According to the factor determination, ℎ has a variation potential between 0.98 and 0.998 according to the efficiency diagram from Abele (Abele 1986). Further, due to the temperature sensation in the cab by the driver, & may vary between 0.92 to 0.97. Such a variation consequently leads to a different variation range for the excavator of -1 % to -6 %. This difference is within the acceptable range.

### **7.2.2 Single drum roller**

On 27/11/2018 as well as on 14/12/2018 the evaluation of the collected data from the single drum roller in Ludwigsburg was done according to the same principle. Contrary to the excavator, a CANBUS reading device could be installed on the single drum roller. This made it possible to record the signals available on the BUS like velocity, fuel consumption and engine speed during the observation time.

On 27/11/2018, the roller was in use for 28 min. 8 minutes of this time was driving the single drum roller in and out of the construction site. Driving is regarded as preparatory work in the CO2e quantification method and is according to the system boundary not taken into account. The process to be validated therefore consists of 20 min, from 16:22 to 16:42. In Table 7-11 the observation notes complemented with the recorded data from the CANBUS readout device are shown.

**Table 7-11: Single drum roller observation notes complemented with recorded data from the CANBUS readout device, taken on 27/11/2018**

#### Practical approach

From the notes, it can be seen that tworking lasted 0.28 h and tidle 0.06 h. The fuel consumption during compacting and idling could be recorded with the CANBUS readout device. The fuel consumption while idling corresponded to 0.07 l diesel with a bidle of 1.1 l/h. The total fuel consumption during the compacting process was 2.06 l diesel. This corresponds to a total fuel consumption of 2.13 l or 7 kg CO2e. Table 7-12 summarises the respective fuel consumptions and CO2e emissions. The processes in pink correspond to the processes which will be validated with the CO2e quantification method.

**Table 7-12: Summary of the fuel consumption of the single drum roller in Ludwigsburg 27/11/2018**

#### Theoretical approach

Also here the theoretical approach consists of applying the CO2e quantification method from mobile construction machines during the construction application for rollers. First, the basic performance of the single drum roller will be calculated with equation

*(4-29)*. The velocity on the construction site was measured with the CANBUS readout device and corresponded to 1,741 m/h on average. Four passages of the single drum roller took place during this compaction process. According to the datasheet of the machine, the effective working width was 1.7 m. Consequently, the basic performance of this machine on this day equalled 550 m²/h (see Table 7-13).

**Table 7-13: The basic performance of the single drum roller in Ludwigsburg on 27/11/2018**

The datasheet of the machine, machine operator surveys, construction site observations, measurements with the multi measuring device and the vibration measuring device permitted defining the values for the factors determined in chapter 4. The single drum roller has an engine with an exhaust after-treatment system stage IV ( = 1.00), driving in ECO-mode ( = 0.87) and has different other significant improvement technologies corresponding to a fuel consumption reduction of 35 % ( = 0.65). The roller is 3 years old ( = 1.05) and is subject to regular service maintenance work ( = 1.00). Time recordings of idling time compared to the total active time of the machine shows that the construction site organisation is very good ( . = 0.18). The calculation of the value of . is described in equation (7-4).

$$f\_{site\,orga.} = \frac{t\_{ldling}}{t\_{compacting} + t\_{idling}} = 0.18\tag{7-4}$$

No observed idle time was considered unavoidable for the construction processes ( = 0). The operator is considered to be a good driver (& = 0.83) and can therefore profit to a certain degree from the advantages of the process assistant systems integrated in the roller such as the measurement of the compaction degree and the automatic continuously variable amplitude system ( = 1.23). On this day the weather conditions (effective weather temperature -0.50 °C and average wind speed of 0.95 m/s), the available construction time and construction site freedom were ideal (ℎ = 1.00; = 1.00; = 1.00). During the whole work task, the single drum roller drove with diesel (2⁄ = 3.18 kg CO2e/l diesel). The compacting process was on that day the last construction task of the worker. ℎ& is therefore considered to be equal to 0.99. Noise measurements and vibration measurements were under the lower limit value. The light state and the view from the cabin were not optimal because the sun was already down and so it was dark. Therefore & has the value 0.97. Based on the time recordings, no standstill time took place.& is therefore equal 1.00. The single drum roller was not equipped with a CO2e capture and storage system ( = 0).

In the following Table 7-14 all values of the influencing factors on the CO2e amount emitted by the single drum roller are summarised.

By inserting the factor values in equation *(4-25)*, the following fuel consumption and CO2e emissions in Table 7-15 are calculated for the work processes of the single drum roller.

**Process Vmaterial [m²] QB [m²/h] tworking [h] tidle [h] bm [l/h] bidle [l/h] fui B [l diesel] [kg CO2e] Compacting + idle** 152 550 0.28 0.06 12.7 1.6 1 2.2 7

**Table 7-15: Fuel consumption and CO2e emissions for the single drum roller**

#### Practical vs. theoretical approach

In Table 7-16, the results from the measurements at the construction site (practical approach) are compared to the results determined by using the quantification equation *(4-25)* (theoretical approach). The factor /2 used for the calculation of climate costs of the additionally emitted CO2e 2, has the value of 30 € per ton CO2e emitted (OECD 2018). The difference of 5 % between the practical and theoretical approach is within are within the acceptable range of 20 % (according to the Pareto principle).

**Table 7-16: Comparison of the practical and theoretical approach for the single drum roller on 27/11/2018**

According to the observation at the construction site ℎ& and & are the only factors in the quantification method that can vary between 0.90 to 1.00 and 0.95 to 1.00, respectively. Consequently the difference between the practical and theoretical approach can vary between +5 % to +17 %.

According to the same procedure, the fuel consumption and CO2e amount emitted by the single drum roller on 14/12/2018 during construction were determined (practical approach). These results were compared to the calculated amounts with equation *(4-25)* (theoretical approach). The comparison results are shown in the following Table 7-10. Also in this case, the difference of 10 % between the practical and theoretical approach is within the acceptable range.

According to the observation at the construction site, no factors are variable. Therefore, no analysis to calculate the possible difference variation is needed. According to the equation (4-25) and (4-26), the fuel consumption at idle (,) is the general fuel consumption for machine r, in this case the single drum roller. If instead of , the fuel consumption at idle for elementary process α would be used (,,) then the difference would be 3 %.

**Table 7-17: Comparison of the practical and theoretical approach for the single drum roller on 14/12/2018**

### **7.2.3 Road pavers**

In Mannheim, on 12/12/2019, the two pavers described in Figure 7.2 were observed. The pavers could not be equipped with a CANBUS readout device. The total fuel consumption was therefore determined through refuelling before and after the work task. Three processes were observed for both road pavers: idling, driving and asphalt laying. The process "driving" is regarded as preparatory work in the CO2e quantification method and is according to the system boundary not taken into account. The process to be validated therefore consists of "idling" and "asphalt laying".

#### Practical approach

The road paver A was active 11.88 h and consumed 148 l of diesel, the road paver B was active 8.18 h and consumed 49 l diesel. This corresponds to an emitted greenhouse gas emission quantity of 471 kg CO2e for road paver A and 156 kg CO2e for road paver B. The fuel consumption and respective CO2e emissions of the process "driving" must be deducted from the total measured fuel consumption and total emitted CO2e. Fuel consumption from driving was estimated at 22.40 l/h for road paver A and 14 l/h for road paver B based on the machine manufacturers data. The process "driving" consisted of driving interrupted by idle time. The respective fuel consumption and greenhouse gas emissions are calculated in Table 7-18.

**Table 7-18: Quantity of greenhouse gas emissions from road pavers during the "driving" process**

The deduction of the process "driving" results in a fuel consumption of 124 l diesel and an emission quantity of 394 kg CO2e for the road paver A and in a fuel consumption of 16 l diesel and 50 kg CO2e for the road paver B (see Table 7-19).

**Table 7-19: Fuel consumption and greenhouse gas emissions emitted by the pavers on 12/12/2019**

#### Theoretical approach

The theoretical approach consists of applying the CO2e quantification method from mobile construction machines during the construction application for pavers. First, the basic performance of the road pavers will be calculated with equation

*(4-28)*. The working width b' is determined based on the data sheets of the two pavers. The layer height of the material is determined with measurements made at the construction site. The recommended velocities from the company Vögele are chosen for the calculation (Vögele). The respective values chosen for the parameters as well as the resulting basic performance are described in Table 7-20.

