A multi-objective optimization based on genetic algorithms for the sustainable design of Warm Mix Asphalt (WMA)

Figures & data

Figure 1. Proposed framework for multi-objective optimization. Legend: HFO – heavy fuel oil.

Table 1. Synthesis of investigations regarding LCA efforts on WMA.

Research	Location	Software	Objective	Results
(Vidal et al., 2013)	Spain	SimaPro	Compare an HMA against a WMA (foaming process). Various RAP contents were evaluated.	Regarding the HMA control, the production of a WMA with 15% RAP reduced between 13-14% of the climate change potential, consumption of fossil fuels, and energy consumption.
(Blankendaal et al., 2014)	The Netherlands	SimaPro	Analyze the efficiency of different sustainable alternatives for hydraulic and asphalt concretes (including WMAs).	WMAs generate less environmental impact than HMAs by approximately 33%.
(Anthonissen et al., 2015)	Belgium	SimaPro	Contrast the environmental impacts of WMAs (zeolite and wax) against an HMA.	HMA was more polluting than WMA made with organic additives but less than WMA made with zeolites.
(Giani et al., 2015)	Italy	SimaPro	Evaluate pavement rehabilitation alternatives. HMA and WMA (with and without RAP) were considered.	The WMA-RAP alternative decreased (compared to HMA without RAP) by 12% of CO2eq, 15% of energy consumption, and 15% of water consumption.
(Rodríguez-Alloza et al., 2015)	Australia	Not specified	Compare an HMA against a WMA. Various CR contents were evaluated.	Compared to HMA, WMA production reduces greenhouse gas emissions and energy consumption by 18% and 20%, respectively.
(J. Santos et al., 2018)	France	OpenLCA	Evaluate HMA and WMA (foaming process and chemical additive), varying the RAP content.	In most impact categories, WMAs turn out to be the alternatives with the lowest environmental burden (compared to the respective HMA).
(Cao et al., 2019)	PR China	Not specified	Evaluate HMA and WMA (foaming process, organic additive, and chemical additive), varying the CR content.	Energy savings are highly dependent on the type of technology used for the modification.
(Hamdar et al., 2020)	Lebanon	SimaPro	Measure the functional, mechanical, environmental, and economic performance of a WMA in a hot climate.	WMA has enormous environmental benefits over HMA in energy consumption and global warming potential.
(Hasan et al., 2020)	United Arab Emirates	SimaPro	Development of LCA to measure environmental contributions of RAP and blast furnace slag within the WMA design.	Low dosages of these materials managed to reduce CO2eq, energy consumption, NOxeq, PM2.5eq, acidification and land use by 34%, 48%, 24.4%, 21.53%, 21.2% and 10.4%, respectively.
(Vega, Martinez-Arguelles, et al., 2020)	Colombia	SimaPro	Comparison of an HMA against a WMA (chemical additive). Various RCA contents were evaluated.	RCA increases the optimal asphalt content; therefore, an excess of this material reduces the environmental benefits attributed to WMA-RCA, even becoming more polluting than a conventional mixture.

Figure 2. Approaches proposed by the FHWA to carry out LCAs in the pavement industry.

Adapted from: (Harvey et al., 2016; Vega et al., 2019).

Figure 3. Boundaries contemplated for modeling the production of WMA in asphalt mixing plants. Legend: NA – natural aggregates.

Table 2. LCI adopted for this research.

LCA stage	LCA sub-stage	SPUP	Modified input data
			Parameters	References
Materials production	NAs extraction	Gravel, crushed {RoW}| production | Cut-off, U	7 lt of diesel / ton of aggregate 0.02 kg of lubricant / ton of aggregate	(Martinez-Arguelles et al., 2019)
	Truck loading of NAs	Loader operation, large, INW/RNA	Efficiency: 4.5 ton of aggregates / hour 7 lt of diesel / ton of aggregate 0.02 kg of lubricant / ton of aggregate
	CR processing	Waste, pneumatic tyres {GLO}| market for waste, pneumatic tyres | Cut-off, U	2.98 lt of diesel / ton of CR 0.1 kg of lubricant / ton of CR 383.33 kWh of electricity / ton of CR 220 kg of water / ton of CR	(Bressi et al., 2018a)
	RAP processing	Rock crushing {RER}| processing | Cut-off, U Excavation, skid-steer loader {RER}| processing | Cut-off, U Machine operation, diesel, ≥74.57 kW, high load factor {GLO}	184 ton of processing capacity / hour (Combined capacity including four activities: crushing, stacking, conveying, and screening)	(J. Santos, Flintsch, et al., 2019)
	RCA processing	Diesel, burned in building machine {GLO}| processing | Cut-off, U	Efficiency: 0.28 lt of diesel / ton of RCA 0.00069 kg of lubricant / ton of RCA 2.33 kWh of electricity / ton of RCA 100 kg of water / ton of RCA	(Vega, Martinez-Arguelles, et al., 2020)
	Asphalt binder production	Bitumen, at refinery/kg/US	"Does not apply.’
	Additive production	Fatty acid {GLO}| market for | Cut-off, U
Materials transport to the asphalt mixing plant	Aggregates transportation	Transport, freight, lorry 16-32 metric ton, EURO4 {RoW}| transport, freight, lorry 16-32 metric ton, EURO4| Cut-off, U	2.12 lt of diesel / tkm - 0.00942 kg of lubricant / tkm	(Vega, Martinez-Arguelles, et al., 2020)
	Asphalt binder transportation		15.78 lt of diesel / tkm - 0.07066 kg of lubricant / tkm
	Additive transportation		7.34 lt of diesel / tkm - 0.03295 kg of lubricant / tkm
Asphalt mix production	NAs processing	- Diesel, burned in building machine {GLO}| processing | Cut-off, U	Efficiency: 0.28 lt of diesel / ton of aggregate 0.00069 kg of lubricant / ton of aggregate 2.33 kWh of electricity / ton of aggregate - 100 kg of water / ton of aggregate
	Mixing process	- Heat, district or industrial, other than natural gas {RoW}| heat production, heavy fuel oil, at industrial furnace 1MW | Cut-off, U	Required thermal energy (MJ / ton of mixture), which is calculated using Equation 1.	(J. Santos et al., 2018; Vega, Santos, et al., 2020b)

