Members of the Zhao lab at the American Geophysical Union (AGU) in December 2023. Photo courtesy of Lei Zhao.
With climate change driving temperature increases, water scarcity, and limited access to energy in urban areas, it has become more important than ever to understand the relationships between urban areas and their resources.
Lei Zhao, Assistant Professor of Civil and Environmental Engineering at the University of Illinois, works with a team of engineers and climate scientists to model the dynamics between climate change and urbanization. Their research, which has received seed funding from iSEE, helps inform policymakers and urban planners of potential climate solutions.
The software currently used by scientists to predict climate conditions and model land, ocean, and atmospheric dynamics, called the Earth Systems Modeling framework, may be underrepresenting urban environments. Zhao describes it as a “legacy issue,” in which the happenings in an urban environment are too small to cause any discernible changes in large-scale dynamics that traditional models were designed to capture. Additionally, because of the great heterogeneity of urban environments, specific details are often overlooked.
“Chicago is different from New York City. New York City is different from San Francisco. The textures and forms of those cities are not the same,” Zhao said.
There’s a common misconception about the availability of urban climate data. Urban weather stations are not placed in areas that are truly representative of the city’s environment.
“People might think urban environments are very data-rich, but in terms of climatology or meteorology, they’re not,” Zhao said. “When you walk into the city center, you’ll seldom see a weather station there. It’s typically in the airport or in some park, which doesn’t represent urban environments.”
Placing observational sites in truly urban areas causes logistical issues. In the city center, citizens prefer shopping malls and other recreational buildings over weather stations. So the lack of documentation from city centers causes a gap in research between the urban landscape and observational and modeling processes.
To address this, engineers and climate scientists are researching how to use process-based climate modeling and machine learning/artificial intelligence approaches to produce a simulation of climate dynamics that is representative of real urban landscapes. The new hybrid modeling framework leverages the few models that capture urban dynamics and integrates their fully coupled simulations with a physics-informed machine-learning approach.
Together, they provide global multi-model projections of local urban climates under different climate change scenarios, with an assessment of the associated robustness and uncertainties. With this framework, when public health or climate interventionists want to initiate change, they can use a model that is precise to the city of interest.
It’s an unfortunate reality in urban engineering that sustainability sometimes conflicts with resilience. Zhao warns that researchers must aim to strike a balance between strategies that make efficient use of energy and strategies that make cities more resilient to hazards and extremes.
Thankfully, many urban infrastructure experts have spearheaded efforts to prevent cities from being major sources of greenhouse gases while still prioritizing high-quality infrastructure. Zhao notes that targeting urban areas in particular may be the most effective way toward a sustainable future: “75% of final energy use is from cities. They’re hotspots of emission, even though they’re only 2-3% of the land. If we don’t act on cities, we won’t have a sustainable future.”
This urban hybrid modeling project is highly interdisciplinary, featuring a team of experts from different fields. Collaboration between atmospheric scientists and civil engineers helps bring the urban systems model to a broader scale. The two teams have weekly discussions about their research, some of which have led to other urban-related sustainability and climate pursuits.
“Our team has grown,” Zhao said. “For example, this project has led to a larger grant to explore how the wind and concentration of heat in the cities affects mosquitoes, and then how that affects dengue disease.”
When it comes to current research successes, Zhao highlights his students and postdocs and their work on urban humid heat stress (Joyce Yang), urban climate-energy interactions (Cathy Li), urban green stormwater infrastructure (Laura Gray), and global urban data and modeling development (Bowen Fang, Yifan Cheng, and Yiwen Zhang).
“Some of our students are working on nature-based solutions,” he said. “One of those solutions, green stormwater infrastructure, was designed for water infiltration and reduced flooding, but it has other co-benefits. Those benefits are what we are trying to evaluate.”
A long-term goal of this research is to advance global urban science, and consequently, global sustainability.
“I hope to build an advanced understanding of global science that is both fundamental and solution-oriented,” Zhao said.
The research team hopes that these findings will help inform decision-making policies and enable climate-sensitive urban design and engineering. Although cities are currently notorious for being energy-costly, pathogenic hotspots, accurate urban modeling can help transform them into resilient, sustainable, and livable spaces for generations to come.
— Article by iSEE Communications Intern Anjali Yedavalli