Global vegetation emits monoterpenes, which influence ecological interactions and atmospheric chemistry. Previous studies used a fixed exponential relationship (β coefficient) to model monoterpene emissions, but recent meta-analysis of 40 years of data shows that this relationship is more complex and sensitive to environmental factors. The β coefficient, representing temperature sensitivity, varies with the coefficient of determination (R²), indicating that plant functional types (PFTs) and other environmental factors influence emissions. A PFT-dependent β in biogenic emission models, coupled with a chemistry-climate model, shows that monoterpene emissions are highly sensitive to temperature changes, affecting atmospheric processes like oxidation and secondary organic aerosol (SOA) formation. The study found that β values vary significantly across different ecosystems, with higher values in tropical and boreal forests. The β coefficient for tropical broadleaf evergreen forests was 0.20°C⁻¹, while for boreal needleleaf evergreen forests, it was 0.15°C⁻¹. These values are higher than the previously used standard β of 0.10°C⁻¹, suggesting that global models may underestimate temperature sensitivity. The study also found that β values derived from field data were higher than those from controlled conditions, indicating greater sensitivity in natural environments. Model simulations using the MEGAN and EMAC models showed that revised β values led to significant changes in emission rates and atmospheric feedbacks. For example, annual MT emissions decreased by 13% in the PFT simulation, with the most pronounced reductions in boreal forests. In contrast, tropical ecosystems, especially the Amazon rainforest, showed increased MT emissions, with potential doubling during dry seasons. These findings highlight the importance of accurately simulating temperature effects on MT emissions to improve understanding of atmospheric chemistry and climate change impacts. The study emphasizes the need for more process-oriented research on biosphere-atmosphere interactions, particularly in tropical, pan-Arctic, grassland, and agricultural ecosystems. Accurate modeling of temperature sensitivity is crucial for predicting the effects of climate change on ecosystems and atmospheric processes. The results underscore the critical role of temperature-dependent MT emissions in shaping atmospheric oxidation and SOA formation, with implications for radiative cooling and climate change. The study concludes that revising β values based on PFTs is essential for improving the accuracy of atmospheric models and understanding the complex interactions between vegetation, climate, and atmospheric chemistry.Global vegetation emits monoterpenes, which influence ecological interactions and atmospheric chemistry. Previous studies used a fixed exponential relationship (β coefficient) to model monoterpene emissions, but recent meta-analysis of 40 years of data shows that this relationship is more complex and sensitive to environmental factors. The β coefficient, representing temperature sensitivity, varies with the coefficient of determination (R²), indicating that plant functional types (PFTs) and other environmental factors influence emissions. A PFT-dependent β in biogenic emission models, coupled with a chemistry-climate model, shows that monoterpene emissions are highly sensitive to temperature changes, affecting atmospheric processes like oxidation and secondary organic aerosol (SOA) formation. The study found that β values vary significantly across different ecosystems, with higher values in tropical and boreal forests. The β coefficient for tropical broadleaf evergreen forests was 0.20°C⁻¹, while for boreal needleleaf evergreen forests, it was 0.15°C⁻¹. These values are higher than the previously used standard β of 0.10°C⁻¹, suggesting that global models may underestimate temperature sensitivity. The study also found that β values derived from field data were higher than those from controlled conditions, indicating greater sensitivity in natural environments. Model simulations using the MEGAN and EMAC models showed that revised β values led to significant changes in emission rates and atmospheric feedbacks. For example, annual MT emissions decreased by 13% in the PFT simulation, with the most pronounced reductions in boreal forests. In contrast, tropical ecosystems, especially the Amazon rainforest, showed increased MT emissions, with potential doubling during dry seasons. These findings highlight the importance of accurately simulating temperature effects on MT emissions to improve understanding of atmospheric chemistry and climate change impacts. The study emphasizes the need for more process-oriented research on biosphere-atmosphere interactions, particularly in tropical, pan-Arctic, grassland, and agricultural ecosystems. Accurate modeling of temperature sensitivity is crucial for predicting the effects of climate change on ecosystems and atmospheric processes. The results underscore the critical role of temperature-dependent MT emissions in shaping atmospheric oxidation and SOA formation, with implications for radiative cooling and climate change. The study concludes that revising β values based on PFTs is essential for improving the accuracy of atmospheric models and understanding the complex interactions between vegetation, climate, and atmospheric chemistry.