**Table 7-20: Basic performance calculation for paver A and paver B**

The datasheet of the machine, machine operator surveys, construction site observations and measurements with the multi measuring device permitted defining the values for the factors determined in chapter 4. The road paver A and B have an engine with an exhaust after-treatment system of stage IIIB ( = 1.03) and stage IV, respectively ( = 1.00). Paver A works in ECO-mode ( = 0.85), paver B in the regular mode ( = 1.00). For both pavers, a fuel consumption reduction of 12 % ( = 0.88) is assumed due to other significant improvement technologies such as ECO-mode and the engine technology. Both pavers are 2 years old ( = 1.04) and are subject to regular service maintenance work ( = 1.00). Time recordings of idling time compared to the total active time of the machine shows that the construction site organisation is from medium to good depending on the time of day. By applying equation (7-5) 4 , paver A has a . of 0.71 in the morning, of 0.64 at noon and of 0.47 in the afternoon. Paver B has a . of 0.81 in the morning and of 0.46 at noon.

$$\begin{split} f\_{\text{slte\,orga.}} &= \frac{t\_{\text{total}} - t\_{\text{working}} + t\_{\text{idle\,unav\,ol}} \mathbf{t}\_{\text{alle\,unav\,ol}} \\ &= \frac{t\_{\text{total}}}{t\_{\text{total}} + t\_{\text{idle}} - t\_{\text{idle\,unav\,ol}} \mathbf{t}\_{\text{alle}}} \end{split} \tag{7-5}$$

On 12/12/2018 the temperature in Mannheim varied between mornings and at noon and afternoons. The average effective temperature was -1.25 °C in the morning with an average wind speed of 0.45 m/s. At noon and in the afternoon the average effective temperature was 1.75 °C with an average wind speed of

 4 See footnote 44

1.02 m/s. Consequently, for ℎ, a value of 0.99 is assumed for work during the morning and a value of 1.00 for work at noon and in the afternoon (according to the efficiency diagram from Abele) (Abele 1986). An unavoidable idle time of 30 min is being assumed for paver A in the morning in order to heat the screed to the right temperature ( = 0.10). The heating time of the screed for paver B is considered to have happened during the process "driving" and therefore is considered in the analysed process as non existing ( = 0). Both operators are considered to be expert drivers (& = 0.92) and work as efficiently as the process assistant systems integrated in the paver ( = 1.00). The available construction site freedom was somewhat restricted by the other construction crews ( = 0.95). The available construction time was ideal in the morning ( = 1.00), at noon somewhat limited due to parallel working of paver A and paver B and ( = 0.90) and in the afternoon paver A was hurrying up to finish the work on time ( = 0.85). However, the paver A crew had to work overtime until 18:30. Both crews were travel teams, sleeping in hotels and travelling from one town to another. Therefore, for ℎ& the value of 0.84 is chosen. The daily noise exposure level for the driver of paver A equalled ,8ℎ = 79.04 () and for paver B equalled ,8ℎ = 77.28 (), which are both below the lower limit value of 80 dB. Paver A started in the morning, when the sun had not yet risen. The temperature in the cabin was not assessed to be unpleasant by the driver. The light state and the view from the cabin were assessed to be ideal for paver B. Therefore, & has the value 0.97 for paver A and 1.00 for paver B.

During the whole work task, the pavers drove with diesel (2⁄ = 3.18 kg CO2e/l diesel). No standstill time was observed, therefore & equals 1.00. In the following Table 7-21 all values of the influencing factors on the CO2e amount emitted by both pavers are summarised.

**Table 7-21: Values for the influencing factors of paver A and paver B on 12/12/2018**

By inserting the factor values in equation *(4-25)*, the following fuel consumption and CO2e emissions in Table 7-22 are calculated for the work processes of both pavers.

**Table 7-22: Fuel consumption and CO2e emissions for both pavers**

#### Practical vs. theoretical approach

In Table 7-23, the results from the measurements at the construction site (practical approach) are compared to the results determined by using the quantification equation *(4-25)* (theoretical approach). The factor /2 used for the calculation of climate costs of the additionally emitted CO2e 2, has the value of 30 € per ton CO2e emitted (OECD 2018). The difference between the practical and theoretical approach is +3 % for paver A and 0% for paver B. The results are therefore within the acceptable range of 20 % (according to the Pareto principle).

**Table 7-23: Comparison of the practical and theoretical approach for both pavers on the 12/12/2018**

According to the factors determination, for Paver A following factors were estimated according to the observations at the construction site: ℎ , , , ℎ& and & . According to Abele, ℎ could take a value between 0.98 and 0.99 in the morning (Abele 1986). According to Ibbs and Vaughan, could take a value between 0.84 and 1.0 (Ibbs and Vaughan 2015). According to the value range definition of , the value can vary between 0.90 and 1.00. According to the construction site observations, ℎ& could take a value between 0.80 and 0.90. For the factor & a value range of 0.95 to 1.00 is assumed for paver A. The factor variations results in a different variation range of +3 % and -19 %. Also this difference range is acceptable.

For Paver B following factors were estimated according to construction site observations: ℎ and . ℎ could also take a value between 0.98 and 0.99 in the morning according to Abele (Abele 1986). For , the estimated range would be between 0.84 and 1.02 (Ibbs and Vaughan 2015). Consequently the difference between practical and theoretical value for paver B would be between negligible and 9 %. Also this difference is in the acceptable range.

### **7.2.4 Tandem roller**

In Mannheim, two tandem rollers were observed and data was recorded according to the same procedure like the single drum roller in Ludwigsburg. On both tandem rollers, a CANBUS readout device was implemented.

#### Practical approach

From observation notes and from data recorded with the CANBUS readout device on 12/12/2018, compacting, idling and standstill times were recorded. Their respective fuel consumption as well as CO2e emissions are summarised in Table 7-24. The processes in pink corresponds to the processes which will be validated using the CO2e quantification method.

**Table 7-24: Summary of the fuel consumption of both tandem rollers in Mannheim on 12/12/2018**

#### Theoretical approach

For the theoretical approach, first, the basic performance of the tandem rollers will be calculated, then the influence factors for the application of the CO2e quantification method for mobile construction machines will be determined. Finally, by inserting the values of the factors in equation *(4-25)*, the CO2e emitted by both tandem rollers will be calculated.

For the basic performance of both rollers, the effective width was determined with the datasheet of the machine, the velocity was calculated by dividing the observed working length by the recorded total working time at the construction site. Four passages of the tandem rollers took place during the process compacting. Consequently, the basic performance of these tandem rollers on this day were 822.79 m²/h and 540.60 m²/h for tandem roller A and tandem roller B, respectively (see Table 7-25).

**Table 7-25: The basic performance of both tandem rollers in Mannheim on 12/12/2019**

The datasheet of the machine, machine operator surveys, construction site observations, measurements with the multi measuring device permitted defining the values for the factors determined in chapter 4.

Tandem roller A has an engine with an exhaust after-treatment system stage IV ( = 1.00) and tandem roller B with an exhaust after-treatment system stage IIIB ( = 1.03). Both rollers drive in ECO-mode ( = 0.87) and have further significant improvement technologies implemented in the machines, corresponding to a fuel consumption reduction of 35 % ( = 0.65). Both rollers are from 2018 ( = 1.00) and are subject to regular service maintenance ( = 1.00).

No observed idling time was considered unavoidable for the construction processes ( = 0). Time recordings of idling time compared to the total active time of the machine shows that the construction site organisation is good to very good concerning the tandem rollers. For tandem roller A . equals 0.24 and for tandem roller B 0.03. The calculation of the value of . is described in equation (7-4) 5 .

$$\begin{split} f\_{\text{site orga.}} &= \frac{t\_{\text{total}} - t\_{\text{working}} + t\_{\text{idle unavolable}}}{t\_{\text{total}}}\\ &= \frac{t\_{\text{ldle}} + t\_{\text{standstill}} - t\_{\text{tdle unavolable}}}{t\_{\text{total}}} \end{split} \tag{7-6}$$

The operator is considered to be an expert driver (& = 0.92) and can therefore profit to a certain degree from the advantages of the process assistant systems integrated in the rollers, such as the measurement of the compaction degree and the automatic continuously variable amplitude system ( = 1.14). On this day, the weather conditions for the rollers was ideal (average effective temperature 0.25 °C and average wind speed of 0.74 m/s); both crews were slightly pressured to finish the work within 3 days, the construction site freedom was limited by the other roller working in parallel on the same asphalt area (ℎ = 1.00; = 0.90; = 0.95). During the whole work task the excavator drove with diesel (2⁄ = 3.18 kg CO2e/l diesel). No concentration

5 See footnote 44

tests for both drivers were undertaken. The physical and mental state of the tandem roller drivers were assumed to be ideal (ℎ& = 1.00). Noise measurements were under the lower limit value. The light state and the view from the cabin were optimal (& = 1.00). Based on the time recordings, only for tandem roller A was standstill time recorded. According to equation (7-3) & equals 0.65 for tandem roller A and 1.00 for tandem roller B. Neither tandem roller was equipped with a CO2e capture and storage system ( = 0).

**Table 7-26: Values for the influencing factors of tandem roller A and B on 12/12/2018**

In Table 7-26 all values of the influencing factors on the CO2e amount emitted by both tandem rollers are summarised.

**Table 7-27: Fuel consumption and CO2e emissions for both tandem rollers**

By inserting the factor values in equation *(4-25)*, the following fuel consumption and CO2e emissions in Table 7-27 are calculated for the work processes of both tandem rollers.

#### Practical vs. theoretical approach

In Table 7-28, the results from the measurements on the construction site (practical approach) are compared to the results determined by using the quantification equation *(4-25)* (theoretical approach). The factor /2 used for the calculation of climate costs of the additionally emitted CO2e 2, has the value of 30 € per ton CO2e emitted (OECD 2018). The difference between the practical and theoretical approach of +4 % and -1 % are within the acceptable range of 20 % (according to the Pareto principle).

The factor determination for these two observed tandem rollers enable a factor variation for and between 0.84 to 1.02 and 0.90 to 1.00, respectively. The resulting difference range for tandem roller A varies between 4 % and 17 %. The resulting difference range for tandem roller B varies between 1 % and 17 %. Both difference ranges are acceptable.

