iVOD / 160703

Field Value
IVOD_ID 160703
IVOD_URL https://ivod.ly.gov.tw/Play/Clip/1M/160703
日期 2025-04-28
會議資料.會議代碼 委員會-11-3-26-8
會議資料.會議代碼:str 第11屆第3會期社會福利及衛生環境委員會第8次全體委員會議
會議資料.屆 11
會議資料.會期 3
會議資料.會次 8
會議資料.種類 委員會
會議資料.委員會代碼[0] 26
會議資料.委員會代碼:str[0] 社會福利及衛生環境委員會
會議資料.標題 第11屆第3會期社會福利及衛生環境委員會第8次全體委員會議
影片種類 Clip
開始時間 2025-04-28T09:53:09+08:00
結束時間 2025-04-28T10:01:39+08:00
影片長度 00:08:30
支援功能[0] ai-transcript
video_url https://ivod-lyvod.cdn.hinet.net/vod_1/_definst_/mp4:1MClips/3f76a0bd18e4ae6a4ba2c82a87492db8e7917adb13da21616fd966abe25693d9c89ebdc37aa605965ea18f28b6918d91.mp4/playlist.m3u8
委員名稱 邱鎮軍
委員發言時間 09:53:09 - 10:01:39
會議時間 2025-04-28T09:00:00+08:00
會議名稱 立法院第11屆第3會期社會福利及衛生環境委員會第8次全體委員會議(事由:邀請環境部部長列席報告業務概況,並備質詢。)
transcript.pyannote[0].speaker SPEAKER_00
transcript.pyannote[0].start 3.59159375
transcript.pyannote[0].end 5.44784375
transcript.pyannote[1].speaker SPEAKER_00
transcript.pyannote[1].start 5.59971875
transcript.pyannote[1].end 6.88221875
transcript.pyannote[2].speaker SPEAKER_00
transcript.pyannote[2].start 8.77221875
transcript.pyannote[2].end 10.64534375
transcript.pyannote[3].speaker SPEAKER_00
transcript.pyannote[3].start 11.15159375
transcript.pyannote[3].end 12.88971875
transcript.pyannote[4].speaker SPEAKER_00
transcript.pyannote[4].start 13.19346875
transcript.pyannote[4].end 39.72096875
transcript.pyannote[5].speaker SPEAKER_01
transcript.pyannote[5].start 22.12034375
transcript.pyannote[5].end 22.44096875
transcript.pyannote[6].speaker SPEAKER_01
transcript.pyannote[6].start 39.72096875
transcript.pyannote[6].end 57.54096875
transcript.pyannote[7].speaker SPEAKER_00
transcript.pyannote[7].start 57.54096875
transcript.pyannote[7].end 57.59159375
transcript.pyannote[8].speaker SPEAKER_01
transcript.pyannote[8].start 57.59159375
transcript.pyannote[8].end 57.76034375
transcript.pyannote[9].speaker SPEAKER_00
transcript.pyannote[9].start 57.76034375
transcript.pyannote[9].end 70.97346875
transcript.pyannote[10].speaker SPEAKER_00
transcript.pyannote[10].start 71.41221875
transcript.pyannote[10].end 72.18846875
transcript.pyannote[11].speaker SPEAKER_00
transcript.pyannote[11].start 72.30659375
transcript.pyannote[11].end 81.33471875
transcript.pyannote[12].speaker SPEAKER_01
transcript.pyannote[12].start 81.41909375
transcript.pyannote[12].end 83.03909375
transcript.pyannote[13].speaker SPEAKER_01
transcript.pyannote[13].start 83.32596875
transcript.pyannote[13].end 84.52409375
transcript.pyannote[14].speaker SPEAKER_00
transcript.pyannote[14].start 83.57909375
transcript.pyannote[14].end 84.70971875
transcript.pyannote[15].speaker SPEAKER_01
transcript.pyannote[15].start 84.57471875
transcript.pyannote[15].end 99.49221875
transcript.pyannote[16].speaker SPEAKER_00
transcript.pyannote[16].start 89.02971875
transcript.pyannote[16].end 89.26596875
transcript.pyannote[17].speaker SPEAKER_00
