環保專案成果報告查詢系統

專案計畫編號	1120233271
經費年度	112
計畫經費	6,730 千元
預算科目	固定污染源管制
專案開始日期	2023/02/18
專案結束日期	2023/11/30
專案主持人	曹志成
主辦單位	中區環境管理中心
承辦人	蕭雅文
執行單位	銓崴國際有限公司
專案分類	環境監測及檢測
中文關鍵字	物聯網、大數據、揮發性有機物、地理資訊系統
英文關鍵字	Internet of Things, Big data, Volatile Organic Compounds, Geographic Information System
協同主持人
共同主持人
計畫聯絡人	曹志成
計畫聯絡電話	02-27039565#
計畫聯絡信箱	terence@chenweivr.com

中文摘要	近年來，行政院環境部前身環保署率先推行空氣品質物聯網之佈建，全省已布建接近10,000顆IOT感測器。本計畫旨在透過先進的智慧稽查方法，針對中區五縣市，約3,700科IOT感測器，整合與分析其中氣象監測、污染源數據及空氣物聯網資料，即時掌握風險潛勢及污染源資訊，以有效執行污染查緝作業。計畫的三大核心目標包括實施智慧稽查，運用科學儀器進行實地驗證，並廣泛宣導教育推廣。在執行過程中，計畫團隊首先建置TrackAIR智慧稽查平台，介接不同來源的重要空品與氣象數據。這些數據不僅包括來自苗栗縣、臺中市、彰化縣、南投縣、雲林縣等五縣市的IoT感測器資料、還有各種尺度的風場資料，這對於進行高精度的氣象模式分析至關重要。藉由這個平台，團隊能夠即時判讀區域內污染事件熱點，並對每個污染事件進行溯源分析，除了依平台排名排放次數最高的工廠，並考慮幾個重要行業別或製程別，共提出10各月份共100家高污染潛勢廠家名單，針對這些名單進一步與各項許可與申報資料進行勾稽，以供後續決定進行現場調查的工廠安排。計畫期間共進行101廠次的現場巡查，並運用紅外線熱顯像測溫儀空拍攝21場次，紅外線氣體檢漏儀(Gas-FindIR) 33場次，提高巡查效率和準確性，其中確實在運作的計80家、現場有逸散及異味情況分別為4家及20家，並提出了一些需要進廠深度查核的對象建議。最終中區管理中心裁決進行了11家工廠的深度查核，檢測包括排放管道中總碳氫化合物(THC)及非甲烷總碳氫化合物(NMHC)7場次，排放管道氣態有機物採樣及檢測(NIEA A722) 4場次，排放管道異味污染物官能測定7場次。其中10間事業皆逕行告發成功，告發率達91%；進行檢測工廠8家中，6家檢測不符排放標準，不合格率達75%。證明了以這種新型態結合IoT大數據演算的智慧平台模式，的確可大幅提升查緝成功率，增進污染源管制的能力。在教育和推廣方面，計畫團隊致力於提高公眾對空氣污染問題和智慧稽查技術的認識。團隊製作了1支專業短片，撰寫5篇新聞稿，並舉辦一場專家會議和一場研討會，這些活動有效地提升了社會各界對計畫成果的關注和對空氣品質改善的支持。
中文關鍵字	物聯網、大數據、揮發性有機物、地理資訊系統

中文摘要

近年來，行政院環境部前身環保署率先推行空氣品質物聯網之佈建，全省已布建接近10,000顆IOT感測器。本計畫旨在透過先進的智慧稽查方法，針對中區五縣市，約3,700科IOT感測器，整合與分析其中氣象監測、污染源數據及空氣物聯網資料，即時掌握風險潛勢及污染源資訊，以有效執行污染查緝作業。計畫的三大核心目標包括實施智慧稽查，運用科學儀器進行實地驗證，並廣泛宣導教育推廣。在執行過程中，計畫團隊首先建置TrackAIR智慧稽查平台，介接不同來源的重要空品與氣象數據。這些數據不僅包括來自苗栗縣、臺中市、彰化縣、南投縣、雲林縣等五縣市的IoT感測器資料、還有各種尺度的風場資料，這對於進行高精度的氣象模式分析至關重要。藉由這個平台，團隊能夠即時判讀區域內污染事件熱點，並對每個污染事件進行溯源分析，除了依平台排名排放次數最高的工廠，並考慮幾個重要行業別或製程別，共提出10各月份共100家高污染潛勢廠家名單，針對這些名單進一步與各項許可與申報資料進行勾稽，以供後續決定進行現場調查的工廠安排。計畫期間共進行101廠次的現場巡查，並運用紅外線熱顯像測溫儀空拍攝21場次，紅外線氣體檢漏儀(Gas-FindIR) 33場次，提高巡查效率和準確性，其中確實在運作的計80家、現場有逸散及異味情況分別為4家及20家，並提出了一些需要進廠深度查核的對象建議。最終中區管理中心裁決進行了11家工廠的深度查核，檢測包括排放管道中總碳氫化合物(THC)及非甲烷總碳氫化合物(NMHC)7場次，排放管道氣態有機物採樣及檢測(NIEA A722) 4場次，排放管道異味污染物官能測定7場次。其中10間事業皆逕行告發成功，告發率達91%；進行檢測工廠8家中，6家檢測不符排放標準，不合格率達75%。證明了以這種新型態結合IoT大數據演算的智慧平台模式，的確可大幅提升查緝成功率，增進污染源管制的能力。在教育和推廣方面，計畫團隊致力於提高公眾對空氣污染問題和智慧稽查技術的認識。團隊製作了1支專業短片，撰寫5篇新聞稿，並舉辦一場專家會議和一場研討會，這些活動有效地提升了社會各界對計畫成果的關注和對空氣品質改善的支持。

