We carried out the environmental study of a sustainable neighborhood located in Belgium (Europe) over 100 years, and then, we adopted the same neighborhood design in 149 other countries, while keeping four parameters specific to each country: energy mix, local climate, building materials, and occupants’ mobility. In addition, we calculated the costs related to two environmental impacts: acidification and eutrophication. Finally, we changed some building materials to evaluate their impacts on the eutrophication and acidification costs.
Overall, this research is constituted of five important steps (1) choice and neighbourhood design;
(2) LCA of the selected neighbourhood in Belgium; (3) modelling the same neighbourhood in 149 other countries with adaptation of the four local parameters and life cycle assessment; (4) study of the cost of (AP and EP); and (5) applying one scenario for mitigating some environmental impacts.
The following sections (2.1 to 2.6) describe neighborhood case study, the countries, and databases for this research, the analysis of data and the environmental indicators, the simulation of LCA for each country, the method of calculating the environmental cost, and the neighbourhood improvement scenario tested.
2.1. Initial analysis of the eco-neighbourhood
This neighborhood is initially located in the Liege city in Belgium, and the same design is adapted in 149 countries represented in the world. The full description of this sustainable neighbourhood is found in 38.
In this research, only the residential section of the neighbourhood was studied. The residential eco-neighbourhood consists of 35000m2comprising 10000m2of roads, residence around 219 inhabitants, studied on a period of 100 years16-17.
2.2. Design of the same eco-neighbourhood in other countries
The same eco-neighborhood is built in capitals located in other 149 countries. The choice of the capital, for representing each country was not random; indeed, in the most of these countries, the capital was considered as the most populated region of the country, with the highest environmental pollution and energy consumption. Thee\population density has a significant influence on all the environmental impacts.
We simultaneously applied four parameters for adapting this neighbourhood in each country:the energy mix of each country, the local climate of each country, typical building materials used in each country and occupants’ mobility.
The International Energy Agency (IEA) database18 and the Energy Information System of each country were used to gather the information on the energy mix and electricity mix. Using the Pleiades-ACV software, it was possible to freely select the different energy sources (in %), such as nuclear, fuel, coal, gas and renewable energy; then, assigning their corresponding values.
The information on the local climate of each country was evaluated with the most recent version of Meteonorm (7.3.1) which contains around of 8,325 weather stations19.
The information on the construction materials was evaluated on the basis of 2018-2020 standard thermal regulation of each country, but also from information issue to the
UN-habitat as well as based on literature reviews (for some African and Asian countries, without recent building standards). Regarding inhabitant mobility, the data was based on a different rate of occupants commuting daily: 80% in developed countries (USA, Japan, Germany, France, UK, etc.) and 50% in developing countries (Cameroon, Madagascar, Haiti, Thailand, etc.). The distanceof the weekly commute between home and trade is 1km; distance from the public transport network is 500m, distance from the daily commute to work is on average between 5km and 10km. Presence of bike path and public transportation such as bus, subway, and tram.
2.3. Environmental data
The data used in this study is based on the ECOINVENT (version 2.2, 2012). Some details were showed in20.The ECOINVENT Centre is known as one of leaders in environmental sustainability data21.
In this study, we assessed two (02) environmental impacts of the studied neighborhood:
Acidification (PA); eutrophication (PE) 22-24.
These different environmental indicators are presented in Table1.
Table1. Average LCA results of the eco-neighbourhood (in Liege city) in terms of calculated impacts
Environmental Indicator(CEN)
|
Unit
|
Yearly value
|
Value(per m2/year)
|
Acidification
|
Kg SO2 eq.
|
860.92
|
0.09
|
Eutrophication
|
kg(PO4)3- eq
|
486.21
|
0.05
|
2.4. LCA Simulation software
In this study, we used a combination of all the new IZUBA energy software.Indeed, the interface of the most recent version (Pleiades-ACV software, version 4.19.1.0)is divided into 6 modules: Library, Modeller(called ALCYONE for the old software version), BIM, Editor(called COMFIE-PLEIADES),Results, and ACV (nova-EQUER). Modeler, ALCYONE software, has as main role to draw the building , solar masks, the zoning… 25.
We used the software essentially made up of five components: Generals (Construction Data, Project Library, LCA Association, Weather and Horizon); Plan; 3D; Calculation. Some physical characteristics of the studied neighbourhood are shown in table2 .
