Characterization of ambient ozone and its precursors around a coking plant

The local-scale relationship between ambient ozone (O₃) and its precursors was examined around a coking plant in northern China. The upwind, plant boundary, and downwind locations were selected for investigation during the summer and autumn seasons in 2012. It was found that propene, toluene, and benzene were the top three non-methane hydrocarbon (NMHC) species for O₃ formation at plant boundary, while propene, toluene, and m/p-xylene were the top three NMHC species at downwind location. Isoprene was the dominant species for O₃ formation at upwind location. It was also found that an O₃ depressing process occurred at plant boundary as a result of high NO emissions. Both local photochemistry and transport led to O₃ accumulation at the downwind locations. The variation of NMHC concentration during O₃ polluted and non-polluted episodes was investigated, and it indicated that NMHC concentration was higher during non-polluted episodes than polluted episodes. The impacts of precursors on O₃ formation under different meteorological conditions were also examined.     

Computational Fluid Dynamics Modelling of the Pollution Dispersion and Comparison with Measurements in a Street Canyon in Helsinki

A measuring campaign was conducted in a street canyon (Runeberg St.) in Helsinki in 2003–2004. The concentrations of NO _x , NO₂, PM₁₀ and PM_2.5 were measured at street level and at roof level at an urban background location. This study utilises the data measured from 1 Jan to 30 April, 2004, when wind speed and direction measurements were also conducted on-site at the roof level. The computational fluid dynamics model ADREA-HF was used to compute the street concentrations, and the results were compared with the measurements. The predictions for the selected cases agreed fairly well (within < 25 % for 15 min average values) with the measured data, except for two cases: a windward flow in case of a low wind speed, and a moderate southerly flow parallel to the street canyon. The main reasons for the differences of predictions and measurements are the negligence of traffic-induced turbulence in the modelling and an under-prediction of ventilation of urban background air from a crossing street. Numerical results are presented for various example cases; these illustrate the formation of the vortices in the canyon in terms of the wind direction and speed and the influence of the characteristics of the flow fields on the concentration distributions.     

Using Archive Data to Investigate Trends in the Sources and Composition of Urban PM10 Particulate Matter: Application to Edinburgh (U.K.) Between 1992 and 1997

By extending the method of Stedman (1998), daily dataof atmospheric concentrations of gravimetricPM₁₀, black smoke (BS) and sulphate aerosol (SA)from national networks were analysed to determine thetrends in time of the contribution of different sources of particulate matter to total PM₁₀ measured in central Edinburgh. Since BS is an indicator of combustion-related primary sources of particulate matter, the quantity obtained by subtraction of daily BS from daily PM₁₀ is indicative of the contribution to total PM₁₀ from other primary sources and from secondary aerosol. This PM₁₀-BS statistic was regressed on SA, since SA is an indicator of variation in secondary aerosol source. For Edinburgh, SA is a considerably better indicator of PM₁₀-BS during summer than winter (reflecting the much greater photochemical generation of secondary aerosol in summer) and there is evidence that the contribution of other secondary aerosol (presumably nitrate aerosol) has increased relative to SA between 1992 and 1997. The concentration of non-combustion primary particulate material (marine aerosol, suspended dust) to PM₁₀ in Edinburgh has not changed over this period but is about twice that calculated as the U.K. national average. The increasing input to PM₁₀ from secondary aerosol sources at regional rather than urban scale has important implications for ensuring local air quality compliance. The method should have general applicability to other locations.     

夏季上海城区大气中二氧化碳浓度特征及相关因素分析

利用连续自动监测仪器,获得CO2源区上海城区2010年夏季高时间分辨率的CO2连续监测数据.监测期间CO2平均浓度为414±16ppm,高于同期全球本底观测站约6%,与中国其他城市化地区的浓度水平基本相当或略低.CO2浓度日变化呈显著早晚双峰特征;周变化呈显著的波浪形,高值集中出现在工作日.除O3外,与其他污染物呈显著...     

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。     

Do the pollution related to high-traffic roads in urbanised areas pose a significant threat to the local population?

