A5043284672- Air Quality and Health Impacts
- Vehicle emissions and performance
- Air Quality Monitoring and Forecasting
- Noise Effects and Management
- Gas Sensing Nanomaterials and Sensors
- Municipal Solid Waste Management
- Atmospheric and Environmental Gas Dynamics
- Housing Market and Economics
- Fire effects on ecosystems
- Economic and Environmental Valuation
- Remote Sensing in Agriculture
- Copper-based nanomaterials and applications
- Advanced Photocatalysis Techniques
- Urban Green Space and Health
- Species Distribution and Climate Change
- Acoustic Wave Phenomena Research
- Vehicle Noise and Vibration Control
- Urban Heat Island Mitigation
- Energy and Environment Impacts
- Atmospheric chemistry and aerosols
- Spatial and Panel Data Analysis
- Remote Sensing and LiDAR Applications
- Tree Root and Stability Studies
Cornell University
2023-2025
China University of Petroleum, Beijing
2025
Ithaca College
2025
University of California, Davis
2020-2023
Monash University
2015
Australian Regenerative Medicine Institute
2014
Introduction Estimating and understanding the yield variability within an individual field is critical for precision agriculture resource management of high value tree crops. Recent advancements in sensor technologies machine learning make it possible to monitor orchards at very spatial resolution estimate level. Methods This study evaluates potential utilizing deep methods predict tree-level almond with multi-spectral imagery. We focused on orchard ‘Independence’ cultivar California, where...
As a promising member of the carbon nitride family, nitrogen-rich g-C3N5 has attracted significant attention because its excellent light absorption performance. Nevertheless, practical application in photocatalytic CO2 reduction is hindered by severe photogenerated charge recombination and limited adsorption capacity. Constructing heterojunction emerged as an effective strategy to mitigate recombination, thereby enhancing performance catalyst. Herein, series CdS/g-C3N5-X catalysts were...
Abstract Background: Research on EGFR-mutated lung cancers has been constrained by the scarcity of large, diverse datasets integrating molecular, clinical, and environmental data. To address this gap, we built Meyer Cancer Center Molecularly Enhanced Lung Database (MCC-MELD), which combines molecular testing results, detailed clinical information, fine-resolution data while leveraging diversity our catchment area. Methods: MCC serves as cancer center for Weill Cornell Medicine, comprising...
Abstract Wildfire activity is increasing globally. The resulting smoke plumes can travel hundreds to thousands of kilometers, reflecting or scattering sunlight and depositing particles within ecosystems. Several key physical, chemical, biological processes in lakes are controlled by factors affected smoke. spatial temporal scales lake exposure extensive under‐recognized. We introduce the concept smoke‐day, number days any given exposed fire season, quantify total smoke‐day North America from...
Urban green space (UGS) is a fundamental infrastructure in modern urban settings, crucial for regulating the climate and improving public health. Accessibility to UGS represents significant environmental justice issue, influencing sustainable development of local communities. In this work, we comprehensively evaluated temporal dynamics accessibility disparity exposure all 31 metropolitan divisions United States from 2013 2022. Our findings indicate that there have been no changes both...
Black carbon (BC) is a significant source of air pollution since it impacts public health and climate change. Understanding its distribution in the complex urban environment challenging. We integrated land use model with four machine learning models to estimate traffic-related BC concentrations Oakland, CA. Random Forest was best-performing model, regression coefficient (R2) values 0.701 on train set 0.695 validation root mean square error (RMSE) 0.210 mg/m3. Vehicle speed local road systems...
In this paper, we calculate exposure concentrations of traffic-related air pollutants for different travel modes in the urban environment. Using recent high-resolution mobile sensor measured pollution concentration data, simulate bicycle, transit, and vehicle trips within Oakland, California nitric oxide (NO), nitrogen dioxide (NO2), black carbon (BC). We draw on highly resolved data (on order seconds) collected by Aclima Google, which was then aggregated to annual median every 30-m road...
In this paper we examine the effects of localized air pollution measurements on housing prices in Oakland, CA. With high-resolution for NO, NO2, and BC, can assess ambient quality a parcel-by-parcel basis within study domain. We combine spatial lag model with an instrumental variable method to consider both autocorrelation endogeneity between concentrations. To best our knowledge, is first work field that combines one accurate concentration each individual parcel. found positive using...