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The estimation of fugitive gas emissions from hydrogen production by natural gas steam reforming
i n t e r n a t i o n a l j o u r n a l o f h y d r o g e n e n e r g y x x x ( 2 0 1 6 ) 1 e1 0
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The estimation of fugitive gas emissions from hydrogen production by natural gas steam reforming Yousef A. Alhamdani a, Mimi H. Hassim a,*, Rex T.L. Ng b, Markku Hurme c a
Department of Chemical Engineering/Institute of Hydrogen Economy, Universiti Teknologi Malaysia, 81310, UTM, Johor Bahru, Johor, Malaysia b Department of Chemical and Biological Engineering, University of WisconsineMadison, Madison, WI, 53706, USA c Department of Biotechnology and Chemical Technology, Aalto University, P.O. Box 16100, FIN-00076, Aalto, Finland
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abstract
Article history:
In recent years, a significant amount of interest has been directed towards using hydrogen
Received 6 October 2015
as an alternative source of energy to fossil fuel. Even though hydrogen is emission free in
Accepted 11 July 2016
its end use; the production of hydrogen itself requires energy and may cause process
Available online xxx
emissions including fugitive emissions from various sources, mainly the piping equipment and fittings. The emissions, even though not as large as stack emissions, they may still
Keywords:
pose risks to the environment and health especially to the workers within the plant area.
Fugitive emissions
This paper presents the estimation of fugitive emissions from hydrogen production pro-
Natural gas reforming
cess via natural gas steam reforming. Firstly, the natural gas steam reforming process was
Greenhouse gases emissions
simulated before the fugitive emissions of carbon monoxide (CO) and greenhouse gases
Occupational health effects
(GHGs), such as methane (CH4) and carbon dioxide (CO2) in the process were estimated. Then, the consequent global warming potential (GWP) and the associated health risks due to the emissions were evaluated. A comparison of the GHG fugitive emissions with other sources of GHG emissions over the hydrogen production life cycle was also performed. Methane (CH4) recorded the highest rate of fugitive emissions contributing to the greatest GWP. On the other hand, CO2 represented the total stack emissions contributing to 100% of the total GWP. The concentrations of the gases emitted as fugitive emissions (CH4, CO2 and CO) in the process area are below the threshold exposure limit indicating that the plant environment is safe for workers daily exposures to the emitted gases. © 2016 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.
Introduction Hydrogen is a vital energy carrier [1] which can serve as an energy source for domestic and commercial applications by
supplying electricity and heating [2]. For instance, it can be used in various appliances such as hydrogen fuel cells [1], hydrogen fuel cell vehicles [2] and internal combustion engines vehicles [3]. Hydrogen can be produced from either renewable sources or fossil fuels [1,3,4]. However at the
* Corresponding author. Fax: þ60 7 553 6165. E-mail address: [email protected] (M.H. Hassim). http://dx.doi.org/10.1016/j.ijhydene.2016.07.274 0360-3199/© 2016 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved. Please cite this article in press as: Alhamdani YA, et al., The estimation of fugitive gas emissions from hydrogen production by natural gas steam reforming, International Journal of Hydrogen Energy (2016), http://dx.doi.org/10.1016/j.ijhydene.2016.07.274
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moment, fossil fuels (e.g., natural gas and coal) contribute up to 96% of the world's total hydrogen production [5]. Natural gas steam reforming or known as steam methane reforming (SMR) is the most common process for hydrogen production in a large-scale. It involves the heating of methane by steam to extract hydrogen in its elemental form and produces carbon dioxide as a by-product [6]. Currently, 80e85% of world's hydrogen is produced via this technology. The remaining hydrogen production is mostly obtained via coal gasification and water electrolysis [7]. Water electrolysis is the cleanest process for producing hydrogen. However, this technology is yet to be economically competitive with the current state of technologies such as SMR [8,9]. From environmental perspective, hydrogen is considered as one of the most promising solution towards emissions reduction [10]. However, hydrogen requires energy to be produced and, depending on the primary source (e.g., natural gas and coal), it may cause greenhouse gases (GHGs) emissions. GHGs emissions either from stack or fugitive emissions are among the unavoidable issues associated with the hydrogen production from fossil fuels which could indirectly indicate hydrogen as an environmentally unfriendly energy source. For example in SMR case, producing one kg of net hydrogen could result in a global warming potential (GWP) of 13.7 kg carbon dioxide (CO2) equivalent [11]. The production of hydrogen with such burden to the environment shows that SMR process suffers a serious disadvantage in terms of compliance with the environmental policies. In the last two decades, various efforts have been made by both academia and industries to assess the economic aspects [12], exergy and energy balances [12e14] of hydrogen production [15]. However, nowadays the concern has also been raised towards the environmental impacts of hydrogen production [16e19]. Many studies have been conducted to quantify and analyze the environmental impact [19e21] as well as to compare the environmental advantages and drawbacks of hydrogen production by different routes such as fossil fuels, biomass, water electrolysis, wind, hydropower and solar electricity [16,17]. Fugitive emissions, however, were not taken into account; they may eventually pose serious issues (e.g. financial loss, health and environmental impacts) if continuously being neglected. In principle emissions, either intentional (via stack) or unanticipated (fugitive emissions), are inherent to any chemical process. Stack emissions can be defined as flue gases that are produced when any fuel (e.g., natural gas, coal, fuel oil, wood, etc.) is combusted in industrial furnace or boiler, steam generator in fossil fuel power plant or other large combustion device, and exhausted to the atmosphere [22]. Meanwhile fugitive emissions are defined as a chemical, or a mixture of chemicals, in any physical form, which represents an unanticipated or spurious leak in an industrial site [23,24]. Since the amount of stack emissions is large, various efforts have been conducted to control the emissions by different technologies. For instance, CO2 capture and storage technology (CCS) is one of the common solutions to control the CO2 emissions [5]. Scrubbing is another mature available technology for stack emissions control in which scrubbers are injected with absorbents in the form of sprays to capture the
impurities [25]. Adsorption technology is commonly adopted for pre-combustion CO2 removal which can be of several types including pressure swing adsorption (PSA), temperature swing adsorption (TSA) or electrical swing adsorption (ESA). Another example is membrane technology in which selective membranes can be used to separate CO2 from flue gas (postcombustion removal) and CO2 from hydrogen (pre-combustion removal) [26]. Fugitive emissions, on the other hand, cannot be captured by the same emissions control technologies as for stack emissions. Unlike stack emissions, fugitive emissions are not point-source emissions and they are not confined to a specific discharge point [27]. Instead, they occur wherever there is sealing equipment between the process fluid and the surrounding environment, for instance through valves, pumps and flanges [24]. In other cases, these emissions can be generated from unsealed sources such as open-ended lines, storage tanks, vents or pressure relief valves [24]. Approximately more than a million metric tons of chemical materials are emitted per year as fugitive emissions from the industrial activities around the world [28]. In Europe (1996), it was reported that the volatile organic components VOC fugitive emissions contribute to about 17% of the total VOC emissions [24]. This somehow calls for attention to control fugitive emissions since these emissions can impact not only the environment and health conditions, but also could be a cause of financial losses since the emitted materials are potentially valuable [24,28]. Basically fugitive emissions can be controlled based on technical and management approaches. From the technical perspective, innovative and higher technology process (e.g., higee distillation and reactive distillation units) and equipment and fittings (e.g., seal-less valves and canned pumps) can be adopted to tackle this problem. Also the improvement of process operations can be made by installing plugs, caps, and blinds for open-ended lines, enclosure of seal area/vent to a combustion control device as well as operating the process at vacuum condition wherever possible [29,30]. From the management side, the most common and widely used practice is to conduct the leak detection and repair (LDAR) program for monitoring and reducing fugitive emissions in petrochemical industries [29,30]. Besides, the requirement for permit application for new installation in industries has been enforced as highlighted in the Directive 2008/1/EC of the European Parliament and of the Council of 15 January 2008 concerning integrated pollution prevention and control (IPPC) [31]. The directive requires the application to provide a description of the sources, nature and quantities of foreseeable emissions from the industrial activities as well as proposing techniques for monitoring and reducing the emissions [31]. All these efforts are directed towards reducing industrial emissions including fugitive emissions, which are often abandoned because of lack of awareness and limited knowledge concerning the emissions. Before fugitive emissions can be reduced, it is necessary to first identify their sources and quantify them. Generally fugitive emissions can be quantified using four techniques of: (1) direct measurement, (2) mass balance, (3) engineering calculation, and (4) emission factors [28]. In principle, direct
Please cite this article in press as: Alhamdani YA, et al., The estimation of fugitive gas emissions from hydrogen production by natural gas steam reforming, International Journal of Hydrogen Energy (2016), http://dx.doi.org/10.1016/j.ijhydene.2016.07.274
