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.     

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。     

2001—2020年合肥市空气质量变化趋势研究

为系统分析合肥市长时间序列空气质量变化特征,对合肥市2001—2020年SO₂、NO₂和PM₁₀,以及2013—2020年CO、O₃和PM_2.5的浓度特征开展研究。采用Mann-Kendall(M-K)时间趋势检验法分析了6项污染物的时间变化规律,同时考虑了人为活动对污染物小时浓度的影响。结果表明,PM_2.5和O₃是目前影响合肥市空气质量的首要污染物。2014年以来,合肥市PM₁₀、PM_2.5、CO和SO₂年均浓度均呈逐年下降趋势,但NO₂和O₃污染有加剧趋势。合肥市SO₂和颗粒物浓度表现为冬春季节高、夏秋季节低;O₃浓度变化趋势与之相反;NO₂和CO浓度呈秋冬季节高、春夏季节低。     

Emissions of SO2, NO x and particulates from a pipe manufacturing plant and prediction of impact on air quality

Integrated pipe manufacturing industry is operation intensive and has significant air pollution potential especially when it is equipped with a captive power production facility. Emissions of SO₂, NO _x , and particulate matter (PM) were estimated from the stationary sources in a state-of-the-art pipe manufacturing plant in India. Major air polluting units like blast furnace, ductile iron spun pipe facility, and captive power production facility were selected for stack gas monitoring. Subsequently, ambient air quality modeling was undertaken to predict ground-level concentrations of the selected air pollutants using Industrial Source Complex (ISC 3) model. Emissions of SO₂, NO _x , and particulate matter from the stationary sources in selected facilities ranged from 0.02 to 16.5, 0.03 to 93.3, and 0.09 to 48.3 kg h^???1, respectively. Concentration of SO₂ and NO _x in stack gas of 1,180-kVA (1 KW = 1.25 kVA) diesel generator exceeded the upper safe limits prescribed by the State Pollution Control Board, while concentrations of the same from all other units were within the prescribed limits. Particulate emission was highest from the barrel grinding operation, where grinding of the manufactured pipes is undertaken for giving the final shape. Particulate emission was also high from dedusting operation where coal dust is handled. Air quality modeling indicated that maximum possible ground-level concentration of PM, SO₂, and NO _x were to the tune of 13, 3, and 18 μg/m³, respectively, which are within the prescribed limits for ambient air given by the Central Pollution Control Board.     

Model Assessment of Air-Pollution in Prague

Results of relatively simple gaussian dispersion model are presented. This model, developed in the beginning of this decade, is suitable mainly for determination of spatial distributions of annual mean concentrations of such kinds of air-pollution as sulphur dioxide (SO₂), mixture of nitrogen oxides (NO_x) or suspended particulate matter (SPM) from all types of emission sources located within the city - point sources, line sources and area sources. Model has been used in years 1994, 1996 and 1998 to assess the air-pollution distributions of the above mentioned kinds in the Prague area and the development of the air quality state. It contributed to the decision making process when possible impact of some changes in traffic system or in system of domestic heating, for example, has been investigated. In this contribution, behaviour of sulphur dioxide (SO₂) and mixture of nitrogen oxides (NO_x) ground concentration distributions are analyzed with respect to changing emission situation in Prague in recent years. Results show that SO₂ ground concentration level decreases mainly due to changes in local heating methods and type of fuel used. Different trend can be seen in NO_x ground concentrations thanks to rapid increase in the traffic density.     

Spatial and temporal variation of surface ozone,NO and NO2 at urban,suburban, rural and industrial sites in the southwest of the Iberian Peninsula

