In issues of policy and negotiations between countries on actions to be taken to mitigate climate change, the country-level figures that get discussed are either total emissions or per capita emissions. While total emissions is an important figure, per capita emissions gets all the attention. I’m starting to think that might be the wrong number to focus on.
The reason it feels like the wrong number are many fold –
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We’re interested in minimizing the world’s emissions not per human but in total.
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If policies are being made by drawing a line down the ranked per-capita-emissions table, a country can manipulate its position in the table by altering its population. A country with a high population growth rate is more problematic than one with a low to negative growth rate.
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Thinking of the emissions problem as though the earth were burning, we want to put out the fires where it is most intense and then go down the list. Even this is simplistic, but works better as a mental model than saying “let’s convince every human to cut down emissions” when the notion of “every human” is in constant flux.
So I computed the per-square-km annual emissions by country for the year 2020 and ranked countries by “emissions per unit area” which is in the units of “tonnes of CO2 per annum per sq. km”. I got the source data from https://ourworldindata.org and much thanks to them for making information like this very accessible. I combined two tables - one giving the annual total CO2 emissions by country and another giving the land area of countries.
Advantages of considering emissions per unit area
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It can be better visualized as different intensities of “burn” happening on the planet that need to be put out.
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It cannot be manipulated by a country by growing or shrinking its population without affecting total emissions.
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Reducing per area emissions amounts to reducing total emissions for each country, since a country’s area remains mostly constant.
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If combined with, perhaps, GDP per unit area, it might give a better picture of the investment neecssary to help put out the fire, and where that investment better come from.
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It can reflect an average level of experienced pollution in a given country. This may be useful to determine which country’s policies are working and which countries may be targets for migration by those who value low emission rates.
Drawbacks of considering emissions per unit area
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Small countries like Singapore are perhaps better compared against cities than other much larger (by land area) countries.
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Very large high GDP countries with relatively small population will turn up low on the list.
So this ranking is skewed at both ends from a policy making perspective. In between though, it does look viable as a number to focus on for policy making instead of per capita emissions.
Cumulative emissions till 1990
A couple of my colleagues at Krea suggested we look at cumulative “production” emissions prior to globalization. 1990 is rough date for that and, again, ourworldindata has the necessary numbers. This makes sense (to me) from a policy perspective because that’s the key argument against industrialized countries appearing to push greenification agenda on those countries that industrialized much later.
CSV files –
- Cumulative emissions per unit area till 2020
- Cumulative emissions per unit area till 1990
- Cumulative emissions per unit area till 1970
Annual emissions (for year 2020)
Some surprises (for me)
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Many European countries have recently benefited from a narrative that they’re somehow “cleaner and greener” than the rest. They feature fairly high up on this list though. Germany, Netherlands, Belgium are all above India in this ranking. (My interest here is in understanding the climate decisions India is making.)
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Many middle-eastern countries essentially top this ranking.
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Malaysia, India, Vietnam and Switzerland are pretty close to each other in emissions per unit area.
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The world average ranks at 87 on this list. Not too far off from the median.
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Australia and New Zealand rank well below the world average, with Australia right alongside Bhutan. However the country wide average for Australia is perhaps not representative, considering its sparsely inhabited central lands. That’s perhaps applicable to Russia as well.
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Finland looks good too from this perspective relative to its European peers, but that wasn’t a surprise.
The data
It might be more useful to remove small countries like Singapore from this ranking as the impact of emission control there is unlikely to impact the world at large. However, in the interest of completeness, I’ve decided to keep all the data as is.
All numbers are truncated to two decimal places. Some numbers use scientific notation like “1.24e6” which means “1240000”.
