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GHG Risk Assessment Tool (Beta Version) USER MANUAL

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4. and the mean square errors Table 1 expresses how to estimate the values of the limits of the 67 confidence interval for the models adopted in this Tool Table 1 lower limit and upper limit of the 67 confidence interval for the models adopted in this Tool Predicted Value lower limit upper limit Gross C CO Flux 1 Predicted Gross C CO Flux 2 3 Predicted Gross C CO Flux 2 3 Gross C CH Flux predicted Gross C CH Flux 3 55 Predicted Gross C CH Flux 3 55 Obs Both models have uncertainty best described on a base 10 logarithmic scale Consequently the factors 2 3 and 3 55 are derived from 10 and mo respectively Page 17 GHG Risk Assessment Tool Beta Version USER MANUAL 602 ANNEX 3 DATASET FOR THE DEVELOPMENT OF THE EMPIRICAL MODELS Page 18 603 604 605 606 607 608 609 610 611 612 613 614 615 616 617 618 619 620 621 622 623 624 625 626 627 628 629 630 631 632 633 GHG Risk Assessment Tool Beta Version USER MANUAL ANNEX 3 DATASET FOR THE DEVELOPMENT OF THE EMPIRICAL MODELS The initial source for data was obtained from Barros et al 2011 This data was revised by comparing with the information from the original sources and complemented by data from more recent papers see bibliographic references in the dataset tables and at the end of this ANNEX and by estimates of the p
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6. puo Bu e264 memmun amano So M RE emma mes sumo ang RO sone rel Pees sey men me ian ening seng ung Swen rom a seni xn HO 09 ng HO xny 670 Page 24 671 672 673 674 675 676 677 678 679 680 681 682 683 684 685 686 687 688 689 690 691 692 693 694 695 696 697 698 699 700 701 702 703 704 705 706 707 708 709 710 GHG Risk Assessment Tool Beta Version USER MANUAL Bibliographic References berg J Bergstr m A K Algesten G S derback K amp Jansson M 2004 A comparison of the carbon balances of a natural lake L rtr sket and a hydroelectric reservoir L Skinnmuddselet in northern Sweden Water Research 38 3 531 538 Abril G Gu rin F Richard S Delmas R Galy Lacaux C Gosse P Tremblay A Varfalvy L Santos A and Matvienko 2005 Carbon dioxide and methane emissions and the carbon budget of a 10 years old tropical reservoir Petit Saut French Guiana Global Biogeochem Cycles 19 GB 4007 doi 10 1029 2005GB002457 Barros N Cole J J Tranvik L J Prairie Y T Bastviken D Huszar V L M del Giorgio P Roland F 2011 Carbon emission from hydroelectric reservoirs linked to reservoir age and latitude Nature Geoscience http dx doi org 10 1038 ngeo1211 2011 Bergstrom A K Algesten G Sobek S
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9. Climatic Change 66 1 2 9 21 Santos M A 2003 Ciclo e emiss es de gases de efeito estufa derivadas do reservat rio hidroel trico de Ribeirdo das Lajes LIGHT In Relat rio Final out Projeto IVIG 3856 LIGHT Rio de Janeiro RJ Santos M A Rosa L P Sikar B Sikar E amp Dos Santos E O 2006 Gross greenhouse gas fluxes from hydro power reservoir compared to thermo power plants Energy Policy 34 4 481 488 Schellhase H U Maclsaac E A amp Smith H 1997 Carbon Budget estimates for reservoirs on the Columbia River in British Columbia The Environmental Professional 19 48 57 Sherman B and Ford P 1997 Destratification and water quality in Chaffey Dam ANCOLD IEAUST Seminar Sydney June 27 Sikar E Santos M A Matvienko B Silva M B Rocha C H Santos E Bentes Junior A P and Rosa L P 2005 Greenhouse gases and initial findings on the carbon circulation in two reservoirs and their watersheds Verh Internat Verein Limnol 29 573 576 Smith L K amp Lewis W M 1992 Seasonality of methane emissions from five lakes and associated wetlands of the Colorado Rockies Global Biogeochem Cycles 6 323 338 Page 26 748 749 750 751 752 753 754 755 756 757 758 759 760 761 762 763 764 765 766 767 768 GHG Risk Assessment Tool Beta Version USER MANUAL Soumis N Duchemin E Canuel R amp Lucotte M 2004 Greenhouse gas emissions from reservoirs
10. Malaysia Carlos Tucci IPH UFRGS Brazil Comments and suggestions from members of the UNESCO IHA Peer Review Group Jean Pierre Chabal Tractebel Engineering France Vincent Chanudet EDF France Doug Dixon EPRI USA William J Hamlin Manitoba Hydro Canada Alan Irving Rio Tinto Canada Sonia Lacombe Rio Tinto Canada Niels Nielsen Kator Research Services Australia Jodo Padua EDP Portugal Alan Petitjean EDF France Fabio Roland UFJF Brazil Andrew Scanlon Hydro Tasmania Australia Martin Schmid EAWAG Switzerland Elizabeth Sikar Construmaq S o Carlos Brazil Hakon Sundt SINTEF Norway Page iii 110 111 GHG Risk Assessment Tool Beta Version USER MANUAL LIST OF CONTENTS 1 Introduction viro rr a GT 1 1 1 Background 1 1 2 Objectives and purposes of the GHG Risk Assessment 2 1 3 Updating the GHG Risk Assessment Tool 2 2 The concept of Net GHG Emissions Lynu mmunrmmssmnaemmdkeinnmdm vanniniennn im 3 3 User Guide sake Teen 4 3 1 Structure OF the 4 3 2 Use of the Tool spreadsheet rrinin EENEN 5 3 2 1 Parameters required to run the model sse 5 3 2 2 Results of the simulations crie 5 3 3 Analysis and int
11. While the Project did test the same model structure as for CO little predictive gain was obtained relative to simpler empirical modelling approaches In the end the Project used a semi logarithmic model combined to a regression tree approach with different empirical models for different segments of the variable space In particular we developed a model where CH flux is a function of mean annual temperature mean annual precipitation and age for reservoirs that are 32 years old or less For older reservoirs diffusive methane emissions are constant in time at a level which is determined by temperature and precipitation only The following models were developed For Age lt 32 years C CH4 Flux 1001 46 0 056 Temp 0 00053 Prec 0 0186 Age 0 000288 Age Eq 3 For Age gt 32 years 1 16 0 056 Temp 0 00053 Prec C CH4 Flux 10 Eq 4 The combined equations explain about 42 of the observed variation Its uncertainty is best described by a logarithmic root mean square error of 0 55 Range of variability of the estimates The range of variability of the estimates can be expressed by the confidence interval of the predicted values see section 3 3 2 The confidence interval for the predictions is obtained as P lower limit lt GHG flux lt upper limit a Eq 5 The values of lower limit and the upper limit can be estimated as a function of the predicted values of gross GHG fluxes of CH and
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13. of the western United States Global Biogeochemical Cycles 18 GB3022 doi 10 1029 2003GB002197 St Louis V L Kelly C A Duchemin E Rudd J W M amp Rosenberg D M 2000 Reservoir surfaces as sources of greenhouse gases to the atmosphere A global estimate Bioscience 50 9 766 775 Tadonl k R D Marty J amp Planas D 2011 Assessing factors underlying variation of CO2 emissions in boreal lakes vs reservoirs FEMS Microbiology Ecology 79 2 282 297 doi 10 1111 j 1574 6941 2011 01218 x Therrien J Tremblay A and Jacques R 2005 CO2 Emissions from Semi arid Reservoirs and Natural Aquatic Ecosystems In Tremblay A L Varfalvy C Roehm et M Garneau Eds Greenhouse Gas Emissions Fluxes and Processes Hydroelectric Reservoirs and Natural Environments Environmental Science Series Springer Berlin Heidelberg New York pp 233 250 Tremblay A Therrien J Hamlin B Wichmann E LeDrew L J 2005 In Tremblay A L Varfalvy C Roehm et M Garneau Eds Greenhouse Gas Emissions Fluxes and Processes Hydroelectric Reservoirs and Natural Environments Environmental Science Series Springer Berlin Heidelberg New York pp 233 250 Tremblay A Varfalvy L Roehm C and Garneau M eds 2005 Greenhouse Gas Emissions Fluxes and Processes Hydroelectric Reservoirs and Natural Environments Environmental Science Series Springer New York 732 pages Page 27 769 GHG Risk Assessme
14. Tranvik L amp Jansson M 2004 Emission of CO2 from hydroelectric reservoirs in northern Sweden Archiv Fur Hydrobiologie 159 1 25 42 Chanudet V Descloux S Harby A Sundt H Hansen B H Brakstad O Serca D Guerin F 2011 Gross CO2 and CH4 emissions from the Nam Ngum and Nam Leuk sub tropical reservoirs in Lao PDR Sci Total Environ doi 10 1016 j scitotenv 2011 09 018 Del Sontro T Mcginnis D F Sobek S Ostrovsk y I Wehrl B 2010 Extreme Methane Emissions from a Swiss Hydropower Reservoir Contribution from Bubbling Sediments Environ Sci Technol 2010 44 2419 2425 Demarty M Bastien J 2011 GHG emissions from hydroelectric reservoirs in tropical and equatorial regions Review of 20 years of CH4 emission measurements Energy Policy Volume 39 Issue 7 July 2011 Pages 4197 4206 Diem T Koch S Schwarzenbach S Wehrli B amp Schubert C J 2008 Greenhouse gas emissions CO2 CH4 and N20 from perialpine and alpine hydropower reservoirs Biogeosciences Discussions 5 5 3665 4207 Duchemin E Lucotte M Canuel R amp Chamberland A 1995 Production of the greenhouse gases CH4 and CO2 by hydroelectric reservoirs of the boreal region Global Biogeochem Cycles 9 4 529 540 Fetke Balazs M et al 2000 Global Composite Runoff Fields Based on Observed River Discharge and Simulated Water Balances Complex Systems Research Center University of New Hampshire UNH GRDC Com