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measurement is applicable to existing processes only. Several works on quantifying fugitive emissions using this technique have been conducted e.g., in a Canadian refinery with substances of interest of methane, C2þ hydrocarbons (i.e., ethane, propane, butane, etc.), and benzene [32,33] as well as the fugitive VOC-emissions in six different Swedish refineries [34]. For a process which is not even yet constructed, the fugitive emissions can be estimated using mass balance technique. However, this technique suffers from low accuracies due to the very small amount of material losses involved in the estimation. Engineering calculation is more accurate but also at the same time becomes more complicated as it usually involves software tools and requires detailed information which is not available at the early stage of process design. The final approach which is the emission factors based method is the most suitable option to be used for estimating fugitive emissions for process conceptual stage because it does not require detailed process information. In 2010, the U.S. Environmental Protection Agency (U.S. EPA) used emission factors technique to estimate the contribution of fugitive emissions from natural gas systems to the U.S. greenhouse gas (GHG) emissions [35]. They further extended the study using the same technique to quantify the fugitive emissions from the transmission pipelines, storage and distribution systems [36e38]. Based on the description of the four techniques above, for this particular study, the emission factor method will be adopted since the process is still in preliminary design stage. Based on the previous studies [11,20], steam reforming of natural gas is regarded as a process with the least CO2 emissions compared to other conventional industrial processes such as coal gasification. Nevertheless, the emissions of CO2 as well as the other greenhouse gases from this process cannot be neglected. Stack emissions from this process technology have been studied [19] but the work on fugitive emissions is still lacking. Generally, several studies have been conducted in relation to estimate fugitive emissions from chemical processes at different stages of process design [28,39,40]. However such work for H2 production processes (e.g., SMR, coal and biomass gasification) has never been attempted before. In this study, a method proposed by Hassim et al. [28] is adopted to estimate the amount of fugitive emissions from the SMR process design stage. Basically, Hassim and her co-workers developed a precalculated fugitive emissions database from typical process modules in chemical processes (e.g., distillation column, absorber, stripper, CSTR, PFR, compressor etc.) [28]. However, some process modules in the SMR process studied in this work are not available in the aforementioned database. Therefore in this work, before estimating the amount of fugitive emissions, the emissions database of new process modules involved in the hydrogen production via SMR process (e.g., adsorber, normal and reforming furnace, pressure swing adsorber (PSA), and tail holding gas tank) were first created based on the approach described by Hassim and others in [28]. Then, the global warming potential (GWP) and health risks as consequential effects of the fugitive emissions of the GHGs (CH4 and CO2) and CO were calculated and discussed. Also, a comparative analysis of the estimated fugitive emissions with stack GHG emissions over the hydrogen production life cycle was conducted.
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Fugitive emissions estimation in chemical process design As mentioned in the previous section, among the available fugitive emissions techniques, the average emission factor is the most suitable to be used in the absence of detailed process information at the early stage of conceptual design [28,41]. Basically, this method only requires the information on the equipment and piping item count and the average of emission factors [28]. Even though this sounds simple, it should be noted that the piping item count data is not available throughout the whole process design lifecycle as the design phase itself comprises of several stages (i.e., conceptual design, preliminary design, basic engineering and detailed design). The earliest where such information is available is at the basic engineering stage, which is from the piping & instrumentation diagram. Therefore, Hassim et al. [28] proposed different approaches for fugitive emissions estimation during different stages of design. The idea is to make use of the information available at that particular stage of assessment and not to demand for data beyond the stage of interest to ensure the practical applicability of the method. For conceptual and preliminary design stages, Hassim et al. [28] established precalculated modules-based methods. The approach enables quick and simple estimation of fugitive emissions without requesting for data on piping item as this is not yet available at these stages. Precalculated modules refer to database of fugitive emission rates established for standard process modules. Here, standard process modules refer to typical process units in chemical processes such as distillation, reactor, flash, etc. [28]. Basically, in both conceptual and preliminary design, information on process modules is already available. But the difference is, in the conceptual stage, only the rough drawing of the process flow (called simple flow diagrams) is available. Meanwhile, in the preliminary design, the process flow sheet diagrams (PFDs) are already generated; thus users also have access to the mass balance data. Such difference, even though looks small, does have significant impact on the result accuracy. Both conceptual and preliminary design share common approaches in the beginning part of the fugitive emissions estimation from the proposed design. Both require the identification of the main streams for each process module (e.g., inlet, top outlet and inlet fuel stream if applicable). Then, the chemical substances present in each module stream are identified before determining the service type of each stream (either gas, light liquid or heavy liquid). In the conceptual design stage, the stream is classified as light liquid service if it primarily contains highly volatile chemicals with atmospheric vapor pressure of more than 0.3 kPa or instead, it is heavy liquid. In preliminary design, if the chemicals with individual vapor pressure above 0.3 kPa (at 20 C) are totalled up to 20 wt% of the total weight composition in that stream, the stream is in a light liquid service; otherwise, it is in a heavy liquid phase. In both stages, the stream's fugitive emissions rate is determined based on the same approach, which is by referring to the emissions database for the type of service determined. The difference is in determining the fugitive emissions rate of each chemical substance in the mixture of
Please cite this article in press as: Alhamdani YA, et al., The estimation of fugitive gas emissions from hydrogen production by natural gas steam reforming, International Journal of Hydrogen Energy (2016), http://dx.doi.org/10.1016/j.ijhydene.2016.07.274
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that particular stream. For conceptual design since the mass balance data is not yet available, the most toxic chemical in the mixture is determined to represent the stream emission rate. Meanwhile for preliminary design stage, with the availability of mass balance data, the emissions rate of each chemical substance is determined by multiplying its weight composition with the stream's fugitive emissions rate. Finally, for both stages, the rates of fugitive emissions for each type of chemical substance in all streams throughout the process are summed up [28] to get the total amount of fugitive emissions for that particular chemical in the evaluated process. For a complete database of precalculated fugitive emission rates for process module stream, it can be referred to the original work of Hassim et al. [28]. In the basic engineering design stage where the P&ID is available, the estimation of fugitive emissions is conducted based on piping equipment data. The detailed piping data available at this stage gives a much accurate estimation of fugitive emissions compared to the earlier two stages. Now, the estimation approach is not anymore based on the stream service type. First, the number (nk) of a certain type of piping component (k) in a process stream is identified and multiplied with the fugitive emissions factor (EFk) of that component. A complete database of fugitive emission factor for piping components is provided for fluids and dust by Hassim et al. [28]. Then, the fugitive emission rates from different piping components in the same process stream are totalled up as given in Eq. (1). Fugitive emissions of a chemical substance (FEi) in that stream are determined by multiplying the total fugitive emissions (FE) with its weight composition (wt.%) Eq. (2). Finally the fugitive emissions rate of each chemical type throughout the process are totalled up [28]. FE ¼
X ðEFk *nk Þ
FEi ¼ FE*wt%
(1)
process, the natural gas feed is compressed from 101.3 to 1013 kPa (K-100) before heated up from 270 to 400 C in (H100) as a preparation for hydrodesulfurization (HDS) process. Hydrogenation reaction takes place in (R-100) to convert sulfur into hydrogen sulfide (H2S). For H2S removal, the feed is sent to an adsorber (C-100). After the pretreatment, the feed is sent to reformer unit (F-100) where reforming reaction takes place between steam and methane. The reforming unit comprises of furnace to directly provide heat for the highly endothermic reaction. The syngas, which is the product of the reforming process, is rich in H2 and CO. The syngas is then transported to the conversion unit which comprises of high (R-101) and low (R-102) temperature shifting reactors. The purpose of these reactions is to convert CO to CO2 and increase the H2 content at 350 C in the high temperature reactor and at 200 C in the low temperature reactor. The shifted syngas is then sent to pressure sewing adsorption unit for purification process to remove unwanted byproducts (CO2, H2O, CH4 and CO). This is to achieve high quality hydrogen production [43]. Due to the availability of the PFD of the SMR process under study, the preliminary design method was adopted to estimate the amount of fugitive emissions throughout the process. The calculation was done based on the precalculated modules emissions database established by Hassim et al. [28]. As illustrated in Fig. 1, the SMR process in this case study also has several process modules which are not covered in the existing emissions database [28] i.e., normal and reformer furnace, adsorber, tail gas holding tank and pressure swing adsorber (PSA). Therefore, prior to the estimation of GHGs and CO fugitive emissions, a database of the precalculated fugitive emission rates for those new modules was established in this work. In this case study, the PSA is an operation unit which consists of six adsorbers on operation mode and another six adsorbers in regeneration mode.
