In 2023, approximately 988,943 people lived in Stockholm, making it not only the capital, but also the biggest city in Sweden. The second biggest city, Gothenburg (Göteborg) had about half as many inhabitants, with about 596,840 people. Move to the citySweden is a country with a very high urbanization rate, the likes of which is usually only seen in countries with large uninhabitable areas, such as Australia, or in nations with very little rural landscape and agrarian structures, like Cuba. So why do so few Swedes live in rural areas, even though based on total area, the country is one of the largest in Europe? The total population figures are the answer to this question, as Sweden has only about 10.3 million inhabitants as of 2018 – that’s only 25 inhabitants per square kilometer. Rural exodus or just par for the course?It is no mystery why most Swedes flock to the cities: Jobs, of course. Over 65 percent of Sweden’s gross domestic product is generated by the services sector, and agriculture only contributes about one percent to the GDP. Employment mirrors this, with 80 percent of the workforce being deployed in services, namely in foreign trade, telecommunications, and manufacturing, among other industries.

Stockholm was ranked as the best city for startups in Sweden in 2023, with a total score of 33.46. Malmö followed in second with a score of 4.78, followed by Gothenburg. That year, Sweden was ranked as the second best country for startups in Europe and the fifth best worldwide.

The aim of this study is to throw light on why inequality in the distribution of income in Sweden fell from the mid-1920s to the second part of the 1950s. For this reason the project decided to collect income information referring to different years from a sample of households for one Swedish city. A database was created by coding tax records and other documents for the city of Göteborg, the second largest city in Sweden.

The determination of which years to investigate was critical. For analysing changes over time it was thought as essential to have roughly equal numbers of years between years studied. Further, it was thought advisable to avoid years with too much macroeconomic turmoil as well as the years of the two World Wars. Balancing the resources for the data collection between the size of a sub sample and the number of subsamples, it was decided to assemble data for four years. The years 1925, 1936, 1947 and 1958 was chosen to investigate. It should be pointed out that the year 1947 was preferred to the following years as large social insurance reforms leading to increases in pension benefits and the introduction of child allowances were put in effect in 1948.

Household is defined from registers kept in the archives (Mantalslängder). A household is defined as persons with the same surname living in the same apartment or single-family house. This means that there can be people belonging to more than two generations in the same household; siblings living together can make up a household as well. Foster children are included as long as they are registred at the same address. Adult children are considered to be living in the household of their parents as long as they are registred at the same address. In almost all cases, servants and tenants not belonging to the household are treated as separate households.

Background

Battery electric vehicles (BEVs) are crucial for a sustainable transportation system. As more people adopt BEVs, it becomes increasingly important to accurately assess the demand for charging infrastructure. However, much of the current research on charging infrastructure relies on outdated assumptions, such as the assumption that all BEV owners have access to home chargers and the "Liquid-fuel" mental model. To address this issue, we simulate the travel and charging demand on three charging behavior archetypes. We use a large synthetic population of Sweden, including detailed individual characteristics, such as dwelling types (detached house vs. apartment) and activity plans (for an average weekday). This data repository aims to provide the BEV simulation's input, assumptions, and output so that other studies can use them to study sizing and location design of charging infrastructure, grid impact, etc.

A journal paper published in Transportation Research Part D: Transport and Environment details the method to create the data (particularly Section 2.2 BEV simulation).

https://doi.org/10.1016/j.trd.2023.103645

Methodology

This data product is centered on the 1.7 million inhabitants of the Västra Götaland (VG) region, which includes the second largest city in Sweden, Gothenburg. We specifically simulated 284,000 car agents who live in VG, representing 35% of all car users and 18% of the total population in the region. They spend their simulation day (representing an average weekday) in a variety of locations throughout Sweden.

