靳全鋒,黃海松,沈培福,陳兵紅,柴紅玲,郭福濤
?
基于MODIS影像內(nèi)蒙古草地火排放污染物動(dòng)態(tài)研究
靳全鋒1,2,黃海松1,沈培福1,陳兵紅1,柴紅玲1,郭福濤2*
(1.麗水職業(yè)技術(shù)學(xué)院林業(yè)科技學(xué)院,浙江 麗水 323000;2.福建農(nóng)林大學(xué)林學(xué)院,福建 福州 350002)
運(yùn)用自主設(shè)計(jì)生物質(zhì)燃燒系統(tǒng),測(cè)定草本燃燒排放因子,基于MODIS火點(diǎn)數(shù)據(jù),運(yùn)用排放因子法對(duì)內(nèi)蒙古區(qū)域2000~2017年草本燃燒排放污染物時(shí)空格局進(jìn)行分析.結(jié)果表明,狼尾草、蘆葦、拂子茅和狗尾草CO2、CO、NO、CH、PM2.5、TC、OC和EC排放因子范圍為1402.6~1550.1,140.3~253.8,0.67~1.55,21.5~93.7,3.74~6.89,1.66~3.06,1.42~2.71和0.23~0.44g/kg;區(qū)域生物質(zhì)密度時(shí)空分布不均勻,地上生物質(zhì)密度總體呈東北向西南遞減趨勢(shì).草地總?cè)紵锪繛?061.46kt,排放各污染物CO2、CO、NO、CH、PM2.5、TC、OC和EC總量分別為:11296.13,1609.79,10.80, 408.96,44.50,20.06,17.23,2.83kt;共發(fā)生49374次草地火,火面積和火點(diǎn)密度從東北向西南逐漸遞減,月變化呈雙峰分布,主峰火點(diǎn)(3月)顯著高于次峰(9月).
內(nèi)蒙古;草地火;排放因子;污染物;時(shí)空格局
草地是地球生態(tài)系統(tǒng)重要組成部分,維護(hù)生態(tài)系統(tǒng)碳、氮、水平衡及生態(tài)系統(tǒng)結(jié)構(gòu)功能穩(wěn)定性和多樣性[1-2].草地火是一種最危險(xiǎn)自然災(zāi)害,對(duì)草地結(jié)構(gòu)、功能及生態(tài)系統(tǒng)有重要影響[3-4],排放大量污染性氣體、顆粒物和氣溶膠顯著影響空氣質(zhì)量和人類健康[5-6].研究顯示全球每年有3/7草地資源遭到火災(zāi)威脅[7],草地資源燃燒排放大量污染性氣體和顆粒物,顯著影響空氣質(zhì)量[8-9].CO2、CH4、N2O和顆粒物排放促進(jìn)長(zhǎng)波輻射吸收,導(dǎo)致氣候變暖[10-11]; PM2.5、EC、NO和VOC排放促進(jìn)太陽(yáng)光吸收、散射及環(huán)境光化學(xué)煙霧及陰霾的形成,降低區(qū)域空氣能見度[12-13];鹵代烴大量排放破壞O3層,增強(qiáng)區(qū)域紫外線[14].草地火災(zāi)釋放煙氣嚴(yán)重影響人類健康,大量CO、NO和VOCs等嚴(yán)重刺激眼、鼻、咽喉以及皮膚,損傷肺粘膜而引發(fā)哮喘,甚至引起白血病和癌癥[15-16].此外,煙氣中大量NO、SO2和HCOOH等沉降,影響土壤pH值和理化性質(zhì)[17-18].因此,解析草地火災(zāi)煙氣排放對(duì)大氣環(huán)境評(píng)估具有重要意義.
中國(guó)約有4.0×109hm2草地資源,占全球草地面積1/10,占國(guó)土面積2/5[19].我國(guó)每年約1/3草地遭受火災(zāi)破壞[20].目前國(guó)內(nèi)草地火災(zāi)研究已經(jīng)展開, Leys等[1]和宮大鵬等[21]基于衛(wèi)星火數(shù)據(jù)探討草地火時(shí)空分布及驅(qū)動(dòng)因子,李興華等[22]探索氣候變化對(duì)內(nèi)蒙古東北部草地火影響;以往研究主要集中在草地火險(xiǎn)區(qū)劃[23-24]、驅(qū)動(dòng)因子分析及草地火行為分析[25-27].本課題組[20]利用遙感影像結(jié)合國(guó)外草本排放因子估測(cè)內(nèi)蒙古區(qū)域草地火污染物排放,而國(guó)內(nèi)草本燃燒排放因子研究尚未見報(bào),因此極大地增強(qiáng)探討草地火災(zāi)排放因子特性及成分組成的意義.
本研究選擇內(nèi)蒙古區(qū)域主要草本蘆葦()、狗尾草()、狼尾草()和拂子茅()為研究對(duì)象,利用自主設(shè)計(jì)生物質(zhì)燃燒煙氣分析系統(tǒng),結(jié)合衛(wèi)星遙感影像數(shù)據(jù)對(duì)內(nèi)蒙古地區(qū)2000~2017年間草地燃燒排放污染物時(shí)空變化趨勢(shì)進(jìn)行分析.揭示不同草本燃燒排放因子,估算2000~2017年區(qū)域草本燃燒量,估算2000~ 2017年區(qū)域草本燃燒排放CO2、CO、NO、CH、PM2.5、TC、OC和EC總量,分析不同區(qū)域污染物時(shí)空格局,為相關(guān)模型研究和政府大氣環(huán)境污染防控提供科學(xué)依據(jù).
