Publications by authors named "Bijie Huang"
Article Synopsis
- Particulate matter (PM) and ozone (O) are significant air pollutants that can be influenced by nitrogen oxides, leading to complex interactions in pollution dynamics.
- The study utilized theoretical analysis and machine learning to assess how atmospheric reactive nitrogen affects PM and ozone levels, identifying both co-directional and contra-directional factors that influence their concentrations.
- Recommendations for reducing PM and ozone pollution highlight the importance of tailored strategies: co-directional factors should be addressed simultaneously for effective reduction, while contra-directional factors require careful management to avoid inadvertently increasing one pollutant while reducing the other.
With the rapid development of artificial intelligence, bionic algorithm has been gradually applied in various fields, and neural network has become an important and hot issue in the field of scientific research and engineering in recent years. This article proposes a BP neural network model to predict the capture ability and sensitivity of CO in monoethanolamine (MEA) aqueous scrubbing technique from a 2 × 1,000 MW coal-fired power plant expansion project in eastern China. The predicted values agree well with the experimental data with a satisfactory mean square root error (MSRE) ranging from 0.
View Article and Find Full Text PDF[Study on volatile organic compounds emission of straw combustion and management countermeasure in Wuhan city].
Huan Jing Ke Xue
December 2013
Straw combustion is an important anthropogenic source of volatile organic compounds (VOCs) in China. Emissions of VOCs from straw combustion significantly affect climate forcing and human health. A reliable estimation of VOCs emission from the source is the important prerequisite for emission impact assessment and control strategy in the urban or regional areas.
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