Control, Grand Island, NY, USA) for 10 seconds to eliminate static charge. The duplicate or triplicate measurements were averaged to obtain the pre- and post-sample filter weights used in all calculations.

The limit of detection (LOD) for the filter samples was calculated from
the change in mass of 203 blanks collected over the duration of the study (one
or two per sample date). Blank filters were pre-weighed, loaded into filter
cartridges, removed from their filter cartridges, and post-weighed using the
same procedures applied to the sample filters; however, the blank filters never
left the laboratory. The filter LOD was calculated as three times the standard
deviation of the mass accumulated on the blanks (3s_{blank}) and was
equal to 31 μg (which corresponded to a 33-hour average concentration of
4 μg·m^{−3}). The LOD of the pDR-1200 was estimated
to be 3 μg·m^{−3} based on experiments conducted in
a laboratory aerosol chamber (_{2.5} concentrations recorded by
the nephelometer that were below the LOD were replaced with

The RH measured on the backpack was used to calculate dry
PM_{2.5} mass
(_{2.5,dry};
μg·m^{−3}) from each LOD-adjusted 10-s average
data point recorded by the nephelometer
(_{2.5,wet};
μg·m^{−3}) as shown in _{2.5,wet} and
_{2.5,dry} given by

If the RH sensor on the backpack malfunctioned during a sample (n =
71/333), RH was assumed to be 30%. This assumed RH resulted in essentially no
adjustment being applied to the nephelometer data using _{2.5} concentration decreased by a median value of 6% (see

The LOD- and RH-corrected 10-second average PM_{2.5}
concentrations derived from the nephelometer measurements were averaged over the
entire sample period (~33 hours) for comparison to the average
PM_{2.5} concentration derived from the filter sample. Samples were
only included in the main analysis if: (1) 10-second average nephelometer
measurements were available for at least 85% of the sample period (309/377), (2)
the mass accumulated on the filter was above the LOD (292/377 samples), and (3)
the filter-derived PM_{2.5} concentration was less than 145
μg·m^{−3} (375/377). A total of 249 samples,
collected by 44 participants on 100 sample dates, were retained after applying
these three criteria. The two filter-derived concentrations greater than 145
μg·m^{−3} were suspected to be erroneous, since
they were: (a) over an order of magnitude higher than the median filter-derived
concentration (7 μg·m^{−3} for all 377 samples),
(b) more than 50% higher than the next highest filter-derived concentration (90
μg·m^{−3}), and (c) not corroborated by
higher-than-average nephelometer-derived concentrations.

The first objective was to assess how well the PM_{2.5} mass
concentrations measured using the nephelometer agreed with the PM_{2.5}
mass concentrations measured using the filter sample. Spearman’s rho
(ρ) was calculated to evaluate rank-order correlation between the 33-hour
average nephelometer-derived concentration and the filter-derived concentration.
Spearman’s rho is a measure of a monotonic relationship between two
variables—the relationship need not be linear (_{2.5} mass
concentrations were calculated.

The second objective was to determine how much the nephelometer/filter
ratio varied. The nephelometer/filter ratio is the factor that would be used to
correct the light-scattering measurements to the gravimetric sample in
post-processing (_{2.5} concentration derived from the nephelometer
measurements divided by the 33-hour average PM_{2.5} concentration
derived from the filter sample. To assess the fraction of the variance in the
nephelometer/filter ratio that could be explained by (1) differences between
versus within participants and (2) differences between versus within sample
dates, we fitted separate one-way random effects models and estimated intraclass
correlation coefficients (ICC) (see

Sensitivity analyses were conducted to examine how the results of the
analyses described above were affected by: (a) not replacing 10-second average
nephelometer readings below the LOD with

In the main analysis, and in each of the four filtering steps, samples
were only included if 10-s average nephelometer measurements were available for
at least 85% of the sample period (309/377 samples). The sensitivity of the
results to this criterion was also investigated by considering data sets that
only included samples for which 10-s average nephelometer measurements were
available for at least 90% (294/377) and 95% (240/377) of the sample period (see

