1. Introduction
Nowadays, cities are confronted by traffic problems, resulting in increasing environmental impacts. Looking at the traffic volume of motorized private transport in Germany in 2017, 17.5% [
1] results from shopping trips. After leisure trips (35.4%) and commuting (20.0%), this occupies the third position in official statistics [
1]. As a proportion of all shopping trips relates to the supply of foodstuffs, the delivery of groceries instead of an individual customer pickup offers a chance to reduce traffic in cities. In this respect, tours by delivery vehicles can substitute customer shopping trips. This scenario simultaneously offers an opportunity for reducing energy and carbon dioxide emissions.
In many studies, the delivery of goods is compared to customer pickup. Siikavirta et al. [
2] analyze this scenario in a case study for a grocery shop in Finland. There, the substitution of shopping trips by delivery would lead to a reduction of CO
2 emissions in the range from 18% to 87%. Similar results were presented by Halldórsson et al. [
3]. The authors investigated the specific CO
2 emissions for delivery and customer pickup by averaging various statistical data. While a delivery would lead to emissions of 181 g CO
2 per drop, the customer pickup scenario would emit around 4274 g CO
2. They also examined the influence of the success rate of first delivery on the specific emissions. If the first delivery is not successful, the emissions are clearly increased.
Since the delivery of groceries can be seen as a case of deliveries on the last mile of city logistics, many scientific papers deal with this part of the supply chain. Thereby, the energy efficiency over this last part of a delivery chain is often discussed [
4]. In general, the last mile is seen as the least efficient part of a supply chain [
5]. Because of customer requirements, such as fast and reliable delivery, many delivery vehicles are used, resulting in a low average vehicle utilization [
6]. Hence, different optimization approaches were developed in order to reduce the environmental impact of deliveries in this part of the supply chain. Bányai [
7], for example, presents a real-time optimization model in order to increase energy efficiency. Since the delivery vehicle’s drivetrain affects energy consumption and emissions, the use of electric delivery vehicles is seen as an alternative to internal combustion engine vehicles [
8]. Due to high costs, the use of battery electric vehicles is not yet profitable today, but might be viable in the near future [
9,
10]. Davis and Figliozzi [
11] analyzed the competitiveness of electric compared to diesel delivery vans. Evaluating the results of their model, they name different factors, such as fleet size, battery life, and route characteristics as important influencing parameters for the competitiveness of electric delivery vehicles. Oliveira et al. [
12] carried out a systematic literature review on the use of different delivery vehicles on the last mile, which offer the opportunity to increase sustainability. In addition to electric delivery vehicles, they reviewed the use of bicycles and tricycles, as well as smaller commercial vehicles, as alternatives. Moreover, autonomous delivery vehicles are under development, but the legal situation still needs to be clarified for future productive use [
13]. In general, the use of intermodal transportation, or a shift to other transportation modes, offers a chance to influence the environmental aspects of deliveries [
14]. Göçmen et al. [
15], for example, use ecologic, economic, as well as social impact factors to optimize the intermodal transportation network of a logistics company in Turkey.
Looking at the delivery of groceries, the approach of a modal shift to reduce environmental impacts can also be identified. Using a delivery based approach, the transportation of groceries is shifted from individual shopping trips to a set of delivery van tours. As the delivery of foodstuffs also consumes energy and emits CO
2, it also forms a possible ecological load. Hence, break-even points must be analyzed to determine from what point the delivery of groceries is environmentally more beneficial than individual shopping trips. In other words, as motorized private transport is mainly responsible for the energy consumption and emissions of individual shopping trips [
16], minimum shares of private vehicle use in order to avoid additional energy consumption and CO
2 emissions caused by the delivery must be evaluated. In order to rate the environmental impact and increase the sustainability of future grocery supply of cities, the knowledge of those break-even points is relevant for different stakeholders, such as governments, city administrations, possible users of grocery deliveries, and delivery services.
