Underprediction of peak ambient pollution by air quality models hinders development of effective strategies to protect health and welfare. The U.S. Environmental Protection Agency's community multiscale air quality (CMAQ) model routinely underpredicts peak ozone and fine particulate matter (PM2.5) concentrations. Temporal misallocation of electricity sector emissions contributes to this modeling deficiency. Hourly emissions are created for CMAQ by use of temporal profiles applied to annual emission totals unless a source is matched to a continuous emissions monitor (CEM) in the National Emissions Inventory (NEI). More than 53% of CEMs in the Pennsylvania-New Jersey-Maryland (PJM) electricity market and 45% nationally are unmatched in the 2008 NEI. For July 2006, a United States heat wave with high electricity demand, peak electric sector emissions, and elevated ambient PM2.5 mass, we match hourly emissions for 267 CEM/NEI pairs in PJM (approximately 49% and 12% of unmatched CEMs in PJM and nationwide) using state permits, electricity dispatch modeling and CEMs. Hourly emissions for individual facilities can differ up to 154% during the simulation when measurement data is used rather than default temporalization values. Maximum CMAQ PM2.5 mass, sulfate, and elemental carbon predictions increase up to 83%, 103%, and 310%, at the surface and 51%, 75%, and 38% aloft (800 mb), respectively.
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http://dx.doi.org/10.1021/es5050248 | DOI Listing |
Environ Pollut
January 2025
University of Southern California, Department of Civil and Environmental Engineering, Los Angeles, California, USA. Electronic address:
Airborne particulate matter (PM) in urban environments poses significant health risks by penetrating the respiratory system, with concern over lung-deposited surface area (LDSA) as an indicator of particle exposure. This study aimed to investigate the diurnal trends and sources of LDSA, particle number concentration (PNC), elemental carbon (EC), and organic carbon (OC) concentrations in Los Angeles across different seasons to provide a comprehensive understanding of the contributions from primary and secondary sources of ultrafine particles (UFPs). Hourly measurements of PNC and LDSA were conducted using the DiSCmini and Scanning Mobility Particle Sizer (SMPS), while OC and EC concentrations were measured using the Sunset Lab EC/OC Monitor.
View Article and Find Full Text PDFNat Commun
January 2025
Department of Chemical Engineering, University College London, London, WC1E 7JE, UK.
Selective catalytic oxidation (SCO) of NH to N is one of the most effective methods used to eliminate NH emissions. However, achieving high conversion over a wide operating temperature range while avoiding over-oxidation to NO remains a significant challenge. Here, we report a bi-metallic surficial catalyst (PtCuO/AlO) with improved Pt atom efficiency that overcomes the limitations of current catalysts.
View Article and Find Full Text PDFEnviron Pollut
December 2024
Associate Unit CSIC-University of Huelva "Atmospheric Pollution", Center for Research in Sustainable Chemistry-CIQSO, University of Huelva, E21007, Huelva, Spain; Department of Earth Sciences, Faculty of Experimental Sciences, University of Huelva, Campus El Carmen s/n, E21007, Huelva, Spain.
Emissions of metals and metalloids as a result of industrial processes, entail a great risk to human health. A high time resolution study on arsenic levels in PM in the city of Huelva (SW Spain) was carried out between September 2021 and September 2022. Hourly data obtained with a near real-time technique based on X-ray fluorescence were inter-compared with other offline analytical instrumentation.
View Article and Find Full Text PDFJ Environ Manage
December 2024
Chemical Oceanography Unit, University of Liège, Liège, Belgium. Electronic address:
Reaching net-zero carbon emissions requires large shares of intermittent renewable energy and the electrification of end-use consumption, such as heating, making the future energy system highly dependent on weather variability and climate change. Weather exhibits fluctuations on temporal scales ranging from sub-hourly to yearly while climate variations occur on decadal scales. To investigate the intricate interplay between weather patterns, climate variations, and power systems, we developed a database of time series of wind and solar power generation, hydropower inflow, heating and cooling demand using an internally consistent modeling framework.
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