15. at Age 1 year was made to potentially vary according to other variables as well After many attempts using different variable combinations the best model had the following structure Flux C 186 0 0 148 Runoff 944 485 1 91 Temp 0 09727 Temp e70 0044 52 339 0 7033 Temp 0 0358 Temp Age Eq 2 The structure of this model implies that 1 the maximum CO2 emission occurring immediately after flooding is a positive function of temperature i e maximum for higher temperatures 2 the new long term equilibrium emissions after the initial pulse is a positive function of runoff higher in locations with higher runoff 3 the steepness of the initial decline the exponential term is a negative function of temperature i e steeper and faster decline at lower temperatures The model explained about 45 of the variation and had an uncertainty best described on a base 10 logarithmic scale root mean square error 0 36 The range of variability of the estimates can be expressed by the confidence interval of the predicted values as described in section 3 3 2 Page 16 572 573 574 575 576 577 578 579 580 581 582 583 584 585 586 587 588 589 590 591 592 593 594 595 596 597 598 599 600 601 GHG Risk Assessment Tool Beta Version USER MANUAL C CH Flux model In the case of methane the same dataset was used but a different modelling approach was adopted
16. availahle High vulnerability to gross GHG emissions NEED TO ASSESS VULNERABILITY TO NET GHG EMISSIONS 500 501 Figure 1 Three step decision tree approach 502 Page 13 Step one Analysis of the capacity of the system upstream catchment to provide carbon and nutrients to the reservoir Step two Analysis of the capacity of the reservoir to create stock Step three Analysis of the capacity of the reservoir to release the available stock 503 504 505 506 507 508 509 510 511 512 513 514 515 516 517 518 519 520 521 522 523 524 525 526 527 528 529 530 531 532 GHG Risk Assessment Tool Beta Version USER MANUAL Summary description of the decision tree Figure 1 The first step estimates the potential supply of organic carbon and nutrients by evaluating the capacity of the contributing areas upstream catchment and flooded area to deliver these to the reservoir This evaluation is done by assessing the carbon and nutrient stock in the catchment vegetation and soil including flooded areas and also by verifying if the available carbon and nutrients are labile If the stock of carbon and nutrient in the catchment is small the carbon and nutrient loads will be small and the site will have a low vulnerability to gross GHG emissions the risk assessment analysis is then complete Otherwise it is necessary to determine if the available carbon and nutrient is labile If the carbon an
17. it is noteworthy that emissions from artificial reservoirs do not involve returning long term sequestered carbon into the system Page 3 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 GHG Risk Assessment Tool Beta Version USER MANUAL 3 User Guide 3 1 Structure of the Tool The tool is presented in an Excel spreadsheet divided in three worksheets Main Simulations and Auxiliary The contents of any of these worksheets can be viewed or printed by the User at any time but the only cells unlocked for the user are the Input Values on worksheet Main A general description of how the input data and results are presented in each of these worksheets is presented below e Worksheet Main e includes the cells for allowing the User to provide the values for all input parameters e shows information on the status of the values provided by the User informing if these values are inside or outside the range of the data used for calibration of the model e shows the results of the simulations Predicted values of gross GHG fluxes of CH and and its associated 67 confidence intervals Qualification of the predicted values as LOW MEDIUM or HIGH emissions compared to the distribution of observed values in the dataset used for calibrat
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19. of a reservoir All river basins naturally emit greenhouse gases The introduction of a reservoir may change the way this carbon is distributed in the system by changing removals GHG burial in sediments and emission patterns The GHG status of freshwater reservoirs is properly assessed only when considering the impact on GHG emissions in a river basin resulting from the creation of such a reservoir at all portions of the river basin influenced by the reservoir and subtracting the effects of unrelated anthropogenic and natural sources As net GHG emissions cannot be measured directly their value has to be estimated by assessing total gross GHG emissions in the affected area comparing values for the pre and post impoundment conditions and excluding unrelated anthropogenic sources UAS This approach has been reported by IPCC 2011 which defines net GHG emissions from freshwater reservoirs as those excluding unrelated anthropogenic sources and pre existing natural emissions and asserts that the assessment of man made net emissions involves a appropriate estimation of the natural emissions from the terrestrial ecosystem wetlands rivers and lakes that were located in the area before impoundment and b abstracting the effect of carbon inflow from the terrestrial ecosystem both natural and related to human activities on the net GHG emissions before and after impoundment Several other recent publications also acknow
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22. resulting from the creation of such a reservoir has been discussed in both scientific and policy forums The uncertainties and lack of consensus on the assessment of the GHG status of freshwater reservoirs led to consultation between scientists the International Hydropower Association IHA and UNESCO s International Hydrological Programme UNESCO IHP with the subsequent launch of the UNESCO IHA GHG Research Project GHG Status of Freshwater Reservoirs This Project hosted by the IHA in collaboration with UNESCO IHP aims to improve understanding of the impact of reservoirs on natural GHG emissions and of the processes involved and to help fill knowledge gaps in this area The Project has run since August 2008 through a consensus based scientific approach involving collaboration among many institutions and experts through participation in workshops development of products deliverables and acting as peer review The resulting deliverables have been reviewed by the Project s peer review group the UNESCO IHA Forum which comprises more than 200 researchers scientists and professionals working in this field from more than 100 institutions including universities research institutes specialist companies and sponsoring agencies The original objectives of the Project are to 1 develop standard guidance for net GHG estimations 2 promote measurements and calculate net emissions from a representative set of reservoirs building a
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25. 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 NATIO SN i gt wane GHG Risk Assessment Tool Beta Version USER MANUAL Derived from The UNESCO IHA Greenhouse Gas Emissions from Freshwater Reservoirs Research Project August 2012 28 GHG Risk Assessment Tool Beta Version USER MANUAL 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 GHG Risk Assessment Tool Beta Version USER MANUAL Derived from The UNESCO IHA Greenhouse Gas Emissions from Freshwater Reservoirs Research Project General Editor Joel A Goldenfum we Er United Nations International Greenhouse Gas Educational Scientific and Hydrological Status of Freshwater Cultural Organization Programme Reservoirs Project 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 GHG Risk Assessment Tool Beta Version USER MANUAL ACKNOWLEDGEMENTS This publication draws from ongoing research hosted by the International Hydropower Association IHA in collaboration with the International Hydrological Programme IHP of UNESCO The collaboration between UNESCO and IHA on this topic is longstanding with dialogue continuing since the late 1990s The first international UNESCO IHA GHG workshop on the topic was convened in Paris France i
