Abstract
A new method for the estimation of initial conditions (ICs) in a PM2.5 transport adjoint model is proposed in this paper. In this method, we construct the field of ICs by interpolating values at independent points using the surface spline interpolation. Compared to the traditionally used linear interpolation, the surface spline interpolation has an advantage for reconstructing continuous smooth surfaces. The method is verified in twin experiments, and the results indicate that this method can produce better inverted ICs and less simulation errors. In practical experiments, simulation results show good agreement with the ground-level observations during the 22nd Asia-Pacific Economic Cooperation summit period, demonstrating that the new method is effective in practical application fields.
Highlights
In recent years, air pollution has escalated to hazardous levels in Chinese cities
The surface spline interpolation (SSI) enables the mean absolute gross error (MAGE) between the prescribed and inverted initial conditions (ICs) reduced by 81.99%, which is 4.58% better than the results obtained from the CI
The CI gets the mean normalized gross error (MNGE) reduced to 6.66%, while the SSI gets the MNGEs reduced to 6.09%
Summary
Air pollution has escalated to hazardous levels in Chinese cities. Among numerous types of air pollution, PM2.5 (fine particles with diameter of 2.5μm or less) is considered the most threatened kind to life expectancy and public health (e.g., [1,2,3,4]). A background value (a small constant) was given to the model with the first few days as the spin-up period to minimize the influence of initial conditions by Fu et al [12] Another efficient and accurate way to estimate the ICs is through data assimilation using the adjoint method (e.g., [13,14,15,16,17]). Data assimilation provides a configuration for combining observations and models to form an optimal initial model state In this method, uncertain model parameters can be constrained by minimizing the distance between the model simulations and observations. Due to its proved superior performance, the surface spline interpolation (SSI) is applied to inversion of ICs with a PM2.5 transport adjoint model in this study.
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