Impacts of E-Micromobility on the Sustainability of Urban Transportation—A Systematic Review

Abstract

When considering the sharp growth rate of the use of e-micromobility vehicles, such as e-scooters and e-bikes, it is necessary to investigate whether these emerging modes of transport play a sustainable role in cities in terms of their energy efficiency, emissions, and their relationship with other modes of mobility, such as public transport. This paper aims to provide a comprehensive overview of the impacts of e-micromobility through a systematic review of relevant studies in the field of e-scooters and e-bikes. We followed the steps of PRISMA to conduct a systematic literature review, including identification, screening, eligibility and inclusion steps. One hundred forty-six studies were reviewed and compiled, and 29 of these studies were selected for the focus of this review and their research data were synthesized. The impacts of e-micromobilities were categorized into four categories—travel behaviors, energy consumption, environmental impacts, and safety and related regulations. The category of travel behaviors includes the analysis of the purposes of travel, modal shift from different modes of transport to e-micromobility vehicles, average travel time, and distance. In this review, the findings of relevant studies in different cities around world are compared to each other and synthesized to give an insight into the role of e-micromobility in the present and in the future of urban transportation.

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applied
sciences
Review
Impacts of E-Micromobility on the Sustainability of Urban
Transportation—A Systematic Review
Buket ¸Sengül 1and Hamid Mostofi 2, *


Citation: ¸Sengül, B.; Mostofi, H.
Impacts of E-Micromobility on the
Sustainability of Urban
Transportation—A Systematic
Review. Appl. Sci. 2021,11, 5851.
https://doi.org/10.3390/app11135851
Academic Editors:
Roland Jachimowski and
Michał Kłodawski
Received: 17 May 2021
Accepted: 21 June 2021
Published: 24 June 2021
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1Sustainable Mobility Management, Euref Campus, Technische Universität Berlin, 10623 Berlin, Germany;
buket.sengul@campus.tu-berlin.de
2
Mobility Research Cluster, Department of Work, Technology and Participation, Technische Universität Berlin,
10587 Berlin, Germany
*Correspondence: mostofidarbani@tu-berlin.de
Abstract:
When considering the sharp growth rate of the use of e-micromobility vehicles, such as
e-scooters and e-bikes, it is necessary to investigate whether these emerging modes of transport
play a sustainable role in cities in terms of their energy efficiency, emissions, and their relationship
with other modes of mobility, such as public transport. This paper aims to provide a comprehensive
overview of the impacts of e-micromobility through a systematic review of relevant studies in the
field of e-scooters and e-bikes. We followed the steps of PRISMA to conduct a systematic literature
review, including identification, screening, eligibility and inclusion steps. One hundred forty-six
studies were reviewed and compiled, and 29 of these studies were selected for the focus of this
review and their research data were synthesized. The impacts of e-micromobilities were categorized
into four categories—travel behaviors, energy consumption, environmental impacts, and safety and
related regulations. The category of travel behaviors includes the analysis of the purposes of travel,
modal shift from different modes of transport to e-micromobility vehicles, average travel time, and
distance. In this review, the findings of relevant studies in different cities around world are compared
to each other and synthesized to give an insight into the role of e-micromobility in the present and in
the future of urban transportation.
Keywords:
e-micromobility; e-scooter; e-bike; systematic literature review; sustainable mobility;
urban transportation; mobility behaviors
1. Introduction
Transportation is one of the most dynamic elements of cities, substantially affecting
the other components of cities, as well as citizens’ lives. In this context, there is a significant
association between urban transportation and the sustainability of the urban environment
in terms of energy consumption and emissions. According to the International Energy
Agency (IEA, 2020), the transportation sector produced 24 percent of total CO
2
emissions
in the world in 2019, and it consumed 28 percent of the total energy in the USA. Further-
more, in Europe the transport sector accounted for 25 percent of CO
2
emissions in 2016
and approximately 94 percent of the energy demand which is provided by fossil energy.
Therefore, it is necessary to develop more sustainable mobility systems, which is defined as
a sector that uses efficiently energy resources and generates fewer emissions and pollution
related to transport congestion [1–5].
Recently, newly emerging mobility services have been developed in cities around the
world, which citizens have adopted remarkably quickly. One of these new mobility modes
is e-micromobility, which has gained a considerable share in the distribution of urban
modes of transport. For instance, in the USA, e-scooter and e-bike sharing led to around
45 million trips in 2018 [
6
]. In this paper, e-micromobility refers to e-bikes and e-scooters.
Micromobility is defined as small and lightweight (less than 500 kg) modes of transport
with speeds less than 25 km/h, most of which are used individually, such as the use of
Appl. Sci. 2021,11, 5851. https://doi.org/10.3390/app11135851 https://www.mdpi.com/journal/applsci

Appl. Sci. 2021,11, 5851 2 of 20
bicycles, and with standing position, such as the use of scooters. E-micromobility vehicles
are different from micromobility vehicles due to their motorized powertrains, which are
electric, as in e-bikes, e-scooters, and e-skateboards [
7
,
8
]. Regarding the rapid growth rate
of e-micromobility in global metropolises, some studies indicate that car ownership and car
dependency have declined among young generations compared to older generations, and
shared services are largely accepted and popular among them. Thus, it is already possible
to see their impacts on citizens’ mobility behaviors, city infrastructure, and the related
energy consumption behaviors. Nevertheless, e-micromobility is a new mode of urban
transportation, and it is not yet known whether these emerging modes play a sustainable
role in cities, whether they are used as supplementary or complementary modes of public
transport, for instance as last- and first-mile solutions, or whether they are used just for
fun and recreational travel purposes. There are a few international literature reviews in
this field examining previous studies in different urban forms and geographies to give an
insight into the future role of these new mobility modes. For instance, a systematic review
by Boglietti et al. (2021) analyzed the effects of e-power micro-personal mobility from
two different perspectives, examining its impacts on transport and urban planning, and
safety issues and the environment. The main point of divergence between the article by
Boglietti et al. and this study is the analysis of travel behaviors, including travel purposes,
and the frequency of use presented in this study. In addition, the energy consumption of
e-micromobilities is one of the main parts of this review, which thus differs significantly
from other reviews such as that of Boglietti et al. (2021) [
9
]. To understand the role of e-
micromobility in the sustainability of transportation, it is necessary to consider four aspects
together, which are travel behaviors, energy consumption, the urban environment, and the
safety issues of e-micromobility as well as the required regulations. Another systematic
review by O’Hern and Estgfaeller (2020) studied articles about powered micromobility
published between 1991 and 2020 by their data and topic, keywords, most cited authors,
most cited articles, and their country. The objectives of O’Hern and Estgfaeller were to
study the evolution of mobility research in the field of micromobility in terms of time,
region, and the numbers of citations; however, the indicators and measurement of the four
above-mentioned impact aspects were not compared and synthesized [10].
This paper reviews and compiles former studies to gain broader knowledge about
the impacts of e-micromobility on cities and presents an international review in this field
for forthcoming studies. In this paper, we studied how e-micromobility affects people’s
mobility behaviors and urban transport systems. The research purposes can be formulated
as four key questions to analyze the impacts of e-micromobility, as follows:
•Q1: What are e-micromobility’s impacts on current travel behaviors?
•Q2: What are e-micromobility’s impacts on energy consumption?
•Q3: What are e-micromobility’s impacts on the urban environment?
•Q4: What are the safety issues of e-micromobility and the required regulations?
The questions are divided into subtopics, as shown in Figure 1.
The framework of this article proceeds as follows, with the Materials and Methods
section clarifying how the literature was determined within the search method, providing
the inclusion/exclusion criteria, the final selection, and the method used for the analysis of
the studies.
Afterwards, in the Results section, the key questions are studied based on the chosen
literature, analyzing the impacts of e-micromobility on travel behaviors, energy consump-
tion, and the related safety issues and regulations. Its impacts on mobility behaviors are
reviewed in four sub-topics, including the average number of e-micromobility trips per day,
the average daily distance and time traveled by means of e-micromobility, the purposes of
this travel, and modal shifts from different mobility modes to e-micromobility vehicles. All
these sub-topics give an indication of how people change their travel behaviors. Secondly,
the impacts of energy consumption are reviewed and analyzed in the related studies about
energy consumption. Afterwards, the environmental impacts of e-micromobility are exam-

