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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: 聚光 瀏覽量:1731

  來源:中國環境報(bao)第8版

  2020年(nian)(nian)中央經濟工作會(hui)議明確提出(chu),打好(hao)污(wu)(wu)(wu)染(ran)防(fang)治(zhi)攻堅戰,堅持(chi)方向不變、力(li)度不減,突(tu)出(chu)精準(zhun)治(zhi)污(wu)(wu)(wu)、科(ke)學治(zhi)污(wu)(wu)(wu)、依(yi)法(fa)治(zhi)污(wu)(wu)(wu),推動生態環(huan)(huan)境質(zhi)量(liang)(liang)(liang)持(chi)續好(hao)轉。近(jin)年(nian)(nian)來大(da)氣(qi)污(wu)(wu)(wu)染(ran)治(zhi)理成效(xiao)顯(xian)(xian)著,環(huan)(huan)境空(kong)氣(qi)質(zhi)量(liang)(liang)(liang)明顯(xian)(xian)改(gai)善,細顆粒物濃度明顯(xian)(xian)下(xia)降,重(zhong)污(wu)(wu)(wu)染(ran)天氣(qi)明顯(xian)(xian)減少。但臭氧污(wu)(wu)(wu)染(ran)問題逐步顯(xian)(xian)現(xian),濃度呈逐年(nian)(nian)上(shang)升(sheng)態勢,成為(wei)影響(xiang)環(huan)(huan)境空(kong)氣(qi)質(zhi)量(liang)(liang)(liang)的(de)(de)又一(yi)重(zhong)要污(wu)(wu)(wu)染(ran)物,加強細顆粒物和(he)臭氧協同(tong)控(kong)制成為(wei)改(gai)善環(huan)(huan)境空(kong)氣(qi)質(zhi)量(liang)(liang)(liang)的(de)(de)關鍵。大(da)氣(qi)污(wu)(wu)(wu)染(ran)防(fang)治(zhi)工作的(de)(de)艱巨性和(he)復雜性,亟需監(jian)測(ce)科(ke)技(ji)(ji)力(li)量(liang)(liang)(liang)的(de)(de)支持(chi)。聚(ju)光科(ke)技(ji)(ji)(杭州)股份有(you)限公(gong)司(以下(xia)簡稱“聚(ju)光科(ke)技(ji)(ji)”)成立于(yu)2002年(nian)(nian),經過近(jin)20年(nian)(nian)的(de)(de)發展,現(xian)已成為(wei)國(guo)內高端分析(xi)儀器儀表領軍企業,其(qi)自主研發的(de)(de)全流程監(jian)測(ce)設備技(ji)(ji)術成熟(shu),已廣(guang)泛應用于(yu)眾(zhong)多國(guo)家級(ji)/省級(ji)重(zhong)點項目建設。通過多年(nian)(nian)技(ji)(ji)術研發,公(gong)司目前取得專利(li)800余項,計(ji)算機軟件(jian)著作權300余項,主持(chi)或參與標準(zhun)制定70余項,累計(ji)承擔國(guo)家和(he)地方科(ke)技(ji)(ji)計(ji)劃項目100余項。