The third objective was to evaluate how much correction factors derived
from a subset of gravimetric samples improved the accuracy of the
nephelometer-derived concentrations. We evaluated two approaches that could
reduce the number of filter samples that would need to be collected during a
study. In both approaches, gravimetric correction factors were predicted using a
subset of 44 samples; this number was selected because it was equal to the
number of participants. The first approach was to obtain gravimetric correction
factors for a random subset of 44 samples, and then correct all of the
nephelometer-derived concentrations (n = 249) using the median factor calculated
for that subset. The second approach was to obtain a gravimetric correction
factor for the first sample collected by each participant, and then correct all
samples collected by that participant (including the first) using that initial
factor. The first approach adjusted for population effects, whereas the second
approach adjusted for time-invariant subject-specific effects. The extent to
which these two approaches improved the accuracy of the nephelometer-derived
concentrations was assessed by comparing the filter- and nephelometer-derived
PM_{2.5} concentrations, before and after correction, using the
following metrics: (1) the fraction of samples for which the absolute difference
was ≤ 5 μg·m^{−3}, (2) the fraction of
samples for which the percent difference was ≤ 20%, (3) the median
absolute difference, and (4) the median percent difference.

The fourth objective was to evaluate how much model-predicted correction
factors improved the accuracy of the nephelometer-derived concentrations. We
developed linear mixed models to predict the gravimetric correction factor
(

First, a series of 15 linear mixed models was developed—using the
lme4 package in R (_{2.5} mass that was black carbon; time-averaged particle number
concentration; time-averaged personal carbon monoxide mixing ratio;
time-averaged ambient temperature in Fort Collins; participant age; the fraction
of time spent at home, work, in transit, in an eatery, or elsewhere; and the
fraction of PM_{2.5} exposure received at home, work, in transit, in an
eatery, or elsewhere. To make the fixed-effect coefficients comparable, all
variables were standardized to have a mean of zero and unit variance. For each
model, the 95% confidence interval for the fixed-effect coefficient was
calculated using the lmerTest package (

Second, a single mixed model—including all fixed effects from the first step with 95% confidence intervals that did not include zero (with no interaction terms) and random participant intercept—was fit to the training data set (without standardizing the variables to have a mean of zero and unit variance). Because not all effects remained significant once combined into a single model, backward elimination of fixed effects was performed using the ‘step()’ function in the lmerTest package.

The fixed-effect coefficients and overall fixed intercepts from the five
final mixed models (one for each of the five folds) were used to predict
correction factors for each sample. For example, the model developed using a
training set consisting of folds 2, 3, 4 and 5 was used to predict correction
factors for samples in fold 1. This step was repeated five times to predict
correction factors for the samples in all five folds. The extent to which the
model-predicted correction factors improved the accuracy of the
nephelometer-derived concentrations was assessed by comparing the filter- and
nephelometer-derived PM_{2.5} concentrations, before and after
correction, using the aforementioned four metrics.

All participants were adults who worked outside their homes, meaning that
they transitioned between different microenvironments (

Nephelometer data recorded during two example samples are shown in _{2.5} mass concentration as a
participant transitioned between microenvironments and activities. For the sample
shown in the top panel, a peak in PM_{2.5} exposure occurred shortly after
18:00 hours on the first day. This exposure, which was likely due to cooking (the
participant indicated that they began frying food for dinner at 18:30), persisted
through the remainder of the evening. Another, smaller, peak occurred around 6:30
the next morning, when the participant was making breakfast. The participant
commuted to work shortly before 9:00 and then went to an eatery for lunch shortly
before noon. A large peak in exposure occurred at the eatery. The participant then
returned to work for the remainder of the afternoon before commuting back home at
approximately 17:00. Exposures were lowest during the early morning, when the
participant was at home and likely to be asleep, and during working hours. For this
sample, the nephelometer/filter ratio was close to 1 and 95% of the 10-second
average PM_{2.5} concentrations recorded by the nephelometer were above the
LOD. For most of the 249 samples retained in the main analysis, the
nephelometer/filter ratio was less than one (median = 0.52), and a smaller fraction
of 10-s average nephelometer readings were above the LOD (median = 38%).

A sample with a more typical nephelometer/filter ratio (0.55) and fraction
of 10-s nephelometer readings above the LOD (45%) is shown in the bottom panel of

Nephelometer- and filter-derived 33-hour average personal PM_{2.5}
concentrations are compared in _{2.5} concentrations ranged
from 5 to 83 μg·m^{−3}, with a median of 8
μg·m^{−3} (_{2.5} concentration was strongly correlated with
the filter-derived concentration (Spearman’s ρ = 0.77; ^{−3} for 73% of samples. A difference of 5
μg·m^{−3} is small from an absolute standpoint but
represents a percent difference of 63% for the median concentration of 8
μg·m^{−3}. The percent difference between the
nephelometer- and filter-derived concentrations had a median value of 49% (

The histogram of nephelometer/filter ratios shown in _{2.5} concentration. The
nephelometer/filter ratio had a median value of 0.52 and was less than one for 88%
of samples (^{−3}) as well as differences in particle size
distribution and index of refraction between SAE Fine test dust and ambient aerosols
(_{2.5} inlet used on the pDR, the size distribution of the
aerosols to which participants were exposed, and/or the low 33-hour average
PM_{2.5} concentrations to which participants were exposed. In
laboratory studies, pDR nephelometers have been found to underestimate PM
concentrations for some aerosol types (_{2.5} inlet would have
prevented large particles from entering the nephelometer.