Appl. Sci. 2021,11, 5851 3 of 20
ined and the last topic focuses on the related safety issues and regulations in different cities
around world.
Appl. Sci. 2021, 11, x FOR PEER REVIEW 3 of 20
Figure 1. Organization of the study.
The framework of this article proceeds as follows, with the Materials and Methods
section clarifying how the literature was determined within the search method, providing
the inclusion/exclusion criteria, the final selection, and the method used for the analysis
of the studies.
Afterwards, in the Results section, the key questions are studied based on the chosen
literature, analyzing the impacts of e-micromobility on travel behaviors, energy consump-
tion, and the related safety issues and regulations. Its impacts on mobility behaviors are
reviewed in four sub-topics, including the average number of e-micromobility trips per
day, the average daily distance and time traveled by means of e-micromobility, the pur-
poses of this travel, and modal shifts from different mobility modes to e-micromobility
vehicles. All these sub-topics give an indication of how people change their travel behav-
iors. Secondly, the impacts of energy consumption are reviewed and analyzed in the re-
lated studies about energy consumption. Afterwards, the environmental impacts of e-mi-
cromobility are examined and the last topic focuses on the related safety issues and regu-
lations in different cities around world.
2.
Materials and Methods
It is an undeniable fact that e-micromobility has attracted the attention of researchers,
urban planners, and policymakers. Since it is a new topic in mobility research, there is a
limited number of studies in this field, and it is expected that the number of studies will
increase considerably in the future. Therefore, related studies from around the world were
reviewed and presented to gain a widespread understanding the e-micromobility phe-
nomenon and its impacts.
2.1. Search Method for the Identification of Studies
In this study, we conducted an online search using search engines, such as Google
Scholar, Scopus, Web of Science, and Research Gate. Figure 2 shows the Prisma Flow
Chart (Preferred Reporting Items for Systematic Reviews and Meta-Analyses), which
shows the whole process from the identification of the literature to the inclusion and ex-
clusion processes of the systematic review, including qualitative and quantitative synthe-
sis. Studies were gathered based on their titles and abstracts in the identification phase to
gather all related studies.
Figure 1. Organization of the study.
2. Materials and Methods
It is an undeniable fact that e-micromobility has attracted the attention of researchers,
urban planners, and policymakers. Since it is a new topic in mobility research, there is
a limited number of studies in this field, and it is expected that the number of studies
will increase considerably in the future. Therefore, related studies from around the world
were reviewed and presented to gain a widespread understanding the e-micromobility
phenomenon and its impacts.
2.1. Search Method for the Identification of Studies
In this study, we conducted an online search using search engines, such as Google
Scholar, Scopus, Web of Science, and Research Gate. Figure 2shows the Prisma Flow Chart
(Preferred Reporting Items for Systematic Reviews and Meta-Analyses), which shows
the whole process from the identification of the literature to the inclusion and exclusion
processes of the systematic review, including qualitative and quantitative synthesis. Studies
were gathered based on their titles and abstracts in the identification phase to gather all
related studies.
2.2. Inclusion/Exclusion Criteria for the Selection of Studies
A total of 146 studies were compiled through searching the keywords “micromobility”
and “e-micromobility” in their titles and abstracts. In the identification stage, duplicate
studies were removed. Hence, 124 studies were screened and 83 of them were excluded,
regarding their topics and contents. In the eligibility stage, full-text articles were assessed
for eligibility, and 29 studies were selected based on the relevance of their data to the main
research purposes of this study.
2.3. Selection and Analysis of Studies
In the inclusion phase, 29 scientific articles, journal articles, conference proceedings,
and reports were selected to be reviewed. Those studies were categorized into seven

Appl. Sci. 2021,11, 5851 4 of 20
sub-topics depending on the research questions, as stated above. Those categories are
explained in detail in the following sections.
Appl. Sci. 2021, 11, x FOR PEER REVIEW 4 of 20
Figure 2. Systematic review scheme.
2.2. Inclusion/Exclusion Criteria for the Selection of Studies
A total of 146 studies were compiled through searching the keywords “micromobil-
ity” and “e-micromobility” in their titles and abstracts. In the identification stage, dupli-
cate studies were removed. Hence, 124 studies were screened and 83 of them were ex-
cluded, regarding their topics and contents. In the eligibility stage, full-text articles were
assessed for eligibility, and 29 studies were selected based on the relevance of their data
to the main research purposes of this study.
2.3. Selection and Analysis of Studies
In the inclusion phase, 29 scientific articles, journal articles, conference proceedings,
and reports were selected to be reviewed. Those studies were categorized into seven sub-
topics depending on the research questions, as stated above. Those categories are ex-
plained in detail in the following sections.
The 29 studies were reviewed in this study in different sections based on their find-
ings and contexts. Studies from before 2016 were not included in the literature review, in
order to examine up-to-date studies only. E-scooters and e-bikes entered the market in
different years; e-scooter studies have been conducted since 2018, and the studies con-
ducted after 2016 have mostly been carried out in the field of e-bikes. An additional con-
sideration is the geographical allocation of the data. Studies were gathered mostly from
the USA, Europe, Canada, UK, and New Zealand. Nine studies contained both e-scooters
and e-bikes. On the other hand, five studies discussed only e-scooters, whereas four stud-
ies investigated dockless bikes and e-bikes, along with docked bikes and e-bikes.
Figure 2. Systematic review scheme.
The 29 studies were reviewed in this study in different sections based on their findings
and contexts. Studies from before 2016 were not included in the literature review, in order
to examine up-to-date studies only. E-scooters and e-bikes entered the market in different
years; e-scooter studies have been conducted since 2018, and the studies conducted after
2016 have mostly been carried out in the field of e-bikes. An additional consideration is the
geographical allocation of the data. Studies were gathered mostly from the USA, Europe,
Canada, UK, and New Zealand. Nine studies contained both e-scooters and e-bikes. On
the other hand, five studies discussed only e-scooters, whereas four studies investigated
dockless bikes and e-bikes, along with docked bikes and e-bikes.
3. Results
3.1. Impacts on Travel Behaviors
Micromobility has the capability to be used for all trips with different travel purposes
which are less than 8 km, which represents 50 to 60 percent of total trips in China, the Euro-
pean Union, and the United States [
11
]. Therefore, it could be assumed that micromobility
vehicles might become a substitute for most car trips, as is it known that most car trips
are made to travel less than an 8-km distance [
12
]. To address the first research question,
that is, determining “e-micromobility’s impacts on current travel behaviors”, in this paper
we discuss the average trips per day, the average distance and time for the daily usage of
e-micromobility vehicles, as well as modal shifts to e-micromobility from different modes
of transport. These findings are essential in order to evaluate their impacts on the current
travel behaviors of citizens and to predict forthcoming travel behaviors.
3.1.1. Average E-Micromobility Trips per Day
E-micromobility services offer unique pleasure to their users, such as riding in the
open air, control of the vehicle, liberty, and flexibility during their travels [
6
]. Table 1shows
the findings from the selected literature in terms of how many trips were made per day. It
is considerably challenging to reach any common result among the studies. For instance,

Appl. Sci. 2021,11, 5851 5 of 20
in Chicago, with a population of 2,725,296, 105,479 e-scooter trips were made per day
in 2019 [
13
]. Meanwhile, in Washington, with a population of around 5,322,000, 2821 e-
scooter trips were made per day in 2019 [
14
]. In Zurich, with around 434,000 inhabitants
(1.5 million in the metropolitan area), 1032 dockless e-scooter trips were made in 2020 [
15
].
Table 1. Literature review regarding average trips per day.
Source
Literature Review Regarding Average Trips per Day (the
Results Were Acquired by Dividing the Total Amount of
Trips by the Days of the Research Period.)
Bielinski and Wazna (2020)
168,300 trips were made per day with an electric bike-sharing
system of 4080 vehicles in Tricity, Poland.
Castro et al. (2019)
A survey conducted in seven European cities (PASTA project)
with 204 people reported that the average number of trips per
day with e-bikes was 0.8.
Chery et al. (2016)
The number of e-bike trips in 2008 was reported as 1.16, in
2011 it was reported as 1.05, and in 2012 it was reported as
1.03 per day in Kunming, China.
City of Chicago, Pilot
Evaluation (2020)
According to the information that e-scooter companies
provided, an average of 6846 trips per day were made with
e-scooters in Chicago, USA.
Feng et al. (2020)
It was reported that 105,479 e-scooter trips were made per day
in the USA (according to The National Association of City
Transportation Officials (NACTO)).
Fyhri and Fearnley (2015)
The study conducted with 66 participants in Norway reported
1.4 e-bike trips per day.
Hardt and Bogenberger (2019)
As a result of a pilot project with 6 vehicles and
38 participants in Munich, an average of 49 trips were
made per day.
Li et al. (2020)
In Zurich, Switzerland, according to the provided data,
465 trips per day were made with docked e-bikes in a normal
period, which covered 15 February to 14 March, 2020. During
COVID-19 (15 March to 14 April 2020), 299 trips per day were
made. For dockless e-bikes, 241 trips per day were made in
the normal period, and 102 trips per day during COVID-19.
For dockless e-scooters, 60 trips per day were made in the
normal period, and 50 trips per day during COVID-19 (for
each of the three types of micromobility services, trip data
were collected from three operators: Publibike, Bond,
and Bird)
Mathew et al. (2019) In Indianapolis, 4830 e-scooters trips were made per day.
McKenzie (2019)
According to the collected data, Bird reported 170 trips per
day, Lime reported 214 per day, Lyft reported 835 trips per
day, Skip reported 1487 trips per day, reported has 115 trips
per day, and Jump e-bikes reported 325 trips per day, which
led to a total of 2821 e-scooter trips per day, in Washington,
USA (the results were obtained by dividing the total amount
of trips over the 4-month research period).
Reck et al. (2020)
This study, based on Zurich, Switzerland, reported
approximately 2800 trips per day, 1181 docked e-bike trips,
419 docked bike trips, 244 dockless e-bike trips, and 1032
dockless e-scooter trips.
According to Hardt and Bogenberger (2019), 49 trips were made per day in their
pilot project conducted in Munich, Germany, and this amount was considerably higher
than those of the other studies, presumably due to the fact that this pilot project was
conducted with a relatively small number of vehicles and participants [
16
]. Another
survey in Munich in 2019 reported 5.5 trips per day using e-scooters [
12
]. Furthermore,
according to a future model concerning 2030 made by McKinsey and Company (2019),
there will be approximately 250 million shared-micromobility trips in Munich, which

