Example of Process-Based Life Cycle Inventory:

Although energy consumption and CO2 emissions are often good indicators of over-all emissions and impacts of energy-related processes (Beck 1999; Huijbregts et al.

2010), they are not sufficient to estimate other impacts, such as human toxicity and ecotoxicity. For these impact categories, all emissions must be carefully inventoried to analyze their different impacts. The generalization of the inventory analysis phase to a large number of substances emitted or extracted is illustrated using the concrete example of the front-end panel of a car. For this study, the goal definition (the first phase of the LCA) can be summarized as follows:

• Function and FU: The function of the front-end panel is to hold various parts (lights, ventilator, etc.) throughout the lifetime of the automobile.

The FU is a front-end panel with an adequate rigidity, transported over 200,000 km, which is a typical distance traveled by an automobile over its lifetime.

• System boundary: The analysis accounts for the entire chain of energy extraction and preparation needed for the component, the manufacturing and disposal of the component, and, most importantly, the component use during car operation.

• Scenarios and reference flows: Four scenarios are considered and com-pared, each with a front-end panel made from one of the following

58 Environmental Life Cycle Assessment materials—steel, a composite plastic material, virgin aluminum, and recy-cled aluminum. The necessary reference flows for each scenario are listed in Table 4.4.

Table 4.4 presents the reference and first-tier intermediary flows for each front-end panel scenario, including the material mass and electricity use for each process in the extraction, manufacturing, use, and end-of-life stages. The quantity of gaso-line used to transport a front-end panel over 200,000  km is calculated assuming consumption of 0.00004 L more gasoline for each additional kilogram that is car-ried 1 km. At the end of life, the steel and virgin aluminum front-end panels are placed in landfills. The composite front-end panel is assumed to be incinerated in an incineration plant for household waste. Finally, the recycled aluminum front-end panel is recycled once more after usage, so we do not include any ultimate end of life in this scenario.

The emission and extraction factors for each reference flow are given in Table 4.5, and Table 4.6 presents the final inventory results of extraction and emission.

The emission and extraction matrix E lists the emissions or extraction factors of each substance over the whole production chain for each process; it speci-fies the extraction from or emission to different environmental media (air, water, and soil) per main intermediary unit process (material, electricity, etc.). Table 4.5 presents an excerpt of this matrix for a few substances and for the nonrenewable primary energy consumption. The complete inventory considers more than 500 substances.

TABLE 4.4

Reference Flows and Main Intermediary Flows for a Front-End Panel Transported over 200,000 km

Unit Steel Composite

Virgin Aluminum

Recycled Aluminum Materials

Final weight kg 10.0 7.0 3.8 3.8

Manufacturing

Electricity kWh 19.7 4.7 15.2 15.2

Oil kg 2.3 0.56 1.8 1.8

Use

Gasoline L 80.0 56.0 30.4 30.4

End of Life

Incineration kg – 7.0 – –

Controlled landfilling kg – – 3.8 –

Landfilling for inert materials kg 10.0 – – –

Inventory Analysis of Emissions and Extractions 59

TABLE 4.5 Matrix E of Aggregated Emission and Extraction Factors for the Inputs Involved in the Production of a Front-End Panel Transported over 200,000 km (excerpt from ecoinvent 1.0a) SteelComposite MaterialNonrecycled AluminumRecycled AluminumElectricity (Europe)OilGasolineLandfilled SteelLandfilled AluminumPropylene Incineration kgkgkgkgkWhkgLkgkgkg Resources EnergyMJ24.779.916221.810.556.943.20.210.530.21 Emissions to Air CO2kg1.281.859.501.200.453.672.800.010.022.54 CO kg0.0230.000760.00570.00110.000160.00130.000670.0000420.0000970.00026 CH4kg0.00270.00600.0150.00150.000640.00320.00131.8E–053.8E–052.2E–05 N2Okg3.8E–051.3E–070.000272.5E–051.1E–054.1E–058.1E–062.1E–075.4E–074.8E–06 NOxkg0.00540.00960.0220.00250.000820.00370.00180.000150.000290.00039 SO2kg0.00400.0130.0380.00350.00180.00520.00441.1E–053.0E–051.9E–05 Particleskg0.00210.000380.00550.000430.000120.000240.000181.4E–052.8E–051.3E–05 Pbkg5.6E–065.1E–091.9E–064.2E–056.5E–083.5E–071.7E–072.3E–091.0E–087.7E–09 Emissions to Water Nitrateskg1.6E–051.9E–051.9E–041.6E–057.9E–061.1E–057.4E–065.3E–081.9E–075.4E–05 Pbkg1.5E–051.0E–061.1E–054.8E–064.5E–071.3E–067.1E–072.9E–082.6E–051.5E–06 a For future studies, we recommend using the latest ecoinvent data for these factors.

