Prediction of Downwind Range of Impacts for Liquefied Natural Gas Vapour Cloud Dispersion Arising From

Spillage Over Tropical Water Bodies

F.A. Akeredolu1, I.A. Isafiade2, and J.A. Sonibare1

1Environmental Engineering Research Laboratory, Department of Chemical Engineering

Obafemi Awolowo University, Ile-Ife. Nigeria

2Department of Chemical Engineering,

University of Cape Town, Private Bag, Rodenbosch 7701,

South Africa

Abstract Liquefied natural gas spillage, spread, vapourization and subsequent dispersion constitute some of the complex problems related to risk assessments of intercontinental marine transportation of that commodity. The warmer climates of the tropics imply that the vapourization rates of the spilled cryogen would be much faster than those reported for the temperate zone. The need to generate the data on the phenomenon for the tropics informed the writing of the paper. The fate of LNG spilled on a water body was modelled by mathematically describing its spread, heat transfer from the water and vapourization. The dispersion of the vapourized LNG was then modelled using dense gas dispersion models such as Aerial Location of Hazardous Atmospheres (ALOHA) and Heavy Gas Dispersion from Area Sources run in the steady state mode(HEGADAS S). Predictions of the downwind range from the two models agreed to within 0.5-50% depending on the wind speed. The downwind ranges predicted were compared with those predicted from published scaling laws (Withers,1980). Wind direction dependence was observed in that regard. For instance, with southwesterlies and north westerlies, the downwind distances of occurrence of undesired impacts predicted by ALOHA and HEGADAS S were higher than those by the scaling laws. The reverse was found with westerly winds. Simulations were carried out for various spill sizes. The downwind

ranges found ranged between 1 and 10 km. For a spill of 14500t resulting from a total tank rupture (a highly improbable occurrence, but which was considered as the “worst case scenario”), the time elapsed for the vapour cloud to reach sensitive receptors situated 5.5km away from the spill was predicted as 22 minutes. Thus, the time available for emergency response activation can be quite brief. Other risk-related issues such as indoor concentrations of methane at downwind receptor locations were modelled and reported.

Introduction

This study relates to the spill behaviour of LNG on tropical waters. A case study was run with the Nigerian data. Nigeria is currently developing several utilization projects for its natural gas. The Nigeria Liquefied Natural Gas (NLNG) Ltd located in Niger Delta (Western Coast of Bonny Island) in the Southern part of the country is the largest of these. Presently, it processes about 1050 Mmscf per day for export. This is to be increased to about 2050 Mmcf per day through 2 trains set to be added in the end of 2005. The plant is sandwiched between Bonny Crude oil Terminal (BCOT) and Mobil Liquefied Petroleum Gas sites (Figure 1). Two towns, Bonny and Finima are also close by. About 3 km away on the southern coast of the Island is a permanent residential area for the plant’s workforce. One of the facilities of the industry is the Jetty, which is approximately 700 m in length, and designed to accommodate LNG carriers with a cargo load of 122,000 to 145,000m3 [5]. The temperature of Bonny Island ranges between 29 0C (high) and 26.5 0C (low) with little variation over the year (±50C). Relative Humidity values are between 94.0% and 77.0%. Wind blows predominantly from the sea (southwesterly to westerly) across the NLNG plant site, Shell terminal site and Bonny town) but

during the harmattan period, spanning December to March, northeasterly winds blow. The annual rainfall is more than 4,000 mm. The Island is relatively flat with Mangrove, freshwater swamp forest and dry land rainforest as the vegetation. As at the period of this study, the populations of Bonny and Finima towns are 46,368 and 22,980 respectively. The proposed production capacity of 17 million tonnes per annum of LNG from Nigeria Liquefied Natural Gas (NLNG) Company translates to an increased possibility of LNG spill on water during loading and transportation, and this poses a great danger to the host environment. Since LNG can asphyxiate, cause freeze burns, and burn when its concentration by volume in air lies between 5% and 15% [13], its spill on the Bonny River can have impact on the installations and residential zones on the Island. The conventional dispersion modeling techniques cannot predict the atmospheric impact of spilled LNG. The release characteristics, local terrain, and meteorological conditions are factors that influence the dispersion of the LNG vapour cloud [9]. Two recently developed models, ALOHA and HEGADAS, were used in this study. The models predicted the spatial footprints of the vulnerable neighbourhood zones in the event of LNG spill on water. It

also predicted at what period the hazard can prevail as well as the indoor concentrations of LNG that can result. The maximum threat zone was geo-referenced on the Bonny LNG site map and a safe distance is recommended.

