Fig  3 Comparison of existing sustainability with PAIRS cooperati

Fig. 3 Comparison of existing sustainability with PAIRS cooperative metric for potential improvement Figures 4 and 5 present the pairwise analysis results for the water and waste subsections of the PAIRS metric. Figure 4 presents click here results from the water sector and demonstrates the diversity of the resulting scores. No discernible trends emerge, indicating that the water demands and resources of each city are unique. Opportunities for mutual benefit may present themselves between

the most unlikely of pairings and may often support reciprocity of different sectoral partnerships. Water will remain a crucial component for sustainability, particularly within the arid southwest, and any potential resources must be evaluated. The results from the waste sector MK-8931 mouse strongly reflect those of the complete PAIRS

metric in that small agrarian cities pair well with urban centers. This is in response to several sustainability practices which pair waste streams with an application. Composting of urban food waste can help meet the fertilizer needs of the rural farmers, while farming waste, cellulosic biomass, can be processed into biofuel for fleet vehicles such as urban mass transit. The potential for sustainability improvement is greatest in the waste category because not only is a resource matched to an application, but the waste stream from both cities is reduced through repurposing and recycling. Fig. 4 Water sector heat map result of pairwise analysis using PAIRS metric Fig. 5 Waste sector heat map result of pairwise analysis simulation PAIRS community assessment Reflective of the cities tested above, a survey was sent to Southern California voters via email three consecutive Mondays mornings from 7:00 a.m. to 10:00 a.m. PCT. Each

“blast” included 5,000 randomly selected and distinct emails. Of those emailed, 145 responded and completed the survey. Sample demographic characteristics were similar to Los Angeles County and US Census statistics in all categories (gender, age, race, and income), aside from education and political affiliation. Quite a few more respondents had a bachelor’s degree or higher than in LA County and the USA. The sample had the same percent CYTH4 of Democrats as the USA (~51 %), but far less than LA County (~69 %) and far fewer Republicans than both LA County and the US. The results of a logistic regression analysis are presented in Table 3. The use of odds ratios rather than predicted probabilities from logistic regression outputs not only provided a robust method that is selleck chemical invariant to sample design, but also allowed for ease in interpretation. Results are presented in terms of beta values, ranging from +1 to −1, where positive values reflect a positive correlation, while negative values reflect an inverse correlation. Among independent variables, while many significant correlations were revealed, none were so strong as to raise concern of multi-collinearity.

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