If the nephelometer measurements were accurate and precise, the histogram
shown in ^{th}–90^{th} percentile = 0.35–1.1). These
results illustrate that the nephelometer measurements were not accurate, nor was the
factor that would be used to correct the nephelometer measurements to the
gravimetric filter sample consistent between personal samples.

This analysis assumes that the filter-derived PM_{2.5} concentration
was the true exposure, and that disagreement between the nephelometer- and
filter-derived 33-hour average concentrations was largely due to bias and
imprecision in the nephelometer measurements; however, bias and imprecision in the
filter measurements can also contribute to variability in the nephelometer/filter
ratio. The filter concentrations were assumed to be unbiased because: (1) they were
derived from direct measurements of PM_{2.5} mass and (2) quality control
procedures (

One possible explanation for the wide range of nephelometer/filter ratios
seen in

Another possible explanation for the range of nephelometer/filter ratios
seen in

As filtering progressed from the 1st to 3rd steps in the sensitivity
analyses, samples with high fractions of 10-second nephelometer readings equal
to zero or below the nephelometer LOD (3 μg·m^{−3})
were removed from the data set. In the 4^{th} filtering step, samples
that captured 33-hour average exposures below 4
μg·m^{−3} (as measured by the nephelometer)
were removed. Between the first and fourth filtering steps, the median
filter-derived personal PM_{2.5} concentration increased from 8 to 12
μg·m^{−3} and the median fraction of 10-second
nephelometer readings above the LOD increased from 38% to 72%. In addition, the
median nephelometer/filter ratio increased from 0.44 to 0.74 and the fraction of
nephelometer/filter ratios equal to 1.0 ± 0.2 increased from 11% to 29%
(

The inconsistency in the nephelometer/filter ratio shown in _{2.5} exposure for all
samples. When all 249 nephelometer-derived concentrations from the main analysis
were corrected using the median gravimetric correction factor measured for a
random subset of 44 samples (0.55), the median nephelometer/filter ratio shifted
from 0.52 to 0.95 and the fraction of the nephelometer-derived concentrations
that were within 20% of the filter-derived concentration increased from 13% to
43% (^{th} and 90^{th} percentiles.

Participant-specific correction factors did not perform better than the
median correction factor calculated from a random subset of 44 samples. When the
nephelometer-derived concentrations for each participant were corrected using
the nephelometer/filter ratio measured during the first sample collected by each
participant (see

Estimates and 95% confidence intervals (CIs) for the fixed-effect
coefficients associated with the 15 metrics tested as predictors in linear mixed
models are shown in _{2.5,neph}
was the 33-hour average nephelometer-derived PM_{2.5} concentration;
_{2.5,filter} was the
filter-derived PM_{2.5} concentration;
_{i} was the
participant-specific random intercept,
_{j} was a
fixed-effect coefficient;
_{exp,transit,},
_{exp,eat}, and
_{exp,work} were
the fractions of exposure received in transit, at an eatery, and at work,
respectively; _{time,home} was the
fraction of time spent at home; _{BC} was
the fraction of PM_{2.5} mass that was black carbon; and

Four of the seven predictors that appeared in the final models were
associated with specific microenvironments
(_{exp,transit},
_{exp,eat},
_{exp,work}, and
_{time,home}). The importance of
these predictors might be explained by the variation in aerosol properties (and,
consequently, the nephelometer response to a given mass concentration of
aerosol) that would be expected between the different microenvironment
categories (

When the 33-hour average nephelometer-derived PM_{2.5}
concentrations were corrected using model-derived factors, the median
nephelometer/filter ratio shifted from 0.52 to 0.98 and the fraction of the
nephelometer-derived concentrations that were within 20% of the filter-derived
concentration increased from 13% to 42% (

The strong rank-order correlation between the nephelometer- and
filter-derived concentrations (ρ = 0.77) indicates that portable
light-scattering instruments can provide useful information about relative
PM_{2.5} concentrations. For example, _{2.5} pollution within a large city. Using the nephelometer data
presented here, _{2.5} concentrations than adults who commuted to work by car. In
other words, the nephelometer data were useful for examining relative differences in
exposure within a single microenvironment category (in transit).

