Improving NOx emission estimates in Beijing using network observations and a perturbed emissions ensemble
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Published:2022-07-05
Issue:13
Volume:22
Page:8617-8637
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ISSN:1680-7324
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Container-title:Atmospheric Chemistry and Physics
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language:en
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Short-container-title:Atmos. Chem. Phys.
Author:
Yuan LeORCID, Popoola Olalekan A. M.ORCID, Hood ChristinaORCID, Carruthers David, Jones Roderic L., Sun Haitong Zhe, Liu Huan, Zhang Qiang, Archibald Alexander T.ORCID
Abstract
Abstract. Emissions inventories are crucial inputs to air quality
simulations and represent a major source of uncertainty. Various methods
have been adopted to optimise emissions inventories, yet in most cases the
methods were only applied to total anthropogenic emissions. We have
developed a new approach that updates a priori emission estimates by source sector, which are particularly relevant for policy interventions. At its core is a perturbed emissions ensemble (PEE), constructed by perturbing parameters in an a priori emissions inventory within their respective uncertainty ranges. This PEE is then input to an air quality model to generate an ensemble of forward simulations. By comparing the simulation outputs with observations from a dense network, the initial uncertainty ranges are constrained, and a posteriori emission estimates are derived. Using this approach, we were able to derive the transport sector NOx emissions for a study area centred around Beijing in 2016 based on a priori emission estimates for 2013. The absolute emissions were
found to be 1.5–9 × 104 Mg, corresponding to a 57 %–93 % reduction from the 2013 levels, yet the night-time fraction of the emissions was 67 %–178 % higher. These results provide robust and independent evidence
of the trends of traffic emission in the study area between 2013 and 2016
reported by previous studies. We also highlighted the impacts of the
chemical mechanisms in the underlying model on the emission estimates
derived, which is often neglected in emission optimisation studies. This
work paves forward the route for rapid analysis and update of emissions
inventories using air quality models and routine in situ observations, underscoring the utility of dense observational networks. It also highlights some gaps in the current distribution of monitoring sites in Beijing which result in an underrepresentation of large point sources of NOx.
Funder
Tsinghua University Met Office National Centre for Atmospheric Science
Publisher
Copernicus GmbH
Subject
Atmospheric Science
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