About

Yang Zhang is an Assistant Professor in the Department of Textile Engineering, Chemistry and Science at NC State University. His research develops fluorescent and stimuli-responsive materials, as well as single-molecule methods to color-map and engineer the nanoscopic biological and man-made world. His work particularly focuses on nanofiber networks at the subcellular level, including DNA, cytoskeleton, and cell membranes. Zhang is interested in imaging biocompatible textile nanofibers and understanding their nanoscopic structure-function relationships for biomedical and energy-related applications. His research aims to generate innovative molecular constructs with specific photochemical and photophysical properties to enable high-throughput multiplexed single-molecule tracking of proteins in live cells, contributing to advancements in super-resolution microscopy and cellular imaging techniques.

Research topics

• Geography
• Meteorology
• Environmental science
• Agroforestry
• Geology
• Environmental planning
• Remote sensing
• Environmental resource management
• Climatology
• Atmospheric sciences
• Agronomy
• Physics
• Ecology
• Biology

Selected publications

• Multi-year evaluation and application of the WRF-chem model for two major urban areas in Brazil - Part I: Initial application and model improvement

  Atmospheric Environment · 2025-10-28

  articleOpen accessCorresponding

  High-resolution retrospective simulations of air quality can generate O 3 and PM 2.5 concentrations to estimate their health effects and establish a baseline to assess the impacts of future climate and emission scenarios. To this end, the Weather Research and Forecasting Model coupled with Chemistry (WRF-Chem) is applied to a triple-nested domain over Brazil, with a high spatial resolution of 3-km over the metropolitan areas of São Paulo (MASP) and Rio de Janeiro (MARJ) for the period of 2012–2016. This work is presented in two-part papers. Part I describes an initial application and evaluation of WRF-Chem for August 2012 to study the impacts of improved inputs and wind speed correction parameterization options on the model performance. These simulations aim to improve the model's accuracy in reproducing the observed meteorological variables and air pollutant levels. The model results with updated land use and cover and urban fraction show a lower positive bias in temperature at 2-m. Updated elevation based on high-resolution (30-m) data reduces the positive bias on wind speed at 10-m for MARJ. The modified wind speed correction reduces the systematic bias of wind speed at 10-m for all domains. WRF-Chem using the combined emissions based on global and local inventories performs well with lower bias and better temporal and spatial representations of historical concentrations of major air pollutants than those using global emissions only. These sensitivity simulations identify the best possible model inputs and wind speed correction parameterization option for simulations for the period of 2012–2016, which will be presented in Part II paper. • Improved model skill by updating land use, urban fraction, and elevation datasets for key domains. • Reduced wind speed bias using an updated wind speed correction parameterization scheme. • Better captured pollutant levels using global and local emission inventories with new time profiles. • Enhanced agreement with O 3 and PM 2.5 observations, lowering model biases after improvements. • Validated model results with surface and satellite meteorological and chemical observations.

  PublisherDOI

• A Mine Water Inrush Source Identification Method Based on IWOA-SVM

  Mine Water and the Environment · 2025-11-24 · 2 citations

  article
  PublisherDOI

• Human Health Impacts of Energy Transitions across the United States among Sociodemographic Subpopulations for the Year 2050

  Environmental Science & Technology · 2025-06-11 · 2 citations

  article

  Strategies to reduce greenhouse gas emissions may provide health benefits through improved air quality, yet these benefits might not be equitably distributed. Understanding these cobenefits and who receives them can aid policymakers in prioritizing mitigation strategies. We investigated four future energy scenarios (port electrification, electric vehicles, natural gas, energy efficiency) and a business-as-usual scenario to determine how changes to ambient fine particle (PM2.5) levels impact health within the contiguous United States (U.S.) by region, race/ethnicity, urbanicity, and income. We also investigated how methodological assumptions affect findings. Our projections of avoided mortalities from energy transition policies range from 67,011 (95% CI: 45,692, 82,397) to 81,003 (55,286, 99,532) in 2050. The monetized health benefits from avoided mortalities and hospitalizations range from $785.8 billion to $949.9 billion/year. These benefits vary by region and subpopulation, with Black, suburban, and less wealthy Americans experiencing higher percent avoided mortality across scenarios. Results were sensitive to assumptions for future concentration–response functions relating pollution levels to health, baseline incidence rates, and population projections. Our findings indicate energy policies transitioning from fossil fuel production in the U.S. provide substantial health and economic benefits that vary across populations and help reduce environmental health inequities in exposure and associated morality.

