Indoor Air Quality While Traveling: What We Learned After 1 Year Across 12 Countries

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Last year, we published our first deep dive into indoor air quality after carrying a portable monitor through more than three years of full-time travel. That article explained why we started measuring the air inside our Airbnbs, apartments, hotels, and cruise-ship cabins. It also covered the basics of PM2.5, CO₂, humidity, temperature, and the small routines we use to evaluate a new home.

But we kept collecting data and also built our own analysis tool to turn thousands of individual monitor readings into consistent daily, stay-level, and full-year comparisons.

For this follow-up, we selected one complete reporting year:

June 1, 2025 to May 31, 2026.

During those 12 months, our monitor traveled through Europe, North America, Australia, Southeast Asia, Taiwan, South Korea, and across the Pacific Ocean aboard the Noordam.

We collected:

• 8,056 source readings
• Data on 350 calendar days
• 20 separate stays
• 12 countries
• One 27-day Pacific Ocean crossing
• 337 days with strong A or B measurement coverage
• 16 stays with enough data to qualify for our destination rankings

What We Learned After One Full Year

The main lesson was not simply that some places had cleaner air than others.

It was this:

The destination with the highest average pollution is not necessarily the destination responsible for our greatest total exposure.

How long we stay matters but so do:

• The season
• The specific building
• Ventilation
• Humidity
• Outdoor conditions
• Indoor activities
• How consistently pollution remains elevated

A short stay with poor air may contribute less total monitored burden than a two-month stay with moderately elevated pollution. That distinction is especially important for us as slow travelers.

How to Read Our Analysis

Before looking at the results, it helps to explain three parts of our methodology:

1. Daily coverage grades
2. Our chart colors
3. Sustained pollution episodes

These are analytical tools we created for our personal dataset.

What the A, B, C, and D Coverage Grades Mean

A daily average is useful only when the monitor collected enough data to reasonably represent that day. A reading collected for two hours should not carry the same confidence as one that covers most of the day. Our script assigns every measured day a coverage grade:

• Coverage Grade A: At least 18 hours of measurement span, with no gap longer than four hours
• Coverage Grade B: At least 12 hours of measurement span
• Coverage Grade C: At least six hours of measurement span
• Coverage Grade D: Less than six hours of measurement span

These are data-completeness grades. They do not describe the air itself. An grade A does not mean the air was good. It means we have relatively complete data about that day. A grade D does not mean the air was bad. It means we do not have enough data to confidently characterize the whole day.

Across the year:

• 322 days received an A
• 15 days received a B
• 12 days received a C
• 1 day received a D

That gave us 337 A/B days overall.

Note: We excluded four short stops with fewer than three measured days from our destination rankings. Their readings remain in the technical report, but a few hours or one day of monitoring should not be compared directly with a 70-day stay.

What the Chart Colors Mean

We use the same five colors across the charts:

• Green: 0 to 5 µg/m³
• Yellow: Above 5 through 15 µg/m³
• Orange: Above 15 through 55.4 µg/m³
• Red: Above 55.4 through 150.4 µg/m³
• Maroon: Above 150.4 µg/m³

These are custom visualization bands. They are not official AQI categories, indoor-health classifications, or medical thresholds. We use 15 µg/m³ as an important boundary because it is the World Health Organization’s 24-hour PM2.5 guideline. That guideline applies to a daily average. It does not mean that one reading above 15 represents an emergency.

Caption: Daily indoor PM2.5 results for stays with at least three measured days. The percentage above 15 uses A/B coverage days only. Colors are custom visualization bands, not official AQI categories.

What We Mean by a Sustained Pollution Episode

One high reading can result from a short activity such as cooking, cleaning, burning something, or opening a window. We therefore wanted to distinguish individual spikes from pollution that stayed elevated across multiple readings. Our script uses three independent episode definitions:

• Elevated episode: PM2.5 remained above 25 µg/m³ for at least 30 represented minutes
• High episode: PM2.5 remained above 35 µg/m³ for at least 20 represented minutes
• Extreme episode: PM2.5 remained above 100 µg/m³ for at least 5 represented minutes

Because our readings are not perfectly continuous, the script counts only the amount of observed time each reading can reasonably represent. It does not assume that a long unmeasured gap had the same conditions.

