Técnicas para la identificación y/o evaluación de riesgos

In order to assess the environmental impact battery storage options can have when included in a decentralised RET system, a LCA is undertaken of the four main available options. In addition an evaluation of the repurposing of EOL batteries from automotive uses is completed to assess the offsetting benefits second life batteries can have.

The International Organisation for Standardisation (ISO) standards for LCA (ISO 14040 and 14044) are used as a guide for the completion of this study.

3.2.1.Goal & Scope Of LCA

The goal of the LCA completed in this study was to establish and compare the additional environmental impacts which can be attributed to a decentralised RET system through the use of various chemical energy storage systems, and explore how these impacts can offset the carbon saving made through the use of RETs.

The LCA considered the cradle-to-gate emissions emitted during the production of a battery with the functional unit being 1 kg of battery. Data was gathered from literature sources to quantify the emissions of GHGs (CH4, N2O, CO2) and those which lead to

localised air pollution (particulate matter (PM), volatile organic compounds (VOC), mono-nitrogen oxides (NOx)).

The results were used to establish the total global warming potential (GWP) (tCO2e)

and volume of additional CO2 which is attributable to a battery system suitable to meet

the per capita energy demands of India’s rural households using 3 different energy demand scenarios.

Furthermore the LCA explored the offsetting effect repurposing Li-ion batteries can have on reducing the carbon footprint of decentralised RET system. In order to do this, the total CO2 avoided during the batteries primary use phase was calculated and then the

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3.2.2.LCA Assumptions

Total emissions of individual GHGs and other selected pollutants were quantified through a cradle-to-gate LCA by Sullivan & Gaines (2012). These results are used as a basis for this study and constitute the total emissions for individual battery production from raw material extraction through to final product assembly (Sullivan & Gaines 2012).

From these quantified emissions, the total GWP of each battery was calculated by taking the GWP value of each GHG outlined by the IPCC (IPCC 2013) and converting the relative emissions from each battery into their kg CO2e/kg and then aggregating the

total value.

Energy density denotes the amount of energy that can be stored relative to a given mass and thus the battery size required to meet a set level of demand. The energy density of each battery was calculated by taking the mean from multiple literature sources (Appendix 2) (Díaz-González et al. 2012, Evans et al. 2012, Hadjipaschalis et al. 2009, Kousksou et al. 2014, Råde & Andersson 2001, Rahman et al. 2012, Rantik & Tekniska 1999, Rydh & Karlström 2002, Sullivan & Gaines 2010, Sullivan & Gaines 2012, Van den Bossche et al. 2006, Yekini Suberu et al. 2014).

To represent the repurposing of an EOL Li-ion battery, it is assumed that its capacity has degraded by 20.0% as is suggested in the literature (Ahmadi et al. 2014, Richa et al. 2014, Williams & Lipman 2010).

The life span of a Li-ion battery in a hybrid passenger vehicle varies considerably from 150,000 to 360,000 km (Ahmadi et al. 2014, Broussely 2010, Faria et al. 2014, Samaras 2008, Sullivan & Gaines 2012, Van den Bossche et al. 2006, Williams & Lipman 2010). The difference in life span impacts upon the volume of CO2e avoided a longer

life span the more CO2e that is avoided in comparison to a conventional passenger

vehicle. These batteries are however expected to last the total service life of the vehicle they are installed in and be comparable to conventional passenger vehicles. Thus in this LCA, it is assumed that the Li-ion will match the predicted service life of a passenger vehicle as specified by the EU of 200,000 km (EU 2009).

Working under this assumption and using the volume of CO2 emitted during the use

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it is possible to estimate the CO2 saving made per km and throughout the entire vehicles

service life.

The methods of calculating the total carbon saving made per km by a hybrid vehicle compared to a conventional passenger vehicle is outlined in Equation 3.1 Part A. Part B summarises the total carbon saving that would be made by a hybrid vehicle meeting the EU specified service life target of 200,000 km for a passenger vehicle.

Equation set 3.2 Part A outlines the method of calculating the distance a hybrid vehicle needs to travel to offset the total carbon debt associated with its Li-ion batteries production.

The data used to calculate the total kg CO2 emitted per km are obtained from Ahmadi et

al (2014), with the total battery mass (M) used from Samaras (2008) when calculating total distance to offset 1 kg of Li-ion battery.

Equation 3.1: Part A 𝑨 = 𝟑𝟕, 𝟒𝟎𝟎 𝟏𝟔𝟎, 𝟎𝟎𝟎 𝑩 = 𝟏𝟎, 𝟕𝟎𝟎 𝟏𝟔𝟎, 𝟎𝟎𝟎 𝑪𝒔 = 𝑨 − 𝑩 Part B 𝑻𝑪𝒔 =𝑪𝒔 ∙ 𝑪 𝟏𝟎𝟎𝟎

A = total kg CO2 emitted/km by conventional passenger

vehicle.

B = total kg CO2 emitted/km by hybrid passenger vehicle using

Li-ion battery.

Cs = total carbon saving kg/km.

C = EU specified passenger vehicle service life distance (km). TCs = total carbon saving across whole service life (tonnes).

Equation 3.2: Part A 𝑻𝑪𝒅 = 𝑴 ∙ 𝑮𝑾𝑷

𝑻𝒐𝑫

TCd = total carbon debt (kg CO2e).

M = 252 kg (battery mass).

GWP = global warming potential (CO2e) per kg of battery.

ToD = distance for total carbon offset of battery (km). Cs = total carbon saving kg/km (Equation 5.1: Part A). D = distance to offset carbon debt of 1 kg (km).

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The per capita energy demand of India’s rural households is measured in end-use energy demand rather than total energy consumption. Total energy is a measure of the energy used without considering levels of efficiency. End-use energy is adjusted and accounts for losses to measure actual energy used (Khandker et al. 2010).

The per capita energy demand was calculated using rural energy use patterns available from the Development and Research group at The World Bank (Khandker et al. 2010). The efficiency values used by the World Bank as well as energy consumption estimates of different appliances (O’Sullivan & Barnes 2006, Rogers et al. 2008) were used to calculate an estimate of the per capita energy consumption of the archetypal rural household based on the survey findings from Chapters 4 and 5 (Appendix 3). Comparisons of these separate scenarios allow evaluation of how per capita energy demand varies depending upon the scope of population being assessed. Table 3.1 provides a summary of each scenario.

Table 3.1: Scenarios for per capita energy demand comparison

Scenario details Scenario level

Scenario 1 National per capita energy usage of India’s rural

communities (Khandker et al. 2010) National Scenario 2 Typical household from Uddhar village in Raigarh

district Maharashtra. Summary Chapter 4.2.7 Single village Scenario 3 Standard household from state of Orissa.

Summary Chapter 5.3.7 Single state