论文检索
    当前位置: 首页>>论文检索>>论文检索>>正文
    城市绿地对大气环境的潜在负面效应
    2019-07-19  点击:[]

    城市绿地对大气环境的潜在负面效应

    Potential Negative Effects of Urban Green Space on the Atmospheric Environment

     

    张倩 李洪远 *

    ZHANG Qian,LI Hongyuan

     

    张倩 / 1992 年生 / / 深圳市深港产学研环保工程技术股份有限公司 / 工程师ZHANG Qian, born in 1992,female, is an engineer of the IER En-vironmental Protection Engineering Technology Co.,Ltd.

     

    李洪远 / 1963 年生 / / 南开大学环境科学与工程学院教授 / 博士生导师 / 研究方向 :生态恢复与植被重建

    通讯作者邮箱(Correspondent author E-mail):eialee@nankai.edu.cn

    LI Hongyuan,born in 1963, male, is a professor and doctoral supervisor in the College of Environmental Science and Engineering of Nankai Univer-sity. Research direction: Ecological restoration and vegetation reconstruction

    摘要:城市绿地释放的天然源 VOCs 对大气环境质量具有潜在的负面影响。基于遥感图像解译的土地利用类型数据和植被资料,专业人员采用 GloBEIS 模型估算了 2015 年北京市天然源 VOCs 排放通量,并分析了天然源 VOCs O3 生成潜势(OFP) SOA 生成潜势。结果显示,2015 年度北京市天然源 VOCs 的年排放总量(以C计)为34971.631 t,异戊二烯、单萜烯和其他 VOCs OVOCs)分别为10572.582 t30.23%)、11328.896 t 32.39%)、 13070.152 t37.37%);天然源 VOCs 排放通量的空间分布情况与城镇化程度、林区和农作物的区域分布有一定的相关性;天然源 VOCs O3 生成潜势的贡献总量为157943.839 t,异戊二烯为主要贡献者;对 SOA 生成潜势的贡献量为3610.120 t,单萜烯为主要贡献者。

    关键词:城市绿地;北京市;天然源 VOCs;臭氧;二次有机气溶胶

    Abstract: Biogenic VOC (BVOCs) estimated by urban green space had a potential negative impact on atmospheric environmental quality. Based on the GloBEIS model, the emission of BVOCs in Beijing in 2015 was estimated by using remote-sensing image interpretation of land use and vegetation data, and the ozone formation potential (OFP) and the secondary organic aerosols (SOA) formation potentials from the BVOCs were analyzed. The results showed that the total annual BVOCs emissions of Beijing in 2015 was estimated to be approximately 34971.631 t, of which isoprene, monoterpenes, and the other VOCs accounted for 10572.582 t (30.23%), 11328.896 t (32.39%), and 13070.152 t (37.37%), respectively. The spatial distribution of BVOCs emission was related to the urbanization, forest area and crops distribution. The ozone formation potential and the secondary organic aerosol formation potentials from the BVOCs were estimated to be 157943.839 t and 3610.120 t, of which isoprene and monoterpenes were the main contributor to OFP and SOA formation, respectively.

    Key words: urban green space; Beijing; Biogenic VOCs; O3; SOA

    引言

    挥发性有机物(Volatile Organic Compounds, VOCs)指沸点在50℃260℃ 之间,室温下饱和蒸汽压超过133.32 Pa的易挥发性有机化合物,其主要成分包括烃类、氧烃类、氮烃、硫烃类与低沸点的多环芳烃类[1]VOCs 按其来源可分为天然源(BVOCs)和人为源(AVOCs),其中由植被释放的 VOCs 90%以上[2-3]VOCs 作为二次有机气溶胶(SOA)形成的重要前体物[4-7],对大气颗粒物污染的形成起着至关重要的作用。同时,VOCs 对城市 O3 的形成具有较大贡献,对流层 O3 浓度与 O3 生成速率与 VOCs 联系密切[8-9]。在 NOx 充足的条件下,一些常见的天然源 VOCs 比人类活动排放的 VOCs 更易形成 O3 。城市绿地系统是城市植被的聚集地,天然源 VOCs 的释放以及其对大气环境所产生的潜在负面效应也不容忽视。

    本研究采用 GIS RS 结合的手段,基于 Landsat8 OLI 遥感图像解译的土地利用现状和植被资料,运用 GloBEIS 模型,估算了 2015 年北京天然源 VOCs 排放通量并分析其空间分布特征。此外,基于辖区天然源 VOCs 情况,估算了其产生的 O3 SOA 生成潜势,为评价北京市天然源 VOCs 对华北地区空气质量的影响提供数据支撑,对区域空气环境污染的整治和改善有重要的现实意义。

     

    1 材料与方法

    1.1 研究区域

    本研究的模拟范围为 115°42'-117°24'E39°24'-41°36'N,覆盖北京市市辖区和郊县。选取北京市 2015 Landsat8 OLI 遥感影像作为数据源,结合土地利用数据,利用 ArcMAP 建立了2.5 km×2.5 km的网格,以每个网格的中心点经纬度坐标标识该网格的地理位置。模拟域内共包含 2624 个网格。

    1.2 估算模型

    1.2.1 天然源 VOCs 排放通量估算模型

    本研究采用 GloBEIS 模型估算 2015 年北京市天然源挥发性有机物的排放通量。由于植被排放的挥发性有机物种类很多,以异戊二烯和单萜烯为主,因此,研究将北京市生态植被排放的挥发性有机物划分为异戊二烯、单萜烯和其他所有 VOCs(醇、醛、酮、有机酸、低碳烷烃和烯烃等多种)三类。

