Table 1 Availability of personal exposure variables and data sources

1. Physical activity environment (infrastructure and land use deter-mining the way the surroundings can be accessed and used)

Altitude in centimetres

2000–2018

Ac, NB, P4, P6

AHN.nl—cooperation of provinces, central government and water boards

The altitude map of the Netherlands is a laser altimetry product in raster format available on different horizontal scales levels

-25 m. resolution (AHN1)

2000 (ca.)

-5 m. resolution (AHN2)

2010 (ca.)

-50 cm. resolution (AHN3)

2018 (ca.)

Bicycle path density

2019

NB

Basic topography register system (BRT—TOP10—Cadastre, 2019) with point and line layers of roads, railways, junctions, ramps and exits, bridges, tunnels, cycle lanes, footpaths, etc

Topographic cycle path line data joined with data ‘Landelijk fietsplatform

Road density

2015

NB

The (car)road density is derived from the dataset TOP10 NL 2015 (line feature layer WEGDEEL_HARTLIJN)

Street connectivity

1989 1993 2001 2003 2012 2015 2019

A_{150,250,350,500,750,} 1000,1650,2000

Key register Large-scale Topography (BGT—Cadastre) including among others polygon layers of separate bicycle lanes and sideways

Connectivity of the street network, represented by the ratio between the number of true intersections (three or more legs) to the size of the selected area

NB, P4, P6

Sidewalk density

1989 1993 1996 2000 2003 2008 2012 2015 2019

A_{150,250,350,500,750,}

Density of sidewalk polygon area calculated as Z-scores. Years before 2015 are constructed using auxiliary data

_{1000,1650,2000}

NB, P4, P6

Land use

1989 1993 1996 2000 2003 2006 20082020 2012 2015

Ac, NB, P4, P6

Land use—Statistics Netherlands (CBS) based on a.o. TOP10 and aerial photography. Classification in 9 main land use classes and ca. 40 subclasses

Land use concerns generalized data. Classification changes occur between 1993 and 1996

Land use mix/ entropy index

1989 1993 1996 2000 2003 2006 2008 2010 2012 2015

A_{150,250,350,500,750, 1000,1650,2000} NB, P4, P6

Land use—Statistics Netherlands (CBS)

The land use mix is calculated as Z-scores and indicates the heterogeneity of five specific land use classes

Land use classes

1-residential

2-commercial

3-social-cultural services

4-offices/ public services

5-greenspace/ recreation

Green space density

1989 1993 1996 2000 2003 2006 2008 2010 2012 2015

A_{150,250,350,500,750, 1000,1650,2000}

NB, P4, P6

Land use—Statistics Netherlands (CBS)

Greenspace density calculated as Z-scores. Greenspace includes public gardens, parks, forests and graveyards

Green space (10 m. res.)

2017

NB, P4, P6

Institute for Public Health and the Environment (RIVM)/ Atlas Leefomgeving (ALO)

Combination of different datasets related to green space derived from the AHN2 and AHN3 files, the BAG buildings and the Infrared aerial photo (CIR file, resolution of 0.25 m)

-% Trees

-Tree height classes

-% Shrubs

-% Low vegetation

Sport accommodation density (indoor and outdoor)

2017

NB

Databestand SportAanbod (DSA) Mulier instituut

Accommodation density is calculated from a national dataset with xy coordinates from ca. 22.000 sport accommodations managed by the Mulier institute

Base topography—TOP10 BRT—(a.o. roads, tracks, water, terrain, furnishing elements)

2003 2005 2010 2011 2012 2013 2015 2019

NB, P4, P6

Basic topography register system (BRT—TOP10—Cadastre

Key register large-scale Topography—BGT (point, line and polygon layers of topographical objects)

2012–2020 continuous

NB, P4, P6

Key register large-scale Topography—BGT—Cadastre

Application scale 1:500–1:5.000

Walkability index

1989 1993 1996 2000 2003 2006 2008 2010 2012 2015

A_{150,250,350,500,750, 1000,1650,2000}

NB, P4, P6

GECCO project based on land use and population Statistics Netherlands (CBS) and basic/ large scale topography Cadastre Netherlands

Walkability is calculated by summing the z-scores of its six components and normalizing the results to values between 0 and 100

Composite score based on six components:

1) Population density

2) Density of retail and service destinations

3) Land-use mix

4) Street connectivity

5) Green space

6) Side walk density

Bicycle and walking network including cycling and walking routes, networks and transport nodes

