Sparse lateral displacement arrays are easier to scale up than full deterministic lateral displacement arrays or deterministic ratchets, because they require lower pressure drop and simplify the construction of the device. However, the asymmetry of sparse arrays leads to a non-homogeneous pressure distribution with as a consequence an uneven flow field and limited separation performance. Furthermore, the construction of high throughput displacement sparse ratchet devices that allow separation of small particles is challenging. Therefore, in this study we investigated the use of sieves to replace obstacles in sparse systems. Moreover, we investigated a strategy to optimize the separation performance by adjusting the internal pressure distribution. Our experiments showed in first instance that the introduction of sieves negatively affects separation performance, which was explained by the lower porosity of the sieves. However, via fluid flow calculations and high-speed camera analyses we found that pressure distribution can be optimized by adapting the flow rates of the different outlets preventing high pressure drop across the obstacles arrays near the bottom of the device. Experimental separation data for adjusted outlet flow conditions indeed showed better particle displacement, especially in the bottom region, and as a result improved separation behavior. These findings demonstrate the potential of the scalable sieve-based lateral displacement device to effectively separate particles.