**Table 7-28: Comparison of the practical and theoretical approach for both pavers on 12/12/2018**

### **7.3 Discussion**

The CO2e amount emitted at the construction sites in Ludwigsburg and Mannheim were comparable to the theoretical results quantified using the developed quantification method of CO2e emitted by construction machines during their construction application. According to the Pareto principle, the method should at least consider 80 % of the CO2e emissions emitted by each sub process. A difference in the theoretical and practical approach ranging between negligible and 10 % were found. This difference range is below the maximum acceptable range of 20 % (Pareto principle). This result is better than the result obtained using the Lewis Method, where only 5 of 18 machines had a difference below 20 % or the results obtained with the NONROAD model, where all 18 analysed machines had a difference above 60 % (Heidari and Marr 2015).

Contrary to the NONROAD–Model (see p. 14), the focus on the developed CO2e quantification method does not only lie on the engine of the construction machine. The developed method considers the different types of construction processes. Further, contrary to the EMEP/EEA Air pollutant Emission Inventory Guidebook (see p. 18), the method considers not only wear on the engine but wear on the whole machine. A state differentiation is possible between a privately owned and rental machines. Accordingly, the method closes the defined research gap G1 by not only focusing on the engine but considering the whole machine.

Differently to the Swiss non-road Database (see p. 22) or analysed tools for construction equipment (see p. 25), the developed method considers the construction process and machine operation and so takes into account effects of possible efficiencies in these fields. Additionally, by not mixing up working time with idle time, the model gains in accuracy relative to reality. Ergo, the method also closes the defined research gap G4 by considering the construction operation and differentiating idling and working time.

During the validation method in Ludwigsburg and Mannheim, the same method was used for different machine types such as the excavator, single drum roller, road pavers and tandem rollers. Also the same method was used for two different construction applications: in canal construction, being part of earthmoving and in road construction. The difference between reality and the theoretical approach being in the acceptable range, showed that the method is valid for different machine types and different construction applications and thus fulfils the defined research gap G5.

In addition, the method considers not only the amount of CO2 emissions but the total amount of greenhouse gases emitted by taking into account the production and consumption of fuel. As a result, the method also bridges the defined research gap G7.

In conclusion, the validation process at construction sites in Ludwigsburg and Mannheim was able to show that the developed quantification method of CO2e emitted by construction machines during their construction application is valid and bridges the defined research gaps G1, G4, G5 and G7.

Nevertheless, the validation process was only made possible through the cooperation of construction industries and construction machine producers. This shows that need N3, cooperation of industries are essential in order to reach the climate goals set by the government.

The system boundary of the method states that the process "driving" of the machine to the construction place is regarded as preparatory work and therefore neglected. The observation at the construction sites showed that "driving" occurs on a regular basis and can even occur several times a day. "Driving" is strongly dependent on construction site organisation and the machine operator's behaviour. In order to better understand the effect of "driving" on the total amount of CO2e emissions emitted, further examinations and research work are recommended.

## **8 Transformation of mobile construction machines into zero greenhouse gas emitters**

This chapter focuses on measures derived from the previous chapter resulting in reducing or eliminating CO2e emissions from mobile construction machines during their construction applications.

The developed CO2e quantification method permitted identifying the factors influencing the amount of CO2e emissions emitted by construction machines during their construction applications. The impact importance of these factors is shown in Table 6-10 from chapter 6.4. In third place, the largest impact on the amount of CO2e emissions is held by the factor 2⁄ . That is the reason why the focus will lie on finding an adequate alternative energy carrier for mobile machines in order to reduce their climate impact. By combining the adequate alternative energy carrier with the adequate primary energy converter, it is further possible to reduce the amount of emitted greenhouse gas emissions. Finally, in order to reach zero emissions, two concepts on how a carbon capture system for mobile machines could look will be described. The chapter will end with a short discussion about the sustainability aspects of mobile machines.

### **8.1 Adequate alternative energy carrier**

In order to ensure freedom of movements, a mobile machine must be able to store a certain amount of energy so that its respective working process does not have to be interrupted (Ays et al. 2017, pp. 126–127). For an adequate alternative energy carrier, different energy carriers are compared to each other in Table 8-1. For comparison, a mobile machine with a tank volume of 500 l is taken as a reference. Additionally, an internal combustion engine with an efficiency of 34 % is assumed for all analysed energy carriers except for the lithium-air battery. For the lithium-air battery combined with an electric motor, an efficiency of 80 % is being assumed.

**Table 8-1: Comparison of different energy carriers with a usable energy amount of 6,067 MJ (based on Geimer and Ays 2014; Wu 2018)**

The analysis shows that hydrogen has the lowest gravimetric energy density but a high volumetric energy density. By using hydrogen, many components in the machine would have to be replaced with hydrogen-resistant materials, since hydrogen reduces the strength, ductility and service life of many metallic materials (Fraunhofer IWM 2018). Further, lithium-air batteries are heavy and need a lot of space1 and are therefore considered inadequate for mobile machines with an energy disposal of 6,067 MJ or more. By considering the calorific value as well as the gravimetric and volumetric energy densities of the energy carrier, liquefied methane is the most promising option as alternative fuel to diesel. Although liquefied methane has a similar volume to ethanol, dimethyl ether or oxymethylene ether, it is lighter.

1 4,150-12,450 kg and 3.1 m³ for a lithium-air battery machine with an energy disposal of 6,067 MJ.

Alternative energy carriers have different compositions and manufacturing processes than fossil diesel and can therefore influence the greenhouse gases emitted by mobile machines. Biomass has absorbed CO2 emissions from the atmosphere during its growth. Therefore, if biomass is used for the production of the alternative energy carrier, the conversion of chemical energy into mechanical energy, i.e. during internal combustion of this energy carrier, it is assessed as climate-neutral (Edwards et al. 2014b). The amount of CO2 absorbed is assumed to be equal to the amount emitted (ibid.). Equally, if the primary energy converter uses energy carriers produced synthetically with wind energy from emitted CO2 emissions from e.g. power plants, then the conversion process is considered climate-neutral (ibid.). In summary, if the well-to-wheel cycle2 corresponds to a closed CO2 cycle, then the mobile machine can be described as climate-neutral.

A second analysis takes place in Table 8-2 by comparing the total amount of greenhouse gas emissions (well-to-wheel-analysis3 ) of the liquefied energy carriers from Table 8-1.

The most climate friendly alternative energy carrier to diesel is liquefied hydrogen under the condition that it is produced with CO2 emitted from power plants and electric energy produced with wind turbines. If liquefied hydrogen is produced with the current EU-Mix electricity, then the energy carrier hydrogen becomes the worst alternative with the biggest climate impact of the analysed energy carriers. By considering the calorific value, the gravimetric and volumetric energy density as well as the amount of emitted CO2e emissions, OME from Biomass and liquefied methane are the two most promising alternative energy carriers for mobile machines.

2 The well-to-wheel cycle consider the production as well as the combustion of an energy carrier.

3 The well-to-wheel analysis takes into account the greenhouse gas emissions emitted during production and during fuel consumption by the primary energy carrier.

**Table 8-2: Comparison of alternative energy carriers with their CO2e emissions (based on Edwards et al. 2014b; Wu 2018)**

OME is the short form of oxygen-containing oligomeric oxymethylene ethers [CH3O-(CH2O-)nCH3] (Wu et al. 2019). It is considered a further developed fuel form of the toxic and at ambient temperatures high vapour pressured dimethyl ether (DME) or methanol (Maus and Jacob 2014). On the contrary, OME, is a non-toxic and colourless liquid fuel (Wu et al. 2019). The physical properties of the individual OMEn (n ≥ 1) depend on their chain length (ibid.). Sustainable OME is a possible fuel alternative or can be used as a diesel additive for mobile machines in order to reduce greenhouse gas emissions (up to 70 % with pure OME from biomass). However, due to the limited availability of sustainable OME, only an admixture in diesel is currently an option for reducing pollutants and CO2e (Wu et al. 2019).

Liquefied methane, also called LNG (liquefied natural gas) can be from fossil, biogenic or synthetic sources. Liquefied methane is a colourless and odourless energy carrier. Its composition and calorific value is defined according to the DIN 51624 norm. Liquefied methane has to be composed of at least 75 % of methane. A distinction is made between L-gas (low) with a calorific value of 39-46 MJ/kg and H-gas (high) with a minimum of 46 MJ/kg. The exact composition defines the energy carrier's properties which have an energy density between 430 kg/m³ up to 470 kg/m³ and a liquefied storage at -166°C to - 157°C. (Ays et al. 2017)

Liquefied methane is an alternative energy carrier for mobile machines and can reduce greenhouse gas emissions up to 85 %. A possible methane infrastructure is already available with the natural gas network throughout Europe. Only methane liquefiers need to be installed to complete the infrastructure for liquefied methane. Through EU initiatives like "LNG Blue Corridors Project" or "Trans-European Networks", the liquefied methane network is developed and expanding. Additionally, Germany has the largest natural gas storage capacities in the EU and the fourth largest in the world. (Engelmann et al. 11/20/2018; Ays et al. 2017)

### **8.2 Adequate combination of energy carriers and primary energy converters**

In this subchapter, the two primary energy converters further analysed using alternative energy carriers are the internal combustion engine and the fuel cell. First, four different concept combinations will be explained: OME combined with an internal combustion engine, liquefied methane combined with an internal combustion engine, liquefied methane combined with a fuel cell and liquefied hydrogen combined with a fuel cell. Then the subchapter will end with comparing weight, volume and amount of CO2e emissions of the conventional diesel-internal combustion engine combination with the four concepts presented before.