 強化多污染物協同管控 

  針(zhen)對(dui)大氣(qi)(qi)復合(he)污(wu)(wu)(wu)染(ran)(ran)(ran)(ran)(ran)日(ri)益突出的問(wen)題(ti)(ti),聚光(guang)科技準確分(fen)(fen)析大氣(qi)(qi)復合(he)污(wu)(wu)(wu)染(ran)(ran)(ran)(ran)(ran)成(cheng)因,強化(hua)(hua)多(duo)污(wu)(wu)(wu)染(ran)(ran)(ran)(ran)(ran)物(wu)(wu)(wu)(wu)(wu)協(xie)(xie)同(tong)(tong)管(guan)(guan)(guan)(guan)控(kong)(kong),落實(shi)(shi)污(wu)(wu)(wu)染(ran)(ran)(ran)(ran)(ran)源(yuan)治(zhi)理(li)任務(wu)(wu),加(jia)快實(shi)(shi)現環境空(kong)氣(qi)(qi)質(zhi)量(liang)(liang)(liang)改善,其《環境空(kong)氣(qi)(qi)質(zhi)量(liang)(liang)(liang)達(da)標管(guan)(guan)(guan)(guan)控(kong)(kong)服務(wu)(wu)方案(an)》通過(guo)當地基礎數據分(fen)(fen)析,建立污(wu)(wu)(wu)染(ran)(ran)(ran)(ran)(ran)成(cheng)因案(an)例庫,掌(zhang)握(wo)污(wu)(wu)(wu)染(ran)(ran)(ran)(ran)(ran)物(wu)(wu)(wu)(wu)(wu)歷史(shi)變化(hua)(hua)規(gui)律,指導多(duo)污(wu)(wu)(wu)染(ran)(ran)(ran)(ran)(ran)物(wu)(wu)(wu)(wu)(wu)的日(ri)常協(xie)(xie)同(tong)(tong)管(guan)(guan)(guan)(guan)控(kong)(kong)與(yu)重(zhong)污(wu)(wu)(wu)染(ran)(ran)(ran)(ran)(ran)應急。采(cai)用(yong)細顆(ke)粒物(wu)(wu)(wu)(wu)(wu)(PM2.5)、可(ke)吸(xi)入顆(ke)粒物(wu)(wu)(wu)(wu)(wu)(PM10)、臭(chou)氧(O3)、二(er)氧化(hua)(hua)硫(SO2)、二(er)氧化(hua)(hua)氮(NO2)、一氧化(hua)(hua)碳(CO)、揮發性有機物(wu)(wu)(wu)(wu)(wu)(VOCs)、甲(jia)醛(HCOH)、過(guo)氧乙酰硝酸酯(PANs)、光(guang)解(jie)速率等多(duo)因子、全流(liu)程協(xie)(xie)同(tong)(tong)走航監測(ce)技術與(yu)激光(guang)雷(lei)達(da)掃描技術,開展(zhan)重(zhong)點(dian)地區(qu)走航摸排(pai)(pai),快速掌(zhang)握(wo)區(qu)域污(wu)(wu)(wu)染(ran)(ran)(ran)(ran)(ran)物(wu)(wu)(wu)(wu)(wu)濃度與(yu)污(wu)(wu)(wu)染(ran)(ran)(ran)(ran)(ran)源(yuan)時(shi)空(kong)分(fen)(fen)布狀況,識別熱點(dian)管(guan)(guan)(guan)(guan)控(kong)(kong)區(qu)域與(yu)時(shi)段;進一步結合(he)車(che)載顆(ke)粒物(wu)(wu)(wu)(wu)(wu)來源(yuan)解(jie)析、臭(chou)氧光(guang)化(hua)(hua)學污(wu)(wu)(wu)染(ran)(ran)(ran)(ran)(ran)綜合(he)監測(ce)系(xi)統,源(yuan)排(pai)(pai)放清單及(ji)空(kong)氣(qi)(qi)質(zhi)量(liang)(liang)(liang)模擬(ni)技術,分(fen)(fen)析各項(xiang)污(wu)(wu)(wu)染(ran)(ran)(ran)(ran)(ran)成(cheng)因與(yu)生(sheng)成(cheng)機制(zhi),識別主要污(wu)(wu)(wu)染(ran)(ran)(ran)(ran)(ran)源(yuan)類,定量(liang)(liang)(liang)評估一次、二(er)次污(wu)(wu)(wu)染(ran)(ran)(ran)(ran)(ran)貢(gong)獻,識別重(zhong)點(dian)管(guan)(guan)(guan)(guan)控(kong)(kong)行業,為(wei)從(cong)時(shi)、空(kong)、物(wu)(wu)(wu)(wu)(wu)各角度制(zhi)定差異(yi)化(hua)(hua)協(xie)(xie)同(tong)(tong)管(guan)(guan)(guan)(guan)控(kong)(kong)策略,提(ti)供(gong)決(jue)策支(zhi)撐(cheng)。依托多(duo)元數據分(fen)(fen)析成(cheng)果及(ji)相關(guan)工作(zuo)流(liu)程與(yu)機制(zhi)構建測(ce)管(guan)(guan)(guan)(guan)治(zhi)一體化(hua)(hua)達(da)標管(guan)(guan)(guan)(guan)控(kong)(kong)服務(wu)(wu)體系(xi),可(ke)根(gen)據區(qu)域、點(dian)位差異(yi)性,形(xing)成(cheng)日(ri)常與(yu)重(zhong)污(wu)(wu)(wu)染(ran)(ran)(ran)(ran)(ran)分(fen)(fen)級(ji)管(guan)(guan)(guan)(guan)控(kong)(kong)策略,保障重(zhong)點(dian)區(qu)域空(kong)氣(qi)(qi)質(zhi)量(liang)(liang)(liang);針(zhen)對(dui)各類污(wu)(wu)(wu)染(ran)(ran)(ran)(ran)(ran)源(yuan)形(xing)成(cheng)行業管(guan)(guan)(guan)(guan)理(li)、治(zhi)理(li)體系(xi),落實(shi)(shi)污(wu)(wu)(wu)染(ran)(ran)(ran)(ran)(ran)源(yuan)管(guan)(guan)(guan)(guan)治(zhi)任務(wu)(wu),協(xie)(xie)同(tong)(tong)減少污(wu)(wu)(wu)染(ran)(ran)(ran)(ran)(ran)物(wu)(wu)(wu)(wu)(wu)排(pai)(pai)放;并多(duo)維度量(liang)(liang)(liang)化(hua)(hua)評估管(guan)(guan)(guan)(guan)控(kong)(kong)效(xiao)果,確保及(ji)時(shi)發現問(wen)題(ti)(ti),精(jing)準定位問(wen)題(ti)(ti),有效(xiao)解(jie)決(jue)問(wen)題(ti)(ti),實(shi)(shi)現環境空(kong)氣(qi)(qi)質(zhi)量(liang)(liang)(liang)協(xie)(xie)同(tong)(tong)管(guan)(guan)(guan)(guan)控(kong)(kong),助(zhu)力環境空(kong)氣(qi)(qi)質(zhi)量(liang)(liang)(liang)持續改善。

