Skip to main content
SpringerLink
Log in

Spatial and temporal distribution of carbon dioxide gas using GOSAT data over IRAN

  • Published:
Environmental Monitoring and Assessment Aims and scope Submit manuscript

A Correction to this article was published on 26 January 2018

This article has been updated

Abstract

CO2 concentration (XCO2) shows the spatial and temporal variation in Iran. The major purpose of this investigation is the assessment of the spatial distribution of carbon dioxide concentration in the different seasons of 2013 based on the Thermal And Near Infrared Sensor for Carbon Observation–Fourier Transform Spectrometer (TANSO-FTS) level 2 GOSAT data by implementing the ordinary kriging (OK) method. In this study, the Land Surface Temperature (LST), Normalized Difference Vegetation Index (NDVI) data from the MODerate resolution Imaging Spectroradiometer (MODIS), and metrological parameters (temperature and precipitation) were used for the analysis of the spatial distribution of CO2 over Iran in 2013. The spatial distribution maps of XCO2 show the highest concentration of this gas in the south and south-east and the lowest concentration in the north and north-west. These results indicate that the concentration of carbon dioxide decreased with the increase of LST and temperature and a decrease of NDVI and humidity in the study area. Therefore, the existence of vegetation has an effective role in capturing carbon from the atmosphere by photosynthesis phenomena, and sustainable land management can be effective for carbon absorption from the atmosphere and mitigation of climate change in arid and semi-arid regions.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

Similar content being viewed by others

Change history

  • 26 January 2018

    The original version of this article unfortunately contained an error in the affiliation section.

References

  • Alexe, M., Bergamaschi, P., Segers, A., Detmers, R., Butz, A., Hasekamp, O., & Scheepmaker, R. A. (2015). Inverse modelling of CH4 emissions for 2010–2011 using different satellite retrieval products from GOSAT and SCIAMACHY. Atmospheric Chemistry and Physics, 15(1), 113–133. https://doi.org/10.5194/acp-15-113-2015.

    Article  Google Scholar 

  • Andrews, A. E., Boering, K. A., Daube, B. C., Wofsy, S. C., Loewenstein, M., Jost, H., Podolske, J. R., Webster, C. R., Herman, R. L., Scott, D. C., Flesch, G. J., Moyer, E. J., Elkins, J. W., Dutton, G. S., Hurst, D. F., Moore, F. L., Ray, E. A., Romashkin, P. A., & Strahan, S. E. (2001). Mean ages of stratospheric air derived from in situ observations of CO2, CH4, and N2O. Journal of Geophysical Research. Atmospheres, 106, 32295–32314. https://doi.org/10.1029/2001JD000465.

    Article  CAS  Google Scholar 

  • Badripour, H. (2004). Islamic Republic of Iran. Country pasture/forage resource profiles. Rangeland management expert in the Technical Bureau of Rangeland–grown at three environments. Crop Science, 16, 347–349.

    Google Scholar 

  • Bai, W., Zhang, X., & Zhang, P. (2010). Temporal and spatial distribution of tropospheric CO2 over China based on satellite observations. Chinese Science Bulletin, 55, 3612–3618. https://doi.org/10.1007/s11434-010-4182-4.

    Article  CAS  Google Scholar 

  • Cambardella, C. A., Moorman, T. B., Parkin, T. B., Karlen, D. L., Novak, J. M., Turco, R. F., & Konopka, A. E. (1994). Field-scale variability of soil properties in central Iowa soils. Soil Science Society of America Journal, 58, 1501–1511. https://doi.org/10.2136/sssaj1994.03615995005800050033x.

    Article  Google Scholar 

  • Chevallier, F., Engelen, R. J., & Peylin, P. (2005). The contribution of AIRS data to the estimation of CO2 sources and sinks. Geophysical Research Letters, 32, L23801. https://doi.org/10.1029/2005GL024229.

  • Chow, F. K., Granvold, P. W., & Oldenburg, C. M. (2009). Modeling the effects of topography and wind on atmospheric dispersion of CO2 surface leakage at geologic carbon sequestration sites. Energy Procedia, 1, 1925–1932. https://doi.org/10.1016/j.egypro.2009.01.251.

    Article  CAS  Google Scholar 

  • Cressot, C., Chevallier, F., Bousquet, P., Crevoisier, C., Dlugokencky, E. J., Fortems-Cheiney, A., & Montzka, S. A. (2014). On the consistency between global and regional methane emissions inferred from SCIAMACHY, TANSO-FTS, IASI, and surface measurements. Atmospheric Chemistry and Physics, 14, 577–592. https://doi.org/10.5194/acp-14-577-2014.

