A Dynamic Disequilibrium Model of Material Consumption in Primary and Secondary Economic Sectors. Ali Kerem Saysel*, Birnur Özbaş**

Transcription

1 A Dynamic Disequilibrium Model of Material Consumption in Primary and Secondary Economic Sectors Ali Kerem Saysel*, Birnur Özbaş** * Boğaziçi University, Institute of Environmental Sciences, 34342, Bebek - İstanbul, Turkey ** Boğaziçi University, Industrial Engineering Department, 34342, Bebek - İstanbul, Turkey correspondence: ali.saysel@boun.edu.tr Abstract A dynamic simulation model of material flow in primary and secondary economic sectors is developed. Model structure considers the material flow accounting framework, i.e. it differentiates between material stocks and flows and conforms to the idea of mass balance. Formulations take into account the information and material feedbacks between different economic sectors and utilize disequilibrium approach in decision rules. In these respects, the model is built according to the principles of system dynamics method. The purpose is to explore the complex relationships of economic growth and material consumption and to create insights to the policies aiming at reduced material use. I. Introduction Ecological economists criticize current view of macro economics for perceiving the circular flow of production and consumption factors between firms and households as a perpetual motion machine, a phenomenon against the second law of thermodynamics (Daly and Farley 2004). This circular flow model ignores the throughput of matter-energy, which should be strictly subject to the laws of conservation of mass and energy and the second law of thermodynamics (the entropy law). According to this model, as long as the circular flow is in units of abstract exchange value, it can nominally grow forever but that does not necessarily represent a qualitative development or increased satisfaction in wants. There have been attempts to develop an understanding of the dependencies of human economic systems on natural environments that they are embedded in. (Fisher-Kowalski and Haberl 1997) proposed the social metabolism concept and the socio-economic system unit as the appropriate boundary of analysis. Social metabolism is the mode in which societies

2 organize the exchange of matter and energy with their natural environments. It comprises the extraction of materials and energy resources, their transformation in the process of production, consumption and transport and their eventual release into the environment. The socioeconomic system comprises labor (population), livestock and all human artifacts together with all symbolic and cultural elements that constitute a society. There are several empirical approaches that serve this conception of human-nature interactions. Material flow accounting (MFA), energy flow accounting (EFA) and human appropriation of net primary production (HNPP) aim to give an overall picture of the physical dimensions of socio-economic systems (the metabolism) and their effects on the energy availability in ecosystems (colonization) (Schandl, Grünbühel et al. 2002). The proposed, overall MEFA (material and energy flow accounting) - HNPP framework builds on a rigorous description of the boundaries of the socio-economic system and its interactions with the environment in terms of material and energy flows. MFA tries to create a complete material balance of a society (the socio-economic system) by taking into account what crosses the system s boundaries. The net accumulation of materials in a system is calculated as the difference between what enters (input) the system and what goes out (outputs). Therefore, stock (accumulation) and flow (rate of change) concepts and the principle of conservation of mass are fundamental to economy wide material flow accounting (Schandl, Grünbühel et al. 2002). In this research, we develop a dynamic simulation model representing the material flows in extraction and manufacturing sectors in MFA terms. The socio economic unit is a national economy. What crosses in minus out the boundary of this socio economic unit is accumulated in material stocks. Materials are aggregated under biomass, minerals and fossil fuels. Manufacturing sectors are represented by consumer goods and capital production. Extractive sectors are aggregated under agriculture and mining. Model also comprises population and employment to generate indicators of economic growth and welfare together with the material consumption indicators. Agents represented in the economy take extraction, production, investment and employment decisions based on disequilibrium approach, confirming the rules and principles of behavioral decision making. The purpose is to create an understanding of the complex relationships between economic growth and material use and to evaluate the usefulness of proposed material accounts in environmental policy design.

3 II. The model Model structure consists of five interacting sub-models (Figure 1). Boxes are the sub-models, solid arrows are material flows and dashed arrows are information flows. Population sector receives labor requirement from all economic sectors and supplies labor. It also creates demand for goods. Goods sector produces goods and creates demand for labor, agricultural raw material (biomass) and machinery (capital). Note that, to reduce model complexity, goods do not create demand for minerals. Agriculture produces biomass for goods production and creates demand for labor and machinery. Mining produces minerals for machinery production and creates demand for labor and machinery. Machinery (capital) sector produces machinery for all economic activities and creates demand for minerals. It also creates self demand (the capital multiplier of the economy) which is not illustrated in the model overview diagram. agriculture capital supply biomass supply capital demand biomass demand capital demand goods goods demand population machinary goods supply capital supply mineral demand mining mineral supply capital demand capital supply Figure 1. Model overview diagram Goods sector represents production of non-durable consumption goods (food, textile, paper) and comprises the generic stock management structure and ordering heuristic (Sterman 2000), pp ). Goods producers aim to keep a certain amount of finished goods in their inventories so as to satisfy the demand from the consumers. As they ship their products, they try to replace what they sell by ordering production (Figure 2.). Desired production is the sum of expected shipments and adjustment terms for the inventory stock and the supply line of goods. Production requires machinery, labor and biomass. Therefore, production decision is a function of available resources and desired production.

