In‐flight particulate matter concentrations in commercial flights are

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Indoor Air. 2021;31:1484–1494.wileyonlinelibrary.com/journal/ina

1 | INTRODUCTION

Humans spend most of their time in indoor environments.

This

makes the air quality indoors especially important for their com-

fort, health, and productivity. Due to the substantial amount of time

spent indoors, air can be a dominant exposure route for environ-

mental pollutants. Indoor Air Quality (IAQ) depends on many fac-

tors including environmental parameters such as temperature and

relative humidity, ventilation, as well as concentrations of irritants

including volatile organic compounds (VOCs), ozone, nitrogen di-

oxide, and particulate matter (PM).

Among these, the importance

of PM in indoor environments has commonly been acknowledged

in the context of vaping and cigarette smoke, with several studies

measuring indoor particle mass concentrations before and after

bans on smoking.

3– 5

Outdoors, the United States Environmental Protection Agency

(US EPA) sets standards and actively regulates the mass concentra-

tions (µg m

−3

) of fine and coarse particles (PM

2.5

and PM

, particles

with diameters ≤2.5 µm and ≤10 µm, respectively). This is enforced

via a PM monitoring network in outdoor locations throughout the

United States.

The availability of PM data has enabled clear epi-

demiological links between outdoor PM mass concentration and

human health.

7,8

While small particles account for a negligible frac-

tion of PM mass concentration, they penetrate deeply into the lungs

and can be further distributed throughout the body via circulation.

Thus, small particles are better quantified by number concentration

Received: 1 December 2020

Revised: 26 January 2021

Accepted: 13 February 2021

DOI: 10.1111/ina.12812

ORIGINAL ARTICLE

In- flight particulate matter concentrations in commercial flights

are likely lower than other indoor environments

Jean C. Rivera- Rios

| Taekyu Joo

| Masayuki Takeuchi

| Thomas M. Orlando

Tracy Bevington

| John W. Mathis

| Cliffton D. Pert

| Brandon A. Tyson

Tyler M. Anderson- Lennert

| Joshua A. Smith

| Nga Lee Ng

1,2,3

School of Chemical and Biomolecular

Engineering, Georgia Institute of

Technology, Atlanta, GA, USA

School of Earth and Atmospheric

Sciences, Georgia Institute of Technology,

Atlanta, GA, USA

School of Civil and Environmental

Engineering, Georgia Institute of

Technology, Atlanta, GA, USA

School of Chemistry and Biochemistry,

Georgia Institute of Technology, Atlanta,

GA, USA

Delta Air Lines, Atlanta, GA, USA

Correspondence

Nga Lee Ng, School of Chemical and

Biomolecular Engineering, School of Earth

and Atmospheric Sciences, School of Civil

and Environmental Engineering, Georgia

Institute of Technology, Atlanta, GA

30332, USA.

Email: [email protected]

Funding information

Delta Air Lines

Abstract

Air quality in indoor environments can have significant impacts on people's health,

comfort, and productivity. Particulate matter (PM; also referred to as aerosols) is an

important type of air pollutant, and exposure to outdoor PM has been associated

with a variety of diseases. In addition, there is increasing recognition and concern of

airborne transmission of viruses, including severe acute respiratory syndrome corona-

virus 2 (SARS- CoV- 2), especially in indoor environments. Despite its importance, in-

door PM data during the COVID- 19 pandemic are scarce. In this work, we measured

and compared particle number and mass concentrations in aircraft cabins during com-

mercial flights with various indoor environments in Atlanta, GA, during July 2020,

including retail stores, grocery stores, restaurants, offices, transportation, and homes.

Restaurants had the highest particle number and mass concentrations, dominated by

cooking emissions, while in- flight aircraft cabins had the lowest observed concentra-

tions out of all surveyed spaces.

KEYWORDS

aircraft air quality, indoor particulate matter

1485

RIVERA- RIOS Et Al.

in the context of their health impacts.

10,11

Currently, PM number

concentrations are not regulated; however, their importance has

been recognized, particularly when considering the adverse health

effects of ultrafine particles (particles with diameters ≤100 nm),

which are abundant in ambient environments.

Indoor PM mass

and number concentrations data are available, but due to the large

variety and heterogeneity of indoor environments, it is often diffi-

cult to make broad assessments of IAQ outside of concerted efforts

by government agencies.

13,14

Indoor sources of PM include particles

emitted directly from activities such as cooking, smoking, cleaning,

and/or from oxidation of VOCs followed by gas- particle partition-

ing.

Humans are also a source of particles indoors, through breath-

ing, talking,

or singing,

17,18

and through shedding skin flakes.

addition, incursion of ground- level ambient air can introduce PM

and ozone from outdoor sources into the indoor environment, which

is usually characterized in Inside/Outside (I/O) PM concentration

measurements.

