Hydroxylamine production: will a QRA help you decide?

Hydroxylamine production: will a QRA help you decide?

Kiran Krishna, Yanjun Wang, Sanjeev R. Saraf, William J. Rogers, John T. Baldwin,Jai P. Gupta, M. Sam Mannan*

Mary Kay O’Connor Process Safety Center, Department of Chemical Engineering, Texas A&M University, College Station, TX 77843-3122, USA

Received 20 January 2003; accepted 22 April 2003

Abstract

The recent publication by the US Chemical Safety Board (CSB) concerning its findings on the Concept Sciences Inc. (CSI) incident

involving hydroxylamine (HA) has raised issues with regard to safe production of HA. This CSI incident was followed by another incident

that destroyed the Nissin Chemical HA plant in Japan, and today BASF is the sole commercial producer of HA. HA is an important solvent in

the pharmaceutical industry and is used as an etching agent in the semi-conductor industry.

This paper discusses a Quantitative Risk Assessment of a generic HA production plant, which integrates the findings of the CSB report and

the knowledge of potential HA reactivity hazards based on research at the Mary Kay O’Connor Process Safety Center. The intent is to

highlight safety concerns and major risk factors in the production and handling of HA and to provide risk assessment guidelines for potential

manufacturers. These guidelines are also applicable to the production strategies for other hazardous chemicals.

q 2003 Elsevier Science Ltd. All rights reserved.

Keywords: Hydroxylamine; Quantitative Risk Assessment; Reactivity; Run-away; Chemical process safety

1. Introduction

The chemical process industries handle, produce, and

store hazardous materials that are capable of potential

catastrophes. Often, changes during plant operations or lack

of accurate knowledge of reactive chemistry of the

components have been the cause of serious incidents in

the plant [1,2]. For example, the Concept Sciences Inc.

(CSI) hydroxylamine (HA:NH2OH) manufacturing unit in

Pennsylvania was destroyed in February 1999 [3] and was

followed by an explosion at the Nissin Chemical HA plant

in Japan in May 2000 [4].

Today BASF is the sole producer of HA, which is an

important solvent in the pharmaceutical industry and is used

as an etching agent in the vast semi-conductor industry. The

recent publication by the US Chemical Safety Board (CSB)

of its findings on the CSI incident [5] involving HA has

raised concerns with regard to the safe production of HA.

The CSB concluded that the process safety management

systems were incapable of addressing the hazards posed by

HA manufacture, but more importantly recognizes the fact

that the collection and analysis of process safety information

specific to the reactive and explosive hazards of HA were

inadequate. To prevent incidents in the future, designing a

safer HA production process requires an understanding of

the underlying hazards and risks due to the unstable nature

of the compound.

The aim of this paper is to perform a Quantitative Risk

Assessment (QRA) on a generic HA production plant based

on available data. Such an analysis should give an insight

into possible events that may lead to serious incidents and

help design a safer process. The risk involved in handling

other hazardous chemicals, can be evaluated using a similar

methodology.

2. HA production

The objective of the production unit is to manufacture

50 wt% (weight percent) HA (NH2OH) aqueous solution,

which is the maximum possible HA concentration permiss-

ible to be transported in the US. The process consists of the

following units: a continuous stirred tank reactor (CSTR),

multiple filtration units, and a packed distillation tower,

as shown in Fig. 1. The design of the plant is based on

0951-8320/03/$ - see front matter q 2003 Elsevier Science Ltd. All rights reserved.

doi:10.1016/S0951-8320(03)00115-7

Reliability Engineering and System Safety 81 (2003) 215–224

www.elsevier.com/locate/ress

* Corresponding author. Tel.: þ1-979-862-3985; fax: þ1-979-458-1493.

E-mail address: [email protected] (M.S. Mannan).

http://www.elsevier.com/locate/ress

the information available in the CSB report [5]. The

properties utilized for elementary process design are

summarized in Table 1. Details of the calculations performed

for preliminary process design are available on request.