2019 continuous

NB, P4

Derived from TOP10 NL road data by Landelijk Fietsplatform and Wandelnet

Vector line data

2. Transport/mobility environment

Parking spaces (public street parking spaces, private residential places and paid/ unpaid parking garages and car parks)

2019 (park spaces BAG 2015)

NB

Derived from dataset ‘Parking places’ Cadastre/ RDW (Netherlands Vehicle Authority). Combines vector point and polygon data from BGT, TOP10, BAG and RDW on scales 1:2.500–1:10.000

Statistical summaries have been made for the neighbourhood borders of 2016. The BAG data for private built-up parking spaces concerns the year 2015, the other data concerns 2019

-Number of parking places

-Park space density in

number of parking places per household

-Number of parking places per hectare

-Park space ratio as

-Number of cars/ number of parking places

Public transport stop density (bus, ferry, metro, taxi and tram stops)

2018 (updated from 2015)

NB

Geodienst Rijksuniversiteit Groningen/ databank Nationale Data Openbaar Vervoer (NDOV)

Kernel point densities (1000-m search radius) of public transport stops are calculated to overcome MAUP neighbourhood effect

Railway stations

2019

A(r), NB, P4, P6

Esri Netherlands Datasets

On the basis of this dataset several distance and density based exposure variables can be derived on request

3. Environmental pollution (pollution/ nuisance in surroundings, air, soil or water, measured, modeled and/or perceived)

Traffic noise—daily mean (mixed road, rail and air) in Lden

2000 2004, 2005 2007 2008

Ac, P4, P6

PBL Netherlands Environmental Assessment Agency

Modelled data with Empara noise tool with 25 × 25 m resolution on mixed traffic noise in dB

Traffic noise—daily mean (road only) in Lden

2000 2004 2007 2008 2010 2011

Ac, P4, P6

PBL Netherlands Environmental Assessment Agency

Modelled data with Empara noise tool with 25 × 25 m resolution on road noise in dB. Several factors are accounted including traffic intensity, road types and sound barriers

Traffic noise— national roads (high ways)

2006 2011 2016

Ac, P4, P6

Dep. of Waterways and Public Works (Min. of IenW)

Airport noise Schiphol

2016

Ac, P6

Ministry of Infrastruc-ture and Water Management (IenW)

Separate data available for day and night (noise in Lden)

Air pollution < 25 m resolution modelled annual average of min., max. and mean values

2009

Ac, P4, P6

Institute of Risk Assessment Sciences (IRAS)/ European Study of Cohort for Air Pollution Effects (ESCAPE)

Annual average outdoor pollution concentrations modelled/ interpolated with measurement data, traffic data and the physical environment. See online mapviewer

-Particulate matter (PM_2.5)

-PM 2.5 absorbance

-Particulate matter (PM₁₀)

-Particulate matter (PM_coarse)

-Nitrogen dioxide (NO₂)

-Nitrogen oxide (NO_x)

Air pollution 25 m. resolution modelled annual average

-Particulate matter (PM_2.5)

-Particulate matter (PM₁₀)

-Nitrogen dioxide (NO₂)

-Soot (EC)

2013 2014 2015 2016 2017 (NO₂ not for 2013)

Ac, NB, P4, P6

Institute for Public Health and the Environment (RIVM)

Annual average outdoor pollution concentrations based on a combination of model calculations and measurements from official measurement locations. SOOT (EC) maps indicative only

Air pollution 1 km resolution modelled annual average

1995-2018 Yearly

Ac, NB, P4, P6

Institute for Public Health and the Environment (RIVM)

Modelled future concentra-tions are available for all variables for 2020, 2025 and 2030, apart for C₆H₆ and CO

-Benzene (C₆H₆)

2011–2018

-Carbon monoxide (CO)

2011–2018

-Carbon monoxide p98 (CO)

2011–2018

-Particulate matter (PM_2.5)

2017–2018

-Particulate matter (PM₁₀)

1995–2018

-Ammonia (NH₃)

2011–2018

-Nitrogen dioxide (NO₂₎

1995–2018

-Nitrogen oxide (NO_x)

2011–2018

-Ozone (O₃)

2011–2018

-Soot (EC)

2011–2018

-Sulphur dioxide (SO₂)

2011–2018

4. Food and retail environment

Food environment healthiness-index (other variables derived from Locatus point data on request)

2016 (other years on request)

NB (on the basis of this dataset several distance and density based exposure variables can be derived on request)

Retail point coordinate data LOCATUS (2004–2020)

