Since we can estimate the relative percentages of these unit types across our three scenarios, we could then calculate approximate energy use for the new households in each scenario. We adjusted for assumed trends in household energy use and efficiency within each scenario, using the 1985 to 2005 statewide reduction of approximately 15 percent per household as a baseline for the A2 scenario .Under the A2 story line development is dispersed in and around existing urban areas . The new development footprint is highest at over 14,000 acres. The urbanization pattern reflects an urban sprawl pattern of growth that is typical today and likely to continue into the future unless there are changes to planning policies and a reduction in population growth. Dunnigan, an area of the county where growth is currently being proposed, receives new development under A2. The B1 story line has urbanization that is more attracted to existing urban features. Under B1, growth is less dispersed and more concentrated in and around the urban sphere of influence; new development takes up over six thousand acres . Due to the AB32+ story line’s strict infill planning policy and mask on non‐urban lands, almost all new development occurs within existing city boundaries . No development occurs in West Sacramento,hydroponic nft channel which is within the one‐hundred‐year floodplain and was thus masked from development within this scenario.
The urbanization policy reflected in the UPlan variables and the amount of population growth under each story line creates a unique pattern and footprint of development. AB32+ is by far the most compact, has the smallest urban footprint, and consumes the least amount of crop‐ and irrigated land, as well as non‐irrigated grazed lands. The story lines vary in the amount and type of new land uses . Under the A2 story line, for example, residential low, commercial low, and residential very low categories take up 9,081 , 2,687 , and 1,441 acres , respectively, by 2050. In this story line, residential medium‐density development takes up a larger percentage of newly developed land area, and in the AB32+ story line, most development is either residential medium or residential high density. One of the most striking findings is just how little land is required to house future populations at these higher densities. The B1 and AB32+ scenarios require 44 percent and 7 percent of the urbanized land of the A2 scenario respectively. Even holding population increase constant at B1 levels, these scenarios use 63 percent and 38 percent of the land of the A2 scenario; most or all of it within existing urban areas.A detailed GIS map of cropland in Yolo County for 2008 was overlaid onto UPlan results to show the crop acreage lost to urban growth under each scenario. The acreages of crops lost to development varied greatly among the three story lines, ranging from 10,562 in A2 to 3,363 in B1 to 23 in AB32+ . These results reflect the lower total population growth and stricter urbanization policies in the B1 and AB32+ story lines. Alfalfa, processing tomatoes, and pasture lands had the highest acreage loss under the A2 story line. The same three crops were most affected under the B1 story line but impacts were higher on processing tomatoes than alfalfa. In the A2 story line, the new development footprint resulted in about 3 percent of irrigated crop land being lost in the county, while in the B1 story line 1 percent was lost, and for AB32+, only 0.04 percent was lost.
Floodplains were more likely to support urbanization under the A2 story line compared to B1 . The B1 story line assumed much more discouragement to wetland and floodplain urbanization, both for protection of constructed units, and for environmental benefits. Urbanization on wetlands under frequent inundation was unlikely in either scenario, partly because flooding risk discourages building construction. Vernal pools, a landform that supports many endemic species, were more vulnerable to urbanization under the A2 story line . The wetland area is currently increasing in Yolo County due to creation of freshwater wetlands for flood conveyance for the high flows from several northern California waterways to the Sacramento‐San Joaquin River Delta, and for wildlife habitat . Wetland conversion can indeed be a “Best Management Practice” in some circumstances, and there can be additional ecosystem services provided by specific management of wetlands. But the loss of agricultural land is still a significant concern for the viability of agricultural operations, markets, and related industries in the county. The Williamson Act is a California law that reduces property taxes to owners of farmland and open‐space land in exchange for a ten‐year agreement that the land will not be developed. Under the A2 story line, farmers would be more likely release their holdings in the Williamson Act. The A2 outcome was nearly four times greater losses compared to B1, whereas AB32+ assumed no change in Williamson Act . Not surprisingly, transportation‐related GHG emissions from new development vary greatly across the three story lines . As noted above, this difference is a function of assumptions about reduced driving by residents of infill development compared with development on previously unbuilt lands at the urban fringe, about improved vehicle fuel efficiency under the lower GHG emission scenarios, and about different rates of population growth in the three scenarios.
