# Closing Gaps in Emissions Monitoring with Climate TRACE

arXiv: https://arxiv.org/abs/2511.19277 · HTML: https://mlsanity.com/paper/2511.19277/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 3 of its 93 references that are in the map.
- First posted on arXiv 24 Nov 2025.

## Builds on (most cited first, 3 of 3)

- [Tackling Climate Change with Machine Learning](https://mlsanity.com/paper/1906.05433/) (2019)
- [Satellite Monitoring of Terrestrial Plastic Waste](https://mlsanity.com/paper/2204.01485/) (2022)
- [Towards Indirect Top-Down Road Transport Emissions Estimation](https://mlsanity.com/paper/2103.08829/) (2021)

## Built on by (most cited first, 1 of 1)

- [Global Building Area Estimation Products: How Accurate Are They?](https://mlsanity.com/paper/2607.19766/) (2026)

## Abstract (arXiv)

Global greenhouse gas emissions estimates are essential for monitoring and mitigation planning. Existing emissions datasets provide critical foundations for understanding emissions patterns across sectors, geographies, and time scales. Through a structured assessment of recent emissions datasets, we identified opportunities to further increase the actionability of emissions data through more comprehensive source-level coverage, finer spatial and temporal resolution, and more frequent updates. Building on existing resources to address these opportunities, we present the Climate TRACE framework and resulting dataset, which is available on an open-access platform (climatetrace.org). The Climate TRACE framework synthesizes existing emissions data, prioritizing accuracy, coverage, and resolution, and fills remaining gaps using sector-specific estimation approaches. The resulting dataset is the first to provide global emissions estimates for individual sources (e.g., individual power plants) for most anthropogenic emitting sectors. The dataset spans January 1, 2021, to the present, with a two-month reporting lag and monthly updates. This dataset and open-access platform provides access to detailed emissions estimates for most subnational governments worldwide. By combining source-level spatial detail, monthly updates, and broad sectoral coverage, the dataset is designed to support analyses relevant to emissions monitoring and mitigation planning.