  PublisherDOI

• The impact of air pollution on influenza incidence in high-altitude regions: a time-stratified case-crossover study based on Qinghai Province

  International Archives of Occupational and Environmental Health · 2025-01-28 · 1 citations

  article1st authorCorresponding
  PublisherDOI

• The correlation mechanism and transmission path of green regeneration of urban industrial brownfields from the perspective of social-ecological system resilience

  Ecological Indicators · 2025-06-16 · 3 citations

  articleOpen access1st author

  • Introduce the social-ecosystem resilience theory to enrich the research system of industrial brownfields green regeneration. • Construct the influencing factor system of green regeneration of industrial brownfields. • Using DEMATEL-AISM to study correlation and transmission path in industrial brownfield social-ecological systems. As a bearing space for urban social-ecological systems, industrial brownfields have exposed dual vulnerabilities in the social and ecological sectors. Therefore, this study introduces social-ecosystem resilience theory, which is pivotal for transforming industrial brownfields into a more resilient and robust green regeneration mode. From the perspective of social-ecological system resilience, a system of factors influencing green regeneration in industrial brownfields was constructed. Using the DEMATEL-AISM model, this study investigated the internal correlation mechanism and transmission path of the social-ecological system, providing valuable insights for the green regeneration of industrial brownfields. The findings reveal that (1) DEMATEL identifies key factors of green regeneration in industrial brownfields, including natural resource endowment, soil remediation ability, water treatment ability, regional quality, living service ability, multiple-input mechanisms, economic trends, green regeneration strategies, and green regeneration technologies. (2) The AISM clarifies the hierarchical transmission paths between factors. The seven levels were categorized into essential, transitional, and surface causes, and the resilience response relationship of the key factors was analyzed. These results provide valuable guidance for green regeneration in industrial brownfields. The coupled interaction of social-ecological systems promotes the resilient and sustainable progression of green regeneration.

  PublisherDOI

• Assessing air pollution exposure disparities in disadvantaged communities of Greater Boston: a new cumulative environmental justice score system

  Environmental Research Letters · 2025-02-03 · 3 citations

  articleOpen access

  Abstract Disadvantaged communities in the U.S. experience higher levels of air pollution, leading to increased environmental justice (EJ) challenges. In this work, we combine socioeconomic metrics with spatially interpolated fine particulate matter and ozone concentrations from fifty-nine low-cost sensors and nine reference monitors to investigate inequality in air pollution exposure among different population groups in Greater Boston. The results indicate that the disadvantaged groups are exposed to higher levels of air pollution. Air pollution is concentrated in the center of Boston, Cambridge, Chelsea, and Everett, corresponding to high population density and anthropogenic activities. We further assess the environmental equality by reconstructing the EJ map for Massachusetts using median household income, percentage of minority, and percentage of limited English speaking as indicators. The EJ blocks are clustered in large cities across Massachusetts. Many communities in Greater Boston are classified as EJ communities due to the high percentage of minorities. Chelsea and Everett face more severe EJ issues, with most of their communities exceeding multiple EJ indicators. Additionally, we introduce and demonstrate a new method for determining EJ communities by utilizing the multi-criterion framework to calculate the cumulative EJ score for every census block, integrating air quality with socioeconomic indicators, and each indicator can be viewed as a policy action. Chelsea, Everett, and Lynn consistently exhibit the highest EJ scores with no improvements over the years. The EJ score system provides the time evolution to assist authorities and the residents in tracking the progress in improving the EJ scores of their communities. The method indicates the strength of the efforts needed to maintain or improve the EJ scores for achieving better EJ in the communities, allowing authorities to take immediate actions to improve the environmental well-being of vulnerable communities.