Across the full year, the script detected:

• 71 Elevated episodes
• 41 High episodes
• 1 Extreme episode
• 113 sustained episodes in total
• 288 represented hours inside those episodes

This does not mean we experienced 113 separate health emergencies. It means elevated particle conditions persisted across multiple observations rather than appearing as isolated spikes.

Caption: App-defined sustained episodes based on concentration, continuity, and represented observed time. These analytical thresholds are independent from the chart colors.

Our Full-Year PM2.5 Results

Across the eligible measurements, our overall interval-weighted indoor PM2.5 average was: 11.1 µg/m³

Of the 336 qualifying A/B days used in our stay comparisons:

101 days, or 30.1%, had a daily average above 15 µg/m³.

That overall average hides major differences between destinations. Our European summer, San Francisco stay, Pacific crossing, and Sydney stay generally produced low particle readings. Our later stays in Southeast Asia, Taiwan, and South Korea produced more frequent and persistent elevations.

Our Five Cleanest Stays

Our cleanest stays by average daily time-weighted PM2.5 were:

1. Pacific Ocean crossing: 0.8 µg/m³
2. Sydney, Australia: 3.7 µg/m³
3. San Francisco, USA: 3.9 µg/m³
4. Valencia, Spain: 4.9 µg/m³
5. Cologne, Germany: 5.5 µg/m³

None of the qualifying A/B days across these five stays had a daily average above 15 µg/m³.

Our cleanest stay was not on land

The most surprising result came from our cabin aboard the Noordam cruise ship. During the 27-day Pacific crossing from Seattle to Sydney, average daily PM2.5 was only: 0.8 µg/m³

The cabin also recorded:

• Zero A/B days above 15 µg/m³
• Median CO₂ of approximately 480 ppm
• Almost no represented time above 1,000 ppm CO₂

It was easily the cleanest indoor environment we measured during the year.

Sydney was our cleanest city

Once we exclude the Pacific crossing, Sydney was our cleanest city. During 15 measured days:

• Average daily PM2.5 was 3.7 µg/m³
• No A/B days exceeded 15 µg/m³
• No represented CO₂ time exceeded 1,000 ppm

That is a useful reminder that low PM2.5 does not automatically mean every aspect of the indoor environment is ideal.

Our Most Concerning Stays

The five highest average daily PM2.5 values were:

1. Koh Samui, Thailand: 19.4 µg/m³
2. Da Nang, Vietnam: 17.0 µg/m³
3. Taipei, Taiwan: 16.3 µg/m³
4. Busan, South Korea: 15.4 µg/m³
5. Ubud, Indonesia: 12.9 µg/m³

Average PM2.5 tells only part of the story. The share of well-covered days above 15 gives additional context.

Koh Samui had our worst average

During our 35-day Koh Samui stay:

• Average daily PM2.5 was 19.4 µg/m³
• 27 of 34 A/B days exceeded 15 µg/m³
• That represents 79% of the well-covered days

Koh Samui did not necessarily produce the worst isolated reading. Its problem was consistency. Elevated conditions appeared across most of the stay.

Taipei combined particles, and ventilation concerns

Taipei averaged 16.3 µg/m³. Thirteen of its 27 A/B days exceeded 15 µg/m³, or approximately 48%. It also recorded:

• CO₂ above 1,000 ppm for approximately 22% of represented time
• Frequent sustained PM2.5 episodes

This is why we no longer judge an apartment using a single measurement.

Ubud’s average concealed frequent elevated days

Ubud averaged 12.9 µg/m³, below our 15 µg/m³ daily comparison reference. That initially sounds reassuring. However, 8 of its 21 A/B days, or 38%, exceeded 15 µg/m³.

A moderate-looking average can hide both frequent particle elevations and a separate moisture problem.

Why Da Nang Was Our Most Important Result

Koh Samui had our highest average PM2.5. Da Nang generated our largest cumulative monitored burden.