Appl. Sci. 2021,11, 5851 6 of 20
represents approximately 8 to 10 percent of all trips in Munich in that year, in which
shared-micromobility trips made up less than 0.1 percent of all trips in 2019 [
12
]. According
to the data collected by McKenzie (2019), Bird reported 170 trips per day, Lime reported
214 per day
, Lyft reported 835 trips per day, Skip reported 1487 trips per day, Spin reported
115 trips per day, and Jump e-bikes reported 325 trips per day, which is in total 2821 e-
scooter trips per day, in Washington, USA [
17
]. Furthermore, regarding e-bike trips, another
study conducted with 66 participants in Norway reported 1.4 e-bike trips per day [
18
].
During COVID-19, 50 to 60 percent of the passenger-kilometers decreased, which also
affected the use of micromobility, according to the survey they conducted in May 2020,
including seven countries such as China, Germany, France, Japan, Italy, the US, and UK.
They assume that after COVID-19 the use of micromobility may increase, suggesting that
9 percent of people tend to have private micromobility and 12 percent of them tend to
use shared micromobility in the “next normal” era [
19
]. Moreover, according to the 2019
Global ACES2 Consumer Survey, 70 percent of participants would consider buying their
own micromobility vehicles for commuting to work or school, which will result in more
micromobility trips per day [19].
3.1.2. Average Distance and Time of E-Micromobility Usage
E-bikes and e-scooters have shown different average travel distances and times in
cities. The findings of various studies indicate that the average distance traveled on e-
scooters is shorter than that on e-bikes (Figure 3). The difference in the travel distance
and time between e-bikes and e-scooters depends on several factors, such as the speed
and electric power of the vehicles [
20
]. Moreover, people have reported that when they
want to make longer recreational trips, they choose e-bikes instead of conventional bikes,
which shows that e-bikes are mostly preferred for longer trips [
21
]. Figure 3illustrates the
average daily distances traveled using e-scooters which were estimated in seven studies.
Appl. Sci. 2021, 11, x FOR PEER REVIEW 7 of 20
Figure 3. Average daily distance traveled on e-scooters (km).
a
Spin,
b
Skip,
c
Lyft,
d
Lime,
e
Bird.
Hardt and Bogenberger (2019) reported that the longest distance traveled using e-
scooters was 11 km, which was estimated in a pilot study including 38 participants in
Munich (Germany) [16]. Presumably, it was because this was a pilot project with a small
number of people and vehicles that the average distance was significantly high [16]. In
contrast, e-scooters are known to be used for short trips, and according to Chang et al.
(2019), 70 percent to 73 percent of trips are less than 1 mile (1.6 km) in Washington [6].
However, the findings in the literature were mostly between 0.72 and 2.4 km for the aver-
age e-scooter distance, and the average duration spent using e-scooters was between 8
and 12 min (Figure 4).
Figure 4. Average daily duration of use of e-scooters (minutes).
a
Spin,
b
Skip,
c
Lyft,
d
Lime,
e
Bird.
The data on the average daily distance traveled on e-bikes, collected from eight des-
ignated studies, are presented in Figure 5.
Figure 3. Average daily distance traveled on e-scooters (km). aSpin, bSkip, cLyft, dLime, eBird.
Hardt and Bogenberger (2019) reported that the longest distance traveled using e-
scooters was 11 km, which was estimated in a pilot study including 38 participants in
Munich (Germany) [
16
]. Presumably, it was because this was a pilot project with a small
number of people and vehicles that the average distance was significantly high [
16
]. In
contrast, e-scooters are known to be used for short trips, and according to Chang et al.
(2019), 70 percent to 73 percent of trips are less than 1 mile (1.6 km) in Washington [
6
].
However, the findings in the literature were mostly between 0.72 and 2.4 km for the average
e-scooter distance, and the average duration spent using e-scooters was between 8 and
12 min (Figure 4).

Appl. Sci. 2021,11, 5851 7 of 20
Appl. Sci. 2021, 11, x FOR PEER REVIEW 7 of 20
Figure 3. Average daily distance traveled on e-scooters (km).
a
Spin,
b
Skip,
c
Lyft,
d
Lime,
e
Bird.
Hardt and Bogenberger (2019) reported that the longest distance traveled using e-
scooters was 11 km, which was estimated in a pilot study including 38 participants in
Munich (Germany) [16]. Presumably, it was because this was a pilot project with a small
number of people and vehicles that the average distance was significantly high [16]. In
contrast, e-scooters are known to be used for short trips, and according to Chang et al.
(2019), 70 percent to 73 percent of trips are less than 1 mile (1.6 km) in Washington [6].
However, the findings in the literature were mostly between 0.72 and 2.4 km for the aver-
age e-scooter distance, and the average duration spent using e-scooters was between 8
and 12 min (Figure 4).
Figure 4. Average daily duration of use of e-scooters (minutes).
a
Spin,
b
Skip,
c
Lyft,
d
Lime,
e
Bird.
The data on the average daily distance traveled on e-bikes, collected from eight des-
ignated studies, are presented in Figure 5.
Figure 4.
Average daily duration of use of e-scooters (minutes).
a
Spin,
b
Skip,
c
Lyft,
d
Lime,
e
Bird.
The data on the average daily distance traveled on e-bikes, collected from eight
designated studies, are presented in Figure 5.
Appl. Sci. 2021, 11, x FOR PEER REVIEW 8 of 20
Figure 5. Average daily distance traveled on e-bikes (km).
a
Jump.
To be more precise, in the case of Castro et al. (2019), the data were gathered from a
survey of 10,000 people from seven cities in Europe, and it was stated that 365 people used
e-bikes [21]. It is known that in these cities, bicycles are used as one of the major daily
modes of transportation, and e-bikers used e-bike for almost half of the month. Further-
more, they stated that e-bikers’ daily usage of bikes was significantly more than that of
conventional bikers, and with 8 km and 32.2 min, the longest average time of use was
reported by this study, among the studies (Figure 6) [21]. The longest average distance
was 11.4 km, reported for Kunming, China, by Chery et al. (2016) [20]. Moreover, the
shortest average distance for docked and dockless e-bikes was 1.6 km, which was declared
for Zurich, Switzerland, by Reck et al. (2020) [15], and the shortest time was 15 min, again
for Zurich, Switzerland, by Li et al. (2020) [22]. However, most studies reported average
distances traveled by e-bike in the range of 3–4.5 km and travel times in the range of 15
and 20 min.
Figure 6. Average daily duration of use of e-bikes (minutes).
a
Jump.
The trip distance for dockless e-bikes and e-scooters has remained similar during
COVID-19, whereas the trip distance for docked e-bikes has increased compared to the
normal period in Zurich [22]. In contrast, US micromobility companies have reported that
the average e-scooter trip distance increased by 26 percent during COVID-19; e.g., in De-
troit, trip distances have increased up to 60 percent [11,12]. Therefore, people tend to use
e-scooters for a longer distance than before, instead of using public transportation during
COVID-19.
3.1.3. Purpose of E-Micromobility Usage
As mentioned in the previous section, e-scooters are used mostly for less than 1.5-km
trips. Moreover, it is clear that e-scooters are not preferred for long journeys, which means
Figure 5. Average daily distance traveled on e-bikes (km). aJump.
To be more precise, in the case of Castro et al. (2019), the data were gathered from
a survey of 10,000 people from seven cities in Europe, and it was stated that 365 people
used e-bikes [
21
]. It is known that in these cities, bicycles are used as one of the major
daily modes of transportation, and e-bikers used e-bike for almost half of the month.
Furthermore, they stated that e-bikers’ daily usage of bikes was significantly more than
that of conventional bikers, and with 8 km and 32.2 min, the longest average time of use
was reported by this study, among the studies (Figure 6) [
21
]. The longest average distance
was 11.4 km, reported for Kunming, China, by Chery et al. (2016) [
20
]. Moreover, the
shortest average distance for docked and dockless e-bikes was 1.6 km, which was declared
for Zurich, Switzerland, by Reck et al. (2020) [
15
], and the shortest time was 15 min, again
for Zurich, Switzerland, by Li et al. (2020) [
22
]. However, most studies reported average
distances traveled by e-bike in the range of 3–4.5 km and travel times in the range of 15
and 20 min.