The details of the process are as follows:

1. The CSTR is fed with stoichiometric amounts of

potassium hydroxide (KOH) and hydroxylammonium

sulfate ((NH2)2SO4). The two streams combine in the

reactor according to the following stoichiometry:

2KOH þ ðNH2Þ2SO4 ! K2SO4 þ 2NH2OH

Preliminary studies performed in our laboratory indicate

that KOH catalyses the decomposition of HA.

2. The product stream from the reactor is fed to a filtration

unit to remove the solid potassium sulfate (K2SO4).

Fig. 1. Hydroxylamine production.

K. Krishna et al. / Reliability Engineering and System Safety 81 (2003) 215–224216

3. An accumulator is used to isolate the preceding process

(reaction and filtration) from the distillation. A heat

exchanger with an outlet temperature control is also

employed to achieve a suitable feed temperature for this

stream, which consists of approximately 30 wt% HA.

4. The stream is then fed to a vacuum distillation tower

to concentrate it to 50 wt% HA at the bottoms.

Preliminary calculations indicate that a packed dis-

tillation tower operated at 250 mmHg, and a reflux

ratio of 0.5 should enable the desired separation. Our

calculations also indicate that the distillation system is

sensitive to feed concentration and temperature.

Based on available values and calculations performed

on the various units, the production of 50 wt% HA

appears to be feasible. It is worth noting that the CSI

process involved concentrating HA to 80 wt% aqueous

solution and then lowering the concentration to 50 wt%

[5]. Studies performed at the Mary Kay O’Connor

Process Safety Center (MKOPSC) indicate that decompo-

sition of 50 wt% HA is initiated at ,120 8C (onset

temperature) and is extremely sensitive to metal con-

tamination [21] (e.g. iron, titanium). The onset tempera-

ture ðTONSETÞ is defined as the temperature at which a

detectable temperature rise is observed in the sample due

to exothermic reactions and is an indicator of incipience

of a reaction. Another study performed on HA indicates

that the decomposition onset temperature reduces with

increasing HA concentration [22]. The same paper also

reports that 80 wt% and higher concentrations of HA–

water solutions could detonate on mechanical impact.

The relationship between decomposition temperature HA

and concentration is shown in Fig. 2. This figure can be

used as a rough guide to estimate the hazards in the

process due to thermal instability of HA. The onset

temperature decreases with the addition of metal

contamination. If multiple filters are used in parallel,

deionized water is recommended for cleaning purposes to

avoid possible contamination.

Table 1

Summary of hydroxylamine properties

Property Value Reference

Physical appearance White-colorless [6]

Odor less

Solid crystals

Melting point (8C) 33.05 [6]

32.05 [7]

Boiling point 56–57 8C at 22 mmHg [7]

70 8C at 60 mmHg [8]

142 8C at 760 mmHg

(extrapolated)

[7]

Vapor pressure 0.27 mmHg at 0 8C [9]

5.3 mmHg at 32 8C [7]

10 mmHg at 47.2 8C [7]

40 mmHg at 64.6 8C [7]

100 mmHg at 77.5 8C [7]

400 mmHg at 99.2 8C [7]

Density of solid 1.2255 g/ml at 0 8C [10]

Density of liquid 1.204 g/ml at 33 8C [7]

1.2255 g/ml at 0 8C [11]

Specific gravity of vapor

(calculated)

1.14 [6]

Heat of formation, solid 225.5 kcal/mol at 25 8C [9]

Free energy of formation 25.6 kcal/mol at 25 8C [12]

Heat of fusion 3.94 kcal/mol at 32.05 8C [9]

Heat of sublimation 15.34 kcal/mol at 0

and 32 8C

[9]

Heat of solution (kcal/mol) 3.795 [6]

Heat of hydrolysis 1.96 kcal/mol at 20 8C [13]