(2)
Development of precalculated fugitive emissions database
Case study e hydrogen production via steam methane reforming Steam methane reforming (SMR) is among the most common and mature technologies for hydrogen production. Generally, it comprises of two main reactions. Reforming reaction is highly endothermic in which methane reacts with pure water in steam form to produce hydrogen. CH4 þ H2 OðgÞ/CO þ 3H2
(3)
Water-gas shift reaction is moderately exothermic; it typically takes place in water-gas-shift reactor where carbon monoxide CO (a byproduct from the reforming reaction) is converted into carbon dioxide to enhance the hydrogen production [8,42]. CO þ H2 OðgÞ/CO2 þ 3H2
(4)
Fig. 1 is a PFD for a simulated SMR plant with a capacity of 10,000 kmol/h of hydrogen. The process is basically comprised of four main operations of the pretreatment, reforming, shifting and purification. In the pretreatment
Among the main contributions of this work is establishing a database of fugitive emission rates for those process modules employed in the SMR process but not in the existing database by Hassim et al. [28]. The average emission factors approach was utilized to calculate the emission rates for these modules. The emission rate data were calculated for different fluid services (gas/light liquid/heavy liquid) of each module stream. This was obtained based on the number of equipment (flanges, valves … etc.) in each module stream and the corresponding service emission factor provided by EPA, 1988. Table 1 summarizes the precalculated fugitive emission rate for each main stream of the process modules. Fig. 2 shows the diagrams of the five process modules with the streams locations. These diagrams are to be used together with Table 1 in defining the streams labeling. The database was created by analyzing the number of potential leak points in each new process modules [28]. The typical P&IDs for the process modules were collected from literature to identify and count the number of the leaking points from piping equipment and fittings. This is done stream by stream since different streams in a process module could be of the same or different type of fluid service; gas/
Please cite this article in press as: Alhamdani YA, et al., The estimation of fugitive gas emissions from hydrogen production by natural gas steam reforming, International Journal of Hydrogen Energy (2016), http://dx.doi.org/10.1016/j.ijhydene.2016.07.274
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Pre-treatment
Reforming Steam H2O
3
R-100 E-100
1
K-100
2
5
C-100
H-100
K-101
F-100
7
6
4 Fuel
8 PSA System Purification
Shifting
10
R-101
E-102
R-102
E-101
12 C-101
11
9
H2
C-102
C-103
C-104
C-105
C-106
13
T-100
14
Fig. 1 e Process flow diagram for the simulated SMR Process.
Table 1 e Database of precalculated fugitive emission rates for process module stream. Process module (fugitive emission rate, kg/h) Stream Inlet
Outlet
Fuel
Service
Adsorber
Normal furnace
Reforming furnace
PSA
Tail gas holding tank
G/V LL HL G/V LL HL G/V LL HL
0.33724 0.31784 0.27984 0.33724 0.31784 0.27984 N/A N/A N/A
0.03987 0.03405 0.02265 0.14387 N/A N/A 0.17007 0.14097 0.08397
0.09996 0.08056 0.04256 0.48902 N/A N/A 0.20582 0.17136 0.10296
0.0573 0.0476 0.0286 0.0573 0.0476 0.0286 N/A N/A N/A
0.14753 0.14171 0.13031 0.14753 0.14171 0.13031 N/A N/A N/A
G/V: Gas/Vapor, LL: Light Liquid, HL: Heavy Liquid.
vapor, light liquid, and heavy liquid. Based on the average emission factors provided by the U.S. EPA (1988) [44], the total emissions from each stream was calculated for all possible service types [28].
Estimation of fugitive emissions from the hydrogen plant case study After establishing the emissions database (Table 1 and Fig. 2), the amount of fugitive emissions from the studied SMR case study was estimated. As mentioned earlier in this section, the preliminary design method was adopted to conduct the estimation due to the availability of information on the process units and mass balances from the PFD of the case study. First, the PFD of the SMR process was divided into the standard modules before the chemicals present in each module stream were identified. The SMR process is operating in gas phase and therefore all the streams in this process were calculated with
the emissions value of gas/vapour service type. Basically the emission value given in the database is the stream's fugitive emissions rate (FEr), which represents the emissions of all chemicals in the mixture contained in the stream. Therefore for calculating the fugitive emission of a specific chemical substance, the FEr value needs to be multiplied with the weight composition (wt.%) of that specific chemical substance in that particular stream (Eq. (5)). Finally, the emission values of the same chemical substance (FEi) from different streams throughout the process are summed up to get its total emissions. This applies to all chemical substances present in the process. It should be noted that the air stream to the furnace (H-100) and steam stream to the reformer (F-100) (see Fig. 1) were not considered in the fugitive emissions calculation since the chemical substances included represent no harm to both environment and workers' health. Fig. 3 summarizes the step-by-step procedures for fugitive emissions estimation from the SMR process [28].
Please cite this article in press as: Alhamdani YA, et al., The estimation of fugitive gas emissions from hydrogen production by natural gas steam reforming, International Journal of Hydrogen Energy (2016), http://dx.doi.org/10.1016/j.ijhydene.2016.07.274
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Outlet
Inlet
Adsorber
Inlet
Outlet
Inlet
Outlet
Fuel
Fuel Reforming Furnace
Normal Furnace
Inlet Inlet
Outlet
Outlet Tail Gas Holding Tank
PSA
Fig. 2 e Process module diagram for defining stream presented in Table 1.
Dividing SMR process into standard modules
Identify chemical present in each module stream * SMR process is running in gas phase. Hence all module streams are calculated as gas/vapor service type.
* Determining stream type of service
Determining stream’s emissions rate from Table 1 * Multiply the stream emissions rate with the respective chemical weight composition.
* Determining fugitive emissions rate for each chemical, FEi
Summing up the FEi of the same chemical throughout the SMR process
Fig. 3 e Flowchart of fugitive emissions calculation for SMR process based on the preliminary design method [28].
FEi ¼ FEr *wt%
(5)
In this study, the substances of interest are the greenhouse gases (CH4 and CO2) and CO due to their possibility to cause global warming and adverse health impacts. Table 2 presents the fugitive emissions estimate of these substances. The total emissions for CH4, CO2 and CO are 1117.55 mg/s, 864.16 mg/s, and 163.05 mg/s, respectively. Mind that the process module listed in the first column of the table is arranged top-down according to the process flow in the PFD (i.e. starting from
the compressor and ends up with the gas holding tank). The table shows that the CH4 emissions decrease as it passes through the process modules starting from the pretreatment process (244.44 mg/s in compressor K-100) to the purification process (7.33 mg/s in tail holding gas T-100). Conversely, the fugitive emissions of CO2 increase from 7.44 mg/s at the pretreatment process to 47.77 mg/s in the tail holding gas (T-100). The highest emissions of CO are attributed to the reforming process (37.50 mg/s) while its lowest emissions are from the storage part (6.55 mg/s). The reason is that; CH4 represents 94% of the feed composition hence justifying its higher
Please cite this article in press as: Alhamdani YA, et al., The estimation of fugitive gas emissions from hydrogen production by natural gas steam reforming, International Journal of Hydrogen Energy (2016), http://dx.doi.org/10.1016/j.ijhydene.2016.07.274
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Table 2 e Fugitive emission rates of GHGs and CO from the SMR process. Fugitive emissions (mg/s) Process module Compressor (K-100) Furnace (H-100) Reactor (R-100) Adsorber (C-100) Compressor (K-101) Heat Exchanger (E-100) Reformer Furnace (F-100) Reactor (R-101) Heat Exchanger (E-100) Reactor (R-102) Heat Exchanger (E-101) Pressure Swing Adsorber (C-101) e (C-106) Holding Gas Tank (T-100) Total
CH4
CO2
CO
244.44 96.66 59.72 181.66 244.72 88.83 70.55 3.438 5.083 3.43 5.08 105.83
7.44 1.38 1.80 5.52 7.22 2.69 1.05 14.19 28.50 21.55 33.27 691.11
e e e e e e 37.50 8.30 7.61 3.61 4.55 94.72
7.33 1117.55
47.77 864.16
6.55 163.05
emissions value in the early part of the process. Later in the process as the CH4 is converted into CO and H2 during the reforming, CH4 emissions decrease. The CO emissions increase until the point where it is converted into CO2 during the shifting process to enhance H2 production, hence explaining the phenomena of CO2 increasing emissions towards the end part of the whole process.
Estimation of global warming potential In this sub-section, the global warming potential (GWP) as a result of the GHGs fugitive emissions is calculated. GWP is the contribution of the GHGs to the warming of the atmosphere. In general, the capacity of CH4 contribution to global warming is 21 times higher than that of CO2 for a 100 year time [19]. As for this case study, total fugitive emissions of CH4 are 1117.55 mg/s (4.023 kg/h) compared to CO2 with amount of 864.16 mg/s (3.11 kg/h) of fugitive emissions. Given that the H2 production capacity of the SMR plant is 10,000 kmol/h (20,150 kg/h), the amount of CH4 and CO2 fugitive emissions are 0.198 g and 0.153 g, respectively, per each kg of net hydrogen produced (see Table 3).
