Development of baseline (air quality) data in Pakistan

During 2003–2004, SUPARCO, the Pakistan Space and Upper Atmosphere Research Commission has conducted a year long baseline air quality study in country’s major urban areas (Karachi, Lahore, Quetta, Rawalpindi, Islamabad and Peshawar). The objective of this study was to establish baseline levels and behavior of airborne pollutants in urban centers with temporal and spatial parameters. This study reveals that the highest concentrations of CO were observed at Quetta (14 ppm) while other pollutants like SO₂ (52.5 ppb), NO _x (60.75 ppb) and O₃ (50 ppb) were higher at Lahore compared to other urban centers like Karachi, Peshawar etc. The maximum particulate (TSP) and PM10 levels were observed at Lahore (996 ug/m³ and 368 ug/m³ respectively), Quetta (778 ug/m³, 298 ug/m³) and in Karachi (410 ug/m³, 302 ug/m³). In all major cities the highest levels were recorded at major intersections and variations were directly correlated with traffic density. These pollutants showed highest levels in summer and spring while lowest were observed in winter and monsoon. A data bank has been generated for future planning and air pollution impact studies.     

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.     

Transformation of nitrogen dioxide into ozone and prediction of ozone concentrations using multiple linear regression techniques

Analysis and forecasting of air quality parameters are important topics of atmospheric and environmental research today due to the health impact caused by air pollution. This study examines transformation of nitrogen dioxide (NO₂) into ozone (O₃) at urban environment using time series plot. Data on the concentration of environmental pollutants and meteorological variables were employed to predict the concentration of O₃ in the atmosphere. Possibility of employing multiple linear regression models as a tool for prediction of O₃ concentration was tested. Results indicated that the presence of NO₂ and sunshine influence the concentration of O₃ in Malaysia. The influence of the previous hour ozone on the next hour concentrations was also demonstrated.     

上海市臭氧污染时空分布及影响因素

分析2006—2016年上海市的监测数据发现,臭氧(O_3)浓度存在逐年上升趋势,污染持续时间有所增加,但除水平风速有下降趋势外,其他相关气象因素的年际变化趋势并不显著。空间分析结果表明,上海市O_3超标主要集中在西南部郊区,但市区O_3超标潜势不容忽视。O_3污染高发季节的污染玫瑰图分析发现,上海市南部地区是影响上海市O_3污染的关键区域;对于NO_2减排的影响分析发现,尽管上海市O_3平均浓度总体处于上升趋势,但在NO_2下降幅度最为明显的内环市区和北部郊区,O_3上升幅度低于NO_2下降幅度较小的内外环区域和西部郊区,表明上海市的O_3污染控制仍需持续推进NOx的减排,并同步推进VOCs的减排。     

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。     

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。     

嘉善前体物与气象因子对臭氧生成的影响及臭氧潜在源区分析

利用2017年嘉善善西超级站臭氧（O₃）及其前体物（NO_x和VOCs）以及气象因子（温度、湿度、风速）逐小时数据,分析了2017年全年NO_x和O₃的变化特征以及春季（4—5月）、夏季（7—8月）NO_x和气象因子对O₃生成的影响,利用O₃生成潜势（OFP）评估了VOCs大气化学反应活性,并通过潜在源区贡献（PSCF）和浓度权重轨迹（CWT）方法分析了嘉善春、夏季O₃潜在源区贡献特征。研究发现：O₃日变化特征为单峰结构,NO_x为弱双峰结构。O₃浓度在3—9月较高,春、夏季O₃浓度峰值分别出现在15：00和14：00,春、夏季的NO_x、O₃日变化与2017年全年日变化趋势基本一致。NO_x对O₃存在滴定作用,且低湿高温有利于O₃浓度的升高。春、夏季O₃生成潜势贡献均表现为烯烃 > 芳香烃 > 烷烃,由于烯烃光化学活性较高,夏季烯烃浓度升高导致其贡献较春季增长约18.1个百分点,且夏季VOCs平均最大O₃增量反应活性高于春季。PSCF和CWT分析结果表明,嘉善春季的潜在源区主要为本地、西南方向和东南方向,夏季的潜在源区主要为本地、西北方向、西南方向以及东南方向。     

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 elemental concentration using ICP-AES and pathogen indicator in drinking water of Qasim Abad, District Rawalpindi, Pakistan