Theory Spreading of LNG on water surface Assumptions: Flat water surface, instantaneous spills, and prevailing gravitational-inertia regime (Conrado and Vesovic, 2000). Equation 1 describes the rate of change of radius with time to determine maximum radius that could be attained by each simulated spill mass (Fannelop and Waldman, 1972)

( )R12

1WMg64.1

dtdR

⎥⎦

⎤⎢⎣

⎡ −=

Wπρρρρ (1)

where, M = mass of liquid remaining in the pool (kg); ρ and ρw = densities of LNG and water respectively (kg m-3); R = pool radius (m); g = acceleration due to gravity (m s-2); and t = time (s).

Heat transfer Heat transfer from other sources apart from the water body was neglected, water evaporation was neglected, and Nigeria’s LNG was assumed to comprise principally methane. The heat transferred to pool was modelled using: q = h(TW – T) = h∆T (2) where, h = heat transfer coefficient; TW = water temperature (K); T = LNG temperature (K); ∆T = characteristic temperature difference. h in Equation (2) is film heat transfer coefficient determined by Klimenko (1981) as

Cl

UNfh Vλ= (3)

where λV = thermal conductivity; NU = Nusselt number; hf = film heat transfer coefficient and lC is the critical wavelength of instability given by

( )V-g

2Cl ρρσ

π= (4)

where, ρ = cryogen density; (subscript v indicates vapour phase of the cryogen) and σ = surface tension. The Nusselt number NU is determined by the empirical correlation:

NU = 0.19[ArPr]0.33 f1 Ar < 810 (5)

231

U fArPr0086.0N = Ar> 810 (6)

where the Prandtl number, Pr , refers to the vapour phase and the Archimedes number Ar defined as:

( )( )V

2VV

23

3

-g2Ar

ρρνρ

σπ= (7)

where, ν is the Kinematic viscosity f1 and f2 for brevity are omitted. Film heat transfer coefficients were computed at a water temperature (TW) of 295 K. Thermo-physical properties of LNG (i.e. methane) were estimated at its boiling temperature (Tsat) i.e. 111.62 K but the vapour phase thermo-physical properties were computed at the mean film temperature Tav (Mills, 1995).

Vaporization model for the spreading LNG The vaporization of the LNG as it spreads out over the water surface was modeled by a first order differential equation (Conrado and Vesovic, 2000):

LmqR

dtdM

V2

V π=−≡ (8)

where, V is the vaporization rate (kg s-1 ), MV is the mass of liquid vaporized (kg), q is heat transferred to the pool from the water surface (kJ s-1 m-2), Lm is Latent heat per unit mass (kJ kg-1), R is Pool radius (m), t is time for the pool to vaporize (s). As the pool spreads out, its radius R increases with time, and the cryogen vaporizes simultaneously. Therefore the spread equation (1) and the vaporization equation (8) were solved simultaneously using the following initial conditions: t = 0 M = M0 R = 0 (9) with R0 taking values ranging from 1 to 1.5 depending on the mass spilled. The model equation was solved by the fourth order Runge-Kutta method.

