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This methodological note describes a Sustainable Asset Valuation (SAVi) assessment conducted by the International Institute for Sustainable Development (IISD) for a proposed mass rapid transit (MRT) system in Pampanga, Philippines. The document outlines the SAVi framework, which integrates system dynamics, multi-criteria analysis, and project finance modelling to evaluate the economic, social, and environmental impacts of the project compared to a 'no action' scenario.

This report details a Sustainable Asset Valuation (SAVi) assessment of peatland and mangrove restoration in Indonesia, specifically focusing on the Katingan peatlands and Belitung mangroves. It evaluates the societal benefits and costs of various policy and climate scenarios, concluding that sustainable management is cost-effective for climate mitigation and community support, provided that local communities have alternative income sources to avoid environmentally damaging activities.

This technical report by the International Institute for Sustainable Development (IISD) uses System Dynamics (SD) modelling to forecast the employment impacts of circular economy (CE) interventions in Finland across six key areas: electronics, textiles, food, mining, forestry, and buildings. The study compares a business-as-usual (BAU) scenario with two levels of CE ambition (CE1 and CE2) from 2020 to 2040, finding that while some sectors like electronics and forestry see net job gains due to the labour intensity of recycling and refurbishment, others like food and textiles face net losses due to reduced primary production and retail demand.

This supplementary technical note describes the methodologies and unit cost models used to estimate the 'cost gap' for five key clean energy technologies in India: Battery Energy Storage Systems (BESS), offshore wind, solar photovoltaic (PV), electric vehicles (EVs), and green hydrogen (GH2). It details how these cost gaps are calculated relative to conventional benchmarks and how they are integrated into the Green Economy Model (GEM) to analyze the macroeconomic impacts of various levels of government support on GDP, employment, and emissions.