A novel process integrating vacuum distillation with atmospheric chlorination reaction for flexible production of tetrachloroethane and pentachloroethane

In this paper, we developed a novel process integrating vacuum distillation with atmospheric chlorination reaction(VD-ACR) to realize the flexible production of tetrachloroethane(TeCA) and pentachloroethane(PCA)from 1,2-dichloroethane(DCA). During the simulation, the distillation column and reactors were operated for separation and chlorination respectively under variable pressures and temperatures. It is interesting to note that VD-ACR processes producing pure TeCA or PCA can exhibit the similar configuration parameters after optimization, which enables the flexible production of TeCA and PCA with different molar ratios via changing operating parameters. The molar ratio of TeC A/PCA can be fine-tuned within the range of 0.9:0.1-0.1:0.9 through adjusting the amount of chlorine pumped into side reactors, giving rise to the increase of the heat duty of reboiler by five times. A pilot-scale experiment was then operated based-upon this VD-ACR process and the result matched well with the simulation. Therefore, the VD-ACR model presented in this study will be beneficial for the industrial-scale flexible production of TeCA and PCA from DCA.

Pre-Processing,Quality Assurance,and Use of Global Atmospheric Motion Vector Observations in CRA

Assimilation of atmospheric motion vectors(AMVs)is important in the initialization of the atmospheric state in numerical weather prediction models,especially over oceans and at high latitudes where conventional data are sparse.This paper presents a detailed description of the pre-processing,quality assurance,and use of global AMVs in China’s first generation of the 40-yr(1979-2018)CRA global atmospheric reanalysis product.A new AMV archive is integrated from near real-time operational Global Telecommunication System data and reprocessed AMV datasets released or produced mainly during 2014-2016 according to a priority principle.To avoid the misuse of data with systematic quality problems,the observations of all 18 types of AMVs from 54 satellites are pre-evaluated over the whole time series.The pre-evaluation system developed by the CRA team is based on the NCEP Gridpoint Statistical Interpolation(GSI)three-dimensional variational assimilation system and the ERA-Interim reanalysis product.The AMVs in the new AMV archive are denser than the AMVs prepared for the Climate Forecast System Reanalysis product,the bias and root-mean-square values are smaller,and the time series are steadier.The new AMV archive is assimilated in the CRA product based on the NCEP GSI assimilation procedure and quality control configuration with reference to the pre-evaluation results.This is the first time that the reprocessed AMVs from Fengyun-2 satellites from June 2005 to July 2017 are assimilated in a reanalysis product.The assimilation features inspire confidence in the accuracy and stability of these data.The mean root-mean-square values of the observation minus analysis infrared,water vapor,and visible AMV were 1.5-3.4,2.7-3.6,and 1.3-2.1 m s-1,respectively.This experience of integrating,pre-evaluating,and assimilating AMV observations is valuable for the next generation of reanalysis products.

Integration, Quality Assurance, and Usage of Global Aircraft Observations in CRA

This paper presents a detailed description of integration, quality assurance procedure, and usage of global aircraft observations for China's first generation global atmospheric reanalysis(CRA) product(1979–2018). An integration method named "classified integration" is developed. Aircraft observations from nine different sources are integrated into the Integrated Global Meteorological Observation Archive from Aircraft(IGMOAA), a new dataset from the National Meteorological Information Center(NMIC) of the China Meteorological Administration(CMA). IGMOAA consists of global aircraft temperature, wind, and humidity data from the surface to 100 h Pa, extending from 1973 to the present. Compared with observations assimilated in the Climate Forecast System Reanalysis(CFSR) of NCEP,the observation number of IGMOAA increased by 12.9% between 2010 and 2014, mainly as a result of adding more Chinese Aircraft Meteorological Data Relay(AMDAR) data. Complex quality control procedures for aircraft observations of NCEP are applied to detect data errors. Observations are compared with ERA-Interim reanalysis from 1979 to 2018 to investigate data quality of different types and aircraft, and subsequently to develop the blacklists for CRA. IGMOAA data have been assimilated in CRA in 2018 and are real-time updated at the CMA Data-as-a-Service(CMADaa S) platform. For CRA, the fits to observations improve over time. From 1994 to 2018, root-meansquare error(RMSE) of observations relative to CRA background decreases from 1.8 to 1.0℃ for temperature above 300 h Pa, and from 4.5 to 3 m s^(-1) for zonal wind. The RMSE for humidity appears to exhibit an apparent seasonal variation with larger errors in summer and smaller ones in winter.