Mapping global flows of chemicals: from fossil fuel feedstocks to

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Mapping global flows of chemicals: from fossil fuel feedstocks to chemical products Peter Levi, and Jonathan M. Cullen Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.7b04573 • Publication Date (Web): 24 Jan 2018 Downloaded from http://pubs.acs.org on January 30, 2018

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Environmental Science & Technology

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Mapping global flows of chemicals: from fossil fuel feedstocks to chemical products

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Authorship

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Peter G. Levi a* and Jonathan M. Cullen a

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*Corresponding author: [email protected]

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a

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Abstract

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Chemical products are ubiquitous in modern society. The chemical sector is the largest industrial energy consumer and

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the third largest industrial emitter of carbon dioxide. The current portfolio of mitigation options for the chemical sector

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Department of Engineering, University of Cambridge, Trumpington Street, Cambridge, CB2 1PZ, United Kingdom

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emphasises upstream ‘supply-side’ solutions, whilst downstream mitigation options, such as material efficiency, are

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given comparatively short shrift. Key reasons for this are the scarcity of data on the sector’s material flows, and the

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highly intertwined nature of its complex supply chains. We provide the most up to date, comprehensive and

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transparent dataset available publicly, on virgin production routes in the chemical sector: from fossil fuel feedstocks to

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chemical products. We map global mass flows for the year 2013 through a complex network of transformation

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processes, and by taking account of secondary reactants and by-products, we maintain a full mass balance throughout.

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The resulting dataset partially addresses the dearth of publicly available information on the chemical sector’s supply

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chain, and can be used to prioritise downstream mitigation options.

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1. Introduction

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Industrial chemicals and their derivatives pervade modern society. Although often diffuse in their application (e.g.

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pharmaceuticals), the bulk outputs of the chemical and petrochemical sector – hereafter the chemical sector – are

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deployed in huge volumes to make millions of tonnes per year (Mt yr-1) of chemical products, such as fertilizers and

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plastics. Our industrialised economy is dependent on chemicals.

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In performing this pivotal role, the chemical sector exerts a large environmental burden. It is responsible for

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approximately 7% of global anthropogenic global greenhouse gas (GHG) emissions, and 5.5% when just counting CO2

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emissions.1 The sector’s final energy consumption is the largest among industrial sectors: 42.5 EJ in 2014, of which 25 EJ

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ACS Paragon Plus Environment


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is feedstock energy.2 Other sources of emissions include those stemming directly from the chemical transformations

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mobilised in reactors (process emissions), and from energy conversion in the transformation sector (indirect emissions).

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In addition to these gaseous emissions, chemical products can spawn pernicious aqueous discharges. The oft-publicised

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problem of fertilizer run-off contributing to hypertrophication,3 and the more recent exposition of plastic waste ending

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up in the world’s oceans4,5 and organisms6 are notable examples.

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This environmental strain magnifies as demand rises – the International Energy Agency (IEA) projects a 2.8-fold increase

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in demand for the sector’s 18 most energy-intensive chemicals by 2050.1 The IEA also estimate that to maintain a ‘2DS’

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trajectory (in which there is a 50% chance of limiting global mean temperature rise to 2 degrees Celsius above pre-

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industrial levels), a 30% reduction in direct industrial CO2 emissions by 2050 is required, relative to 2014 levels.2, p.166

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Without a disproportionate emissions reduction elsewhere, achieving a 30% cut in absolute chemical sector emissions

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levels while sustaining a 2.8-fold increase in output, means a 75% reduction in emissions per unit of production by

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2050. This is a daunting task for a competitive industrial sector in which efficiency gains are already incentivised by

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exposure to fuel and feedstock price volatility.

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1.1 Current options for reducing feedstock energy consumption

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Theoretical estimates made by Neelis et al. reveal the chemical sector’s overall exothermicity – i.e. if fully captured, the

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energy released in processing chemical feedstocks would be sufficient to supply all process energy requirements. 7 This

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seems to be reflected by the increase of feedstock energy as a share of the sector's total energy input; from 44% in

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1971 to 58% in 2013. However, this could be because of changes to reporting regimes used to compile these statistics.