This open data repository contains the core model inputs and outputs. The numbers in parentheses correspond to the data sets. We use individual agents' activity plans (1) and travel trajectories from MATSim simulation for the BEV simulation (2), in which we consider overnight charger access (3), car fleet composition referencing the current private car fleet in Sweden (4), and Swedish road network with slope information (5) with realistic BEV charging & discharging dynamics. For the BEV simulation, we tested ten scenarios of charging behavior archetypes and fast charging powers (6). The output includes the time history of travel trajectories and charging of the simulated BEVs across the different scenarios (7).

Data description

The current data product covers seven data files.

(1) Agents' experienced activity plans

File name: 1_activity_plans.csv

Column	Description	Data type	Unit
person	Agent ID	Integer	-
act_id	Activity index of each agent	Integer	-
deso	Zone code of Demographic statistical areas (DeSO)1	String	-
POINT_X	Coordinate X of activity location (SWEREF99TM)	Float	meter
POINT_Y	Coordinate Y of activity location (SWEREF99TM)	Float	meter
act_purpose	Activity purpose (work, home, other)	String	-
mode	Transport mode to reach the activity location (car)	String	-
dep_time	Departure time in decimal hour (0-23.99)	Float	hour
trav_time	Travel time to reach the activity location	String	hour:minute:second
trav_time_min	Travel time in decimal minute	Float	minute
speed	Travel speed to reach the activity location	Float	km/h
distance	Travel distance between the origin and the destination	Float	km
act_start	Start time of activity in minute (0-1439)	Integer	minute
act_time	Activity duration in decimal minute	Float	minute
act_end	End time of activity in decimal hour (0-23.99)	Float	hour
score	Utility score of the simulation day given by MATSim	Float	-

1 https://www.scb.se/vara-tjanster/oppna-data/oppna-geodata/deso--demografiska-statistikomraden/

(2) Travel trajectories

File name: 2_input_zip

Produced by MATSim simulation, the zip folder contains ten files (events_batch_X.csv.gz, X=1, 2, …, 10) of input events for the BEV simulation. They are the moving trajectories of the car agents in their simulation days.

Column	Description	Data type	Unit
time	Time in second in a simulation day (0-86399)	Integer	Second
type	Event type defined by MATSim simulation2	String	-
person	Agent ID	Integer	-
link	Nearest road link consistent with (5)	String	-
vehicle	Vehicle ID identical to person	Integer	-

² One typical episode of MATSim simulation events: Activity ends (actend) -> Agent’s vehicle enters traffic (vehicle enters traffic) -> Agent’s vehicle moves from previous road segment to its next connected one (left link) -> Agent’s vehicle leaves traffic for activity (vehicle leaves traffic) -> Activity starts (actstart)

(3) Overnight charger access

File name: 3_home_charger_access.csv

Column	Description	Data type	Unit
person	Agent ID	Integer	-
home_charger	Whether an agent has access to a home garage charger/living in a detached house (0=no, 1=yes)	Integer	-

(4) Car fleet composition

File name: 4_car_fleet.csv

Column	Description	Data type	Unit
person	Agent ID	Integer	-
income_class	Income group (0=None, 1=below 180K, 2=180K-300K, 3=300K-420K, 4=above 420K)	Integer	-
car	Car model class (B=40 kWh, C=60 kWh, D=100 kWh)	String	-

(5) Road network with slope information

File name: 5_road_network_with_slope.shp (5 files in total)

Column	Description	Data type	Unit
length	The length of road

The MPP was started in the early 70's as a screening survey in the middle-aged population of Malmö, the third largest city of Sweden. Subjects born in Malmö and residents of the city were invited for a clinical examination, questionnaire and blood sampling. In all 22,444 men and 10,902 women participated during the period 1974-1992. During a later follow-up, the MPP-Re-examination (MPP-RES) in all 17,284 of the original screenes attended in 2002-2006.

Purpose: 1. To screen for cardiovascular risk-factors and alcohol abuse in the local population, and to offer intervention to subjects at risk;

1. To use DNA (at MPP-RES) for analyses of genetic risks of type-2 diabetes and cardiovascular disease, as well as some cancers.

