Cornell University
UNDERSTANDING MISSING DATA IN REAL-TIME POLLUTION MONITORING SYSTEM IN CHINA
Abstract
dc:description.abstractUsing both remote sensing data on air pollution and publicly reported hourly PM2.5 data from ground-level monitoring stations, this paper examines whether the quality of the publicly reported PM2.5 is affected by selective reporting whereby high-level hourly pollution readings are dropped in the reported data. Our analysis shows that the contemporaneous level of air pollution measured by the Aerosol Optical Depth (AOD) has a negative relationship with the frequency of data missing. This relation- ship is weaker in dirty cities measured by the average AOD during the sample period and is reversed in very dirty cities.
Degree
thesis:*- Name thesis:degree_name
- M.S., Applied Economics and Management
- Level thesis:degree_level
- Master of Science
- Discipline thesis:degree_discipline
- Applied Economics and Management
- Grantor
- Cornell University
- Year dc:date.issued
- 2019
Author and committee
dc:creator, dc:contributor.*- Author dc:creator
-
- Han, Congyan
Subjects
dc:subject × 1Rights
- Language dc:language.iso
- en_US
Identifiers
dc:identifier.*- Dc Identifier Other
-
ProQuest Submission ID: 10639
ProQuest Publication ID: 22587009 - OAI identifier oai:identifier
- oai:ecommons.cornell.edu:1813/67479