Difference between revisions of "Assessment of climate mitigation policies related to indoor environment"

Revision as of 08:13, 30 April 2010

Related to Mega_case_study

Scope

Purpose

What are the greenhouse gas emission and health impacts of some policies in the buildings sector that might help mitigate climate change?

Boundaries

• Spatial: European Union
  • The case study looks at the European scale (EU 30). The spatial resolution differs for areas as appropriate. For air pollutants, e.g. it is based on 50x50 km Emep grid cells for regional effects and on a smaller grid for local effects (e.g. traffic in cities). For water, modelling might be based on river basins, while for indoor air pollution a country basis with probability distributions will be applied.
• Temporal: years 2030, 2030, 2050
  • The case study looks at the years 2020, 2030 and 2050, i.e. at the state of the system (policies, physical parameters…) and emissions of pollutants in these years. Effects of those emissions might be observed only later (e.g. exposure is delayed due to a slow dispersion of stressors in the environment, or health impacts can occur only years after exposure) but are attributed to the year of emission – in this case they are discounted to the year of emission (or to a common year for comparison) to reflect the time preference people give to effects in the future.
• Population: The whole population living in the European Union
  • Receptor for the exposure is the European population. According to needs it is stratified by age groups (5 years) and gender for each 50x50 km Emep grid cell. Its growth is also projected to the years 2020, 2030, and 2050.
• Scenarios:
  • The assessment is of a prognostic nature, i.e. a policy scenario is compared to a business as usual scenario (BAU) in the future years (for a description of the scenarios see chapter 4). Scenarios are needed to compare a do-nothing situation with a do-something situation, i.e. with a situation in which mitigation measures have been applied to change the system boundaries (in this case the temperature implying also other changes like decreased air conditioning use compared to the BAU).

The scenarios are defined in such a way that feedback loops and adaptive processes (e.g. behaviour) have been dynamically modelled in advance and the scenarios have been selected as possible equilibrium states of the respective modelled part. They feed into the actual assessment as assumptions and input parameters.

Policies considered

• Insulation of buildings for improved energy efficiency and change of air exchange, buiding codes
• Increased need for air conditioning
• Increase of heating homes by solid fuels, e.g. wood heating (considered renewable resource).
• urban planning: improving air exchange, more water in the city, shading, vegetation
• increasing the albedo by colouring the roofs of the houses in white

Pollutants considered

• PM2.5
• Radon
• Tobacco smoke
  • PM2.5
  • Benzene, formaldehyde, NNK
• Dampness and mold

Scenarios

Summary: Two European and two global scenarios are considered. The bases for our calculations are the European scenarios:

• Business as usual: BAU
• Policy: 2°C aim (-> Climate and Energy Package).

In the BAU adaptation measures need to be considered (e.g. more air conditioning due to a higher temperature). Direct health effects like excessive heat and UV radiation are also considered. The policy scenario assumes that the temperature rise can be limited to 2°C. This requires the implementation of mitigation measures. The EU plans to reach the 2°C aim by implementing the climate and energy package (at least 20% reduction of green house gases by 2020 compared to 1990, increasing energy efficiency to save 20% of energy consumption by 2020, 20% use of renewable energy, including 10% bio fuels in petrol and diesel). Thus, the aims of the package have been translated into measures. We made use of several sources for this: NEEDS project (TIMES model) for energy, transport, industry and waste and IIASA GAINS for agriculture, waste and product use, e.g. solvent use.

For more information see Mega_case_study

Intended users

   * Intended users are those for whom the assessment is made.

Participants

   * Participants are those who may participate in the making of the assessment. 
     The minimum group of people for a successful assessment is always described. 
     If some groups must be excluded, this must be explicitly motivated.

Definition

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Decision variables

   * Decision variables: decisions that are considered.

Indicators

   * Indicators: outcome variables of interest.

Value variables

   * Value variables: value judgements (usually about indicators).

Other variables

   * Other variables: any variables that link to the causal network and are within the boundaries of the assessment.

Analyses

   * Analyses: statistical and other analyses that contain two or more variables, e.g. optimizing.

Indices

   * Indices: lists of particular locations along spatial, temporal, or other dimensions. 

Result

   * Results of indicators and assessment-specific analyses. 

Results

Conclusions

   * Conclusions are based on the results, given the scope. 

See also

References