Bu Zhao

University of Michigan | U-M · School of Natural Resources and Environment

Water scarcity is increasingly perceived as a great challenge to the sustainable development of human society. The economic output loss due to water scarcity is defined as water scarcity risk (WSR), which constitutes local water scarcity risk (LWSR, local economic output loss in water-using sectors due to water scarcity) and virtual water scarcity...

Environmental footprint accounting relies on economic input-output (IO) models. However, the compilation of IO models is costly and time-consuming, leading to the lack of timely detailed IO data. The RAS method is traditionally used to predict future IO tables but suffers from doubts for unreliable estimations. Here we develop a machine learning-au...

The COVID-19 pandemic has posed severe threats to global sustainable development. However, a comprehensive quantitative assessment of the impacts of COVID-19 on Sustainable Development Goals (SDGs) is still lacking. This research quantified the post-COVID-19 SDG progress from 2020 to 2024 using projected GDP growth and population and machine learni...

Spatially explicit urban air quality information is important for urban fine-management and public life. However, existing air quality measurement methods still have some limitations on spatial coverage and system stability. A micro station is an emerging monitoring system with multiple sensors, which can be deployed to provide dense air quality mo...

Hundreds of indicators are available to monitor progress of countries and regions towards the Sustainable Development Goals (SDGs). However, the sheer number of indicators poses unprecedented challenges for data collection and compilation. Here we identify a subset of SDG indicators (principal indicators) that are relatively easy to collect data fo...

Spatially explicit urban air quality information is important for developing effective air quality control measures. Traditionally, urban air quality is measured by networks of stationary monitors that are not universally available and sparsely sited. Mobile air quality monitoring using equipped vehicles is a promising alternative but has focused o...

Sustainable consumption and production (SCP) have been extensively discussed, studied, and implemented by various stakeholders in tandem to achieve greater gains in environmental sustainability. However, SCP research and practice still face substantial challenges due to various issues related to data. This dissertation sheds light on how data scien...

Peroxyacyl nitrates (PANs) are important secondary pollutants in ground-level atmosphere. Accurate prediction of atmospheric pollutant concentrations is crucial to guide effective precautions for before and during specific pollution events. In this study, four models based on the back-propagation (BP) artificial neural network (ANN) and multiple li...

Peroxyacyl nitrates (PANs) are photochemical secondary pollutants that play a key role in the atmospheric chemistry of the troposphere. However, there have been few studies on the long-term variation and inter-regional transport of PANs. In this study, summertime ambient PAN concentrations were monitored at urban and rural sites in Beijing and Hebe...

The prevention and treatment of epidemic is always an urgent problem faced by the human being. Due to the special space structure, huge passenger flow and great people mobility, the subway lines have become the areas with high epidemic transmission risks. However, there is no recent study related to epidemic transmission in the subway network on ur...