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Introduction: Cities have long been known to be society's predominant engine of innovation and wealth creation, yet they are also hotspots of pollution and disease partly due to current urban and transport practices. The aim of the European Urban Burden of Disease project is to evaluate the health burden and its determinants related to current and future potential urban and transport planning practices and related exposures in European cities and make this evidence available for policy and decision making for healthy and sustainable futures., Methods and Analysis: Drawing on an established comparative risk assessment methodology (ie, Urban and Transport Planning Health Impact Assessment) tool), in nearly 1000 European cities we will (1) quantify the health impacts of current urban and transport planning related exposures (eg, air pollution, noise, excess heat, lack of green space) (2) and evaluate the relationship between current levels of exposure, health impacts and city characteristics (eg, size, density, design, mobility) (3) rank and compare the cities based on exposure levels and the health impacts, (4) in a number of selected cities assess in-depth the linkages between urban and transport planning, environment, physical activity and health, and model the health impacts of alternative and realistic urban and transport planning scenarios, and, finally, (5) construct a healthy city index and set up an effective knowledge translation hub to generate impact in society and policy., Ethics and Dissemination: All data to be used in the project are publicly available data and do not need ethics approval. We will request consent for personal data on opinions and views and create data agreements for those providing information on current and future urban and transport planning scenarios.For dissemination and to generate impact, we will create a knowledge translation hub with information tailored to various stakeholders., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: Large nation- and region-wide epidemiological studies have provided important insights into the health effects of long-term exposure to outdoor air pollution. Evidence from these studies for the long-term effects of ultrafine particles (UFP), however is lacking. Reason for this is the shortage of empirical UFP land use regression models spanning large geographical areas including cities with varying topographies, peri-urban and rural areas. The aim of this paper is to combine targeted mobile monitoring and long-term regional background monitoring to develop national UFP models., Method: We used an electric car to monitor UFP concentrations in selected cities and towns across the Netherlands over a 14-month period in 2016-2017. Routes were monitored 3 times and concentrations were averaged per road segment. In addition, we used kriging maps based on regional background monitoring (20 sites; 3 × 2 weeks) over the same period to assess annual average regional background concentrations. All road segments were used to model spatial variation of UFP with three different land-use (regression) approaches: supervised stepwise regression, LASSO and random forest. For each approach, we also tested a deconvolution method, which segregates the average concentration at each road segment into a local and background signal. Model performance was evaluated with short-term (400 sites across the Netherlands; 3 × 30 minutes) and external longer-term measurements (42 sites in two major cities; 3 × 24 hours). We also compared predictions of all six models at 1000 random addresses spread over the country., Results: We found similar predictive performance for the six models, with validation R 2 values from 0.25 to 0.35 for short-term measurements and 0.52 to 0.60 for longer-term external measurements. Models with and without deconvolution had similar predictive performance. All models based on the deconvolution method included a regional background kriging map as important predictor. Correlations between predictions at random addresses were high with Pearson correlations from 0.84 to 0.99. Models overestimated exposure at the short-term and long-term sites by about 20-30% in all cases, with small differences between regions and road types., Conclusion: We developed robust nation-wide models for long-term UFP exposure combining mobile monitoring with long-term regional background monitoring. Minor differences in predictive performance between different algorithms were found, but the deconvolution approach is considered more physically realistic. The models will be applied in Dutch nation-wide health studies., (Copyright © 2021. Published by Elsevier Ltd.)