內(nèi)蒙古位于華北北部,蒙古高原南部區(qū)域(圖1),位于37°24′N~53°23′N和97°12′ E~126°04′E,是典型大陸性氣候,從東北到西南依次為是溫帶草甸草原,典型草原和沙漠草原等植被類型.該區(qū)域平均最低氣溫為-18~-22℃,平均最高氣溫為19~22℃,年均降水量200~300mm,具有明顯季節(jié)變化特征,冬季寒冷干燥,夏季雨熱同期.內(nèi)蒙古區(qū)域是草地火災(zāi)高發(fā)區(qū),靳全鋒等研究表明2005~2014年共發(fā)生草地火災(zāi)1.29萬(wàn)余次,年均草地火災(zāi)超過(guò)1000余次[20].
圖1 內(nèi)蒙古草地空間分布 Fig.1 Spatial distribution of grassland in Inner Mongolia
1.2.1 生物質(zhì)燃燒煙氣分析系統(tǒng) 圖2為本試驗(yàn)設(shè)計(jì)半開放式燃燒系統(tǒng)[28],該系統(tǒng)由密閉空間、燃燒系統(tǒng)、煙罩、煙氣流通管道、電子可控排氣扇、煙氣分析系統(tǒng)及顆粒物采樣器等部分組成.生物質(zhì)在燃燒系統(tǒng)內(nèi)燃燒,煙氣經(jīng)煙道冷卻、稀釋進(jìn)入煙氣分析系統(tǒng)(Testo350和TSI8533),在線實(shí)時(shí)監(jiān)測(cè),讀取CO2、CO、NO、CH和PM2.5等污染物濃度變化,利用顆粒物采樣器對(duì)草本燃燒顆粒物進(jìn)行采集,用于顆粒物成分分析.
圖2 半開放生物質(zhì)燃燒煙氣分析系統(tǒng) Fig.2 Semi-open biomass combustion system
1.2.2 樣品燃燒與顆粒物采樣 材料選取、處理參照國(guó)內(nèi)外研究成果[29],本試驗(yàn)選用內(nèi)蒙古區(qū)域廣泛分布草本(蘆葦、狗尾草、狼尾草和拂子茅),清除表面雜物和泥土,放在室內(nèi)自然風(fēng)干,后將樣品剪切成5cm左右小段保存?zhèn)溆?每種樣品用電子天平稱量3份,每份30g左右.多次調(diào)節(jié)生物質(zhì)燃燒系統(tǒng)電熱爐溫度(280℃),達(dá)到明火要求,每種燃燒樣品均進(jìn)行3次平行燃燒試驗(yàn).
1.2.3 氣態(tài)物排放檢測(cè) 不同草本燃燒排放的CO2、CO、NO和CH等氣體運(yùn)用Testo350進(jìn)行分析,試驗(yàn)前需用標(biāo)準(zhǔn)氣體進(jìn)行校準(zhǔn),試驗(yàn)時(shí),將儀器與電腦連接好,調(diào)試正常,記錄數(shù)據(jù),記錄間隔為5s,儀器靈敏度是 CO2為0.01%、CO、NO和CH為1′10-6.
1.2.4 顆粒物排放測(cè)定 不同草本燃燒排放細(xì)小顆粒物(PM2.5)運(yùn)用TSI8533顆粒物分析儀分析,儀器每次試驗(yàn)前需要校零,試驗(yàn)時(shí)調(diào)試設(shè)備正常,記錄間隔為5s.儀器靈敏度為0.001mg/m3.
1.2.5 碳質(zhì)組分測(cè)定 選用無(wú)機(jī)石英濾膜進(jìn)行碳質(zhì)組分測(cè)定,使用石英濾膜采樣前,需將濾膜放入馬弗爐內(nèi)500℃下烘烤2h,除去揮發(fā)分和水分,減少對(duì)試驗(yàn)結(jié)果影響,后置于干燥器中平衡24h后稱量使用,濾膜采集樣品后在干燥器中平衡24h后稱重.樣品分析采用德國(guó) Elementar元素分析儀直接測(cè)定樣品中總碳(TC)和有機(jī)碳(OC)質(zhì)量含量.通過(guò)EC=TC-OC計(jì)算元素碳EC[30].
1.2.6 數(shù)據(jù)來(lái)源 2000~2017年內(nèi)蒙古草地火數(shù)據(jù)來(lái)源于空間分辨率為500m、時(shí)間分辨率為1d的MODIS- MCD64A1火面積數(shù)據(jù),該MODIS產(chǎn)品在監(jiān)測(cè)植被火災(zāi)方面具有良好可靠性[31],成功監(jiān)測(cè)率為90%左右[32].研究提取了2000~2017年內(nèi)蒙古地區(qū)衛(wèi)星火點(diǎn)數(shù)據(jù)與植被類型圖(1km空間分辨率)進(jìn)行疊加(http://westdc.westgis.ac.cn/),提取草地火數(shù)據(jù),數(shù)據(jù)包含每次火發(fā)生時(shí)間、地理坐標(biāo)、面積和植被類型.草地地上生物質(zhì)密度運(yùn)用Ma等[33]估算內(nèi)蒙古區(qū)域草地生物量,草地燃燒效率采用、Akagi等[34]、Wu等[35]和Kato等[36]研究成果的平均值(95%)作為本研究結(jié)果.