26. 1908 is syouepior 02 SO0Z ye va Aeyquias y 1088 69 oraoce 901 601 LI or a s oz t os 19100 erer eres ores os souesoy O OLOZ re ie fol vt 996529 ber Bir Orie tree wz a se opt ow s S06r Orsi 06222 55 vum 29 I 0102 ie je 906579 tur oni tree tre a vio ort ver eu o t st orai I ss emun 28 D 0102 i 995529 ber Bir Oris tree Lud a der opt st or ere tr st soer or gi 00008 0098 ss Un 99 9002 sowes vore soley Scecuo 19 nz 969 tst sc et e Lo 996 ot s v Ss vs BEST 108 69 09 82 s ndien co sez ez u p oL 100 i89 0009 5002 wie veu 55 99 rd var 1982 185 ze 9 68000 ero so z ere sc LTU Lr zs wopBupund t9 9007 2 weer 981 o 269 656 sero em co t 99 60 9s ore gie 79 4661 pue ueuueus 9oscos 4 988 ub zer 06 eal oze oz 0002 r OE ESL 08T 061 os 19 SO0Z re ia feyauuan LI uc 2801 sez a oz z z v9 sels or 09 002 ye 18 veu 186501 o 1961 ue srzi su ooo 801 vie to z stsro ie Lte zeroz ec pw nnbeng Bu gapu ser sneg mou ees p uodu ao gun m pausen oos 1 mou 908
27. 4 oz t se sr sese re S6 Spk v9 por 0050 ost SELEN sal SEL 9008 fie fequi ERIN roser m EN use oo t a sez oe e i or 9r 9005 n eee oro ori anorsnouoL 81 0002 je 1 simons o sie ocv sez oz D n og 09 009 ou 0009 E vernis cal 002 i ia Kor rn og ice a ze ost vo om oz ie oror m zel 1002 Ie 1 47475 968 ire 9oz g 918 sc oe ot LH L3 00807 t wou oris 008781 ort ONS 181 9008 re fequi 161262 191815 sosesz scs uz 1 oz i se usse 59 orosz sri sieges 081 007 vere disset ver wz coa ozi o a 186256 oos ov ou z s oz st c9 9962 0996 z BLI 1008 iea onsdag 198681 se ies oot a us oL coer en EET 9007 ie 18 195785 0990 SPPELP 68 099 99 a ese ro Ort vo ov V 9999 69 o 098 oro 9c00 oro 05521 en NS LV 007 1838 sunos serer z z 999 es cs oz t 91601 seor we 01 in meus 500 mis ducer usiz uz us r a a z oz z u oss suey SLL Bu 9 au ses m ww p g sou em p Bw p u28u am ux Ww paoues cepuem ure embeg Pwo p uoSu
28. Silva M B Rocha C H E D Cimbleris A C P Rosa L P Silicon as a permanent carbon sedimentation tracer Inland Waters v 2 n 3 p 119 128 2012 Tardieu B Pigeon J L 2005 Greenhouse Gas Emissions How Hydro and Thermal Plants Differ HRW Hydro Review Worldwide p 1 4 November 2005 Tremblay A J Bastien M C Bonneville P del Giorgio M Demarty M Garneau J F H lie L Pelletier Y Prairie N Roulet Strachan and C Teodoru 2010 Net Greenhouse Gas Emissions at Eastmain 1 reservoir Quebec Canada Proceedings of the 21th World Energy Congress Montr al September 12 16 Page 10 454 GHG Risk Assessment Tool Beta Version USER MANUAL ANNEX 1 THREE STEP DECISION TREE APPROACH Page 11 455 456 457 458 459 460 461 462 463 464 465 466 467 468 469 470 471 472 473 474 475 476 477 478 479 480 481 482 483 484 485 486 487 488 489 490 491 492 493 494 495 496 497 498 GHG Risk Assessment Tool Beta Version USER MANUAL ANNEX 1 THREE STEP DECISION TREE APPROACH The UNESCO IHA GHG Research Project proposed a technical approach for the risk assessment of the vulnerability of a freshwater reservoir to enhanced GHG emissions presented as a three step process The present version of the GHG Risk Assessment Tool was developed as an empirical model based on already available published information As further data becomes available future versio
29. arameters mean annual temperature mean annual precipitation mean annual runoff bioclimatic factor net primary productivity and soil carbon density obtained from datasets available from various open sources The data adopted for the development and calibration of the empirical models of this GHG Risk Assessment Tool were derived from 212 field assessments of gross GHG emissions on 169 reservoirs as presented in the tables of this ANNEX The following notes present explanations of aspects of theses tables to allow a proper understanding of the meaning of some elements as well as to detail the data sources Note 1 q bathymetric shape q is the exponent from the bathymetric expression Az AO 1 Z Zmax due to Imboden 1973 q accomodates many shapes from cup shape q 1 to almost completely flat with a small deep hole q 5 6 Integrating this equation a simple relationship between mean and maximum depths is obtained Zmean Zmax q 1 allowing the estimation of the value of q for the reservoirs from average and maximum depths Note 2 Reservoir cross section and shape categories The most representative cross section and shape of the reservoir using the elements shown in figure 2 Cross sectional shape Shape seen from above bird s eye view Q Figure 2 Typical cross section and shape of the reservoir to compute a reservoir shape index Note 3 Weighting index The criteria for weighting the data was based on the lev
30. arch Across Boundaries 35 1 29 68 Keller M amp Stallard R F 1994 Methane Emission by Bubbling from Gatun Lake Panama Journal of Geophysical Research Atmospheres 99 D4 8307 8319 Kelly C Rudd J W M St Louis V L amp Moore T 1994 Turning attention to reservoir surfaces a neglected area in greenhouse studies Eos Trans AGU 75 29 332 Kemenes A Forsberg B R amp Melack J M 2007 Methane release below a tropical hydroelectric dam Geophysical Research Letters 34 p L1 2809 doi 10 1029 2007GL029479 Lima 1 B T 2005 Biogeochemical distinction of methane releases from two Amazon hydroreservoirs Chemosphere 59 11 1697 1702 Lima 1 B T Novo E M L M Ballester M V R amp Ometto J P H B 1998 Methane Production Transport and Emission in Amazon Hydroelectric Plants Veranlundgen der Internationalen Vereinigung f r Theoretische und Angewandte Limnologie Ometto J P Cimbleris A C P Santos M A Rosa L P Abe D Tundisi J G Stech J L Barros N O Roland F 2010 Patterns of carbon emission as a function of energy generation in hydroelectric reservoirs personal communication Roland F et al 2010 Variability of carbon dioxide flux from tropical Cerrado hydroelectric reservoirs Aquatic Sciences 72 3 283 293 Rosa L P dos Santos M A Matvienko B dos Santos E O amp Sikar E 2004 Greenhouse gas emissions from hydroelectric reservoirs in tropical regions
31. are available in the reservoir and the reservoir has the capacity to release them the vulnerability to gross GHG emissions is high and there is a need to assess the vulnerability to net GHG emissions otherwise the site is likely to present medium vulnerability to gross GHG emissions and there is a possible need to assess the vulnerability to net GHG emissions The decision tree also has the option of no information available directing the decision in the same direction as false i e remaining on the high vulnerability track Page 14 533 GHG Risk Assessment Tool Beta Version USER MANUAL ANNEX 2 DESCRIPTION OF THE EMPIRICAL MODELS Page 15 534 535 536 537 538 539 540 541 542 543 544 545 546 547 548 549 550 551 552 553 554 555 556 557 558 559 560 561 562 563 564 565 566 567 568 569 570 571 GHG Risk Assessment Tool Beta Version USER MANUAL ANNEX 2 DESCRIPTION OF THE EMPIRICAL MODELS C CO Flux model The article by Barros et al 2011 was the initial source for data for the development of this tool This data was revised and complemented by data from more recently published papers see ANNEX 3 and by estimates of additional parameters such as mean annual temperature mean annual precipitation and mean annual runoff obtained from datasets available from various open sources as described in ANNEX 3 However the modelling approach developed by t
32. d with the possible inclusion of new parameters as input data for the model Page 6 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 GHG Risk Assessment Tool Beta Version USER MANUAL 3 3 3 Results of the simulations Alerts Alerts are shown on the table with the results of the simulations to indicate that there is need to consider the results with care for cases in which the input values are outside the ranges used for model calibration Tables Predicted gross CO flux and Predicted gross CH flux The tables Predicted gross annual CO flux and Predicted gross annual CH diffusive flux show the predicted values of gross GHG fluxes for the selected reservoir age and for the average over an integration period of 100 years in accordance with IPCC 2006 the lifecycle assessment period for GHG emissions in freshwater reservoirs is 100 years as well as the upper and lower limits of their associated 67 confidence intervals The uncertainty for the average over the 100 year integration period is smaller than the uncertainty for an individual year The much narrower confidence intervals of the integrated flux assumes that the uncertainties in the predicted yearly fluxes are independent of one another and therefore average themselves out over the i
