Desertification susceptibility in ecoregions of Khorasan-Razavi based on Life Cycle Assessment (LCA)

Document Type : Full length article

Authors

1 MSc. Student in Desert Region Management, Ferdowsi University of Mashhad, Mashhad, Iran

2 Assistant Professor of Environment, Ferdowsi University of Mashhad, Mashhad, Iran

3 Professor of Environment, Ferdowsi University of Mashhad, Mashhad, Iran

4 MSc. in Environmental Sciences, Ferdowsi University of Mashhad, Mashhad, Iran

Abstract

Introduction
In the recent decades, mismanagement, human activities and climatic conditions developed a new view of Iran ecosystems, called desertification. Life cycle assessment (LCA) is a method to construct environmental profile of production systems. That was developed by industrial instruments, but in recent years it is applied by agricultural production process as well. Today, it is acknowledged that land use should be assessed by LCA, but there is still no consensus on the parameters for assessment. In order to assess such land use impact, it is initially necessary to define the variables in the LCI. Once the inventory data is gathered, the LCI results have to be characterized in the impact assessment phase. The main framework of LCA is based on the "from cradle to grave" where we are able to evaluate environmental impacts truly from start point to the end. In this way, we can use the theory of LCA to assess desertification indicators and estimation of ecosystem resistance to this phenomenon. Thus, in this research an LCA approach was applied for estimate ecosystem susceptibility to desertification.
 
Materials and Methods
This research concentrated on the role of LCA to distinguish ecosystem susceptibility to desertification phenomenon. In this way, at first the land units were considered Ecoregions, the region with similar ecological and climatic characteristics, and six ecoregions has been identified. Then, based on Delphi methodology, six main factors were determined. These are aridity, landuse, wind erosion, soil erodibility, salinity, and vegetation density. To calculate aridity, FAO/UNEP aridity index (P/ETP) was used. The land use map was developed by ETM+ imagery data and distinguished six classes including; desert, bare lands, cultivated lands, settlements, rangelands and forest. A report of critical center of wind erosion prepared by KR organization of Natural Resources and watershed management was applied for wind erosion. Soil erodibility was calculated based on the Sepehr et al. 2014. Salinity and vegetation indices were calculated by spectural ratio of imagery data. To assess susceptibility degree a characteristic factor (CF) for each ecoregion has been calculated. One of the main contributions of this study is the establishment of desertification impact CFs for the ecoregion. The divisions between these areas are based on climatic and vegetative cover factors, both aspects having a major influence on soil desertification risk. Thus, after calculating CF for each ecoregion total characteristic factor was developed by geometric mean of each CF. Ultimately, the susceptibility degree to the desertification was evaluated and mapped.
 
Results and Discussion
The results indicated the high preference aridity and wind erosion at Khorasan Razavi province which is in relation to the climatic conditions and land use changes in the recent years. The greatest desertification risk is found in the moderate arid desert ecoregion, with a CF of 2.21. The susceptible ecoregions mainly covered more than 70% of the KR areas. In this case, the desertification impact of the activity should not be integrated in LCA studies. This can be used to identify those cases without desertification impact. The LCIA Desertification value is also zero when CFi or any other variable is zero. A value of zero for CFi means that the activity being studied is in an ecoregion with no desertification risk. The LCI Desertification value of the activity being assessed is determined by the addition of the individual values given to each of the sex variables, according to a scale of values. This paper provides CFs including desertification impact in LCA studies, and the variables suggested allow the comparison of the benefits and threats posed by different human activities.
 
Conclusion
In this research, an LCA methodology was developed for assessment of ecosystem susceptibility to desertification phenomenon. Main biophysical variables including aridity, wind erosion, landuse, erodibility, salinity, and vegetation density belong to the driving force, state and pressure frameworks. The desertification impact evaluation of any human activity in a LCA should include these common, basic four variables. The purpose of this research is to investigate desertification susceptibility degree of ecoregions at Khorasan Razavi as vulnerable province to land degradation and desertification in Iran. In this study, we applied Life Cycle Assessment (LCA) framework to assess susceptibility. In the first, an ecoregions map was provided by adjusted De-Marton climate index. Six main indicators including aridity, land use, wind erosion, soil erodibility, salinity, and vegetation cover were determined by Delphi methodology. The preference degree of each indicator was calculated using Entropy algorithm. Ultimately, we estimated characterization factor (CF) for each ecoregion. The layer integration was done using geometric mean with desertification susceptibility map. The results showed that the ecoregion of moderate arid desert is most susceptible to desertification.

Keywords

Main Subjects


  • اختصاصی، م.ر. و سپهر، ع. (۱۳۹۰). روش‌ها و مدل‌های ارزیابی و تهیة نقشة بیابان‌زایی، انتشارات دانشگاه یزد.
  • سپهر، ع. (1392). تعادل ترمودینامیکی و فروپاشی کاتاستروفیک اکوسیستم: بیابانی‌شدن و گذرهای بحرانی، مجلة جغرافیا و برنامه‌ریزی محیطی، 25(2): 119-132.
  • سپهر، ع. و پرویان، ن. (۱۳۹۲). تهیة نقشة آسیب‌پذیری بیابان‌زایی و اولویت‌بندی راهبردهای مقابله در اکوسیستم‌های استان خراسان رضوی بر پایة الگوریتم نارتبه‌ای پرامسه، مجلة پژوهش‌های دانش‌زمین، 2(8): ۵۸-۷۱.
  • مومنی، م. (۱۳۸۵). مباحث نوین تحقیق در عملیات، انتشارات دانشکدة مدیریت دانشگاه تهران.