Estimation of the health risk associated with the emitted gases In order to calculate the health risk to workers as a result of the exposure to the fugitive emissions of CH4, CO2 and CO, the concentration of these substances in the process air environment need to first be calculated. This can be done based on the approach developed by Hassim et al. [28]. Basically they proposed that the airborne concentration due to fugitive emissions (commonly expressed in term of mass rate) can be calculated by dividing the fugitive emissions rate by the air
volumetric flow rate within the process area. The air volumetric flow rate, V is calculated from the equation below: V m3 s ¼ dðmÞ*vðm=sÞ*hðmÞ
(6)
where d is the edge width of the process area that corresponds to the wind direction, v is the wind speed and h is the height of the plant. Since the estimation is still in the preliminary design stage and not much information is already available on the plant's layout, actual area, geographical location etc., Hassim et al. [28] proposed a simple yet reliable approach to obtain the values for all these parameters. The d value can be estimated based on the typical floor area of the process modules (the database for the floor areas is presented in [28]) by assuming that the plant has a square shape, so that the width can be calculated as the square root of the total floor area of the whole process. Upon the availability of more detailed information on the process, such data should be used instead (e.g. process plot plan). For this SMR case study, the d value is 172 m based on the size of a typical hydrogen plant from the literature [45]. The height of the plant is also difficult to determine since the plant is outdoor facility. Therefore an assumption of 7 m is assumed and is considered acceptable since this is the maximum height where piping component/ fitting is located and at which the emissions can still have effect on the workers exposure [46]. As for the wind speed, the typical value of 4 m/s for outdoor facility can be used [47]. By applying Eq. (6), the air volumetric flow rate (V) calculated for the SMR case study is 4816 m3/s. This gives the concentration estimates for CH4, CO2 and CO as follows: 0.232 mg/m3 (0.353 ppm), 0.180 mg/m3 (0.100 ppm) and 0.0338 mg/m3 (0.0295 ppm), respectively. To calculate the health risk, the concentration of each gas was then compared against its threshold exposure limit, EL (see Table 4). The resulted risk value shows that the risk is acceptable for all the three substances since theoretically the workers are exposed to those gases at concentration below the exposure limits.
Comparison of GHG fugitive emissions vs GHG stack emissions In this section, the fugitive emissions of GHGs are compared to those from the stack as well as their associated contribution to the global warming potential. The data for the life cycle and stack emissions of H2 production via SMR were extracted from a study conducted by the National Renewable Energy Laboratory in the US (NREL) as summarized in Table 5 [19]. These data were used to compare the estimated GHG fugitive emissions with the GHG stack emissions calculated by NREL (refer to Table 6). Besides, the same data also were used to compare the total GHG emissions (fugitive and stack) from the whole life cycle of hydrogen production with the total GHG emissions from the hydrogen plant alone (Table 7). The study by
Table 3 e Global warming potential due to GHG fugitive emissions. GHGs Emission (g/kg of H2) Percent of GHGs (%) GWP relative to CO2 GWP (g CO2-equivalent/kg of H2) Contribution to GWP (%) CO2 CH4
0.153 0.198
43.59 56.41
1 21
0.153 4.16
3.56 96.44
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Table 4 e Health risk calculation for the SMR process. Emitted gases CH4 CO2 CO
FEs rate (mg/s) 1117.55 864.16 163
Concentration, mg/ EL, mg/m3 Health risk for individual (ppm) substances m3 (ppm) 0.232 (0.353) 0.180 (0.1) 0.0338 (0.0295)
3.5 104 < 1 0.2 104 < 1 1.16 103 < 1
656.442 (1000) 9000 (5000) 29 (25)
Health risk for the chemicals mixture 0.353/1000 þ 0.1/5000 þ 0.029/25 ¼ 1.5 103 < 1
Table 5 e The lifecycle and stack GHGs emissions and their associated GWP [19]. GHGs
Emissions (g/kg of H2)
CO2 a CH4 a
Percent of GHGs (%) GWP relative to CO2
10,621 60
99.4 0.6
GWP (g CO2-equivalent/kg of H2)
Contribution to GWP (%)
10,621 1256
89.3 10.6
1 21
Emissions value for CH4 does not represent its emissions from the stack.
Table 6 e Overall fugitive and stack GHG emissions from the Hydrogen Production Plant. Emissions
Fugitive emissions (calculated)
Plant stack emissions [19]
Total emissions (fugitive & stack)
GHGs
CH4
CO2
CH4
CO2
CH4
CO2
Emissions g/kg of H2 Emissions in% GWP relative to CO2 GWP (g CO2-equivalent/kg of H2) Contribution to GWP (%)
0.198 56.41 21 4.16 96.44
0.153 43.59 1 0.153 3.552
0 0 21 0 0
8889.44 100 1 8889.44 100
0.198 0.0022 21 4.158 0.045
8889.59 99.998 1 8889.59 99.95
NREL reported that the amount of CO2 and CH4 emitted are 10,621 and 60 (g/kg of H2), accounting for 99.4% and 0.6% of the total emissions from the H2 production life cycle. These emissions contribute to 89.3% and 10.6% of the GWP, respectively. Another interesting finding from the study is, the vast majority of the CO2 (8889.44 g/kg of H2) is released from the hydrogen plant alone (from the stack), contributing to 83.7% of the overall GWP attributed by the total amount of CO2 emitted throughout the H2 production life cycle. On the other hand, CH4 makes no contributions to the stack emissions (refer to Tables 6 and 7) [19]. The comparison between the fugitive and stack emissions is summarised in Table 6. The fugitive-emitted greenhouse gases may not amount as much in comparison to stack GHG emissions; but still the former one may cause an increase in the GHG load. The results demonstrate that with regards to fugitive emissions, CH4 is the main GHG component emitted from the H2 plant accounting for 56.41% and responsible for 96.44% of the total GWP. Meanwhile CO2 accounts for 43.6% of GHGs contributing to 3.56% of the total GWP. In contrary, CH4 makes no contribution to the plant emissions via stack whereas CO2 represents the total GHG emissions contributing to 100% of the total GWP (Table 6). The justification for this
outcome is that CH4 is highly converted into H2 and CO during the reforming process. In turn, CO is converted by steam into H2 and CO2 during high and low temperature shifting process (HTS & LTS). Owing to that, the composition of the off gas mainly consists of CO2, which presents the greatest contributor to the amount of stack GHG emissions. The overall plant GHG emissions of the overall plant (fugitive and stack emissions) mainly comprise of CO2 which accounts for 99.99% of the total plant emissions and contributes to 99.95% of the total GWP. Methane (CH4), which is only attributed to the fugitive emissions, represents only a minor quantity accounting for 0.002% of the plant emissions and contributing to 0.045% of the total GWP (Table 6). It is evident that hydrogen production plant makes a major contribution to the environmental burdens by emitting 83.7% of the total CO2 emitted through the lifecycle of H2 production. In methane case, the contribution of the plant is, however, limited by emitting 0.33% of the total CH4 emitted through the lifecycle system. Owing to that, H2 plant alone contributes to 83.7% of the total GWP attributed to the lifecycle system starting from natural gas extraction from the well to the production of high purity hydrogen at the plant (Table 7).
Table 7 e Greenhouse gases emissions, Lifecycle system vs. H2 plant (fugitive and stack). GHGs CO2 CH4
Emissions (g/kg of H2) LC
Emissions (g/kg of H2) P
Emissions LC
Emissions P
GWP LC
GWP P
10,621 60
8889.6 (S þ F) 0.198 (F)
99.4% 0.6%
83.7% 0.33%
89.3% 10.6%
83.7% 0.33%
LC: Life Cycle P: Plant S: Stack F: Fugitive.
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Conclusion In this paper, the amount of fugitive emissions of GHGs (CH4 and CO2) and CO from steam methane reforming (SMR) processes were estimated using precalculated modules approach. Such study has never been attempted before since previously, all works related to emissions assessment in this nature of processes were focusing on stack emissions only as the source of process losses. The estimation was done using an existing precalculated modules-based approach, which provides a database of fugitive emission rates for standard process modules. The database allows quick and easy estimation of fugitive emissions to be performed based on a limited process data during the early stage of design. Since the emissions data for several process modules constituted in the SMR process is not available, the precalculated emissions database for those modules was developed prior to the emissions estimation. In this study, the amount of GHGs fugitive emissions and the corresponding global warming potential (GWP) are mainly attributed to methane (CH4) emissions whereas the GHGs stack emissions and consequential GWP are completely attributed to carbon dioxide (CO2) emissions. Since the GHGs emitted from the stack are far larger than the GHGs fugitive emissions, it becomes evident that the largest amount of GHGs emitted from the plant (fugitive and stack) is attributed to CO2 emissions and so is the GWP. It is also believed that the concentrations of GHGs fugitive emissions (CH4, CO2) and CO in the breathable zone do not exceed the threshold exposure limit value. The outdoor SMR process plant allows well-ventilated workplace and hence the plant is considered as a safe workplace to workers from an occupational health point of view. In the future work, fugitive emissions from different process routes for H2 production can be estimated and the comparison of all alternatives can be conducted.
