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The transportation and electricity sectors are major sources of U.S. greenhouse gas (GHG) emissions because fossil fuels are the dominant energy source for the transportation sector and for electricity generation. Both sectors are facing the challenge of shifting to a more sustainable future. In the transportation sector, plug-in electric vehicles (PEV) and hydrogen fuel cell electric vehicles (FCEV) will play a key role in meeting California’s 2050 GHG goals. This research studied the feasibility of the deployment of renewable hydrogen fueling for FCEVs and DC fast charging stations for PEVs at Highway Safety Roadside Rest Areas (SRRAs) and the integration of the stations with the electricity grid, including solar electric generation, to lower the infrastructure cost and to accelerate the usage of renewable energy in the California transportation sector. Three hydrogen fueling/DC fast charging system configurations were studied: two integrated stations with energy storage using compressed hydrogen or batteries as the energy storage medium located on a single site, and a distributed system configuration deployed on different sites. In this analysis, we assessed the sustainable integrated fueling/charging stations based on 100% of utilization of the local PV electricity for hydrogen fueling/DC fast charging. The hydrogen fuelings and EV chargings were evenly divided based on their energy consumption. However, in the early stage of FCEV and PEV adoption, a relatively low utilization of fueling/charging stations is likely. In that case, the integrated stations could function as distributed power generation and energy storage for the grid. As the market for FCEVs and EVs develops, the integrated stations have the potential to serve the larger numbers of FCEVs and PEVs by using grid electricity during off-peak hours.View the NCST Project Webpage

Mesocosm experiments have become increasingly popular in climate change research as they bridge the gap between small-scale, less realistic, microcosm experiments, and large-scale, more complex, natural systems. Characteristics of aquatic mesocosm designs (e.g., mesocosm volume, study duration, and replication) vary widely, potentially affecting the magnitude and direction of effect sizes measured in experiments. In this global systematic review we aim to identify the type, direction and strength of climate warming effects on aquatic species, communities and ecosystems in mesocosm experiments. Furthermore, we will investigate the context-dependency of the observed effects on several a priori determined effect moderators (ecological and methodological). Our conclusions will provide recommendations for aquatic scientists designing mesocosm experiments, as well as guidelines for interpretation of experimental results by scientists, policy-makers and the general public. We will conduct a systematic search using multiple online databases to gather evidence from the scientific literature on the effects of warming experimentally tested in aquatic mesocosms. Data from relevant studies will be extracted and used in a random effects meta-analysis to estimate the overall effect sizes of warming experiments on species performance, biodiversity and ecosystem functions. Experimental characteristics (e.g., mesocosm size and shape, replication-level, experimental duration and design, biogeographic region, community type, crossed manipulation) will be further analysed using subgroup analyses.

Two pioneer states, California and New York, have set their ambitious targets to get 100% and 70% of their electricity from renewable energy resources by 2045 and 2030, respectively. Aligned with these endeavors, currently 19.2% of the electricity in California is coming from the solar energy where the utilities are expected to add an additional 60% solar energy in the next five years. To achieve this goal, Electrification- the transition from non-electric end-use energy consumers to the electric consumers is a trend in the energy sector, as it facilitates to have access to sustainable and clean energy infrastructure. The fact that 28% of the energy in the USA is consumed by the transportation sector where 92% is provided by the fossil fuel energy motivates Electrication strongly. This revolution is specifically happening in the California state where 50% of the electric vehicle (EV) owners are living. The increasing penetration of renewable energies, such as solar energy, as well as Electrification in the electrical grids introduce new challenges for system operation and planning. Solar energy, inherently, is intermittent and shows stochastic behavior which makes it a non-dispatchable source of electricity. Therefore, the conventional models to capture its generation profile are no longer applicable. Also according to a new report by National Renewable Energy Laboratory (NREL) [MJL18], EVs are introduced as one of the most influential elements of Electrification. EVs can drastically change the load pattern, thus their integration in the power grids is carefully observed by the electric utilities.To mitigate the stochastic behavior of solar energy and make it a dispatchable resource, the energy storage can be utilized to capture its intermittency through the coordinated charging and discharging sequences. That is one reason why the California and New York states plan to integrate an additional 1.3 GW and 3.0 GW energy storage in their power grids by 2024 and 2030, respectively. Moreover, EVs are controllable ...

Today’s electric grid must be transformed to meet modern consumption behaviors and safely integrate renewable energy sources. This has led to major efforts to develop grid-scale energy management solutions and ensure safety and reliability of our modern power network. In particular, large penetrations of Plug-in Electric Vehicles (PEVs) are expected increase energy needs and peak consumption, which would bring new challenges for utilities and grid operators.In this work, we develop optimization methods to coordinate the charging of large fleets of PEVs in distribution grids. We show that different methods should be applied, based on the infrastructure requirements and the objective of the controller.The first Chapter Optimal Charging of Fleets of Electric Vehicles with Discrete Charging rates: PDE Modeling and Control Techniques presents a continuum modeling framework to coordinate PEV charging with discrete charging rates. We consider PEVs as loads, which diffuse along the State Of Energy (SOE) axis, and can be in three different categories: charging, discharging or idle. We use a discretized form of Partial Differential Equations (PDEs) to model the dynamics of the system and control the transitions between each category. The second Chapter Dual Splitting Framework for Optimal Charging of Fleets of Electric Vehicles with Continuous Charging rates proposes a tailored distributed optimization method to coordinate PEV charging for load shaping. Three iteration methods are presented and their convergence characteristics are detailed. The third Chapter Electric Vehicle Charging in the Smart Grid: Plug-and-Play Model Predictive Control techniques studies a voltage-regulation scenario for PEV charging. Power flow and distribution grid constraints are modeled, and PEV charging is controlled with Plug-and-Play Model Predictive Control. Finally, the final chapter Behavioral study of Demand Response programs studies the impact of non rational choices on energy consumption and on the success of Demand Response programs.

