We develop innovative tools, algorithms and methodologies at the intersection of climate and social sciences, grounded in the core of statistics and econometrics, and powered by artificial intelligence, to advance knowledge and support partners and countries across the world.
We exist to bridge rigorous academic research and the urgent, real-world demands of climate policy, sustainable development and environmental governance, working alongside partners and institutions that share our commitment to science-driven change.
We develop innovative tools and algorithms grounded in the core sciences and strengthened by statistics, econometrics and artificial intelligence. Our work is not theoretical: it is deployed in real policy contexts, from EU-level reporting frameworks to national climate transparency systems in developing nations.
Our work spans climate change, energy, environment, environmental economics, climate finance and policy analysis, partnering with institutions, governments, international organisations and research networks across the world. We operate at every scale, from local initiatives to global frameworks, and across all levels of public administration.
Our tools are peer-reviewed, internationally published and operationally validated, recognised by organisations such as the UNFCCC Secretariat and the IPCC.
Chemistry, physics and engineering principles underpin our models, ensuring scientific rigour in all quantitative approaches.
Robust statistical methodologies for causal inference, uncertainty quantification and evidence-based policy evaluation.
We develop and apply AI and machine learning across scientific domains, from climate projection to NLP-powered literature research, automated processing pipelines and AI-assisted policy analysis.
Partnerships and research spanning European institutions, national governments and international organisations across more than 70 countries.
Six interconnected knowledge domains, all contributing to a unified mission: generating knowledge that enables better decisions on climate and sustainability.
Simulation models, long-term projections and complex systems integration, connecting physical, socioeconomic and environmental variables to inform policy and planning.
Advanced statistical frameworks for causal inference, quasi-experimental methods, uncertainty analysis and rigorous policy impact evaluation.
Cost-benefit analysis of environmental and climate policies, carbon pricing, externality valuation, energy market modelling and climate finance assessment.
Machine learning, deep learning and NLP applied across scientific domains, from climate projections and automated data processing to AI-assisted literature review and policy analysis support.
Development of bespoke computational tools and software tailored to the specific needs of policy assessment, scientific reporting and evidence-based decision-making.
Geospatial computation, remote sensing analysis, satellite data processing and interactive dashboards that turn complex scientific outputs into accessible, actionable insights.
We don't adapt existing software to our problems. We build the tools our research demands, validated, peer-reviewed and deployable in real-world policy contexts.
Macroeconomic damage functions, sector by sector
A quantitative modelling framework linking physical climate projections to macroeconomic outcomes: GDP, sectoral output, employment and welfare, under different warming and policy scenarios.
Combines climate science with econometric and input-output modelling to produce country-level economic damage functions that can inform adaptation and mitigation cost-benefit analysis.
Local land use from satellite observation and computational analysis
A remote sensing and machine learning pipeline extracting high-resolution local land use and land cover data from satellite imagery, providing ground-truth inputs for GHG inventories, REDD+ accounting and environmental assessments in data-sparse contexts.
Addresses a critical bottleneck in climate reporting for developing nations: the absence of reliable, granular land use data at sub-national scale.
Satellite-physics enhanced climate downscaling for regional adaptation
A physically-grounded, satellite-integrated climate downscaling pipeline that transforms coarse regional climate model outputs (CORDEX, around 25 km) into high-resolution projections at approximately 1 km for any country on Earth, using Copernicus satellite data as the spatial refinement layer, with no local weather stations required.
Delivers locally calibrated, multi-scenario projections of temperature, precipitation, humidity and evapotranspiration, plus actionable indices: heat wave frequency (WBGT), drought indicators (SPEI) and seasonal water balance, specifically designed for climate adaptation planning in data-sparse developing nations.
LTBM, pathway modelling from net-zero targets
A quantitative backcasting framework that works backward from defined long-term mitigation targets, such as net-zero by 2050, to derive consistent, sector-level policy pathways and milestone trajectories.
The methodological foundation was peer-reviewed and published in Mitigation and Adaptation Strategies for Global Change (Springer, 2023), applied to design a long-term low-emission development strategy (LT-LEDS) for Tajikistan under the Paris Agreement.
Active engagements and validated deployments across Europe, Latin America, Central Asia, Asia-Pacific and beyond. Our research is local in calibration, global in ambition.
Active projects applying our methodologies in real policy contexts, from European institutional reporting to developing-country climate transparency.
Supporting the EEA in quality assurance and data flow management for energy and GHG reporting within the Energy Community framework, applying proprietary QA/QC methodologies to ensure compliance with European and international reporting standards.
The project directly leverages our core competencies in GHG data quality, statistical validation and transparent environmental reporting.
Full technical support to the Guyana Forestry Commission for the development of Guyana's BTR2 under the UNFCCC Enhanced Transparency Framework, including the REDD+ Technical Annex, the critical component for forest carbon accounting.
Enabling a developing country to meet its Paris Agreement reporting obligations with consistent, inventory-linked methodology, leveraging our full GHG modelling and projections expertise.
