Regional background ozone estimation for China through data fusion of observation and simulation.

Regional background ozone (O3_RBG) is an important component of surface ozone (O3). However, due to the uncertainties in commonly used Chemical Transport Models (CTMs) and statistical models, accurately assessing O3_RBG in China is challenging. In this study, we calculated the O3_RBG concentrations with the CTM - Brute Force Method (BFM) and constrained the results with site observations of O3 with the multiple linear regression (MLR) model. The annual average O3_RBG concentration in China region in 2020 is 35 ± 4 ppb, accounting for 81 ± 5 % of the maximum 8-h average O3 (MDA8 O3). We applied the random forest and Shapley additive explanations based on meteorological standardization techniques to separate the contributions of meteorology and natural emissions to O3_RBG. Natural emissions contribute more significantly to O3_RBG than meteorology in various Chineses regions (30-40 ppb), with higher contributions during the warm season. Meteorological factors show higher contributions in the spring and summer seasons (2-3 ppb) than the other seasons. Temperature and humidity are the primary contributors to O3_RBG in regions with severe O3 pollution in China, with their individual impacts ranging from 30 % to 62 % of the total impacts of all meteorological factors in different seasons. For policy implications, we tracked the contributions of O3_RBG and local photochemical reaction contributions (O3_LC) to total O3 concentration at different O3 levels. We found that O3_LC contribute over 45 % to MDA8 O3 on polluted days, supporting the current Chinese policy of reducing O3 peak concentrations by cutting down precursor emissions. However, as the contribution of O3_RBG is not considered in the policy, additional efforts are needed to achieve the control groal of O3 concentration. As the implementation of stringent O3 control measurements in China, the contribution of O3_RBG become increasingly significant, suggesting the need for attention to O3_RBG and regional joint prevention and control.

Hidden image recovery using a biased photorefractive crystal in the Fourier plane of an optical imaging system.

Self-diffraction can be induced using a biased photorefractive crystal in the Fourier plane of an imaging system where the light beam intensity is naturally high due to the concentration effect of an optical lens. The spatial frequency spectrum of the output image is proportional to the optical power density distribution in the Fourier plane. A photorefractive crystal with small size can be used and hence an reduced amount of biased voltage is needed to obtain significant diffraction effect in the image plane. When the input image is an overlay of a signal and a noise pattern, theoretic model reveals that the induced diffraction in the Fourier plane may be preferably applied on the noise pattern. In order to illustrate the effect experimentally, a signal from a weakly illuminated object is coupled with an overwhelming noise pattern and then the hidden signal is successfully recovered using a SBN61 crystal with an applied voltage of 800 V in the Fourier plane. Such technology can be employed in encrypted spatial communication systems for security purposes.