Liquid Air Power Transport Supply Chain The Big Wins Policy Recommendations

Chapter 10: Climate change

The ability of liquid air to reduce carbon dioxide emissions depends largely on the carbon intensity of the electricity used to produce it. However, the scale of emissions reductions is also application specific: some liquid air concepts such as refrigerated food transport would reduce carbon emissions even based on current grid average carbon intensity; others would start to deliver emissions reductions only on the basis of lower carbon electricity.

The carbon intensity of the grid is projected to fall significantly over the next two decades as coal fired power stations close and more wind generation continues to be added. This will reduce grid emissions overall, but will have an even more pronounced impact on off-peak or overnight carbon intensity, when demand is lower and nuclear and wind capacity will on average deliver a bigger proportion of the necessary power.

This is important because at present liquid nitrogen  is invariably produced at night to take advantage of lower cost electricity. This coincidence of lower cost and lower carbon electricity means emissions from liquid air technologies will fall faster than if they were charged at the grid average. It means for example that a diesel-cryogenic hybrid bus running on overnight liquid air would start to emit less CO₂ than a standard diesel from 2015, and emissions would continue to improve thereafter.

As well as reducing transport emissions, liquid air can also further reduce emissions from grid electricity  in two ways. First, it can harvest excess wind power that would otherwise be wasted (‘curtailed’) at times of low demand, and use it to displace carbon intensive generators at peak times. Second, it allows fossil plant to run more efficiently at full load rather than ‘ramping’ up and down to accommodate variable wind generation, as this role is assumed by storage. These two factors have the effect of lowering average emissions from grid electricity beyond any reductions achieved by simply changing the primary generating mix.

In this chapter we explore how, and under what conditions, liquid air can help reduce carbon emissions on the grid, and show how some liquid air transport concepts could have the lowest lifecycle emissions of any competing vehicle by 2030.

Of the many benefits electricity storage could potentially contribute towards future electricity systems, its CO₂ reduction potential is among the least understood. Only a small proportion (around 4%) of the benefits of storage identified by stakeholders relates directly to CO₂ savings¹, and many commentators do not regard emissions reduction as the primary reason for installing storage.²

As a result, policy tools such as the DECC 2050 emissions calculator do not attribute any CO₂ reduction to the deployment of storage.³ Indeed, many of the models used to support the 80% UK emissions reduction target for 2050 do so by imposing an external emission constraint, which they try to meet at least cost. Including storage in these models can open up new plant mix options and reduce the overall cost, but the total emissions remain unchanged because they constitute the externally imposed limit.⁴ Exceeding the constraint is not ‘optimal’ within the narrative of such models.

Nevertheless, storage has the potential to improve system operation and lead to CO₂ reductions – even if that is not the owners’ main motivation. We deliberately calculated CO₂ reductions for commercially operated storage, rather than seeking to maximise this emissions reductions per se. In other words, the model was instructed to make money rather than cut carbon and any emissions reductions were a side-benefit. This is a conservative assumption: bigger carbon savings could be achieved by optimising emissions reductions directly, but we wanted to see what might be achieved under ‘real world’ conditions.

Storage can help to reduce grid emissions by:

• Capturing excess wind or other lower carbon overnight power and using it to displace carbon intensive generators at peak times.

• Allowing fossil plant to run more efficiently at full load, while storage devices assume their ‘load following’ role – raising or reducing output to match demand.

To estimate the potential savings offered by the first factor, we adopt the dynamic wind and demand model for the UK developed by Grünewald and colleagues and assume 40GW  of wind capacity. This would generate around 116TWh a year, of which around 17TWh might need to be curtailed according to our model -  the energy equivalent of around 3,000 x 2MW wind turbines. Storage could, to some extent, reduce this curtailment and in turn displace high emitting plants. Assuming an emissions factor of 473gCO₂/kWh^* for those displaced generators, up to 8 million tonnes of CO₂ (Mt/CO₂) could in theory be avoided. For this scenario, in which grid emissions total 125MtCO₂, the projected savings are equivalent to around 6.5%.