Many large neighbourhoods are located near heavy-traffic roads; therefore, it is necessary to control the levels of air pollution near road exposure. The primary air pollutants emitted by motor vehicles are CO, NO₂ and PM. Various investigations identify key health outcomes to be consistently associated with NO₂ and CO. The objective of this study was the measurement-based assessment for determining whether by high-traffic roads, such as motorways and express ways, and the concentrations of CO and NO₂ are within normal limits and do not pose threat to the local population. Average daily values (arithmetic values calculated for 1-h values within 24 h or less, depending on result availability) were measured for concentrations of NO₂ and CO by automatic stations belonging to the Voivodship Environmental Protection Inspectorate in Katowice, in areas with similar dominant source of pollutant emission. The measurements were made in three sites: near the motorway and expressway, where the average daily traffic intensity is 100983 and 35414 of vehicles relatively. No evidence was found of exceeding average daily values equal to the maximum allowable NO₂ concentration due to the protection of human health in the measurement area of the stations. No daily average values exceeding the admissible CO concentration (8-h moving average) were noted in the examined period. The results clearly show lack of hazards for general population health in terms of increased concentrations of CO and NO₂ compounds that are closely related to high intensity car traffic found on selected motorways and speedways located near the city centres.     

Time series modelling of respiratory hospital admissions and geometrically weighted distributed lag effects from ambient particulate air pollution within Kathmandu Valley,Nepal

The distributed lag effects of ambient particulate air pollution exposure on respiratory hospital admissions in Kathmandu Valley are modelled using daily time series data. The extended exposure to PM₁₀ is accounted for by assigning weights to daily average PM₁₀ which decline geometrically as the lag period increases in days. Results show that the percent increase in chronic obstructive pulmonary disease (COPD) hospital admissions and respiratory admissions including COPD, asthma, pneumonia, and bronchitis per 10 μg/m³ rise in PM₁₀ are found to be 4.85% for 30 days lag effect, about 15.9% higher than that observed for same-day lag effect and 3.52% for 40 days lag effect, about 28.9% higher than the observed value for same-day lag effect, respectively.     

Meteorological influence on predicting surface SO2 concentration from satellite remote sensing in Shanghai,China

In this study, we explored the potential applications of the Ozone Monitoring Instrument (OMI) satellite sensor in air pollution research. The OMI planetary boundary layer sulfur dioxide (SO₂_PBL) column density and daily average surface SO₂ concentration of Shanghai from 2004 to 2012 were analyzed. After several consecutive years of increase, the surface SO₂ concentration finally declined in 2007. It was higher in winter than in other seasons. The coefficient between daily average surface SO₂ concentration and SO₂_PBL was only 0.316. But SO₂_PBL was found to be a highly significant predictor of the surface SO₂ concentration using the simple regression model. Five meteorological factors were considered in this study, among them, temperature, dew point, relative humidity, and wind speed were negatively correlated with surface SO₂ concentration, while pressure was positively correlated. Furthermore, it was found that dew point was a more effective predictor than temperature. When these meteorological factors were used in multiple regression, the determination coefficient reached 0.379. The relationship of the surface SO₂ concentration and meteorological factors was seasonally dependent. In summer and autumn, the regression model performed better than in spring and winter. The surface SO₂ concentration predicting method proposed in this study can be easily adapted for other regions, especially most useful for those having no operational air pollution forecasting services or having sparse ground monitoring networks.     

中国高分辨率近地面NO2浓度反演

通过分析2010年全国333个县级以上城市卫星遥感的NO2对流层年均柱浓度与地面实际观测浓度之间的相关性,发现两者具有一定的线性相关性(r=0.54,n=333),并建立了NO2"遥感柱浓度"与"地面观测浓度"之间的关联方程,通过该方程反演了中国0.125°分辨率近地面NO2污染分布特征。结果表明,全国近地面NO2浓度超过《环境空气质量标准》(GB 3095—2012)要求的年均浓度二级标准(0.04 mg/m3)的区域约为5.95万平方千米,超标地区主要集中在华北平原、长三角地区、四川盆地和珠三角地区,这些地区NO2污染水平远高于333个城市的年平均值(0.028 mg/m3)。NO2污染极不平衡,以大中型城市为中心的区域污染特征显著。NO2人口加权浓度分析结果表明,NO2人口加权浓度高值区主要集中在能源消费量大、机动车保有量大及人口密集的地区,全国约5.7%的人口暴露在NO2超标区域。     