33. d nutrient are available in the catchment but they are not labile the supply of organic carbon and nutrients to the reservoir will be small Consequently the site vulnerability to gross GHG emissions is considered to be low to medium and the risk assessment analysis is complete If not it is necessary to proceed to the second step The second step has the objective of evaluating whether the necessary conditions for storing GHG are present The parameters that modulate the rates of the biological processes creating a stock were identified by IHA 2010 as Primary parameters If there is an adequate supply of carbon and nutrients but the reservoir does not have the conditions needed to convert this supply to GHGs there can be no GHG emission from the reservoir consequently the site is likely to present a low to medium vulnerability to gross GHG emissions and the risk assessment analysis is complete Otherwise the GHGs will be available dissolved in the water of the reservoir and it is necessary to proceed to the third step to evaluate if the vulnerability to gross GHG emissions is medium or high The third step identifies whether the reservoir has the necessary conditions to release the available stock of GHG from the water into the atmosphere The parameters that modulate gas exchange between the atmosphere and the reservoir or downstream river allowing the release of GHGs were identified by IHA 2010 as Secondary parameters If the GHGs
34. database of reliable comparable data 3 develop predictive modelling tools and 4 develop guidance and assessment tools for mitigation The standard guidance for net GHG estimations was achieved with the publication of the GHG Measurement Guidelines UNESCO IHA 2010 These guidelines are being applied to a broad range of sites around the world more than 20 reservoirs located in Asia Europe South America and North America with measurements captured in a Project database The database is an ongoing task during the Project lifetime to ensure the availability of reliable and comparable data for the development of the other Project products including predictive modelling and mitigation tools The development of the predictive models relies on data from the measurement programmes which will effectively only be available after application of the GHG Measurement Guidelines to a set of representative reservoirs during a period of at least two years While there is not yet enough data available the Project is making use of existing published data of gross GHG emissions from previous assessments on 169 reservoirs around the world taking account of the involved uncertainties to develop an empirical model GHG Risk Assessment Tool in order to provide estimation of the level of GHG emissions on proposed or existing freshwater reservoirs The development of guidance and assessment tools for mitigation can only be performed after completion of the
35. el of confidence that the value reported in the data template is an accurate representation of the annual fluxes The estimation of this level of confidence was assessed with basis on the following criteria Level 1 Very few samples in both in time and in space Possibly frequent and or severe methodological problems and uncertainties Overall assessment Poor confidence that the reported value is an accurate representation of the annual flux A first cut Page 19 634 635 636 637 638 639 640 641 642 643 644 645 646 647 648 649 650 651 652 653 654 655 656 657 658 659 660 661 662 663 664 665 666 GHG Risk Assessment Tool Beta Version USER MANUAL Level 2 Limited sampling campaigns with significant gaps in the temporal and spatial coverage Possibly frequent and or severe methodological problems and uncertainties Overall assessment Limited confidence that the reported value is an accurate representation of the annual flux A coarse approximation Level 3 Several sampling campaigns covering a significant portion of the annual cycle and of the surface area Some methodological uncertainties and some independent validation of techniques Good replicability and moderate variability in the results Overall assessment Moderate confidence that the reported value is an accurate representation of the annual flux A good approximation Level 4 Multiple sampling campaigns in multiple stations cove
36. en into consideration Consequently the causes of high CO emissions have to be properly investigated HIGH CH predicted values The assessment of Net GHG emissions is recommended This recommendation is based on the importance of CH emissions in reservoirs As stated in section 1 2 reservoirs may create the conditions under which CH can be produced and released As CH has the potential over a period of 100 years to produce 25 times the effect of CO on global warming the Global Warming Potential GWP any change in CH emissions has to be properly acknowledged Page 7 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 GHG Risk Assessment Tool Beta Version USER MANUAL Graphs for predicted CO and CH fluxes and associated uncertainty Graphs for predicted gross and CH fluxes and their associated 67 confidence intervals over a 100 year period are provided on the worksheet Main The predicted values of fluxes and limits for the 67 confidence intervals are also available for printing on worksheet Simulations Please note that the predicted gross CO fluxes are provided as mg C CO m d and predicted gross CH diffusive fluxes are provided as mg C CH m d For more details and conversion factors see ANNEX 4 3 3 4 General but important features Predicted fluxes nominally only include di
37. erpretation of the outputs of the Tool 6 3 23 Table INPUT DATA ata 6 3 3 2 Uncertainty of the estimates 6 3 3 3 Results of the simulations 7 3 3 4 General but important features 8 4 References 9 ANNEX 1 THREE STEP DECISION TREE APPROACH esee 11 ANNEX 2 DESCRIPTION OF THE EMPIRICAL MODELS seen 15 ANNEX DATASET FOR THE DEVELOPMENT OF THE EMPIRICAL MODELS 18 ANNEX 4 CONVERSION FACTORS cc cccssssecssscecssscecsseeecsseeecsseeecseeesseeecsseeseseeeesaeeess 28 Page iv 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 GHG Risk Assessment Tool Beta Version USER MANUAL 1 Introduction 1 1 Background Mitigating climate change is one of the most important goals for strategic sustainable development There is a clear and pressing need to quantify the greenhouse gas GHG footprint of all human activities The GHG status of freshwater reservoirs that is any change in GHG emissions in a river basin
38. ess GHG in CO equivalents CO eq or CO equiv Emissions of gases other than CO are translated into CO eq by multiplying by the respective global warming potential GWP From the 2007 IPCC report GWP relative to CO at different time horizon for carbon dioxide and methane RER Chemical Global warming potential GWP for given time horizon formula 20 yr 100 yr 500 yr Carbon dioxide CO 1 1 1 Methane CH 72 25 7 6 Source 2007 IPCC Fourth Assessment Report AR4 The IPCC considers the GWP of GHGs in a 100 year time frame It is important to note that care must be taken on the use of GWP as the conversion factor for calculation of gases warming potential equivalences as the IPCC GWP is not widely accepted to correctly represent the relative weight of the gases on the change in global temperature Page 29 801 802 803 804 805 806 807 808 809 810 811 812 813 814 815 816 817 818 819 820 821 822 823 824 825 826 827 828 829 830 831 832 833 834 835 836 837 838 839 840 841 GHG Risk Assessment Tool Beta Version USER MANUAL 3 Conversion from g of GHG to g of Carbon The conversion between g of GHG and g of Carbon is directly related to the ratio of the atomic mass of a GHG molecule to the atomic mass of a carbon atom Essentially this practice accounts for the carbon in the GHG molecule as opposed to counting
39. ffusive fluxes Due to the lack of reliable information from a sufficient variety of sources other pathways could not be included in the models Consequently the predicted total fluxes do not include some pathways such as CH bubbling and downstream degassing Predicted fluxes are gross emissions including emissions from unrelated anthropogenic sources UAS and emissions in the area before impoundment An assessment of the GHG impact of creating a reservoir can only be performed by estimating the NET GHG emissions All fluxes are expressed mg C m d they are noted as mg C CO or mg C CH to make clear that these mg of C refer to Carbon in a CO or a CH molecule respectively The integrated fluxes correspond to the cumulative emissions over the integration period 100 years divided by the total length of the integration period It thus corresponds to the average emission rate over the 100 year integration period Lower and upper confidence limits are indicative only of the likely precision of the models and of the uncertainty of the results For the purposes of estimating expected fluxes the predicted values should be used not the outer limits Page 8 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432 433 434 435 GHG Risk A