1.3.1 排放因子計(jì)算方法 本研究采用碳守恒方法來(lái)計(jì)算釋放煙氣排放因子[37],該方法基本假設(shè)是燃料中的碳排放主要以氣態(tài)CO2、CO、THC和顆粒物形態(tài)的碳存在,分別計(jì)算CO2、CO、NO、CH和PM2.5排放因子.
計(jì)算目標(biāo)化合物排放因子,可通過(guò)CO2濃度和目標(biāo)化合物濃度比乘以CO2排放因子得到.
1.3.2 草地燃燒量計(jì)算 草本燃燒用式(4)進(jìn)行計(jì)算[38].
式中:為草本燃燒量,t;為燃燒面積,ha;為地上生物質(zhì)密度,t/ha.
1.3.3 草本排放污染物計(jì)算 草本排放污染物利用公式(5)計(jì)算.
式中:為污染物排放量,t;為草本燃燒量,t;EF為種污染物排放因子,g/kg;為燃燒效率.
1.3.4 不確定分析 本研究使用IPCC[39]提供排放清單不確定性評(píng)估方法,總體不確定性采用公式(6)計(jì)算.
4種草本燃燒CO2、CO、NO、CH、PM2.5、TC、OC和EC排放因子存在差異,部分草本間差異顯著.結(jié)果表明草本燃燒排放CO2、CO、NO、CH、PM2.5、TC、OC和EC排放因子均值分別為1475.0,210.0,1.41,53.4,5.81,2.62,2.25,0.37g/kg,其不同草本燃燒排放因子詳見表1.Goode等[40]研究草本燃燒CO2、NO排放因子為1567,1.41g/kg; Akagi等[34]研究草本燃燒顯示CO2、NO、PM2.5、OC、EC排放因子分別為1692,1.5,2.6,0.4g/kg,該研究結(jié)果與本研究結(jié)果較為接近.草本燃燒主要以碳排放形式釋放,其狼尾草、蘆葦、拂子茅和狗尾草等CO2排放分別占總污染物90.0%,83.3%,82.3%和81.4%, CO排放分別占總污染物8.2%、10.8%、14.3%和14.7%,剩余6種其比例為1.7%~5.9%,該研究結(jié)果與Akagi等[34]研究結(jié)果一致.
表1 不同草本燃燒污染物排放因子(g/kg)
Table 1 Emission factors of contaminants from different types of herbaceous burning (g/kg)
內(nèi)蒙古區(qū)域草地生物量基于Ma等[33]研究成果,運(yùn)用生長(zhǎng)季(5~9月)平均NDVI與地上生物量關(guān)系模型,繪制2000~2017年內(nèi)蒙古草地地上生物量空間分布(圖3).圖3顯示內(nèi)蒙古區(qū)域生物質(zhì)密度空間分布不均勻,地上生物質(zhì)密度總體呈東北向西南遞減趨勢(shì),時(shí)間上區(qū)域生物質(zhì)密度存在差異,該研究結(jié)果與玉山[41]、都瓦拉[42]和Mu等[43]研究結(jié)果一致.陳效逑等[44]研究顯示草地生物質(zhì)密度受經(jīng)緯度、溫度、相對(duì)濕度和降水等因素影響.靳全鋒等[20]研究顯示生物質(zhì)密度與經(jīng)緯度、濕度和降水呈正相關(guān),與溫度和干燥度呈負(fù)相關(guān)關(guān)系.
圖3 2000~2017年內(nèi)蒙古地區(qū)草地生物量空間分布(隔6年)Fig.3 Spatial distribution of biomass density in Inner Mongolia during 2000~2017 (six-year interval)
基于2000~2017年MODIS-MCD64A1內(nèi)蒙古草地火面積數(shù)據(jù),運(yùn)用ArcGIS10.2軟件疊加分析方法,提取2000~2017年燃燒區(qū)域草地生物質(zhì)密度.圖4顯示2000~2017年內(nèi)蒙古區(qū)域燃燒生物量為8061.46kt,年均447.86kt;每年燃燒草地生物量呈波動(dòng)變化,2003、2008和2014年燃燒區(qū)生物量達(dá)到極大值,燃燒區(qū)生物量分別為1404.11,1207.68kt, 791.54kt.Yan等[45]估算中國(guó)大陸生物質(zhì)燃燒污染物排放指出內(nèi)蒙古區(qū)域每年有124~899kt草地生物量燃燒,本研究結(jié)果平均值(447.86kt)與Yan等研究結(jié)果較為接近.