transcript.pyannote[17].start 98.47971875
transcript.pyannote[17].end 100.38659375
transcript.pyannote[18].speaker SPEAKER_01
transcript.pyannote[18].start 100.30221875
transcript.pyannote[18].end 106.05659375
transcript.pyannote[19].speaker SPEAKER_00
transcript.pyannote[19].start 106.05659375
transcript.pyannote[19].end 106.93409375
transcript.pyannote[20].speaker SPEAKER_01
transcript.pyannote[20].start 106.93409375
transcript.pyannote[20].end 107.03534375
transcript.pyannote[21].speaker SPEAKER_00
transcript.pyannote[21].start 107.03534375
transcript.pyannote[21].end 107.28846875
transcript.pyannote[22].speaker SPEAKER_01
transcript.pyannote[22].start 107.28846875
transcript.pyannote[22].end 112.03034375
transcript.pyannote[23].speaker SPEAKER_00
transcript.pyannote[23].start 110.91659375
transcript.pyannote[23].end 111.97971875
transcript.pyannote[24].speaker SPEAKER_00
transcript.pyannote[24].start 112.03034375
transcript.pyannote[24].end 112.78971875
transcript.pyannote[25].speaker SPEAKER_01
transcript.pyannote[25].start 112.78971875
transcript.pyannote[25].end 112.95846875
transcript.pyannote[26].speaker SPEAKER_00
transcript.pyannote[26].start 112.95846875
transcript.pyannote[26].end 112.97534375
transcript.pyannote[27].speaker SPEAKER_01
transcript.pyannote[27].start 112.97534375
transcript.pyannote[27].end 115.23659375
transcript.pyannote[28].speaker SPEAKER_00
transcript.pyannote[28].start 113.07659375
transcript.pyannote[28].end 116.62034375
transcript.pyannote[29].speaker SPEAKER_01
transcript.pyannote[29].start 116.29971875
transcript.pyannote[29].end 130.55909375
transcript.pyannote[30].speaker SPEAKER_00
transcript.pyannote[30].start 129.63096875
transcript.pyannote[30].end 134.96346875
transcript.pyannote[31].speaker SPEAKER_01
transcript.pyannote[31].start 134.13659375
transcript.pyannote[31].end 135.01409375
transcript.pyannote[32].speaker SPEAKER_00
transcript.pyannote[32].start 134.98034375
transcript.pyannote[32].end 170.92409375
transcript.pyannote[33].speaker SPEAKER_01
transcript.pyannote[33].start 170.92409375
transcript.pyannote[33].end 171.63284375
transcript.pyannote[34].speaker SPEAKER_00
transcript.pyannote[34].start 171.63284375
transcript.pyannote[34].end 179.63159375
transcript.pyannote[35].speaker SPEAKER_01
transcript.pyannote[35].start 178.55159375
transcript.pyannote[35].end 178.78784375
transcript.pyannote[36].speaker SPEAKER_01
transcript.pyannote[36].start 179.80034375
transcript.pyannote[36].end 191.64659375
transcript.pyannote[37].speaker SPEAKER_00
transcript.pyannote[37].start 189.09846875
transcript.pyannote[37].end 191.78159375
transcript.pyannote[38].speaker SPEAKER_01
transcript.pyannote[38].start 191.78159375
transcript.pyannote[38].end 191.88284375
transcript.pyannote[39].speaker SPEAKER_00
transcript.pyannote[39].start 191.88284375
