>Evaluation of dust activity and climate effects in North China

TOMS/AI data with nearly 20 years are utilized in the paper to evaluate dust activities in North China. Combined with simultaneous NCEP reanalysis climate data, climate effects on dust activities are assessed. The results showed that the whole North China suffers impact by dust aerosols, with three centers standing out in TOMS/AI spring average map that are western three basins, which are characterized by lower annual precipitation and elevation. Gobi deserts in Mongolia Plateau do not attain higher TOMS/AI value due to cloud contamination and relative higher elevation. Spring is the season with the highest TOMS dust aerosol index; within the western three basins, high dust aerosol index appears in both spring and summer, especially in Tarim Basin. Wind speed in spring and precipitation in previous rainy season play important roles in controlling dust activities, higher wind speed and less precipitation than the normal are in favor of dust activities in spring. Temperature in spring and previous winter also affect dust activity to a certain extent, but with contrary spatial distribution. Temperature in winter exert effect principally in west part, contrarily, temperature effect in spring is mainly shown in east part. Both of them have negative correlation with dust activity.

Interannual variations of dust activity in western Iran and their possible mechanisms

Through an analysis of station observations and reanalysis data,in this study,we investigate the variations of dust activity during 1979-2015 in western and southwestern Iran and their associated mechanisms.The dust day frequency(DDF)is used to identify dust activities.The results show larger interannual variabilities in the DDF in spring and summer,with standard deviations(σ)of 10%and 13%,respectively.Correlation analyses reveal that the interannual variability of DDF in western Iran is largely regulated by wind speed,precipitation and soil moisture in the region.The regional mean spring(March-May)DDF shows strong negative correlations with spring precipitation(correlation coefficient R=−0.5)and soil moisture(R=−0.6)over western to southwestern Iran,but strong positive correlations between the springtime DDF and surface winds can be found with the R reaching 0.4-0.6.Dust activity in the summer dry season(June-August)is mainly associated with surface winds over southwestern Iran,especially in regions near the Persian Gulf,where the R between the DDF and surface winds reaches 0.5.Meanwhile,the summer DDF also shows strong negative correlations(R<−0.4)with soil moisture of the top layer in the middle to southern part of the region.These results highlight the key roles of wind speed,precipitation and soil moisture in determining the interannual variation of dust activities in western and southwestern Iran.

Reduction of chromium oxides in stainless steel dust

The recovery of metal oxides from stainless steel dust using C（graphite）, SiFe, and Al as reductants was investigated under various conditions. The apparent distribution ratio of Cr（L Cr ′^m/s ） in the recovered metal and residual slag phases was defined as the major performance metric. The results show that the recovery ratio of metals increases as the ratio of CaO ：SiO2 by mass in the residual slag increases to 1.17. The residual content of metals in the slag decreases as the Al2O3 content of the slag is increased from approximately 8wt% to 10wt%. The recovery ratio of Cr increases with increasing L Cr ′^ m/s , and a linear relationship between L Cr ′^m/s and the activity coefficient ratio of CrO in the slag and the recovered metal phase is observed. The combination of C and SiFe or Al as the reducing agents reveals that Si is the more effective coreductant.

An Overview of Passive and Active Dust Detection Methods Using Satellite Measurements

In this paper,the methods to detect dust based on passive and active measurements from satellites have been summarized.These include the visible and infrared（VIR） method,thermal infrared（TIR） method,microwave polarized index（MPI） method,active lidar-based method,and combined lidar and infrared measurement（CLIM） method.The VIR method can identify dust during daytime.Using measurements at wavelengths of 8.5,11.0,and 12.0 fan,the TIR method can distinguish dust from other types of aerosols and cloud,and identify the occurrence of dust over bright surfaces and during night.Since neither the VIR nor the TIR method can penetrate ice clouds,they cannot detect dust beneath ice clouds.The MPI method,however,can identify about 85%of the dust beneath ice clouds.Meanwhile,the active lidar-based method,which uses the Cloud-Aerosol Lidar with Orthogonal Polarization（CALIOP） data and five-dimensional probability distribution functions,can provide very high-resolution vertical profiles of dust aerosols.Nonetheless,as the signals from dense dust and thin clouds are similar in the CALIOP measurements,the lidar-based method may fail to distinguish between them,especially over dust source regions.To address this issue,the CLIM method was developed,which takes the advantages of both TIR measurements（to discriminate between ice cloud and dense dust layers） and lidar measurements（to detect thin dust and water cloud layers）.The results obtained by using the new CLIM method show that the ratio of dust misclassification has been significantly reduced.Finally,a concept module for an integrated multi-satellites dust detection system was proposed to overcome some of the weaknesses inherent in the single-sensor dust detection.