Vertical distributions of COS and CS2 in Beijing City

Vertical distributions of COS and CS2 were measured at a meteorological tower in Beijing City. The mixing ratios of COS and CS2 are in the range of 371--1681 pptv and 246--1222 pptv, respectively. The significant high mixing ratios of the two compounds at ground level and distinct vertical distributions indicated the existence of strong anthropogenic sources of COS and CS2 in Beijing City. Domestic stoves and central heaters are important sources of COS during winter season. Cesspools may play significant role on COS over whole seasons. Chemical productions may be responsible for the observed hiah mixina ratios of CS2 in Beiiina Citv.     

北京上甸子区域大气本底站四氯化碳(CCl_4)在线观测

利用自组装GC-ECD系统在北京上甸子区域大气本底站开展大气四氯化碳(CCl4)摩尔分数在线观测.2007年4月～2008年3月期间,该站CCl4本底摩尔分数(89.4±0.7)×10-12,与北半球同纬度带Mace Head和Trinidad Head本底站观测结果基本一致;非本底摩尔分数(94.7±5.1)×10-12,出现频率63.6%,表明该站也能捕捉到高摩尔分数CCl4空气团输送信息;CCl4本底摩尔分数变化较小,且没有明显的季节变化;非本底摩尔分数呈现夏高冬低的特点,平均非本底摩尔分数最高月份(6月)比最低月份(1月)高7.6×10-12.应用CO比值相关法初步估算2007年4月～2008年3月我国CCl4排放量约4.7kt·a-1,与文献报道Bottom-up方法估算我国同期CCl4排放量接近;CO比值相关法估算CCl4排放量的不确定性主要来自同源假设及观测站代表性.     

Identification of long-range transport pathways and potential sources of PM2.5 and PM10 in Beijing from 2014 to 2015

Trajectory clustering, potential source contribution function (PSCF) and concentration-weighted trajectory (CWT) methods were applied to investigate the transport pathways and identify potential sources of PM_2.5 and PM₁₀ in different seasons from June 2014 to May 2015 in Beijing. The cluster analyses showed that Beijing was affected by trajectories from the south and southeast in summer and autumn. In winter and spring, Beijing was not only affected by the trajectories from the south and southeast, but was also affected by trajectories from the north and northwest. In addition, the analyses of the pressure profile of backward trajectories showed that backward trajectories, which have important influence on Beijing, were mainly distributed above 970 hPa in summer and autumn and below 950 hPa in spring and winter. This indicates that PM_2.5 and PM₁₀ were strongly affected by the near surface air masses in summer and autumn and by high altitude air masses in winter and spring. Results of PSCF and CWT analyses showed that the largest potential source areas were identified in spring, followed by winter and autumn, then summer. In addition, potential source regions of PM₁₀ were similar to those of PM_2.5. There were a clear seasonal and spatial variation of the potential source areas of Beijing and the airflow in the horizontal and vertical directions. Therefore, more effective regional emission reduction measures in Beijing''s surrounding provinces should be implemented to reduce emissions of regional sources in different seasons.     

Vertical profiles of biogenic volatile organic compounds as observed online at a tower in Beijing

Vertical profiles of isoprene and monoterpenes were measured by a proton transfer reaction-time of flight-mass spectrometry (PTR-ToF-MS) at heights of 3, 15, 32, 64, and 102 m above the ground on the Institute of Atmospheric Physics (IAP) tower in central Beijing during the winter of 2016 and the summer of 2017. Isoprene mixing ratios were larger in summer due to much stronger local emissions whereas monoterpenes were lower in summer due largely to their consumption by much higher levels of ozone. Isoprene mixing ratios were the highest at the 32 m in summer (1.64 ± 0.66 ppbV) and at 15 m in winter (1.41 ± 0.64 ppbV) with decreasing concentrations to the ground and to the 102 m, indicating emission from the tree canopy of the surrounding parks. Monoterpene mixing ratios were the highest at the 3 m height in both the winter (0.71 ± 0.42 ppbV) and summer (0.16 ± 0.10 ppbV) with a gradual decreasing trend to 102 m, indicting an emission from near the ground level. The lowest isoprene and monoterpene mixing ratios all occurred at 102 m, which were 0.71 ± 0.42 ppbV (winter) and 1.35 ± 0.51 ppbV (summer) for isoprene, and 0.42 ± 0.22 ppbV (winter) and 0.07 ± 0.06 ppbV (summer) for monoterpenes. Isoprene in the summer and monoterpenes in the winter, as observed at the five heights, showed significant mutual correlations. In the winter monoterpenes were positively correlated with combustion tracers CO and acetonitrile at 3 m, suggesting possible anthropogenic sources.     

