alexa A Satellite-based Geographically And Temporally Weighted Regression Model For Ground-level PM2.5 Estimation Over Beijing-Tianjin-Hebei Region In China | 70200
ISSN: 2375-4397

Journal of Pollution Effects & Control
Open Access

OMICS International organises 3000+ Global Conferenceseries Events every year across USA, Europe & Asia with support from 1000 more scientific Societies and Publishes 700+ Open Access Journals which contains over 50000 eminent personalities, reputed scientists as editorial board members.

Open Access Journals gaining more Readers and Citations
700 Journals and 15,000,000 Readers Each Journal is getting 25,000+ Readers

This Readership is 10 times more when compared to other Subscription Journals (Source: Google Analytics)

Annual Congress on Environmental Pollution and Sustainable Energy

Qingqing He
The Chinese University of Hong Kong, Hong Kong
Posters & Accepted Abstracts: J Pollut Eff Cont
DOI: 10.4172/2375-4397-C1-006
Abstract
Statement of the Problem: Using satellite-retrieved aerosol optical depth (AOD) and statistical model is a potential approach to estimate exposure to PM2.5 for regional studies. However, studies of assessment of ground-level PM2.5 for China at a high spatial resolution have been limited due to the lack of high resolution AOD product. The purpose of this study is to estimate daily highresolution distribution of ground-level PM2.5 using satellite remote sensing. Methodology & Theoretical Orientation: The newly released MODIS AOD data at 3 km resolution were processed as the main predictor. A geographically and temporally weighted regression (GTWR) model was developed to estimate daily PM2.5 concentrations over Beijing-Tianjin-Hebei region from January 1, 2013 to December 31, 2015. The surface PM2.5 measurements were the dependent variable and combined AOD data, land use and meteorological data were used as the independent variables. The GTWR model is able to simultaneously accounts for spatial non-stationarity and temporal variability of the relationship between PM2.5 and AOD, which can enhance the PM2.5 estimation accuracy. Findings & Conclusion: The overall model R2 value generated by GTWR model was 0.84 in model validating process, which was significantly better than those from geographically weighted regression (R2 of 0.51) and temporally weighted regression (R2 of 0.58) models. The annual mean of satellite-derived PM2.5 for China was 70.80 μg/m3 over the study period, 100% higher than the national ambient PM2.5 standard of 35 μg/m3. The ground PM2.5 predictions shows significant seasonality and winter was the most polluted season. There was virtually no ascending or descending trend for ground PM2.5 concentrations (-0.0002 day-1) from Jan 1, 2013 to Dec 31, 2015. In addition, predicted PM2.5 maps at high-resolution grid are useful to present the detailed particle gradients and investigate PM2.5 hotspots. The findings from the study demonstrated the promising potential of GTWR model for air pollution mapping.
Biography

Email: [email protected]

image PDF   |   image HTML
 

Relevant Topics

Peer Reviewed Journals
 
Make the best use of Scientific Research and information from our 700 + peer reviewed, Open Access Journals
International Conferences 2018-19
 
Meet Inspiring Speakers and Experts at our 3000+ Global Annual Meetings

Contact Us

Agri & Aquaculture Journals

Dr. Krish

[email protected]

1-702-714-7001Extn: 9040

Biochemistry Journals

Datta A

[email protected]

1-702-714-7001Extn: 9037

Business & Management Journals

Ronald

[email protected]

1-702-714-7001Extn: 9042

Chemistry Journals

Gabriel Shaw

[email protected]

1-702-714-7001Extn: 9040

Clinical Journals

Datta A

[email protected]

1-702-714-7001Extn: 9037

Engineering Journals

James Franklin

[email protected]

1-702-714-7001Extn: 9042

Food & Nutrition Journals

Katie Wilson

[email protected]

1-702-714-7001Extn: 9042

General Science

Andrea Jason

[email protected]

1-702-714-7001Extn: 9043

Genetics & Molecular Biology Journals

Anna Melissa

[email protected]

1-702-714-7001Extn: 9006

Immunology & Microbiology Journals

David Gorantl

[email protected]

1-702-714-7001Extn: 9014

Materials Science Journals

Rachle Green

[email protected]

1-702-714-7001Extn: 9039

Nursing & Health Care Journals

Stephanie Skinner

[email protected]

1-702-714-7001Extn: 9039

Medical Journals

Nimmi Anna

[email protected]

1-702-714-7001Extn: 9038

Neuroscience & Psychology Journals

Nathan T

neuropsyc[email protected]

1-702-714-7001Extn: 9041

Pharmaceutical Sciences Journals

Ann Jose

[email protected]

1-702-714-7001Extn: 9007

Social & Political Science Journals

Steve Harry

[email protected]

1-702-714-7001Extn: 9042

 
© 2008- 2018 OMICS International - Open Access Publisher. Best viewed in Mozilla Firefox | Google Chrome | Above IE 7.0 version
Leave Your Message 24x7