The impact of urban configuration types on urban heat islands, air pollution, CO2 emissions, and mortality in Europe: a data science approach.

BACKGROUND: The world is becoming increasingly urbanised. As cities around the world continue to grow, it is important for urban planners and policy makers to understand how different urban configuration patterns affect the environment and human health. However, previous studies have provided mixed findings. We aimed to identify European urban configuration types, on the basis of the local climate zones categories and street design variables from Open Street Map, and evaluate their association with motorised traffic flows, surface urban heat island (SUHI) intensities, tropospheric NO2, CO2 per person emissions, and age-standardised mortality. METHODS: We considered 946 European cities from 31 countries for the analysis defined in the 2018 Urban Audit database, of which 919 European cities were analysed. Data were collected at a 250 m × 250 m grid cell resolution. We divided all cities into five concentric rings based on the Burgess concentric urban planning model and calculated the mean values of all variables for each ring. First, to identify distinct urban configuration types, we applied the Uniform Manifold Approximation and Projection for Dimension Reduction method, followed by the k-means clustering algorithm. Next, statistical differences in exposures (including SUHI) and mortality between the resulting urban configuration types were evaluated using a Kruskal-Wallis test followed by a post-hoc Dunn's test. FINDINGS: We identified four distinct urban configuration types characterising European cities: compact high density (n=246), open low-rise medium density (n=245), open low-rise low density (n=261), and green low density (n=167). Compact high density cities were a small size, had high population densities, and a low availability of natural areas. In contrast, green low density cities were a large size, had low population densities, and a high availability of natural areas and cycleways. The open low-rise medium and low density cities were a small to medium size with medium to low population densities and low to moderate availability of green areas. Motorised traffic flows and NO2 exposure were significantly higher in compact high density and open low-rise medium density cities when compared with green low density and open low-rise low density cities. Additionally, green low density cities had a significantly lower SUHI effect compared with all other urban configuration types. Per person CO2 emissions were significantly lower in compact high density cities compared with green low density cities. Lastly, green low density cities had significantly lower mortality rates when compared with all other urban configuration types. INTERPRETATION: Our findings indicate that, although the compact city model is more sustainable, European compact cities still face challenges related to poor environmental quality and health. Our results have notable implications for urban and transport planning policies in Europe and contribute to the ongoing discussion on which city models can bring the greatest benefits for the environment, climate, and health. FUNDING: Spanish Ministry of Science and Innovation, State Research Agency, Generalitat de Catalunya, Centro de Investigación Biomédica en red Epidemiología y Salud Pública, and Urban Burden of Disease Estimation for Policy Making as a Horizon Europe project.

Investigating the spatiotemporal associations between meteorological conditions and air pollution in the federal state Baden-Württemberg (Germany).

When analyzing health data in relation to environmental stressors, it is crucial to identify which variables to include in the statistical model to exclude dependencies among the variables. Four meteorological parameters: temperature, ultraviolet radiation, precipitation, and vapor pressure and four outdoor air pollution parameters: ozone ( O 3 ), nitrogen dioxide ( NO 2 ), particulate matter ( P M 2.5 , P M 10 ) were studied on a daily basis for Baden-Württemberg (Germany). This federal state covers urban and rural compartments including mountainous and river areas. A temporal and spatial analysis of the internal relationships was performed among the variables using (a) cross-correlations, both on the grand ensemble of data as well as within subsets, and (b) the Local Indications of Spatial Association (LISA) method. Meteorological and air pollution variables were strongly correlated within and among themselves in time and space. We found a strong interaction between nitrogen dioxide and ozone, with correlation coefficients varying over time. The coefficients ranged from negative correlations in January (-0.84), April (-0.47), and October (-0.54) to a positive correlation in July (0.45). The cross-correlation plot showed a noticeable change in the correlation direction for O 3 and NO 2 . Spatially, NO 2 , P M 2.5 , and P M 10 concentrations were significantly higher in urban than rural regions. For O 3 , this effect was reversed. A LISA analysis confirmed distinct hot and cold spots of environmental stressors. This work examined and quantified the spatio-temporal relationship between air pollution and meteorological conditions and recommended which variables to prioritize for future health impact analyses. The results found are in line with the underlying physico-chemical atmospheric processes. It also identified postal code areas with dominant environmental stressors for further studies.

