Mixing State And Morphology Of Black Carbon Aerosol In The North China Plain

Black carbon(BC)aerosol in the atmosphere has a strong light-absorbing capacity and heating effect,which can have a significant impact on global and regional climate through direct and semi-direct effects,and also affect atmospheric pollution processes by altering the thermal structure of the boundary layer.There is still considerable uncertainty in the current understanding of the regional climate and environmental effects of BC,and in particular,there is considerable disagreement in the assessment of the radiative effects of BC.The main reason is that the morphology and mixed state of the black carbon changes considerably with the aging of the black carbon during atmospheric transport,resulting in changes in its physicochemical properties.The North China Plain is one of the most polluted regions in China,but information about BC mixing state and morphology in this region is currently scarce due to the limitation of observation technologies.Therefore,the study of the mixing state and morphology of BC aerosol in the North China Plain is an important basis for the accurate assessment of the environmental climate effects of BC and the formulation of effective atmospheric haze control policies.In this thesis,a new toolkit for parallel processing of the Single-particle Soot Photometer(SP2)data is built based on the principle of SP2,which improves some existing data processing algorithms.The new toolkit,written in the open-source Python language,has an "out-of-the-box" feature that can be deployed on high-performance computer clusters for parallel computing,greatly improving the efficiency and accuracy of SP2 data processing.The new toolkit can efficiently and accurately obtain the mass and mixing state of BC(single particle).Based on this,this thesis also proposes a new algorithm for distributions of BC particle optical sizing and mixing state.The new algorithm retrieves the concentration distributions of BC particle optical sizing and coating thickness according to different BC particle core size and its mixing state.This new algorithm reduces the impact of systematic and random errors during instrumental measurements and calculations,improving the efficiency of SP2 data utilization and the accuracy of BC mixing state information.Using the newly built SP2 data parallel processing toolkit and data-retrieving algorithm,this thesis discusses the particle size distributions of BC and the distributions of mixing states under different meteorological conditions,different emission sources and compound pollution conditions based on the data obtained from the winter 2018 campaign in the North China Plain.Furthermore,this thesis also reproduces an existing SP2-based black carbon morphology classification(Coated-type and Attached-type)algorithm and discusses the technical limitations in the algorithm.Through this algorithm,the thesis discusses the actual morphological characteristics of BC in the North China Plain.The results show that most of the BC particles in the North China Plain are Coated-type,and only a small fraction of the BC particles is Attached-type.