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
Viewed
Total article views: 2,978 (including HTML, PDF, and XML)
HTML
PDF
XML
Total
BibTeX
EndNote
2,124
724
130
2,978
131
212
HTML: 2,124
PDF: 724
XML: 130
Total: 2,978
BibTeX: 131
EndNote: 212
Views and downloads (calculated since 05 Jul 2023)
Cumulative views and downloads
(calculated since 05 Jul 2023)
Total article views: 2,086 (including HTML, PDF, and XML)
HTML
PDF
XML
Total
BibTeX
EndNote
1,549
429
108
2,086
113
185
HTML: 1,549
PDF: 429
XML: 108
Total: 2,086
BibTeX: 113
EndNote: 185
Views and downloads (calculated since 30 Oct 2023)
Cumulative views and downloads
(calculated since 30 Oct 2023)
Total article views: 892 (including HTML, PDF, and XML)
HTML
PDF
XML
Total
BibTeX
EndNote
575
295
22
892
18
27
HTML: 575
PDF: 295
XML: 22
Total: 892
BibTeX: 18
EndNote: 27
Views and downloads (calculated since 05 Jul 2023)
Cumulative views and downloads
(calculated since 05 Jul 2023)
Viewed (geographical distribution)
Total article views: 2,978 (including HTML, PDF, and XML)
Thereof 2,890 with geography defined
and 88 with unknown origin.
Total article views: 2,086 (including HTML, PDF, and XML)
Thereof 2,053 with geography defined
and 33 with unknown origin.
Total article views: 892 (including HTML, PDF, and XML)
Thereof 837 with geography defined
and 55 with unknown origin.
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...