The aim of this paper is to introduce a modeling approach based on real-world geodata and Monte Carlo simulations in order to identify and analyze these break-even points for energy consumption and CO
2 emissions in the case of Haidhausen Süd, a district in the center of the city of Munich, Germany. Using the model, the general potential to reduce energy and carbon dioxide emissions by delivery of groceries is first analyzed. As the use of freight electric vehicles for deliveries in city logistics becomes more and more popular, the evaluations address Internal Combustion Engine Freight Vehicles (ICEFV), as well as Electric Freight Vehicles (FEV). In relation to the goals of the German government to reduce the environmental impact of the transportation sector [
17], the use of electric vehicles in the field of motorized private transport is named. Hence, the influence of a complete electrification of the German private vehicle fleet on break-even points is integrated in the analyses of this paper.
Brown et al. [
18] also analyzed break-even points for carbon dioxide emissions. For this purpose, they compared the customer pickup to the delivery with combustion-engine delivery vans. Davis and Figliozzi [
11] integrated FEVs in their study and calculated economic break-even points, depending on different parameters. Martín et al. [
19] analyzed trends and research gaps in the field of e-groceries, which can be seen as directly related to the delivery of foodstuffs. Their investigations showed that this research topic plays a minor role in Germany in recent years. This fact is affirmed looking at the cited studies of Brown et al. [
18], Siikavirta et al. [
2], and Davis and Figliozzi [
11], dealing with comparisons in the United States and Finland. As the electricity mix has a huge influence on the carbon dioxide emissions of electric vehicles [
20] and the use of different transportation modes for grocery shopping is influenced by the country-specific behavior of customers [
18], it is necessary to analyze break-even points for Germany.
Hence, this paper focuses on the following points:
An assessment methodology for the investigation of energy and CO2 savings as well as break-even points based on real-world geodata derived from OpenStreetMap and Monte Carlo simulations is presented
The use of electric vehicles for the delivery of groceries
Break-even points for energy and carbon dioxide emissions
Impact evaluation of electric and combustion-engine private vehicle fleets for customer pickup trips on possible savings
Evaluation of two different amounts of delivered customers
Results analysis for a district of Munich, Germany
Following the introduction,
Section 2 presents the used materials and methods. This section first describes the calculation of the distances the delivery vehicles and customers must drive. For this purpose, geodata from OpenStreetMap [
21] is used in combination with a Monte-Carlo-Simulation. Then, the approach to calculate energy consumption and emissions of delivery vans and private vehicles is introduced. In
Section 3, results are presented and discussed. Here, the potential to save energy and CO
2-emissions by a delivery of groceries in Haidhausen Süd using ICEFV and FEV is analyzed and discussed. To do so, the modal split of customer shopping trips in Germany is used. Subsequently, the break-even points, influenced by the already named parameters, are analyzed.
Section 4 draws conclusions based on the results and gives an outlook.
3. Results and Discussion
3.1. Potential for Saving of Energy and CO2 at the Current Share of Private Vehicle Use for Shopping Trips
It is well-known that not all customer shopping trips for groceries are executed with private vehicles. In order to identify the potential of a delivery of groceries to save energy and CO2, the modal split for shopping trips needs to be considered.
Figure 5 shows the modal split for shopping trips in Germany dependent of the community size [
16]. The visualized values are valid for people who have permanent access to motorized private vehicles. Only shopping trips are considered. The use of motorized private transport clearly decreases as the number of inhabitants in a community increases. Combining the shares of driver and co-driver, in communities with less than 20,000 inhabitants, a share of 72% [
16] uses private vehicles for its grocery shopping. Looking at cities with more than 500,000 inhabitants, only around 46.5% [
16] use this mode. As this percentage decreases, other modes become more popular. Due to reduced distances to the nearest shopping facility, there is a higher share of pedestrian or cyclist shoppers. Equally, a higher share uses public transport for this application. This can be traced back to a higher availability of this mode plus a higher serving rate of public transport. The availability of parking lots as well as the traffic flow in cities can also be seen as drivers for the reduced percentage of motorized private transport used for shopping trips [
16].