Heat of vaporization

(kcal/mol)

11.4 [9]

Entropy of sublimation 40.4 cal/K/mol at 0

and 32 8C

[9]

Entropy for gas, calculated 56.33 cal/K/mol at 25 8C [14]

Heat capacity of gas 11.17 cal/K/mol at 25 8C [14]

Molecular volume (cm3) 27.4 [7]

Dissociation constant 1.07 £ 1028 at 20 8C [7]

Dielectric constant 77.63–77.85 [7]

Proton affinity (kcal/mol) 211 [7]

pKa (NH3OH)þ 6.04 at 20 8C [15]

pKb 8.13 at 20 8C [15]

pH (50% aq.) 11 [15]

N–O bond distance (A) 1.46 [14]

Bond dissociation energy (kcal/mol)

H2N–OH 61.3 [9]

HO–OH 51.0 [9]

H2N–NH2 60.0 [9]

Flash point Explodes at 129 8C [16]

NFP classification Health 2 [17]

Fire 0

Stability 3

Heat of formation solid

(kcal/mol)

227.3 [7]

Heat of formation liquid

(kcal/mol)

225.5 [18]

221.7 [19]

Heat of formation gas (kcal/mol) 210.2 [9]

Vapor pressure data A: 73.552 [20]

lnðPÞ ¼ A þ B=T þ C lnðTÞ þ DTE ;

where P—pressure (atm), T—

temperature (K)

B: 21.0434 £ 104

C: 25.8582

D: 1.7605 £ 10217

E: 6.0Fig. 2. The effect of HA concentration on the onset temperature.

K. Krishna et al. / Reliability Engineering and System Safety 81 (2003) 215–224 217

In addition, KOH catalyses the decomposition of HA and

may lead to potential runaway behavior. Therefore,

operation of the reactor in a semi-batch mode, where

KOH is added to the bulk (NH2)2SO4 in the reactor, with

good mixing, is suggested. However, the use of semi-batch

mode complicates the reactor operation and as a result

increases the risk due to human error. Further investigation

by the MKOPSC involves design of a safer operation for the

reactor.

3. Development of a reactivity risk index

The decomposition of HA is sensitive to excursions of

temperature, HA concentration, metal contamination, and

KOH concentration (as indicated by recent studies in our

laboratory). In this section, we discuss development of an

algebraic equation called a reactivity risk index (RRI) that

will take account of the reactivity hazards due to

temperature, concentration and metal contamination. At

present we do not have sufficient information to quantify the

effect of pH on the decomposition.

The RRI was defined earlier in the context of reactive

chemicals [23] and in this case is defined as follows:

RRI¼TPROCESS

TONSET

CHA;MAX

CHA;CRITICAL

expCCONTAMINANTS

CCONTAMINANTS;CRITICAL

!

where

TPROCESS maximum process temperature

TONSET onset temperature indicating the onset of a

significant reaction

CHA;MAX maximum HA concentration

CHA;CRITICAL critical HA concentration

CCONTAMINANTS concentration of metal ions

CCONTAMINANTS;CRITICAL critical concentration of metal

ions

From Fig. 2 we obtain the following relationship between

onset temperature and HA concentration:

TONSETð8CÞ ¼ 415:6 expð22:8CHA;MAXÞ

where

CHA;MAX maximum HA concentration (wt%).

A value of 0.8 can be assigned to CHA;CRITICAL since HA

is reported to decompose spontaneously at 80% and higher

concentrations [22]. An exponential functional dependence

is assigned for the effect of contamination so that for the

limiting case, CCONTAMINANTS ¼ 0; the exponential term

is unity. Therefore, in the absence of contaminants and

substituting the TONSET with the earlier relationship, the RRI

becomes:

RRI ¼TPROCESS

415:6 e22:8CHA;MAX

CHA;MAX

0:8

We obtain the following values of RRI for the different

units:

1. Reactor: TPROCESS ¼ 50 8C; CHA;MAX ¼ 0:3; RRI ¼ 0:11

2. Filter: TPROCESS ¼ 25 8C; CHA;MAX ¼ 0:3; RRI ¼ 0:06

3. Distillation: TPROCESS ¼ 75 8C; CHA;MAX ¼ 0:5; RRI ¼

0:46

The above results indicate that the distillation tower

poses the maximum risk due to thermal and concentration

excursions and without any safeguards.

