道路绿化带影响大气颗粒物分布实测研究

以福州市西三环快速路某路段为实验靶区，利用微型环境检测仪采集路边细颗粒物(PM_2.5)、亚微米颗粒物(PM_1.0)和黑碳(BC)的空间分布样本，解析其在道路绿化带前后(绿化带前是指干道和辅道外边缘线位置，其他位置均视为绿化带后)的变化特征及原因。结果表明：(1)颗粒物浓度随着采样点远离干道而整体趋于递减，呈现BC>PM_2.5>PM_1.0的衰减率变化特征，且植被稠密的路边环境对应更大的颗粒物浓度降幅。(2)夏季绿化带后的颗粒物浓度降幅高于冬季，冬季绿化带后部分采样点的PM_1.0和PM_2.5浓度甚至有所抬升。在植被茂密的路边环境下，风自干道吹向绿化带情景的路边空气质量介于风自绿化带吹向干道情景和风平行于干道情景之间。(3)BC对交通变化的敏感性高于PM_2.5和PM_1.0,植被茂密的绿化带后的颗粒物浓度降幅会因交通强度的上升而增大。风自干道吹向绿化带时，绿化带对颗粒物的调节作用会随交通源强和季节的变化而不同...     

Monitoring Of Vehicles Derived Particulates Using Magnetic Properties Of Leaves

Biomonitoring of vehicle-derived particulates is conducted by taking magnetic measurements of roadside tree leaves. Remanent magnetization (IRM_{300 mT}) of more than 400 Delbergia sissoo leaves was determined and IRM_{300 mT} normalized for the leaf area. The normalized 2-D magnetization as shown by results is dominantly controlled by the tree's distance to the road. The spatial and temporal variations of vehicle-derived particulates were mapped using magnetic analysis. 2D-magnetizations values were higher for leaves collected adjacent to major road sections than for those from village road suggesting vehicle emissions, rather than resuspended road dust, as the major cause of magnetic particles of roadside tree leaves. Vehicles derived particulates are responsible for tree leaf magnetism, and the leaf magnetizations values fall significantly from high values proximal to the roadside to lower values at the distal side. This suggests the ability of trees to reduce particulates concentrations in the atmosphere. The rainfall produces a net decrease in the leaf magnetic dust loadings.     

Simulation of Urban-Scale Air Pollution Patterns in Luxembourg: Contributing Sources and Emission Scenarios

The aim of this study is to investigate the air pollution situation in an urban area in southwestern Luxembourg and to simulate annual NO₂ and PM₁₀ concentrations in response to changes in meteorological conditions and emissions using a Gaussian dispersion model. Simulations are carried out for the years 1998–2006. Emission scenarios related to road transport and nonindustrial combustion are performed in order to predict changes of air pollution levels. Road transport is by far the most important local emission source in the study area. Scenarios with more stringent emission standards for vehicles, less traffic, and fewer heavy-duty vehicles lead to reductions of NO_x and primary PM₁₀ emissions. As a result, the annual NO₂ concentrations are decreasing in most parts of the study area and are below the European annual limit value of 40 μg?m^?3. In contrast, a scenario with increased use of wood pellets for domestic heating shows an increase in urban PM₁₀ concentration. The year-to-year variability of meteorological conditions accounts for the same magnitude of absolute NO₂ and PM₁₀ concentration changes as the emission scenarios. The comparison with measurements located in the study area shows that the model is able to predict urban-scale annual average air pollution. The proposed application results show that the model can be appropriate for policy-driven air quality management and planning queries.     