圖4 2000~2017年內(nèi)蒙古區(qū)域燃燒草地生物量時(shí)間變化 Fig.4 Temporal change of burning zone biomass in Inner Mongolia during 2000~2017
基于2000~2017年MODIS-MCD64A1草地火點(diǎn)數(shù)據(jù),運(yùn)用ArcGIS10.2在GWS-84投影下劃分為1km×1km網(wǎng)格,將草地火點(diǎn)運(yùn)用核密度原理,繪制18年火點(diǎn)密度圖(圖5a).2000~2017年內(nèi)蒙古區(qū)域共發(fā)生草地火49374次,年均2743次,火點(diǎn)在空間分布不均勻,火點(diǎn)密度分布規(guī)律為東北向西南區(qū)域呈遞減趨勢(shì),火密度主要集中在呼倫貝爾東部、中部和西北區(qū)域,興安盟東部、錫林郭勒盟交匯區(qū)域及錫林郭勒盟北部區(qū)域,通遼、錫林郭勒盟、赤峰、烏蘭察布、呼和浩特、包頭、鄂爾多斯和巴彥淖爾等區(qū)域有少量火點(diǎn)密度較高區(qū)域分布.該研究結(jié)果與靳全鋒等[20]和峰芝等[46]研究結(jié)果較為接近,研究顯示草地生物量是影響火行為重要因子,草地生物量與草地火點(diǎn)分布具有較強(qiáng)一致性.
圖5 2000~2017年內(nèi)蒙古區(qū)域草地火密度(a)和面積(b)區(qū)域分布 Fig.5 Regional distribution of grassland fire density and total fire area in Inner Mongolia during 2000~2017
圖5b顯示2000~2017年內(nèi)蒙古區(qū)域草地火面積為1.92′106hm2,年均1.07′105hm2,火面積區(qū)域分布不均勻.呼倫貝爾、錫林郭勒、興安盟、赤峰、烏蘭察布、通遼、巴彥淖爾市、呼和浩特、鄂爾多斯和包頭分別占區(qū)域火面積72.4%、13.2%、9.0%、1.3%、1.0%、0.7%、0.7%、0.7%、0.6%和0.5%.該研究結(jié)果與都瓦拉等研究結(jié)果一致[41].
圖6 2000~2017年內(nèi)蒙古區(qū)域地區(qū)草地火點(diǎn)和面積時(shí)間變化 Fig.6 Temporal change of the grassland fire counts and fire area in Inner Mongolia during 2000~2017
圖6顯示 2000~2017 年內(nèi)蒙古區(qū)域草地火次數(shù)和面積,年季波動(dòng)較大.2003、2008和2014年草地火次數(shù)和面積皆達(dá)到極大值,草地火次數(shù)分別是6.84×103,7.24×103,4.54×103次;林火面積分別為 2.97×105,2.60×105,1.82×105hm2.峰芝等[46]研究顯示草原火災(zāi)次數(shù)和面積受生物質(zhì)、枯落物、動(dòng)物糞便等易燃物因子影響,火災(zāi)次數(shù)和面積與生物質(zhì)、枯落物及動(dòng)物糞便呈正相關(guān).
圖7顯示內(nèi)蒙古區(qū)域草地火次數(shù)、面積和平均火面積月變化存在差異火點(diǎn)、火面積和平均火面積呈明顯雙峰分布,火點(diǎn)和火面積主峰(3月)顯著高于次峰(9月),平均火面積主峰和次峰皆落后于火災(zāi)次數(shù)和火面積1~2個(gè)月.時(shí)間上草地火發(fā)生比率高低順序?yàn)榇杭?秋季>夏季>冬季,春、夏、秋和冬季發(fā)生草火次數(shù)比率分別是59.5%、13.7%、23.3%和3.6%;火面積比率分別為64.3%、10.4%、22.8%和2.6%;平均火面積比率分別是31.00%、22.28%、25.81%和20.92%.該結(jié)果與靳全鋒[20]、張正祥等[47]和周懷林等[48]研究結(jié)果一致.草地火災(zāi)集中在春、秋兩季主要受自然因素(降水、空氣濕度、溫度和風(fēng)速等)、草地植被性質(zhì)和植被含水率等因素影響.張正祥等[47]研究顯示春季前一年剩余生物質(zhì)較多、氣溫回暖較快、降水少、空氣相對(duì)濕度、低風(fēng)速較大等因素加快草本水分蒸發(fā),促進(jìn)草地火災(zāi)形成;秋季生物質(zhì)大量死亡、降水較少、空氣濕度降低和風(fēng)速較強(qiáng)有利于草地火災(zāi)的形成,但由于氣溫下降較快降低火頻率,導(dǎo)致春季火災(zāi)頻率顯著高于秋季;夏季植被處于生長(zhǎng)季節(jié)和強(qiáng)降水等因素阻礙草地火發(fā)生.冬季植被更多被冰雪覆蓋,草地火發(fā)生更為困難; Zhang等[49]研究顯示單次草地火面積大小受植被屬性、氣象因子及環(huán)境因子影響,單次火面積與空氣相對(duì)濕度和降水量呈負(fù)相關(guān)關(guān)系,與草地生物量風(fēng)速等因素呈正相關(guān).
