THERMAL SCIENCE

International Scientific Journal

Yi Zhang

,

Xiaoming Li

,

Hao Wang

,

Shuailin Wang

,

Kaiqiang Ren

,

Ding Sun

,

Tingyu Zhang

,

Xin Zhang

VERTICAL CONCENTRATION DISTRIBUTIONS OF ATMOSPHERIC PARTICULATES IN TYPICAL SEASONS OF WINTER AND SUMMER DURING WORKING AND NON-WORKING DAYS: A CASE STUDY OF HIGH-RISE BUILDINGS

ABSTRACT
It is important to understand the vertical distribution characteristics of outdoor particulates concentration in typical seasons of winter and summer when people’s living spaces are getting higher and higher above the ground. The different heights of floors (1st, 7th, 11th, 17th, and 27th) of a high-rise building in Xi’an at 8:00 a. m., 12:00 a. m., 3:00 p. m., 6:00 p. m., and 10:00 p. m., respectively, were tested and analyzed in this paper. The results showed that the concentrations on non-working days were much lower than that on working days at different times and on different floors, and the concentrations of particulates were relatively low in summer. The particulates reached the highest at 12:00 a. m. in summer, with the average concentrations of PM10, PM2.5, and PM1.0 were 37.3 μg/m3, 31.6 μg/m3, and 29.4 μg/m3. While reached the highest at 3:00 p. m. in winter, with the average concentrations of PM10, PM2.5, and PM1.0 were 82.4 μg/m3, 64.8 μg/m3, and 57.7 μg/m3. The distribution of atmospheric environment in Xi’an is mainly dominated by small particulates. The particle sizes of low floors are mainly range from 1.0 μm to 2.5 μm, and the high floors are less than 1.0 μm. With the increase of floors and time, PM1.0/PM2.5 and PM2.5/PM10 show a trend of first decreasing and then increasing on working days, while PM1.0/PM2.5 and PM2.5/PM10 show a trend of first increasing, then decreasing and next increasing on non-working days. In addition, outdoor meteorological parameters will also have a certain impact on particulates concentration distribution. It provides reference values for controlling the particulates concentration in high-rise buildings.
KEYWORDS
High rise buildings, winter and summer, working and non working days, particulates, vertical distribution
PAPER SUBMITTED: 2023-07-29
PAPER REVISED: 2023-12-20
PAPER ACCEPTED: 2023-12-27
PUBLISHED ONLINE: 2024-03-10
DOI REFERENCE: https://doi.org/10.2298/TSCI230729051Z
CITATION EXPORT: view in browser or download as text file
THERMAL SCIENCE YEAR 2024, VOLUME 28, ISSUE Issue 4, PAGES [3171 - 3182]
REFERENCES
  1. He, B., et al., Correction of Direction Reduction Factors of Extreme Wind Speed Considering the Ekman Spiral in The Wind Load Estimation of Super High-Rise Buildings With Heights of 400-800 m, The Struc­tural Design of Tall and Special Buildings, 32 (2023), e2004
  2. Xie, M., et al., Determination of Pressure Difference Coefficient of Shuttle Elevator Doors in Super High- Rise Buildings under Stack Effect, Building and Environment, 232 (2023), 110076
  3. Zhang, Y. T., et al., A Spectral-Velocity-Based Combination-Type Earthquake Intensity Measure for Su­per High-Rise Buildings, Bulletin of Earthquake Engineering, 16 (2018), Sept., pp. 643-677
  4. Zhang, X., et al., Comparison of the Application of Three Methods for the Determination of Outdoor PM2.5 Design Concentrations for Fresh Air Filtration Systems in China, International Journal of Envi­ronmental Research and Public Health, 19 (2022), 16537
  5. Song, H., et al., Concentration Characteristics and Correlations with Other Pollutants of Atmospheric Particulate Matter As Affected by Relevant Policies, International Journal of Environmental Research and Public Health, 20 (2023), 1051
  6. Brook, R. D., et al., Excess Global Blood Pressure Associated with Fine Particulate Matter Air Pollution Levels Exceeding World Health Organization Guidelines, Journal of the American Heart Association, 12 (2023), e029206
  7. Zhang, X., et al., Modifying the Fiber Structure and Filtration Performance of Polyester Materials Based on Two Different Preparation Methods, Langmuir, 39 (2023), 9, pp. 3502-3511
  8. Wei, T., et al., Operational Parameters Impact on Spatial and Temporal Distribution and Multifractal Characteristics of Particulate Matter Concentration under the Sink Effect, Chemical Engineering Science, 269 (2023), 118447
  9. Shen, Y. W., et al., Distribution Characteristics and Health Risk Assessment of Antimony in Atmo­spheric Particulates in a Northern City of China, Chemical Research in Chinese Universities, 39 (2023), May, pp. 465-471
  10. Mi, K., et al., Spatiotemporal Characteristics of PM2.5 and Its Associated Gas Pollutants, A Case in Chi­na, Sustainable Cities and Society, 45 (2019), Feb., pp. 287-295
  11. Zhang, X., et al., Variation of Particulate Matter and Its Correlation with Other Air Pollutants in Xi'an, China, Polish Journal of Environmental Studies, 30 (2021), 4, pp. 3357-3364
  12. Zhang, X., et al., Spatiotemporal Distribution of PM2.5 and Its Correlation with other Air Pollutants in Winter during 2016-2018 in Xi'an, China, Polish Journal of Environmental Studies, 30 (2021), 2, pp. 1457-1464