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The estimation of fugitive gas emissions from hydrogen production by natural gas steam reforming Yousef A. Alhamdani a, Mimi H. Hassim a,*, Rex T.L. Ng b, Markku Hurme c a
Department of Chemical Engineering/Institute of Hydrogen Economy, Universiti Teknologi Malaysia, 81310, UTM, Johor Bahru, Johor, Malaysia b Department of Chemical and Biological Engineering, University of WisconsineMadison, Madison, WI, 53706, USA c Department of Biotechnology and Chemical Technology, Aalto University, P.O. Box 16100, FIN-00076, Aalto, Finland
article info
abstract
Article history:
In recent years, a significant amount of interest has been directed towards using hydrogen
Received 6 October 2015
as an alternative source of energy to fossil fuel. Even though hydrogen is emission free in
Accepted 11 July 2016
its end use; the production of hydrogen itself requires energy and may cause process
Available online xxx
emissions including fugitive emissions from various sources, mainly the piping equipment and fittings. The emissions, even though not as large as stack emissions, they may still
Keywords:
pose risks to the environment and health especially to the workers within the plant area.
Fugitive emissions
This paper presents the estimation of fugitive emissions from hydrogen production pro-
Natural gas reforming
cess via natural gas steam reforming. Firstly, the natural gas steam reforming process was
Greenhouse gases emissions
simulated before the fugitive emissions of carbon monoxide (CO) and greenhouse gases
Occupational health effects
(GHGs), such as methane (CH4) and carbon dioxide (CO2) in the process were estimated. Then, the consequent global warming potential (GWP) and the associated health risks due to the emissions were evaluated. A comparison of the GHG fugitive emissions with other sources of GHG emissions over the hydrogen production life cycle was also performed. Methane (CH4) recorded the highest rate of fugitive emissions contributing to the greatest GWP. On the other hand, CO2 represented the total stack emissions contributing to 100% of the total GWP. The concentrations of the gases emitted as fugitive emissions (CH4, CO2 and CO) in the process area are below the threshold exposure limit indicating that the plant environment is safe for workers daily exposures to the emitted gases. © 2016 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.
Introduction Hydrogen is a vital energy carrier [1] which can serve as an energy source for domestic and commercial applications by
supplying electricity and heating [2]. For instance, it can be used in various appliances such as hydrogen fuel cells [1], hydrogen fuel cell vehicles [2] and internal combustion engines vehicles [3]. Hydrogen can be produced from either renewable sources or fossil fuels [1,3,4]. However at the
* Corresponding author. Fax: þ60 7 553 6165. E-mail address: [email protected] (M.H. Hassim). http://dx.doi.org/10.1016/j.ijhydene.2016.07.274 0360-3199/© 2016 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved. Please cite this article in press as: Alhamdani YA, et al., The estimation of fugitive gas emissions from hydrogen production by natural gas steam reforming, International Journal of Hydrogen Energy (2016), http://dx.doi.org/10.1016/j.ijhydene.2016.07.274
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moment, fossil fuels (e.g., natural gas and coal) contribute up to 96% of the world's total hydrogen production [5]. Natural gas steam reforming or known as steam methane reforming (SMR) is the most common process for hydrogen production in a large-scale. It involves the heating of methane by steam to extract hydrogen in its elemental form and produces carbon dioxide as a by-product [6]. Currently, 80e85% of world's hydrogen is produced via this technology. The remaining hydrogen production is mostly obtained via coal gasification and water electrolysis [7]. Water electrolysis is the cleanest process for producing hydrogen. However, this technology is yet to be economically competitive with the current state of technologies such as SMR [8,9]. From environmental perspective, hydrogen is considered as one of the most promising solution towards emissions reduction [10]. However, hydrogen requires energy to be produced and, depending on the primary source (e.g., natural gas and coal), it may cause greenhouse gases (GHGs) emissions. GHGs emissions either from stack or fugitive emissions are among the unavoidable issues associated with the hydrogen production from fossil fuels which could indirectly indicate hydrogen as an environmentally unfriendly energy source. For example in SMR case, producing one kg of net hydrogen could result in a global warming potential (GWP) of 13.7 kg carbon dioxide (CO2) equivalent [11]. The production of hydrogen with such burden to the environment shows that SMR process suffers a serious disadvantage in terms of compliance with the environmental policies. In the last two decades, various efforts have been made by both academia and industries to assess the economic aspects [12], exergy and energy balances [12e14] of hydrogen production [15]. However, nowadays the concern has also been raised towards the environmental impacts of hydrogen production [16e19]. Many studies have been conducted to quantify and analyze the environmental impact [19e21] as well as to compare the environmental advantages and drawbacks of hydrogen production by different routes such as fossil fuels, biomass, water electrolysis, wind, hydropower and solar electricity [16,17]. Fugitive emissions, however, were not taken into account; they may eventually pose serious issues (e.g. financial loss, health and environmental impacts) if continuously being neglected. In principle emissions, either intentional (via stack) or unanticipated (fugitive emissions), are inherent to any chemical process. Stack emissions can be defined as flue gases that are produced when any fuel (e.g., natural gas, coal, fuel oil, wood, etc.) is combusted in industrial furnace or boiler, steam generator in fossil fuel power plant or other large combustion device, and exhausted to the atmosphere [22]. Meanwhile fugitive emissions are defined as a chemical, or a mixture of chemicals, in any physical form, which represents an unanticipated or spurious leak in an industrial site [23,24]. Since the amount of stack emissions is large, various efforts have been conducted to control the emissions by different technologies. For instance, CO2 capture and storage technology (CCS) is one of the common solutions to control the CO2 emissions [5]. Scrubbing is another mature available technology for stack emissions control in which scrubbers are injected with absorbents in the form of sprays to capture the
impurities [25]. Adsorption technology is commonly adopted for pre-combustion CO2 removal which can be of several types including pressure swing adsorption (PSA), temperature swing adsorption (TSA) or electrical swing adsorption (ESA). Another example is membrane technology in which selective membranes can be used to separate CO2 from flue gas (postcombustion removal) and CO2 from hydrogen (pre-combustion removal) [26]. Fugitive emissions, on the other hand, cannot be captured by the same emissions control technologies as for stack emissions. Unlike stack emissions, fugitive emissions are not point-source emissions and they are not confined to a specific discharge point [27]. Instead, they occur wherever there is sealing equipment between the process fluid and the surrounding environment, for instance through valves, pumps and flanges [24]. In other cases, these emissions can be generated from unsealed sources such as open-ended lines, storage tanks, vents or pressure relief valves [24]. Approximately more than a million metric tons of chemical materials are emitted per year as fugitive emissions from the industrial activities around the world [28]. In Europe (1996), it was reported that the volatile organic components VOC fugitive emissions contribute to about 17% of the total VOC emissions [24]. This somehow calls for attention to control fugitive emissions since these emissions can impact not only the environment and health conditions, but also could be a cause of financial losses since the emitted materials are potentially valuable [24,28]. Basically fugitive emissions can be controlled based on technical and management approaches. From the technical perspective, innovative and higher technology process (e.g., higee distillation and reactive distillation units) and equipment and fittings (e.g., seal-less valves and canned pumps) can be adopted to tackle this problem. Also the improvement of process operations can be made by installing plugs, caps, and blinds for open-ended lines, enclosure of seal area/vent to a combustion control device as well as operating the process at vacuum condition wherever possible [29,30]. From the management side, the most common and widely used practice is to conduct the leak detection and repair (LDAR) program for monitoring and reducing fugitive emissions in petrochemical industries [29,30]. Besides, the requirement for permit application for new installation in industries has been enforced as highlighted in the Directive 2008/1/EC of the European Parliament and of the Council of 15 January 2008 concerning integrated pollution prevention and control (IPPC) [31]. The directive requires the application to provide a description of the sources, nature and quantities of foreseeable emissions from the industrial activities as well as proposing techniques for monitoring and reducing the emissions [31]. All these efforts are directed towards reducing industrial emissions including fugitive emissions, which are often abandoned because of lack of awareness and limited knowledge concerning the emissions. Before fugitive emissions can be reduced, it is necessary to first identify their sources and quantify them. Generally fugitive emissions can be quantified using four techniques of: (1) direct measurement, (2) mass balance, (3) engineering calculation, and (4) emission factors [28]. In principle, direct
Please cite this article in press as: Alhamdani YA, et al., The estimation of fugitive gas emissions from hydrogen production by natural gas steam reforming, International Journal of Hydrogen Energy (2016), http://dx.doi.org/10.1016/j.ijhydene.2016.07.274
