An Estimated 11,000 International Delegates at COP 26 Will Generate 5400 Tons of CO2 emissions

At this years G7, it was only a matter of time before news stories relayed the climate outrage of politicians and their entourages flying (sometime only 100’s of km’s) into Cornwall, UK.

I share the outrage at such stories.

I expect the same at this years COP 26 conference in Glasgow this year.

According to the Energy and Climate Intel Unit:

It will involve upwards of 30,000 people in the city, representing over 200 countries, businesses, NGOs, faith groups and many more.

With such a large number of delegates in attendance, the climate footprint will be significantly greater than the G7. As my mind started whirring, I wondered if it was possible to quantify just how much impact to the environment travel to and from the conference could cause.


In 2019, the UN published the list of all delegates attending the COP 26 Summit.

In summary;

States/organisations Participants
Parties 196 11406
Observer States 1 8
United Nations Secretariat units and bodies 28 306
Specialized agencies and related organizations 23 400
Intergovernmental organizations 76 652
Non-governmental organizations 1049 7417
Media 844 2165
2217 22354

Download full dataset.

I’ll make a very rough assumption that half the attendees will come from the UK, so let’s round down and say 11,000 attendees will come from outside the UK.


CO2 per passenger

Now we know 11,000 will be flying into Glasgow, lets calculate average fuel consumption.

One way to calculate CO2 emissions is from fuel consumption per flight. Using old data (published 2010) comparing a Boeing 737-400 (short haul) and Boeing 747-400 (long haul);

Boeing 737-400 Boeing 747-400
Distance (kms) 926 5556
Fuel user (tons) 3.61 59.6
Seats 164 416
Ave load factor % 65 80
Ave pax 107 333
Fuel use (g) per pax km 36.57118312 32.23299828
CO2 emissions (g) from aviation fuel per gram of fuel 3.15 3.15
Total CO2 emissions (g) per pax km 115.1992268 101.5339446

OK, so both of these planes are quite old (both have many newer versions). Fair point. I used them as the above statistics were freely available.

According to

The aviation sector’s short-term goal to improve fleet fuel efficiency by an average of 1.5% per annum from 2009-2020 is on track, with current analysis showing a 2.3% improvement on a rolling average − an efficiency improvement of 17.3% since 2009.

Let’s assume then that newer planes are 17.3% more efficient, we get an emissions figure of 89.316 g CO2 per passenger km ((101+115)/2)*(1-0.173).

This figure is very close to on reported from the International Council on Clean Transportation:

On average, passenger aviation emitted 90 grams of CO2 per passenger-kilometer in 2019

Both calculations will be a little optimistic for COP 26, as the original calculations were based on high load factors, which have reduced significantly, and still remain so, because of COVID. But let’s go with it for now…

Average travel distance per passenger

Attendees travel from all over the world, but it would appear from reports most travel will be from European delegates given location. I wasn’t able to easily break the 2019 delegate list by country (although that was held in Chile, so the delegate count by country will no doubt be quite different this year).

There has already been coverage that some nations not being able to field delegates this year due to travel restrictions. Namely in Asia, Oceanic, and African countries.

Given the above, I considered the edge of Europe, Istanbul as a rough guess for “average distance” attendees will travel.

Let’s assume then, that on average, delegate travel the distance of Istanbul to Glasgow (shortest distance = 2912 km, rounded up to 3000km, and doubled for the return journey 6000km).

Delegate emissions from flights

We now estimate delegates will have a round trip to Glasgow of about 6000km. Therefore, one passenger will produce 540kg CO2 pin CO2 emissions flying to and from the conference (0.09*6000).

For all 11,000 delegates, that’s 5,400,000 kilograms of CO2 or roughly 5400 tons of aviation CO2 emissions to fly international delegates in and out of Glasgow.

Note, this does not factor in the increased warming effect other, non-CO2, emissions, such as nitrogen oxides, have when they are released at high altitudes can also make a significant difference to emissions calculations.

What if…

Due to Glasgows position in the UK, and the fact that the UK is an island, it’s likely most people will fly into to Scotland directly.

Perhaps some Europeans will take advantage of the Eurostar to London, and then a 5 hour train journey to Glasgow, but my assumption is that a very small number of attendees will choose this route owing to the low cost, much faster air routes.

However, let’s compare aviation to other available methods of transport.

Total C02 emissions (tons) for 11000 international delegates at COP 26 by transport type

Download chart.

According to DEFRA research, driving alone is almost twice as bad as flying (11,286 tons of CO2 emissions if all international delegates drove alone)!

However, remember, we have ignored +50% of attendees, assuming them to be UK residents… many of whom will be very likely to drive (probably alone)! The 11286 tons represents a 6000km round trip. Dividing this by 10 (600km round trip for UK residents), still leaves 1128.6 tons of CO2 emissions for the driving domestic delegates.

Car sharing (assuming 4 delegates) almost cuts emissions in half from driving alone. Though, roughly, two people to a car (probably more realistic) delivers the same emissions as a comparable plane journey, per passenger, over the same distance.

Unsurprisingly rail is much more efficient when it comes to CO2 emissions per passenger (lets hope most UK delegates choose this over a solo car car journey as rail is 6.3 times more efficient). Sadly, the UK doesn’t have a highly efficient rail infrastructure like that of the Eurostar (which is over 4 times more efficient than general rail). Is HS2 still happening?


This really is a “back-of-the-napkin” analysis. Journalists, please don’t credibly cite these figures unless you make this clear!


The 22,000+ delegates (under-estimate) travelling to the COP 26 conference in Glasgow are likely to generate over 10,000 tons in CO2 emissions.


  1. Data sources + data used in this post.

There are over 200 electrically propelled aircraft projects in development (though most have a range far below 200 kilometers)

269 billion litres of jet fuel was burned in 2017 — Enough fuel to fill 5.4 billion VW Golfs

We’ve all seen the headlines; commercial aviation is bad for the environment.