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A countervailing downward pressure on the share of feedstock energy is process yield improvement. However, this

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lever is constrained by stoichiometry, and in many cases process yields are close to practical limits, leaving only a

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marginal (and hard-won) improvement potential. The quantity, and importance of feedstock energy is likely to continue

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growing. In their latest annual modelling effort, BP seem to concur, stating that ‘non-combusted fuel use becomes the

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largest source of fossil fuel demand growth towards [2035]’,8, p.17 in part because of ‘limited scope for efficiency gains’8,

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p.27

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This prognosis is uncontroversial, and there is little disagreement around the prescriptions for mitigation. Broadly

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speaking, three main decarbonisation levers receive most attention: feedstock and fuel substitution (including

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biomass),9–14 process energy efficiency potential7,15–19 and innovative low carbon technologies1,20,21 (including Carbon

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Capture and Storage (CCS)). These prescriptions are all ‘upstream’ measures, i.e. closer to the supply-side and the

in the petrochemical sector.

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producer. ‘Downstream’ mitigation options, i.e. those closer to the demand-side and the consumer, receive

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comparatively scarce attention. Material efficiency strategies, whereby the same service is provided with less material –

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thereby reducing material demand – are a key group of downstream mitigation options. Allwood and Cullen22 explore

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several strategies for bulk materials, including light-weighting and process yield improvement, but even among the

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vanguard of global energy modelling efforts, sophisticated chemical sector analyses tend to be restricted to the

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recycling of certain plastics.2,23–25

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Pioneering material and end-use efficiency analyses relating to the chemical sector are not without incidence. Worrell

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et al.26, Hekkert et al.27 and Gielen28 examined some of the key sectors (fertilizer, plastic packaging) and strategies

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(efficient application, recycling) available downstream of the chemical sector. Scholarship in these areas has not

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evolved much since. The main reason for this is the complexity of the sector’s supply chain, and the subsequent lack of

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publicly available material flow data. There is an urgent need for a mass-balanced and transparently-compiled account

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of the sector’s main material flows, so that reliable estimates of the impacts of downstream mitigation options can be

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made. Until this gap in the literature is addressed, these options will remain under-represented relative to their

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potential in recommendations to policy makers.

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1.2 Chemical sector data: few and far too costly

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This work follows similar studies of the steel29 and aluminum30 industries, but the dearth of public data on the chemical

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sector has made it substantially more challenging. We suppose three principal reasons for the inferior data landscape.

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Firstly, the chemical sector is a complex multi-sector industry, despite its aggregated accounting entries in energy

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statistics.31,32 Its outputs are numerous and diverse, supplying a wide variety of material and energy services. Secondly,

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the International Council of Chemical Associations (ICCA), a trade association and ‘worldwide voice of the chemical

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industry’,33 falls short of its counterparts in the steel (worldsteel)34 and aluminium (International Aluminium Institute)35

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industries on data provision. These metal industry associations’ data were instrumental in the steel and aluminium

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studies cited above. Some reliable subsets of data on the chemical sector have been identified, such as those from the

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International Fertilizer Association (IFA)36 and Plastics Europe37, but these tend to be fragmented with respect to their

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sectoral and geographic coverage. Lastly, the comprehensive data that are collected on the sector are proprietary and

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highly commoditised. Such databases are generally not available for use in academic studies; this analysis being no

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exception.

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1.3 Components of mapping in previous studies

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For our stated purpose – establishing a firm basis on which to appraise downstream mitigation options – a sufficiently

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detailed, globally balanced and publicly available map of the chemical sector is required. No such map has been

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identified in the academic or grey literatures. However, several elements of chemical sector mapping have been

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conducted as components of previous studies for, broadly speaking, three purposes: examining the robustness of

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emissions and energy statistics; compiling emissions estimates associated with the non-energy use of fossil fuels; and to

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inform bottom-up energy modelling efforts for the sector. In this section, we highlight salient studies with a focus on

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the mapping work involved.

