Atmospheric and Climate Sciences

Atmospheric and Climate Sciences

ISSN Print: 2160-0414
ISSN Online: 2160-0422
www.scirp.org/journal/acs
E-mail: acs@scirp.org
"Pollution Characteristics of PM2.5 during a Typical Haze Episode in Xiamen, China"
written by Fuwang Zhang, Jinsheng Chen, Tianxue Qiu, Liqian Yin, Xiaoqiu Chen, Jianshuan Yu,
published by Atmospheric and Climate Sciences, Vol.3 No.4, 2013
has been cited by the following article(s):
  • Google Scholar
  • CrossRef
[1] Estimating PM2. 5 concentrations via random forest method using satellite, auxiliary, and ground-level station dataset at multiple temporal scales across China in 2017
2021
[2] Spatiotemporal Variations in Particulate Matter and Air Quality over China: National, Regional and Urban Scales
2021
[3] Relationship between Visibility, Air Pollution Index and Annual Mortality Rate in Association with the Occurrence of Rainfall—A Probabilistic Approach
Energies, 2021
[4] Hysteretic effects of meteorological conditions and their interactions on particulate matter in Chinese cities
2020
[5] An eigenvector spatial filtering based spatially varying coefficient model for PM2. 5 concentration estimation: A case study in Yangtze River Delta region of China
2019
[6] Haze Formation During Winter in Delhi.
2018
[7] Haze Formation During Winter in Delhi
2018
[8] Investigation of PM10, PM2. 5 and PM1 during Pollution Episodes: Fog and Diwali Festival
2018
[9] A method for the spectral analysis and identification of Fog, Haze and Dust storm using MODIS data
2017
[10] Assessment of PM2.5 chemical compositions in Delhi: primary vs secondary emissions and contribution to light extinction coefficient and visibility degradation
2017
[11] Determination of organic particle composition in Ankara atmosphere and investigation of their contribution to receptor modeling
2017
[12] Spatial Distributions, Chemical Properties, and Sources of Ambient Particulate Matters in China
Air Pollution in Eastern Asia: An Integrated Perspective, 2017
[13] Selective ensemble based on extreme learning machine and improved discrete artificial fish swarm algorithm for haze forecast
Applied Intelligence, 2017
[14] 厦门市冬季大气 PM_ (2.5) 中有机碳和元素碳的污染特征
地球与环境, 2016
[15] Exploring spatiotemporal patterns of PM2. 5 in China based on ground-level observations for 190 cities
Environmental Pollution, 2016
[16] Seasonal Chemical Characteristics of Atmospheric Aerosol Particles and its Light Extinction Coefficients over Pune, India
2016
[17] Exploring spatiotemporal patterns of PM 2.5 in China based on ground-level observations for 190 cities
Environmental Pollution, 2016
[18] Chemical characterization and source apportionment of atmospheric submicron particles on the western coast of Taiwan Strait, China
Journal of Environmental Sciences, 2016
[19] Development of an on-line source-tagged model for sulfate, nitrate and ammonium: A modeling study for highly polluted periods in Shanghai, China
Environmental Pollution, 2016
[20] Assessment of PM2. 5 chemical compositions in Delhi: primary vs secondary emissions and contribution to light extinction coefficient and visibility degradation
Journal of Atmospheric Chemistry, 2016
[21] Review on the Recent PM 2.5 Studies in China
2015
[22] Artificial intelligence based approach to forecast PM 2.5 during haze episodes: A case study of Delhi, India
Atmospheric Environment, 2015
[23] Atmospheric Deposition of 7Be in the Southeast of China: A Case Study in Xiamen
Aerosol and Air Quality Research, 2015
[24] 최근 중국의 초미세먼지 오염 연구 동향
Journal of Korean Society for Atmospheric Environment, 2015
[25] Artificial intelligence based approach to forecast PM2. 5 during haze episodes: A case study of Delhi, India
Atmospheric Environment, 2015
[26] Review on the Recent PM2.5 Studies in China
2015
[27] Impacts of the high loadings of primary and secondary aerosols on light extinction at Delhi during wintertime
Atmospheric Environment, 2014
Free SCIRP Newsletters
Copyright © 2006-2024 Scientific Research Publishing Inc. All Rights Reserved.
Top