transcript.pyannote[39].end 191.93346875
transcript.pyannote[40].speaker SPEAKER_02
transcript.pyannote[40].start 192.84471875
transcript.pyannote[40].end 195.49409375
transcript.pyannote[41].speaker SPEAKER_00
transcript.pyannote[41].start 196.03409375
transcript.pyannote[41].end 205.92284375
transcript.pyannote[42].speaker SPEAKER_02
transcript.pyannote[42].start 207.08721875
transcript.pyannote[42].end 207.22221875
transcript.pyannote[43].speaker SPEAKER_02
transcript.pyannote[43].start 207.54284375
transcript.pyannote[43].end 209.24721875
transcript.pyannote[44].speaker SPEAKER_00
transcript.pyannote[44].start 209.80409375
transcript.pyannote[44].end 221.22846875
transcript.pyannote[45].speaker SPEAKER_02
transcript.pyannote[45].start 221.66721875
transcript.pyannote[45].end 223.52346875
transcript.pyannote[46].speaker SPEAKER_00
transcript.pyannote[46].start 223.05096875
transcript.pyannote[46].end 224.92409375
transcript.pyannote[47].speaker SPEAKER_02
transcript.pyannote[47].start 224.24909375
transcript.pyannote[47].end 230.88096875
transcript.pyannote[48].speaker SPEAKER_00
transcript.pyannote[48].start 230.52659375
transcript.pyannote[48].end 232.85534375
transcript.pyannote[49].speaker SPEAKER_00
transcript.pyannote[49].start 233.27721875
transcript.pyannote[49].end 234.64409375
transcript.pyannote[50].speaker SPEAKER_00
transcript.pyannote[50].start 235.74096875
transcript.pyannote[50].end 237.47909375
transcript.pyannote[51].speaker SPEAKER_02
transcript.pyannote[51].start 237.79971875
transcript.pyannote[51].end 240.63471875
transcript.pyannote[52].speaker SPEAKER_02
transcript.pyannote[52].start 240.73596875
transcript.pyannote[52].end 242.54159375
transcript.pyannote[53].speaker SPEAKER_00
transcript.pyannote[53].start 240.75284375
transcript.pyannote[53].end 244.14471875
transcript.pyannote[54].speaker SPEAKER_02
transcript.pyannote[54].start 244.76909375
transcript.pyannote[54].end 248.70096875
transcript.pyannote[55].speaker SPEAKER_00
transcript.pyannote[55].start 248.86971875
transcript.pyannote[55].end 251.04659375
transcript.pyannote[56].speaker SPEAKER_02
transcript.pyannote[56].start 251.41784375
transcript.pyannote[56].end 257.96534375
transcript.pyannote[57].speaker SPEAKER_00
transcript.pyannote[57].start 257.15534375
transcript.pyannote[57].end 262.38659375
transcript.pyannote[58].speaker SPEAKER_02
transcript.pyannote[58].start 259.09596875
transcript.pyannote[58].end 259.56846875
transcript.pyannote[59].speaker SPEAKER_00
transcript.pyannote[59].start 262.47096875
transcript.pyannote[59].end 263.02784375
transcript.pyannote[60].speaker SPEAKER_00
transcript.pyannote[60].start 263.51721875
transcript.pyannote[60].end 293.63909375
transcript.pyannote[61].speaker SPEAKER_01
transcript.pyannote[61].start 293.63909375
transcript.pyannote[61].end 300.30471875
transcript.pyannote[62].speaker SPEAKER_00
