Atmospheric GHG Measurements

Statistical Inverse Model

The a priori emission inventories are modified by scaling the emissions to best match the measured and predicted GHG signals in a Bayesian model which gives separate statistical weights to the model-measurement difference and the a priori emissions. The result is a posterior estimate of the scaling factor for each of the different sources or sub-regions of California (Jeong et al., 2012).


State of California Energy Commission U.S. Department of Energy Lawrence Berkeley National Lab U.S. National Oceanic and Atmospheric Administration California Air Resources Board