A5031875164- Atmospheric chemistry and aerosols
- Atmospheric aerosols and clouds
- Atmospheric Ozone and Climate
- Atmospheric and Environmental Gas Dynamics
- Air Quality Monitoring and Forecasting
- Air Quality and Health Impacts
- Dielectric materials and actuators
- High voltage insulation and dielectric phenomena
- Remote Sensing in Agriculture
- Polymer Nanocomposites and Properties
- Remote Sensing and LiDAR Applications
- Advanced Antenna and Metasurface Technologies
- Advanced Sensor and Energy Harvesting Materials
- Electromagnetic wave absorption materials
- MXene and MAX Phase Materials
- Climate variability and models
- Vehicle emissions and performance
- Meteorological Phenomena and Simulations
- Water-Energy-Food Nexus Studies
- Geophysics and Gravity Measurements
- Precipitation Measurement and Analysis
- Ocean Acidification Effects and Responses
Sichuan University
2024-2025
University of Toronto
2024-2025
Beijing Normal University
2020-2024
State Key Laboratory of Remote Sensing Science
2020-2024
Lanzhou University
2017-2019
Fugitive road dust (FRD) particles emitted by traffic-generated turbulence are an important contributor to urban ambient fine particulate matter (PM2.5). Especially in areas of developing countries, FRD PM2.5 emissions a serious environmental threat air quality and public health. have been neglected or substantially underestimated previous study, resulting the underestimation modeling PM concentrations estimating their health impacts. This study constructed inventory major inland city China...
Particulate matter with a mass concentration of particles diameter less than 2.5 μm (PM2.5) is key air quality parameter. A real-time knowledge PM2.5 highly valuable for lowering the risk detrimental impacts on human health. To achieve this goal, we developed new deep learning model-EntityDenseNet to retrieve ground-level concentrations from Himawari-8, geostationary satellite providing high temporal resolution data. In contrast traditional machine model, model has capability automatically...
To quantitatively estimate the divergences in natural and anthropogenic dust emission fluxes among different climatic regions, total emissions at global scale from 2007 to 2010 were simulated this study. Despite widely scattered distribution, area of potential sources was found slightly higher than that sources. The distribution 1.61 × 107 km2 January 1.54 July, respectively. contributed 81.0% 19.0% residual. flux 6.34 ± 0.31 μg m−2 s−1 1.01 0.07 s−1, Especially, situated regions. Natural...
The ground-based microwave radiometer (MWR) retrieves atmospheric profiles with a high temporal resolution for temperature and humidity up to height of 10 km. Such are critical understanding the evolution climate systems. To improve accuracy profile retrieval in MWR, we developed deep learning approach called batch normalization robust neural network (BRNN). In contrast traditional backpropagation (BPNN), which has previously been applied MWR retrieval, BRNN reduces overfitting greater...
Artificial intelligence is widely applied to estimate ground-level fine particulate matter (PM2.5) from satellite data by constructing the relationship between aerosol optical thickness (AOT) and surface PM2.5 concentration. However, size properties, such as mode fraction (FMF), are rarely considered in satellite-based modeling, especially machine learning models. This study investigated linear non-linear relationships AOT (fAOT) over five AERONET stations China (Beijing, Baotou, Taihu,...
Abstract Events of stratospheric intrusions to the surface (SITS) can lead severe ozone (O 3 ) pollution. Still, what extent SITS events impact O on a national scale over years remains long-lasting question, mainly due difficulty resolving three key metrics: frequency, duration and intensity. Here, we identify 27,616 China during 2015-2022 based spatiotemporally dense measurements carbon monoxide, two effective indicators SITS. An overview metrics is presented, illustrating large influences...
Despite their extremely small size, fine-mode aerosols have significant impacts on the environment, climate, and human health. However, current understandings of global changes in are limited. In this study, we employed newly developed satellite retrieval data an attentive interpretable deep learning model to explore status, changes, association factors aerosol optical depth (fAOD) fraction (FMF) from 2008 2017. At scale, results show a increasing trend land FMF (2.34 × 10-3/year); however,...