  《環(huan)境空氣質量達標管控服務方(fang)案(an)(an)》已在海南省、宿州(zhou)市(shi)、武威市(shi)、徐州(zhou)市(shi)、聊城市(shi)、宜昌(chang)市(shi)等多個(ge)省市(shi)區(qu)進行了應用,并(bing)取得顯(xian)著效果(guo)。方(fang)案(an)(an)配置的(de)核心(xin)在線監(jian)測設備均為公司自產設備,各項技術指標均達到國內領先水平,可為大氣污染(ran)防治提供精準(zhun)數據支撐。




 

  管控提升空氣質量排名 

  2017年,聚(ju)光(guang)科技(ji)在(zai)歷(li)史數據研(yan)判分(fen)析(xi)基(ji)礎上(shang),采用空氣質量(liang)走航監(jian)測(ce)車、激光(guang)雷達監(jian)測(ce)車等(deng)技(ji)術對宿州市(shi)顆粒物(wu)的整體污染特征進行了摸排分(fen)析(xi),并制(zhi)(zhi)定了管(guan)控(kong)策(ce)略。2018年-2019年,通過(guo)在(zai)當地(di)組建技(ji)術組、走航巡(xun)(xun)查(cha)組等(deng)專業團隊,建立網(wang)格分(fen)級(ji)、部門聯動、污染巡(xun)(xun)查(cha)等(deng)機制(zhi)(zhi),并提供動態研(yan)判分(fen)析(xi)、污染巡(xun)(xun)查(cha)處置、敏感點防控(kong)策(ce)略以及工地(di)揚塵、散(san)煤、餐飲油(you)煙(yan)等(deng)污染源專項(xiang)管(guan)控(kong)服務(wu),逐步降低PM2.5濃度,提升空氣質量(liang)排名。

