*4.3. Mobility Flow Impact Assessment*

This section analyzed the impact of mobility on the neighborhood's environmental record.

Figure 11 shows an analysis of the environmental impact on the mobility scenarios. It is seen that all environmental impact indicators are reduced from 6% to 50%. Seven indicators out of 12 are reduced by more than 20%. Thus, it was concluded that mobility has a significant impact on the neighborhood's environmental record.

"Photochemical ozone production" is reduced by more than 50% over the entire life cycle of the neighborhood. In fact, the combustion of fuels is the main source of nitrogen oxide production, which transforms into ozone under the effect of sunlight [64]. In our urban site scenario, 54% of photochemical ozone production in the use phase is avoided, by reducing the use of automobiles. Indeed, 95% of transport-related ozone production during the operational phase is avoided in this scenario. Another photochemical ozone production station is waste management. The previous figure (Figure 11) shows the same observation with the "greenhouse gases". Indeed, a decrease of 40% of the emissions is observed on the total life cycle of the neighborhood, thanks to a decrease of 93% transport emissions during the use phase. On the other hand, it is interesting to note that "acidification" has also been strongly impacted by the suppression of automobile use. We have observed a 35% decrease in this impact indicator over the entire life cycle of the neighborhood. It is the same for "depletion of abiotic resources" and "damage to health", which saw their score reduced by 34% and 32%, respectively. Indeed, much less fuel and fossil resources are consumed and the pollution responsible for many health problems is also greatly reduced.

**Figure 11.** Comparative diagram of the environmental impacts of mobility scenarios (functional unit: entire neighborhood). For example, mobility and the use of personal vehicles to carry out daily commuting distances have a huge impact on the neighborhood's environmental record. Climate impact indicators are the most affected. It is possible to reduce them by half. The cumulative demand for energy, acidification, depletion of biotic resources and damage to health can be reduced by a third, thanks to a mobility scenario.

Decreasing the use of cars can create huge savings in energy. Public transport uses the energy contained in fuels in a more efficient and rational manner. Thus, the cumulative energy demand is reduced by 28%. It is also shown that there has been a 23% decrease in damage to biodiversity, 17% in eutrophication, 15% in radioactive waste, 13% in odors and 6% in waste produced.

Some data are showed on Table 7.



(1) Greenhouse gas; (2) acidification; (3) cumulative energy demand; (4) waste water; (5) waste products; (6) depletion of abiotic resource; (7) eutrophication; (8) photochemical ozone production; (9) biodiversity damage; (10) radioactivity waste; (11) health damage; (12) odor.

Detailed responses on the urban mobility are showed in Table 8.



(1) Greenhouse gas; (2) acidification; (3) cumulative energy demand; (4) waste water; (5) waste products; (6) depletion of abiotic resource; (7) eutrophication; (8) photochemical ozone production; (9) biodiversity damage; (10) radioactivity waste; (11) health damage; (12) odor.

### *4.4. Density Impact Assessment*

Table 9 estimates the heating requirements of the various buildings in the study area.

**Table 9.** Heating requirements of the different neighborhood buildings in the basic and high configuration of a floor.


Analysis of this data showed that the heating requirements with an additional floor dropped slightly. We thought that the additional shading created should act as solar masks, which would reduce solar gain and increase heating needs. However, it seemed that the increase in compactness caused by the rise of the buildings was more impacting. Figure 12 shows the comparative diagram of the environmental impacts of the scenarios.

In Figure 12a, the results are expressed on the basis of a functional unit encompassing the entire neighborhood. This is because the indicator scores had all increased in fairly similar proportions, from about 25% to 30%. Indeed, the share of the indicators related to the buildings was modified, but not that related to the district, which remained unchanged. This functional unit did not allow us to draw any interesting conclusions. This is why we are going to translate the results of the study into the "Occupant" functional unit, to be able to compare per capita impacts in both configurations.

As shown in Figure 12b, if we compare the environmental indicators by reporting them to the number of inhabitants, we notice that the high-rise one-story has a better environmental performance. The odor indicator is reduced by 26% and eutrophication by 19%. The other ten indicators are reduced between 11% and 15%. Indeed, even the site welcomes more occupants and the consumption by these added to the initial consumption, all impacts from the site itself and public spaces remain unchanged. Thus, the built surface is more profitable.

In the case of an increase in density built by adding buildings to the site (Figure 13a), the results were not as favorable as in the previous case. In fact, apart from odors, radioactive waste and eutrophication, the scores of which decreased by 21%, 3% and 10%, respectively, the other indicators had increased. They all earned between 1% and 5%. Indeed, we did not benefit here from a gain in compactness and we did not pool the networks. In addition, the construction of new buildings was greener in materials and energy than the rise of a floor. The analysis of Figure 13b showed that densifying the neighborhood vertically was more remarkable environmentally. The impact on the total LCA of the district was much more pronounced than during horizontal densification, for which the assessment was mixed.

