環保專案成果報告查詢系統

專案計畫編號	YLEPB-107-057
經費年度	107
計畫經費	8,575 千元
專案開始日期	2018/11/24
專案結束日期	2019/11/23
專案主持人	林毓珣
主辦單位	雲林縣環境保護局
承辦人	曾建閔
執行單位	勤智興業有限公司
專案分類	大氣空氣
中文關鍵字	PM2.5檢測/指紋圖譜、PM2.5排放係數/排放量、空氣品質預報/分析系統優化、污染來源貢獻佔比分析、PM2.5管制策略成效評估
英文關鍵字	PM2.5 sources profile, Emission coefficients, Air quality forecast/analysis model, PM2.5 pollution sources analysis, Control strategies assessment
協同主持人
共同主持人
計畫聯絡人	白凱棣
計畫聯絡電話	02-22261158#
計畫聯絡信箱	al1990918@gamil.com

中文摘要	本計畫統計107年11月24日至108年11月23日為止，完成2次排放管道、6次農廢燃燒、4次金紙燃燒及2次柴油車排煙PM2.5採樣及指紋建置(包含離子成分、碳成分及金屬成分分析)；PM2.5排放量推估並與TEDS比對；空品預報系統優化提升準確性；污染分析系統優化提升污染源追縱能力，整合模式系統展示網頁；探討雲林縣PM2.5污染來源；評估策略減量成效提出政策建議；60天電台廣播及4場內部會議，整體達成率100%。粉煤溼底鍋爐皆以SO42-、EC、OC所佔比例最高，金屬元素以Al、Fe、Ca、Na、Mg、K等地殼元素為主，Ba元素為燃煤鍋爐之特徵元素。因物種分佈與105年檢測結果均一致，且本年度透過增加樣品數量以有效掌握污染源製程排放污染物之變異與排放特性，確認本計畫建置之雲林縣排放管道PM2.5指紋資料庫已具相當代表性。粉煤溼底鍋爐(塑化三廠C1、塑化二廠C2)過濾性PM2.5排放係數分別為104與20.1 g/ton，凝結性PM2.5排放係數分別為31.4與21.9 g/ton，較105年相同管道檢測為低，C1因增加樣品數量提升代表性，且檢測排放係數與六輕工業區大型燃煤鍋爐較相近，評估較105年檢測結果具代表性；C2推斷因已增設煙氣加熱設施(MGGH)，較105年檢測時未加裝該設備，可提升PM2.5去除效率所致。樟木及小葉欖仁枝葉燃燒PM2.5排放係數約1,000~2,600 mg/kg-AW，木麻黃約2,000~2,200 mg/Kg-AW。PM2.5指紋以碳為主要特徵，樟木及小葉欖仁的EC多於OC，木麻黃的OC多於EC，三樹種的離子特徵以Cl-、K+為主要，但木麻黃的Cl-、Na+遠高於K+，為海線行道樹農廢燃燒的特徵物種。宮廟及居商金紙燃燒PM2.5排放係數約1,400~1,650 mg/kg-AW，兩類金紙燃燒PM2.5指紋以元素碳為主要特徵，離子特徵有豐富的SO42-、Na+、Cl-，金屬元素以Na、K元素較豐富，為金紙燃燒的指標物種。柴油車所排放的粒狀物幾乎都是PM2.5，其中EC、OC與Na為柴油車PM2.5之特徵元素，柴油大貨車安裝濾煙器前後端過濾性PM2.5排放係數為0.19與0.01 g/km，凝結性PM2.5排放係數為0.498與0.509 g/km。顯示加裝濾煙器能有效改善過濾性PM2.5排放，但對凝結性PM2.5影響不大。推估雲林縣污染源PM2.5排放量，六輕大型燃煤鍋爐共19根管道過濾性FPM2.5排放量合計約721公噸/年，總PM2.5排放量(含凝結性微粒)合計約1,118公噸/年，相較TEDS10高出約2.1倍及3.3倍，顯示TEDS可能低估大型燃煤鍋爐PM2.5排放量。另檢測揚塵之粗細粒PM2.5/PM10係數，發現TEDS可能低估河川揚塵排放PM10中之PM2.5，特別是出海口揚塵之PM2.5排放潛勢高，及海線鄉鎮街道揚塵PM2.5排放較山線鄉鎮高之區域特性，可作為未來環保署建置新版TEDS之本土化係數調整參考。統計預報系統準確度，以當日小時濃度曾超過35μg/m3為事件日基準，事件日預報準確度(預報準確日數/總日數)達83%以上，已能準確預測境內及境外污染事件的發生；本年度預報系統更新排放清冊至TEDS10.0，並修正土地利用型態，各空品區統計指標都有獲得改善。污染來源分析系統則加入檢測之PM2.5氣膠指紋資料做為轉換係數，優化模式之光化模組表現。並整合展示網頁平台，每日提供GTx及CMAQ兩種模式PM2.5預報之空間分布圖及環保署觀測結果，及雲林四測站污染來源占比(工廠源、交通源及逸散源)，提供環保局作為啓動空品惡化前之預警應變決策參考依據。分析雲林縣PM2.5污染來源，斗六及崙背站於東風境內污染時，PM2.5主要來自國道1號交通源(柴油大貨車)、中部大型污染源(台中電廠)及鄰近工業區；麥寮及台西站PM2.5主要來自麥寮工業區、船舶及柴油車。模擬雲林縣、環保署及國營企業各項污染減量措施(固定/移動/面源)，若如期實施預估斗六、崙背、台西與麥寮站PM2.5年均減量可達8.16、4.12、3.44與3.07 μg/m3，其中管制移動源(柴油車汰換)與港區排放量對雲林縣PM2.5改善成效最顯著，而管制六輕工業區亦對下風處的嘉南縣市PM2.5改善有貢獻。
中文關鍵字	PM2.5檢測/指紋圖譜、PM2.5排放係數/排放量、空氣品質預報/分析系統優化、污染來源貢獻佔比分析、PM2.5管制策略成效評估

