石化工業所排放污染物來源複雜,當中的有害空氣污染物(Hazardous Air Pollutants, HAPs)對人體有致癌性。許多研究指出石化工業鄰近居民致癌率遠高於其他地區。但風險熱區管理透過控制工業區裡工廠污染排放卻極少文獻有討論到。 任何污染控制行動,經濟會是工廠最優先考量問題。本研究首先進行案例區域的風險評估,了解風險分佈狀況。利用線性規畫原理建構風險減量模型,探討排放減量成本最小化的目標下,降低風險的控制策略,從模型中得知的資訊可提供環境管理決策者參考用。 模式設定了四種污染物共有十個污染源,結果顯示有2個污染源需優先減量,一個為風險最高之污染源,另一個為排放量最大污染源。另外以每百萬人致癌率為單位,當風險標準為10-6~3.29×10-6之間,其影子價格為24.67,當風險標準超過3.29×10-6,則影子價格降低為6.32。當成本為主要考量時,建議風險標準可訂定於3.29×10-6人,因風險減量成本較低,使工廠較有意願遵守。往後有更佳控制技術,在相同成本條件下削減風險更多,就可將標準訂定更嚴格。
Many researches have identified cancer incidence among residents adjacent to petrochemical complexes is much higher than that of other communities. Yet, few studies have addressed the risk management of hot spots by controlling emissions of their industrial plant. However for any pollutantion control action, the economic impact on manufacturers is a major concern. This study conducts a risk assessment to understand the distribution of risk, and uses the linear programming to build a risk reduction model to explore possible control strategies the risk reduction with cost minimization consideration. The model developed is easily useful for decision makers concerning environment management. The model simulates a total of ten sources of the four pollutants in a case study area. The results show two of these ten sources of the pollution as reduction targets, one is the highest risk source, and the other the largest source emission. With a constraint on target maximum risk between 10-6 of 3.29×10-6, the shadow price of risk reduction is 24.For risk more than 3.29×10-6, the shadow price decreases to NT 6.Considering the large change in shadow price, 3.29×10-6 would be a plausible reference point for control.