南京市臭氧、VOCs和PANs污染特征及变化趋势

对2013—2016年基于国家环境空气质量监测站以及省建大气多参数站所获取的南京市O_3、NO_2、CO、VOCs、PANs观测结果进行综合评价,结果表明:2016年南京市O_3第90百分位日最大8 h平均质量浓度比2013年上升33.3%,超标天数中O_3引起的超标占比增至32.0%。南京市区大气中非甲烷总烃冬季浓度高于夏季,含氧挥发性有机物则与之相反;在5—9月,含氧挥发性有机物组分在日变化过程中出现峰值的时间先后顺序依次为醚、醛、酮类,且O_3和过氧乙酰硝酸酯(PANs)生成存在有一定的线性关系。VOCs/NOx比值表明南京市处于VOCs控制区,因此对NO_2浓度下降不敏感,植物源挥发性有机物连续3年上升,夏季大气光化学反应活性未显著下降,这些现象是城市O_3浓度维持在较高水平的重要因素。     

Case studies on summertime measurements of O3, NO2, and SO2 with a DOAS system in an urban semi-industrial region in Athens, Greece

The objective of this study is to analyze the concentrations of SO₂, NO₂, and O₃ measured by a Differential Optical Absorption Spectroscopy (DOAS) system that was operating at the campus of Technological Education Institute of Piraeus during 2008 and 2009 warm periods (July to September) in relation to the prevailing meteorological conditions. The DOAS system was operating in a particularly polluted area of the West part of Attica basin on a continuous basis, measuring the concentration levels of the main pollutants (O₃, NO₂, and SO₂) as well as aromatic hydrocarbon substances (benzene, toluene, and xylene). According to the analysis, the SO₂ concentration levels at this measuring site are rather high and this may be attributed to the characteristics of this measuring site. Proximity of roadways and local circulation are just some of the factors that can affect the concentration levels of monitoring of pollutant concentrations such as NO₂ and surface ozone. The results provide evidence for the occurrence of an atmospheric phenomenon that produces higher ozone concentrations during weekends despite lower concentrations of ozone precursors. This phenomenon is known as the weekend effect.     

在线分析宁波市北仑区VOCs组成、趋势及来源

利用VOCs在线监测技术,对2010年宁波市北仑区空气内的VOCs的浓度、组成、变化规律及来源进行分析研究。结果表明,在北仑区域内的16种VOCs中,苯、甲苯、二甲苯、乙苯和己烷的比例占到了总数的82．9％,且该5种有机物浓度存在较为典型的季节性变化规律和日变化规律;采用CMD模型法对VOCs的来源进行解析后发现,北仑区域内的VOCs主要来源于汽车尾气、汽油蒸气和石油液化气,而且汽车尾气的贡献值要比一些大城市低得多,且夏季和冬季的成分源贡献率存在明显差异。     

Study on concentration of ambient NH 3 and interactions with some other ambient trace gases

We present diurnal variation of ambient ammonia (NH₃) in relation with other trace gases (O₃, CO, NO, NO₂, and SO₂) and meteorological parameters at an urban site of Delhi during winter period. For the first time, ambient ammonia (NH₃) was monitored very precisely and continuously using ammonia analyzer, which operates on chemiluminescence method. NH₃ estimation efficiency of the chemiluminescence method (>90%) is much higher than the conventional chemical trapping method (reproducibility 4.5%). Ambient NH₃ concentration reaches its maxima (46.17 ppb) at night and minimum during midday. Result reveals that the ambient ammonia (NH₃) concentration is positively correlated with ambient NO (r ²?=?0.79) and NO₂ (r ²?=?0.91) mixing ratio and negatively correlated with ambient temperature (r ²?=???0.32). Wind direction and wind speed indicates that the nearby (~500 m NW) agricultural fields may be major source of ambient NH₃ at the observational site.     