中文摘要

本計畫統計107年11月24日至108年11月23日為止，完成2次排放管道、6次農廢燃燒、4次金紙燃燒及2次柴油車排煙PM2.5採樣及指紋建置(包含離子成分、碳成分及金屬成分分析)；PM2.5排放量推估並與TEDS比對；空品預報系統優化提升準確性；污染分析系統優化提升污染源追縱能力，整合模式系統展示網頁；探討雲林縣PM2.5污染來源；評估策略減量成效提出政策建議；60天電台廣播及4場內部會議，整體達成率100%。粉煤溼底鍋爐皆以SO42-、EC、OC所佔比例最高，金屬元素以Al、Fe、Ca、Na、Mg、K等地殼元素為主，Ba元素為燃煤鍋爐之特徵元素。因物種分佈與105年檢測結果均一致，且本年度透過增加樣品數量以有效掌握污染源製程排放污染物之變異與排放特性，確認本計畫建置之雲林縣排放管道PM2.5指紋資料庫已具相當代表性。粉煤溼底鍋爐(塑化三廠C1、塑化二廠C2)過濾性PM2.5排放係數分別為104與20.1 g/ton，凝結性PM2.5排放係數分別為31.4與21.9 g/ton，較105年相同管道檢測為低，C1因增加樣品數量提升代表性，且檢測排放係數與六輕工業區大型燃煤鍋爐較相近，評估較105年檢測結果具代表性；C2推斷因已增設煙氣加熱設施(MGGH)，較105年檢測時未加裝該設備，可提升PM2.5去除效率所致。樟木及小葉欖仁枝葉燃燒PM2.5排放係數約1,000~2,600 mg/kg-AW，木麻黃約2,000~2,200 mg/Kg-AW。PM2.5指紋以碳為主要特徵，樟木及小葉欖仁的EC多於OC，木麻黃的OC多於EC，三樹種的離子特徵以Cl-、K+為主要，但木麻黃的Cl-、Na+遠高於K+，為海線行道樹農廢燃燒的特徵物種。宮廟及居商金紙燃燒PM2.5排放係數約1,400~1,650 mg/kg-AW，兩類金紙燃燒PM2.5指紋以元素碳為主要特徵，離子特徵有豐富的SO42-、Na+、Cl-，金屬元素以Na、K元素較豐富，為金紙燃燒的指標物種。柴油車所排放的粒狀物幾乎都是PM2.5，其中EC、OC與Na為柴油車PM2.5之特徵元素，柴油大貨車安裝濾煙器前後端過濾性PM2.5排放係數為0.19與0.01 g/km，凝結性PM2.5排放係數為0.498與0.509 g/km。顯示加裝濾煙器能有效改善過濾性PM2.5排放，但對凝結性PM2.5影響不大。推估雲林縣污染源PM2.5排放量，六輕大型燃煤鍋爐共19根管道過濾性FPM2.5排放量合計約721公噸/年，總PM2.5排放量(含凝結性微粒)合計約1,118公噸/年，相較TEDS10高出約2.1倍及3.3倍，顯示TEDS可能低估大型燃煤鍋爐PM2.5排放量。另檢測揚塵之粗細粒PM2.5/PM10係數，發現TEDS可能低估河川揚塵排放PM10中之PM2.5，特別是出海口揚塵之PM2.5排放潛勢高，及海線鄉鎮街道揚塵PM2.5排放較山線鄉鎮高之區域特性，可作為未來環保署建置新版TEDS之本土化係數調整參考。統計預報系統準確度，以當日小時濃度曾超過35μg/m3為事件日基準，事件日預報準確度(預報準確日數/總日數)達83%以上，已能準確預測境內及境外污染事件的發生；本年度預報系統更新排放清冊至TEDS10.0，並修正土地利用型態，各空品區統計指標都有獲得改善。污染來源分析系統則加入檢測之PM2.5氣膠指紋資料做為轉換係數，優化模式之光化模組表現。並整合展示網頁平台，每日提供GTx及CMAQ兩種模式PM2.5預報之空間分布圖及環保署觀測結果，及雲林四測站污染來源占比(工廠源、交通源及逸散源)，提供環保局作為啓動空品惡化前之預警應變決策參考依據。分析雲林縣PM2.5污染來源，斗六及崙背站於東風境內污染時，PM2.5主要來自國道1號交通源(柴油大貨車)、中部大型污染源(台中電廠)及鄰近工業區；麥寮及台西站PM2.5主要來自麥寮工業區、船舶及柴油車。模擬雲林縣、環保署及國營企業各項污染減量措施(固定/移動/面源)，若如期實施預估斗六、崙背、台西與麥寮站PM2.5年均減量可達8.16、4.12、3.44與3.07 μg/m3，其中管制移動源(柴油車汰換)與港區排放量對雲林縣PM2.5改善成效最顯著，而管制六輕工業區亦對下風處的嘉南縣市PM2.5改善有貢獻。

