The identification of particulate matter (PM) sources and the quantification of their contribution to the urban environment is a necessary input for policymakers to reduce the air pollution impacts. The association between the PM sources and the oxidative potential (OP) is also a key indicator for evaluating the ability of PM sources to induce <em>in-vivo</em> oxidative stress and lead to adverse health effects, which becomes an emerging metric in the Directive on ambient air quality (22024/2881/EU). Most studies in Europe have focused on PM and OP sources in the short term, for only 1 or 2 years. However, the efficiency of reduction policies, trends, and epidemiological impacts cannot be properly evaluated with such short-term studies due to a lack of statistical robustness. Here, long-term PM₁₀ filter sampling at the Grenoble (France) urban background supersite and detailed chemical analyses were used to investigate decadal trends of the main PM sources and related OP metrics. Positive matrix factorization (PMF) analyses were conducted on the corresponding 11-year dataset (Jan 2013 to May 2023, n = 1570), enlightening the contributions of 10 PM sources: mineral dust, sulfate-rich, primary traffic, biomass burning, primary biogenic, nitrate-rich, MSA-rich, aged sea salt, industrial and chloride-rich. The stability of the chemical profile of these sources was validated by comparison with the profiles retrieved from shorter-term (3 years) successive PMF analyses. A Seasonal-Trend using LOESS decomposition was then applied to evaluate the trends of these PM₁₀ sources, which revealed a substantial decrease in PM₁₀ (-0.73 &micro;g m^-3 yr^-1) as well as that of many of the PM₁₀ sources. Specifically, negative trends for primary traffic and biomass burning sources are detected, with a reduction of 0.30 and 0.11 &micro;g m^-3 yr^-1,respectively. The OP PM₁₀ source apportionment in 11 years confirmed the high redox activity of the anthropogenic sources, including biomass burning, industrial, and primary traffic. Eventually, downward trends were also observed for OP_AA and OP_DTT, mainly driven by the reduction of residential heating and transport emissions, respectively.