Rehabilitation of Childs Park, Delaware Water Gap National Recreation Area (NRA) : environmental assessment, public scoping meetings, July 11 & 12, 2006 /

Shows recommended changes at the Childs Park recreation area within the N.R.A. on the Pa. side of the Delaware River.

Metodologia de avaliação de sistemas municipais de meio ambiente : aplicação a RIDE-DF e Entorno

Dissertação (mestrado)—Universidade de Brasília, Faculdade de Tecnologia, Departamento de Engenharia Civil e Ambiental, Pós-Graduação em Tecnologia Ambiental e Recursos Hídricos, 2015.

Environmental assessment of proton exchange membrane fuel cell platinum catalyst recycling

International audience

Standardized environmental management systems as an internal management tool

In a principal-agent model we analyze the firm’s decision to adopt an informal or a standardized Environmental Management System (EMS). Our results are consistent with empirical evidence in several respects. A standardized EMS increases the internal control at the cost of introducing some degree of rigidity that entails an endogenous setup cost. Standardized systems are more prone to be adopted by big and well established firms and under tougher environmental policies. Firms with standardized EMS tend to devote more effort to abatement although this effort results in lower pollution only if public incentives are strong enough, suggesting a complementarity relationship between standardized EMS and public policies. Emission charges have both a marginal effect on abatement and a qualitative effect on the adoption decision that may induce a conflict between private and public interests. As a result of the combination of these two effects it can be optimal for the government to distort the tax in a specific way in order to push the firm to choose the socially optimal EMS. The introduction of standardized systems can result in win-win situations where firms, society and the environment get better off.

Local productive arrangements for biodiesel production in Brazil: Environmental assessment of small-holders integrated oleaginous crops management.

Sustainability assessments were carried out in small-holders? farms in four territories where productive arrangements have been organized for production of minor oleagi- nous crops under the Brazilian biodiesel program. The study aimed at checking local impacts of the biodiesel productive chains at the rural establishment scale, and pro- moting the environmental performance of the selected farms, henceforth proposed as sustainable management demonstration units. Assessments were carried out with the APOIA-NovoRural system, which integrates 62 objective and quantitative indicators re- lated to five sustainability dimensions: i) Landscape Ecology, ii) Environmental Quality (Atmosphere, Water and Soil), iii) Socio-cultural Values, iv) Economic Values and v) Management and Administration. The main results point out that, in general, the eco- logical dimensions of sustainability, that is, the Landscape Ecology and Atmosphere, Water, and Soil quality indicators, show adequate field conditions, seemingly not yet negatively affected by increases in chemical inputs and natural resources use predicted as important potential impacts of the agro-energy sector. The Economic Values indica- tors have been favorably influenced in the studied farms, due to a steadier demand and improved prices for the oleaginous crops. On the other hand, valuable positive conse- quences expected for favoring farmers? market insertion, such as improved Socio-cultural Values and Management & Administration indicators, are still opportunities to be ma-terialized. The Environmental Management Reports issued to the farmers, based on the presented sustainability assessment procedures, offer valuable documentation and com-munication means for consolidating the organizational influence of the local productive arrangements studied. These productive arrangements were shown to be determinant for the selection of crop associations and diversification, as well as for the provision of technical assistance and the stabilization of demand - conditions that promote value aggregation and income improvements, favoring small-holders? insertion in the market. More importantly, these locally organized productive arrangements have been shown to strongly influence the valorization of natural resources and environmental assets, which are fundamental if sustainable rural development is to take place under the emerging agro-energy scenario.

Building environmental assessment scheme for residential building in Brunei

Building's construction activities, operation and demolition are increasingly recognised as a major source of environmental impact. One strategy for reducing such impacts is most widely known by the term Building Environmental Assessment (BEA). The research is an attempt to develop a new BEA scheme for residential buildings in Brunei which focussing on identifying BEA indicators that best suit for Brunei environment, social and economy. Studies show that Brunei residential sector needs urgent attention to transform its current consumption rate in more sustainable way. Recent launch of Brunei Green Building Council, mandatory energy efficiency guidelines and declaration of ambitious energy intensity reduction target, a new BEA scheme will help contribute sustainability target in residential sector. However the issues of developing a new BEA schemes using existing methods may face constraints in their effectiveness. In this regard, a consensus-forming technique-Delphi method-helps improve greater communication and gain consensus from experts in the construction industry through series of questionnaires. As a result, the final framework is produced comprises of 7 key categories and 37 applicable criteria that achieved high degree of consensus and importance.

Occupant health and productivity : an Australian perspective

The issue of whether improved building services such as air quality, provision of daylight, thermal comfort etc, have a positive impact on the health and productivity of building occupants is still an open question. There is significant anecdotal evidence supporting the notion that health and productivity of building occupants can be improved by improving the quality of the indoor environment, but there are actually few published quantitative studies to substantiate this contention. This paper reports on a comprehensive review of the worldwide literature which relates health of building occupants with the different aspects of the indoor environment which are believed to impact of these issues, with a particular focus on studies in Australia, The paper analyses the existing research and identifies the key deficiencies in our existing understanding of this problem. The key focus of this research is office and school buildings, but the scope of the literature surveyed includes all commercial buildings, including industrial buildings. There is a notable absence of detailed studies on this link in Australian buildings, although there are studies on thermal comfort, and a number of studies on indoor air quality in Australia, which do not make the connection to health and productivity. Many international studies have focused on improved lighting, and in particular the provision of daylight in buildings, but again there are few studies in Australia which focus in this area.