根據(jù)內(nèi)蒙古區(qū)域每次火災(zāi)面積、每年區(qū)域生物質(zhì)密度和燃燒效率,結(jié)合實(shí)測(cè)排放因子,計(jì)算2000~ 2017年內(nèi)蒙古草地火排放各污染物CO2、CO、NO、CH、PM2.5、TC、OC和EC總量分別為:11296.13, 1609.79, 10.80, 408.96, 44.50, 20.06, 17.23, 2.83kt;年均排放量分別為:627.56, 89.43, 0.60, 22.72, 2.47, 1.11, 0.96, 0.16kt.圖8顯示各污染物排放空間上不均衡,呈東多西少分布特征.阿拉善盟、巴彥卓爾、包頭、赤峰、鄂爾多斯、呼和浩特、呼倫貝爾、通遼、烏蘭察布、錫林郭勒和興安盟區(qū)域草地火災(zāi)釋放污染物總量分別為:87.83, 48.13, 47.47, 137.60, 34.13, 50.03, 10465.79, 78.43, 55.98, 1168.91, 1013.29kt;年均排放量分別為4.88, 2.67, 2.64, 7.64, 1.90, 2.78, 581.43, 4.36, 3.11, 64.94, 56.29kt;CO2、CO、NO、CH、TC、OC、EC和PM2.5等污染物排放占各區(qū)域比率分別為84.23%、12.00%、0.08%、3.05%、0.15%、0.13%、0.02%和0.33% .Yan等[45]研究?jī)?nèi)蒙古區(qū)域草地火排放顯示CO2、CO、NO、CH和PM2.5年均排放量分別為:178.75~1295.91, 11.10~90.46, 0.15~1.10, 0.57~4.14, 0.74~5.35kt,該研究結(jié)果與本研究結(jié)果較為接近.
2000~2017年內(nèi)蒙古區(qū)域草地火災(zāi)排放污染物CO2、CO、NO、CH、PM2.5、TC、OC和EC年變化見表2,區(qū)域各污染物年季排放存在差異,其排放強(qiáng)弱順序?yàn)?CO2> CO > CH> PM2.5> TC > OC > NO>EC.2003、2008和2014年草地火排放污染物達(dá)到極大值,2004、2007和2015年排放污染物為極小值.
表2 2000~2017年內(nèi)蒙古地區(qū)草地火排放污染物時(shí)間變化
Table 2 Time change of pollutants discharged from grassland fire in Inner Mongolia during 2000~2017
研究顯示草地火災(zāi)排放污染物受生物量、火災(zāi)面積、燃燒效率、排放因子、氣象因子和經(jīng)濟(jì)環(huán)境等因素影響.本研究參照Ma等[33]基于實(shí)測(cè)模型結(jié)果進(jìn)行生物質(zhì)密度不確定性分析,精度高達(dá)80%以上;該研究火災(zāi)面積基于MODIS-MCD64A1數(shù)據(jù)進(jìn)行不確定性分析,其精度高達(dá)85%以上;燃燒效率受草本類型、含水率、自然環(huán)境等因素影響,為了估算的精確性,以多個(gè)草本燃燒效率平均值作為燃燒效率,增強(qiáng)燃燒效率可靠性,誤差控制在50%以內(nèi);排放因子是污染物排放估算中至關(guān)重要因子,直接決定污染物排放估算準(zhǔn)確性,受草本類型、燃燒方式、自然環(huán)境等因素影響,本研究以區(qū)域常見草本類型實(shí)測(cè)數(shù)據(jù)平均值作為排放因子,增加排放因子可靠性,誤差在10%~50%;基于各因子總體不確定性運(yùn)用公式(6)定量計(jì)算各污染物排放結(jié)果不確定性見表3.
表3 排放源估算誤差分析(%)
Table 3 Estimation error from different emission sources (%)
3.1 內(nèi)蒙古區(qū)域草本CO2、CO、NO、CH、PM2.5、TC、OC和EC排放因子范圍分別是1402.6~1550.1、140.3~253.8、0.67~1.55、21.5~93.7、3.74~6.89、1.66~3.06、1.42~2.71和0.23~0.44g/kg.
3.2 內(nèi)蒙古區(qū)域生物質(zhì)密度時(shí)空分布不均勻,地上生物質(zhì)密度總體呈東北向西南遞減趨勢(shì),區(qū)域燃燒生物量為8061.46kt,年均447.86kt.
3.3 內(nèi)蒙古區(qū)域草地火點(diǎn)和面積時(shí)空分布不均衡,時(shí)間上多集中在春、秋兩季;空間上火點(diǎn)密度和火面積分布規(guī)律具有從東北向西南逐漸遞減趨勢(shì).
3.4 內(nèi)蒙古草地火排放各污染物CO2、CO、NO、CH、PM2.5、TC、OC和EC總量分別為:11296.13、1609.79、10.80、408.96、44.50、20.06、17.23和2.83kt,年均排放量分別為:627.56、89.43、0.60、22.72、2.47、1.11、0.96和0.16kt.
[1] Leys B, Umbanhowar C, Marlon J R, et al. Global fire history of grassland biomes [J]. Ecology & Evolution, 2018. https://doi.org/ 10.1002/ece3.4394.
[2] Leys B, Brewer S C, Mcconaghy S, et al. Fire history reconstruction in grassland ecosystems: amount of charcoal reflects local area burned [J]. Environmental Research Letters, 2015,10(11):114-129.
[3] Allison R S, Johnston J M, Craig G, et al. Airborne optical and thermal remote sensing for wildfire detection and monitoring [J]. Sensors, 2016,16(8):1310-1324.
[4] Conver J L, Falk D A, Yool S R, et al. Modeling Fire Pathways in Montane Grassland-forest Ecotones [J]. Fire Ecology, 2018,14(1).doi: 10.4996/fireecology.140117031.