Estimating the impact of the second factor is more involved, since emissions reductions come from rescheduling of generation from high emitting plant to more efficient generators and from the more efficient operation of those plants by running at closer to full capacity and avoiding ramping (raising or lowering output). We calculate the combined impact of this and avoided wind curtailment on system-wide emissions below.

The analysis presented here is based on a techno-economic model for the assessment of the role of electricity storage in low carbon energy systems developed by Grünewald and colleagues.⁵ It consists of a data-rich representation of load and wind profiles across the UK, scaled to suit selected decarbonisation pathways. The model balances supply and demand based on a simple merit order stack with hourly resolution. Storage operation is optimised for maximum revenue in an assumed competitive wholesale market. Generally speaking, storage charges during periods of low net load (demand-wind) and discharges when net loads are high or rising fast, thereby displacing costly dispatch from peaking plants.

Since peaking plants also happen to have higher emissions factors than base load and mid-merit plants, one would expect a reduction in emissions when comparing a given scenario with added storage compared to a counterfactual case without storage. This approach differs from previous studies in that the plant mix is not ‘re-optimised’ after storage has been added to the system, so that the ‘before’ and ‘after’ emissions can be compared.

It is worth noting that this model does not seek to maximise emission reductions as its objective function, which could lead to bigger savings. Instead, the reported figures are a ‘by-product’ of a revenue maximising strategy for storage operation.

Storage is represented through technology agnostic high level parameters, such as the installed capacity [GW], the round trip efficiency [%], and the storage duration [h], which is the ratio of the energy storage capacity [GWh] and the installed capacity. The round trip efficiency of storage in low carbon, high wind scenarios has been shown by Strbac and colleagues⁶ to have a minor impact, and efficiency of 75% was assumed.

Our scenario assumptions are informed by the DECC 2050 Grassroots pathway. The plant mix evolving from 2010 to 2050 is shown in Figure 10.1. We assume deployment of 40GW of wind, which in this scenario would occur around the mid 2020s.⁷

_{* Based on interpolated values from the DECC Grassroots scenario for all plants other than wind and nuclear}

 

Figure 10.1: Generating mix evolution to 2050. Source: DECC Grassroots scenario

 

Assumed emission factors are based on Macleay and colleagues⁸ and shown in Table 10.1. The average emissions apply to the entire fuel based generation across the year. The emissions factor for peaking plants is more than twice the average, due to lower efficiencies and less favourable operating conditions. In high wind scenarios this capacity operates at low load factors of below 20% and is required to ramp up and down to suit the combined slew rate of demand and wind. Wind and nuclear plants on the other hand are assumed to serve base loads and have marginal emission factors assumed as zero.

  

Table 10.1: Assumed emissions factors. Source: Macleay, 2010⁹

 

The reduction in output from peaking capacity and mid merit capacity is calculated for each storage configuration and the resulting emission reduction is calculated as:

 

 

where E is the total energy output from a given merit order class (pk = peaking plant, mm = mid merit plant). The suffix ref denotes the reference case without storage and str are outputs after storage has been added to the system.

The results presented in Figure 10.2 show the impact of storage on overall emissions in our scenario with 40GW of wind. The first 10GW of storage delivers only modest emission reductions of less than 5% compared to the counterfactual scenario under the operating strategy simulated here.

 

 

Figure 10.2: The impact of storage on emissions with 40GW wind capacity

 

Higher capacities of storage with longer durations, such as those achievable by liquid air energy storage devices, can displace larger shares of peaking capacity and thereby increase the CO₂ reductions. One hour storage, even with large scale deployment, produces maximum savings of around 7–8%. This level can be achieved with around half the capacity if storage durations exceed three hours. At six hours’ storage duration, easily achievable with Liquid Air Energy Storage, 15GW of storage capacity would save 5.6 million tonnes (Mt) while 20GW would save 14Mt.  A far more ambitious scenario of 30GW would save 24Mt, or almost a fifth (19.4%) of total grid emissions of 125Mt. 

