Qianyu Zhao

Qianyu Zhao

PhD student at the University of Illinois at Urbana-Champaign

Posts by Collection

portfolio

publications

Aerosols in an arid environment: The role of aerosol water content, particulate acidity, precursors, and relative humidity on secondary inorganic aerosols

Published in Science of The Total Environment, 2019

This study demonstrated that aerosol water content and particulate acidity were positively associated with secondary SO4, while NO2 and RH had a significant impact on secondary NO3 in an arid atmosphere. The findings explain the relationship between gaseous precursors, relative humidity, aerosol pH and temperature in the arid city of Hohhot.

Recommended citation: Wang, H., Ding, J., Xu, J., Wen, J., Han, J., Wang, K., ... & Russell, A. G. (2019). Aerosols in an arid environment: The role of aerosol water content, particulate acidity, precursors, and relative humidity on secondary inorganic aerosols. Science of the Total Environment, 646, 564-572. http://qianyuzhao.github.io/files/aerosol_arid_env.pdf

High-Resolution Data Sets Unravel the Effects of Sources and Meteorological Conditions on Nitrate and Its Gas-Particle Partitioning

Published in Environmental Science & Technology, 2019

The findings of this work provide an effective approach for exploring the formation mechanisms of nitrate under different influencing factors.

Recommended citation: Shi, X., Nenes, A., Xiao, Z., Song, S., Yu, H., Shi, G., ... & Russell, A. G. (2019). High-resolution data sets unravel the effects of sources and meteorological conditions on nitrate and its gas-particle partitioning. Environmental science & technology, 53(6), 3048-3057. http://qianyuzhao.github.io/files/NO3_paper.pdf

Aerosol pH Dynamics During Haze Periods in an Urban Environment in China: Use of Detailed, Hourly, Speciated Observations to Study the Role of Ammonia Availability and Secondary Aerosol Formation and Urban Environment

Published in Journal 1, 2019

In this study, we found high acidy (pH < 3), light pollution (total water soluble ions < 30 μg/m3), and low water content (less than 5 μg/m3) were more correlated with higher rates of sulfate formation than nitrate formation in the winter.

Recommended citation: Shi, G., Xu, J., Shi, X., Liu, B., Bi, X., Xiao, Z., ... & Russell, A. G. (2019). Aerosol pH dynamics during haze periods in an urban environment in China: Use of detailed, hourly, speciated observations to study the role of ammonia availability and secondary aerosol formation and urban environment. Journal of Geophysical Research: Atmospheres, 124(16), 9730-9742. http://qianyuzhao.github.io/files/aerosol_ph_dynamics.pdf

Using High-Temporal-Resolution Ambient Data to Investigate Gas-Particle Partitioning of Ammonium over Different Seasons

Published in Environmental Science & Technology, 2020

This paper is about gas-particle partitioning of ammonia in the inorganic aerosols. It is the first time that we created the joint source-NH3/HNO3 maps to integrate sources, aerosol pH and liquid water content, and ions (altogether in one map), which can provide useful information for designing effective strategies to control particulate matter pollution.

Recommended citation: Zhao, Q., Nenes, A., Yu, H., Song, S., Xiao, Z., Chen, K., ... & Russell, A. G. (2020). Using High-Temporal-Resolution Ambient Data to Investigate Gas-Particle Partitioning of Ammonium over Different Seasons. Environmental Science & Technology, 54(16), 9834-9843. http://qianyuzhao.github.io/files/NH4paper.pdf

Aboveground Storage Tank Detection Using Faster R-CNN and High-Resolution Aerial Imagery

Published in Master Dissertation, 2021

In this study, an effort was made to locate aboveground storage tanks from remotely sensed imagery. A dataset that identifies different types of tanks was generated.

Recommended citation: Zhao, Q. (2021). Aboveground Storage Tank Detection Using Faster R-CNN and High-Resolution Aerial Imagery (Master dissertation, Duke University). http://qianyuzhao.github.io/files/AST_detection.pdf

DiGAN Breakthrough: Advancing diabetic data analysis with innovative GAN-based imbalance correction techniques

Published in Computer Methods and Programs in Biomedicine Update, 2024

This paper uniquely applies Generative Adversarial Network, traditionally used in image processing, to diabetes data analysis and classification, achieving a weighted F1 score of 90%, a 20% improvement over traditional methods.