    GloBEIS 模型的基本算法参考了 Guenther[10-12] 等提出的方法,计算公式如下:

    说明: 图片包含 物体已生成高可信度的说明

    式中:EISOETMTEOVOC 分为异戊二烯、单萜烯和其他 VOCs 排放通量,μgC/(m2·h)ε为标准排放速率,μg C/(g·h)D 为叶生物量密度, g/m2γpγT 分别为光合有效辐射影响因子、温度影响因子;ρ为逸出效率,即排放总量中逸散到树冠上方大气中的部分所占的比例,取值为1。由于异戊二烯、单萜烯和其他 VOCs 的排放量受气温和辐射等外界条件的影响不同,异戊二烯排放同 校正因子(γP)的计算公式为:

     

    式中:α(0.0027)CL(1.066)为经验常数;Q是当前的光量子密度(PPFD)μmol/(m ·s)

    温度校正因子(γT)的计算公式为:

    式中:T为当前叶表面温度(K),该 用树冠外的气温代替叶表面温度;Ts(303 K)为标准条件下的叶温;CT1(95000 J/mol)CT2(230000 J/mol)Tm(314 K)均为经验常数;R(8.314 J/K)为气体常数。

    单萜烯和其他 VOCs 排放受温度影响,温度校正因子(γT)的计算公式为:

    说明: 图片包含 物体已生成极高可信度的说明

    1.2.2 O3   SOA 生成潜势估算模型

    本研究利用 O3 SOA 生成潜势来表征城市绿地对大气环境的潜在影响。由于植被释放 VOCs 的种类较多,且其化学反应活性具有明显的差异性,因此,对臭氧的贡献率也大不相同。研究仅对天然源 VOCs 组分中占比较大的异戊二烯和单萜烯的臭氧生成潜势和二次有机气溶胶生成潜势进行计算。

    本研究采用 VOCs 的最大增量反应活性对其臭氧生成潜势进行量化。其计算公式为:

    说明: 图片包含 物体已生成极高可信度的说明

    式中:OFPi 为某 VOCs 物种 i 生成 O3 的最大值,ug/m3; VOCi 为第 i VOC 物种的环境浓度或释放量,ug/m3 MIR 是第 i VOC物种的最大增量反应活性,g/g。 果,异戊二烯取值为10.61 g/g,单萜烯取值为4.04 g/g

    二次有机气溶胶 (SOA) 生成潜势是天然源 VOCs 对大气环境质量影响的评价指标之一。本研究利用气溶胶生成系数以量化 VOCs SOA 生成潜势。且基于 Grosjean[14] 烟雾箱实验假设 SOA 光化学反应仅在白天8:00-17:00时间段发生,而 VOCs 仅与 OH-反应生成 SOA。其计算公式为:

    说明: 图片包含 物体已生成极高可信度的说明

    式中:SOA 为某 VOC 物种 i 二 机气溶胶的生成量,ug/m3VOCi0为排放源排出第 i VOC 物种的初始浓度或排放量,ug/m3,研究假设植物i0 i 释放的 VOCs 全部由 VOC 反应得来;FAC 是第 i VOC 物种的 SOA 生成系数,以 Grosjean[14] FAC研究数据为参考,异戊二烯取2%,单萜烯取30%

    1.3 参数选取

    1.3.1 植被分布数据

    通过卫星遥感解译获得 2015 年北京市的土地利用分布情况(图1,精度为80%),并依据《土地资源分类系统》,本研究将研究区域的土地利用类型划分为水域、水田、旱地、草地、有林地、灌木林、疏林地、其他林地、城乡工矿居民用地、未利用地等十类土地利用类型。就北京市的植被分布而言,有林地、灌木林所占面积相对较大,且有林地主要集中在怀柔区、密云县和延庆县,灌木林主要分布在门头沟区、房山区和昌平区西部。各土地类型面积见表1

     

    1 北京市土地利用分布图

    Figure 1 Land Use Distribution in Beijing

     

     

    1 北京市土地利用类型面积统计

    Table 1 Area Summary of Different Land Use Types in Beijing

    序号

    土地利用类型

    面积 /km2

    1

    水田

    280.327

    2

    旱地

    1418.442

    3

    有林地

    3169.986

    4

    灌木林

    2231.083

    5

    疏林地

    1839.566

    6

    其他林地

    1738.493

    7

    草地

    1775.196

    8

    水域

    178.689

    9

    城乡工矿居民用地

    2703.557

    10

    未利用地

    1058.572

    1.3.2 标准排放因子

    本研究中对于不同植被类型的 VOCs 标准排放因子,优先采用北京地区或相近地区的实测值[15-16],其次采用分档方法进行取值(表2)。基于国内外各类植被 VOCs 标准排放因子实测值,各植被类型分布占比与之加权平均,比较加权平均值与 VOCs 标准排放因子分档值差异程度,取与数值差距最小的分档值作为相应植被类型的 VOCs 标准排放因子。对异戊二烯的排放(C)分为 6 档取值,分别为0.11.06.08.034.060.0 μg C/(g·h);对单萜烯的排放分为 5 档,分别为0.1, 0.2, 0.65, 1.5, 3.0 μg C/(g·h);对其他 VOCs,一律取为 1.5μgC/(g·h)

    1.3.3 叶生物量密度和叶面积指数

    根据国内目前叶生物量密度和叶面积指数的实测研究结果,研究数据主要参考北京市及其附近地区乃至全国的叶面积指数和叶生物量密度实测数据和其计算方法获得[17-21],具体见表2