南京北郊大气VOCs变化特征及来源解析

利用2011-03-01~2012-02-29南京北郊大气VOCs观测资料,对大气VOCs浓度变化特征和特征物比值差异展开研究,并应用PCA/APCS受体模型对不同季节VOCs来源进行了解析.结果表明,南京大气总VOCs体积混合比为43.52×10-9,其中烷烃占45.1%、烯烃占25.3%、炔烃占7.3%和芳香烃占22.3%.总VOCs体积混合比呈现夏季高,冬季低的季节变化.VOCs组分中烷烃在冬季最高,烯烃夏季最高,芳香烃春季最高,炔烃冬季最高.特征物比值(VOCs/乙炔)和T/B比值反映出观测点受周边工业区影响较大.VOCs源解析表明,主要来源来自工厂生产、机动车排放、燃料燃烧、生产活动挥发、溶剂使用和自然源.虽然有季节变化,但与工业生产活动相关的来源占大气VOCs 45%~63%,其次为机动车来源占34%~50%.     

江西景德镇站大气CH4和CO季节变化及源解析

基于江西景德镇温室气体站2017年12月~2018年11月筛分获得的CH₄及CO大气本底和污染浓度数据,对大气CH₄和CO浓度季节变化及其排放源特征进行研究,结果表明：大气CH₄和CO本底浓度季节变化特征与浙江临安本底站类似,即夏季低而冬季高,而夏季江西地区水稻田和湿地排放导致CH₄污染浓度显著抬升,相比本底浓度抬升幅度可达133.9×10^-9,冬季受西北部地区取暖排放的区域输送的影响,1月CO污染平均浓度较本底浓度抬升达227.2×10^-9.基于本底数据及污染数据,结合后向轨迹模型分析发现景德镇站大气CO潜在排放源主要分布在湖北东南部（四季）、安徽（秋冬季）、山东中部（秋季）、长江三角洲上海及杭州（夏秋季）、湖南东部和江西地区（冬季）等区域,其中冬季湖南东部和江西地区贡献率达53.7%,CH₄排放源主要集中在江西地区（夏季）、长江三角洲杭州、南京及安徽南部覆盖区域（夏季）、湖北东南部（夏秋季）以及安徽（秋季）、山东中部（秋季）等区域,夏季南京、杭州及安徽南部覆盖区域的CH₄排放对景德镇站CH₄浓度抬升的贡献率达到69.5%.大气CH₄及CO呈现较好的相关性,冬季其相关系数可达0.86,受CH₄和CO源汇季节变化影响,CH₄/CO排放比呈现冬季低值（0.31）、夏季高值（1.06）.     

Trend and seasonal variations of atmospheric CH4 in Beijing

The atmospheric CH4 in Beijing is still increasing, even though its increasing rate has significantly decreased from 1.76 ％/a during 1985-1989 to 0.50 ％/a during 1990-1997. The seasonal variation of CH4 concentration showed a double-peak pattern, one peak appearing in winter and the other in summer. It is evident that the annually seasonal variations of atmospheric CH4 in Beijing are different. From 1986 to 1997, the atmospheric CH4 increased by 185 ppbv, 37％ and 21％ of which were due to the increase in winter and in summer, respectively. After 1993, the annually seasonal increasing rate of CH4 concentration in summer (due to emission from biogenic sources) is negative while the increasing rate in winter (due to emission from non-biogenic sources) is positive about 25 ppbv/a. As a result, the increase of CH4 emission from non-biogenic sources in winter is the major reason that caused theannually seasonal increasing rate from 1993 to 1997. The biogenic sources in Beijing are shrinking while the non-biogenic ones (such as fossil fuel combustion) are enlarging.     