The aim of this study is to throw light on why inequality in the distribution of income in Sweden fell from the mid-1920s to the second part of the 1950s. For this reason the project decided to collect income information referring to different years from a sample of households for one Swedish city. A database was created by coding tax records and other documents for the city of Göteborg, the second largest city in Sweden.

The determination of which years to investigate was critical. For analysing changes over time it was thought as essential to have roughly equal numbers of years between years studied. Further, it was thought advisable to avoid years with too much macroeconomic turmoil as well as the years of the two World Wars. Balancing the resources for the data collection between the size of a sub sample and the number of subsamples, it was decided to assemble data for four years. The years 1925, 1936, 1947 and 1958 was chosen to investigate. It should be pointed out that the year 1947 was preferred to the following years as large social insurance reforms leading to increases in pension benefits and the introduction of child allowances were put in effect in 1948.

Household is defined from registers kept in the archives (Mantalslängder). A household is defined as persons with the same surname living in the same apartment or single-family house. This means that there can be people belonging to more than two generations in the same household; siblings living together can make up a household as well. Foster children are included as long as they are registred at the same address. Adult children are considered to be living in the household of their parents as long as they are registred at the same address. In almost all cases, servants and tenants not belonging to the household are treated as separate households.

Purpose:

The aim of this study is to throw light on why inequality in the distribution of income in Sweden fell from the mid-1920s to the second part of the 1950s

In Sweden, the Region of Stockholm had the highest number of police officers in 2022. This comes as no surprise as this is also the most populous of the regions. The regions South and West, where the second and third largest cities Malmö and Gothenburg are located, had the second highest number of police officers. In total, there were nearly 22,000 police officers in Sweden that year.

Russia is the largest country in Europe, and also the largest in the world, its total size amounting to 17 million square kilometers (km2). It should be noted, however, that over three quarters of Russia is located in Asia, and the Ural mountains are often viewed as the meeting point of the two continents in Russia; nonetheless, European Russia is still significantly larger than any other European country. Ukraine, the second largest country on the continent, is only 603,000 km2, making it about 28 times smaller than its eastern neighbor, or seven times smaller than the European part of Russia. France is the third largest country in Europe, but the largest in the European Union. The Vatican City, often referred to as the Holy Sea, is both the smallest country in Europe and in the world, at just one km2. Population Russia is also the most populous country in Europe. It has around 144 million inhabitants across the country; in this case, around three quarters of the population live in the European part, which still gives it the largest population in Europe. Despite having the largest population, Russia is a very sparsely populated country due to its size and the harsh winters. Germany is the second most populous country in Europe, with 83 million inhabitants, while the Vatican has the smallest population. Worldwide, India and China are the most populous countries, with approximately 1.4 billion inhabitants each. Cities Moscow in Russia is ranked as the most populous city in Europe with around 13 million inhabitants, although figures vary, due to differences in the methodologies used by countries and sources. Some statistics include Istanbul in Turkey* as the largest city in Europe with its 15 million inhabitants, bit it has been excluded here as most of the country and parts of the city is located in Asia. Worldwide, Tokyo is the most populous city, with Jakarta the second largest and Delhi the third.

People between 25 and 34 years made up the largest age group in the Swedish Capital of Stockholm in 2022. There were nearly 180,000 people of this age living in the city. 35 to 44-year-old people made up the second largest age group. In total, there were 984,748 people living in Stockholm that year.

Most of the job openings in Sweden are located in the capital Stockholm. In the last quarter of 2023, there were around 26,000 job openings available in Stockholm. The number of job openings in Stockholm was at its lowest in the second quarter of 2020 after the outbreak of COVID-19. West Sweden had the second highest number of job openings in the last quarter of 2023. The lowest number of job openings were registered in the sparsely populated region Central Norrland.