中文關鍵字

物聯網、大數據、揮發性有機物、地理資訊系統

類型	檔名	檔案大小	說明	最新版公開日期
期末報告	112AA068成果報告定稿本_上傳用.pdf	9MB		2024/1/31 上午 12:00:00

摘要	In recent years, the Ministry of Environment, the predecessor of the Environmental Protection Administration (EPA) of the Executive Yuan has been at the forefront of deploying the Internet of Things (IoT) for air quality, with nearly 10,000 IoT sensors already deployed across the island. This project aims to utilize advanced smart inspection methods for approximately 3,700 IoT sensors in the central region's five counties and cities. It integrates and analyzes meteorological monitoring, pollution source data, and air IoT data to instantly grasp the potential risks and information about pollution sources, effectively executing pollution inspection operations. The three main objectives of the project include implementing smart inspections, conducting on-site verification using scientific instruments, and widely promoting education and awareness. During the execution, the project team first established the TrackAIR smart inspection platform, integrating crucial air quality and meteorological data from various sources. These data include IoT sensor data from five counties and cities, such as Miaoli County, Taichung City, Changhua County, Nantou County, and Yunlin County, as well as wind field data at various scales, crucial for high-precision meteorological model analysis. Through this platform, the team can instantly identify pollution event hotspots in the region, conduct traceability analysis for each pollution event, and propose a list of 100 high-pollution potential factories for further investigation, considering both the platform-ranked highest emission factories and several important industries or processes. This list is cross-referenced with various permits and declaration data for subsequent on-site investigations. Throughout the project, the team conducted 101 on-site inspections, using infrared thermal imaging thermometers for aerial shots in 21 instances, Gas-FindIR in 33 instances, enhancing on-site inspection efficiency and accuracy. Among the operational factories, 80 were verified, with 4 showing emissions and 20 exhibiting odor issues. The team suggested targets for in-depth factory inspections. Ultimately, the Central Region Management Center conducted in-depth inspections on 11 factories, including testing total hydrocarbons (THC) and non-methane total hydrocarbons (NMHC) in emission pipelines for 7 sessions, gas-phase organic compound sampling and testing (NIEA A722) for 4 sessions, and odor pollutants functional determination for 7 sessions. All 10 companies were successfully reported, achieving a reporting rate of 91%. Among the tested factories, 6 out of 8 did not meet emission standards, resulting in a non-compliance rate of 75%. This validates that the intelligent platform model combining IoT big data algorithms can significantly improve the success rate of inspections and enhance the ability to control pollution sources. In terms of education and promotion, the project team dedicated efforts to raise public awareness of air pollution issues and smart inspection technology. They produced a professional video, wrote 5 press releases, and organized an expert meeting and a seminar, effectively increasing societal interest in the project's outcomes and support for improving air quality.
英文關鍵字	Internet of Things, Big data, Volatile Organic Compounds, Geographic Information System

摘要

In recent years, the Ministry of Environment, the predecessor of the Environmental Protection Administration (EPA) of the Executive Yuan has been at the forefront of deploying the Internet of Things (IoT) for air quality, with nearly 10,000 IoT sensors already deployed across the island. This project aims to utilize advanced smart inspection methods for approximately 3,700 IoT sensors in the central region's five counties and cities. It integrates and analyzes meteorological monitoring, pollution source data, and air IoT data to instantly grasp the potential risks and information about pollution sources, effectively executing pollution inspection operations. The three main objectives of the project include implementing smart inspections, conducting on-site verification using scientific instruments, and widely promoting education and awareness. During the execution, the project team first established the TrackAIR smart inspection platform, integrating crucial air quality and meteorological data from various sources. These data include IoT sensor data from five counties and cities, such as Miaoli County, Taichung City, Changhua County, Nantou County, and Yunlin County, as well as wind field data at various scales, crucial for high-precision meteorological model analysis. Through this platform, the team can instantly identify pollution event hotspots in the region, conduct traceability analysis for each pollution event, and propose a list of 100 high-pollution potential factories for further investigation, considering both the platform-ranked highest emission factories and several important industries or processes. This list is cross-referenced with various permits and declaration data for subsequent on-site investigations. Throughout the project, the team conducted 101 on-site inspections, using infrared thermal imaging thermometers for aerial shots in 21 instances, Gas-FindIR in 33 instances, enhancing on-site inspection efficiency and accuracy. Among the operational factories, 80 were verified, with 4 showing emissions and 20 exhibiting odor issues. The team suggested targets for in-depth factory inspections. Ultimately, the Central Region Management Center conducted in-depth inspections on 11 factories, including testing total hydrocarbons (THC) and non-methane total hydrocarbons (NMHC) in emission pipelines for 7 sessions, gas-phase organic compound sampling and testing (NIEA A722) for 4 sessions, and odor pollutants functional determination for 7 sessions. All 10 companies were successfully reported, achieving a reporting rate of 91%. Among the tested factories, 6 out of 8 did not meet emission standards, resulting in a non-compliance rate of 75%. This validates that the intelligent platform model combining IoT big data algorithms can significantly improve the success rate of inspections and enhance the ability to control pollution sources. In terms of education and promotion, the project team dedicated efforts to raise public awareness of air pollution issues and smart inspection technology. They produced a professional video, wrote 5 press releases, and organized an expert meeting and a seminar, effectively increasing societal interest in the project's outcomes and support for improving air quality.

英文關鍵字

Internet of Things, Big data, Volatile Organic Compounds, Geographic Information System