Under the A2 scenario, transportation emissions related to new development are approximately 789,229 metric tons CO2e annually. The B1 scenario produces similar emissions of 254,243 MT CO2e, compared to 63,244 MT CO2e in the AB 32 scenario. .Residential energy‐related greenhouse gas emissions also show strong differences among the three scenarios, due to the lower energy usage of multifamily units compared with single‐ family homes, as well as other assumptions about different efficiency improvements and electric portfolio composition between the scenarios. Annual electricity‐related emissions from new development built in the 2010 to 2050 time period range from 132,104 MT CO2e in the A2 scenario to 60,548 MT CO2e in the B1 scenario, and just 11,536 MT CO2e in the AB32+ scenario. Holding population constant across the three scenarios diminishes differences only slightly; holding assumptions constant about efficiency improvements and changes to utility portfolio mix still yields substantial differences solely due to the different mix of dwellings between infill‐heavy scenarios and the greater urban sprawl in the A2 scenario. Greenhouse gas emissions from residential gas consumption are slightly higher than for electricity consumption, in part because electricity will become cleaner over time as utilities develop renewable production sources; GHG emissions from gas will remain the same per unit of energy. . Annual gas‐related GHG emissions from new development built in the 2010–2050 time period range from 196,414 MT CO2e in the A2 scenario to 84,384 MT CO2e in the B1 scenario to 15,259 MT CO2e in the AB32+ scenario . Many of these reductions result from different assumptions about improved energy efficiency; if those assumptions are held constant at the A2 level, emissions still decline from 196,414 to 147,673 and 106,813 MT CO2e because of different mixes of dwelling types. Thus, GHG emissions from residential energy use, as from transportation, will be much greater if urban development sprawls onto agricultural land in the countryside. Overall, our three scenarios vary dramatically in their GHG emissions from new urbanization . AB32+ produces much lower GHG emissions from residential development— approximately 8 percent of the emissions in A2, or about 14 percent with population held constant. The B1 scenario also produces substantial GHG savings—about 36 percent and 50 percent of those in A2 under the two different population levels. The strong implication is that preserving agricultural land from development is essential if the county is to stabilize and reduce its GHG emissions.
The preceding analysis shows that a strong growth management framework for Yolo County, by channeling much or all future development into existing urban areas rather than onto agricultural lands, would have significant value in terms of preserving agricultural land,nft growing system and extraordinary value in terms of reducing the county’s GHG emissions. Agriculture plays a modest role in Yolo County’s GHG emissions; farming occupies approximately 87 percent of the land area, but is estimated to produce only 14 percent of total county‐wide GHG emissions in 1990 . Detailed analysis of all urban GHG emissions in the county are not yet available, yet preliminary estimates suggest that the MT of CO2e per hectare of agricultural lands are >70 times less than cities and towns .The A2 scenario produces a relatively dispersed pattern of growth that consumes more farmland, although it is still a small percentage of the county’s agricultural acreage. This would be likely to occur in a pattern often referred to as “leapfrog development,” in which developers build on separated parcels across the agricultural landscape. Such development would occur primarily between and around the towns of Davis and Woodland. Also, to the extent that urbanization generally makes agriculture more difficult , the A2 scenario could amplify operational or economic hardships due to climate change. Higher‐quality soils are present in the floodplain region near the towns of Davis and Woodland, and support the crops with the highest income per acre . This helps explains why leapfrog development in the A2 scenario resulted in the greatest loss of land classified as either excellent or good soils with the Storie Index. Previous UPlan modeling showed, however, that protecting only prime agricultural land in California’s San Joaquin Valley resulted in greater use of less desirable land, and more urban sprawl than prioritizing compact growth . Beardsley et al. also used UPlan to show that compact growth was the most effective way to preserve biologically valuable land in the Central Valley. Such effects would be somewhat less pronounced in the B1 scenario, although our model shows leapfrog development was still widespread in the same locations, just at lower intensities. The AB32+ scenario prohibits most urbanization of current agricultural land, and so these effects would be essentially nonexistent. In a previous survey, growers with land in the Williamson Act tax relief program were more likely to be concerned about climate change . Individuals who are most committed to agricultural preservation are more likely to recognize the need for options to adapt to climate change, especially to decreased water availability .By fragmenting the landscape in the vernal pools and floodplain, urbanization in the A2 scenario could work against the provision of ecosystem services related to water quality, biodiversity conservation, open space, and its aesthetic and recreational value. By adopting a more “business as usual” story line than B1, the A2 scenario would also be less conducive to investment in new programs to restore wetlands waterways, riparian vegetation, and hedgerows in agricultural landscapes, a strategy that could increase these types of ecosystem services as well as carbon sequestration .Urbanized areas with a large percentage of their land covered by asphalt and other hard surfaces absorb solar radiation and reach ambient temperatures well above the surrounding areas . Road, roof, and parking surfaces within urban areas have been shown to lead to increased speed and volume of storm water runoff and lower groundwater recharge . In a nationwide assessment, the large increase in population and assumption of dispersed development under the A2 scenario results in about 10 percent increase in the surface area of impervious surfaces compared to the B1 story line, and at least one‐third of the nation’s wetlands will be affected by 2050 in both scenarios . Urban planning to date has done relatively little to try to mitigate these effects, and by extension our A2 scenario might continue to produce them, especially since the urban footprint would expand under a “business as usual” story line. However, the story lines of the B1 and AB32+ scenarios might well reduce these effects through extensive tree‐planting in urban areas, reduced amounts of paved surfaces, green roofs, lighter‐colored paving and roofing materials, and other steps. The extent to which urban heat island effects would actually undermine agricultural adaptation in Yolo County, however, is highly uncertain. Towns such as Davis and Woodland are relatively small, and would likely produce much smaller warming effects on surrounding farmland than a larger city like Sacramento. Prevailing winds, particularly on summer evenings, are from the west, and would tend to carry the Sacramento region’s heat toward the Sierra Nevada foothills rather than Yolo County.