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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(shi)間:2022-01-14 聚光 來源: 聚光 瀏(liu)覽量(liang):1731

  來源:中國環境報(bao)第(di)8版

  2020年(nian)(nian)(nian)中央經濟工(gong)作(zuo)會議明(ming)確提出,打好(hao)污(wu)(wu)(wu)(wu)染(ran)防治攻堅(jian)戰,堅(jian)持方(fang)向不(bu)變、力(li)度(du)(du)不(bu)減,突(tu)出精準治污(wu)(wu)(wu)(wu)、科(ke)學(xue)治污(wu)(wu)(wu)(wu)、依法(fa)治污(wu)(wu)(wu)(wu),推(tui)動生態(tai)(tai)環(huan)境質(zhi)量(liang)持續好(hao)轉。近年(nian)(nian)(nian)來大氣污(wu)(wu)(wu)(wu)染(ran)治理成(cheng)(cheng)效顯著,環(huan)境空氣質(zhi)量(liang)明(ming)顯改(gai)善,細顆粒物濃度(du)(du)明(ming)顯下降,重污(wu)(wu)(wu)(wu)染(ran)天(tian)氣明(ming)顯減少(shao)。但臭(chou)(chou)氧污(wu)(wu)(wu)(wu)染(ran)問(wen)題逐(zhu)步顯現(xian),濃度(du)(du)呈逐(zhu)年(nian)(nian)(nian)上升態(tai)(tai)勢,成(cheng)(cheng)為(wei)影響環(huan)境空氣質(zhi)量(liang)的(de)又一重要污(wu)(wu)(wu)(wu)染(ran)物,加強細顆粒物和臭(chou)(chou)氧協同(tong)控(kong)制(zhi)(zhi)成(cheng)(cheng)為(wei)改(gai)善環(huan)境空氣質(zhi)量(liang)的(de)關鍵。大氣污(wu)(wu)(wu)(wu)染(ran)防治工(gong)作(zuo)的(de)艱巨性(xing)和復雜性(xing),亟(ji)需(xu)監測科(ke)技(ji)力(li)量(liang)的(de)支持。聚(ju)光科(ke)技(ji)(杭州)股份(fen)有(you)限(xian)公(gong)司(以下簡稱(cheng)“聚(ju)光科(ke)技(ji)”)成(cheng)(cheng)立(li)于2002年(nian)(nian)(nian),經過(guo)近20年(nian)(nian)(nian)的(de)發展,現(xian)已成(cheng)(cheng)為(wei)國內高端分析儀器儀表領軍企業(ye),其自主研發的(de)全流程(cheng)監測設備技(ji)術(shu)成(cheng)(cheng)熟(shu),已廣泛應用于眾多(duo)國家級/省級重點項目(mu)建設。通(tong)過(guo)多(duo)年(nian)(nian)(nian)技(ji)術(shu)研發,公(gong)司目(mu)前取得專利800余(yu)項,計(ji)算(suan)機(ji)軟件著作(zuo)權(quan)300余(yu)項,主持或參(can)與標準制(zhi)(zhi)定70余(yu)項,累計(ji)承擔國家和地方(fang)科(ke)技(ji)計(ji)劃項目(mu)100余(yu)項。


