## 4 Discussion
These scale factors could be used whenever estimating annual emissions from an instantaneous emission estimate. For instance, OCO-2 observations over the US always occur in the afternoon, when emissions are above the daily mean. If the daily cycle is not corrected for, the annual emission estimates will be systematically over-estimated. Achieving the required number of overpasses with a single Low Earth Orbit (LEO) satellite now seems unlikely in the near future. By the end of CarbonSat's phase A/B1, the design had evolved to a 185-240 km swath (2016), similar to plans for the Copernicus CO\({}_{2}\) monitoring mission currently underconsideration by the European Commission in partnership with ESA. Furthermore, past theoretical studies expected that a 4 km\({}^{2}\) pixel would deliver about 23% cloud-free observations [17; 18] but real OCO-2 statistics and a smaller pixel size (\(\leq\)3 km\({}^{2}\)) suggest only 7-12% of observations per month pass all data screening filters (clouds and others) [6]. With about half the swath width and one fifth of the clear-sky observations (7-12% instead of 30-70%) from [PERSON] et al. [13], rather than 50 overpasses for a typical midlatitude site, a single satellite would likely obtain \(\sim\)5 clear-sky overpasses/year. A constellation of multiple wide-swath LEO missions is of course one way to obtain the required revisit rate, however geostationary (GEO) observations are another approach, with the potential for sub-daily revisit rates over land from \(\sim\)50\({}^{\circ}\)N-50\({}^{\circ}\)S [10; 19] and limited glint observations. Quasi-geostationary observations of high latitude regions can be obtained using from a highly elliptical orbit (HEO) [20; 21]. Including GEO and HEO in the constellation, along with LEO is the longterm vision for CO\({}_{2}\) monitoring for Europe [2] and suggested for the global architecture by CEOS [22]. Including GEO and HEO would likely lower the total number of satellites required since these vantage points better facilitate frequent revisits for key regions and flexible, cloud-informed pointing strategies can improve efficiency by timing observations for cloud avoidance [21]. Regardless of orbit, passive measurements using reflected sunlight would still lack night time data. The number of overpasses required for annual emission estimates also suggests that a short-duration campaign approach as with aircraft [23] will be severely limited in providing annual emission estimates on its own; however, aircraft in situ measurements could be complementary to a satellite-based approach by providing night time data for better overall daily emission estimates of showing consistency with daytime satellite-based estimates. By combining the new image averaging method and our estimates of revisit rates, we show that even for relatively weak sources (\(\sim\)6 Mt yr\({}^{-1}\)), the overall approach is actually limited by the variability in the power plant emissions, not the uncertainty in daily emission estimates. If we were able to sample daily emissions exactly (\(\epsilon_{est}=0\)), we would still require 16 such samples to constrain annual emissions within 15%. We have also shown that with 16 observations, we can estimate the emissions from a 6 Mt yr\({}^{-1}\) source within 6.78%. Therefore, by averaging a collection of images, the limiting factor in estimating annual emissions is the power plant variability itself, instead of the uncertainty in the instantaneous estimates, even for sources we can not see in the observations from single images.