Across the United States, urban sprawl, its impacts, and appropriate containment policies have become the most hotly debated issues in urban planning. Today's debates have no anchoring definition of sprawl, which has contributed to their unfocused, dogmatic quality. Efforts to measure sprawl and test for relationships between sprawl and transportation outcomes are described. This is the first use of the newly minted Rutgers-Cornell sprawl indicators. Sprawl is operationalized by combining many variables into a few factors representing density, land use mix, degree of centering, and street accessibility. This consolidation of variables is accomplished with principal component analysis. These factors are then related to vehicle ownership, commute mode choice, commute time, vehicle miles traveled per capita, traffic delay per capita, traffic fatalities per capita, and 8-h ozone level. These associations are made with multiple regression analysis. For most travel and transportation outcomes, sprawling regions perform less well than compact ones. The exceptions are average commute time and annual traffic delay per capita, which do not clearly favor compactness over sprawl. The main limitation of this study has to do with the data it uses. By necessity, the study uses highly aggregate data from a variety of sources that are not always consistent as to the area under study and time period. They are simply the best data available from national sources with sufficient breadth to provide a panoramic view of sprawl in the United States. Results will have to be validated through follow-up work of a more focused nature.Publication of this paper sponsored by Committee on Transportation and Land Development.
The COVID-19 pandemic has been a source of ongoing challenges and presents an increased risk of illness in group environments, including jails, long-term care facilities, schools, and residential college campuses. Early reports that the SARS-CoV-2 virus was detectable in wastewater in advance of confirmed cases sparked widespread interest in wastewater-based epidemiology (WBE) as a tool for mitigation of COVID-19 outbreaks. One hypothesis was that wastewater surveillance might provide a cost-effective alternative to other more expensive approaches such as pooled and random testing of groups. In this paper, we report the outcomes of a wastewater surveillance pilot program at the University of North Carolina at Charlotte, a large urban university with a substantial population of students living in on-campus dormitories. Surveillance was conducted at the building level on a thrice-weekly schedule throughout the university's fall residential semester. In multiple cases, wastewater surveillance enabled the identification of asymptomatic COVID-19 cases that were not detected by other components of the campus monitoring program, which also included in-house contact tracing, symptomatic testing, scheduled testing of student athletes, and daily symptom reporting. In the context of all cluster events reported to the University community during the fall semester, wastewater-based testing events resulted in the identification of smaller clusters than were reported in other types of cluster events. Wastewater surveillance was able to detect single asymptomatic individuals in dorms with resident populations of 150–200. While the strategy described was developed for COVID-19, it is likely to be applicable to mitigation of future pandemics in universities and other group-living environments.
The COVID-19 pandemic has been a source of ongoing challenges and presents an increased risk of illness in group environments, including jails, long term care facilities, schools, and, of course, residential college campuses. Early reports that the SARS-CoV-2 virus was detectable in wastewater in advance of confirmed cases sparked widespread interest in wastewater based epidemiology (WBE) as a tool for mitigation of COVID-19 outbreaks. One hypothesis was that wastewater surveillance might provide a cost-effective alternative to other more expensive approaches such as pooled and random testing of groups. In this paper, we report the outcomes of a wastewater surveillance pilot program at the University of North Carolina at Charlotte, a large urban university with a substantial population of students living in on-campus dormitories. Surveillance was conducted at the building level on a thrice-weekly schedule throughout the university’s fall residential semester. In multiple cases, wastewater surveillance enabled identification of asymptomatic COVID-19 cases that were not detected by other components of the campus monitoring program, which also included in-house contact tracing, symptomatic testing, scheduled testing of student athletes, and daily symptom reporting. In the context of all cluster events reported to the University community during the fall semester, wastewater-based testing events resulted in identification of smaller clusters than were reported in other types of cluster events. Wastewater surveillance was able to detect single asymptomatic individuals in dorms with total resident populations of 150-200. While the strategy described was developed for COVID-19, it is likely to be applicable to mitigation of future pandemics in universities and other group-living environments.
ABSTRACT:With the increased awareness of energy consumption as well as the environmental impact of building operations, architects, designers and planners are required to place more consideration on sustainability and energy performance of the building. To ensure most of those considerations are reflected in the building performance, critical design decisions should be made by key stakeholders early during the design development stage. The application of BIM during building energy simulations has profoundly improved the energy analysis process and thus this approach has gained momentum. However, despite rapid advances in BIM-based processes, the question still remains how ordinary building stakeholders can perform energy performance analysis, which has previously been conducted predominantly by professionals, to maximize energy efficient building performance. To address this issue, we identified two leading building performance analysis software programs, Energy Plus and IES
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