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measurement is applicable to existing processes only. Several works on quantifying fugitive emissions using this technique have been conducted e.g., in a Canadian refinery with substances of interest of methane, C2þ hydrocarbons (i.e., ethane, propane, butane, etc.), and benzene [32,33] as well as the fugitive VOC-emissions in six different Swedish refineries [34]. For a process which is not even yet constructed, the fugitive emissions can be estimated using mass balance technique. However, this technique suffers from low accuracies due to the very small amount of material losses involved in the estimation. Engineering calculation is more accurate but also at the same time becomes more complicated as it usually involves software tools and requires detailed information which is not available at the early stage of process design. The final approach which is the emission factors based method is the most suitable option to be used for estimating fugitive emissions for process conceptual stage because it does not require detailed process information. In 2010, the U.S. Environmental Protection Agency (U.S. EPA) used emission factors technique to estimate the contribution of fugitive emissions from natural gas systems to the U.S. greenhouse gas (GHG) emissions [35]. They further extended the study using the same technique to quantify the fugitive emissions from the transmission pipelines, storage and distribution systems [36e38]. Based on the description of the four techniques above, for this particular study, the emission factor method will be adopted since the process is still in preliminary design stage. Based on the previous studies [11,20], steam reforming of natural gas is regarded as a process with the least CO2 emissions compared to other conventional industrial processes such as coal gasification. Nevertheless, the emissions of CO2 as well as the other greenhouse gases from this process cannot be neglected. Stack emissions from this process technology have been studied [19] but the work on fugitive emissions is still lacking. Generally, several studies have been conducted in relation to estimate fugitive emissions from chemical processes at different stages of process design [28,39,40]. However such work for H2 production processes (e.g., SMR, coal and biomass gasification) has never been attempted before. In this study, a method proposed by Hassim et al. [28] is adopted to estimate the amount of fugitive emissions from the SMR process design stage. Basically, Hassim and her co-workers developed a precalculated fugitive emissions database from typical process modules in chemical processes (e.g., distillation column, absorber, stripper, CSTR, PFR, compressor etc.) [28]. However, some process modules in the SMR process studied in this work are not available in the aforementioned database. Therefore in this work, before estimating the amount of fugitive emissions, the emissions database of new process modules involved in the hydrogen production via SMR process (e.g., adsorber, normal and reforming furnace, pressure swing adsorber (PSA), and tail holding gas tank) were first created based on the approach described by Hassim and others in [28]. Then, the global warming potential (GWP) and health risks as consequential effects of the fugitive emissions of the GHGs (CH4 and CO2) and CO were calculated and discussed. Also, a comparative analysis of the estimated fugitive emissions with stack GHG emissions over the hydrogen production life cycle was conducted.
3
Fugitive emissions estimation in chemical process design As mentioned in the previous section, among the available fugitive emissions techniques, the average emission factor is the most suitable to be used in the absence of detailed process information at the early stage of conceptual design [28,41]. Basically, this method only requires the information on the equipment and piping item count and the average of emission factors [28]. Even though this sounds simple, it should be noted that the piping item count data is not available throughout the whole process design lifecycle as the design phase itself comprises of several stages (i.e., conceptual design, preliminary design, basic engineering and detailed design). The earliest where such information is available is at the basic engineering stage, which is from the piping & instrumentation diagram. Therefore, Hassim et al. [28] proposed different approaches for fugitive emissions estimation during different stages of design. The idea is to make use of the information available at that particular stage of assessment and not to demand for data beyond the stage of interest to ensure the practical applicability of the method. For conceptual and preliminary design stages, Hassim et al. [28] established precalculated modules-based methods. The approach enables quick and simple estimation of fugitive emissions without requesting for data on piping item as this is not yet available at these stages. Precalculated modules refer to database of fugitive emission rates established for standard process modules. Here, standard process modules refer to typical process units in chemical processes such as distillation, reactor, flash, etc. [28]. Basically, in both conceptual and preliminary design, information on process modules is already available. But the difference is, in the conceptual stage, only the rough drawing of the process flow (called simple flow diagrams) is available. Meanwhile, in the preliminary design, the process flow sheet diagrams (PFDs) are already generated; thus users also have access to the mass balance data. Such difference, even though looks small, does have significant impact on the result accuracy. Both conceptual and preliminary design share common approaches in the beginning part of the fugitive emissions estimation from the proposed design. Both require the identification of the main streams for each process module (e.g., inlet, top outlet and inlet fuel stream if applicable). Then, the chemical substances present in each module stream are identified before determining the service type of each stream (either gas, light liquid or heavy liquid). In the conceptual design stage, the stream is classified as light liquid service if it primarily contains highly volatile chemicals with atmospheric vapor pressure of more than 0.3 kPa or instead, it is heavy liquid. In preliminary design, if the chemicals with individual vapor pressure above 0.3 kPa (at 20 C) are totalled up to 20 wt% of the total weight composition in that stream, the stream is in a light liquid service; otherwise, it is in a heavy liquid phase. In both stages, the stream's fugitive emissions rate is determined based on the same approach, which is by referring to the emissions database for the type of service determined. The difference is in determining the fugitive emissions rate of each chemical substance in the mixture of
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that particular stream. For conceptual design since the mass balance data is not yet available, the most toxic chemical in the mixture is determined to represent the stream emission rate. Meanwhile for preliminary design stage, with the availability of mass balance data, the emissions rate of each chemical substance is determined by multiplying its weight composition with the stream's fugitive emissions rate. Finally, for both stages, the rates of fugitive emissions for each type of chemical substance in all streams throughout the process are summed up [28] to get the total amount of fugitive emissions for that particular chemical in the evaluated process. For a complete database of precalculated fugitive emission rates for process module stream, it can be referred to the original work of Hassim et al. [28]. In the basic engineering design stage where the P&ID is available, the estimation of fugitive emissions is conducted based on piping equipment data. The detailed piping data available at this stage gives a much accurate estimation of fugitive emissions compared to the earlier two stages. Now, the estimation approach is not anymore based on the stream service type. First, the number (nk) of a certain type of piping component (k) in a process stream is identified and multiplied with the fugitive emissions factor (EFk) of that component. A complete database of fugitive emission factor for piping components is provided for fluids and dust by Hassim et al. [28]. Then, the fugitive emission rates from different piping components in the same process stream are totalled up as given in Eq. (1). Fugitive emissions of a chemical substance (FEi) in that stream are determined by multiplying the total fugitive emissions (FE) with its weight composition (wt.%) Eq. (2). Finally the fugitive emissions rate of each chemical type throughout the process are totalled up [28]. FE ¼
X ðEFk *nk Þ
FEi ¼ FE*wt%
(1)
process, the natural gas feed is compressed from 101.3 to 1013 kPa (K-100) before heated up from 270 to 400 C in (H100) as a preparation for hydrodesulfurization (HDS) process. Hydrogenation reaction takes place in (R-100) to convert sulfur into hydrogen sulfide (H2S). For H2S removal, the feed is sent to an adsorber (C-100). After the pretreatment, the feed is sent to reformer unit (F-100) where reforming reaction takes place between steam and methane. The reforming unit comprises of furnace to directly provide heat for the highly endothermic reaction. The syngas, which is the product of the reforming process, is rich in H2 and CO. The syngas is then transported to the conversion unit which comprises of high (R-101) and low (R-102) temperature shifting reactors. The purpose of these reactions is to convert CO to CO2 and increase the H2 content at 350 C in the high temperature reactor and at 200 C in the low temperature reactor. The shifted syngas is then sent to pressure sewing adsorption unit for purification process to remove unwanted byproducts (CO2, H2O, CH4 and CO). This is to achieve high quality hydrogen production [43]. Due to the availability of the PFD of the SMR process under study, the preliminary design method was adopted to estimate the amount of fugitive emissions throughout the process. The calculation was done based on the precalculated modules emissions database established by Hassim et al. [28]. As illustrated in Fig. 1, the SMR process in this case study also has several process modules which are not covered in the existing emissions database [28] i.e., normal and reformer furnace, adsorber, tail gas holding tank and pressure swing adsorber (PSA). Therefore, prior to the estimation of GHGs and CO fugitive emissions, a database of the precalculated fugitive emission rates for those new modules was established in this work. In this case study, the PSA is an operation unit which consists of six adsorbers on operation mode and another six adsorbers in regeneration mode.
