predictive factors of contamination in cooling tower water

predictive factors of contamination in cooling tower water

;Pipat Luksamijarulkul;Sumawadee Kornkrerkkiat;Chayaporn Saranpuetti;Dusit Sujirarat
air, soil and water research 2014 Vol. 7 pp. -
145
luksamijarulkul2014air,predictive

Abstract

A cross-sectional study of 160 water samples collected from 72 cooling towers in 4 hospitals, 7 department stores, and 3 hotels in Bangkok was carried out to investigate Legionella pneumophila contamination and its predictive factors. All water samples were cultured for Legionella spp. and tested for L. pneumophila by real-time polymerase chain reaction (PCR). Some cooling tower parameters were measured and recorded. Data were analyzed using χ 2 -test, odds ratio and stepwise logistic regression analysis at the significant level of α = 0.05. Results revealed that the Legionella spp. contamination was 20.0% (32/160) and for L. pneumophila was 61.3% (98/160). The sensitivity of real-time PCR was higher than that of the culture. Factors significantly associated with L. pneumophila contamination by χ 2 -test were: the cooling tower model, size, use duration, pH, water temperature, use of ozone, and residual free chlorine (95% CI of OR > 1.0, P < 0.05). After stepwise logistic regression analysis, four predictive factors remained. These included the cooling tower model being a cross-flow type (adjusted OR = 3.1, 95% CI = 1.2-7.8, P = 0.017), use duration >5 years (adjusted OR = 3.6, 95% CI = 1.3-10.1, P = 0.016), water temperature <29.4°C (adjusted OR = 7.9, 95% CI = 2.1-29.6, P = 0.002), and residual free chlorine <0.2 ppm (adjusted OR = 8.5, 95% CI = 2.1-34.9, P = 0.003). Additionally, the risk probability for L. pneumophila contamination was estimated to be 13.9-97.1%, depending on the combination of predictive factors.

Citation

ID: 144351
Ref Key: luksamijarulkul2014air,predictive
Use this key to autocite in SciMatic or Thesis Manager

References

Blockchain Verification

Account:
NFT Contract Address:
0x95644003c57E6F55A65596E3D9Eac6813e3566dA
Article ID:
144351
Unique Identifier:
10.4137/ASWR.S12972
Network:
Scimatic Chain (ID: 481)
Loading...
Blockchain Readiness Checklist
Authors
Abstract
Journal Name
Year
Title
5/5
Creates 1,000,000 NFT tokens for this article
Token Features:
  • ERC-1155 Standard NFT
  • 1 Million Supply per Article
  • Transferable via MetaMask
  • Permanent Blockchain Record
Blockchain QR Code
Scan with Saymatik Web3.0 Wallet

Saymatik Web3.0 Wallet