If the industry bounces back to pre-COVID growth, which most analysts believe will be the case, an alternative to fossil fuels is desperately required to stop the devastating impacts of global warming.

Whilst electric cars are now at a point where they can compete (and out-do) oil powered cars, the size and power requirements of planes have meant further improvements to battery technologies are required before we see electric aircraft.

According to Elon Musk in 2019:

But two years is a long time in battery technology.

How close are we to electric powered commercial aviation? I decided to take a look at the current state of the market.


For this analysis I used a report produced by Roland Berger in 2020 on the electric aircraft industry which reported detailed information about 218 planes. The numbers include planes across all stages of development from concepts to airworthy models (albeit there are currently very few).


Count of Aircraft by Market (2020)

Count of Aircraft by Market

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Download full table.

Urban air taxis still dominate the scene, representing about 45% of all aircraft, though general aviation (typically recreational planes) is close behind, comprising 85 projects globally.

Count of Aircraft by Type (2020)

Count of Aircraft by Type

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Download full table.

48% of all projects are VTOL (vertical take off and landing) craft. Given most projects are focused on short range / intercity aviation, likely operating in cities, VTOL makes most sense.

Count of Aircraft by Power Type

Count of Aircraft by Power Type

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Download full table.

Battery power (including hybrid battery / oil) powered planes account for 97% of all projects.

Solar and hydrogen make up the rest. Solar being employed in concepts for general aviation for small recreational planes. Hydrogen seems to be attractive to manufacturers building autonomous craft, like HES developing the Element One.

The majority of all these planes are using propellors for propulsion although a tiny number of projects like Airbus’s E-Fan-X are using turbofan engines.

Pax capacity of battery powered aircraft (2020)

Pax capacity of battery powered aircraft (2020)

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Looking at the 122 battery powered plane projects that report passenger capacity, the maximum capacity is 19, touted by Heart Aerospace’s concept.

The mean/median passenger load is 2, which highlights how most planned aircraft are aimed at consumers (potential replacements for cars).

Range of battery powered aircraft (inc. estimates) (2020)

Range of battery powered aircraft (inc. estimates) (2020)

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Download full table.

Looking at the 53 battery powered planes that have reported range in distance (keep in mind these are for the most part estimates), all but 4 have ranges below 1000km. The median advertised range of these aircraft is 150km (mean is 298km).

The aircraft with the longest range, 2000km, is Avioneo’s conceptual 2345 craft. Wether it makes it to market is questionable, but it currently boasts costs of 0.12EUR per/km with a cruise speed of up to 300 km/h.


Many of these projects are small and will probably never enter the market. Most information being reported is estimated (and in many cases not even estimates, e.g. for range, are provided), as the planes are still mostly in conceptual phase.

At best this post can be considered a projection on the market. It needs revisiting in one years time, when it is likely a good number of viable planes will be entering early construction and some certifications being conducted.


The median advertised range of battery powered aircraft is 150km… most are still in concept phase. Electrically powered international commercial aviation is still some way off. On the other-hand, city based short-haul aviation is looking like a brand new market that might be realised in the near-future.


  1. Data sources + data used in this post.

The Plane You’re Flying on is Newer than Your Car

Four years ago I wrote how larger airlines (by fleet size) tend to offer worse service than their smaller counterparts.

In last months post I looked at the oldest commercial planes still operating (tl;dr, some are very old).

Many older planes are unnoticeable from their newer counterparts with newer interiors fitted.

Though can redecoration really hide 40 years of use? How does the age of a fleet impact customer satisfaction?


I took Skytrax 2019 World’s Best Airline rankings to get an ordered list of 100 airlines.

For aircraft count and ages for planes operated by these airlines I then used data from AirFleets.


Average age of airline fleet

Average age of airline fleet

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Skytrax rank Airline Airline year started Average age of fleet (yrs) Count of planes in fleet
88 Air Seychelles 1979 1.6 2
69 Vistara 2014 3.1 47
51 Air Astana 2001 3.5 19
94 LEVEL 2017 3.9 3
86 Peach 2011 4.2 34
68 United Airlines 1931 16.4 807
100 Icelandair 1937 17.9 25
73 AtlasGlobal 1992 23.3 69
85 PAL Express 1972 25.8 14
28 Asiana Airlines 1988 33.1 85

Download full table.

The median age of planes in Skytrax 100 fleets is just 9 years (mean age is 9.7 years).

Asiana Airlines, ranked 25th in the Skytrax ranking (and last by average fleet age) has an average fleet age of 33.1 years. They are the only airline in the bottom 10 for aircraft age to have a Skytrax ranking above 50th!

It’s also worth noting the divide between old and new airlines. The newest fleets are operated by airlines established post 2000, whereas the older fleets tend to be operated by some of the oldest airlines.

Correlation between Skytrax rank and fleet age

Correlation between Skytrax rank and fleet age

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A cursory glance at the graph above shows no correlation between age of aircraft and Skytrax rank.

Some of the newest fleets have the worst scores, which is understandable as they are generally smaller with less money to spend on overall customer experience (a factor of Skytrax ranking).


I’ve used aggregate stats on each airline for the analysis. The next step for me would be to look at each airline and see the spread of ages for each aircraft. For instance, in United Airlines fleet of 807 planes; are there very old planes? Lack of new planes? Or a spread of all ages that contribute to the fleets overall average age of 16.4 years?


The median age of planes in Skytrax 100 fleets is just 9 years (mean age is 9.7 years).


  1. Data sources + data used in this post.

The Plane You’re Flying on is 47 Years Old

Airbus announced that it would cease production of the A380 a few years ago with the final plane rolling off the production line this year.

248 A380’s have been delivered since it entered production in 2003, the first order being delivered in October 2007, fourteen years ago.

Boeing also recently announced the end of production of its 747 in 2022though its life stretches back an impressive 50 years with over 1500 delivered!

50 years!

Which got me thinking; what are the oldest planes still flying commercially? Are there any 50 year old 747’s still in service?