Trend and seasonal variations of atmospheric CH_4 in Beijing

ＩｎｔｒｏｄｕｃｔｉｏｎＭｅｔｈａｎｅ (ＣＨ4 )ｉｓａｎｉｍｐｏｒｔａｎｔｔｒａｃｅｏｒｇａｎｉｃ ｇａｓｗｉｔｈｔｈｅｈｉｇｈｅｓｔｃｏｎｃｅｎｔｒａｔｉｏｎｉｎｔｈｅａｔｍｏｓｐｈｅｒｅ.ＢｅｃａｕｓｅＣＨ4 ｈａｓｓｔｒｏｎｇａｂｉｌｉｔｙｔｏａｂｓｏｒｂｉｎｆｒａｒｅｄ ｒｅｄｌｉｇｈｔａｎｄｔｈｅｎｗａｒｍｔｈｅａｔｍｏｓｐｈｅｒｅ,ｉｔｓｇｒｅｅｎｈｏｕｓｅｅｆｆｅｃｔｓａｒｅｃｌｏｓｅｌｙｆｏｌｌｏｗｉｎｇｔｈｏｓｅｏｆｃａｒｂｏｎｄｉｏｘｉｄｅ (ＣＯ2 ) .Ｔｈｅｍａｉｎｂｉｏｇｅｎｉｃｓ…     

Gaseous emissions from compressed natural gas buses in urban road and highway tests in China

The natural gas vehicle market is rapidly developing throughout the world, and the majority of such vehicles operate on compressed natural gas(CNG). However, most studies on the emission characteristics of CNG vehicles rely on laboratory chassis dynamometer measurements, which do not accurately represent actual road driving conditions. To further investigate the emission characteristics of CNG vehicles, two CNG city buses and two CNG coaches were tested on public urban roads and highway sections. Our results show that when speeds of 0–10 km/hr were increased to 10–20 km/hr, the CO_2, CO, nitrogen oxide(NO_x), and total hydrocarbon(THC) emission factors decreased by(71.6 ± 4.3)%,(65.6 ± 9.5)%,(64.9 ± 9.2)% and(67.8 ± 0.3)%, respectively. In this study, The Beijing city buses with stricter emission standards(Euro Ⅳ) did not have lower emission factors than the Chongqing coaches with Euro Ⅱ emission standards. Both the higher emission factors at 0–10 km/hr speeds and the higher percentage of driving in the low-speed regime during the entire road cycle may have contributed to the higher CO_2 and CO emission factors of these city buses. Additionally, compared with the emission factors produced in the urban road tests, the CO emission factors of the CNG buses in highway tests decreased the most(by 83.2%), followed by the THC emission factors, which decreased by 67.1%.     

北京及周边地区大气羰基化合物的时空分布特征初探

利用2,4-二硝基苯肼（DNPH）/HPLC方法,于2010年6月24日、7月22日、8月24日、9月14日（夏季）和2011年1月13日（冬季）,在北京及周边地区38个采样点组织5次同步观测,测定了大气中23种羰基化合物的浓度水平.观测结果表明,北京市各类站点夏季和冬季的总羰基化合物体积分数分别为（16.38±6.03）×10-9,（8.50±5.27）×10-9;周边城市夏季和冬季的体积分数分别为（13.19±5.71）×10-9,（13.05±2.44）×10-9.区域大气中最主要的羰基化合物是甲醛、乙醛和丙酮,三者约占总羰基化合物浓度的78%～91%.夏季羰基化合物的浓度水平明显高于冬季,并且上午09：00～12：00时段的浓度高于下午13：00～16：00时段的浓度.在空间分布上,北京市夏季羰基化合物的高值区主要集中在交通密集的主城区,而冬季受西北风影响呈现由西北向东南递增的趋势.夏季,机动车尾气对大气羰基化合物有显著的一次和二次贡献,同时在不利的气象条件影响下,造成城市地区羰基化合物的污染现象.冬季,大气羰基化合物以一次排放为主,燃煤和机动车可能是主要的污染源.