transcript.pyannote[62].start 299.52846875
transcript.pyannote[62].end 301.85721875
transcript.pyannote[63].speaker SPEAKER_01
transcript.pyannote[63].start 301.85721875
transcript.pyannote[63].end 302.92034375
transcript.pyannote[64].speaker SPEAKER_00
transcript.pyannote[64].start 302.63346875
transcript.pyannote[64].end 306.54846875
transcript.pyannote[65].speaker SPEAKER_01
transcript.pyannote[65].start 307.05471875
transcript.pyannote[65].end 307.34159375
transcript.pyannote[66].speaker SPEAKER_02
transcript.pyannote[66].start 307.34159375
transcript.pyannote[66].end 309.60284375
transcript.pyannote[67].speaker SPEAKER_00
transcript.pyannote[67].start 309.60284375
transcript.pyannote[67].end 324.06471875
transcript.pyannote[68].speaker SPEAKER_02
transcript.pyannote[68].start 310.53096875
transcript.pyannote[68].end 310.86846875
transcript.pyannote[69].speaker SPEAKER_01
transcript.pyannote[69].start 324.38534375
transcript.pyannote[69].end 324.72284375
transcript.pyannote[70].speaker SPEAKER_01
transcript.pyannote[70].start 325.11096875
transcript.pyannote[70].end 328.40159375
transcript.pyannote[71].speaker SPEAKER_00
transcript.pyannote[71].start 325.14471875
transcript.pyannote[71].end 325.80284375
transcript.pyannote[72].speaker SPEAKER_00
transcript.pyannote[72].start 328.24971875
transcript.pyannote[72].end 335.53971875
transcript.pyannote[73].speaker SPEAKER_01
transcript.pyannote[73].start 330.32534375
transcript.pyannote[73].end 330.96659375
transcript.pyannote[74].speaker SPEAKER_00
transcript.pyannote[74].start 335.79284375
transcript.pyannote[74].end 338.08784375
transcript.pyannote[75].speaker SPEAKER_01
transcript.pyannote[75].start 338.35784375
transcript.pyannote[75].end 345.02346875
transcript.pyannote[76].speaker SPEAKER_00
transcript.pyannote[76].start 345.02346875
transcript.pyannote[76].end 345.07409375
transcript.pyannote[77].speaker SPEAKER_01
transcript.pyannote[77].start 345.07409375
transcript.pyannote[77].end 348.12846875
transcript.pyannote[78].speaker SPEAKER_00
transcript.pyannote[78].start 345.10784375
transcript.pyannote[78].end 346.23846875
transcript.pyannote[79].speaker SPEAKER_00
transcript.pyannote[79].start 348.21284375
transcript.pyannote[79].end 359.14784375
transcript.pyannote[80].speaker SPEAKER_00
transcript.pyannote[80].start 359.45159375
transcript.pyannote[80].end 388.96596875
transcript.pyannote[81].speaker SPEAKER_01
transcript.pyannote[81].start 367.51784375
transcript.pyannote[81].end 367.85534375
transcript.pyannote[82].speaker SPEAKER_01
transcript.pyannote[82].start 388.96596875
transcript.pyannote[82].end 414.83534375
transcript.pyannote[83].speaker SPEAKER_00
transcript.pyannote[83].start 406.26284375
transcript.pyannote[83].end 408.91221875
transcript.pyannote[84].speaker SPEAKER_00
transcript.pyannote[84].start 411.34221875