I used production list search for each major aircraft type still flying. reports the status of the plane, including the last flight recorded, however, it seems these dates are manually submitted by users (some are very old). Therefore, I verified dates with

I consider planes still in service if they made a flight in 2020 — my assumption being many have been temporarily taken out of service due to the reduction in air travel during the COVID-19 pandemic. Only planes that had first flights before 1990 are considered.

I do not consider military or non-commercial passenger operators (e.g. military or shipping).


Difference between first flight ever and oldest commercial model in operation first flew

Oldest commercial plane still in operation by model vs. first flight (April 2021)

Download chart.

Manufacturer/model First commercial flight of model Oldest plane still in operation first flew Years between first and oldest
Boeing 737 1967-05-13 1974-05-09 6
Boeing 747 1969-05-10 1984-02-28 14
Airbus A300 1972-10-28 1986-12-31 14
Boeing 767 1981-11-04 1982-09-25 0
Airbus A310 1982-04-03 1989-03-08 6
Boeing 757 1982-10-25 1988-02-19 5
Embraer 120 Brasilia 1983-07-27 1986-03-21 2
De Havilland Canada Dash 8 1983-10-26 1985-09-11 1
Airbus A320 1987-02-22 1989-04-25 2

Download full table.

Older 747’s and A300’s seems to leave service quickly, relatively speaking — the oldest planes still flying are 14 years older than the first models that flew.

Conversely, the 737 has remarkable longevity with some of the oldest versions still in operation delivered only 6 years longer than the first ever commercial flight of the model (and first delivered before the 747 and A300).

Age of oldest commercial model still flying

Age of oldest commercial plane still in operation by model

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Manufacturer/model Oldest plane still in operation first flew Todays date Age (years)
Airbus A310 1989-03-08 2021-05-31 32
Airbus A320 1989-04-25 2021-05-31 32
Boeing 757 1988-02-19 2021-05-31 33
Airbus A300 1986-12-31 2021-05-31 34
De Havilland Canada Dash 8 1985-09-11 2021-05-31 35
Embraer 120 Brasilia 1986-03-21 2021-05-31 35
Boeing 747 1984-02-28 2021-05-31 37
Boeing 767 1982-09-25 2021-05-31 38
Boeing 737 1974-05-09 2021-05-31 47

Download full table.

C-GNLK, a 737 currently operated by Nolinor Aviation has been flying for over 47 years — almost 10 years longer than any other model.

By aircraft type

Boeing 737
  • First commercial flight of type:
    • Registration: N701PJ
    • First flight: 1967-05-13
    • Status: Scrapped
    • AirFleets info
  • Oldest plane still in commercial service:
Boeing 747
  • First commercial flight of type:
    • Registration: N474EV
    • First flight: 1969-05-10
    • Status: Scrapped
    • AirFleets info
  • Oldest plane still in commercial service:
Boeing 757
  • First commercial flight of type:
    • Registration: G-BIKA
    • First flight: 1982-10-25
    • Status: Scrapped
    • AirFleets info
  • Oldest plane still in commercial service:
Boeing 767
  • First commercial flight of type:
      • Registration: N601UA
      • First flight: 1981-11-04
      • Status: Scrapped
      • AirFleets info
    • Oldest plane still in commercial service:
Airbus A300
  • First commercial flight of type:
      • Registration: F-OCAZ
      • First flight: 1972-10-28
      • Status: Scrapped
      • AirFleets info
    • Oldest plane still in commercial service:
Airbus A310
  • First commercial flight of type:
      • Registration: N450FE
      • First flight: 1982-04-03
      • Status: Stored
      • AirFleets info
    • Oldest plane still in commercial service:
Airbus A320
  • First commercial flight of type:
      • Registration: F-WWBA
      • First flight: 1987-02-22
      • Status: Stored
      • AirFleets info
    • Oldest plane still in commercial service:
De Havilland Canada Dash 8
  • First commercial flight of type:
      • Registration: C-GGMP
      • First flight: 1983-10-26
      • Status: Stored
      • AirFleets info
    • Oldest plane still in commercial service:
Embraer 120 Brasilia
  • First commercial flight of type:
      • Registration: PT-ZBA
      • First flight: 1983-07-27
      • Status: Stored
      • AirFleets info
    • Oldest plane still in commercial service:


The McDonnell Douglas DC-10 and MD-11 didn’t quite make this list, but only because I considered commercial, passenger carrying commercial airlines. Currently, these planes are only operated by Air Forces and logistics companies. FedEx operate N303FE, a DC-10 that’s 48.1 years old!

I’ve also only included major manufactures I am aware of and is listed on AirFleets. It would be worth validating if there are airlines flying from other manufacturers I am unaware of (I suspect there might be some in Russia).

Finally, I’ve only considered a single plane of each model. Keep in mind, 26% of all commercial airliners are 737’s — there will be many other of these old models still flying.


C-GNLK, a 737 currently operated by Nolinor Aviation has been flying for over 47 years — almost 10 years longer than any other model.


  1. Data sources + data used in this post.

Only 2% of the world’s population travelled internationally in 2018

This year felt a little odd (said everyone, everywhere).

I usually fly a lot for work. 2 or 3 times a month. So far this year, no business flights.

I’m torn on this fact. On one hand, I believe such face-to-face interaction with teams is vital (at least to me), on the other I realise I am part of the environmental problem.

As a human, I try and wrestle with my moral conscious. “I’m not as bad a Sarah”, “I don’t take flights for the sake of points“, I tell myself in a weak attempt to justify my flights.

It got me thinking, how do I compare to the average person?


Global Environmental Change (Volume 65, November 2020, 102194) recently released a study titled; The global scale, distribution and growth of aviation: Implications for climate change.

This report used industry statistics, data provided by supranational organisations, and national surveys to develop a pre-COVID understanding of air transport demand at global, regional, national and individual scales.

Whilst I stress these are pre-pandemic estimates (although many suggest air travel will soon bounce back to normal levels).

