Concept: Urban heat island
There is an increasingly hot debate on whether the replacement of conventional vehicles (CVs) by electric vehicles (EVs) should be delayed or accelerated since EVs require higher cost and cause more pollution than CVs in the manufacturing process. Here we reveal two hidden benefits of EVs for addressing climate change to support the imperative acceleration of replacing CVs with EVs. As EVs emit much less heat than CVs within the same mileage, the replacement can mitigate urban heat island effect (UHIE) to reduce the energy consumption of air conditioners, benefitting local and global climates. To demonstrate these effects brought by the replacement of CVs by EVs, we take Beijing, China, as an example. EVs emit only 19.8% of the total heat emitted by CVs per mile. The replacement of CVs by EVs in 2012 could have mitigated the summer heat island intensity (HII) by about 0.94°C, reduced the amount of electricity consumed daily by air conditioners in buildings by 14.44 million kilowatt-hours (kWh), and reduced daily CO2 emissions by 10,686 tonnes.
While photovoltaic (PV) renewable energy production has surged, concerns remain about whether or not PV power plants induce a “heat island” (PVHI) effect, much like the increase in ambient temperatures relative to wildlands generates an Urban Heat Island effect in cities. Transitions to PV plants alter the way that incoming energy is reflected back to the atmosphere or absorbed, stored, and reradiated because PV plants change the albedo, vegetation, and structure of the terrain. Prior work on the PVHI has been mostly theoretical or based upon simulated models. Furthermore, past empirical work has been limited in scope to a single biome. Because there are still large uncertainties surrounding the potential for a PHVI effect, we examined the PVHI empirically with experiments that spanned three biomes. We found temperatures over a PV plant were regularly 3-4 °C warmer than wildlands at night, which is in direct contrast to other studies based on models that suggested that PV systems should decrease ambient temperatures. Deducing the underlying cause and scale of the PVHI effect and identifying mitigation strategies are key in supporting decision-making regarding PV development, particularly in semiarid landscapes, which are among the most likely for large-scale PV installations.
The co-occurrence of consecutive hot and humid days during a heat wave can strongly affect human health. Here, we quantify humid heat wave hazard in the recent past and at different levels of global warming. We find that the magnitude and apparent temperature peak of heat waves, such as the ones observed in Chicago in 1995 and China in 2003, have been strongly amplified by humidity. Climate model projections suggest that the percentage of area where heat wave magnitude and peak are amplified by humidity increases with increasing warming levels. Considering the effect of humidity at 1.5° and 2° global warming, highly populated regions, such as the Eastern US and China, could experience heat waves with magnitude greater than the one in Russia in 2010 (the most severe of the present era). The apparent temperature peak during such humid-heat waves can be greater than 55 °C. According to the US Weather Service, at this temperature humans are very likely to suffer from heat strokes. Humid-heat waves with these conditions were never exceeded in the present climate, but are expected to occur every other year at 4° global warming. This calls for respective adaptation measures in some key regions of the world along with international climate change mitigation efforts.
The public health consequences of extreme heat events are felt most intensely in metropolitan areas where population density is high and the presence of the urban heat island phenomenon exacerbates the potential for prolonged exposure. This research develops an approach to map potential heat stress on humans by combining temperature and relative humidity into an index of apparent temperature. We use ordinary kriging to generate hourly prediction maps describing apparent temperature across the Greater Toronto Area, Canada. Meteorological data were obtained from 65 locations for 6 days in 2008 when extreme heat alerts were issued for the City of Toronto. Apparent temperature and exposure duration were integrated in a single metric, humidex degree hours (HDH), and mapped. The results show a significant difference in apparent temperature between built and natural locations from 3 PM to 7 AM; this discrepancy was greatest at 12 AM where built locations had a mean of 2.8 index values larger, t(71) = 5.379, p < 0.001. Spatial trends in exposure to heat stress (apparent temperature, ≥30°C) show the downtown core of the City of Toronto and much of Mississauga (west of Toronto) as likely to experience hazardous levels of prolonged heat and humidity (HDH ≥ 72) during a heat alert. We recommend that public health officials use apparent temperature and exposure duration to develop spatially explicit heat vulnerability assessment tools; HDH is one approach that unites these risk factors into a single metric.
Most studies examining the temperature-mortality association in a city used temperatures from one site or the average from a network of sites. This may cause measurement error as temperature varies across a city due to effects such as urban heat islands. We examined whether spatiotemporal models using spatially resolved temperatures produced different associations between temperature and mortality compared with time series models that used non-spatial temperatures. We obtained daily mortality data in 163 areas across Brisbane city, Australia from 2000 to 2004. We used ordinary kriging to interpolate spatial temperature variation across the city based on 19 monitoring sites. We used a spatiotemporal model to examine the impact of spatially resolved temperatures on mortality. Also, we used a time series model to examine non-spatial temperatures using a single site and the average temperature from three sites. We used squared Pearson scaled residuals to compare model fit. We found that kriged temperatures were consistent with observed temperatures. Spatiotemporal models using kriged temperature data yielded slightly better model fit than time series models using a single site or the average of three sites' data. Despite this better fit, spatiotemporal and time series models produced similar associations between temperature and mortality. In conclusion, time series models using non-spatial temperatures were equally good at estimating the city-wide association between temperature and mortality as spatiotemporal models.