40. he Project was quite different from that of Barros et al 2011 It was intrinsically non linear and therefore had to be fitted to the data using non linear algorithms and more complex but afforded more flexibility in the shapes of the curve describing the initial decline of emissions following flooding Several alternative formulations were attempted but the following general expression provided both the best empirical fit and a realistic representation of the processes Flux C CO BO B1 X1 B2 B3 X2 e B4 X3 Age Eq 1 where the Bs are the fitted coefficients and the Xs are variables chosen from a suite of potential independent variables see section 3 2 This particular formulation was chosen because it satisfied four main conditions First it allows the model to potentially create a plateau to non zero emissions Second the level of GHG emission at this new equilibrium can also be modulated by other factors such as local climatic conditions runoff precipitation temperature etc Third the initial decline in GHG emission following flooding was made more flexible that the double logarithmic model of Barros et al 2011 In particular the steepness of this initial decline the exponential term was made to potentially interact with other variables Thus the shape of this decline could be modulated i e made more or less steep by the influence of other variables Lastly the initial GHG emission i e
41. ience Basis Contribution of Working Group to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change Solomon S D Qin M Manning Z Chen M Marquis K B Averyt M Tignor and H L Miller eds Cambridge University Press Cambridge United Kingdom and New York NY USA Goldenfum J A 2009 Filling the knowledge gap greenhouse gas research HRW Hydro Review Worldwide p 36 37 March 2009 Goldenfum J A Taylor R M Fink M 2009 THE UNESCO IHA MEASUREMENT SPECIFICATION GUIDANCE FOR EVALUATING THE GHG STATUS OF FRESHWATER RESERVOIRS a new tool to evaluate the impact of freshwater reservoirs on natural GHG emissions First International Greenhouse Gas Symposium San Francisco USA Goldenfum J A 2010a Does Hydro REALLY emit greenhouse gases Where is the truth Hydrovision International 2010 Charlotte NC USA Goldenfum J A 2010b Tool of the Trade Details on the UNESCO IHA GHG Measurement Guidelines for Freshwater Reservoirs International Water Power amp Dam Construction v 62 p 10 12 IHA 2010 GHG Measurement Guidelines for Freshwater Reservoirs Derived from the UNESCO IHA GHG Emissions from Freshwater Reservoirs Research Project Edited by Goldenfum J A London UK The International Hydropower Association IHA 138p Intergovernmental Panel on Climate Change IPCC 2006 2006 IPCC Guidelines for National Greenhouse Gas Inventories Prepared by the National Greenhouse Gas I
42. ion of the model Indication of the need for assessment of net GHG emissions Graphs for predicted gross GHG fluxes and their associated 67 confidence intervals e Worksheet Simulations e shows all values predicted for gross GHG fluxes and their associated 67 confidence intervals in a table that can be printed by the User e Worksheet Auxiliary e Shows auxiliary elements needed by the model Input parameter values for simulation Range of the data used for calibration of the model Atomic mass of the chemical elements involved N C O H Molar mass of the main GHG species Thresholds adopted for qualification of the predicted values as LOW MEDIUM or HIGH emissions compared to the distribution of observed values in the dataset used for calibration of the model see section 3 3 3 for more details More detailed descriptions of these elements as well as of the criteria adopted in the model are provided in sections 3 2 and 3 3 A description of the empirical models developed for this tool is provided in ANNEX 2 and the dataset used for its development is shown in ANNEX 3 Page 4 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 GHG Risk Assessment Tool Beta Version USER MANUAL 3 2 Use of the Tool spreadsheet 3 2 1 Parameters required to run the model The values for all input pa
43. ledge the importance of properly assessing the net GHG emissions from freshwater reservoirs such as Chanudet et al 2011 Demarty and Bastien 2011 Goldenfum et al 2009 Goldenfum 2009 2010a 2010b Tremblay et al 2010 IHA 2010 and Sikar et al 2012 Recently developed knowledge shows that reservoir emissions may be smaller than previously estimated Barros et al 2011 Chanudet et al 2011 and the terrestrial GHG sink may be smaller than currently believed Bastviken et al 2011 Also new studies show evidence that tropical and sub tropical reservoirs can sometimes behave as carbon sinks Sikar et al 2009a 2009b Chanudet et al 2011 Ometto et al 2010 and that anthropogenic activities contribute to increasing GHG reservoir emissions Del Sontro et al 2010 These research efforts imply that a proper assessment of the GHG emissions from reservoirs must take into account all main processes involved identifying when there is a need for assessment of net GHG emissions This GHG Risk Assessment Tool does not evaluate Net GHG emissions It predicts Gross GHG diffusive fluxes of CH and CO and gives indication of when the assessment of Net GHG emissions may be relevant it is important to notice that reservoirs do not change the amount of carbon in the hydrosphere biosphere atmosphere system the short term carbon cycle as they do not include new carbon in the system As recalled in Tardieu and Pigeon 2005
44. lexibility in the shapes of the curve describing the initial decline of GHG emissions following flooding see ANNEX 2 for more details on the empirical model The model for predicting CO diffusive fluxes was able to explain about 45 of the variation observed in the data used for calibration and had an uncertainty best described on a base 10 logarithmic scale root mean square error 0 36 The model for predicting CH diffusive fluxes was able to explain about 42 of the variation observed in the data used for calibration Its uncertainty is best described by a logarithmic root mean square error of 0 55 The range of variability of the estimates can be expressed by the confidence interval of the predicted values The confidence interval for the predictions is obtained as P lower limit lt GHG flux lt upper limit a meaning that there is a of probability that the GHG flux will be in the interval between the lower limit and the upper limit The values for lower limit and upper limit of the 67 confidence interval for the predictions are provided by the Tool as explained in section 3 3 3 As already described in sections 1 2 and 1 3 the models were developed based on already available published information The level of uncertainty will be reduced as new data becomes available providing conditions for obtaining better fit of the model as well as allowing the model formulation to be revise
45. lity to an increase in GHG emissions and there is limited need to assess net GHG emissions if there is a medium to high capacity to release the available GHG stock the reservoir is expected to present high vulnerability to gross GHG emissions and it is necessary to measure and assess the net GHG emissions relating to the specific reservoir Factors affecting GHG release in reservoirs e Wind speed and direction e Presence of low level outlets e Increased turbulence downstream of the dam associated with ancillary structures e g spillways and weirs e Reservoir shape shoreline surface ratio e Average water depth Figure 1 shows how these steps are interlinked in a decision tree structure Page 12 GHG Risk Assessment Tool Beta Version USER MANUAL 499 Catchment characteristics Low carbon Low vulnerability to gross and nutrient GHG emissions stock END OF ANALYSIS False or No information available Non labile Low to medium vulnerability carbon to gross GHG emissions nutrient END OF ANALYSIS False or No information available Reservoir Conditions Primary Parameters Low capacity Low to medium vulnerability to create to gross GHG emissions GHG stock END OF ANALYSIS False or No information available Reservoir Conditions Secondary Parameters Low capacity Low to medium vulnerability to release to gross GHG emissions GHG stock POSSIBLE NEED TO ASSESS VULNERABILITY TO NET GHG EMISSIONS False or No information