西安市黑碳气溶胶浓度特征及与气象因素和常规污染物相关性

利用西安市环境监测站超级站2013年9月1日—2015年5月31日黑碳气溶胶(BC)的监测数据,研究空气中BC浓度特征及其与气象因素和常规污染物相关性。结果表明:BC小时平均浓度均值在春季、夏季和冬季的变化趋势呈"W"型,秋季呈"V"型,且冬季的第一个最低值和峰值比春季和夏季的分别延迟1 h和2~3 h,且20:00~次日6:00秋季BC小时平均浓度均值高于当年冬季。BC浓度在秋季和冬季较高,夏季较低。冬季BC/PM_(2.5)基本最低,秋季BC/PM_(2.5)相对最高。BC日平均浓度与气温、降水和风速的日平均值为极负显著相关,且风速小于1.0 m/s时,其与风速呈最显著的负相关。除O_3外,BC日平均浓度与其他常规空气污染物浓度呈显著相关,表明其同源性很强,且受机动车尾气排放的影响更大。     

江苏省空气质量预报准确度及改进方法分析

介绍了江苏省重污染天气监测预报预警系统以及大气重污染预警会商流程,将2015年13个地级市的模式预报、人工预报结果分别与实际观测值进行比较。结果表明:人工预报更准确,PM_(2.5)日均值、臭氧日最大8 h平均值、AQI 3个指标人工预报和实况的相关性分别比模式预报高出12.8%、0.3%、11.4%,平均标准误差(MNE)分别低20.7%、3.1%、23.1%。依据国家空气质量预报技术指南评分办法,对各市2015年全年空气质量级别为"良"时进行评分。通过开展07∶00预报更新,使2015年上半年空气质量预报级别得分平均提高了0.9分,全年级别得分平均提高了2.6分;通过改进模式预报参数,使PM_(2.5)日均预报值、臭氧日最大8 h平均预报值、AQI预报值和实际观测值的相关性比上年同期分别提高26.0%、5.0%、33.9%,MNE分别降低3.6%、31.3%、7.6%。     

Seasonal change and correlation with environmental parameters for 2-MIB in Feng-Shen Reservoir, Taiwan

Two common drinking water earthy/musty odorants, 2-methyl-isoborneol (2-MIB) and trans-1,10-dimethyl-trans-9-decalol (geosmin), were monitored and analyzed for their correlation with environmental conditions in Feng-Shen Reservoir (FSR), Taiwan. Long-term monitoring results, from December 2000 to July 2003, indicated that 2-MIB was present in the reservoir at concentrations between 10 and 200 ng L(-1), and those of geosmin were always smaller than 10 ng L(-1). The 2-MIB concentrations followed a trend of higher concentrations during the warm seasons. After being analyzed with 10 water quality and three meteorological parameters, 2-MIB concentration was found to correlate with corresponding air and water temperatures. An analysis of air temperature history versus 2-MIB concentration in FSR suggested that 2-MIB concentration was best correlated with the mean of average daily temperature from 1 to 9 days before sampling, with R (2) = 0.90. This correlation was further employed to predict the 2-MIB concentration observed during another sampling period in FSR. A similar degree of fit was observed between predictions and experimental data, suggesting the potential applicability of the approach. In addition to the effect of temperature, heavy rainfalls that occurred before the sampling time may also reduce the 2-MIB concentration in the reservoir. A short-term continuous monitoring of the odorants for 32 h showed that both geosmin and 2-MIB concentrations in the reservoir remained almost constant, with only about a 10% difference during the sampling period. This may suggest that the odorants were uniformly distributed in the water near the sampling location in the reservoir.     

重庆市北碚区空气质量改善效果评估分析

基于2014—2020年重庆市中心城区北碚区环境监测数据及地面观测气象要素,分析了北碚区大气污染特征,利用KNN算法建立大气污染的评估模型,对空气质量改善效果进行评估。结果表明,重庆市中心城区北碚区的PM_2.5浓度逐年呈明显下降趋势,O₃浓度除夏季有一个弱的下降趋势外,其余3个季节和年平均值整体均呈上升趋势。全年以优良天气为主且呈增加趋势。O₃与气温、日照时间呈正相关,与相对湿度呈负相关性,PM_2.5与气温、降水及风速呈负相关。基于KNN算法对空气质量改善状况评估表明,减排对O₃污染平均贡献率在-4.7%左右,对PM_2.5污染平均贡献率为-52%,气象条件对O₃污染的平均贡献率在17%左右,对PM_2.5污染的平均贡献率在-7%左右。该大气污染评估模型能够有效地评估空气改善效果。     

