Skip to main content

Advertisement

SpringerLink
Log in

Estimation of greenhouse gas emission flux from agricultural lands of Khuzestan province in Iran

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

Abstract

Greenhouse gas emissions and their effects on global warming are one of the serious challenges of developed and developing countries. Investigating the amount of greenhouse gas emissions of different countries makes it possible to determine the share of countries in the production of greenhouse gases. The purpose of this study is to use DAYCENT and DNDC models to estimate the emission rate of methane, nitrous oxide, and carbon dioxide greenhouse gases as well as to estimate the global warming potential in Khuzestan agricultural lands in Iran. For this purpose, the gas sampling was done in rice, wheat, and sugarcane fields using a static chamber, and then the concentration of methane, nitrous oxide, and carbon dioxide was determined by using gas chromatography. In the following, DAYCENT and DNDC models were used to estimate gas emissions and the global warming potential of these gases was estimated. Finally, TOPSIS method was used to prioritize gas emissions. In order to evaluate the modeling accuracy, the statistical indicators of maximum error, root mean square error, determination coefficient, model efficiency, and residual mass coefficient were used. According to the results, the highest measured gas flux was obtained for rice fields at Baghmalek and the lowest for sugarcane in Abadan. The results of DAYCENT model estimation showed that the highest emissions were obtained for methane gas and rice cultivation, and lowest gas emissions were obtained for sugarcane cultivation. The results of DNDC model estimation also showed that the highest flux was determined for nitrous oxide gas in rice cultivation. The results of the estimation of global warming potential also showed that it was the highest in sugarcane cultivation (Shushtar station) and the DAYCENT model, and the lowest was also in wheat cultivation and the DNDC model. The statistical results of the estimation of DAYCENT and DNDC models showed that the DAYCENT model in sugarcane cultivation (Shushtar station) was the most accurate in estimating carbon dioxide gas, and the lowest accuracy was related to the DNDC model and sugarcane cultivation (Shushtar station) in estimating nitrous oxide gas. According to the results of agricultural activities in Khuzestan province, they have made a major contribution to the production of greenhouse gases, which, or the lack of attention to this issue, will have an effect on the future climate of this region.

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

Similar content being viewed by others

Data availability

The data set created and/or analyzed during the current study is provided at the request of the relevant author.

Notes

  1. Technique for Order Preference by Similarity to Ideal Solution.

References

  • Abdalla, M., Jones, M., Yeluripati, J., Smith, P., Burke, J., & Williams, M. (2010). Testing DAYCENT and DNDC model simulations of N2O fluxes and assessing the impacts of climate change on the gas flux and biomass production from a humid pasture. Atmospheric Environment, 44(25), 2961–2970.

    Article  CAS  Google Scholar 

  • Agussabti, A., Diansyah, R., Satriyo, P., & Munawar, A. A. (2020). Data analysis on near infrared spectroscopy as apart of technology adoption for cocoa farmer in Aceh Province, Indonesia. Data in Brief, 29(2020), 105251. https://doi.org/10.1016/j.dib.2020.105251

    Article  CAS  Google Scholar 

  • Andrews, J. A., Harrison, K. G., Matamala, R., & Schlesinger, W. H. (1999). Separation of root respiration from total soil respiration using Carbon-13 labeling during free-air carbon dioxide enrichment (FACE). Soil Science Society of America Journal, 63, 1429–1435.

    Article  CAS  Google Scholar 

  • Ansari, M. J., Khoramdel, S., Ghorbani, R., & Pirdashti, H. (2015). Evaluation of global warming potential for rice in the first and second cropping patterns (Case study: Sari Province). Research in Fields Crops, 3(1), 14–26.

    Google Scholar 

  • Begum, K., Kuhnert, M., Yeluripati, J., Ogle, S., Parton, W., Kader, M. A., & Smith, P. (2018). Model based regional estimates of soil organic carbon sequestration and greenhouse gas mitigation potentials from rice croplands in Bangladesh. Land, 7, 82. https://doi.org/10.3390/land7030082

    Article  Google Scholar 

  • Bowden, R. D., Nadelhoffer, K. J., Canary, J. D., & Kaye, J. P. (1993). Contributions of aboveground litter, belowground litter and root respiration to soil respiration in a temperate mixed hardwood forest. Canadian Journal of Forest Research, 23, 1402–1407.

    Article  Google Scholar 

  • Brejda, J. J., Moorman, T. B., Karlen, D. L., & Dao, T. H. (2000). Identification of regional soil quality factors and indicators: I. Central and southern high plains. Soil Science Society of America Journal, 64, 2115–2124.

