Document Type : Original Article

Authors

1 Assistant Prof., Dep. of Climatology, University of Kurdistan

2 Associate Prof., Dep. of Environment, University of Kurdistan

3 M.Sc. of Climatology, University of Kurdistan

Abstract

The aim of this study was to evaluate the accuracy of MODIS satellite data in monitoring aerosol (PM10 particles) to compare with ground pollution station data It was done in Sanandaj. In this case, the performance of satellite data in measuring dust particles at Sanandaj ground station is identified. At first, the aerosol optical depth data provided by MODIS sensor was prepared based on the corresponding of the PM10 measured by pollution monitoring station located in Sanandaj.Then, the correlation coefficient between two series of data was calculated. In order to obtain the accurate prediction of PM10 the ARIMA and artificial neural network were used.The AOD of MODIS sensor was combined using maximum likelihood and root mean square error for input of prediction models. At last, a single comparison method for each model as well as models comparison was evaluated to identify the accurate model in predicting of PM10. In the ANN model R2 was acquired in training phase as 0.52, and testing phase as 0.53 with RMSE=1.62 and MAE=2.62. The analysis showed that the ARIMA model 1-0-3 with R2=0.46, MAE=0.06 and RMSE=0.69 is the only acceptable model.It states that ARIMA model, is a suitable model for prediction of PM10. However, the ANN model was more accurately estimated for the correlation between the data.The results of presented study showed that there is direct relationship between the MODIS sensor AOD data and ground station PM10 data.The results conclude that this algorithm is capable for detecting of dust and can be good alternative to the PM10 provided by the ground stations measurement.

Keywords

Adamson, I., Prieditis, H. & Vincent, R.,1999, Pulmonary Toxicity of an Atmospheric Particulate Sample Is Due to the Soluble Fraction, Toxicology and Applied Pharma-cology, 157, PP. 43-50.
Amanollahi J., Kaboodvanpour, S., Abdullah, A.M. & Ramli, M.F., 2011, Accuracy Assessment of Moderate Resolation Image Spectroradiometer Products for Dust Storms in Semiarid Environment, International Journal of Environmental Science and Technology, 8(2), PP. 373-380.
Chrysoulakis, N., Spiliotopoulos, M., Domenikiotis, C. & Dalezios, N., 2003, Towards Monitoring of Regional Atmospheric Instability through MODIS/Aqua Images, Proceedings of the International Symposium held at Volos, Greece, 7-9.
Ghorbani salkhord, R., Mubasheri, M., Rahimzadegan, M., 1389, Capability of MODIS sensor data in qualitative and quantitative analysis of air quality in urban areas, Climatological Research, Volume 1, Numbers 3 and 4, pp. 74-61.
Gupta, P., Christopher, S.A., Box, M.A. & Box, G.P., 2007, Multiyear Satellite Remote Sensing of Particulate Matter Air Quality over Sydney Australia, International Journal of Remote Sensing, 20, PP. 4483-4498.
Haywood, J. & Boucher, O., 2000, Estimates of the Direct and Indirect Radiative Forcing Due to Tropospheric Aerosols: A Review, Reviews of Geophysic, 38(4), PP. 513-543.
Kampe, T.U., 2008, Data Analysis from Remote Sensing to Better Constrain Emission and Transport of Carbonaceous Aerosol and Carbon Monoxide Resulting from Burning Processes, PhD Thesis, Colorado University.
Khoshsima, M., Aliakbari Beidokhti, A., Ahmadi Givi, F., 1392. Determination of optical depth of airships using horizontal vision and remote sensing data in two urban areas, Earth and space physics, Volume 39, Number 1, pp. 174-163. 
 