### **8.2.1 Oxymethylene ethers & internal combustion engine**

By designing an oxymethylene ether (OME) power train concept for mobile machines, the first step is to decide if OME will be used as a pure fuel or as a diesel fuel additive. Different mixture ratios exist for OME3-6 4 as an additive to diesel. As shown in Table 8-2, the lower energy density of pure OME3-6 requires 1.7 times as much installation space and weighs 2.3 times more than a diesel tank. As a result, for machines that have short working shifts or can be fuelled several times per shift, pure OME can be used despite the lower energy density. On the other hand, for machines where installation space is limited and where fuelling during working shift is unwanted, OME3-6 diesel mixture is recommended. Due to the high oxygen content (42-49 wt. %) of OME, an adapted injection system is needed. Two injection systems are available: the cam-operated injection system and the common rail injection system. The compacted construction of the cam-operated injection system is favourable in small machines where installation space is limited. For machines with high driving power, an effective combustion is possible with the common-rail injection system because of its high flexibility in positioning and quantity of the injection. The absence of soot formation when using pure OME3-6 permits running the internal combustion engine at an air-fuel ratio of λ = 1. On the other hand, engines running with OME3-6 diesel mixture can only be operated like conventional diesel engines at λ > 1.2. When using pure OME as energy carrier, no Diesel Particulate Filter (DPF) is necessary because of the absence of soot formation. In stoichiometric operation (λ = 1) a three-way-catalyst (TWC) can be used. (Wu et al. 2019)

In case of an OME3-6 diesel mixture as energy carrier, a "standard" exhaust after-treatment system is needed, composed of a Diesel Oxidation Catalyst (DOC) combined with a Diesel Particulate Filter (DPF) and a Selective Catalytic Reduction (SCR). In Figure 8.1, an example of a drive train powered with pure OME fuel is illustrated for mobile construction machines. For this concept, the maximum tank capacity is chosen so that the longest possible operating time per working shift is reached. In fact, it is not unusual that construction machines are operated in 2 or 3 shifts. An increase of weight due to the use of pure OME3-6 is acceptable for construction machines that hardly drive or drive slowly. For machines driving frequently or at high speed, the increased weight needs to be evaluated according to their working cycles and applications. For

4 For the energy carrier OME3-6, the numbers"3-6" describe its chain length, which defines its physical properties.

high efficiency, the common-rail injection system and an air-fuel ratio of λ ≥ 1.2 are chosen. This implies the use of an exhaust after-treatment system consisting of a DOC and an SCR. (Wu et al. 2019)

**Figure 8.1: Exemplary drive train of a mobile construction machine driving with pure OME (Wu et al. 2019)**

### **8.2.2 Liquefied methane & internal combustion engine**

Liquefied methane is stored at -166°C to -157°C and therefore needs a special tank with a multi-layered vacuum insulation. The temperature difference between the interior of the tank and exterior causes heat inflows into the tanks. This leads to a constant evaporation of the energy carrier, also referred to as "boil-off gas". The tanks are designed so that no boil-off gas is released until a maximum permissible pressure level is reached. Consequently, liquefied methane tanks have 1.6 to 2.9 times the weight and at least twice the construction volume of diesel tanks per energy content. Three main combustion processes are differentiated for liquefied methane: the Otto process, the diesel-gas process and the gas-diesel process. In the Otto process, liquefied methane without additional fuel is burned in the combustion process. Further, this process produces up to 3 dB(A) less noise than diesel engines. Most of the time, dieselgas and gas-diesel processes require diesel fuel for operation in addition to liquefied methane. The diesel-gas process, also referred to as a dual-fuel process, has a gas fraction of about 60-80 %. While the gas-diesel process also called HPDI (high-pressure direct injection) process has a gas fraction above 90 %. The efficiency and power density of the gas-diesel engine corresponds to that of a diesel engine. The current exhaust emission regulation demands the same exhaust gas cleaning system used in diesel engines. Depending on exhaust emission regulations, in the Otto process a three-way catalytic converter can be sufficient. (Weberbeck et al. 2016)

**Figure 8.2: Exemplary drive train of a mobile construction machine driving with a gas-diesel process (HPDI) and liquefied methane (based on Weberbeck et al. 2016)**

In Figure 8.2, an exemplary drive train for a mobile construction machine is shown. For this concept, a gas-diesel process (HPDI) for a high power supply, a large tank capacity in order to maximise operating without interruptions and a tank cooling system are chosen. The tank cooling system is operated with an electric cooling system. Alternatively, a cooling system driven with boil-off gas could be envisaged. Machines with an electric system should be equipped with a torch to burn off gas in case of downtimes without electric power supply. Also here, a potential weight gain in machines hardly driving or driving very slowly are acceptable. For machines driving frequently or at high speed, the

increased weight needs to be evaluated in each case according to their working cycles and applications. (Weberbeck et al. 2016)

#### **8.2.3 Liquefied methane & fuel cells**

A fuel cell converts the chemical energy into electricity. It is a compact technology, emitting no noise, having no moving parts and producing no vibrations. Additionally, the electrical efficiency5 of the fuel cell can reach 50-65 % (Ivers-Tiffée 2017/2018). The total efficiency6 of the fuel cell can reach over 80 % (Ivers-Tiffée 2017/2018). In Figure 8.3 an exemplary drive train powered with liquefied methane is shown for a mobile construction machine. It is composed of a PEMFC as the fuel cell because of its high energy density and efficiency and of a lithium-ion battery because of its high energy density. In Figure 8.3, the range-extender drive concept is chosen so that load fluctuations impact the fuel cell as little as possible and thus handing this off to the battery.

In this concept, liquefied methane flows through a heat exchanger in order to enter an external reformer in a gaseous state. There two reactions take place: the steam reforming process and the water gas shift reaction. In the first reaction, methane reacts with the water vapour to produce syngas or synthesis gas which consists of hydrogen (H2) and carbon monoxide (CO). The second reaction serves to increase hydrogen production. Both reactions are described in (8-1) and (8-2). (Ays and Geimer 2019)

4 + 2 → + 32 ∆° = 206. −1 *(8-1)*

+2 → 2 + 2 ∆° = −41 . −1

*(8-2)*

Hydrogen (H2) flows into the fuel cell in order to produce electricity for the traction drive. For efficient use of the chemically bound energy, a burner is located directly after the fuel cell. It burns the residual gases left in the exhaust gas leaving the fuel cell. The heat produced thereby is then recuperated and used for the heat exchangers, reformer and H2O separator. The exhaust gas is

 5 =

ℎ

6 The total efficiency of a fuel cell system: = + ℎ with ℎ = ℎ ℎ ℎ

composed of O2, CO2 and because of the residual gas burner very low levels (<10 ppm) of CO and NOx. (Ays and Geimer 2019)

**Figure 8.3: Exemplary liquefied methane and fuel cell drive train for mobile construction machines**

### **8.2.4 Liquefied hydrogen & fuel cells**

Even if it was shown in subchapter 8.1 that hydrogen in gas form or in liquid form is not an interesting solution for mobile construction machines, a general predesign of a possible drive train takes place because of its current popularity with companies and the media. It combines liquefied hydrogen with a fuel cell and a battery similar to the fuel cell drive train with liquefied methane presented before. In the tanks, hydrogen is stored in liquid form, therefore no reformer is needed. Consequently, the weight and volume of the reformer is subtracted as well as the efficiency decrease because the reformer is omitted.

### **8.2.5 Comparison**

For comparison, the four concepts are applied to an excavator of 30 t with an energy output of 6,340 MJ. An efficiency of 34 % is assumed for the internal combustion engine, of 50 % for the fuel cell system, of 75 % for the reformer and of 90 % for the electric engine. The respective weight and volume for the main components of the five drive trains are calculated in Table 8-3.

In the calculations, the weight and volume of the fuel, tank, primary energy converter and exhaust after-treatment system are considered. For the OME concept combined with an internal combustion engine (ICE), the exhaust aftertreatment system has no DPF. For the concept combining liquefied methane with an ICE, the whole energy is supplied by the energy carrier liquefied methane and no diesel fraction is assumed. According to current regulations, the concepts with a fuel cell do not need an exhaust after-treatment system. Liquefied methane combined with a fuel cell produces only CO2 and water. Liquefied hydrogen combined with a fuel cell produces only water. The results of the comparison of these five concepts are shown in Table 8-4. The conventional diesel & ICE combination is the lightest drive train. It is then followed by the OME & ICE combination with a weight increase of 44 % and a volume increase of 15 % (reference is the diesel & ICE drivetrain). Taking into account the total weight of 30 t for the excavator, the weight increase for all four concepts is between 2 and 6 %. The volume increase for all four concept ranges

from 0.2 m³ to 3.9 m³. The weight as well as the volume increase are within an acceptable range for an excavator7 .

**Table 8-3: Weight and volume calculation of the five drive train concepts8**

 7 An excavator has a varying operating weigth (± 0.5-4 t) and is equipped with a counter weight (± 3-6 t), see excavator brochures. Therefore, an additional weight for an excavator of 0.6 to 1.7 t are in an acceptable range. Further, a 30 t excavator is usually used on large construction sites where an additional occupancy volume of 1.6 to 5.5 m³ does not impair the construction work.

**Table 8-4: Comparison of the five drive train concepts (based on Edwards et al. 2014b; Wu 2018)**

### **8.3 CO2 capture and storage systems for mobile machines**

Installing a CO2 capture and storage (CCS) system before the exhaust gas is released in the air can enable a reduction in the amount of emitted CO2 emissions. If the CO2 emissions are already considered as zero during combustion because the energy carrier has been produced in a sustainable way, then the CO2 captured and stored by the CCS systems have a negative value which means more CO2 has been removed than produced in the atmosphere.

