Fabrication of a multifaceted mapping mirror using two-photon polymerization for a snapshot image mapping spectrometer

A design and fabrication technique for making high-precision and large-format multifaceted mapping mirrors is presented. The method is based on two-photon polymerization, which allows more flexibility in the mapping mirror design. The mirror fabricated in this paper consists of 36 2D tilted square pixels, instead of the continuous facet design used in diamond cutting. The paper presents a detailed discussion of the fabrication parameters and optimization process, with particular emphasis on the optimization of stitching defects by compensating for the overall tilt angle and reducing the printing field of view. The fabricated mirrors were coated with a thin layer of aluminum (93 nm) using sputter coating to enhance the reflection rate over the target wave range. The mapping mirror was characterized using a white light interferometer and a scanning electron microscope, which demonstrates its optical quality surface (with a surface roughness of 12 nm) and high-precision tilt angles (with an average of 2.03% deviation). Finally, the incorporation of one of the 3D printed mapping mirrors into an image mapping spectrometer prototype allowed for the acquisition of high-quality images of the USAF resolution target and bovine pulmonary artery endothelial cells stained with three fluorescent dyes, demonstrating the potential of this technology for practical applications.

Comparison of PM2.5 in Seoul, Korea Estimated from the Various Ground-Based and Satellite AOD

Based on multiple linear regression (MLR) models, we estimated the PM2.5 at Seoul using a number of aerosol optical depth (AOD) values obtained from ground-based and satellite remote sensing observations. To construct the MLR model, we consider various parameters related to the ambient meteorology and air quality. In general, all AOD values resulted in the high quality of PM2.5 estimation through the MLR method: mostly correlation coefficients >~0.8. Among various polar-orbit satellite AODs, AOD values from the MODIS measurement contribute to better PM2.5 estimation. We also found that the quality of estimated PM2.5 shows some seasonal variation; the estimated PM2.5 values consistently have the highest correlation with in situ PM2.5 in autumn, but are not well established in winter, probably due to the difficulty of AOD retrieval in the winter condition. MLR modeling using spectral AOD values from the ground-based measurements revealed that the accuracy of PM2.5 estimation does not depend on the selected wavelength. Although all AOD values used in this study resulted in a reasonable accuracy range of PM2.5 estimation, our analyses of the difference in estimated PM2.5 reveal the importance of utilizing the proper AOD for the best quality of PM2.5 estimation.

Comparison of INSAT-3D retrieved total column ozone with ground-based and AIRS observations over India

Ozone plays an important role in the thermal structure and chemical composition of the atmosphere. The present study compares the temporal and spatial distributions of Total Column Ozone (TCO) over the Indian sub-continent retrieved from a geostationary Indian National Satellite (INSAT-3D) and Atmospheric Infrared Sounder (AIRS). The INSAT-3D TCO values are also evaluated against the Dobson spectrophotometer observations at two locations. The inter-comparison results reveal a good correlation of 0.8, the bias of -5 DU, and Root Mean Square Error (RMSE) of 15 DU approximately between the TCO retrieved from INSAT-3D and AIRS. The lowest RMSE and highest correlation coefficient were found in the pre-monsoon season. The INSAT-3D and AIRS show reasonable agreement with the RMSE varying between 10 and 30 DU. On the other hand, evaluation of the INSAT-3D TCO with the ground-based observations from Dobson spectrophotometers located at New Delhi and Varanasi showed fair agreement with a maximum monthly mean correlation coefficient of 0.68 and 0.76, respectively, and RMSE varying from 11 to 16 DU for both the stations. The seasonal distribution of TCO and its variation over the Indian region has also been studied using INSAT-3D and AIRS data. The analysis exhibits strong seasonal variations, with higher values in pre-monsoon season and minimum values in winter season. The noticeable seasonal variability of TCO can be attributed to complex combination of photochemical and dynamical processes in the troposphere and stratosphere. The main objectives of the study are to compare the INSAT-3D TCO with two independent ground-based Dobson spectrophotometer observations and Atmospheric Infrared Sounder (AIRS) aboard NASA's Aqua satellite.

Validation of OMI-DOAS total ozone column amounts against ground-based measurements at an African equatorial belt site

The total ozone column amount (TOCA) values from the Ozone Monitoring Instrument (OMI) derived from OMI/Aura ozone (O3) differential optical absorption spectroscopy (DOAS) V003 (OMDOAO3) have been validated against the ground-based TOCA values derived from Dobson and the Norwegian Institute for Air Research UV measurements in Kampala (0.31º N, 32.58º E, 1200 m), Uganda, for the period between 2005 and 2018. Under all-sky conditions, the OMI retrieval algorithm was found to underestimate the TOCA values with mean bias (MnB), root mean square error (RMSE), and correlation coefficient (r) values ranging from about -3.4% to -1.7%, 2.4% to 4.9%, and 0.73 to 0.90, respectively. When only days with a radiation modification factor greater than or equal to 65% were considered, the MnB, RMSE, and r values between TOCA values derived from ground-based and OMI measurements improved, and they ranged from -2.5% to -1.3%, 1.4% to 3.8%, and 0.8 to 0.91, respectively. A good agreement was found between TOCA values derived from Dobson measurements and those derived from OMI satellite measurements with MnB, RMSE, and r values of about -1.8%, 1.4%, and 0.91, respectively. This was due to the fact that Dobson measurements were taken only when the sky was perceived clear. The underestimation of TOCA values by the OMI retrieval algorithm was found to be due mainly to clouds and aerosols.

Remote sensing of particulate pollution from space: have we reached the promised land?

The recent literature on satellite remote sensing of air quality is reviewed. 2009 is the 50th anniversary of the first satellite atmospheric observations. For the first 40 of those years, atmospheric composition measurements, meteorology, and atmospheric structure and dynamics dominated the missions launched. Since 1995, 42 instruments relevant to air quality measurements have been put into orbit. Trace gases such as ozone, nitric oxide, nitrogen dioxide, water, oxygen/tetraoxygen, bromine oxide, sulfur dioxide, formaldehyde, glyoxal, chlorine dioxide, chlorine monoxide, and nitrate radical have been measured in the stratosphere and troposphere in column measurements. Aerosol optical depth (AOD) is a focus of this review and a significant body of literature exists that shows that ground-level fine particulate matter (PM2.5) can be estimated from columnar AOD. Precision of the measurement of AOD is +/-20% and the prediction of PM2.5 from AOD is order +/-30% in the most careful studies. The air quality needs that can use such predictions are examined. Satellite measurements are important to event detection, transport and model prediction, and emission estimation. It is suggested that ground-based measurements, models, and satellite measurements should be viewed as a system, each component of which is necessary to better understand air quality.