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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:中國環境報第8版

  2020年(nian)中央經濟工(gong)(gong)作會議明(ming)確(que)提出(chu),打(da)好污(wu)(wu)(wu)染防治攻(gong)堅戰,堅持方向不(bu)變、力度(du)不(bu)減,突出(chu)精準治污(wu)(wu)(wu)、科(ke)(ke)學治污(wu)(wu)(wu)、依(yi)法治污(wu)(wu)(wu),推動生(sheng)態環境(jing)質量(liang)持續好轉(zhuan)。近(jin)年(nian)來(lai)大(da)氣(qi)(qi)(qi)污(wu)(wu)(wu)染治理成效顯著,環境(jing)空氣(qi)(qi)(qi)質量(liang)明(ming)顯改善,細顆粒(li)(li)物(wu)(wu)濃度(du)明(ming)顯下降(jiang),重(zhong)污(wu)(wu)(wu)染天氣(qi)(qi)(qi)明(ming)顯減少(shao)。但臭氧污(wu)(wu)(wu)染問題逐步顯現(xian),濃度(du)呈逐年(nian)上升態勢(shi),成為(wei)影響環境(jing)空氣(qi)(qi)(qi)質量(liang)的(de)又(you)一重(zhong)要污(wu)(wu)(wu)染物(wu)(wu),加(jia)強細顆粒(li)(li)物(wu)(wu)和臭氧協(xie)同控制(zhi)(zhi)成為(wei)改善環境(jing)空氣(qi)(qi)(qi)質量(liang)的(de)關鍵。大(da)氣(qi)(qi)(qi)污(wu)(wu)(wu)染防治工(gong)(gong)作的(de)艱巨性(xing)和復(fu)雜性(xing),亟需監測科(ke)(ke)技力量(liang)的(de)支持。聚(ju)光(guang)科(ke)(ke)技(杭州)股份有限公(gong)司(以下簡稱(cheng)“聚(ju)光(guang)科(ke)(ke)技”)成立于(yu)2002年(nian),經過近(jin)20年(nian)的(de)發展,現(xian)已成為(wei)國內高端分析儀器儀表領軍(jun)企業,其自主研(yan)發的(de)全流程監測設備(bei)技術成熟,已廣(guang)泛應用于(yu)眾多(duo)國家級/省級重(zhong)點項(xiang)(xiang)目(mu)(mu)建設。通過多(duo)年(nian)技術研(yan)發,公(gong)司目(mu)(mu)前取得專(zhuan)利800余(yu)(yu)(yu)項(xiang)(xiang),計算(suan)機軟件著作權300余(yu)(yu)(yu)項(xiang)(xiang),主持或(huo)參(can)與標準制(zhi)(zhi)定(ding)70余(yu)(yu)(yu)項(xiang)(xiang),累計承擔國家和地方科(ke)(ke)技計劃(hua)項(xiang)(xiang)目(mu)(mu)100余(yu)(yu)(yu)項(xiang)(xiang)。