 強化多污染物協同管控 

  針(zhen)對(dui)大(da)氣(qi)(qi)(qi)復合(he)污(wu)(wu)(wu)(wu)染(ran)(ran)(ran)(ran)(ran)日(ri)益(yi)突出的問(wen)題(ti)(ti),聚(ju)光(guang)(guang)科(ke)技準確(que)分析(xi)(xi)大(da)氣(qi)(qi)(qi)復合(he)污(wu)(wu)(wu)(wu)染(ran)(ran)(ran)(ran)(ran)成(cheng)(cheng)(cheng)因(yin),強化(hua)多污(wu)(wu)(wu)(wu)染(ran)(ran)(ran)(ran)(ran)物協(xie)(xie)同(tong)管(guan)(guan)(guan)(guan)控(kong)(kong),落(luo)實(shi)污(wu)(wu)(wu)(wu)染(ran)(ran)(ran)(ran)(ran)源(yuan)治(zhi)(zhi)理任務,加(jia)快實(shi)現環境(jing)空(kong)(kong)氣(qi)(qi)(qi)質(zhi)量(liang)改善,其《環境(jing)空(kong)(kong)氣(qi)(qi)(qi)質(zhi)量(liang)達(da)標管(guan)(guan)(guan)(guan)控(kong)(kong)服(fu)務方案(an)》通過(guo)當地(di)基(ji)礎數據(ju)分析(xi)(xi),建立污(wu)(wu)(wu)(wu)染(ran)(ran)(ran)(ran)(ran)成(cheng)(cheng)(cheng)因(yin)案(an)例庫,掌(zhang)握污(wu)(wu)(wu)(wu)染(ran)(ran)(ran)(ran)(ran)物歷史變化(hua)規律,指導多污(wu)(wu)(wu)(wu)染(ran)(ran)(ran)(ran)(ran)物的日(ri)常協(xie)(xie)同(tong)管(guan)(guan)(guan)(guan)控(kong)(kong)與(yu)(yu)(yu)重(zhong)污(wu)(wu)(wu)(wu)染(ran)(ran)(ran)(ran)(ran)應急(ji)。采(cai)用細顆(ke)粒物(PM2.5)、可吸(xi)入顆(ke)粒物(PM10)、臭(chou)氧(O3)、二氧化(hua)硫(SO2)、二氧化(hua)氮(NO2)、一(yi)氧化(hua)碳(CO)、揮發(fa)性有(you)機物(VOCs)、甲醛(HCOH)、過(guo)氧乙酰(xian)硝酸(suan)酯(PANs)、光(guang)(guang)解速率等多因(yin)子(zi)、全(quan)流程協(xie)(xie)同(tong)走(zou)航監(jian)測(ce)(ce)技術與(yu)(yu)(yu)激(ji)光(guang)(guang)雷(lei)達(da)掃(sao)描技術,開展重(zhong)點(dian)(dian)地(di)區(qu)(qu)(qu)走(zou)航摸(mo)排(pai),快速掌(zhang)握區(qu)(qu)(qu)域(yu)污(wu)(wu)(wu)(wu)染(ran)(ran)(ran)(ran)(ran)物濃度(du)與(yu)(yu)(yu)污(wu)(wu)(wu)(wu)染(ran)(ran)(ran)(ran)(ran)源(yuan)時(shi)空(kong)(kong)分布狀(zhuang)況,識別(bie)熱點(dian)(dian)管(guan)(guan)(guan)(guan)控(kong)(kong)區(qu)(qu)(qu)域(yu)與(yu)(yu)(yu)時(shi)段(duan);進一(yi)步(bu)結合(he)車載顆(ke)粒物來源(yuan)解析(xi)(xi)、臭(chou)氧光(guang)(guang)化(hua)學污(wu)(wu)(wu)(wu)染(ran)(ran)(ran)(ran)(ran)綜(zong)合(he)監(jian)測(ce)(ce)系(xi)統,源(yuan)排(pai)放清單及(ji)空(kong)(kong)氣(qi)(qi)(qi)質(zhi)量(liang)模(mo)擬技術,分析(xi)(xi)各(ge)項(xiang)污(wu)(wu)(wu)(wu)染(ran)(ran)(ran)(ran)(ran)成(cheng)(cheng)(cheng)因(yin)與(yu)(yu)(yu)生成(cheng)(cheng)(cheng)機制(zhi),識別(bie)主要污(wu)(wu)(wu)(wu)染(ran)(ran)(ran)(ran)(ran)源(yuan)類,定量(liang)評估一(yi)次、二次污(wu)(wu)(wu)(wu)染(ran)(ran)(ran)(ran)(ran)貢獻,識別(bie)重(zhong)點(dian)(dian)管(guan)(guan)(guan)(guan)控(kong)(kong)行業(ye),為從時(shi)、空(kong)(kong)、物各(ge)角度(du)制(zhi)定差異化(hua)協(xie)(xie)同(tong)管(guan)(guan)(guan)(guan)控(kong)(kong)策略,提供(gong)決策支撐(cheng)。依托多元數據(ju)分析(xi)(xi)成(cheng)(cheng)(cheng)果(guo)及(ji)相(xiang)關工作流程與(yu)(yu)(yu)機制(zhi)構建測(ce)(ce)管(guan)(guan)(guan)(guan)治(zhi)(zhi)一(yi)體化(hua)達(da)標管(guan)(guan)(guan)(guan)控(kong)(kong)服(fu)務體系(xi),可根據(ju)區(qu)(qu)(qu)域(yu)、點(dian)(dian)位差異性,形成(cheng)(cheng)(cheng)日(ri)常與(yu)(yu)(yu)重(zhong)污(wu)(wu)(wu)(wu)染(ran)(ran)(ran)(ran)(ran)分級(ji)管(guan)(guan)(guan)(guan)控(kong)(kong)策略,保障重(zhong)點(dian)(dian)區(qu)(qu)(qu)域(yu)空(kong)(kong)氣(qi)(qi)(qi)質(zhi)量(liang);針(zhen)對(dui)各(ge)類污(wu)(wu)(wu)(wu)染(ran)(ran)(ran)(ran)(ran)源(yuan)形成(cheng)(cheng)(cheng)行業(ye)管(guan)(guan)(guan)(guan)理、治(zhi)(zhi)理體系(xi),落(luo)實(shi)污(wu)(wu)(wu)(wu)染(ran)(ran)(ran)(ran)(ran)源(yuan)管(guan)(guan)(guan)(guan)治(zhi)(zhi)任務,協(xie)(xie)同(tong)減(jian)少污(wu)(wu)(wu)(wu)染(ran)(ran)(ran)(ran)(ran)物排(pai)放;并多維(wei)度(du)量(liang)化(hua)評估管(guan)(guan)(guan)(guan)控(kong)(kong)效(xiao)果(guo),確(que)保及(ji)時(shi)發(fa)現問(wen)題(ti)(ti),精(jing)準定位問(wen)題(ti)(ti),有(you)效(xiao)解決問(wen)題(ti)(ti),實(shi)現環境(jing)空(kong)(kong)氣(qi)(qi)(qi)質(zhi)量(liang)協(xie)(xie)同(tong)管(guan)(guan)(guan)(guan)控(kong)(kong),助力環境(jing)空(kong)(kong)氣(qi)(qi)(qi)質(zhi)量(liang)持續(xu)改善。

