Dynamic baselines depending on REDD+ payments: A comparative analysis based on a system dynamics approach. (July 2022)

• Record Type: Journal Article
• Authors: Li, Xi; Wang, Weifeng; Zhang, Han; Wu, Ting; Yang, Hongqiang
• Is Part Of: Ecological indicators. Volume 140(2022)
• Publication Date: 2022-07
• Subjects: REDD+ -- Baseline -- System dynamics -- Payments -- Impact evaluation; Environmental monitoring -- Periodicals; Environmental management -- Periodicals; Environmental impact analysis -- Periodicals; Environmental risk assessment -- Periodicals; Sustainable development -- Periodicals; 333.71405
• DOI: 10.1016/j.ecolind.2022.108983
• Languages: English
• ISSNs: 1470-160X

Abstract

Highlights: We develop a comprehensive forest-carbon-economy model using VENSIM software. We simulate effects of REDD+ on changes in deforestation with a dynamic baseline. Results show that REDD+ is usually more cost-efficient under a dynamic baseline. Countries may choose data sources by their differential impact on reductions. Carbon and agricultural price changes affect REDD+ climate-effectiveness. Abstract: 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.