Table 3. Parameters considered to calculate TE.

Abbreviation	Parameter	Unit	Value
TE	Thermal Energy	MJ/ton of mixture	Variable
Tmix	Mixing temperature	°C
M1	NAs mass	kg
M2	CR mass	kg
M3	RAP mass	kg
M4	RCA mass	kg
M5	Asphalt binder mass	kg
C1	Specific heat of NAs	KJ/kg/°C	0.74^a
C2	Specific heat of CR	KJ/kg/°C	2.01^c
C3	Specific heat of RAP	KJ/kg/°C	0.74^b
C4	Specific heat of RCA	KJ/kg/°C	0.74 ^a
C5	Specific heat of asphalt binder	KJ/kg/°C	2.09 ^a
W1	Water content of NAs	%*	3 ^a
W2	Water content of CR	%*	0^c
W3	Water content of RAP	%*	0 ^b
W4	Water content of RCA	%*	3 ^a
to	Ambient temperature	°C	25 ^a
Cw	Specific heat of water at 15°C	KJ/kg/°C	4.19 ^a
Cvap	Specific heat of water vapor	KJ/kg/°C	1.83 ^a
Lv	Latent heat of vaporization of water	KJ/kg	2256 ^a
CL	Casing loses factor	%/100	0.27 ^a

Notes: * By the mass of aggregates; ^a (Vega, Santos, et al., 2020b);^b Value taken from the literature (Vandewalle et al., 2020); ^c Typical value.

Figure 4. Incidence of RAP and RCA in WMAs produced with chemical additives.

Table 4. Characterization results for the materials production stage.

ICs [Unit]	NAs extraction (1 ton)	Truck loading of NAs (1 ton)	CR processing (1 ton)	RAP processing (1 ton)	RCA processing (1 ton)	AB production (1 ton)	CA production (1 ton)
Acidification [H+ mmole eq]	1450000	17000	31100	369	314	366000	467000
Ecotoxicity [g 2.4-D eq]	19600	36.7	650	7.59	9.28	4450	17800
Eutrophication [g N eq]	9270	17.9	150	3.11	1.6	249	19500
Global warming [g CO2 eq]	2790000	22200	104000	1340	873	508000	4400000
Habitat alteration [T&E count]	1.47E-11	0	9.69E-13	5.09E-15	8.25E-15	0	2.02E-11
HH cancer [g C6H6 eq]	17800	10.7	226	3.4	2.94	1750	6400
HH criteria air pollutants [microDALYs]	526	2.35	11.2	0.131	0.121	93	403
HH noncancer [g C7H7 eq]	20300000	8270	800000	7130	8760	1360000	25300000
Indoor air quality [g TVOC eq]	0	0	0	0	0	0	0
Natural resource depletion [MJ surplus]	42300	42.9	148	2.27	2.66	7050	925
Ozone depletion [g CFC-11 eq]	3.19	9.19E-7	0.00474	0.00015	0.000161	0.000151	0.0498
Smog [g NOx eq]	15300	485	261	8.18	3.62	4010	10100
Water intake [liters]	3470	0	1460	5.83	111	0	41700

Legend: AB - asphalt binder; CA - chemical additive.

Table 5. Characterization results for the for the second and third stage.

