About

Dan Li is an Associate Professor and Associate Chair of Faculty Actions at Boston University in the Department of Earth & Environment. He holds a Ph.D. in Civil & Environmental Engineering from Princeton University, obtained in 2013, and a Bachelor's degree in Hydraulic Engineering from Tsinghua University, earned in 2009. His research focuses on urban microclimate, urban hydrology, environmental fluid mechanics, turbulence, atmospheric boundary layer, multi-scale climate modeling, and land-atmosphere interactions. He teaches courses including Introduction to Hydrology, Environmental and Geophysical Fluid Dynamics, and Introduction to the Atmospheric Boundary Layer, contributing to the education of students in the field of Earth and Environmental Sciences.

Research topics

• Environmental science
• Geology
• Ecology
• Climatology
• Biology
• Geography
• Computer Science
• Physical geography
• Botany
• Mathematics
• Traditional medicine
• Psychiatry
• Meteorology
• Atmospheric sciences
• Medicine

Selected publications

• Rethinking Sustainability in <scp>BRICS</scp> : How Economic Policy Uncertainty, Energy Efficiency, and Cultural Integration Shapes Environmental Outcomes

  Sustainable Development · 2026-04-01

  article1st authorCorresponding

  ABSTRACT Global environmental degradation continues to threaten human welfare, biodiversity, and ecosystem stability, particularly in emerging economies where growth pressures remain intense. This study examines the roles of economic policy uncertainty, renewable and non‐renewable energy use, and social globalization in shaping ecological footprints in the BRICS economies Brazil, Russia, India, China, and South Africa over the period 1990– 2024. Using the Method of Moments Quantile Regression estimator, the analysis captures heterogeneous effects across low, middle, and high quantile conditions for BRICS countries. The results confirm a nonlinear inverted U‐shaped relationship between economic growth and ecological footprints, validating the Environmental Kuznets Curve hypothesis within the BRICS bloc. Renewable energy use significantly reduces ecological footprints across most quantiles, while non‐renewable energy consumption increases environmental pressure, particularly at higher footprint levels. Social globalization exerts a mitigating effect on ecological footprints, though its magnitude varies across countries and quantiles. Economic policy uncertainty consistently worsens environmental outcomes by discouraging long‐term investments in clean energy and sustainability. These findings highlight the importance of stable policy environments, accelerated renewable energy transitions, and socially embedded sustainability strategies for achieving climate and environmental goals in emerging economies.

  PublisherDOI

• NSII: a novel soybean identification index based on Sentinel-2 imagery for accurate and efficient soybean mapping

  Frontiers in Plant Science · 2026-04-01

  articleOpen accessSenior author

  Accurate mapping of soybean cultivation areas is crucial for agricultural monitoring, resource management, and food security. However, the spectral overlap between soybean and other crops, such as corn, poses significant challenges for remote sensing-based identification. This study proposes a novel soybean identification index (NSII), which is calculated using the second red-edge band (RE2), the first short-wave infrared band (SWIR1), and the Enhanced Vegetation Index (EVI) derived from Sentinel-2 imagery within the optimal time window identified through spectral feature analysis. NSII was implemented in 12 major soybean producing regions in the United States and China over a three-year period (2020-2022). Experimental results from 2020 to 2022 show that the average accuracy of NSII is 0.85, and the average F1 score is 0.80. Compared with the existing Soybean Mapping Composite Index (SMCI), the accuracy increased by 8 percentage points and the F1 score increased by 6 percentage points. NSII also exhibits strong stability and transferability, with consistent performance across diverse climatic and cropping conditions. This study provides a robust and efficient tool for soybean mapping, offering significant potential for precision agriculture and sustainable resource management.

  PublisherDOI

• Using Issues-based Art Education to Facilitate Middle School Students’ Learning in Racial Issues

  Pennsylvania Libraries: Research & Practice (University of Pittsburgh) · 2026-04-09 · 4 citations

  articleOpen access1st authorCorresponding
  PublisherDOI

• Interdecadal feature and mechanism of global dusty weather

  Atmospheric Environment · 2025-08-12 · 1 citations

  article
  PublisherDOI

• Modeling the Distribution, Impacts, and Mitigation of Anthropogenic Heat in Los Angeles

  2025-12-12

  articleOpen access

  Anthropogenic heat emissions from human energy consumption contribute to the urban heat island (UHI) effect, yet their spatiotemporal distributions and impacts remain uncertain. In this study, we develop a 100 m resolution, hourly anthropogenic heat flux (AHF) dataset for Los Angeles (LA) County and we use the Weather Research and Forecasting (WRF) model to quantify both meteorological impacts of AHF and heat mitigation potential of electrification and energy efficiency (EE) measures. For 2016, annual mean AHF (AHFmean) across LA County was 2.54 W m-2, increasing to 9.65 W m-2 over urban areas. Neighborhood aggregated AHFmean ranged from ~0 W m-2 to more than 30 W m-2; and maximum hourly AHFmean was ~30–40% higher than daily AHFmean. AHF increased mean 2 m air temperature (T2m) by 0.27 ◦C in summer and 0.32 ◦C in winter, and canopy air temperature (Tc) by 1.17 ◦C and 1.56 ◦C, respectively, with localized Tc warming exceeding 4 ◦C in certain neighborhoods. EE measures reduced T2m and Tc by up to 0.16 ◦C and 0.65 ◦C, respectively, under the most aggressive EE scenario, with stronger cooling effects near highways. This study confirms AHF as a major driver of LA’s UHI and introduces key advances, including spatiotemporally resolved traffic AHF and the first quantitative assessment of EE-driven heat mitigation. Our methods are highly transferrable to other cities and underscore the value of high-resolution AHF and meteorological modeling data for targeted impact assessment and mitigation planning.