Without correction to gravimetric samples, however, research-grade
nephelometers provided accurate (± 20%) estimates of absolute 33-hour average
personal PM_{2.5} concentrations for only 13% of samples collected by
working adults exposed to low daily average concentrations (median = 8
μg·m^{−3}). The results of the sensitivity analyses
suggested that the accuracy of the nephelometer-derived 33-hour average
concentrations was sensitive to the number of 10-s average nephelometer readings
below the nephelometer limit of detection. These limitations of light-scattering
instruments are important to keep in mind, especially when one wishes to evaluate
absolute, as opposed to relative, personal exposures.

^{th} percentile (0.35) and
the 90^{th} percentile (1.1), meaning that the calibration factor used to
correct the nephelometer measurements to gravimetrically-determined PM_{2.5}
concentrations did not remain constant. When nephelometer-derived concentrations
were corrected using a median gravimetric correction factor calculated from a random
subset of 44 samples, the fraction of the nephelometer-derived concentrations that
were within 20% of the filter-derived concentration increased to 43%. This result
indicates that collecting gravimetric measurements for just a subset of samples can
improve the accuracy of nephelometer-derived estimates of personal exposure to
PM_{2.5}; however, accuracy remained less than 20% for the majority of
samples. Neither constant participant-specific correction factors (calculated from
the first gravimetric sample collected by each participant) nor correction factors
predicted using a more complicated linear modeling approach performed better than
the constant correction factor calculated from a random subset of samples.

The authors thank the members of the Fort Collins Commuter Study research team: Anna Mölter, Charis Ackerson, Annette Bachand, Taylor Carpenter, Kristen M. Fedak, Ashleigh Kayne, Kirsten Koehler, Brianna Moore, Christian L’Orange, Casey Quinn, Viney Ugave, and Amy L. Stuart.

Funding: This work was funded by the United States Department of Health and Human Services (HHS), National Institute of Health (NIH), National Institute of Environmental Health Sciences (NIEHS) under grant ES020017 and under grant OH009229 by CDC NIOSH Mountain and Plains Education and Research Center. The funding sources had no role in the study design; in collection, analysis, and interpretation of data; in the writing of this article; or in the decision to submit this article for publication.

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GPS traces from single 33-hour samples collected by four participants.
Circles represent time spent in stationary locations (

The 10-second average LOD- and RH-corrected PM_{2.5}
concentrations recorded by the nephelometer during example 33-hour samples. Top:
the filter-derived personal PM_{2.5} concentration was 10
μg·m^{−3}, the nephelometer/filter ratio was
0.96, and 95% of the 10-second average nephelometer readings were above the
limit of detection (LOD) of 3 μg/m^{3}. Bottom: the
filter-derived personal PM_{2.5} concentration was 8
μg·m^{−3}, the nephelometer/filter ratio was
0.55, and 45% of the 10-second nephelometer readings were above the LOD.

A scatterplot of the 33-hour average PM_{2.5} concentrations
derived from the filter and nephelometer samples (n = 249). The solid line is y
= x. Samples collected using different pDR-1200 units are shown in different
colors (six total) to improve readability.

A histogram of nephelometer/filter ratios for the data used in the main analysis (n = 249).

Ratio of the 33-hour average nephelometer- and filter-derived
PM_{2.5} concentrations (n = 249) vs. participant number (n = 44).
Marker colors are varied between participants to improve readability. The first
sample collected by each participant is shown with a white marker. The solid
vertical line represents a ratio of 1.

Summary of results from the main analysis and the sensitivity analyses
(1^{st} filtering step, 2^{nd} filtering step,
3^{rd} filtering step, 4^{th} filtering step). For the main
analysis, 10-second average nephelometer readings below the limit of detection
(LOD) were adjusted to

Main analysis | Sensitivity analyses: 1^{st} filtering
step | Sensitivity analyses: 2^{nd} filtering
step | Sensitivity analyses: 3^{rd} filtering
step | Sensitivity analyses: 4^{th} filtering
step | |
---|---|---|---|---|---|

Filtering criteria | Filter mass > LOD^{−3} | Filter mass > LOD^{−3} | Filter mass > LOD^{−3}^{−3} | Filter mass > LOD^{−3}^{−3} | Filter mass > LOD^{−3}^{−3}^{−3} |