    1.3.4 气象数据

    本研究中所涉及的温度、湿度、风速和总辐射照度数据来源于中国气象数据服务网上北京市的年平均气象数据,光合有效辐射值根据气候学的经验公式[22-23]计算获得。

     

    2 北京市土地利用类型面积统计

    Table 2 Area Summary of Different Land Use Types in Beijing

     

    土地利用类型

    排放因子 [ugC/g·h]

    LMD

    (g/m2

    LAI

    (m2/m2

    异戊二烯

    单萜烯

    OVOCs

    水田

    0.20

    0.51

    0.31

    500

    4

    旱地

    0.10

    0.10

    0.02

    740

    4

    有林地

    2.67

    1.75

    1.50

    785

    5

    灌木林

    7.67

    0.60

    1.85

    89

    2

    疏林地

    1.22

    3.05

    1.83

    31

    4

    其他林地

    1.00

    0.65

    1.70

    650

    4

    草地

    0.50

    0.20

    0.56

    105.2

    2.5

    水域

    0.00

    0.00

    0.00

    0

    0

    城乡工矿居民用地

    0.10

    0.10

    1.50

    31

    2

    未利用地

    0.10

    0.10

    1.50

    31

    1.3

    2 结果与分析

    2.1 北京市天然源 VOCs 排放总量

    2015 年度北京市天然源 VOCs 的年排放总量(以C计)约为34971.631 t。其中,异戊二烯为10572.582 t,占年度总排放量的30.23%;单萜烯为11328.896 t,占年度总排放量的32.39%;其他 VOCsOVOCs)为13070.152 t,所占比例最高,达37.37%。从各土地利用类型对三类 VOCs 的贡献情况来看,有林地异戊二烯、单萜烯和 OVOCs 的释放量均居于第一,占比均在57%以上,原因在于有林地占全市土地面积比例较大,植被种类组成丰富,落叶树种和常绿树种覆盖较广,释放 VOCs 的能力较强;灌木林对异戊二烯的贡献量仅次于有林地,但数值上相差较大。其他林地对单萜烯和 OVOCs的贡献位居第二,贡献率分别为13.10%29.69%

    2.2 北京市天然源 VOCs 的空间分布特征

    异戊二烯排放高值区整体集中在辖区北部,主要分布在怀柔区、延庆县的东北部和西部、密云县的东部和西北部、平谷区的北部、门头沟区的西部以及其与房山区的交界处、昌平区与延庆县的交界处。这些区域大多为林区密集的地方,加之林地排放因子较高,因此,异戊二烯排放量较高,最高排放量超过2.0×103 kg/(km2·a)。异戊二烯排放中值区主要集中在门头沟区与房山区,该区域灌木林与其他林地面积占比相对较大,其排放值在750 kg/(km2·a)左右;而在经济较发达、城镇化相对较高的区域,如城市中心区、顺义区、城市中心区与通州区的交界处、大兴区和昌平区的交界处,异戊二烯年度排放通量均比较小,一般在100 kg/(km2·a)以下。

    单萜烯高值区的分布情况与异戊二烯高值区大体一致,该区域植被面积较大,且几乎均是阔叶林和针叶林的聚集之处,其最高值超过异戊二烯,在2.5×103 kg/(km2·a)以上。单萜烯排放中值区面积较小且分布较为零散,其中平谷区分布较为集中,通州区、大兴区与房山区也均有小面积分布。单萜烯中低值区集中分布在延庆县、门头沟区与房山区,覆盖之地植被较为匮乏,林地较为稀疏。单萜烯低值区区域分布与异戊二烯低值区一致。

    其他 VOCs 排放量较高的地区多集中在辖区北部郊县,而在辖区南部地区分布较为零散,最高排放通量达2.3×103 kg/(km2·a)。同时 OVOCs 的排放高值区总面积也要明显大于异戊二烯和单萜烯的排放高值区总面积。天然源 VOCs 的排放高值区主要集中在延庆县东北部、怀柔区以及其与密云县和延庆县的交界处,而平谷区、密云县的边界处、门头沟区的边界处及其与房山区交界处也有一定的分布,其值高达7.4×103 kg/(km2·a),这些地方均存在林区密集、城镇化低等特点。

    天然源 VOCs 年度排放通量空间分布差异较大,最高排放通量约为最低排放通量的 70 倍左右。对于门头沟区和房山区两地而言,异戊二烯、单萜烯、其他 VOCs 和总 VOCs 的排放通量均处在中等水平,这是由于其主要植被为排放因子较高的灌木林,但其叶生物量密度相对较低。结合北京市土地利用情况和植被分布可得,天然源 VOCs 排放通量的空间分布情况与城镇化程度、林区和农作物的区域分布有一定的相关性。

    2 天然源 VOCs 各组分年度排放通量空间分布 [kg/(km2·a)]

    Figure 2 Spatial Distribution of Annual Emission of Biogenic VOC Contents [kg/(km2·a)]

     

