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中國環境報報道 | 協同管控 快速實現空氣質量達標改善
聚光 發布時間:2022-01-14 聚光 來源(yuan): 聚光 瀏覽量:1731

  來源(yuan):中國環境報第8版

  2020年(nian)中央(yang)經(jing)濟(ji)工作(zuo)會議明(ming)(ming)確提出(chu),打(da)好污(wu)(wu)染(ran)(ran)(ran)防治攻堅戰,堅持方向不(bu)變、力(li)度不(bu)減(jian),突出(chu)精準(zhun)(zhun)治污(wu)(wu)、科學(xue)治污(wu)(wu)、依法治污(wu)(wu),推動(dong)生態環(huan)境(jing)質(zhi)量(liang)持續好轉。近(jin)年(nian)來(lai)大(da)氣污(wu)(wu)染(ran)(ran)(ran)治理(li)成效顯著,環(huan)境(jing)空(kong)氣質(zhi)量(liang)明(ming)(ming)顯改善,細(xi)(xi)顆粒物濃(nong)度明(ming)(ming)顯下降,重污(wu)(wu)染(ran)(ran)(ran)天氣明(ming)(ming)顯減(jian)少。但臭(chou)氧(yang)污(wu)(wu)染(ran)(ran)(ran)問題(ti)逐步顯現,濃(nong)度呈逐年(nian)上升態勢(shi),成為(wei)影響環(huan)境(jing)空(kong)氣質(zhi)量(liang)的又一重要污(wu)(wu)染(ran)(ran)(ran)物,加強細(xi)(xi)顆粒物和臭(chou)氧(yang)協同控制(zhi)成為(wei)改善環(huan)境(jing)空(kong)氣質(zhi)量(liang)的關鍵(jian)。大(da)氣污(wu)(wu)染(ran)(ran)(ran)防治工作(zuo)的艱巨(ju)性和復雜性,亟需監(jian)測(ce)科技(ji)力(li)量(liang)的支持。聚光(guang)科技(ji)(杭州)股份有限公司(以下簡稱“聚光(guang)科技(ji)”)成立于2002年(nian),經(jing)過近(jin)20年(nian)的發(fa)展,現已成為(wei)國內高端分析(xi)儀器儀表領軍企業,其自主研發(fa)的全(quan)流(liu)程監(jian)測(ce)設備技(ji)術成熟,已廣泛應(ying)用于眾多國家級/省級重點項(xiang)(xiang)目建(jian)設。通(tong)過多年(nian)技(ji)術研發(fa),公司目前取(qu)得專(zhuan)利800余(yu)項(xiang)(xiang),計算機軟件著作(zuo)權300余(yu)項(xiang)(xiang),主持或參與標準(zhun)(zhun)制(zhi)定70余(yu)項(xiang)(xiang),累計承擔國家和地方科技(ji)計劃(hua)項(xiang)(xiang)目100余(yu)項(xiang)(xiang)。