In this scenario, emissions reductions reach a saturation point at around 30GW of six hour storage. Additional capacity can even lead to lower emission reductions as round trip losses - simulated here as 25% - begin to outweigh the gains from displacing high emitting plant, as shown in Figure 10.1. Further extension of storage durations beyond six hours have also been simulated, but these deliver only marginal improvements over the results shown here.

 

Since liquid nitrogen is invariably produced overnight when power prices are lowest, it is important to understand the likely evolution of the off-peak carbon intensity of grid electricity. To calculate this we make some simplifying assumptions and build on scenarios from DECC’s 2050 pathway analysis. We focus here on a highly renewable scenario, as this illustrates most clearly how storage can support decarbonisation of the wider energy system. The generation mix is the same as illustrated in Figure 10.1.

The simulation uses static conditions as opposed to dynamic simulation, and we assume that storage charges only for up to 10 hours during the night when demand is below 35GW. The lower we set this operating threshold, the better the environmental performance of storage would become. 35GW is, therefore, a conservative estimate which coincides with the highest night time demand presently experienced during the winter months in the UK. The underpinning DECC Grassroots pathway suggests reductions in overall electricity demand towards 2030. Instead of reducing the night time load threshold over time, we keep this value at a constant level to allow for additional demand from storage, which could contribute towards off-peak demand. The results are therefore not expected to be adversely affected by storage itself increasing the night time emissions factor.

We also assume that nuclear and wind capacity are dispatched whenever possible, thereby displacing unabated plant during periods of low demand. Based on a load factor of 33% for wind, we estimate that the share of zero carbon generation during these low demand periods could increase from 42% in 2020 to as much as 80% in 2030 (Table 10.1).

The emissions factors for the remaining fleet have been derived from the DECC scenarios by dividing the total emissions for the respective year by the electricity provided by all plants other than wind or nuclear.

As shown in Figure 10.3 and Table 10.2, the emissions factor for ‘non wind and nuclear’ plants remains relatively high in this pathway, whereas the increasing share of wind and nuclear generation reduces the emissions factor during low demand periods to levels that are well below the average. By 2030 the emissions factor during low demand periods could become as low as 53gCO₂/kWh, for a system that on average still emits 93gCO₂/kWh.

 

Figure 10.3: Reducing emission factors in Grassroots scenario. During low demand periods the emissions factor is lower than average. The combined emissions factor for plants other than wind and nuclear—here labelled as ‘non wind/nuclear’— also falls over time, but the ratio between these generators and low demand emissions increases, favouring the use of storage from an emissions perspective.

 

Table 10.2: Emission factors in the DECC Grassroots scenario. Charging storage over night during low demand (here defined as below 35GW) leads to reduced emission factors. Assuming 33% load factor for wind, the contribution of zero-emitting plants towards low demand periods increases substantially over time. Emissions during these periods therefore reduce faster than average emissions, giving storage the opportunity to reduce emissions by shifting energy between low and high demand periods.

  

In conventional vehicles, the dominant source of greenhouse gas emissions is the combustion of fossil fuels in the vehicles themselves. Life-cycle studies¹⁰ have shown that, for a passenger car, about 80% of total emissions come from fuel use – overwhelmingly from the exhaust pipe, with a much smaller fraction caused by oil production and refining – and 20% from ‘embedded’ emissions due to manufacturing and disposal of the vehicle. In commercial vehicles, which are used more intensively, fuel use accounts for an even higher share of lifecycle emissions – typically 90% or more.