Abstract. The quantification of long-term free-tropospheric ozone trends is essential for understanding the impact human activities and climate change on atmospheric chemistry, but challenged by diversity between satellite tropospheric records sparse temporal spatial sampling ground-based measurements. Here, we explore if a more consistent geographical distribution column (TrOC) can be obtained focusing regional calculated from Regions were determined with correlation analysis modelled TrOCs...
An intense summer dust storm over East Asia during June 24–27, 2010, was systematically analyzed based on the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) a variety of in situ measurements satellite retrievals. The results showed that WRF-Chem captures spatial temporal distributions meteorological factors aerosol well. This is initiated by approach transverse trough northwestern Xinjiang. Because passage cutoff-low, large amount cold air transported southward...
Abstract. The aerosol fine-mode fraction (FMF) is valuable for discriminating natural aerosols from anthropogenic ones. However, most current satellite-based FMF products are highly unreliable over land. Here, we developed a new global land daily dataset (Phy-DL FMF) by synergizing the advantages of physical and deep learning methods at 1∘ spatial resolution covering period 2001 to 2020. Phy-DL comparable Aerosol Robotic Network (AERONET) measurements, based on analysis 361 089 data samples...
Tree-based machine learning and deep approaches are widely applied in ozone (O3) retrieval, but they cannot achieve high accuracy interpretability simultaneously. To overcome this limitation, a tree-based ensemble model, named semi-SILDM, was proposed for O3 prediction at both national (5 km) urban scales (250 m) China. The Moderate Resolution Imaging Spectroradiometer (MODIS) Top of Atmosphere (TOA) measurements were first investigated through significant linear nonlinear relationships with...
Significant levels of aerosols originate from anthropogenic activities, markedly influencing regional air quality and, consequently, human health. Generally, fine-mode aerosol optical depth (fAOD) data are used to evaluate the concentration aerosols. Although moderate resolution imaging spectroradiometer (MODIS) provides fraction (FMF) that can be produce fAOD products, these remain highly uncertain over land, in terms global validation, relative Aerosol Robotic Network (AERONET)...
Coarse-mode aerosol optical depths (cAODs) are critical for understanding the impact of coarse particle sizes, especially dust aerosols, on climate. Currently, limited data length and high uncertainty satellite products diminish applicability cAOD climate research. Here, we propose a spatiotemporal coaction deep-learning model (SCAM) retrieval global land (500 nm) from 2001–2021. In contrast to conventional models, SCAM considers impacts feature interactions can simultaneously describe...
Abstract. A global-scale horizontally- and vertically-resolved ozone climatology can provide a detailed assessment of variability. Here, the Trajectory-mapped Ozonesonde dataset for Stratosphere Troposphere (TOST) is improved updated to recent decade (1970s–2010s) on grid 5° × 1 km (latitude, longitude, altitude) from surface 26 altitude, with most ozonesonde data re-evaluated following ASOPOS-2 guidelines (GAW Report No. 268, 2021). Comparison between independent trajectory-derived shows...
Table S1.Information on the ozonesonde stations used, including each station's ID number, name, locations, number of profiles and measurement period.The in bold fonts are showing a drop-off 2-8% stratospheric ozone total column since 2013.
<title>Abstract</title> Epoxy materials with superior dielectric, mechanical, and thermal performance are of great interesting for electrical equipment power electronics. However, integrating these excellent advantages into epoxy presents a formidable challenge. Herein, we detail simple yet effective strategy the concurrent enhancement dielectric breakdown strength, mechanical toughness, strength by incorporation minimal amount aramid nanofibers (ANFs). It is revealed that robust interfacial...
Abstract. Dust emissions refer to the spatial displacement of dust particles from wind forcing, which is a key component circulation. It plays an important role in energy, hydrological, and carbon cycles Earth's systems. However, most emission schemes only consider natural dust, neglecting anthropogenic induced by human activities, led large uncertainties quantitative estimations numerical modeling. To fully mechanisms emissions, both indirect direct were constructed developed study....