Next Article in Journal
Role of Water Vapor Content in the Effects of Aerosol on the Electrification of Thunderstorms: A Numerical Study
Next Article in Special Issue
Impact of Stratospheric Volcanic Aerosols on Age-of-Air and Transport of Long-Lived Species
Previous Article in Journal
On Practical Implementation of Electromagnetic Models of Lightning Return-Strokes
Previous Article in Special Issue
Retrieval of Aerosol Optical Depth over Arid Areas from MODIS Data
Article Menu

Export Article

Open AccessArticle
Atmosphere 2016, 7(10), 136; doi:10.3390/atmos7100136

Inversion of Nighttime PM2.5 Mass Concentration in Beijing Based on the VIIRS Day-Night Band

Institute of Meteorology and Oceanograph, PLA University of Science and Technology, Nanjing 211101, China
*
Author to whom correspondence should be addressed.
Academic Editors: Giovanni Pitari and Gabriele Curci
Received: 24 September 2016 / Revised: 13 October 2016 / Accepted: 14 October 2016 / Published: 19 October 2016
(This article belongs to the Special Issue Atmospheric Aerosols and Their Radiative Effects)
View Full-Text   |   Download PDF [3064 KB, uploaded 19 October 2016]   |  

Abstract

In order to monitor nighttime particular matter (PM) air quality in urban area, a back propagation neural network (BP neural network) inversion model is established, using low-light radiation data from the day/night band (DNB) of the Visible Infrared Imaging Radiometer Suite (VIIRS) aboard the Suomi National Polar-orbiting Partnership (S-NPP) satellite. The study focuses on the moonless and cloudless nights in Beijing during March–May 2015. A test is carried out by selecting surface PM2.5 data from 12 PM2.5 automatic monitoring stations and the corresponding night city light intensity from DNB. As indicated by the results, the linear correlation coefficient (R) between the results and the corresponding measured surface PM2.5 concentration is 0.91, and the root-mean-square error (RMSE) is 14.02 μg/m3 with the average of 59.39 μg/m3. Furthermore, the BP neural network model shows better accuracy when air relative humility ranges from 40% to 80% and surface PM2.5 concentration exceeds 40 μg/m3. The study provides a superiority approach for monitoring PM2.5 air quality from space with visible light remote sensing data at night. View Full-Text
Keywords: low-light; nighttime PM2.5; VIIRS/DNB; BP neural network low-light; nighttime PM2.5; VIIRS/DNB; BP neural network
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Supplementary material

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Zhao, X.; Shi, H.; Yu, H.; Yang, P. Inversion of Nighttime PM2.5 Mass Concentration in Beijing Based on the VIIRS Day-Night Band. Atmosphere 2016, 7, 136.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Atmosphere EISSN 2073-4433 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top