Modification of AQI as an Effective Representation of Air Quality by Considering Weighting Factors

Li Wei Lai; Wan Li Cheng

doi:doi:10.11648/j.ajese.20200401.12

| Peer-Reviewed

Modification of AQI as an Effective Representation of Air Quality by Considering Weighting Factors

Li Wei Lai, Wan Li Cheng

Published in American Journal of Environmental Science and Engineering (Volume 4, Issue 1)

Received: 18 April 2020 Accepted: 9 May 2020 Published: 28 May 2020

Views: Downloads:

Download PDF

Share This Article

Twitter
Linked In
Facebook

Abstract

Controversy persists because residents in regions where air quality is poor are always dissatisfied with the presentation of the air quality index (AQI). To make management policies acceptable, it needs to be determined whether adding the various weighting factors can make the AQI more reasonable and practical. The authors selected three indices i.e. AQI, revised air quality index (RAQI), and the air-dispersion AQI (ADRAQI) to compare their results in different atmospheric situations and to determine whether the AQI was made more reliable by adding various weighting factors such as multi-air pollutants and air dispersion derived from the mean function and an entropy function. Results show in comparison to AQI, the RAQI and ADRAQI have greater values in the multi-air pollutant and poor dispersion events, leading to a great difference between single air pollutant and multi-air pollutant events. The eclipsed phenomena in the AQI for the means of diseases related to air pollution such as acute atopic conjunctivitis, other chronic allergic conjunctivitis, other atopic dermatitis and related conditions, contact dermatitis and other eczema, and unspecified causes clearly appear. The findings suggest that the representation of AQI can be modified by considering the weighting factors of multiple air pollutants along with air dispersion; these can easily be applied to similar regions elsewhere.

Published in	American Journal of Environmental Science and Engineering (Volume 4, Issue 1)
DOI	10.11648/j.ajese.20200401.12
Page(s)	7-12
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Air Quality Index, Air-dispersion, Multi-air Pollutant, Weighting Actors, Diseases Related to Air Pollution