Some of the processed data detailed in the report is used in this post alongside directly cited data.


% of population that travel

According to IATA (2019), there were 4.378 billion passengers in 2018 (international and domestic). This is not equivalent to trip numbers or individual travellers. Most air trips are symmetrical, i.e. they will involve a departure as well as a return.

As ten percent of all flights involve a transfer, 4.378 billion passengers would thus represent a maximum of 1.99 billion trips.

The share of the global population participating in international air travel is even smaller, as a significant share of all air travel takes place within countries. Domestic air travel included 2.566 billion passengers in 2018, out of this 590 million in the USA, 515 million in China, and 116 million in India (IATA, 2019).

International air travel consequently only comprised 1.811 billion passengers, who are also more likely to move through hubs. On the basis of the conservative assumption that one international trip comprises 2.2 flights (IATA, 2019), some 823 million international trips were made in 2018.

Non flying population

This does not consider that there is a significant share of the population in every country that does not fly, while some air travellers participate in one, two, or multiple trips.

% non-flying pop est. (2018-2019)

Download chart.

% non-flying pop est. (2018-2019)
United States 53
Germany 65
Taiwan 66
UK 59

Full table.

For example, data for the USA suggests that 53% of the adult population do not fly (Airlines for America, 2018). In Germany, 65% of the population do not fly (IFD Allensbach, 2019), while this share is 66% in Taiwan (Tourism Bureau Taiwan, 2019). In the UK, the non-flying share of the population 16 years or older is 59% (DEFRA, 2009).

These national surveys indicate that in high income countries, between 53% and 65% of the population will not fly in a given year. The share of non-fliers is likely larger in low-income, lower-middle and upper-middle income countries. The share of non-fliers is likely larger in low-income, lower-middle and upper-middle income countries.

International multi-trip flyers

An alternative way of calculating the share of the population participating in international air travel is to divide the number of international trips by an average trip number per traveler.

For example, Airlines for America (2018) suggest that the average air traveler makes 5.3 trips per year, with a relatively large share of travellers participating in only one or two trips, and a rather small share accounting for large trip numbers.

Applying the US average of 5.3 trips as an indication of skewed demand, 823 million international trips involved only 155 million unique air travellers, or 2% of the world population (world population of 7.594 billion).

Similarly, for domestic trips, applying this logic, 5.3 trips for the average traveller with 2.566 billion domestic passengers in 2018, means about 6% of the world’s population (456 million) travelled domestically.

Global distribution of aviation fuel use (2019)

Global distribution of aviation fuel use (2019)

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Type % share of aviation fuel use
Commercial aviation: Passengers 71
Commercial aviation: Freight 17
Military 8
Private 4

Full table.

There’s some guesswork here, as there is no global data for military operations or private flights.

It has been suggested that military aircraft consumed 22% of US jet fuel in 2008 (Spicer et al., 2009), though a lower recent estimate for the US in absolute numbers is 18.35 Mt CO2 (in 2017; Belcher et al., 2020). In a global estimate for 2002, Eyers et al. (2004) concluded that global military operations required 19.5 Mt of fuel, leading to emissions of 61 Mt CO2, or 11.1% of global emissions from aviation.

For an estimate, the current contribution of military flight to global emissions from aviation is assumed to be 8%. This estimate is uncertain, but highlights the importance of military flight in aviation emissions.

Data on private aviation is equally limited. The global business aviation market is estimated to have included 22,295 jets, 14,241 turboprops, and 19,291 turbine helicopters in 2016 (AMSTAT Market Analysis, 2018). Assuming an average of 400 h of flight time per year for the global fleet of private jets, with an estimate of a 1200 kg/hour fuel use (Gössling, 2019), jet fuel burn was 10.7 Mt in 2016, corresponding to 33.7 Mt of CO2.

Adding the fuel use of turboprops and helicopters, overall emissions from private transport may be in the order of 40 Mt CO2. This would suggest that private aviation accounts for about 4% of global emissions from aviation

At first glance the military and private aviation fuel use might seem low, but considering it on a per passenger basis, this share of fuel is actually comparatively high.

Fuel use Mt CO2 by aviation travel type (2017)

Fuel use Mt CO2 by aviation travel type (2017)

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Estimates of global fuel use vary. More recent estimates presented by IATA (2018) suggest that civil aviation – including international and domestic, passengers and freight – emitted 859 Mt CO2 in 2017.

Assuming this is 88% of total consumption (71% passengers + 17% freight), then global fuel consumption in 2017 was 976 Mt CO2.

Therefore, commercial aviation (passengers) contributed 693 Mt CO2 in 2017.

The International Energy Agency (IEA, 2019a) specifies that about 60.4% of this for international aviation (416 Mt CO2), and 39.6% for domestic aviation (277 Mt CO2).

Over the past 20 years, global carbon dioxide (CO2) emissions from fossil fuels and industry have been steadily increasing, and by 2018 reached a record high of 36.6 billion metric tons (Statista).

Looking at all emissions, commercial aviation (passengers) contributed 0.693 Bt CO2 emissions in 2017, which is 1.9% of all global emissions (0.693/36.6).

Thus, 2% of all CO2 emissions (0.693 Bt CO2) are caused by an estimated 6%-8% of the worlds population (from air travel).


In many cases the data in the post considers data reported over different time periods, or uses aggregated data. Being able to access like-for-like raw data would improve accuracy.


823 million international trips involved only 155 million unique air travellers, or 2% of the world population

2.566 billion domestic trips involved only 456 million unique air travellers, or 6% of the world population.

Together, these passengers created 2% of all CO2 emissions.


  1. Data sources + data used in this post.

A New Record: Guns Caught at US Airport Security Checkpoints

Belt. Off.

Shoes. Off.

Phone out of pocket. Yes.

Laptop and iPad in separate trays. Done.

Guns. Ermmmm…


Travellers who bring firearms to the checkpoint are subject to criminal charges from law enforcement and civil penalties from TSA.