 

  • Allbed, A. and Kumar, L. (2013). Soil Salinity Mapping and Monitoring in Arid and Semi-Arid Regions Using Remote Sensing Technology, Advances in Remote Sensing, 2: 373-385.
  • Bailey, R.G. (2014). Ecoregions, Springer Science, New York.
  • Bailey, R.G. (1996). Ecosystem geography, Springer, New York.
  • Blonk, H.; Lindeiger, E. and Broers, J. (1997). Towards a Methodology for Taking Physical Degradation of Ecosystems into Account in LCA, 6th SETAC-Europe Meeting, 2: 91-98.
  • Cowell, S.J. and Clift, R. (2000). A methodology for assessing soil quantity and quality in life cycle assessment, Journal of Cleaner Production, 8(4): 321-331.
  • Cowell, S.J. and Lindeijer, E. (2000). Impacts on ecosystems due to land use: biodiversity, life support, and soil quality in life cycle assessment, In Agricultural data for life cycle assessment, 8(4): 313-319.
  • DESERTLINKS (2004). Desertification Indicator System for Mediterranean Europe (DIS4ME). European Commission, Contract EVK2-CT-2001-00109, http://www.kcl.ac.uk/projects/desertlinks/ (last accessed date August 5, 2008).
  • Ekhtesasi, M.R. and Sepehr, A. (2011). Methods and Models of Desertification Assessment and Mapping, Yazd Univercity.
  • Garrigues, E.; Corson, M.S.; Angers, D.A.; Werf, H. and Walter, C. (2012). Soil quality in Life Cycle assessment: Towards development of an indicator, Elsevier, 18: 434-442.
  • ISO, 2006a. ISO 14040 International Standards. In: Environmental Management – Life Cycle Assessment – Principles and Framework. International Organisation for Standardization, Geneva, Switzerland.
  • Jabbar, M.T. (2012). Assessment of Soil Salinity Risk on the Agricultural Area in Basrah Province, Iraq: Using Remote Sensing and GIS Technique, Journal of Earth Science, 23(6): 881–891.
  • Khan, M.N.; Rastoskuev, V.V.; Sato, Y. and Shiozawa, S. (2005). Assessment of hydrosaline land degradation by using a simple approach of remote sensing indicators, Elsevier, 77(1-3): 96-109.
  • Koellner, T. and Scholz, R. (2007). Assessment of Land Use Impacts on the Natural Environment, International Journal of Life Cycle Assessment, 13(1): 32-48.
  • Mehta, M.; Anh, V.Le.; Saha, S.K. and Agrawal, Sh. (2012). Evaluation of Indices and Parameters Obtained from Optical and Thermal Bands of Landsat 7 ETM+ for Mapping of Salt- Affected Soils and Water-Logged Areas, Asian Journal of Geoinformatics, 12(4): 9-16.
  • Mila i Canals, L.; Bauer, C.; Depestele, J.; Dubreuil, A.; Freiermuth Knuchel, R.; Gaillard, G.; Michelsen, O.; Muller-Wenk, R. and Rydgren, B. (2007). Key elements in framework for land use impact assessment within LCA, The International Journal of Life Cycle Assessment, 12(1): 5–15.
  • Momeni, M. (2007). New Issues of Operation Research, Univercity of Tehran.
  • Nunez, M. (2011). Modelling Location-dependent environmental impacts in Life Cycle Assessment: Water use, desertification and soil erosion. Doctoral thesis, Dr. Assumpcio Anton Vallejo, Environmental Science and Technology, Univercity Autonoma de Barcelona, 203p.
  • Nunez, M.; Civit, B.; Muñoz, P.; Arena, A.P.; Rieradevall, J. and Antón, A. (2010). Assessing potential  desertification environmental impact in life cycle assessment, Int J Life Cycle Assess, 15(1): 67–78.
  • Sepehr, A. (2014). Thermo­ dynamic Equlibrium and Catastrophic Collapse: Desertification and Critical Transition, Geography and Environmental Planning, 25(2): 119-132.
  • Sepehr, A. and Parvian, N. (2014). Desertification vulnerability mapping and Developing Combating Strategies in the Ecosystem of Khorasan Razavi Province using PROMETHEE Algoritm, Journal of Earth Science researchers, 2(8): 58-71.
  • Sepehr, A.; Zucca, Cl. and Nowjavan, M.R (2014). Desertification Inherent Status Using Factors Representing Ecological Resilience, British Journal of Environment & Climate Change, 4(3): 279-291.
  • Society of Environmental Toxicology and Chemistry (SETAC) and SETAC Foundation for Environmental Education Inc. (1991). ‘A Technical Framework for Life−cycle Assessment’, Washington, DC: Society of Environmental Toxicology and Chemistry and SETAC Foundation for Environmental Education Inc. (Workshop held in Smugglers Notch, Vermont, August 18-83, 1990).
  • Tervonen, T.; Sepehr, A. and Kadzinski, M. (2015). Regional anti-desertification management with a multi-criteria inference approach, Journal of Environmental Management, 162: 9-19.
  • United Nations (1994). United Nations Convention to Combat Desertification in Countries Experiencing serious Drought and/or Desertification, Particularly in Africa.
  • Wagendrop, T.; Gulinck, H.; Coppin, P. and Muys, B. (2006). Land use impact evaluation in life cycle assessment based on ecosystem thermodynamics, Elsevier, 31(1): 112-125.