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This prospective cross-sectional study aimed to evaluate the agreement of two new biometers for measuring ocular biometric parameters in young healthy eyes. ocular biometric parameters were measured using IOLMaster 700 and OA-2000. Power vector analyses of Cartesian (J0) and oblique (J45) components of corneal astigmatism were performed. The right eyes of 103 healthy volunteers were analyzed. The 95% limits of agreement ranged from −0.03 to 0.03 mm, −0.08 to 0.07 mm, −0.18 to 0.18 diopters (D), −1.09 to 1.16 D, −1.18 to 1.15 D for axial length (AL), anterior chamber depth (ACD), mean keratometry, J0 and J45 respectively, which were all comparable between the two biometers, while significant differences were detected in lens thickness (LT), central corneal thickness (CCT), whiteto-white (WTW) and pupil diameter (PD). Predicted intraocular lens (IOL) powers were comparable between the two biometers by Haigis and Barrett Universal II formulas, while not by SRK/T, Hoffer Q and Holladay 2. Excepting CCT, WTW and PD meaurements, IOLMaster 700 and OA-2000 have excellent agreement on ocular biometric measurements and astigmatism power vectors, which provides more options for ocular biometric measurements and enables constant optimization for IOL power calculation.

Abstract. The explosive growth of PM2.5 mass usually results in extreme PM2.5 levels and severe haze pollution in eastern China, and is generally underestimated by current atmospheric chemistry models. Based on one such model, GRAPES_CUACE, three sensitivity experiments – a “background” experiment (EXP1), an “online aerosol feedback” experiment (EXP2), and an “80 % decrease in the turbulent diffusion coefficient of chemical tracers” experiment, based on EXP2 (EXP3) – were designed to study the contributions of the aerosol–radiation feedback (AF) and the decrease in the turbulent diffusion coefficient to the explosive growth of PM2.5 during a “red alert” heavy haze event in China's Jing–Jin–Ji (Beijing–Tianjin–Hebei) region. The results showed that the turbulent diffusion coefficient calculated by EXP1 was about 60–70 m−2 s−1 on a clear day and 30–35 m−2 s−1 on a haze day. This difference in the diffusion coefficient was not enough to distinguish between the unstable atmosphere on the clear day and the extremely stable atmosphere during the PM2.5 explosive growth stage. Furthermore, the inversion calculated by EXP1 was obviously weaker than the actual inversion from sounding observations on the haze day. This led to a 40 %–51 % underestimation of PM2.5 by EXP1; the AF decreased the diffusion coefficient by about 43 %–57 % during the PM2.5 explosive growth stage, which obviously strengthened the local inversion. In addition, the local inversion indicated by EXP2 was much closer to the sounding observations than that indicated by EXP1. This resulted in a 20 %–25 % reduction of PM2.5 negative errors in the model, with errors as low as −16 % to −11 % in EXP2. However, the inversion produced by EXP2 was still weaker than the actual observations, and the AF alone could not completely explain the PM2.5 underestimation. Based on EXP2, the 80 % decrease in the turbulent diffusion coefficient of chemical tracers in EXP3 resulted in near-zero turbulent diffusion, referred to as a “turbulent intermittence” atmospheric state, which subsequently resulted in a further 14 %–20 % reduction of the PM2.5 underestimation; moreover, the negative PM2.5 errors were reduced to −11 % to 2 %. The combined effects of the AF and the decrease in the turbulent diffusion coefficient explained over 79 % of the underestimation of the explosive growth of PM2.5 in this study. The results show that online calculation of the AF is essential for the prediction of PM2.5 explosive growth and peaks during severe haze in China's Jing–Jin–Ji region. Furthermore, an improvement in the planetary boundary layer scheme with respect to extremely stable atmospheric stratification is essential for a reasonable description of local “turbulent intermittence” and a more accurate prediction of PM2.5 explosive growth during severe haze in this region of China.