Even if a traveller has a concealed weapon permit, firearms are not permitted to be carried onto an aeroplane.

However, travellers with proper firearm permits can travel legally with their firearms in their checked bags if they follow a few simple guidelines to transport firearms and ammunition safely.

The data reported in this post covers all guns identified, which includes both those authorised to be carried on-board as well as guns seized.


Guns identified at US airports

Year Nationwide
2008 926
2009 976
2010 1,123
2011 1,320
2012 1,556
2013 1,813
2014 2,212
2015 2,653
2016 3,391
2017 3,957
2018 4,239
2019 4,432

View full table.

Number of Weapons Identified by TSA at US Airports (2008 - 2019)

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Transportation Security Administration officers caught more firearms at checkpoints nationwide in 2019, more than ever recorded previously.

In total, 4,432 firearms were discovered in carry-on bags or on passengers at checkpoints across the country last year, averaging about 12.1 firearms per day, approximately a 5% increase nationally in firearm discoveries from the total of 4,239 detected in 2018.

What’s more, eighty-seven percent of firearms detected at checkpoints last year were loaded.

Worst airports

Airport Weapons Identified
Hartsfield-Jackson Atlanta International (ATL) 323
Dallas/Fort Worth International (DFW) 217
Denver International (DEN) 140
George Bush Intercontinental (IAH) 138
Phoenix Sky Harbor International (PHX) 132

View full table.

Number of Weapons Identified by TSA at US Airports (2019)

View chart.

Firearms were caught at 278 airport checkpoints in the US.

The top five airports where TSA officers detected guns at checkpoints in 2019 were: Hartsfield-Jackson Atlanta International with 323; Dallas/Fort Worth International with 217; Denver International with 140; George Bush Intercontinental with 138; and Phoenix Sky Harbor International with 132.


As noted, there is no distinction between guns authorised to be carried on-board and guns carried illegally. Being able to extrapolate how many guns were seized would add a different perspective to the analysis.


4432 guns were identified at US airports security checkpoints in 2019 (compared to just 926 in 2008).


  1. Data sources + data used in this post.

The Great TSA Robbery

Waiting at a baggage carousel is never enjoyable.

You’ve stepped off the plane, cleared security, and then, the 300 plus people who have just disembarked the plane rush to get as close to where the bags enter the carousel with latecomers forced to pack tightly around its perimeter.

If you’re lucky, or have paid for the privilege, your bag will arrive first. If you’re unlucky, me, you’ll be waiting until the very end.

If you’re really unlucky, your bag won’t arrive at all, and you’ll spend the next hour or two waiting at the baggage information desk to find out what to do next.

In many cases, your bag just wasn’t loaded on your flight, and in such cases the bag will be carried on the next flight.

Though even with highly computerised baggage processes, bags do still inevitably go missing — from hand baggage at security checkpoints to checked luggage at the destination.

But why?


The Transport Security Administration (TSA) are responsible for the security of the travelling public in the United States.

This includes everything from checking passengers are not carrying prohibited items into the cabin through to checking bags going into the hold.

The TSA periodically publish claims made against them during a screening process of persons or passenger’s property due to an injury, loss, or damage.

The latest in Excel format is for 2015, and is the version used in this post (I guess it takes them a long time to process and publish claims, as you’ll see even claims from 2015 are still showing as open…)


Overview of claims

Question Answer
Total claims 8667
Total open claims 2066
Total closed claims 3027
Value of all closed claims USD 611,137.05
Mean average payout USD 201.90
Highest claim USD 5,403.46
Lowest claim USD 2.00
Total rejected claims 3574
Most claimed for category Passenger Property Loss (4551)
Most claimed for item type Baggage/Cases/Purses
Most claimed for site Checked baggage (6261)
Most claimed for airport John F. Kennedy International (523)

Full table.

Over $611K USD has been paid out representing just over 3000 claims. 3500 we’re rejected. 200 claims remain open (outcome undecided) for the year 2015.

JFK (New York), the 6th busiest US airport (61 million pax/yr), is the airport that received the most claims from passengers.

Months with most claims

Count of TSA Claims vs Month (2015)

Download chart.

Unsurprisingly the busy summer months (July and August), where passenger traffic is generally at its highest level, saw the most claims.

Most common items stolen

Item Category Count of claims
Baggage/Cases/Purses 1004
Computer & Accessories 736
Clothing 723
Other 570
Personal Electronics 561
Jewelry & Watches 509
Travel Accessories 454
Personal Accessories 347
Cosmetics & Grooming 310

Full table.

Computer & accessories, after suitcases and purses, are the items that go missing the most.

Worst airports

Airport Code Airport Name Count of claims (all, inc pending) Value of paid claims USD
JFK John F. Kennedy International 523 50635.31
LAX Los Angeles International Airport 495 28864.61
MCO Orlando International Airport 372 25795.49
ATL Hartsfield-Jackson Atlanta International Airport 362 17725.27
EWR Newark International Airport 312 32630.15
MIA Miami International Airport 306 22801.2
ORD Chicago O’Hare International Airport 261 17446.55
LAS McCarran International 256 9533.35
PHX Phoenix Sky Harbor International 245 22239.19
SEA Seattle-Tacoma International 244 18362.59

Full table.

The TSA at JFK has the highest number of claims made against them (523). Those claims that have been paid out represent $50k total so far.


My assumption is many claims go straight to insurance companies and never reach the TSA (I’d love to see a data set covering claims made to insurers). I estimate no more than $1 million will be paid out by the TSA for all claims made in 2015 — significantly lower than the figures I would expect after analysing other data sources.

If the latest data is 2016/2017, there is a significant lag in publishing statistics. I also wonder how much data is actually missing. It would be interesting to see a longer timeseries of data to see changes in the number and types of claims.


Avoid JFK airport in the summer months if you’re travelling with particularly valuable items.


  1. Data sources + data used in this post.

Please Arrive at the Airport 6 Hours Before Your Flight to Clear Security

It has been a little different over the last few months.

