Presentation on theme: "Parameterization of EUSES Chemical Fate Model for Israel: EUSES-IL Ella Cohen-Hilaleh Mary Kloc June 2010."— Presentation transcript:
Parameterization of EUSES Chemical Fate Model for Israel: EUSES-IL Ella Cohen-Hilaleh Mary Kloc June 2010
Project Outlines Introduction Model description – EUSES. Data collection. Findings – test case, sensitivity analysis. Conclusion.
Project outlines Pollution of natural resources is a main concern of the developing world. Pollution sources: Natural sources – fire, oil leak, saline springs… Man-made sources – industrial spills, agricultural fertilizers and pesticides, domestic sewage, transportation emissions… Prediction of pollutant concentration in the environment is required.
Project outlines Purpose: Adjusting EUSES model to Israel for interface with Eco–Indicator. Method: Wide data collection, reprogramming of EUSES, test sample by comparison with local data of spills and residues monitoring, sensitivity analysis. EUSES – a European model for steady state pollutant distribution.
Introduction to Mass Balance Models This represents one environmental compartment (either air, water, soil, etc.) at one spatial location.
Introduction to Mass Balance Models Chemical, such as a pesticide, is emitted into the compartment at a certain rate.
Introduction to Mass Balance Models Chemical can move between different environmental compartments (e.g., from water to soil)
Introduction to Mass Balance Models Chemical can move between different environmental compartments (e.g., from water to soil) and between different spatial compartments.
Introduction to Mass Balance Models Chemical can also be formed and degraded through reactions.
Introduction to Mass Balance Models flow inflow out Mass flow for the single compartment:
Introduction to Mass Balance Models flow inflow out Mass flow for the single compartment: 0= Steady state approximation
Relevant Output Concentration in the compartment: Residence Time: the average time the chemical spends in the box
Extension to Two Compartments
SimpleBox nested spatial scales, each with a set of environmental compartments:
Example from SimpleBox model Emitted into soil only
Example from SimpleBox model Moves between environmental compartments at various rates
Example from SimpleBox model Moves between spatial compartments at various rates
Example from SimpleBox model Degrades through reaction
Example from SimpleBox model Most of the chemical remains in the soil compartment.
Parameterization for Israel unchanged Israel Element from our partition
Input data to the model – Demographic data Geophysical data Chemical data Sources: Direct from literature – Scientific & Governmental sources. Indirect - Estimations. Will see some main informative figures..
CBS’ division of Israel - Districts, Sub-Districts and Natural Regimes,
Population density - Israel
CBS’ division of Israel - Districts, Sub-Districts and Natural Regimes, Population density - Israel South sk.km Center – 1300 sk.km Jerusalem – 650 sk.km North – 4600 sk.km Israel – 22,000 sk.km Tel Aviv – 170 sk.km Hifa – 860 sk.km Land use distribution in Israel by district 2
Yearly rain average map ( ) 6
Drainage basins of Israel 4,5 Yearly rain average map ( ) 6
Soil map of Israel 7 Runoff coefficients were estimated according to: Soil type Land use Rational Equation Q=ciA Q = Peak discharge [L 3 /T] c = Rational method runoff coefficient i = Rainfall intensity [L/T] A = Drainage area, [L 2 [ Runoff determination 11
Converted Soil Erosion (mm/year) Soil Erosion in literature (ton/km^2/ year) Hilly areas under vines Wheat areas Olives Shrubland Yatir 10 Assuming bulk density of 1.4 g/cm 3 Conversion via bulk density: Sandy soils – g/cm 3 Fine-textured soils– g/cm 3 Soil erosion degree 8
Converted Soil Erosion (mm/year) Soil Erosion in literature (ton/km^2/ year) Hilly areas under vines Wheat areas Olives Shrubland Yatir 10 Assuming bulk density of 1.4 g/cm 3. Conversion via bulk density: Sandy soils – g/cm 3 Fine-textured soils– g/cm 3 Soil erosion degree 8 Color index for soil erosion rate (Estimated) Color soil erosion (mm/year) green0.05 brown0.1 red0.2 light green0.05 pink0.1 purple0.2 dark yellow0.1 yellow0.2 blue0.3 greybuilt up area Golan, Negev and Yehuda desert0.2 Wadi0.3 other0.2
Water table 12 Large variation over time – so minimum water tables were taken: Coastal aquifer Yarkon-Taninim aquifer Western Galilee
Test sample – Pesticides in Lake Kinneret Comparison of EUSES-IL prediction to measured concentration in the main water compartment. Input: Estimated amounts that are released to the environment each year, from documented purchase-lists.
