Abstract
The aim of this study was to analyze dispersion behavior characteristics and pollution hazard risk after a release of liquid chlorine. A full-scale model of liquid chlorine tanks in an area with a radius range of 3 km was established using FLACS (Flame Acceleration Simulator) code, and the chlorine dispersion characteristics of six leakage scenarios were calculated according to the POOL model, and the individual risk and social risk under different conditions as calculated quantitatively. The results show that leakage occurs in three stages: dynamic dispersion, gravity dispersion, and atmospheric dispersion. Variations in dispersion processes were expressed as “outward expansion” and “inward contraction.” At the same time, dispersion was accompanied by the phenomenon of “cloud separation.” In the six leakage scenarios, the total distance of chlorine dispersion was 84–1000 m for a concentration of 225 ppm, and 27.5–401.3 m for a concentration of 900 ppm. The corresponding times (duration) to the farthest dispersion distance were 235–1345 s and 185–680 s, respectively. Chlorine concentration and dispersion distance are consistent in trend; however, the farthest dispersion distance shows a “delay effect” in time. At 225 ppm and 900 ppm, the delay time was 125–1145 s and 75–480 s indifferent leakage scenarios. The installation of a safety instrument system (SIS) can effectively reduce the risk of chlorine dispersion.
Similar content being viewed by others
Data availability
Some or all data, models, or code generated or used during the study are available from the corresponding author by request.
Abbreviations
- n j :
-
vector of the control volume surface pointing outward perpendicular to the jth direction
- u j :
-
velocity in the jth direction
- S Φ :
-
the source term of Φ
- R Φ :
-
Additional resistance, additional mixing, and/or additional heat transfer due to solid obstacles in the flow
- V cv :
-
volume, m3
- A cv :
-
surface area, m2
- x :
-
hole size, mm
- X j :
-
integral in j direction
- β v :
-
volume porosity
- β j :
-
area porosity
- ρ :
-
fluid density, kg/m3
- ΓΦ :
-
effective turbulent dispersion coefficient
References
Bauer TJ (2013) Comparison of chlorine and ammonia concentration field trial data with calculated results from a Gaussian atmospheric transport and dispersion model. J Hazard Mater 254–255:325–335. https://doi.org/10.1016/j.jhazmat.2013.04.002
Beji T, Merci B (2018) Development of a numerical model for liquid pool evaporation. Fire Saf J 102:48–58. https://doi.org/10.1016/j.firesaf.2018.11.002
Braatz AL, Hisken H (2017) Response surfaces for advanced consequence models: two approaches. J Loss Prev Process Ind 49(Part B):683–699. https://doi.org/10.1016/j.jlp.2017.02.007
Brambilla S, Manca D (2009) Accidents involving liquids: a step ahead in modeling pool spreading, evaporation and burning. J Hazard Mater 161:1265–1280. https://doi.org/10.1016/j.jhazmat.2008.04.109
Dasgotra A, Varun Teja GVV, Sharma A, Mishra KB (2018) CFD modeling of large-scale flammable cloud dispersion using FLACS. J Loss Prev Process Ind 56:531–536. https://doi.org/10.1016/j.jlp.2018.01.001
Efthimiou GC, Andronopoulos S, Tavares R, Bartzis JG (2017) CFD-RANS prediction of the dispersion of a hazardous airborne material released during a real accident in an industrial environment. J Loss Prev Process Ind 46:23–36. https://doi.org/10.1016/J.JLP.2017.01.015
Gant S, Weil J, Delle Monache L, McKenna B, Garcia MM, Tickle G, Tucker H, Stewart J, Kelsey A, McGillivray A, Batt R, Witlox H, Wardman M (2018) Dense gas dispersion model development and testing for the Jack Rabbit II phase 1 chlorine release experiments. Atmos Environ 192:218–240. https://doi.org/10.1016/j.atmosenv.2018.08.009
Gexcon AS (2019) FLACS v10.9 user’s manual. Norway
Hankin RKS (2003) Heavy gas dispersion: integral models and shallow layer models. J Hazard Mater 103:1–10. https://doi.org/10.1016/S0304-3894(03)00219-X
Hanna S, Chang J, Huq P (2016) Observed chlorine concentrations during Jack Rabbit I and Lyme Bay field experiments. Atmos Environ 125(Part A):252–256. https://doi.org/10.1016/j.atmosenv.2015.11.029
Hansen OR, Gavelli F, Ichard M, Davis SG (2010) Validation of FLACS against experimental data sets from the model evaluation database for LNG vapor dispersion. J Loss Prev Process Ind 23:857–877. https://doi.org/10.1016/j.jlp.2010.08.005
Law WP, Erain N, Ramli NI, Gimbun J (2019) Assessment of chlorine leak dispersion around Gebeng industrial area and potential evacuation route. Atmos Res 216:117–129. https://doi.org/10.1016/j.atmosres.2018.10.003
Li QY, Cai XH, Wang X et al (2012) The environmental risk analysis of toxic gas leakage in Taiyuan coal chemistry industrial zone. Acta Sci Circumst 32:537–544. https://doi.org/10.13671/j.hjkxxb.2012.03.013