中文關鍵字

PM2.5檢測/指紋圖譜、PM2.5排放係數/排放量、空氣品質預報/分析系統優化、污染來源貢獻佔比分析、PM2.5管制策略成效評估

類型	檔名	檔案大小	說明	最新版公開日期
期末報告	YLEPB-107-057.DOC.pdf	30MB	期末報告定稿本	2020/2/20 上午 12:00:00

摘要	This year project implementation period from November 24, 2018 to November 23, 2019, completed 2 times discharge pipes flue gas, 6 times agricultural waste combustion, 4 times gold paper combustion and 2 times diesel vehicle PM2.5 sampling and chemical composition analysis, to establish the source profile , PM2.5 emission estimation and comparison with TEDS data, optimization of Air quality forecasting/Pollution analysis system to improve accuracy and pollution source tracking ability, PM2.5 pollution source analysis in different Meteorological Parameters ,and control strategy benefit assessment. And the completion of the 60-day radio broadcast and 4 internal meetings. The overall progress towards rate is 100%. PM2.5 emissions from coal-fired boiler are the highest in sulfate (SO42-) and carbon(EC,OC). The metal elements are mainly crustal elements such as Al, Fe, Ca, Na, Mg, and K, and Ba is a characteristic element of coal fired boiler. Because the PM2.5 species distribution is consistent with the sampling results in 2016, and this year results is obtained by increasing the number of samples to effectively master process variability and emission characteristics,it is confirmed that the PM2.5 source profile database established of coal-fired boiler at Yunlin County in this study has been quite representative. The filterable PM2.5 emission coefficient of coal-fired boiler (C1 and C2) is 104 g/ton and 20.1 g/ton,and the condensable PM2.5 emission coefficients is 31.4 g/ton and 21.9 g/ton, respectively, which are lower than the same coal-fired boiler pipeline sampling in 2016 study. C1 due to the increase in the number of samples to improve the representativeness,and the emission coefficient is similar to that of the large coal-fired boilers in the Mailiao industrial zones, and more representative than the sampling results in 2016. C2 concludes that the media gas-gas heater(MGGH) has been added, which can improve the PM2.5 removal efficiency compare when this equipment is not installed. The Camphor and Madagascar Almond agricultural waste burning PM2.5 sampling results showed PM2.5 emission coefficient are about 1,000~2,600 mg/kg-AW, and Casuarina is about 2,000~2,200 mg/Kg-AW. The major chemical composition is carbon. Among them, there are more elemental carbon(EC) in Camphor and Madagascar Almond, and there are more organic carbon(OC) in Casuarina. The ion characteristics of the three species are mainly chloride ion(Cl-) and potassium ion(K+), but Casuarina was Cl-, sodium ion(Na+) is much higher than K+, which is the characteristic species for burning of agricultural waste on the seaside street trees. The PM2.5 emission coefficient of gold paper burning is about 1,400~1,650 mg/kg-AW. The source profile of PM2.5 burning of two types of gold paper are mainly characterized by elemental carbon(EC). The ionic characteristics are relatively rich in sulfate(SO42-), sodium ion(Na+), chloride ion(Cl-), sodium(Na) and potassium (K), which are the major species for gold paper burning. Almost all particulates emitted by diesel vehicles are