    2.3 O3 SOA 生成潜势

    北京市天然源 VOCs 对臭氧生成潜势 (OFP) 的贡献总量为157943.839 t,其中异戊二烯对 OFP 的贡献量为112175.099 t,占比71.02%,为主要贡献者;单萜烯对 OFP 的贡献量为45768.740 t,占比28.98%。为了评价OFP 对北京市大气环境质量的影响,本研究对北京市 O3 生成潜势的区域分布进行了分析(图 3)。整体来看,辖区北部区县 O3 生成潜势较高,高值区空间分布与 BVOCs 空间分布一致,主要集中分布在延庆县和怀柔区,覆盖之地林区密集,其植被密度较大,物种丰富,多为天然林和人工林交织的有林地。OFP 中值区、中低值区和低值区的空间分布情况与异戊二烯相应值区的空间分布一致。OFP 中值区多集中分布在位于辖区西南部的门头沟区、房山区等区县,该区域大多为矮林地与灌丛林地交织的灌木林及其他林地。OFP 中低值区分布较为广泛,其中旱地、草地、疏林地面积占比较大;OFP 低值区覆盖了城乡建设水平较高的城市中心区,且未经利用的土地和水域面积较广,可能由于这些区域异戊二烯和单萜烯排放能力较弱,臭氧生成潜势较低。

    通常情况下,OFP 与对应的 O3 浓度成正比,该区域 OFP 越高,O3 浓度也越大。为更准确评价 OFP 对北京市大气环境质量的影响,后续还应将环境监测 O3 浓度分布与 OFP 空间分布做进一步的对比分析。

    北京市天然源 VOCs 对二次有机气溶胶 (SOA) 生成的贡献量为3610.120 t,其中异戊二烯形成的 SOA 生成潜势为 211.452 t,贡献率仅为5.86%;而单萜烯作为主要贡献者,产生的 SOA 生成潜势为 3398.669 t,贡献率 94.14%SOA 生成潜势空间分布如图4 所示,整体而言,SOA 生成潜势空间分布状态与 OFP 相近,但从数值上来看,SOA 生成潜势与 OFP 相比却相差一个数量级。SOA 生成潜势高值区区域分布与 BVOCs 排放高值区相一致,该区域以针叶林、阔叶林和针阔混交林居多,植被释放 BVOCs 的能力较强。SOA 生成潜势中低值区与低值区主要集中在城镇化程度较高、水域面积较大和植被覆盖度较低的区域,该区域异戊二烯和单萜烯的排放能力均较弱,两个值区 SOA 生成潜势之和仅占全区 SOA 生成潜势总量的 3.93%

     

    3 讨论

    国内外许多学者致力于城市地区、不同国家乃至全球范围内天然源 VOCs排放通量估算的研究。通过与国内外不同学者对北京市天然源挥发性有机物排放的研究结果相比较发现(表3),本研究中各组分天然源挥发性有机物的排放量均高于文献[17]的估算值,其中总 BVOCs 排放通量与文献[15]的估算值最为接近,但与文献[2]的估算值相差较大;异戊二烯排放量的估算值与文献[24]与文献[17]的估算值相近;OVOCs 排放量的估算值与文献[2]最为接近;而单萜烯排放量的估算值均高于其余文献的估算值。推断是在估算过程中,由于标准排放因子、气象条件、土地利用、植被分布等数据获取途径的差异,不同研究针对同一地区的估算结果会存在一定差异。

    3 臭氧生成潜势空间分布(t

    Figure 3 Spatial Distribution of Ozone Formation Potential (t)

    4 二次有机气溶胶生成潜势空间分布(t

    Figure 4 Spatial Distribution of Secondary Organic Aerosol Formation Potential (t)

     

     

    3 北京市区域天然源挥发性有机物排放量估算值对比(单位 :t

    Table 3 Comparison of Estimated Emission of Biogenic

    Volatile Organic Compounds of Beijing (unit: t)

    数据来源

    异戊二烯

    草萜烯

    OVOCs

    总 BVOCs

    文献【17】

    0.79×104

    0.35×104

    0.48×104

    1.6×104

    文献【15】

    3.09×104

    0.59×104

    0.16×104

    3.85×104

    文献【2】

    2.78×104

    0.8×104

    1.69×104

    5.27×104

    文献【24】

    1.39×104

    0.78×104

    2.36×104

    4.8×104

    本研究

    1.06×104

    1.13×104

    1.13×104

    3.50×104

    4 结论

    12015 年度北京市天然源 VOCs 的年排放总量(以C计)约为34971.631 t,异戊二烯、单萜烯和其他 VOCsOVOCs)分别为10572.582 t11328.896 t13070.152 t,分别占年度总排放量的30.23%32.39%37.37%

    2)天然源 VOCs 年度排放通量空间分布差异较大,异戊二烯和单萜烯排放高值区主要集中在辖区北部,低值区主要集中分布在城市中心区。天然源VOCs 排放通量的空间分布情况与城镇化程度、林区和农作物的区域分布有一定的相关性。

    3)北京市天然源 VOCs 对臭氧生成潜势 (OFP) 的贡献总量为157943.839 t,异戊二烯为主要贡献者;天然源 VOCs 对二次有机气溶胶(SOA) 生成的贡献量为 3610.120 t,单萜烯为主要贡献者。臭氧生成潜势与二次有机气溶胶生成潜势高值区空间分布与 BVOCs 排放高值区相一致。