For alternative technologies such as electric vehicles (EVs), hydrogen fuel cell vehicles (FCVs) and future vehicles powered by liquid air engines such as the Dearman Engine (DE), emissions are dominated by the carbon intensity of the electricity used to make the ‘fuel’ and the efficiency of the powertrain. This makes the lifecycle emissions of all three technologies sensitive to the pace of decarbonisation of the electricity grid. On a ‘well-to-wheels’ basis, which considers emissions from fuel use only, emissions from a DE vehicle would be twice those of an ICE today, but fall to less than a third by the 2030s assuming overnight grid emissions intensity falls as projected in section 1. ICE-DE hybrids could produce carbon savings from 2015.

Another significant factor is embedded emissions. EV’s and FCVs have higher embedded emissions than internal combustion engine (ICE) vehicles because of the lithium and platinum needed to make batteries and fuel cells. However, DE vehicles are likely to have embedded emissions similar to ICE vehicles in the early years of production, and probably lower in the longer term, since the DE runs at ambient temperatures (10-20C) and could therefore be manufactured from lighter materials (chapter 8). Even disregarding this last factor, we calculate that DE lifecycle emissions will be lower than those of current EVs and FCVs by the 2030s.

One application, food transport refrigeration, could achieve major CO₂ reductions even on the basis of the current grid average carbon intensity. We calculate a large refrigerated lorry fitted with a Dearman Engine to provide both shaft power and cooling could save 38 tonnes of CO₂ per year, a reduction of 80% against conventional diesel-powered refrigeration. If applied across the entire sector, this would amount to savings of 240,000 tonnes per year, or 0.04% of total UK greenhouse gas emissions.¹¹ 
The analysis below considers the impacts on CO₂ emissions of using grid average and overnight electricity to produce liquid air for three potential applications.

 

The ‘well-to-wheels’ emissions of a DE vehicle are strongly related to the carbon intensity of the electricity used to produce liquid air. At current grid average of 547gCO₂/kWh the DE is likely to produce emissions of 2188gCO₂/kWh at the drive shaft – more than twice the emissions of an ICE.¹² However, at 50gCO₂/kWh, which is roughly the level we project for overnight power in 2030 in section 1, and which is also the Climate Change Committee’s target for average emissions in a ‘decarbonised’ grid, the DE would emit around 200gCO₂/kWh, less than a third of those from a 30% blend of biodiesel, but still higher than those of and EV or FCV (Table 10.3).

 

Table 10.3: Well-to-wheels emissions of various powertrains compared

 

However, embedded carbon also has a significant impact on lifecycle emissions. A recent report by Ricardo for the Low Carbon Vehicle Partnership estimated carbon emissions from the production and disposal of a variety of powertrains for a medium sized car (Table 10.4).¹⁶ A cryogenic engine such as the Dearman Engine is likely to be made from similar materials to an ICE – at least in the early years of production - and is therefore likely to have comparable emissions during its production and disposal.

 

Table 10.4: Embedded emissions of various powertrains compared. Source: Ricardo¹⁷

 

Ricardo went on to calculate the lifecycle emissions of ICE, EV and FCV cars on the basis of the embedded emissions in Table 10.2, and making uniform assumptions about lifetime mileage (150,000km) and the amount of energy required per kilometre driven (0.13kWh/km), meaning each powertrain would need to deliver 19,500kWh of shaft power over its lifetime. If we apply the same assumptions to the DE, on the basis of the overnight grid carbon intensity projected in Table 10.1 its lifecycle emissions are lower in 2030 than all other powertrains (Table 10.5). Until 2030 EVs have the lowest lifecycle emissions under all grid carbon intensity assumptions, but at that point the lower embedded emissions of the DE tip the balance. In all cases, the FCV produces the smallest carbon savings of the three powertrains. Both the FCV and the EV are likely to have higher capital costs than the DE.

DE lifecycle emissions could fall further as the technology develops, since the engine runs at ambient temperatures, and could therefore be built with lighter materials  and potentially produced using 3-D printing (chapter 8).