PM2.5. Among them, EC, OC and Na are the characteristic elements of PM2.5 for diesel vehicles. The diesel trucks which added the Diesel Particulate Filter(DPF),the filterable PM2.5 emission coefficient between DPF is 0.19 g/km and 0.01 g/km, the condensation PM2.5 emission coefficient between DPF is 0.498 g/km and 0.509 g/km. Shows that installing a DPF can effectively improve filterable PM2.5 removal, but has no effect on condensable PM2.5. Estimated PM2.5 emissions from pollution sources in Yunlin County. A total of 19 pipelines of the large-scale coal-fired boilers have a total filterable FPM2.5 emissions of about 721 T/yr. The total PM2.5 emissions (including condensable PM2.5) total about 1,118 T/yr, which is 2.1 times and 3.3 times higher than TEDS10 database, indicating that TEDS may underestimate PM2.5 emissions from coal-fired boilers. In addition, the PM2.5/PM10 coefficient of the dust of the sampling results, and it is found that TEDS may underestimate the PM2.5 in the PM10 emitted by river dust, especially the PM2.5 emission potential of the dust at the estuary, and the characteristics of the PM2.5 emissions from sea line township streets dust which is higher than the mountain line townships dust. It can be used as a reference for the localization coefficient adjustment of the new TEDS in the future for EPA. The accuracy of the event day forecast (accurate forecast days/total days) is more than 83%. which means that it can accurately predict domestic and foreign pollution events occurred. This year's forecast system updated the emissions database to TEDS10, and revised the land use pattern, and the statistical indicators of all air quality areas have improved. The pollution source analysis system adds the detected PM2.5 aerosol profile data as a conversion coefficient to optimize the performance of the photochemical module of the model. It also integrates the display web platform, and provides daily spatial distribution maps of PM2.5 forecasts in GTx and CMAQ modes, as well as the observation results of the EPA, and the proportion of pollution sources(factory, traffic, area sources). Provide EPA as a reference for early warning and emergency decision-making before the deterioration of the air quality deteriorates. Analyze the source of PM2.5 in Yunlin, At Douliu and Lunbei mainly comes from National Road No. 1(diesel truck), large central pollution source (Taichung Power Plant), and adjacent industrial areas; The PM2.5 at Mailiao and Taixi mainly come from Mailiao Industrial Zone, ships and diesel vehicles. Simulate various pollution reduction measures (factory, traffic, area sources) of Yunlin County, EPA and Public enterprise. If implemented as scheduled, the annual average reduction of PM2.5 in Douliu, Lunbei, Taixi and Mailiao can reach 8.16, 4.12, 3.44, and 3.07μg/m3, of which the control of mobile sources (diesel vehicle replacement) and port area emissions have the most significant effect on improving PM2.5 in Yunlin. And control Mailiao Industrial also has a contributed on Chiayi and Tainan city PM2.5 improvement.
英文關鍵字	PM2.5 sources profile, Emission coefficients, Air quality forecast/analysis model, PM2.5 pollution sources analysis, Control strategies assessment