60 Environmental Life Cycle Assessment

For each scenario (Equation 4.1), the inventory vector u of emissions and extrac-tions per FU (Table 4.6) is the product of the matrix of aggregated emission and extraction factors E (Table 4.5) with the demand vector y of first-tier intermediary flows (Table 4.4).

Inventory of Emissions and Extractions for a Front-End Panel Transported over 200,000 km

Substance Unit Steel Composite Aluminum

Recycled Aluminum Resources

Energy MJ 4043 3061 2193 1658

Emissions in air

CO₂ kg 253.9 176.4 134.6 103.2

CO kg 0.294 0.045 0.047 0.029

CH₄ kg 0.154 0.122 0.112 0.062

N2O kg 0.0013 0.0005 0.0015 0.0006

NO_x kg 0.221 0.172 0.156 0.083

SO₂ kg 0.439 0.348 0.315 0.184

Particles kg 0.0383 0.0136 0.0287 0.0095

Pb kg 7.16 × 10^–5 1.03 × 10^–5 1.41 × 10^–5 1.65 × 10^–4 Emissions in water

Nitrates kg 9.30 × 10^–4 6.44 × 10^–4 1.07 × 10^–3 4.25 × 10^–4 Pb kg 2.13 × 10^–4 5.13 × 10^–5 9.70 × 10^–5 4.91 × 10^–5

Inventory Analysis of Emissions and Extractions 61

The units and calculations can be checked by writing out the matrix multiplica-tion for a whole row, such as CO2 emissions in the second row:

1.28  kgCO2/kg steel × 10.0  kg steel/FU + 0.45  kgCO2/kWh electricity × 19.7  kWh electricity + 3.67  kgCO2/kg fuel × 2.3  kg fuel/FU + 2.80  kgCO2/L gas × 80.0  L gas/

FU + 0.01 kgCO2/kg landfilled steel × 10.0 kg landfilled steel/FU = 253.9 kgCO2/FU.

In comparing the inventories for the different scenarios (Table 4.6), we see that no single scenario has the minimum values for all polluting substances and energy consumption. Indeed, the steel scenario results in the highest CO2, CO, and SO2 air emissions, but the virgin aluminum scenario emits more nitrates, and the recycled aluminum scenario emits more lead (Pb) to air. For many substances (e.g., CO2, CH4, NOx), the composite scenario emits less than the steel scenario, but more than both aluminum scenarios. At this stage, it is therefore impossible to rank the scenarios by environmental impact. The subsequent impact assessment phase (Chapter 5) is essential to compare the impacts generated by these different emissions and thus compare scenarios.

It is nevertheless interesting to interpret the raw inventory results, which have less uncertainty than the impact assessment results and can already provide guid-ance on the effects of different assumptions or choices. The most primary energy is consumed in the steel scenario, which is mainly due to gasoline usage under the assumption of 200,000 km travel distance. By recalculating primary energy usage based on varying distances (Figure 4.3), we find that although the recycled alumi-num front-end panel consumes the least energy regardless of distance traveled, the virgin aluminum front-end panel actually consumes more energy than the steel and composite front-end panels below around 27,000 and 50,000 km, respectively. The steel scenario consumes more primary energy over its life cycle than the composite scenario as soon as the distance traveled surpasses 10,000 km.

In the example given previously, the calculation is based on the emission and extraction factors provided by large inventory databases, and are the result of aggre-gated data from hundreds of unit processes. The use of these factors is easy, but determination of their values requires lengthy, rigorous work; thus, it is advantageous

62 Environmental Life Cycle Assessment

to use existing databases whenever possible. Use of such databases also helps scale up the simple and practical approach illustrated here to calculate the environmen-tal inventory for a large number of unit processes using matrix calculations (see Section 4.2.4).