Achieving ambitious climate change mitigation targets clearly requires a focus on transport that should include changes in travel behaviour in addition to increased vehicle efficiency and low-carbon fuels. Most available energy/economy/environment/engineering (E4) modelling tools focus however...

We decompose the contribution of five drivers of energy use and CO2 emissions reductions in achieving climate change goals over 2005–2100 for various climate policy scenarios. This study contributes to the decomposition literature in three ways. First, it disaggregates drivers of energy demand...

The use of log-linear experience curves (or learning curves) relating reductions in the unit cost of technologies to their cumulative production or installed capacity has become a common method of representing endogenous technical change in energy-economic models used for policy analysis. Yet,...

The CA-TIMES optimization model of the California Energy System (v1.5) is used to understand how California can meet the 2050 targets for greenhouse gas (GHG) emissions (80% below 1990 levels). This model represents energy supply and demand sectors in California and simulates the technology and...

Heavy-duty vehicles (HDV) account for less than 2-5% of the vehicles on the road in Europe but contribute to 15-22% of CO2 emissions from road transport. Battery electric trucks (BETs) could be deployed on a large scale to reduce greenhouse gas emissions but they require charging infrastructure...