{"query_echo":{"q":"","filters":{"analysis_type":["mathematical modeling"]},"warnings":[{"code":"facet_value_not_in_vocabulary","message":"Value 'mathematical modeling' for facet 'analysis_type' is not in the controlled vocabulary."}]},"total":{"value":3,"relation":"eq"},"page":1,"page_size":20,"self":"https://climateinsightsdirectory.org/api/v1/search?analysis_type=mathematical+modeling","stability":"beta","ai_marking":{"digital_source_type":{"uri":"http://cv.iptc.org/newscodes/digitalsourcetype/trainedAlgorithmicMedia","name":"Created using Generative AI"},"notice":"Summary and key insights are generated using artificial intelligence."},"results":[{"id":"trendas-000040","url":"https://climateinsightsdirectory.org/document/trendas-000040","title":"ADU KLAIM MENURUNKAN EMISI","publisher":{"name":"Trend Asia","organization":"trend-asia"},"document_type":"report","language":"id","date_published":"2022-08","source_url":"https://trendasia.org/wp-content/uploads/2022/08/ADU-KLAIM-EMISI-1.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"Trend Asia challenges PT PLN's claim that biomass co-firing facilitates an energy transition and reduces emissions. The report argues that the massive land requirements for energy plantation forests (HTE) to supply wood pellets would lead to significant deforestation, resulting in net carbon emissions rather than reductions. It finds that biomass has become a complement to, rather than a substitute for, coal, with total coal consumption continuing to rise.","ai_generated":true,"unit":"trendas-000040#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"PT PLN claims that replacing 5-10% of coal supply with biomass in coal-fired power plants (PLTU) constitutes an energy transition to renewable sources, targeting a 23% renewable energy mix by 2025.","ai_generated":true,"unit":"trendas-000040#insight-1","date_modified":"2026-10-23"},{"text":"Trend Asia estimates that implementing 10% co-firing across 107 PLTUs would require 10.23 million tons of wood pellets annually, necessitating energy plantation forests (HTE) covering at least 2.33 million hectares.","ai_generated":true,"unit":"trendas-000040#insight-2","date_modified":"2026-10-23"},{"text":"The expansion of HTE is likely to cause significant deforestation; based on MapBiomas Indonesia data showing 38% of industrial forest plantations (HTI) came from natural forest clearing, the report projects high potential deforestation for various HTE species, with Gamal having the highest potential at 2,099,843 hectares.","ai_generated":true,"unit":"trendas-000040#insight-3","date_modified":"2026-10-23"},{"text":"Mathematical modeling by Trend Asia indicates that 10% biomass co-firing in 107 PLTUs could generate total emissions between 7.9 million and 26.48 million tons of CO2e per year, depending on the tree species used.","ai_generated":true,"unit":"trendas-000040#insight-4","date_modified":"2026-10-23"},{"text":"The report refutes the 'carbon neutral' claim of wood biomass, stating that the carbon stocks of natural forests lost during HTE construction cannot be compensated for by the carbon absorbed by the new plantations, resulting in a net emission gap of approximately 6.8 million to 11.3 million tons of CO2e.","ai_generated":true,"unit":"trendas-000040#insight-5","date_modified":"2026-10-23"},{"text":"Biomass co-firing has not reduced coal usage; PLN's coal consumption increased from 66.68 million tons in 2020 to 68.47 million tons in 2021, while biomass use rose from 9,731 tons to 282,628 tons in the same period.","ai_generated":true,"unit":"trendas-000040#insight-6","date_modified":"2026-10-23"},{"text":"The report concludes that co-firing is being used as a justification to extend the operational life of coal plants that should be retired, while coal demand is projected to rise from 111 million tons in 2021 to 153 million tons by 2030.","ai_generated":true,"unit":"trendas-000040#insight-7","date_modified":"2026-10-23"}],"climate_tags":["biomass","Cofiring","coal-fired power station","deforestation","greenhouse gas emissions","energy transition","carbon neutrality"],"geography_discussed":["Jakarta","West Kalimantan","Lombok Island","West Nusa Tenggara","Ende","East Nusa Tenggara","Rembang","Central Java","Central Kalimantan","Banten","Indramayu","United Kingdom","United States"],"frame_perspective":[],"analysis_type":["mathematical modeling","policy analysis","life cycle assessment"]},{"id":"bc3res-000070","url":"https://climateinsightsdirectory.org/document/bc3res-000070","title":"Local and Global Externalities, Environmental Policies and Growth","publisher":{"name":"Basque Centre for Climate Change","organization":"basque-centre-for-climate-change"},"document_type":"research paper","language":"en","date_published":"2010-10","source_url":"https://www.bc3research.org/h6T8Uy8Nm4gFs0O/201010251116161103791392.