  PublisherOA PDFDOI

• Planar vs. Vertical Dominance? A Nonlinear Analysis of the Urban Landscape-Land Surface Temperature Nexus

  Applied Spatial Analysis and Policy · 2025-07-15 · 4 citations

  articleOpen access

  Abstract Urban landscape modifications are proposed as a potential solution to mitigate urban heat islands (UHIs). Previous research has explored the effects of planar and vertical urban landscape characteristics on land surface temperature (LST). However, these studies predominantly assume a yet-to-be-validated linearity in these effects, and overlook the multifaceted nature of these characteristics. As a result, the nuanced impact of urban landscapes and the accurate relative importance of planar versus vertical characteristics in shaping LST remain unclear. This study, focusing on Wuhan, China, investigates the nonlinear associations between planar and vertical urban landscapes and LST using random forest models. Our findings indicate that planar landscape characteristics contribute more significantly to LST variation than vertical characteristics (73% vs. 11%). Nevertheless, despite the seemingly small contribution of vertical characteristics, their impact is nearly equivalent to that of location characteristics (12%) and substantially surpasses that of socioeconomic factors (4%). Water area proportion, building density, greenspace proportion, and floor area ratio emerge as the most influential urban landscape characteristics. Moreover, our results reveal prevalent but distinct nonlinear relationships between urban landscapes and LST, identifying four patterns: L−/inverted-L- shape, stepwise-decline−/increase, inverted-U-shaped, and N-shaped patterns. Our research provides valuable insights into multidimensional urban planning strategies for effective UHI mitigation. Taking into account the revealed nonlinearity, we also propose planning strategies to address the complex challenges of regulating urban thermal environments.

  PublisherOA PDFDOI

• Assessing health risks and socioeconomic disparities associated with ambient air pollution and point sources across the United States

  Environmental Pollution · 2025-04-26 · 9 citations

  articleOpen accessSenior authorCorresponding

  Air quality in the United States (U.S.) has significantly improved over the last few decades. Nevertheless, many parts of the country still suffer from high levels of air pollution, including numerous non-attainment areas. This study aims to provide a systematic analysis to quantify the impact of air pollution on human health across the entire U.S. By combining the 2023 Centers for Disease Control and Prevention health surveys, criteria air pollutants, and socioeconomic status at the census tract level, we seek to (1) assess the impacts of air pollution on human health, and (2) investigate environmental health and air pollution disparities across the U.S. Our analysis suggests that fine particulate matter (PM 2.5 ) is associated with most diseases, while ozone (O 3 ) is highly correlated with the prevalence of cancer and kidney disease. Sulfur dioxide (SO 2 ) is positively correlated with multiple health outcomes, whereas nitrogen oxide (NO) shows mixed correlations across different diseases. Health risks significantly increase as the levels of PM 2.5 and O 3 exceed 14 μg m −3 and 40 ppb, respectively. Furthermore, there is a strong correlation between disease prevalence, air pollution levels, and socioeconomic status. Minority and low-income groups across the U.S. are exposed to higher levels of PM 2.5 and are prone to greater health risks, including asthma, high blood pressure, mental health, physical health, diabetes, and kidney disease. Notably, individuals exposed to PM 2.5 levels greater than 9.0 μg m −3 have a higher risk of self-rating their health as poor status (RR: 1.202, 95 % CI: 1.200, 1.203). Residents living within a 5-km radius of point source emissions from the oil and gas sector experience significant health impacts, particularly to naphthalene and other polycyclic aromatic hydrocarbons emitted during oil and gas production. This study highlights significant health disparities driven by environmental pollution inequality, impacting low-income and minority groups across the U.S. • Health risks rise significantly when PM 2.5 exceeds 14 μg m −3 and O 3 exceeds 40 ppb. • Residents within 5-km of point source emissions experience elevated health risks. • Disadvantaged groups face disproportionately higher exposure and worse health. • Risk ratios confirm pollutant exposure increases disease prevalence. • Findings call for targeting point sources and addressing health disparities.