20,21

Ozone, either from outside or directly emitted

from office equipment, can initiate reactions that lead to the for-

mation of PM indoors.

The use of particle filters in HVAC (heat-

ing, ventilation, and air conditioning) systems and ventilation rates

also modulate indoor particle concentrations and can be a dominant

removal pathway (sink) of PM.

Another PM sink is collision with

surfaces which leads to deposition. The presence of furniture and

other items in indoor environments leads to a larger surface area to

volume ratio relative to outdoors, which increases the importance

of deposition as a loss mechanism of PM indoors. Resuspension of

dust from carpets or other surfaces can also contribute significantly

to PM levels.

24,25

Over the course of the COVID- 19 pandemic, there is increasing

recognition of the importance of airborne transmission of the dis-

ease.

26– 31

Particles are emitted as infected individuals breathe and

talk, and in larger concentrations during singing, coughing, or sneez-

ing, where the particles can range from 0.1 to 1,000 µm in diame-

ter.

32– 35

The physical properties of particles depend on their size.

Bigger particles (>100 µm; droplets) are quickly removed via deposi-

tion and have limited airtime. However, smaller particles (<100 µm;

aerosols) can linger in the air for extended periods of time, allowing

them to be transported away from their initial sources.

26,28,36,37

environments below 100% relative humidity, liquid water in particles

can quickly evaporate, reducing their sizes and extending the time

they spend airborne.

These exhaled particles can accumulate in in-

door environments, particularly if these spaces are densely occupied

and poorly ventilated. Aircraft are well ventilated indoor environ-

ments, but are by design, densely occupied and require passengers

to remain in them for a prolonged amount of time. Cases of airborne

disease transmission in commercial aircraft are relatively rare but

have been reported.

39– 44

The factors that contribute to aircraft cabin PM concentrations

are similar to those in other indoor environments. This includes hu-

mans, human activities, deposition and resuspension from surfaces,

the presence of filters, intrusion of outside air during “cabin door

open” periods, and air exchange rates. Air in the aircraft is typically

exchanged 10– 30 times per hour (every 2– 6 minutes depending on

aircraft type). There are two typical aircraft designs, those that recir-

culate air within the cabin and those that do not. In aircraft that do

recirculate air, the air supplied to the passenger cabin while in flight is

a combination of fresh ambient air and recirculated air. Recirculated

air is passed through a HEPA filter before being reintroduced into

the cabin.

Aircraft that do not recirculate air (ie, 100% fresh am-

bient air supply) are not equipped with HEPA filters. PM measure-

ments in aircraft during commercial flights are extremely limited.

Previous studies in aircraft have mostly focused on cabin air quality

after smoking bans or on cabin conditions as related to passenger

comfort.

Guan et al. measured ultrafine particle number concen-

trations and found that they decreased during cruising (mean: 72 #

−3

The same group measured size distributions during flights,

reporting an average of 10.4, 1.4, 0.37, 0.19, 0.018, and 0.013 # cm

−3

for particle sizes of 0.3– 0.5, 0.5– 1, 1– 2, 2– 5, 5– 10, and >10 µm in

diameter, respectively.

A few other studies measured particle mass

concentrations during flights, with PM

mass concentrations typi-

cally below 15 µg m

−3

5,49– 51

To our knowledge, no co- located mea-

surements of particle number and mass distributions (over a wide

particle size range) during all stages of a commercial flight, terminal

to terminal, have been reported in the literature.

In this work, we performed particle number and mass concentra-

tion measurements during 19 domestic (U.S.A.) commercial flights.

On each flight, measurements were taken during the entire trip,

from terminal (departure) to terminal (arrival). To place these data

into context, similar measurements were taken in a variety of indoor

environments where a person might find themselves spending a sig-

nificant amount of time. These environments include retail stores,

grocery stores, restaurants, offices, transport (cars, buses, and

trains), and homes (living rooms). These measurements were carried

out in the city of Atlanta, GA, during July 2020. The data were gath-

ered using handheld instruments described in the Methods section.

It is noted that these instruments measure all airborne particles;

they do not discriminate between biological particles versus nonbio-

logical particles. The measured parameters include the number con-

centrations of particles with diameters ≤1 µm (PM

), size- resolved

particle number distributions from 0.3 to 25 µm, and sized- resolved

particle mass concentrations (PM

, PM

2.5

, PM

, and PM

The data were summarized as box plots to facilitate the compari-

son of their distributions. The results show that PM levels in aircraft

Practical Implications

• Particulate matter (PM) concentrations were measured

in a variety of indoor spaces

• In- flight aircraft had the lowest PM concentrations of all

observed locations, likely due to the fast circulation and

clean fresh air

• Restaurants had the largest PM concentrations, domi-

nated by cooking

1486

RIVERA- RIOS Et Al.

cabins, particularly while in- flight, were substantially lower than all

other surveyed indoor environments.