    Article  CAS  Google Scholar 

  • Cui, X., Wang, Y., Niu, H., Wu, J., Wang, S., Schnug, E., Rogasik, J., Fleckenstein, J., & Tang, Y. (2005). Effect of long-term grazing on soil organic carbon content in semiarid steppes in Inner Mongolia. Ecological Research, 20, 519–527.

    Article  Google Scholar 

  • Dashtaki, S. G., Homaee, M., & Khodaverdiloo, H. (2010). Derivation and validation of pedotransfer functions for estimating soil water retention curve using a variety of soil data. Soil Use and Management, 26(1), 68–74.

    Article  Google Scholar 

  • Dastan, S., Soltani, A., Noormohamadi, G., Madani, H., & Yadi, R. (2016). Estimation of the carbon footprint and global warming potential in rice production systems. Environmental Sciences Quarterly, 14(1), 19–28.

    Google Scholar 

  • Davidson, E. A., Belk, E., & Boone, R. D. (1998). Soil water content and temperature as independent or confounded factors controlling soil respiration in a temperate mixed hardwood forest. Global Change Biology, 4, 217–227.

    Article  Google Scholar 

  • Davidson, E. A., & Janssens, I. A. (2006). Temperature sensitivity of soil carbon decomposition and feedbacks to climate change. Nature, 440, 165–173. https://doi.org/10.1038/nature04514

    Article  CAS  Google Scholar 

  • Del Grosso, S. J., Halvorson, A. D., & Parton, W. J. (2008). Testing DAYCENT model simulations of corn yields and nitrous oxide emissions in irrigated tillage systems in Colorado. Journal of Environmental Quality, 37, 1383–1389.

    Article  Google Scholar 

  • Della Chiesa, T., Del Grosso, S. J., Hartman, M. D., & Parton, W. J., Echarte, L., Yahdjian, L., & Piñeiro, G. (2022). A novel mechanism to simulate intercropping and relay cropping using the DayCent model, Ecological Modelling, Elsevier, vol. 465(C). https://doi.org/10.1016/j.ecolmodel.2021.109869

  • Energy Balance. (2014). Department of energy. Power and energy affairs.

  • Ewert, F., Rounsevell, M. D. A., Reginster, I., Metzger, M. G., & Leemans, R. (2005). Future scenarios of European agricultural land use. Estimating changes in crop productivity. Agricultura Ecosystem Environmental, 107, 101–116.

    Article  Google Scholar 

  • Gaillard, R. K., Jones, C. D., Ingraham, P., Collier, S., Izaurralde, R. C., Jokela, W., Osterholz, W., Salas, W., Vadas, P., & Ruark, M. D. (2017). Underestimation of N2O emissions in a comparison of the DayCent, DNDC, and EPIC models. Ecological Applications, 28(3), 694–708.

    Article  Google Scholar 

  • Gathany, M. A., & Burke, I. C. (2012). DAYCENT simulations to test the influence of fire regime and fire suppression on trace gas fluxes and nitrogen biogeochemistry of Colorado forests. Forests, 3, 506–527. https://doi.org/10.3390/f3030506

    Article  Google Scholar 

  • Grant, B. B., Smith, W. N., Campbell, C. A., Desjardins, R. L., Lemke, R. L., Kröbel, R., McConkey, B. G., Smith, E. G., & Lafond, G. P. (2015). Comparison of DayCent and DNDC models: Case studies using Ddata from long‐term experiments on the Canadian prairies. First published, Book series: Advances in agricultural systems modeling.

  • Guest, G., Kröbel, R., Grant, B., Smith, W., Sansoulet, J., Pattey, E., Desjardins, R., Jégo, G., Tremblay, N., & Tremblay, G. (2017). Model comparison of soil processes in eastern Canada using DayCent, DNDC and STICS. Nutrient Cycling in Agroecosystems, 109(3), 211–232.

    Article  CAS  Google Scholar 

  • Hartman, M., Merchant, E. R., Parton, W. J., Gutmann, M. P., Lutz, S., & Williams, S. A. (2011). Impact of historical land-use changes on greenhouse gas exchange in the U.S. Great plains, 1883–2003. Ecological Applications, 21(4), 1105–1119.

    Article  Google Scholar 

  • Homaee, M., Dirksen, C., & Feddes, R. (2002). Simulation of root water uptake: I. Non-uniform transient salinity using different macroscopic reduction functions. Agricultural Water Management, 57(2), 89–109.

    Article  Google Scholar 

  • IPCC. (2007). Summary for policy makers. Climate change 2007: The physical science basis. Contribution of working group I to the fourth assessment report. Cambridge university press, Cambridge.

