|摘要: ||空氣品質之良窳，關乎全體國民之健康。本提案之研究主軸，乃針對環境、經濟與健康三者間之關聯性，作一系統性之探討，希冀能填補目前國內這一區塊資訊缺乏之現況。從筆者之先期研究得知，目前政府各部門已然建構有完整且可供下載研究之相關資料庫，包括：社會經濟，或環境保護、甚或國民健康等基本資料。因此，透過使用上述資料，本提案之研究目標，具體來說，包括以下幾方面：- 搜尋、擷取並建構相關之研究資料庫：社會經濟資料(人口、生產毛額、能源效率)、環保資料(特別是各種指標性空氣污染物、空氣污染或品質指標)、國民健康資料 (特別是惡性腫瘤、肺癌死亡率等資料)。- 架構並分析社會經濟發展與空氣品質之關聯性。- 架構並分析空氣品質與重大疾病致死率之關聯性。- 歸納分析空氣品質、社會經濟發展、重大疾病致死率三者間之關聯性。本計畫之執行規畫為三年期程，根據上述研究目標，透過隨機衝擊回歸(Stochastic Impact by Regression on Population, Abundance and Technology；STIRPAT)及類神經網路(Artificial Neural Networks; ANNs)兩種模式，並使用政府部門所建立並開放之相關資料庫資料，藉此模擬並建立空氣品質、社會經濟、重大疾病致死率三者間之關聯性。詳細地來說，在台灣未來人口消長、經濟成長，以及能源技術進展程度之假定下，可以藉所建構之模式預測空氣品質以及重大疾病致死率。最終，預期本計畫之三年研究成果，可以彌補跨「空氣品質/社會經濟/國民健康」三領域研究資訊不足之現況，並且，可以提出具體之政府決策參考資訊與警訊。|
As is understood, air quality affects human health significantly. Thus, the key theme of this research proposal focuses on the systemic investigation of connectedness among the environment, economy and health. It is intended to provide relevant information to the rarely explored area of the aforementioned issue. According to our preliminary study, most of the governmental departments have established their individual databases, which are currently open to the access of the general public, including socioeconomic, environmental, and health databases. Hence, using those national databases, specific works will be performed in this proposal, including:- Searching, accessing, and establishing the relevant research databases such as socioeconomic database (population, gross domestic production, energy efficiency), environmental database (ambient air quality pollutants, air quality index), and national health database (malignant tumor mortality, lung cancer mortality); - Constructing and analyzing the connectedness between the socioeconomic development and air quality;- Constructing and analyzing the connectedness between the air quality and severe disease-causing mortality; - Summarizing and analyzing the connectedness among the air quality, socioeconomic development and severe disease-causing mortality.This proposal is to be implemented within the research timeline of 3 years. Based on the research methods of Stochastic Impact by Regression on Population, Abundance and Technology (STIRPAT) and Artificial Neural Networks (ANNs) and using governmental open data, it is expected that the relational modes of connectedness among the air quality, socioeconomic development and severe disease-causing mortality can be simulated and further applied for future prediction purpose. In detail, given the future Taiwan population growth profile, GDP growth, and energy technology efficiency, the established modes can be used to describe predictively the air quality and severe disease-causing mortality. Ultimately, the outcomes of this 3-year project can make up the lack of the current research information on the connectedness among the air quality, socioeconomic development and national health. Furthermore, both national decision-making policy and warning information will be provided to the government, as a result of this proposed project implementation.