An Analysis of Secondary Pollutants in Buenos Aires City

Air pollutant concentrations from a monitoring campaign in Buenos Aires City, Argentina, are used to investigate the relationships between ambient levels of ozone (O₃), nitric oxide (NO) and nitrogen dioxide (NO₂) as a function of NO _x (=NO + NO₂). This campaign undertaken by the electricity sector was aimed at elucidating the apportionment of thermal power plants to air quality deterioration. Concentrations of carbon monoxide (CO) and sulphur dioxide (SO₂) were also registered. Photo stationary state (PSS) of the NO, NO₂, O₃ and peroxy radicals species has been analysed. The ‘oxidant’ level concept has been introduced, OX (=O₃ + NO₂), which varies with the level of NO _x . It is shown that this level is made up of NO _x -independent and NO _x -dependent contributions. The former is a regional contribution that equates the background O₃ level, whereas the latter is a local contribution that correlates with the level of primary pollution. Furthermore, the anticorrelation between NO₂ and O₃ levels, which is a characteristic of the atmospheric photo stationary cycle has been verified.The analysis of the concentration of the primary pollutants CO and NO strongly suggests that the vehicle traffic is the principal source of them. Levels of continuous measurements of SO₂ for Buenos Aires City are reported in this work as a complement of previously published results.     

2022年春季南京臭氧污染特征及成因分析

2022年春季,受新一轮新冠疫情影响,长三角各城市采取了一系列管控措施,使得大气污染物排放水平降低。对2022年春季(3—5月)南京及长三角地区的六项污染物尤其是臭氧(O₃)的变化特征进行了分析,从气象因素和O₃前体物方面,同时利用基于观测的模型(OBM)对南京O₃污染变化原因进行了研究,并分析了南京挥发性有机物(VOCs)的关键活性组分和来源。结果表明:2022年春季,南京PM_2.5、PM₁₀、NO₂和CO均值浓度均同比下降,但O₃日最大8 h滑动平均质量浓度(O₃-8 h)同比上升19.8%,O₃-8 h超标时间同比增加9 d;长三角区域O₃-8 h同比上升17.9%,O₃-8 h超标天数为2021年同期的2.5倍。南京O₃浓度上升的原因:一方面是由于不利的气象条件,另一方面是由于南京O₃生成处于VOCs控制区,但氮氧化物(NO_x)降幅大于VOCs降幅,同时结合O₃前体物削减方案的分析结果发现,VOCs和NO_x不当的削减比例会导致O₃浓度不降反升。南京O₃生成的关键VOC活性物种依次为乙醛、丙烯、间/对二甲苯、丙烯醛和乙烯;正定矩阵因子分解(PMF)解析结果显示,机动车尾气是南京城区VOCs的主要来源,其次为液化石油气/天然气使用和石油化工。     

Analysis of volatile organic compounds released during food decaying processes

A number of volatile organic compounds (VOCs) including acetone, methyl ethyl ketone, toluene, ethylbenzene, m,p-xylene, styrene, and o- xylene released during food decaying processes were measured from three types of decaying food samples (Kimchi (KC), fresh fish (FF), and salted fish (SF)). To begin with, all the food samples were contained in a 100-mL throwaway syringe. These samples were then analyzed sequentially for up to a 14-day period. The patterns of VOC release contrasted sharply between two types of fish (FF and SF) and KC samples. A comparison of data in terms of total VOC showed that the mean values for the two fish types were in the similar magnitude with 280 ± 579 (FF) and 504 ± 1,089 ppmC (SF), while that for KC was much lower with 16.4 ± 7.6 ppmC. There were strong variations in VOC emission patterns during the food decaying processes between fishes and KC that are characterized most sensitively by such component as styrene. The overall results of this study indicate that concentration levels of the VOCs differed significantly between the food types and with the extent of decaying levels through time.     