Management of air quality in the vicinity of congested area in Kuwait

An assessment of air quality in the vicinity of a selected school has been carried out by monitoring the concentrations of primary pollutants. The results has shown that during the school hours, the measured pollutants emitted from the cars next to the selected school, such as CO and NO(2), are always under the allowable limits for Kuwaiti air quality standards. On the other hand, the concentrations of non methane hydrocarbon pollutant (nm-HC), some of which are considered to be cancergenic, are found to be above the Kuwaiti standard most of the times. A traffic counter is used to record the number of cars in the main road next to the school in 15 min intervals for 10 days during the monitoring period for air quality. Statistical analysis is performed to develop a relation for prediction of the necessary reduction in traffic, based on CO concentrations, during morning and afternoon periods on working days. A computer dispersion model (CALINE4) is also used to assess the CO concentrations based on recorded flow of traffic and emission inventory with the prevailing meteorological conditions existed at the specified time. After the validation of model, different scenarios have been evaluated to provide an acceptable solution to resolve the traffic congestion problem near the schools in the early morning hours with substantial reduction in pollution levels. The optimal solution for CO concentration reduction by managing smooth traffic flow is to reduce the traffic intensity by half in early morning and afternoon rush hours. The results of the predicted CO concentration in the vicinity of the school for the model and the statistical analysis has shown reduction of 30% and 42% respectively, for approximately 50% decrease in the car use. On the other hand the predicted CO concentration for the model and the statistics reached 24% and 33% respectively when 50% of students opted for buses instead of using private cars.     

重庆市内环货车错时限行对空气质量的影响

在分析货车实施错时限行后内环车流量时段分布变化基础上,通过对PM_(2.5)、NO_2等指标的ADMS模型模拟和实际监测数据对比分析,探讨了内环货车错时限行对环境空气质量的影响。结果表明,货车错时限行后主城区环境空气中PM_(2.5)、NO_2小时平均质量浓度分别降低了9.4%和6.0%,峰值浓度明显降低,晚上出现峰值时间往后推移了2~3 h。经ADMS模型模拟计算,内环高峰时段机动车排放对主城区NO_2、PM、VOCs的浓度贡献分别降低了54.1%、56.3%、17.5%,CO浓度贡献不大。内环货车错时限行措施对重庆市主城区空气质量的改善有一定的积极作用。     

Air pollution in Athens basin and health risk assessment

An inventory of air pollution sources within the Athens basin is carried out for the years 1989, 1992 and 1998 and the results areinputted in a climatological model for predicting ambient concentrations. Despite of the significant growth in the numberof road vehicles and the deteriorating traffic, the emissions andambient concentrations of fine particulates, CO, NO_x and VOCappear to remain reasonably constant over for the period 1989 to 1998, while these of SO₂ and Pb are reduced, mainly due to the renewal of vehicle fleet, the use of catalytic technologies and the improved quality of the used fuel. The results further indicate that for CO, NO_x and VOC the major source is road traffic, while for PM_2.5 and SO₂ both space heating andtraffic share responsibility. The air pollutant concentrations monitored by the network of 11 stations are reviewed and statistics related to air quality guidelines are presented. As fine particulate levels are not monitored, approximate PM_2.5and PM₁₀ concentrations are derived from black smoke ones on basis of experimentally determined conversion factors. The computed and monitored air pollution levels are compared and found in reasonable agreement. The results of the above analysisshow that the levels of all `classical' pollutants, with the exception of SO₂ and Pb, exceed significantly the WHO guidelines and are thus expected to exert a significant healthimpact. The latter could be quantified in relation to the PM_2.5 or PM₁₀ levels on the basis of risk assessment information developed by the World Health Organization (WHO). The results show that the existing levels of fine particle concentrations in Athens increase significantly the mortality and morbidity, and reduce the average longevity of the entirepopulation from 1.3 to 1.7 years.     

Assessment of Urban Air Quality in South Estonia by Simple Measures

In countries having limited resources, it is difficult to assess urban air quality on contemporaneously, due to the absence of on-line information about air pollution levels and emission rates. An alternative approach is recommended for smaller cities with lower demands of resources. The applied scheme consists of a database of air pollution sources (NO _x and CO from industry, traffic, and domestic heating), the simple Gaussian-plume model AEROPOL and a series of measurements by passive monitors. This method was used in Tartu, a small city situated in the valley of the river Emajõgi, within a landscape with noteworthy topographical variations. Simulations of annual average and maximal concentrations were performed, and a fair agreement obtained with NO₂ monitoring results from passive Palmes monitors. Inventories of pollution sources in 1998 revealed that official statistics of stationary sources covered 64% of SO₂,36% of CO, 37% of NO _x and 32% of total particulate matter emissions. Recommendations for measures for reducing air pollution levels and for further investigations towards improving air quality assessment and management, are given.     