As Haidhausen Süd is a part of the city of Munich, which has around 1.45 million [
22] inhabitants, the modal split for communities with more than 500,000 inhabitants is used for further investigation. Applying data for communities with a lower number of inhabitants would not reflect the urban structure of Haidhausen Süd. Hence,
Table 6 summarizes the distribution of the shopping trips amongst the different traffic modes for a delivery probability of 10% and 20% in Haidhausen Süd. Here, the shares of motorized private transport or simplified use of private vehicles are the major drivers for energy consumption and carbon dioxide emissions caused by private shopping trips. Neglecting the low percentage of public transport, and based on the fact that cyclist or pedestrian shopping trips do not consume energy or produce carbon dioxide emissions, this statement can be approved.
Using the data from
Table 6, at a delivery probability of 10% a total distance of approximately 388 km is covered by private vehicles. Doubling the amount of delivered customers, a total of 775 km is driven by this mode. With those distances, the potential to save energy at the current share of private vehicle use can be evaluated.
Figure 6 compares the energy demand of ICECVs at the current share of private vehicle use for grocery shopping (46.5%) with the energy consumption of FEVs and ICEFVs. At both investigated delivery probabilities, a grocery delivery would lead to energy savings. Due to the higher efficiency or lower specific energy consumption of FEVs, the absolute as well as relative savings show higher values when using those vehicles. As the doubling of the amount of delivered customers leads not to a doubling of the energy use of the delivery vehicles, the energy savings are not constant at different delivery probabilities.
Table 7 gives an overview of absolute and relative energy savings. Even at the share of private vehicle use of 46.5%, the delivery of groceries with ICEFVs would lead to energy savings of around 73.6% and 78.4% compared to individual shopping trips with ICECVs, at a delivery probability of 10% and 20%, respectively. The energetic advantages of FEVs lead to savings of 92.3% and 93.7%.
Looking at the CO
2 emissions (
Figure 7), delivery instead of customer pickup would also lead to savings. Here, the relative CO
2 savings in the case of a delivery with ICEFVs show almost the same values when compared to the energy savings, because the emission factors of ICEFVs and ICECVs are more or less equal. Applying FEVs for the delivery of groceries, the CO
2 savings are decreased compared to energy savings. This fact arises from the significantly higher specific emissions of the electricity mix compared to the German private vehicle fleet. Based on
Table 8, relative as well as absolute savings of CO
2 can be concretized. At a delivery probability of 10%, the use of ICEFVs instead of customer shopping trips would lead to CO
2 savings of around 49.5 kgCO
2 per delivery tour, or 73.3%. Using FEVs, the absolute savings increase to a value of approximately 58 kgCO
2, or 85.8%.
Combining the results, the delivery of groceries in this district of the city of Munich would provide an opportunity to save energy and CO2.
3.2. Analysis of Break-Even Points for Energy Consumption
Figure 8 shows the resulting energy savings at a delivery probability of 10% for shares of private vehicle use in the range from 0% to 100%. Neglecting public transport again, the minimum share of private vehicle use to generate energy savings or the break-even point is visualized as the intersection of the saving-curves with the axis of private vehicle share.
Looking at the curve of customer and delivery vehicles with combustion engines (ICEFV + ICECV), a delivery would offer the chance to save energy at shares greater than 12.3%. Since the FEVs consume less energy than ICEFVs, this minimum share is reduced to 3.6% (FEV + ICECV). As ECVs show a lower energy consumption than ICECVs, the minimum share of customer trips for energy savings is increased in general, when looking at an electrified customer vehicle fleet. The view on FEVs and ECVs (FEV + ECV) leads to a minimum share of 15.7%. In the case of a delivery with ICEFVs, ECVs would lead to an intersection at 53.9% (ICEFV + ECV). Assuming a constant modal split for future developments, this scenario would lead to additional energy consumption or no savings caused by the delivery, as the current share of private vehicle use is 46.5%. Since all other named scenarios show break-even points below this share, this leads to the statement that electrification of the customer vehicle fleet requires the electrification of delivery vehicles for energy savings still to be made.
