1. High resolution temporal profiles in the Emissions Database for Global Atmospheric Research
- Author
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Marilena Muntean, Efisio Solazzo, Ernest Koffi, Ganlin Huang, Greet Janssens-Maenhout, Christian Schieberle, Rainer Friedrich, Diego Guizzardi, and Monica Crippa
- Subjects
Statistics and Probability ,Pollution ,Data Descriptor ,Earth observation ,010504 meteorology & atmospheric sciences ,media_common.quotation_subject ,High resolution ,010501 environmental sciences ,Library and Information Sciences ,computer.software_genre ,01 natural sciences ,Education ,Environmental impact ,Atmosphere ,Air pollutants ,Atmospheric science ,lcsh:Science ,0105 earth and related environmental sciences ,media_common ,Database ,Atmospheric models ,Atmospheric research ,Computer Science Applications ,Greenhouse gas ,Environmental science ,lcsh:Q ,Statistics, Probability and Uncertainty ,computer ,Information Systems - Abstract
Emissions into the atmosphere from human activities show marked temporal variations, from inter-annual to hourly levels. The consolidated practice of calculating yearly emissions follows the same temporal allocation of the underlying annual statistics. However, yearly emissions might not reflect heavy pollution episodes, seasonal trends, or any time-dependant atmospheric process. This study develops high-time resolution profiles for air pollutants and greenhouse gases co- emitted by anthropogenic sources in support of atmospheric modelling, Earth observation communities and decision makers. The key novelties of the Emissions Database for Global Atmospheric Research (EDGAR) temporal profiles are the development of (i) country/region- and sector- specific yearly profiles for all sources, (ii) time dependent yearly profiles for sources with inter-annual variability of their seasonal pattern, (iii) country- specific weekly and daily profiles to represent hourly emissions, (iv) a flexible system to compute hourly emissions including input from different users. This work creates a harmonized emission temporal distribution to be applied to any emission database as input for atmospheric models, thus promoting homogeneity in inter-comparison exercises., Measurement(s)air pollution • greenhouse gas • temporal measurementTechnology Type(s)computational modeling techniqueFactor Type(s)sector • geographic locationSample Characteristic - Environmentclimate systemSample Characteristic - LocationEarth (planet) Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.12052887
- Published
- 2020
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