  • Izaurralde, R., Williams, C. J. R., Post, W. M., & Thomson, A. M. (2007). Long-term modeling of soil C erosion and sequestration at the small watershedscale. Climatic Change, 80, 73–90.

    Article  CAS  Google Scholar 

  • Jamalipor, M., Ghorbani, M., & Koocheki, A. R. (2016). Estimating the economic value of greenhouse gases emissions of oilseeds in Iran. Journal of Agricultural Economics and Development, 29(3), 224–241.

    Google Scholar 

  • Jozi, S. A., & Majd, N. M. (2014). Health, safety, and environmental risk assessment of steel production complex in central Iran using TOPSIS. Environmental Monitoring and Assessment, 186(10), 6969–6983.

    Article  CAS  Google Scholar 

  • Khodaverdiloo, H., Homaee, M., Van Genuchten, M. T., & Dashtaki, S. G. (2011). Deriving and validating pedotransfer functions for some calcareous soils. Journal of Hydrology, 399(1), 93–99.

    Article  CAS  Google Scholar 

  • Kottegoda, N. T., & Rosso, R. (2008) . Applied statistics for civil and environmental engineers. Wiley-Blackwell.

  • Lafleur, P. M., Moore, T. R., Roulet, N. T., & Frolking, S. (2005). Ecosystem respiration in a cool temperate bog depends on peat temperature but not water table. Ecosystems, 8, 619–629.

    Article  CAS  Google Scholar 

  • Li, C. (2000). Modelling trace gas emissions from agricultural ecosystems. Nutrient Cycling in Agroecosystems, 58, 259–276.

    Article  CAS  Google Scholar 

  • Li, C., Frolking, S., & Frolking, T. A. (1992). A model of nitrous oxide evolution from soil driven by rainfall events: 2. Applications. Journal of Geophysical Research: Atmospheres, 97(D9), 9777–9783.

    Article  CAS  Google Scholar 

  • Marquardt, D. (1963). An algorithm for least-squares estimation of nonlinear parameters. SIAM Journal on Applied Mathematics, 11, 431–441. https://doi.org/10.1137/0111030

    Article  Google Scholar 

  • Mayer, A., & Silver, W. (2022). DayCent simulations for California annual grasslands: Monthly data outputs, Dryad, Dataset. https://doi.org/10.6078/D1DD85

  • Mielnick, P. C., & Dugas, W. A. (2000). Soil CO2 flux in a tallgrass prairie. Soil Biology & Biochemistry, 32, 221–228.

    Article  CAS  Google Scholar 

  • Ostad-Ali-Askar, K., Su, R., & Liu, L. (2018). Water resources and climate change. Journal of Water and Climate Change, 9(2), 239. https://doi.org/10.2166/wcc.2018.999

    Article  Google Scholar 

  • Ostad-Ali-Askari, K., Shayannejad, M., Eslamian, S., Zamani, F., Shojaei, N., Navabpour, B., Majidifar, Z., Sadri, A., Ghasemi-Siani, Z., Nourozi, H., Vafaei, O., & Homayouni, S. M. A. (2017). Chapter No. 18: Deficit irrigation: Optimization models. Management of drought and water scarcity. Handbook of drought and water scarcity, Vol. 3, pp: 373–389. Taylor & Francis Publisher. Imprint: CRC Press. eBook ISBN: 9781315226774. 1st Edition. https://doi.org/10.1201/9781315226774

  • Ozkan, B., & Akcaoz, H. (2002). Impacts of climate factors on yields for selected crops in Turkey. Mitigation and Adaptation Strategy for Global Change, 7, 367–380.

    Article  Google Scholar 

  • Rajabi, M. H., Soltani, A., Zeinali, E., & Soltani, E. (2012). Evaluation of greenhouse gas emission and global warming potential in wheat production in Gorgan, Iran. Electronic Journal of Crop Production, 5(3), 23–44.

    Google Scholar 

  • Rajan, K. (2010). Soil organic carbon-The most reliable indicator for monitoring land degradation by soil erosion. Current Science, 99(6), 823–827.

    CAS  Google Scholar 

  • Reay, D. S., Davidson, E. A., Smith, K. A., Smith, P., Melillo, J. M., Dentener, F., & Crutzen, P. J. (2012). Global agriculture and nitrous oxide emissions. Nature Climate Change, 2, 410–416.

    Article  CAS  Google Scholar 

  • Robertson, G. P., Paul, E. A., & Harwood, R. R. (2000). Greenhouse gases in intensive agriculture: Contributions of individual gases to the radiative forcing of the atmosphere. Science, 289, 1922–1935.

