# Investigating the Spectral Characteristics of High-Temperature Gases in Low-Carbon Chemical Pool Fires and Developing a Spectral Model

## TL;DR

This paper studies the spectral features of gases from low-carbon chemical fires and creates a model to help monitor pollution remotely.

## Contribution

The study introduces a high-precision spectral radiation model for remote monitoring of low-carbon chemical fire emissions.

## Key findings

- Distinct spectral bands were identified for CO2, SO2, NO, and NO2 from low-carbon chemical fires.
- The developed spectral model accurately predicts peak positions and shapes with high accuracy for combustion products like carbon disulfide and acetonitrile.

## Abstract

Low-carbon chemical fires pose significant hazards, and remote sensing of high-temperature gas emissions from these fires is a critical method for identifying and assessing their environmental impact. Analyzing the spectral characteristics of gases produced by low-carbon chemical pool fires and developing spectral radiation models can establish a foundation for remote pollution monitoring. However, such studies remain scarce. Using a custom-built high-temperature gas spectroscopy platform, this study extracts spectral features of gases emitted by low-carbon chemical pool fires. We investigate spectral interference mechanisms among combustion products and develop a high-precision spectral radiation model to support remote fire pollution monitoring. Experimental results reveal distinct spectral bands for key gases: CO2 peaks near 2.7 μm and 4.35 μm, SO2 at 4.05 μm, 7.5 μm, and 9.0 μm, NO at 5.5 μm, and NO2 at 3.6 μm and 6.3 μm. The proposed spectral radiation model accurately simulates the position and shape of spectral peaks. For carbon disulfide and acetonitrile combustion products, the model achieves prediction accuracies of 83.4–96.9% and 79.2–95.3%, respectively.