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Loughlin, Dan

Publications and source records attributed to Loughlin, Dan.

Interactions Between Climate Policy and Technology-influenced Travel Behavior: Mitigating Induced Demand from CACC

Advances in vehicle technology have influenced the development of automated vehicle systems, where vehicles that do not require human intervention are already deployed in the roadway networks. While these advances are proved to increase roadway safety and highway capacity, more research is needed to understand the long-term and regional-level impacts on mobility, land use, energy consumption, and emissions. This study proposes a multi-model approach to analyze the effect of vehicle automation and deep decarbonization policies over a period from 2020 to 2040 in Austin, Texas. We use the Global Change Analysis Model (GCAM) to develop internally the scenarios that are then passed to the SMART Mobility modeling workflow, a large-scale simulation framework combining the POLARIS activity-based travel demand model and mesoscopic traffic simulator with the Autonomie vehicle energy consumption model and the UrbanSim land use simulator. Results suggest that the introduction of vehicles with advanced automation could increase fuel consumption when no decarbonization policies are implemented. Also, advances in vehicle technology research and development could lead to a decline in energy use in the long-term. Energy pricing and vehicle electrification incentives could help reduce the impact of vehicle automation. Finally, our analysis indicates the relevance of introducing land use processes in longterm vehicle automation studies.

land use↗

The quest for improved air quality may push China to continue its CO 2 reduction beyond the Paris Commitment

China is challenged with the simultaneous goals of improving air quality and mitigating climate change. The “Beautiful China” strategy, launched by the Chinese government in 2020, requires that all cities in China attain 35 μg/m 3 or below for annual mean concentration of PM 2.5 (particulate matter with aerodynamic diameter less than 2.5 μm) by 2035. Meanwhile, China adopts a portfolio of low-carbon policies to meet its Nationally Determined Contribution (NDC) pledged in the Paris Agreement. Previous studies demonstrated the co-benefits to air pollution reduction from implementing low-carbon energy policies. Pathways for China to achieve dual targets of both air quality and CO 2 mitigation, however, have not been comprehensively explored. Here, we couple an integrated assessment model and an air quality model to evaluate air quality in China through 2035 under the NDC scenario and an alternative scenario (Co-Benefit Energy [CBE]) with enhanced low-carbon policies. Results indicate that some Chinese cities cannot meet the PM 2.5 target under the NDC scenario by 2035, even with the strictest end-of-pipe controls. Achieving the air quality target would require further reduction in emissions of multiple air pollutants by 6 to 32%, driving additional 22% reduction in CO 2 emissions relative to the NDC scenario. Results show that the incremental health benefit from improved air quality of CBE exceeds 8 times the additional costs of CO 2 mitigation, attributed particularly to the cost-effective reduction in household PM 2.5 exposure. The additional low-carbon energy polices required for China’s air quality targets would lay an important foundation for its deep decarbonization aligned with the 2 °C global temperature target.

54 ENVIRONMENTAL SCIENCES↗

Spatially Refined Aerosol Direct Radiative Forcing Efficiencies

Global aerosol direct radiative forcing (DRF) is an important metric for assessing potential climate impacts of future emissions changes. However, the radiative consequences of emissions perturbations are not readily quantified nor well understood at the level of detail necessary to assess realistic policy options. To address this challenge, here we show how adjoint model sensitivities can be used to provide highly spatially resolved estimates of the DRF from emissions of black carbon (BC), primary organic carbon (OC), sulfur dioxide (SO2), and ammonia (NH3), using the example of emissions from each sector and country following multiple Representative Concentration Pathway (RCPs). The radiative forcing efficiencies of many individual emissions are found to differ considerably from regional or sectoral averages for NH3, SO2 from the power sector, and BC from domestic, industrial, transportation and biomass burning sources. Consequently, the amount of emissions controls required to attain a specific DRF varies at intracontinental scales by up to a factor of 4. These results thus demonstrate both a need and means for incorporating spatially refined aerosol DRF into analysis of future emissions scenario and design of air quality and climate change mitigation policies.

Climate↗