During our 70-day Da Nang stay:

• Average daily PM2.5 was 17.0 µg/m³
• 44 of 69 A/B days exceeded 15 µg/m³
• That represents approximately 64%
• The worst seven-day average was 26.5 µg/m³
• We detected 40 sustained episodes
• Those episodes totaled 103.5 represented hours
• Da Nang generated approximately 13,458 µg/m³ × hours of monitored PM2.5 burden

Da Nang was not dramatically worse than every other destination on every day.

The issue was the combination of:

• Moderately elevated average conditions
• Frequent elevated days
• Sustained episodes
• A long 70-day stay

Those factors added up.

Caption: Cumulative monitored burden combines PM2.5 concentration with represented measurement time. Longer stays naturally accumulate more. This is a relative comparison, not a medical dose.

Da Nang produced more cumulative monitored burden than Koh Samui and Taipei combined. That does not mean Da Nang was always the most polluted destination. It means we stayed long enough for moderately poor conditions to matter more.

For slow travelers, duration can be as important as the headline average.

We Still Plan to Return to Da Nang

These results do not mean we are crossing Da Nang off our travel list. We still love the city and plan to return next year. Air quality is one factor in a much larger decision that also includes:

• Community
• Food
• Cost
• Convenience
• Walkability
• Lifestyle
• How much we enjoy being there

The data does mean that we need a better prevention plan. Our monitor remained inside the apartment. It did not measure what we inhaled while walking, exercising, eating outside, or moving around the city.

On days when outdoor PM2.5 is worse than indoor air, the stationary monitor understates our total exposure.
So during our next Da Nang stay, we plan to:

• Keep checking outdoor PM2.5 before long outdoor activities
• Wear well-fitting, approved N95 respirators on poor-air days
• Reduce, reschedule, or move prolonged outdoor exercise indoors when pollution is elevated
• Keep windows closed when outdoor particle levels are worse than indoors
• Check air-conditioning filters early in the stay

CDC travel guidance recommends NIOSH-approved particulate respirators such as N95 or P100 respirators when travelers are exposed to poor outdoor air quality. Proper fit matters because air leaking around the edges reduces protection.

For stays longer than one month, we are also considering buying or renting a portable air purifier.

We would look for:

• A unit sized for the room where we spend the most time
• Replacement filters that are locally available
• Quiet operation at a setting we can use consistently

EPA recommends selecting a portable air cleaner with a particle Clean Air Delivery Rate (CADR) large enough for the intended room. Many portable cleaners achieve a high particle CADR by using a HEPA filter.

As nomads, buying an appliance for every short stop would be expensive and wasteful. For a six-to-ten-week stay, however, buying a local unit and then reselling, donating, or leaving it with the host may make sense.

Our monitor would let us verify whether the filter actually reduces indoor PM2.5 instead of simply assuming that it works.

If you are worried about Air Quality, some must-have for hotel rooms or Airbnbs are the Levoit Air Purifier for longer stays or PureZone Mini as a carry-on

Clean PM2.5 Did Not Always Mean Good Indoor Conditions

PM2.5 was our primary destination-comparison metric, but it was not the only useful signal. Our newer monitor also recorded:

• CO₂
• Relative humidity
• Temperature
• A relative TVOC index

The full-year timeline made one point particularly clear:

There is no single indoor-air-quality number.

Caption: Daily PM2.5, CO₂, relative TVOC, humidity, and temperature across the full reporting period. Gray sections indicate missing or excluded measurements.

What the CO₂ data showed

Across the reporting period, median CO₂ was approximately 575 ppm.

• CO₂ exceeded 1,000 ppm for roughly 10% of represented measurement time.
• San Francisco and Valencia were among our cleanest stays for particles, yet both showed meaningful periods above 1,000 ppm CO₂.

That can happen when an apartment keeps outdoor particles out but does not bring in enough fresh air for the number of occupants. CO₂ is not a complete air-quality or safety score. It is useful primarily as context for occupancy and ventilation.

• When outdoor air is clean, opening a window may improve ventilation.
• When outdoor PM2.5 is elevated, opening the window can improve CO₂ while worsening particle pollution.
• Ventilation and filtration therefore need to be considered together.

Humidity was our most persistent indoor problem

Relative humidity was above 60% for approximately half of represented measurement time across the year.