4. Risk assessment

Quantitative risk analysis helps the chemical process

industry in two ways: it identifies the dominant contributors

to the total risk, and it quantifies the benefits of possible

changes. The first step is to analyze the total risk associated

with the base case and to calculate the contributions. These

findings lead naturally to the specification of possible

measures to improve reliability or reduce the damage

potential. Fig. 3 depicts the procedure involved in

quantitative risk analysis.

The first step in evaluating the risk associated with a

chemical process is to identify potential hazards. As stated

earlier, our concern here is an exothermic decomposition

reaction occurring in the process. Based on our knowledge,

Fig. 3. Quantitative risk analysis scheme.


the major risk lies in the CSTR and distillation tower

besides the design fault, construction error, and other

external factors. The Top Event, ‘Significant decomposition

of HA occurs in the process’, consists of four sub-events:

corrosion, external heat, decomposition in the CSTR, and

decomposition in the distillation tower. Fault tree tech-

niques are used to estimate the probability of these events

with the existing safeguards. The results of the fault tree are

analyzed and conclusions and recommendations are

determined.

4.1. Fault tree analysis

Fault tree analysis (FTA) is a deductive technique to

analyze systematically and logically how equipment

failures, operator errors, and external factors can cause an

incident. A fault tree can be generated by asking ‘What can

cause this event?’ until primary failures or faults are

achieved.

As described in the above section, an auto-oxidation can

occur under any of the following conditions:

1. High temperature: Under clean conditions, the onset

temperature of 50 wt% HA is around 120 8C, according

to MKOPSC research [21]. This temperature is not

normally present in the process. The neutralization

reaction in the reactor is only mildly exothermic, local

hot spot may not achieve this temperature even if the

agitator is not working properly. However, high

temperature can be caused by external heat such as a fire.

Fig. 4. The fault tree with the Top Event: ‘Significant decomposition of HA occurs in the process’.


2. High concentration (70 wt% or above): Under normal

operation conditions, the process cannot achieve this

concentration. But local high concentration can be

caused by water evaporation as a result of external heat

or distillation malfunction. Our calculation shows that

decreased feed temperature, lower pressure, condenser

failure and sub-cooled feed, and increased re-boiler heat

load of the distillation tower can cause higher

concentration.

3. Contamination: Contaminants including heavy metals

like iron, copper, chromium, nickel, their alloys, and

their ions, dust, oxidizing agents, and bases must be

avoided. Experiments show that HA decomposition is

significantly enhanced by metal/bases even in trace

quantities. The CSTR is close-topped. Contaminants

can enter the process via a feed line or construction

material corrosion.

Table 2

Failure rate data

Rate Units Description Sources

1.36 £ 1026 H Agitator failure [24]

2.40 £ 1024 H Analyzer system did not

catch the high concen-

tration event

[24]

1.00 £ 1026 H Condenser failure Engineering

estimate

4.00 £ 1027 H Controller fails high [24]

1.36 £ 1026 H Controller stuck [24]

0.0001 0 Construction fault [25]

0.0001 0 Sufficient conta-

minants exists in

the KOH feed

Engineering

estimate

0.0001 0 Sufficient contaminants

exists in the (NH2)2SO4 feed

Engineering

estimate

3.00 £ 1027 H Control valve fails open [24]

3.00 £ 1027 H Control valve fails to

open on demand

[24]

3.00 £ 1027 H Control valve stuck [24]

0.0001 0 Design fault [25]