摘要

This year project implementation period from November 24, 2018 to November 23, 2019, completed 2 times discharge pipes flue gas, 6 times agricultural waste combustion, 4 times gold paper combustion and 2 times diesel vehicle PM2.5 sampling and chemical composition analysis, to establish the source profile , PM2.5 emission estimation and comparison with TEDS data, optimization of Air quality forecasting/Pollution analysis system to improve accuracy and pollution source tracking ability, PM2.5 pollution source analysis in different Meteorological Parameters ,and control strategy benefit assessment. And the completion of the 60-day radio broadcast and 4 internal meetings. The overall progress towards rate is 100%. PM2.5 emissions from coal-fired boiler are the highest in sulfate (SO42-) and carbon(EC,OC). The metal elements are mainly crustal elements such as Al, Fe, Ca, Na, Mg, and K, and Ba is a characteristic element of coal fired boiler. Because the PM2.5 species distribution is consistent with the sampling results in 2016, and this year results is obtained by increasing the number of samples to effectively master process variability and emission characteristics,it is confirmed that the PM2.5 source profile database established of coal-fired boiler at Yunlin County in this study has been quite representative. The filterable PM2.5 emission coefficient of coal-fired boiler (C1 and C2) is 104 g/ton and 20.1 g/ton,and the condensable PM2.5 emission coefficients is 31.4 g/ton and 21.9 g/ton, respectively, which are lower than the same coal-fired boiler pipeline sampling in 2016 study. C1 due to the increase in the number of samples to improve the representativeness,and the emission coefficient is similar to that of the large coal-fired boilers in the Mailiao industrial zones, and more representative than the sampling results in 2016. C2 concludes that the media gas-gas heater(MGGH) has been added, which can improve the PM2.5 removal efficiency compare when this equipment is not installed. The Camphor and Madagascar Almond agricultural waste burning PM2.5 sampling results showed PM2.5 emission coefficient are about 1,000~2,600 mg/kg-AW, and Casuarina is about 2,000~2,200 mg/Kg-AW. The major chemical composition is carbon. Among them, there are more elemental carbon(EC) in Camphor and Madagascar Almond, and there are more organic carbon(OC) in Casuarina. The ion characteristics of the three species are mainly chloride ion(Cl-) and potassium ion(K+), but Casuarina was Cl-, sodium ion(Na+) is much higher than K+, which is the characteristic species for burning of agricultural waste on the seaside street trees. The PM2.5 emission coefficient of gold paper burning is about 1,400~1,650 mg/kg-AW. The source profile of PM2.5 burning of two types of gold paper are mainly characterized by elemental carbon(EC). The ionic characteristics are relatively rich in sulfate(SO42-), sodium ion(Na+), chloride ion(Cl-), sodium(Na) and potassium (K), which are the major species for gold paper burning. Almost all particulates emitted by diesel vehicles are PM2.5. Among them, EC, OC and Na are the characteristic elements of PM2.5 for diesel vehicles. The diesel trucks which added the Diesel Particulate Filter(DPF),the filterable PM2.5 emission coefficient between DPF is 0.19 g/km and 0.01 g/km, the condensation PM2.5 emission coefficient between DPF is 0.498 g/km and 0.509 g/km. Shows that installing a DPF can effectively improve filterable PM2.5 removal, but has no effect on condensable PM2.5. Estimated PM2.5 emissions from pollution sources in Yunlin County. A total of 19 pipelines of the large-scale coal-fired boilers have a total filterable FPM2.5 emissions of about 721 T/yr. The total PM2.5 emissions (including condensable PM2.5) total about 1,118 T/yr, which is 2.1 times and 3.3 times higher than TEDS10 database, indicating that TEDS may underestimate PM2.5 emissions from coal-fired boilers. In addition, the PM2.5/PM10 coefficient of the dust of the sampling results, and it is found that TEDS may underestimate the PM2.5 in the PM10 emitted by river dust, especially the PM2.5 emission potential of the dust at the estuary, and the characteristics of the PM2.5 emissions from sea line township streets dust which is higher than the mountain line townships dust. It can be used as a reference for the localization coefficient adjustment of the new TEDS in the future for EPA. The accuracy of the event day forecast (accurate forecast days/total days) is more than 83%. which means that it can accurately predict domestic and foreign pollution events occurred. This year's forecast system updated the emissions database to TEDS10, and revised the land use pattern, and the statistical indicators of all air quality areas have improved. The pollution source analysis system adds the detected PM2.5 aerosol profile data as a conversion coefficient to optimize the performance of the photochemical module of the model. It also integrates the display web platform, and provides daily spatial distribution maps of PM2.5 forecasts in GTx and CMAQ modes, as well as the observation results of the EPA, and the proportion of pollution sources(factory, traffic, area sources). Provide EPA as a reference for early warning and emergency decision-making before the deterioration of the air quality deteriorates. Analyze the source of PM2.5 in Yunlin, At Douliu and Lunbei mainly comes from National Road No. 1(diesel truck), large central pollution source (Taichung Power Plant), and adjacent industrial areas; The PM2.5 at Mailiao and Taixi mainly come from Mailiao Industrial Zone, ships and diesel vehicles. Simulate various pollution reduction measures (factory, traffic, area sources) of Yunlin County, EPA and Public enterprise. If implemented as scheduled, the annual average reduction of PM2.5 in Douliu, Lunbei, Taixi and Mailiao can reach 8.16, 4.12, 3.44, and 3.07μg/m3, of which the control of mobile sources (diesel vehicle replacement) and port area emissions have the most significant effect on improving PM2.5 in Yunlin. And control Mailiao Industrial also has a contributed on Chiayi and Tainan city PM2.5 improvement.

英文關鍵字

PM2.5 sources profile, Emission coefficients, Air quality forecast/analysis model, PM2.5 pollution sources analysis, Control strategies assessment