The captured CO2 by such CCS systems can be sold and reused for the production of e-fuels or other industrial products.

In order to predesign a possible CO2 capture and storage system, a morphological box has been developed giving an overview of possible solutions for the functions defined in 4.3.7. Each level represents a step for the designing process and solutions are proposed on how to fulfil the function. The first step is to choose a way to adjust the temperature and pressure of the exhaust gas, so the right conditions for the CO2 separation process is obtained. The separation process is chosen in the second step. Depending on the separation process, a regeneration of the CO2 separating agent can be necessary. The choice of the type of regeneration process takes place in step three. The fourth step is the

storage of the separated CO2. For this purpose, first the temperature and pressure of the CO2 has to be adjusted so that it can be stored under the right conditions. The choice of the type of storage is the fifth step. Finally, a solution has to be chosen on how to remove the stored CO2 from the mobile machine (step six). Figure 8.4 depicts the morphological box showing possible solutions for each design step.

**Figure 8.4: Design method for a possible CCS system for mobile machines**

Based on the morphological box, two systems for mobile machines of the type "post-combustion" have been developed. Both system concepts separate the CO2e emissions by adsorbing CO2. In the first system, an adsorber material is used as filter and as storage. When the filter is full of adsorbed CO2, it is removed and replaced with a new filter. The filter has to be able to store as much CO2 as is produced by a full consumed tank. Ideally, when a fuel tank has to be filled up at a gas station, the filter can be replaced with a new one. The saturated filter can then together with others be brought into a central regeneration centre. For such a system, a gas cooler and a compressor are needed to bring the exhaust gas to the right temperature and pressure before flowing through the filter. The temperature and pressure to set, depends of the material used. The first system is schematically represented in Figure 8.5. Overall, this system has the advantage that it can be built in existing machines with little effort. A major disadvantage is the need for an existing infrastructure and regeneration centre to get the filters regenerated.

**Figure 8.5: CO2 capture and storage system 1 with an adsorber material used as a filter and as storage (based on Zeng 2018)**

The second system is schematically represented in Figure 8.6. Instead of a gas cooler, the system uses a turbocharger to cool down the exhaust gas with air to the right temperature. The cooled down exhaust gas is then lead through a three way valve through the filter of an adsorber material. The CO2 molecules are adsorbed by the filter and the exhaust gas now free of CO2 can be released into the atmosphere. In the meantime, when one filter is in the adsorption state, the other parallel filter is in the desorption or regeneration state where CO2 is released from the filter and lead through the three-way valve, the gas cooler and compressor into a storage tank. In the storage tank, the CO2 is stored in liquid form at ambient temperature and 200 bar in order to need the minimum storage space.

**Figure 8.6: CO2 capture and storage system 2 with an adsorber material used as a filter and a CO2 tank as storage**

Depending on the adsorber material used in the system, the adsorption and desorption conditions (temperature and pressure) will vary. For both systems, the following three materials are the best adequate: Metal-Organic Framework (MOF), zeolite material or activated carbon.

**Table 8-5: Properties overview of 3 possible CO2-adsorbent materials (Ben-Mansour et al. 2016; Zeng 2018)**

MOF materials are light, crystalline, sponge-like materials used to store or filter and separate selected elements from gases while letting the other elements pass through (MOF Technologies Adsorbent Nanomaterials). Zeolite material is composed of "an aluminosilicate framework which is comprised of a tetrahedral arrangement of silicon cations (Si4+) and aluminium cations (Al3+) that are surrounded by four oxygen anions (O2- )" (Moshoeshoe et al. 2017). Zeolite occurs in nature but can also be produced synthetically (ibid.). Activated carbon "is a porous carbon material, a char which has been subjected to a reaction with gases, sometimes with the addition of chemicals (e.g. ZnCl2) before, during or after carbonisation in order to increase its adsorptive properties" (Marsh and Rodríguez-Reinoso 2006). An overview of the CO2 capturing properties of all three materials are shown in Table 8-5.

**Table 8-6: Additional mass, volume and energy calculations for both systems9**

no reactivation process is necessary for the material contrary to activated carbon. Both system are designed for an excavator of 30t, 152 kW.

The additional mass, volume and energy necessary can be seen in Table 8-6. System 1 implemented in the reference excavator will correspond to an additional mass of 3.11 %, to an additional volume of 2.52 m³ and to an additional energy consumption of 1.96 %. System 2 implemented in the reference excavator will correspond to an additional mass of 0.71 %, to an additional volume of 1.68 m³ and to an additional energy consumption of 7.07 %. In both cases, the resulting additional mass, volume and energy consumption are within an acceptable range for the excavator.

In conclusion with such CO2 capture and storage systems implemented in mobile machines suited for conventional diesel engines drives or alternative future drives like fuel cells or use of alternative fuels, the CO2 emissions produced by the machine can be reduced over 99 %. The liquid CO2 stored in the machine can be sold and reused for the production of e-fuels or other industrial products. This results in new business models for construction companies. The additional workload of the system for the driver is low, as only the CO2 storage tank has to be emptied. This can take place at the same time as filling the fuel tank without needing additional time.

### **8.4 Climate-friendly mobile machine**

The analysis of alternative energy carriers resulted in OME and liquefied methane being the most promising alternatives for mobile machines. The combination of these fuels with a primary energy converter like an engine or a fuel cell compared to the conventional drive of an excavator resulted in a better overview of the resulting variations of weight, volume and greenhouse gas emissions. Considering all three criteria, drives with liquefied methane show the best results. By combining the drives of mobile machines with an additional system capturing and storing CO2, greenhouse gas emissions can further be reduced, eliminated or even reduced below zero so that the mobile machine becomes a CO2 atmosphere cleaning machine, see Table 8-7.

These are only some measure examples on how to transform the mobile machine into a greenhouse gas emissions reduced or free machine. All possible alternatives need to be further examined concerning environmental constraints, duty cycles of the specific mobile machine, etc.

# **9 Summary**

In order to slow down the wide-ranging impact of global warming, manmade greenhouse gas emissions have to be reduced. Each industry sector has to contribute to reducing their share of greenhouse gas emissions. The present work focused on developing a method for assessing the CO2e emitted from construction equipment during various construction processes.

On these grounds, it was first essential to define greenhouse gas emissions and understand how they affect the temperature on earth. By increasing gas concentrations in the atmosphere called greenhouse gases, more long-wave radiation (heat) is reflected back to the earth's surface which leads to a global temperature rise.

For a scientifically robust CO2e quantification method, requirements need to be specified. Therefore, first measures taken in different industries were analysed and needs were derived.

Then, through the analysis of existing CO2e quantification methods for construction equipment and construction applications shortfalls and thus research gaps were identified for these methods.

Identified needs and research gaps permitted developing the CO2e quantification method. First, a general common approach was defined on how to quantify CO2e emissions and their reduction valid for the construction sector and by extension, the agriculture sector. In fact, it is not uncommon to find e.g. tractors specifically developed for the agricultural sector working at construction sites or e.g. wheel loaders developed for construction applications working in the agricultural sector. The general common approach consisted of defining six common CO2e reduction potential pillars which cover past, present and future measures taken by the industry. The method should not only focus on machine engines but rather on machines in their various application areas. In order to quantify the CO2e reduction reached and expected, the method permits CO2e emissions assessment over different time periods. The CO2e emission amount difference between each period represents an increase or a reduction of greenhouse gas emissions reached or expected to be reached.

#### **Table 9-1: Influencing factors categorised according to the six pillars**

In order to quantify the CO2e emission consequences of certain measures taken, it is essential to correctly define the system boundaries of the method. If the system is too broad, the method becomes too complex and measures taken won't be apparent in the total CO2e emissions assessment. On the contrary, if the system is too narrow, the result does not yield the correct effect for measures taken to reduce CO2e emissions and can lead to false conclusions. Therefore, in this work, it was decided to take into account the destruction of CO2e sinks considered as preparatory work before construction takes place and the new formation of CO2e sinks after construction. Further, the method not only focuses on machine efficiencies but considers also process efficiencies, energy sources, operation efficiencies, material efficiencies and CO2e capture and storage technologies (the six CO2e reduction potential pillars). For each of the six pillars corresponding factors were defined (see Table 9-1). The factors categorised according to the pillar machine efficiency for example consider not only the engine, but the whole technology system of the machine as well as the machine's condition. Therefore, the method considers the whole machine and not just components like e.g. the engine (G1).

Some scientists argue that the amount of CO2e emissions is not informative enough to be able to deduce if the amount is within an acceptable range or simply too much (Stocker 9/19/2018). Therefore, the method gives the possibility of converting the CO2e amount into a currency value e.g. €, so that everybody including non-scientific persons can understand the impact of emitted greenhouse gas emissions.

In order to show that the method is valid for different construction applications, first, representative construction applications for the European sector were defined for the times past, present and near future.

Afterwards, through literature and expert surveys, it was possible to verify the defined individual factors for each of the six CO2e reduction potential pillars as well as to define their value ranges. By defining their values for the times past, present and near future, an influence analysis of these factors on an excavator took place. On the example of the excavator, it was possible to show the range of influence some factors can take on the total amount of CO2e emitted. The weather is the factor with the greatest influence range potential. It is followed by the factor representing the workplace and working environment conditions. This factor influences the driver of the machine and can consequently affect total CO2e emissions. The factor with the third largest potential in influencing the total greenhouse gas emissions is the energy source, e.g. using an alternative energy carrier to fossil diesel.

