# Parameterising the effect of human occupancy and kinetic energy on indoor air pollution

## TL;DR

This study explores how human presence and activity affect indoor air pollution in office spaces, finding strong links between movement and pollutant levels.

## Contribution

The study introduces a framework combining occupancy and kinetic energy data to model indoor air pollution sources and improve air quality management.

## Key findings

- PM10 concentrations correlate strongly with occupancy (up to r = 0.65) and even more with kinetic energy (up to r = 0.74).
- TVOCs and CO2 show strong correlations with kinetic energy (up to r = 0.83), suggesting their use as pollution proxies.
- Room characteristics and usage influence how additional occupants affect air quality, highlighting the need for contextual models.

## Abstract

Indoor air quality (IAQ) is increasingly recognised as one of the most important aspects for public health, workplace safety and productivity. While indoor and outdoor factors both influence indoor pollutant levels, human presence and activity are key drivers of the emission of specific pollutants, including particulate matter (PM), total volatile organic compounds (TVOCs) and carbon dioxide (CO2). This study investigates the relationship between occupancy, physical activity measured by kinetic energy (KE), and air pollution concentrations in a real-world office setting, by combining data from air quality and radar motion sensors. Two exemplar office spaces were investigated, comprising an open-office area and a meeting room. PM, in the PM1 and PM2.5 size fractions, were found to be highly correlated with the outdoor conditions, whereas PM10 correlates more closely with indoor occupancy (up to r = 0.65). Even higher correlations, up to r = 0.74, were found between human activity, quantified as KE, and the PM10 concentrations. The TVOCs and CO2 showed even stronger correlations with KE (up to r = 0.83), suggesting that these metrics can be used as excellent proxies for estimating certain types of indoor air pollution. Notably, the impact of additional occupants varies depending on room characteristics and usage, underscoring the need for contextualised models of IAQ. By quantifying both outdoor infiltration and indoor emissions, this study offers a framework for disentangling pollutant sources and guiding interventions to optimise IAQ. These insights support evidence-based strategies to create healthier and more productive office environments.