Entity | Code | Annual CO2 emissions | Land area (sq. km) | EmissionsPerUnitArea | Rank |
---|---|---|---|---|---|
Singapore | SGP | 45503904 | 709.0 | 64180.40 | 1 |
Bahrain | BHR | 34960075 | 780.0 | 44820.60 | 2 |
Macao | MAC | 1262755 | 32.90 | 38381.60 | 3 |
Hong Kong | HKG | 31238788 | 1050.0 | 29751.22 | 4 |
Sint Maarten (Dutch part) | SXM | 623462 | 34.0 | 18337.11 | 5 |
Bermuda | BMU | 624448 | 54.0 | 11563.85 | 6 |
Qatar | QAT | 106654967 | 11490.0 | 9282.41 | 7 |
Curacao | CUW | 3335066 | 444.0 | 7511.40 | 8 |
Trinidad and Tobago | TTO | 35509414 | 5130.0 | 6921.91 | 9 |
South Korea | KOR | 597605055 | 97520.0 | 6128.02 | 10 |
Maldives | MDV | 1796469 | 300.0 | 5988.23 | 11 |
Kuwait | KWT | 88935077 | 17820.0 | 4990.74 | 12 |
Malta | MLT | 1594903 | 320.0 | 4984.07 | 13 |
Aruba | ABW | 753218 | 180.0 | 4184.54 | 14 |
Netherlands | NLD | 138100074 | 33670.0 | 4101.57 | 15 |
Luxembourg | LUX | 8174648 | 2430.0 | 3364.05 | 16 |
Nauru | NRU | 56731 | 20.0 | 2836.55 | 17 |
Japan | JPN | 1030775384 | 364500.0 | 2827.91 | 18 |
Belgium | BEL | 83748962 | 30280.0 | 2765.81 | 19 |
Israel | ISR | 56350861 | 21640.0 | 2604.01 | 20 |
Lebanon | LBN | 25969298 | 10230.0 | 2538.54 | 21 |
Barbados | BRB | 1086743 | 430.0 | 2527.30 | 22 |
United Arab Emirates | ARE | 150268152 | 71020.0 | 2115.85 | 23 |
Mauritius | MUS | 3979358 | 2030.0 | 1960.27 | 24 |
Brunei | BRN | 10158494 | 5270.0 | 1927.60 | 25 |
Germany | DEU | 644310352 | 349380.0 | 1844.15 | 26 |
United Kingdom | GBR | 329578911 | 241930.0 | 1362.29 | 27 |
Czechia | CZE | 87974706 | 77200.0 | 1139.56 | 28 |
China | CHN | 10667887453 | 9,424,703 | 1131.90 | 29 |
Seychelles | SYC | 491067 | 460.0 | 1067.53 | 30 |
Italy | ITA | 303815294 | 297730.0 | 1020.43 | 31 |
Andorra | AND | 466294 | 470.0 | 992.11 | 32 |
Poland | POL | 299592767 | 306170.0 | 978.51 | 33 |
Antigua and Barbuda | ATG | 430410 | 440.0 | 978.20 | 34 |
British Virgin Islands | VGB | 139250 | 150.0 | 928.33 | 35 |
Liechtenstein | LIE | 141012 | 160.0 | 881.32 | 36 |
Grenada | GRD | 294834 | 340.0 | 867.15 | 37 |
Marshall Islands | MHL | 151282 | 180.0 | 840.45 | 38 |
Malaysia | MYS | 272607434 | 328550.0 | 829.72 | 39 |
India | IND | 2441792313 | 2,973,190 | 821.27 | 40 |
Vietnam | VNM | 254303169 | 310070.0 | 820.14 | 41 |
Switzerland | CHE | 32298333 | 39516.03 | 817.34 | 42 |
Saint Kitts and Nevis | KNA | 212040 | 260.0 | 815.53 | 43 |
Austria | AUT | 60634876 | 82520.0 | 734.79 | 44 |
Saint Lucia | LCA | 439905 | 610.0 | 721.15 | 45 |
Bangladesh | BGD | 92841625 | 130170.0 | 713.23 | 46 |
Cyprus | CYP | 6496162 | 9240.0 | 703.04 | 47 |
Jamaica | JAM | 7429454 | 10830.0 | 686.00 | 48 |
Denmark | DNK | 26194912 | 40000.0 | 654.87 | 49 |
