4 resultados para ENVIRONMENTAL INFORMATION
em Digital Commons - Michigan Tech
Resumo:
As environmental problems became more complex, policy and regulatory decisions become far more difficult to make. The use of science has become an important practice in the decision making process of many federal agencies. Many different types of scientific information are used to make decisions within the EPA, with computer models becoming especially important. Environmental models are used throughout the EPA in a variety of contexts and their predictive capacity has become highly valued in decision making. The main focus of this research is to examine the EPA’s Council for Regulatory Modeling (CREM) as a case study in addressing science issues, particularly models, in government agencies. Specifically, the goal was to answer the following questions: What is the history of the CREM and how can this information shed light on the process of science policy implementation? What were the goals of implementing the CREM? Were these goals reached and how have they changed? What have been the impediments that the CREM has faced and why did these impediments occur? The three main sources of information for this research came from observations during summer employment with the CREM, document review and supplemental interviews with CREM participants and other members of the modeling community. Examining a history of modeling at the EPA, as well as a history of the CREM, provides insight into the many challenges that are faced when implementing science policy and science policy programs. After examining the many impediments that the CREM has faced in implementing modeling policies, it was clear that the impediments fall into two separate categories, classic and paradoxical. The classic impediments include the more standard impediments to science policy implementation that might be found in any regulatory environment, such as lack of resources and changes in administration. Paradoxical impediments are cyclical in nature, with no clear solution, such as balancing top-down versus bottom-up initiatives and coping with differing perceptions. These impediments, when not properly addressed, severely hinder the ability for organizations to successfully implement science policy.
Resumo:
Information management is a key aspect of successful construction projects. Having inaccurate measurements and conflicting data can lead to costly mistakes, and vague quantities can ruin estimates and schedules. Building information modeling (BIM) augments a 3D model with a wide variety of information, which reduces many sources of error and can detect conflicts before they occur. Because new technology is often more complex, it can be difficult to effectively integrate it with existing business practices. In this paper, we will answer two questions: How can BIM add value to construction projects? and What lessons can be learned from other companies that use BIM or other similar technology? Previous research focused on the technology as if it were simply a tool, observing problems that occurred while integrating new technology into existing practices. Our research instead looks at the flow of information through a company and its network, seeing all the actors as part of an ecosystem. Building upon this idea, we proposed the metaphor of an information supply chain to illustrate how BIM can add value to a construction project. This paper then concludes with two case studies. The first case study illustrates a failure in the flow of information that could have prevented by using BIM. The second case study profiles a leading design firm that has used BIM products for many years and shows the real benefits of using this program.
Resumo:
Reed canary grass (Phalaris arundinacea L.) is an invasive species originally from Europe that has now expanded to a large range within the United States. Reed canary grass possesses a number of traits that allow it to thrive in a wide range of environmental factors, including high rates of sedimentation, bouts of flooding, and high levels of nutrient inputs. Therefore, the goals of our study were to determine if 1) certain types of wetland were more susceptible to Reed canary grass invasion, and 2) disturbances facilitated Reed canary grass invasion. This study was conducted within the Keweenaw Bay Indian Community reservation in the Upper Peninsula of Michigan, in Baraga County. We selected 28 wetlands for analysis. At each wetland, we identified and sampled distinct vegetative communities and their corresponding environmental attributes, which included water table depth, pH, conductivity, calcium and magnesium concentrations, and percent organic matter. Disturbances at each site were catalogued and their severity estimated with the aid of aerial photos. A GIS dataset containing information about the location of Reed canary grass within the study wetlands, the surrounding roads and the level of roadside Reed canary grass invasion was also developed. In all, 287 plant species were identified and classified into 16 communities, which were then further grouped into three broad groupings of wetlands: nonforested graminoid, Sphagnum peatlands, and forested wetlands. The two most common disturbances identified were roads and off-road recreation trails, both occurring at 23 of the 28 sites. Logging activity surrounding the wetlands was the next most common disturbance and was found at 18 of the sites. Occurrence of Reed canary grass was most common in the non-forested graminoid communities. Reed canary grass was very infrequent in forested wetlands, and almost never occurred in the Sphagnum peatlands. Disturbance intensity was the most significant environmental factor in explaining Reed canary grass occurrence within wetlands. Statistically significant relationships were identified at distances of 1000 m, 500 m, and 250 m from studied wetlands, between the level of road development and the severity of Reed canary grass invasion along roadsides. Further analysis revealed a significant relationship between roadside Reed canary grass populations and the level of road development (e.g. paved, graded, and ungraded).