Test sample – Pesticides in Lake Kinneret Comparison of EUSES-IL prediction to measured concentration in the main water compartment. Input: Estimated amounts that are released to the environment each year, from documented purchase-lists. Pesticide use comparison for 1996, 1997 and The Agricultural Extension Service recommendations (SHAHAM) between different crops 13 : No significant differences between crops, years and professional recommendations.
Pesticides bought in
GroupChemical class Commercial name Active material Insecticide & AcaricideOrganochlorineThionexEndosulfan Insecticide & AcaricideOrganophosphateDiazolDiazinon HerbicideTriazineAtranexAtrazine Endosulfan Diazinon Atrazine Tested chemicals
Pesticide residue concentration (ppb) in lake Kinneret water 14 Monitoring data -
Results of Testing Endosulfan Diazinon Atrazine
Comparison with EUSES and measured values Endosulfan Diazinon Atrazine 0.93 ton/year0.03 ton/year 4.44 ton/year
TemperatureWind speedRain RateRiver FlowSea Area Area Fraction Agricultural Soil Our model is more dependent on geographical information than EUSES. We divide the regions using mostly geographical data We also consider the geographical locations of different soil types, water types, etc., within each region. Geographical parameters are not distributed throughout large regions as in EUSES, but are very region-specific. Most other non-geographical parameters had similar sensitivities between models. Except wind speed (?)
Chemical properties of tested chemicals EndosulfanDiazinon Atrazine
EndosulfanDiazinon Atrazine Chemical properties of tested chemicals
Conclusion EUSES-IL is a significantly improved model compared to EUSES. Possible future improvements: Incorporate more accurate chemical equations into the model. More specific information is required for optimizing results (chemical use, geophysical data). Find more measured data for testing and optimizing the model.
References 1.Central Bureau of Statistics - Statistical Abstract of Israel No Statistical Abstract of Israel 2009-No.60, Table Perlmutter M. Springs and streams in Israel report of the SPNI (1), according to Hydrological Service data. 4. Israel Hydrological service. 5. Website of Moto Track: 6. Gvirtzman, H Israel Water Resources, Chapters in Hydrology and Environmental Sciences, Yad Ben-Zvi Press, Jerusalem, 301 p. 7. Ministry of Agriculture – Agricultural research organization & soil conservation and drainage department Soil Survey, Ministry of Agriculture, Soil Conservation unit, Kosmasa C et al. The effect of land use on runoff and soil erosion rates under Mediterranean conditions(1997) Catena, 29 (1), pp Laronne J., Lekach J., Cohen H., Alexandrov Y. Experimental Drainage Basins in Israel: Rainfall, Runoff, Suspended Sediment and Bedload Monitoring American Geophysical Union, Fall Meeting 2002, abstract #H51B Website of Mountain Empire Community College – Big Stone Gap, Virginia: 12. Hydrological Representative Date - February 2010, Israel Water Authority, Israel Hydrological Service: elyon1.court.gov.il/heb/mayim/Hodaot/hs_01.pdf 13. Bar-Ilan I., Melman G. Survey of pesticides use in the Northern drainage basin of Lake Kinneret (1998) MIGAL - Galilee Technology Center. Kiryat-Shmona, Israel. 14. Zohary T. et al. Kinneret research and monitoring – lab work report for 2008 (T 9/2009) ) Kinneret Limnonological Laboratory, Israel Oceanographic and Limnological Research. 15. Kawamoto K, MacLeod M, Mackay D. Evaluation and comparison of multimedia mass balance models of chemical fate: application of EUSES and ChemCAN to 68 chemicals in Japan. Chemosphere 44 (2001) Brandes LJ, den Hollander H, van de Meant D. SimpleBox 2.0: a nested multimedia fate model for evaluating the environmental fate of chemicals. RIVM report no , Netherlands.
Parameterization for Israel Units EUSES Default CIsrael C Land Areakm Sea Areakm Area Fraction Fresh Water Area Fraction Natural Soil Area Fraction Agricultural Soil Area Fraction Other Soil Average Temperature ◦C◦C1220 Average Wind Speedm/s34.5 Rain Ratemm/yr Depth of Fresh Waterm33 River Flow between continent and region Runoff Fraction 0.25 Infiltration Fraction 0.25 Soil Erosionmm/yr0.03