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Bottom-up analyses of the main feedstock consuming processes in the chemical sector are employed to scrutinise top-

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down international energy statistics on non-energy use, such as an international study38 by Weiss et al. and a Dutch

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study39 by Neelis & Pouwelse. Multiple reporting irregularities are identified, and each study indicates a need for

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increasing the quality of chemical sector energy statistics. Studies with similar findings stem from a broader energy

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efficiency analysis of European industry by Worrell et al.40 in the early 1990s, and are most recently echoed nearly two

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decades later by Saygin et al.41 in their analysis of the German chemical sector. These studies contain partial data on

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feedstock energy consumption, upstream chemicals production, installed capacity and feedstock requirements. With

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the exception of the latter41 they focus on upstream chemical production, thereby providing little information on the

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majority of the sector’s material flows. In all cases the mapping work is the means rather than the end, and is either

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undisclosed, insufficiently detailed or limited in scope.

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Neelis et al.42 construct a NEAT (Non-energy Emissions Accounting Table) model to compile CO2 emission estimates

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associated with non-energy use flows, which is employed to analyse Korea,43 Italy,44 Germany45 and the Netherlands.46

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By better describing the degree to which non-energy consuming products are oxidised during or after use, the model

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allows the authors to improve emissions inventories, relative to those compiled with the IPCC reference approach

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available at the time.47 The model requires production and trade data for 77 organic and 18 inorganic chemicals, which

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the authors acknowledge is an extensive data requirement. The country studies prove it is possible, but only with close

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cooperation from national statistical offices or consultancies. No intermediate mapping data are presented in the

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country-level studies.

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The MATTER (MATerials Technologies for greenhouse gas Emission Reduction) project in the late 1990s may have

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represented peak of ambition with regards to integrated energy and materials climate change mitigation research.

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Kram et al.48 summarise the overall MATTER project findings: the inclusion of demand-side options (e.g. material

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efficiency and substitution) alongside supply-side options (e.g. wind turbines and solar panels) hastens progress

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towards, and brings down the costs of emissions mitigation. Groenendaal & Gielen49 summarise a sector-specific study

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of the petrochemical sector. In a related project, Joosten50 examines plastic flows in the Netherlands using national

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supply and use statistics. Each provides a contemporary snapshot of aspects of the petrochemical industry, and some of

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the most detailed energy and materials maps of the industry identified in the literature. However; only Western Europe

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is covered (where data are relatively plentiful and publicly available); some important feedstock-consuming chemicals

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such as ammonia are excluded; and the studies are nearly 30 years old.

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Other elements of chemical sector mapping are identified in: industrial energy51 and exergy52 efficiency studies; specific

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analyses of plastics flows;53 broader analyses of chemical sector energy consumption and emissions in the UK54 and

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globally;14,55,56 and in flowcharts published by trade associations.57,58 However, among the existing information we have

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examined, no mapping component or selection thereof is sufficient to provide us with the framework we require. This is

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not a criticism of studies where this was not their purpose. The remainder of this study outlines the methodology

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(section 2) used to assemble the mapping results (section 3) required to fill this gap in the literature. In section 4, we

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use comparisons and a sensitivity analysis to critically examine our results.

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2. Methodology

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This section contains an overview of the methods used to construct a dataset of global chemical sector mass flow. A

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snapshot of the Material Flow Analysis (MFA)-based dataset is presented as a Sankey diagram – a complementary

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pairing of analytical tools for supply chain analyses.59–62 The full details of the dataset are delineated in the Supporting

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Information (SI) accompanying this article. After outlining the scope of the analysis, this section summarises the

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upstream and downstream calculations sequentially.

