Table 5 Summary of city emission datasets (Δ is uncertainty) and comparison statistics including coefficient of determination (R2), mean relative difference (Rd), and sample size (n) when compared with CM-Cities.
From: Carbon Monitor Cities near-real-time daily estimates of CO2 emissions from 1500 cities worldwide
Dataset | CM-Cities | CEADs | MEIC | CDP-ICLEI Track | Vulcan |
|---|---|---|---|---|---|
Spatial coverage | Global cities | China national, provincial, prefectural | China national, provincial | Global cities | U.S. counties |
Temporal coverage | 2019–2021 | 1997–2019 | 2000–2017 | 2010–2021 | 2010–2015 |
Temporal resolution | Daily | Monthly | Annual | Annual | Annual, hourly |
Protocol | — | — | — | Various | — |
Overall uncertainty | ±21.7% | −15% to 30% | ±15% | All data is self-reported, CDP-ICLEI Track does not assess the uncertainty | Sectoral uncertainties provided below |
Area definition | GADM, FUA | — | Population density, GDP | Mostly city administrative, some include adjacent areas | Administrative county area |
Total emissions comparison (with CM-Cities) | — | R2 = 0.96, Rd = 11%, n = 30 | — | R2 = 0.74, Rd = 31%, n = 24 | R2=0.82, Rd=26%, n=50 |
Power sector method | Daily power generation downscaling. Δ= ±10% | Energy consumption for production and supply of electric power, steam and hot water | Unit-level power generation. Δ = −15% to 16% | City report (scope 1–3 for relevant GPC stationary energy subsectors, including residential and commercial buildings, industry, agriculture, forestry and fishing) | CAMD, DOE/ EIA fuel, EPA NEI point electricity production. Δ= ±13% |
Power comparison (with CM-Cities) | — | R2 = 0.76, Rd = 30%, n = 30 | R2 = 0.93, Rd = 21%, n = 30 | — | R2 = 0.60, Rd = 114%, n = 50 |
Industry sector method | Industrial production index downscaling. Δ= ±36% | Energy consumption for individual manufacturing sectors | — | City report (direct scope 1 emissions from industrial processes and product use) | EPA NEI industrial point sources. Δ= ±12.8% |
Industry comparison (with CM-Cities) | — | R2 = 0.92, Rd = 28%, n = 30 | — | — | R2 = 0.58, Rd=67%, n=50 |
Residential sector method | HDD. Δ= ±40% | — | — | City report (scope 1–3 for relevant GPC stationary energy subsectors, including residential and commercial buildings) | EPA NEI residential and commercial nonpoint buildings. Δ= ±12.8% |
Residential comparison (with CM-Cities) | — | — | — | — | R2 = 0.82, Rd = 35%, n=50 |
Ground transport sector method | TomTom congestion index. Δ= ±9.3% | — | Vehicle ownership statistics and digital road map | City report (scope 1–3 for GPC transportation subsectors, including on-road, railways, waterborne navigation, aviation, and off-road) | EMFAC, EPA NEI onroad. Δ= ±14.2% |
Ground transport comparison (with CM-Cities) | — | — | R2 = 0.62, Rd = 31%, n = 30 | — | R2 = 0.90, Rd=41%, n=50 |
Aviation sector method | Flightradar24 flight data. Δ= ±10.2% | — | — | City report aviation under transportation sector | EPA NEI point airport. Δ= ±7.8% |
Aviation comparison (with CM-Cities) | — | — | — | — | R2 = 0.69, Rd = 58%, n=50 |
References | — | — |
