The Use of Imitation Models at Developing and Introducing Information-Control Systems

Imitation models for computing the environmental water pollution level depending on the intensity of pollution sources created by the author over the years are presented. For this purpose, an additive model of a non-stationary random process is considered. For the modeling of its components, models that consider only dilution and self-purification processes are proposed for waste water and three-dimensional turbulent diffusion equations for river waters, and multidimensional Gaussian Markov series are proposed for modeling the random component. The purpose, the capabilities and the peculiarities of such imitation models are discussed taking into account the peculiarities of the water objects. The modular principle of creating imitation models is proposed to facilitate their development and use.

Performance of MODIS aerosol products at various timescales and in different pollution conditions over eastern Asia

High-quality aerosol optical depth(AOD)data derived from MODIS is widely used in studying spatiotemporal trends of fine particulate matter(PM2.5)concentrations in eastern Asia.However,the differences of MODIS-AOD(3/10 km DT;10 km DB)under four pollution situations(No-Po;Sl-Po;Mo-Po;Se-Po)are rarely considered.In this study,the MODIS-AOD and AODDifference spatial distributions from 2008 to 2017 are analyzed through annual/seasonal mean AOD maps generated at 0.1°×0.1°resolution.The MODIS-AOD performances are validated using AERONET AOD data for various pollution situations and aerosol types.Annual validations indicate that the 10-km DB algorithm provides the best performance,followed by 3-km DTand 10 km DT.The DB algorithm can provide spatially continuous AOD data for all seasons,whereas the DT algorithm often fails to yield valid data during winter.The validations under different pollution conditions illustrate that severe pollution significantly affects the validity of data obtained by the DB algorithm.However,the accuracy of DT-derived AOD data is robust against interference.Under the same pollution conditions,the correlation coefficient of the DB algorithm is smaller than that of the DT algorithm.The quantity of valid data in the DB product is higher than those in DT products for all pollution conditions,especially under Se-Po.

Influence of haze pollution on water-soluble chemical species in PM2.5 and size-resolved particles at an urban site during fall

To investigate the influence of haze on the chemical composition and formation processes of ambient aerosol particles,PM_（2.5） and size-segregated aerosol particles were collected daily during fall at an urban site of Gwangju,Korea.During the study period,the total concentration of secondary ionic species（SIS） contributed an average of 43.9% to the PM_（2.5） ,whereas the contribution of SIS to the PM_（2.5） during the haze period was 62.3%.The NO_3 and SO^（2-）_4 concentrations in PM_（2.5） during the haze period were highly elevated,being 13.4 and 5.0 times higher than those during non-haze period,respectively.The PM,NO^-_3,SO^（2-）_4,oxalate,water-soluble organic carbon（WSOC）,and humic-like substances（HULIS） had tri-modal size distributions peaks at 0.32,1.0,and 5.2 μm during the non-haze and haze periods.However,during the non-haze period they exhibited dominant size distributions at the condensation mode peaking at 0.32 μm,while on October 21 when the heaviest haze event occurred,they had predominant droplet mode size distributions peaking at 1.00 μm.Moreover,strong correlations of WSOC and HULIS with SO^（2-）_4,oxalate,and K＋at particle sizes of 〈 1.8 μm indicate that secondary processes and emissions from biomass burning could be responsible for WSOC and HULIS formations.It was found that the factors affecting haze formation could be the local stable synoptic conditions,including the weak surface winds and high surface pressures,the long-range transportation of haze from eastern China and upwind regions of the Korean peninsula,as well as the locally emitted and produced aerosol particles.