2 | METHODS

2.1 | Instrumentation

Three handheld instruments were deployed to each location to

measure particle number and particle mass concentrations. A P- Trak

(TSI 8525) measures particle number concentration from 0.02 to

1 μm in aerodynamic diameter (PM

number concentration). Number

concentrations are expressed as # cm

−3

. Prior studies have shown

that data taken with the P- Trak correlated very well with those from

research- grade condensation particle counters.

An AeroTrak (TSI

9306) measures size- resolved particle number concentrations from

0.3 to 25 μm in diameter with ±5% accuracy. The resolved size bins

are 0.3– 0.5 µm, 0.5– 1 µm, 1– 3 µm, 3– 5 µm, 5– 10 µm, and 10– 25 µm.

The third instrument is a DustTrak (TSI 8534), which measures size-

resolved particle mass concentrations with PM

, PM

2.5

, PM

and PM

size bins with units of µg m

−3

. The uncertainty in DustTrak

measurements is ±0.1% of the reading or 1 µg m

−3

whichever is

greater. DustTrak mass concentrations can be biased high depending

on the aerosol type which we do not correct for. The time resolution

for all instruments was 1 minute. The instruments were calibrated by

TSI prior to the study and zeroed regularly. Data were analyzed using

IGOR Pro software. The whisker box plots represent the following

statistics: lower- whisker: 10th percentile, box: lower quartile, me-

dian, and upper quartile, upper- whisker: 90th percentile, solid circle:

mean value.

2.2 | Sampling schedule

Three sets of handheld instruments were deployed simultaneously

in Atlanta, GA, from 7/13/2020 to 7/30/2020. A total of 6 different

types of indoor spaces were investigated and categorized as follows:

retail stores (6 different locations), grocery stores (6), restaurants (6),

office spaces (6), transport (4 private cars, 2 buses, and 2 trains), and

homes (living rooms) (6). The number of locations per category is

similar to other studies looking at IAQ in a variety of buildings.

The dates and sampling times for each individual location are given

in the Supplementary Information. Grocery stores, restaurants, re-

tail stores, and offices were sampled in sets of three (by three dif-

ferent researchers; each sampled at one location) at the same time

of day to avoid potential differences due to occupancy or ambient

environmental conditions (that could affect building intake air). The

individual indoor locations were chosen based on their accessibil-

ity to the researchers and the indoor environment category. The

other three locations for the same category were sampled at the

same time of day the next day. This sampling method was performed

twice to have duplicate measurements in all 6 locations of each of

these categories. All cars were sampled in the same hour window,

on consecutive days, while driving the same route (each car had its

own route). Further, sampling in cars was carried out with the same

conditions: riders were wearing masks, windows were up, and air

conditioning was on, with air recirculation off. Buses and trains were

measured in the same hour window, but on different routes. The

instruments were placed in backpacks or bags, using lines of conduc-

tive tubing to sample the air in each location. Researchers moved

within the sampled indoor locations as any other visitor would. The

instruments remained in the backpacks or bags, but these were

sometimes placed in more convenient locations, such as across the

table while inside the restaurants. We aimed for at least 30 minutes

of sampling at each location. Sampling in offices and homes lasted

for 3 hours; however, to be consistent with the other indoor spaces,

only the first 30 minutes of office data and first hour of home data

were reported in this study, the first 30 minutes may or may not

include cooking events in homes. The sampling in buses and trains

lasted as long as the ride allowed, ranging from 16 to 30 min.

2.3 | Data acquired during flights

Delta employees deployed a set of the instruments described above

in a total of 23 trips from 7/21/2020 to 7/31/2020. The Georgia

Institute of Technology team trained Delta employees by providing

step- by- step sampling instructions, as well as virtual meetings and

in- person guidance, on how to properly operate, troubleshoot, and

extract data from the instruments. Flights were chosen to cover a

range of flight durations/destinations and aircraft models. Due to

instrument issues on some of the trips, only the data from 19 flights

were analyzed in this work. Instrument issues included batteries

running out of power, tilted instrument / low alcohol warning (P-

Trak), which resulted in loss of data (data not being logged). Table 1

contains relevant information for the 19 analyzed flights.

3 | RESULTS AND DISCUSSION

3.1 | Sampling in aircraft cabins during commercial

flights

A total of 19 flights were analyzed for our comparison (Table 1). A de-

tailed description of the sampling and instrumentation is provided in

the Methods section. All 9 stages of travel were measured: Terminal

(departure), Boarding, Taxiing (out), Climbing, Cruising, Descending,

Taxiing (in), Deplaning, and Terminal (arrival). Figure 1 shows the

number concentrations, PM

0.3– 25

number concentrations, and

mass concentrations during all travel stages. The data shown in

Figure 1 were averaged data from all 19 flights. Figure S1 A- F shows

the same data for all individual flights. The particle number and mass

concentrations varied widely across the different stages of travel.

