Dynamic baselines depending on REDD+ payments: A comparative analysis based on a system dynamics approach

Ecological Indicators

Hongqiang Yang¹  Weifeng Wang²  Han Zhang³  Xi Li⁴  Ting Wu⁵ 

[1] F University, Yangling 712100, China;Research Center for Economics and Trade in Forest Products of the State Forestry Administration (SINO-RCETFOR), Nanjing 210037, China;College of Biology and the Environment, Nanjing Forestry University, Nanjing 210037, China;College of Economics and Management, Nanjing Forestry University, Nanjing 210037, China;;College of Economics and Management, Northwest A &

关键词: REDD+;    Baseline;    System dynamics;    Payments;    Impact evaluation;   

DOI  :  

来源: DOAJ

【 摘 要 】

The mechanism of reducing deforestation emissions in developing countries (REDD+) could play an increased role in climate mitigation by determining country-specific emission baselines. An impact evaluation able to assess the baselines change in response to carbon payments must be considered in order to highlight effective baselines. In this study, we proposed dynamic baselines and developed a forest-carbon-economy system-dynamic model to assess reduced deforestation emissions and payments for emission reductions. We conducted a comparative analysis from five countries, which were representatives of four forest country types. The results showed that the average dynamic baselines were lower than static baselines in Brazil, Cameroon, Guyana and Indonesia. It implied, in the context of limited climate funding, use of dynamic baselines will help REDD+ achieve more cost-efficient emissions reductions in these countries. Furthermore, the uncertainty analysis of the key parameters showed that different data sources of carbon density, carbon prices and changes in agricultural product prices affect emission reductions. Thus, when a country has high flexibility in determining data sources, it may choose profitable data under alternative data sources, which can compromise the climate effectiveness and cost efficiency of the entire REDD+ mechanism.

【 授权许可】

Unknown