Difference between revisions of "Hämeenkyrö MSWI risk assessment: Fine particles"

Revision as of 22:10, 29 December 2006

See the main page of this assessment: Hämeenkyrö MSWI risk assessment: General

PM_2.5 emissions in Hämeenkyrö

Scope

Existing primary PM_2.5 emissions from all the sources in Hämeenkyrö. Annual emissions. Emissions from the sources in Hämeenkyrö municipality area only.

Description

PM_2.5 means particles with diameter less than 2,5 µm. Important sources of these fine particles are domestic combustion, traffic, industries and energy production. There are some quite large industries and power plants (e.g. M-Real Kyro cardboard factory, Finnforest Oyj sawmill and Kyro gas power plant) that also cause fine particle emissions.

Well-being of the population (smells, comfort, noise) are discribed elsewhere. D↷

Subvariables: D↷

• emission (domestic combustion)
• emission (traffic)
• emission (M-real)
• emission (Finnforest)
• emission (Kyro power plant)
• emission (others)

References

• [Hämeenkyrön kunta]
• [VTT Liisa]
• Länsi-Suomen ympäristölupavirasto, Lupapäätös 48/2004/1

Definition

Formula:

var Total_emissions:= emission (domestic combustion) + emission (traffic) + emission (M-real) + emission (Finnforest) + emission (Kyro power plant) + emission (others)

Data:

• Traffic (2004): 11
• Kyro power plant (2002) <0,1

Unit

tonnes/year

Result

• Traffic (2004): 11
• Kyro power plant (2002) <0,1

PM_2.5 emissions from MSWI, biofuel plant, and natural gas plant in Hämeenkyrö

Scope

Gives PM_2.5 emissions for the three power plants according to their actual/planned production. Annual PM_2.5 emissions for each power plant.

Description

This variable gives the PM_2.5 emissions separately for each of the three power plant options to be considered in the Hämeenkyrö case. The emissions are calculated based on annual activities and exact technical configurations of the power plants. The technical data are entered in the FIRE (Factor Information Retrieval) software of the US EPA to obtain Emission Estimation Factors. The annual amounts of activity (in e.g. MWh/a or MSW burned/a) are then multiplied by the EF to get annual emissions from each plant. Note: This formulation leaves room for experimenting with adjustments in the power plants (e.g. if the amount of waste burned increases). Alternatively we can just use predetermined values and calculate one single annual emission figure for each plant.

(Comment: There might be ready-made plant-specific data in FRES-model.)

Subvariables:

• MSWI
• natural gas plant
• biofuel plant

References

• [Here you can find and install the FIRE software among other things]

Definition

Formula

<anacode>

Index plant:= ['MSWI','Gas','Biofuel'];

var plant_activity:= [80,60,80];

var emission_factor:= [?,?,?];

var emission:= plant_activity_gas*emission_factor;

</anacode>

Data

• MSWI: 11
• Gas: 0.1
• Biofuel:?

Unit

ton/a

Result

• MSWI: 11
• Gas: 0.1
• Biofuel:?

Baseline PM_2.5 exposure in Hämeenkyrö

Scope

Existing PM2.5 exposure in Hämeenkyrö. Annual average exposure concentration.

Description

Fine particulate matter is a mixture of solid particles and liquid droplets in the air. PM2.5 is particulate matter that is 2.5 micrometers or smaller in size. PM2.5 exposure route is inhalation and the level of exposure dependents on level of PM2.5 consentartion in the air and the length of time spent indoors and outdoors. Personal exposure of individuals can be calculated using air pollution levels from environment, which are weighted with the time-activity pattern.

Inputs = This variable is linked to PM2.5 emissions in Hämeenkyrö, PM2.5 emissions from MSWI, biofuel plant, and natural gas plant in Hämeenkyrö, population size of Hämeenkyrö, Intake fraction for PM2.5 emissions in Hämeenkyrö, Pm2.5 exposure due to MSWI in Hämeenkyrö, PM2.5 exposure-response function on population level and Health effects of dioxins and PM2.5. D↷

Exposure to ambient-generated particles (Eag) is dominated by home ventilation and are estimated from ambient concentrations (Ca) multiplied by the fraction of time spent outdoors (F_o) and the fraction of time spent indoors (F_i) modified by the particle infiltration efficiency (F_inf).(WHO, 2006.)

Mean personal daytime exposure in Helsinki were 8-11 ug/m3 (Koistinen 2002). In Europe average fairly uniform rural background concentrations were 11-13ug/m3,15-20 ug/m3 in urban background and 20-30 ug/m3 at traffic sites (WHO, 2006.). Urban US highest PM_2.5 concs 20-30 mikrog/m³, concentration in Helsinki over several years 8-11 mikrog/m³, non-urban US concs 1-6 mikrog/m³ (Koistinen 2002). Thus, small Finnish town: maybe 7 mikrog/m³?

References

• Koistinen Kimmo: Exposure of an Urban Adult Population to PM2.5. 2002. Methods, determination and sources. Publications of the National Public Health Institute A3/2002.
• WHO: Health risks of particulate matter from long-range transboundary air pollution. 2006.
• [1]

Definition

Formula

E_ag = C_a * (F_o + F_i x F_inf)

Data

Based on expert judgement.