Long-term exposure and health risk assessment from air pollution: impact of regional scale mobility.

BACKGROUND: The negative effect of air pollution on human health is widely reported in recent literature. It typically involves urbanized areas where the population is concentrated and where most primary air pollutants are produced. A comprehensive health risk assessment is therefore of strategic importance for health authorities. METHODS: In this study we propose a methodology to perform an indirect and retrospective health risk assessment of all-cause mortality associated with long-term exposure to particulate matter less than 2.5 microns (PM2.5), nitrogen dioxide (NO2) and ozone (O3) in a typical Monday to Friday working week. A combination of satellite-based settlement data, model-based air pollution data, land use, demographics and regional scale mobility, allowed to examine the effect of population mobility and pollutants daily variations on the health risk. A Health Risk Increase (HRI) metric was derived on the basis of three components: hazard, exposure and vulnerability, utilizing the relative risk values from the World Health Organization. An additional metric, the Health Burden (HB) was formulated, which accounts for the total number of people exposed to a certain risk level. RESULTS: The effect of regional mobility patterns on the HRI metric was assessed, resulting in an increased HRI associated with all three stressors when considering a dynamic population compared to a static one. The effect of diurnal variation of pollutants was only observed for NO2 and O3. For both, the HRI metric resulted in significantly higher values during night. Concerning the HB parameter, we identified the commuting flows of the population as the main driver in the resulting metric. CONCLUSIONS: This indirect exposure assessment methodology provides tools to support policy makers and health authorities in planning intervention and mitigation measures. The study was carried out in Lombardy, Italy, one of the most polluted regions in Europe, but the incorporation of satellite data makes our approach valuable for studying global health.

Temperature and particulate matter as environmental factors associated with seasonality of influenza incidence - an approach using Earth observation-based modeling in a health insurance cohort study from Baden-Württemberg (Germany).

BACKGROUND: Influenza seasonality has been frequently studied, but its mechanisms are not clear. Urban in-situ studies have linked influenza to meteorological or pollutant stressors. Few studies have investigated rural and less polluted areas in temperate climate zones. OBJECTIVES: We examined influences of medium-term residential exposure to fine particulate matter (PM2.5), NO2, SO2, air temperature and precipitation on influenza incidence. METHODS: To obtain complete spatial coverage of Baden-Württemberg, we modeled environmental exposure from data of the Copernicus Atmosphere Monitoring Service and of the Copernicus Climate Change Service. We computed spatiotemporal aggregates to reflect quarterly mean values at post-code level. Moreover, we prepared health insurance data to yield influenza incidence between January 2010 and December 2018. We used generalized additive models, with Gaussian Markov random field smoothers for spatial input, whilst using or not using quarter as temporal input. RESULTS: In the 3.85 million cohort, 513,404 influenza cases occurred over the 9-year period, with 53.6% occurring in quarter 1 (January to March), and 10.2%, 9.4% and 26.8% in quarters 2, 3 and 4, respectively. Statistical modeling yielded highly significant effects of air temperature, precipitation, PM2.5 and NO2. Computation of stressor-specific gains revealed up to 3499 infections per 100,000 AOK clients per year that are attributable to lowering ambient mean air temperature from 18.71 °C to 2.01 °C. Stressor specific gains were also substantial for fine particulate matter, yielding up to 502 attributable infections per 100,000 clients per year for an increase from 7.49 µg/m3 to 15.98 µg/m3. CONCLUSIONS: Whilst strong statistical association of temperature with other stressors makes it difficult to distinguish between direct and mediated temperature effects, results confirm genuine effects by fine particulate matter on influenza infections for both rural and urban areas in a temperate climate. Future studies should attempt to further establish the mediating mechanisms to inform public health policies.

[Satellite data for recording health-relevant environmental conditions: examples and interdisciplinary potential]. / Satellitendaten zur Erfassung gesundheitsrelevanter Umweltbedingungen: Beispiele und interdisziplinäre Potenziale.