    Article  Google Scholar 

  • Dai, L., Jia, J., Yu, D., Lewis, B. J., Zhou, L., Zhou, W., Zhao, W., & Jiang, L. (2013). Effects of climate change on biomass carbon sequestration in old-growth forest ecosystems on Changbai Mountain in Northeast China. Forest Ecology and Management, 300, 106–116. https://doi.org/10.1016/j.foreco.2012.06.046.

    Article  Google Scholar 

  • Davidson, O., Bosch, P., Dave, R., & Meyer, L. (2007). Mitigation of climate change. Cambridge: Cambridge University Press.

    Google Scholar 

  • Deng, S., Shi, Y., Jin, Y., & Wang, L. (2011). A GIS-based approach for quantifying and mapping carbon sink and stock values of forest ecosystem: a case study. Energy Procedia, 5, 1535–1545. https://doi.org/10.1016/j.egypro.2011.03.263.

    Article  Google Scholar 

  • Dong, Y., Zhang, S., Qi, Y., Chen, Z., & Geng, Y. (2000). Fluxes of CO2, N2O and CH4 from a typical temperate grassland in Inner Mongolia and its daily variation. Chinese Science Bulletin, 45, 1590–1594. https://doi.org/10.1007/BF02886219.

    Article  CAS  Google Scholar 

  • Englund, E., Weber, D., & Leviant, N. (1992). The effects of sampling design parameters on block selection. Mathematical Geology, 24, 329–343. https://doi.org/10.1007/BF00893753.

    Article  Google Scholar 

  • ENI. (2016). ENCYCLOPAEDIA IRANICA. http://www.iranicaonline.org . Accessed 12 Nov 2016.

  • Fu, L., Zhao, Y., Xu, Z., & Wu, B. (2015). Spatial and temporal dynamics of forest aboveground carbon stocks in response to climate and environmental changes. Journal of Soils and Sediments, 15, 249–259. https://doi.org/10.1007/s11368-014-1050-x.

    Article  CAS  Google Scholar 

  • Gavrilov, N. M., Makarova, M. V., Poberovskii, A. V., & Timofeyev, Y. M. (2014). Comparisons of CH4 ground-based FTIR measurements near Saint Petersburg with GOSAT observations. Atmospheric Measurement Techniques, 7, 1003–1010. https://doi.org/10.5194/amt-7-1003-2014, 2014.

    Article  Google Scholar 

  • Guo, M., Wang, X., Li, J., Yi, K., Zhong, G., & Tani, H. (2012). Assessment of global carbon dioxide concentration using MODIS and GOSAT data. Sensors, 12, 16368–16389. https://doi.org/10.3390/s121216368.

    Article  CAS  Google Scholar 

  • Guo, M., Wang, X., Li, J., Wang, H., & Tani, H. (2013a). Examining the relationships between land cover and greenhouse gas concentrations using remote-sensing data in East Asia. International Journal of Remote Sensing, 34, 4281–4303. https://doi.org/10.1080/01431161.2013.775535.

    Article  Google Scholar 

  • Guo, M., Wang, X. F., Li, J., Yi, K. P., Zhong, G. S., Wang, H. M., & Tani, H. (2013b). Spatial distribution of greenhouse gas concentrations in arid and semi-arid regions: a case study in East Asia. Journal of Arid Environments, 91, 119–128. https://doi.org/10.1016/j.jaridenv.2013.01.001.

    Article  Google Scholar 

  • Hannah, L. (2014). Carbon sinks and sources. In L. Hannah (Ed.), Climate change biology second ed (pp. 403–422). Santa Barbara: University of California.

    Google Scholar 

  • Hou, Y., Wang, S., Zhou, Y., Yan, F., & Zhu, J. (2013). Analysis of the carbon dioxide concentration in the lowest atmospheric layers and the factors affecting China based on satellite observations. International Journal of Remote Sensing, 34, 1981–1994. https://doi.org/10.1080/01431161.2012.730159.

    Article  Google Scholar 

  • IMO, (2016). Iran Meteorological Organization. http://www.irimo.ir/far/. Accessed 9 Sep 2016.

  • Inoue, M., Morino, I., Uchino, O., Miyamoto, Y., Saeki, T., Yoshida, Y., & Machida, T. (2014). Validation of XCH4 derived from SWIR spectra of GOSAT TANSO-FTS with aircraft measurement data. Atmospheric Measurement Techniques, 7, 2987–3005. https://doi.org/10.5194/amt-7-2987-2014.

    Article  Google Scholar 

  • Isaaks, E. H., & Srivastava, R. M. (1989). An introduction to Applied Geostatistics. New York: Oxford University Press.