  《環境空氣質量達標管控服(fu)務(wu)方案》已(yi)在海南省、宿州市(shi)、武(wu)威市(shi)、徐(xu)州市(shi)、聊城市(shi)、宜昌市(shi)等多個省市(shi)區進行了(le)應用,并(bing)取得(de)顯著效果。方案配(pei)置的核心在線監測設(she)備(bei)均為公司自產設(she)備(bei),各項(xiang)技術指標均達到國內領先(xian)水平,可為大(da)氣污染(ran)防治(zhi)提供精準數據支撐。




 

  管控提升空氣質量排名 

  2017年(nian),聚光科技在歷史數據研判分析(xi)基礎上,采用空(kong)氣質量走(zou)航監測車、激光雷達監測車等(deng)技術對宿州市(shi)顆粒物的整體(ti)污(wu)染(ran)特征進行(xing)了摸排分析(xi),并(bing)(bing)制(zhi)定了管(guan)控策略。2018年(nian)-2019年(nian),通過在當地組(zu)建技術組(zu)、走(zou)航巡查(cha)(cha)組(zu)等(deng)專(zhuan)業團隊,建立網格分級、部門聯動(dong)、污(wu)染(ran)巡查(cha)(cha)等(deng)機制(zhi),并(bing)(bing)提(ti)供動(dong)態研判分析(xi)、污(wu)染(ran)巡查(cha)(cha)處置、敏感點防控策略以及工地揚塵、散煤(mei)、餐(can)飲油煙等(deng)污(wu)染(ran)源專(zhuan)項(xiang)管(guan)控服務,逐步降低PM2.5濃度,提(ti)升空(kong)氣質量排名。

  2018年(nian)宿州市PM2.5濃(nong)度明(ming)顯下降(jiang),擺脫(tuo)倒一,下降(jiang)率全省第(di)3(-17.71%)。