Slovakia | SVK | 30730385 | 48080.0 | 639.15 | 50 |
Slovenia | SVN | 12562986 | 20136.40 | 623.89 | 51 |
Dominican Republic | DOM | 27769310 | 48310.0 | 574.81 | 52 |
Saint Vincent and the Grenadines | VCT | 208876 | 390.0 | 535.57 | 53 |
Hungary | HUN | 48275451 | 91260.0 | 528.98 | 54 |
United States | USA | 4712770573 | 9,147,420 | 515.20 | 55 |
Turkey | TUR | 392794051 | 769630.0 | 510.36 | 56 |
France | FRA | 276633893 | 547557.0 | 505.21 | 57 |
Thailand | THA | 257765782 | 510890.0 | 504.54 | 58 |
Serbia | SRB | 43135397 | 87460.0 | 493.20 | 59 |
Faeroe Islands | FRO | 683898 | 1396.0 | 489.89 | 60 |
Iraq | IRQ | 210829146 | 434128.0 | 485.63 | 61 |
Ireland | IRL | 33348699 | 68890.0 | 484.08 | 62 |
Palestine | PSE | 2898754 | 6020.0 | 481.52 | 63 |
Palau | PLW | 219358 | 460.0 | 476.86 | 64 |
New Caledonia | NCL | 8692686 | 18280.0 | 475.52 | 65 |
Iran | IRN | 745035109 | 1.62e6 | 457.42 | 66 |
Azerbaijan | AZE | 37720462 | 82654.0 | 456.36 | 67 |
Philippines | PHL | 136017950 | 298170.0 | 456.17 | 68 |
Portugal | PRT | 40387817 | 91605.60 | 440.88 | 69 |
Bosnia and Herzegovina | BIH | 21417961 | 51200.0 | 418.31 | 70 |
Spain | ESP | 208914968 | 499603.46 | 418.16 | 71 |
Greece | GRC | 52235141 | 128900.0 | 405.23 | 72 |
South Africa | ZAF | 451957087 | 1.21e6 | 372.56 | 73 |
Ukraine | UKR | 213908873 | 579400.0 | 369.19 | 74 |
Equatorial Guinea | GNQ | 10265267 | 28050.0 | 365.96 | 75 |
Bulgaria | BGR | 37444110 | 108560.0 | 344.91 | 76 |
Sri Lanka | LKA | 21106254 | 61864.0 | 341.17 | 77 |
Indonesia | IDN | 589500368 | 1.87e6 | 313.97 | 78 |
Romania | ROU | 71475046 | 230080.0 | 310.65 | 79 |
Pakistan | PAK | 234754740 | 770880.0 | 304.52 | 80 |
Croatia | HRV | 16982010 | 56590.0 | 300.08 | 81 |
El Salvador | SLV | 6123716 | 20720.0 | 295.54 | 82 |
Saudi Arabia | SAU | 625507882 | 2.14e6 | 290.97 | 83 |
Jordan | JOR | 25487430 | 88780.0 | 287.08 | 84 |
North Macedonia | MKD | 7146509 | 25220.0 | 283.36 | 85 |
Belarus | BLR | 57445417 | 202980.0 | 283.01 | 86 |
World | OWID_WRL | 34807259099 | 1.29e8 | 267.85 | 87 |
Uzbekistan | UZB | 112784345 | 440555.0 | 256.00 | 88 |
Tuvalu | TUV | 7564 | 30.0 | 252.13 | 89 |
North Korea | PRK | 29311104 | 120410.0 | 243.42 | 90 |
Estonia | EST | 10452414 | 43470.0 | 240.45 | 91 |
French Polynesia | PYF | 828267 | 3520.0 | 235.30 | 92 |
Bahamas | BHS | 2337684 | 10010.0 | 233.53 | 93 |
Lithuania | LTU | 13799480 | 62630.0 | 220.33 | 94 |
Egypt | EGY | 213456746 | 995450.0 | 214.43 | 95 |
Turks and Caicos Islands | TCA | 202546 | 950.0 | 213.20 | 96 |
Micronesia (country) | FSM | 147500 | 700.0 | 210.71 | 97 |
Armenia | ARM | 5890292 | 28470.0 | 206.89 | 98 |
Oman | OMN | 62162570 | 309500.0 | 200.84 | 99 |
Tonga | TON | 143718 | 720.0 | 199.60 | 100 |