工业园区和城区VOCs组成及化学活性的空间差异对清远大气臭氧污染分布的影响

工业化与城镇化交替演进使珠三角及其周边地区土地利用类型较为复杂。快速的城市化进程使城市建成区与大量村镇工业园区互相交错。这种变化势必会增加挥发性有机物(VOCs)在组分构成和空间分布上的复杂性,并对臭氧(O₃)污染的时空变化产生影响。为厘清这种排放的空间异质性特征及其对O₃污染分布的影响,分别选取可以代表清远市典型工业园区和城市建成区的站点开展观测研究。结果表明:工业园区和城市建成区VOCs浓度水平和污染特征有较大的空间差异,其中代表村镇工业园区的龙塘站VOCs日均浓度为30.42×10^-9,高于代表城市建成区的技师学院站(17.32×10^-9)。龙塘站二甲苯和甲苯的臭氧生成潜势(OFP)比技师学院站高57.6×10^-9,且该值相当于技师学院站排名前10位物种OFP的总和。气象分析表明:2个站点之间并非彼此的上、下风向,而是共同受到局地气团的影响。源解析结果表明:源排放是造成这种空间异质性的内因,其中交通源对技师学院的贡献更高,而工业相关排放源对龙塘的贡献更高。该研究进一步比较了周边站点O₃时间序列的一致性,并模拟2个站点的O₃生成速率。研究发现O₃在局地范围内变化较小,高VOCs排放的地点对局地O₃有较高的贡献,局地内不同地点的O₃生成过程也存在较大差异。据此,笔者提出O₃污染防控建议:短期内可通过技术手段和观测数据发现O₃污染的重要贡献点,并进行针对性的"散乱污"清理整治和涉VOCs行业综合整治,长期看应科学合理规划城市发展布局和产业布局,预留城市通风廊道,以有效减少O₃污染。     

中原城市群臭氧浓度分布特征及来源

利用2015年臭氧(O_3)自动监测数据和源排放清单,分析了中原城市群O_3浓度的空间、时间分布情况,探讨了中原城市群中城市间O_3的相关性,以及O_3浓度、NOx、VOCs、CO及汽车保有量间的相关性。指出中原城市群是全国更是河南O_3污染的严重地区,O_3浓度年内月度变化呈倒"V"型分布,具有明显的北部城市特征;中原城市群9个城市间除开封外其他8个城市间都呈高度正相关性,相关系数均为0.892~0.991;9个城市机动车保有量及NOx、VOCs和CO等前体物的年排放量与其年均O_3浓度之间存在正相关性。分析认为,NOx、VOCs和CO等前体物的排放是中原城市群O_3浓度偏高的主要影响因素,同时O_3浓度也与日照时间、降雨量、植物源VOCs排放量及相邻城市间污染物的空间输送等因素有着密切的关系。     

典型化工园区大气中挥发性有机物污染调查

对常州市某典型化工园区大气中挥发性有机物(VOCs)污染状况进行了调查。结果表明,该化工园区大气中检出挥发性有机物共有58种,组分有芳香烃、饱和烷烃、卤代烃、烯烃、醛酯类化合物及其他类;苯、甲苯、乙苯、二甲苯为主要挥发性有机污染物,质量浓度为1.0~194μg/m~3;均未超出参考标准的限值。背景点位和园区点位大气中主要ρ总(VOCs)在秋冬季最高,敏感点大气VOCs随季节变化也较为明显;园区T1和T2ρ总(VOCs)年均值高于敏感点位,背景点位年均值最低;园区点位除了汽车尾气排放之外,溶剂的挥发和生产工艺中污染物的排放也增加了大气中苯系物的浓度,同时也对敏感点位和对照点位的大气质量产生了一定的影响。     

A Wavelet-based Neural Network Model to Predict Ambient Air Pollutants’ Concentration