Applying the factor values for past, present and near future on the defined representative construction applications, enabled showing the development over time of CO2e emissions and thereby prove that the method is valid for different time periods (G2) and for different construction applications (G5). The simulation also showed that through variation of the factors from the six pillars, the resulting CO2e difference can be assessed with the method. Materials, construction processes, energy sources as well as operating conditions are taken into account in the method thus closing the research gaps G3, G4 and G6. In other words, by considering the six pillars, need N2 is fulfilled since the focus not only lies on the machine but rather on a holistic approach.

Another simulation on the example of a BK10 road construction showed that CO2e sinks destruction can contribute to an important CO2e share of the total amount of greenhouse gases emitted (13 %). However, this effect can be reduced or even eliminated with the right measures.

The CO2e quantification method was then validated at construction sites. An excavator, single drum roller, road pavers and tandem rollers were observed at a construction site. The total amount of fuel consumed was assessed and converted into CO2e emissions. The results were then compared with the theoretical amount of CO2e, resulting from application of the CO2e quantification method. According to the Pareto principle, the method should at least consider 80 % of the CO2e emissions emitted by each sub process. The difference between the practical and theoretical approaches were all within the acceptable range below 20 %.

In summary, the developed CO2e quantification method can be applied in different construction sectors and show the evolution of CO2e emissions along a specific timeline. By applying the method, comparisons between different processes or CO2e reduction measures can be made. The validation procedure of the method showed that the resulting CO2e amount values are credible, sufficiently representative estimates, enabling making statements about which measures should be taken and about how much influence these measures will have on the total CO2e amount emitted during a construction process. The method therefore fulfils need N4.

Through the application of the method, different measures could be derived on how to reduce CO2e emissions from mobile construction machines. One measure consisted of choosing an alternative energy carrier for mobile machines. Synthetic liquefied methane was determined as the most promising alternative for mobile machines. This measure closes research gap G7 by proving that the CO2e quantification method not only quantifies CO2 emissions but all greenhouse gas (CO2e) emissions and thus fulfils need N1.

Another measure consisted of combining an adequate alternative energy carrier with an adequate primary energy converter. Here the most promising solution seemed to be liquefied methane combined with a fuel cell drive.

Finally, in order to reach zero CO2e emissions, two concepts on what a carbon capture system for mobile machines could look like have been designed.

Combining all three measures in a mobile machine together, greenhouse gas emissions can be further reduced, eliminated or even reduced below zero so that the mobile machine removes CO2 from the atmosphere. These are only some measure examples on how to transform the mobile machine into a greenhouse gas emissions reduced or free machine. All possible alternatives need to be further examined concerning environmental constraints, duty cycles of the specific mobile machine, etc.

The focus in this thesis was on the reduction or elimination of CO2 emissions which is only one ecological aspect of sustainability. Ecological, economic and social aspects need to be considered for the whole chain from material extraction, through machine production, transportation, construction applications to recycling of the machine in order to develop a sustainable mobile machine in a sustainable construction environment.

Nevertheless, the validation of the CO2e quantification method was only made possible through the cooperation of construction industries and construction machine producers. Additionally, a transformation of mobile machines with an alternative drive as well as/or with an alternative energy source will only be possible if cooperation between different industry sectors and government takes place (N3).

To conclude, the "*empire of climate is* [indeed] *the first empire among all*" influencing men and society (Montesquieu 1748).

# **Appendices**

### **A.1 Results of the expert survey according to the Delphi method**

**2** 12/03/2019 Institute of Vehicle System Technology (FAST)

volume: 0.5m³

Average fuel consumption (bm) 23,8 l/h 11.4 l/h 20,4 l/h 12.7 l/h

**Info.:** bm is the average fuel consumption of the machine under ideal conditions, which equals to the fuel consumption during test drives (without idle).

volume: 3.3m³

Results of the expert survey according to the Delphi method

Dipl.-Ing. Isabelle Ays

Chair of Mobile Machines (Mobima)

width: 8m

11 t Working width: 1.9 m

#### **Elaboration of machine related efficiency**

Define the average fuel consumption at idle (bidle) **Definition of idle:** Idle, also called "low idle" is when only the engine is switch on but no driving or other operation takes place (no air conditioning).

Chair of Mobile Machines (Mobima)

**6** 12/03/2019 Institute of Vehicle System Technology (FAST) Dipl.-Ing. Isabelle Ays Results of the expert survey according to the Delphi method

205

#### **Elaboration of machine related efficiency**

**(***fsignificant improvement***)**

Describe shortly other significant technology improvements (single technologies or combination of technologies) having an influence on the fuel consumption (the reduction percentage is referenced to the value of

Describe shortly other significant technology improvements (single technologies or combination of technologies) having an influence on the fuel consumption

#### **Elaboration of machine related efficiency**

**(***fsignificant improvement***)**

Describe shortly other significant technology improvements (single technologies or combination of technologies) having an influence on the fuel consumption

#### **fdriver experience** Driver Effects of "process assistant systems" on the driver performance *fprocess assistant (driver experience)*

### **A.2 Simulation parameters of representative applications**

### **Building construction**

#### **Flat construction**

#### **Past**

#### **Present**

#### **Future**

#### **Office building**

#### **Past**

#### **Present and future**

#### **Road construction**

### **Road renewal**

### **Earthmoving work**

#### **Pit construction for a flat**

#### **Pit construction for an office building**

#### **Dam construction for a BK10 road**

#### **Slot construction for a BK10 road**

**Machines Number of**

**machines**

**tworking/day [h/day]**

**bl or bm [l/h]**

Appendices

### **A.3 Weight and volume calculation details of the five drive train concepts**

For the calculations, an excavator of 30 t with an engine power of 152 kW and a fuel tank of 520 l diesel, corresponding to 6,340 MJ is taken as reference.

### **Fuel**

The volume of fuel () is calculated for each concept with following formula:

$$V\_{fuel} = \frac{m\_{fuel}}{\rho\_{fuel}}\tag{I}$$

Where stands for the fuel mass and for the fuel density. The following table shows the density value and the lower heating values used for the calculations.

**Table A.3-1: Fuel density and lower heating value**

The fuel mass for concepts working with an ICE is calculated with following equation *(2)*.

$$m\_{fuel} = \frac{E}{H\_{u,fuel} \times \eta\_{ICE}}\tag{2}$$

Where E equals the energy output of 6,340 MJ, the ICE engine efficiency of 0.34 and , the lower heating value of the fuel.

The fuel mass for the concept working with a fuel cell and hydrogen H2 (2 ) is calculated with following equation *(3)*.

$$m\_{H\_2} = \frac{E}{H\_{\text{u,H}\_2} \times \eta\_{E-\text{Motor}} \times \eta\_{Fuel\ cell}} \tag{3}$$

Where E equals the energy output of 6,340 MJ, − the electric engine efficiency of 0.9 and ,2 the lower heating value of hydrogen.

The fuel mass for the concept "Liquefied 4 & fuel cell" is calculated based on the stoichiometric ratio of reactions *(4)*.

$$\begin{array}{l}CH\_4 + H\_2O \rightarrow CO + 3H\_2\\\hline CO + H\_2O \rightarrow CO\_2 + H\_2\\\hline CH\_4 + 2H\_2O \rightarrow CO\_2 + 4H\_2\end{array} \tag{4}$$

This leads to the following stoichiometric ratio:

$$n\_{CH\_4} = \frac{1}{4} \times n\_{H\_2} \tag{5}$$

Where nx stands for the mol of molecule x. Further, by inserting the mathematical relation *(6)* in *(5)*, equation *(7)* is obtained.

$$m\_{\chi} = \frac{m\_{\chi}}{M\_{\chi}}\tag{6}$$

$$m\_{CH\_4} = \frac{1}{4} \times \frac{m\_{H\_2}}{M\_{H\_2}} \times M\_{CH\_4} \tag{7}$$

Where stands for the mass and for the molar mass of molecule x. The mass of hydrogen 2 is calculated with equation *(8)*.

$$m\_{H\_2} = \frac{E}{\eta\_{fuel\ cell} \times \eta\_{Reference} \times \eta\_{E-motor} \times H\_{u,H\_2}} \tag{8}$$

Where is the fuel cell efficiency with 0.5, the reformer efficiency with 0.75, − the electric engine efficiency with 0.9 and ,2 the lower heating value of hydrogen.

#### **Tank**

The diesel and OME tank volume corresponds to the fuel volume. The volume of the hydrogen tank is considered to be twice as large as the volume of the fuel it contains. According to Weberbeck, the volume of the liquefied methane tank is twice as large as that of a diesel tank with the same energy output (Weberbeck 2016).

The mass of the tank of fuel x is calculated by multiplying the tank density , by the tank volume , , see equation *(9)*.

$$m\_{tank, \times} = \rho\_{tank, \times} \times V\_{fuel, \times} \tag{9}$$

The tank densities used are listed in Table A.3-2 and are calculated on the basis of tank data available on the market.

#### **Table A.3-2: Tank densities**

### **Drive**

According to CAT, the diesel engine of a 30 t excavator has a weight of approximately 715 kg and a volume of 0.79 m³ (CAT 2011). The weight and volume of the fuel cell, battery and reformer are approximate values calculated on the basis of existing products on the market.