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2.1 Analysis scope

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The temporal (2013) and geographic (global) boundaries of this study are chosen to align with common reporting

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intervals for production statistics, and to negate the need to consider trade. 2013 is recent enough to construct a

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contemporary picture of the industry, but not so recent as to limit data availability. Stocks of products within the supply

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chain boundary are assumed to be negligible, based on evidence for several chemicals where supply and demand

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information is available.63 Furthermore many of the sector’s products are gaseous and/or toxic, incurring hefty expense

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when stored. ‘In-use’ stocks are not considered in static analyses, but any subsequent dynamic analysis would need to

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take account of varying product lifetimes, especially for plastics.

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Only virgin production routes and fossil fuel feedstocks are considered. Secondary production routes (those based on

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recyclate) and alternative feedstocks form a small fraction of overall inputs to the sector. Global demand for plastics – a

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subset of chemical products for which scalable secondary and bio-based routes exist – is currently estimated at 311 Mt

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yr-1.37 Global inputs of plastic recyclate are of the order of 10 Mt yr-1, and total bioplastic production capacity is

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approximately 1.7 Mt yr-1.51,64-65

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The European Chemicals Agency (ECHA) keeps an inventory of commercially manufactured chemicals. The entries

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currently number 106,213, ranging from fertilizer pre-cursors produced on the 1011 kg scale, such as ammonia, to

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powerful analgesics administered in dosages on the 10-6 kg scale, such as fentanyl.66 Clearly a narrower focus is

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required. Just 18 chemicals account for 63% and 75% of the sector’s process energy consumption and GHG emissions

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respectively.1 Tracing these chemicals and their main derivatives downstream to chemical products results in the

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inclusion of 77 chemicals and 65 processes. We return to assess the degree of coverage achieved in section 4.

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2.2 Mapping upstream chemical production

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The upstream portion of the dataset maps inputs of fossil fuel feedstocks to the sector’s largest-volume chemicals, the

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salient details of which are described under the headings below.

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Ammonia and methyl alcohol

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Although promising carbon-free routes to ammonia and methyl alcohol are available via various types of electrolysis,67

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the vast majority of global capacity is based on natural gas, oil product (naphtha, LPG etc.) and coal feedstocks. We

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apply estimates of feedstock input percentages68 to production figures36,69 to get tonnages of ammonia (120.5, 14.4,

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and 34.8 Mt yr-1) and methyl alcohol (50.3, 1.9, and 10.7 Mt yr-1) produced globally from natural gas, oil and coal

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respectively.

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Generalised stoichiometric expressions are formulated to characterise the ammonia and methyl alcohol production

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processes, which each comprise synthesis gas (syngas) production and chemical synthesis steps. We assume the

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chemical synthesis steps are consistent irrespective of the feedstock used, but distinguish between Steam Methane

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Reforming (SMR) and Partial Oxidation (POX) syngas units. The water gas shift and reverse water gas shift reactions,

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employed to obtain the appropriate CO:H2 syngas ratios for each feedstock/product combination, are integrated within

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the syngas production characterisations. All terms in the generalised stoichiometric expressions can be described

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precisely with chemical notation (NH3, CO2 etc.), apart from the feedstock inputs, which are non-uniform combinations

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of carbon/hydrogen (C/H), and some non-C/H content. Generalised characterisations in the form CHn are used, where

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‘n’ determines the average carbon-to-hydrogen ratio of the feedstock’s constituent molecules. Appl70 and Rainer et al.71

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provide feed and product profiles for several real-world syngas plants. From multiple plants’ feed data, typical values of

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n for natural gas, oil and coal feeds of 3.951, 1.873 and 0.456 were calculated. The terms are then combined and

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balanced, resulting in the full stoichiometric expressions for each product and process route.