transcript.pyannote[84].end 411.73034375
transcript.pyannote[85].speaker SPEAKER_00
transcript.pyannote[85].start 413.11409375
transcript.pyannote[85].end 414.07596875
transcript.pyannote[86].speaker SPEAKER_00
transcript.pyannote[86].start 414.41346875
transcript.pyannote[86].end 429.17909375
transcript.pyannote[87].speaker SPEAKER_01
transcript.pyannote[87].start 421.80471875
transcript.pyannote[87].end 422.83409375
transcript.pyannote[88].speaker SPEAKER_01
transcript.pyannote[88].start 428.58846875
transcript.pyannote[88].end 429.58409375
transcript.pyannote[89].speaker SPEAKER_00
transcript.pyannote[89].start 429.58409375
transcript.pyannote[89].end 430.61346875
transcript.pyannote[90].speaker SPEAKER_01
transcript.pyannote[90].start 430.84971875
transcript.pyannote[90].end 435.96284375
transcript.pyannote[91].speaker SPEAKER_00
transcript.pyannote[91].start 435.79409375
transcript.pyannote[91].end 435.94596875
transcript.pyannote[92].speaker SPEAKER_00
transcript.pyannote[92].start 435.96284375
transcript.pyannote[92].end 435.97971875
transcript.pyannote[93].speaker SPEAKER_01
transcript.pyannote[93].start 435.97971875
transcript.pyannote[93].end 436.03034375
transcript.pyannote[94].speaker SPEAKER_00
transcript.pyannote[94].start 436.03034375
transcript.pyannote[94].end 440.73846875
transcript.pyannote[95].speaker SPEAKER_01
transcript.pyannote[95].start 437.65034375
transcript.pyannote[95].end 438.40971875
transcript.pyannote[96].speaker SPEAKER_01
transcript.pyannote[96].start 440.73846875
transcript.pyannote[96].end 447.67409375
transcript.pyannote[97].speaker SPEAKER_00
transcript.pyannote[97].start 441.00846875
transcript.pyannote[97].end 441.43034375
transcript.pyannote[98].speaker SPEAKER_00
transcript.pyannote[98].start 446.52659375
transcript.pyannote[98].end 451.79159375
transcript.pyannote[99].speaker SPEAKER_00
transcript.pyannote[99].start 452.38221875
transcript.pyannote[99].end 461.64659375
transcript.pyannote[100].speaker SPEAKER_01
transcript.pyannote[100].start 461.64659375
transcript.pyannote[100].end 461.84909375
transcript.pyannote[101].speaker SPEAKER_00
transcript.pyannote[101].start 461.84909375
transcript.pyannote[101].end 462.32159375
transcript.pyannote[102].speaker SPEAKER_01
transcript.pyannote[102].start 461.86596875
transcript.pyannote[102].end 461.88284375
transcript.pyannote[103].speaker SPEAKER_01
transcript.pyannote[103].start 462.10221875
transcript.pyannote[103].end 462.52409375
transcript.pyannote[104].speaker SPEAKER_00
transcript.pyannote[104].start 462.52409375
transcript.pyannote[104].end 471.18096875
transcript.pyannote[105].speaker SPEAKER_01
transcript.pyannote[105].start 471.56909375
transcript.pyannote[105].end 474.57284375
transcript.pyannote[106].speaker SPEAKER_00
transcript.pyannote[106].start 471.63659375
transcript.pyannote[106].end 472.12596875