In metropolitan regions made up of multiple independent jurisdictions, adaptation to increased coastal flooding due to sea level rise requires coordinated strategic planning of the physical and organizational approaches to be adopted. Here, we explore a flexible method for estimating physical adaptation costs along the San Francisco Bay shoreline. Our goal is to identify uncertainties that can hinder cooperation and decision-making. We categorized shoreline data, estimated the height of exceedance for sea level rise scenarios, and developed a set of unit costs for raising current infrastructure to meet future water levels. Using these cost estimates, we explored critical strategic planning questions, including shoreline positions, design heights, and infrastructure types. For shoreline position, we found that while the shortest line is in fact the least costly, building the future shoreline at today’s transition from saltwater to freshwater vegetation is similar in cost but allows for the added possibility of conserving saltwater wetlands. Regulations requiring a specific infrastructure design height above the water level had a large impact on physical construction costs, increasing them by as much as 200%. Finally, our results show that the costs of raising existing walls may represent 70% to 90% of the total regional costs, suggesting that a shift to earthen terraces and levees will reduce adaptation costs significantly.

Planning scholars have identified economic, safety, and social benefits of converting one-way streets to two-way. Less is known about how conversions could impact vehicular distances traveled—of growing relevance in an era of fleet automation, electrification, and ride-hailing. We simulate such a conversion in San Francisco, California. We find that its current street network’s average intra-city trip is about 1.7% longer than it would be with all two-way streets, corresponding to 27 million kilometers of annual surplus travel. As transportation technologies evolve, planners must consider different facets of network efficiency to align local policy and street design with sustainability and other societal goals.

Ocean acidification (OA) is increasing due to anthropogenic CO2 emissions and poses a threat to marine species and communities worldwide. To better project the effects of acidification on organisms' health and persistence, an understanding is needed of the 1) mechanisms underlying developmental and physiological tolerance and 2) potential populations have for rapid evolutionary adaptation. This is especially challenging in nonmodel species where targeted assays of metabolism and stress physiology may not be available or economical for large-scale assessments of genetic constraints. We used mRNA sequencing and a quantitative genetics breeding design to study mechanisms underlying genetic variability and tolerance to decreased seawater pH (-0.4 pH units) in larvae of the sea urchin Strongylocentrotus droebachiensis. We used a gene ontology-based approach to integrate expression profiles into indirect measures of cellular and biochemical traits underlying variation in larval performance (i.e., growth rates). Molecular responses to OA were complex, involving changes to several functions such as growth rates, cell division, metabolism, and immune activities. Surprisingly, the magnitude of pH effects on molecular traits tended to be small relative to variation attributable to segregating functional genetic variation in this species. We discuss how the application of transcriptomics and quantitative genetics approaches across diverse species can enrich our understanding of the biological impacts of climate change.

China's road transportation contributed about 8% of the country’s GHG emissions in 2020. Chinese government has made the commitment of reaching “carbon peak in 2030 and carbon neutrality in 2060”. Among all the sectors, transportation is one of the most challenging and essential ones to mitigate GHG emissions. The experienced economic development and improvement in people's living standards have increased vehicle ownership for both passenger vehicles and freight trucks. For the road transportation sector, electrification of the fleet represents one of the most important measures to reduce criteria pollutants and GHG emissions.By modeling passenger and freight vehicle fleets, this study projects the vehicle growth based on economic projections and the changes in demographic characteristics of the population during 2010 to 2050. The study developed a stock and sales model considering vehicle survival rates by vehicle types to reflect the different vehicle retirement and replacement schedules. Moreover, the study designed three sets of fleet electrification scenarios considering different technology penetration and deployment levels for different vehicle type. The scenario analysis extensively explored the energy consumption and GHG emission trajectories for the different vehicle growth scenarios, electrification pathways and renewable energy penetration rates in the grid. The scenarios also considered, as mentioned, changes in the demographics. For instance, in aging society scenario (considering an aging and decreasing fertility demographic), fleet growth rates slow down in the following three decades. This scenario results in a reduction of energy consumption and GHG emission from the road transportation sector. The scenario analysis extensively explored the energy consumption and GHG emission trajectories of the different vehicle growth scenarios, electrification pathways, and renewable energy penetration rates in the grid. From the scenarios analysis, in the aging society vehicle growth scenario, the ...

Automated driving has attracted intense attention in the media and among the general public, based on extremely optimistic predictions from some industry participants, but these have started to become more realistic in the last couple of years, after the “hype cycle” for automation peaked. This paper explains the opportunities for Automated Driving System (ADS) technology to improve the urban transport of people and goods, together with the challenges that will limit the scope and timing of the deployment of urban ADS. The discussion emphasizes the diversity of ADS applications and services, each of which has its own opportunities, challenges, and uncertainties, leading to diverse deployment scopes and schedules. The associated challenges are sufficiently daunting that ADS deployment will lag behind electrification and connectivity, leaving more time for cities to prepare for it.