Whilst the holiday you’ve been looking forward to since the start of the outbreak might not be going ahead this year, it will come around.

We’ll all be back flying soon. And so will the familiar, often stressful, journey from car to plane.

Wait to check-in. Wait to drop your bags. Wait until the person in front of you at security empties the backpack full of all their electronics (sorry!).

In this period of travel downtime, I decided to take a look at the best and worst performing airports for security waiting times in the UK and US. Perhaps it’ll change my decision on where to fly from once travel restrictions are lifted.


Which? asked asked 4,499 passengers to provide an estimated wait time for security on their most recent visit to the airport in their recent annual airport survey (end of 2019). Note: this survey was conducted before any COVID-19 restrictions were put in place.

The passenger numbers from each UK airport are sourced from CAA figures published for 2018, the latest full year dataset available at the time of writing. Note, the numbers are reported per airport. I could not find individual terminal data as is reported in the waiting time data. Therefore to perform my analysis I simply divided airport passenger number by number of terminals at the airport. Clearly this is not perfect.

For US airport data, I used data from Upgraded Points, who compiled wait time data directly from the Transportation Security Administration (TSA) They collected data from late Spring for every hour at each airport to calculate overall averages.


Mean security wait time at UK airports
Mean security wait time at UK airports

Download chart.

This one’s personal. I used to travel to Belfast monthly. I don’t miss the queues.

Belfast International is by-far-and away the worst performing airport for security waiting times, taking on average over 22 minutes  — over 5 minutes longer than any other airport considered.

Compare that with Southend or Southampton, the latter of which I used to fly to and from Belfast coincidently, where queuing can regularly take less than 5 minutes.

Mean security wait (mins) 2019 vs UK airport size

Mean security wait versus airport size

Download chart.

Gatwick and Heathrow have the lowest average security queue times for large UK airports. They are also the only two airports in the UK whose queue targets are set externally – by the Civil Aviation Authority.

They hit their queue targets, which are to get 99% of flyers through security in less than 10 minutes (Heathrow) and 98% in less than 15 minutes (Gatwick).

For a long time, my personal hypothesis was that smaller airports would have slower security primarily due to the fact they often cater for low-cost airlines, and thus people who might not travel as regularly.

How wrong I was.

In fact, larger airports are about 2 minutes slower. When I think more deeply about this, it makes perfect sense. Larger airport, more passengers, slower security queues.

Mean security wait (mins) 2019 vs UK airport passenger number

Number of passengers to add 1 minute to security wait times at UK airports (2019)

Download chart.

Comparing wait times to the number of passengers travelling gives us a better picture of how efficient security at each airport is.

Every 2.68 million passengers adds about a minute to the security waiting times at Gatwick South terminal, making it the most efficient airport considered. The North terminal at Gatwick doesn’t fare much worse with every 2.69 million passengers adding an extra minute.

Compare that to Bournemouth where every 88,000 passengers adds a minute to the security wait times.

Comparing to US airports

Airport Mean security wait (mins) 2019 Country
Southend 5.2 UK
Southampton 5.2 UK
Exeter 6.9 UK
Cardiff 7.1 UK
London City 7.5 UK
Bournemouth 7.7 UK
Newcastle 8.1 UK
Bristol 8.5 UK
Heathrow Terminal 5 8.6 UK
Gatwick South Terminal 8.6 UK
Gatwick North Terminal 8.7 UK
Salt Lake International Airport 9.1 US
Heathrow Terminal 4 9.4 UK
Heathrow Terminal 2 9.6 UK
Liverpool (John Lennon) 10.1 UK
Heathrow Terminal 3 10.3 UK
Dulles International Airport 10.5 US
Edinburgh 10.5 UK
Boston Logan International Airport 10.6 US
Leeds Bradford 10.6 UK
Birmingham 10.6 UK
Luton 11.7 UK
Glasgow International 12.2 UK
East Midlands 12.7 UK
Minneapolis−Saint Paul International Airport 13 US
Detroit Metropolitan Wayne County Airport 13.2 US
Charlotte Douglas International Airport 13.2 US
Philadelphia International Airport 13.3 US
Stanstead 13.7 UK
Denver International Airport 13.8 US
Los Angeles International Airport 14.2 US
Fort Lauderdale-Hollywood International Airport 14.3 US
Phoenix Sky Harbor Airport 14.7 US
Orlando International Airport 14.9 US
Chicago O’Hare International Airport 15 US
San Diego International Airport 15.5 US
Manchester Terminal 2 15.5 UK
Manchester Terminal 3 15.5 UK
Dallas/Fort Worth International Airport 15.9 US
San Francisco International Airport 16 US
John F. Kennedy International Airport 16 US
Seattle-Tacoma International Airport 16.3 US
Hartsfield-Jackson Atlanta International Airport 16.9 US
LaGuardia Airport 17 US
Manchester Terminal 1 17 UK
McCarran International Airport 17.3 US
Baltimore/Washington International Thurgood Marshall Airport 18.2 US
Miami International Airport 19.6 US
Houston Airport System 19.8 US
Belfast International 22.3 UK
Newark Liberty International Airport 23.1 US

Full table.

The best performing airports based on security wait times are all in the UK. Salt Lake International Airport is the best performing airport in the US (9.1 mins).

The worst airport, Newark Liberty International Airport in New York where average security wait times are 23.1 minutes — about one minute slower than Belfast International.

4 of the 5 worst performing airports are all in the US.

US vs UK airports average security wait times 2019

Download chart.

As a result, US airports security queues, are on average, 5 minutes slower than their UK counterparts.


The UK figures are based on estimates. Which? collected the data by asking 4,499 passengers to provide an estimated wait time for security on their most recent visit to the airport in our recent annual airport survey.

This is far from accurate. The analysis would be much improved if I was able to use the actual figures similar to the way they are reported by the TSA in the US, although I could not find anywhere where UK airports reported these numbers.