In general, they all exhibited a V- shape pattern, with the lowest

concentrations observed while cruising, having a mean PM

num-

ber concentration of 104 # cm

−3

, PM

0.3– 25

number concentration of

1487

RIVERA- RIOS Et Al.

0.44 # cm

−3

, and PM

mass concentration of 13 µg m

−3

. As seen in

Figure 1A and B, the number concentration of PM

is two to three

orders higher than PM

0.3– 25

for every travel stage. Since the PM

number concentration measurement includes particles smaller than

0.3 µm in diameter, this indicates that most of the particles have

diameters below 0.3 µm. For most of our PM measurements, the

observed medians tend to be lower than the means. This is due to

short spikes in PM concentrations, outliers, or different behaviors

between locations within the same type of indoor spaces.

Terminals are complex environments which can feature retail

stores, restaurants, and large numbers of passengers. As such, parti-

cle concentrations will depend on what part of the terminal is being

measured. For example, a large spike in PM number concentration

(up to PM

: 130,566 # cm

−3

, PM

0.3- 25

: 810 # cm

−3

) and mass concen-

tration (PM

: 342 µg m

−3

) was observed near a restaurant in the

Atlanta terminal prior to boarding the ATL- ORD (Atlanta- Chicago

O’Hare) flight (Figure S2A). Typically, both number and mass con-

centrations were elevated during the boarding process. Particle

concentrations began decreasing after the cabin door was closed

and the plane took off, owing to aircraft Environmental Control

Systems (ECS) packs and Auxiliary Power Unit (APU) operation. PM

concentrations continued decreasing and reached a stable minimum

concentration during cruising. Slight increases in particle mass con-

centration during food service with corresponding increases in num-

ber concentration (Figure S2B) were occasionally observed. When

the plane began descending, particle concentrations started increas-

ing and an abrupt increase was typically observed once the cabin

door was opened and the deplaning process began. This V- shape

pattern has been shown previously for ultrafine particles during

flights.

47,53

The increase of particle concentrations during boarding

and deplaning can be due to incursions from outside the aircraft

and resuspension of particles from the floor as passengers find their

seats or prepare to leave.

Air exchange rates in the cabin are rapid

during flight, reducing the number of particles in the cabin signifi-

cantly. In addition, ambient air at altitude contains fewer particles

than air at the surface, contributing to low cruising particle number

and mass concentrations and which also explains the decrease and

increase observed during climbing and descending, respectively.

More insights on the characteristics of particles can be obtained

by examining the number and mass distributions over wide particle

size ranges across all travel stages. Overall, the observed V- shape

pattern is more prominent for the smaller particle size ranges (bins),

which was reflected in the strong variation in particle number con-

centrations but relatively modest changes in mass concentrations.

Figure 2A shows the measured PM

0.3– 25

number distributions during

all stages of travel. The number concentration in each stage is dom-

inated by particles with 0.3– 0.5 µm in diameter. Interestingly, while

the number concentration of particles of all sizes varies across each

travel stage, the extent of change is highly dependent on the particle

size. Specifically, the size bins from 0.3 to 3 µm show a one to two

orders of magnitude decrease in numbers from Terminal to Cruising

stages. The size bins from 3 to 25 µm also have the same V- shape

pattern, but it is attenuated significantly. This difference in behav-

ior between small and large particles could arise from differences in

TABLE 1 Commercial flights where measurements were conducted.

Tail number Date Leg Aircraft type

Age of aircraft

(y) Air supply

†

Aircraft

capacity

Aircraft

load

696 7/24/2020 A T L - S L C 757– 20 0 21.5 F + R 199 106

3702 7/24/2020 S L C - P D X 737– 800 22 F + R 160 79

276 7/25/2020 P D X - S E A ERJ 175– 100 - F + R 70 28

3841 7/26/2020 SEA- ATL 737– 900 5 F + R 180 93

8970 7/30/2020 A T L - A E X C R J - 2 0 0 - F 50 20

A E X - A T L - 50 25

9513 7/30/2020 ATL- CHS 717– 10 0 20 F 110 52

7/31/2020 CHS- ATL 110 45

8110 7/24/2020 A T L - O R D A220 - 100 1.4 F + R 109 63

O R D - L G A 109 50

3084 7/30/2020 A T L - J F K A321- 200 4 F + R 191 43

J F K - A T L 185 109

9573 7/23/2020 ATL- MKE 717– 10 0 19.9 F 110 47

3017 7/22/2020 A T L - L G A A321- 200 3.5 F + R 191 59

8242 7/23/2020 L G A - C L T ERJ 175– 200 - - 76 22

9547 7/23/2020 C L T - A T L 717– 10 0 18 F 110 59

9337 7/21/2020 A T L - X N A C R J - 9 0 0 - F + R 76 39

XNA- ATL - 76 29

3608 7/30/2020 A T L - E Y W 737– 70 0 11 F + R 124 57

†

F + R corresponds to Fresh ambient air + Recirculated air (HEPA filtered); F corresponds to 100% Fresh ambient air.