The present paper proposes a wavelet based recurrent neural network model to forecast one step ahead hourly, daily mean and daily maximum concentrations of ambient CO, NO₂, NO, O₃, SO₂ and PM_2.5 — the most prevalent air pollutants in urban atmosphere. The time series of each air pollutant has been decomposed into different time-scale components using maximum overlap wavelet transform (MODWT). These time-scale components were made to pass through Elman network. The number of nodes in the network was decided on the basis of the strength (power) of the corresponding input signals. The wavelet network model was then used to obtain one-step ahead forecasts for a period extending from January 2009 to June 2010. The model results for out of sample forecast are reasonably good in terms of model performance parameters such as mean absolute error (MAE), mean absolute percentage error (MAPE), root mean square error (RMSE), normalized mean absolute error (NMSE), index of agreement (IOA) and standard average error (SAE). The MAPE values for daily maximum concentrations of CO, NO₂, NO, O₃, SO₂ and PM2.5 were found to be 9.5%, 17.37%, 21.20%, 13.79%, 17.77% and 11.94%, respectively, at ITO, Delhi, India. Bearing in mind that the forecasts are for daily maximum concentrations tested over a long validation period, the forecast performance of the model may be considered as reasonably good. The model results demonstrate that a judicious selection of wavelet network design may be employed successfully for air quality forecasting.     

Relationship between environmental exposure to toluene,xylene and ethylbenzene and the expired breath concentrations for gasoline service workers

This study evaluated the relationship between the breath concentrations of, and personal exposure to, toluene, xylene and ethylbenzene of thirty workers from ten gasoline stations. Personal exposure air samples and workplace samples were collected simultaneously. Each subject provided a sample of exhaled breath after his or her personal exposure air was sampled. Twenty-five personal air, 17 workplace and 30 breath samples were collected in this study. Results indicated that breath concentrations of toluene and xylene were significantly correlated with personal monitoring concentrations. Furthermore, multiple regression analysis showed that exhaled toluene levels were highly influenced by personal toluene concentrations and the amount of personal gasoline sold (r2 = 0.762), while exhaled xylene levels depended on wind speed and personal xylene exposure concentrations (r2 = 0.665). Exhaled ethylbenzene levels were too low to present a relationship between concentrations and personal exposure levels. The exhaled toluene, xylene and ethylbenzene concentrations ranged from 4.3 to 41.8, 0.9 to 13.9, and 0.2 to 6.5 ppb, and the corresponding personal monitoring concentrations ranged from 60.3 to 572.3, 16.4 to 156.6, and 10.7 to 136.6, respectively. The average number of symptoms per person, according to neurotoxic questionnaire 16 (abbreviated as Q16) was 4.1 and six workers showed over six symptoms in Q16. This study suggests that exhaled toluene and xylene levels are suitable for use as biological exposure indices even at the ppb-level of exposure. Gasoline service workers are exposed to high levels of volatile organic compounds (VOCs) and the potential threats to their neurological systems deserve further investigation.     

Temporal evolution of the main processes that control indoor pollution in an office microenvironment: a case study

The aim of this study is to examine the relative contribution of the outdoor concentration, the ventilation rate, the geometric characteristics of the indoor environment (i.e., extent of indoor surfaces and indoor volume), the deposition, and chemical reactions to the indoor air quality of the office microenvironment. For this case study, the NO, NO₂, and O₃ concentrations indoors and outdoors and TVOCs and CO₂ concentrations indoors were measured in an office microenvironment in Athens, Greece, that was ventilated both naturally and mechanically. The calculated ventilation and loss rates and the measured outdoor concentrations of NO, NO₂, and O₃ were set as input to Multi-chamber Indoor Air Quality Model in order to study the temporal variation of the indoor NO, NO₂, and O₃ concentrations. Results showed that when the ventilation rate and outdoor concentration are high, the relative contribution of the transport process contributes significantly, while the chemical process depends on the contemporary interplay between the indoor O₃, NO, and NO₂ concentrations and lighting levels. The significance of each process was further examined by performing sensitivity tests, and it was found that the most important parameters were the deposition velocities, the UV infiltration rates (which determines the indoor chemical reaction rates), the ventilation rates, and the filtration (when a mechanical ventilation system is used). The effect of the hydrocarbon chemistry was not significant.     