Surface ozone is one of the most important photochemical pollutants in the low atmosphere, causing damage to human health, vegetation, materials and climate. The weather (high temperatures and high solar radiation), orography (presence of the Guadalquivir valley) and anthropogenic (the cities of Cádiz, Córdoba, Huelva and Seville and two important industrial complexes) characteristics of the southwestern Iberian Peninsula make this region ideal for the formation and accumulation of ozone. To increase the knowledge of ozone behaviour in this area, the monthly, daily and weekly variations of ozone and its precursors, nitrogen oxides (NO_x?=?NO?+?NO₂), were analysed over a 4-year period (2003 to 2006). Using the k-means cluster technique, 12 representative stations of five different areas with different ozone behaviour were selected from a total of 29 monitoring sites. This is the first time that the analysis of these atmospheric pollutants has been carried out for the whole area, allowing therefore a complete understanding of the dynamics and the relationships of these compounds in this region. The results showed an opposite behaviour among ozone and NO and NO₂ concentrations in urban and suburban zones, marked by maximums of ozone (minimums NO_x) in spring and summer and minimums (maximums) in autumn and winter. A seasonal behaviour, with lower amplitude, was also observed in rural and industrial areas for ozone concentrations, with the NO and NO₂ concentrations remaining at low and similar values during the year in rural zones due to the absence of emission sources in their surroundings. The daily cycles of ozone in urban, suburban and industrial sites registered a maximum value in the early afternoon (14:00–17:00 UTC) while for NO_x two peaks were observed, at 7:00–10:00 UTC and 20:00–22:00. In the case of rural stations, no hourly peak of ozone or NO_x was registered. The weekend effect was studied by using a statistical contrast tests (Student’s t). The results indicated that only areas influenced by important traffic emissions presented a weekend effect for NO and NO₂, whereas an ozone weekend effect was not detected in any case.     

临汾市大气污染物的时间分布特征与源区分析

多年来，临汾市多次名列我国生态环境部公布的空气质量最差的重点城市之列，对其大气污染的时间分布特征和潜在源区进行分析对其环境管理与污染防治具有重要意义。利用2015—2019年临汾市5个国控空气环境质量监测站点的6种空气污染物(SO₂、NO₂、CO、O₃、PM_2.5和PM₁₀)浓度数据和气象观测数据，使用HYSPLIT模型研究了该市空气污染物的时间变化特征、轨迹输送特征和可能的来源。结果表明，PM_2.5和PM₁₀的年均浓度均超过了《环境空气质量标准》(GB 3095—2012)Ⅱ级标准，SO₂仅在2016—2017年超过该标准，其余3种污染物的年均浓度均低于该标准。6种污染物2015—2019年的月均浓度的变化特征表现为O₃浓度呈以6、7月为中心的近似正态分布，SO₂、NO₂和CO以及PM_2.5和PM₁₀浓...     

Influence of Meteorological Factors NO2, SO2, CO and PM10 on the Concentration of O3 in the Urban Atmosphere of Eastern Croatia

Ozone, NO₂, SO₂, CO, PM₁₀ and meteorological parameters were measured simultaneously during the summer?Cautumn season 2007 in Osijek??the eastern, flat, agricultural part of Croatia. Fourier analysis confirms the existence of variation in ozone volume fractions with periods ranging from the usual semi-daily and daily to 7 and 28 daily cycles. The relationships between O₃ and other variables were modelled in three ways: principal component analysis, multiple linear regression and principal component regression. The results of the principal component analysis detected underlying relationships among ozone concentrations and meteorological variables. An extremely simple meteorological model is suitable for the prediction of ozone levels. The meteorological factors, temperature and cloudiness played a main role in the MLR model (R ²?=?0.83). The application of the principal component regression approach confirmed that the original variables associated with the valid principal components were meteorological variables (R ²?=?0.82).     

2001年～2008年及奥运会期间天津市大气污染特征分析

根据天津市大气质量监测数据,对2001年～2008年及奥运会期间天津市大气污染特征和主要大气污染物的变化规律进行了分析。结果表明,2001年～2008年天津市的PM10、SO2和NO2污染总体呈下降趋势,但质量浓度仍相对较高。2008年8月奥运会期间天津市PM10和SO2质量浓度达到国家空气质量二级标准,NO2质量浓度达到国家空气质量一级标准,空气质量良好。天津市PM10污染相对稳定,SO2和NO2的污染分布呈现明显的季节性,时间上表现为冬强夏弱。气象条件对污染物浓度影响明显,沙尘、大雾等天气可使污染物浓度急剧升高。     

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).