Spatial profiles of impurity emission measurements in the extreme ultraviolet (EUV) spectroscopic range in radiofrequency (RF)-heated discharges are combined with one-dimensional and three-dimensional transport simulations to study the effects of resonant magnetic perturbations (RMPs) on core impurity accumulation at EAST. The amount of impurity line emission mitigation by RMPs appears to be correlated with the ion Z for lithium, carbon, iron and tungsten monitored, i.e. stronger suppression of accumulation for heavier ions. The targeted effect on the most detrimental high-Z impurities suggests a possible advantage using RMPs for impurity control. Profiles of transport coefficients are calculated with the STRAHL one-dimensional impurity transport code, keeping
$\nu /D$
fixed and using the measured spatial profiles of
$\textrm{F}{\textrm{e}^{20 + }}$
,
$\textrm{F}{\textrm{e}^{21 + }}$
and
$\textrm{F}{\textrm{e}^{22 + }}$
to disentangle the transport coefficients. The iron diffusion coefficient
${D_{\textrm{Fe}}}$
increases from
$1.0- 2.0\;{\textrm{m}^2}\;{\textrm{s}^{ - 1}}$
to
$1.5- 3.0\;{\textrm{m}^2}\;{\textrm{s}^{ - 1}}$
from the core region to the edge region
$(\rho \gt 0.5)$
after the onset of RMPs. Meanwhile, an inward pinch of iron convective velocity
${\nu _{\textrm{Fe}}}$
decreases in magnitude in the inner core region and increases significantly in the outer confined region, simultaneously contributing to preserving centrally peaked
$\textrm{Fe}$
profiles and exhausting the impurities. The
${D_{\textrm{Fe}}}$
and
${\nu _{\textrm{Fe}}}$
variations lead to reduced impurity contents in the plasma. The three-dimensional edge impurity transport code EMC3-EIRENE was also applied for a case of RMP-mitigated high-Z accumulation at EAST and compared to that of low-Z carbon. The exhaust of
${\textrm{C}^{6 + }}$
toward the scrape-off layer accompanying an overall suppression of heavier
${\textrm{W}^{30 + }}$
is observed when using RMPs.
Improved profile fitting and quantification of uncertainty in experimental measurements of impurity transport coefficients using Gaussian process regression