skip to main content

Search for: All records

Creators/Authors contains: "Cao, Yi"

Note: When clicking on a Digital Object Identifier (DOI) number, you will be taken to an external site maintained by the publisher. Some full text articles may not yet be available without a charge during the embargo (administrative interval).
What is a DOI Number?

Some links on this page may take you to non-federal websites. Their policies may differ from this site.

  1. Abstract

    The return level estimation is an essential topic in studying spatial extremes for environmental data. Recently, various models for spatial extremes have emerged, which generally yield different estimates for return levels, given the same data. In the meantime, several approaches that obtain confidence intervals (CIs) for return levels have arisen, and the results from different approaches can also largely disagree. These pose natural questions for assessing different return level estimation methods and different CI derivation approaches. In this article, we compare an array of popular models for spatial extremes in return level estimation, as well as three approaches in CI derivation, through extensive Monte Carlo simulations. Our results show that in general, max‐stable models yield return level estimates with similar mean squared error, and the spatial generalized extreme value model also provides comparable estimates. The bootstrap method is recommended for max‐stable models to compute the CI, and the profile likelihood CI works well for spatial generalized extreme value. We also evaluate the methods for return level interpolation at unknown spatial locations and find that kriging of marginal return level estimates performs as well as max‐stable models.

    more » « less
  2. A novel strategy of “waste treating waste” has been implemented in this work. Copper/carbon (Cu/C) composites prepared by the carbonization of waste printed circuit boards (PCBs) were used for the degradation of Acid Orange 7 (AO7). Catalytic degradation of AO7 was conducted by varying carbonization temperatures, catalyst dosage, H2O2dosage, AO7 concentration, pH values, and anions. Ultrasound significantly improved AO7 degradation, obtaining 93.27% degradation within 90 min. We report that Cu/C composites show good catalytic activity in a broad pH range. Cu/C catalysts were characterized by multitechniques. Cu0was the main active component for the generation of •OH that was the reactive oxidant for AO7 degradation. The plausible pathway and catalytic mechanism for AO7 degradation were proposed. The unique structure of Cu/C composites gave a combined mechanism of adsorption and catalysis. Cu/C composites showed superior durability for AO7 degradation. Using Cu/C composites as catalysts provides a green approach for wastewater treatment and waste management. © 2019 American Institute of Chemical Engineers AIChE J, 65: 1234–1244, 2019

    more » « less