Environmental Externalities of Secondhand Markets—Based on a Dutch Auctioning Company
Abstract
:1. Introduction
2. Literature Review
3. Materials and Methods
3.1. Unit of Measurement
3.2. Calculation of the Effects of the Secondhand Market
3.3. Troostwijk Data
3.4. Levels of the Calculation
Product | N (Survey) | Age a (Years) | Residual Life r (Years) | Lifespan l (Years) | Volume (m3) | Mass w (kg) | Fuel | Metal |
---|---|---|---|---|---|---|---|---|
Chair | 12 (12) | 9 | 15 | 10 | 0.23 | - | None | None |
Table | 9 (8) | 3 | 7 | 10 | 0.89 | - | None | None |
Refrigerator | 12 (11) | 7 | 8 | 12 | 1.80 | 278 | None | None |
Laptops | 22 (20) | 5 | 4 | 7 | 0.003 | - | None | None |
Hand drill | 12 (11) | 11 | 7 | 12 | - | 7.5 | None | None |
Car | 19 (19) | 18 | 6 | 10 | 17.37 | 1576 | Diesel | None |
Forklift truck | 29 (29) | 14 | 9 | 16 | 7.12 | 3677 | Electric | None |
Lawn mower | 21 (21) | 8 | 8 | 12 | 0.87 | 41 | Gasoline | None |
Tractor | 7 (7) | 15 | 10 | 17 | 36.82 | 6573 | Diesel | None |
Power generator | 16 (16) | 7 | 9 | 10 | 4.47 | 1229 | Diesel | None |
Hardwood | 21 (19) | 1 | 24 | 8 | 0.64 | - | None | None |
Scaffolds | 9 (8) | 3 | 11 | 19 | 0.99 | 211 | None | Steel |
Name in Troostwijk Data (Name in Database) | Mean | Distribution |
---|---|---|
Dining chairs (Furniture) | 10.4 | Weibull ( = 11.6, = 1.55) |
Electric hand drills (Other household electric appliances) | 12.4 | Weibull ( = 14.0, = 1.84) |
Cars (Passenger Cars) | 10.2 | Weibull ( = 11.5, = 2.32) |
Forklift trucks (Forklift trucks) | 16.1 | Weibull ( = 18.1, = 2.40) |
Hardwood (Wood products) | 7.5 | Weibull ( = 8.4, = 2.76) |
Horeca refrigerators (Electric refrigerators) | 12.3 | Weibull ( = 13.8, = 1.83) |
Laptops (Personal computers) | 6.5 | Weibull ( = 7.3, = 2.76) |
Lawn mowers (Other products) | 12.1 | Weibull ( = 13.5, = 1.52) |
Power generators (Generators and Motors) | 10.3 | Weibull ( = 11.4, = 1.55) |
Restaurant tables (Furniture) | 10.4 | Weibull ( = 11.6, = 1.55) |
Scaffolding (Steel pipes and tubes) | 18.6 | Weibull ( = 21.0, = 1.92) |
4-Wheel Drive Tractors (Agricultural machinery and equipment) | 17.3 | Weibull ( = 19.5, = 1.95) |
3.5. Carbon Footprints (Manufacture, EoL, Utilization)
Product | Source Manufacturing Emissions | Source Annual Usage Emissions | Efficiency Changes |
---|---|---|---|
Lawn mower | ADEME [29] | ADEME [29] | No efficiency changes (no literature found and no GHG regulation [30]) |
Power generators | ADEME [29] | ADEME CIGREF [31] (p. 120) (total, and basis for mean lifespan) | No efficiency changes (Li et al. [32]; and no GHG regulation [30,33]) |
Scaffolds | ADEME [29] (steel products), this roughly corresponds to Laleicke et al. [34] | - | - |
Refrigerators | ADEME [29] | ADEME [29] (total, and mean lifespan) | National Statistics UK [35], fitted with an exponential function (Figure 2) |
Laptops | ADEME [29] | ADEME [29] (total, and mean lifespan) | National Statistics UK [35], fitted with an exponential function (Figure 2) |
Hand drills | ADEME [29] | ADEME [29] (total, and mean lifespan) | No efficiency changes (no literature found and Cooper Gutowski [10] imply that power tools are expected to become more efficient only in the future) |
Cars (diesel and gasoline) | ADEME [29] (’vehicles’, per tonne) | ADEME [29] (per km, and data on annual distance) | “Technical efficiency improvements” [15], fitted with an exponential function (Figure 2) |
Tables | ADEME [29] (’Representative table 4 places’) | - | - |
Chairs | ADEME [29] (’Mix chair (wood structure and textile cover)’) | - | - |
Hardwood | ADEME [29] (’timber’, per tonne) | - | - |
Forklift trucks (general) | - | 2000 operating hours/year (50 working weeks, see unofficial sources such as [36]) | 0.5% annual efficiency increase, based on 1% for trucks and vans [37,38], halved because improvements in light-weighting and aerodynamics [15] will play a smaller role during lifting and because of low speed, respectively |
Forklift trucks (electric) | ADEME [29] (’vehicles’, per tonne, assuming that battery production adds about 38% to vehicle production [39]) | Hourly emissions [40], with the GHG intensity of electricity replaced by that of Europe according to Base Carbone | See above |
Forklift trucks (fossil fuel) | ADEME [29] (’vehicles’, per tonne) | Hourly emissions [40], different fossil fueled forklift trucks assumed comparable because they form one main class of forklift trucks together [40] | See above |
Tractors | ADEME [29] (’vehicles’, per tonne) | Total usage contributes to 85% of emissions in 15 years [41] | NTTL [42] (kWh/liter of 4-wheel drive tractors at rated engine speed in 1990–2020 (), fitted with an exponential function (Figure 2) |
- Uncertainty about emission factors;
- Variation in the goods of the same product type.