If the electricity used to make liquid air is supplied through ‘wind-twinning’ arrangements that contractually connect cryogen production to the output of a specific wind farm, then substantial emissions reductions would be achieved sooner than on the basis of overnight carbon intensities.Emissions would also be low in a number of countries that already have low carbon electricity due to nuclear or renewable generation:¹⁸

• Brazil 87g/kWh.

• France 78g/kWh.

• Norway 3g/kWh.

• Sweden 41g/kWh.

• Switzerland 7g/kWh.

The efficiency of cryogenic engines such as the Dearman Engine is increased by the addition of waste heat, raising the possibility of an ICE-DE hybrid. The simplest formulation would be small cryogenic engine to harvest waste heat from the ICE radiator fluid to generate extra shaft power.

An ICE-DE hybrid would effectively substitute shaft power that would otherwise be generated by the ICE for shaft power generated by vaporising liquid air. Different applications would require different relative sizes of DE and IC engines, but a general picture of the type of carbon impacts that could be achieved by this approach can be shown by comparing CO₂ emissions from producing a kWh of shaft power with liquid air and those produced by a kWh of diesel power.

Waste heat from an ICE at 90-100C would increase the specific energy of liquid air by about 20%. So at current grid average carbon intensity, a DE waste heat hybrid would emit 1823gCO₂/kWh of shaft power.¹⁹ However, the balance changes as grid carbon intensities fall, as shown in Table 10.6. On the basis of the grid average and overnight carbon intensities projected in Table 10.1, Dearman Engines and Dearman heat hybrids produce lower emissions than diesel under all scenarios by 2025, and lower emissions than biodiesel by 2030.

Burning a litre of diesel causes 3.24kgCO₂e emissions, which corresponds to 0.839kgCO₂e/kWh of shaft power²⁰, while burning a litre of pure biodiesel is estimated to emit 2.49kgCO₂e²¹, which equates to 645gCO₂e/kWh of shaft power. By contrast, at a grid carbon intensity of 53gCO₂/kWh, the DE prime mover would emit 212gCO₂/kWh, and the heat hybrid would emit 177gCO₂/kWh. Switching from diesel to biodiesel cuts emissions by only 23%, whereas switching from biodiesel to a heat hybrid saves a further 70% when based on 2030 overnight grid carbon intensity. Switching from diesel to the heat hybrid would save almost 80%. The carbon intensity of crude oil can be expected to increase over time as production shifts to more energy intensive unconventional resources.

 

Table 10.6: DE heat hybrid emissions compared to diesel and biodiesel emissions

 

This calculation shows the idealised emissions reductions that could be achieved in principle by switching fuels and powertrains, but takes no account of the practical factors that affect vehicle performance in the real world. The Dearman Engine Company and E4tech have conducted more detailed modelling that includes factors such as embedded carbon, tank size, cooling constraints and operating strategies that use the system to best effect on a city drive cycle. The results suggest a smoother trajectory: Dearman heat hybrids would offer emissions reductions compared to a standard diesel almost immediately, but emissions reductions in the long term would not be as large as shown as shown above - although this does not take account of the likely long term reductions in embedded emissions.

The two key conclusions of this modelling are that a Dearman heat hybrid would allow the ICE to be downsized significantly, perhaps by a factor of 2 or more where the duty cycle allows, as it has been in some EV hybrid buses. The other is that, with the right configuration and operating strategy, emissions break-even is achieved with electricity at around 400g/kWh, meaning that such hybrids would deliver emissions reductions on the basis of the projected carbon intensity of overnight electricity in 2015. At 50g/kWh, roughly the projected overnight carbon intensity for 2030, such a hybrid would deliver more than 20% well-to-wheel CO₂ saving and a short payback time. In all cases, consumption of diesel is around 25% lower than baseline.

 

Refrigerated food transport is a significant and growing source of carbon emissions. The global market is growing fast because of changing diets in Asia, and the rise of home delivery in western countries. At the same time, mobile refrigeration equipment is inevitably less efficient than static, since it has to fit into a smaller space and deal with a wider range of conditions. Both factors put pressure on the food industry to find ways to cut emissions from refrigerated transport.

