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Share of residential
emissions in urban areas
Residential emissions
derive mainly from domestic heating and their share in European urban areas
strongly depend on local climate, with longer and higher emissions in cold
northern or mountain towns and shorter heating periods with less intensive fuel
combustion in Mediterranean cities.
As an example,
residential emissions for the city of Milano (Italy)
account for the 60% of annual SO2, 10% of NOx
and 13% of PM10 urban emissions (2001 INEMAR Emission Inventory).
Total emissions are
estimated with the same methods used for assessing industrial emissions, as
similar devices are involved but, obviously, domestic emissions follow seasonal
and daily cycle different from industrial ones.
In certain cases local
administrators decide the period in the year and the hours of the day when
buildings are heated, whereas in other cases citizens are free to manage
heating on their own.
Residential
emissions in air quality modelling
When dealing with air
quality modelling, residential emissions are usually considered as area
emissions distributed accordingly to the urban density.
If no other information
is available, emission height could be estimated equal to the average building
height. Depending on the scale of the simulation, it could be useful to
distinguish between at least town centre, residential zones and suburbs
assigning different emission heights, especially when dealing with large
cities.
The main problem of
residential emissions modelling is the high aggregation level of data used to
calculate air pollution. In Italy databases of firewood (ISTAT) and oil fuel (Oil
Bulletin of Ministry of Industry) consumption is available with year-nation
resolution and rarely year-region and year-province. Moreover, methane
market liberalization makes difficult locating of distribution companies
(ITALGAS, SNAM, etc.) on territory. Data are never at urban scale.
Temporal disaggregation is still more difficult
because autonomous heating doesn’t obey old law 373 (1976). In fact, this
imposed heating lighting timetable per regional zones. Now these data sets are
not available.
To disaggregate data to
urban scale these proxy variables can be used:
- Population;
- Buildings volume heated;
- Buildings thermal requirement.
Typical data source for
these proxies is ten-yearly ISTAT census.
Approximate thermal
requirement can also be so assessed: volume heated x building dispersion
parameter x day mean temperature. More complex treatment, with decreasing of
heat dispersion during heating plant stop phase due to internal temperature
decreasing, needs knowledge of building thermal capacity.
Finally, to
disaggregate annual data the following proxy variables can be used:
- Monthly proxy: to be calculated
as difference between inside (for example 20°) and outside (monthly mean)
temperature and multiplied for number of work days. Then to be normalized
to 1.
- Weekly proxy: for residential
heating a uniform proxy variable is used; for tertiary, it is appropriated
to look for specific weekly profiles, because activity diversification is
enormous (offices, shops, hospitals, etc).
- Daily proxy: to be calculated
based on mean hourly difference between inside and outside temperature and
multiplied by 0 when there is no work, by 1,1 or more when heating plant
starts to work (bigger consumption) by 1 in other hours. Then to be
normalized to 1.
Autonomous heating
specific questions adding to ISTAT census could be an economic and effective
solution.
Emissions and energy
saving
Building energy
efficiency is a major concern, as pointed in the “EcoBuilding”
Directive 2002/91/CE, and Member States are encouraged to act in order to
minimize heat and energy waste in residential buildings.
According to the
Directive, for new buildings with floor area larger than 1000 m2 and
for buildings that undergo a major renovation, the feasibility of alternative
and more efficient heating systems should be considered.
More efficient heating
systems are, for example, decentralised energy supply systems district or block
heating or cooling or heat pumps.
Furthermore, the same
Directive states that residential boilers fired by non-renewable liquid or
solid fuel of an effective rated output of 20 kW to 100 kW have to be inspected
on a regular basis whereas boilers of an effective rated output of more than
100 kW shall be inspected at least every two years.
This continuous
maintenance of boilers imposed by the directive is expected to improve domestic
heating emissions and is likely that emission factors will undergo an important
revision.
Wood burning
Wood burning is a
popular method for domestic heating, especially in northern countries.
According to the CORINAIR Guidebook the contribution of wood burning to total
emissions is thought to be insignificant (i.e. < 1%). Nevertheless, recently
a number of studies have been published showing that emission factors for PM2.5
from wood burning are strongly dependent on technology employed and that
emissions from conventional stoves and manually fed boilers are often one or
two orders of magnitude higher than emissions from newly designed boilers and
stoves. Other studies are underway and extensive revision and updating of
emission factors is expected in future years.
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