Influence of Waste Management on the Environmental Footprint of Electricity Produced by Photovoltaic Systems
Abstract
:1. Introduction
1.1. Motivation
1.2. LCA of Waste Management for PV Systems
2. Materials and Methods
2.1. Product Systems Description
- Life expectancyModules: 30 years (for any type)Inverters: 15 yearsMounting structure: 30 years (for any type of module)Cabling: 30 yearsManufacturing plant: 30 years (for any type of module)Recycling plant: 30 years (for any type of module)
- Performance Ratio: Standard value of 0.75
- Degradation rate: Standard linear degradation rate of 0.7% per year
- Conversion efficiency from primary energy to electricity: ηG = 30%
- Irradiation: Conditions in Germany: 1.055 kWh/m2 [23]
2.2. Characterization of Modules and Input Waste
2.3. Description of the EoL Approaches
2.4. Sensitivity Analysis
- Scenario n°2: Changing recycling efficiency due to enhanced processes or bigger flows of material. An energy demand of 60% of the value in the baseline scenario is assumed.
- Scenario n°3: Changing primary material content due to increased recycled fraction. Usually, environmental credits are given for the primary material content existing in the market at the moment the recycling is performed. However, since recycling is assumed to take place after 30 years of installment of the modules, its environmental performance would be better described if the calculations contained estimates of the primary material content in 2040. For the baseline scenario, these values are 48%, 56% and 77%, while for 2040, these are assumed to be 41%, 48% and 65% for aluminum, copper and silver respectively [26,27].
- Scenario n°4: Reduced transportation due to an efficient collection network. It will be assumed that the waste management network is optimized in a way that transportation demands are reduced 50% of the initial estimate.
- Scenario n°5: Year 2040, combined conditions. It is fair to assume that future conditions would be better represented by the combination of the previously described scenarios. To obtain a more accurate perspective of the overall impact in the future the assumptions in the previous scenarios have been taken into account in one single analysis. This scenario is shown for illustrative purposes and entails a high level of uncertainty.
3. Results
3.1. Electricity Production
3.2. Sensitivity Analysis
3.3. Greenhouse Gas Emissions
3.4. Energy Payback Time
4. Discussion
5. Conclusions
Author Contributions
Funding
Conflicts of Interest
Appendix A
Climate Change | Human Toxicity (Non-Cancer) | Human Toxicity (Cancer Effects) | Particulate Matter | Acidification | Freshwater Ecotoxicity | Resource Depletion | |
---|---|---|---|---|---|---|---|
Appr. n°1 | −2.0% | −0.6% | −6.6% | −1.4% | −2.0% | 0.0% | −0.2% |
Appr. n°2 | −2.0% | −0.9% | −6.8% | −1.5% | −2.0% | −0.1% | −0.2% |
Appr. n°3 (A) | −2.1% | −0.7% | −6.7% | −1.5% | −2.0% | 0.0% | −0.2% |
Appr. n°3 (B) | −2.1% | −0.7% | −6.6% | −1.5% | −2.0% | 0.0% | −0.2% |
Appr. n°4 (A) | −2.0% | −0.6% | −6.5% | −1.4% | −2.0% | 0.0% | −0.2% |
Appr. n°4 (B) | −2.0% | −0.6% | −6.5% | −1.4% | −2.0% | 0.0% | −0.2% |
Appr. n°5 | −3.7% | −4.2% | −7.7% | −4.6% | −3.0% | −1.1% | −12.1% |
Appr. n°6 | −3.9% | −4.1% | −7.9% | −4.6% | −3.0% | −1.1% | −12.1% |
Climate Change | Human Toxicity (Non-Cancer) | Human Toxicity (Cancer Effects) | Particulate Matter | Acidification | Freshwater Ecotoxicity | Resource Depletion | |
---|---|---|---|---|---|---|---|
Appr. n°1 | −3.0% | −0.7% | −7.6% | −2.2% | −2.7% | 0.0% | −0.2% |
Appr. n°2 | −3.1% | −1.0% | −7.9% | −2.3% | −2.8% | −0.1% | −0.2% |
Appr. n°3 (A) | −3.3% | −0.7% | −7.8% | −2.2% | −2.7% | 0.0% | −0.2% |
