以物質流分析強化經濟系統活動之風險評估與管理

Abstract

近年來，許多環境問題的思考，已從污染排放端的管理，擴展至預防性思考，不只關心環境損害之復原或賠償，亦關注何為環境影響的驅動力。本研究目的在於發展一整合性方法，以鑑定特定人類經濟活動，因帶動有害物質在經濟體系與環境體系的流動，而成為多種環境健康風險來源或驅動力。透過本研究，得從一個較寬廣的視野，探討有害物質透過環境所造成之人體健康風險。該工具方法的應用，可以量化各種造成環境健康風險活動之貢獻比例，亦有助於評估多種有害物質管理手段，對於環境風險減輕之效果潛力。 本研究之核心方法整合物質流分析、產業投入產出分析與風險評估三種方法，以物質流分析作為描繪經濟系統中，物質代謝與環境釋放的與各種物質相關經濟活動間之關係；再以產業投入產出分析解析國內與出口需要對於國內各產業複雜的驅動效果；並以風險評估量化進入環境中的有害物質對人類健康之損害程度。本研究之對於有害物質之環境釋放，分別在國家尺度與縣市尺度進行盤查，並開發整合上述3方法之模式，區別各別物質流或經濟需求對於環境風險之因果關係，以代表貢獻度的系統流程圖，檢視有害物質的風險如何受到經濟系統活動所驅動，因此得以評估不同風險管理策略情境，計算其環境健康風險之減量潛勢。 為整合三種核心方法的優點，本研究對物質流模型、環境經濟模型以及健康衝擊量化方法進行的回顧，並依歐盟所提的DPSIR環境衝擊的因果關係鏈架構，設計模式之整合架構，明確定義有害物質流動的驅動力(D)、環境排放的壓力(P)、環境濃度的狀態變化(S)、人體暴露的健康衝擊(I)，R則是檢視D、P、S及的關聯，回應風險的需要所做的管理方案，本研究建立其相關情境案例，分析風險減輕效果。DPSIR架構的整合模式以模組設計，包括國家經濟部門活動模型組、物質流動模組、排放強度模組、污染及廢棄物管控模組以及健康衝擊指標量化模組，各模組以分配係數矩陣之方式設計，因此可以用來追蹤危害風險的來源以及傳遞路徑，比較不同來源或不同途徑對於受體暴露風險的貢獻度，結合敏感度分析則是可以篩選關鍵之決策因子，各模組具有設計彈性，可隨問題焦點與界定之範疇做調整，定義程序、部門與環境傳輸媒介。 在彈性架構下，以砷物質流案例分析地區之風險，並針對風險高之地區，從物質流與風險之因果鏈中建立風險改變之情境，依地區燃煤發電、煉油廠之技術規模變動估算其平均砷環境風險之變動幅度。另一案例以鉛之物質流系統為基礎，做為物質流與產業經濟整合模式之範例，示範各模組編製之過程，以及如何在試算表軟體中建置分析模型。鉛模式最主要功能在於國家尺度經濟活動對區域物質流與區域風險之影響，反映產業變化趨勢，透過改變鉛排放對環境風險造成之影響，國家尺度之評估則反映系統排放量之增減。本研究方法所推估情境之健康風險變化結果，宜以相對於該物質既有之健康風險之增減幅度來解釋，不適用於預測精確之實地風險。

This research faces a pressing need in environmental risk assessment. The care of the public about the preventative risk management is upsurging. However, a knowledge gap for risk management for hazardous substances still exist for the complicated linkage between the causes and effects with the scope of interacting economy and environmental systems. Aiming at filling this gap, this research took the advantages of different systemic analysis tools to illustrate the health risks due to the exposure to anthropogenic hazardous substances. With the big pictures derived from our analyses, more opportunities through changing the causes can be identified to reduce the risks. The three key methods are substance flow analysis, input-output modeling, and environmental risk assessment. Substance flow analysis was used to characterize metabolism of society; input-output modeling was used to elaborate the complicated supply-demand interaction between sectors; environmental risk assessment was used to quantify the damage on human health caused by anthropogenic sources. This research investigated the opportunities in the systems of country-wde scope and city/county-wide scope. The potential of environmetal health risk was measured at both scopes in the case studies of arsenic and that of lead, including their compounds. One novelty of our approach is the integration of method in to a model that allows to backtrack the contributions of different causes to the overall anthropogenic health risk of a substance. The model was designed with the inspiration of the DPSIR framework, which addresses the key components of the cause-effect chain of environmental problem. The models combines the DPSI modules for economic metabolism as the Driving forces, emissions as the Pressure, addition to envirionmental concentration as the State changes, and exposure and characterized health risk as the Impact. Thus, the complicated linkage can be presented and examined for effect of changes toward the current state of economic metabolism of a hazardous substance. To derive the options for changes, the proposed approach provides two major advantages, includinhg the insights into the possible rise of risk in the trend of industrial development and possible level of risk reduction. Several scenarios were analyzed and compare to demonstrate the magnitude of increment or reduction, in comparison with the state of the base line health risk. Regarding the value and application of the proposed approach, the uncertainty is specified and discussed for the applicability. The combination of the normally national-scaled substance flow analysis, and the normally locally-scaled environmental risk analysis inevitably lead to a compromise in the precsion and accuracy of model result, though a big picture of the interaction between economic metabolism and environmental health risk can be generated. Therefore, the results derived from our modelling technique should serve as quick screening tool for findling the actors playing big role to the increment of anthropogenic envornmental health risk. The rough comparsion of the scenarios, with respect to the changes, can be taken as a referencial information for the decision makers to set their priority of their environmental health risk management measures.