Belfast International is by-far-and away the worst performing UK airport for security waiting times, taking on average over 22 minutes  — over 5 minutes longer than any other airport considered.

In the US it’s Newark Liberty International Airport in New York, where security queues are a little over 23 minutes on average.


  1. Data sources + data used in this post.

Electric Trains, Electric Cars, or Electric Bikes. Which is best for the environment?

You’ve swapped your petrol car for a plug-in hybrid.

Or perhaps you’ve gone full electric.

Maybe you’ve given up the car entirely to take the train to work instead.

Many of us are playing our part in trying to fix the climate crisis we’re all facing.

Though you might be surprised at the environmental cost of seemingly green modes of transport.

Before you buy that electric scooter, you’ll want read this.

Methodology have curated a great data set analysing the environmental (carbon) impact of a range of popular transport types.

  • Operation (direct): The environmental impact caused by the direct operation of the vehicle (e.g. abrasion emissions from brake linings, wheels…)
  • Operation (indirect): The environmental impact of indirect operation is determined, which primarily includes the provision of energy (e.g, processes from energy extraction from the environment to delivery to the tank…).
  • Maintenance: All the processes required to keep the vehicle roadworthy during its service life are counted (e.g. changing the tires of cars and replacing consumables in railway trains…).
  • Manufacture & Disposal: This category includes all processes that affect the manufacturing of the vehicle that are not included in maintenance (e.g. raw materials, operating emissions of the production facilities…)
  • Roadway: The construction, maintenance, and disposal of all types of tracks are counted (e.g for road transport these include roads, car parks etc., for rail traffic these include entire lines, safety walls, bridges…)

The impact of each of these factors is measured as carbon emissions in grams per passenger kilometre.

There are a number of assumptions that have been made to compile the data, including average level of occupancy per transport type (although in cases of transport types that carry multiple passengers, this figure if not reported) and the average lifetime (distance travelled) for each transport type.


Operational Emissions

Carbon emissions for transport operation in grams per passenger kilometre

Download chart.

Category Operation (direct) g p/pkm Operation (indirect) g p/pkm Operation total g p/pkm
by Foot 0.00 0.00 0.00
Bike 0.00 0.00 0.00
E-Bike 0.00 1.01 1.01
E-Scooter (Vespa-Like) 0.00 2.28 2.28
E-Kick-Scooter (Dockless) 5.92 0.00 5.92
Tram 0.37 13.63 14.00
E-Bus 1.45 14.31 15.76
Car (Electric) 4.07 12.68 16.75
Car (Plug-In-Hybrid) 20.35 5.68 26.02
Bus (>200km) 32.32 6.31 38.63
Train (Highspeed) 0.03 40.65 40.68
Bus (<200km) 43.30 8.43 51.73
Train (Regional) 9.11 45.15 54.26
Scooter (Gasoline) 75.64 15.15 90.79
Car (Hybrid) 86.22 20.96 107.18
Motorbike (Gasoline) 97.24 24.82 122.05
Car (Diesel) 106.01 20.65 126.67
Autobus 112.25 22.10 134.35
Ferry (<200km) 123.65 23.86 147.51
Car (Gasoline) 130.23 34.11 164.34

Full table.

A gasoline car has the highest direct operating emissions (130.23 grams per pax km) and indirect emissions (34.11 g p/pkm). That’s more than a ferry (123.65 g p/pkm // 34.11 g p/pkm).

High-speed trains are very efficient for day-to-day direct operation (0.03 g p/pkm), though the indirect costs are carbon expensive (40.68 g p/pkm).

Combined, an electric car is more carbon friendly than a train from a direct and indirect operational perspective (4.07 g p/pkm // 12.68 g p/pkm).

Manufacture & Disposal Emissions

Carbon emissions for transport manufacture and disposal in grams per passenger kilometre

Download chart.

Category Manufacture & Disposal g p/pkm
by Foot 0.00
Train (Highspeed) 0.55
Train (Regional) 0.73
Tram 1.38
Bus (>200km) 1.75
Bus (<200km) 1.88
E-Bus 2.80
Autobus 3.28
Ferry (<200km) 3.75
Scooter (Gasoline) 5.40
Bike 5.91
E-Bike 10.96
Motorbike (Gasoline) 16.36
E-Scooter (Vespa-Like) 23.09
Car (Gasoline) 32.69
Car (Hybrid) 37.30
Car (Diesel) 39.48
Car (Plug-In-Hybrid) 42.20
Car (Electric) 62.57
E-Kick-Scooter (Dockless) 63.00

Full table.

Electric powered transport is by far the most expensive to create and dispose of. That said, the carbon cost of this is likely to reduce significantly in future years as technology advances.

Currently, an E-Kick-Scooter is the worst type of transport based on the carbon cost (63g p/pkm) — that’s more than an electric car (62.57 g p/pkm)!

Despite their size, trains and trams have a low carbon cost to manufacture and dispose of (high-speed train 0.55- g p/pkm) – this is almost certainly due to the amount of passengers they carry in comparison to other forms of transport considered.

Lifetime Emissions

Carbon emissions total for transport in grams per passenger kilometre (2019)

Download chart.

Category Total g p/pkm
by Foot 0.00
Bike 7.64
E-Bike 16.12
E-Bus 25.15
E-Scooter (Vespa-Like) 29.84
Tram 37.47
Bus (>200km) 44.64
Train (Highspeed) 49.90
Bus (<200km) 58.20
Train (Regional) 59.64
Car (Plug-In-Hybrid) 82.30
Car (Electric) 92.37
Scooter (Gasoline) 100.57
E-Kick-Scooter (Dockless) 126.00
Motorbike (Gasoline) 145.02
Autobus 145.41
Ferry (<200km) 151.45
Car (Hybrid) 158.06
Car (Diesel) 179.60
Car (Gasoline) 208.28

Full table.

Adding in maintenance and roadway costs, in addition to other factors considered, traditional diesel and gasoline cars are the most polluting over their lifetime (179.60 g p/pkm and 208.28 g p/pkm, respectively).

