Rapid Adaptive Optimization Model for Atmospheric Chemistry (ROMAC) v1.0
Jiangyong Li,Chunlin Zhang,Wenlong Zhao,Shijie Han,Yu Wang,Hao Wang,and Boguang Wang
Jiangyong Li
Australia–China Centre for Air Quality Science and Management (Guangdong), Institute for Environmental and Climate Research, Jinan University, Guangzhou, 511443, China
Guangdong Provincial Observation and Research Station for Atmospheric Environment and Carbon Neutrality in Nanling Forests, Guangzhou, 511443, China
Chunlin Zhang
Australia–China Centre for Air Quality Science and Management (Guangdong), Institute for Environmental and Climate Research, Jinan University, Guangzhou, 511443, China
Guangdong Provincial Observation and Research Station for Atmospheric Environment and Carbon Neutrality in Nanling Forests, Guangzhou, 511443, China
Wenlong Zhao
Australia–China Centre for Air Quality Science and Management (Guangdong), Institute for Environmental and Climate Research, Jinan University, Guangzhou, 511443, China
Shijie Han
Australia–China Centre for Air Quality Science and Management (Guangdong), Institute for Environmental and Climate Research, Jinan University, Guangzhou, 511443, China
Guangdong Provincial Observation and Research Station for Atmospheric Environment and Carbon Neutrality in Nanling Forests, Guangzhou, 511443, China
Yu Wang
Australia–China Centre for Air Quality Science and Management (Guangdong), Institute for Environmental and Climate Research, Jinan University, Guangzhou, 511443, China
Air Quality Studies, Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Hong Kong, China
Australia–China Centre for Air Quality Science and Management (Guangdong), Institute for Environmental and Climate Research, Jinan University, Guangzhou, 511443, China
Guangdong Provincial Observation and Research Station for Atmospheric Environment and Carbon Neutrality in Nanling Forests, Guangzhou, 511443, China
Australia–China Centre for Air Quality Science and Management (Guangdong), Institute for Environmental and Climate Research, Jinan University, Guangzhou, 511443, China
Guangdong Provincial Observation and Research Station for Atmospheric Environment and Carbon Neutrality in Nanling Forests, Guangzhou, 511443, China
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Photochemical box models, crucial for understanding tropospheric chemistry, face challenges due to slow computational efficiency with large chemical equations. The model introduced in this study, ROMAC, boosts efficiency by up to 96 % using an advanced atmospheric solver and an adaptive optimization algorithm. Moreover, ROMAC exceeds traditional box models in evaluating the impact of physical processes on pollutant concentrations.
Photochemical box models, crucial for understanding tropospheric chemistry, face challenges due...