 強化多污染物協同管控 

  針(zhen)對(dui)大(da)(da)氣(qi)復合污(wu)(wu)(wu)(wu)染(ran)(ran)(ran)(ran)(ran)日(ri)(ri)益突出(chu)的問(wen)題,聚光(guang)科技準(zhun)確分(fen)析大(da)(da)氣(qi)復合污(wu)(wu)(wu)(wu)染(ran)(ran)(ran)(ran)(ran)成(cheng)因,強化(hua)(hua)(hua)(hua)(hua)多(duo)污(wu)(wu)(wu)(wu)染(ran)(ran)(ran)(ran)(ran)物(wu)協(xie)同管(guan)(guan)控(kong)(kong)(kong),落實污(wu)(wu)(wu)(wu)染(ran)(ran)(ran)(ran)(ran)源治(zhi)(zhi)理任務(wu),加快實現環(huan)境空(kong)(kong)(kong)氣(qi)質量(liang)(liang)改善,其《環(huan)境空(kong)(kong)(kong)氣(qi)質量(liang)(liang)達標管(guan)(guan)控(kong)(kong)(kong)服(fu)務(wu)方案》通過(guo)當地基礎數據分(fen)析,建(jian)立污(wu)(wu)(wu)(wu)染(ran)(ran)(ran)(ran)(ran)成(cheng)因案例(li)庫,掌握(wo)污(wu)(wu)(wu)(wu)染(ran)(ran)(ran)(ran)(ran)物(wu)歷史變化(hua)(hua)(hua)(hua)(hua)規律,指導多(duo)污(wu)(wu)(wu)(wu)染(ran)(ran)(ran)(ran)(ran)物(wu)的日(ri)(ri)常協(xie)同管(guan)(guan)控(kong)(kong)(kong)與重污(wu)(wu)(wu)(wu)染(ran)(ran)(ran)(ran)(ran)應(ying)急。采用細(xi)顆(ke)粒物(wu)(PM2.5)、可(ke)(ke)吸入顆(ke)粒物(wu)(PM10)、臭(chou)氧(O3)、二氧化(hua)(hua)(hua)(hua)(hua)硫(SO2)、二氧化(hua)(hua)(hua)(hua)(hua)氮(NO2)、一氧化(hua)(hua)(hua)(hua)(hua)碳(tan)(CO)、揮(hui)發性有機物(wu)(VOCs)、甲(jia)醛(HCOH)、過(guo)氧乙酰硝酸酯(PANs)、光(guang)解速率等多(duo)因子(zi)、全流程協(xie)同走(zou)航監(jian)測技術與激光(guang)雷達掃描技術,開展(zhan)重點地區(qu)走(zou)航摸排(pai),快速掌握(wo)區(qu)域(yu)污(wu)(wu)(wu)(wu)染(ran)(ran)(ran)(ran)(ran)物(wu)濃度與污(wu)(wu)(wu)(wu)染(ran)(ran)(ran)(ran)(ran)源時空(kong)(kong)(kong)分(fen)布狀況(kuang),識(shi)別(bie)熱點管(guan)(guan)控(kong)(kong)(kong)區(qu)域(yu)與時段;進(jin)一步(bu)結合車載顆(ke)粒物(wu)來源解析、臭(chou)氧光(guang)化(hua)(hua)(hua)(hua)(hua)學污(wu)(wu)(wu)(wu)染(ran)(ran)(ran)(ran)(ran)綜合監(jian)測系(xi)(xi)(xi)統,源排(pai)放清單及空(kong)(kong)(kong)氣(qi)質量(liang)(liang)模擬技術,分(fen)析各項(xiang)污(wu)(wu)(wu)(wu)染(ran)(ran)(ran)(ran)(ran)成(cheng)因與生成(cheng)機制,識(shi)別(bie)主要污(wu)(wu)(wu)(wu)染(ran)(ran)(ran)(ran)(ran)源類,定量(liang)(liang)評(ping)估一次、二次污(wu)(wu)(wu)(wu)染(ran)(ran)(ran)(ran)(ran)貢獻,識(shi)別(bie)重點管(guan)(guan)控(kong)(kong)(kong)行業,為從時、空(kong)(kong)(kong)、物(wu)各角(jiao)度制定差異(yi)化(hua)(hua)(hua)(hua)(hua)協(xie)同管(guan)(guan)控(kong)(kong)(kong)策(ce)(ce)略,提(ti)供決(jue)策(ce)(ce)支撐。依托多(duo)元數據分(fen)析成(cheng)果及相(xiang)關工作(zuo)流程與機制構(gou)建(jian)測管(guan)(guan)治(zhi)(zhi)一體(ti)化(hua)(hua)(hua)(hua)(hua)達標管(guan)(guan)控(kong)(kong)(kong)服(fu)務(wu)體(ti)系(xi)(xi)(xi),可(ke)(ke)根據區(qu)域(yu)、點位(wei)差異(yi)性,形成(cheng)日(ri)(ri)常與重污(wu)(wu)(wu)(wu)染(ran)(ran)(ran)(ran)(ran)分(fen)級(ji)管(guan)(guan)控(kong)(kong)(kong)策(ce)(ce)略,保障重點區(qu)域(yu)空(kong)(kong)(kong)氣(qi)質量(liang)(liang);針(zhen)對(dui)各類污(wu)(wu)(wu)(wu)染(ran)(ran)(ran)(ran)(ran)源形成(cheng)行業管(guan)(guan)理、治(zhi)(zhi)理體(ti)系(xi)(xi)(xi),落實污(wu)(wu)(wu)(wu)染(ran)(ran)(ran)(ran)(ran)源管(guan)(guan)治(zhi)(zhi)任務(wu),協(xie)同減少污(wu)(wu)(wu)(wu)染(ran)(ran)(ran)(ran)(ran)物(wu)排(pai)放;并多(duo)維(wei)度量(liang)(liang)化(hua)(hua)(hua)(hua)(hua)評(ping)估管(guan)(guan)控(kong)(kong)(kong)效果,確保及時發現問(wen)題,精(jing)準(zhun)定位(wei)問(wen)題,有效解決(jue)問(wen)題,實現環(huan)境空(kong)(kong)(kong)氣(qi)質量(liang)(liang)協(xie)同管(guan)(guan)控(kong)(kong)(kong),助力環(huan)境空(kong)(kong)(kong)氣(qi)質量(liang)(liang)持續改善。