Improving the management of building life cycle : a data mining approach

The construction industry has adapted information technology in its processes in terms of computer aided design and drafting, construction documentation and maintenance. The data generated within the construction industry has become increasingly overwhelming. Data mining is a sophisticated data search capability that uses classification algorithms to discover patterns and correlations within a large volume of data. This paper presents the selection and application of data mining techniques on maintenance data of buildings. The results of applying such techniques and potential benefits of utilising their results to identify useful patterns of knowledge and correlations to support decision making of improving the management of building life cycle are presented and discussed.

Using Agents for Mining Maintenance Data while interacting in 3D Objectoriented Virtual Environments

This report demonstrates the development of: (a) object-oriented representation to provide 3D interactive environment using data provided by Woods Bagot; (b) establishing basis of agent technology for mining building maintenance data, and (C) 3D interaction in virtual environments using object-oriented representation. Applying data mining over industry maintenance database has been demonstrated in the previous report.

Developing Software Agents for Data Mining : [AIMM] Agents for Improving Maintenance Management

This report demonstrates the development of: • Development of software agents for data mining • Link data mining to building model in virtual environments • Link knowledge development with building model in virtual environments • Demonstration of software agents for data mining • Populate with maintenance data

Demonstration of Software Agents Prototype System : [AIMM] Agents for Improving Maintenance Management

This report presents the demonstration of software agents prototype system for improving maintenance management [AIMM] including: • Developing and implementing a user focused approach for mining the maintenance data of buildings. This report presents the demonstration of software agents prototype system for improving maintenance management [AIMM] including: • Developing and implementing a user focused approach for mining the maintenance data of buildings. • Refining the development of a multi agent system for data mining in virtual environments (Active Worlds) by developing and implementing a filtering agent on the results obtained from applying data mining techniques on the maintenance data. • Integrating the filtering agent within the multi agents system in an interactive networked multi-user 3D virtual environment. • Populating maintenance data and discovering new rules of knowledge.

Life Cycle Modelling and Design Knowledge Development in 3D Virtual Environments

Experience plays an important role in building management. “How often will this asset need repair?” or “How much time is this repair going to take?” are types of questions that project and facility managers face daily in planning activities. Failure or success in developing good schedules, budgets and other project management tasks depend on the project manager's ability to obtain reliable information to be able to answer these types of questions. Young practitioners tend to rely on information that is based on regional averages and provided by publishing companies. This is in contrast to experienced project managers who tend to rely heavily on personal experience. Another aspect of building management is that many practitioners are seeking to improve available scheduling algorithms, estimating spreadsheets and other project management tools. Such “micro-scale” levels of research are important in providing the required tools for the project manager's tasks. However, even with such tools, low quality input information will produce inaccurate schedules and budgets as output. Thus, it is also important to have a broad approach to research at a more “macro-scale.” Recent trends show that the Architectural, Engineering, Construction (AEC) industry is experiencing explosive growth in its capabilities to generate and collect data. There is a great deal of valuable knowledge that can be obtained from the appropriate use of this data and therefore the need has arisen to analyse this increasing amount of available data. Data Mining can be applied as a powerful tool to extract relevant and useful information from this sea of data. Knowledge Discovery in Databases (KDD) and Data Mining (DM) are tools that allow identification of valid, useful, and previously unknown patterns so large amounts of project data may be analysed. These technologies combine techniques from machine learning, artificial intelligence, pattern recognition, statistics, databases, and visualization to automatically extract concepts, interrelationships, and patterns of interest from large databases. The project involves the development of a prototype tool to support facility managers, building owners and designers. This Industry focused report presents the AIMMTM prototype system and documents how and what data mining techniques can be applied, the results of their application and the benefits gained from the system. The AIMMTM system is capable of searching for useful patterns of knowledge and correlations within the existing building maintenance data to support decision making about future maintenance operations. The application of the AIMMTM prototype system on building models and their maintenance data (supplied by industry partners) utilises various data mining algorithms and the maintenance data is analysed using interactive visual tools. The application of the AIMMTM prototype system to help in improving maintenance management and building life cycle includes: (i) data preparation and cleaning, (ii) integrating meaningful domain attributes, (iii) performing extensive data mining experiments in which visual analysis (using stacked histograms), classification and clustering techniques, associative rule mining algorithm such as “Apriori” and (iv) filtering and refining data mining results, including the potential implications of these results for improving maintenance management. Maintenance data of a variety of asset types were selected for demonstration with the aim of discovering meaningful patterns to assist facility managers in strategic planning and provide a knowledge base to help shape future requirements and design briefing. Utilising the prototype system developed here, positive and interesting results regarding patterns and structures of data have been obtained.

Using data mining to improve building life cycle

The building life cycle process is complex and prone to fragmentation as it moves through its various stages. The number of participants, and the diversity, specialisation and isolation both in space and time of their activities, have dramatically increased over time. The data generated within the construction industry has become increasingly overwhelming. Most currently available computer tools for the building industry have offered productivity improvement in the transmission of graphical drawings and textual specifications, without addressing more fundamental changes in building life cycle management. Facility managers and building owners are primarily concerned with highlighting areas of existing or potential maintenance problems in order to be able to improve the building performance, satisfying occupants and minimising turnover especially the operational cost of maintenance. In doing so, they collect large amounts of data that is stored in the building’s maintenance database. The work described in this paper is targeted at adding value to the design and maintenance of buildings by turning maintenance data into information and knowledge. Data mining technology presents an opportunity to increase significantly the rate at which the volumes of data generated through the maintenance process can be turned into useful information. This can be done using classification algorithms to discover patterns and correlations within a large volume of data. This paper presents how and what data mining techniques can be applied on maintenance data of buildings to identify the impediments to better performance of building assets. It demonstrates what sorts of knowledge can be found in maintenance records. The benefits to the construction industry lie in turning passive data in databases into knowledge that can improve the efficiency of the maintenance process and of future designs that incorporate that maintenance knowledge.