In the UK, food transport – including propulsion and refrigeration – accounts for 1.8% of total emissions.²² About a third of this is from refrigerated transport, and refrigeration accounts for about 8% of these vehicles’ fuel consumption, meaning food transport refrigeration alone accounts for 0.05% of total UK emissions, or about 295,000 tonnes of CO₂e per year.²³

Mobile refrigeration units are typically powered by an alternator on the main vehicle engine or a co-located diesel generator. These systems are typically very inefficient because they have to be affordable and mobile and accommodate highly variable cooling loads caused by door openings or the addition of a warm payload.²⁴

Liquid nitrogen absorbs about 112Wh/kg of heat when it is vaporised and heated up to 0C.²⁵ A number of industrial gas companies such as Linde and Air Liquide, and other market participants such as EcoFridge, have developed systems that use liquid nitrogen as a heat sink to provide cooling. These systems either pass liquid nitrogen through a heat exchanger where it vaporises to absorb heat indirectly, or spray liquid nitrogen directly into the compartment. The second method has the advantage of being about a third more efficient, but means oxygen monitors and other safety equipment must be installed to prevent the operator entering the compartment until the atmosphere is breathable. However, neither approach recovers any shaft power from the evaporation process.

If a Dearman Engine or similar were used to exploit the nitrogen vaporisation process, it could generate as much as 50Wh/kg²⁶ of shaft power. If this shaft power were used to drive a refrigeration cycle with similar efficiency to those used in other mobile refrigeration applications, then about 25 to 75Wh/kg of extra cooling could be available.²⁷ Expanding from a high pressure to low also creates a temperature drop, so as much as another 40Wh/kg of cooling may be available from this source. In total then between 65 and 115Wh/kg of additional cooling may be available from recovering some work from vaporisation and this would correspond to a 58% to 102% improvement in cooling available per kilogramme of liquid nitrogen, or a reduction in nitrogen consumption of about 37-50%.

The analysis below is based on figures produced by Air Liquide for a truck carrying frozen products for eight hours a day, 300 days per year with five door openings per day.²⁸ Table 10.7 shows the CO₂ savings achieved by the Air Liquide approach against conventional diesel refrigeration, and in the final column we have calculated the additional reductions that could be obtained by exploiting the vaporisation of liquid air or nitrogen with a Dearman Engine or similar. The calculation assumes current grid average carbon intensity of  547gCO2/kWh.  

The Air Liquide approach saves 31tCO₂/year/vehicle compared to diesel refrigeration, while the DE approach saves 38tCO₂/year, a reduction of 80%. If applied across the entire sector, this would amount to savings of 240,000 tonnes of CO₂ per year, or 0.04% of total UK greenhouse gas emissions. On the basis of projected overnight carbon intensity in 2030, the DE approach would emit less than 1 tonne, a saving of almost 47 tonnes or 98%.

 

Table 10.7: Annual CO₂ emissions from refrigeration by diesel and liquid nitrogen compared

Source: Air Liquide³⁰, and Liquid Air Energy Group calculation

 

The potential emissions savings from such an approach should increase over time, since demand for refrigerated transport is growing strongly in both developing and developed economies. Global sales of mobile refrigeration equipment are expected to exceed $6.5billion per annum in sales by 2015.³¹ The largest market is North America with $1.25 billion sales in 2010.³² In the EU there are about 650,000 refrigerated road vehicles in use primarily for food distribution, of which about 8% or 52,000 are in the UK.

 

 

While the analysis presented above is simple and has a low level of hardware validation, it indicates significant potential for liquid air once the realities of a highly transient energy grid, future renewable generation capacity growth, and the synergies with the heat-wasteful internal combustion engine are considered. During the transition to a low carbon grid, liquid air transport applications appear to offer CO₂ reductions of at least 25% and sometimes much more.