  《環境(jing)空氣(qi)質量達(da)標管控服務方案(an)》已在海南省、宿州市(shi)、武(wu)威(wei)市(shi)、徐州市(shi)、聊城市(shi)、宜(yi)昌市(shi)等多個省市(shi)區進行了應用,并取得顯著(zhu)效果。方案(an)配置的核心在線監測(ce)設備均為(wei)公司(si)自產設備,各項技(ji)術(shu)指標均達(da)到國內領先水(shui)平,可為(wei)大氣(qi)污染防治(zhi)提供(gong)精準(zhun)數據(ju)支撐。




 

  管控提升空氣質量排名 

  2017年,聚光科(ke)技在歷史數(shu)據(ju)研判分析基礎(chu)上,采(cai)用(yong)空(kong)氣(qi)質量走(zou)(zou)航監(jian)測(ce)車、激光雷達監(jian)測(ce)車等技術對宿州市(shi)顆(ke)粒物的整體污(wu)(wu)(wu)染(ran)特征進行了摸排(pai)分析,并(bing)(bing)制定了管控(kong)策略。2018年-2019年,通過(guo)在當地組(zu)建技術組(zu)、走(zou)(zou)航巡(xun)查(cha)(cha)組(zu)等專業團隊,建立網(wang)格分級(ji)、部門聯動、污(wu)(wu)(wu)染(ran)巡(xun)查(cha)(cha)等機制,并(bing)(bing)提供動態研判分析、污(wu)(wu)(wu)染(ran)巡(xun)查(cha)(cha)處置、敏感點防控(kong)策略以及工地揚(yang)塵(chen)、散煤、餐飲油煙等污(wu)(wu)(wu)染(ran)源專項管控(kong)服務,逐步降低PM2.5濃(nong)度,提升(sheng)空(kong)氣(qi)質量排(pai)名。

  2018年(nian)宿州市PM2.5濃度明顯下降(jiang)(jiang),擺脫倒(dao)一,下降(jiang)(jiang)率全省(sheng)第3(-17.71%)。

  2019年宿州市PM2.5濃度明顯下降,下降率省內排(pai)名(ming)第1(-9.09%)。

  2019年1-12月宿州(zhou)市(shi)空氣質量改善幅(fu)度居168重點城市(shi)第(di)一。




 精準臭氧管控技術服務 

  2020年4月(yue),聚(ju)光(guang)科技進駐(zhu)湖北宜昌,利用當地基礎空氣質量(liang)監(jian)測數(shu)(shu)據、光(guang)化學(xue)全流程監(jian)測數(shu)(shu)據以及走航技術開(kai)(kai)展臭(chou)(chou)(chou)氧(yang)污染特(te)征(zheng)(zheng)分(fen)(fen)析、VOCs區域(yu)整體特(te)征(zheng)(zheng)摸排、臭(chou)(chou)(chou)氧(yang)成(cheng)因診斷及來(lai)源解析工(gong)作,并組(zu)建數(shu)(shu)據分(fen)(fen)析組(zu)、走航巡查(cha)(cha)組(zu),確定指導專家(jia),建立了宜昌市本地化臭(chou)(chou)(chou)氧(yang)研判分(fen)(fen)析機(ji)制(zhi)、日會商機(ji)制(zhi)、預報預警(jing)機(ji)制(zhi)。針對宜昌市工(gong)業企業、加(jia)油站等行(xing)業開(kai)(kai)展了拉網式巡查(cha)(cha)和突擊(ji)巡查(cha)(cha),形成(cheng)巡查(cha)(cha)問(wen)題臺賬,整理特(te)征(zheng)(zheng)因子庫,保障臭(chou)(chou)(chou)氧(yang)污染防治(zhi)工(gong)作有序推進。

  2019年5-8月(yue)均為不降(jiang)反升,2020年均改善為同比(bi)顯著下降(jiang)。變化(hua)率(lv)湖北省(sheng)內排名各月(yue)均有提升,2020年8月(yue)下降(jiang)率(lv)居全省(sheng)第一。

