Atmospheric Composition and Climate
Nexus between air pollution and climate change
Welcome to the Wang Research Group at Stanford!
Recent Research Highlights
Climate Impacts of Regional Clean-air Strategies
Our recent Nature Communications paper reveals that, for an unexpectedly long time through ~2070, China’s air pollutant reductions can cause a large global surface temperature increase that almost fully offsets the cooling from concurrent CO2 emission reduction. A comprehensive and fully coupled Earth system model and recently updated future anthropogenic emission scenarios are employed to evaluate the climate impacts of China’s carbon neutrality and pollution mitigation strategies over a realistic and policy-relevant timescale.
The Rising Risk of Pacific Hurricane Rainfall
In our recent Nature Climate Change paper, we employ physics-based synthetic TC downscaling and rainfall prediction models and estimate that the rising Eastern Pacific sea surface temperature will increase the likelihood of TC related heavy rainfall events such as Hurricane Hilary (2023) by about 100% by the end of this century. Coupling the downscaled TC rainfall and a landslide hazard model, we further project a widespread increase in landslide hazard exposure. Media coverage by Stanford Report.
Review on Air Pollutants and Climate Forcers
Our recent paper on Reviews of Geophysics synthesizes the latest progress in understanding changes in short-lived atmospheric compositions, that is, aerosols, ozone, methane, and nitrogen oxides (NOx), in response to COVID-19 induced emission reductions and the associated climate impacts on regional and global scales. It reviews the detection and attribution methods adopted by COVID research and discusses the science implications for future research and policy guidances on emission controls.
New Particle Formation During Heat waves
Wang Lab recently contributed to a Science paper (featured by the journal cover) showing unexpected new particle formation events during heat waves. Measurements and quantum chemical calculations reveal a kinetic pathway for supramolecular nanoparticle production by organic acids, an important consideration for assessing the potential impacts of new particle formation on public health and climate in a warming world in which heat waves are becoming more frequent and intense..
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 single-particle-level observations reveal multi-level microphysical complexities in BC-containing particles, and suggest likely overestimated BC absorption in current aerosol-climate models. Our another recent paper on JAMES develops an improved aerosol optical model in a global climate model to better account for those observations.
ML of Pullution Source Apportionment
We introduce a machine learning (ML)-based source apportionment model that leverages multiscale aerosol composition data to achieve near-real-time tracking and accurate quantification of PM2.5 sources in our recent EST paper. Models show strong generalization potential and identify distinctive pollution sources driven by different socio-environmental factors. The findings emphasize potential bottlenecks in further urban emission reductions to meet increasingly stringent PM2.5 standards and demonstrate the ability of ML models to support timely policy-making.