    Google Scholar 

  • Janssens-Maenhout, G., Petrescu, A. M. R., Muntean, M., & Blujdea, V. (2011). Verifying greenhouse gas emissions: methods to support international climate agreements. Greenhouse Gas Measurement and Management, 1, 132–133. https://doi.org/10.1080/20430779.2011.579358.

    Article  Google Scholar 

  • Journel, A. G., & Huijbregts, C. J. (1978). Mining Geostatistics. Caldwell: Blackburn Press.

    Google Scholar 

  • Laslett, G. M. (1994). Kriging and splines: an empirical comparison of their predictive performance in some applications. Journal of the American Statistical Association, 89, 391–400.

    Article  Google Scholar 

  • Li, J., & Heap, A. D. (2011). A review of comparative studies of spatial interpolation methods in environmental sciences: performance and impact factors. Ecological Informatics, 6, 228–241. https://doi.org/10.1016/j.ecoinf.2010.12.003.

    Article  Google Scholar 

  • Li, J., & Heap, A. D. (2014). Spatial interpolation methods applied in the environmental sciences: a review. Environmental Modelling and Software, 53, 173–189. https://doi.org/10.1016/j.envsoft.2013.12.008.

    Article  Google Scholar 

  • Modarres, R., & da Silva, V. D. P. R. (2007). Rainfall trends in arid and semi-arid regions of Iran. Journal of Arid Environments, 70, 344–355. https://doi.org/10.1016/j.jaridenv.2006.12.024.

    Article  Google Scholar 

  • Morino, I., Uchino, O., Inoue, M., Yoshida, Y., Yokota, T., Wennberg, P. O., Toon, G. C., Wunch, D., Roehl, C. M., Notholt, J., Warneke, T., Messerschmidt, J., Griffith, D. W. T., Deutscher, N. M., Sherlock, V., Connor, B., Robinson, J., Sussmann, R., & Rettinger, M. (2011). Preliminary validation of column-averaged volume mixing ratios of carbon dioxide and methane retrieved from GOSAT short-wavelength infrared spectra. Atmospheric Measurement Techniques, 4, 1061–1076. https://doi.org/10.5194/amt-4-10612011.

    Article  CAS  Google Scholar 

  • Mousavi, S. M., Falahatkar, S., & Farajzadeh, M. (2017). Assessment of seasonal variations of carbon dioxide concentration in Iran using GOSAT data. Natural Resources Forum, 41, 83–91. https://doi.org/10.1111/1477-8947.12121.

    Article  Google Scholar 

  • Oldenburg, C. M., & Unger, A. J. (2004). Coupled vadose zone and atmospheric surface-layer transport of carbon dioxide from geologic carbon sequestration sites. Vadose Zone Journal, 3, 848–857. https://doi.org/10.2136/vzj2004.0848.

    Article  CAS  Google Scholar 

  • Prasad, P., Rastogi, S., & Singh, R. P. (2014). Study of satellite retrieved CO2 and CH4 concentration over India. Advances in Space Research, 54, 1933–1940. https://doi.org/10.1016/j.asr.2014.07.021.

    Article  CAS  Google Scholar 

  • Prasad, P., Rastogi, S., & Singh, R. P. (2016). Study of CO2 variability over India using data from satellites. Paper presented at the Conference of the International Society for Optics and Photonics, 10–14 may 2016. Doi:https://doi.org/10.1117/12.2228029.

  • Robertson, G. P., Klingensmith, K. M., Klug, M. J., Paul, E. A., Crum, J. R., & Ellis, B. G. (1997). Soil resources, microbial activity, and primary production across an agricultural ecosystem. Ecological Applications, 7, 158–170. https://doi.org/10.1890/1051-0761(1997)007[0158:SRMAAP]2.0.CO;2.

  • Sasakawa, M., Shimoyama, K., Machida, T., Tsuda, N., Suto, H., Arshinov, M., Davydov, D., Fofonov, A., Krasnov, O., Saeki, T., Koyama, Y., & Maksyutov, S. (2010). Continuous measurements of methane from a tower network over Siberia. Tellus Series B: Chemical and Physical Meteorology, 62, 403–416. https://doi.org/10.1111/j.1600-0889.2010.00494.x.

    Article  Google Scholar 

  • Shim, C., Lee, J., & Wang, Y. (2013). Effect of continental sources and sinks on the seasonal and latitudinal gradient of atmospheric carbon dioxide over East Asia. Atmospheric Environment, 79, 853–860. https://doi.org/10.1016/j.atmosenv.2013.07.055.

    Article  CAS  Google Scholar 

  • SIO, (2017). Scripps Institution of Oceanography. https://scripps.ucsd.edu/programs/keelingcurve/. Accessed 8 Sep 2016.