References

[1]	United States Environmental Protection Agency (US EPA). Air quality reporting. Federal Register, 1999, 64 (149): 42530–42549.
[2]	Taiwan Environmental Protection Administration (Taiwan EPA). Air Quality Annual Report of R. O. C. (Taiwan). Taipei, R. O. C.: Taiwan EPA, 2001.
[3]	Taiwan Environmental Protection Administration (Taiwan EPA). Air Quality Annual Report of R. O. C. (Taiwan). Taipei, R. O. C.: Taiwan EPA, 2016.
[4]	Wark RM, Wong KFV. Methodologies for incorporation of synergistic effects in the calculation of the Pollutant Standards Index. International Journal of Environment and Pollution, 1999, 12 (1): 81–90. https://doi.org/10.1504/IJEP.1999.002285.
[5]	United States Environmental Protection Agency (US EPA). Technical assistance document for the reporting of daily air quality-the air quality index (AQI). EPA454/B-13-001, 2013.
[6]	Kim HH, Lee CS, Jeon JM, et al. Analysis of the association between air pollution and allergic diseases exposure from nearby sources of ambient air pollution within elementary school zones in four Korean cities. Environmental Science and Pollution Research, 2013, 20 (7): 4831–4846. doi: 10.1007/s11356-012-1358-2.
[7]	Lee C, Kim H, Lim Y, et al. Evaluation of the relationship between allergic diseases in school children at Seoul's roadside elementary schools and air pollution. Atmospheric Pollution Research, 2015, 6 (6): 1004–1012. https://doi.org/10.1016/j.apr.2015.05.006.
[8]	Hong J, Zhong T, Li H, et al. Ambient air pollution, weather changes, and outpatient visits for allergic conjunctivitis: A retrospective registry study. Scientific Reports, 2016, 6: 23858. doi: 10.1038/srep23858.
[9]	Mimura T, Ichinose T, Yamagami S, et al. Airborne particulate matter (PM_2.5) and the prevalence of allergic conjunctivitis in Japan. Science of the Total Environment, 2014, 487: 493–499. doi: 10.1016/j.scitotenv.2014.04.057.
[10]	Szyszkowicz M, Kousha T, Castner J. Air pollution and emergency department visits for conjunctivitis: A case-crossover study. International Journal of Occupational Medicine and Environmental Health, 2016, 29 (3): 381–393. doi: 10.13075/ijomeh.1896.00442.
[11]	Cheng WL, Kuo YC, Lin PL, et al. Revised air quality index derived from an entropy function. Atmospheric Environment, 2004, 38 (3): 383–391. https://doi.org/10.1016/j.atmosenv.2003.10.006.
[12]	Cheng WL, Chen YS, Zhang J, et al. Comparison of the revised air quality index with the PSI and AQI indices. Science of the Total Environment, 2007, 382 (2–3): 191–8. doi: 10.1016/j.scitotenv.2007.04.036.
[13]	Taiwan Central Weather Bureau (Taiwan CWB). The introduction of characteristics of climate in Taiwan; 2015. Available from: http://www.cwb.gov.tw/V7/climate/climate_info/statistics/statistics_1_1.html.
[14]	Du C, Liu S, Yu X, et al. Urban boundary layer height characteristics and relationship with particulate matter mass concentrations in Xi’an, Central China Aerosol and Air Quality Research, 2013, 13: 1598–1607. doi: 10.4209/aaqr.2012.10.0274.
[15]	Swamee PK, Tyagi A. Formation of an air pollution index. Journal of the Air & Waste Management Association, 1999, 49: 88–91. doi: 10.1080/10473289.1999.10463776.
[16]	Pandolfi M, Tobias A, Alastuey A, et al. Effect of atmospheric mixing layer depth variations on urban air quality and daily mortality during Saharan dust outbreaks. Science of the Total Environment, 2014, 494: 283–289. doi: 10.1016/j.scitotenv.2014.07.004.
[17]	Prakash D, Payra S, Verma S, et al. Aerosol particle behavior during dust storm and Diwali over an urban location in north western India. Natural Hazards, 2013, 69 (3): 1767–1779. https://doi.org/10.1007/s11069-013-0780-1.
[18]	Holzworth GC. Mixing depth, wind speeds and air pollution potential for selected locations in the United States. Journal of Applied Meteorology and Climatology, 1967, 6: 1039–1044. https://doi.org/10.1175/1520-0450(1967)006<1039:MDWSAA>2.0.CO;2.
[19]	Mayer H. Air pollution in cities. Atmospheric Environment, 1999, 33: 4029–4037. http://dx.doi.org/10.1016/S1352-2310(99)00144-2.

Cite This Article

Plain Text BibTeX RIS

APA Style

Li Wei Lai, Wan Li Cheng. (2020). Modification of AQI as an Effective Representation of Air Quality by Considering Weighting Factors. American Journal of Environmental Science and Engineering, 4(1), 7-12. https://doi.org/10.11648/j.ajese.20200401.12

Copy | Download

ACS Style

Li Wei Lai; Wan Li Cheng. Modification of AQI as an Effective Representation of Air Quality by Considering Weighting Factors. Am. J. Environ. Sci. Eng. 2020, 4(1), 7-12. doi: 10.11648/j.ajese.20200401.12

Copy | Download

AMA Style

Li Wei Lai, Wan Li Cheng. Modification of AQI as an Effective Representation of Air Quality by Considering Weighting Factors. Am J Environ Sci Eng. 2020;4(1):7-12. doi: 10.11648/j.ajese.20200401.12

