政府開放式巨量資料分析研究－以產業發展與空汙程度關聯性分析為例

10.29428/9789860544169.201801.0115

許家源；李冠榮

空氣汙染 ； 多元迴歸分析 ； 開放資料 ； Air pollution ； multiple regression analysis ； open data

NCS 2017 全國計算機會議

2017（2018 / 01 / 01）

608 - 613

繁體中文

現今，開放資料的資料量在全球急遽成長，有許多開放資料已由政府單位主動公開。本篇論文以政府開放資料研究產業發展與空汙程度關聯性，使用多元迴歸分析分析空氣品質測站資料、製造業生產指數、發電量統計、公路交通量及人口統計資料等，空氣汙染物排放量較嚴重的空氣汙染源，比較相對的影響力大小，以實證分析結果解釋我國各項污染源對PM2.5濃度的危險程度。研究最終證實，排放SOx相關的產業發展，與空氣惡化有所關聯，在未來我國產業發展，不應該只關注在PM2.5，SOx是另一個空氣惡化的元兇。

Today, the amount of open information in the global rapid growth, there are many open information has been openly open by the government units. In this paper, the paper analyzes the relationship between the development of the industry and the degree of air pollution, and analyzes the air quality station data, the manufacturing index, the power generation statistics, the traffic volume and the demographic data, and so on, using the multiple regression analysis. A more serious source of air pollution, the relative influence of the size of the empirical analysis of the results of China's pollution sources to explain the concentration of PM2.5 concentration. The study finally confirmed that SOxrelated industrial development, associated with the deterioration of the air in the future of China's industrial development, should not only focus on PM2.5, SOx is another culprit in the deterioration of the air.