The present study was conducted to investigate drinking water quality (groundwater) from water samples taken from Qasim Abad, a locality of approximately 5,000 population, situated between twin cities Rawalpindi and Islamabad in Pakistan. The main sources of drinking water in this area are water bores which are dug upto the depth of 250–280 ft in almost every house. The study consists of the determination of physico-chemical properties, trace metals, heavy metals, rare earth elements and microbiological quality of drinking water. The data showed the variation of the investigated parameters in samples as follows: pH 6.75 to 8.70, electrical conductivity 540 to 855 μS/cm, total dissolved solids 325.46 to 515.23 ppm and dissolved oxygen 1.50 to 5.64 mg/L which are within the WHO guidelines for drinking water quality. The water samples were analysed for 30 elements (aluminium, iron, magnesium, manganese, silicon, zinc, molybdenum, titanium, chromium, nickel, tungsten, silver, arsenic, boron, barium, beryllium, cadmium, cobalt, copper, gallium, mercury, lanthanum, niobium, neodymium, lead, selenium, samarium, tin, vanadium and zirconium) by using inductively coupled plasma atomic emission spectroscopy. The organic contamination was detected in terms of most probable number (MPN) of faecal coliforms. Overall, elemental levels were lower than the recommended values but three water bores (B-1, B-6, B-7) had higher values of iron (1.6, 2.206, 0.65 ppm), two water bores (B-1, B-6) had higher values of aluminium (0.95, 1.92 ppm), respectively, and molybdenum was higher by 0.01 ppm only in one water bore (B-11). The total number of coliforms present in water samples was found to be within the prescribed limit of the WHO except for 5 out of 11 bore water samples (B-2, B-3, B-4, B-8, B-11), which were found in the range 5–35 MPN/100 mL, a consequence of infiltration of contaminated water (sewage) through cross connection, leakage points and back siphoning.     

我国典型南方城市臭氧污染特征

分析了我国典型南方城市的臭氧污染特征,选取我国4个有代表性的南方重点城市武汉、宁波、中山和南宁的2013—2015年监测数据,使用EXCEL、ORIGIN和MATLAB等统计软件开展研究,结果表明:我国南方典型城市的臭氧质量浓度分布有明显时间变化特征,超标时间跨度大,部分南方城市与氮氧化物存在较明显负相关性,相关系数高于-0.6;受城市所在不同地理位置、气象因素、大气扩散条件及可能的不同本地排放污染源构成等因素影响,4个城市的近3年臭氧浓度月均值、超标情况和年内峰值均存在一定差异和分组相似性;与部分气象因素也表现出显著相关性。     

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.     

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。     

衡水夏季典型时段VOCs污染特征及O3污染过程分析

选取臭氧（O₃）污染高发的7月为夏季典型月，采用自动观测设备，从前体物VOCs的浓度水平及O₃生成潜势（OFP），前体物、气象因素与O₃相关性等多方面研究了衡水市O₃污染影响因素，并剖析了一次典型的O₃污染过程，以期为衡水市夏季O₃污染防治提供科学参考。研究结果表明：衡水市VOCs主要组分浓度占比为烷烃 > 烯烃 > 芳香烃 > 乙炔，主要组分对总OFP的贡献为烯烃 > 芳香烃 > 烷烃 > 乙炔；O₃与前体物VOCs、NO₂存在负相关性，与温度存在正相关性；相对湿度低于48%时，O₃和相对湿度呈负相关性，相对湿度高于48%时，O₃和相对湿度呈正相关性；气团中VOCs化学组成稳定性较低，平均VOCs最大增量反应活性（MIR）较低，为4.855gO₃/gVOCs；衡水市7月2—4日重度污染过程受本地生成和区域传输叠加影响。     

宁波市大气污染概况及影响因素分析

为研究宁波市大气污染状况及其影响因素，利用2013—2018年宁波市国控站点实时监测污染物数据以及气象数据，探讨分析了宁波市大气污染特征以及所受气象因素的影响概况。结果表明：宁波市颗粒物污染和O₃污染呈现典型的季节性特征，颗粒物浓度冬季最高，O₃最大滑动8 h平均质量浓度春、秋季最高。宁波市O₃污染问题越来越突出，且呈现出春、秋季O₃超标天数最多的季节变化特征。O₃小时质量浓度与气温和太阳辐射成正相关关系，NO₂和颗粒物浓度与气温成负相关关系。NO₂与O₃浓度成负相关关系，与颗粒物浓度成正相关关系。     

Elemental contamination in urban parks of Rawalpindi/Islamabad—a source identification and pollution level assessment study

The soil quality of urban parks is of vital importance as the children playing in the parks get themselves easily contaminated. A study was conducted to assess the level of elemental pollution caused by constant urbanization and industrialization, in various parks of Islamabad and Rawalpindi. The soil samples, collected from 14 urban parks of Islamabad and Rawalpindi areas, were analysed for their elemental concentrations. In each sample, 32 elements were quantified using semi-absolute k (0)-instrumental neutron activation analysis and flame atomic absorption spectrophotometry. The quality of analysis was assured by analysing the International Atomic Energy Agency (IAEA) reference material IAEA-S7 (soil). The pollution level was assessed by enrichment factor, pollution load index and our suggested indicator called "average toxic element concentration". The elemental concentrations measured in the parks of two cities were compared by t test. Four sources of different elements in the soils were identified by employing principal component analysis and cluster analysis. The results of multivariate techniques grouped all parks into four classes. The use of enrichment factor indicated the presence of Ni at slightly higher level in all parks while the pollution load index revealed that the parks of Rawalpindi were relatively more polluted as compared to that of Islamabad. The hot spot areas of elemental concentration were closely related to high traffic conditions.     