In contrast to the break-even points, a share of 100% reflects the fact that all customers use private vehicles for shopping trips. There, the use of FEVs and a customer vehicle fleet consisting of ICECVs leads to the highest savings. The use of ICEFVs in combination with ECVs would offer the chance to save around 45% of energy. In general, the relative savings increase with an increasing share of private vehicle use. In addition to the shifting of the break-even point, a decreasing specific energy consumption of the private vehicle fleet is damping to the curve of the savings.
The doubling of the amount of served customers leads to a left-shift of the savings-curves (
Figure 9), resulting in lowered cutting-points and higher savings at a share of 100%. The course of the savings is affected by the increase of the energy consumption of the delivery vehicles. At a delivery probability of 20%, the use of ICEFVs compared to a fleet of ECVs would offer the opportunity to save energy at the current share of private vehicle use for shopping trips. In general, the left-shift derives from the increased absolute number of substituted shopping trips.
Except for the investigation of ICEFV + ECV at a delivery probability of 10%, all depicted scenarios would lead to energy savings at the current share of private vehicle use for grocery shopping.
3.3. Analysis of Break-Even Points for CO2 Emissions
Compared to the energy savings, the break-even of carbon dioxide savings are clearly different in some scenarios.
Figure 10 and
Figure 11 show the results for a delivery probability of 10% and 20%, respectively.
The use of ICEFVs for the delivery of groceries instead of individual shopping trips by an ECV-fleet would offer the chance of reducing CO2-emissions starting at shares greater than 29.4%, at a delivery probability of 10%. The distinct lowering of the break-even point compared to energy savings (53.9%) in this case derives from the high difference between the specific CO2-emissions of electricity and diesel fuel. Decreasing specific emissions of the charging electricity mix would result in higher minimal shares of private vehicle use in order to generate savings. As the reduction of specific emissions of the electricity mix is a declared goal for future development, the statement derived at the analysis of energy savings for this scenario is supported. Assuming a constant modal split for shopping trips in future, a complete electrification of the private vehicle fleet must presuppose the use of FEVs for the delivery of groceries simultaneously to save CO2.
This behavior is depicted in the scenario of FEV + ECV. There, the minimum shares of private vehicle use are equal to the ones derived for analysis of energy savings for both examined delivery probabilities. This can be drawn back to the equal specific emissions of the charging electricity mix.
Looking at the use of ICEFVs in contrast to an ICECV-Fleet, the break-even point is also almost constant compared to energy savings. Since the specific emissions of those vehicle types are more or less the same, the share is almost unchanged. While the share for saving energy is 12.3%, it increases marginally to 12.4% when considering the CO2 savings at a delivery probability of 10%.
Lastly, the consideration of FEVs and ICECVs leads to increased break even points of emissions compared to the energy savings. At a delivery probability of 10%, a minimum of approximately 6.6% of all shopping trips must be accomplished by private vehicles in order to save carbon dioxide. This behavior again can be lead back to the difference between the specific emissions.
With a view to doubling the amount of customers using the delivery of groceries, the same tendency as already described for the break-even points of CO
2 emissions can be observed. In contrast to energy savings, all depicted scenarios would lead to CO
2 savings at the current share of private vehicle use for grocery shopping, considering the current specific emissions.
Table 9 puts together the results for the break-even points in order to save energy and carbon dioxide in Haidhausen Süd by a delivery of groceries.
