The potential of satellite data used for particular matter monitoring is a crucial subject in air quality
research. PM10 is influenced by many meteorological factors and has a difference correlation with
aerosol optical depth in different place. Geographically weighted regression (GWR) model have been
proved to be an effective methods for spatial variation analysis. This paper presented results from a
study of PM10 concentration from API in eastern China from 2005 to 2010. Wavelet analysis was used
for analyzing the periodicity characteristics of PM10 and AOD. The correlations between PM10 and
meteorological factors were also analyzed without AOD and with AOD added, respectively. Obvious
spatial and seasonal non-stationary distributions of PM10 concentration were found with spatial
auto-correlation analysis. PM10 concentration and AOD have similar periods and discontinuity
characteristics in 41 months scale and 70 months scale. Correlation between PM10 concentration and
meteorological factors were improved when AOD added as a factor, and the tempo-spatial distributions
of the correlations were non-stationary in eastern China because of differences of the regional weather
conditions and the pollution sources.
Carbon dioxide (CO2) is one of major green house gases affecting global climate. Biomass burning caused by fire is an
important emission source of CO2 in the atmosphere. CO2 concentration retrieved from Atmospheric Infrared Sounder
(AIRS) and fire pixel counts (FPC) obtained from Moderate Resolution Imaging Spectroradiometer (MODIS) from 2003
to 2010 over China were obtained and analyzed. The characteristics of correlation between CO and FPC were analyzed
in time series. To investigate the spatial characteristics of correlation between CO2 and fire, energy fires emitted based
on the Global Fire Emissions Database v3 (GFED3) was used. CO2 concentration was steadily increased in both daytime
and nighttime. The seasonal distribution of CO2 concentration and FPC had the similar pattern as the highest value
appeared in Spring and lowest value in Autumn. What’s more, the changes of the aggregated CO2 concentration had a
good agreement with the changes of the total FPC. However, the concentration of CO2 emitted from fires was low except
Heilongjiang province. And the tempo-spatial characteristic of CO2 and FPC were similar with each other. It was
different with characteristic of correlation between CO2 and FPC in whole country.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.