Appl. Sci. 2021,11, 5851 8 of 20
Appl. Sci. 2021, 11, x FOR PEER REVIEW 8 of 20
Figure 5. Average daily distance traveled on e-bikes (km).
a
Jump.
To be more precise, in the case of Castro et al. (2019), the data were gathered from a
survey of 10,000 people from seven cities in Europe, and it was stated that 365 people used
e-bikes [21]. It is known that in these cities, bicycles are used as one of the major daily
modes of transportation, and e-bikers used e-bike for almost half of the month. Further-
more, they stated that e-bikers’ daily usage of bikes was significantly more than that of
conventional bikers, and with 8 km and 32.2 min, the longest average time of use was
reported by this study, among the studies (Figure 6) [21]. The longest average distance
was 11.4 km, reported for Kunming, China, by Chery et al. (2016) [20]. Moreover, the
shortest average distance for docked and dockless e-bikes was 1.6 km, which was declared
for Zurich, Switzerland, by Reck et al. (2020) [15], and the shortest time was 15 min, again
for Zurich, Switzerland, by Li et al. (2020) [22]. However, most studies reported average
distances traveled by e-bike in the range of 3–4.5 km and travel times in the range of 15
and 20 min.
Figure 6. Average daily duration of use of e-bikes (minutes).
a
Jump.
The trip distance for dockless e-bikes and e-scooters has remained similar during
COVID-19, whereas the trip distance for docked e-bikes has increased compared to the
normal period in Zurich [22]. In contrast, US micromobility companies have reported that
the average e-scooter trip distance increased by 26 percent during COVID-19; e.g., in De-
troit, trip distances have increased up to 60 percent [11,12]. Therefore, people tend to use
e-scooters for a longer distance than before, instead of using public transportation during
COVID-19.
3.1.3. Purpose of E-Micromobility Usage
As mentioned in the previous section, e-scooters are used mostly for less than 1.5-km
trips. Moreover, it is clear that e-scooters are not preferred for long journeys, which means
Figure 6. Average daily duration of use of e-bikes (minutes). aJump.
The trip distance for dockless e-bikes and e-scooters has remained similar during
COVID-19, whereas the trip distance for docked e-bikes has increased compared to the
normal period in Zurich [
22
]. In contrast, US micromobility companies have reported
that the average e-scooter trip distance increased by 26 percent during COVID-19; e.g.,
in Detroit, trip distances have increased up to 60 percent [
11
,
12
]. Therefore, people tend
to use e-scooters for a longer distance than before, instead of using public transportation
during COVID-19.
3.1.3. Purpose of E-Micromobility Usage
As mentioned in the previous section, e-scooters are used mostly for less than 1.5-km
trips. Moreover, it is clear that e-scooters are not preferred for long journeys, which means
that they are used for limited travel purposes. Figure 7illustrates the usage purposes of
e-scooters among the selected literature. In the USA, most e-scooters were used to commute
to work and school, or fun/recreation, and proportions of these purposes were notably
close to each other [
6
,
13
,
23
]. Percentages varied from city to city in the USA, as well as
in Europe. For instance, in Chicago, 50 percent of users stated that they had been using
e-scooters for social/entertainment reasons [
13
]; however, in Austin, Portland, and San
Francisco, the most commonly specified purpose of usage was commuting to work or
school [6].
Appl. Sci. 2021, 11, x FOR PEER REVIEW 9 of 20
that they are used for limited travel purposes. Figure 7 illustrates the usage purposes of
e-scooters among the selected literature. In the USA, most e-scooters were used to com-
mute to work and school, or fun/recreation, and proportions of these purposes were no-
tably close to each other [6,13,23]. Percentages varied from city to city in the USA, as well
as in Europe. For instance, in Chicago, 50 percent of users stated that they had been using
e-scooters for social/entertainment reasons [13]; however, in Austin, Portland, and San
Francisco, the most commonly specified purpose of usage was commuting to work or
school [6].
Figure 7. Purposes for using e-scooters.
a
San Francisco,
b
Austin,
c
Portland.
In the study by Chang et al. (2019), in Portland, the most common e-scooter usage
was recreational, reported by 28 percent of participants, and the second most common
form of e-scooter usage was commuting to work and school, reported by 20 percent [6].
Moreover, in Austin, the most common purpose for dockless e-scooter and e-bike usage
was commuting to work and school, reported by 35 percent of participants. In San Fran-
cisco, the most common e-scooter usage was commuting to work and school, at 55 percent
[6]. In the study by Hardt and Bogenberger conducted in Munich (2019), the usage pur-
poses for e-scooters were reported as 38 percent for commuting trips, 31 percent for lei-
sure, 16 percent for business trips, 8 percent for shopping, and 6 percent for errands [16].
In the study by Li et al. (2020) from Zurich (Switzerland), 24.64 percent of e-scooter trips
were for leisure purposes, 22.77 percent were for going home, and 20.06 percent were for
going to work in the normal period (in the study, the normal period referred to before the
COVID-19 pandemic) [22]. Furthermore, according to Pimentel and Lowry (2020), in
Washington, Oregon and Idaho, USA, the most common purpose for e-scooter usage was
recreation, at 23 percent [23].
Regarding the pilot evaluation made by the city of Chicago (2020), the travel pur-
poses for e-scooter users consisted of 50 percent for social/entertainment, 42 percent for
going to or from restaurants, 41 percent for fun/recreation, 30 percent for commuting, 34
percent for going to or from transit, 28 percent for shopping/errands, 10 percent for going
to/from business appointment, 4 percent for going to or from school, and 2 percent for
exercise [13]. Presumably, in the Chicago survey, participants were able to choose more
than one option for their travel preferences. Therefore, the cumulative percentages are
higher than one hundred, as is the case in the study by Leger et al. (2018) [13,14]. Regard-
Figure 7. Purposes for using e-scooters. aSan Francisco, bAustin, cPortland.
In the study by Chang et al. (2019), in Portland, the most common e-scooter usage was
recreational, reported by 28 percent of participants, and the second most common form of e-

Appl. Sci. 2021,11, 5851 9 of 20
scooter usage was commuting to work and school, reported by 20 percent [
6
]. Moreover, in
Austin, the most common purpose for dockless e-scooter and e-bike usage was commuting
to work and school, reported by 35 percent of participants. In San Francisco, the most
common e-scooter usage was commuting to work and school, at 55 percent [
6
]. In the study
by Hardt and Bogenberger conducted in Munich (2019), the usage purposes for e-scooters
were reported as 38 percent for commuting trips, 31 percent for leisure, 16 percent for
business trips, 8 percent for shopping, and 6 percent for errands [
16
]. In the study by
Li et al. (2020) from Zurich (Switzerland), 24.64 percent of e-scooter trips were for leisure
purposes, 22.77 percent were for going home, and 20.06 percent were for going to work
in the normal period (in the study, the normal period referred to before the COVID-19
pandemic) [
22
]. Furthermore, according to Pimentel and Lowry (2020), in Washington,
Oregon and Idaho, USA, the most common purpose for e-scooter usage was recreation, at
23 percent [23].
Regarding the pilot evaluation made by the city of Chicago (2020), the travel purposes
for e-scooter users consisted of 50 percent for social/entertainment, 42 percent for going to
or from restaurants, 41 percent for fun/recreation, 30 percent for commuting, 34 percent
for going to or from transit, 28 percent for shopping/errands, 10 percent for going to/from
business appointment, 4 percent for going to or from school, and 2 percent for exercise [
13
].
Presumably, in the Chicago survey, participants were able to choose more than one option
for their travel preferences. Therefore, the cumulative percentages are higher than one
hundred, as is the case in the study by Leger et al. (2018) [
13
,
14
]. Regarding Leger et al.
(2018), in Ontario (Canada), the usage purposes for e-scooters were reported as commuting
(70 percent), recreation (more than 80 percent), errands (more than 50 percent) and first-
/last-mile travel (about 40 percent) [14].
As indicated in Figure 8, in the study by Cairns et al. (2017) in Brighton, UK, the most
common purpose of the use of e-bikes was commuting to work, followed by recreational
usage, including daily activities, in second place [
24
]. Castro et al. (2019) reported that it can
be presumed that e-bikes were used for longer recreational trips compared to conventional
bikes [21].
Appl. Sci. 2021, 11, x FOR PEER REVIEW 10 of 20
ing Leger et al. (2018), in Ontario (Canada), the usage purposes for e-scooters were re-
ported as commuting (70 percent), recreation (more than 80 percent), errands (more than
50 percent) and first-/last-mile travel (about 40 percent) [14].
As indicated in Figure 8, in the study by Cairns et al. (2017) in Brighton, UK, the most
common purpose of the use of e-bikes was commuting to work, followed by recreational
usage, including daily activities, in second place [24]. Castro et al. (2019) reported that it
can be presumed that e-bikes were used for longer recreational trips compared to conven-
tional bikes [21].
Figure 8. Purposes for using e-bikes.
As mentioned earlier in relation to the purposes of using e-scooters, participants
could choose more than one option for their travel preferences in the survey by Leger et
al. (2018) [14]. Therefore, the cumulative percentages are higher than one hundred. In that
study, the purposes for the usage of e-bikes were reported as commuting to work (more
than 80 percent), recreational purposes (more than 90 percent), first-/last-mile travel (50
percent), and errands (more than 70 percent) in Ontario, Canada [14]. Li et al. (2020) re-
ported that the most common purpose for the usage of docked bikes and e-bikes was com-
muting in Zurich, Switzerland [22]. In the COVID-19 period, the most common usage pur-
pose was home activity, at 28.58 percent [22]. Pimentel and Lowry (2020) stated recreation
purposes as the most common purpose for the usage of e-bikes, at 37.5 percent in Wash-
ington, Oregon, and Idaho, USA [23].
In the case of the purpose of the usage of e-bikes, most e-bikes are thus used for com-
muting. Admittedly, the purpose of recreation is also significantly common. Notably, in
the study by Reck et al. (2020), they stated that docked modes were used mostly for com-
muting in Zurich, Switzerland [15]. Thus, we can presume that people’s mode choices are
more risk-free when traveling for certain reasons such as commuting [15].
3.1.4. Modal Shift to E-Micromobility
Cities have been struggling with traffic congestion over the past several years. The
modal shift from private cars to new mobility solutions such as ICT-based mobility modes
and sharing modes in cities, particularly in central business districts (CBDs), will be a sus-
tainable and effective way of improving urban transportation systems [25–28]. With the
launch of e-micromobility in urban transportation, their use rises day by day. However,
it has been stated that, based on the growth in the European and Asian scooter market
since 2014, the modal shifts from walking and public transportation have been increasing
oriented to this new mode of mobility [16]. It would be an advantage for urban sustaina-
bility if e-micromobility vehicles replace private cars and are used as last-mile or first-mile
solutions as a complement to public transport. In this section, modal shift data were col-
lected through the literature review, as indicated in Figure 9.
Figure 8. Purposes for using e-bikes.
As mentioned earlier in relation to the purposes of using e-scooters, participants
could choose more than one option for their travel preferences in the survey by Leger et al.
(2018) [
14
]. Therefore, the cumulative percentages are higher than one hundred. In that
study, the purposes for the usage of e-bikes were reported as commuting to work (more than
80 percent), recreational purposes (more than 90 percent), first-/last-mile travel (50 percent),
and errands (more than 70 percent) in Ontario, Canada [
14
]. Li et al. (2020) reported that
the most common purpose for the usage of docked bikes and e-bikes was commuting in
Zurich, Switzerland [
22
]. In the COVID-19 period, the most common usage purpose was
home activity, at 28.58 percent [
22
]. Pimentel and Lowry (2020) stated recreation purposes
as the most common purpose for the usage of e-bikes, at 37.5 percent in Washington,
Oregon, and Idaho, USA [23].