A comparative study of respirable particulate microenvironmental concentrations and personal exposures

Personal monitoring (PM) for respirable suspended particulate matter (RSP) of thirty subjects was performed as part of an air pollution health effects study conducted in Houston, Texas. Parallel RSP measurements were performed in the study subjects' homes and two fixed site monitoring stations. The participants' daytime activities were independently recorded by study techicians. These data were used to characterize RSP concentrations in each microenvironment visited by the participants. Four estimates of daytime exposure to RSP were calculated based on two different microenvironmental models, and home and fixed site mean daytime RSP concentrations. These estimates were compared to mean daytime personal exposure from PM. Hourly estimates of exposure were calculated from a microenvironmental model and mean hourly home RSP concentrations and compared to hourly PM data. The results of the study indicate that, as in the case of NO₂, it is important to characterize indoor microenvironmental RSP concentrations according to location, sources, and concurrent activities, both qualitatively and quantitatively. Stratification of concentrations according to sources present and self-reported activity can lead to misclassification of exposures. For RSP and, probably, other pollutants with indoor sources and with short exposure integration times, adequate measures of exposure can only be obtained with very detailed and complex microenvironmental models or comprehensive personal monitoring.     

Relating Background NO2 Concentrations in Air to Air Mass History Using Non-Parametric Regression Methods: Application at Two Background Sites in Ireland

The concentration of nitrogen dioxide (NO₂) in background air varies temporally and spatially and is influenced by meteorological and anthropogenic factors. Background concentrations used in local air quality modelling studies have a significant effect on the accuracy of the overall result and when based on short-term monitoring data, variation in concentrations with air mass history is often unaccounted for. The current paper presents a powerful tool for the quantification and separation of local and regional air mass effects on background air quality. The origin of and the regions traversed by an air mass prior to reaching a receptor has been modelled using HYsplit-4. Trajectories (between 12 and 96?h duration) were defined based on the frequency with which they passed into 16 predefined compass quadrants and each represented as a vector. Using this vector as the predictor variable and the background concentration as the response variable, non-parametric regression using a Gaussian kernel function was carried out. A graphical output indicated the trajectory direction of maximum NO₂ concentration, while allowing distinction to be made between spurious and true peaks. In all cases, air mass history was found to have a statistically significant effect on NO₂ concentrations. Incorporating emissions data into the analysis local and regional effects were separated and quantified. It was found that emissions in the UK and Europe have a significant effect on background NO₂ concentrations in Ireland and in some instances supersede domestic emissions. The methods can be used to identify source regions, separate local and regional effects and improve predictions of background concentrations based on limited monitoring data. In particular, the results highlight the importance of considering air mass history when assessing background concentration levels for use in local air quality modelling studies.     

基于SHERPA的环境空气质量减排情景模拟评估

分析了SHERPA综合评价模型的基本原理和主要建模理念,重点介绍了其在环境空气质量减排情景模拟评估方面的作用,以及在排放源与受体关系(SRR)方面的处理方法,比较了其与欧盟常用的其他情景模拟模型的优缺点。SHERPA模型的特点是空间灵活性较好,对于任何给定地点,可以快速评估不同地区对该研究地点空气质量的影响。SHERPA模型的3个主要功能为污染物来源分析、决策支持和情景模拟。基于SHERPA模型对法国环境空气中PM_(2.5)、PM_(10)和NO_2年均浓度进行污染来源分析、决策支持分析和减排情景模拟评估,展示了模型在环境治理措施优先级筛选和政府间联合治理措施协调建议方面的功能和作用,以期为中国环境空气质量预测预报、环境质量管理措施的制定和成效评估等环境服务与管理工作提供借鉴。     

Modelling the Size Separated Particulate Matter (SSPM10) from Vehicular Exhaust at Traffic Intersections in Mumbai