Substitution of the initial conditions in both Equations (1) and (8) for spread and vaporization respectively, their simplified forms become:

0

21

0f

R1

M106.0)t(d)R(d

××= (10a)

20

f R16897.0)t(d

)M(d×−= (10b)

Simulations were carried out for different cases representing different instantaneous mass spillages to determine the vaporization rates. Results Table 1 shows the theoretically predicted vaporization rates as a function of spill masses. Tables 2 – 7 are results obtained using the wind directions for each of the vulnerable receptor zones of interest that could be reached by the dispersing vapour cloud. Figure 2 shows the footprint plot over Bonny Island and the pollutant dispersal (top-view) respectively. These two are predicted by HEGADAS S for wind speed 6.7 1−ms and Pasquill stability class D (Figure 3). Figures 4 and 5 show the concentration versus time graph and footprint diagram for wind speed 6.7 1−ms and Pasquill stability class D as predicted by ALOHA.

Table 1: Theoretically Predicted Vaporization Rates for different Spill Masses* Nos. Mass

Spilled M0 (kg)

Initial Radius R0 (m)

Final Time(s)

Mass Remaining in the Pool Mf (kg)

Final Radius Rf (m)

Average Radius Rave (m)

Downwind Length, DL (m)

CrosswindWidth, CW (m)

Vaporization Rate kgs-1

1 70,000 1 128 78.311 74.60 53.09 94.11 47.05 546.88 2 100,000 1 140 18.46 85.28 60.7 107.61 53.81 714.54 3 130,000 1 149 36.73 94.10 67 118.76 59.38 866.67 4 200,000 1 166 35.65 110.51 78.79 139.66 69.83 1202.6 5 300,000 1 184 197.67 128.76 91.84 162.8 81.40 1633.10 6 600,000 1 218 133.96 166.98 119.41 211.67 105.83 2756.09 7 900,000 1 240 0 194.25 139.34 246.99 123.49 3748.28 8 1,250,000 1 260 0 219.91 157.98 280.03 140.01 4813.25 9 1,300,000 1 262 0 222.99 160.22 284.00 142.00 4958.05 10 1,700,000 1 279 816.47 246.79 177.77 315.10 157.55 6093.19 11 1,900,000 1 287 340.89 257.32 185.56 328.93 164.50 6620.21 12 2,300,000 1 300 1363.6 276.44 199.79 354.14 177.07 7666.67 13 3,200,000 1 323 787.07 312.94 213.8 378.98 189.49 9907.12 14 3,600,000 1 332 2358.7 327.09 237.83 421.58 210.79 10843.4 15 4,200,000 1 344 682.45 346.6 252.6 447.83 223.91 12209.3 16 4,600,000 1 352 786.85 358.66 261.84 464.14 232.07 13077.47 17 6,000,000 1.5 382 1228.9 396.05 285.82 506.64 253.32 15706.81 18 7,600,000 1.5 403 4252.8 432.79 313.19 555.15 277.57 18858.56 19 8,000,000 1.5 408 1369.7 441.22 319.52 566.37 283.19 196040 20 10,000,000 1.5 429 1702.2 479.79 348.51 617.77 308.89 23291.02 21 14,500,000 1.5 466 -493.5 551.26 403.26 714.8 357.40 31086.53 *Isafiade (2004)

Table 2. Predictions of Parameters of Hazardous Vapour Cloud Transport from Spill Site and of Indoor Vapours Concentrations at Bonny town and BCOT

Maas

Spilled (kg)

Wind Speed ( )1−ms

Distance Covered

by Cloud as Predicted by ALOHA (m)

Time of Day, ALOHA

(GMT)

Distance Covered

by Cloud as Predicted by

HEGADAS S (m)

Time Cloud reaches Bonny

Town as Predicted by

ALOHA (mins.)

Time Cloud Lingers over

BCOT, as Predicted by

ALOHA (mins.)

