Exposures to fine particulate matter (PM$$_1$$
1
) have been associated with health impacts, but the understanding of the PM$$_1$$
1
concentration-response (PM$$_1$$
1
-CR) relationships, especially at low PM$$_1$$
1
, remains incomplete. Here, we present novel data using a methodology to mimic lung exposure to ambient air (2$$<PM_1<$$
<
P
M
1
<
60 $$\upmu$$
μ
g m$$^{-3}$$
-
3
), with minimized sampling artifacts for nanoparticles. A reference model (Air Liquid Interface cultures of human bronchial epithelial cells, BEAS-2B) was used for aerosol exposure. Non-linearities observed in PM$$_1$$
1
-CR curves are interpreted as a result of the interplay between the aerosol total oxidative potential (OP$$_t$$
t
) and its distribution across particle size (d$$_p$$
p
). A d$$_p$$
p
-dependent condensation sink (CS) is assessed together with the distribution with d$$_p$$
p
of reactive species . Urban ambient aerosol high in OP$$_t$$
t
, as indicated by the DTT assay, with (possibly copper-containing) nanoparticles, shows higher pro-inflammatory and oxidative responses, this occurring at lower PM$$_1$$
1
concentrations (< 5 $$\upmu$$
μ
g m$$^{-3}$$
-
3
). Among the implications of this work, there are recommendations for global efforts to go toward the refinement of actual air quality standards with metrics considering the distribution of OP$$_t$$
t
with d$$_p$$
p
also at relatively low PM$$_1$$
1
.