The study was carried out to predict the size separated particulate matter below 10 microm size (SSPM10) from vehicular exhausts at traffic intersections using modified general finite line source model (GFLSM). Two air quality control regions (AQCRs) were selected in Mumbai City for this study. One was industrial area (AQCR1) containing the busy intersection, i.e. Marol link road, with the heavy inflow of two-three wheelers. And, the other was commercial busy district area (AQCR2) containing the busy intersection, i.e. Dadar circle, with a heavy traffic flow especially cars. The model was applied at both the traffic intersections. The data were collected for modelling study for three winter months in 1995 using cascade impactor of nine size ranges. The prediction results revealed that modified GFLSM underpredicted the SSPM10 concentrations for all the size ranges. However, showed considerable correlation between observed and predicted values for the size range below 4.7 microm at both the intersections. The relative high concentrations observed in the coarser range of 10-4.7 microm are attributed to the resuspension of the roadside particulate matter. Hence, the amount of underprediction was more for this range, which was due to the characteristics of model that does not take into account the factor for resuspension of roadside particulate matter caused by traffic movements. The model was also applied to predict the total particulate matter for downwind distances from the road intersection. The statistical evaluation of model was done, which indicated that the model's performance was good for the finer range of particles (below 4.7 microm) with r-square values of 0.49 and 0.57 found at both the intersections in AQCR1 and AQCR2, respectively. However, it is not unusual that the model uncertainty is likely to exist due to data input errors and stochastic fluctuations irrespective of the models accurateness. The statistical distribution model was therefore identified using Kolmogorov-Smirnov test. At both the intersections, SSPM10 concentration data were found lognormally distributed.     

Use of a MM5–CAMx–PSAT Modeling System to Study SO2 Source Apportionment in the Beijing Metropolitan Region

A coupled MM5–CAMx air quality modeling system was used to simulate SO₂ concentrations in Beijing, China during the heating season. Particulate matter source apportionment technology was employed to investigate the apportionment of SO₂ sources in the study area. Comprehensive analysis of the industry and region revealed that the most important SO₂ contributors were publicly and privately supplied heating emission sources and other industry emission sources from the urban areas of Beijing, with 66.1?% of the emission source contribution ratio. Four SO₂ emission reduction scenarios based on our SO₂ source apportionment research were established to assess the potential for improving the SO₂ air quality in Beijing during the heating season. By weighing the desired SO₂ improvement, the availability of technology, and economic considerations, a suitable SO₂ reduction plan was able to be recommended for Beijing city.     

New Metal Emission Patterns in Road Traffic Environments

The increased awareness of traffic as a major diffuse metal emission source emphasizes the need for more detailed information on the various traffic-related sources and how and where the metals are dispersed. In this study, metal emission patterns in the road traffic environment were examined from the perspective of different surrounding factors, e.g. the importance of intersections, deceleration, vehicle speed and traffic density. A total of 148 topsoil samples from 18 south Swedish roads were analysed (using GFAAS) for traffic-emitted metals, i.e. Cd, Cr, Cu, Ni, Pb, Sb and Zn. The roadside topsoil metal concentrations were used to examine correlations between metals and surrounding factors. The studied metals were divided into three groups corresponding to different emission sources: metals from decelerating activities (Cu, Sb and Zn), metals as historical residues from the combustion of petrol (Pb and Cd), and non-source-specific metals (Cr and Ni). It was found that Cu and Sb, despite their rather short history as traffic-emitted metals, have increased more than eightfold in roadside soils compared to background levels. The major source of road traffic related Cu and Sb is brake linings. The significant increase of Cu and Sb in roadside topsoil stresses the need for metal transport studies as well as effect studies of these metals. Metals emitted due to decelerating activities were not correlated to elevated concentrations near road junctions. Emission patterns of traffic-related metals alongside roads are crucial in order to be able to evaluate the optimal localization of storm water treatment ponds.     

Hybrid Neural Networks and Boosted Regression Tree Models for Predicting Roadside Particulate Matter