### **Exhaust aftertreatment system**

The weight and volume of the exhaust aftertreatment system are approximate values calculated on the basis of existing products on the market.

### **A.4 Calculation details of two CCS systems**

For both systems, the weight and volume of the components are approximate values calculated on basis of existing products on the market.

### **System 1**

According to Göttlicher, the specific compaction work amounts at 35 bar approximately to 0.091 kWh per kg CO2 () (Göttlicher 1999).

An excavator with a diesel fuel tank of 520 l () will produce 1,368 kg CO2/Tank (2/), see calculation in *(1)*.

$$\begin{split} m\_{CO\_2/tank} &= V\_{Diesel} \times f\_{CO\_2,TTW} = 520 \text{ l} \times 2.63 \text{ kg } CO\_2/l \\ &= 1,368 \text{ kg } CO\_2 \end{split} \tag{1}$$

Where 2, stands for the converting factor of diesel into CO2 during combustion (tank-to-wheel).

The compressor will have an energy demand of 124 kWh for 1,368 kg CO2e, see equation *(2)*.

$$E\_{Compressor} = m\_{CO\_2/tank} \times f\_\chi = 1,368 \text{ kg } CO\_2 \times 0.091 \frac{\text{kWh}}{\text{kg } CO\_2} \quad (2)$$

$$= 124 \text{ MJ}$$

### **System 2**

The energy demand for the compressor of system 2 is calculated as for the compressor of system 1 using equation *(2)*. The only difference is the CO2 mass 2/, which is composed of the mass of CO2 produced by the combustion of the fuel (2,)and the mass of CO2 in the air absorbed to cool the exhaust gas (2, ), see equation *(3)*.

$$m\_{CO\_2/tank} = m\_{CO\_2,fuel} + m\_{CO\_2,absorbed\ air} \tag{3}$$

Where 2, is equals to the value calculated in *(1)* and 2, is calculated with equation *(7)*.

In order to calculate 2, with equation *(7)*, the following calculations must be performed beforehand:

a) Calculation of the mas of the exhaust gas

The mass of the exhaust gas ℎ is calculated according to equation *(4)*.

$$\begin{aligned} m\_{exhaust\ gas} &= m\_{delsel} + m\_{air\ for\ fuel\ combustion} \\ &= V\_{diesel} \times \varrho\_{delsel} + V\_{diesel} \times \varrho\_{diesel} \times f\_{air/diesel} \\ &= 520 \ l \times 0.832 \ \frac{kg\ diesel}{l} \times \left(1 + 14.5 \ \frac{kg\ air}{kg\ diesel}\right) \\ &= 6,706 \ kg \end{aligned} \tag{4}$$

Where ⁄ stands for the factor of how much air is needed in the ICE to burn diesel.

The heat energy Δℎ to cool down the exhaust gas from 300°C to 30°C is calculated with equation *(5)*.

$$\begin{aligned} \Delta Q\_{exhaus\,\,gas} \\ &= (m\_{exhaus\,\,gas}) \\ = \left( 303 \text{ K} \times 1,042 \frac{J}{kg \,\,K} - 573 \text{ K} \times 1,108 \frac{J}{kg \,\,K} \right) \times 6,706 \\ &= 2,143 \text{ MJ} \end{aligned} \tag{5}$$

Where ,ℎ stands for the specific heat capacity at different temperatures, 2 for the target temperature to cool down, 1 for the original temperature of the exhaust gas before flowing the turbine, see Figure 8.6.

The heat energy necessary to cool down the exhaust gas will be provided with the absorbed air. Therefore Δℎ equals Δ, which leads to equation *(6)*.

$$=\frac{\begin{array}{c} m\_{alr} = \\ \text{2,143 MJ} \end{array}}{\begin{pmatrix} 303 \ K \times 1,007 \frac{J}{kg \ K} - 573 \ K \times 1,108 \frac{J}{kg \ K} \end{pmatrix}} \tag{6}$$

The air contains 0.058 % of CO2 which means that according to equation *(7)*, 3.76 kg CO2 are contained in 6,491 kg air

$$\begin{split} m\_{\text{CO}\_2, \text{absorbed } air} &= f\_{\text{CO}\_2/air} \times m\_{air} = 0.058 \,\% \times 6,491 \, kg \\ &= 3.76 \, kg \end{split} \tag{7}$$

According to equation *(3)* the total mass of CO2 (2/) equals 1,372 kg. The demand of energy for the compressor in system 2 equals consequently 449 MJ.

## **List of all scientific publications**

#### **Analysis and Preliminary Design of Oxymethylene ether (OME) Driven Mobile Machines**

Wu, Y.; Ays, I.; Geimer, M. 2019. Karlsruher Institute of Technology, Karlsruhe. doi:10.5445/IR/1000097941

#### **Methane-Fuel cell-CCS-Drive: the emission-free working machine** Ays, I.; Geimer, M.

2019. Hybride und energieeffiziente Antriebe für mobile Arbeitsmaschinen : 7. Fachtagung, 20. February 2019, Karlsruhe, 143–163, KIT Scientific Publishing, Karlsruhe. doi:10.5445/IR/1000091557

#### **Flüssiges Methan als alternativer Energieträger für Landmaschinen**

Engelmann, D.; Ays, I.; Geimer, M. 2018. 76. Internationale Tagung LAND.TECHNIK (2018), Leinfelden-Echterdingen, 20.–21. November 2018

#### **Flüssigerdgas (LNG) als alternativer Energieträger für Landmaschinen-Geschlossener CO2 Kreislauf mit synthetischem Methan**

Ays, I.; Engelmann, D.; Geimer, M.

2018. Land. Technik - Agricultural Engineering - Das Forum für agrartechnische Innovationen, Leinfelden-Echterdingen, 20. - 21. November 2018, 119– 128, VDI Verlag, Düsseldorf

#### **Maschinenkonzepte für Mobile Arbeitsmaschinen mit Methanantrieb**

Ays, I. A.; Weberbeck, L.; Engelmann, D.; Geimer, M. 2018.  Mobile Maschinen, (4), 24–29

#### **CO2e Quantifizierung von mobilen Arbeitsmaschineneinsätzen im Erdbau, Steinbruch, Straßen- und Hochbau**

Ays, I.; Geimer, M. 2017. Hybride und energieeffiziente Antriebe für mobile Arbeitsmaschinen : 6. Fachtagung, 15. February 2017, Karlsruhe, 145–161, KIT Scientific Publishing, Karlsruhe

#### **Flüssiges Methan als alternativer Energieträger für mobile Arbeitsmaschinen**

Ays, I.; Engelmann, D.; Geimer, M. 2017. Hybride und energieeffiziente Antriebe für mobile Arbeitsmaschinen : 6. Fachtagung, 15. February 2017, Karlsruhe, 125–143, KIT Scientific Publishing, Karlsruhe

#### **Liquefied Natural Gas in Mobile Machines**

Weberbeck, L.; Engelmann, D.; Ays, I.; Geimer, M. 2016. ATZoffhighway worldwide, 9 (4), 38–45. doi:10.1007/s41321-016- 0532-8

#### **Verflüssigtes Erdgas in mobilen Arbeitsmaschinen**

Weberbeck, L.; Engelmann, D.; Ays, I.; Geimer, M. 2016. ATZ offhighway, 9 (4), 40–46. doi:10.1007/s35746-016-0033-9

#### **Sustainable energy storages for mobile machines**

Geimer, M.; Ays, I. 2015. Symposium on Efficiency of mobile machines and their processes in Brunswick 10/11. March 2015

#### **CO2 Quantification for Typical Mobile Machine Application Processes in Road Building, Earthmoving**

Ays, I.; Geimer, M. 2015. Symposium on Efficiency of mobile machines and their processes in Brunswick 10/11. March 2015

#### **Nachhaltige Energiekonzepte für mobile Arbeitsmaschinen - in welche Richtung gehen sie?**

Geimer, M.; Ays, I. 2014. Mobile Maschinen, (6), 18–25

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### **Karlsruher Schriftenreihe Fahrzeugsystemtechnik (ISSN 1869-6058)**

Herausgeber: FAST Institut für Fahrzeugsystemtechnik

### Karlsruher Schriftenreihe Fahrzeugsystemtechnik

Motivated by global warming, this work focuses on the development of a quantification method for greenhouse gas (CO2e) emissions from construction equipment. The method considers CO2e reduction potentials through influencing factors from six pillars: Machine efficiency, process efficiency, energy source, operating efficiency, material efficiency and CO2e capture and storage. Applying the method to representative construction applications for Europe in the timeline past - present - future, demonstrate that the method can be applied to any construction application and to any timeline. By comparing the results from two timelines, it is possible to quantify the reduction or increase of greenhouse gas emissions. On the example of selected construction machineries, it is shown that the method is valid and thus allows for making statements about certain CO2e reduction measures. Finally, transformation solutions are proposed to reduce greenhouse gas emissions from construction machinery. Liquid methane is able to reduce CO2e emissions by up to 85 %, combined with a fuel cell drive by over 100 % and by additionally combining it with a CO2 capture and storage system negative CO2e emissions are generated. This proposed combination transforms mobile machines into machines that cleanse the atmosphere of greenhouse gases.