Little is known about the intensity and extension of subsurface urban heat islands (UHI), and the individual role of the driving factors has not been revealed either. In this study, we compare groundwater temperatures in shallow aquifers beneath six German cities of different size (Berlin, Munich, Cologne, Frankfurt, Karlsruhe and Darmstadt). It is revealed that hotspots of up to +20K often exist, which stem from very local heat sources, such as insufficiently insulated power plants, landfills or open geothermal systems. When visualizing the regional conditions in isotherm maps, mostly a concentric picture is found with the highest temperatures in the city centers. This reflects the long-term accumulation of thermal energy over several centuries and the interplay of various factors, particularly in heat loss from basements, elevated ground surface temperatures (GST) and subsurface infrastructure. As a primary indicator to quantify and compare large-scale UHI intensity the 10-90%-quantile range UHII(10-90) of the temperature distribution is introduced. The latter reveals, in comparison to annual atmospheric UHI intensities, an even more pronounced heating of the shallow subsurface.
Urban ecosystems are the most complex mosaics of vegetative land cover that can be found. In a recent paper, Francis and Lorimer (2011) evaluated the reconciliation potential of living roofs and walls. For these authors, these two techniques for habitat improvement have strong potential for urban reconciliation ecology. However they have some ecological and societal limitations such as the physical extreme environmental characteristics, the monetary investment and the cultural perceptions of urban nature. We are interested in their results and support their conclusions. However, for a considerable time, green roofs have been designed to provide urban greenery for buildings and the green roof market has only focused on extensive roof at a restricted scale within cities. Thus, we have strong doubts about the relevance of their use as possible integrated elements of the network. Furthermore, without dynamic progress in research and the implementation of well-thought-out policies, what will be the real capital gain from green roofs with respect to land-use complementation in cities? If we agree with Francis and Lorimer (2011) considering that urban reconciliation ecology between nature and citizens is a current major challenge, then “adaptive collaborative management” is a fundamental requirement.
In urban environments, green roofs provide a number of benefits, including decreased urban heat island effects and reduced energy costs for buildings. However, little research has been done on the non-plant biota associated with green roofs, which likely affect their functionality. For the current study, we evaluated whether or not green roofs planted with two native plant communities in New York City functioned as habitats for soil fungal communities, and compared fungal communities in green roof growing media to soil microbial composition in five city parks, including Central Park and the High Line. Ten replicate roofs were sampled one year after planting; three of these roofs were more intensively sampled and compared to nearby city parks. Using Illumina sequencing of the fungal ITS region we found that green roofs supported a diverse fungal community, with numerous taxa belonging to fungal groups capable of surviving in disturbed and polluted habitats. Across roofs, there was significant biogeographical clustering of fungal communities, indicating that community assembly of roof microbes across the greater New York City area is locally variable. Green roof fungal communities were compositionally distinct from city parks and only 54% of the green roof taxa were also found in the park soils. Phospholipid fatty acid analysis revealed that park soils had greater microbial biomass and higher bacterial to fungal ratios than green roof substrates. City park soils were also more enriched with heavy metals, had lower pH, and lower quantities of total bases (Ca, K, and Mg) compared to green roof substrates. While fungal communities were compositionally distinct across green roofs, they did not differentiate by plant community. Together, these results suggest that fungi living in the growing medium of green roofs may be an underestimated component of these biotic systems functioning to support some of the valued ecological services of green roofs.
A Bicycle-Based Field Measurement System for the Study of Thermal Exposure in Cuyahoga County, Ohio, USA
- International journal of environmental research and public health
- Published about 5 years ago
Collecting a fine scale of microclimate data can help to determine how physical characteristics (e.g., solar radiation, albedo, sky view factor, vegetation) contribute to human exposure to ground and air temperatures. These data also suggest how urban design strategies can reduce the negative impacts of the urban heat island effect. However, urban microclimate measurement poses substantial challenges. For example, data taken at local airports are not representative of the conditions at the neighborhood or district level because of variation in impervious surfaces, vegetation, and waste heat from vehicles and buildings. In addition, fixed weather stations cannot be deployed quickly to capture data from a heat wave. While remote sensing can provide data on land cover and ground surface temperatures, resolution and cost remain significant limitations. This paper describes the design and validation of a mobile measurement bicycle. This bicycle permits movement from space to space within a city to assess the physical and thermal properties of microclimates. The construction of the vehicle builds on investigations of the indoor thermal environment of buildings using thermal comfort carts.
As is true in many regions, India experiences surface Urban Heat Island (UHI) effect that is well understood, but the causes of the more recently discovered Urban Cool Island (UCI) effect remain poorly constrained. This raises questions about our fundamental understanding of the drivers of rural-urban environmental gradients and hinders development of effective strategies for mitigation and adaptation to projected heat stress increases in rapidly urbanizing India. Here we show that more than 60% of Indian urban areas are observed to experience a day-time UCI. We use satellite observations and the Community Land Model (CLM) to identify the impact of irrigation and prove for the first time that UCI is caused by lack of vegetation and moisture in non-urban areas relative to cities. In contrast, urban areas in extensively irrigated landscapes generally experience the expected positive UHI effect. At night, UHI warming intensifies, occurring across a majority (90%) of India’s urban areas. The magnitude of rural-urban temperature contrasts is largely controlled by agriculture and moisture availability from irrigation, but further analysis of model results indicate an important role for atmospheric aerosols. Thus both land-use decisions and aerosols are important factors governing, modulating, and even reversing the expected urban-rural temperature gradients.