4. Conclusions and Outlook
The results of this paper show that the delivery of groceries in Haidhausen Süd, a district of the city of Munich, has the potential to save energy and CO
2 compared to individual shopping trips. A distinctive finding is that not only combustion-engine, but also electric delivery vehicles, have the potential to save energy and CO
2. Another finding is that the substitution of customer shopping trips by FEVs leads to higher relative CO
2 savings than the use of ICEFVS, which derives from the higher efficiency of electric vehicles, although the specific emissions of the German electricity mix clearly are higher compared to diesel fuel. The fact that even the use of ICEFVs offers the opportunity to save energy and CO
2 compared to individual customer shopping trips calls into question whether FEVs are necessary to decrease the environmental impact. On the one hand, the use of FEVs offers the opportunity of a diversification of energy sources through sector coupling and helps to improve the sustainability of transportation. On the other hand, the purchase costs of FEVs are currently rather [
9,
10]. Although the use of FEVs might not be economically profitable yet, the use of FEVs for the delivery of groceries is an option to further decrease the environmental impact compared to customer pickup and the use of ICEFVs.
As the results showed, the delivery of groceries leads to savings across a wide range of private vehicle use for shopping trips in Haidhausen Süd. This statement is supported by the location of the break-even points, marking the share of private vehicle use where the delivery starts to be environmentally beneficial compared to individual grocery shopping trips with private vehicles. Hence, even if a huge share of customers shifts to environmentally friendly modes for the shopping of groceries, a delivery would still offer opportunities to save energy and CO2. This statement is also valid if the average distance of one customer pickup increases, for example, if the supermarket is located at the borders of the region of investigation. Therefore, the delivery would show benefits even at lower shares of private vehicle use. Consequently, the length of a customer shopping trips has a huge effect on the break-even points or savings. On the other hand, if the depot of the delivery vehicles is located further away from the region of investigation, savings may be reduced. Additionally, the quantity of avoided customer shopping trips affects the savings. As the number of substitutions increases, more delivery vehicles must be employed. Hence, the results indicate higher energy use and CO2 emissions of the delivery vehicles.
The results of the paper can be summarized in the following:
Specific energy consumption and specific CO2 emissions of private as well as delivery vehicles clearly affect the position of break-even points
Break-even points for energy use and carbon dioxide emissions must be evaluated independently of each other, because the results can differ
When internal combustion-engine delivery vehicles are used, a complete electrification of the private vehicle fleet can cause additional energy consumption at the current share of private vehicle use for shopping trips in Germany
In this case, a reduction of the specific CO2 emissions of the electricity mix could also lead to additional emissions caused by the delivery
At the current share of private vehicle use, an electrification of the private vehicle fleet requires the use of electric delivery vehicles in the future if energy savings and emission reductions are still to be made
Interpreting the results, the limitations of this study have to be considered, as they can affect the positions of the break-even points:
The trips of the customers start and end at the same positions. Chained customer shopping trips are not considered. The integration of the grocery purchase in other trips (for example in the trip to return from work) leads to a shift of the break-even points as the distances of customer trips decrease. Hence, more customers can use the private vehicle for grocery shopping to reach the energy consumption and CO2 emissions of the delivery vehicles.
Time windows for delivery are not considered in the optimization of the route; the integration of this approach would also lead to a shift of the break-even points, since the distance covered by the delivery vehicles changes. In addition to that, perhaps more delivery vehicles must be employed.
The refrigeration of the stowage of the delivery vehicles is not considered; a consideration would lead to higher specific energy consumption, resulting in a shift of the break-even points.
Since new concepts for urban mobility have been developed in recent years, the share of private vehicle use might change in the future. The methodology presented in this paper can be used for future evaluations of break-even points and potentials for energy savings and reductions in emissions. For future research, the effects of the ongoing decarbonization of the German electricity mix on break-even points should be analyzed in detail. Here, the influence of a time-shift of deliveries in order to use time slots with low carbon dioxide intensity for the charging of electric vehicles should be investigated.