4 INV maximum delivery minimum inventory processing time effect on production start production start production shi pment ref consumption per capita feasible production start from biomass ~ feasible production start desired production start adjustment production cycle time adjustment inventory inventory adjustment time time to average orders expected orders customer orders POPULATION feasible production start from capital feasible production start from labor adjustment time desired desired production desired inventory desired inventory coverage Figure 2. The stock management structure in goods production sector As goods are ordered, produced and shipped, model keeps track of biomass stocks as raw biomass, biomass in semi-finished and finished goods and in artifacts. This process is a coflow of goods production, illustrated in Figure 2. Raw biomass is delivered from the agriculture sector with respect to biomass demand created by desired production. After that, as production starts, raw biomass is transformed to biomass in semi-finished goods. As production proceeds, biomass in semi-finished goods is transformed to biomass in finished goods. As finished goods are shipped, the biomass in finished goods is transferred to biomass in artifact and then disposed (Figure 3.). This process represents the material flow in MFA terms and conforms to the principles of conservation of mass.

5 biomass unused extraction domestic biomass raw indirect related to export biomass raw export biomass domestic extraction biomass raw import biomass raw indirect related to import RAW biomass sfp indirect related to export biomass raw waste biomass sfp primary production export biomass primary production biomass raw dissipative consumption bomass raw biomass sfp import biomass sfp indirect related to import IN SFP biomass fp indirect related to export biomass sfp waste seondary production biomass fp export biomass secondary production biomass sfp dissipative consumption biomass fp import bomass sfp biomass sfp reuse remanufacture recycle biomass fp indirect related to import IN FP biomass fp waste distribution biomass fp distribution consumption biomass fp dissipative consumption bomass fp IN ARTEF biomass artefact waste disposal biomass artefact depreciation biomass artecat biomass itensity consumer goods biomass raw waste consumption biomass intensity biomass intensity INV INV biomass fp waste consumption production start production shi pment Figure 3. Biomass stock-flow structure in goods production sector A second model sector (machinery) represents the durable capital goods production and capacity expansion (Sterman 2000), pp. 799). Here, the stock-management structure in Figure 2 is applied to capital investment, acquisition and depreciation (in machinery, goods, agriculture and mining industries). Similar to the production model, investment creates demand on material goods and the investment decision is realized as a function of available machinery, labor and minerals. Again, a stock-flow chain of minerals keeps track of mineral flows in the socio-economic system created by mining and the capital investment cycle, similar to that in Figure 3. Agriculture and mining sub-models respond to the desired biomass production and desired mineral production from goods and machinery sub-models respectively by changing their production activities. Biomass and mineral production in these sectors are constrained by the available labor and machinery. Fifth model sector represents the population growth, maturation and aging together with nonparticipating and participating workforce further classified under unemployed and employed categories. All sectors create demand on labor. Labor is hired and laid off with respect to the discrepancy between industry requirements and labor stocks.

6 Model drives economic and MFA indicators to observe their behavior over 360 months. Economic indicators are represented by variables such as employment rate and economic growth. MFA indicators are standard measures suggested in (Schandl, Grünbühel et al. 2002) such as direct material input, direct material output and domestic material consumption. III. Results and conclusion As an illustrative output, Figure 4 shows the disequilibrium dynamics of inventory of goods, capital in use and biomass and mineral stocks subject to an experiment (step increase in consumption at t=90) for over next 270 months. Figure 4. Dynamics of material stocks subject to a step increase in consumption Model is at development and analysis stage and promises to be an experimental platform to explore the complex relationships between the indicators of economic welfare and material consumption. The discrepancy between nominal production and MFA measures will be used as an indicator of decoupling between economic growth and material consumption. The effect of material efficiency factors, recycling /reuse, taxation of raw materials on economic growth and material consumption will be investigated. The purpose is to further develop the model to include energy flow accounting (EFA). References Daly, H. E. and J. Farley (2004). Ecological Economics. Washington, Island Press. Fisher-Kowalski, M. and H. Haberl (1997). "Tons, Joules, and Moeny: Modes of Production and Their Sustainability Problems." Society & Natural Resources 10:

7 Schandl, H., C. M. Grünbühel, et al. (2002). Handbook of Physical Accounting: Measuring Bio-physical Dimensions of Soico-economic Activities (MFA-EFA-HNPP). Social Ecology Working Papers. Vienna, Iff Social Ecology. Sterman, J. D. (2000). Business Dynamics: Systems Thinking and Modeling for a Complex World, McGraw-Hill.