Fig. 1: Comparison of sector emission trends.

a, Population-weighted histogram of surface-transport trends from Apple driving data, Google transit mobility data and the high estimate from Le Quéré et al.³ for available countries in the different datasets averaged over April 2020. b, Violin plots showing the distribution, minimum, maximum and median levels of national trends weighted by CO₂ emissions for the Google and Le Quéré et al.³ datasets and the differences between the datasets evaluated over April 2020. c, Estimates of emission changes for the datasets across four sectors for April 2020 and the sum of the four sectors. The CO₂ emission estimates from Liu et al.² are also shown on this panel. In b and c, data are shown for 60 countries with overlapping data in the Google and Le Quéré et al.³ datasets (representing 60% of global CO₂ emissions). In c, Apple data are shown for 57 countries, covering 58% of the global emissions. The Liu et al.² estimate is for a global emission change. The high estimate from Le Quéré et al.³ data is used in a and b. Panel c shows the Le Quéré et al.³ low and high estimates as the range of the error bar on the mid-level estimate. For baselines, see Methods.