    Introduction

    The volatile organic compounds (VOCs) indicate volatile organic compounds whose boiling points are between 50℃ and 260℃ and saturated steam pressure is over 133.32Pa in an indoor temperature. Such VOCs mainly include hydrocarbons, oxygen hydrocarbons, nitrogen hydrocarbons, sulfur hydrocarbons and low-boiling point polycyclic aromatic hydrocarbons [1]. VOCs are divided by source into biogenic (BVOCs) and man-made source (AVOCs). The VOCs emission of vegetation accounts for over 90%[2-3]. As an important precursor formed by the secondary organic aerosol (SOA) [4-7], VOCs plays a critical role in the formation of atmospheric particulates pollution. VOCs contributes much to the formation of O3 in cities. The concentration of O3 on the troposphere layer is closely associated with O3 formation rate and VOCs[8-9]. When NOx is sufficient, some frequent biogenic VOCs can form O3 easier compared to VOCs emitted in the human being activities. The urban green system is the gathering place of vegetation. The biogenic VOCs emission and their potential negative effect on atmospheric environment cannot be ignored. By combing GIS with RS, the biogenic VOC emission of Beijing in 2015 is estimated by using the GloBEIS model and its spatial distribution characteristics are analyzed based on the land use conditions and vegetation data interpreted by using Landsat8 OLI remote-sensing images. In addition, the formed O3 and SOA formation potential are estimated based on biogenic VOCs conditions of areasunder jurisdiction, so it puation of the influences of rovides supporting data for evalbiogenic VOCs of Beijing on air quality in North China and has realistic significance for governance and improvement of regional air environment pollution.

    1 Materials and Methods

    1.1 Research Areas

    The simulation area covers 115°42'-117°24'E, 39°24'-41°36'N in Beijing for this research, which includes areas under jurisdiction of Beijing and suburban counties. The Landsat8 OLI remote-sensing images of Beijing in 2015 are selected as the data source. By combining land use data, AP is used to establish some 2.5 km×2.5 km grids. The geographical conditions of a grid is marked by using the latitude and longitude coordinate of the center point of each grid. The simulation

    areas cover 2624 grids.

    1.2 Estimation Model

    1.2.1 Estimation model of biogenic VOC emission

    The emission of the volatile organic compounds of Beijing in 2015 is estimated by using the GloBEIS model in this research. The volatile organic compounds emitted by vegetation are diversified. The isoprene and monoterpene are ranked

    as top volatile organic compounds. Therefore, the volatile organic compounds

    emitted by ecological vegetation in Beijing are divided into isoprene, monoterpene and all other VOCs (alcohol, aldehyde, ketone, organic acid, alkanes and olefin). The basic algorithm of the GloBEIS model refers to the method proposed by Guenther [10-12] and its calculation equation is described as follows:

    说明: 图片包含 物体已生成高可信度的说明

     

    In this equation, EISO, E and E indicate isoprene, monoterpene and VOCs emission (unit: μgC/(m²·h)), ε g C/(g•h)), D is the leaf biomass density (unit: g/m ), and γ and γT indicate the photosynthetically active radiation influence factor and temperature influence factor, ρindicates the escape efficiency, namely the proportion of emission escaped to the atmosphere above the crown in total, which takes the value 1. The isoprene, monoterpene and other VOCs emission are affected by external conditions such as temperature and radiation. The isoprene is affected by light and temperature simultaneously and the photosynthetically active radiation correction factor (γP) is calculated by using the following equation:

    In this equation, α(0.0027) and CL(1.066) indicate the empirical constant, Q is the current optical quantum d 2·s)). The temperature correction factor (γT) is calculated as follows:

    n this equation, T indicates the current leaf surface temperature (K). Thetem-perature outside the crown is used to replace the leaf surface temperature in this research. Ts(303 K) indicates the leaf temperature, CT1(95000 J/mol),CT2(230000 J/mol) and Tm(314 K) are the empirical constant, and R(8.314 J/K) indicates the air constant.

    Emission of monoterpene and other VOCs is affected by temperature and the temperature correction factor (γT) is calculated by using the following equation:

    说明: 图片包含 物体已生成极高可信度的说明

    1.2.2 Estimation Model of O and SOA Formation Potential

    The O3 and SOA formation potential is used to express potential influences of the urban green space on atmospheric environment in this research. The VOCs emitted by vegetation are diversified and their chemical reaction activities are significantly different, therefore, they contribute to ozone very differently. The ozone formation potential and secondary organic aerosol formation potential of top isoprene and monoterpene in the biogenic VOC are only calculated in this research.

    The maximum incremental reaction activities of VOCs is used to quantify the ozone formation potential and it is calculated by using the following equation:

    说明: 图片包含 物体已生成极高可信度的说明

    In this equation, OFPi is the maximum of O3 formed by a VOCs species ((unit:ug/m3),VOCi is the environmental concentration or emission of ith VOC species (unit: ug/m3), MIRi is the maximal incremental reaction activities of ith VOC species (unit:g/g). The latest research results of Carter[13] for MIR are used in calculation, the isoprene value is 10.61 g/g, and the monoterpene value is 4.04 g/g.

    The secondary organic aerosol (SOA) formation potential is one of the evaluation indexes of influences of the biogenic VOC on the atmospheric environment quality. The aerosol formation coefficient is used to quantify SOA formation potential of VOCs in this research. The SOA photochemical reaction is assumed to only [14]happen in the period 8:00-17:00 in Grosjean smoke box experiment and VOCs only reacts with OH- to generate SOA. The calculation equation is described as follows:

    说明: 图片包含 物体已生成极高可信度的说明

    In this equation, SOAi is the formed secondary organic aerosol of a VOC species (unit: ug/m3), VOCi0 is the initial concentration or emission of ith VOC species of the emission source (unit: ug/m3). All VOCs emitted by vegetations are from VOCi0 reaction in research, and FACi is SOA formation coefficient of ith VOC species.With FAC research data of Grosjean[14] as reference, the isoprene takes 2% and the monoterpene takes 30%.