大连市夏季近地面臭氧污染数值模拟和控制对策研究

通过区域空气质量模型CAMx对大连市2015年8月近地面臭氧(O_3)污染进行模拟,探讨了O_3及其生成前体物(NOx和VOCs)的来源,O_3生成控制区,并根据敏感性分析结果对前体物排放的控制效果进行了定量评估。结果表明:本地NOx排放对大连地区的NOx浓度贡献占90%以上,本地VOCs排放对大连地区的VOCs浓度贡献占80%以上,而本地NOx和VOCs排放对大连地区O_3浓度贡献仅占29%;大连市整体上为VOCs控制区,控制VOCs能有效降低O_3污染,还能有效削减O_3的峰值浓度;通过敏感性分析结果计算得出,削减大连本地工业源VOCs和民用源VOCs能够有效降低大连地区O_3浓度,削减10%的工业源VOCs能使市区O_3平均浓度降低2%左右,削减10%的民用源VOCs能使大连市区平均O_3浓度降低1%左右。建议NOx与VOCs削减比例为1∶2,对大连市O_3和PM2.5污染进行协同控制。     

Study of urban atmospheric pollution in Navarre (Northern Spain)

An ambient air quality study was undertaken in two cities (Pamplona and Alsasua) of the Province of Navarre in northern Spain from July 2001 to June 2004. The data were obtained from two urban monitoring sites. At both monitoring sites, ambient levels of ozone, NO_x, and SO₂ were measured. Simultaneously with levels of PM₁₀ measured at Alsasua (using a laser particle counter), PM₁₀ levels were also determined at Pamplona (using a beta attenuation monitor). Mean annual PM₁₀ concentrations in Pamplona and Alsasua reached 30 and 28 μg m⁻³, respectively. These concentrations are typical for urban background sites in Northern Spain. By using meteorological information and back trajectories, it was found that the number of exceedances of the daily PM₁₀ limit as well as the PM₁₀ temporal variation was highly influenced by air masses from North Africa. Although North African transport was observed on only 9% of the days, it contributed the highest observed PM₁₀ levels. Transport from the Atlantic Ocean was observed on 68% of the days; transport from Europe on 13%; low transport and local influences on 7%; and transport from the Mediterranean region on 3% of the days. The mean O₃ concentrations were 45 and 55 μg m⁻³ in Pamplona and Alsasua, respectively, which were above the values reported for the main Spanish cities. The mean NO and NO₂ levels were very similar in both sites (12 and 26 μg m⁻³, respectively). Mean SO₂ levels were 8 μg m⁻³ in Pamplona and 5 μg m⁻³ in Alsasua. Hourly levels of PM₁₀, NO and NO₂ showed similar variations with the typically two coincident maximums during traffic rush hours demonstrating a major anthropogenic origin of PM₁₀, in spite of the sporadic dust outbreaks.     

杭州市大气污染物排放清单及特征

以杭州市区为研究区域,通过调查整合多套污染源数据库及其他统计资料,研究文献报道及模型计算的各种污染源排放因子,获得杭州市区各行业PM10、PM2.5、SO2、NOx、CO、VOCs、NH3等污染物的排放量,建立了杭州市区2010年1 km×1 km大气污染物排放清单。结果表明,2010年杭州市区PM10、PM2.5、SO2、NOx、CO、VOCs和NH3的排放总量分别为7.96×104、4.02×104、7.23×104、8.98×104、73.90×104、39.56×104、3.32×104t。从排放源的行业分布来看,机动车尾气排放是杭州市区大气污染物最重要排放源之一,对PM10、PM2.5、NOx、CO和VOCs的贡献分别达到14.4%、27.1%、40.3%、21.4%、31.1%。道路扬尘、电厂锅炉、工业炉窑、植被、畜禽养殖对不同污染物分别有着重要贡献,道路扬尘对PM10和PM2.5的贡献分别为44.6%和20.0%、电厂锅炉对SO2和NOx的贡献分别为37.0%和25.7%、工业炉窑对CO的贡献为41.5%、植被排放对VOCs的贡献为27.1%、畜禽养殖对NH3的贡献为76.5%。从空间分布来看,萧山区和余杭区对SO2、NH3和植被排放BVOC的贡献要显著高于主城区;而主城区机动车对PM2.5、NOx和VOCs的贡献分别达到36.3%、56.0%和47.4%,较市区范围内显著增加,表明机动车尾气排放已成为杭州主城区大气污染最重要的来源之一。     