ICs [Unit]	Aggregates transportation (1 tkm)	AB transportation (1 tkm)	CA transportation (1 tkm)	NAs processing (1 ton)	Mixing process (1 MJ)
Acidification [H+ mmole eq]	177	22	509	314	31.1
Ecotoxicity [g 2.4-D eq]	2.74	14.1	7.07	9.28	0.29
Eutrophication [g N eq]	1.07	6.67	3.21	1.6	0.0513
Global warming [g CO2 eq]	442	118	1110	873	95.3
Habitat alteration [T&E count]	5.15E-15	1.38E-14	8.44E-15	8.25E-15	9.38E-17
HH cancer [g C6H6 eq]	2.02	12.5	6.04	2.94	0.131
HH criteria air pollutants [microDALYs]	0.0721	0.384	0.191	0.121	0.00923
HH noncancer [g C7H7 eq]	3180	14400	7470	8760	0.131
Indoor air quality [g TVOC eq]	0	0	0	0	0
Natural resource depletion [MJ surplus]	4.32	30	14.1	2.66	0.167
Ozone depletion [g CFC-11 eq]	0.000324	0.00226	0.00106	0.000161	125000
Smog [g NOx eq]	2.4	11.7	5.97	3.62	0.196
Water intake [liters]	0	0	0	111	0.0398

Legend: AB - asphalt binder; CA - chemical additive.

Table 6. Parameters that define Equation (2).

Acronyms	Description	Unit
IC	Estimation of the environmental impacts for each IC.	The one corresponding to each IC evaluated
fi	Unitary characterization results of material production stage determined for each material for each IC.
si	Unitary characterization results of material transport stage determined for each material for each IC.
t1	Unitary characterization results of NAs processing sub-stage determined for each IC.
t2	Unitary characterization results of mixing process sub-stage determined for each IC.
mi	Mass of each material required to produce 1 ton of WMA.	ton
mNAs	Mass of NAs required to produce 1 ton of WMA.
di	One-way transport distance of each material.	km
TE	Thermal energy required to produce 1 ton of WMA.	MJ
n	Number of materials employed for the WMA production.	-

Table 7. Numerical factors to perform the weighting process in the BEES+ model.

Source: SimaPro 9.1.1 and (Gloria et al., 2007).

IC	Unit	Weights (W)
Acidification	H+ mmole eq	5
Ecotoxicity	g 2.4-D eq	11
Eutrophication	g N eq	5
Global warming	g CO2 eq	16
Habitat alteration	T&E count	16
HH cancer	g C6H6 eq	5.5
HH criteria air pollutants	microDALYs	6
HH noncancer	g C7H7 eq	5.5
Indoor air quality	g TVOC eq	11
Natural resource depletion	MJ surplus	5
Ozone depletion	g CFC-11 eq	5
Smog	g NOx eq	6
Water intake	liters	3
TOTAL		100

Table 8. Parameters that define Equation (4).

Acronyms	Description	Unit
PC	Production costs of 1 ton of WMA.	USD
P_COSTi	Production or processing costs of each material.	USD/ton
T_COSTi	Hauling costs of each material.	USD/ton/km
mi	Mass of each material required to produce 1 ton of WMA.	ton
di	One-way transport distance for each material.	km
TE	Thermal energy required to produce 1 ton of WMA.	MJ
HFO_price	Price of heavy fuel oil (typical fuel for asphalt mixing plants).	USD/kg
LHV	Lower heating value of heavy fuel oil.	MJ/kg
n	Number of materials employed for the WMA production.	-

Figure 5. Optimization process through GAs proposed for this study.

Table 9. Selected hyperparameter values to the proposed optimization process through GAs.

Hyperparameter	Value
Number of individuals	400
Number of generations	80
Crossover probability, Pcx	0.8
Mutation probability, Pmut	0.2
Independent probability for mutUniformInt	0.1

Table 10. Composition and characteristics of the control WMA. Taken from: (Vega, Martinez-Arguelles, et al., 2020; Vega, Santos, et al., 2020a).

Item	Unit	Value
NAs	%^a	95.6
Asphalt binder	%^a	4.4
Chemical additive	%^b	0.3
Ambient temperature	°C	25
Mixing temperature	°C	120

Notes: ^a Percentage of total mixture weight; ^b Percentage of asphalt binder weight.

Table 11. Hauling distances adopted for this study. Taken from: (Vega, Santos, et al., 2020a).

Material	One-way transport distance (km)
Asphalt binder	592
Chemical additive	248
NAs	73

* Value assumed considering the worst possible scenario.

Table 12. Standard prices in the northern region of Colombia.

Material	Acquisition costs
	Unit	Value
Asphalt binder	USD/ton	115
Chemical additive	USD/ton	150
NAs	USD/ton	9.4
HFO	USD/kg	1.18

Figure 6. Pareto front obtained for the case study.

Figure 7. Percentage composition of the materials that compose two of the most suitable WMA designs. Legend: mAB – modified asphalt binder.

Figure 8. Ternary plot for the unitary composition of CR, RAP, and RCA in the viable mix designs.

Figure 9. Effect of supplementary materials on optimization criteria.

Figure 10. Optimal contents of supplementary materials considering a single IC. Acronyms: AC – acidification; EC – ecotoxicity; EU – eutrophication; GW – global warming; HA – habitat alteration; HHC – HH cancer; HHP – HH criteria air pollutants; HHN – HH noncancer; IAQ – indoor air quality; NRD – natural resource depletion; OD – ozone depletion; SM – smog; WI – water intake.

Figure 11. Record of the running time of the proposed methodology in 100 independent executions.

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