Indoor Concentration

at Bonny Town

as Predicted by

ALOHA (ppm)

600,000 4.4 2,400 (D) 2,300 (C)

0-5 & 18-23 (D) 6-17 (C)

1,541 (D) 1,049 (C)

11 3 – 7.5 2,100

900,000 6.7 2,400 (D) 0-23 (D) 1,676 (D) 7.5 2.5 – 7 3,230 1,250,000 9.35 2,400 (D) 0-23 (D) 1,822 (D) 6.5 2.5 – 7 4,530 1,300,000 2.45 2,400 (C)

2,300 (E) 6-17 (C)

0-5 &18-23 (E) 1,753 (C) 8,601 (E)

16 6 – 12 1,860 1,650

1,700,000 12.35 2,400 (D) 0-23 (D) 2,089 (D) 2.7 1.7 - 7 6,150

Table 3. Predictions of Parameters of Hazardous Vapour Cloud Transport from Spill Site and of Indoor Vapours Concentrations at BCOT

Mass Spilled

(kg)

Wind Speed ( )1−ms

Distance Covered by Cloud as Predicted by ALOHA (m)

Time of Day ALOHA (GMT)

Distance Covered by Cloud as Predicted

by HEGADAS S (m)

Time for Cloud to get to BCOT, as

Predicted by LOHA (mins.)

70,000 2.45 1,200 (C) 1,200 (E)

0 -5 & 18 – 23 16 – 17

592 (C) 2,397 (E)

10

100,000 4.4 1,300 (D) 1,200 (C)

0 – 5 & 18 – 23 6 – 17

782 (D) 472 (C)

5

130,000 6.7 1,200 (D) 0 – 23 921 (D) 4.5 200,000 9.35 1,200 (D) 0 – 23 1,057 (D) 3 300,000 12.35 1,200 (D) 0 - 23 1,207 (D) 2.5

Table 4: Predictions of Parameters of Hazardous Vapour Cloud Transport from Spill Site and of Indoor Vapour Concentrations at Finima Town, Mobil LPG & NLNG

Mass

Spilled (kg)

310×

Wind Speed ( )1−ms

Distance Covered

by Cloud, as Predicted by ALOHA (m)

Time of Day

(GMT)

Distance Covered by Cloud, as

Predicted by HEGADAS S

(m)

Time Cloud gets to Finima Town as Predicted

By ALOHA (mins.)

Time & Distance

Cloud Impacts on

LPG Plant as Predicted by

ALOHA (mins.), (m)

Time &Distance

Cloud Impacts on NLNG plantas Predicted by

ALOHA (mins.), (m)

Indoor Concentration in New Finima

Town as Predicted by

ALOHA (ppm)

4,600 2.45 3,200 (F) 2,700 (B)

0-5 & 8-23

6-17

11,470 (F) 1,442 (B)

20

17

14, (F) !x =2000 !y =1,200

13, (B)

!x =2,000 !y =1,054

14, (F) !x =2,000 !y =1,200

13, (B)

!x =2,000 !y =1,054

2,010

2,080

6,000 4.4 3,300 (E) 2,500 (B)

0-5 & 18-23

6-17

7,270 (E) 1,140 (B)

13

9.5

7, (E) !x =2,000

!y =797

8.5, (B) !x =2,000

!y =595

7, (E) !x =2,000

!y =797

8.5 (B) !x =2,000

!y =595

2,750

3,050

!x is Downwind Distance (m) !y is Crosswind Distance (m)

Table 5: Predictions of Distances Covered by Hazardous Vapour Cloud and Elapsed Time When it reaches the NLNG Plant Perimeter and BCOT

Mass Spilled

(kg)

Wind Speed ( )1−ms

Distance Covered

by Cloud, as Predicted by ALOHA (m)

Time of Day,

ALOHA (GMT)

Distance Covered

by Cloud, as Predicted by

HEGADAS S (m)

Time Cloud Reaches NLNG

Boundary, as Predicted by

ALOHA (mins.)