Table 2. Wall Composition
element
|
component
|
E(cm)
|
ρ*e(kg/m2)
|
λ (w/m.k)
|
R(m2.K/W)
|
Coated exterior wall
|
exterior coating
|
1.5
|
26.0
|
1.150
|
0.01
|
Expanded polystyrene
|
32.0
|
8.0
|
0.032
|
10.0
|
Limestone silico block
|
15.0
|
270.0
|
0.136
|
1.10
|
ceiling
|
1.3
|
11.0
|
0.325
|
0.04
|
Barded outer wall
|
Cement fiber cladding
|
2.0
|
36.0
|
0.950
|
0.02
|
Air blade
|
1.2
|
0.0
|
0.080
|
0.15
|
polyurethane
|
24.0
|
7.0
|
0.025
|
9.60
|
Limestone silico block
|
15.0
|
27.0
|
0.136
|
1.10
|
ceiling
|
1.3
|
11.0
|
0.325
|
0.04
|
High floor
|
PDM sealing
|
-
|
-
|
-
|
-
|
Polyurethane
|
40.0
|
12
|
0.025
|
16.00
|
Concrete slab
|
25.0
|
325
|
1.389
|
0.18
|
Ceiling
|
1.3
|
11
|
0.325
|
0.04
|
Intermediate floor
|
Chappe + coating
|
8.0
|
144
|
0.700
|
0.11
|
polyurethane
|
1.0
|
0
|
0.030
|
0.33
|
Aerated concrete
|
8.0
|
48
|
0.210
|
0.38
|
Concrete slab
|
25.0
|
325
|
1.389
|
0.18
|
Ceiling
|
1.3
|
11
|
0.325
|
0.04
|
Low floor
|
Chappe + coating
|
8.0
|
144
|
0.700
|
0.11
|
polyurethane
|
25.0
|
8
|
0.025
|
10.00
|
Concrete slab
|
25.0
|
575
|
1.750
|
0.14
|
Internal wall
|
Ceiling
|
1.3
|
11
|
0.325
|
0.04
|
Limestone silico block
|
15.0
|
270
|
0.136
|
1.1
|
Expanded polystyrene
|
4.0
|
1
|
0.032
|
1.25
|
Limestone silico block
|
15.0
|
270
|
0.136
|
1.10
|
ceiling
|
1.3
|
11
|
0.325
|
0.04
|
Editor, COMFIE-PLEIADES software is designed for making the thermel simulation of buildings25-26. This neighbourhood was regrouped in 10 blocks with heating requirements shown in Table 3.
Table 3.Heating requirements of different neighbourhood buildings in the basic and high configuration of a floor.
|
Heating requirements(kWh/m2.year)
|
Buildings
|
Initial situation
|
First floor
|
A3
|
15
|
14
|
B2
|
12
|
12
|
B3
|
14
|
13
|
D1
|
19
|
20
|
D2
|
20
|
20
|
D3
|
20
|
21
|
D4
|
18
|
19
|
C1
|
12
|
11
|
C2
|
13
|
12
|
C3
|
13
|
11
|
Mean
|
15.6
|
15.3
|
ACV module,nova-EQUER, is required to assessment the different environmental impacts26.This module is essentially made up of four datasets as follows:
(i) Building/neighborhood data
The original data come from the Pleiades, this thermal/ACV coupling allows to automatically recover all the characteristics of the building: data on the structure of the building and the elements involved in thermal calculations and/or energy consumption. These data are then supplemented with specific LCA data: all elements that are not part of the thermal study; general and administrative data concerning the current operation and the building or neighbourhood; specific or adjusted seizures for energy, water, waste, and transport.
(ii) Software organization
The Pleiades ACV interface is structured around five axes:
- Library: Environmental Impact Data Libraries, General Calculation Characteristics. In this research, we fixed: surplus of materials at the site 5%, default typical service life of families of element: interior and exterior doors 30 years, global equipment 20 years, glazing 30 years, coating 10 years; distance of transport: site of production towards building site 100km, site towards inert discharge finally of life: 20km.
- Project: Project management with structure data for any type of project and use of the building with the EQUER engine. In this research, we fixed: Loss of electrical network from 9% to 40% according to country. Water system yield: 80%, hot water consumption 40L/day/person; cold water consumption 100L/day/person; Selective collection of glass: yes; sorted glass: 90%; incinerated waste 40%; recovery to incineration: yes; substituted energy: gas or fuel oil (depending on the country); recovery yield: 80%; selective collection of paper: yes; sorted paper: 80%; lane between the site and the garbage dump: 20km; distance from the site to the incinerator: 10km; distance from the site to the recycling center: 100km.
