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We are focusing on:

Nexus between air pollution and climate change

Our Research

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Welcome to the Wang Research Group at Stanford!

We are looking for new graduate students and postdoctoral fellows to join us! Learn more

Recent Research Highlights

AI/ML Boost Pollution and EJ Assessment

Air pollution in metropolitan areas varies with city-level, urban-rural, and neighborhood-level disparities. Our recent EST paper introduces a machine-learning approach that leverages the real-world dynamic traffic profiles to continuously estimate community-level year-long air pollutant (nitrogen dioxide, maximum daily 8-h average ozone, and fine particulate matter). The model shows the ability to capture the traffic-induced exposure disparities and significantly improve residents’ exposure to PM2.5, especially for disadvantaged communities.

Insight of Physical Biases Using Simpler GCM

Marine boundary-layer clouds remain poorly predicted in global climate models due to multiple entangled uncertainty sources. Our recent ACP paper uses the in situ observations from a recent field campaign to constrain and evaluate cloud physics in a simplified version of climate model. Progress and remaining issues in the cloud physics parameterizations are identified. We systematically evaluate the impacts of large-scale forcing, microphysical scheme, and aerosol concentrations on the cloud property.

Factory in middle of corn field

Pollution and Climate Change on Crops

Our recent paper published on Earth's Future develops a robust crop yield prediction model and reveals a critical role of particulate pollution in determining annual crop yields. The present study demonstrates the co-benefit of the recent air pollution control policy from agriculture and food perspectives. However, this benefit will eventually be diminished after the air pollution becomes alleviated in the full scale, while persisting or even exacerbated global warming will pose larger threat on the future food security.

Climate Driver of Carbon Update by Forests

By leveraging the emerging high-resolution measurements of solar-induced chlorophyll fluorescence (SIF) from contemporary satellites, our recent GCB paper shows that the dependence of SIF on climate variables is highly heterogeneous, with two regimes identified: water and energy limited. We find that the coupling between SIF and water supply increases with the mean dryness, while the current suite of vegetation models fail to capture it, casting doubt on the projections of future changes in carbon dynamics.

Direct Observational Constraints on Black Carbon Forcing

Black carbon (BC) is the largest warming agent amoung all aerosol species. Our recent paper on One Earth based on our particle level observations reveal multi-level microphysical complexities in BC-containing particles, and these explain the lower observed BC absorption. Our another recent paper on JAMES develops an improved aerosol optical model in a global climate model to better account for those observations.

Car driving down the road in a snow storm

Air Cleaning Suppressed Winter Extremes

Anthropogenic aerosol emissions decreased over North America and Europe but increased over Asia since the 1970s. Our recent paper on Nature Climate Change revealed that this aerosol forcing caused jet stream winds to shift poleward over the Atlantic, decreasing planetary wave activity and partially inhibiting extreme winter weather over northern Eurasia. It stresses the importance of anthropogenic aerosols and their spatiotemporal variability in assessing the drivers of extreme weather in historical and future climate.

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