Unit

µg/m³

Result

7

Intake fraction for PM_2.5 emissions from Hämeenkyrö

PM_2.5 exposure due to MSWI in Hämeenkyrö

Scope

Additional primary PM_2.5 exposure due to the Hämeenkyrö MSWI plant emissions. Annual average exposure concentration in Hämeenkyrö.

Description

Describes the variables affecting the personal exposure to MSWI-produced PM_2.5. Certain concentration assumed and dose calculated from it.

Data needed to evaluate the personal exposure

1. Data needed to model the PM_2.5 concentration distribution around the MSWI:
   1. The emission produced by MSWI
   2. Stack height and location of MSWI in relation to municipality
   3. Meteorological data: average (e.g. daily) temperatures, wind speeds and directions, solar radiation etc.
   4. Geographical data: vegetation, elevations, town build, lakes etc.
   5. ...
2. Data needed to convert exposure to dose:
   1. inhalable fraction of PM_2.5
   2. concentration of PM_2.5 around the person in the locations the person moves in
   3. time spent in different locations
   4. breathing rate of the person
   5. weight of the person
   6. ...

References:

• Schwela D, Morawska L, Kotzias D (Eds.) 2002. Guidelines for concentration and exposure-response measurement of fine and ultra fine particulate matter for use in epidemiological studies. WHO and JRC Expert Task Force meeting, Ispra, Italy, November 2002.
• Atmospheric dispersion model of FMI.

Definition

Formula:

D = ((IR)(P)(RF)(ET)(EF)(ED))/(BW)(AT) where

• D = dose (mg/kg.day)
• IR = inhalation rate (m³/h)
• P = particle concentration in air (mg/m³)
• RF = respirable fraction of particles (dimensioless)
• ET = exposure time (hours/day)
• EF = exposure frequency (days/year)
• ED = exposure duration (years)
• BW = body weight (kg)
• AT = averaging time (days)(Schwela ym. 2002)

For dose over a lifetime the formula can be simplified to D = (IR)(P)(RF)/BW

Assumptions:

• IR = 13 m³/d
• P = the background concentration, as the emission caused by the MSWI is distributed wide and thus diluted to negligible, thus 7 mikrog/m³/d = 0,007 mg/m³/d
• RF = 0,6
• BW = 70 kg

HOWEVER, in most dose-response studies and health effect evaluations the dose = the exposure or even the concentration in air.

Data

0.02 µg/m3

Unit

mg d ^-1 kg^-1

Result

Dispute:

• 0,0008 (based on formula)
• 0.02 µg/m3 (based on data)

PM_2.5 exposure-response function on population level

Scope

The relationship between PM_2.5 exposure and specific health effects in a given timeperiod. General population.

Description

PM_2.5 are fine particles less than 2.5 μm in diameter. Their exposure-response function is needed to determine the effect of PM_2.5 exposure on Hämeenkyrö inhabitants' health. Exposure-response function can be derived from exposure modelling, animal toxicology, small clinical or panel studies, and epidemiological studies. Exposed population can be divided into subpopulations (e.g. adults, children, infants, the elderly), and exposure is assessed per certain timeperiod (e.g. daily or annual exposure).

• Health effects related to short-term exposure
  • respiratory symptoms
  • adverse cardiovascular effects
  • increased medication usage
  • increased number of hospital admissions
  • increased mortality
• Health effects related to long-term exposure (more relevance to public health)
  • increased incidence of respiratory symptoms
  • reduction in lung function
  • increased incidence of chronic obstructive pulmonary disease (COPD)
  • reduction in life expectancy
    • increased cardiopulmonary mortality
    • increased lung cancer mortality

Sensitive subgroups: children, the elderly, individuals with heart and lung disease, individuals who are active outdoors.

References

• Health aspects of air pollution. Results from the WHO project "Systematic review of health aspects of air pollution in Europe". World Health Organization, 2004. [2]
• Pope et al. 2002. Lung cancer, cardiopulmonary mortality, and long-term exposure to fine particulate air pollution. JAMA 287(9), 1132-1141.
• Pope et al. 2004. Cardiovascular mortality and long-term exposure to particulate air pollution. Circulation (109), 71-77.
• Service Contract for Carrying out Cost-Benefit Analysis of Air Quality Related Issues, in particular in the Clean Air for Europe (CAFE) Programme. Volume 2: Health Impact Assessment. AEA Technology Environment, 2005. [3]
• [4]

Definition

Data

• 6% increase in the risk of deaths from all causes (95% CI 2-11%)
• 12% increase in the risk of death from cardiovascular diseases and diabetes (95% CI 8-15%)
• 14% increase in the risk of death from lung cancer (95% CI 4-23%)

per each 10 µg/m³ elevation in PM_2.5 air pollution

Unit

•  % change in the risk of death/health effect per each 10 µg/m³ change in PM_2.5

Result

• 6% increase in the risk of deaths from all causes (95% CI 2-11%)
• 12% increase in the risk of death from cardiovascular diseases and diabetes (95% CI 8-15%)
• 14% increase in the risk of death from lung cancer (95% CI 4-23%)

per each 10 µg/m³ elevation in PM_2.5 air pollution