This paper examines the application of artificial neural network (ANN) and boosted regression tree (BRT) methods in air quality modelling. The methods were applied to developing air quality models for predicting roadside particle mass concentration (PM₁₀, PM_2.5) and particle number counts (PNC) based on air pollution, traffic and meteorological data from Marylebone Road in London. Elastic net, Lasso and principal components analysis were used as feature selection methods for the ANN models to reduce the number of predictor variables and improve their generalisation. The performance of the ANN with feature selection (ANN hybrid) and the BRT models was evaluated and compared using statistical performance metrics. The performance parameters include root mean square error (RMSE), fraction of prediction within a factor of two of the observation (FAC2), mean bias (MB), mean gross error (MGE), the coefficient of correlation (R) and coefficient of efficiency (CoE) values. The input variables selected by the elastic net produced the best performing ANN models. The ANN hybrid produced models performed only slightly better than the BRT models. The R values of the ANN elastic net and BRT models were 0.96 and 0.95 for PM₁₀, 0.96 and 0.96 for PM_2.5 and 0.89 and 0.87 for PNC, respectively. Their corresponding CoE values were 0.72 and 0.70 for PM₁₀, 0.74 and 0.76 for PM_2.5 and 0.81 and 0.71 for PNC respectively. About 80–99% of all the model predictions are within a factor of two of the observed particle concentrations. The BRT models offer more advantages regarding model interpretation and permit feature selection. Therefore, the study recommends the use of BRT over ANN where the model interpretation is a priority.     

The performance evaluation of WinOSPM model for urban street canyons of Nantes in France

Air quality modelling is primarily the quantative approach. It is more difficult as it demands input data accuracy, uncertainties and the efficient methodologies to judge the extent of models accuracy. As a result, model validation has to be regarded as an integral part of the modelling process. Furthermore, models are often validated on a limited number of testcases therefore, appropriate evaluation procedure must be implemented to ensure these models will be applicable for various conditions. The study presented here was carried out to evaluate theWinOSPM (Preliminary version of windows based Operational Street Pollution Model) for air pollutants viz. CO, NO, NO₂, NO_x and C₆H₆ for three street canyons of Nantes (France) and for the three base years 1999, 2000, and 2001. Each street canyon selected for this study has typical and unidentical features. The rue de Strasbourg and Boulevard Victor Hugo have many building exceptions whereas rue Crébillon has not any. Application of the model above to the three street canyons revealed that WinOSPM could be used in the case when measurements are not available. This was justified from the results at rue Crébillon. The special interest was in the benzene modelled values as its content in fuel has been targeted to reduce to 1% for the years 2000 and onwards (from its 5% until the year 1999). The 50 to 70% reduction in the benzene concentrations is found for both the years i.e. in 2000 and 2001. This has further justified that air quality models are useful and interesting tools in optimising emission reduction strategies. Moreover, it is also the new pollutant added to the measurement campaign of Air Pays de la Loire (APL) for the city of Nantes. For benzene weekly averages are estimated from the hourly-modelled values for all the streets and compared with that of measurements. They are found in excellent agreement with each others. For other pollutants annual means and percentiles were compared. The statistical analysis was done to evaluate the models performance using index of agreement and correlation coefficient. The index of agreement (d) and correlation coefficient (r) for all the streets show that estimated concentration levels are in good agreement with that of measurements. From the index of agreements, it can be inferred that model has very less potential for errors. The models sensitivity to building-exceptions was also tested for the rue de Strasbourg. Results did not reflect this feature very well. It is perceived that the influence of this feature might have been suppressed in averaging the annual hourly values. This influence is apparently seen in hourly average time series variations. Finally, WinOSPM model was found a simple but very useful model. It could very well represent the detailed flow and dispersion conditions in urban streets.     

2013—2019年青岛市空气质量变化特征分析

为掌握滨海城市环境空气质量变化特征,为污染精准管控和打赢蓝天保卫战提供科学参考,以沿海重要中心城市青岛市为研究区域,基于青岛市9个国控空气监测点位监测结果,对2013—2019年青岛市6项空气污染物浓度监测结果进行分析,总结归纳青岛市空气质量时间变化特征。结果表明：2019年,青岛市空气质量超标,超标指标为颗粒物;青岛市2014年空气质量最差,2018年空气质量最好;2013—2019年,青岛市O₃浓度总体呈上升趋势,其余5项污染物浓度呈下降趋势;青岛市环境空气主要污染物是PM_2.5,其次是O₃;青岛市空气质量冬季差于其他季节,春节期间烟花爆竹燃放等人为活动使空气质量变差。     

Evaluation of the Trend of Air Quality in Taipei, Taiwan from 1994 to 2003

The data collected from the five air quality monitoring stations established by the Taiwan Environmental Protection Administration (TEPA) in Taipei City were analyzed to assess the changes in air quality. The analyses reveal that the air quality in Taipei City improved over the last decade from 1994 to 2003, as evidenced by the significant downward trends of the various primary air pollutant concentrations, such as CO, NO_X, SO₂, and PM₁₀. An air pollution fee was collected by TEPA in 1995, and several air pollution control measures were likewise taken to improve the air quality in Taiwan. However, although the extreme daily maximum O₃ concentrations occurred more frequently in earlier years and showed a downward trend, its moderately high concentrations increased annually in recent years. It implied that after the reduction of various primary pollutant concentrations, the effective reduction of O₃ pollution still remains an important issue.     