 強化多污染物協同管控 

  針(zhen)對大(da)氣(qi)(qi)復合污(wu)(wu)(wu)(wu)(wu)(wu)染(ran)(ran)(ran)日(ri)益突出的(de)問題(ti),聚(ju)光科技準確(que)分析大(da)氣(qi)(qi)復合污(wu)(wu)(wu)(wu)(wu)(wu)染(ran)(ran)(ran)成(cheng)(cheng)因,強化(hua)(hua)多污(wu)(wu)(wu)(wu)(wu)(wu)染(ran)(ran)(ran)物(wu)(wu)(wu)協(xie)(xie)同管(guan)(guan)(guan)(guan)(guan)控(kong),落(luo)實污(wu)(wu)(wu)(wu)(wu)(wu)染(ran)(ran)(ran)源治(zhi)(zhi)理任務,加快實現環境空(kong)(kong)氣(qi)(qi)質(zhi)(zhi)(zhi)量(liang)改(gai)善,其《環境空(kong)(kong)氣(qi)(qi)質(zhi)(zhi)(zhi)量(liang)達(da)(da)標管(guan)(guan)(guan)(guan)(guan)控(kong)服(fu)務方(fang)案》通(tong)過當(dang)地(di)(di)基礎數據(ju)(ju)分析,建立污(wu)(wu)(wu)(wu)(wu)(wu)染(ran)(ran)(ran)成(cheng)(cheng)因案例庫,掌握污(wu)(wu)(wu)(wu)(wu)(wu)染(ran)(ran)(ran)物(wu)(wu)(wu)歷史變(bian)化(hua)(hua)規律(lv),指導多污(wu)(wu)(wu)(wu)(wu)(wu)染(ran)(ran)(ran)物(wu)(wu)(wu)的(de)日(ri)常(chang)(chang)協(xie)(xie)同管(guan)(guan)(guan)(guan)(guan)控(kong)與(yu)(yu)重污(wu)(wu)(wu)(wu)(wu)(wu)染(ran)(ran)(ran)應急(ji)。采(cai)用(yong)細顆粒(li)物(wu)(wu)(wu)(PM2.5)、可(ke)(ke)吸(xi)入顆粒(li)物(wu)(wu)(wu)(PM10)、臭氧(yang)(O3)、二氧(yang)化(hua)(hua)硫(SO2)、二氧(yang)化(hua)(hua)氮(NO2)、一氧(yang)化(hua)(hua)碳(CO)、揮發性有機(ji)物(wu)(wu)(wu)(VOCs)、甲醛(HCOH)、過氧(yang)乙(yi)酰硝酸酯(PANs)、光解速率(lv)等多因子(zi)、全流(liu)程(cheng)協(xie)(xie)同走航監(jian)測(ce)技術(shu)與(yu)(yu)激光雷達(da)(da)掃描技術(shu),開展重點地(di)(di)區(qu)(qu)走航摸排(pai),快速掌握區(qu)(qu)域(yu)(yu)污(wu)(wu)(wu)(wu)(wu)(wu)染(ran)(ran)(ran)物(wu)(wu)(wu)濃度(du)與(yu)(yu)污(wu)(wu)(wu)(wu)(wu)(wu)染(ran)(ran)(ran)源時空(kong)(kong)分布狀況(kuang),識別熱點管(guan)(guan)(guan)(guan)(guan)控(kong)區(qu)(qu)域(yu)(yu)與(yu)(yu)時段;進一步結合車(che)載(zai)顆粒(li)物(wu)(wu)(wu)來源解析、臭氧(yang)光化(hua)(hua)學污(wu)(wu)(wu)(wu)(wu)(wu)染(ran)(ran)(ran)綜合監(jian)測(ce)系統,源排(pai)放清單及空(kong)(kong)氣(qi)(qi)質(zhi)(zhi)(zhi)量(liang)模擬技術(shu),分析各(ge)項污(wu)(wu)(wu)(wu)(wu)(wu)染(ran)(ran)(ran)成(cheng)(cheng)因與(yu)(yu)生成(cheng)(cheng)機(ji)制,識別主(zhu)要污(wu)(wu)(wu)(wu)(wu)(wu)染(ran)(ran)(ran)源類,定(ding)量(liang)評估一次、二次污(wu)(wu)(wu)(wu)(wu)(wu)染(ran)(ran)(ran)貢獻,識別重點管(guan)(guan)(guan)(guan)(guan)控(kong)行(xing)業(ye),為從時、空(kong)(kong)、物(wu)(wu)(wu)各(ge)角(jiao)度(du)制定(ding)差(cha)異化(hua)(hua)協(xie)(xie)同管(guan)(guan)(guan)(guan)(guan)控(kong)策略(lve),提供決(jue)(jue)策支撐。依托多元數據(ju)(ju)分析成(cheng)(cheng)果(guo)(guo)及相關工作流(liu)程(cheng)與(yu)(yu)機(ji)制構建測(ce)管(guan)(guan)(guan)(guan)(guan)治(zhi)(zhi)一體(ti)化(hua)(hua)達(da)(da)標管(guan)(guan)(guan)(guan)(guan)控(kong)服(fu)務體(ti)系,可(ke)(ke)根據(ju)(ju)區(qu)(qu)域(yu)(yu)、點位差(cha)異性,形成(cheng)(cheng)日(ri)常(chang)(chang)與(yu)(yu)重污(wu)(wu)(wu)(wu)(wu)(wu)染(ran)(ran)(ran)分級(ji)管(guan)(guan)(guan)(guan)(guan)控(kong)策略(lve),保(bao)障重點區(qu)(qu)域(yu)(yu)空(kong)(kong)氣(qi)(qi)質(zhi)(zhi)(zhi)量(liang);針(zhen)對各(ge)類污(wu)(wu)(wu)(wu)(wu)(wu)染(ran)(ran)(ran)源形成(cheng)(cheng)行(xing)業(ye)管(guan)(guan)(guan)(guan)(guan)理、治(zhi)(zhi)理體(ti)系,落(luo)實污(wu)(wu)(wu)(wu)(wu)(wu)染(ran)(ran)(ran)源管(guan)(guan)(guan)(guan)(guan)治(zhi)(zhi)任務,協(xie)(xie)同減少污(wu)(wu)(wu)(wu)(wu)(wu)染(ran)(ran)(ran)物(wu)(wu)(wu)排(pai)放;并(bing)多維度(du)量(liang)化(hua)(hua)評估管(guan)(guan)(guan)(guan)(guan)控(kong)效果(guo)(guo),確(que)保(bao)及時發現問題(ti),精準定(ding)位問題(ti),有效解決(jue)(jue)問題(ti),實現環境空(kong)(kong)氣(qi)(qi)質(zhi)(zhi)(zhi)量(liang)協(xie)(xie)同管(guan)(guan)(guan)(guan)(guan)控(kong),助力環境空(kong)(kong)氣(qi)(qi)質(zhi)(zhi)(zhi)量(liang)持續改(gai)善。

