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Abstract. Sensitivity analysis in chemical transport models quantifies the response of output variables to changes in input parameters. This information is valuable for researchers engaged in data assimilation and model development. Additionally, environmental decision-makers depend upon these expected responses of concentrations to emissions when designing and justifying air pollution control strategies. Existing sensitivity analysis methods include the finite-difference method, the direct decoupled method (DDM), the complex variable method, and the adjoint method. These methods are either prone to significant numerical errors when applied to nonlinear models with complex components (e.g. finite difference and complex step methods) or difficult to maintain when the original model is updated (e.g. direct decoupled and adjoint methods). Here, we present the implementation of the hyperdual-step method in the Community Multiscale Air Quality Model (CMAQ) version 5.3.2 as CMAQ-hyd. CMAQ-hyd can be applied to compute numerically exact first- and second-order sensitivities of species concentrations with respect to emissions or concentrations. Compared to CMAQ-DDM and CMAQ-adjoint, CMAQ-hyd is more straightforward to update and maintain, while it remains free of subtractive cancellation and truncation errors, just as those augmented models do. To evaluate the accuracy of the implementation, the sensitivities computed by CMAQ-hyd are compared with those calculated with other traditional methods or a hybrid of the traditional and advanced methods. We demonstrate the capability of CMAQ-hyd with the newly implemented gas-phase chemistry and biogenic aerosol formation mechanism in CMAQ. We also explore the cross-sensitivity of monoterpene nitrate aerosol formation to its anthropogenic and biogenic precursors to show the additional sensitivity information computed by CMAQ-hyd. Compared with the traditional finite difference method, CMAQ-hyd consumes fewer computational resources when the same sensitivity coefficients are calculated. This novel method implemented in CMAQ is also computationally competitive with other existing methods and could be further optimized to reduce memory and computational time overheads. 

Abstract Three-dimensional (3D) bioprinting precisely deposits picolitre bioink to fabricate functional tissues and organs in a layer-by-layer manner. The bioink used for 3D bioprinting incorporates living cells. During printing, cells suspended in the bioink sediment to form cell aggregates through cell-cell interaction. The formation of cell aggregates due to cell sedimentation have been widely recognized as a significant challenge to affect the printing reliability and quality. This study has incorporated the active circulation into the bioink reservoir to mitigate cell sedimentation and aggregation. Force and velocity analysis were performed, and a circulation model has been proposed based on iteration algorithm with the time step for each divided region. It has been found that (a) the comparison of the cell sedimentation and aggregation with and without the active bioink circulation has demonstrated high effectiveness of active circulation to mitigate cell sedimentation and aggregation for the bioink with both a low cell concentration of 1 × 10⁶cells ml⁻¹and a high cell concentration of 5 × 10⁶cells ml⁻¹; and (b) the effect of circulation flow rate on cell sedimentation and aggregation has been investigated, showing that large flow rate results in slow increments in effectiveness. Besides, the predicted mitigation effectiveness percentages on cell sedimentation by the circulation model generally agrees well with the experimental results. In addition, the cell viability assessment at the recommended maximum flow rate of 0.5 ml min⁻¹has demonstrated negligible cell damage due to the circulation. The proposed active circulation approach is an effective and efficient approach with superior performance in mitigating cell sedimentation and aggregation, and the resulting knowledge is easily applicable to other 3D bioprinting techniques significantly improving printing reliability and quality in 3D bioprinting.