  PublisherDOI

• Multi-year evaluation and application of the WRF-chem model for two major urban areas in Brazil part II: Multi-Year evaluation and urban-centric analysis

  Atmospheric Environment · 2025-11-01

  articleOpen accessCorresponding

  In this part II paper, the Weather Research and Forecasting Model coupled with Chemistry (WRF-Chem) described in the Part I paper is applied for 2012-2016 at 36-km, 9-km, and 3-km grid resolutions over Brazil, the Southeast region, and metropolitan areas of São Paulo (MASP) and Rio de Janeiro (MARJ), respectively, and evaluated using meteorological and chemical observations from surface stations and satellite retrieval. Meteorological performance is acceptable, with good performance for temperature (MBs < 0.2°C for 9-km and 3-km) and precipitation (NMBs within ±15%) and acceptable performance for most cases for absolute humidity (MBs up to 1 g/kg) and wind speed (NMBs up to 1.5 m/s). The model results show good agreement with satellite observations of radiation (GLW, GSW, OLR, and SWDOWN) and cloud fraction, however, for other cloud-related variables (LWCF, SWCF, CCN, COT, CWP, and CDNC) the model show reasonable results. The maximum 8-hour average O 3 performance at 3-km is good (NMBs within ±6.4%) but the model underpredicts 8-hour moving average O 3 (NMB=-16.2% for MASP and NMB=-29.9% for MARJ). The PM 2.5 performance at 3-km is in good agreement with observations in MASP in terms of composition and biases (NMBs=-6.2% for MASP and NMB=-3.6% for MARJ). Overall, the results show reasonably good spatiotemporal agreement with the observations for meteorology and air quality. These results will be used to study the health impact of O 3 and PM 2.5 and to serve as the baseline for assessment of the impact of future emission scenarios in future work.

  PublisherDOI

• Mineral Deposition from Liquid Precursors Triggered by Complementary Polyelectrolytes

  ChemRxiv · 2025-12-10

  articleOpen access

  Polymer-induced liquid precursors are hydrated, metastable, amorphous droplets rich in insoluble ionic compounds; they form in aqueous solutions that are supersaturated with mineral ions in the presence of charged polymers that delay the onset of crystal nucleation. This work reports that rapid crystallization of a range of inorganic mineral salts can be triggered by the addition of polycations to polyanion-stabilized precursor solutions that would otherwise be stably amorphous for over ten days. In complex coacervate systems, entropic gains drive the competitive displacement of small (e.g.) cationic species from anionic binding partners by larger molecules with more positive charges. We build evidence that the constituents of the stabilized mineral salt are displaced from the stabilizing polyanion by the added polycation in a similar manner. By exposing liquid precursor solutions to arrays of polycationic hydrogels, we demonstrate the ability to deposit crystals in a site-selective manner, enabling spatial control over mineral formation.

  PublisherDOI

Recent grants

• Climate Mitigation and Earth System Management from Local to Global Scale: Modeling Technology-Driven Futures

  NSF · $2.3M · 2011–2017

• CAREER: Forecasting Chemical Weather with a Coupled Meteorology-Chemistry Model System: Research and Education Challenges

  NSF · $693k · 2004–2011

Frequent coauthors

• Kai Wang

  China Geological Survey

  44 shared

• L. Ruby Leung

  Pacific Northwest National Laboratory

  33 shared

• Kebin He

  Tsinghua University

  27 shared

• Qiang Zhang

  Nanchang Institute of Technology

  20 shared

• Athanasios Nenes

  École Polytechnique Fédérale de Lausanne

  20 shared

• Khairunnisa Yahya

  National Environment Agency

  18 shared

• Patrick Campbell

  Lawrence Livermore National Laboratory

  17 shared

• Michelle L. Bell

  University of Washington

  16 shared

Labs

• Research Lab at Wilson College of TextilesPI