1.14 £ 1029 H External fire exposure [26]

0.001 0 Feed too hot Engineering

estimate

1.10 £ 1026 H Fire detector fails to

detect external fire

[24]

6.60 £ 1027 H Flow meter fails high [24]

6.60 £ 1027 H Flow meter fails low [24]

1.14 £ 1028 H Flow meter on (NH2)2SO4

feed line leaks externally

[27]

1.14 £ 1028 H Flow meter stuck [27]

0.1 0 (NH2)2SO4 feed pressure

decreases

Engineering

estimate

0.1 0 KOH feed pressure increases Engineering

estimate

0.0001 0 Loss of purge air Engineering

estimate

0.1 0 Liquid level too high Engineering

estimate

0.001 0 Operator failure [25]

4.57 £ 10210 H Manual valve on (NH2)2SO4

feed line

leaks externally

[28]

3.00 £ 1027 H Manual valve stuck open [24]

0.001 0 Operator add concentrated

HA to accumulator by mistake

[25]

0.03 0 Operator fails to respond

to the flame alarm

[24]

0.001 0 Operator failure [25]

0.07 0 Alarm failure [24]

6.60 £ 1027 H Pressure indicator fails high [24]

6.60 £ 1027 H Pressure indicator fails low [24]

0.04 0 Vacuum pump fails to stop

on demand

[24,27]

0.001 0 Re-boiler design error [25]

0.0001 0 Control set point too high [25]

0.0001 0 Pressure set point too low [25]

0.07 0 Alarm failure [24]

9.70 £ 1025 H Temperature sensor failure [24]

6.60 £ 1027 H Temperature sensor fails low [24]

6.60 £ 1027 H Temperature sensor stuck [24]

Note: H represents failure rate per hour and 0 represents probability of

failure.

Table 3

QRA results

Event Probability

Corrosion occurs in the process 2.00 £ 1024

High temperature/high concentration due to external heat 3.93 £ 1027

Significant decomposition occurs in the CSTR 3.21 £ 1026

Significant decomposition occurs in the distillation tower 9.50 £ 1026

Table 4

High-risk contributors

Cut set Probability Contribution (%)

Design fault 1.00 £ 1024 46.9

Construction material error 1.00 £ 1024 46.9

Table 5

Results of the cut set analysis

Cut set Probability Contribution to

the remaining

6.2% (%)

Condenser fails, vacuum pump

fails to stop on demand, operator

fails to respond to alarm

2.59 £ 1026 19.5

Distillation re-boiler heat load too high,

vacuum pump fails to stop on demand,

operator fails to respond to alarm

1.20 £ 1026 9.0

CSTR agitator failure, control valve of

temperature interlock system fails to

open, operator fails to respond to alarm

9.39 £ 1027 7.1

Pressure indicator on distillation tower

fails high, vacuum pump fails to stop

on demand, operator fails to respond

to alarm

5.7 £ 1027 4.3


The fault tree with the Top Event designated as

significant decomposition of HA occurs in the process is

shown in Fig. 4.

4.2. Data and data sources

The failure rate and probability data have been provided

in Table 2. The primary reference is CCPS [24]. Other

references include Moss [28], Rasmussen et al. [27], and

Lees [25]. Contamination and corrosion data are based on

engineering judgment.

4.3. Results and discussion

With the failure rate data above, the calculated results are

summarized in Table 3. The four sub-events, listed in

Fig. 5. Partial sub-tree for the event: ‘Significant decomposition occurs in the CSTR’.


Table 3, lead to a probability of 2.13 £ 1024 to the TOP

event—significant decomposition of HA occurs in the

process. From the cut set analysis, the two cut sets that

contribute the most (93.8% together) are shown in Table 4.

Since HA decomposition is significantly catalyzed by

metal/dust contaminants, design fault and construction

errors become dominant. To eliminate the human errors in

the design and construction materials, multiple independent

inspections are recommended.