衡阳市区和衡山背景站臭氧浓度变化规律的对比分析

选取衡阳市区和衡山背景站臭氧自动监测数据,分析两地的臭氧污染特征。对空气质量的优良率情况、臭氧作为首要污染物的变化情况、臭氧浓度的日变化特征、典型时段的浓度变化特征、臭氧浓度的月际变化特征和臭氧与PM_(2.5)的关联情况等进行了分析。结果表明,多云及阴雨天气时,衡阳市区的臭氧浓度日变化幅度大于衡山背景站。夏季,衡阳市区和衡山背景站的臭氧浓度的日变化特征规律差异较大,臭氧浓度分布比较分散,前者为典型的单峰形,后者则波动平缓。冬季,日变化幅度不大,但衡阳市区的臭氧浓度明显低于衡山背景站。衡山背景站和衡阳市区的臭氧基本同步变化,但日均值高于衡阳市区。     

沈阳市冬季环境空气质量统计预报模型建立及应用

利用沈阳市2013年1—2月大气自动监测数据和同期气象资料,选取19项预报因子,采用逐步回归方法建立了沈阳市冬季环境空气质量统计预报模型,预报项目包括细颗粒物(PM2.5)、可吸入颗粒物(PM10)、二氧化硫(SO2)、二氧化氮(NO2)、一氧化碳(CO)日均浓度及臭氧(O3)日最大8 h平均浓度。2013年11月至2014年1月,应用该模型并结合人为经验修订,开展了沈阳市环境空气质量预报工作,预报结果与实测结果的对比验证结果表明,环境空气预测结果级别准确率达到79.1%,首要污染物准确率为73.6%。     

洞庭湖水体叶绿素a时空分布及与环境因子的相关性

2013年6月至2014年5月逐月对洞庭湖水体叶绿素a质量浓度和主要环境因子进行测定,分析洞庭湖水体叶绿素a质量浓度的时空分布特征,探讨洞庭湖水体叶绿素a质量浓度与环境因子的相关性。结果表明,洞庭湖水体叶绿素a质量浓度为0.11~8.62 mg/m~3,年均值为(1.89±1.23)mg/m~3,属贫营养;叶绿素a质量浓度随季节变化明显,总体呈现夏、秋季明显大于冬、春季的规律;在空间上,总体表现为西洞庭湖和东洞庭湖明显大于南洞庭湖。全湖叶绿素a质量浓度与水温、电导率、COD和TP呈极显著正相关,与DO、NH3-N、TN和TN/TP呈极显著负相关,与NO-3-N呈显著负相关,与p H和透明度无显著相关性。全湖TN/TP的年均值为28.5,磷可能是洞庭湖水体浮游植物生长的限制性营养盐。     

Distribution behavior and carcinogenic level of some polycyclic aromatic hydrocarbons in roadside soil at major traffic intercepts within a developing city of India

A study of polycyclic aromatic hydrocarbons (PAHs) pollution in roadside soil was conducted at a developing city locations of Jalandhar (Punjab), India in winter season to ascertain the contamination levels and their distribution behavior in roadside soil. PAHs concentration level of ten locations was measured at 1, 2, and 3 m distances from roadside soil covering all the major traffic intercepts within a city. Samples were extracted in acetone and dichloromethane (1:1) using soxhlet extraction. The extracts were filtered on a silica gel micro column to remove impurities and eluate was subjected to GC-FID. The total average PAHs concentration (city average) was found to be 4.04 μg g(-1), whereas the concentration of 16 individual PAHs was found to vary between 0.008 and 28.4 μg g(-1). The average concentration of noncarcinogenic and carcinogenic PAHs in all the samples was 2.17 and 6.41 μg g(-1) (ratio 1:2.95). The concentration of five ringed PAHs was found to be 45% to 60%, whereas two ringed PAHs were found to be in the range from 0.28% to 0.56% in all most all locations. The average highest PAHs concentration for any individual location was found as 12.23 μg g(-1) at DAV Chowk at 1 m distance and minimum concentration was 0.98 μg g(-1) at Maqsuda Chowk at 1 m distance from roadside. DiB (ah) A was the individual PAHs found in highest concentration in all the intercepts ranging between 1.26 and 28 μg g(-1). At most of the city intercepts, total carcinogenic PAHs concentration was found to range from 60% to 80% in comparison to noncarcinogenic PAHs (20%-40%) at most of the intercepts. The pollution level our study was compared with other cities of India/worldwide.     

