Introduction: The AIRCARD study is designed to investigate the relationship between long-term exposure to air and noise pollution and cardiovascular disease incidence and mortality. We aim to conduct a robust prospective cohort analysis assessing the cumulative and differential impacts of air and noise pollution exposure on cardiovascular disease and mortality. This study will adjust for relevant confounders, including traditional cardiovascular risk factors, socioeconomic indicators, and lipid-lowering agents. Methods: This prospective cohort study will include 27,022 male participants aged 65–74, recruited from the two large Danish DANCAVAS and VIVA trials, both population-based randomized, multicentered, clinically controlled studies. We will assess long-term exposure to air pollutants using the state-of-the-art DEHM/UBM/AirGIS modeling system and noise pollution through the Nord2000 and SoundPLAN models, covering data from 1979 to 2019. This statistical analysis plan is strictly formulated to predefine the analytical approach for all outcomes and key study variables before data access. The primary analysis will utilize Cox proportional hazards models, adjusted for confounders identified in our cohort (age, body mass index, hypertension, diabetes, smoking status, family history of heart disease, socioeconomic factors, and lipid-lowering agents). This statistical analysis plan further includes Spearman rank correlation to explore inter-pollutant associations. Conclusion: The AIRCARD study addresses global concerns about the impact of air and noise pollution on cardiovascular disease. This research is important for understanding how the pollutants contribute to cardiovascular disease. We aim to provide insights into this area, emphasizing the need for public health measures to mitigate pollution exposure. Our goal is to provide policymakers and healthcare professionals with information on the role of environmental factors in cardiovascular health that could influence global strategies to reduce the cardiovascular disease burden associated with pollution. The design of this SAP ensures transparency and verifiability, considering the complexities of evaluating environmental health impacts over an extended period.