Time and Distance Cloud impacts on

BCOT, as Predicted by ALOHA

(mins.) & (m)

2,300,000 2.45 2,400 (E) 2,200 (C)

0 – 5 & 18 -23 6 – 17

3,436 (E) 1,449 (C)

15 (E) 14.5 (C)

11, (E) 1x = 2,000 1y = 1,000

3,600,000 4.4 2,400 (D) 2,200 (C)

0 – 5 & 18 -23 6 – 17

1,522 (D) 1,195 (C)

10 (D) 8.5 (C)

No appreciable impact on BCOT

6,000,000 6.7 2,400 (D) 0 – 23 1,779 (D) 5 (D) 8,000,000 9.35 2,400 (D) 0 – 23 1,913 (D) 3 (D) 10,000,000 12.35 2,400 (D) 0 - 23 2, 312 (D) 2.5 (D) Note: 1x is downwind distance (m) 1y is crosswind distance (m)

Table 6: Effect of Wind speed on Predicted Hazardous Areas for a Mass Spillage of 14,500,000 kg of LNG

Wind Speed (ms-1)

Distance Covered

by Cloud, as Predicted by ALOHA (m)

Time of Day

(ALOHA) GMT

Distance Covered

by Cloud, as Predicted by

HEGADAS S (m)

Time for Cloud to Reach Maximum Distance, as Predicted by ALOHA

(mins.)

Time & Distance at which Cloud Impacts on

BCOT, as Predicted by ALOHA

(mins.) & (m)

2.45 4,200 (E) 4,000 (C)

0-5 & 18-23 6-17

8,473 (E) 2,593 (C)

22 20

5, (C) x1 = 960, y1

= 960 4.4 4,100 (D)

3,800 (C) 0-5 & 18-23 6-17

2,378 (D) 1,818 (C)

15 15

3, (C) x1 = 1,200, y1 = 672

6.7 3,400 (D) 0-23 2,352 (D) 5.5 2.5, (D) x1 = 1,034, y1 = 475

9.35 3,000 (D) 0-23 2,469 (D) 4.5 2.3, (D) x1 = 1,878, y1= 446

12.35 2,700 (D) 0-23 2,465 (D) 2.2 1.8, (D) x1 = 1,514, y1= 324

x1 is the Downwind Distance (m) y1 is the Crosswind Distance (m)

Table 7: Predictions of Parameters of Hazardous Vapour Cloud Transport from Spill Site and of Indoor Vapours Concentrations at New Finima Town

Mass

Spilled (kg)

Wind Speed ( )1−ms

Distance Covered

by Cloud, as Predicted by ALOHA (m)

Time of Day, ALOHA (GMT)

Distance Covered

by Cloud, as Predicted by

HEGADAS S (m)

Time for Cloud

to Reach New Finima Town, as Predicted by ALOHA

(mins.)

Indoor Concentration in New Finima

Town as Predicted by

ALOHA (ppm)

1,900,000 2.45 2,200 (E) 2,100 (C)

0 - 5 & 18 – 23 6 – 17

1,330 (E) 4,207 (C)

13 (E) 13 (C)

1,530 (E) 1,600 (C)

3,200,000 4.4 2,200 (D) 2,100 (C)

0 -5 & 18 – 17 6 – 17

1,445 (D) 1,134 (C)

8 (D) 7.5 (C)

2,480 (D) 2,470 (C)

4,200,000 6.7 2,100 (D) 0 – 23 1,538 (D) 4.5 (D) 3,570 (D) 6,000,000 9.35 2,100 (D) 0 – 23 1,839 (D) 3 (D) 5,380 (D) 7,600,000 12.35 2,100 (D) 0 - 23 2,078 (D) 2.5 (D) 7,350 (D)

F i g u r e 1 M a p o f B o n n y I s l a n d : N L N G L o c a t i o n

Discussion of Results

According to Tables 2 - 7, as the wind speed increases, the disparity between the predictions by ALOHA and HEGADAS S, for the distance covered by the dispersing cloud, decreases from 50% to 0.5%. . For very low wind speeds such as 2.45 and 4.4 1−ms , ALOHA predicts the time of day and cloud cover and sets a flag if inconsistencies were encountered. Such features were not in HEGADAS S.

