Accurate modelling of natural dust emissions in East Asia remains challenging mainly due to complex surface conditions. Previous dust schemes often exhibited diverse sensitivities of dust emission flux to friction velocity and relied heavily on highly uncertain topography-based static source strength functions (<em>S</em>). To overcome these limitations, we developed the Asian Dust Emission Scheme version 1.0 (ADES v1.0), a new semi-empirical dust emission scheme optimized for the East Asian region, directly constrained by <em>in situ</em> micrometeorological and multi-level PM₁₀ observations obtained from the Horqin Desert area. Rather than relying on simple log-linear regression between dust emission flux and friction velocity, the new scheme introduces a refined dust flux formulation by directly optimizing it against field measurements. This yields a robust relationship where the dust emission flux is proportional to the friction velocity raised to the power of 1.72 (<em>F</em> &prop; <em>u</em>_*^1.72), which contrasts with the conventional third to fourth power relationships. Furthermore, the new scheme completely eliminates the conventional dependence on static source strength functions (<em>S</em>) and incorporates dynamic surface condition properties, such as soil freezing, vegetation cover, and snow fraction, as direct reduction factors that better reflect the complex land conditions of East Asia. The new scheme was implemented into the three-dimensional WRF-Chem model (version 3.9.1) along with the updated dust source region map and evaluated against two distinct Asia dust events: a wintertime event in February 2015 and a springtime event in March 2021. The control simulation utilizing the existing schemes (GOCART, AFWA, and UC schemes) exhibited severe underestimation or overestimation depending on the friction velocity and soil texture configurations. Conversely, the new semi-empirical scheme significantly reduced these systematic biases, demonstrating substantially improved performance in capturing both the onset and magnitude of dust outbreaks. Strikingly, the new scheme effectively suppressed the chronic overestimation of PM₁₀ concentrations under strong wind conditions by accounting for the realistic gentler slope of dust emission fluxes, while successfully capturing the long-range transport of dust plumes to downwind regions, including the Korean Peninsula. These findings underscore that incorporating direct in situ tower constraints and dynamic source maps into numerical models is essential for mitigating the long-lasting uncertainties in regional dust simulations over East Asia.