scholarly journals In situ observations and model calculations of black carbon emission by aircraft at cruise altitude

1999 ◽  
Vol 104 (D18) ◽  
pp. 22171-22181 ◽  
Author(s):  
A. Petzold ◽  
A. Döpelheuer ◽  
C. A. Brock ◽  
F. Schröder
Keyword(s):  
Black Carbon ◽  
Carbon Emission ◽  
Model Calculations ◽  
In Situ Observations

scholarly journals In situ observations of black carbon in snow and the corresponding spectral surface albedo reduction

2015 ◽  
Vol 120 (4) ◽  
pp. 1476-1489 ◽  
Author(s):  
C. A. Pedersen ◽  
J.-C. Gallet ◽  
J. Ström ◽  
S. Gerland ◽  
S. R. Hudson ◽  
...  
Keyword(s):  
Black Carbon ◽  
Surface Albedo ◽  
In Situ Observations

scholarly journals Changes in black carbon emissions over Europe due to COVID-19 lockdowns

2020 ◽  
Author(s):  
Nikolaos Evangeliou ◽  
Stephen M. Platt ◽  
Sabine Eckhardt ◽  
Cathrine Lund Myhre ◽  
Paolo Laj ◽  
...  
Keyword(s):  
Black Carbon ◽  
Remote Sensing Data ◽  
Pollutant Emissions ◽  
World Health ◽  
Socioeconomic Impacts ◽  
Global Pandemic ◽  
The World ◽  
In Situ Observations ◽  
Health Organization

Abstract. Following the emergence of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) responsible for COVID-19 in December 2019 in Wuhan (China) and its spread to the rest of the world, the World Health Organization declared a global pandemic in March 2020. Without effective treatment in the initial pandemic phase, social distancing and mandatory quarantines were introduced as the only available preventative measure. Despite the socioeconomic impacts, air quality improved due to lower pollutant emissions. Here we investigate the effects of the COVID-19 lockdowns on ambient black carbon (BC), which affects climate and damages health, using in-situ observations from 17 European stations in a Bayesian inversion framework. BC emissions declined by 11 % in Europe (20 % in Italy, 32 % in Germany, 20 % in Spain) during lockdown compared to the same period in the previous five years. BC temporal variation in the countries enduring the most drastic restrictions showed the most distinct lockdown impacts. Increased particle light absorption in at the beginning of the lockdown, confirmed by assimilated satellite and remote sensing data, suggests residential combustion was the dominant BC source. Accordingly, in Central and Eastern Europe, which experienced lower than average temperatures, BC was elevated compared to the previous five years. Except for the comparison of BC emissions in the lockdown with the previous five years, an immediate decrease was also seen, as compared with the period before the lockdown, which averaged about 10 % over Europe. Such a decrease was not seen in the previous years, which also confirms an impact on BC emissions from COVID-19.

In situ observations of electromigration induced void behavior

1995 ◽  
Vol 53 ◽  
pp. 244-245
Author(s):  
T. Marieb ◽  
J. C. Bravman ◽  
P. Flinn ◽  
D. Gardner ◽  
M. Madden
Keyword(s):  
Electron Microscopy ◽  
Void Nucleation ◽  
Plan View ◽  
Transmission Electron ◽  
Nucleation Sites ◽  
Microelectronics Industry ◽  
In Situ Observations ◽  
Backscatter Electron Detector ◽  
Voltage Scanning

Electromigration and stress voiding have been active areas of research in the microelectronics industry for many years. While accelerated testing of these phenomena has been performed for the last 25 years[1-2], only recently has the introduction of high voltage scanning electron microscopy (HVSEM) made possible in situ testing of realistic, passivated, full thickness samples at high resolution.With a combination of in situ HVSEM and post-testing transmission electron microscopy (TEM) , electromigration void nucleation sites in both normal polycrystalline and near-bamboo pure Al were investigated. The effect of the microstructure of the lines on the void motion was also studied.The HVSEM used was a slightly modified JEOL 1200 EX II scanning TEM with a backscatter electron detector placed above the sample[3]. To observe electromigration in situ the sample was heated and the line had current supplied to it to accelerate the voiding process. After testing lines were prepared for TEM by employing the plan-view wedge technique [6].

scholarly journals In situ observations of coral spawning and spawn slick at Lankayan Island, Sabah, Malaysia

