Articles | Volume 9, issue 17
https://doi.org/10.5194/acp-9-6459-2009
© Author(s) 2009. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/acp-9-6459-2009
© Author(s) 2009. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Analysing spatio-temporal patterns of the global NO2-distribution retrieved from GOME satellite observations using a generalized additive model
M. Hayn
Institut für Mathematik, University of Potsdam, Potsdam, Germany
S. Beirle
MPI for Chemistry, Mainz, Germany
F. A. Hamprecht
Interdisciplinary Center for Scientific Computing, University of Heidelberg, Heidelberg, Germany
U. Platt
Institut für Umweltphysik, University of Heidelberg, Heidelberg, Germany
B. H. Menze
Interdisciplinary Center for Scientific Computing, University of Heidelberg, Heidelberg, Germany
Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge/MA, USA
T. Wagner
MPI for Chemistry, Mainz, Germany
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31 citations as recorded by crossref.
- Statistical and machine learning methods for evaluating trends in air quality under changing meteorological conditions M. Qiu et al. 10.5194/acp-22-10551-2022
- Recent satellite-based trends of tropospheric nitrogen dioxide over large urban agglomerations worldwide P. Schneider et al. 10.5194/acp-15-1205-2015
- Statistical analysis of factors driving surface ozone variability over continental South Africa T. Laban et al. 10.1080/1943815X.2020.1768550
- A high resolution satellite view of the aerosol weekly cycle variability over Central Europe A. Georgoulias & K. Kourtidis 10.1016/j.atmosres.2012.01.003
- Tropospheric NO<sub>2</sub> vertical column densities over Beijing: results of the first three years of ground-based MAX-DOAS measurements (2008–2011) and satellite validation J. Ma et al. 10.5194/acp-13-1547-2013
- Common summertime total cloud cover and aerosol optical depth weekly variabilities over Europe: Sign of the aerosol indirect effects? A. Georgoulias et al. 10.1016/j.atmosres.2014.07.031
- Tropospheric NO2Trends over South Asia during the Last Decade (2004–2014) Using OMI Data Z. ul-Haq et al. 10.1155/2015/959284
- Trend estimates of AERONET-observed and model-simulated AOTs between 1993 and 2013 J. Yoon et al. 10.1016/j.atmosenv.2015.10.058
- Mining spatio-temporal chaining patterns in non-identity event databases B. Chen et al. 10.3233/IDA-170873
- Satellite derived air pollution climatology over India and its neighboring regions: Spatio-temporal trends and insights S. Dhankar et al. 10.1016/j.pce.2024.103769
- Changes in OMI tropospheric NO2 columns over Europe from 2004 to 2009 and the influence of meteorological variability Y. Zhou et al. 10.1016/j.atmosenv.2011.09.024
- A study of tropospheric NO2 variability over Pakistan using OMI data Z. ul–Haq et al. 10.5094/APR.2014.080
- Abrupt recent trend changes in atmospheric nitrogen dioxide over the Middle East J. Lelieveld et al. 10.1126/sciadv.1500498
- Spatial and temporal variation of nitrogen dioxide measurement in the Middle East within 2005–2014 M. Mansouri Daneshvar & N. Hussein Abadi 10.1007/s40808-017-0293-0
- Anthropogenic emissions of NOxover China: Reconciling the difference of inverse modeling results using GOME-2 and OMI measurements D. Gu et al. 10.1002/2014JD021644
- Weekly cycle assessment of PM mass concentrations and sources, and impacts on temperature and wind speed in Southern Italy M. Perrone et al. 10.1016/j.atmosres.2018.11.013
- Semiparametric Integrated and Additive Spatio-Temporal Single-Index Models H. Mahmoud & I. Kim 10.3390/math11224629
- Aura OMI observations of regional SO<sub>2</sub> and NO<sub>2</sub> pollution changes from 2005 to 2015 N. Krotkov et al. 10.5194/acp-16-4605-2016
- The influence of synoptic weather regimes on UK air quality: regional model studies of tropospheric column NO<sub>2</sub> R. Pope et al. 10.5194/acp-15-11201-2015
- Estimation of monthly bulk nitrate deposition in China based on satellite NO2 measurement by the Ozone Monitoring Instrument L. Liu et al. 10.1016/j.rse.2017.07.005
- Neural networks for probabilistic environmental prediction: Conditional Density Estimation Network Creation and Evaluation (CaDENCE) in R A. Cannon 10.1016/j.cageo.2011.08.023
- Satellite-sensed tropospheric NO2 patterns and anomalies over Indus, Ganges, Brahmaputra, and Meghna river basins Z. ul-Haq et al. 10.1080/01431161.2017.1283071
- Assessing large-scale weekly cycles in meteorological variables: a review A. Sanchez-Lorenzo et al. 10.5194/acp-12-5755-2012
- Maintaining production while reducing local and global environmental emissions in dairy farming A. Soteriades et al. 10.1016/j.jenvman.2020.111054
- Long-term changes of tropospheric NO<sub>2</sub> over megacities derived from multiple satellite instruments A. Hilboll et al. 10.5194/acp-13-4145-2013
- A survey of factors affecting the citizen’s behaviors in Mashhad, Iran M. Esnaashari & H. Sarvari 10.1007/s10668-020-00660-x
- City-level variations in NOx emissions derived from hourly monitoring data in Chicago B. de Foy 10.1016/j.atmosenv.2017.12.028
- Changes in atmospheric aerosol loading retrieved from space-based measurements during the past decade J. Yoon et al. 10.5194/acp-14-6881-2014
- Nitrogen dioxide decline and rebound observed by GOME-2 and TROPOMI during COVID-19 pandemic S. Liu et al. 10.1007/s11869-021-01046-2
- The influence of synoptic weather regimes on UK air quality: analysis of satellite column NO2 R. Pope et al. 10.1002/asl2.492
- Detection of the Yorkshire power stations from space: an air quality perspective R. Pope & M. Provod 10.1002/wea.2651
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