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The mass proportions of the terms in the balanced stoichiometric expressions, along with the global production

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estimates above, are used to calculate corresponding quantities of feedstocks, secondary reactants and secondary

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products. Aggregated loss terms are incorporated to account for imperfect conversion and selectivity at the syngas and

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chemical synthesis steps, and any non-C/H content transiting the process. Typical syngas conversion efficiencies – the

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higher heating value (HHV) of the CO/H2 product relative to that of the feedstock input – were computed using typical

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HHV values for each fuel72 and the syngas profile data:70,71 86.1% for natural gas (SMR), 80.8% for oil (POX) and 76.0%

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for coal (POX). There are also small losses at the synthesis steps, described by the chemical yield: 98.0% for ammonia73

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and 99.0% for methyl alcohol syntheses.74 These calculation steps result in a global mass-balance for ammonia and

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methyl alcohol production. For more information, see section 4 of the SI.

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Steam cracking

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Capacity (in Mt yr-1 of ethylene) and feed (in percentages of ethane, naphtha etc.) data for 277 steam crackers were

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taken from the Oil & Gas Journal’s annual surveys.75,76 Estimates were made for omitted data, using adjacent countries’

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or regions’ figures. Typical yield profiles for steam crackers run on various feeds are provided by the European

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Commission.77 The following identity describes the relationship between theses quantities:

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𝑦𝑎,1 𝑦𝑏,1 𝐹𝑡 ∙ 𝑦𝑐,1 ⋮ [ 𝑦𝑖,1

𝑦𝑎,2 𝑦𝑏,2 𝑦𝑐,2 ⋮ 𝑦𝑖,2

𝑦𝑎,3 𝑦𝑏,3 𝑦𝑐,3 ⋮ 𝑦𝑖,3

⋯ 𝑦𝑎,𝑛 𝑓1 𝑃𝑎 ⋯ 𝑦𝑏,𝑛 𝑓2 𝑃𝑏 ⋯ 𝑦𝑐,𝑛 ∙ 𝑓 = 𝑃𝑐 3 ⋱ ⋮ ⋮ ⋮ ⋯ 𝑦𝑖,𝑛 ] [𝑓𝑛 ] [ 𝑃𝑖 ]

(1)

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Where F t is the total quantity of all feeds in Mt yr-1, P a - i are capacities of each product (ethylene, propylene etc.) in Mt

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yr-1, y i , n is the yield of product ‘i’ from a unit of feed ‘n’ and f 1 - n are the fractions each feed forms of F t .

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The results of using [1] – first by solving for F t using one known production quantity (say P a ), and then using F t to

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compute the quantities of the remaining products P b - i – are in capacity rather than production terms. An average

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utilisation rate was estimated using global ethylene production data published by the Japanese government,63 and

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applied to the capacity-based profile to obtain production quantities. For more information, see section 5 of the SI.

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BTX aromatics and C4 olefins

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C4 olefins are co-produced alongside ethylene and propylene in steam crackers run on both light (e.g. ethane) and

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heavy (e.g. naphtha) feeds, as opposed to the BTX (benzene, toluene and xylene) aromatics, which are only produced

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when cracking heavier feedstocks. The remaining quantities of BTX aromatics and C4 olefins produced globally are

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mainly recovered from various refining processes’ raffinate and pyrolysis gasoline streams, such as those from fluid

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catalytic crackers and catalytic reformers. Bender78,79 provides recent global average estimates of the proportions of C4

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olefins and BTX aromatics obtained from each of these sources.

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BTX aromatics streams often undergo further transformation after extraction. Principal among these transformations is

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the conversion of toluene to xylene and benzene, via hydrodealkylation and disproportionation. Burdick and Leffler80

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provide typical feed and product profiles for each process. For more information, see sections 6-7 of the SI.

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On-purpose technologies

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Multi-product processes, such as steam cracking, may not yield products in a ratio equal to that of their demands. On-

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purpose technologies can help address such an imbalance, by producing products in a complementary ratio, or one at a

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time. Three on-purpose technologies are characterised in this mapping work: propane dehydrogenation (PDH),

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metathesis (MTS) and methanol-to-olefins (MTO). These flexibility-enhancing technologies’ capacities are relatively

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small (

Mapping global flows of chemicals: from fossil fuel feedstocks to

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