 

From the discussion presented in this chapter we conclude:

• The carbon reduction potential of liquid air technologies depends heavily on the carbon intensity of the electricity used to produce liquid air.

• Liquid air storage could reduce emissions from grid electricity, by harvesting excess wind power that would otherwise be wasted and by increasing the efficiency of fossil generating plant.

• Savings from avoided wind curtailment alone could amount to 8 million tonnes of CO2 per year and the energy equivalent of 3,000 x 2MW wind turbines. Total system savings could reach 24MtCO₂ per year, or almost a fifth of total grid emissions in a 40GW wind scenario.

• The carbon intensity of overnight electricity used to produce liquid nitrogen and liquid air will fall faster than the grid average, increasing the emissions reductions achievable from liquid air technologies over time.

• On the basis of projected overnight grid carbon intensities, a Dearman heat hybrid would start to cut emissions compared to a standard diesel from 2015, and the Dearman Engine has lower lifecycle carbon emissions than either the EV or the FCV in 2030.

• A Dearman Engine used to provide refrigeration in food transport could save 38 tonnes of CO₂ per lorry per year, a reduction of 80%, on the basis of current grid carbon intensity, and 47 tonnes or 98% on the basis of projected overnight carbon intensity in 2030.

• If applied across the sector, the emissions savings in food transport on current grid average carbon intensity could save 240,000 tonnes of CO₂ per year, or 0.04% of total UK greenhouse gas emissions.

 

Endnotes

¹
The socio-technical transition of distributed electricitystorage into future networks - System value and stakeholder views, P. H. Grünewald et al., Energy Policy 50, pp449-457.

²
Energy Storage (presentation), D. J. C. MacKay, 6 June2012 at University of Oxford Department of Physics.

³
2050 Pathway Analysis, DECC, 2010, , accessed 1 February 2011.

⁴
Energy 2050: Making the transition to a secure low carbon energy system, J. Skea et al., Earthscan, 2011, ISBN 978-1849710848; Strategic Assessment of the Role and Valueof Energy Storage Systems in the UK Low Carbon Energy Future, report for the Carbon Trust, G. Strbac et al., June 2012, http://www.carbontrust.com/resources/reports/technology/energy-storage-systems-strategic-assessment-role-and-value

⁵
The role of large scale storage in a GB low carbon energy future:Issues and policy challenges, P. Grünewald et al., Energy Policy 39, 2011, pp4807 -4815.

⁶
Strategic Assessment of the Role and Value of Energy Storage Systems in the UK Low Carbon Energy Future, report for the Carbon Trust, G. Strbac et al., June 2012.

⁷
Ibid.

⁸
Digest of United Kingdom Energy Statistics (DUKES), Technical  Report, I. MacLeay et al., DECC, 2010.

⁹ Ibid.                 

¹⁰
Preparing for a lifecycle CO₂ measure, Ricardo, August 2011,  http://www.lowcvp.org.uk/news/1644/lowcvp-study-highlights-importance-of-measuring-whole-life-carbon-emissions/

¹¹
Figures derived from those supplied by Professor Savvas Tassou, Brunel University, personal communication, February 2013.

¹²
The energy cost to produce 1kg of liquid air is about 0.4kWh/kg at scale. The UK grid average   emissions for electricity is 547gCO₂/kWh. Therefore CO₂ emissions per kg of liquid air produced are 218.8gCO₂/kg if the UK grid average is used. Practical energy density is likely to be around 0.1kWh/kg, therefore shaft power generated by the Dearman Engine produces 2188gCO₂/kWh. The Committee on Climate Change believes the carbon intensity of UK grid can be reduced to less than 50gCO₂/kWh during the 2020s. This would have the impact of reducing Dearman Engine’s CO₂ emissions to 200gCO₂/kWh.

¹³
Ibid.