[5] Weldemichael Y, Assefa G. Assessing the energy production and GHG (greenhouse gas) emissions mitigation potential of biomass resources for Alberta [J]. Journal of Cleaner Production, 2016,112(20):4257-4264.
[6] Wang J, Xi F, Liu Z, et al. The spatiotemporal features of greenhouse gases emissions from biomass burning in China from 2000~2012 [J]. Journal of Cleaner Production, 2018,181.https://doi.org/10.1016/ j.jclepro. 2018.01.206.
[7] Werf G R, Randerson J T, Giglio L, et al. Global fire emissions and the contribution of deforestation,savanna,forest,agricultural,and peat fires (1997~2009) [J]. Atmospheric Chemistry and Physics, 2010,10(23): 11707-11735.
[8] Zha S, Zhang S, Cheng T, et al. Agricultural fires and their potential impacts on regional air quality over China [J]. Aerosol Air Qual. Res. 2013,13:992-1001.
[9] Zong Z, Wang X, Tian C, et al. Biomass burning contribution to regional PM2.5during winter in the North China [J]. Atmospheric Chemistry and Physics, 2016,16:1-41.
[10] Enkhjargal A, Burmaajav B. Impact of the ambient air PM2.5on cardiovascular diseases of Ulaanbaatar residents [J]. 2015,8(4):35-41.
[11] 靳全鋒,王文輝,馬祥慶,等.福建省2000~2010年林火排放污染物時(shí)空動(dòng)態(tài)變化[J]. 中國(guó)環(huán)境科學(xué), 2017,37(2):476-485. Jin Q, Wang W, Ma X, et al. Temporal and spatial dynamics of pollutants emission from forest fires in Fujian during 2000~2010 [J]. China Environmental Science, 2017,37(2):476-485.
[12] Sonomdagva C, Batdelger B, Chuluunpurev B. Characteristics of PM10and PM2.5in the ambient air of Ulaanbaatar, Mongolia [J]. International Journal of Environmental Science & Development, 2016, 7(11):827-830.
[13] 靳全鋒,馬祥慶,王文輝,等.中國(guó)亞熱帶地區(qū)2000~2014年林火排放顆粒物時(shí)空動(dòng)態(tài)變化[J]. 環(huán)境科學(xué)學(xué)報(bào), 2017,37(6):2238-2247. Jin Q, Ma X, Wang W, et al. Temporal and spatial characteristics of particulate matter emission from forest fires in Subtropical China during 2000~2014 [J]. Acta Scientiae Circumstantiae, 2017,37(6): 2238-2247.
[14] Ibanez J G, Hernandez-Esparza M, Doria-Serrano C, et al. Halogenated Hydrocarbons and the Ozone Layer depletion [J]. 2008:115-121.
[15] 靳全鋒,陳 磊,黃 娟,等.甲醛對(duì)富貴竹的生理生化響應(yīng)[J]. 環(huán)境科學(xué)與技術(shù), 2016,39(8):45-50. Jin Q, Chen L, Huang J, et al. Influence of Indoor Formaldehyde on Physiological and Biochemical Characteristics of Dracaena Sanderiana [J]. Environmental Science & Technology, 2016,39(8):45-50.
[16] Udeigwe T K, Teboh J M, Eze P N, et al. Implications of leading crop production practices on environmental quality and human health [J]. Journal of environmental management, 2015,151:267-279.
[17] Xue J, Yuan Z, Griffith S M, et al. Sulfate formation enhanced by a cocktail of high NO, SO2, particulate matter, and droplet pH during Haze-Fog events in Megacities in China: An observation-based modeling investigation [J]. Environmental Science & Technology, 2016,50(14):7325.
[18] Mazurkiewiczzapa?owicz K, Janowicz K, Nowak A, et al. Effect of the product of radiational refinement of combustion gases of SO2and NOon the chosen soil microorganisms [J]. Folia Universitatis Agriculturae Stetinensis Agricultura, 2000.
[19] Chen Y. A new digital georeferenced database of grassland in China [J]. 1998,24(2):228-231.
[20] 靳全鋒,鞠園華,楊夏捷,等.2005~2014年內(nèi)蒙古草地火災(zāi)排放污染物的時(shí)空格局[J]. 草業(yè)學(xué)報(bào), 2017,26(2):21-29. Jin Q, Ju Y, Yang X, et al. Temporal and spatial patterns of emissions and pollutants from grassland burned in Inner Mongolia during 2005~2014 [J]. Acta Prataculturae Sinica, 2017,26(2):21-29.
[21] 宮大鵬,康峰峰,劉曉東.新巴爾虎草原火時(shí)空分布特征及對(duì)氣象因子響應(yīng)[J]. 北京林業(yè)大學(xué)學(xué)報(bào), 2018,40(2):82-89. Gong D, Kang F, Liu X. Spatial and temporal distribution patterns of grassland fire and its response to meteorological factors in XinBarag Prairie of northwestern China [J]. Journal of Beijing Forestry University, 2018,40(2):82-89.
[22] 李興華,武文杰,張存厚,等.氣候變化對(duì)內(nèi)蒙古東北部森林草原火災(zāi)的影響[J]. 干旱區(qū)資源與環(huán)境, 2011,25(11):114-119. Li X, Wu W, Zhang C, et al. Influence of climate change on north- eastern of Inner Mongolia grassland forest fire [J]. Journal of Arid Land Resources and Environment, 2011,25(11):114-119.