 
Liu, X., Nie, D., Zhang, K., Wang, Z., Li, X., Shi, Z., Wang, Y., Huag, L., Chen, M., Ge, X., Ying, Q., Yu, X., Liu, X. & Hu, J, 2019, Evaluation of Particulate Matter Deposition in the Human Respiratory Tract During Winter in Nanjing Using Size and Chemically Resolved Ambient Measurements, Air Quality, Atmosphere & Health, 12(5), PP. 529-538.
Lorrain & Remer, 2006, Global Aerosol Climatology from the MODIS Satellite Sensors, Journal of Geophysical Reserch, 113, PP. 7-14.
Mirzaei, M., Amanollahi, J. & Tzanis, C.G., 2019, Evaluation of Linear, Nonlinear, and Hybrid Models for Predicting PM2.5 Based on a GTWR Model and MODIS AOD Data, Air Quality, Atmosphere & Health, 12(10), PP. 1215-1224.
Park, S., Lee, J., Im, J., Song, C-K., Choi, M., Kim, J., Lee, S., Park, R., Kim, J., Yoon, J., Lee, D.-W. & Quackenbush, L.J., 2020, Estimation of Spatially Continuous Daytime Particulate Matter Concentrations under All Sky Conditions through the Synergistic Us of Satellite-Based AOD and Numerical Models, Scince of the Total Environmet, 713, P. 136516
Rahimi M., Yazdani, M., Asadi, M., Heydari, M., 1394, Investigation of air pollution in Sanandaj with emphasis on temporal changes in PM10 concentration, Urban Ecology Research, Volume 6, Number 11,p p. 99 -116. 
Sahu, S.K., Zhang, H., Guo, H., Hu, J., Ying, Q. & Kota, S.K., 2019, Helath Risk Associated with Potential Source Regions of PM2.5 in Indian Cities, Air Quality, Atmosphere & Health, 12(3), PP 327-340.
  Soleimani A., Mohammad Asgari, H., Dadalehi, SA., Elmizadeh, H., Cheraghi, S. H., 1394, Optical depth evaluation of MODIS sensor images in the Persian Gulf, Marine Science and Technology, Volume 14, Number 4, p. 83-75.
  Sotoudian S., Arhami, M., 1390, Investigation of Satellite Data in Model Development to Predict Pollutant Concentrations at Ground Surface: A Case Study of Tehran, Fifth Specialized Conference on Environment, University of Tehran.
Tanre, D., Kaufman, Y.J., Herman, M. & Mattoo, S., 1997, Remote Sensing of Aerosol over Oceans from EOS-MODIS, J. Geophys. Res, 102, PP. 16971-16988.
Tzanis, C., Varotsos, C., Christodoulakis, J., Tidblad, J., Ferm, M., Ionescu, A., Lefevre, R.A., Theodorakopoulou, K. & Kreislova, K., 2011, On the Corrosion and Soiling Effects on Materials by Air Pollution in Athens, Greece, Atmospheric Chemistry and Physic, 11, PP. 12039-12048.
Wang, J. & Christopher, S.A., 2003, Inter Comparison between Satellite-Derived Aerosol Optical Thickness and PM2.5 Mass: Implication for Air Quality Studies, Geophysical Research Letters, 30, P. 2095.
Wang, J., Pan, Y., Tian, S., Chen, X., Wang, L. & Wang, Y., 2016, Size Distributions and Health Risks of Particulate Trace Elements in Rural Areas in Northeastern China, Atmospheric Research, 168, PP. 191-204.
Wei, C., Aiping, F. & Lei, Y., 2017, Performance of MODIS C6 Aerosol Product during Frequent Haze-Fog Events: A Case Study of Beijing, Remote Sensing, 9, PP. 496.
Xu, H., Guanga, J., Xue, Y., Gerrit, D.L., Leeuwc, Y.H., Che, J., Guo, X.W., He, T. & Wang, K., 2015, A Consistent Aerosol Optical Depth (AOD) Dataset over Mainland China by Integration of Several AOD Products, Atmospheric Environment, 114, PP. 48-56.
Yadav, A.K., Sahoo, S.K., Dubey, J.S., Kumar, A.V., Pandey, G. & Tripathi, R.M., 2019, Assessment of Particulate Matter, Metals of Toxicological Concentration, and Health Risk Around a Mining Area, Odisha, India, Air Quality, Atmosphere & Health, 12(7), PP. 775-783.