| 北京市黑碳气溶胶浓度特征及其主要影响因素 |
| 摘要点击 2522 全文点击 638 投稿时间：2021-03-05 修订日期：2021-06-01 |
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| 中文关键词 黑碳(BC) 路边站 浓度特征 日变化 吸收埃斯特朗指数(AAE) 污染过程 |
| 英文关键词 black carbon(BC) roadside site concentration characteristic diurnal variation absorption Angstrom exponent(AAE) pollution episode |
| 作者 | 单位 | E-mail | | 曹阳 | 北京市生态环境监测中心, 北京 100048
大气颗粒物监测技术北京市重点实验室, 北京 100048 | caoyang1990x@hotmail.com | | 安欣欣 | 北京市生态环境监测中心, 北京 100048
大气颗粒物监测技术北京市重点实验室, 北京 100048 | | | 刘保献 | 北京市生态环境监测中心, 北京 100048
大气颗粒物监测技术北京市重点实验室, 北京 100048 | liubaoxian28@163.com | | 景宽 | 北京市生态环境监测中心, 北京 100048
大气颗粒物监测技术北京市重点实验室, 北京 100048 | | | 王琴 | 北京市生态环境监测中心, 北京 100048
大气颗粒物监测技术北京市重点实验室, 北京 100048 | | | 罗霄旭 | 北京市生态环境监测中心, 北京 100048
大气颗粒物监测技术北京市重点实验室, 北京 100048 | |
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| 中文摘要 |
| 为探究北京市黑碳（black carbon，BC）气溶胶时空分布特征及其主要影响因素，对4个站点2019年的ρ（BC）、ρ（PM2.5）、ρ（CO）和φ（NOx）及同期气象因子进行比对分析.结果表明，背景区（BA）、城区（UA）、城区路边（UR）和外环路边（HR）的平均ρ（BC）分别为（1.58±1.15）、（2.27±1.67）、（3.35±2.13）和（3.57±2.40）μg·m-3，ω（BC/PM2.5）分别为（5.3±1.6）%、（6.0±2.3）%、（9.0±3.6）%和（8.1±3.5）%；除UR站点ρ（CO）高于HR站点以外，4个站点的ρ（BC）、ρ（PM2.5）、ρ（CO）和φ（NOx）由低到高排序均为：背景区 < 城区 < 城区路边 < 外环路边，且采暖季是非采暖季的1.1~1.7倍；用最大频率法估算各站本底ρ（BC），UR站点最高，BA站点最低，分别为0.56 μg·m-3和0.19 μg·m-3；交通排放导致路边站点本底ρ（BC）、平均ρ（BC）和ω（BC/PM2.5）均高于其他站点.ρ（BC）日变化曲线呈双峰型结构，非采暖季早高峰时段（07：00~08：00）峰值较高，采暖季全天浓度高于非采暖季且凌晨时段（00：00~02：00）峰值较高，谷值均在午后（14：00~16：00）出现.4个站点的平均吸收埃斯特朗指数（AAE）为1.38、1.34、1.26和1.26，表明全市BC主要来自化石燃料燃烧；采暖季平均AAE为1.46，高于非采暖季的1.23，主要是由于采暖季生物质燃烧排放占比增加；非采暖季各站点AAE日变化曲线主要受机动车活动时间影响，一致呈凌晨低、午后高的分布特点，采暖季曲线各异.BC与PM2.5、CO、NOx、风速和相对湿度的Pearson相关系数（r）为0.86、0.81、0.69、-0.37和0.34；由于燃煤源作为4种污染物的共同来源贡献增加，采暖季较非采暖季|r|更高.4个站点的ΔBC/ΔCO值分别为3.1×10-3、3.5×10-3、3.9×10-3和4.1×10-3.一次污染过程中，城区站点BC以区域传输为主要来源，路边站点局地排放BC积累过程较明显，易发生颗粒物二次生成过程. |
| 英文摘要 |
| Black carbon (BC), PM2.5, CO, NOx, and meteorological factors were observed throughout 2019 at four different sites. The spatial and temporal characteristics of BC were analyzed along with the main influencing factors. The main results were as follows:the average ρ(BC) were (1.58±1.15), (2.27±1.67), (3.35±2.13), and (3.57±2.40) μg·m-3 at the background area (BA), urban area (UA), urban roadside (UR), and highway roadside (HR), respectively. BC accounted for (5.3±1.6)%, (6.0±2.3)%, (9.0±3.6)%, and (8.1±3.5)% of PM2.5 at the four sites. The ρ(BC), ρ(PM2.5), ρ(CO), and φ(NOx) at the four sites ranked in the order of BAρ(CO) at UR was higher than that at HR. Pollutants during the heating season were 1.1-1.7 times higher than those in the non-heating season. The background ρ(BC) were estimated using the maximum frequency method, with the maximum value (0.56 μg·m-3) and minimum value (0.19 μg·m-3) being at UR and BA, respectively. The background ρ(BC), the average ρ(BC), and the proportion of BC in PM2.5 at UR and HR were higher than those at UA and BA, as a result of traffic emissions. The ρ(BC) showed bimodal diurnal variations, and the heating season curve was higher than the non-heating season curve throughout the day. Further, the morning peak (07:00-08:00) was higher in the non-heating season, and the midnight peak (00:00-02:00) was higher during the heating season, with the minimum always occurring in the afternoon (14:00-16:00). The absorption Angstrom exponents (AAE) were 1.38, 1.34, 1.26, and 1.26 at the four sites (BA, UA, UR, and HR, respectively). It was concluded that BC was dominated by fossil fuel emissions in the entire city. AAE in the heating season (1.46) was higher than that in the non-heating season (1.23) as a result of the high proportion of biomass combustion. The diurnal variation trend of the AAE at the four sites showed the similar trend during the non-heating season of high values in the afternoon and low values in the early morning, indicating that low AAE was caused by vehicle activity. The Pearson correlation coefficients (r) between BC and PM2.5, CO, NOx, wind speed, and relative humidity were 0.86, 0.81, 0.69, -0.37, and 0.34, respectively. The |r| was higher during the heating season because coal combustion contributed more as the common source of these pollutants. The ΔBC/ΔCO ratio at the four sites (BA, UA, UR, and HR) were 3.1×10-3, 3.5×10-3, 3.9×10-3, and 4.1×10-3, respectively. In a pollution episode, the increase in ρ(BC) at UA was mainly caused by regional transmission, whereas the accumulation process of BC at UR was obvious. The secondary generation process of particulate matter might occur due to the high concentration of precursors at UR. |
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