Appl. Sci. 2021,11, 5851 10 of 20
In the case of the purpose of the usage of e-bikes, most e-bikes are thus used for
commuting. Admittedly, the purpose of recreation is also significantly common. Notably,
in the study by Reck et al. (2020), they stated that docked modes were used mostly for
commuting in Zurich, Switzerland [
15
]. Thus, we can presume that people’s mode choices
are more risk-free when traveling for certain reasons such as commuting [15].
3.1.4. Modal Shift to E-Micromobility
Cities have been struggling with traffic congestion over the past several years. The
modal shift from private cars to new mobility solutions such as ICT-based mobility modes
and sharing modes in cities, particularly in central business districts (CBDs), will be a
sustainable and effective way of improving urban transportation systems [
25
–
28
]. With the
launch of e-micromobility in urban transportation, their use rises day by day. However,
it has been stated that, based on the growth in the European and Asian scooter market
since 2014, the modal shifts from walking and public transportation have been increasing
oriented to this new mode of mobility [
16
]. It would be an advantage for urban sustainabil-
ity if e-micromobility vehicles replace private cars and are used as last-mile or first-mile
solutions as a complement to public transport. In this section, modal shift data were
collected through the literature review, as indicated in Figure 9.
Appl. Sci. 2021, 11, x FOR PEER REVIEW 11 of 20
Figure 9. Modal shift to e-scooter usage.
a
San Francisco,
b
Denver,
c
Portland,
d
San Francisco
, e
Portland (Visitors/Tourists),
f
Portland (Locals),
g
France.
In three surveys conducted by Agora Verkehrswende (2019), participants were asked
what they would have done in their most recent trips if e-scooters were not available, and
the answers were as follows. Forty-seven percent of French respondents would have
walked, and 29 percent of them would have used public transportation instead of e-scoot-
ers; 20 percent of respondents in Portland would have used private cars, and 15 percent
of them would have taken taxis, Uber, or Lyft, if the e-scooters were not available; almost
half of the tourists in Portland would have used cars; and in San Francisco, one-third of
participants would have used Uber, taxis, or Lyft if e-scooters were not available [29].
Chang et al. (2019) reported that 43 percent of e-scooter users replaced walking, 14 percent
of them replaced biking, and 32 percent of them replaced ride sourcing and private vehi-
cles in Denver [6]. In Portland, 37 percent of the participants reported that they would
have walked, and 9 percent would have cycled in their most recent trips if e-scooters were
not available [6]. According to a Lime survey in San Francisco, 61 percent of the partici-
pants reported they would have walked, 12 percent would have chosen station-based
bike-sharing, and 7 percent would have chosen personal bikes in their most recent trips if
e-scooters were not available [6]. The survey of the City of Chicago indicated that 31.8
percent of e-scooter users would have used ride-hailing, 30.2 percent would have walked,
10.8 percent would have driven, 9.9 percent would have used a bus, 4.8 percent would
have used bike-sharing, 4.2 percent would have used a train, 2.9 percent would not have
taken the trip, and 2.6 percent would have cycled in their most recent trips if e-scooters
were not available [13]. In Hollingsworth et al. (2019) in Raleigh, USA, it was reported that
7 percent of users would not have taken the trip; otherwise, 49 percent would have biked
or walked, 34 percent would have used a personal automobile or ride-share service, and
11 percent would have taken a public bus in their most recent trips if e-scooters were not
available [30]. It can be observed in the study by Hollingsworth et al. (2019) that nearly
half of the respondents would have walked the distance they traveled using e-scooters in
Raleigh, USA [30]. Therefore, it can be assumed that they had been using e-micromobility
Figure 9.
Modal shift to e-scooter usage.
a
San Francisco,
b
Denver,
c
Portland,
d
San Francisco,
e
Portland (Visitors/Tourists),
fPortland (Locals), gFrance.
In three surveys conducted by Agora Verkehrswende (2019), participants were asked
what they would have done in their most recent trips if e-scooters were not available,
and the answers were as follows. Forty-seven percent of French respondents would have
walked, and 29 percent of them would have used public transportation instead of e-scooters;
20 percent of respondents in Portland would have used private cars, and 15 percent of them
would have taken taxis, Uber, or Lyft, if the e-scooters were not available; almost half of the
tourists in Portland would have used cars; and in San Francisco, one-third of participants
would have used Uber, taxis, or Lyft if e-scooters were not available [
29
]. Chang et al. (2019)
reported that 43 percent of e-scooter users replaced walking, 14 percent of them replaced

Appl. Sci. 2021,11, 5851 11 of 20
biking, and 32 percent of them replaced ride sourcing and private vehicles in Denver [
6
].
In Portland, 37 percent of the participants reported that they would have walked, and
9 percent would have cycled in their most recent trips if e-scooters were not available [
6
].
According to a Lime survey in San Francisco, 61 percent of the participants reported
they would have walked, 12 percent would have chosen station-based bike-sharing, and
7 percent would have chosen personal bikes in their most recent trips if e-scooters were
not available [
6
]. The survey of the City of Chicago indicated that 31.8 percent of e-
scooter users would have used ride-hailing, 30.2 percent would have walked, 10.8 percent
would have driven, 9.9 percent would have used a bus, 4.8 percent would have used
bike-sharing, 4.2 percent would have used a train, 2.9 percent would not have taken
the trip, and 2.6 percent would have cycled in their most recent trips if e-scooters were
not available [
13
]. In Hollingsworth et al. (2019) in Raleigh, USA, it was reported that
7 percent of users would not have taken the trip; otherwise, 49 percent would have biked
or walked, 34 percent would have used a personal automobile or ride-share service, and
11 percent would have taken a public bus in their most recent trips if e-scooters were not
available [
30
]. It can be observed in the study by Hollingsworth et al. (2019) that nearly
half of the respondents would have walked the distance they traveled using e-scooters in
Raleigh, USA [
30
]. Therefore, it can be assumed that they had been using e-micromobility
vehicles for distances which they could have walked, as replacing walking was considerably
common. In contrast, according to Cairns et al.’s (2017) pilot project in Brighton, known
for its extraordinary walking levels, the use of e-bikes during the project led to reductions
in car driving among 43 percent of the participants [
24
]. According to Lime, 30 percent of
users replaced car trips, whereas 27 percent used e-scooters as first-/last-mile solutions for
their recent trips [31].
Notably, it was reported by Reck et al. (2020), that docked e-bikes were preferred for
commuting instead of using private cars in traffic in peak hours in Zurich, Switzerland [
15
].
Likewise, in the UK and the Netherlands, e-bike users have replaced cars, as well as
in Sacramento, California [
14
]. In contrast, in China e-bike users have replaced public
transit [
20
]. In Cairns et al. (2017), it was reported that 20 percent of car mileage was
reduced and at least 70 percent of participants would like to have an e-bike in Brighton,
UK [
24
]. They also found that most of the participants’ walking habits tended to be replaced
with cycling [
24
]. At the end of trial carried out by Castro et al. (2019), it was observed
that among participants who replaced their mode of travel with e-bikes, 25 percent of
participants used to travel by means of private motorized vehicles (car or motorbike),
23 percent of participants by means of non-electric bicycles, and 15 percent of participants
by means of public transport, based on data from seven European cities [21]. In Antwerp,
bicycle and private motorized vehicle users shifted to e-bikes; in contrast, public transport
users shifted to e-bikes in Zurich [
21
]. According to the surveys conducted by Pimentel
and Lowry (2020) in Washington, Oregon, and Idaho, USA, it was found that 66 percent of
the participants expected to use these modes of transport more often in the future [23].
Consequently, the modes of transport replaced by e-micromobility vehicles are dif-
ferent based on the country or even differ from city to city; e.g., in Denver 43 percent of
e-scooter users replaced walking [
6
], yet in Raleigh 34 percent replaced personal auto-
mobile or ride-share services [
30
]. In cities with extreme urban density, people tended to
replace public transportation with e-bikes [
20
]. In contrast, it was reported that e-bike users
replaced more cars than other modes of transport in Sacramento, California [14].
Furthermore, millennials have a go-nowhere attitude and fewer traveling habits than
back in the days. They do not tend to spend as much money on cars as previous generations
did and for this reason, micromobility may be a more attractive form of transport for these
people. It has been stated that car trips are the least joyful trips, and even this might cause
a modal shift from the use of private cars [
6
]. According to Campisi et al. (2020), it has been
declared that there is a correlation between car ownership (85.5 percent of participants) and
the willingness to rent a micromobility vehicle [
32
]. Therefore, an increase in car ownership
decreased the willingness to rent micromobility vehicles. Furthermore, it has been claimed