    1.3 Parameter Selection

    1.3.1 Vegetation Distribution Data

    Land use distribution of Beijing in 2015 can be obtained by interpreting the satellite’s remote-sensing images (shown as the figure 1, the precision is 80%) and the research areas are divided by land use type into water area, paddy field, dry land, grass land, forest land, shrub forest, open forest land, other forest land, residential land for urban and rural industrial mines and unused lands. For vegetation distribution in Beijing city, the forest land and shrub forest cover larger areas and the forest lands are mainly distributed in Huairou district, Miyun county and Yanqing county. The shrub forest is mainly distributed in Mentougou district, Fangshan district and west Changping district. For the areas of different land types, refer to the table 1.

    1.3.2 Standard Emission Factor

    The measured values in Beijing or close areas will be the priority slection for VOC standard emission factor of different vegetation types in this research [15-16]. Otherwise, the grading method is used to take values (table 2). Based on measured value of VOC standard emission factors of different vegetation at home and abroad, the weighted average of the distribution proportions of different vegetation and these values is calculated. Differences between the weighted average and the grading values of VOCs standard emission factor are compared. The grading value with minimal difference is taken as the VOCs standard emission factor of the corresponding vegetation types. 6 grades are taken for isoprene emission (counted by C), including 0.1, 1.0, 6.0, 8.0, 34.0 and 60.0 μg C/(g·h). Monoterpene emission is divided into five grades, including 0.1, 0.2, 0.65, 1.5 and 3.0 μg C/(g·h). Generally 1.5μgC/(g·h) is taken for other VOCs.

    1.3.3 Leaf Biomass Density and Leaf Area Index

    Based on the research results on measured leaf biomass density and leaf area index in China, the research results are obtained by referring to the measured leaf area index and leaf biomass density in Beijing, surrounding areas and the whole country and its calculation method[17-21]. For details, refer to the table 2.

    1.3.4 Meteorological Data

    The temperature, humidity, wind speed and total radiant illumination data involved in this research is from the annual average meteorological data of Beijing at the China meteorological data service website and the photosynthetic effective radiation value is obtained according to the experience equation of the climatology[22-23].

    2 Results and Analysis

    2.1 Total Biogenic VOCs Emission of Beijing

    Total biogenic VOCs emission of Beijing in 2015 (counted by C) is about 34971.631t. The isoprene emission is 10572.582 t and accounts for 30.23% of total annual emission. The monoterpene emission is 11328.896 t and accounts for 32.39% of total annual emission. Other VOCs (OVOCs) emission is 13070.152 t and accounts for 37.37% of total annual emission. From contribution of different land use types to three VOCs, the contribution of the forest land to isoprene, monoterpene and OVOCs emission is ranked first and total proportion is over 57% because the forest lands have a higher proportion in total land, the vegetation are diversified, the deciduous species and evergreen species are covered extensively, and they emit large amount of VOCs strongly. The contribution of the shrub forest to the isoprene is only inferior to that of the forest land, but the difference is bigger. The contribution of other forest lands to monoterpene and OVOCs is ranked as the second position. The contribution rate is 13.10% and 29.69% respectively.

    2.2 Spatial Distribution Characteristics of Biogenic VOC of Beijing

    On the whole, the high emission areas of the isoprene are mainly distributed in the north area under jurisdiction, including Huairou district, north-east and west of Yanqing county, east and north-west of Miyun county, north of Pinggu district, west of Mentougou district and its boundary with Fangshan district, and boundary between Changping district and Yanqing county. Most of these areas have dense forest lands and the forest lands have higher emission factor, so isoprene emission is higher. The maximum emission is over 2.0×103 kg/(km²·a). The median emission areas of the isoprene are mainly distributed in Mentougou district and Fangshan district. The shrub forest and other lands are larger in this area and the emission is about 750 kg/(km²·a). The developed areas and highly urbanized areas such as urban center area, Shunyi district and boundary between urban center area and Tongzhou district and between Daxing district and Changping district have smaller annual isoprene emission. Generally it is under 100 kg/(km²·a).

    The distribution law of the high emission areas of the monoterpene are roughly consistent with the high area of the isoprene emission. This area has large vegetation area and is nearly the gathering area of the broad-leaved forest and the coniferous forest. Its maximum emission is over that of isoprene and exceeds 2.5×103 kg/(km²·a). The median emission areas of the mono ne are smaller and are distributed dispersedly. These areas are mainly distri n the Pinggu district and small areas are distributed in Tongzhou district, Daxing district and Fangshan district. The low emission areas of the monoterpene are mainly distributed in Yanqing county, Mentougou district and Fangshan district. The vegetation are scare and the forest lands are disperse. The distribution of the low monoterpene mission is consistent with that of the low isoprene emission.

    The higher emission areas of VOCs are mainly distributed in the north suburban counties under jurisdiction and are disperse in the south area under jurisdiction. The maximum emission is 2.3×103 kg/(km²·a). Total high emission areas of OVOCs emission are significantly bigger than total high emission areas of the isoprene and monoterpene. The high emission areas of biogenic VOC are mainly distributed in the north-east of Yanqing county, Huairou district and the boundary with Miyun county and Yanqing county. Some areas are distributed in Pinggu district, boundary of Miyun county, boundary of Mentougou district and boundary with Fangshan district. The maximum reaches 7.4×103 kg/(km²·a). These areas feature dense forest areas and low urbanization.

    The spatial distribution of the annual biogenic VOC emission is very different. The maximum emission is about 70 times of the minimum emission. For Mentougou district and Fangshan district, the emission of isoprene, monoterpene, other VOCs and total VOCs ranked as the middle level because the main vegetation is the shrub with higher emission and its leaf biomass density is relatively low.

    By combining the land use and vegetation distribution in Beijing, the spatial distribution of biogenic VOC emission is related to urbanization, forest area and crop distribution to some extent.

