README.md (6705B)
1 This file explains how the carbon footprint of Highlights'24 was computed. 2 3 ## Data collection 4 5 We collected information about the travel plans of participants using a 6 web form (originally hosted at [this 7 URL](https://framaforms.org/highlights-and-jewels-of-automata-theory-2024-1715936947)). 8 Filling in the form was part of the registration process. 9 10 One participant registered as attending on-site and then as attending online, so 11 we counted this participant as attending online. We then eliminated online 12 participants. We arrive at 160 on-site participants. 13 14 We then eliminated local participants, estimating a CO2 footprint of 0 for them. 15 We arrive at 135 on-site non-local participants. 16 17 We sanitized the data by hand as follows: 18 19 - when participants indicated multiple possible places, we selected the first 20 - when participants did not specify a place, we use their affiliation location 21 - when participants did not select a means of transportation, we assumed that 22 trips of >400km were done by plane (which covered all cases with missing 23 information) 24 - we manually fixed some typos in locations and disambiguated some locations to 25 ensure a correct geocoding output 26 27 The registration form asks about "Other scientific activities during your stay 28 (including HCRW)", giving people to indicate the option "Yes, I am extending my 29 trip for other scientific reasons.". The form also asks participants whether 30 they will participate to HCRW. (Not all participants who ticked the second box 31 also ticked the first.) We propagate this information about extended stays (both 32 fields) in the data that we generate and release, but we do not take it into 33 account in the computation. 34 35 From the data, we then use the Geonames service to transform the location 36 indicated by participants, by extracting to locations.txt the locations and 37 geocoding them using geocode.py to the file locations_with_latlon.txt. 38 39 We then have the file locations_with_latlon.txt giving all locations preceded by 40 their latitude-longitude in the format, e.g.,: 41 42 44.84044 -0.5805 Bordeaux 43 44 And we have the file 45 highlights_and_jewels_of_automata_theory_2024_onsite_nonlocal_manualclean.csv 46 containing lines of the following form for each onsite nonlocal participant 47 (numbered from 0, and tab-separated): 48 49 - fields 0 and 1 are irrelevant 50 - fields 2 and 3 give first and last name (only used for debugging) 51 - field 4 is irrelevant 52 - field 5 gives university (only used for debugging) 53 - fields 6 say "I'm coming to Bordeaux" 54 - field 7 gives participant type (unused) 55 - field 8 says "External Participant" 56 - field 9 gives the origin place (text) 57 - field 10 gives the origin mode among "Plane", "Train", "Bus/Coach" 58 - fields 12 and 13 give the same information for the destination place 59 - fields 14 and 15 are the information of the two boxes about extended stays 60 (propagated in the files but not used in the computation) 61 62 (These files are not versioned because they can be considered private 63 information.) 64 65 We run: 66 67 ./generate_trips.py 44.84044 -0.5805 0.2 68 69 Where the arguments are the latitude and longitude of Bordeaux, and 0.2 is the 70 noise to add. This generates a file trips_anonymized.csv containing, for each 71 trip leg, the mode ("plane", "train", "bus/coach"), the distance (in km, 72 rounded, with noise), and the information about extended stays. A file 73 trips.csv is also produced for debugging (with the data without noise and with 74 personal information). A file map.geojson is also produced with the map of 75 participants and transportation modes and private information (to be used as an 76 image only). 77 78 The file trips_anonymized.csv can then be fed to co2.py which computes the 79 carbon footprint (see below). This gives (from the anonymized data): 80 81 total CO2e emissions (tons): 41.159883 82 for mode train: CO2e emissions (tons): 5.264101 83 for mode plane: CO2e emissions (tons): 35.871842 84 for mode bus/coach: CO2e emissions (tons): 0.023940 85 for distances <2000 km, plane is used for 68/243 trips 86 for distances >=2000 km, plane is used for 22/27 trips 87 flights of over 2000 km account for 18149946.000000 CO2e emissions (tons) i.e. 44.096204 percent of total for 22/270 total legs 88 distance by plane: 201579 89 90 Hence, the total CO2 footprint is 41 tons CO2e (it is the same with the 91 non-anonymized file). Around 87% of emissions are due to plane travel, and 44% 92 of the emissions are due to 8% of the transportation legs, namely, 93 the plane trips of over 2000 km. (Note that most trips of over 2000km are done 94 by plane, but not all.) 95 96 The average footprint per onsite non-local participant (135) is around 97 307 kgCO2e. The average footprint per onsite participant (160) is around 98 260 kgCO2e. (These figures are computed from the non-anonymized data.) 99 100 ### Carbon footprint 101 102 Like in 2022, we compute the CO2 fotprint following the 103 [labos1point5](https://labos1point5.org/ges-1point5) data, which is adapted from 104 the French agency [Ademe](https://www.ademe.fr/). We use the values from 2022 105 without updating them to ensure that the methodology is comparable. 106 107 - For train, we count **37 gCO2e/pkm** (international train). This is pessimistic in France, very 108 pessimistic for TGV, but similar to the 41 gCO2e/pm for national (UK) rail 109 given by [Our World in 110 Data](https://ourworldindata.org/travel-carbon-footprint). 111 - Plane is counted following 112 [labos1point5](https://labos1point5.org/ges-1point5), including the effect 113 of contrails: 114 - 258 gCO2e/pkm for less than 1000km 115 - 187 gCO2e/pkm between 1001km and 3500km 116 - 152 gCO2e/pkm above 3500km. This value is consistent to the 150 gCO2e/pkm 117 value for long-haul flight given by [Our World in 118 Data](https://ourworldindata.org/travel-carbon-footprint) (also including 119 contrails) 120 - For bus/coach, we count 28 gCO2e/pkm as the coach value given by [Our World in 121 Data](https://ourworldindata.org/travel-carbon-footprint) as there is no 122 value in labos1point5. 123 124 ## Trends relative to 2022 125 126 We now compare the footprint relative to 2022. (In 2023, there was no 127 computation of the footprint.) 128 129 In 2022, there were 173 registered onsite participants, 127 registered onsite 130 nonlocal participants, and a total of 42 tons of CO2e. Relative te 2022, and 131 with the same methodology: 132 133 - The total CO2 footprint of Highlights'24 is essentially the same as in 2022 134 - the CO2 footprint per registered onsite participant has evolved from 240 135 kgCO2e to 260 kgCO2e, i.e., a 8% increase 136 - the CO2 footprint per registered onsite nonlocal participant has evolved from 137 330 kgCO2 to 260 kgCO2e, a 22% decrease 138 139 In an nutshell, the total emissions are about the same, but Highlights'2024 has 140 slightly less onsite participants but slightly more onsite nonlocal 141 participants. 142