(2)
Development of precalculated fugitive emissions database
Case study e hydrogen production via steam methane reforming Steam methane reforming (SMR) is among the most common and mature technologies for hydrogen production. Generally, it comprises of two main reactions. Reforming reaction is highly endothermic in which methane reacts with pure water in steam form to produce hydrogen. CH4 þ H2 OðgÞ/CO þ 3H2
(3)
Water-gas shift reaction is moderately exothermic; it typically takes place in water-gas-shift reactor where carbon monoxide CO (a byproduct from the reforming reaction) is converted into carbon dioxide to enhance the hydrogen production [8,42]. CO þ H2 OðgÞ/CO2 þ 3H2
(4)
Fig. 1 is a PFD for a simulated SMR plant with a capacity of 10,000 kmol/h of hydrogen. The process is basically comprised of four main operations of the pretreatment, reforming, shifting and purification. In the pretreatment
Among the main contributions of this work is establishing a database of fugitive emission rates for those process modules employed in the SMR process but not in the existing database by Hassim et al. [28]. The average emission factors approach was utilized to calculate the emission rates for these modules. The emission rate data were calculated for different fluid services (gas/light liquid/heavy liquid) of each module stream. This was obtained based on the number of equipment (flanges, valves … etc.) in each module stream and the corresponding service emission factor provided by EPA, 1988. Table 1 summarizes the precalculated fugitive emission rate for each main stream of the process modules. Fig. 2 shows the diagrams of the five process modules with the streams locations. These diagrams are to be used together with Table 1 in defining the streams labeling. The database was created by analyzing the number of potential leak points in each new process modules [28]. The typical P&IDs for the process modules were collected from literature to identify and count the number of the leaking points from piping equipment and fittings. This is done stream by stream since different streams in a process module could be of the same or different type of fluid service; gas/
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Pre-treatment
Reforming Steam H2O
3
R-100 E-100
1
K-100
2
5
C-100
H-100
K-101
F-100
7
6
4 Fuel
8 PSA System Purification
Shifting
10
R-101
E-102
R-102
E-101
12 C-101
11
9
H2
C-102
C-103
C-104
C-105
C-106
13
T-100
14
Fig. 1 e Process flow diagram for the simulated SMR Process.
Table 1 e Database of precalculated fugitive emission rates for process module stream. Process module (fugitive emission rate, kg/h) Stream Inlet
Outlet
Fuel
Service
Adsorber
Normal furnace
Reforming furnace
PSA
Tail gas holding tank
G/V LL HL G/V LL HL G/V LL HL
0.33724 0.31784 0.27984 0.33724 0.31784 0.27984 N/A N/A N/A
0.03987 0.03405 0.02265 0.14387 N/A N/A 0.17007 0.14097 0.08397
0.09996 0.08056 0.04256 0.48902 N/A N/A 0.20582 0.17136 0.10296
0.0573 0.0476 0.0286 0.0573 0.0476 0.0286 N/A N/A N/A
0.14753 0.14171 0.13031 0.14753 0.14171 0.13031 N/A N/A N/A
G/V: Gas/Vapor, LL: Light Liquid, HL: Heavy Liquid.
vapor, light liquid, and heavy liquid. Based on the average emission factors provided by the U.S. EPA (1988) [44], the total emissions from each stream was calculated for all possible service types [28].
Estimation of fugitive emissions from the hydrogen plant case study After establishing the emissions database (Table 1 and Fig. 2), the amount of fugitive emissions from the studied SMR case study was estimated. As mentioned earlier in this section, the preliminary design method was adopted to conduct the estimation due to the availability of information on the process units and mass balances from the PFD of the case study. First, the PFD of the SMR process was divided into the standard modules before the chemicals present in each module stream were identified. The SMR process is operating in gas phase and therefore all the streams in this process were calculated with
the emissions value of gas/vapour service type. Basically the emission value given in the database is the stream's fugitive emissions rate (FEr), which represents the emissions of all chemicals in the mixture contained in the stream. Therefore for calculating the fugitive emission of a specific chemical substance, the FEr value needs to be multiplied with the weight composition (wt.%) of that specific chemical substance in that particular stream (Eq. (5)). Finally, the emission values of the same chemical substance (FEi) from different streams throughout the process are summed up to get its total emissions. This applies to all chemical substances present in the process. It should be noted that the air stream to the furnace (H-100) and steam stream to the reformer (F-100) (see Fig. 1) were not considered in the fugitive emissions calculation since the chemical substances included represent no harm to both environment and workers' health. Fig. 3 summarizes the step-by-step procedures for fugitive emissions estimation from the SMR process [28].
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Outlet
Inlet
Adsorber
Inlet
Outlet
Inlet
Outlet
Fuel
Fuel Reforming Furnace
Normal Furnace
Inlet Inlet
Outlet
Outlet Tail Gas Holding Tank
PSA
Fig. 2 e Process module diagram for defining stream presented in Table 1.
Dividing SMR process into standard modules
Identify chemical present in each module stream * SMR process is running in gas phase. Hence all module streams are calculated as gas/vapor service type.
* Determining stream type of service
Determining stream’s emissions rate from Table 1 * Multiply the stream emissions rate with the respective chemical weight composition.
* Determining fugitive emissions rate for each chemical, FEi
Summing up the FEi of the same chemical throughout the SMR process
Fig. 3 e Flowchart of fugitive emissions calculation for SMR process based on the preliminary design method [28].
FEi ¼ FEr *wt%
(5)
In this study, the substances of interest are the greenhouse gases (CH4 and CO2) and CO due to their possibility to cause global warming and adverse health impacts. Table 2 presents the fugitive emissions estimate of these substances. The total emissions for CH4, CO2 and CO are 1117.55 mg/s, 864.16 mg/s, and 163.05 mg/s, respectively. Mind that the process module listed in the first column of the table is arranged top-down according to the process flow in the PFD (i.e. starting from
the compressor and ends up with the gas holding tank). The table shows that the CH4 emissions decrease as it passes through the process modules starting from the pretreatment process (244.44 mg/s in compressor K-100) to the purification process (7.33 mg/s in tail holding gas T-100). Conversely, the fugitive emissions of CO2 increase from 7.44 mg/s at the pretreatment process to 47.77 mg/s in the tail holding gas (T-100). The highest emissions of CO are attributed to the reforming process (37.50 mg/s) while its lowest emissions are from the storage part (6.55 mg/s). The reason is that; CH4 represents 94% of the feed composition hence justifying its higher
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Table 2 e Fugitive emission rates of GHGs and CO from the SMR process. Fugitive emissions (mg/s) Process module Compressor (K-100) Furnace (H-100) Reactor (R-100) Adsorber (C-100) Compressor (K-101) Heat Exchanger (E-100) Reformer Furnace (F-100) Reactor (R-101) Heat Exchanger (E-100) Reactor (R-102) Heat Exchanger (E-101) Pressure Swing Adsorber (C-101) e (C-106) Holding Gas Tank (T-100) Total
CH4
CO2
CO
244.44 96.66 59.72 181.66 244.72 88.83 70.55 3.438 5.083 3.43 5.08 105.83
7.44 1.38 1.80 5.52 7.22 2.69 1.05 14.19 28.50 21.55 33.27 691.11
e e e e e e 37.50 8.30 7.61 3.61 4.55 94.72
7.33 1117.55
47.77 864.16
6.55 163.05
emissions value in the early part of the process. Later in the process as the CH4 is converted into CO and H2 during the reforming, CH4 emissions decrease. The CO emissions increase until the point where it is converted into CO2 during the shifting process to enhance H2 production, hence explaining the phenomena of CO2 increasing emissions towards the end part of the whole process.
Estimation of global warming potential In this sub-section, the global warming potential (GWP) as a result of the GHGs fugitive emissions is calculated. GWP is the contribution of the GHGs to the warming of the atmosphere. In general, the capacity of CH4 contribution to global warming is 21 times higher than that of CO2 for a 100 year time [19]. As for this case study, total fugitive emissions of CH4 are 1117.55 mg/s (4.023 kg/h) compared to CO2 with amount of 864.16 mg/s (3.11 kg/h) of fugitive emissions. Given that the H2 production capacity of the SMR plant is 10,000 kmol/h (20,150 kg/h), the amount of CH4 and CO2 fugitive emissions are 0.198 g and 0.153 g, respectively, per each kg of net hydrogen produced (see Table 3).