- Experimentation: Specific seizures PEBN E+C-;
- Calculation and results: Start the calculations and consult the results.
- Neighbourhood: neighbourhood Management.
The acidification potential of soils and water is evaluated by the potential of H+ ion. It is also sometimes evaluated by the ability to release an equivalent amount of SO2.The indicator is calculated as follows:
![](https://myfiles.space/user_files/83062_751fab6dfaef2446/83062_custom_files/img1628494851.png)
With mi: mass of (i) element emitted in kg. The eutrophication potential is:
![](https://myfiles.space/user_files/83062_751fab6dfaef2446/83062_custom_files/img1628494866.png)
With mi: quantity of substance i released into the air, water or soil in kg. The indicator is therefore expressed in kg of equivalents (PO4)2-.
2.5. Environmental cost
The acidification and eutrophication quantities were translated into environmental costs, which make them comparable to each other. The cost calculation is based on the method Monetization of the (Global method monetize) 27-29. The tables below show the conversion values of the environmental impacts of environmental costs.
Table4 .Monetary indicators for CEN indicators30.
Environmental Indicator(CEN)
|
Unit
|
Belgium( € /unit )
|
Rest of World( € /unit
|
Acidification
|
kg SO2 eq.
|
1.01
|
0.17
|
Eutrophication
|
kg(PO4)3- eq
|
40.00
|
8
|
Table5.The average environmental cost of each phase of the eco-neighbourhood in Belgium.
Environmental impacts
|
Year
|
€ /unit
|
Construction
|
Operation
|
Maintenance
|
Dismantling
|
Total cost
|
Acidification
|
2030
|
€/dwelling
|
448.2
|
607.1
|
66.3
|
8.8
|
1130.4
|
€/m2
|
0.5
|
0.5
|
0.1
|
0
|
1.2
|
€/inhabitant
|
20.4
|
27.6
|
3.1
|
0.4
|
51.4
|
2050
|
€/dwelling
|
1137.8
|
1540.9
|
168.4
|
22.4
|
1620.5
|
€/m2
|
1.4
|
1.7
|
0.4
|
0
|
3.2
|
€/inhabitant
|
51.7
|
65.5
|
|
7.6
|
130.4
|
Eutrophication
|
2030
|
€/dwelling
|
8850.9
|
15272.4
|
1089.9
|
69.7
|
25282.9
|
€/m2
|
10.4
|
15.6
|
0
|
0
|
26.0
|
€/inhabitant
|
402.5
|
694.2
|
49.5
|
3.2
|
1149.2
|
2050
|
€/dwelling
|
22467.7
|
38768.4
|
2766.7
|
176.9
|
64179.7
|
€/m2
|
26.4
|
39.6
|
0
|
0
|
66.0
|
€/inhabitant
|
1021.3
|
1762.2
|
125.8
|
8.1
|
2917.3
|
2.6. Mitigation of impacts
We also examined a scenario to reduce both environmentals costs. The sustainable strategy involved using photovoltaic panels combined with mobility.
In the reference scenario, the total electricity was supplied from the central electricity grid of each country. In this new configuration, we have a photovoltaic system on all the roofs on the site.Installed photovoltaic panels cover a total area of 580 m2that can yield a peak power of 82.8kW. The residential buildings use energy only for light and HVAC systems. The installation will consist of monocrystalline photovoltaic solar panels. They will be oriented toward the south in the northern hemisphere and toward the north in the southern hemisphere; they will also be inclined at 37° for the countries located in the temperate and cold zones and inclined at 45° for the countries located in the hot zone. This allows us to have optimal inclination in all the countries. We have thenperformed the thermal simulation of each building and completed the final LCA of the neighbourhood.
We have also examined the impact of mobility on the neighborhood's environmental record. In our basic scenario, we considered an important use of the car for daily commuting. We recapitulated the mobility hypotheses: (i) Initial scenario: 80% of the occupants commute daily in developed countries and 50% of the occupants commute daily in developing countries; the distance from home to work of 5-10 km is carried out daily by car; the distance from home to shops of 1 km is done weekly by car. (ii) new scenario or "Urban Site" scenario: 100% of the occupants make the trip daily in all the countries; the distance from home to work of 2-5 km is done daily by bus; the distance from home to shops of 0.5-1km is carried out weekly by bike or on foot. Finally, both scenarios have been combined to obtain a mixed scenario having a significant effect on the three environmental impacts assessment.