    2.3 O3 and SOA Formation Potential

    The total contribution of the biogenic VOC to the ozone formation potential (OFP) is 157943.839 t in Beijing. The contribution of the isoprene to OFP is 112175.099 t, which accounts for 71.02% and is the main contributor. The contribution of the monoterpene to OFP is 45768.740 t, which account for 28.98%. To evaluate influences of OFP on the atmospheric environmental quality in Beijing, distribution of the O3 formation potential areas is analyzed for Beijing in this research (shown as the figure 3). On the whole, the O3 formation potential is higher in the north districts and counties under jurisdiction. The spatial distribution of high value areas is consistent with the spatial distribution of BVOCs and these areas are mainly distributed in Yanqing county and Huairou district. The forests are dense, vegetation density is higher, species are diversified and the natural forests and man-made forests are interwoven in these areas. The spatial distribution of median OFP areas, median and low OFP areas and low OFP areas is consistent with that of the corresponding isoprene areas. The median OFP areas are mainly distributed in the Mentougou district and Fangshan district in the south areas under jurisdiction. Most areas are the shrub forest and other forest lands with interweaving coppice-land and shrub lands. The median and low OFP areas are distributed extensively, among which the areas of the dry lands, grass lands and open forest lands are larger. The low OFP areas cover the urban center areas with higher urban and rural construction level. The unused lands and water areas are distributed extensively. The isoprene and monoterpene emission capabilities are weaker and the ozone formation potential is lower in these areas.

    Generally the OFP is proportional to the corresponding O3 concentration. The OFP is higher in this area and O3 concentration is higher. To accurately evaluate influences of OFP on the atmospheric environmental quality in Beijing, the environmental O3 concentration distribution will be further monitored and be compared with the OFP spatial distribution.

    The contribution of the biogenic VOC to the secondary organic aerosol is 3610.120 t. The SOA formation potential formed by the isoprene is 211.452 t and its contribution rate is only 5.86%. The monoterpene is the main contributor, its formed SOA formation potential is 3398.669 t and the contribution rate is 94.14%. The distribution of SOA formation potential is shown as the figure 4. On the whole, the spatial distribution of the SOA formation potential is similar to OFP. The SOA formation potential is inferior to OFP by one magnitude. The distribution of the high areas of SOA formation potential is consistent with the high areas of BVOCs emission. The coniferous forest, broad-leaved forest and the mixed-broadleafconiferforest are dominant in this area. The vegetation emit large amount of BVOCs strongly. The middle and low areas and low areas of the SOA formation potential are mainly distributed in the areas with higher urbanization, larger water areas and lower vegetation coverage. The isoprene and monoterpene emission capabilities are weaker in this area and the SOA formation potential sum of two areas is only 3.93% of total SOA formation potential in the whole area.

    3 Discussions

    Plentiful domestic and foreign scholars are dedicated to research on biogenic VOC emission estimation in urban areas, different countries and the world. By comparing research results of domestic and foreign scholars on biogenic volatile organic compound emission of Beijing (table 3), the emission of the biogenic volatile organic compounds of different groups in this research is higher than the estimation value in the reference [17]. Total BVOCs emission approaches to the estimated value in the reference [15], but it is very different from the estimation value in the reference [2]. The estimated isoprene emission approaches to the estimation value in the reference [24] and [17]. The estimated OVOCs emission approaches to that in the reference [2]. The estimated monoterpene emission is higher than the estimated values in other references. It is deduced that the estimation results of one area in different research will vary due to different acquisition manners of standard emission factor, meteorological conditions, land use and vegetation distribution in estimation.

    4 Conclusions

    (1) Total annual emission of biogenic VOC of Beijing in 2015 (counted by C) is bout 34971.631 t and the emission of isoprene, monoterpene and other VOCs (OVOCs) are 10,572.582 t, 11,328.896 t and 13,070.152 t, which account for 30.23%, 32.39% and 37.37% of total annual emission respectively.

    (2) The spatial distribution of annual emission of the biogenic VOC varies much. The high emission areas of the isoprene and monoterpene are mainly distributed in the north areas under jurisdiction and the low emission areas are mainly distributed in the urban center area. The spatial distribution of the biogenic VOC emission is related to distribution of the urbanization, forest and crops.

    (3) Total contribution of the biogenic VOC to the ozone formation potential (OFP) is 15,7943.839 t in Beijing and the isoprene is main contributor. The contribution of the biogenic VOC to the secondary organic aerosol (SOA) formation is 3,610.120 t and the monoterpene is the main contributor. The spatial distribution of high emission areas of the ozone formation potential and the secondary organic aerosol formation potential is consistent with the high emission area of BVOCs.

    参考文献(References:

    [1] Weetman D F. Volatile organic chemicals in the environment[J]. Indoor Environment. 1994, 3(1):55-57.

    [2] Guenther A, Hewitt CErickson D, et al.A global model of natural volatile organic compound emissions. Journal of Geoghysical Research Atmospheres, 1995100(D5):8873-8892

    [3] Laothawornkitkul J, Taylor J E, Paul N D, et al. Biogenic volatile organic compounds in the Earth system. New Phytologist, 2009, 183(1): 27-51.

    [4]Chung S H, Seinfeld JH .Global distribution and climate forcing of carbon aceousaerosols[J].Journal of Geophysical Research:Atmospheres,2002,107(D19):AAC14-1-AAC14-33

    [5] Hallquist M, Wenger J C, Baltensperger U, et al. The formation, properties and impact secondary organic aerosol: current and emerging issues [J]. Atmospheric Chemistry and Physics, 2009, 9(14):5155-5236.