Index score (food environment healthiness index) between − 5 and + 5 according to FEHI score as described elsewhere [32]. Data is aggregated to neighbourhoods using point density kernels to prevent MAUP issue

5. Socio-economic environment (administrative divisions, key demography, social and economic parameters and cultural amenities)

Neighbourhood statistics

Two-yearly 1995–2001

One-yearly 2002–2019

Ac, NB

‘Wijk- en buurtkaarten’ Statistics Netherlands (CBS)

The Dutch statistical office (CBS), records a range of demographic variables per neighbourhood

Neighbourhood borders/divisions can change over the years and also the recorded variables can change over the years

-Demographics (age classes, sex, mortality, etc.) -Population density

-Provenance-Urbanization

-Housing stock-Living (rent, ownership, residence types, etc.)-Energy consumption (gas/ electricity)-Education-Labour-Income

-Crime-Social security -Businesses-Motor vehicles -Land use

-Amenities (average distance to specific facilities and average number of specific facilities within a radius around addresses in a neighbourhood)-Overlapping PC4 area-Area land/water

Buildings/addresses (BAG)

2011–2020

Continuous

Ac, NB, P4, P6

Key register addresses and buildings (BAG), Cadastre NL

Vector dataset (point/ polygon) containing more than 10 million buildings and 9,3 million addresses (2020) on a scale starting from 1:2.500

including:

-houses, buildings, berths, beach pavilions, caravans, trailers, etc.

-utilization function

-construction year

-building area

Education

2018

A(r), NB, P4, P6

Dienst Uitvoering Onderwijs (DUO) - Ministry of Education, Culture and Science

Coordinates and address data per school / institution. Data can be spatially summarized per indicated exposure zone

-primary schools

-secondary schools

-special schools

-higher education

Key statistics 4-digit postal code (a.o. sex and age of inhabitants, household composition, migration background)

1998–2018

P4

PC4 statistics - Statistics Netherlands (CBS)

Available variables for PC4 and PC6 zones can differ. PC4 contains additional statistics from 2015 onwards

Other statistics 4-digit postal code (accessibility, childcare, facilities culture, -education, -health care, -sport, housing benefits/stock, income, land use, livability, living environ-ment typology, offices, retail and businesses, post offices, travel time, transactions/house prices)

1990–2015 (range can differ per variable)

P4

Miscellaneous (a.o. ABF Research, SWING Real Estate Monitor, Statistics Netherlands (CBS), Dutch Ministry of the Interior and Kingdom Relations)

Key statistics 6-digit postal code (a.o. demographics, income, immigrants, housing stock)

2004, 2010

P6

PC6 statistics—Statistics Netherlands (CBS)

Purchased data

Key statistical figures

2000–2018

Ac, NB, P4, P6

Vierkantstatistieken Statistics Netherlands (CBS)

The CBS dataset ‘vierkantstatistieken’ contains basic statistics on number of inhabitants, dwellings, residential density and urbanity for all years and additional statistics from 2011 onwards

per 100 x 100 meter grid cell

    Number of inhabitants

    Inhabitants < 15 years

    Inhabitants 15–25 years

    Inhabitants 25–45 years

    Inhabitants 45–65 years

    Inhabitants > 65 years

    Total number of men

    Total number of women

    Percentage classes:

    Native Dutch

    Migr. backgr—western

    Migr. backgr—nonwestern

    Number or dwellings

Property values

Other statistics (households, property age classes, owned/ rented property, single/ multiple family dwellings, social security, energy use number of ca. 30 different destinations within 1/2/ 3 km, distance to nearest destinations (ca. 30))

2015–2018

Poverty in % ‘poor’ households

2017

NB, P4

The Netherlands Institute of Social Research (SCP)

Percentage of ‘poor’ households according to SCP definitions per PC4 area and neighbourhood

Socio-economic status score

1998 2002 2006 2010 2014 2016 2017

P4 (NB 2016)

The Netherlands Institute of Social Research (SCP)

Socio-economic status scores are based on: education, income and position in the labour market)

6. Safety, aesthetics, air temperature

Temperature per km grid

1961-current (daily per year

Ac, NB, P4, P6

Royal Netherlands Meteorological Institute (KNMI)

1 × 1 km grids of interpolated data (Inverse Distance Weighted interpolation, with 2.0 power parameter, block size 20 km and search radius of 110 km) based on 33–35 automatic KNMI observation stations

-Daily average

-Daily minimum

-Daily maximum

Traffic incidents

Yearly 2003–2017

P6

Bestand geRegistreerde Ongevallen

Nederland (BRON)

Provided via ESRI Nl datasets