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Building-related health impacts in European and Chinese cities: a scalable assessment method

Overview of attention for article published in Environmental Health, December 2015
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Title
Building-related health impacts in European and Chinese cities: a scalable assessment method
Published in
Environmental Health, December 2015
DOI 10.1186/s12940-015-0082-z
Pubmed ID
Authors

Jouni T. Tuomisto, Marjo Niittynen, Erkki Pärjälä, Arja Asikainen, Laura Perez, Stephan Trüeb, Matti Jantunen, Nino Künzli, Clive E. Sabel

Abstract

Public health is often affected by societal decisions that are not primarily about health. Climate change mitigation requires intensive actions to minimise greenhouse gas emissions in the future. Many of these actions take place in cities due to their traffic, buildings, and energy consumption. Active climate mitigation policies will also, aside of their long term global impacts, have short term local impacts, both positive and negative, on public health. Our main objective was to develop a generic open impact model to estimate health impacts of emissions due to heat and power consumption of buildings. In addition, the model should be usable for policy comparisons by non-health experts on city level with city-specific data, it should give guidance on the particular climate mitigation questions but at the same time increase understanding on the related health impacts and the model should follow the building stock in time, make comparisons between scenarios, propagate uncertainties, and scale to different levels of detail. We tested The functionalities of the model in two case cities, namely Kuopio and Basel. We estimated the health and climate impacts of two actual policies planned or implemented in the cities. The assessed policies were replacement of peat with wood chips in co-generation of district heat and power, and improved energy efficiency of buildings achieved by renovations. Health impacts were not large in the two cities, but also clear differences in implementation and predictability between the two tested policies were seen. Renovation policies can improve the energy efficiency of buildings and reduce greenhouse gas emissions significantly, but this requires systematic policy sustained for decades. In contrast, fuel changes in large district heating facilities may have rapid and large impacts on emissions. However, the life cycle impacts of different fuels is somewhat an open question. In conclusion, we were able to develop a practical model for city-level assessments promoting evidence-based policy in general and health aspects in particular. Although all data and code is freely available, implementation of the current model version in a new city requires some modelling skills.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 93 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 1%
Germany 1 1%
South Africa 1 1%
Unknown 90 97%

Demographic breakdown

Readers by professional status Count As %
Researcher 18 19%
Student > Master 12 13%
Student > Ph. D. Student 11 12%
Student > Bachelor 6 6%
Professor > Associate Professor 5 5%
Other 12 13%
Unknown 29 31%
Readers by discipline Count As %
Environmental Science 18 19%
Social Sciences 9 10%
Medicine and Dentistry 7 8%
Engineering 6 6%
Energy 5 5%
Other 10 11%
Unknown 38 41%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 16 May 2016.
All research outputs
#15,351,847
of 22,835,198 outputs
Outputs from Environmental Health
#1,138
of 1,490 outputs
Outputs of similar age
#228,713
of 389,743 outputs
Outputs of similar age from Environmental Health
#20
of 23 outputs
Altmetric has tracked 22,835,198 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,490 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 31.3. This one is in the 18th percentile – i.e., 18% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 389,743 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 32nd percentile – i.e., 32% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 23 others from the same source and published within six weeks on either side of this one. This one is in the 13th percentile – i.e., 13% of its contemporaries scored the same or lower than it.