ISSN 1869-6058 ISBN 978-3-7315-1033-8


**Author details**

Xiaoxi Men1\*, Chun'an Tang2 , Shanyong Wang3 , Yongping Li4 , Tao Yang2 and Tianhui Ma2 [8] Abbass, T, & André, V. Effect of Layer Orientation on the Failure of Layered Sand‐ stone under Brazilian Test Conditions. International Journal of Rock Mechanics and

Numerical Simulation of Hydraulic Fracturing in Heterogeneous Rock: The Effect of Perforation Angles…

http://dx.doi.org/10.5772/56012

511

[9] Abbass, T. Failure of Layered Sandstone under Brazilian Test Conditions: Effect of Micro-scale Parameters on Macro-scale Behaviour. Rock Mechanics and Rock Engi‐

[10] Tang, C A, Tham, L G, Lee, P, Yang, K, & Li, T H. L C. Coupled Analysis of Flow, Stress and Damage (FSD) in Rock Failure. International Journal of Rock Mechanics &

[11] Leng, X F, & Yang, T H. Numerical Simulation and Analysis of Rocks with Single Hole Each Under Hydraulic Fracturing. World Nonferrous Metals (2002). , 10, 32-34.

[12] Tang, C A. Numerical Simulation to Influence of Pore Pressure Magnitude and Gra‐ dient on Fracture Propagation in Brittle Heterogeneous Rocks. Rock and Soil Me‐

[13] Yang, T H. Influence of Heterogeneity of Mechanical Properties on Hydraulic Frac‐ turing in Permeable Rocks. Rock Mechanics and Rock Engineering (2004). , 37(4),

[14] Li, G, & Tang, C A. Three-Dimensional Micro Flow-Stress-Damage (FSD) Model and Application in Hydraulic Fracturing in Brittle and Heterogeneous Rocks. Key Engi‐

[15] Yang, T H. Numerical Approach to Hydraulic Fracturing in Heterogeneous and Per‐

[16] Yang, T H, & Tang, C A. Numerical Simulation of Hydraulic Fracturing Process in Heterogeneous Rocks under Different Confining Pressures. Chinese of Computation‐

Mining Sciences (2010). , 47(2), 313-322.

Mining Sciences (2002). , 39(4), 477-489.

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chanics (2003). , 24, 17-20.

neering Materials (2011).

meable Rocks. Key Engineering Materials (2003).

al Mechanics (2004). , 21(4), 419-424.

251-275.

\*Address all correspondence to<EMAIL_ADDRESS><EMAIL_ADDRESS>Sha‐<EMAIL_ADDRESS><EMAIL_ADDRESS><EMAIL_ADDRESS><EMAIL_ADDRESS>
1 Northeastern University, Shenyang, China

2 Dalian University of technology, Dalian, China

3 ARC Centre for Geotechnical Science and Engineering, The University of Newcastle, NSW, Australia

4 Fracturing and Acidizing Technical Service Center, Research Institute of Petroleum Exploration & Development-Langfang, Petrochina, Langfang, China

### **References**

[8] Abbass, T, & André, V. Effect of Layer Orientation on the Failure of Layered Sand‐ stone under Brazilian Test Conditions. International Journal of Rock Mechanics and Mining Sciences (2010). , 47(2), 313-322.

**Author details**

<EMAIL_ADDRESS>
Australia

**References**

Xiaoxi Men1\*, Chun'an Tang2

510 Effective and Sustainable Hydraulic Fracturing

1 Northeastern University, Shenyang, China

Oct (1993). Paper SPE 26597.

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2 Dalian University of technology, Dalian, China

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, Yongping Li4

\*Address all correspondence to<EMAIL_ADDRESS><EMAIL_ADDRESS>Sha‐<EMAIL_ADDRESS><EMAIL_ADDRESS><EMAIL_ADDRESS>
3 ARC Centre for Geotechnical Science and Engineering, The University of Newcastle, NSW,

4 Fracturing and Acidizing Technical Service Center, Research Institute of Petroleum

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**Chapter 25**

**Quantitative Evaluation of Completion Techniques on**

In many of the active shale plays, the extremely low permeability of the shale means simple, bi-planar hydraulic fractures do not provide enough surface area to make an economic well. In these cases, the optimal, economic completion requires stimulation of the natural fracture system - often called increasing the 'complexity' of the stimulation. A number of different multi-well completion techniques have been proposed to enhance shale complexity. The 'simul-frac' technique is where companion wells are stimulated at the same location at the same time, whereas the 'zipper-frac' technique employs companion wells that are stimulated in staggered locations at the same time. The intention with these techniques is to alter either or both the stress field and the pore pressure field to enhance the shearing of natural fractures.

In this paper, we present the results of a numerical study to quantitatively evaluate the effectiveness of multi-well completion techniques, particularly the 'modified zipper-frac' technique, to optimize shale completions. The study includes a parametric study of the effects of in-situ stress conditions, natural fracture orientation and fracture friction, and hydraulic fracture layout on changing near and far-field natural fracture shear (complexity). Changes in the stress field, particularly shear stress, are considered the primary means of increasing fracture complexity. The quantitative results of the study provide a means to optimize the application and design of different multi-well completion techniques as a function of the presented parameters. Optimized completion designs mean lower well costs, greater produc‐

**Keywords:** Hydraulic fracturing, stimulation, unconventional, complexity, well comple‐ tion, shale, numerical simulation, simul-frac, zipper-frac, discrete element model, DEM,

and reproduction in any medium, provided the original work is properly cited.

© 2013 Nagel et al.; licensee InTech. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use,

© 2013 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution,

distribution, and reproduction in any medium, provided the original work is properly cited.

**Influencing Shale Fracture 'Complexity'**

N. Nagel, F. Zhang, M. Sanchez-Nagel and B. Lee

Additional information is available at the end of the chapter

tion and, ultimately, improved well economics.

http://dx.doi.org/10.5772/56304

**Abstract**

microseismicity


**5. Conclusion**

Many published works have discussed the CMOS transceiver design for communications, but few demonstrated the CMOS transceiver design for medical radar sensing. This chapter demonstrates the design of biomedical radar sensing on the single CMOS integrated UWB transceiver. The advantage of using integrated CMOS UWB technology in biomedical sensing is that this technology provides ultra-low power, ultra-low cost, and ultra-low area solutions with much accurate and reliable performance. This chapter proposes an integrated radar system architecture which can achieve the radar sensing for heart rate monitoring, and explores and implements the integrated single chip radar transceiver circuit in CMOS IC. This chapter shows the implementation of the low-power low cost CMOS biomedical radar using UWB pulse for bio-monitoring.

This chapter can be expended further to apply in biomedical imaging using impulse radio radar. By characterizing the reflection properties of different tissues inside human body, an image of fluoroscopy of the human body can be generated under UWB radar scanning. The UWB radar will lead a technology breakthrough in the medical imaging area.


**Author details**

Tae Moon Jeong and Jongmin Lee\*

\*Address all correspondence to<EMAIL_ADDRESS>
Handong Global University, Pohang, Republic of Korea

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gated by light pulses with an ultrashort time scale. Since the invention of laser, the application field of laser has been dramatically expanded as the laser intensity increases. Now, the acceleration of charged particle by intense coherent light field became possible in the relativ‐ istic laser intensity regime, and new era for studying the laser-plasma interaction in the

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30 High Energy and Short Pulse Lasers

Tae Moon Jeong and Jongmin Lee\*

\*Address all correspondence to<EMAIL_ADDRESS>
Handong Global University, Pohang, Republic of Korea

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**Author details**

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*Article* **Nanomechanical Concepts in Magnetically Guided Systems to Investigate the Magnetic Dipole Effect on Ferromagnetic Flow Past a Vertical Cone Surface**

**Auwalu Hamisu Usman 1,2, Zahir Shah 3, Poom Kumam 4,5, Waris Khan 6 and Usa Wannasingha Humphries 1,\***

**Abstract:** Because of the floating magnetic nanomaterial, ferrofluids have magneto-viscous properties, enabling controllable temperature changes as well as nano-structured fluid characteristics. The study's purpose is to evolve and solve a theoretical model of bioconvection nanofluid flow with a magnetic dipole effect in the presence of Curie temperature and using the Forchheimer-extended Darcy law subjected to a vertical cone surface. The model also includes the nonlinear thermal radiation, heat suction/injection, viscous dissipation, and chemical reaction effects. The developed model problem is transformed into nonlinear ordinary differentials, which have been solved using the homotopy analysis technique. In this problem, the behavior of function profiles are graphically depicted and explained for a variety of key parameters. For a given set of parameters, tables representthe expected numerical values and behaviors of physical quantities. The nanofluid velocity decreases as the ferrohydrodynamic, local inertia, and porosity parameters increase and decrease when the bioconvection Rayleigh number increases. Many key parameters improved the thermal boundary layer and temperature. The concentration is low when the chemical reaction parameter and Schmidt number rises. Furthermore, as the bioconvection constant, Peclet and Lewis numbers rise, so does the density of motile microorganisms.

**Keywords:** ferromagnetic; nanofluid; bioconvection; porous medium; heat suction/injection; magnetic dipole


**Author details**

Isaac O. Daniel1 \* and Mulualem T. Kassa2

1 Excel Agrology – SeedTech. Inc., Winnipeg, Canada

2 BioTEI Inc., University of Manitoba, Winnipeg, Canada

\*Address all correspondence to<EMAIL_ADDRESS>
© 2021 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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*DOI: http://dx.doi.org/10.5772/intechopen.96273*

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*Advances in Food Development with Plant-Based Proteins from Seed Sources DOI: http://dx.doi.org/10.5772/intechopen.96273*