Fred Meier

Evaluating the Effects of Façade Greening on Human Bioclimate in a Complex Urban Environment

The evaluation of the effectiveness of countermeasures for a reduction of urban heat stress, such as facade greening, is challenging due to lacking transferability of results from one location to another. Furthermore, complex variables such as the mean radiant temperature are necessary to assess outdoor human bioclimate. We observed in front of a building facade in Berlin, Germany, which is half-greened while the other part is bare. was reduced (mean 2 K) in front of the greened compared to the bare facade. To overcome observational shortcomings, we applied the microscale models ENVI-met, RayMan, and SOLWEIG. We evaluated these models based on observations. Our results show that (MD = −1.93 K) and downward short-wave radiation (MD = 14.39 W/m2) were sufficiently simulated in contrast to upward short-wave and long-wave radiation. Finally, we compare the simulated reduction of with the observed one in front of the facade greening, showing that the models were not able to simulate the effects of facade greening with the applied settings. Our results reveal that facade greening contributes only slightly to a reduction of heat stress in front of building facades.

Modification of Heat-Related Mortality in an Elderly Urban Population by Vegetation (Urban Green) and Proximity to Water (Urban Blue): Evidence from Lisbon, Portugal.

Background: Urban populations are highly vulnerable to the adverse effects of heat, with heat-related mortality showing intra-urban variations that are likely due to differences in urban characteristics and socioeconomic status. Objectives: We investigated the influence of urban green and urban blue, that is, urban vegetation and water bodies, on heat-related excess mortality in the elderly > 65 years old in Lisbon, Portugal, between 1998 and 2008. Methods: We used remotely sensed data and geographic information to determine the amount of urban vegetation and the distance to bodies of water (the Atlantic Ocean and the Tagus Estuary). Poisson generalized additive models were fitted, allowing for the interaction between equivalent temperature [universal thermal climate index (UTCI)] and quartiles of urban greenness [classified using the Normalized Difference Vegetation Index (NDVI)] and proximity to water (≤ 4 km vs. > 4 km), while adjusting for potential confounders. Results: The association between mortality and a 1°C increase in UTCI above the 99th percentile (24.8°C) was stronger for areas in the lowest NDVI quartile (14.7% higher; 95% CI: 1.9, 17.5%) than for areas in the highest quartile (3.0%; 95% CI: 2.0, 4.0%). In areas > 4 km from water, a 1°C increase in UTCI above the 99th percentile was associated with a 7.1% increase in mortality (95% CI: 6.2, 8.1%), whereas in areas ≤ 4 km from water, the estimated increase in mortality was only 2.1% (95% CI: 1.2, 3.0%). Conclusions: Urban green and blue appeared to have a mitigating effect on heat-related mortality in the elderly population in Lisbon. Increasing the amount of vegetation may be a good strategy to counteract the adverse effects of heat in urban areas. Our findings also suggest potential benefits of urban blue that may be present several kilometers from a body of water. Citation: Burkart K, Meier F, Schneider A, Breitner S, Canário P, Alcoforado MJ, Scherer D, Endlicher W. 2016. Modification of heat-related mortality in an elderly urban population by vegetation (urban green) and proximity to water (urban blue): evidence from Lisbon, Portugal. Environ Health Perspect 124:927–934; http://dx.doi.org/10.1289/ehp.1409529