  《環(huan)境空氣質量達標管(guan)控服務(wu)方案(an)(an)》已在(zai)海南省、宿(su)州市、武(wu)威市、徐(xu)州市、聊(liao)城(cheng)市、宜(yi)昌市等多(duo)個(ge)省市區進(jin)行(xing)了應(ying)用(yong),并取得顯著(zhu)效果(guo)。方案(an)(an)配置的核心在(zai)線監測設(she)備均為公(gong)司自產設(she)備,各(ge)項(xiang)技術指(zhi)標均達到國內(nei)領先水平,可為大(da)氣污(wu)染防治提供精準數據支撐。




 

  管控提升空氣質量排名 

  2017年(nian),聚光科技(ji)在(zai)歷史數據研判(pan)分(fen)(fen)析基礎(chu)上,采用空(kong)氣質量走(zou)航監測(ce)車、激光雷達監測(ce)車等(deng)技(ji)術(shu)對(dui)宿州市顆粒物的(de)整體污染(ran)特征(zheng)進行(xing)了摸排(pai)分(fen)(fen)析,并制(zhi)(zhi)定了管控(kong)(kong)策(ce)略(lve)。2018年(nian)-2019年(nian),通過(guo)在(zai)當地(di)組(zu)建技(ji)術(shu)組(zu)、走(zou)航巡(xun)查(cha)組(zu)等(deng)專(zhuan)業團隊,建立網格分(fen)(fen)級、部門聯(lian)動、污染(ran)巡(xun)查(cha)等(deng)機制(zhi)(zhi),并提供動態研判(pan)分(fen)(fen)析、污染(ran)巡(xun)查(cha)處(chu)置、敏感點防控(kong)(kong)策(ce)略(lve)以及工地(di)揚塵、散煤(mei)、餐飲(yin)油煙等(deng)污染(ran)源專(zhuan)項管控(kong)(kong)服務,逐步降低PM2.5濃度(du),提升空(kong)氣質量排(pai)名(ming)。

  2018年宿州市PM2.5濃(nong)度明顯(xian)下(xia)(xia)降(jiang),擺脫倒一,下(xia)(xia)降(jiang)率全省(sheng)第3(-17.71%)。