[23] Na L, Zhang J, Bao Y, et al. Himawari-8satellite based dynamic monitoring of grassland fire in China-Mongolia border regions [J]. Sensors, 2018,18(1):276-285.
[24] Chen J, Zheng W, Liu C. Application of grassland fire monitoring based on Himawari-8geostationary meteorological satellite data [J]. Natural Disasters, 2017,26:197–204.
[25] Liu X P, Zhang J Q, Tong Z J. Modeling the early warning of grassland fire risk based on fuzzy logic in Xilingol, Inner Mongolia [J]. Natural Hazards, 2015,75(3):2331-2342.
[26] Liu X P, Zhang J Q, Tong Z J, et al. GIS-based multi-dimensional risk assessment of the grassland fire in northern China [J]. Natural Hazards, 2012,64(1):381-395.
[27] 辛 喆,王順喜,云 峰,等.基于火災(zāi)模擬軟件(FDS)的草原火災(zāi)蔓延規(guī)律數(shù)值分析[J]. 農(nóng)業(yè)工程學(xué)報(bào), 2013,29(11):156-163+296. Xin Z, Wang S, Yun F, et al. Numerical analysis on spreading laws of grassland fire based on fire dynamics simulator FDS [J]. Transactions of the Chinese Society of Agricultural Engineering, 2013,29(11):156-163.
[28] 郭福濤,靳全鋒,蘇漳文,等.一種生物質(zhì)燃燒的采樣系統(tǒng).中國(guó), CN207336163U [P], 2018-05-08. Guo F, Jin Q, Su Z, et al. Biomass combustion sampling system. China, CN207336163U [P]. 2018-05-08.
[29] Zhang Y S, Min S, Yun L, et al. Emission inventory of carbonaceous pollutants from biomass burning in the Pearl River Delta region, China [J]. Atmospheric Environment, 2013,76(5):189-199.
[30] Chow J C, Watson J G, Chen L W A, et al. Equivalence of elemental carbon by thermal/optical reflectance and transmittance with different temperature protocols [J]. Environ. Sci. Technol., 2004,38(16):4414-4422.
[31] Amraoui M, Pereira M G, Dacamara C C, et al. Atmospheric conditions associated with extreme fire activity in the Western Mediterranean region [J]. Science of the Total Environment, 2015, 524:32-39.
[32] Zhou X C, Wang X Q. Validate and improvement on arithmetic of identifying forest fire based on EOS-MODIS data [J]. Remote Sensing Technology & Application, 2006,21(3):206-211.
[33] Ma W H, Fang J Y, Yang Y H, et al. Biomass carbon stocks and their changes in northern China’s grasslands during 1982~2006 [J]. Science China-life Sciences, 2010,53:841~850, https://doi:10.1007/s11427- 010-4020-6.
[34] Akagi S K, Yokelson R J, Wiedinmyer C, et al. Emission factors for open and domestic biomass burning for use in atmospheric models [J]. Atmospheric Chemistry & Physics, 2011,11(9):27523-27602.
[35] Wu J, Kong S, Wu F, et al. Estimating the open biomass burning emissions in Central and Eastern China from 2003 to 2015 based on satellite observation [J]. Atmospheric Chemistry & Physics, 2018:1-49,https://doi.org/10.5194/acp-18-11623-2018.
[36] Kato E, Michio K Y, Kinoshita T, et al. Development of spatially explicit emission scenario from land-use change and biomass burning for the input data of climate projection [J]. Procedia Environmental Sciences, 2011,6(1).146-152.
[37] Shen G, Yang Y, Wang W, et al. Emission factors of particulate matter and elemental carbon for crop residues and coals burned in typical household stoves in China [J]. Environmental science & technology, 2011,44(18):7157-7162.
[38] Zhou Y, Xing X, Lang J, et al. A comprehensive biomass burning emission inventory with high spatial and temporal resolution in China [J]. Atmospheric Chemistry and Physics, 2017,17(4):2839.
[39] IPCC. Quantifying uncertainties in practice, Chapter 6. In: Good practice guidance and uncertainty management in national greenhouse gas inventories. Bracknell: IES,IPCC,OECD, 1997.
[40] Goode J G, Yokelson R J, Susott R A, et al. Trace gas emissions from laboratory biomass fires measured by open‐path Fourier transform infrared spectroscopy: Fires in grass and surface fuels [J]. Journal of Geophysical Research: Atmospheres, 1999,104(D17):21237-21245.
[41] 玉 山,都瓦拉,劉桂香.內(nèi)蒙古草原枯草期可燃物量遙感估測(cè)模型研究[J]. 干旱區(qū)資源與環(huán)境, 2014,28(11):145-151. Yu S, Du W, Liu G . Remote sensing estimation model for the withered season fuel weight in Inner Mongolia grassland [J]. Journal of Arid Land Resources & Environment, 2014,28(11):145-151.
[42] 都瓦拉.內(nèi)蒙古草原火災(zāi)監(jiān)測(cè)預(yù)警及評(píng)價(jià)研究[D]. 北京:中國(guó)農(nóng)業(yè)科學(xué)院, 2012. Du W. A stutly of garassland fire Monitoring and early warning and Assessment Inner Mongolia [D]. Beijing: Chinese academy of agricultural science, 2012.
