Low-CO(2) electricity and hydrogen: a help or hindrance for electric and hydrogen vehicles?

Emissions reductions from expanding state-level renewable portfolio standards

In the United States, state-level Renewable Portfolio Standards (RPS) have served as key drivers for the development of new renewable energy. This research presents a method to evaluate emissions reductions and costs attributable to new or expanded RPS programs by integrating a comprehensive economic dispatch model and a renewable project selection model. The latter model minimizes incremental RPS costs, accounting for renewable power purchase agreements (PPAs), displaced generation and capacity costs, and net changes to a state's imports and exports. We test this method on potential expansions to Michigan's RPS, evaluating target renewable penetrations of 10% (business as usual or BAU), 20%, 25%, and 40%, with varying times to completion. Relative to the BAU case, these expanded RPS policies reduce the CO2 intensity of generation by 13%, 18%, and 33% by 2035, respectively. SO2 emissions intensity decreased by 13%, 20%, and 34% for each of the three scenarios, while NOx reductions totaled 12%, 17%, and 31%, relative to the BAU case. For CO2 and NOx, absolute reductions in emissions intensity were not as large due to an increasing trend in emissions intensity in the BAU case driven by load growth. Over the study period (2015 to 2035), the absolute CO2 emissions intensity increased by 1% in the 20% RPS case and decreased by 6% and 22% for the 25% and 40% cases, respectively. Between 26% and 31% of the CO2, SO2, and NOx emissions reductions attributable to the expanded RPS occur in neighboring states, underscoring the challenges quantifying local emissions reductions from state-level energy policies with an interconnected grid. Without federal subsidies, the cost of CO2 mitigation using an RPS in Michigan is between $28 and $34/t CO2 when RPS targets are met. The optimal renewable build plan is sensitive to the capacity credit for solar but insensitive to the value for wind power.

Cost-effective choices of marine fuels in a carbon-constrained world: results from a global energy model

The regionalized Global Energy Transition model has been modified to include a more detailed shipping sector in order to assess what marine fuels and propulsion technologies might be cost-effective by 2050 when achieving an atmospheric CO2 concentration of 400 or 500 ppm by the year 2100. The robustness of the results was examined in a Monte Carlo analysis, varying uncertain parameters and technology options, including the amount of primary energy resources, the availability of carbon capture and storage (CCS) technologies, and costs of different technologies and fuels. The four main findings are (i) it is cost-effective to start the phase out of fuel oil from the shipping sector in the next decade; (ii) natural gas-based fuels (liquefied natural gas and methanol) are the most probable substitutes during the study period; (iii) availability of CCS, the CO2 target, the liquefied natural gas tank cost and potential oil resources affect marine fuel choices significantly; and (iv) biofuels rarely play a major role in the shipping sector, due to limited supply and competition for bioenergy from other energy sectors.

Electric vehicles in China: emissions and health impacts

E-bikes in China are the single largest adoption of alternative fuel vehicles in history, with more than 100 million e-bikes purchased in the past decade and vehicle ownership about 2× larger for e-bikes as for conventional cars; e-car sales, too, are rapidly growing. We compare emissions (CO(2), PM(2.5), NO(X), HC) and environmental health impacts (primary PM(2.5)) from the use of conventional vehicles (CVs) and electric vehicles (EVs) in 34 major cities in China. CO(2) emissions (g km(-1)) vary and are an order of magnitude greater for e-cars (135-274) and CVs (150-180) than for e-bikes (14-27). PM(2.5) emission factors generally are lower for CVs (gasoline or diesel) than comparable EVs. However, intake fraction is often greater for CVs than for EVs because combustion emissions are generally closer to population centers for CVs (tailpipe emissions) than for EVs (power plant emissions). For most cities, the net result is that primary PM(2.5) environmental health impacts per passenger-km are greater for e-cars than for gasoline cars (3.6× on average), lower than for diesel cars (2.5× on average), and equal to diesel buses. In contrast, e-bikes yield lower environmental health impacts per passenger-km than the three CVs investigated: gasoline cars (2×), diesel cars (10×), and diesel buses (5×). Our findings highlight the importance of considering exposures, and especially the proximity of emissions to people, when evaluating environmental health impacts for EVs.