Zhonghua Zheng

Assistant Professor in Data Science & Environmental Analytics

The University of Manchester

United Kingdom

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Dr. Zhonghua Zheng is an Assistant Professor in Data Science & Environmental Analytics at The University of Manchester, UK. His research focuses on the quantitative impacts of climate change, air quality, and urban environmental dynamics, as reflected in his recent articles on surface ozone pollution and urban flood datasets. He employs advanced modeling techniques and data-driven approaches to address critical environmental challenges.

Zhonghua Zheng

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Articles (20)

Quantitative impacts of dominant large-scale circulation systems on surface ozone pollution in China

Data-Driven Detection of Nocturnal Pollen Fragmentation Triggered by High Humidity in an Urban Environment

Human–Earth system interactions under climate change

Integrating Simulations and Observations: A Foundation Model for Estimating the Aerosol Mixing State Index

Integration and execution of Community Land Model Urban (CLMU) in a containerized environment

Absorption enhancement and shielding effect of brown organic coating on black carbon aerosols

Improved Crop-specific NOx Emissions from Croplands in Southeast Asia over 1980–2019

Creating a national urban flood dataset for China from news texts (2000–2022) at the county level

Improving Urban Climate Adaptation Modeling in the Community Earth System Model (CESM) Through Transient Urban Surface Albedo Representation

Uncertainty Quantification in Reduced‐Order Gas‐Phase Atmospheric Chemistry Modeling Using Ensemble SINDy

A machine learning approach targeting parameter estimation for plant functional type coexistence modeling using ELM-FATES (v2.0)

Morphology and Fractal Dimension of Size‐Resolved Soot Particles Emitted From Combustion Sources

Automated Machine Learning to Evaluate the Information Content of Tropospheric Trace Gas Columns for Fine Particle Estimates Over India: A Modeling Testbed

Quantifying the effects of mixing state on aerosol optical properties

Improving the WRF/urban modeling system in China by developing a national urban dataset

Quantifying the structural uncertainty of the aerosol mixing state representation in a modal model

Estimating Submicron Aerosol Mixing State at the Global Scale With Machine Learning and Earth System Modeling

Water uptake and optical properties of mixed organic-inorganic particles

A narrative review on environmental impacts of cannabis cultivation

Large model structural uncertainty in global projections of urban heat waves

Collaborators (5)

Matthew West

Christopher Tessum

Caroline Jay

Hugh Coe

Congbo Song

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