Environmental conditions influence human health and interact with other factors such as DNA, lifestyle, or the social environment. Earth observations from space provide data on the most diverse manifestations of these environmental conditions and make it possible to quantify them spatially. Using two examples - the availability of open and recreational space and the spatial distribution of air pollution - this article presents the potential of Earth observations for health studies. In addition, possible applications for health-related issues are discussed. To this end, we try to outline key points for an interdisciplinary approach that meets the conceptual, data technology, and ethical challenges.

Sensitivity of erythemally effective UV irradiance and daily exposure to temporal variability in total ozone.

The provision of information to the public about current levels of the erythemally effective UV radiation is an important issue in health care. The quality of promoted values is therefore of special importance. The atmospheric parameter which affects the erythemally effective UV radiation under clear sky most is the total ozone content of the atmosphere. In this paper we examined the sensitivity of the erythemally effective irradiance and daily radiant exposure to the temporal variability of total ozone on time scales from 1 to 15 days. The results show that the sensitivity is highest for the first 24 h. Larger time scales do not exhibit a similar influence. Total ozone measurements of the previous day may already cause uncertainties higher than 0.5 UV index (UVI) independent of the geolocation. For comparison, a temporal persistence of 15 days may cause uncertainties of 1.2 UVI at 50 degrees N, 1 UVI at 30 degrees S and less than 1 UVI at the equator. The results of this study allow finding the necessary temporal resolution of total ozone values when a certain accuracy for the UVI or for the purpose of sun protection is required. The results are compared with those of two preceding studies where we quantified the influence of measurement uncertainties and spatial total ozone variability to the erythemally effective irradiance at noon and to the daily dose. We conclude that temporal variability of total ozone is the most critical issue, but also measurement uncertainties do have a noticeable influence on the erythemally effective radiation.

Sensitivity of UV erythemally effective irradiance and daily dose to spatial variability in total ozone.

The total ozone column (TOC) is the most significant quantity for estimating the erythemally effective UV radiation under clear sky conditions. Uncertainties in TOC measurements and a limited spatial and temporal resolution therefore influence the quality of calculated erythemally effective radiation. The UV Index, the internationally accepted measure of the erythemally effective radiation, is used in public and the media to inform about current levels of UV radiation and builds the base for sun protection. Thus, the accuracy of the promoted values is essential. While in a preceding study we estimated the influence of measurement uncertainties, in this study we analyze the influence of spatial gaps and variability of TOC to the erythemally effective irradiance at noon and to the daily dose. The results allow defining the necessary spatial resolution of TOC values when a certain accuracy for the UV Index or for the purpose of sun protection is required. In case of the erythemally effective irradiance this study reveals that spatial gaps in TOC or the assumption of spatial invariability causes similar uncertainties independent of the geographic location. At higher latitudes the higher spatial variability of TOC counteracts the lower level of irradiance. For the daily dose gaps in TOC have an even higher impact at higher latitudes.

Sensitivity of erythemally effective UV irradiance and daily exposure to uncertainties in measured total ozone.

In this study the sensitivity of the erythemally effective radiation to uncertainties in operationally measured total ozone content of the atmosphere (TOC) was estimated. For this, daily operational TOC measurements from different instruments were applied covering the period from 1997 to 1999. Measurements were gained from space by Earth Probe Satellite, Earth Remote Sensing satellite/Global Ozone Monitoring Experiment and Operational Vertical Sounder and from the ground by Dobson and Brewer spectrophotometers for the locations of Hradec Kralove (Czech Republic, 50 degrees N), Nairobi (Kenya, 1 degrees S) and Springbok (Republic of South Africa, 30 degrees S). The values were used as input parameter to model calculations of erythemally effective irradiance and daily radiant exposure. The differences due to the use of TOC from different sources were analyzed with respect to the Ultraviolet Index (UVI). The UVI was introduced as a tool for sun protection and health care. Therefore, it is of special importance to know the restriction of accuracy. As a tool of health care, the maximum uncertainties are of interest and are described in using the 95%-percentile and the maximum differences. This study shows that differences, i.e. uncertainties (95%-percentile) are in the order of 1 UVI. Independently on the location, however, extreme differences may overstep 3 UVI. For the daily dose the 95%-percentile is around 7.5 UVI hours (UVIh) but differences higher than 20 UVIh were also found.