    [6] Carlton A G, Wiedinmyer C, Kroll J H. A review of secondary organic aerosol (SOA) formation from isoprene [J]. Atmospheric Chemistry and Physics, 2009, 9(14):4987-5005.

    [7] 李莹莹 , 李想 , 陈建民.植物释放挥发性有机物 (BVOC) 向二次有机气溶胶 (SOA) 转化机制研究 [J]. 环境科学 , 2011, 32(12):3588-3592. LI Yingying, LI Xiang, CHEN Jianmin. Study on transformation mechanism of SOA from biogenic VOC under UV-B Condition[J]. Environmental Science, 2011, 32(12):3588-3592.

    [8]  Arimura G, Ozawa R, Kugimiya S, et al. Herbivore-induced defense response in a model legume: Two-spotted spider mites induce emission of (E)-β-ocimene and transcript accumulation of (E)-β-ocimene synthase in Lotus japonicas[J]. Plant Physiology, 2004, 135(4):1976-1983.

    [9] Derwent R G, Jenkin M E, Saunders S M, et al. Photochemical ozone formation in north west Europe and its contro1 [J]. Atmospheric Environment, 2003, 37:1983-1991.

    [10] Skaltsas T, Avgouropoulos G, Tasis D. A global model of natural volatile organic compound emissions [J]. J.geophys.res, 1995, 100(D5):8873-8892.

    [11] Guenther A, Baugh B, Brasseur G, et al. Isoprene emission estimates and uncertainties for the central African EXPRESSO study domain [J]. Journal of geophysical research atmospheres, 1999, 104(D23): 30 625, 30 639.

    [12] Guenther A, Geron C, Pierce T, et al. Natural emissions of non-methane volatile organic compounds, carbon monoxide, and oxides of nitrogen from North America [J]. Atmospheric environment, 2000, 34(s12/14): 2205-2230.

    [13] Carter W P L. Updated maximum incremental reactivity scale and hydrocarbon bin for reactivities regulatory applications [EB/OL]. (2010-01-28)[2018-03-14]. http://www.cert.ucr.edu/ ~carter/SAPRC/MIR10/.

    [14] Grosjean D. In situ organic aerosol formation during a smog episode: estimated production and chemical functionality [J]. Atmospheric Environment, Part A, General Topics, 1992, 26(6):953-963.

    [15] 谢扬飏 , 邵敏,陆思华,等 . 北京市园林绿地植被挥发性有机物排放的估算 [J].中国环境科学,2007,27(4):498-502.XIE Yang-yang, SHAO Min, LU Si-hua, et al. The estimation of volatile organic compounds emission from landscape plants in Beijing[J]. China Environmental Science, 2007,27(4):498-502.

    [16] 赵静,白郁华,王志辉,等 . 我国植物 VOCs 排放速率的研究 [J]. 中国环境科学,2004,24(6):654-657.ZHAO Jing, BAI Yuhua, WANG Zhihui, et al. Studies on the emission rates of plants VOCs in China[J]. China Environmental Science, 2004,24(6):654-657.

    [17] Wang Z H, Bai Y H. A biogenic volatile organic compounds emission inventory for Beijing[J]. Atmospheric Environment, 2003, 37: 3771-3782.

    [18]  陈传国,朱俊凤,东北主要林木生物量手册 [M]. 北京 : 中国林业出版 ,1989. CHEN Chuanguo, ZHU Junfeng. Handbook of biomass of major forest in northeastern China[M]. Beijing: China Forestry Publishing House, 1989.

    [19] 陈自新 . 北京城市园林绿化生态效益的研究 [J]. 中国园林 1998,14(1):54-59. CHEN Zixin. Study on Ecological benefits of urban landscaping in Beijing[J]. Chinese Landscape Architecture,1998,14(1):54-59.

    [20]  肖传法,刘建生,光增云,等 . 木材立木材积速算表 [M]. 郑州:河南科学技术出版社 , 2005XIAO Chuanfa, LIU Jiansheng, GUANG Zengyun, et al. Speedsheet of timber standing volume[M].Zhengzhou: Henan Science and Technology Press,2005.

    [21] 胡永涛,张远航,谢绍东,等 . 区域高时空分辨率 VOC 天然源排放清单的建立 [J].环境科学 ,2001,22(6):1-6. HU Yongtao, ZHANG Yunhang, XIE Shaodong, et al. Development of biogenic VOC emissions inventory with high temporal and spatial resolution[J]. Environment Science. 2001, 22(6):1-6.

    [22] 周允华, 项月琴, 栾禄凯 . 光合有效量子通量密度的气候学计算 [J]. 气象学报 , 1996,54(4):447-455.ZHOU Yunhua, XIANG Yueqin, LUAN Lukai. Climatological estimation of photosynthetically active quantum flux [ J ] . Acta Met eorologica Sinica,1996,54(4):447-455.

    [23]  白建辉. 华北地区光合有效辐射的计算方法研究[J]. 气象与环境学报 ,2009,25(2):1-8. BAI Jianhui. Calculating photosynthetically active radiation in North China[J]. Journal of Meteorology and Environment,2009,25(2):1-8.

    [24] Klinger L, Li Q, Guenther A, et a. Assessment of volatile organic compound emissions from ecosystems of China[J]. Journal of Geophysical Research-Atmospheres,2002,107(21): 4603-4624.

     

    (整理:赵迪 译:汪渊)

    上一条:打开绿生活,社群共创都市社区景观 下一条:走向公园城市——天津大学公园城市实践

    关闭