Wind speeds 6.7 1−ms to 12.35 1−ms explored corresponded to Pasquil-Gifford stability class D, for most of the day (0-23 hrs). Also, these Tables showed that ALOHA predicted the time for the dispersing cloud to reach Bonny town at the the level of concern (LOC for short, corresponding to 50,000 ppm for methane) and also how much time the cloud spends hovering over some of the vulnerable receptor locations (Areas of Concern, shortened as “AOC”). These downwind ranges are geo-referenced in Figs 2-4. In addition to this, ALOHA estimates the indoor concentration by assuming that the windows were shut. Accordingly, the predictions made from ALOHA were below LOC (50,000 ppm). The time to mitigate hazardous mass effects of LNG spill was predicted to be 22 minutes but this could be as low as 2 minutes if very strong winds prevailed.

Figure 2: Footprint plot (wind speed 6.7 1−ms , Pasquil stability class D) over Bonny Island, as predicted by HEGADAS S

Figure 3: Pollutant dispersal top-view (wind speed 6.7 1−ms , Pasquil stability class D) as predicted by HEGADAS S

LO

0 20 40 60 010,00020,00030,00040,00050,000 ppm

Figure 4: Concentration Vs. Time Graph (Wind speed 12.5 m/s, Pasquil Stability Class D). ALOHA

1.50.5 00.51.5kilometers

km

Figure 5: Footprint diagram (wind speed 6.7 1−ms , Pasquil stability class D), as predicted by ALOHA

Conclusion The spatial receptor areas (AOC) vulnerable to the impact by the spill of known quantities of LNG were predicted as an environmental management input for interested stakeholders. The maximum threat zones predicted based on ALOHA and HEGADAS S were generally in agreement. Within the range of validity of the models, the disparity between those predictions was as low as 0.5% at high wind speeds but was as high as 50% at low wind speeds. This gives an assurance about the accuracy of the predictions. The commercial version of ALOHA software does not have a provision for handling cryogen spills on water. A little modification was therefore carried out on it in order to use the same basis for the input information as HEGADAS S. The modifications done in the course of this research predicted very good results for the steady state case. For the steady state case, the values predicted by both software were generally in agreement. It could be concluded that the predictions by ALOHA for the transient aspect of the dispersion would also be dependable. ALOHA was also employed for predicting the indoor concentrations in the residential zones located downwind of the LNG plant. The predicted indoor

concentrations were below threshold limit values (TLV) but those in the immediate environment of the spill points could be exposed to the risk of asphyxiation. The time to mitigate hazardous mass effects of LNG spill was predicted to be about 22 minutes but this could be lower to about 2 minutes under very strong winds as predicted by ALOHA. as the wind speed increased. From this work, it was deduced that the NLNG plant is located rather too close to third party installations and the resident communities on the island. It is recommended that the closest point to the Bonny River at which any of the installations LPG terminal, BCOT and the two towns, Bonny and Finima can be located is about 5.5 km away as shown on Table 6. The basis was that ALOHA predicted 4.2 km at wind speed 145.2 −ms and Pasquill-Gifford stability class E, which gave the information about the maximum distance at which there could be a risk of impact in the event of the largest spill possible occurring. The existing situation of close proximity these third party facilities and residential towns on the one hand and the NLNG industry on the other, indicates that adequate contingency measures should be in place to cope with emergencies involving LNG spillage on water within the time frame indicated in the preceding paragraph, wth the desirable response time being under 30 minutes.

References Conrado, C. and Vesovic, V., (2000). The influence of chemical composition on vapourization of LNG and LPG on unconfined water surfaces, http//www.huxley.ic.ac.uk/research/PETENG/Perm/Publications. Fannelop, T.K. and G.D. Waldman, 1972. Dynamics of oil slicks. American Institute of Aeronautics and Astronautics 10; 506-510. Klimenko, V.V. (1981). Film boiling on a horizontal plate-new correlation. International Journal of Heat and Mass Transfer 24; 69-79 Mills, A.F. (1995). Heat and Mass Transfer. Richard D. IRWIN, INC., Chicago, pp.640-643, 890. Withers, J., (1980) "Major Industrial Hazards". John Wiley & Sons, Inc., New York. 1988, pp 100-102, 109,128