3.6. Efficiency Changes
3.7. Lifespans
3.8. Transport Emissions
3.9. Displacement Rate and Residual Lifetime
3.10. Age, Mass and Volume
4. Results
4.1. Effects of Typical Lots on GHGs
4.2. Residual Lifetime Models
4.3. Sums of Lots
5. Discussion
5.1. Summary of Findings
5.2. Comparison with Existing Literature
5.3. Implications for Policy and Practice
5.4. Limitations
5.5. Recommendations for Further Research
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
Abbreviations
Abbreviations | |
ADEME | Agence de l’Environnement et de la Maîtrise de l’Énergie |
CO2 | Carbon dioxide |
CO2e | Carbon dioxide equivalents |
EoL | End-of-life |
EU | European Union |
GHG | Greenhouse gas |
GWP | Global warming potential |
LCA | Life cycle assessment |
N2O | Nitrous oxide |
R-squared | |
Notation | |
a | Age of a good (years) |
c | Relative increase in energy consumption for each year that a good is older |
The distance between seller x and buyer y (km) | |
Displacement rate for new goods (number of purchases of new goods that a sold | |
secondhand good avoids) | |
Displacement rate for used goods (number of purchases of used goods that a sold | |
secondhand good avoids) | |
Expected value | |
The end-of-life emissions of a new product including all the other emissions | |
downstream (kg of CO2e) | |
The emission factor of transportation between seller x and buyer y (kg of CO2e | |
per km) | |
l | The lifespan of a new good (years) |
The manufacturing emissions of a new good including all the other emissions | |
upstream (kg of CO2e) | |
n | Sample size |
r | The residual lifetime of a secondhand good (years) |
Random variable with a Student’s t distribution with degrees of freedom | |
T | Transaction emissions of a secondhand sale (kg of CO2e) |
The share of total goods of a certain type going from seller x to buyer y | |
Emissions due to the usage of a new good (kg of CO2e) | |
Annual emissions due to the usage of a new good (kg of CO2e) | |
Emissions due to the usage of a secondhand good (kg of CO2e) | |
Annual emissions due to the usage of a secondhand good (kg of CO2e) | |
Y | The total impact in terms of greenhouse gases of a secondhand sale (kg of CO2e) |
w | Weight or mass (kg) |
The shape parameter in the Weibull distribution | |
Coefficient in a linear regression | |
Residual term in a linear regression | |
The scale parameter in the Weibull distribution | |
Standard deviation |
Appendix A. Survey Questions
- What kind of lot have you bought in 2020 or 2021? If you have bought multiple lots, you would be of big help if you filled in the survey for the other lots as well! If you do not want to do that, please fill in this survey for the oldest lot of the highest possible category as listed below.Options: Restaurant Tables; 4-Wheel Drive Tractors; Horeca Refrigerators; Power Generators, Electric hand drills; Scaffolding; Hardwood; Dining Chairs; Lawn Mower; Laptops; Cars; Vans; Forklift Trucks; Garages
- How old is your lot?
- How many years do you expect your lot to be used from now?
- What would you have done if you had not been able to purchase this product secondhand online?Options: I would have bought nothing; I would have bought a new product of the same quality; I would have bought a new, cheap product; I would have bought an older used product (offline); I would have bought a similar used product (offline); Other, namely…
- By buying at Troostwijk…Options: …I save money; …I spend more money; …I do not spend more or less money than without Troostwijk; Cannot answer
- What kind of lot have you bought in 2020 or 2021? If you have bought multiple lots, you would be of big help if you filled in the survey for the other lots as well! If you are unable to do so, please fill in this survey for the oldest lot of the highest possible category as listed below.[So if you have won multiple lots, choose the lot that is highest on the list below. For example, if you won a scaffold and a laptop, please choose the scaffold. If you won multiple lots of the same type, please choose the one with the oldest construction year.]Options: 4-Wheel Drive Tractors; Horeca Refrigerators; Restaurant Tables; Scaffolding; Electric hand drills; Vans; Cars; Dining Chairs; Power Generators; Laptops; Hardwood; Lawn Mowers; Forklift Trucks; Garages
- What is your lot’s construction year?[For example, a 17-year old lot was manufactured in 2004.]
