The Uncertainty Determination of Emergy Analysis Modified

The conflict between environmental protection and further economic development is becoming a much serious problem in front of human being nowadays. To realize human being’s sustainable development, some scientific methods are firstly required to objectively evaluate the real wealth，including both economic and environmental aspects. Emergy theories and methods, created by H.T. Odum and his colleagues in the 1980s, can convert energy, material and monetary flows of all kinds in an ecological economic system to solar emjoules as a common basis allowing direct comparison, addition and subtraction among them. As a bridge linking environment and economy, emergy analysis has been developed into a common and tested evaluation method applied to integrating study of ecological economic systems and processes. However, like many groundbreaking theory and methods, emergy analysis has also encountered some criticism from some economists, physicists and engineers, because of lack of uncertainty analysis. Although the Monte Carlo method (a stochastic method) can address this problem to a certain extent, it requires the assumption that input variables follow some probability distribution and be independent to each other.

Recently, under the direction of Dr. REN Hai and Dr. LU Hongfang Lu, the PhD candidate LI Linjun at the Vegetation and Landscape Ecology Research Group of the South China Botanical Garden, introduced two analytical methods provided by the Guide to the Expression of Uncertainty in Measurement (GUM), i.e., the Variance method and the Taylor method, to estimate the uncertainty of emergy table-form calculations for two different types of data, and compared them with the stochastic method in two case studies. The results showed that, when replicate data are available at the system level, the Variance method is the simplest and most reliable method for determining the uncertainty of the model output, since it considers the underlying covariance of the inputs and requires no assumptions about the probability distributions of the inputs. However, when replicate data are only available at the subsystem level, the Taylor method will be a better option for calculating uncertainty, since it requires less information and is easier to understand and perform than the Monte Carlo method. Furthermore, they may be also useful in quantifying the uncertainty in ecosystem models and scaling up or down in ecological studies.

The results of this study will contribute greatly to the uncertainty determination of emergy analysis and promote the acceptance of emergy theories and methods. And the related paper has been online published in the Journal Ecological Modelling（http://www.sciencedirect.com/science/article/pii/S0304380011002535）.