Higher temperatures are associated with morbidity and mortality. Most epidemiological studies use outdoor temperature data, however, people spend most of their time indoors. Indoor temperatures and determinants of indoor temperatures have rarely been studied on a large scale. We measured living room and bedroom temperature in 113 homes of elderly subjects, as well as outdoor temperatures, in two cities in the Netherlands. Linear regression was used to determine the influence of building characteristics on indoor living room and bedroom temperatures in the warm episode. During the warm episode, indoor temperatures were higher during the night and lower during the day than outdoor temperatures. Indoor temperatures on average exceeded outdoor temperatures. The weekly average indoor temperature in living rooms varied between 23.1 and 30.2 °C. Dwellings that warmed up easily, also cooled down more easily. Outdoor and indoor temperatures were moderately correlated (R 2  = 0.36 and 0.34 for living rooms and bedrooms, respectively). Building year before 1930 and rooms being located on the top floor were associated with higher indoor temperatures. Green in the vicinity was associated with lower temperatures in bedrooms. This study shows that indoor temperatures vary widely between dwellings, and are determined by outdoor temperatures and building characteristics. As most people, especially the elderly, spend most of the time indoor, indoor temperature is a more exact predictor of heat exposure than outdoor temperature. The importance of mitigating high indoor temperatures will be more important in the future because of higher temperatures due to climate change., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Competing Interests: I declare no competing interests.

Background: Ambient air pollution is a major environmental cause of morbidity and mortality worldwide. Cities are generally hotspots for air pollution and disease. However, the exact extent of the health effects of air pollution at the city level is still largely unknown. We aimed to estimate the proportion of annual preventable deaths due to air pollution in almost 1000 cities in Europe., Methods: We did a quantitative health impact assessment for the year 2015 to estimate the effect of air pollution exposure (PM 2·5 and NO 2 ) on natural-cause mortality for adult residents (aged ≥20 years) in 969 cities and 47 greater cities in Europe. We retrieved the cities and greater cities from the Urban Audit 2018 dataset and did the analysis at a 250 m grid cell level for 2015 data based on the global human settlement layer residential population. We estimated the annual premature mortality burden preventable if the WHO recommended values (ie, 10 μg/m 3 for PM 2·5 and 40 μg/m 3 for NO 2 ) were achieved and if air pollution concentrations were reduced to the lowest values measured in 2015 in European cities (ie, 3·7 μg/m 3 for PM 2·5 and 3·5 μg/m 3 for NO 2 ). We clustered and ranked the cities on the basis of population and age-standardised mortality burden associated with air pollution exposure. In addition, we did several uncertainty and sensitivity analyses to test the robustness of our estimates., Findings: Compliance with WHO air pollution guidelines could prevent 51 213 (95% CI 34 036-68 682) deaths per year for PM 2·5 exposure and 900 (0-2476) deaths per year for NO 2 exposure. The reduction of air pollution to the lowest measured concentrations could prevent 124 729 (83 332-166 535) deaths per year for PM 2·5 exposure and 79 435 (0-215 165) deaths per year for NO 2 exposure. A great variability in the preventable mortality burden was observed by city, ranging from 0 to 202 deaths per 100 000 population for PM 2·5 and from 0 to 73 deaths for NO 2 per 100 000 population when the lowest measured concentrations were considered. The highest PM 2·5 mortality burden was estimated for cities in the Po Valley (northern Italy), Poland, and Czech Republic. The highest NO 2 mortality burden was estimated for large cities and capital cities in western and southern Europe. Sensitivity analyses showed that the results were particularly sensitive to the choice of the exposure response function, but less so to the choice of baseline mortality values and exposure assessment method., Interpretation: A considerable proportion of premature deaths in European cities could be avoided annually by lowering air pollution concentrations, particularly below WHO guidelines. The mortality burden varied considerably between European cities, indicating where policy actions are more urgently needed to reduce air pollution and achieve sustainable, liveable, and healthy communities. Current guidelines should be revised and air pollution concentrations should be reduced further to achieve greater protection of health in cities., Funding: Spanish Ministry of Science and Innovation, Internal ISGlobal fund., (Copyright © 2021 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY-NC-ND 4.0 license. Published by Elsevier Ltd.. All rights reserved.)