transcript.pyannote[107].speaker SPEAKER_00
transcript.pyannote[107].start 474.03284375
transcript.pyannote[107].end 474.23534375
transcript.pyannote[108].speaker SPEAKER_00
transcript.pyannote[108].start 474.28596875
transcript.pyannote[108].end 492.74721875
transcript.pyannote[109].speaker SPEAKER_01
transcript.pyannote[109].start 492.74721875
transcript.pyannote[109].end 496.03784375
transcript.pyannote[110].speaker SPEAKER_00
transcript.pyannote[110].start 493.82721875
transcript.pyannote[110].end 505.48784375
transcript.pyannote[111].speaker SPEAKER_01
transcript.pyannote[111].start 504.42471875
transcript.pyannote[111].end 506.28096875
transcript.pyannote[112].speaker SPEAKER_00
transcript.pyannote[112].start 507.59721875
transcript.pyannote[112].end 507.61409375
transcript.pyannote[113].speaker SPEAKER_01
transcript.pyannote[113].start 507.61409375
transcript.pyannote[113].end 508.20471875
transcript.pyannote[114].speaker SPEAKER_01
transcript.pyannote[114].start 508.81221875
transcript.pyannote[114].end 508.93034375
transcript.pyannote[115].speaker SPEAKER_01
transcript.pyannote[115].start 509.60534375
transcript.pyannote[115].end 509.97659375
transcript.whisperx[0].start 3.855
transcript.whisperx[0].end 24.186
transcript.whisperx[0].text 主席好,我們請部長部長好從上任我就聽到你很積極在處理這個垃圾山的問題那112年裸露的垃圾原本是84萬公噸到去年年底下降到74.5萬公噸達成率大概是11%
transcript.whisperx[1].start 29.048
transcript.whisperx[1].end 44.886
transcript.whisperx[1].text 但今年我看這個四月又胖了我們的垃圾山又漲胖了那變成79.7萬公噸目標達成率又降到5.1%這是什麼原因第一個是因為過年第二個是去年颱風比較多所以整個又累積起來了
transcript.whisperx[2].start 45.447
transcript.whisperx[2].end 70.339
transcript.whisperx[2].text 那現在也跟委員報告大概是預計下半年我們因為這個計畫是包含了整個處理也要委外要發包那我們預計大概下半年應該數字就會降得比較快因為我看到比較擔心就是看到這個圖裸露的垃圾監控平台上面的實際值跟我們的目標值越分越開我還以為是這個壽成失敗
transcript.whisperx[3].start 71.48
transcript.whisperx[3].end 100.13
transcript.whisperx[3].text 那我們這個部分就是說我們部長說在原先在115年說要把這些清掉那現在進度會影響嗎明年的年底不要有裸露就是說我說的是裸露就是很多外面那個媒體說什麼叫裸露裸露就是說就是生垃圾在外面然後很多的蒼蠅很多的生態系鳥類你這個標準這樣很模糊啊
transcript.whisperx[4].start 100.39
transcript.whisperx[4].end 129.065
transcript.whisperx[4].text 喔 就是說你不要看到垃圾丟在這個一堆一個山上我們至少把它那跑到山上看還是看得到是吧呃 基本上上面會有覆土然後有的會打包喔 看還是就可以掩埋的你就把它掩埋一下對 你會去處理就可以燒的就會完全燒掉這樣的意思嗎對對 就是說等於是如果可以因為現在的情況就是說呃 這個處理的量能不夠所以只好裸露在那邊那野豹園因為大概有40快要接近50個地方那附近的居民喔 非常的辛苦
transcript.whisperx[5].start 129.885
transcript.whisperx[5].end 157.324
transcript.whisperx[5].text 那我希望部長加油啦不要說講了然後又忘記了2024年底我們太陽能發電大概是4.28G瓦如果民進黨政府還是我們不檢討這個能源政策我想要持續加速發展光電的話那接下來成長的數字可能會更可觀假設每年要每發電千瓦要用3.3片這個太陽面板
transcript.whisperx[6].start 159.105
transcript.whisperx[6].end 179.347
transcript.whisperx[6].text 那換算下來全台裝了4712萬片的太陽能板相當於94.2萬公噸那廢棄的太陽能板就會變成一個大問題對不對對 沒錯那我們在裝光電板的時候我記得經濟部會先收一些模組的回收費那這些錢在哪裡
transcript.whisperx[7].start 180.788
transcript.whisperx[7].end 209.043
transcript.whisperx[7].text 這個現在的是由能源署在代收,然後要處理的時候是由我們循環署跟業者會來前收了也交到這邊來嗎?有,我們會去申請過來現在收了多少錢?現在大概,給我們大概是一兩億有一兩億,那如果飛溪光電要丟,我們要先到我們環境部的網站去做填單對不對?沒錯是滿五十片才會清理嗎?對,要有一定的數量
