The ten scenarios were assessed using the performance indicators described in Section III and that were selected based on the Pilot Project's goals described in Section I. This section summarizes the overall performance of the scenarios and provides details on the comparative results for climate change mitigation and adaptation and transit accessibility, which reflect the primary goals of the Pilot Project. Details and graphs for the indicators representing the impact of development on other areas of interest can be found in the Technical Scenario Report.
Overall, the performance of the various scenarios demonstrated tradeoffs between the mitigation and adaptation indicators, especially in terms of intensifying development in existing commercial and residential areas that are vulnerable to SLR, and between indicators representing other land use interests. In comparing the scenarios, it is important to note the context in which each set - preliminary, workshop, and refined - were developed, including consideration of realistic expectations, feasibility constraints, and vetting by local entities. For the workshop, but even more so for the refined scenario, the goal was to minimize negative impacts and maximize positive impacts, as measured by each of the indicators, of development and transit placement.
The performance of all scenarios in reducing GHG emissions was compared to that of the Trend scenario as a baseline and was solely based on changes in VMT and not on changes in technology, fuel, or transportation mode. Therefore, the percentage change in VMT was the same as the percentage change in GHG emissions for each scenario. These results are shown in Figure 15.
The Dispersed-Standard scenario performed closest to the Trend scenario, improving by less than one percent, while the Dispersed-Enhanced scenario performed slightly better. The other scenarios resulted in a five to eight percent improvement (decrease) in VMT and GHG emissions, with the two Targeted scenarios and two of the Workshop scenarios performing best. The Targeted scenarios were expected to perform well in VMT and GHG emissions reduction, since they were designed with the purpose of maximizing the performance indicator results without a full account of local considerations. The Workshop scenarios from breakout groups A and C performed well, a result of the proactive, intense development pattern and high number of additional transit stops pursued by those participants.
The Refined scenario did not perform as well on this measure, primarily due to the consideration of feasibility constraints that resulted from consultation with local entities, including the Cape Cod Regional Transit Authority, on realistic and vetted future investments. This differed from the Targeted scenario's limited consideration of adaptation implications and the Workshop scenarios' lack of constraints.
Figure 15: Percentage change from Trend scenario in regional VMT and GHG emissions. Source: PlaceMatters and Placeways.
Figure 16 illustrates how each scenario performed in terms of the percentage of new population placed in areas that are potentially vulnerable to SLR. The Targeted-Standard scenario resulted in the highest percentage of new population in vulnerable areas, reflecting that most of the existing high density residential and commercial centers on Cape Cod are located in vulnerable areas. Most of the Workshop scenarios as well as the Refined scenario placed fewer population in vulnerable areas than the Trend scenario. Similar to its performance with GHG emissions, the Refined scenario did not perform as well as the Workshop scenarios, reflecting the additional tradeoffs that stakeholders considered in refining the scenario in the months following the workshop.
Figure 16: Percentage of New Population in Vulnerable Areas. Source: PlaceMatters and Placeways.
Table 3 shows the percentage of new growth placed in areas with identified constraints. Overall, the Refined scenario performed best for nearly all categories, with the exception of percentage of land area developed from previously undeveloped or rural and the percentage of new population in water resource and wellhead protection areas. The poor performance of the latter seems to indicate that there may be overlap between sensitive water resource areas and desired development locations identified through this exercise and that, as discussed in Section IV, water constraints should be considered to a greater extent in future planning efforts. However, it should be noted that the Refined scenario performed well in terms of having only a small percentage of new population in water resource and wellhead in low density areas. In contrast to the GHG emissions and vulnerability indicators, the Refined scenario performed better than the Workshop scenarios in most of the resource preservation indicators, reflecting Cape Cod's prioritization of conservation areas over climate change mitigation and adaptation considerations in the short term, as indicated by the poll conducted at the workshop.
Table 3: Indicator results for preservation of natural/existing ecosystems and impact on other areas. One asterisk (*) indicates the best performing scenario while two asterisks (**) indicate the lowest performing scenario for each indicator.
|Indicator||Preliminary Scenarios||Workshop Breakout Group Scenarios||Refined Scenario|
|Percentage of new population in critical habitat areas||49.6**||49.6**||20.9||25.7||40.6||31.6||20.7||14.2*|
|Percentage land area developed (from previously undeveloped or rural)||33.3**||29.9||0.0*||1.9||1.7||0.0*||2.8||4.5|
|Percentage of new population in undeveloped or rural lands||41.1**||36.4||31.1||15.1||35.7||28.6||15.6||12.4*|
|Percentage of new population in other high priority conservation areas||64.4**||62.1||31.4||31.5||54.0||38.2||29.9||25.2*|
|Percentage of new population in historic preservation areas||4.8||5.1||6.4||8.0**||0.4||0.2||1.7||0.1*|
|Percentage of new population in water resource areas||47.9**||41.4||39.9||21.5*||52.4||43.1||32.0||47.8|
|Percentage of new population in water resource areas in low density areas (less than three dwelling units per acre)||41.1**||36.4||31.1||15.1||35.7||28.6||15.6||12.4*|
|Percentage of new population in wellhead protection areas||33.4||30.1||36.4||15.5*||32.6||32.9||28.1||42.0**|
|Percentage of new population in wellhead protection areas in low density areas (less than three dwelling units per acre)||33.3**||29.9||0.0*||1.9||1.7||0.0*||2.8||4.5|
The indicators for transit accessibility measured the percentage of new jobs and new homes within a mile of proposed passenger rail stops and/or a quarter mile from existing and planned bus stops. As mentioned above, two additional scenarios were included in these results (Dispersed - Enhanced, and Targeted - Enhanced) because their assumptions had impacts on transit access. As shown in Figure 17 and Figure 18, the Enhanced scenarios resulted in higher access than their Standard equivalents for Dispersed and Targeted respectively, as expected. The Refined scenario did not perform as well as either of the Enhanced scenarios or the Targeted-Standard scenario, but did perform better than the Dispersed-Standard and Trend scenarios. It is likely that as additional planned improvements in the transit system are added to the model - and as expected mode shift, ridership, and the impact of service frequency increases are better captured - the Refined scenario will improve in performance.
Figure 17: Percentage of new population served by transit
Figure 18: Percentage of new jobs served by transit.
The performance of the scenarios underscores the value of the scenario planning process as well as the tradeoffs that the town and regional planners of Cape Cod will need to consider in addressing climate change adaptation and mitigation through land use planning. For instance, the Refined scenario's reduction of VMT and the associated GHG emissions fell short of that achieved by other scenarios due to several likely reasons. First, as discussed earlier, stakeholders avoided further development of certain existing high-density areas that were identified as vulnerable. This decision likely improved the Refined scenario's performance in the vulnerable areas indicator at the expense of a more modest reduction of VMT and GHG emissions. Second, the Refined scenario was constrained by coordination with pre-existing plans, by feasibility considerations such as cost and vetting by the responsible local jurisdiction, and by consultation with local entities, including the Cape Cod Regional Transit Authority, on realistic and vetted future investments. These constraints differed significantly from the unrestrained exercise conducted during the workshop.
As the regional and local partners use this model in the future, they will be able to update plans for transit investments and development and measure the projected impact on VMT and GHG emissions. In the future, water resources can also be considered in more detail, and the importance of natural resource and ecosystem preservation can continue to be preserved, reflecting the top priorities indicated in the poll conducted at the workshop.