The most humid qualifying stays included:

• Ubud: approximately 90% of represented time above 60%
• Koh Samui: approximately 89%
• Da Nang: approximately 77%
• Taipei: approximately 76%

High humidity does not prove that a property contains mold. However, sustained moisture creates conditions that deserve attention. EPA recommends maintaining indoor relative humidity below 60%, ideally between 30% and 50%. (Read: Care for Your Air: A Guide to Indoor Air Quality)

We now inspect apartments in humid countries more carefully for:

• Musty smells
• Condensation
• Mold around windows or air-conditioning units
• Damp cabinets and closets
• Water damage
• Bathrooms without effective exhaust
• Air conditioners that cannot reduce humidity

We also use air-conditioning or dry mode when available and avoid drying large amounts of laundry inside the main living space.

How This Data Changed the Way We Travel

We have either stopped visiting place with terrible air and have become more deliberate about:

• When we visit
• How long we remain
• Which apartment we choose

Before booking

For longer stays, we research seasonal pollution patterns rather than checking only the current AQI.

We look for:

• Burning seasons
• Wildfire risk
• Nearby highways
• Construction
• Air conditioning
• Air purifiers
• Reviews mentioning smoke, dust, mold, or musty smells

For a month-long booking, we may ask when the air-conditioning filters were last cleaned and whether the apartment has experienced moisture issues.

During the first few days

We place our Temtop M10+ Wifi Air Quality Monitor in the main living area.

We keep it away from:

• The stove
• Open windows
• Air-conditioning vents
• Direct sunlight
• Humidifiers
• Dehumidifiers

We try to collect several days of data before reaching a conclusion.

When PM2.5 is elevated

We:

• Check for indoor sources such as cooking, smoke, candles, or cleaning
• Compare indoor and outdoor conditions
• Close windows when outdoor pollution is worse
• Reach out to the landlord when elevated conditions persist during a long stay

When CO₂ is elevated

We:

• Ventilate when outdoor air is clean
• Open internal doors
• Avoid sleeping in a tightly sealed room
• Check whether the air conditioner only recirculates indoor air

When humidity remains high

We:

• Use air-conditioning or dry mode
• Improve airflow
• Inspect for moisture

What This Dataset Cannot Tell Us

This remains a personal travel dataset, not a scientific study. The monitor stayed inside our temporary homes. It did not follow us while we:

• Walked outside
• Exercised
• Ate in restaurants
• Took flights or trains
• Explored each destination

We also did not consistently record:

• Cooking and cleaning activities
• Weather
• Nearby fires
• Construction
• …

Consumer monitors are useful for identifying patterns and testing interventions, but they do not measure every pollutant or provide a complete picture of personal exposure. Placement, temperature, humidity, processing methods, and sensor limitations can also affect results.

Our numbers are best interpreted as directional evidence about the indoor spaces where we stayed, not as precise measurements of everything we personally inhaled.

Our Bottom Line

After 8,056 source readings over one complete year, our main conclusion is not simply that some destinations have cleaner air than others. It is that indoor air quality depends on:

• The season
• The specific property
• The length of the stay
• Ventilation
• Humidity
• Outdoor conditions
• What happens inside the apartment

Our Pacfic crossing produced our cleanest measured environment. Sydney was our cleanest city. Koh Samui produced our highest average PM2.5 and the most consistently elevated days. Da Nang generated our largest cumulative monitored burden because moderately elevated pollution continued across a 70-day stay. Ubud showed how a reasonable-looking average can hide frequent elevated days and persistent humidity. San Francisco and Valencia showed why low PM2.5 does not necessarily mean good ventilation.

None of those lessons would have been obvious from Airbnb photos or a city’s annual AQI ranking.

That is why our air-quality monitor has become one of the most useful pieces of technology in our travel bag. It does not give us certainty. It gives us visibility.

That visibility helps us make better decisions without automatically avoiding the places we love.

Measure – If you are interested to measure air quality arround you, we recommend the Temtop M10+ Wifi Air Quality Monitor.

Protect yourself – If you are worried about Air Quality, some must-have for hotel rooms or Airbnbs are the Levoit Air Purifier for longer stays or PureZone Mini as a carry-on

Have you ever measured the air inside an Airbnb, hotel room, or apartment? Were the results what you expected? Let us know in the comment section below.