[43] Mu S, Zhou S, Chen Y, et al. Assessing the impact of restoration- induced land conversion and management alternatives on net primary productivity in Inner Mongolian grassland, China [J]. Global and Planetary Change, 2013,108:29-41.
[44] 陳效逑,鄭 婷.內(nèi)蒙古典型草原地上生物量的空間格局及其氣候成因分析[J]. 地理科學(xué), 2008,28(3):369-374. Chen X, Zheng T. Spatial patterns of aboveground biomass and its climatic attributions in typical steppe of Inner Mongolia [J]. Scientia Geographica Sinica, 2008,28(3):369-374.
[45] Yan X Y, Ohara T, Akimoto H. Bottom-up estimate of biomass burning in mainland China [J]. Atmospheric Environment, 2006, 40(27):5262-5273.
[46] 峰 芝.近30年內(nèi)蒙古牧區(qū)草原火時(shí)空演化特征分析[D]. 呼和浩特:內(nèi)蒙古師范大學(xué), 2015. Feng Z. Spatiotem poral changes of grassland fire in Inner Mongolia in recent 30 years [D]. Hohhot: Inner Mongolia Normal University, 2015.
[47] 張正祥,張洪巖,李冬雪,等.呼倫貝爾草原人為火空間分布格局[J]. 生態(tài)學(xué)報(bào), 2013,33(7):2023-2031. Zhang Z, Zhang H, Li D, et al. Spatial distribution pattern of human-caused fires in Hulunbeir grassland [J]. Acta Ecologica Sinica, 2013,33(7):2023-2031.
[48] 周懷林,王玉輝,周廣勝.內(nèi)蒙古草原火的時(shí)空動(dòng)態(tài)特征研究[J]. 草業(yè)學(xué)報(bào), 2016,25(4):16-25. Zhou H, Wang Y, Zhou G. Temporal and spatial dynamics of grassland fires in Inner Mongolia [J]. Acta Prataculturae Sinica, 2016,25(4): 16-25.
[49] Zhang Z X, Zhang H Y, Zhou D W. Using GIS spatial analysis and logistic regression to predict the probabilities of human-caused grassland fires [J]. Journal of arid environments, 2010,74(3):386-393.
[50] 陸 炳,孔少飛,韓 斌,等.2007年中國(guó)大陸地區(qū)生物質(zhì)燃燒排放污染物清單[J]. 中國(guó)環(huán)境科學(xué), 2011,31(2):186-194. Lu B, Kong S, Han B, et al. Inventory of atmospheric pollutants discharged from biomass burning in China continent in 2007 [J]. China Environmental Science, 2011,31(2):186-194.
Dynamic changes of pollutants emission from grassland fires based on MODIS images in Inner Mongolia.
JIN Quan---feng1,2, HUANG Hai-song1, SHENPei-fu1, CHENBing-hong1, CHAIHong-ling1, GUO Fu-tao2*
(College of Foresery Science and Technology, Lishui Vocational and Technical College,Lishui 323000, China;2.Forestry College, Fujian Agriculture and Forestry University, Fuzhou 350002, China)., 2019,39(3):1154~1163
A self-designed biomass combustion system was used to measure the emission factors of grassland burning based on the MODIS image data of Inner Mongolia zone and the temporal and spatial patterns of pollutants emitted from burning of grassland from 2000 to 2017 were analyzed. The results showed that the average emission factors of CO2, CO, NO, CH,PM2.5, TC, OC and EC from the burning of Phragmites communis, Setaria viridis, Pennisetum alopecuroides and Calamagrostis epigeiosare were 1402.6~1550.1, 140.3~253.8, 0.67~1.55, 21.5~93.7, 3.74~6.89, 1.66~3.06, 1.42~2.71, 0.23~0.44g/kg, respectively. Inner Mongolia grassland biomass density had uneven spatial and temporal distribution and the distribution of biomass density had gradually decreasing from northeast to southwest. The total biomass burnt was 8061.46kt, and the total amounts of the emitted CO2, CO, NOCH, PM2.5, TC, OC and EC were 11296.13 kt, 1609.79 kt, 10.80 kt, 408.96 kt, 44.50 kt, 20.06 kt, 17.23 kt and 2.83 kt, respectively. A total of 49,374 grassland fires had occurred, with the fire points and fire areas were unbalanced in time and space. The monthly variation exhibited a bi-modal distribution, the main-peak fire point (March) was significantly higher than the secondary-peak fire point (September), and the distribution of fire density and fire area had a gradually decreasing trend from northeast to southwest.
Inner Mongolia;grassland fire;emission factors;pollutants;temporal and spatial patterns
X511
A
1000-6923(2019)03-1154-10
靳全鋒(1988-),男,安徽省,阜陽(yáng)市,講師,主要從事林火模型預(yù)測(cè)及林火生態(tài)研究.發(fā)表論文20余篇.
2018-08-06
國(guó)家自然科學(xué)基金資助項(xiàng)目(31770697);浙江省教育廳一般項(xiàng)目(Y201840513);2017年浙江省訪問(wèn)工程師項(xiàng)目(FG2017240)
* 責(zé)任作者, guofutao@126.com