中国城市臭氧的形成机理及污染影响因素研究进展

中国城市臭氧(O3)污染问题日趋严重.O3主要来源于汽车尾气及工业排放氮氧化合物(NOx)和挥发性有机物(VOCs)光化学反应生成,少部分来自于平流层的向下传输.文章介绍了城市O3形成机理研究情况,概述了中国城市臭氧污染浓度特征及气象因子、气候变化、前体物等影响因素研究进展情况,并对未来研究方向进行了展望.     

成都市夏季近地面臭氧污染气象特征

利用2016年7月成都市8个环境监测站点的臭氧、NO_2的监测资料以及成都市国家基准气象站和基本气象站的观测资料,对成都市夏季臭氧、NO_2浓度和气象要素的日变化特征和臭氧污染过程进行了分析。研究结果表明:成都市臭氧污染受综合气象条件和NO_2浓度的影响,高温、低湿、强辐射有利于臭氧大量生成,NO_2浓度高低决定了臭氧浓度的峰值大小;在污染期间,大气边界层高度远高于本地平均水平,数值约为平均水平的2～3倍;成都市臭氧污染的主要影响因子存在地区差异,成都市区的臭氧主要来自于自身的光化学反应,而灵岩寺地区的臭氧来自于VOCs和大气水平输送。     

山西省大气污染特征及对公众健康的空间影响

利用山西省11个地级市大气环境监测站的PM_2.5、PM₁₀和O₃浓度数据,分析了2015—2020年山西省PM_2.5、PM₁₀和O₃浓度时空变化特征,采用空间计量模型和岭回归方法,分析了空气污染对公众健康的空间影响。结果表明:PM_2.5和PM₁₀年均质量浓度总体下降,两者在2017年最高,2020年最低;O₃年均浓度总体增加。在季节尺度上,PM_2.5和PM₁₀质量浓度在冬季的12月和1月最高,夏季的8月最低;O₃浓度在6月最高。空间上,相较2015年,2020年山西省各地级市PM_2.5污染程度均有改善,其中长治改善效果最好;2020年山西各地级市PM₁₀污染兼有加重和减轻的情形,所有地级市PM_2.5和PM₁₀污染水平均超过国家二级污染浓度限值;2020年山西多数地级市O₃浓度升高。山西公众健康水平具有明显的空间离散特征,PM_2.5和PM₁₀浓度的局部空间自相关特征高度一致,呈现"南高北低"的格局,O₃浓度分布呈"南部高,中北部低"的格局。大气环境质量和经济发展水平均对医疗机构诊疗人数和健康体检人数的变化有正向影响,每万人卫生技术人员数量和公共财政支出比例对公众健康均有负向影响,其中经济发展水平和大气环境质量的影响最显著。山西省PM_2.5治理取得一定成效,但大部分城市PM_2.5和PM₁₀达标率较低,O₃浓度有持续升高的趋势,PM₁₀和O₃污染改善缓慢,深度减排仍面临挑战。PM_2.5和PM₁₀是危害山西公众健康的主要大气污染物,未来需要加强PM_2.5、PM₁₀和O₃的精细化管理及协同治理。     

京津冀区域臭氧污染趋势及时空分布特征

为研究京津冀区域的臭氧(O_3)污染情况及其时空分布特征,对2013—2015年京津冀区域13个城市80个国家环境空气监测点位的监测数据进行了统计分析。结果表明:2013—2015年,京津冀区域O_3污染状况整体呈加重趋势,其中2014年污染状况最为严重。13个城市中O_3污染最严重的城市为北京和衡水,连续3年均超标,且处于上升态势中。区域内不同城市O_3污染趋势并不相同。京津冀区域O_3浓度变化呈明显的季节变化特征,春末和夏季的O_3污染最严重。O_3-8 h(臭氧日最大8 h均值)年均值的高值区主要分布在北京中北部、承德和衡水等,2013—2015年第90百分位O_3-8 h的高值区均集中分布在北京。O_3的浓度峰值时间要晚于NOx2~5 h。O_3在春、夏季呈单峰分布,白天15:00左右出现最大值,在秋、冬季浓度较低,全天波动不大。     

上海臭氧及前体物变化特征与相关性研究

于2010年1~12月期间,在上海城区内采用在线连续观测,分析该地区近地臭氧与其前体物的季节变化规律及相关性,探讨了臭氧浓度与OX和NO₂光解速率之间的关系。结果表明,观测期间,上海地区O₃总超标天数为13天,超标率为3.56%。O₃浓度变化呈现明显的秋冬低、春夏高的季节变化。O₃浓度日变化规律呈典型单峰变化,O₃各前体物呈双峰形分布,冬季O₃与NO_X的相关性最强。对OX的贡献中,秋冬以NO₂为主,春夏以O₃为主;夜间以NO₂为主,白天以O₃为主。臭氧浓度与OX和NO₂光解速率变化规律基本一致。