代理人基模型(agent-based model)應用於空氣污染總量管制之探討

Abstract

行政院環境保護署為降低高屏地區空氣品質不良情形發生，於2015年實施總量管制計畫，且為臺灣第一個實施總量管制計畫之區域。本研究藉由Agent-based Model (ABM)概念方法，以高屏地區之總量管制計畫為研究實證案例，利用Netlogo工具建立虛擬之總量管制與交易模型，以描述高屏地區各污染源在總量管制下之動態性複雜問題，及彼此間之交易交互行為。能進一步研議總量管制策略實施之影響，來預測各污染源減量與交易行為情形外；另設定其他管理策略實施之情境，研析預測調整制度之排放基準線、減量目標與有無交易平台後，模擬各情境之各污染源減量與交易行為情形外，以找出檢討改進制度之可行性。 本研究初步分析高屏地區在總量管制下，交易市場是屬以供大於需情形，但模擬整體交易結果情形並不熱絡。且以本研究分析各模擬方案比較結果來看，僅考量推動高屏地區之空氣品質改善，建議以推動分配減量目標且不需設計交易制度之作法較簡單，且對各業者之平均每單位減量成本相較在有交易制度下亦無明顯提高，但指定削減目標方式推動，對於要新投資案（污染源）進入高屏地區，則不易取得抵換量，需另構思其他取得抵換量之配套方式。反之，若是政策以持續推動總量管制之前提考量，則推動減量有交易制度配套，則有發展（增量）空間之優勢，建議則以7年最大量作為基準年，並配合交易平台機制，使交易市場較為活絡，業者因應之減量衝擊較小。 因此，本研究建議政府相關單位如要進行調整管制計畫之作法，必須針對空污費、減量目標、交易抵換比例之作法做出合宜性的調整，否則交易市場無法發揮效用；另建議如能設置交易平台，使增加交易市場價格之透明度，則對於交易市場能夠更活絡。 本研究之ABM模型的開發與應用必將為總量管制影響之因應對策提供科學方法依據。將有助於臺灣在研議空氣污染管制作法之新方法建立，能予找出經濟發展與空氣品質保護之永續發展策略。

This study uses an agent-based model to set up a virtual world that represents the Kaohsiung and Pingtung regions in Taiwan, which are under the country’s air emissions cap and trade program. The model can simulate each controlled industry’s dynamic behavioral condition with the bottom-up method and can investigate the impact of the program and determine the industry’s emissions reduction and trading condition. We want to find available ways to improve the design of the air emissions cap and trade program by the model. The simulation results show that the emissions trading market has an oversupply, but we find that the market trading amounts are low. Additionally, based on the comparative results of the modeling schemes analyzed in this paper, it is suggested that to improve the distribution of reduction targets without including trading systems can result in the most reduction amount in the study regions. Compared with an approach that includes a trading system, the proposed method provides a simple approach without any obvious increase in the reduction objects’ average cost per unit of reduction. When policy-makers default on making decisions based on the air emissions cap and trade, a reduction scheme based on a supported trading system will be more adaptable for economic development. It is recommended to consider the maximum emission of the previous 7 years as a baseline, along with a trading platform, for making the market more effective and ensuring a smaller impact on the reduction target of the polluters. Therefore, if authorities want to intervene in the emissions trading market, they must be careful in adjusting the air pollution fee and program rules. Otherwise, the trading market system cannot work effectively. We also suggest setting up a trading platform to help the dealers negotiate successfully. Nonetheless, the development of the modeling tools and methods discussed in this paper will facilitate policy makers to establish new methods when studying and discussing the methods for providing a sustainable development strategy for air quality management.