Enhancement of the polynomial functions response surface model for real-time analyzing ozone sensitivity

Authors：Jin, Jiangbo; Zhu, Yun^*; Jang, Jicheng; Wang, Shuxiao; Xing, Jia; Chiang, Pen-Chi; Fan, Shaojia; Long, Shicheng

Source：Frontiers of Environmental Science & Engineering, 2021, 15(2): 31.

DOI：10.1007/s11783-020-1323-0

• Response surface model
• Hill-climbing algorithm
• Ozone pollution
• Precursor emissions
• Control strategy

Quantification of the nonlinearities between ambient ozone (O-3) and the emissions of nitrogen oxides (NOx) and volatile organic compound (VOC) is a prerequisite for an effective O-3 control strategy. An Enhanced polynomial functions Response Surface Model (Epf-RSM) with the capability to analyze O-3-NOx-VOC sensitivities in real time was developed by integrating the hill-climbing adaptive method into the optimized Extended Response Surface Model (ERSM) system. The Epf-RSM could single out the best suited polynomial function for each grid cell to quantify the responses of O-3 concentrations to precursor emission changes. Several comparisons between Epf-RSM and pf-ERSM (polynomial functions based ERSM) were performed using out-of-sample validation, together with comparisons of the spatial distribution and the Empirical Kinetic Modeling Approach diagrams. The comparison results showed that Epf-RSM effectively addressed the drawbacks of pf-ERSM with respect to over-fitting in the margin areas and high biases in the transition areas. The O-3 concentrations predicted by Epf-RSM agreed well with Community Multi-scale Air Quality simulation results. The case study results in the Pearl River Delta and the north-western area of the Shandong province indicated that the O-3 formations in the central areas of both the regions were more sensitive to anthropogenic VOC in January, April, and October, while more NOx-sensitive in July.

• Institution
  中山大学; y; 清华大学