Copy | Download

@article{10.11648/j.ajese.20200401.12,
  author = {Li Wei Lai and Wan Li Cheng},
  title = {Modification of AQI as an Effective Representation of Air Quality by Considering Weighting Factors},
  journal = {American Journal of Environmental Science and Engineering},
  volume = {4},
  number = {1},
  pages = {7-12},
  doi = {10.11648/j.ajese.20200401.12},
  url = {https://doi.org/10.11648/j.ajese.20200401.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajese.20200401.12},
  abstract = {Controversy persists because residents in regions where air quality is poor are always dissatisfied with the presentation of the air quality index (AQI). To make management policies acceptable, it needs to be determined whether adding the various weighting factors can make the AQI more reasonable and practical. The authors selected three indices i.e. AQI, revised air quality index (RAQI), and the air-dispersion AQI (ADRAQI) to compare their results in different atmospheric situations and to determine whether the AQI was made more reliable by adding various weighting factors such as multi-air pollutants and air dispersion derived from the mean function and an entropy function. Results show in comparison to AQI, the RAQI and ADRAQI have greater values in the multi-air pollutant and poor dispersion events, leading to a great difference between single air pollutant and multi-air pollutant events. The eclipsed phenomena in the AQI for the means of diseases related to air pollution such as acute atopic conjunctivitis, other chronic allergic conjunctivitis, other atopic dermatitis and related conditions, contact dermatitis and other eczema, and unspecified causes clearly appear. The findings suggest that the representation of AQI can be modified by considering the weighting factors of multiple air pollutants along with air dispersion; these can easily be applied to similar regions elsewhere.},
 year = {2020}
}

Copy | Download

TY  - JOUR
T1  - Modification of AQI as an Effective Representation of Air Quality by Considering Weighting Factors
AU  - Li Wei Lai
AU  - Wan Li Cheng
Y1  - 2020/05/28
PY  - 2020
N1  - https://doi.org/10.11648/j.ajese.20200401.12
DO  - 10.11648/j.ajese.20200401.12
T2  - American Journal of Environmental Science and Engineering
JF  - American Journal of Environmental Science and Engineering
JO  - American Journal of Environmental Science and Engineering
SP  - 7
EP  - 12
PB  - Science Publishing Group
SN  - 2578-7993
UR  - https://doi.org/10.11648/j.ajese.20200401.12
AB  - Controversy persists because residents in regions where air quality is poor are always dissatisfied with the presentation of the air quality index (AQI). To make management policies acceptable, it needs to be determined whether adding the various weighting factors can make the AQI more reasonable and practical. The authors selected three indices i.e. AQI, revised air quality index (RAQI), and the air-dispersion AQI (ADRAQI) to compare their results in different atmospheric situations and to determine whether the AQI was made more reliable by adding various weighting factors such as multi-air pollutants and air dispersion derived from the mean function and an entropy function. Results show in comparison to AQI, the RAQI and ADRAQI have greater values in the multi-air pollutant and poor dispersion events, leading to a great difference between single air pollutant and multi-air pollutant events. The eclipsed phenomena in the AQI for the means of diseases related to air pollution such as acute atopic conjunctivitis, other chronic allergic conjunctivitis, other atopic dermatitis and related conditions, contact dermatitis and other eczema, and unspecified causes clearly appear. The findings suggest that the representation of AQI can be modified by considering the weighting factors of multiple air pollutants along with air dispersion; these can easily be applied to similar regions elsewhere.
VL  - 4
IS  - 1
ER  -

Copy | Download

Author Information

Li Wei Lai

Centre for General Education, National Taipei University of Business, Taipei, Taiwan, Republic of China
Wan Li Cheng

Green Science Technology Co. Ltd., Taichung, Taiwan, Republic of China

Download PDF

Sections

Plain Text BibTeX RIS

APA Style

Li Wei Lai, Wan Li Cheng. (2020). Modification of AQI as an Effective Representation of Air Quality by Considering Weighting Factors. American Journal of Environmental Science and Engineering, 4(1), 7-12. https://doi.org/10.11648/j.ajese.20200401.12

Copy | Download

ACS Style

Li Wei Lai; Wan Li Cheng. Modification of AQI as an Effective Representation of Air Quality by Considering Weighting Factors. Am. J. Environ. Sci. Eng. 2020, 4(1), 7-12. doi: 10.11648/j.ajese.20200401.12