Appl. Sci. 2021,11, 5851 12 of 20
that the likelihood of renting micromobility vehicles is higher among students compared
to the working class [32].
3.2. Impacts on Energy Consumption
Two thirds of the world’s population will live in cities by 2050, and inevitably, urban
settlements will face several further problems [
33
]. Due to the fact that the world’s resources
are being depleted, cities are becoming less livable every day, e.g., global warming has
reached a very serious level. To change this situation, it is reasonable to focus on cities, and
the first place should be the transport sector, which is responsible for 24 percent of global
CO
2
emissions, 29 percent of global energy demand, and 65 percent of the world’s total
oil consumption [
34
]. The development of e-micromobility might change overall energy
consumption in the mobility sector. Bedmutha et al. (2020) indicated that if trips of 5–8 km
that are currently made using conventional motorized vehicles were replaced with the use
of e-micromobility vehicles, energy demand would drop by 50 percent in Pittsburg [
35
].
Since that study was based on Pittsburg, if we consider this in the wider context of the USA
and China, which are the largest CO
2
producers in the world, e-micromobility could be a
game-changer. In this section, the energy consumption of e-micromobility vehicles and
their environmental impacts are reviewed.
The question of whether electric vehicles are energy efficient is still the subject of many
studies, and there are many dependent variables in relation to this topic. Hence, it does not
seem to be possible to reach a definitive conclusion for now. Nevertheless, in this section,
the related studies are examined to gain a general estimation. Although there is not yet a
very extensive body of literature on this subject, we have compiled and compared studies
in terms of energy consumption per mile/km, as well as impacts on global warming in
respect to environmental impacts, i.e., the amount of CO
2
emitted per passenger-km will
be compared among various modes of transport and studies.
As shown in Figure 10, Martínez-Navarro et al. (2020) estimated e-scooters’ energy
consumption to be 0.012 kWh/km, Brdulak et al. (2020) reported it to be 0.04 kWh/km,
and Agora Verkehrswende (2019) reported it to be 0.01 kWh/km [
29
,
34
,
36
]. Plainly, the
numbers by themselves do not mean anything; it is necessary to associate them with other
comparable variables to reach a conclusion. Some comparative studies have indicated that
electric scooters can travel 128 km with 1 kW/h of energy, whereas a gasoline-powered
car can travel less than 1.6 km and a more energy efficient Tesla can travel 6.4 km with the
same amount of energy [
37
]. Furthermore, approximately the same numbers are given in
the study by Agora as follows—with the same amount of energy, an e-scooter can travel a
50-times greater distance than a conventional car [
29
]. Based on the Bird e-scooter, with
1 kW/h of energy, e-scooters can travel approximately 100 km, whereas an electric car can
travel 6 km [
29
]. According to Brdulak et al. (2020), who made an assumption based on data
from rental companies in Poland, an e-scooter can travel 100 km with 4 kWh energy [
36
].
According to Wired (2018), e-micromobility vehicles are 20 times more efficient than electric
vehicles and 102 times more efficient than conventional fossil fuel vehicles; furthermore,
e-scooters cover their cost in just 4 months and are seen as the most cost-effective vehicles
for short distances compared to other transportation modes [31].
Hence, it shows that when e-scooters substitute either conventional cars or electric
cars, it leads to a reduction in energy consumption for transportation. Meanwhile, studies
have shown that the environmental impact of the amount of energy used while charging
e-scooters has a considerably lower impact than their production phase and their collection
each night for recharging [30].
A simulation of the demand for electricity in Poland from e-scooters was performed
by Brdulak et al. (2020). At the time of their calculations, they made a four-year forecast,
claiming that e-scooter ownership in 2023 would reach 30,000 vehicles, and they found
that the daily energy consumption of an e-scooter was 1.12 kWh, and that 9.24 GWh
was required by a city to power a private e-scooter fleet including 30,000 units for one
year [
36
]. Moreover, to make a comparison, it has been stated that the energy demands

Appl. Sci. 2021,11, 5851 13 of 20
of the Warsaw M1 and M2 Metro Lines annually totaled about 125 GWh in 2018, so the
difference between two variables is considerably high [
36
]. In this case, the energy demand
of private e-scooters would not be a major load for Polish cities if the ownership rate
continues as expected [
36
]. Nevertheless, a transition to green energy solutions will be a
necessary step to generate more electricity from renewable energy resources.
Appl. Sci. 2021, 11, x FOR PEER REVIEW 13 of 20
The question of whether electric vehicles are energy efficient is still the subject of
many studies, and there are many dependent variables in relation to this topic. Hence, it
does not seem to be possible to reach a definitive conclusion for now. Nevertheless, in this
section, the related studies are examined to gain a general estimation. Although there is
not yet a very extensive body of literature on this subject, we have compiled and com-
pared studies in terms of energy consumption per mile/km, as well as impacts on global
warming in respect to environmental impacts, i.e., the amount of CO2 emitted per passen-
ger-km will be compared among various modes of transport and studies.
As shown in Figure 10, Martínez-Navarro et al. (2020) estimated e-scooters’ energy
consumption to be 0.012 kWh/km, Brdulak et al. (2020) reported it to be 0.04 kWh/km, and
Agora Verkehrswende (2019) reported it to be 0.01 kWh/km [29,34,36]. Plainly, the num-
bers by themselves do not mean anything; it is necessary to associate them with other
comparable variables to reach a conclusion. Some comparative studies have indicated that
electric scooters can travel 128 km with 1 kW/h of energy, whereas a gasoline-powered
car can travel less than 1.6 km and a more energy efficient Tesla can travel 6.4 km with the
same amount of energy [37]. Furthermore, approximately the same numbers are given in
the study by Agora as follows—with the same amount of energy, an e-scooter can travel
a 50-times greater distance than a conventional car [29]. Based on the Bird e-scooter, with
1 kW/h of energy, e-scooters can travel approximately 100 km, whereas an electric car can
travel 6 km [29]. According to Brdulak et al. (2020), who made an assumption based on
data from rental companies in Poland, an e-scooter can travel 100 km with 4 kWh energy
[36]. According to Wired (2018), e-micromobility vehicles are 20 times more efficient than
electric vehicles and 102 times more efficient than conventional fossil fuel vehicles; fur-
thermore, e-scooters cover their cost in just 4 months and are seen as the most cost-effec-
tive vehicles for short distances compared to other transportation modes [31].
Hence, it shows that when e-scooters substitute either conventional cars or electric
cars, it leads to a reduction in energy consumption for transportation. Meanwhile, studies
have shown that the environmental impact of the amount of energy used while charging
e-scooters has a considerably lower impact than their production phase and their collec-
tion each night for recharging [30].
Figure 10. Energy consumption of e-scooters (kWh/km).
A simulation of the demand for electricity in Poland from e-scooters was performed
by Brdulak et al. (2020). At the time of their calculations, they made a four-year forecast,
claiming that e-scooter ownership in 2023 would reach 30,000 vehicles, and they found
that the daily energy consumption of an e-scooter was 1.12 kWh, and that 9.24 GWh was
required by a city to power a private e-scooter fleet including 30,000 units for one year
[36]. Moreover, to make a comparison, it has been stated that the energy demands of the
Warsaw M1 and M2 Metro Lines annually totaled about 125 GWh in 2018, so the differ-
ence between two variables is considerably high [36]. In this case, the energy demand of
Figure 10. Energy consumption of e-scooters (kWh/km).
Modal shift from non-motorized modes which do not demand any energy to e-
micromobility increases energy demands. If these energy demands continue to be supplied
through electricity from fossil fuels, this will create a new burden on energy load, especially
for countries that meet most of their energy demand through the use of fossil fuels.
The topographic profiles of cities should be considered in terms of the energy con-
sumption of e-micromobility vehicles. The amount of energy used by e-micromobility
vehicles is higher in hilly cities. Martinez-Navarro et al. (2020) estimated the maximum trip
distance for e-scooters as 22.2 km with a fully charged battery [
34
]. However, the maximum
travel distance depends on the battery capacity and life. Another factor to be considered is
the different amounts of energy consumption between shared and private electric scooters
and bikes [
38
]. To recharge shared micromobility vehicles, it is necessary to collect all the
vehicles with combustion-engine cars/trucks, whereas for private scooters and bikes, there
is no need for this surplus energy consumption [
38
]. However, if shared e-micromobility
vehicles are used instead of unsustainable modes of transport such as private fossil fuel
cars, then this disadvantage of surplus energy consumption can be ignored compared to
the energy savings caused by the modal shift away from fossil fuel cars [38].
3.3. Environmental Impacts
Hollingsworth et al. (2019) conducted a Monte Carlo analysis of an e-scooter’s CO
2
life
cycle and produced an estimate of 125 g CO
2
-eq per passenger per km, of which 50 percent
comes from materials and manufacturing, and 43 percent from the collection process for
overnight charging (Figure 11) [30].
Moreau et al. (2020) estimated the global warming potential (GWP) of the use of
shared e-scooters and regarding that the GWP was 131 g CO
2
-eq/passenger-km more than
the users’ replaced mode of transportation, which is 110 g of CO
2
-eq/passenger-km [
39
].
On the other hand, it should not be ignored that all of these are related to the short lifetime
of the vehicles, because this finding was based on shared e-scooters, which have a shorter
lifespan compared to private e-scooters, and private e-scooters’ CO
2
-eq/passenger-km
is 67 g [
39
]. Thus, the difference in CO
2
-eq/passenger-km between shared and private
e-scooters is considerably high. There are dozens of pieces of misinformation about these
vehicles’ lifespans. The lifetime of e-scooters varies according to the quality of the product.
There are even rumors that shared e-scooters last only 28 days [
40
]. Another opinion on
this issue is that first generation shared e-scooters are not designed for renting in the United