2021 ◽  
Vol 51 (1) ◽  
Author(s):  
Sze Hoon Gan ◽  
Zarinah Waheed ◽  
Fung Chen Chung ◽  
Davies Austin Spiji ◽  
Leony Sikim ◽  
...  
Keyword(s):  
Coral Spawning ◽  
In Situ Observations

scholarly journals Snow Depth Fusion Based on Machine Learning Methods for the Northern Hemisphere

2021 ◽  
Vol 13 (7) ◽  
pp. 1250
Author(s):  
Yanxing Hu ◽  
Tao Che ◽  
Liyun Dai ◽  
Lin Xiao
Keyword(s):  
Machine Learning ◽  
Northern Hemisphere ◽  
Snow Depth ◽  
Learning Algorithm ◽  
Random Forest Regression ◽  
Machine Learning Methods ◽  
Long Time ◽  
In Situ Observations ◽  
Input Variables

In this study, a machine learning algorithm was introduced to fuse gridded snow depth datasets. The input variables of the machine learning method included geolocation (latitude and longitude), topographic data (elevation), gridded snow depth datasets and in situ observations. A total of 29,565 in situ observations were used to train and optimize the machine learning algorithm. A total of five gridded snow depth datasets—Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E) snow depth, Global Snow Monitoring for Climate Research (GlobSnow) snow depth, Long time series of daily snow depth over the Northern Hemisphere (NHSD) snow depth, ERA-Interim snow depth and Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2) snow depth—were used as input variables. The first three snow depth datasets are retrieved from passive microwave brightness temperature or assimilation with in situ observations, while the last two are snow depth datasets obtained from meteorological reanalysis data with a land surface model and data assimilation system. Then, three machine learning methods, i.e., Artificial Neural Networks (ANN), Support Vector Regression (SVR), and Random Forest Regression (RFR), were used to produce a fused snow depth dataset from 2002 to 2004. The RFR model performed best and was thus used to produce a new snow depth product from the fusion of the five snow depth datasets and auxiliary data over the Northern Hemisphere from 2002 to 2011. The fused snow-depth product was verified at five well-known snow observation sites. The R2 of Sodankylä, Old Aspen, and Reynolds Mountains East were 0.88, 0.69, and 0.63, respectively. At the Swamp Angel Study Plot and Weissfluhjoch observation sites, which have an average snow depth exceeding 200 cm, the fused snow depth did not perform well. The spatial patterns of the average snow depth were analyzed seasonally, and the average snow depths of autumn, winter, and spring were 5.7, 25.8, and 21.5 cm, respectively. In the future, random forest regression will be used to produce a long time series of a fused snow depth dataset over the Northern Hemisphere or other specific regions.

scholarly journals Pelagic deep-sea fauna observed on video transects in the southern Norwegian Sea

Polar Biology ◽  
2021 ◽  
Author(s):  
Philipp Neitzel ◽  
Aino Hosia ◽  
Uwe Piatkowski ◽  
Henk-Jan Hoving
Keyword(s):  
First Record ◽  
Observation System ◽  
In Situ Observation ◽  
Norwegian Sea ◽  
Video Recordings ◽  
In Situ Observations ◽  
Abundance And Distribution ◽  
Oceanic Food Webs ◽  
Deep Sea Fauna

AbstractObservations of the diversity, distribution and abundance of pelagic fauna are absent for many ocean regions in the Atlantic, but baseline data are required to detect changes in communities as a result of climate change. Gelatinous fauna are increasingly recognized as vital players in oceanic food webs, but sampling these delicate organisms in nets is challenging. Underwater (in situ) observations have provided unprecedented insights into mesopelagic communities in particular for abundance and distribution of gelatinous fauna. In September 2018, we performed horizontal video transects (50–1200 m) using the pelagic in situ observation system during a research cruise in the southern Norwegian Sea. Annotation of the video recordings resulted in 12 abundant and 7 rare taxa. Chaetognaths, the trachymedusaAglantha digitaleand appendicularians were the three most abundant taxa. The high numbers of fishes and crustaceans in the upper 100 m was likely the result of vertical migration. Gelatinous zooplankton included ctenophores (lobate ctenophores,Beroespp.,Euplokamissp., and an undescribed cydippid) as well as calycophoran and physonect siphonophores. We discuss the distributions of these fauna, some of which represent the first record for the Norwegian Sea.

In situ observations of isothermal cuspidine crystallization in molten mould fluxes with varying basicity

2020 ◽  
pp. 1-6
Author(s):  
Jiangling Li ◽  
Feifei Lai ◽  
Mei Leng ◽  
Qingcai Liu ◽  
Jian Yang ◽  
...  
Keyword(s):  
In Situ Observations
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