- How many years do you expect your lot to be used from now? If you do not know, please give a rough estimate.
- What would you have done if you had not been able to purchase this item secondhand online (so if online platforms such as Troostwijk had not existed)?Options: I would have bought nothing; I would have bought a new item of the same quality (this can be either online or offline); I would have bought a new, cheap item of lower quality (this can be either online or offline); I would have bought an older used item (offline, for example at a dealer or in a store); I would have bought a similar used item (offline); Other, namely…
- By buying at Troostwijk…Options: …I save money, …I spend more money, …I do not spend more or less money than without Troostwijk; Cannot answer
Appendix B. Other Figures and Tables
Chair | Table | Refrigerator | Laptop | |
---|---|---|---|---|
Lower bound | −11.65 | −81.72 | −43.82 | −74.47 |
Expectation | −3.22 | −43.83 | 34.33 | −12.81 |
Upper bound | 1.20 | −22.25 | 104.88 | 42.89 |
Hand drill | Car | Forklift truck | Lawn mower | |
Lower bound | −12.94 | 3663.84 | 49,704.09 | −41.79 |
Expectation | −5.89 | 7147.77 | 124,614.02 | 76.75 |
Upper bound | −0.00 | 10,608.52 | 377,981.80 | 175.21 |
Tractor | Hardwood | Power generator | Scaffolding | |
Lower bound | 4342.88 | −6.40 | −5103.46 | −216.10 |
Expectation | 31,986.53 | −0.33 | 1148.31 | −141.91 |
Upper bound | 65,655.70 | 5.59 | 6292.19 | −92.11 |
Chair | Table | Refrigerator | Laptop | |
---|---|---|---|---|
Lower bound | −49.53 | −306.00 | −464.67 | −425.69 |
Expectation | −21.04 | −180.77 | −279.53 | −260.69 |
Upper bound | −10.60 | −118.87 | −121.05 | −99.06 |
Hand drill | Car | Forklift truck | Lawn mower | |
Lower bound | −54.98 | −7450.89 | −37,822.54 | −652.30 |
Expectation | −33.76 | −2775.76 | 69,972.78 | −295.93 |
Upper bound | −14.70 | 1766.14 | 550,504.55 | −111.46 |
Tractor | Hardwood | Power generator | Scaffolding | |
Lower bound | −72,840.91 | −30.30 | −38,561.82 | −773.72 |
Expectation | −45,637.64 | −20.66 | −21,274.70 | −548.72 |
Upper bound | −21,781.11 | −12.06 | −7918.60 | −421.38 |
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Aspect | Included? |
---|---|
Delayed or prevented manufacturing and end-of-lofe (EoL) emissions [5,10]; the EoL phase can also reduce emissions due to recycling [10]. | Yes |
Higher energy efficiency of newly manufactured goods [2,6,10,14] | Yes |
Transportation emissions [2,5] | Yes |
A displacement rate below 1, i.e., not all buyers of used goods would alternatively have purchased a new good [5,10,13,14]. | Yes |
Changing efficiency over a good’s lifetime [10,11,15] | No |
Decreasing product lifespans [11] | No |
Acceleration of consumption [2] because of the existance of a secondhand market [10] and less minimalist attitudes [4,14] | No |
A rebound effect due to the monetary gains from secondhand trade [2,7,14] | No |
Different recycling effectiveness internationally, formally or informally, when used goods are sold to other countries [16,17]. | No |
Used goods replacing even older goods [18] | No |
Higher environmental impact of cheap new goods than of higher-quality new goods [2] | No |
Used goods displacing goods of other types [13] | No |
Estimate | Std. Error | p-Value | |
---|---|---|---|
: Intercept | 4.870 | 1.134 | 0.000 |
: Age () | −1.761 | 0.600 | 0.004 |
: Lifespans () | −1.133 | 0.481 | 0.020 |
Age × lifespans | 0.696 | 0.246 | 0.005 |
Estimate | Std. Error | p-Value | |
---|---|---|---|
: Intercept | 2.535 | 0.308 | 0.000 |
: Age () | 0.076 | 0.034 | 0.028 |
: Lifespans () | −0.045 | 0.027 | 0.096 |
: Age/lifespans | −0.828 | 0.377 | 0.029 |
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Mak, M.; Heijungs, R. Environmental Externalities of Secondhand Markets—Based on a Dutch Auctioning Company. Sustainability 2022, 14, 1682. https://doi.org/10.3390/su14031682
Mak M, Heijungs R. Environmental Externalities of Secondhand Markets—Based on a Dutch Auctioning Company. Sustainability. 2022; 14(3):1682. https://doi.org/10.3390/su14031682
Chicago/Turabian StyleMak, Martijn, and Reinout Heijungs. 2022. "Environmental Externalities of Secondhand Markets—Based on a Dutch Auctioning Company" Sustainability 14, no. 3: 1682. https://doi.org/10.3390/su14031682