1488

RIVERA- RIOS Et Al.

their sources. Small particles are likely from ambient air entering the

aircraft (hence, more sensitive to altitude) while the sources of larger

particles are likely from human activities within the aircraft. In terms

of particle mass, large particles (PM

10– 15

) dominate the PM mass

concentration at most travel stages, with higher contributions from

small particles at the departure terminals. This is shown in Figure 2B

where PM mass concentrations for different size bins within a travel

stage tend to stay at the same level but show a substantial increase

in the final size bin (10– 15 µm). The slight variation in the number

concentrations of larger particles across all stages (Figure 2A) is mir-

rored by the PM mass concentrations shown in Figure 2B, with the

exception of the largest size bin (PM

10– 15

) which varied significantly.

Human activities being the source of larger particles explains why

the highest increase in PM mass concentration was observed during

boarding/deplaning as the passengers manage their luggage and

enter/exit the aircraft.

3.2 | Sampling in various indoor environments in

Atlanta, GA

Six types of indoor environments were sampled: retail stores, gro-

cery stores, restaurants, offices, transport (cars, buses, and trains),

and homes (living rooms). Only a few previous studies have looked

at PM in several different types of indoor environments, and most

studies focused on one particular type of indoor environment.

20,21

Six different locations for each indoor environment type were stud-

ied. Transport was an exception where 4 cars, 2 trains, and 2 buses

were sampled. Each location sampled is referred to by Category (eg,

Restaurant, Retail, Office, etc) and a letter (A- F), such as Restaurant

A, Restaurant B, etc. For the purpose of our discussion, we grouped

data from all locations in each sampled indoor environment cat-

egory and compared them with one another. Additional details of

the sampled locations in each indoor category are provided in the

Supporting Information. Indoor spaces showed large variabilities

in their particle levels. Figure 3 shows (A) PM

number concentra-

tions, (B) mean number distributions of particles larger than 0.3 µm,

colored by size bin, and (C) mean particle mass distributions, also

colored by size bins, for indoor locations grouped by category. To

facilitate a comparison of the PM concentrations in aircraft to other

indoor locations, all travel stages where the plane had its door closed

were grouped into an “In- Flight” category. This category includes

Taxiing (out), Climbing, Cruising, Descending, and Taxiing (in), and it

is also shown in Figure 3.

Restaurants had the highest particle number and mass concen-

trations among all indoor spaces, the mean PM

number and PM

mass concentrations were 29,400 # cm

−3

and 50 µg m

−3

(Figure 3A

and C), respectively. A large spread in PM levels was observed

across all restaurants (Figures S3 and S4). A major reason for the

spread were restaurants that had separate cooking and eating

areas and those that did not. Cooking aerosols are a well- known

source of indoor PM which has been previously shown to lead to

elevated PM concentrations, sometimes well above outdoor reg-

ulatory standards for PM

2.5

mass concentration (ie, 35 µg m

−3

for

24- hour standard).

55,56

Cooking in the same space as the seating

area (Restaurants C and D) allows cooking aerosols to mix freely

within the restaurant, leading to enhanced particle concentrations

in the seating area.

Notably, the mean PM

number and mass

concentrations were as high as 91,392 # cm

−3

and 109 µg m

−3

these restaurants, respectively. On the other hand, restaurants

that had separate kitchen areas (Restaurants A and B) exhibited

low mean PM

levels (16 and 17 µm

−3

). Interestingly, although

all the major enhancements in PM mass that are due to cooking

appear to be in the PM

size bin, the cooking method and type

of food also influence the size distributions of cooking aerosols

in larger size bins. PM

is almost always enhanced during cook-

ing but PM

can also be affected.

58,59

For instance, PM mass in

FIGURE 1 PM number and mass concentrations across flight stages

(A) PM

number concentrations, (B) PM

0.3– 25

number concentrations,

and (C) PM

mass concentrations during each travel stage

20x10

Number Conc. (# cm

-3

)

Terminal

Boarding

Taxiing

Climbing

Cruising

Descending

Taxiing

Deplaning

Terminal

0.3-25

Number Conc. (# cm

-3

)

Terminal

Boarding

Taxiing

Climbing

Cruising

Descending

Taxiing

Deplaning

Terminal

140

120

100

Mass Conc. (µg m

-3

)

Terminal

Boarding

Taxiing

Climbing

Cruising

Descend

ing

Taxiing

Deplaning

Terminal

(A)

(B)

(C)

1489

RIVERA- RIOS Et Al.