  2019年宿州市PM2.5濃度明顯下(xia)降,下(xia)降率省內排名(ming)第1(-9.09%)。

  2019年1-12月宿(su)州市(shi)空氣質量改善(shan)幅(fu)度居168重點城市(shi)第一。




 精準臭氧管控技術服務 

  2020年4月(yue),聚光科(ke)技進駐湖北(bei)宜昌(chang),利(li)用(yong)當地(di)基礎空氣質量監測數(shu)據(ju)、光化學全流程監測數(shu)據(ju)以及走(zou)航技術開展臭(chou)氧(yang)污染特(te)征(zheng)分析(xi)、VOCs區域(yu)整(zheng)體(ti)特(te)征(zheng)摸排、臭(chou)氧(yang)成因診斷(duan)及來源解析(xi)工(gong)作,并(bing)組建數(shu)據(ju)分析(xi)組、走(zou)航巡查(cha)(cha)組,確(que)定指(zhi)導專家,建立了宜昌(chang)市(shi)本地(di)化臭(chou)氧(yang)研判分析(xi)機制、日會商機制、預報預警機制。針對宜昌(chang)市(shi)工(gong)業(ye)企業(ye)、加油站等行業(ye)開展了拉網式巡查(cha)(cha)和突擊巡查(cha)(cha),形成巡查(cha)(cha)問題(ti)臺(tai)賬,整(zheng)理特(te)征(zheng)因子(zi)庫,保(bao)障臭(chou)氧(yang)污染防治工(gong)作有(you)序推進。

  2019年5-8月(yue)(yue)均為(wei)不降反升,2020年均改善(shan)為(wei)同比顯著下(xia)降。變化率(lv)湖北省(sheng)(sheng)內排名各月(yue)(yue)均有提升,2020年8月(yue)(yue)下(xia)降率(lv)居全省(sheng)(sheng)第一。

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

  臭氧濃度顯著下(xia)降,6月(yue)(yue)同比(bi)下(xia)降29μg/m3;7月(yue)(yue)同比(bi)下(xia)降38μg/m3,8月(yue)(yue)同比(bi)下(xia)降30μg/m3。

  2020年1-6月,宜(yi)昌市(shi)空氣質量(liang)改善(shan)幅度居全國168城(cheng)市(shi)第(di)一。



 


 多項技術應用于重點項目中 

  聚(ju)光(guang)科(ke)技(ji)涉及顆粒物(wu)(wu)來源(yuan)解(jie)析(xi)、光(guang)化(hua)學(xue)反應全過程因子監(jian)(jian)測(ce)(ce)(ce)(ce)系列設(she)備(bei)技(ji)術成熟,已(yi)應用(yong)(yong)于眾多(duo)國家(jia)級(ji)/省(sheng)級(ji)重點(dian)項(xiang)目建(jian)(jian)設(she),可(ke)提(ti)供準確可(ke)靠的(de)(de)大(da)氣污(wu)染(ran)監(jian)(jian)測(ce)(ce)(ce)(ce)數據(ju),開(kai)展精(jing)細化(hua)污(wu)染(ran)成因分(fen)(fen)析(xi)及精(jing)細化(hua)管控(kong)指導(dao),協助客戶實現大(da)氣污(wu)染(ran)管控(kong)“產品-技(ji)術-服務應用(yong)(yong)”的(de)(de)一(yi)站式(shi)購買。目前(qian)公司(si)已(yi)建(jian)(jian)設(she)中國環境監(jian)(jian)測(ce)(ce)(ce)(ce)總(zong)站國家(jia)大(da)氣顆粒物(wu)(wu)組(zu)分(fen)(fen)-光(guang)化(hua)學(xue)監(jian)(jian)測(ce)(ce)(ce)(ce)網(wang)(wang)建(jian)(jian)設(she)項(xiang)目,海(hai)南省(sheng)大(da)氣復(fu)合污(wu)染(ran)綜合來源(yuan)解(jie)析(xi)項(xiang)目、廣(guang)東顆粒物(wu)(wu)組(zu)分(fen)(fen)監(jian)(jian)測(ce)(ce)(ce)(ce)網(wang)(wang)(二期)建(jian)(jian)設(she)項(xiang)目、浙江省(sheng)環境監(jian)(jian)測(ce)(ce)(ce)(ce)中心(xin)-杭州光(guang)化(hua)學(xue)監(jian)(jian)測(ce)(ce)(ce)(ce)網(wang)(wang)-金華(hua)光(guang)化(hua)學(xue)監(jian)(jian)測(ce)(ce)(ce)(ce)網(wang)(wang)、石(shi)家(jia)莊大(da)氣復(fu)合超級(ji)站及應用(yong)(yong)項(xiang)目。此外,公司(si)擁有專(zhuan)業化(hua)數據(ju)分(fen)(fen)析(xi)服務團隊,均由國內雙一(yi)流高校(北京大(da)學(xue)、浙江大(da)學(xue)、復(fu)旦大(da)學(xue)、南開(kai)大(da)學(xue)等)碩博學(xue)歷的(de)(de)高素質人才組(zu)建(jian)(jian),并(bing)與國內知名高校、科(ke)研院所(suo)有深入合作(zuo)。



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