2018年11月上旬一次中韩PM2.5相互影响传输过程分析

2018年11月5—7日,韩国首尔出现了一次PM_(2.5)污染过程。利用拉格朗日轨迹分析(HYSPLIT)模型分析了首尔峰值浓度气团的来源,结合污染物监测和气象资料,定性分析了中国对韩国浓度高值可能的影响及其程度。利用嵌套网格空气质量预报模式(NAQPMS)及其耦合的在线污染来源追踪模块进行了污染来源解析和敏感性测试,分别计算了同一时期中韩两国相互间的PM_(2.5)传输贡献。结果显示:2018年11月5—7日,中国对韩国首尔污染过程的日均贡献不足10%;此次污染过程后期,首尔的污染气团对上海PM_(2.5)浓度峰值产生了影响。     

Modeling of Hydrodynamics and Cohesive Sediment Processes in an Estuarine System: Study Case in Danshui River

The Danshui River estuarine system is the largest estuarine system in northern Taiwan and is formed by the confluence of Tahan Stream, Hsintien Stream, and Keelung River. A comprehensive one-dimensional (1-D) model was used to model the hydrodynamics and cohesive sediment transport in this branched river estuarine system. The applied unsteady model uses advection/dispersion equation to model the cohesive sediment transport. The erosion and deposition processes are modeled as source/sink terms. The equations are solved numerically using an implicit finite difference scheme. Water surface elevation and longitudinal velocity time series were used to calibrate and verify the hydrodynamics of the system. To calibrate and verify the mixing process, the salinity time series was used and the dispersion coefficient of the advection/dispersion equation was determined. The cohesive sediment module was calibrated by comparing the simulated and field measured sediment concentration data and the erosion coefficient of the system was determined. A minimum mean absolute error of 4.22 mg/L was obtained and the snapshots of model results and field measurements showed a reasonable agreement. Our modeling showed that a 1-D model is capable of simulating the hydrodynamics and sediment processes in this estuary and the sediment concentration has a local maximum at the limit of salinity intrusion. Furthermore, it was indicated that for Q ₅₀ (the flow which is equaled or exceeded 50% times), the turbidity maximum location during neap tide is about 1 km closer to the mouth compared to that during spring tide. It was found that deposition is the dominant sediment transport process in the river during spring–neap periods. It was shown that, while sediment concentration at the upstream depends on the river discharge, the concentration in the downstream is not a function of river discharge.     

Distribution of PM2.5 and PM10-2.5 in PM10 Fraction in Ambient Air Due to Vehicular Pollution in Kolkata Megacity

This research paper aims at establishing baseline PM₁₀ and PM_2.5 concentration levels, which could be effectively used to develop and upgrade the standards in air pollution in developing countries. The relative contribution of fine fractions (PM_2.5) and coarser fractions (PM_10-2.5) to PM₁₀ fractions were investigates in a megacity which is overcrowded and congested due to lack of road network and deteriorated air quality because of vehicular pollution. The present study was carried out during the winter of 2002. The average 24h PM₁₀ concentration was 304 μg/m³, which is 3 times more than the Indian National Ambient Air Quality Standards (NAAQS) and higher PM₁₀ concentration was due to fine fraction (PM_2.5) released by vehicular exhaust. The 24h average PM_2.5 concentration was found 179 μg/m³, which is exceeded USEPA and EU standards of 65 and 50 μg/m³ respectively for the winter. India does not have any PM_2.5 standards. The 24 h average PM_10-2.5 concentrations were found 126 μg/m³. The PM_2.5 constituted more than 59% of PM₁₀ and whereas PM₁₀-PM_2.5 fractions constituted 41% of PM₁₀. The correlation between PM₁₀ and PM_2.5 was found higher as PM_2.5 comprised major proportion of PM₁₀ fractions contributed by vehicular emissions.