  2018年宿(su)州市(shi)PM2.5濃(nong)度明(ming)顯下降,擺脫倒一(yi),下降率全(quan)省(sheng)第3(-17.71%)。

  2019年(nian)宿州市PM2.5濃度(du)明(ming)顯下降,下降率省內排名第1(-9.09%)。

  2019年1-12月(yue)宿(su)州市空氣質量改(gai)善幅度居168重點城市第一。




 精準臭氧管控技術服務 

  2020年4月,聚光(guang)科技(ji)進駐(zhu)湖北(bei)宜昌,利用(yong)當地基礎空氣(qi)質(zhi)量(liang)監測(ce)數(shu)據、光(guang)化學全(quan)流程(cheng)監測(ce)數(shu)據以及走航技(ji)術開展(zhan)臭氧(yang)污染特(te)征(zheng)分析、VOCs區(qu)域整體特(te)征(zheng)摸排、臭氧(yang)成因診(zhen)斷及來源(yuan)解析工作,并(bing)組(zu)(zu)建數(shu)據分析組(zu)(zu)、走航巡查(cha)(cha)組(zu)(zu),確定指導專家(jia),建立了(le)宜昌市本(ben)地化臭氧(yang)研(yan)判分析機(ji)制、日會商(shang)機(ji)制、預報預警機(ji)制。針對宜昌市工業企業、加油站等行(xing)業開展(zhan)了(le)拉(la)網式巡查(cha)(cha)和突擊巡查(cha)(cha),形成巡查(cha)(cha)問(wen)題臺賬(zhang),整理特(te)征(zheng)因子庫,保障臭氧(yang)污染防(fang)治工作有序推進。

  2019年5-8月均(jun)為不降反升,2020年均(jun)改善為同比顯著下(xia)降。變(bian)化率湖北(bei)省內排名(ming)各月均(jun)有提(ti)升,2020年8月下(xia)降率居全省第一。

  優(you)(you)良(liang)(liang)天(tian)同(tong)比(bi)(bi)增加(jia)21天(tian)。5月同(tong)比(bi)(bi)增加(jia)3天(tian);6月全月優(you)(you)良(liang)(liang),同(tong)比(bi)(bi)增加(jia)7天(tian);7月全月優(you)(you)良(liang)(liang),同(tong)比(bi)(bi)增加(jia)4天(tian);8月同(tong)比(bi)(bi)增加(jia)7天(tian)。

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

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



 


 多項技術應用于重點項目中 

  聚光(guang)(guang)科技(ji)(ji)涉(she)及(ji)顆粒物來(lai)源(yuan)解(jie)析(xi)(xi)、光(guang)(guang)化(hua)(hua)(hua)學(xue)反應(ying)全過程因子監測系(xi)列設(she)(she)備技(ji)(ji)術(shu)成熟(shu),已應(ying)用于眾多國(guo)(guo)家(jia)(jia)級/省級重點項(xiang)目(mu)建(jian)(jian)設(she)(she),可(ke)提供(gong)準確可(ke)靠(kao)的(de)大(da)(da)氣(qi)(qi)污染(ran)(ran)監測數(shu)據,開(kai)展精細(xi)化(hua)(hua)(hua)污染(ran)(ran)成因分(fen)析(xi)(xi)及(ji)精細(xi)化(hua)(hua)(hua)管控指導,協助客戶實現大(da)(da)氣(qi)(qi)污染(ran)(ran)管控“產品-技(ji)(ji)術(shu)-服務應(ying)用”的(de)一(yi)站(zhan)式購(gou)買(mai)。目(mu)前公(gong)司已建(jian)(jian)設(she)(she)中(zhong)國(guo)(guo)環(huan)境(jing)(jing)監測總站(zhan)國(guo)(guo)家(jia)(jia)大(da)(da)氣(qi)(qi)顆粒物組分(fen)-光(guang)(guang)化(hua)(hua)(hua)學(xue)監測網建(jian)(jian)設(she)(she)項(xiang)目(mu),海南省大(da)(da)氣(qi)(qi)復合污染(ran)(ran)綜合來(lai)源(yuan)解(jie)析(xi)(xi)項(xiang)目(mu)、廣東顆粒物組分(fen)監測網(二期)建(jian)(jian)設(she)(she)項(xiang)目(mu)、浙江省環(huan)境(jing)(jing)監測中(zhong)心-杭州光(guang)(guang)化(hua)(hua)(hua)學(xue)監測網-金(jin)華光(guang)(guang)化(hua)(hua)(hua)學(xue)監測網、石家(jia)(jia)莊大(da)(da)氣(qi)(qi)復合超級站(zhan)及(ji)應(ying)用項(xiang)目(mu)。此外,公(gong)司擁有專(zhuan)業化(hua)(hua)(hua)數(shu)據分(fen)析(xi)(xi)服務團隊,均由國(guo)(guo)內雙(shuang)一(yi)流高(gao)校(xiao)(北(bei)京大(da)(da)學(xue)、浙江大(da)(da)學(xue)、復旦大(da)(da)學(xue)、南開(kai)大(da)(da)學(xue)等)碩博(bo)學(xue)歷的(de)高(gao)素(su)質人(ren)才組建(jian)(jian),并與國(guo)(guo)內知名(ming)高(gao)校(xiao)、科研院(yuan)所有深入(ru)合作。



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