Quantifying rice dry biomass to determine the influence of straw burning on BC and NO2 emissions in the Hanoi metropolitan region

Abstract

The urban setting notwithstanding, rice cultivation prevails on the outskirts of Hanoi, with the burning of rice straw in the fields posing a significant challenge. Therefore, it is crucial to conduct spatial mapping of rice distribution, assess dry biomass, and determine emissions from rice straw burning within Hanoi city. The efficacy of the deep convolutional neural networks (DCNN) model has been evident in accurately mapping the spatial distribution of rice in Hanoi, where rice cultivation extensively thrives in suburban areas. In the tropical climate of Vietnam, data derived from synthetic aperture radar (SAR) could serve as a valuable resource for mapping rice fields. Additionally, the amalgamated model, Ant Colony Optimization-eXtreme Gradient Boosting (ACO-XGBoost), could serve as a potent instrument in gauging the aboveground biomass (AGB) of rice within this urban center. The current research reveals the spatial distribution of rice biomass in Hanoi city. Among the six levels of the rice biomass distribution map, the majority of regions in Hanoi city were dominated by the fifth tier, ranging between 3.0 and 4.0 kg/m². This emerges as a pivotal source of emissions impacting the atmospheric quality of the city. It should be emphasized that the incidence of rice straw burning remains substantial, exceeding 80% in the monitored districts of Hanoi city, notably higher in proximity to the city center. These findings serve a significant function for management and policy making to generate data and calculate air pollution levels in Hanoi.