In this study, we introduce the Turbulent Enhancement Ratio (TER) method as a new approach for characterizing local emission sources in complex urban environments, with a focus on the city of Innsbruck, Austria. The idea behind the approach is to take advantage of highly time resolved trace gas observations, that allow identifying turbulent air motions, from which a turbulent enhancement ratio can be constructed. We use a comprehensive measurement setup at the Innsbruck Atmospheric Observatory utilizing advanced instruments to test the approach. Our dataset, spanning from mid-2018 to early 2022, includes periods affected by the COVID-19 pandemic, allowing us to assess the impact of reduced traffic and changes in domestic fuel use on NO<sub>x</sub>/CO<sub>2</sub> emission ratios. We test the approach by comparing with direct eddy covariance flux measurements of these tracers. The results show a statistically significant linear relationship between TER and the flux ratio of NO<sub>x</sub> over CO<sub>2</sub>, with regression slopes ranging between 0.96 to 1.1. Weekday TER values are generally higher due to increased traffic, while weekend values are lower, reflecting reduced commuter activity. Seasonal analysis shows that winter TER is influenced significantly by domestic heating, while in summer, traffic is the predominant source of NO<sub>x</sub> and CO<sub>2</sub> emissions within the measurement footprint. The diurnal cycle of TER also highlights the role of valley wind systems in modulating local emissions through changes in footprint, with valley-up winds bringing higher traffic-related emissions to the site during the day. Our findings demonstrate that TER is a robust predictor for emission ratios in urban settings, offering insights into the dynamics of local emissions. The method's ability to capture turbulent fluctuations provides a more nuanced understanding of source contributions, particularly in environments with complex and mixed emission sources.