Except for the design fault and construction errors, the

five major contributors to the remaining 6.2% are listed in

Table 5, where the last column is the contribution to the

remaining 6.2%. While cut set analysis quantitatively

describes each cut set and identifies the major risk

contributors, it obscures the observation without identify-

ing the intermediate gates. If we examine the fault tree

directly, part of which is shown in Figs. 4 and 5, some

conclusions can be easily reached. For the sub-event

‘Significant decomposition occurs in the CSTR’, a large

portion of the risk comes from the ‘excessive KOH fed or

local KOH concentration too high’ gate. From Fig. 5, the

probability of ‘decomposition in the CSTR’ without the

protection system is 1.41 £ 1022, of which 1.39 £ 1022

comes from ‘excessive KOH feed or local KOH

concentration too high’. This is reasonable since OH2

catalyzes HA decomposition. Therefore, the performance

of the flow ratio control and agitator becomes a major

safety concern. To remedy this problem, an alternative

reaction mechanism or a semi-batch/batch reactor design

is preferred.

5. Benefit of design changes and safeguards

Decomposition reaction of HA is exothermic, and a large

heat and volume of toxic gases can be generated and

released. Different designs or safeguards will either reduce

the probability of significant decomposition or lessen the

severity level. The benefit of design changes and safeguards

can be easily verified and compared by the fault tree results.

For illustration, we present here the benefits of a

temperature interlock system on the reactor and quench

valve protection at the bottom of the distillation tower.

Application to other design changes and safeguards can be

done similarly.

Without the temperature interlock on the CSTR, the

protection against temperature rise, upon occurrence of HA

decomposition in the reactor, is solely provided by alarms

and operator, which is obviously less reliable than an

automatic interlock. In the absence of the ‘temperature

interlock fails to shutdown the CSTR’ scenario, a

probability of 5.6 £ 1024 of ‘significant decomposition in

the CSTR’ is obtained, which is much higher than original

3.21 £ 1026 with the temperature interlock, as can been

seen from Figs. 5 and 6. Therefore, the temperature

interlock can improve process safety by two orders of

magnitude in this process.

Likewise, without the quench valve protection, the safety

operation of the distillation tower depends on the alarms and

workers only. Re-evaluating the fault tree, with the

‘automatic protection system fails’ in Fig. 7, we obtain a

probability of 1.81 £ 1024 for sub-event ‘significant

Fig. 6. Partial sub-tree for the event: ‘Temperature interlock fails and operator does not respond to alarm’.


decomposition occurs in the distillation tower’, which again

is higher than the previous value of 9.5 £ 1026 with quench

valve protection.

6. Conclusions

This paper discusses QRA of a generic HA production

plant, integrating the findings of the CSB incident report and

the knowledge of potential HA reactivity hazards from

research at the MKOPSC. Our work shows that HA

production process is inherently highly hazardous. A

layered, highly reliable protection system is required to

ensure a safe operation [29 – 31]. The benefit of a

temperature interlock on the CSTR and automatic quench

valve protection on the distillation tower are quantified and

verified by FTA. Due to the high sensitivity of HA

decomposition to the hydroxyl (OH2) ion, a semi-batch

Fig. 7. Partial sub-tree for the event: ‘Significant decomposition occurs in the distillation tower’.


reactor design, or the development of alternate reaction

mechanisms for the production of HA, is suggested.

Development of a RRI will indicate relative risk

associated with the various parts of the process and help

identify high-risk contributors. This information will help in

developing layers of protection to ensure a safer process.

This paper demonstrates that a very thorough study of the

reactive hazards is required. Existing assessment methods

would have identified the high-risk hazards in the

production process and adopting safeguards would have

helped to reduce the risk in the process.

A better understanding of the chemicals and processes

involved in a chemical plant will ultimately help in

improving chemical process safety.

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http://www.csb.gov

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Hydroxylamine production: will a QRA help you decide?