No. samples | 249 | 249 | 159 | 81 | 68 |

No. participants | 44 | 44 | 42 | 35 | 31 |

Sample dates | 100 | 100 | 86 | 57 | 51 |

_{2.5}
^{−3} | |||||

Median | 8 | 8 | 9 | 11 | 12 |

Interquartile range | 6 – 11 | 6 – 11 | 6 – 13 | 8 – 19 | 9 – 24 |

Range | 5 – 83 | 5 – 83 | 5 – 83 | 5 – 83 | 5 – 83 |

Spearman’s rho | 0.77 | 0.76 | 0.77 | 0.74 | 0.66 |

Fraction ≤ |5|
μg-m^{−3} | 183/249 (73%) | 157/249 (63%) | 108/159 (68%) | 50/81 (62%) | 39/68 (57%) |

Fraction ≤ 20% | 32/249 (13%) | 28/249 (11%) | 25/159 (16%) | 20/81 (25%) | 20/68 (29%) |

Median absolute difference
(μg·m^{−3}) | 3.6 | 4.5 | 4.0 | 4.0 | 4.3 |

Median percent difference | 49% | 57% | 50% | 42% | 36% |

Median | 0.52 | 0.44 | 0.52 | 0.68 | 0.74 |

25^{th} - 75^{th}
percentile | 0.43 – 0.70 | 0.29 – 0.68 | 0.38 – 0.77 | 0.49 – 1.0 | 0.54 – 1.0 |

10^{th} - 90^{th}
percentile | 0.35 – 1.1_ | 0.17 – 1.0_ | 0.29 – 1.1_ | 0.39 – 1.2 | 0.44 – 1.3 |

Fraction = 0.8 – 1.2 | 32/249 (13%) | 28/249 (11%) | 25/159 (16%) | 20/81 (25%) | 20/68 (29%) |

Fraction < 1 | 220/249 (88%) | 222/249 (89%) | 136/159 (86%) | 61/81 (75%) | 48/68 (71%) |

Between participants (95% CI) | 0.27 (0.15–0.42) | 0.30 (0.18–0.45) | 0.26 (0.10–0.44) | 0.23 (0.00–0.49) | 0.30 (0.18 – 0.45) |

Between dates (95% CI) | 0.14 (0.00–0.29) | 0.07 (0.00–0.22) | 0.20 (0.00–0.41) | 0.00 (0.00–0.27) | 0.07 (0.00 – 0.22) |

Accuracy of uncorrected nephelometer-derived 33-hour personal
PM_{2.5} concentrations, relative to the filter-derived
concentrations, compared to accuracy after correction using: (1) the median
nephelometer/filter ratio calculated from a random subset of 44 samples, (2) the
nephelometer/filter ratio calculated from the first sample for each of the 44
participants, and (3) factors predicted using linear models fit and tested using
five-fold cross-validation. Model-predicted correction factors were only
available for 245/249 samples because not all predictor variables were
successfully measured during all samples.

Correction factor (CF) type | None | Median | Participant-specific | Model-predicted |
---|---|---|---|---|

Used to calculate CF(s) or train model | - | 44 | 44 | ≈200 per fold |

Used to test CF(s) or Model | - | 249 | 249 | ≈50 per fold |

Total | 249 | 249 | 249 | 245 |

Fraction ≤ |5
μg·m^{−3}| | 183/249 (73%) | 188/249 (76%) | 189/249 (76%) | 189/245 (77%) |

Fraction ≤ 20% | 32/249 (13%) | 106/249 (43%) | 109/249 (44%) | 103/245 (42%) |

Median absolute difference | 3.6
μg·m^{−3} | 2.0
μg·m^{−3} | 2.0
μg·m^{−3} | 2.0
μg·m^{−3} |

Median percent difference | 49% | 24% | 25% | 24% |

Median | 0.52 | 0.95 | 1.0 | 0.98 |

25^{th}–75^{th}
percentile | 0.43 – 0.70 | 0.78 – 1.3 | 0.77 – 1.3 | 0.77 – 1.3 |

10^{th}–90^{th}
percentile | 0.35 – 1.1 | 0.63 – 1.9 | 0.48 – 1.7 | 0.63 – 1.7 |

Nephelometer- and filter-derived PM_{2.5} concentrations
were correlated (ρ = 0.77)

The nephelometer tended to underestimate the filter measurement by ~50%

The nephelometer/filter ratio was sensitive to nephelometer readings
below 3 μg·m^{−3}

Gravimetric correction factor varied by 300% between the
10^{th} and 90^{th} percentiles

Modeled corrections brought 45% of nephelometer concentrations within 20% of filter