Diurnal variation of aerosol optical depth and PM_2.5 in South Korea: a synthesis from AERONET, satellite (GOCI), KORUS-AQ observation, and the WRF-Chem model

Spatial distribution of diurnal variations of aerosol properties in South Korea, both long term and short term, is studied by using 9 AERONET (AErosol RObotic NETwork) sites from 1999 to 2017 and an additional 10 sites during the KORUS-AQ (Korea–United States Air Quality) field campaign in May and June of 2016. The extent to which the WRF-Chem (Weather Research and Forecasting coupled with Chemistry) model and the GOCI (Geostationary Ocean Color Imager) satellite retrieval can describe these variations is also analyzed. On a daily average, aerosol optical depth (AOD) at 550&thinsp;nm is 0.386 and shows a diurnal variation of 20 to −30&thinsp;% in inland sites, which is larger than the AOD of 0.308 and diurnal variation of ±20&thinsp;% seen in coastal sites. For all the inland and coastal sites, AERONET, GOCI, and WRF-Chem, and observed PM2.5 (particulate matter with aerodynamic diameter less than 2.5&thinsp;µm) data generally show dual peaks for both AOD and PM2.5, one in the morning (often at  ∼ 08:00–10:00&thinsp;KST, Korea Standard Time, especially for PM2.5) and another in the early afternoon ( ∼ 14:00&thinsp;KST, albeit for PM2.5 this peak is smaller and sometimes insignificant). In contrast, Ångström exponent values in all sites are between 1.2 and 1.4 with the exception of the inland rural sites having smaller values near 1.0 during the early morning hours. All inland sites experience a pronounced increase in the Ångström exponent from morning to evening, reflecting an overall decrease in particle size in daytime. To statistically obtain the climatology of diurnal variation of AOD, a minimum requirement of  ∼ 2 years of observation is needed in coastal rural sites, twice as long as that required for the urban sites, which suggests that the diurnal variation of AOD in an urban setting is more distinct and persistent. While Korean GOCI satellite retrievals are able to consistently capture the diurnal variation of AOD (although it has a systematically low bias of 0.04 on average and up to 0.09 in later afternoon hours), WRF-Chem clearly has a deficiency in describing the relative change of peaks and variations between the morning and afternoon, suggesting further studies for the diurnal profile of emissions. Furthermore, the ratio between PM2.5 and AOD in WRF-Chem is persistently larger than the observed counterparts by 30&thinsp;%–50&thinsp;% in different sites, but spatially no consistent diurnal variation pattern of this ratio can be found. Overall, the relatively small diurnal variation of PM2.5 is in high contrast with large AOD diurnal variation, which suggests the large diurnal variation of AOD–PM2.5 relationships (with the PM2.5&thinsp;∕&thinsp;AOD ratio being largest in the early morning, decreasing around noon, and increasing in late afternoon) and, therefore, the need to use AOD from geostationary satellites to constrain either modeling or estimate of surface PM2.5 for air quality application.</p

The solar WIND and suprathermal ion composition investigation on the WIND spacecraft

The Solar Wind and Suprathermal Ion Composition Experiment (SMS) on WIND is designed to determine uniquely the elemental, isotopic, and ionic-charge composition of the solar wind, the temperatures and mean speeds of all major solar-wind ions, from H through Fe, at solar wind speeds ranging from 175 kms −1 (protons) to 1280 kms −1 (Fe +8 ), and the composition, charge states as well as the 3-dimensional distribution functions of suprathermal ions, including interstellar pick-up He + , of energies up to 230 keV/e. The experiment consists of three instruments with a common Data Processing Unit. Each of the three instruments uses electrostatic analysis followed by a time-of-flight and, as required, an energy measurement. The observations made by SMS will make valuable contributions to the ISTP objectives by providing information regarding the composition and energy distribution of matter entering the magnetosphere. In addition SMS results will have an impact on many areas of solar and heliospheric physics, in particular providing important and unique information on: (i) conditions and processes in the region of the corona where the solar wind is accelerated; (ii) the location of the source regions of the solar wind in the corona; (iii) coronal heating processes; (iv) the extent and causes of variations in the composition of the solar atmosphere; (v) plasma processes in the solar wind; (vi) the acceleration of particles in the solar wind; and (vii) the physics of the pick-up process of interstellar He as well as lunar particles in the solar wind, and the isotopic composition of interstellar helium.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/43776/1/11214_2004_Article_BF00751327.pd

Piezo is essential for amiloride-sensitive stretch-activated mechanotransduction in larval Drosophila dorsal bipolar dendritic sensory neurons

Date of Acceptance: 05/06/2015Peer reviewedPublisher PD

High Level Scheduling of Energy Optimal Trajectories

The reduction of energy consumption is today addressed with great effort in manufacturing industry. In this paper, we improve upon a previously presented method for robotic system scheduling. By applying dynamic programming to existing trajectories, we generate new energy optimal trajectories that follow the same path but in a different execution time frame. With this new method, it is possible to solve the optimization problem for a range of execution times for the individual operations, based on one simulation only. The minimum energy trajectories can then be used to derive a globally energy optimal schedule. A case study of a cell comprised of four six-link manipulators is presented, in which energy optimal dynamic time scaling is compared to linear time scaling. The results show that a significant decrease in energy consumption can be achieved for any given cycle time

State-labeled safety analysis of modular observers for opacity verification

Verification of opacity and anonymity for modular systems is in this paper formulated as safety analysis of local observers with state labels. A unified modeling strategy is presented based on a generalized synchronous composition, including both shared and non-shared state labels. The proposed modeling approach is shown to be flexible and general, making it possible to solve both local, global, and arbitrarily joint secret state problems simultaneously. A scalable modular n-floor, m-elevator security benchmark problem is also formulated and evaluated by two powerful safety analysis methods. It is shown that current-state opacity for non-trivial complex systems involving more than 1025 observer states can be verified in about one second

Hybrid Cost Automata Applied to Energy Optimization

For optimization of hybrid systems, the ordinary hybrid automatonis extended to include a local cost criterion in each location of thehybrid model. The extended model is called a hybrid cost automaton,where generally each local cost depends on the continuoustimestate trajectory in corresponding location, and each cost isupdated as long as its location is active. The total cost criterionis achieved by adding the individual costs from each active location,where the best route among alternative locations is selected inthe optimization. This model is used to achieve an energy optimalschedule for robot cells. Each robot operation including its energycost is then represented as a location, and a number of interactingrobots are modeled as a set of hybrid cost automata, one for eachindividual robot. The energy consumption for each robot operationis modelled and parameterized as a function of the operation’s executiontime, and the energy-optimal schedule is derived by solvinga mixed-integer nonlinear programming (MINLP) problem

Towards Energy Optimization using Trajectory Smoothing and Automatic Code Generation for Robotic Assembly

In automated industrial production, the efficiency of robotic motions directly affects both the final throughput and the energy consumption. By simulating and optimizing robot trajectories, cycle times and energy consumption can be lowered, or redundant robots can be detected. Here a polynomial basis function trajectory parametrization is presented, which enables direct export to executable robot code, and reduces the number of variables in the optimization problem. The algorithm finds time-optimal trajectories, while including collision avoidance and fulfilling joint, velocity and acceleration limitations. Applied torques are used as an approximation of the energy consumption to analyse the smooth trajectories, and successful tests show potential reductions of 10% for a standard industrial robot stud welding station