Cuba | CUB | 20152280 | 103800.0 | 194.14 | 101 |
Dominica | DMA | 139250 | 750.0 | 185.66 | 102 |
Mexico | MEX | 356968119 | 1.94e6 | 183.63 | 103 |
Tunisia | TUN | 28126702 | 155360.0 | 181.04 | 104 |
Guatemala | GTM | 18937908 | 107160.0 | 176.72 | 105 |
Montenegro | MNE | 2309894 | 13450.0 | 171.73 | 106 |
Syria | SYR | 30531928 | 183630.0 | 166.26 | 107 |
Albania | ALB | 4534673 | 27400.0 | 165.49 | 108 |
Turkmenistan | TKM | 75337709 | 469930.0 | 160.31 | 109 |
Moldova | MDA | 5146876 | 32885.30 | 156.50 | 110 |
Costa Rica | CRI | 7907389 | 51060.0 | 154.86 | 111 |
Laos | LAO | 33846818 | 230800.0 | 146.64 | 112 |
Panama | PAN | 10779522 | 74177.0 | 145.32 | 113 |
Morocco | MAR | 64536253 | 446300.0 | 144.60 | 114 |
Georgia | GEO | 9968094 | 69490.0 | 143.44 | 115 |
Comoros | COM | 258456 | 1861.0 | 138.88 | 116 |
Nigeria | NGA | 125462961 | 910770.0 | 137.75 | 117 |
Cape Verde | CPV | 549930 | 4030.0 | 136.45 | 118 |
Finland | FIN | 39287631 | 303920.0 | 129.26 | 119 |
New Zealand | NZL | 33475158 | 263310.0 | 127.13 | 120 |
Ecuador | ECU | 30931763 | 248360.0 | 124.54 | 121 |
Nepal | NPL | 16957668 | 143350.0 | 118.29 | 122 |
Sao Tome and Principe | STP | 112744 | 960.0 | 117.44 | 123 |
Norway | NOR | 41283000 | 365107.84 | 113.07 | 124 |
Chile | CHL | 81171490 | 743532.0 | 109.17 | 125 |
Latvia | LVA | 6772778 | 62090.0 | 109.08 | 126 |
Kazakhstan | KAZ | 291335929 | 2.69e6 | 107.91 | 127 |
Haiti | HTI | 2919510 | 27560.0 | 105.93 | 128 |
Russia | RUS | 1577136041 | 1.63e7 | 96.30 | 129 |
Venezuela | VEN | 84609478 | 882050.0 | 95.92 | 130 |
Sweden | SWE | 38634794 | 407310.0 | 94.85 | 131 |
Samoa | WSM | 245833 | 2830.0 | 86.86 | 132 |
Cambodia | KHM | 15325618 | 176520.0 | 86.82 | 133 |
Honduras | HND | 9659570 | 111890.0 | 86.33 | 134 |
Kiribati | KIR | 68077 | 810.0 | 84.04 | 135 |
Colombia | COL | 89104941 | 1.10e6 | 80.31 | 136 |
Fiji | FJI | 1393413 | 18270.0 | 76.26 | 137 |
Lesotho | LSO | 2183421 | 30360.0 | 71.91 | 138 |
Ghana | GHA | 16001330 | 227540.0 | 70.32 | 139 |
Tajikistan | TJK | 9447656 | 138790.0 | 68.07 | 140 |
Algeria | DZA | 154995460 | 2.38e6 | 65.07 | 141 |
Kyrgyzstan | KGZ | 11507817 | 191800.0 | 59.99 | 142 |
Canada | CAN | 535822990 | 8.96e6 | 59.76 | 143 |
Benin | BEN | 6702765 | 112760.0 | 59.44 | 144 |
Argentina | ARG | 156978063 | 2.73e6 | 57.36 | 145 |
Mongolia | MNG | 88441761 | 1.55e6 | 56.79 | 146 |
Brazil | BRA | 467383500 | 8.35e6 | 55.91 | 147 |
Myanmar | MMR | 36325546 | 652790.0 | 55.64 | 148 |
Eswatini | SWZ | 955776 | 17200.0 | 55.56 | 149 |
Senegal | SEN | 10451209 | 192530.0 | 54.28 | 150 |
Australia | AUS | 391891928 | 7.69e6 | 50.94 | 151 |
Bhutan | BTN | 1925367 | 38140.0 | 50.48 | 152 |