Capacity-building programme for ASEAN Member States on a climate-economy modelling tool, delivered under UNDP's Climate Finance Network (CFN) and the UK-funded Climate Action for Resilient Asia (CARA) programme. The sessions cover modelling the macroeconomic impact of climate change to inform NDCs, national adaptation plans, BTR reporting and climate finance mobilisation.
Delivery is anchored in ASEAN Climate Week 2026 in Manila, during the Philippine ASEAN Chairpersonship, under the theme of bridging climate ambition with finance. The exchange convenes ministries of finance, environment and planning across 11 ASEAN countries.
Interactive tools and infographics that translate our research outputs into explorable, policy-relevant interfaces. Open access, built on the same methodologies behind our institutional work.
An animated, interactive infographic mapping the full cycle of AI-assisted public decision-making: from raw data sources through ML model architectures, expert validation, policy adoption and MRV monitoring. Includes real-world use cases across climate, health, transport and urban planning.
An interactive dashboard exploring GHG emission trajectories for all EU member states under three UNFCCC scenarios (WOM, WM, WAM), aligned with EEA and Eurostat reporting. Select up to five countries simultaneously, toggle scenarios, compare against a target year and download the full dataset as CSV.
Thought pieces from our researchers on the science, methods and policy implications behind our work.
Most countries submit NDCs with projections methodologically disconnected from their own GHG inventories. We explain why this happens and what it takes to solve it.
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A candid assessment of which ML methods perform best on small, noisy climate datasets, and where classical statistics still win.
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Why self-reported land use data falls short, and how satellite-derived classification transforms what developing nations can actually measure.
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IAMs systematically underestimate climate damages. Here is why, and what a more rigorous damage function approach looks like.
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A structural analysis of why most NDCs cannot be credibly tracked, and the conditions that would make them meaningful accountability instruments.
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A novel five-step backcasting approach to assess alternative mitigation scenarios for carbon neutrality by 2050. The methodological foundation for our LTBM model.
Read paper · Springer →
Applying ARDL methodology to test the Environmental Kuznets Curve by economic sector across all 27 EU countries, using audited UNFCCC inventory data from 1990 to 2018.
Read paper · Springer →A team combining academic expertise and hands-on experience in international climate policy, quantitative modelling and applied research.
JLOver 15 years of expertise in climate change, energy and environmental economics. IPCC author for the forthcoming 2027 Methodology Report on Inventories for Short-lived Climate Forcers. UNFCCC Lead Reviewer and Task Manager for GHG projections at ETC/CM (EEA). Has directed or contributed to over 100 international projects across more than 70 countries. Author of peer-reviewed methodologies and architect of integrated models at the interface of econometrics and the physical sciences of the climate.
ORCID · 0000-0002-9836-2020 →
CFData Scientist with 4+ years in R&D applying machine and deep learning to environmental challenges. Specialised in end-to-end data pipelines for heterogeneous datasets and predictive models for risk assessment and early-warning systems. Awarded a HIDA Helmholtz Visiting Researcher Grant at GFZ German Research Centre for Geosciences, developing ML methods based on hyperspectral imagery for environmental monitoring.
Google Scholar →
PLOver 30 years of expertise in climate governance, GHG inventories and reporting, with documented work across more than 120 countries. IPCC Lead Author for the 2027 Methodology Report on SLCFs and for the 2019 Refinement of the IPCC Guidelines (Vol. 3, Chemical Industry). Review Editor of the IPCC AR6 WGIII. UNFCCC Review Officer and Lead Reviewer since 2004, instructor of UNFCCC MRV courses, and moderator of the UNFCCC Transparency Helpdesk.
Our innovation is not incremental. We develop original methodologies, proprietary software and novel scientific approaches where no market equivalent exists.
Our in-house modelling suite (Economic Impact of Climate Change, LOCUS, SPECTRA and LTBM) constitutes demonstrable intellectual property and scientific know-how. Foundational research is peer-reviewed and published in international indexed journals.
We design integrated approaches to GHG reporting under the Paris Agreement that ensure consistency across inventories, projections, mitigation policies and NDC tracking: a scientifically novel angle with no prior equivalent, formally documented in peer-reviewed publications.
The team combines an IPCC author, a UNFCCC Lead Reviewer, a PhD in theoretical physics with 10+ years in climate-risk modelling, and a PhD in microbiology with expertise in ML for environmental monitoring. Research published in indexed international journals and operationally acknowledged by the UNFCCC Secretariat.
Two active engagements with high-profile international public sector partners: the European Environment Agency (EU) and the Guyana Forestry Commission (national government), demonstrating real-world applicability and scalability.
Our methodologies are universally applicable across countries and sectors, with decreasing marginal deployment costs. Explicitly designed for scaling to developing nations: a large, growing area driven by Paris Agreement reporting obligations.
We work alongside institutions, international organisations, research networks and governments that share our commitment to rigorous, science-driven approaches to climate policy, environmental reporting and sustainable development.
Whether you are developing a BTR, designing an NDC, building a GHG projection system or evaluating a climate policy, we'd like to explore how we can advance the science together.