**Figure 12.** Comparative diagram of the environmental impacts of: (**a**) "Initial" and "Vertical Density" (functional unit: occupant); and (**b**) "Initial" and "Density +" scenarios (functional unit: entire neighborhood).

**Figure 13.** Comparative diagram of the environmental impacts of the "Initial" and "Horizontal Density" scenarios (**a**); and "Initial", "Horizontal Density" and "Vertical Density" (functional unit: occupant) (**b**).

Some results are showed on the Table 10.


**Table 10.** Vertical and horizontal density scenarios.

(1) Greenhouse gas; (2) acidification; (3) cumulative energy demand; (4) waste water; (5) waste products; (6) depletion of abiotic resource; (7) eutrophication; (8) photochemical ozone production; (9) biodiversity damage; (10) radioactivity waste; (11) health damage; (12) odor.

#### *4.5. Impact of Renewable Energy Uses*

Taking into account the dynamic thermal simulation, the consumption and electricity production were calculated. For all buildings, production exceeded consumption throughout the year, except for the months of December and January, where the installation covered 45% and 75% of the consumption, respectively. In fact, the buildings consumed, on an average, 12 kWh/m2 of electricity per year. These results were consistent with the Belgian averages for dwellings that did not heat up with electricity. Photovoltaic panels produced an average of 26 kWh/m<sup>2</sup> over the year. Thus, except for the months of January and December, no electrical energy was drawn from the Belgian network. The effects on the LCA of the neighborhood are presented in Figure 14.

Of all the configurations studied, the one comprising the addition of photovoltaic panels is the one that produces the most heterogeneous results on the neighborhood's LCA. Indeed, some indicators are greatly reduced, while others see their score increase considerably.

The most affected impact is the production of radioactive waste. Over the entire life cycle, the production of radioactive waste is reduced by 102%. Indeed, even if this production of waste increases during the construction (9%) and renovation (1893%) phases, because of the impact of the manufacture of panels, the use phase makes up for this delay. The enormous increase in the usage phase score is explained by the fact that the panels are changed every 20 years and that in the previous scenario, the production of radioactive waste of this phase was insignificant. That being said, the production of radioactive waste during the use phase decreases by 127%. This is explained by the fact that production is higher than consumption. As a result, not only is the construction and maintenance of the system offset, but the production of radioactive waste from the use phase is also eliminated. Moreover, it allows other homes to benefit from the clean energy produced. Thus, our neighborhood reduces the production of radioactive waste from other neighborhoods, which gives a negative score for this indicator.

The second-most impacted indicator is the cumulative demand for energy. The total energy needed by the neighborhood to operate over its entire life cycle is reduced by 37%. Once again, the construction and renovation phases are negatively impacted. The construction phase saw its energy consumption increase by 75% and the renovation phase by 978%, due to the manufacture of the panels. However, the occupation phase saw its demand decrease by 47%.

The depletion of abiotic resources and the greenhouse effect also decreased by 14% and 12%, respectively, over the entire life cycle. The evolution of the indicators once again followed the same pattern: a significant increase in the construction and renovation phases. However, once again these increases are offset by a reduction in the environmental impact of the use phase, the most impactful phase of the life cycle. We observed a 25% drop in greenhouse gas emissions over this phase and a 26% decrease in the depletion of the abiotic resources.

Conversely, some indicators see their score increase. This is the case of the production of waste. The renovation phase saw its waste production increase by 742%. In fact, 4400 m<sup>2</sup> of the panel area had to be replaced thrice over the neighborhood's life cycle and in addition included their initial installation. The 15% decrease in waste production during the use phase did not make up for this increase. As a result, the neighborhood's total waste generation over its entire life cycle was up by 21% (Figure 14). Some results are showed on the Table 11.


**Table 11.** Impact of renewable energy.

(1) Greenhouse gas; (2) acidification; (3) cumulative energy demand; (4) waste water; (5) waste products; (6) depletion of abiotic resource; (7) eutrophication; (8) photochemical ozone production; (9) biodiversity damage; (10) radioactivity waste; (11) health damage; (12) odor.

Finally, paradoxically, the damage done to biodiversity is also increasing. It is again the manufacture and the replacement of the panels which is in question. The impact of the construction phase increases by 229% and that of the renovation phase by 849%. The 6% drop in impact during the use phase does not compensate for these losses. Thus, over the cycle, the damage to biodiversity increases by 18%.

### *4.6. Global Analysis of All the Scenarios*

In order to classify the different scenarios and define the design parameters to take into account their priority, we calculated the sum of the variations, as a percentage of all the indicators compared to the initial scenario. We chose to apply no weighting but will remove the indicator "odors", which distorts the results by its important variations. Table 12 shows some obtained results.




It was noted by analyzing this table that mobility has an impact of 282% of the cumulative decrease on all indicators: vertical density (163%), renewable energies (138%), rainwater harvesting (76%), soil permeability (11%), orientation (4%) and horizontal density (−10%).