Estimation of the health risk associated with the emitted gases In order to calculate the health risk to workers as a result of the exposure to the fugitive emissions of CH4, CO2 and CO, the concentration of these substances in the process air environment need to first be calculated. This can be done based on the approach developed by Hassim et al. [28]. Basically they proposed that the airborne concentration due to fugitive emissions (commonly expressed in term of mass rate) can be calculated by dividing the fugitive emissions rate by the air
volumetric flow rate within the process area. The air volumetric flow rate, V is calculated from the equation below: V m3 s ¼ dðmÞ*vðm=sÞ*hðmÞ
(6)
where d is the edge width of the process area that corresponds to the wind direction, v is the wind speed and h is the height of the plant. Since the estimation is still in the preliminary design stage and not much information is already available on the plant's layout, actual area, geographical location etc., Hassim et al. [28] proposed a simple yet reliable approach to obtain the values for all these parameters. The d value can be estimated based on the typical floor area of the process modules (the database for the floor areas is presented in [28]) by assuming that the plant has a square shape, so that the width can be calculated as the square root of the total floor area of the whole process. Upon the availability of more detailed information on the process, such data should be used instead (e.g. process plot plan). For this SMR case study, the d value is 172 m based on the size of a typical hydrogen plant from the literature [45]. The height of the plant is also difficult to determine since the plant is outdoor facility. Therefore an assumption of 7 m is assumed and is considered acceptable since this is the maximum height where piping component/ fitting is located and at which the emissions can still have effect on the workers exposure [46]. As for the wind speed, the typical value of 4 m/s for outdoor facility can be used [47]. By applying Eq. (6), the air volumetric flow rate (V) calculated for the SMR case study is 4816 m3/s. This gives the concentration estimates for CH4, CO2 and CO as follows: 0.232 mg/m3 (0.353 ppm), 0.180 mg/m3 (0.100 ppm) and 0.0338 mg/m3 (0.0295 ppm), respectively. To calculate the health risk, the concentration of each gas was then compared against its threshold exposure limit, EL (see Table 4). The resulted risk value shows that the risk is acceptable for all the three substances since theoretically the workers are exposed to those gases at concentration below the exposure limits.
Comparison of GHG fugitive emissions vs GHG stack emissions In this section, the fugitive emissions of GHGs are compared to those from the stack as well as their associated contribution to the global warming potential. The data for the life cycle and stack emissions of H2 production via SMR were extracted from a study conducted by the National Renewable Energy Laboratory in the US (NREL) as summarized in Table 5 [19]. These data were used to compare the estimated GHG fugitive emissions with the GHG stack emissions calculated by NREL (refer to Table 6). Besides, the same data also were used to compare the total GHG emissions (fugitive and stack) from the whole life cycle of hydrogen production with the total GHG emissions from the hydrogen plant alone (Table 7). The study by
Table 3 e Global warming potential due to GHG fugitive emissions. GHGs Emission (g/kg of H2) Percent of GHGs (%) GWP relative to CO2 GWP (g CO2-equivalent/kg of H2) Contribution to GWP (%) CO2 CH4
0.153 0.198
43.59 56.41
1 21
0.153 4.16
3.56 96.44
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Table 4 e Health risk calculation for the SMR process. Emitted gases CH4 CO2 CO
FEs rate (mg/s) 1117.55 864.16 163
Concentration, mg/ EL, mg/m3 Health risk for individual (ppm) substances m3 (ppm) 0.232 (0.353) 0.180 (0.1) 0.0338 (0.0295)
3.5 104 < 1 0.2 104 < 1 1.16 103 < 1
656.442 (1000) 9000 (5000) 29 (25)
Health risk for the chemicals mixture 0.353/1000 þ 0.1/5000 þ 0.029/25 ¼ 1.5 103 < 1
Table 5 e The lifecycle and stack GHGs emissions and their associated GWP [19]. GHGs
Emissions (g/kg of H2)
CO2 a CH4 a
Percent of GHGs (%) GWP relative to CO2
10,621 60
99.4 0.6
GWP (g CO2-equivalent/kg of H2)
Contribution to GWP (%)
10,621 1256
89.3 10.6
1 21
Emissions value for CH4 does not represent its emissions from the stack.
Table 6 e Overall fugitive and stack GHG emissions from the Hydrogen Production Plant. Emissions
Fugitive emissions (calculated)
Plant stack emissions [19]
Total emissions (fugitive & stack)
GHGs
CH4
CO2
CH4
CO2
CH4
CO2
Emissions g/kg of H2 Emissions in% GWP relative to CO2 GWP (g CO2-equivalent/kg of H2) Contribution to GWP (%)
0.198 56.41 21 4.16 96.44
0.153 43.59 1 0.153 3.552
0 0 21 0 0
8889.44 100 1 8889.44 100
0.198 0.0022 21 4.158 0.045
8889.59 99.998 1 8889.59 99.95
NREL reported that the amount of CO2 and CH4 emitted are 10,621 and 60 (g/kg of H2), accounting for 99.4% and 0.6% of the total emissions from the H2 production life cycle. These emissions contribute to 89.3% and 10.6% of the GWP, respectively. Another interesting finding from the study is, the vast majority of the CO2 (8889.44 g/kg of H2) is released from the hydrogen plant alone (from the stack), contributing to 83.7% of the overall GWP attributed by the total amount of CO2 emitted throughout the H2 production life cycle. On the other hand, CH4 makes no contributions to the stack emissions (refer to Tables 6 and 7) [19]. The comparison between the fugitive and stack emissions is summarised in Table 6. The fugitive-emitted greenhouse gases may not amount as much in comparison to stack GHG emissions; but still the former one may cause an increase in the GHG load. The results demonstrate that with regards to fugitive emissions, CH4 is the main GHG component emitted from the H2 plant accounting for 56.41% and responsible for 96.44% of the total GWP. Meanwhile CO2 accounts for 43.6% of GHGs contributing to 3.56% of the total GWP. In contrary, CH4 makes no contribution to the plant emissions via stack whereas CO2 represents the total GHG emissions contributing to 100% of the total GWP (Table 6). The justification for this
outcome is that CH4 is highly converted into H2 and CO during the reforming process. In turn, CO is converted by steam into H2 and CO2 during high and low temperature shifting process (HTS & LTS). Owing to that, the composition of the off gas mainly consists of CO2, which presents the greatest contributor to the amount of stack GHG emissions. The overall plant GHG emissions of the overall plant (fugitive and stack emissions) mainly comprise of CO2 which accounts for 99.99% of the total plant emissions and contributes to 99.95% of the total GWP. Methane (CH4), which is only attributed to the fugitive emissions, represents only a minor quantity accounting for 0.002% of the plant emissions and contributing to 0.045% of the total GWP (Table 6). It is evident that hydrogen production plant makes a major contribution to the environmental burdens by emitting 83.7% of the total CO2 emitted through the lifecycle of H2 production. In methane case, the contribution of the plant is, however, limited by emitting 0.33% of the total CH4 emitted through the lifecycle system. Owing to that, H2 plant alone contributes to 83.7% of the total GWP attributed to the lifecycle system starting from natural gas extraction from the well to the production of high purity hydrogen at the plant (Table 7).
Table 7 e Greenhouse gases emissions, Lifecycle system vs. H2 plant (fugitive and stack). GHGs CO2 CH4
Emissions (g/kg of H2) LC
Emissions (g/kg of H2) P
Emissions LC
Emissions P
GWP LC
GWP P
10,621 60
8889.6 (S þ F) 0.198 (F)
99.4% 0.6%
83.7% 0.33%
89.3% 10.6%
83.7% 0.33%
LC: Life Cycle P: Plant S: Stack F: Fugitive.
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Conclusion In this paper, the amount of fugitive emissions of GHGs (CH4 and CO2) and CO from steam methane reforming (SMR) processes were estimated using precalculated modules approach. Such study has never been attempted before since previously, all works related to emissions assessment in this nature of processes were focusing on stack emissions only as the source of process losses. The estimation was done using an existing precalculated modules-based approach, which provides a database of fugitive emission rates for standard process modules. The database allows quick and easy estimation of fugitive emissions to be performed based on a limited process data during the early stage of design. Since the emissions data for several process modules constituted in the SMR process is not available, the precalculated emissions database for those modules was developed prior to the emissions estimation. In this study, the amount of GHGs fugitive emissions and the corresponding global warming potential (GWP) are mainly attributed to methane (CH4) emissions whereas the GHGs stack emissions and consequential GWP are completely attributed to carbon dioxide (CO2) emissions. Since the GHGs emitted from the stack are far larger than the GHGs fugitive emissions, it becomes evident that the largest amount of GHGs emitted from the plant (fugitive and stack) is attributed to CO2 emissions and so is the GWP. It is also believed that the concentrations of GHGs fugitive emissions (CH4, CO2) and CO in the breathable zone do not exceed the threshold exposure limit value. The outdoor SMR process plant allows well-ventilated workplace and hence the plant is considered as a safe workplace to workers from an occupational health point of view. In the future work, fugitive emissions from different process routes for H2 production can be estimated and the comparison of all alternatives can be conducted.
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