CHUWD-H v1.0: a comprehensive historical hourly weather database for U.S. urban energy system modeling.

Reliable and continuous meteorological data are crucial for modeling the responses of energy systems and their components to weather and climate conditions, particularly in densely populated urban areas. However, existing long-term datasets often suffer from spatial and temporal gaps and inconsistencies, posing great challenges for detailed urban energy system modeling and cross-city comparison under realistic weather conditions. Here we introduce the Historical Comprehensive Hourly Urban Weather Database (CHUWD-H) v1.

Impacts of climate change, population growth, and power sector decarbonization on urban building energy use.

Climate, technologies, and socio-economic changes will influence future building energy use in cities. However, current low-resolution regional and state-level analyses are insufficient to reliably assist city-level decision-making. Here we estimate mid-century hourly building energy consumption in 277 U.

Energy efficiency to reduce residential electricity and natural gas use under climate change.

Climate change could significantly affect consumer demand for energy in buildings, as changing temperatures may alter heating and cooling loads. Warming climates could also lead to the increased adoption and use of cooling technologies in buildings. We assess residential electricity and natural gas demand in Los Angeles, California under multiple climate change projections and investigate the potential for energy efficiency to offset increased demand.

Improving the accuracy of vehicle emissions profiles for urban transportation greenhouse gas and air pollution inventories.

Metropolitan greenhouse gas and air emissions inventories can better account for the variability in vehicle movement, fleet composition, and infrastructure that exists within and between regions, to develop more accurate information for environmental goals. With emerging access to high quality data, new methods are needed for informing transportation emissions assessment practitioners of the relevant vehicle and infrastructure characteristics that should be prioritized in modeling to improve the accuracy of inventories. The sensitivity of light and heavy-duty vehicle greenhouse gas (GHG) and conventional air pollutant (CAP) emissions to speed, weight, age, and roadway gradient are examined with second-by-second velocity profiles on freeway and arterial roads under free-flow and congestion scenarios.