transcript.whisperx[8].start 209.864
transcript.whisperx[8].end 234.636
transcript.whisperx[8].text 那我請教一下就是說像一般颱風啊或者是一些天災或者是一些小型的就是說小範圍的這個毀損那這些部分回收回來那這些東西他是先放哪裡因為他能買他可以他直接丟掉還是直接收暫存暫存那我們回收回來之後累積到一定的量那會送到那個我們的處理機構我們這邊有管制嘛這邊目前像這些漏下來的就是這些小範圍的啦
transcript.whisperx[9].start 237.884
transcript.whisperx[9].end 266.841
transcript.whisperx[9].text 小範圍的話基本上是他他要自己保管的還是他會直接丟資源回收如果是資源回收的話因為那個要除非是說是小的才有可能你沒有管制嘛像這部分就沒有嘛對不對小的部分就就是等於是說他自己加護他把他拿出來給清潔隊就直接清潔隊這樣處理掉嘛所以我還是覺得這個也是一個問題啦那如果有這樣的話你大概換算一下因為全台灣那麼多
transcript.whisperx[10].start 267.521
transcript.whisperx[10].end 293.353
transcript.whisperx[10].text 它因為雖然是每個範圍雖然數量不多但是這個集中起來就是一個數很大一個數字那我也不希望它變成我們另外一個以後對台灣來講對環境造成影響的一個問題那我希望這個我們環境部這個部分要多再做一個想一個辦法想一個機制讓業者或者是我們一般的回收業者他有一個方向可循好不好
transcript.whisperx[11].start 294.153
transcript.whisperx[11].end 306.5
transcript.whisperx[11].text 幫委員因為這個其實這個是一個資源再回收再利用那現在有五家那未來應該現在我們合格的只有五家對不對應該是我們四間甲級的一間乙級的嘛對不對他們年處理兩次多少
transcript.whisperx[12].start 308.083
transcript.whisperx[12].end 323.819
transcript.whisperx[12].text 年儲量十幾萬噸有到十幾萬嗎?那目前看起來這樣子應該還能因應因為我看到我大概抓了一下大概20到2035年我們每年會超過10萬公噸所以我們也就是說這些國內的這些業者目前還可以消化了
transcript.whisperx[13].start 324.48
transcript.whisperx[13].end 346.599
transcript.whisperx[13].text 是,好那你30年後之後才會慢慢的快速的增加對,31年才會到高峰嘛對不對那我們抓的資料大概3、5年就會每年會超過10萬噸多的我們是送到日本、德國是嗎?其實我們現在有個想法是應該要留在台灣內循環對,應該再回收再利用也會比較好這是一個珍貴的資源
transcript.whisperx[14].start 348.391
transcript.whisperx[14].end 367.111
transcript.whisperx[14].text 對啦 我們當然技術上我也請我們大家協助地方啦讓這個東西不要變成台灣一個問題它能夠繼續循環使用是最好那接下來我再請教就是說我們的這個碳費 碳盤查你們接下來要擴大溫室氣體排放量的盤查其中一個是醫學中心
transcript.whisperx[15].start 367.771
transcript.whisperx[15].end 387.859
transcript.whisperx[15].text 我比較擔心因為醫學中心他的工作內容很繁重那麼我也聽到之前有一些委員在質詢那我們也主要是不希望增加他們的工作負擔那部長說過我們大盤查採三不一沒有嘛那只要登錄就可以是嗎對 登錄所以登錄那是登錄什麼
transcript.whisperx[16].start 388.679
transcript.whisperx[16].end 405.897
transcript.whisperx[16].text 就是說很簡單就是插入你的工商憑證那我們已經跟台電有談好了就是說插入工商憑證之後我們會有一個網站插入工商憑證之後就撈你的電費下來那因為電費通常佔醫院大概八成的排碳量你大概就可以抓到它的排碳量有多少
transcript.whisperx[17].start 406.857
transcript.whisperx[17].end 430.385
transcript.whisperx[17].text 所以我們是抓抓大放小等於是抓大的那其實醫院不會增加醫院不用花時間去盤查對對對我們是希望這樣不要造成我們尤其醫院他本身的業務就很重了不要再增加他們的工作負擔是是不會那看起來我們的碳費遵守還是照一樣這個照原定的進度去進行嗎我們是跟著日本腳步
transcript.whisperx[18].start 431.245
transcript.whisperx[18].end 451.417
transcript.whisperx[18].text 其實日本早就在好幾年前就有地球溫暖化對策稅已經在走了所以我們是跟著他的腳步嘛那部長也在期待台灣會彎道超車嘛對我們期待是說疫情是大家關稅是很辛苦的啦大家還不知道因為最後的判決我現在就是比較擔心就是說我們期待彎道超車但是
transcript.whisperx[19].start 452.435
transcript.whisperx[19].end 470.369
transcript.whisperx[19].text 台灣不要彎道反車了因為現在平良心講我們看到日本的對川普的關稅手段是蠻強硬的那我看到我也希望我們賴政府跟我們的左內閣我們什麼都學日本那這部分關稅會學日本嗎
transcript.whisperx[20].start 472.331
transcript.whisperx[20].end 498.67
transcript.whisperx[20].text 這個關稅不是我的專長我希望說不要對內拿一把大刀啦對外卻一個屁都不敢放那當然我們希望我們對內對外該做對的事情不要說只會欺負我們自己國內的業者不會不會不會我們都有一些很好的輔導措施希望部長我們就不要政府不要再
transcript.whisperx[21].start 500.191
transcript.whisperx[21].end 504.48
transcript.whisperx[21].text 把這個企業的成本一直增加這樣對台灣不是好事啦好謝謝部長謝謝謝謝委員謝謝好謝謝