    Article  CAS  Google Scholar 

  • Rosenzweig, C., & Tubiello, F. N. (2007). Adaptation and mitigation strategies in agriculture: An analysis of potential synergies. Mitigation and Adaptation Strategy for Global Change, 12, 855–873.

    Article  Google Scholar 

  • Salinger, M. J. (2005). Climate variability and change: Past, present and future-An overview. Climate Change, 70, 9–29.

    Article  CAS  Google Scholar 

  • Schimel, J. P., & Gulledge, J. (1998). Microbial community structure and Princeton. NJ. Princeton University Press.

    Google Scholar 

  • Shepherd, A., & Cardenas, L. M. (2019). Metrics of biomass, live-weight gain and nitrogen loss of ryegrass sheep pasture in the 21st century. Sience of the Total Environment, 685, 428–441.

    Article  CAS  Google Scholar 

  • Silva, Y. F., Valadares, R. V., Dias, H. B., Cuadra, S. V., Campbell, E. E., Lamparelli, R. A. C., Moro, E., Battisti, R., Alves, M. R., Magalhães, P. S. G., & Figueiredo, G. K. D. A. (2022). Intense pasture management in Brazil in an integrated crop-livestock system simulated by the DayCent model. Sustainability, 14(6), 3517. https://doi.org/10.3390/su14063517

    Article  CAS  Google Scholar 

  • Talebmorad, H., Abedi-Koupai, J., Eslamian, S., Mousavi, S. F., Akhavan, S., Ostad-Ali-Askari, K., & Singh, V. P. (2021). Evaluation of the impact of climate change on reference crop evapotranspiration in Hamedan-Bahar plain. International Journal of Hydrology Science and Technology, 11(3), 333–347. https://doi.org/10.1504/IJHST.2021.114554

    Article  Google Scholar 

  • Thelen, K. D., Fronning, B. E., Kravchenko, A., Min, D. H., & Robertson, G. P. (2010). Integrating livestockmanure with a corn–soybean bioenergy cropping system improves short-term carbon sequestration rates and net global warming potential. Biomass and Bioenergy, 34, 960–966.

    Article  CAS  Google Scholar 

  • Weiler, D. A., Tornquist, C. G., Zschornack, T., Ogle, S. M., Carlos, F. S., & Bayer, C. (2018). Daycent simulation of methane emissions, grain yield, and soil organic carbon in a subtropical paddy rice system. Revista Brasileira de Ciência do Solo, vol.42, ISSN 1806–9657.

  • Yue, Q., Cheng, K., Ogle, S., Hillier, J., Smith, P., Abdalla, M., Ledo, A., Sun, J., & Pan, G. (2019). Evaluation of four modelling approaches to estimate nitrous oxide emissions in China’s cropland. Science of the Total Environment, 20(652), 1279–1289.

    Article  Google Scholar 

  • Zarinkafsh, M., Sabbaghi, A. M., & Nalbandi-Gharaghieh, Z. (2015). Study and determination of organic carbon sequestration in three types of soils and vegetation in some lands of Qazvin and Zanjan provinces. Environmental Researches, 6(11), 109–118.

    Google Scholar 

Download references

Acknowledgements

The authors express their gratitude to the officials of the Soil Laboratory of Shahid Chamran University of Ahvaz for their assistance in various stages of this research. The authors also thank the Iranian Meteorological Organization for providing the required meteorological data.

Author information

Authors and Affiliations

  1. Department of Climatology, Faculty of Geography and Environmental Sciences, Hakim Sabzevari University, Sabzevar, Iran

    Nasrin Moradi-Majd

  2. Faculty of Geography and Environmental Sciences, Hakim Sabzevari University, Sabzevar, Iran

    Gholamabbas Fallah-Ghalhari

  3. Department of Land evaluation, Soil and Water Research Institute, Agricultural Research, Education and Extension Organization (AREEO), Tehran, Iran

    Mansour Chatrenor

Authors
  1. Nasrin Moradi-Majd
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Gholamabbas Fallah-Ghalhari
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Mansour Chatrenor
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Gholamabbas Fallah-Ghalhari.

Ethics declarations

Conflict of interest

The authors declare no competing interests.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Moradi-Majd, N., Fallah-Ghalhari, G. & Chatrenor, M. Estimation of greenhouse gas emission flux from agricultural lands of Khuzestan province in Iran. Environ Monit Assess 194, 811 (2022). https://doi.org/10.1007/s10661-022-10497-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s10661-022-10497-8

Keywords

Search

Navigation