Appl. Sci. 2021,11, 5851 14 of 20
States and their lifespan has become very short due to irresponsible use by people, and
today their average lifespan is reported to be 2 years [
40
]. In addition, there have been
some improvements to the overnight charging collection process. Now, most e-scooter
companies use swappable charging batteries and collect these batteries with the use of
e-cargo bikes. This makes the whole process more energy efficient [30].
Appl. Sci. 2021, 11, x FOR PEER REVIEW 14 of 20
private e-scooters would not be a major load for Polish cities if the ownership rate contin-
ues as expected [36]. Nevertheless, a transition to green energy solutions will be a neces-
sary step to generate more electricity from renewable energy resources.
Modal shift from non-motorized modes which do not demand any energy to e-mi-
cromobility increases energy demands. If these energy demands continue to be supplied
through electricity from fossil fuels, this will create a new burden on energy load, espe-
cially for countries that meet most of their energy demand through the use of fossil fuels.
The topographic profiles of cities should be considered in terms of the energy con-
sumption of e-micromobility vehicles. The amount of energy used by e-micromobility ve-
hicles is higher in hilly cities. Martinez-Navarro et al. (2020) estimated the maximum trip
distance for e-scooters as 22.2 km with a fully charged battery [34]. However, the maxi-
mum travel distance depends on the battery capacity and life. Another factor to be con-
sidered is the different amounts of energy consumption between shared and private elec-
tric scooters and bikes [38]. To recharge shared micromobility vehicles, it is necessary to
collect all the vehicles with combustion-engine cars/trucks, whereas for private scooters
and bikes, there is no need for this surplus energy consumption [38]. However, if shared
e-micromobility vehicles are used instead of unsustainable modes of transport such as
private fossil fuel cars, then this disadvantage of surplus energy consumption can be ig-
nored compared to the energy savings caused by the modal shift away from fossil fuel
cars [38].
3.3. Environmental Impacts
Hollingsworth et al. (2019) conducted a Monte Carlo analysis of an e-scooter’s CO
2
life cycle and produced an estimate of 125 g CO
2
-eq per passenger per km, of which 50
percent comes from materials and manufacturing, and 43 percent from the collection pro-
cess for overnight charging (Figure 11) [30].
Figure 11. Environmental impact of e-scooters (g CO
2
-eq/passenger-km).
Moreau et al. (2020) estimated the global warming potential (GWP) of the use of
shared e-scooters and regarding that the GWP was 131 g CO
2
-eq/passenger-km more than
the users’ replaced mode of transportation, which is 110 g of CO
2
-eq/passenger-km [39].
On the other hand, it should not be ignored that all of these are related to the short lifetime
of the vehicles, because this finding was based on shared e-scooters, which have a shorter
lifespan compared to private e-scooters, and private e-scooters’ CO
2
-eq/passenger-km is
67 g [39]. Thus, the difference in CO
2
-eq/passenger-km between shared and private e-
scooters is considerably high. There are dozens of pieces of misinformation about these
vehicles’ lifespans. The lifetime of e-scooters varies according to the quality of the product.
There are even rumors that shared e-scooters last only 28 days [40]. Another opinion on
this issue is that first generation shared e-scooters are not designed for renting in the
United States and their lifespan has become very short due to irresponsible use by people,
Figure 11. Environmental impact of e-scooters (g CO2-eq/passenger-km).
3.4. Safety Issues and Regulations
E-micromobility has shown a sharp growth rate in many cities. Therefore, it is essential
to consider the infrastructure of docked or dockless e-micromobility vehicles in relation to
the urban management of space, pavement, and curbs, as well as identifying the related
safety issues, and the potential for accidents and causalities. The implementation of
regulations will be a visible part of city infrastructure. As explained in the previous
section, e-micromobility trips were boosted when the e-scooter entered the market in 2018.
However, most users still do not know how to use them properly and even though their
speeds are around 25 km per hour, they pose a huge safety risk. If we look at the e-scooter
accident numbers, the Austin Public Health Report (2019) indicated that 20 trips out of
every 100,000 e-scooter trips resulted in injuries during their study period [
6
]. According
to another study by Trivedi et al. (2019), 249 e-scooter accidents were reported in Southern
California between September 2017 and August 2018, and 80 percent of injured people
fell, 11 percent crashed into an object, and 9 percent were hit by a moving vehicle [
41
].
Another study on injuries by Feng et al. (2020) collected Tweets and images between
2018 and 2020 and reported 153 injuries, with 22.88 percent of them being head-related,
27.45 percent of them being trunk- and hand-related, and 49.67 percent of them being
leg- and foot-related [
42
]. According to AASHTO’s guide, cycling or riding on sidewalks
causes more accidents than when riding on the road [
6
]. Because sidewalks are designed
for pedestrians, cyclists are not capable of riding on sidewalks properly, and e-scooter users
have also exhibited very low helmet use rates. Furthermore, when they investigated the
injuries, they found that less than 5 percent of users wore a helmet [
6
]. Additionally, the
City of Chicago Pilot Evaluation Survey (2020) found that 24 percent of the participants
stated that they used the e-scooter on the pavement at least for a while, and 5 percent of
them used it on the pavement at least half of the time [
13
]. It was observed that 10 percent
of riders used the e-scooter on the sidewalk in a street with a bike lane, and 2.7 percent of
riders wore a helmet [
13
]. Observations for parking showed that 18.4 percent of e-scooters
were incorrectly parked on the sidewalk, especially on cycle paths, etc. This is another
safety issue for pedestrians and people with disabilities [13].
In another case from Italy, reported by Campisi et al. (2020), for comfort and safety
reasons, men tend to use e-scooters more than women [
32
]. E-scooters have been driven at
approximately 17 km/h on shared sidewalks, which is dangerous for pedestrians [32].

Appl. Sci. 2021,11, 5851 15 of 20
Safety issues mostly result from confusion about the right of way and inappropriate
parking, with these factors causing most accidents, and low rates of the use of helmet
contribute as well. Furthermore, Pimentel and Lowry (2020) stated that misinformation
also causes safety problems. Users should be informed about the rules [23].
Glancing at e-scooter regulations, it is quite possible to encounter inconsistent policies
across states, cities, and regions. One of the reasons for these policy inconsistencies is that
e-scooters are a new and unfamiliar mode of mobility, though they have become one of
the basic ones. These differences among regulations have surely been expected, since city
administrators have tried to regulate e-scooters based on the user experience to date [43].
As shown in Table 2, studies including the regulations and restrictions of e-micro-
mobility were reviewed here. First, we found that many studies have started to regulate
these vehicles, primarily by restricting age and speed. Concerning regulations on the speed
of these vehicles, the limit in Poland is 25 km/h [
44
]. The speed limit in Chicago is 15 mph,
which is approximately 24 km/h, and in Oregon the limit is also 15 mph, except there
is an inconsistency in Oregon, namely, that micromobility vehicles are also prohibited
from traveling at a slower speed than the speed of traffic, i.e., traffic flows at 25 mph, so
e-scooters should not travel more slowly than 25 miles per hour (approx. 40 km/h) [
13
,
45
].
In this case, how quickly should e-scooter users ride? Another significant regulation from
the studies collected here—and perhaps the most agreed-upon one—is the prohibition of
riding these vehicles on the pavement. Considering the pedestrians’ rights of way and
the higher risk of accidents on the pavement, this decision can be seen to be a highly
appropriate decision.
In Japan, e-scooters are prohibited to be used on the pavement and riders should
have license plates [
46
]. In Dubai, the age limitation is 14, riders must wear a helmet
and park at designated areas, and riders are prohibited from carrying objects or a second
passenger [47].
Another implementation that differs among countries is the pricing policy. In this
context, the EU exhibits the cheapest price, almost half of that of the US, and China applies
a 20 percent higher price than the US price [
48
]. Pricing could seem like a company strategy.
However, it is indirectly a city policy that affects people’s travel behavior. Furthermore,
regarding alternative payment options, Atlanta and Los Angeles require non-credit card
payment options, and for non-smartphone users, it is mandatory to have alternative
activation methods in Austin, Los Angeles, and Portland [
49
]. After rising numbers of
e-scooters in the streets of Paris between 2018 and 2019, the city authorities restricted
the shared e-scooter fleet in the city due the fact that too many companies were entering
the market, with numerous vehicles without any regulation [
50
]. In Paris, the service
providers are limited to just three companies, and a limit of 15,000 total vehicles, and this
is also the case in San Francisco, Atlanta, and Washington DC. In addition, e-scooters are
restricted to bike lanes, with designated parking spots [
50
,
51
]. Moreover, regarding the
positive impacts of online navigation apps on the sustainable mobility behaviors of citizens
through optimizing travel time and route planning [
52
], there is a potential to use these
online platforms to inform citizens about the accessibility of shared e-scooters and their
regulations and restrictions in different urban zones.
The other important thing to consider is e-scooter companies’ disruptive distribution
strategies, which affect the right of equal access to services and limits e-micromobility
usage. Equal distribution of services is one of the basic principles that city administrators
should consider [
43
]. For example, in the USA, in Portland, 15 percent of the e-scooter
fleet must be available in East Portland, but in Charlotte, Austin, and Los Angeles, there
is no such practice yet [
49
]. This practice is mostly made so that low-income regions can
obtain equal access to the service. Incentives have been provided to some companies that
implemented the principle of equal distribution in Los Angeles [49].

