Improvements on Gaussian mixture model and its application in identifying aerosol types in two major cities in the Yangtze River Delta, China.

Accurately identifying the authentic local aerosol types is one of the fundamental tasks in studying aerosol radiative effects and model assessment. In this paper, improvements were made to the traditional Gaussian Mixture Model, leading to the following results: 1) This study introduces several improvements to the traditional Gaussian Mixture Model (GMM), referred to as M-GMMs. These improvements include the incorporation of multivariate kurtosis coefficients, Mahalanobis distance instead of Euclidean distance, and weights of variables.

[Establishment and Spatial Distribution of S/IVOCs Emission Inventory in Jiangsu Province in 2019].

The semi-/intermediate volatile organic compound (S/IVOCs) emissions inventory of Jiangsu province was established in 2019 using the activity data of various S/IVOCs emission sources, emission factors, and an estimation method. S/IVOCs emissions for each source and city in Jiangsu province were analyzed. The total amount of S/IVOCs emissions in Jiangsu province in 2019 was 637.