Monitoring,  repor,ng  and  verifica,on  in  NAMAs  using  SAMPLES  

Todd  Rosenstock,  H  Neufeldt,  J  Hickman,  M  Rufino,  K  BuDerbach-­‐Bahl,  E  Wollenberg,  D  Pelster,  L  Verchot,  C  Arias-­‐Navarro,  G  Saiz,  E  Diaz-­‐Pines,  M  Richards,  D  Gil-­‐Kim+  

SBSTA  42  |  Bonn  |  5  June  2015  

Why  do  we  need  more  and  beDer  data?  

Low-­‐emissions  development  

Global  nego,a,ons  

Climate  finance  

Based  on  exis+ng  data,  we  know  very  li5le  about  African  agricultural  GHG  fluxes  

3  

Nitrous  oxide  emissions  from  increasing  fer,lizer  use  in  Africa  

•  Government  subsidy  programs  

•  NGOs  (e.g.,  Alliance  for  Green  Revolu+on  in  Africa)  

•  Used  in  private  sector  (Unilever),  MRV  (Gold  Standard),  &  farmers  

•  Differ  in  input  requirements,  speed  of  assessment  and  ease  of  use  

•  Largely  based  on  the  same  input  data  and  models    

 

Impact  assessment  with  ‘GHG  calculators’  

Colomb et al. 2012

REVIEW OF GHG CALCULATORS IN

AGRICULTURE AND FORESTRY

SECTORS A Guideline for Appropriate Choice and

Use of Landscape Based Tools

Version 2.0

Authors

Vincent COLOMB (Lead Author, IRD, UMR Eco&Sols) Martial BERNOUX (Coordinator, IRD, UMR Eco&Sols, martial.bernoux@ird.fr) Louis BOCKEL (Policy Officer, FAO) Jean-Luc CHOTTE (IRD, UMR Eco&Sols) Sarah MARTIN (ADEME, Agriculture and Forest Service) Cécile MARTIN-PHIPPS (ADEME, International Affairs Division) Jérôme MOUSSET (ADEME, Agriculture and Forest Service) Marianne TINLOT (Junior Consultant, FAO) Ophélie TOUCHEMOULIN (Junior Consultant, FAO)

June, 2012

Small-­‐scale  spa+al  heterogeneity  

Context-­‐  specific  measurement  methods          

At  ~4    +me  points  

Ul,mately  we  need  more  data  

Nyando,  Kenya  

Beyond  field  measurements  of  emissions  

The  Problem  

GHG = f (EF,activity)

The  Approach   Outcome  

Variable  &  uncertain  

Accuracy  unknown  Compara+vely  li5le  

effort  MRV  and  inventories  

based  on  ac,vi,es  

Arial  photo  

Crowd  sourcing  

Remote  sensing   Enabling  carbon  

finance  and  robust  na+onal  policy    

Rapid  assessments  e.g.  scorecards  

Ac,vi,es  

Mapping  pro-­‐poor  mi+ga+on  opportuni+es  

Measurement  guidelines  

Capacity  development  

Integrated  assessment  of  farming  systems  

Priori+es  for  research  and  development  

Consistent  and  comparable  data  

Human  and  ins+tu+onal  infrastructure  

Socially  acceptable,  place-­‐based  solu+ons  

CCAFS’  Standard  Assessment  of  Mi,ga,on  Poten,al  and  Livelihoods  (SAMPLES)  Programme  

hDp://samples.ccafs.cgiar.org  

Ac,v

i,es  

Outcomes  

Thanks  for  a  future