Copy | Download

AMA Style

Li Wei Lai, Wan Li Cheng. Modification of AQI as an Effective Representation of Air Quality by Considering Weighting Factors. Am J Environ Sci Eng. 2020;4(1):7-12. doi: 10.11648/j.ajese.20200401.12

Copy | Download

@article{10.11648/j.ajese.20200401.12,
  author = {Li Wei Lai and Wan Li Cheng},
  title = {Modification of AQI as an Effective Representation of Air Quality by Considering Weighting Factors},
  journal = {American Journal of Environmental Science and Engineering},
  volume = {4},
  number = {1},
  pages = {7-12},
  doi = {10.11648/j.ajese.20200401.12},
  url = {https://doi.org/10.11648/j.ajese.20200401.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajese.20200401.12},
  abstract = {Controversy persists because residents in regions where air quality is poor are always dissatisfied with the presentation of the air quality index (AQI). To make management policies acceptable, it needs to be determined whether adding the various weighting factors can make the AQI more reasonable and practical. The authors selected three indices i.e. AQI, revised air quality index (RAQI), and the air-dispersion AQI (ADRAQI) to compare their results in different atmospheric situations and to determine whether the AQI was made more reliable by adding various weighting factors such as multi-air pollutants and air dispersion derived from the mean function and an entropy function. Results show in comparison to AQI, the RAQI and ADRAQI have greater values in the multi-air pollutant and poor dispersion events, leading to a great difference between single air pollutant and multi-air pollutant events. The eclipsed phenomena in the AQI for the means of diseases related to air pollution such as acute atopic conjunctivitis, other chronic allergic conjunctivitis, other atopic dermatitis and related conditions, contact dermatitis and other eczema, and unspecified causes clearly appear. The findings suggest that the representation of AQI can be modified by considering the weighting factors of multiple air pollutants along with air dispersion; these can easily be applied to similar regions elsewhere.},
 year = {2020}
}

Copy | Download

TY  - JOUR
T1  - Modification of AQI as an Effective Representation of Air Quality by Considering Weighting Factors
AU  - Li Wei Lai
AU  - Wan Li Cheng
Y1  - 2020/05/28
PY  - 2020
N1  - https://doi.org/10.11648/j.ajese.20200401.12
DO  - 10.11648/j.ajese.20200401.12
T2  - American Journal of Environmental Science and Engineering
JF  - American Journal of Environmental Science and Engineering
JO  - American Journal of Environmental Science and Engineering
SP  - 7
EP  - 12
PB  - Science Publishing Group
SN  - 2578-7993
UR  - https://doi.org/10.11648/j.ajese.20200401.12
AB  - Controversy persists because residents in regions where air quality is poor are always dissatisfied with the presentation of the air quality index (AQI). To make management policies acceptable, it needs to be determined whether adding the various weighting factors can make the AQI more reasonable and practical. The authors selected three indices i.e. AQI, revised air quality index (RAQI), and the air-dispersion AQI (ADRAQI) to compare their results in different atmospheric situations and to determine whether the AQI was made more reliable by adding various weighting factors such as multi-air pollutants and air dispersion derived from the mean function and an entropy function. Results show in comparison to AQI, the RAQI and ADRAQI have greater values in the multi-air pollutant and poor dispersion events, leading to a great difference between single air pollutant and multi-air pollutant events. The eclipsed phenomena in the AQI for the means of diseases related to air pollution such as acute atopic conjunctivitis, other chronic allergic conjunctivitis, other atopic dermatitis and related conditions, contact dermatitis and other eczema, and unspecified causes clearly appear. The findings suggest that the representation of AQI can be modified by considering the weighting factors of multiple air pollutants along with air dispersion; these can easily be applied to similar regions elsewhere.
VL  - 4
IS  - 1
ER  -

Copy | Download