Moen A, Mauri L, Narasimhamurthy VD (2019) Comparison of k-ε models in gaseous release and dispersion simulations using the CFD code FLACS. Process Saf Environ Prot 130:306–316. https://doi.org/10.1016/j.psep.2019.08.016
Olewski T, Nayak S, Basha O, Waldram S, Véchot L (2011) Medium scale LNG-related experiments and CFD simulation of water curtain. J Loss Prev Process Ind 24:798–804. https://doi.org/10.1016/j.jlp.2011.06.005
Pintarič ZN (2007) Assessment of the consequences of accident scenarios involving dangerous substances. Process Saf Environ Prot 85:23–38. https://doi.org/10.1205/psep06014
Ruj B, Chatterjee PK (2012) Toxic release of chlorine and off-site emergency scenario - a case study. J Loss Prev Process Ind 25:650–653. https://doi.org/10.1016/j.jlp.2012.01.002
Sanchez EY, Colman Lerner JE, Porta A, Jacovkis PM (2013) Accidental release of chlorine in Chicago: coupling of an exposure model with a Computational Fluid Dynamics model. Atmos Environ 64:47–55. https://doi.org/10.1016/j.atmosenv.2012.09.037
Scargiali F, Grisafi F, Busciglio A, Brucato A (2011) Modeling and simulation of dense cloud dispersion in urban areas by means of computational fluid dynamics. J Hazard Mater 197:285–293. https://doi.org/10.1016/j.jhazmat.2011.09.086
Schleder AM, Martins MR (2016) Experimental data and CFD performance for CO2 cloud dispersion analysis. J Loss Prev Process Ind 43:688–699. https://doi.org/10.1016/j.jlp.2016.03.027
Schleder AM, Pastor E, Planas E, Martins MR (2015) Experimental data and CFD performance for cloud dispersion analysis: the USP-UPC project. J Loss Prev Process Ind 38:125–138. https://doi.org/10.1016/j.jlp.2015.09.003
Sharma RK, Gopalaswami N, Gurjar BR, Agrawal R (2020) Assessment of failure and consequences analysis of an accident: aa case study. Eng Fail Anal 109:104192. https://doi.org/10.1016/j.engfailanal.2019.104192
Sohn MD, Delp WW, Fry RN, Kim Y-S (2019) Analysis of a series of urban-scale chlorine dispersion experiments and implications on indoor health consequences. Atmos Environ 212:83–89. https://doi.org/10.1016/J.ATMOSENV.2019.05.010
Wang XS, Chen B (2016) Effect of flow pattern inside nozzle on spray characteristics of R134a flashing spray. Ciesc J 115:524–536. https://doi.org/10.11949/j.issn.0438-1157.20161083
Wang WH, Sun BJ, Bu Y (2017) Distribution rule of instantaneous leakage and diffusion mass concentration of liquid chlorine storage tank and evaluation of poisoning consequences. J Saf Environ 17:6–11. https://doi.org/10.13637/j.issn.1009-6094.2017.01.001
Wiergowski M, Sołtyszewski I, Sein Anand J, Kaliszan M, Wilmanowska JA, Jankowski Z, Łukasik M (2018) Difficulties in interpretation when assessing prolonged and subacute exposure to the toxic effects of chlorine. J Forensic Legal Med 58:82–86. https://doi.org/10.1016/j.jflm.2018.05.003
Zhao JP, Tian HX, Song QW et al (2014) Study on emergency evacuation of chlorine leakage accident area -- taking a chlorine storage tank of a chemical plant in Xi’an as an example. Chin J Saf Sci 24:163–169. https://doi.org/10.16265/j.cnki.issn1003-3033.2014.01.019
Acknowledgments
We express sincere gratitude to the anonymous reviewers for their insightful suggestions to improve the quality of the manuscript.
Funding
The work was financially supported by the National Natural Science Foundation of China (51574056, 51604057) and Youth Science and Technology Innovation Project of Sinopec Qingdao Research Institute of Safety Engineering (YQ-59).
Author information
Authors and Affiliations
Contributions
Baoquan Xin: methodology, software, writing; Jianliang Yu: conceptualization, reviewing, revise; Wenyi Dang: investigation, reviewing; Lu Wan: data curation, software.
Corresponding author
Ethics declarations
Competing interests
The authors declare that they have no conflict of interest.
Ethics approval and consent to participate
Not applicable.
Consent for publication
On behalf of all authors, I declare that this manuscript is the authors’ original work and has not been published nor has it been submitted simultaneously elsewhere; and all authors have checked the manuscript and have agreed to the publication on ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH.
Additional information
Responsible Editor: Marcus Schulz
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Xin, B., Yu, J., Dang, W. et al. Dynamic characteristics of chlorine dispersion process and quantitative risk assessment of pollution hazard. Environ Sci Pollut Res 28, 46161–46175 (2021). https://doi.org/10.1007/s11356-020-11864-z
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11356-020-11864-z