To assess environmental exposures at the individual level, new assessment methods and tools are required. We developed an exposure assessment system (ExpoApp) for smartphones. ExpoApp integrates: (i) geo-location and accelerometry measurements from a waist attached smartphone, (ii) data from portable monitors, (iii) geographic information systems, and (iv) individual's information. ExpoApp calculates time spent in microenvironments, physical activity level, inhalation rate, and environmental exposures and doses (e.g., green spaces, inhaled ultrafine particles- UFP). We deployed ExpoApp in a panel study of 158 adults from five cities (Amsterdam and Utrecht- the Netherlands, Basel- Switzerland, Norwich- UK, and Torino- Italy) with an UFP monitor. To evaluate ExpoApp, participants also carried a reference accelerometer (ActiGraph) and completed a travel-activity diary (TAD). System reliability and validity of measurements were evaluated by comparing the monitoring failure rate and the agreement on time spent in microenvironments and physical activity with the reference tools. There were only significant failure rate differences between ExpoApp and ActiGraph in Norwich. Agreement on time in microenvironments and physical activity level between ExpoApp and reference tools was 86.6% (86.5-86.7) and 75.7% (71.5-79.4), respectively. ExpoApp estimated that participants inhaled 16.5 × 10 10 particles/day of UFP and had almost no contact with green spaces (24% of participants spent ≥30 min/day in green spaces). Participants with more contact with green spaces had higher inhaled dose of UFP, except for the Netherlands, where the relationship was the inverse. ExpoApp is a reliable system and provides accurate individual's measurements, which may help to understand the role of environmental exposures on the origin and course of diseases., (Copyright © 2019 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Ultrafine particles (UFPs) have been associated with negative effects on human health. Emissions from motor vehicles are the principal source of UFPs in urban air. A study in Vancouver suggested that UFP concentrations were related to density of fast food restaurants near the monitoring sites. A previous monitoring campaign could not separate the contribution of restaurants from road traffic. The main goal of this study has been the quantification of fast food restaurants' contribution to outdoor UFP concentrations. A portable particle number counter (DiscMini) has been used to carry out mobile monitoring in a largely pedestrianized area in the city center of Utrecht. A fixed route passing 17 fast food restaurants was followed on 8 days. UFP concentrations in front of the restaurants were 1.61 times higher than in a nearby square without any local sources used as control area and 1.22 times higher compared with all measurements conducted in between the restaurants. Adjustment for other sources such as passing mopeds, smokers or candles did not explain the increase. In conclusion, fast food restaurants result in significant increases in outdoor UFP concentrations in front of the restaurant.

Recently, short-term monitoring campaigns have been carried out to investigate the spatial variation of air pollutants within cities. Typically, such campaigns are based on short-term measurements at relatively large numbers of locations. It is largely unknown how well these studies capture the spatial variation of long term average concentrations. The aim of this study was to evaluate the within-site temporal and between-site spatial variation of the concentration of ultrafine particles (UFPs) and black carbon (BC) in a short-term monitoring campaign. In Amsterdam and Rotterdam (the Netherlands) measurements of number counts of particles larger than 10nm as a surrogate for UFP and BC were performed at 80 sites per city. Each site was measured in three different seasons of 2013 (winter, spring, summer). Sites were selected from busy urban streets, urban background, regional background and near highways, waterways and green areas, to obtain sufficient spatial contrast. Continuous measurements were performed for 30 min per site between 9 and 16 h to avoid traffic spikes of the rush hour. Concentrations were simultaneously measured at a reference site to correct for temporal variation. We calculated within- and between-site variance components reflecting temporal and spatial variations. Variance ratios were compared with previous campaigns with longer sampling durations per sample (24h to 14 days). The within-site variance was 2.17 and 2.44 times higher than the between-site variance for UFP and BC, respectively. In two previous studies based upon longer sampling duration much smaller variance ratios were found (0.31 and 0.09 for UFP and BC). Correction for temporal variation from a reference site was less effective for the short-term monitoring campaign compared to the campaigns with longer duration. Concentrations of BC and UFP were on average 1.6 and 1.5 times higher at urban street compared to urban background sites. No significant differences between the other site types and urban background were found. The high within to between-site concentration variances may result in the loss of precision and low explained variance when average concentrations from short-term campaigns are used to develop land use regression models., (Copyright © 2014 Elsevier B.V. All rights reserved.)