  • Stellmes, M., Udelhoven, T., Röder, A., Sonnenschein, R., & Hill, J. (2010). Dryland observation at local and regional scale comparison of Landsat TM/ETM+ and NOAA AVHRR time series. Remote Sensing of Environment, 114, 2111–2125. https://doi.org/10.1016/j.rse.2010.04.016.

    Article  Google Scholar 

  • Sun, B., Zhou, S., & Zhao, Q. (2003). Evaluation of spatial and temporal changes of soil quality based on geostatistical analysis in the hill region of subtropical China. Geoderma, 115, 85–99. https://doi.org/10.1016/S0016-7061(03)00078-8.

    Article  Google Scholar 

  • Terao, Y., Mukai, H., Nojiri, Y., Machida, T., Tohjima, Y., Saeki, T., & Maksyutov, S. (2011). Inter annual variability and trends in atmospheric methane over the western Pacific from 1994 to 2010. Journal of Geophysical Research-Atmospheres, 116(D14), 303. https://doi.org/10.1029/2010JD015467.

    Article  Google Scholar 

  • Wada, A., Matsueda, H., Sawa, Y., Tsuboi, K., & Okubo, S. (2011). Seasonal variation of enhancement ratios of trace gases observed over 10 years in the western North Pacific. Atmospheric Environment, 45, 2129–2137. https://doi.org/10.1016/j.atmosenv.2011.01.043.

    Article  CAS  Google Scholar 

  • Wang, H., Liu, G., & Gong, P. (2005). Use of cokriging to improve estimates of soil salt solute spatial distribution in the Yellow River delta. Acta Geographica Sinica, 60, 511–518.

    Google Scholar 

  • Wang, T., Shi, J., Jing, Y., Zhao, T., Ji, D., & Xiong, C. (2016). Correction: Combining XCO2 measurements derived from SCIAMACHY and GOSAT for potentially generating global CO2 maps with high spatiotemporal resolution. PLoS One, 11, e0148152.

    Article  Google Scholar 

  • WMO (2013). World Meteorological Organization. WDCGG data summary. WMO WDCGG No. 37, 2013.

  • Yoshida, Y., Ota, Y., Eguchi, N., Kikuchi, N., Nobuta, K., Tran, H., Morino, I., & Yokota, T. (2011). Retrieval algorithm for CO2 and CH4 column abundances from short-wavelength infrared spectral observations by the greenhouse gases observing satellite. Atmospheric Measurement Techniques, 4, 717–734. https://doi.org/10.5194/amtd-3-4791-2010.

    Article  CAS  Google Scholar 

  • Zeng, Z., Lei, L., Guo, L., Zhang, L., & Zhang, B. (2013). Incorporating temporal variability to improve geostatistical analysis of satellite-observed CO2 in China. Chinese Science Bulletin, 58, 1948–1954. https://doi.org/10.1007/s11434-012-5652-7.

    Article  CAS  Google Scholar 

  • Zhang, Y., Xu, M., Chen, H., & Adams, J. (2009). Global pattern of NPP to GPP ratio derived from MODIS data: effects of ecosystem type geographical location and climate. Global Ecology and Biogeography, 18(3), 280–290. https://doi.org/10.1111/j.1466-8238.2008.00442.x.

  • Zhou, C., Shi, R., & Gao, W. (2013). Interpolation of XCO2 retrieved from GOSAT in China using fixed rank kriging. Paper presented at the Conference of the International Society for Optics and Photonics, 24–28 September 2013. https://doi.org/10.1117/12.2020946.

Download references

Acknowledgements

This work was supported by Iran National Science Foundation. We would like to thank the Islamic Republic of Iran Meteorological Organization, the GOSAT Project of Japan, and NASA for the use of their data in this research.

Author information

Authors and Affiliations

  1. Environmental Science Department, Faculty of Natural Resource and Marine Science, Tarbiat Modares University, Noor, Mazandaran, Iran

    Samereh Falahatkar & Seyed Mohsen Mousavi

  2. Department of Geography, University of Tarbiat Modares University, Tehran, Iran

    Manochehr Farajzadeh

Authors
  1. Samereh Falahatkar
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Seyed Mohsen Mousavi
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Manochehr Farajzadeh
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Samereh Falahatkar.

Additional information

A correction to this article is available online at https://doi.org/10.1007/s10661-018-6473-1.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Falahatkar, S., Mousavi, S.M. & Farajzadeh, M. Spatial and temporal distribution of carbon dioxide gas using GOSAT data over IRAN. Environ Monit Assess 189, 627 (2017). https://doi.org/10.1007/s10661-017-6285-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s10661-017-6285-8

Keywords

Search

Navigation