Accurate estimation of ambient background levels in urban soils is essential for identifying contamination events. This study evaluates multiple methods to determine polycyclic aromatic hydrocarbons (PAHs) background in Macau, China. The sum of 16 priority PAHs was estimated using statistical methods (mean ± 2σ, Lepeltier, iterative 2σ, calculated distribution) and a mass-balanced regression model accounting for urbanization duration. Results across methods showed differences due to computational principles but were generally consistent. Bootstrap resampling quantified uncertainty, confirming model reliability. The proposed approach provides robust background estimation for regions with low diffuse pollution, facilitating effective urban environmental management. © 2022 Elsevier B.V., All rights reserved.