Banca de DEFESA: LUARA LOPES DE ARAUJO FERNANDES

ANALYSIS OF ENVIRONMENTAL PERFORMANCE OF BUILDING WORKS BASED ON PBQP-H SUSTAINABILITY INDICATORS

Indicators. Sustainability. Benchmarking. PBQP-H. Construction.

In the past few years, the construction industry has aroused the need to turn its attention to sustainability in construction and improving its environmental performance. One of the strategies adopted by the sector is to measure performance through the use of indicators to monitor the impacts generated by its activities and to support the decision-making process. The Brazilian Habitat Quality and Productivity Program (PBQP-H) started to require, in 2012, the collection of six sustainability indicators which are: indicator of waste generation throughout the construction, indicator waste generation at the end of the construction, indicator of water consumption throughout the construction, indicator of water consumption at the end of the construction, indicator of energy consumption throughout the construction and indicator of energy consumption at the end of the construction. However, the collection of the indicator does not improve performance by itself. Companies need benchmarks to guide their goals and drive performance improvement. The main purpose of this study is to evaluate the scenario and the evolution of the environmental performance of building construction sites regarded to PBQP-H sustainability indicators. This research also aims to: (a) establish benchmarks for the six PBQP-H indicators, (b) identify construction systems and construction phases that are generating more impact, and (c) develop a predictive model for environmental performance indicators for construction site. The research strategy adopted in this paper is the survey, involving the following steps: (a) literature review, (b) data collection in 9 (nine) Brazilian states and the Federal District, in a total of 186 (one hundred and eighty-six) sites, (c) qualitative and statistical analysis of the data and (d) evaluation of the results obtained. As main results of the study, benchmarks were established for the six PBQP-H indicators in general, by construction system and by construction progress scopes. From the statistical analysis and application of hypothesis tests, it was possible to evaluate the incidence of greater environmental impact based on characteristics of the construction, such as construction system and phase. In addition, a predictive model of indicators of water consumption and energy and waste generation throughout the construction in the general and by construction system scopes was established, using Artificial Neural Networks. The main contribution of this study is the indication of subsidies for managers to improve the environmental performance of building construction by setting goals and implementing good practices to mitigate environmental impacts.