Recommended citation: Zhao, P., Liu, X., Yue, Z., Zhao, Q., Liu, X., Deng, Y., & Wu, J. (2024). DiGAN Breakthrough: Advancing diabetic data analysis with innovative GAN-based imbalance correction techniques. Computer Methods and Programs in Biomedicine Update, 5, 100152. http://qianyuzhao.github.io/files/DiGAN.pdf

talks

Forecasting Alpha Return from 8-K reports via deep learning

Published:

In this study, we propose a novel machine learning approach with dimension reduction stacking to forecast the stock returns of the SP 500 companies by min-ing their SEC 8K reports via different NLP techniques. The proposed method achieves better forecasting performance than the peer methods and can be used as a concrete technology in security return analysis in practice.

Spatio-temporal Changes and Driving Factors of Riverine Nitrogen Export in an Agriculture-dominated Watershed: the Illinois River Basin

Published:

Riverine nutrient load from the Mississippi/Atchafalaya River Basin (MARB) plays a crucial role in the development of the Gulf of Mexico’s hypoxic zone. Agricultural land in the MARB predominately contributes to nitrogen (N) and phosphorus (P) loading in the river system. Quantifying the sources, fate, and transport of nutrients from headwaters to large river basins is critical to diagnose the trend of exported nutrient load and guide conservation planning for nutrient loss reduction. Here taking the Illinois River Basin as an example, this study aims to quantify the changes in nitrate and nitrite (NO3+NO2) loads and yields at HUC12 scale from 2001-2020. We analyzed riverine loads and yields of nitrate and nitrite at 40 USGS gauge stations and simulated high-resolution nitrate and nitrite export throughout the Illinois River Basin using the SPARROW (SPAtially Referenced Regressions On Watershed attributes) model for two time periods (2001-2005, and 2016-2020) to quantify the spatiotemporal pattern and driving factors of changes in nitrogen export from the Illinois River Basin. We found that the five-year averaged total loads of nitrate and nitrite in the Illinois River Basin increased by 28% from 2001 to 2020, along with a 47% increase of discharge flow. Our analysis also revealed a complex spatial pattern of incremental yield of nitrate and nitrite: decreasing yields in the upper Illinois River contrasted with increasing yields in the lower Illinois and Kankakee Rivers. The simulation from the SPARROW model allowed us to identify and quantify contributions from various sources and examine driving factors for the observed spatial and temporal variations in nitrate and nitrite dynamics within the basin. By identifying areas of increasing and decreasing yields, as well as the factors driving these changes, our study provides crucial information for targeted conservation strategies to reduce nutrient load in the Illinois River Basin.

How Do Anthropogenic Activity and Hydrological Variability Control the Spatiotemporal Patterns of Nitrogen and Phosphorus Export in the Mississippi/Atchafalaya River Basin?

Published:

Excessive nutrient exports from the Mississippi/Atchafalaya River Basin (MARB) significantly degrade water quality and lead to the hypoxia zone in the Gulf of Mexico. Quantifying the sources, fate, and transport of nutrients from headwaters to large rivers is critical to diagnose the trend of exported nutrient load and guide efficient and effective conservation planning for nutrient loss reduction. This study investigates the changes in riverine nutrient loads and yields at the HUC12 scale in the MARB from 2001 to 2020. The WRTDS (Weighted Regressions on Time, Discharge and Season) and the SPARROW (SPAtially Referenced Regressions On Watershed attributes) models are integrated to quantify the spatiotemporal patterns and driving factors of riverine nutrient export from the MARB. The integration of the WRTDS model and the SPARROW model allows us to identify and quantify contributions from various sources and examine driving factors for both spatial and temporal variations in nutrient dynamics throughout the MARB. This high-resolution analysis at the HUC12 scale identifies nutrient export hotspots and differentiates areas where nutrient export increases are attributed primarily to anthropogenic activities or hydrological variability. By providing detailed assessments of nutrient source contributions and transport mechanisms, this study offers essential insights for water quality management within the MARB. The identification of local hotspot areas with high and increasing nutrient yields, along with their driving factors at the HUC12 scale, provides crucial local context for targeted conservation strategies to reduce riverine nutrient load in the MARB.

teaching

Environmental Chemistry Laboratory

Undergraduate course, Baylor University, Department of Environmental Science, 2021

This course is an introduction to experimental, field sampling and analytical methods in environmental chemistry. Emphasis on separation and detection of both organic and inorganic compounds in soil, water and air via spectrometric, colorometric, chromatographic, and fluorometric instrumentation.

Introduction to Environmental Studies Laboratory

Undergraduate course, Baylor University, Department of Environmental Science, 2022

This course is to expose students to concepts of scientific sampling, data analysis and presentation and introduce students to basic envrionmental sampling techniques.