The study investigates the high temperature sensitivity of monoterpene emissions from global vegetation, which are crucial for atmospheric chemistry and climate feedbacks. Using a meta-analysis of 40 years of published data, the authors found that the relationship between monoterpene emissions and temperature is more complex and sensitive than previously thought. The meta-analysis revealed a higher temperature sensitivity (β = 0.13 ± 0.01 °C⁻¹) compared to the commonly used fixed value of 0.10 °C⁻¹ in global emission models. This sensitivity varies among plant functional types (PFTs), with boreal needle leaf evergreen forests and tropical broadleaf evergreen forests showing the highest sensitivity. The study also demonstrated that the quality of the regression fit (R²) is a significant factor in determining the temperature sensitivity, with higher R² values leading to higher β coefficients. Model simulations using the MEGAN and EMAC models showed that the revised temperature sensitivity parameters significantly impacted global monoterpene emissions, atmospheric oxidation, and secondary organic aerosol (SOA) formation. The findings highlight the urgent need for accurate simulations of temperature effects on monoterpene emissions to better understand and predict the impacts of climate change on atmospheric chemistry and the biosphere.The study investigates the high temperature sensitivity of monoterpene emissions from global vegetation, which are crucial for atmospheric chemistry and climate feedbacks. Using a meta-analysis of 40 years of published data, the authors found that the relationship between monoterpene emissions and temperature is more complex and sensitive than previously thought. The meta-analysis revealed a higher temperature sensitivity (β = 0.13 ± 0.01 °C⁻¹) compared to the commonly used fixed value of 0.10 °C⁻¹ in global emission models. This sensitivity varies among plant functional types (PFTs), with boreal needle leaf evergreen forests and tropical broadleaf evergreen forests showing the highest sensitivity. The study also demonstrated that the quality of the regression fit (R²) is a significant factor in determining the temperature sensitivity, with higher R² values leading to higher β coefficients. Model simulations using the MEGAN and EMAC models showed that the revised temperature sensitivity parameters significantly impacted global monoterpene emissions, atmospheric oxidation, and secondary organic aerosol (SOA) formation. The findings highlight the urgent need for accurate simulations of temperature effects on monoterpene emissions to better understand and predict the impacts of climate change on atmospheric chemistry and the biosphere.