[HTML][HTML] Ground-level ozone pollution in China: a synthesis of recent findings on influencing factors and impacts
Ozone (O3) in the troposphere is an air pollutant and a greenhouse gas. In mainland China,
after the Air Pollution Prevention and Action Plan was implemented in 2013—and despite …
after the Air Pollution Prevention and Action Plan was implemented in 2013—and despite …
[HTML][HTML] 数据驱动的多源遥感信息融合研究进展
张良培， 何江， 杨倩倩， 肖屹， 袁强强 - 2022 - xb.chinasmp.com
多源遥感信息融合技术是突破单一传感器的观测局限, 实现多平台多模态观测信息互补利用,
生成大场景高“时-空-谱” 无缝的观测数据的重要手段. 随着人工智能理论与技术的日益完善 …
生成大场景高“时-空-谱” 无缝的观测数据的重要手段. 随着人工智能理论与技术的日益完善 …
Air quality indicators and AQI prediction coupling long-short term memory (LSTM) and sparrow search algorithm (SSA): A case study of Shanghai
X Liu, H Guo - Atmospheric Pollution Research, 2022 - Elsevier
Air quality indicators and air quality index (AQI) prediction are effective approaches for urban
decision-makers, planners, managers and even city residents to arrange their risk …
decision-makers, planners, managers and even city residents to arrange their risk …
[HTML][HTML] Cooperative simultaneous inversion of satellite-based real-time PM2. 5 and ozone levels using an improved deep learning model with attention mechanism
Ground-level fine particulate matter (PM 2.5) and ozone (O 3) are air pollutants that can
pose severe health risks. Surface PM 2.5 and O 3 concentrations can be monitored from …
pose severe health risks. Surface PM 2.5 and O 3 concentrations can be monitored from …
[HTML][HTML] Joint estimation of PM2. 5 and O3 over China using a knowledge-informed neural network
China has currently entered a critical stage of coordinated control of fine particulate matter
(PM 2.5) and ozone (O 3), it is thus of tremendous value to accurately acquire high …
(PM 2.5) and ozone (O 3), it is thus of tremendous value to accurately acquire high …
[HTML][HTML] Spatiotemporal estimation of hourly 2-km ground-level ozone over China based on Himawari-8 using a self-adaptive geospatially local model
Abstract Ground-level ozone (O 3) is a primary air pollutant, which can greatly harm human
health and ecosystems. At present, data fusion frameworks only provided ground-level O 3 …
health and ecosystems. At present, data fusion frameworks only provided ground-level O 3 …
Explainable and spatial dependence deep learning model for satellite-based O3 monitoring in China
Environmental exposure to surface ozone (O 3) has become a major public health concern.
To accurately estimate the spatial-coverage O 3 from sparse ground-truth data, we here …
To accurately estimate the spatial-coverage O 3 from sparse ground-truth data, we here …
Remote sensing estimation of surface PM2. 5 concentrations using a deep learning model improved by data augmentation and a particle size constraint
Accurate estimation of PM 2.5 concentrations is critical to understanding and counteracting
air pollution. In the past decade, various machine learning models, especially deep learning …
air pollution. In the past decade, various machine learning models, especially deep learning …
LEarning Surface Ozone from satellite columns (LESO): A regional daily estimation framework for surface ozone monitoring in China
Continuously monitoring surface ozone (O 3) spatial distribution and forecasting its
variations are beneficial to improving air quality and ensuring public health in China …
variations are beneficial to improving air quality and ensuring public health in China …
Estimating near-surface concentrations of major air pollutants from space: A universal estimation framework LAPSO
Like many other countries, China is still facing severe air pollution issues after extensive
efforts. The difficulties in deriving near-surface concentrations from satellite measurements …
efforts. The difficulties in deriving near-surface concentrations from satellite measurements …