  PublisherDOI

• Uncertainty in urban climate modeling: Bridging the gap between science and policy

  PLOS Climate · 2025-10-31

  articleOpen accessSenior authorCorresponding
  PublisherDOI

• Global Existence for the Cauchy Problem of the Parabolic–Parabolic–ODE Chemotaxis Model with Indirect Signal Production on the Plane

  Mathematics · 2025-08-15

  articleOpen accessSenior authorCorresponding

  This paper establishes the global existence of solutions to a chemotaxis system with indirect signal production in the whole two-dimensional space. This system exhibits a mass threshold phenomenon governed by a critical mass mc=8πδ, where δ represents the decay rate of the static individuals. When the total initial mass m=∫R2u0dx&lt;mc, all solutions exist globally and remain bounded. In the critical case of m=mc, the global existence or finite-time blow-up may occur depending on the initial conditions. The critical mass obtained in the whole space coincides with that previously derived in radially symmetric bounded domains. A key novelty lies in extending the analysis to the full plane, where the absence of compactness is overcome by constructing a suitable Lyapunov functional and employing refined Trudinger–Moser-type inequalities.

  PublisherOA PDFDOI

• Ground-Based Evaluation of Hourly Surface Ozone in China Using CAM-Chem Model Simulations and Himawari-8 Satellite Estimates

  Remote Sensing · 2025-08-29

  articleOpen access

  Surface ozone pollution poses a significant threat to human health and ecosystems. However, its highly variable spatiotemporal distribution, especially at hourly scales across China, complicates effective risk management. This variability presents substantial challenges for accurate estimation and forecasting, underscoring the importance of evaluating current hourly surface ozone estimation methods. Therefore, this study collaboratively evaluated the performance of chemical transport model simulations and satellite-based estimates of hourly surface ozone concentrations over mainland China in 2019. Using data from 3185 ground monitoring stations operated by the Ministry of Ecology and Environment, as well as six independent observation sites in Hong Kong, Xianghe, Nam Co, Akedala, Longfengshan, and Waliguan, this study found that both datasets exhibited systematic biases and lacked spatiotemporal consistency. The Community Atmosphere Model with Chemistry simulation results exhibited an average relative bias of 23.17%, generally overestimated ozone concentrations in high-altitude regions, but outperformed the satellite-based estimates at the independent sites, while consistently underestimating ozone concentrations in densely populated urban areas. In contrast, the satellite-based estimates performed better in regions with dense monitoring sites, with mean biases typically within 10% of observations, but their accuracy was limited in remote areas due to sparse ground-based calibration. It is particularly noteworthy that both datasets showed deficiencies in capturing extremely high-value events, nighttime ozone variations, and dynamic transport processes, underscoring challenges in the representation of photochemical processes in the model and in the design of satellite estimation algorithms. The results highlight the importance of optimizing model parameterization schemes, improving satellite estimation algorithms, and integrating multi-source data to enhance the accuracy and stability of hourly ozone estimates. This study provides multi-scale quantitative insights into the relative strengths and limitations of different ozone estimation methods, laying a solid scientific foundation for future data integration, regional air quality management, and policy development.

  PublisherOA PDFDOI

• DeepLabV3+ model of semantic segmentation for nanoparticles agglomeration in micro fluidized beds

  Powder Technology · 2025-10-28 · 2 citations

  articleCorresponding
  PublisherDOI

• Background Wind Speeds Outweigh Urban Heat Islands in Downwind Precipitation Enhancement by Cities

  Geophysical Research Letters · 2025-06-14 · 7 citations

  articleOpen access

  Abstract Ample evidence shows that cities can enhance precipitation in the downwind region due to the urban heat island (UHI) effect and the high momentum roughness of urban land. Surprisingly, global observational results show that the downwind enhancement of precipitation caused by large metropolitan areas is weaker under conditions of stronger surface UHIs. This is because stronger UHIs tend to be associated with lower background wind speeds, while the downwind enhancement of precipitation is stronger with higher background wind speeds. These results suggest a competition between thermodynamic and dynamic factors in regulating the downwind enhancement of precipitation, with the background wind speed playing a more important role than the UHI effect. By considering the urban‐rural difference in momentum roughness length, a simple model is utilized to qualitatively explain the link between the downwind enhancement of precipitation and background wind speed.

  PublisherOA PDFDOI

Recent grants

• Collaborative Research: PREEVENTS Track 2: Land-atmosphere feedbacks over urban terrain under heat waves

  NSF · $680k · 2019–2024

• Collaborative Research: The Role of Coherent Structures in Scalar Transport over Heterogeneous Landscapes

  NSF · $356k · 2019–2024

Frequent coauthors

• Gabriel G. Katul

  Duke University

  93 shared

• Sergej Zilitinkevich

  University of Helsinki

  69 shared

• Chongyang Wang

  Guangdong Academy of Sciences

  38 shared

• Zhiqiu Gao

  Nanjing University of Information Science and Technology

  31 shared

• Shuisen Chen

  30 shared

• Elie Bou‐Zeid

  21 shared

• Hong Zhao

  Yunnan Institute of Tropical Crops

  20 shared

• Weilin Liao

  20 shared

Labs

• Environmental Fluid MechanicsPI

Education

• Ph.D.

  Princeton University

  2013

• B.A., Hydraulic Engineering

  Tsinghua University

  2009