Restaurant D is dominated by PM

but has modest enhancements

in PM mass in every size bin which could also be due to cooking

(Figure S4). Restaurants E and F have minimal cooking (ie, salad

bar or sushi) and lower particle concentrations were observed

(mean PM

number and mass concentrations of 8,685 # cm

−3

and

10 µg m

−3

for Restaurant E). Taken together, the differences in

kitchen/seating area configuration, cooking method, and food

type are key contributors to the large spread of particle number

and mass concentrations across all restaurants.

Homes were also influenced by cooking and follow restau-

rants in terms of PM number and mass concentrations (Figure 3

and Figures S5 and S6). All measurements were conducted in living

rooms, but if living rooms and kitchens are connected, cooking activ-

ities can enhance PM concentrations in both areas.

Some sampled

homes in this study had cooking activities (Homes B, D, and E; all liv-

ing rooms in this study shared the same open space as the kitchens)

and some did not (Homes A, C, and F). The spread in PM levels mea-

sured in homes was related to cooking activities within the houses.

FIGURE 2 Size- resolved particle number and mass concentrations during each travel stage. (A) Number distribution of particles with

diameters from 0.3 to 25 µm and (B) Mass distribution of particles with diameters ≤15 µm. Note that the mass concentration data shown in

(B) are cumulative, where PM

corresponds to mass concentration of particles with diameters ≤x µm

0.001

0.01

0.1

100

Number Conc. (# cm

-3

)

-0

-1

-3

-5

-2

-0

-1

-3

-5

-0

-1

-3

-5

-0

-1

-3

-5

-2

-0

-1

-3

-5

-2

-0

-1

-3

-5

-2

-0

-1

-3

-5

-2

-0

-1

-3

-5

-2

-0

-1

-3

-5

-2

Terminal Boarding Taxiing

Climbing Cruising Descending Taxiing Deplaning

Terminal

120

100

Mass Conc. (µg m

-3

)

Terminal Boarding Taxiing Climbing Cruising TerminalDescending Taxiing Deplaning

(A)

(B)

1490

RIVERA- RIOS Et Al.

For example, a house with (Home B) and without cooking (Home A)

had mean PM

mass concentrations of 166 and 6.53 µg m

−3

, respec-

tively. Figure S7 clearly shows that the particle number and mass

concentrations in Home E were low before cooking but rose signifi-

cantly during and after cooking. Elevated levels of PM from home

cooking have been measured in previous studies, with the amount

of aerosols and their chemical composition depending on the type of

food and method of cooking.

55,57,58,60– 62

There were elevated levels of PM in grocery stores with cooking

activities (Figures S8 and S9). Cooking in grocery stores was carried

out in deli areas (Stores A, C, D, and E), leading to elevated particle

concentrations compared to others. The amount of cooking in these

grocery stores depends on the customer demand for the items at the

deli which can explain why Store D displayed the highest levels ob-

served, with mean PM

number and mass concentrations of 21,805

# cm

−3

and 40.3 µg m

−3

, respectively. However, since grocery stores

were typically much larger than restaurants and homes, cooking

aerosols were more diluted and PM concentrations did not reach

the same levels that were observed in homes and restaurants. In ad-

dition to cooking sources, contributions from outside the location

cannot be disregarded. Grocery stores in Midtown, Atlanta (Stores

A and D), had the highest PM

number concentrations (17,165 and

21,805 # cm

−3

). These PM

number concentrations are likely due to

cooking, but since these two stores are located relatively close to

each other, incursion of aerosols from nearby traffic, construction

work, or secondary organic aerosols in the Midtown area cannot

be ruled out.

63,64

Measurements of particle composition would be

needed to separate the contributions from these sources.

Transport, including cars, buses, and trains, featured higher PM

number concentrations than offices and retail stores, but lower than

locations that had cooking activities (Figure 3A). Cars showed sub-

stantial variability between each other, which could be due to the

presence and condition of air filters, the age of the vehicle, or the

route taken during sampling (Figures S10 and S11). Two of the high-

est particle measurements in cars (Cars C and D, mean PM

number

concentration 5,979 and 7,214 # cm

−3

) were in relatively old vehi-

cles, 2010 and 2002 models with the second having a significant

amount of PM

(mean: 68 µg m

−3

). Trains and buses had similar and

relatively constant concentrations over the course of the measure-

ments. This could be due to their doors opening/closing constantly

and quick air circulation. For these reasons, the PM concentrations

in trains and buses were likely more representative of a mixture of

the air inside and outside the vehicles. Traffic conditions, ambient

PM levels, and localized PM sources can all affect the concentrations

FIGURE 3 Comparison between in- flight aircraft data and other indoor spaces around Atlanta, GA. (A) PM

number concentration

measurements (mean values). (B) PM

0.3- 25

number distributions (mean values), colored by the contribution per size bin. (C) PM

mass

distributions (mean values), colored by the contribution per size bin. The pie charts above the bar show the fractional contribution of each

size bin to the total measured particle number and mass concentrations. Data for particles with similar size ranges in (B) and (C) are shaded in

similar colors

1491

RIVERA- RIOS Et Al.

measured in a vehicle.