46. n 2006 A key reference established through this scientific community is the assessment of the GHG Status of Freshwater Reservoirs Scoping Paper which led to the UNESCO IHA GHG Project Scientific understanding has since advanced under the UNESCO IHA GHG Status of Freshwater Reservoirs Research Project UNESCO IHA GHG Project which started in August 2008 The Project has benefited from the collaboration of numerous research institutions and scientists within its peer review group The group was established through a series of international workshops convened over the past four years and comprises representatives from more than 100 institutions including universities research institutes specialist companies sponsoring agencies and others All documents produced under the Project pass through the peer review group before being published on the IHA and UNESCO websites Further information on the Project s work can be found at www hydropower org To all who have contributed to the production of this GHG Risk Assessment Tool through their knowledge and review we express our sincere appreciation This document lists all contributors Special thanks are due to the project sponsors listed below without whom this Project would not have been possible We also acknowledge the collaboration with UNESCO IPH The continuous support and advice from the UNESCO IHP team and from Prof Dr Andras Szollosi Nagy former Secretary of UNESCO IHP and Di
47. ns of the Tool could include the three step decision tree approach as proposed by the UNESCO IHA GHG Research Project STEP ONE SOURCE Capacity of the system to provide carbon and nutrients to the reservoir If the system upstream catchment characteristics imply a low carbon and nutrient stock or non labile carbon and nutrients the introduction of a reservoir is expected to present low vulnerability to an increase in GHG emissions otherwise it is necessary to evaluate step two Main factors affecting carbon and nutrient supply for reservoirs e Carbon and nutrient load e Rainfall e Soil type and land use e Biomass of plants algae bacteria and animals in the reservoir and in drawdown zone STEP TWO ACCUMULATION Capacity of the reservoir to create stock If the reservoir characteristics imply a low capacity to accumulate GHG stock the reservoir is expected to present low vulnerability to an increase in GHG emissions and there is no need to assess net GHG emissions otherwise it is necessary to evaluate step three Main factors affecting GHG accumulation in reservoirs e Water temperature e Residence time e Stratification of the reservoir body likelihood e Reservoir age e Drawdown zone exposure changes in water depth STEP THREE RELEASE Capacity of the reservoir to release the available stock If the reservoir characteristics imply a low capacity to release its GHG stock the reservoir is expected to present low vulnerabi
48. nt Tool Beta Version USER MANUAL ANNEX 4 CONVERSION FACTORS Page 28 770 771 772 773 774 775 776 777 778 779 780 781 782 783 784 785 786 787 788 789 790 791 792 793 794 795 796 797 798 799 800 GHG Risk Assessment Tool Beta Version USER MANUAL ANNEX 4 CONVERSION FACTORS 1 Conversion from moles to grams In chemistry a mole is considered to be Avogadro s number 6 02 x 10 of molecules or anything of a substance so depending on the density of the substance the mass of that amount of the substance could vary widely To convert from moles to grams you must first find the molar mass of the element or compound Use the periodic table to read off the atomic mass from an element If it is a compound you must know the molecular formula and then you find the total molar mass of the compound by adding up the atomic masses of each atom in the compound The unit of the molar mass will be in grams per moles g mole Once you have the molar mass you can easily convert from grams to moles and also from moles to grams Number of moles of grams molar mass Number of grams of moles x molar mass For carbon dioxide and methane most common GHG species in reservoirs Element Atomic mass GHG Molar mass g mol g mol C 12 CO 44 16 CH 16 H 1 2 CO equivalents CO eq or CO equiv The international practice is to expr
49. ntegration period It is important to stress that the lower and upper confidence limits are indicative only of the likely precision of the models and of the uncertainty of the results see section 3 3 2 For the purposes of estimating expected fluxes the predicted values should be used not the outer limits The predictions are then compared to the distribution of observed values in the dataset used for calibration of the model divided into three categories and are given a heuristic qualifier as LOW first quartile or 0 25 of the data MEDIUM second third quartile or 25 75 or HIGH last quartile or 75 100 emissions see ANNEX 3 for more details on the dataset The column Action Required gives indication of when the assessment of NET GHG emissions may be relevant as follows LOW or MEDIUM predicted values No need to assess Net GHG emissions unless indicated by other predicted values HIGH CO predicted values The assessment of Net GHG emissions should be taken into consideration The criteria for requiring this action takes into consideration that high emissions of can require the assessment of net GHG emissions to have their sources properly explained As stated in section 1 2 although CO may be released at different times and places because of the existence of a reservoir the majority of the natural CO levels are not significantly changed if the whole affected area upstream flooded areas and downstream is tak
50. nventoires Programme Edited by H S Eggleston L Buendia K Miwa T Ngara and K Tanabe Published IGES Japan IPCC 2011 IPCC Special Report on Renewable Energy Sources and Climate Change Mitigation Prepared by Working Group Ill of the Intergovernmental Panel on Climate Change O Edenhofer R Pichs Madruga Y Sokona K Seyboth P Matschoss S Kadner T Zwickel P Eickemeier G Hansen S Schl mer C von Stechow eds Cambridge University Press Cambridge United Kingdom and New York NY USA 1075 pp Page 9 436 437 438 439 440 441 442 443 444 445 446 447 448 449 450 451 452 453 GHG Risk Assessment Tool Beta Version USER MANUAL Ometto J P Cimbleris A C P Santos M A Rosa L P Abe D Tundisi J G Stech J L Barros N O Roland F 20120 Patterns of carbon emission as a function of energy generation in hydroelectric reservoirs Personal communication Sikar E Matvienko B Santos M A Rosa L P Silva M B Santos E O Rocha C H E D and Bentes Jr A P 2009a Tropical reservoirs are bigger carbon sinks than soils Verh Internat Verein Limnol 30 838 840 Sikar E Matvienko B Santos M A Rosa L P Silva M B Santos E O Rocha C H E D and Bentes Jr A P 2009b Tropical reservoirs are bigger carbon sinks than soils ERRATA Scheduled for publication in INLAND WATERS issue 4 Sikar E Matvienko B Santos M A Patchineelam S R Santos E O
51. posite Runoff Fields v1 0 Available at http www grdc sr unh edu Gu rin F Abril G Richard S Burban B Reynouard C Seyler P and Delmas R 2006 Methane and carbon dioxide emissions from tropical reservoirs significance of downstream rivers Geophys Res Let 33 L21407 doi 10 1029 2006GL027929 Hiederer R and M K chy 2011 Global Soil Organic Carbon Estimates and the Harmonized World Soil Database EUR 25225 EN Publications Office of the European Union 79pp Hellsten S K and others 1996 Measured Greenhouse Gas Emissions from Two Hydropower Reservoirs in Northern Finland IAEA Advisory Group Meeting on Assessment of Greenhouse Gas Emissions from the Full Energy Chain for Hydropower Nuclear Power and Other Energy Sources Montreal Qu bec Hydro Qu bec Hydro Qu bec Headquarters Page 25 711 712 713 714 715 716 717 718 719 720 721 722 723 724 725 726 727 728 729 730 731 732 733 734 735 736 737 738 739 740 741 742 743 744 745 746 747 GHG Risk Assessment Tool Beta Version USER MANUAL Huttunen J T V is nen T S Heikkikinen M Hellsten S Nyk nen H Nenonen O and Martikainen P J 2002 Fluxes of CH4 CO2 and N20 in hydroelectric reservoirs Lokka and Porttipahta in the northern boreal zone in Finland Global Biogeochem Cycle 16 1 17 Imboden D M 1973 Limnologische Transport und N hrstoffmodelle Aquatic Sciences Rese