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","analysis_type"],"summary":{"text":"The research examines the interaction between local flow pollution and global stock pollution, specifically focusing on abatement activities that can target one or both. By comparing symmetric and asymmetric internalization scenarios, the authors demonstrate that the degree of internalization affects the capital-abatement ratio and long-run pollution stocks. The paper argues that achieving a first-best global welfare optimum requires two distinct policy instruments—such as taxes on both local and global pollutants—and that in asymmetric cases, subsidizing pollution reduction is superior to subsidizing abatement because the latter fails to correct for negative externalities from capital accumulation.","ai_generated":true,"unit":"bc3res-000070#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"The model distinguishes between two types of abatement: one that reduces only local pollution (e.g., particulate matter filters) and another that mitigates both local and global pollution (e.g., fuel saving technologies).","ai_generated":true,"unit":"bc3res-000070#insight-1","date_modified":"2026-10-23"},{"text":"In a scenario where only local externalities are internalized, the capital-abatement ratio is biased toward local pollution abatement because the mitigating effect on global pollution is ignored.","ai_generated":true,"unit":"bc3res-000070#insight-2","date_modified":"2026-10-23"},{"text":"Internalizing the global externality leads to a lower equilibrium capital-abatement ratio and a lower long-run pollution stock compared to internalizing only local externalities.","ai_generated":true,"unit":"bc3res-000070#insight-3","date_modified":"2026-10-23"},{"text":"Achieving a first-best solution requires two separate policy instruments, such as a tax on local pollution and a tax on global pollutants, because the induced market failures are not perfectly correlated.","ai_generated":true,"unit":"bc3res-000070#insight-4","date_modified":"2026-10-23"},{"text":"The optimal tax for local pollution should equal the marginal damage to current production, whereas the optimal tax for global pollutants must also account for future damages caused by the addition to the pollution stock.","ai_generated":true,"unit":"bc3res-000070#insight-5","date_modified":"2026-10-23"},{"text":"In asymmetric scenarios, subsidizing pollution reduction is the only way to achieve the global welfare optimum because it corrects for both the returns to abatement and the returns to capital.","ai_generated":true,"unit":"bc3res-000070#insight-6","date_modified":"2026-10-23"},{"text":"Subsidizing abatement instead of pollution reduction results in suboptimally high capital accumulation and growth in the receiving country because it fails to capture the negative externality from capital.","ai_generated":true,"unit":"bc3res-000070#insight-7","date_modified":"2026-10-23"}],"climate_tags":["economic growth","climate policy","carbon tax"],"geography_discussed":[],"frame_perspective":[],"analysis_type":["theoretical","mathematical modeling"]},{"id":"sei-001259","url":"https://climateinsightsdirectory.org/document/sei-001259","title":"Calculations for the Greenhouse Development Rights Calculator","publisher":{"name":"Stockholm Environment Institute","organization":"stockholm-environment-institute"},"document_type":"research paper","language":"en","date_published":"2008-09-24","source_url":"https://www.sei.org/mediamanager/documents/Publications/Climate/calculations-gdr-calculator.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","analysis_type"],"summary":{"text":"The document details the calculations for the Greenhouse Development Rights (GDRs) calculator, a tool designed to explore burden-sharing for climate change. It establishes a methodology that uses the individual as the unit of analysis, assuming lognormal income distributions within countries. The paper defines how to calculate individual and national 'capacity' (financial ability to pay) and 'responsibility' (based on emissions), which are then combined into a Responsibility-Capacity Indicator (RCI) to allocate a global tax. It also describes the use of the Suits index to measure the progressivity of this tax system on a global scale.","ai_generated":true,"unit":"sei-001259#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"The GDRs framework utilizes the individual as the primary unit of analysis, requiring data on instantaneous income distributions within countries to calculate burden-sharing.","ai_generated":true,"unit":"sei-001259#insight-1","date_modified":"2026-10-23"},{"text":"Income within countries is assumed to follow a lognormal distribution, characterized by mean income and the standard deviation of the log of income, the latter of which relates to the Gini coefficient.","ai_generated":true,"unit":"sei-001259#insight-2","date_modified":"2026-10-23"},{"text":"The calculator assumes that individual per capita emissions vary with income according to a specific elasticity (gamma), which is consistent across all countries and typically ranges between 0.7 and 1.0.","ai_generated":true,"unit":"sei-001259#insight-3","date_modified":"2026-10-23"},{"text":"Capacity and responsibility are calculated using income thresholds; income below a lower threshold (yl) is exempt from both contributing to the capacity to pay and the responsibility for emissions.","ai_generated":true,"unit":"sei-001259#insight-4","date_modified":"2026-10-23"},{"text":"The Responsibility-Capacity Indicator (RCI) is the central metric for allocating burden-sharing, calculated as a weighted sum of a nation's share of global responsibility and its share of global capacity.","ai_generated":true,"unit":"sei-001259#insight-5","date_modified":"2026-10-23"},{"text":"Burden-sharing is modeled as a tax (T) representing a fraction of the gross world product (GWP), with national and individual tax obligations determined by the RCI.","ai_generated":true,"unit":"sei-001259#insight-6","date_modified":"2026-10-23"},{"text":"The calculator can optionally employ the Suits index to evaluate the progressivity or regressivity of the resulting global tax system by comparing the cumulative share of total tax against cumulative income.","ai_generated":true,"unit":"sei-001259#insight-7","date_modified":"2026-10-23"}],"climate_tags":["climate finance"],"geography_discussed":[],"frame_perspective":[],"analysis_type":["mathematical modeling","technical documentation"]}]}