PM concentrations near roads are usually

enhanced relative to other nearby locations in the urban area.

study in Atlanta showed an urban background PM

2.5

concentration

of 8 µg m

−3

but roadside concentrations of 21 µg m

−3

, an enhance-

ment of a factor of ~3.

Overall, our Transport PM

2.5

concentrations

(mean: 24 µg m

−3

) are in line with previous roadside measurements

and the PM

2.5

concentrations in vehicles (16 and 25 µg m

−3

in the

warm and cold seasons) reported by Brown et al. in Atlanta.

Finally, offices and retail stores (with some exceptions) were

some of the cleanest indoor environments measured excluding

in- flight aircraft (Figures 3A, S12– S15). Offices did show variabil-

ity, with some being enhanced in small particles (Office C, mean

: 32 µg m

−3

) and others in large particles (Office E, mean PM

48 µg m

−3

). All offices were in different buildings in the Georgia

Institute of Technology campus. It is possible that the low PM levels

observed in these offices are due to their low occupancy from lim-

ited campus access forced by the COVID- 19 pandemic. The reason

for the elevated PM

concentrations in Office C could be due to re-

actions between VOCs released from the building materials (mostly

wood) and ozone incursions, which are well- established sources of

secondary organic aerosols.

The retail category was the second

cleanest, following offices, but had some outliers. One of the out-

liers was Retail F, a home improvement store, which featured high

mean PM

concentrations (70.8 µg m

−3

). This could be due to wood-

cutting and other mechanical/abrasive activities that release dust

particles in this store type. The other outlier was Retail E, a phar-

macy that also had a high mean PM

concentrations of 38.6 µg m

−3

Retail E is a carpeted location, and resuspension of dust from the

floor could lead to the observed PM

concentrations.

Dust parti-

cles are larger than cooking or secondary organic aerosols, so they

are observed as an enhancement in the PM

10- 15

size bin. The high

10– 15

contributions from Retails E and F enhance the mean PM

mass shown in Figure 3C for the retail category.

3.3 | Comparison between in- flight and other

indoor environments

Figure 3 shows the measured PM number concentrations and mass

concentrations in various size bins while in- flight and in other indoor

spaces. The PM

number concentrations in Figure 3A are 60– 274

times higher than the PM

0.3– 25

number concentrations in Figure 3B,

highlighting that particles smaller than 0.3 µm dominate the number

size distributions in all spaces, with particles between 0.3– 0.5 µm

being the next most abundant. When compared to other spaces, the

in- flight particle number and mass concentrations are substantially

lower. Specifically, the mean PM

number concentration during the

in- flight period was 1,776 # cm

−3

, 1.4 times lower than the next low-

est mean value (2,473 # cm

−3

for offices, Figure 3A). It is noted that

the mean in- flight PM

number concentration is affected by some

higher concentrations during taxiing periods. The corresponding

median for the in- flight period is much lower at 81 # cm

−3

which is

18 times lower than the median for offices (1,462 # cm

−3

). The mean

in- flight PM

0.3– 25

number concentration was 0.54 # cm

−3

, 49 times

lower than offices (Figure 3B). The mean in- flight particle number

concentrations were low across all size bins in general but compara-

ble to other locations in the >3 µm size bins (0.3– 0.5 µm: 0.8 # cm

−3

0.5– 1 µm: 0.19 # cm

−3

, 1– 3 µm: 0.05 # cm

−3

, 3– 5 µm: 0.01 # cm

−3

5– 10 µm: 0.01 # cm

−3

, and 10– 25 µm: 0.006 # cm

−3

Figure S16). The

pie charts in Figure 3B also highlight that although small particles

dominate particle numbers in all categories, larger particles (>1 µm)

contribute about 7% of the total particles in the in- flight category,

more than any other indoor environment. Interestingly, the in- flight

particle number concentrations measured in this study were 2– 10

times lower than the only other published in- flight size distribution

found in the literature.

This could be due to the lower passenger

loads (Table 1) and the use of masks by everyone on board as re-

quired by the airline, which filters out and reduces the number of

exhaled particles released into the surrounding environment.

The particle mass concentrations in- flight are also lower than

other indoor spaces, though the difference is not as drastic as for

number concentrations. The mass concentration of PM

2.5

and PM

in the cabin was below 10 μg m

−3

(mean = 4.3 and 5.2 μg m

−3

, re-

spectively), about 3 times lower than offices. While EPA does not

set PM standards for indoor air, these values are substantially lower

than the EPA standards for outdoor air (24- hour standards for PM

2.5

and PM

are 35 and 150 μg m

−3

, respectively).