Monitoring of Criteria Air Pollutants in Bursa, Turkey

The concentrations of criteria air pollutants such as CO, NO_x (NO + NO₂), SO₂ and PM were measured in the period of May 2001 and April 2003 in the city of Bursa, Turkey. The average concentrations for this period were 1115±1600 μg/m³, 29±50 μg/m³, 51±24 μg/m³, 79±65 μg/m³, 40±35 μg/m³, 98±220 μg/m³, for CO, NO, NO₂, NO_x, SO₂ and PM, respectively. Temporal changes in concentrations were analyzed using meteorological factors. Correlations among pollutant concentrations and meteorological parameters showed weak relations nearly in all data. Lower concentrations were observed in the summer months while higher concentrations were measured in the winter months. The increase in winter concentrations was probably due to residential heating. Pollutants were associated with each other in order to have information about their origin. NO_x/SO₂ ratio was also examined to bring out the source origin contributing on air pollution (i.e., traffic or stationary).     

Growth impact of O3, NO2 and/or SO2 on pinus taeda

Seedlings of two full-sib families of loblolly pine expressing different degrees of sensitivity to O₃ were exposed to 0.05 ppm O₃, 0.10 ppm NO₂, and/or 0.14 ppm SO₂ for 6 hr/day for 28 consecutive days. The treatments were O₃, NO₂, SO₂ (each used alone), O₃+SO₂, O₃+NO₂, and O₃+NO₂+SO₂. Significant growth suppressions were noted with the relatively sensitive family in all but the the NO₂ alone treatments. The O₃+SO₂ treatment had a more significant effect than O₃ alone, but adding NO₂ had an inconsistent effect. Significant growth suppressions were noted for the relatively non-sensitive family only in the O₃+SO₂ and O₃+SO₂+NO₂ combination treatments. Adding NO₂ to O₃+SO₂ had a slightly stimulatory effect. The relatively sensitive pine family suffered a 30% height growth suppression versus a 14% height growth suppression for the relatively insensitive family when exposed to the 3 pollutant combination. Symptoms were noted on less than 4% of the foliage in the most severe treatments. The pollutant concentrations used in this study were below the National Ambient Air Quality Standards (NAAQS) for each pollutant.     

Spatial Analysis of Volatile Organic Compounds from a Community-Based Air Toxics Monitoring Network in Deer Park,Texas, USA

In the summer of 2003, ambient air concentrations of volatile organic compounds (VOCs) were measured at 12 sites within a 3-km radius in Deer Park, Texas near Houston. The purpose of the study was to assess local spatial influence of traffic and other urban sources and was part of a larger investigation of VOC spatial and temporal heterogeneity influences in selected areas of Houston. Seventy 2-h samples were collected using passive organic vapor monitors. Most measurements of 13 VOC species were greater than the method detection limits. Samplers were located at 10 residential sites, a regulatory air monitoring station, and a site located at the centroid of the census tract in which the regulatory station was located. For residential sites, sampler placement locations (e. g., covered porch vs. house eaves) had no effect on concentration with the exception of methyl tertiary-butyl ether (MTBE). Relatively high correlations (Pearson r > 0.8) were found between toluene, ethylbenzene, and o,m,p-xylenes suggesting petroleum-related influence. Chloroform was not correlated with these species or benzene (Pearson r < 0.35) suggesting a different source influence, possibly from process-related activities. As shown in other spatial studies, wind direction relative to source location had an effect on VOC concentrations.