¹⁴
Assumes 90% charging efficiency and 86% discharging efficiency (energy to the shaft).

¹⁵
Assumes energy consumption of 60.5kWh/kg H₂ and 16kWhout/kg H_2.

¹⁶
Preparing for a lifecycle CO₂ measure, Ricardo, August 2011,  http://www.lowcvp.org.uk/news/1644/lowcvp-study-highlights-importance-of-measuring-whole-life-carbon-emissions/

¹⁷
Ibid.

¹⁸
http://www.ipcc.ch/pdf/special-reports/sroc/Tables/t0305.pdf

¹⁹
The energy cost to produce 1kg of liquid air is about 0.4kWh/kg at scale. The UK grid average CO₂ emissions for electricity is 547gCO₂/kWh. Therefore CO₂ emissions per kg of liquid air produced are 218.8gCO₂/kg if the UK grid average is used. For a waste heat hybrid, practical energy density is likely to be around 0.12kWh/kg, so shaft power generated by the Dearman Engine produces 1823gCO₂/kWh under this arrangement.

²⁰
Burning 1 litre of diesel causes 3.24kgCO2e emissions , and the lower calorific value of diesel is 43.4MJ/kg (http://www.engineeringtoolbox.com/fuels-higher-calorific-values-d_169.html), equivalent to about 9.6kWh/litre (multiply by 0.8 for density of diesel then divide by 3.6 to convert to kWh). Practically, diesel engines may achieve about 40% thermal efficiency under optimal load conditions, and much less if they are at part load or idling. This would practically correspond to about 3.86kWh/litre. The kgCO2e emissions for producing a kWh of shaft power under optimal conditions can be calculated therefore as follows:

                  3.24kgCO₂e/litre

                  3.86kWh/litre         = 0.839kgCO₂e/kWh

²¹
DEFRA Emission Factor from 2012 Guidelines to Defra / DECC’sGHG Conversion Factors for Company Reporting, produced byAEA for the Department of Energy and Climate Change (DECC)and the Department for Environment, Food and Rural Affairs(Defra), 2012, p41.

²²
Food Transport Refrigeration, S.A. Tassou et al., Brunel University, Centre for Energy and Built Environment Research.

²³
Professor Savvas Tassou, Brunel University, personal communication February 2013.

²⁴
Co-efficients of performance typically between 0.5 and 1.5compared to a theoretical limit of around 5; Food Transport Refrigeration, S.A. Tassou et al., Brunel University, Centre for Energy and Built Environment Research.

 ²⁵
Physical property latent heat of vaporisation ~0.055kWh/kg and specific heat capacity 0.0029 kWh/kg/K.

²⁶
Work available from an adiabatic expansion from ~300 bar of nitrogen gas from 0C.

²⁷ 0.5 x 50Wh/kg = 25Wh/kg and 1.5 x 50Wh/kg = 75Wh/kg.

²⁸
Special Report: Cryogenic Truck Refrigeration with Nitrogen, Global Cold Chain News, February 2011.

²⁹
Assumes average UK grid intensity of 0.547kgCO2/kWh, DEFRA Emission Factor from 2012 Guidelines to Defra / DECC’s GHG Conversion Factors for Company Reporting, produced by AEA for the Department of Energy and Climate Change (DECC)and the Department for Environment, Food and Rural Affairs(Defra), 2012, p14. 

³⁰
Special Report: Cryogenic Truck Refrigeration with Nitrogen, Global Cold Chain News, February 2011.

³¹
Refrigerated Transportation, A Global Strategic Business Report, Global Industry Analysts; see also Refrigerated Transportation Market to Cross $6.5 Billion by 2015, According to New Report by Global Industry Analysts, Inc., 13 April 2009, http://www. prweb.com/releases/refrigerated_vans_trucks/transportation_trailers/prweb2308894.htm

³²
Refrigerated Truck/Van Body and Refrigerated Trailer Manufacturing in North America, STN.