A team of Chinese researchers has pioneered a hybrid framework capable of tracking the origins and fluctuations of carbon dioxide emissions from roads in real time, boasting a 30-metre resolution. This is reported by
CGTN, a partner of TV BRICS.
According to experts, this novel approach has the potential to be rolled out across other cities, providing a crucial tool for assessing and promoting carbon dioxide reduction strategies on urban road networks.
According to Wang Li, a researcher at the Aerospace Information Research Institute of the Chinese Academy of Sciences and corresponding author of the study, a significant drawback of existing carbon emission inventories is their limited spatial resolution.
The development of precise monitoring techniques for conducting multifaceted analyses of on-road carbon dioxide levels is therefore considered vital for implementing effective reduction measures.
Wang and his team’s framework combines Panoptic-Artificial Intelligence (Panoptic-AI) with a mobile observation framework to predict hourly on-road carbon dioxide concentrations at the 30-metre resolution. This offers a dynamic, daytime prediction of carbon dioxide increments within urban traffic networks.
This innovative development integrates AI with panoramic cameras, high-precision greenhouse gas analysers, and meteorological sensors to simultaneously collect a range of data. This includes road carbon dioxide concentrations, traffic volumes, building layouts, vegetation cover, and meteorological conditions, all gathered during mobile surveys.
The research team achieved an average identification accuracy of over 93 per cent for emission sources. Furthermore, this framework can quantify the influence of specific factors, such as traffic conditions, surrounding land cover, and meteorological variables, clearly revealing the spatio-temporal dynamics and underlying mechanisms driving carbon emissions.
Photo: Fahroni /
iStock
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