Research framework

Coupling between Atmospheric Composition and Meteorological Processes in the Boundary Layer

Academic positioning: Interactions between Atmospheric Chemical and Meteorological Processes

Overview

Meteorological processes alter the accumulation, transport, and chemical transformation of atmospheric constituents. Conversely, the chemical composition and physicochemical properties of aerosols can affect hygroscopic growth and activation, thereby participating in fog processes and visibility changes. My research examines this coupling between atmospheric composition and meteorological processes in the boundary layer.

The research proceeds in two directions: how meteorology influences atmospheric chemistry, and how atmospheric chemistry participates in meteorological processes. These directions are not presented as one established causal chain; together, they address how atmospheric composition and meteorological states interact within the boundary layer.

Conceptual framework for coupling between atmospheric composition and meteorological processes in the boundary layer
Overall research framework · Click to enlarge

Scientific focus

Atmospheric Oxidative Capacity in Meteorology–Chemistry Coupling

Atmospheric oxidative capacity describes the atmosphere's ability to transform and remove trace gases through chemical reactions. It is a key link between meteorological conditions and atmospheric composition.

Radiation, temperature, water vapour, boundary-layer structure, and regional transport jointly affect the production, loss, and distribution of oxidants. Changes in oxidative capacity then regulate pollutant lifetimes and ozone production and, through secondary particle formation and aging, alter aerosol composition, hygroscopicity, and activation potential, thereby potentially contributing to marine cloud–fog microphysics and visibility evolution.

Research direction 01

Atmospheric Oxidation and Co-pollution under Meteorology–Chemistry Coupling

Meteorological processes → Atmospheric chemistry

How do different meteorological states alter atmospheric oxidative capacity and reshape the formation and mitigation response of PM–ozone co-pollution?

Starting from precursor and emission characteristics, this direction integrates local photochemistry, boundary-layer evolution, and regional transport to identify dynamic changes in the oxidation environment, ozone production sensitivity, and co-pollution responses under high-temperature conditions.

  • Meteorological driversHeat, radiation, water vapour, boundary-layer evolution, and transport
  • Mechanism diagnosisRadical cycling, oxidant budgets, and local–regional interactions
  • Pollution responsesOzone sensitivity, secondary particles, and coordinated-control thresholds

Representative research foundations

From emission characteristics and oxidation chemistry to weather-dependent pollution responses

The 2022 eastern China heatwave and ozone pollution

Extreme heat and regional ozone pollution

Examining how high temperatures, stagnant conditions, electricity demand, and emission changes jointly intensified ozone pollution during the record-breaking 2022 heatwave in eastern China.

Effects of volatile chemical products on urban ozone formation

Changing urban precursors and ozone production

Using detailed chemical mechanisms to quantify how volatile chemical products affect radical cycling, peak ozone, and chemical control regimes.

Radical and ozone chemistry in an oilfield region

Observation-constrained oxidation chemistry

Diagnosing radical sources, OH reactivity, ozone budgets, and limiting factors in an oilfield region with an observation-constrained box model.

VOC emission profiles from oil and gas extraction in China

Emission fingerprints and precursor constraints

Using direct VOC observations and source-profile comparisons in Chinese oilfields to constrain the precursor basis of regional oxidation and ozone formation.

Research direction 02

Effects of Marine Aerosol Chemistry on Fog Processes and Visibility

Atmospheric chemistry → Meteorological processes

How do the chemical composition and physicochemical properties of marine aerosols participate in fog microphysics and visibility changes, and how should models represent these effects?

This direction examines marine reactive gases, oxygenated organics, and the aerosol chemical environment. It seeks to identify how aerosol composition, size, hygroscopicity, and activation affect droplet formation, extinction, and low visibility, and to introduce the key chemical processes into marine-fog simulation and prediction.

  • Marine chemical environmentReactive gases, OVOCs, sea salt, and oxidation conditions
  • Key aerosol propertiesComposition, size, hygroscopicity, and activation potential
  • Fog responsesDroplet activation, extinction, visibility, and model biases

Research foundation and emerging questions

From marine oxidation chemistry to aerosol–fog interactions

Coastal OVOCs and aerosol formation

Investigating sources of carbonyls and other reactive marine gases, their oxidation environment, and potential contributions to secondary aerosol.

Aerosol chemistry in marine-fog models

Testing how chemical composition and hygroscopic activation affect fog visibility and model biases, and improving process representations.

Low-temperature Arctic marine environments

Using Arctic OVOC samples to explore oxidation conditions under low temperature and low NOx, and their links to aerosol properties.

Shared methodology

From observed phenomena to mechanism identification and model representation

Methods serve both research directions and connect phenomenon detection, interaction diagnosis, mechanism testing, and prediction improvement.

Field observations

Urban, mountain, coastal, research-cruise, and polar samples

Chemical diagnosis

Oxidative capacity, source attribution, sensitivity, and process budgets

Numerical models

Box, chemical-transport, and meteorology–chemistry coupled models

Multi-source data

Surface observations, satellite retrievals, reanalysis, and trajectories

Data methods

Interpretable machine learning, dynamic thresholds, and forecast correction

Individual studies may span more than one theme. See the Academic Portfolio for the complete record.