High-frequency fluctuations of surface temperatures in an urban environment

This study presents an attempt to resolve fluctuations in surface temperatures at scales of a few seconds to several minutes using time-sequential thermography (TST) from a ground-based platform. A scheme is presented to decompose a TST dataset into fluctuating, high-frequency, and long-term mean parts. To demonstrate the scheme’s application, a set of four TST runs (day/night, leaves-on/leaves-off) recorded from a 125-m-high platform above a complex urban environment in Berlin, Germany is used. Fluctuations in surface temperatures of different urban facets are measured and related to surface properties (material and form) and possible error sources. A number of relationships were found: (1) Surfaces with surface temperatures that were significantly different from air temperature experienced the highest fluctuations. (2) With increasing surface temperature above (below) air temperature, surface temperature fluctuations experienced a stronger negative (positive) skewness. (3) Surface materials with lower thermal admittance (lawns, leaves) showed higher fluctuations than surfaces with high thermal admittance (walls, roads). (4) Surface temperatures of emerged leaves fluctuate more compared to trees in a leaves-off situation. (5) In many cases, observed fluctuations were coherent across several neighboring pixels. The evidence from (1) to (5) suggests that atmospheric turbulence is a significant contributor to fluctuations. The study underlines the potential of using high-frequency thermal remote sensing in energy balance and turbulence studies at complex land–atmosphere interfaces.

Interaction between urban heat island and urban pollution island during summer in Berlin

Urban Heat Island (UHI) and Urban Pollution Island (UPI) are two major problems of the urban environment and have become more serious with rapid urbanization. Since UHI and UPI can interact with each other, these two issues should be studied concurrently for a better urban environment. This study investigated the interaction between the UHI and UPI in Berlin, through a combined analysis of in-situ and remote sensing observations of aerosols and meteorological variables in June, July, and August from 2010 to 2017. The atmospheric UHI (AUHI), surface UHI (SUHI), atmospheric UPI (AUPI), and near-surface UPI (NSUPI) were analyzed. The SUHI and AUPI are represented by the remote sensing land surface temperature (LST) and aerosol optical depth (AOD), and the AUHI and NSUPI are represented by the in-situ air temperature and Particulate Matter (PM10) concentrations. The study area shows spatial consistency between SUHI and AUPI, with higher LST and AOD in the urban areas. UHI strengthens the turbulent dispersion of particles in the urban areas, decreasing the NSUPI. The NSUPI intensity shows a negative relationship with the AUHI intensity, especially at night with a correlation coefficient of -0.31. The increased aerosols in urban atmosphere reduce the incoming solar radiation and increase the atmospheric longwave radiation in the urban areas. The response of the surface to the change of absorbed radiation is strong at night and weak during the day. This study estimates that the SUHI intensity is enhanced by around 12% at clear night by the increased absorbed radiation in the urban areas using an attribution method. The goal of this paper is to strengthen the understanding of the interactive influence between UHI and UPI and provide a basis for designing mitigation strategies of UHI and UPI.

Development and Application of a Statistically-Based Quality Control for Crowdsourced Air Temperature Data

In urban areas, dense atmospheric observational networks with high-quality data are still a challenge due to high costs to deploy and maintain them over time. Citizen weather stations (CWS) could be one answer to that issue. Since more and more owners of CWS share their measurement data publicly, crowdsourcing, i.e., the automated collection of large amounts of data from an undefined crowd of citizens, opens new pathways for atmospheric research. However, the most critical issue is found to be the quality of data from such networks. In this study, a statistically-based quality control (QC) is developed to identify suspicious air temperature (T) measurements from crowdsourced data sets. The newly developed QC exploits the combined knowledge of the dense network of CWS to statistically identify implausible measurements, independent of external reference data. The evaluation of the QC is performed using data from Netatmo CWS in Toulouse, France, and Berlin, Germany, over a one-year period (July 2016 to June 2017), comparing the quality-controlled data with data from a network of reference stations. The new QC efficiently identifies erroneous data due to solar exposition and siting issues, which are common error sources of CWS. Estimation of T is improved when averaging data from a group of stations within a restricted area rather than relying on data of individual CWS. However, a positive deviation in CWS data compared to reference data is identified, particularly for daily minimum T. To illustrate the transferability of the newly developed QC and the use of CWS data, a mapping of CWS data is performed over the city of Paris, France, where spatial density of CWS is especially high.

Thermal remote sensing of urban microclimates by means of time-sequential thermography

Article history: Received 24 February 2009 Received in revised form 31 July 2009 Accepted 4 August 2009