52. predictive tools A framework for an initial mitigation guidance document is under development by the Project to enable hydropower project developers to take advantage of the knowledge created to date within the UNESCO IHA GHG Research Project Page 1 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 GHG Risk Assessment Tool Beta Version USER MANUAL 1 2 Purposes and objectives of the GHG Risk Assessment Tool The GHG Risk Assessment Tool the Tool provides an estimation of the level of gross GHG emissions existing or future from a freshwater reservoir based on limited and available field data and gives indication of when the assessment of net GHG emissions may be relevant The Tool was developed as an empirical model based on already available published information for application to proposed sites or existing freshwater reservoirs The Tool responds to needs from industry financial institutions and decision makers for a product that can be used as a screening tool as well as being able to provide assessment of the level of gross GHG emissions for unmonitored and or proposed new dam sites Emissions from the following GHG species are evaluated by the Tool Carbon dioxide CO 80 of all GHGs released into the atmosphere are CO Freshwater reservoirs do not significantly change nat
53. r methane e first convert from g of C CH to g of CH multiplying by 16 12 e and then adopting the IPCC GWP for a 100 yr time horizon multiply by 25 in order to obtain the g of CO eq After converting the unit g of Carbon from the different GHG species in analysis to the unit g of CO eq it is possible to compare the emissions or to add subtract all values and then to obtain a total estimated emission expressed as g of CO eq It is also possible to express these values as g of C CO eq grams of Carbon in the CO eq by multiplying the g of CO eq by 12 44 Page 30 842 843 844 845 846 847 848 849 850 851 852 853 GHG Risk Assessment Tool Beta Version USER MANUAL 5 Carbon dioxide equivalents vs carbon equivalents While the international standard is to express emissions in CO equivalents CO eq many U S A sources have expressed emissions data in terms of carbon equivalents CE in the past In particular the United States Environmental Protection Agency USEPA has used the carbon equivalent metric in the past for budget documents For the purposes of national greenhouse gas inventories emissions are expressed as teragrams of equivalent Tg CO eq One teragram is equal to 10 grams or one million metric tons e convert from CE to CO eq multiply by 44 12 e convert from CO eq to CE multiply by 12 44 Page 31
54. rameters must be provided by the User in the Input Value column of the table INPUT DATA on the top of the worksheet Main The variables in this table are categorised in three groups input data needed for estimation of both CO and CH fluxes input data needed for estimation of CO fluxes input data needed for estimation of CH fluxes Selected reservoir age years Number of years since impoundment reservoir filled to full capacity This can refer to the present age of the reservoir or to any other year up to 100 of interest This variable is needed for estimation of both CO and CH fluxes Mean annual air temperature Celsius Mean annual air temperature at the reservoir area This variable is needed for estimation of both CO and CH fluxes Mean annual runoff mm Mean annual runoff of the contributing catchment This variable is needed for estimation of CO fluxes Mean annual precipitation mm Mean annual precipitation on the contributing catchment This variable is needed for estimation of CH fluxes The values for the parameters mean annual temperature C mean annual precipitation mm and mean annual runoff mm were in the development of the model obtained from datasets available from various open sources see ANNEX 3 3 2 2 Results of the simulations The table with the results of the simulations provides information on whether the values entered in the Tool are within the ranges of val
55. rector of the UNESCO Division of Water Sciences currently Rector of UNESCO IHE Institute for Water Education was fundamental for the Project achievements so far And finally we thank the IHA Central Office for their support Project sponsors China Three Gorges Project Corporation Electricit de France Hydro Equipment Association International Aluminium Institute SN Power Statkraft The World Bank Page ii 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 GHG Risk Assessment Tool Beta Version USER MANUAL LIST OF CONTRIBUTORS International Hydropower Association USER MANUAL Analysis Drafting and Revision Joel A Goldenfum Revision Richard Taylor Tracy Lane MODEL DEVELOPMENT Model revision and final layout Joel A Goldenfum Universit du Qu bec a Montr al MODEL DEVELOPMENT Data analysis and Model development Yves Prairie Data processing and analysis Alice Parkes USER MANUAL Analysis and Drafting Yves Prairie Comments and suggestions from members of the Panel of Experts Selected Review Group St phane Descloux EDF France Miguel Doria UNESCO Atle Harby SINTEF Norway Clelia Marti CWR University of Western Australia Yves Prairie UQAM Canada J rgen Schuol Voith Hydro Germany Bradford Sherman CSIRO Land and Water Australia Chen Shiun Sarawak Energy Berhad
56. rimary productivity estimates were obtained from the socioeconomic data and applications centre of Columbia University at http sedac ciesin columbia edu es hanpp html Note 7 Soil Carbon density Soil Carbon density estimates were obtained from Hiederer and K chy 2011 Page 20 900 Te srces 160 WL 7 u a 995 sz si or sor ot i ust ss ss 000 sse 00 iv amino ss 8002 itia ua ue az z a sizz vi se vo D ve ov amori ee iro or jsuus 15 S007 i keen SEG 097 LU Lud ist 905 cc e a oz L 98 00 96 SOS sri 2015 ov st OE 695 sr SJ 95 007 I 196 22 E sor 286 teo a var og c ee ee oser zoz eriet oz wmeo ss 8007 enwai 990125 eset oe 99 ix a Sez so s 06 802 eze 0008 05809 e auno 15 v66Lp eieis isle 896125 ESEL og ouz 9997 192 8861 so sec s ocv og erst 9 BE BL eze PESIS 00285 er ES 9002 06859 a soze VEST ist a sont ee u zo o ou eze 00621 I z eunung 25 0102 e puero rd prozes r ign ezo soz a css 05 cu ra sr STM 4907 or i sewing is 0102 reve puero rd prozos izr igni 1 eoz a ver LZ or er so Lg OR 000041 seunj OG 0102 puero 199895 110285 eco eoz a ces 05 LE or 1 e wo sco 19 ores sewing r
57. ring most of the reservoir surface Some extrapolation made to cover periods that were not sampled No major technical problems or uncertainties and rigorous independent validation of techniques Overall assessment High level of confidence that the reported value is an accurate representation of the annual flux A high quality result Level 5 Extensive and detailed sampling regime covering the complete annual cycle Multiple stations covering the entire surface area Convergent multiple techniques to estimate flux Overall assessment Very high level of confidence that the reported value is an accurate representation of the annual flux The best data money can buy Table 2 summarises these criteria for weighting data in model development Table 2 Criteria for weighting data in model development Method uncertainty Resolution representivity Poor Good Verified Spatial temporal low 1 2 3 Spatial high temporal low 2 3 3 Spatial low temporal high 2 3 4 Spatial temporal high 3 4 5 Note 4 BioClimatic Factor The BioClimatic Factor estimates were obtained from WorldCLim a global climate data GIS data repository The maps with this data can be downloaded at http www worldclim org download Note 5 Mean annual air temperature precipitation and runoff Estimates on mean annual values for air temperature precipitation and runoff were obtained from Fetke et al 2000 Note 6 Net Primary Productivity Net p
58. sk Assessment Tool The GHG Risk Assessment Tool is being developed as a living document As further data are collected and analysed its formulation can be revised and the level of uncertainty can be reduced Future versions of the Tool could incorporate other factors such as soil carbon content water temperature ranges hydrodynamics parameters such as stratification residence time and others primary production and vegetation There is a need for further research to obtain the necessary data to properly test and evaluate the importance of these and other factors The possibility of including a three step decision tree approach into this model will also be left for future versions A description of this approach is provided in ANNEX 1 Three step decision tree approach STEP ONE SOURCE Capacity of the system to provide carbon and nutrients to the reservoir STEP TWO ACCUMULATION Capacity of the reservoir to create stock STEP THREE RELEASE Capacity of the reservoir to release the available stock Page 2 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 222 223 224 GHG Risk Assessment Tool Beta Version USER MANUAL 2 The concept of Net GHG Emissions Net GHG emissions GHG footprint or GHG status of freshwater reservoirs represent the change in GHG emissions due to the creation