Appl. Sci. 2021,11, 5851 16 of 20
Table 2. Literature review about regulations.
Source Literature Review about Regulations
Bielinski and Wazna (2020) In Poland, the speed limit is designated as a maximum of
25 km/h for shared e-scooters.
Campisi et al. (2020)
In Italy, the use of micromobility vehicles is limited by the need
for a license to rent vehicles, certain age groups, and use at certain
times of the day and certain places, and the speed of travel is
regulated by rules.
City of Chicago, Pilot
Evaluation (2020)
In Chicago, the travel speed of e-micromobility vehicles is limited
to 15 mph (approx. 24 km/h), and their use on pavements is
prohibited; they must be used on bicycle paths, but as an
exception, children under 12 years of age can use them on the
pavement. The age restriction for the use of shared electric
scooters is designated as 18. People over 16 years old can ride
with a guardian.
Feng et al. (2020)
Based on ten cities in the USA, users are required to wear
protective gear such as a helmet when using e-scooters. Stickers
or lights should be used to make the vehicles visible during night
rides. Drivers should not use electronic devices while driving, nor
should more than one person use a vehicle unless it is not
specifically designed for more than one person. E-scooters can be
used on bike paths or on the sidewalk with speeds of 15 mph
(approx. 25 km/h) and cannot be parked in car parks or parked
in a way that prevents pedestrians.
Leger et al. (2018)
In British Colombia, the age limit is 6+, max speed is 32 km/h, in
most regions there is no need for licenses or registration, but a
helmet is required. In Alberta, the age limit is 12+, the helmet is
required in most regions; in Manitoba and Quebec the age
limit is 14+.
Pimentel et al. (2020)
The study states that the main problem is inconsistencies in the
law. For instance, in Oregon, e-scooters are prohibited from use
on the pavement, and the speed limit is 25 km per hour (approx.
15 mile/h), although by law, micromobility vehicles are also
prohibited from traveling at a slower speed than the speed of
traffic, i.e., if traffic flows at 25 mph, the e-scooter should not
travel more slowly than 40 km. In West Hollywood, California,
e-bikes are prohibited from driving on the sidewalk. In King
County, Washington, wearing a helmet is mandatory but not
mandatory in other parts of the state. When an e-micromobility
user enters a different district, the age restriction application may
change. Helmets are not compulsory when using e-bikes and
e-scooters in more than 20 states, although 6 states have required
helmets for e-bike users.
It is also crucial to consider that the popularity of e-micromobility has increased
during the COVID-19 pandemic, and cities have embarked on quick implementations,
with effects on the infrastructure of these cities. Some of these implementations are as
follows—in Milan 35 km, in Paris 50 km, in Brussels 40 km, and in Seattle 30 km of car
lanes have been converted to bicycle lanes [
19
]. According to McKinsey and Company
(2019), the micromobility industry will be a USD 300 billion to USD 500 billion market by
2030 [
11
]. Still, the effects of the pandemic on the industry and the micromobility market
cannot be known for certain. Hence, to examine this accelerating market and to prepare
cities for its adoption, as well as to create more sustainable, equitable, and more livable
cities, regulations will have to apply in this field.
4. Conclusions
In this paper, we attempted to shed light on the impacts of e-micromobility vehicles
on urban sustainability through a systematic review of global mobility studies in the field

Appl. Sci. 2021,11, 5851 17 of 20
of e-scooters and e-bikes. This systematic review was categorized into seven sub-topics
related to the impacts of e-micromobility, analyzing them in the terms of the mobility
behaviors of citizens, the energy consumption, the environmental impacts, and the related
safety issues and regulations.
The impact on travel behaviors includes four sub-topics—the analysis of travel pur-
poses, modal shift from different modes of transport to e-micromobility vehicles, average
travel time, and distance. In the USA, e-scooter and e-bike sharing led to around 45 million
trips in 2018 [
6
]. The global findings indicate that the average trip distance and travel time
using e-scooters are in the range of 0.72–2.4 km and 8–12 min. However, most studies
reported the average travel distance using e-bikes to be in the range of 3–4.5 km and the
travel time to be in the range of 15 and 20 min. Therefore, e-micromobility has the capability
to be used for all trips which are less than 8 km, consisting of 50 to 60 percent of total trips
in China, the European Union, and the United States [
11
]. Thus, these findings indicate a
great potential for the modal shift to e-micromobility vehicles.
In the current evaluation, it has been shown that most people replaced walking
which means a substantial increase in the energy demand through the modal shift from
nonmotorized modes to e-modes of transport. The global findings indicate that the modal
shift to e-micromobility depends on urban forms and travel culture. For instance, the
second most replaced mode in the American cities was ride-hailing, whereas in France it
was public transportation [
29
]. In countries with extreme urban density, such as China,
people tended to replace public transportation with the use of e-bikes; in contrast, it was
reported that e-bike users replaced cars more than other modes in most of the US cities
studied [14,20,30].
Another key finding from this research relates to the purposes of the usage of e-
micromobility vehicles. In the USA, the proportions of users using these vehicles for com-
muting to work/school and fun/recreation were notably close to each other
[6,13,23]
. In
Chicago, 50 percent of users stated that they had been using e-scooters for social/entertain-
ment reasons; however, in Austin, Portland, and San Francisco, the specified purpose of us-
age was mostly for commuting to work or school [
6
,
13
]. In the case of e-bikes, most e-bikes
34re using for commuting. Admittedly, the purpose of recreation was also significant.
The findings in the field of the energy consumption indicate that e-scooters could
travel 128 km with 1 kW/h of energy, whereas a fossil fuel car can travel less than 1.6 km
and the best-in-class e-cars can travel 6.4 km with the same amount of energy [
37
]. The
development of e-micromobility might change the overall energy consumption in the
mobility sector. The findings in Pittsburg indicated that the modal shift from conventional
motorized modes of transport to e-micromobility for trips in the range of 5–8 km will
decrease the energy demands of mobility by 50 percent [
35
]. The CO
2
emissions of e-
scooters are approximately between 125–131 g per passenger per km, including 50 percent
from the manufacturing process and materials, and 43 percent from the collection process
for overnight charging. Therefore, their lifespan has an important environmental impact,
because of the considerable emissions involved in their production process [30,39,40].
Regarding safety issues and regulations, the benchmarks mentioned in this paper
give city authorities and regional planners an insight into how the infrastructure of e-
micromobility should be integrated into cities to assure the safety of the citizens.
This study provides an overview of the impacts of e-micromobility on urban transport
in terms of four aspects, including impacts on current travel behaviors, energy consump-
tion, the urban environment, safety issues, and the regulations required. However, it
is advisable to investigate surplus energy demands in future research, considering that
the energy demand will increase due to the modal shift from non-motorized transport to
e-micromobility vehicles. Another future research suggestion is to investigate the impacts
of land use parameters and urban forms on citizens’ propensity to use e-micromobility
vehicles, as well as the impact of population density on mode choice.

Appl. Sci. 2021,11, 5851 18 of 20
Author Contributions:
Conceptualization, H.M. and B.¸S.; methodology, B.¸S. and H.M.; formal
analysis, B.¸S. and H.M.; data curation, B.¸S.; writing—original draft preparation, B. ¸S. and H.M.;
writing—review and editing, B.¸S. and H.M.; visualization, B. ¸S.; supervision, H.M. Both authors have
read and agreed to the published version of the manuscript.
Funding: This research received no external funding.
Institutional Review Board Statement: Not applicable.
Informed Consent Statement: Not applicable.
Data Availability Statement: Not applicable.
Acknowledgments:
We acknowledge support by the German Research Foundation and the Open
Access Publication Fund of Technical University of Berlin.
Conflicts of Interest: The authors declare no conflict of interest.
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