A few studies have

reported PM

mass concentration in flights, which ranged from 1

to 17 µg m

−3

and is consistent with our results.

5,46,49,69

It is noted

that while the in- flight category had the lowest measured mean

mass concentration, the median PM

in- flight (11 µg m

−3

)

was similar to retail stores and offices (both 15 µg m

−3

) but lower

than other indoor spaces (23– 31 µg m

−3

) (Figure S16). This is likely

due to the high concentrations observed during the taxiing peri-

ods. PM

10– 15

contributes 65% of the total PM mass for the in- flight

category. This mass distribution is unique, as highlighted by the pie

charts in Figure 3C where in- flight had the largest contribution from

particles >10 μm in diameter to the overall particle mass, likely aris-

ing from human activities and the carpeted floor in the cabin acting

as sources of dust particles. The only other indoor category with

a large contribution of PM

10– 15

are retail spaces, which are driven

by Retails E (pharmacy; particle resuspension from carpeted floor)

and F (home improvement store; dust particles). On the opposite end

of the spectrum, restaurants and homes had the highest mean PM

concentrations. PM

from cooking emissions dominated these cate-

gories, contributing over 75% of the total PM mass.

4 | CONCLUSION

In this work, we conducted the first simultaneous measurements

of size- resolved particle number and mass concentrations in com-

mercial flights, from terminal to terminal, and compared them to a

variety of other indoor environments. Our main finding is that in-

flight particle number and mass concentrations in aircraft were the

lowest we measured in any of the surveyed indoor environments.

1492

RIVERA- RIOS Et Al.

Particles with diameters smaller than 1 µm dominate the total parti-

cle number concentrations, which is consistent with the fact they are

the most difficult to remove by physical filtration.

The low in- flight

PM concentrations can be attributed to the frequent air exchange

in cabins and low particle numbers outside the aircraft at altitude.

Notably, the PM number concentrations measured in this work were

up to an order of magnitude lower than results reported in the only

other previously published study,

possibly due to lower passenger

loads and the use of masks, which were required for all passengers

by the airline during this period.

There are several limitations in this study. The instruments used,

although useful due to their mobile nature, lack any information on

particle composition or type. This is important when trying to differ-

entiate between aerosol types, such as cooking aerosols, secondary

organic aerosol, or direct emissions from the passengers in the air-

craft. In addition, the instruments operate on broad size bins that

enable us to broadly characterize the size distribution of the number

and mass but cannot be quantitatively compared against each other.

Finally, the particle composition could potentially influence the sen-

sitivity of the instruments making comparisons between different

environment types more challenging.

The measurements in this work alone cannot be used directly

to assess the cabin air safety of commercial flights during the

COVID- 19 pandemic. However, it provides the particle number and

mass concentration distributions needed to assess the PM levels in

flights during this period. Results show that the air in aircraft cabins

had substantially lower PM levels than other indoor environments,

highlighting the role of frequent air exchange and clean air supply

(clean outside air and/or HEPA- filtered recirculated air) in reducing

particle concentration in indoor environments. Though these mea-

surements are an important step in risk mitigation, further studies to

assess the safety of air travel should include direct measurements of

viral loads in aircraft cabins and tracing the movement of particles

within the cabins.

ACKNOWLEDGEMENTS

Funding and support from Delta Air Lines.

AUTHOR CONTRIBUTION

Jean C. Rivera- Rios involved in data curation, formal analysis, meth-

odology, investigation, visualization, writing— original draft, writing—

review, and editing. Taekyu Joo and Masayuki Takeuchi involved

in data curation, formal analysis, methodology, investigation, and

visualization. Thomas M. Orlando, John W. Mathis, Cliffton D. Pert,

Brandon A. Tyson, Tyler M. Anderson- Lennert, and Joshua A. Smith

performed investigation. Tracy Bevington involved in investigation,

project administration, and resources. Nga Lee Ng performed con-

ceptualization, data curation, formal analysis, investigation, method-

ology, project administration, resources, supervision, visualization,

writing— original draft, writing— review, and editing.

ORCID

Jean C. Rivera- Rios https://orcid.org/0000-0003-2108-9131

Taekyu Joo https://orcid.org/0000-0002-8252-4232

Nga Lee Ng https://orcid.org/0000-0001-8460-4765

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SUPPORTING INFORMATION

Additional supporting information may be found online in the

Supporting Information section.

How to cite this article: Rivera- Rios JC, Joo T, Takeuchi M, et al.

In- flight particulate matter concentrations in commercial flights

are likely lower than other indoor environments. Indoor Air.

2021;31:1484–1494. https://doi.org/10.1111/ina.12812