  13. Tian, Y. L., et al., Characteristics of Atmospheric Pollution and the Impacts of Environmental Manage­ment over a Megacity, northwestern China, Urban Climate, 42 (2022), 101114
  14. Zhang, X., et al., Research on Outdoor Design PM2.5 Concentration for Fresh Air Filtration Systems Based on Mathematical Inductions, Journal of Building Engineering, 34 (2021), 101883
  15. Lancia, A., et al., Aerobiological Monitoring in an Indoor Occupational Setting Using a Real-Time Bio­aerosol Sampler, Atmosphere, 14 (2023), 118
  16. Sun, Y. W., et al., Atmospheric Environment Monitoring Technology and Equipment in China: A Review and Outlook, Journal of Environmental Sciences, 123 (2023), Jan., pp. 41-53
  17. Ge, X. R., et al., Impact of Interannual Weather Variation on Ammonia Emissions and Concentrations in Germany, Agricultural and Forest Meteorology, 334 (2023), 109432
  18. Yang, M., et al., Geo-Environmental Factors'Influence on the Prevalence and Distribution of Dental Flu­orosis: Evidence from Dali County, Northwest China, Sustainability, 15 (2023), 1871
  19. Zhou, F. R., et al., Estimating Spatio-Temporal Variability of Aerosol Pollution in Yunnan Province, Chi­na, Atmospheric Pollution Research, 13 (2022), 101450
  20. Zhang, X., et al., Vertical Distribution Characteristics of Outdoor Particles Concentrations in High-Rise Buildings, Polish Journal of Environmental Studies, 30 (2021), 2, pp. 1913-1922
  21. Niu, B. W., et al., Vertical Distribution Characteristics of Outdoor Particulate Matter Concentration in High-Rise Buildings during Working Days and Non-Working Days, Proceedings, E3S Web of Confer­ences, ROOMVENT 2022, Stockholm, Denmark, 2022, Vol. 356, p. 04033
  22. ***, GB/T18883-2002, Indoor air quality standard. China Environmental Science Press, 2002
  23. ***, GB3095-2012, Ambient air quality standards. China Environmental Science Press, 2012
  24. Liu, B. M., et al., The Relationship between Atmospheric Boundary-Layer and Temperature Inversion Layer and Their Aerosol Capture Capabilities, Atmospheric Research, 271 (2022), 106121
  25. Wang, J., et al., Study on the Spatial and Temporal Distribution Characteristics and Influencing Factors of Particulate Matter Pollution in Coal Production Cities in China, International Journal of Environmental Research and Public Health, 19 (2022), 3228
  26. Nie, Y., et al., Clean and Low-Carbon Heating in the Building Sector of China: 10-Year Development Review and Policy Implications, Energy Policy, 179 (2023), 113659
  27. Sun, J. S., et al., Optimizing China's Energy Consumption Structure under Energy and Carbon Con­straints, Structural Change and Economic Dynamics, 47 (2018), Dec., pp. 57-72
  28. Šarić, A., et al., The Role of Intersection Geometry in Urban Air Pollution Management, Sustainability, 15 (2023), 5234
  29. Wu, Z. T., et al., Attributable Risk And Economic Cost of Hospital Admissions for Mental Disorders Due to PM2.5 in Beijing, Science of the Total Environment, 718 (2020), 137274
  30. Leao, M. L. P., et al., Effect of Particulate Matter (PM2.5 and PM10) on Health Indicators: Climate Change Scenarios in a Brazilian Metropolis, Environmental Geochemistry and Health, 45 (2023), July, pp. 2229-2240
  31. Katow, H., Ishikawa, K. L., Eigenmode Analysis of The Multiple Temperature Model: Spectrum Proper­ties, Hierarchical Structures, and Temperature Inversion, Applied Physics A-Materials Science and Pro­cessing, 129 (2023), 165
  32. Zhang, X., et al., Establishment of Air Fiber Filtration Model Based on Fractal Theory and Analysis of Filtration Performances, Materials Today Communications, 34 (2023), 105301
  33. Xu, R., et al., Extreme Temperature Events, Fine Particulate Matter, and Myocardial Infarction Mortality, Circulation, 148 (2023), 4, pp. 312-323
  34. Strouhal, J., et al., The CFD Modelling of an Initial Powdery Layer on Cooled Tubular Surfaces, Heat and Mass Transfer, 60 (2023), June, pp. 807-815
  35. Dai, H. B., et al., Spatio-Temporal Characteristics of PM2.5 Concentrations in China Based on Multiple Sources of Data and LUR-GBM during 2016-2021, International Journal of Environmental Research and Public Health, 19 (2022), 6292
  36. Spiechowicz, J., et al., Diffusion Coefficient of a Brownian Particle in Equilibrium and Non-Equilibrium: Einstein Model and Beyond, Entropy, 25 (2023), 42
  37. Yang, B., et al., Effects of Low‐Level Jets on Near‐Surface Turbulence and Wind Direction Changes in the Nocturnal Boundary-layer, Journal of Geophysical Research: Atmospheres, 128 (2023), e2022JD037657
PDF VERSION [DOWNLOAD]
Vertical concentration distributions of atmospheric particulates in typical seasons of winter and summer during working and non-working days: A case study of high-rise buildings

© 2024 Society of Thermal Engineers of Serbia. Published by the Vinča Institute of Nuclear Sciences, National Institute of the Republic of Serbia, Belgrade, Serbia. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International licence