scholarly journals Real-time estimation of PM2.5 concentrations at high spatial resolution in Busan by fusing observational data with chemical transport model outputs

2022 ◽  
Vol 13 (1) ◽  
pp. 101277
Author(s):  
Eunhwa Jang ◽  
Minkyeong Kim ◽  
Woogon Do ◽  
Geehyeong Park ◽  
Eunchul Yoo
Keyword(s):  
Real Time ◽  
Observational Data ◽  
Spatial Resolution ◽  
High Spatial Resolution ◽  
Transport Model ◽  
Time Estimation ◽  
Chemical Transport ◽  
Chemical Transport Model ◽  
Real Time Estimation

scholarly journals Application of a Fusion Method for Gas and Particle Air Pollutants between Observational Data and Chemical Transport Model Simulations Over the Contiguous United States for 2005–2014

2019 ◽  
Vol 16 (18) ◽  
pp. 3314
Author(s):  
Niru Senthilkumar ◽  
Mark Gilfether ◽  
Francesca Metcalf ◽  
Armistead G. Russell ◽  
James A. Mulholland ◽  
...  
Keyword(s):  
United States ◽  
Air Quality ◽  
Spatial Variation ◽  
Temporal Variation ◽  
Observational Data ◽  
Transport Model ◽  
Chemical Transport ◽  
Daily Basis ◽  
Quality Data ◽  
Chemical Transport Model

Accurate spatiotemporal air quality data are critical for use in assessment of regulatory effectiveness and for exposure assessment in health studies. A number of data fusion methods have been developed to combine observational data and chemical transport model (CTM) results. Our approach focuses on preserving the temporal variation provided by observational data while deriving the spatial variation from the community multiscale air quality (CMAQ) simulations, a type of CTM. Here we show the results of fusing regulatory monitoring observational data with 12 km resolution CTM simulation results for 12 pollutants (CO, NOx, NO2, SO2, O3, PM2.5, PM10, NO3−, NH4+, EC, OC, SO42−) over the contiguous United States on a daily basis for a period of ten years (2005–2014). An annual mean regression between the CTM simulations and observational data is used to estimate the average spatial fields, and spatial interpolation of observations normalized by predicted annual average is used to provide the daily variation. Results match the temporal variation well (R2 values ranging from 0.84–0.98 across pollutants) and the spatial variation less well (R2 values 0.42–0.94). Ten-fold cross validation shows normalized root mean square error values of 60% or less and spatiotemporal R2 values of 0.4 or more for all pollutants except SO2.

Method for Fusing Observational Data and Chemical Transport Model Simulations To Estimate Spatiotemporally Resolved Ambient Air Pollution

2016 ◽  
Vol 50 (7) ◽  
pp. 3695-3705 ◽  
Author(s):  
Mariel D. Friberg ◽  
Xinxin Zhai ◽  
Heather A. Holmes ◽  
Howard H. Chang ◽  
Matthew J. Strickland ◽  
...  
Keyword(s):  
Air Pollution ◽  
Observational Data ◽  
Transport Model ◽  
Chemical Transport ◽  
Ambient Air ◽  
Ambient Air Pollution ◽  
Chemical Transport Model ◽  
Model Simulations

scholarly journals Sensitivity of chemical transport model simulations to the duration of chemical and transport operators: a case study with GEOS-Chem v10-01

2015 ◽  
Vol 8 (11) ◽  
pp. 9589-9616
Author(s):  
S. Philip ◽  
R. V. Martin ◽  
C. A. Keller
Keyword(s):  
Spatial Resolution ◽  
Temporal Resolution ◽  
Transport Model ◽  
Chemical Transport ◽  
Chemical Transport Model ◽  
Transport Models ◽  
Simulation Accuracy ◽  
Chemical Transport Models ◽  
Order Of Magnitude ◽  
Simulation Error

Abstract. Chemical transport models involve considerable computational expense. Fine temporal resolution offers accuracy at the expense of computation time. Assessment is needed of the sensitivity of simulation accuracy to the duration of chemical and transport operators. We conduct a series of simulations with the GEOS-Chem chemical transport model at different temporal and spatial resolutions to examine the sensitivity of simulated atmospheric composition to temporal resolution. Subsequently, we compare the tracers simulated with operator durations from 10 to 60 min as typically used by global chemical transport models, and identify the timesteps that optimize both computational expense and simulation accuracy. We found that longer transport timesteps increase concentrations of emitted species such as nitrogen oxides and carbon monoxide since a more homogeneous distribution reduces loss through chemical reactions and dry deposition. The increased concentrations of ozone precursors increase ozone production at longer transport timesteps. Longer chemical timesteps decrease sulfate and ammonium but increase nitrate due to feedbacks with in-cloud sulfur dioxide oxidation and aerosol thermodynamics. The simulation duration decreases by an order of magnitude from fine (5 min) to coarse (60 min) temporal resolution. We assess the change in simulation accuracy with resolution by comparing the root mean square difference in ground-level concentrations of nitrogen oxides, ozone, carbon monoxide and secondary inorganic aerosols with a finer temporal or spatial resolution taken as truth. Simulation error for these species increases by more than a factor of 5 from the shortest (5 min) to longest (60 min) temporal resolution. Chemical timesteps twice that of the transport timestep offer more simulation accuracy per unit computation. However, simulation error from coarser spatial resolution generally exceeds that from longer timesteps; e.g. degrading from 2° × 2.5° to 4° × 5° increases error by an order of magnitude. We recommend prioritizing fine spatial resolution before considering different temporal resolutions in offline chemical transport models. We encourage the chemical transport model users to specify in publications the durations of operators due to their effects on simulation accuracy.

A machine for real-time estimation of the tribological characteristics of materials

2020 ◽  
Vol 86 (4) ◽  
pp. 61-65
Author(s):  
M. V. Abramchuk ◽  
R. V. Pechenko ◽  
K. A. Nuzhdin ◽  
V. M. Musalimov
Keyword(s):  
Real Time ◽  
Time Estimation ◽  
Tribological Characteristics ◽  
Continuous Processing ◽  
Friction Machine ◽  
Dynamic Friction Coefficient ◽  
Displacement Sensors ◽  
Frictional Interaction ◽  
Real Time Estimation ◽  
Automated Quality Control

A reciprocating friction machine Tribal-T intended for automated quality control of the rubbing surfaces of tribopairs is described. The distinctive feature of the machine consists in implementation of the forced relative motion due to the frictional interaction of the rubbing surfaces fixed on the drive and conjugate platforms. Continuous processing of the signals from displacement sensors is carried out under conditions of continuous recording of mutual displacements of loaded tribopairs using classical approaches of the theory of automatic control to identify the tribological characteristics. The machine provides consistent visual real time monitoring of the parameters. The MATLAB based computer technologies are actively used in data processing. The calculated tribological characteristics of materials, i.e., the dynamic friction coefficient, damping coefficient and measure of the surface roughness, are presented. The tests revealed that a Tribal-T reciprocating friction machine is effective for real-time study of the aforementioned tribological characteristics of materials and can be used for monitoring of the condition of tribo-nodes of machines and mechanisms.

Onboard Real-time Estimation of Mean Orbital Elements with Atmospheric Drag

2013 ◽  
Vol 39 (10) ◽  
pp. 1722
Author(s):  
Zhao-Wei SUN ◽  
Wei-Chao ZHONG ◽  
Shi-Jie ZHANG ◽  
Jian ZHANG
Keyword(s):  
Real Time ◽  
Time Estimation ◽  
Atmospheric Drag ◽  
Orbital Elements ◽  
Real Time Estimation
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