Public health impacts of GHG emission reduction strategies in household energy use
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Assessment is based on the work by Wilkinson et al. 2009[1]
File:HIA housing energy Wilkinson09.ana
Scope
Purpose
Health impacts of different climate change mitigation strategies aimed at reducing GHG emissions from household energy use.
Boundaries
Spatial:
- United Kingdom
Temporal:
- Impacts during one year, reference year 2010
Population:
- UK total population
Policy strategies:
- Increased energy efficiency of household heating by
- Increased insulation by dwelling fabric improvements
- Improved dwelling ventilation control
- Fuel switching from indoor household fossil fuel combustion to electricity
- Reduce in indoor temperatures by change in occupant behaviour
Scenarios
- Baseline
- Distributions of efficiency for UK housing stock and associated GHG emissions and health effects
- Scenario 1: dwelling fabric improvements
- Overall heat loss of the fabric reduced from 224 J/s per ºC to 98 j/s per ºC
- Scenario 2: improved dwelling ventilation control
- The present permeability of the housing stock shifted to present reduced air leakage in all dwellings
- Tightest dwellings (3 m3/m2 per h) assumed to have ideal mechanical ventilation
- Scenario 3: fuel switching
- All indoor combustion replaced by electricity
- Effects on CO2 emission not modelled
- Scenario 4: Occupant behaviour
- Indoor temperature in all dwellings with average temperature > 18 ºC decreased by 1 ºC. Temperatures ≤18 ºC unchanged.
- Scenario 5: combination of scenarios 1-4
Intended users
Participants
Definition
Decision variables
- Dwelling fabric improvements (yes/no)
- Improved ventilation control (yes/no)
- Fuel switch to electricity (yes/no)
- Decrease in indoor temperatures (yes/no)
Indicators
- Disability-adjusted life years (DALYs)
- Premature deaths
- Household energy sector greenhouse gas emissions
Value variables
Other variables
Indoor exposures
- Fine particles (PM2.5, µg/m3)
- Baseline: 5.5
- Scenario 1: 5.5
- Scenario 2: 4.6
- Scenario 3: 3.7
- Scenario 4: 5.5
- Scenario 5: 2.5
- Radon (Bq/m3)
- Baseline: 21.7
- Scenario 1: 21.7
- Scenario 2: 17.2
- Scenario 3: 21.7
- Scenario 4: 21.7
- Scenario 5: 17.2
- Carbon monoxide (CO, probability of poisoning)
- Baseline: 1E-6
- Scenario 1: 1E-6
- Scenario 2: 1E-6
- Scenario 3: 0
- Scenario 4: 1E-6
- Scenario 5: 0
- Environmental tobacco smoke (ETS, exposure expressed in ETS units)
- Baseline: 1.5
- Scenario 1: 1.5
- Scenario 2: 1.7
- Scenario 3: 1.5
- Scenario 4: 1.5
- Scenario 5: 1.7
- Mould growth (% with mold index >1)
- Baseline: 17.7
- Scenario 1: 17.3
- Scenario 2: 20.3
- Scenario 3: 17.7
- Scenario 4: 18.7
- Scenario 5: 20.8
- Cold (winter indoor temperature C)
- Baseline: 18.1
- Scenario 1: 18.4
- Scenario 2: 18.2
- Scenario 3: 18.1
- Scenario 4: 17.9
- Scenario 5: 18.5
Exposure-response functions
- PM2.5 exposure and cardiopulmonary mortality
- RR 1.059 per 10 µg/m3
- PM2.5 exposure and lung cancer
- 1.082 per 10 µg/m3
- ERF for long-term indoor exposure to radon and lung cancer
- Risk of death from acute CO toxicity
- 1 death per million people for dwellings with combustion appliances
- ERF for ETS exposure and mortality due to myocardial infarction
- RR 1.30 if living in the same dwelling as smoker (age >30 years)
- ETS exposure and mortality due to cerebrovascular accident (age >30 years)
- RR 1.25 if living in the same dwelling as smoker
- ERF for indoor exposure to dampness and mold and respiratory symptoms
- ERF for short-term indoor exposure to cold and cardiovascular mortality
Analyses
- Comparative health impact assessment
- Sensitivity analyses
Indices
- Age
- Pollutant
Result
Results
Change per million population compared with baseline scenario
Premature deaths | Scenario 1 | Scenario 2 | Scenario 3 | Scenario 4 | Scenario 5 |
PM2.5 | 0 | -32 | -64 | 0 | -107 |
Radon | 0 | 3 | 0 | 0 | 3 |
CO | 0 | 0 | -1 | 0 | -1 |
ETS | 0 | 24 | 0 | 0 | 24 |
Mold | 0 | 0 | 0 | 0 | 0 |
Cold | -7 | -1 | 0 | 0 | -8 |
Total | -7 | -6 | -65 | 0 | -89 |
DALYs | |||||
PM2.5 | 0 | -310 | -619 | 0 | -1026 |
Radon | 0 | 43 | 0 | 0 | 43 |
CO | 0 | 0 | -25 | 0 | -25 |
ETS | 0 | 219 | 0 | 0 | 219 |
Mold | -2 | 12 | 0 | 5 | 15 |
Cold | -60 | -12 | 0 | 0 | -72 |
Total | -62 | -48 | -644 | 5 | -847 |
CO2 emissions (MT) | -33 | -6 | 0 | 2 | 41 |
Change in disease burdens per MT CO2 saved
Scenario 1 | Scenario 2 | Scenario 3 | Scenario 4 | Scenario 5 | |
Premature deaths | -12.2 | -64 | - | 0 | -133 |
DALYs | -115 | -492 | - | 17.3 | -1267 |
Conclusions
See also
References
- ↑ Wilkinson P., Smith K.R., Davies M., Adair H., Armstrong B.G., Barrett M., Bruce N., Haines A., Hamilton I., Oreszcyn T., Ridley I., Tonne C. & Chalabi Z. Public health benefits of strategies to reduce greenhouse gas emissions: household energy. Health and Climate Series 4, The Lancet. Published online November 25, 2009. Doi:10.1016/S0140-6736(09)61713-X [1]