  2019年宿州市PM2.5濃度明顯(xian)下降,下降率(lv)省內排名第1(-9.09%)。

  2019年(nian)1-12月宿州市空氣(qi)質量改善(shan)幅度(du)居168重點城(cheng)市第一。




 精準臭氧管控技術服務 

  2020年4月(yue),聚(ju)光科技(ji)進(jin)駐(zhu)湖(hu)北宜昌(chang),利用當地基礎空(kong)氣質量監(jian)測(ce)數(shu)據、光化學全流程監(jian)測(ce)數(shu)據以及走航技(ji)術(shu)開展(zhan)臭氧(yang)污染特(te)征(zheng)(zheng)分析、VOCs區域整體特(te)征(zheng)(zheng)摸排(pai)、臭氧(yang)成因診斷及來源解析工(gong)作,并組(zu)(zu)建數(shu)據分析組(zu)(zu)、走航巡(xun)查組(zu)(zu),確定指導專(zhuan)家,建立了宜昌(chang)市(shi)(shi)本地化臭氧(yang)研判(pan)分析機制(zhi)、日會(hui)商機制(zhi)、預報預警(jing)機制(zhi)。針對宜昌(chang)市(shi)(shi)工(gong)業(ye)企(qi)業(ye)、加(jia)油站等行(xing)業(ye)開展(zhan)了拉網式巡(xun)查和突擊巡(xun)查,形成巡(xun)查問題臺(tai)賬,整理特(te)征(zheng)(zheng)因子(zi)庫,保(bao)障臭氧(yang)污染防治(zhi)工(gong)作有序推(tui)進(jin)。

  2019年5-8月均為(wei)不降(jiang)反升(sheng),2020年均改(gai)善為(wei)同比顯著(zhu)下降(jiang)。變化率(lv)湖(hu)北省內排名各(ge)月均有(you)提(ti)升(sheng),2020年8月下降(jiang)率(lv)居全省第一。

  優良天(tian)同比(bi)(bi)增(zeng)加21天(tian)。5月(yue)同比(bi)(bi)增(zeng)加3天(tian);6月(yue)全月(yue)優良,同比(bi)(bi)增(zeng)加7天(tian);7月(yue)全月(yue)優良,同比(bi)(bi)增(zeng)加4天(tian);8月(yue)同比(bi)(bi)增(zeng)加7天(tian)。

  臭氧濃度顯著下降,6月(yue)(yue)同(tong)(tong)比下降29μg/m3;7月(yue)(yue)同(tong)(tong)比下降38μg/m3,8月(yue)(yue)同(tong)(tong)比下降30μg/m3。

  2020年(nian)1-6月,宜昌市(shi)(shi)空氣(qi)質量改善幅度居全國168城市(shi)(shi)第一。



 


 多項技術應用于重點項目中 

  聚光科技(ji)涉及(ji)顆粒(li)(li)物(wu)來源解(jie)析、光化學(xue)(xue)(xue)(xue)反應全過程因子(zi)監測系列設(she)(she)備技(ji)術成熟,已應用(yong)于眾多國(guo)(guo)家級/省(sheng)級重點項(xiang)目(mu)建設(she)(she),可提供準確可靠的大(da)(da)(da)(da)氣(qi)污(wu)染監測數據,開展精細(xi)化污(wu)染成因分(fen)析及(ji)精細(xi)化管控指(zhi)導,協助客戶實(shi)現大(da)(da)(da)(da)氣(qi)污(wu)染管控“產品-技(ji)術-服(fu)務應用(yong)”的一站式購買(mai)。目(mu)前公(gong)司已建設(she)(she)中國(guo)(guo)環(huan)境監測總站國(guo)(guo)家大(da)(da)(da)(da)氣(qi)顆粒(li)(li)物(wu)組分(fen)-光化學(xue)(xue)(xue)(xue)監測網建設(she)(she)項(xiang)目(mu),海南(nan)省(sheng)大(da)(da)(da)(da)氣(qi)復(fu)合(he)(he)污(wu)染綜合(he)(he)來源解(jie)析項(xiang)目(mu)、廣(guang)東(dong)顆粒(li)(li)物(wu)組分(fen)監測網(二期(qi))建設(she)(she)項(xiang)目(mu)、浙江省(sheng)環(huan)境監測中心-杭州(zhou)光化學(xue)(xue)(xue)(xue)監測網-金華光化學(xue)(xue)(xue)(xue)監測網、石家莊(zhuang)大(da)(da)(da)(da)氣(qi)復(fu)合(he)(he)超級站及(ji)應用(yong)項(xiang)目(mu)。此外(wai),公(gong)司擁有專業化數據分(fen)析服(fu)務團隊,均由(you)國(guo)(guo)內(nei)雙一流高(gao)校(xiao)(xiao)(北(bei)京大(da)(da)(da)(da)學(xue)(xue)(xue)(xue)、浙江大(da)(da)(da)(da)學(xue)(xue)(xue)(xue)、復(fu)旦大(da)(da)(da)(da)學(xue)(xue)(xue)(xue)、南(nan)開大(da)(da)(da)(da)學(xue)(xue)(xue)(xue)等)碩博學(xue)(xue)(xue)(xue)歷的高(gao)素質人才組建,并與國(guo)(guo)內(nei)知名高(gao)校(xiao)(xiao)、科研院所有深入(ru)合(he)(he)作。



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