Since the second half of the twentieth century, fast urbanization and indiscreet development caused lots of urban problems such as destruction of the ecosystem and environmental pollution.
Thus, in the architectural arena both in and out of Korea, ef...
Since the second half of the twentieth century, fast urbanization and indiscreet development caused lots of urban problems such as destruction of the ecosystem and environmental pollution.
Thus, in the architectural arena both in and out of Korea, efforts to protect the environment and make a sustainable development have been actively made, and a green building certification system came into operation as a way to institutionalize these efforts.
Despite the efforts, however, a critical analysis shows that the certification system has not been properly contributing to the improvement of the environment quality. In the midst of these problems that are brought up, this study focuses on the current certification system being assessed by the primary relationships of its criteria and on environmental's assessment being carried out by the static assessment method. Understanding the problem of "green building certification system", the study utilizes the system dynamics as a long-term analysis method based on the analysis of interrelations of assessment items and aims to suggest a new model that can dynamically show environmental capacity of green building and verify its efficacy.
It tries to establish foundation on which the sustainable development can be made through effective forecast of future environmental changes.
To do this, the study examined a possibility to develop a dynamic model of certification assessment item using system dynamics through reviews on existing literature and preceding research cases. It looked into causal relations between the assessment items and establish a dynamic model and then verified it. Then, an assessment of long-term environmental capacity of green building was carried out through a simulation using scenarios. First of all, as a qualitative analysis, a total of forty causal relations for green building apartment certification assessment items were drawn by three premises of determining causal relations based on variables belonging to nineteen categories. Seven feedback loops were outcome by constructing loops in which a cause is deemed as a starting point, and a result as an end point. These loops are composed of four positive feedback loops and three negative feedback loops.
It could be judged through the qualitative analysis that variables of causal nature (land use, creation of resident environment, water resource, efficiency of maintenance) are major means for creation of green buildings, and variables of resultative nature (ecological value, energy efficiency) are major goals that green buildings ultimately pursue.
I converted it into a simulation model that can quantify a causal loop diagram through stock/flow modeling.
I decided nineteen stock variables, thirty four flow variables, and forty four subsidiary variables, and constructed a base model by determining functional formulas according to NUMBER's formula deciding standard. 'A' complex which obtained the best grade of preliminary green building certification process was selected as the subject to verify the model, and validity evaluation was performed after constructing Base Run by inputting the assessment values of the subject.
As a result, in verification of soundness, the structure and formula of the model is perfect by establishment of the causal relations and principle of internal system structure. Nineteen stock variables and thirty four flow variables have validity within 95% confidence interval, with consistency in the behavior of model, in an analysis of sensitivity of variables used to analyze dynamic behavior.
Subsequently, objectivity verification was investigated by deciding whether the model was constructed according to the principle of the causal relation previously assumed through the result of Base Run.
According to the investigation, the model was simulated according to the forty causal relations and reflected reality.
Accordingly, it is shown that thanks to development of dynamic model, environmental factors constituting a green building interact and create architectural environment by causal relations rather than independently functioning, which proved that the model can effectively predict long-term change.
For application of the dynamic model, I set up the items as analytic variables, through an analysis of the preceding studies, that was often excluded form actual green building certification process, and conducted first and second scenario analysis. As a result of the analysis of the preceding studies, <ecological value of existing land>, <conservation ratio of existing natural resources>, <use of alternative energy>, <reuse of existing buildings (main structure)>, <reuse of existing buildings (non-bearing wall)>, <use of rainwater>, <installation of Wastewater Reclamation and Reusing System>, <recycle ratio of topsoil>, and <sound environment in the complex> were selected as analytic variables.
In the first scenario analysis, changing behavior of stock variables including analytic variables, and related variables were analyzed in case of nine analytic variables obtained the lowest values. The results are as follows.
First, the increase in <ecological value of existing land> and <conservation ratio of existing natural resources> is greatly improving environmental capacity of 'land use' and 'habitat of plants and animals'.
Second, the increase in <use of alternative energy> is greatly contributing to increase in 'energy efficiency' and reduction of 'global warming'.
Third, <reuse of existing buildings (main structure, non-bearing wall)> had an effect of reducing 'resource recycling' and 'waste', as well as increasing in maintenance efficiency.
Based on the results above, in the second scenario analysis, the relative importance between the stock variables was analyzed by controling the subsidiary variables of the stock variables that response sensitively to the change of the analytic variables in the results of the first scenario analysis. The results are as follows.
First, <the ecological value of the existing land> and <the conservation ratio of the existing natural resources> has been found to realize a better environmental capacity than the creating area and creating techniques ofterrestrial biotope and aquatic biotope in the long run.
Second, <the use of alternative energy> for the reduction of greenhouse gas has been found to realize a better environmental capacity in the long run than the facilities for 'the reduction of carbon dioxide emission' Third, <the reuse of existing buildings(main structure, non-bearing wall)> for the resource conservation has been found to show better environmental capacity in the long run than the 'measure to reduce household waste'.
Accordingly, the items that had relatively high importance by the first and second scenario analysis, were the items that were often excluded from the existing assessment process, however, we could realize that they are the more effective items for the realization of the environmental capacity in the long run.
This fact can suggest institutional reinforcement, such as increase in weight or the introduction of a incentive system, and the assignment of obligatory items, that can incite the application of these items.
As the results of the discussion above, by developing a dynamic model of a green building certification assessment item, the long-term change in environmental capacity of the environmental components of a green building could be predicted, and through an analysis of the sensitivity of variables, it was able to evaluate the relative importance of the environmental components which constitute the whole complex by an environment friendly plan. Accordingly, it is judged to be an effective model for realizing a more sustainable environment because a wider consideration of the environment is possible, In addition, it is remarkable that it provided an implement that can be utilized variously in new business or development projects because a dynamic model can be adapted more flexibly when new assessment items or factors are added.