Plug-in hybrids have half the carbon impact compared to tradition hybrids (82.30 g p/pkm and 158.06 g p/pkm, respectively), and are even more emission friendly over their lifetime than pure electric cars (92.37 g p/pkm).

How far to generate a tonne of C02?

How many km transport type to generate tonne of co2 per pax 2019

Download chart.

Category How many km for tonne co2 / pax?
by Foot
Bike 130,868.61
E-Bike 62,028.67
E-Bus 39,761.43
E-Scooter (Vespa-Like) 33,516.37
Tram 26,685.14
Bus (>200km) 22,401.85
Train (Highspeed) 20,040.19
Bus (<200km) 17,182.13
Train (Regional) 16,767.27
Car (Plug-In-Hybrid) 12,150.77
Car (Electric) 10,826.13
Scooter (Gasoline) 9,943.46
E-Kick-Scooter (Dockless) 7,936.51
Motorbike (Gasoline) 6,895.58
Autobus 6,877.08
Ferry (<200km) 6,602.84
Car (Hybrid) 6,326.73
Car (Diesel) 5,568.01
Car (Gasoline) 4,801.13

Full table.

In a gasoline car it takes on average just 4,800 km for each passenger to contribute a tonne of carbon dioxide. A passenger in an electric car will generate a tonne in just under 11,000 km, and a high-speed train in just over 20,000 km.

Note, it is important to stress, most of the emission are down to manufacturing costs (e.g. a Land Rover Discovery in 2010 required 35 tonnes CO2e for manufacture). See Methodology section for assumptions on lifetime distances.


As the authors of the dataset note:

… [the results] not illustrating scientifically-proven results but provides our best guess on average carbon emissions produced by transport type based on existing third-party research that we were able to identify and combine.

It is also clear, air transport is missed. Interestingly, one of the data sources referenced is Lufthansa Innovation Hub.

It is impossible to get true figures for an analysis, there are simply too many variables, that said, the numbers used for analysis in this post could definitely be improved for a more accurate output.


In a gasoline car it takes just 4,800 km for each passenger to contribute a tonne of carbon dioxide. A passenger in an electric car will generate a tonne in just under 11,000 km, and a high-speed train in just over 20,000 km.


  1. Data sources + data used in this post.

Patient 0 to the World: How Air Travel Makes it Impossible to Contain COVID-19


What was once a summer beer is now synonymous with something far less appealing.

COVID-19, or the Corona virus, has sadly led to over 2,500 deaths and almost 100,000 infections as I write this.

Recently I was reading about the World War 1 flu pandemic that claimed an estimated 16 million lives. It is estimated one fifth of the world’s population was attacked by this deadly virus.

Most researchers attribute the movement of people around the world to the fact the flu virus was able to infect so many.

And this was before the days of commercial aviation.

In 2018 there were 4.8 billion air passengers, total. Add in rail, road and sea journeys, and it’s clear the world is incredibly interconnected. There wasn’t even 4.8 billion people on the planet in 1914 (most estimates put it at between 1.5 and 1.7 billion).

From its origin in Wuhan, here’s a simple analysis for how easily it could have been spread around the world.


I used a variety of sources to obtain data on air travel in China to estimate and analyse passenger traffic and aircraft movements.


Air Pax Volume China (2019)

China air passenger volume 2019

Download chart.

In total, there were about 660 million passengers flying from a Chinese airport in 2019.

Almost 90% were flying domestically (586 million pax), with 72 million flying out of the country — the equivalent of around 49 million domestic and 6 million international pax each month.

Where do people fly to / from in China?

Download chart.

Rank Airport Passengers
1 Beijing Capital International Airport 100,983,290
2 Shanghai Pudong International Airport 74,006,331
3 Guangzhou Baiyun International Airport 69,720,403
4 Chengdu Shuangliu International Airport 52,950,529
5 Shenzhen Bao’an International Airport 49,348,950
6 Kunming Changshui International Airport 47,088,140
7 Xi’an Xianyang International Airport 44,653,311
8 Shanghai Hongqiao International Airport 43,628,004
9 Chongqing Jiangbei International Airport 41,595,887
10 Hangzhou Xiaoshan International Airport 38,241,630

Full chart.

Over 100 million passengers flew in or out of Beijing in 2018, or a mean average of 8.3 million per month.

Even the smallest airport in the top 100 by passenger volume, Nanyang Jiangying Airport, saw over 907,000 passengers through its doors in 2018.

Wuhan Tianhe International Airport had 24.5 million in 2019, or about 2 million per month — about the same amount of time before travel restrictions came into place and the virus was widely reported.

How many flights depart from Wuhan each month?

I could not find specific flight data for Wuhan, so let’s get creative.

Given most travellers are domestic, let’s use one of the most popular short/medium range aircraft, the Boeing 737 (ignoring the ongoing MAX 8 problems).

The 737 MAX 8 typically holds around 178 in a 2 class seat configuration.

Assuming only the 737 Max flew from Wuhan, that would mean over 11,235 flights landed / departed. Given there will be larger planes in operation, let’s assume 10,000 plane movements per month.

Divide that by two, to only consider departures, gives 5,000 plane departures per month.

And this is one city alone.


According to this same calculation using the amount of 737 seats to estimate number of flights would result in the 4.8 billion passengers who flew in 2018 to have done it on about 60 million flights or 5 million each month!

And that’s just air travel.

Without a total ban on travel, I cannot see how COVID-19 will be contained.

To finish, it is important I note this is not meant to be a post designed to scare.  Remember, even if you contract the virus, it is very likely you will survive.


These stats are clearly not accurate model of the spread of COVID-19. The post is designed to highlight how interconnected the modern world is.

I’m very interested to see the models that researchers develop as our understanding of this virus increases. I am no where near skilled enough to do this.


With an estimated 5 million flights taking off around the world each month, stopping viruses penetrating borders is an impossible task.


  1. Data sources + data used in this post.