Gambia | GMB | 499912 | 10120.0 | 49.39 | 153 |
Nicaragua | NIC | 5073650 | 120340.0 | 42.16 | 154 |
Rwanda | RWA | 1032737 | 24670.0 | 41.86 | 155 |
Togo | TGO | 2191571 | 54390.0 | 40.29 | 156 |
Timor | TLS | 525704 | 14870.0 | 35.35 | 157 |
Peru | PER | 44706055 | 1.28e6 | 34.92 | 158 |
Uruguay | URY | 5840060 | 175020.0 | 33.36 | 159 |
Cote d’Ivoire | CIV | 10070733 | 318000.0 | 31.66 | 160 |
Iceland | ISL | 2935990 | 100830.0 | 29.11 | 161 |
Libya | LBY | 50720577 | 1.75e6 | 28.82 | 162 |
Kenya | KEN | 16146074 | 569140.0 | 28.36 | 163 |
Zimbabwe | ZWE | 10531342 | 386850.0 | 27.22 | 164 |
Belize | BLZ | 582795 | 22810.0 | 25.54 | 165 |
Uganda | UGA | 4892203 | 200520.0 | 24.39 | 166 |
Burundi | BDI | 602181 | 25680.0 | 23.44 | 167 |
Bolivia | BOL | 20700023 | 1.08e6 | 19.10 | 168 |
Paraguay | PRY | 7569706 | 397300.0 | 19.05 | 169 |
Afghanistan | AFG | 12160286 | 652860.0 | 18.62 | 170 |
Yemen | YEM | 9768313 | 527970.0 | 18.50 | 171 |
Angola | AGO | 22198161 | 1.24e6 | 17.80 | 172 |
Gabon | GAB | 4298177 | 257670.0 | 16.68 | 173 |
Djibouti | DJI | 351464 | 23180.0 | 15.16 | 174 |
Vanuatu | VUT | 181538 | 12190.0 | 14.89 | 175 |
Malawi | MWI | 1394983 | 94280.0 | 14.79 | 176 |
Papua New Guinea | PNG | 6652121 | 452860.0 | 14.68 | 177 |
Cameroon | CMR | 6889318 | 472710.0 | 14.57 | 178 |
Burkina Faso | BFA | 3969636 | 273600.0 | 14.50 | 179 |
Suriname | SUR | 2224178 | 156000.0 | 14.25 | 180 |
Guinea | GIN | 3394049 | 245720.0 | 13.81 | 181 |
Ethiopia | ETH | 14664773 | 1.12e6 | 12.98 | 182 |
Tanzania | TZA | 10938632 | 885800.0 | 12.34 | 183 |
Sierra Leone | SLE | 877190 | 72180.0 | 12.15 | 184 |
Botswana | BWA | 6518934 | 566730.0 | 11.50 | 185 |
Guyana | GUY | 2212691 | 196850.0 | 11.24 | 186 |
Solomon Islands | SLB | 298781 | 27990.0 | 10.67 | 187 |
Liberia | LBR | 1008984 | 96320.0 | 10.47 | 188 |
Sudan | SDN | 18859244 | 1.84e6 | 10.19 | 189 |
Guinea-Bissau | GNB | 286774 | 28120.0 | 10.19 | 190 |
Congo | COG | 3116760 | 341500.0 | 9.12 | 191 |
Zambia | ZMB | 6572938 | 743390.0 | 8.84 | 192 |
Mozambique | MOZ | 6570936 | 786380.0 | 8.35 | 193 |
Eritrea | ERI | 722332 | 101000.0 | 7.15 | 194 |
Madagascar | MDG | 3679618 | 581800.0 | 6.32 | 195 |
Namibia | NAM | 3877243 | 823290.0 | 4.70 | 196 |
Mauritania | MRT | 3377180 | 1.03e6 | 3.27 | 197 |
Mali | MLI | 3390011 | 1.22e6 | 2.77 | 198 |
South Sudan | SSD | 1179207 | 631928.12 | 1.86 | 199 |
Niger | NER | 1690423 | 1.26e6 | 1.33 | 200 |
Greenland | GRL | 514413 | 410450.0 | 1.25 | 201 |
Democratic Republic of Congo | COD | 2477334 | 2.26e6 | 1.09 | 202 |
Somalia | SOM | 562143 | 627340.0 | 0.89 | 203 |
Chad | TCD | 912301 | 1.25e6 | 0.72 | 204 |
Central African Republic | CAF | 187906 | 622980.0 | 0.30 | 205 |