  優(you)(you)良(liang)(liang)天同(tong)(tong)比(bi)增(zeng)加(jia)(jia)21天。5月(yue)(yue)同(tong)(tong)比(bi)增(zeng)加(jia)(jia)3天;6月(yue)(yue)全(quan)月(yue)(yue)優(you)(you)良(liang)(liang),同(tong)(tong)比(bi)增(zeng)加(jia)(jia)7天;7月(yue)(yue)全(quan)月(yue)(yue)優(you)(you)良(liang)(liang),同(tong)(tong)比(bi)增(zeng)加(jia)(jia)4天;8月(yue)(yue)同(tong)(tong)比(bi)增(zeng)加(jia)(jia)7天。

  臭氧濃度顯著下(xia)(xia)降(jiang),6月同(tong)比(bi)(bi)下(xia)(xia)降(jiang)29μg/m3;7月同(tong)比(bi)(bi)下(xia)(xia)降(jiang)38μg/m3,8月同(tong)比(bi)(bi)下(xia)(xia)降(jiang)30μg/m3。

  2020年(nian)1-6月,宜昌市(shi)空(kong)氣質量(liang)改善幅度居全國(guo)168城市(shi)第(di)一(yi)。



 


 多項技術應用于重點項目中 

  聚光(guang)科技(ji)涉及(ji)顆(ke)粒物(wu)(wu)來(lai)(lai)源(yuan)解析、光(guang)化(hua)(hua)(hua)學(xue)(xue)(xue)(xue)(xue)反應全(quan)過程因子監(jian)(jian)(jian)測系列設(she)備(bei)技(ji)術(shu)成(cheng)熟(shu),已應用于眾多國家(jia)級(ji)(ji)(ji)/省(sheng)級(ji)(ji)(ji)重點項(xiang)目(mu)建(jian)(jian)(jian)設(she),可提供準確可靠的(de)(de)大氣(qi)污(wu)染監(jian)(jian)(jian)測數據,開展精(jing)細(xi)化(hua)(hua)(hua)污(wu)染成(cheng)因分(fen)析及(ji)精(jing)細(xi)化(hua)(hua)(hua)管控指導(dao),協助客戶(hu)實現大氣(qi)污(wu)染管控“產品-技(ji)術(shu)-服務(wu)應用”的(de)(de)一站(zhan)式購買(mai)。目(mu)前公司(si)(si)已建(jian)(jian)(jian)設(she)中國環境(jing)(jing)監(jian)(jian)(jian)測總站(zhan)國家(jia)大氣(qi)顆(ke)粒物(wu)(wu)組(zu)分(fen)-光(guang)化(hua)(hua)(hua)學(xue)(xue)(xue)(xue)(xue)監(jian)(jian)(jian)測網建(jian)(jian)(jian)設(she)項(xiang)目(mu),海(hai)南省(sheng)大氣(qi)復合(he)污(wu)染綜合(he)來(lai)(lai)源(yuan)解析項(xiang)目(mu)、廣東顆(ke)粒物(wu)(wu)組(zu)分(fen)監(jian)(jian)(jian)測網(二期)建(jian)(jian)(jian)設(she)項(xiang)目(mu)、浙(zhe)江(jiang)省(sheng)環境(jing)(jing)監(jian)(jian)(jian)測中心-杭州光(guang)化(hua)(hua)(hua)學(xue)(xue)(xue)(xue)(xue)監(jian)(jian)(jian)測網-金華光(guang)化(hua)(hua)(hua)學(xue)(xue)(xue)(xue)(xue)監(jian)(jian)(jian)測網、石家(jia)莊大氣(qi)復合(he)超級(ji)(ji)(ji)站(zhan)及(ji)應用項(xiang)目(mu)。此外,公司(si)(si)擁有(you)專業(ye)化(hua)(hua)(hua)數據分(fen)析服務(wu)團隊,均由國內(nei)雙一流(liu)高(gao)校(北京大學(xue)(xue)(xue)(xue)(xue)、浙(zhe)江(jiang)大學(xue)(xue)(xue)(xue)(xue)、復旦大學(xue)(xue)(xue)(xue)(xue)、南開大學(xue)(xue)(xue)(xue)(xue)等)碩博學(xue)(xue)(xue)(xue)(xue)歷的(de)(de)高(gao)素質人才組(zu)建(jian)(jian)(jian),并(bing)與國內(nei)知名(ming)高(gao)校、科研(yan)院所有(you)深入合(he)作。



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