Appr. n°3 (B) | −3.2% | −0.7% | −7.7% | −2.2% | −2.7% | 0.0% | −0.2% |
Appr. n°4 (A) | −3.1% | −0.7% | −7.6% | −2.2% | −2.7% | 0.0% | −0.2% |
Appr. n°4 (B) | −3.0% | −0.7% | −7.6% | −2.2% | −2.7% | 0.0% | −0.2% |
Appr. n°5 | −5.8% | −4.5% | −9.0% | −7.1% | −4.1% | −1.2% | −11.0% |
Appr. n°6 | −6.1% | −4.5% | −9.2% | −7.1% | −4.1% | −1.2% | −11.0% |
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Parameter | Mono-Si | Multi-Si | |
---|---|---|---|
Location of Manufacturing (Market Share) | China (CN) | 79.6% | |
Europe (RER) | 14.5% | ||
Asia Pacific (APAC) | 5.9% | ||
Plant size (kWp) | 3 | 3 | |
Module efficiency | 14% | 13.60% | |
Panel capacity rate (Wp/m2) | 140 | 136 | |
Module lifetime (Years) | 30 | 30 | |
Module weight (kg/m2) | 10 | 10 | |
Module Area (m2) | 1.6 | 1.6 |
Module Section | Material | Mass Fraction |
---|---|---|
Front glass | Glass | 70.00% |
Frame | Aluminium | 18.00% |
Junction box | Copper | 0.33% |
Plastic junction box | 0.67% | |
Encapsulant | EVA | 5.10% |
Backsheet | PET | 1.50% |
Solar cell | Silicon | 3.65% |
Aluminium | 0.53% | |
Copper | 0.11% | |
Silver | 0.05% | |
others | other metals (tin, lead) | 0.05% |
Sealant, potting | 0.00% |
Appr. | Materials Recovered | Unrecovered Fraction Disposal Method |
---|---|---|
n°1 | Glass, Aluminum, copper | Landfilling |
n°2 | Glass, Aluminum, copper | Landfilling/Incineration |
n°3 | Glass, Aluminum, copper | Landf *./Inciner **./Inciner. of Backsheet |
n°4 | Glass, Aluminum, copper | Landf./Inciner./Pyrol. of Backsheet |
n°5 | Glass, Aluminum, copper, MG-Si, Silver | Landfilling/Incineration |
n°6 | Glass, Aluminum, copper, MG-Si, Silver | Landfilling/Pyrolysis |
No EoL | Appr. | Appr. | Appr. 3 | Appr. 4 | Appr. | Appr. | |||||
---|---|---|---|---|---|---|---|---|---|---|---|
1 | 2 | (A) Fluor- Free | (B) Fluor | (A) Fluor- Free | (B) Fluor | 5 | 6 | ||||
Mono-Si | CED (GJ) | 127.3 | CED saving (GJ) | −3.00 | −3.70 | −3.24 | −3.20 | −3.05 | −3.05 | −5.93 | −5.69 |
EPBT (Years) | 4.5 | EPBT incl. EoL (years) | 4.36 | 4.34 | 4.35 | 4.36 | 4.36 | 4.36 | 4.26 | 4.27 | |
% Reduction | 2.4% | 2.9% | 2.5% | 2.5% | 2.4% | 2.4% | 4.7% | 4.5% | |||
Multi-Si | CED (GJ) | 88.6 | CED saving (GJ) | −3.20 | −3.95 | −3.45 | −3.41 | −3.25 | −3.25 | −6.32 | −6.07 |
EPBT (Years) | 3.1 | EPBT incl. EoL (years) | 3.00 | 2.97 | 2.99 | 2.99 | 3.00 | 3.00 | 2.89 | 2.90 | |
% Reduction | 3.6% | 4.5% | 3.9% | 3.8% | 3.7% | 3.7% | 7.1% | 6.9% |
Year | Area | PV Waste (Million Tons) | Cumulative Million Ton CO2-eq | |
---|---|---|---|---|
MIN | MAX | |||
2040 | Germany | 2.4 | 2.04 | 4.08 |
Global | 23.5 | 19.95 | 39.90 | |
2050 | Germany | 4.3 | 3.65 | 7.30 |
Global | 69 | 58.57 | 117.16 |
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Herceg, S.; Pinto Bautista, S.; Weiß, K.-A. Influence of Waste Management on the Environmental Footprint of Electricity Produced by Photovoltaic Systems. Energies 2020, 13, 2146. https://doi.org/10.3390/en13092146
Herceg S, Pinto Bautista S, Weiß K-A. Influence of Waste Management on the Environmental Footprint of Electricity Produced by Photovoltaic Systems. Energies. 2020; 13(9):2146. https://doi.org/10.3390/en13092146
Chicago/Turabian StyleHerceg, Sina, Sebastián Pinto Bautista, and Karl-Anders Weiß. 2020. "Influence of Waste Management on the Environmental Footprint of Electricity Produced by Photovoltaic Systems" Energies 13, no. 9: 2146. https://doi.org/10.3390/en13092146
APA StyleHerceg, S., Pinto Bautista, S., & Weiß, K. -A. (2020). Influence of Waste Management on the Environmental Footprint of Electricity Produced by Photovoltaic Systems. Energies, 13(9), 2146. https://doi.org/10.3390/en13092146