59. ssessment Tool Beta Version USER MANUAL 4 References Barros N Cole J J Tranvik L J Prairie Y T Bastviken D Huszar V L M del Giorgio P Roland F 2011 Carbon emission from hydroelectric reservoirs linked to reservoir age and latitude Nature Geoscience http dx doi org 10 1038 ngeo1211 2011 Bastviken D Tranvik L J Downing J A Crill P M Enrich Prast A 2011 Freshwater Methane Emissions Offset the Continental Carbon Sink Science Vol 331 Chanudet V Descloux S Harby A Sundt H Hansen B H Brakstad O Serca D Guerin F 2011 Gross CO2 and CH4 emissions from the Nam Ngum and Nam Leuk sub tropical reservoirs in Lao PDR Sci Total Environ doi 10 1016 j scitotenv 2011 09 018 Del Sontro T Mcginnis D F Sobek S Ostrovsk y l Wehrl B 2010 Extreme Methane Emissions from a Swiss Hydropower Reservoir Contribution from Bubbling Sediments Environ Sci Technol 2010 44 2419 2425 Demarty M Bastien J 2011 GHG emissions from hydroelectric reservoirs in tropical and equatorial regions Review of 20 years of CH4 emission measurements Energy Policy Volume 39 Issue 7 July 2011 Pages 4197 4206 Forster P V Ramaswamy P Artaxo T Berntsen R Betts D W Fahey J Haywood J Lean D C Lowe G Myhre J Nganga R Prinn G Raga M Schulz and R Van Dorland 2007 Changes in Atmospheric Constituents and in Radiative Forcing In Climate Change 2007 The Physical Sc
60. sv umi eux oiz ooz vea eso s200 82 277 sst tis we ss ava z ee co ov ezso t zwe ove 001 a eux eoz 0102 jeg sester 1801 159 996 urs wo s 99 or i 9 1 991 venom 902 9002 1e 1 WIG 257 9100 oe err eeu e a asez ea 99 oz i A usei se w sri e9702 on 27 991 202 5002 1 Aequi were ze ect ue 08 BEL LU a CoL 098 ct oz V e 61224 14096 8052 067052 so SIUN 902 002 io fequi 9 sseszz ie ozo se z a zor coe eu se oz ee m 507 9008 iia scorsi sec szor os zoo o oz i i br Bore 6 erzet EN 02 S002 ye i Aequis 5640 cor Bret ue de a Sk ot LH is orati 806r ver ol oss Ort veuseuM coz 0002 1 0705 VI eseujsuos est ort S PLDE cor ase we ae a St ot V or or orot 806 sezat orzel zor 202 S002 fia fequi 05 26 m us ess 089 050 e a oz o sv woer i 102 002 Ie siunos eere TT ESPZ 65612 0 Ori ie zu L si oz L 9521 dr os P west 9 STS 00 orse 091 EINEM 002 00 Ie Vasey 99i9 vi 0 Sirk 6st L1 Lon ro oo to V w POSE 95790 6st soe eM 661 00 ie 18 958512 c9 0r LJ 13 ut orti Lu ger 0 6582 gu si L 17260 Li SESE shee est an 961 500 ie uouo cose o shiz ies oe
61. the entire molecule For carbon dioxide the ratio of the atomic mass of a CO molecule to the mass of a carbon atom is 44 12 e Toconvert from g of C to g of multiply by 44 12 e convert from g of CO to g of C multiply by 12 44 e Sometimes you find this noted as gC CO or tC CO to make clear that these g of C refer to Carbon in a CO molecule For methane the ratio of the atomic mass of a CH molecule to the atomic mass of a carbon atom is 16 12 e convert from g of C to g of CHz multiply by 16 12 e convert from g of CH to g of C multiply by 12 16 e Itis important to make clear that these g of C refer to Carbon in a CH molecule i e NOT CO eq not taking into account GWP It is common to use gC CH or tC CH 4 Conversion from g of Carbon to g of CO eq With the use of CO equivalents CO eq or CO equiv it is possible to express emissions removals of different GHG species on the same units of mass g of CO eq allowing then to compare and to combine add or subtract these emissions To convert from g of Carbon to g of CO eq it is necessary to e first convert from g of C to g of GHG see item 3 e and then multiply by the respective global warming potential GWP in order to obtain the g of CO eq For as the GWP is 1 it is only necessary to convert from g of C g of multiplying by 44 12 Fo
62. tree e 9891 sei ero a opt ot t o 96201 sree 0009 96 021 002 m i 1909215 o 9292 s ess 9s 0000 ro os oo z 0 501 6st cote 0002 re 13 SORS 122896 ar 618 cor or a 756251 Ler 992 9 00 a oz LI 05291 amp EL 2016 zoor se BL PST oot OG PSE SHE ISOON BLL 9002 sowes SLOT EP VS LETE ses Ln Gort sroc soc 6252 ro oce LI 15 rest LI b o wo 6 BI trsh 516 0081 96 LiL 007 eie 95105 9t scs 101 sroc soc 990 6252 re oce 8 is vest ov 000 26 81 occu 9 1601 0082 06 0601 56 911 Lms wou arsen one Penot Pew oul ux gwy pesoen smed se 5 p w98 pw Bu scum og SEMA ooqjemda dida CUNA seins Wed man tones oe Poun Dai any E E cm POE verden REN agowtyeq b 669 Page 23 GHG Risk Assessment Tool Beta Version USER MANUAL 9002 i FITTE 029608 s 7 73 77 ro 00 oF z 7 gt e 900 oro sei Janez ziz 9008 e 59 D reez eus ves es ermo 59 n i sioz oseo azes uz 900 1e 19 sowes ezooez eni coarse ret sst es arez ss ava z et ete og e s Oo ce 100 o
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64. ues of the data used to develop the models It also shows predicted gross GHG emission values and approximate 6796 confidence intervals for the selected reservoir age and integrates these values over a defined period Graphs for predicted gross CO and CH fluxes are also produced Section 3 3 gives explanation on how to analyse and interpret the results of the Tool 3 obs in the lack of the catchment information a point estimate at the dam site can be adopted Page 5 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 GHG Risk Assessment Tool Beta Version USER MANUAL 3 3 Analysis and interpretation of the outputs of the Tool 3 3 1 Table INPUT DATA The STATUS column on the INPUT DATA table informs the User if the entered values are within the ranges of values of the data used to develop the models If an input value falls outside the range of the data used for calibration of the model it is considered an extrapolation and the results have to be considered with care the Tool was developed as an empirical model so the predicted values are more reliable when there are no extrapolations 3 3 2 Uncertainty of the estimates Empirical models were developed to explain the variability of gross CO and CH diffusive fluxes An intrinsically non linear approach was adopted affording f
65. ural CO levels the great majority of CO emissions would naturally occur even without the reservoir as part of natural transport processes conduction deposition and emission in the water bodies at the area affected by the reservoir upstream catchment flooded areas downstream of the reservoir CO may however be released at different times and places because of the existence of a reservoir High emissions of CO may require the assessment of net GHG emissions to have their sources properly explained Methane CH there is already broad consensus among the scientific community that CH is the main GHG species of concern in freshwater reservoirs It is important to look at CH emissions because some freshwater reservoirs may create conditions for changes in the natural CH levels in the affected area Also according to IPCC Forster et al 2007 the global warming potential GWP of CH is 25 times stronger than that of CO for a 100 year time horizon This means that CH has the potential over a period of 100 years to produce 25 times the effect of CO on global warming This GHG Risk Assessment Tool estimates Gross GHG diffusive fluxes of CH and CO and qualifies the predicted values as LOW MEDIUM or HIGH potential emissions compared to the distribution of observed values in the dataset used for calibration of the model The Tool outputs provide indication of the need for assessment of net GHG emissions 1 3 Updating the GHG Ri
66. z vi or t o sg 000i o ewaeg ii I 5002 1e 18 uae zou sse wor tou 51000 60 i sioi is verte 6 wea OL D S002 r ke Que estie tosroz 1801 sis stor sos is a ozs oz i ee 3 ros ua oreaz 8 weddnwouy 6 S007 pe pa ors 669 ste 209 o a ozs vri oz i ee 3 soos 1966 ozs ov ser 1 swoueN wouy 8 aseugeuos zzocer n iezi sre ss a ozs t ot i u trer SL vet 1 S0DE eva 88 196 sizze ur ter 960 tre oae ozs zr oz i te reer r r roia 009 9 Janowo 9 5002 2 resell o sezi zos 9091 sor 821000 9co 9t sitet te ES IE Sree s SG TOO Ie ja zsoeri ez eso st st a veg Lr 0009 p S00 re 1 fewa 408869 BELL ESS eost ess ss a ot oz t vor PIED E 19002 Vee itso ser vid 9861 661 a ero ou ro t 5201 Li ot ve 60 661 t owen 2 008 ie vem 969812 vorser sieo ot D esee t aedy auss P OPO ONT apua Tu Tu Tai Traou ses EAT PoU QPQWOULN ART w ipmovem Tr siu ses Tes wes atg abg PTO ea FRIE LETT soususja oyesboaia Aysuap yo Abner Breed doped ana ea LI wha ehe petu sana sanv e e oN UD

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