Local Air Quality Impacts due to Downwash Around Thermal Power Plants: Numerical Simulations of the Effect of Building Orientation

One of the primary adverse environmental impacts associated with power generation facilities and in particular thermal power plants is local air quality. When these plants are operated at inland areas the dry type cooling towers used may significantly increase ambient concentrations of air pollutants due to the building downwash effect. When one or more buildings in the vicinity of a point source interrupt wind flow, an area of turbulence known as a building wake is created. Pollutants emitted from relatively low level sources can be caught in this turbulence affecting their dispersion. In spite of the fact that natural gas-fired combined-cycle power plants have lower air emission levels compared to other power plants using alternative fossil fuel, they can still create significant local air pollution problems. In this paper, local air quality impacts of a natural gas-fired combined-cycle power plant located in a coastal area are compared with those of another natural gas-fired combined-cycle power plant having identical air emissions but located in an inland area taking into account differences in topography and meteorology. Additionally, a series of scenarios for the inland site have been envisaged to illustrate the importance of plant lay-out configurations paying particular attention to the building downwash effect. Model results showed that different geometrical configurations of the stacks and cooling towers will cause remarkable differences in ambient air pollutant concentrations; thus it is concluded that when selecting a plant site, a detailed site-specific investigation should be conducted in order to achieve the least possible ambient air pollution concentrations with the given emissions.     

Measurements of SO2, NO X and SPM in an industrial area at the Aegean coast of Turkey

Data from continuous measurements of SO₂ NO _x , suspended particulate matter (SPM) and meteorological parameters at seven sites around a highly industrialized region in the Aegean coast of Turkey, between July 15, 1991 to July 31, 1992 were used to evaluate spatial and temporal variations of air quality parameters. Low annual averages and insignificant differences between day and night concentrations were observed at stations far from sources. At stations close to sources, annual average concentrations were high and diurnal patterns were significant. Annual average SO₂ and SPM concentrations in all stations used the Krigging technique to assess the impact of industries on air quality in the surrounding airshed. Results have demonstrated that Turkish air quality standards for SO₂ were exceeded in a circle with a radius of 4 km and which was centered on the petrochemical complex and refinery. Similarly, standards for SPM were exceeded in a circle with a radius of 1.2 km and which was centered on the ironwork plants. Both SO₂ and SPM showed well defined diurnal variations, particularly in stations close to sources. The SO₂ concentrations showed a maximum during day-time, while SPM concentrations peaked after midnight. Although annual average SO₂ and SPM concentrations were highly variable depending on distances between stations and sources, background concentrations of the same pollutants, calculated by stripping episodes from data, did not change significantly from one station to another. Long range transport and resuspension of local soil were suggested as sources of background SO₂ and SPM, respectively. The difference between observed and background concentrations of SO₂ and SPM in each station was related to the impact of industries on air quality at that particular site.     

Air quality and ventilation fan control based on aerosol measurement in the bi-directional undersea Bømlafjord tunnel

Aerosol, NO and CO concentration, temperature, air humidity, air flow and number of running ventilation fans were measured by continuous analysers every minute for a whole week for six different one-week periods spread over ten months in 2001 and 2002 at measuring stations in the 7860 m long tunnel. The ventilation control system was mainly based on aerosol measurements taken by optical scatter sensors. The ventilation turned out to be satisfactory according to Norwegian air quality standards for road tunnels; however, there was some uncertainty concerning the NO2 levels. The air humidity and temperature inside the tunnel were highly influenced by the outside metrological conditions. Statistical models for NO concentration were developed and tested; correlations between predicted and measured NO were 0.81 for a partial least squares regression (PLS1) model based on CO and aerosol, and 0.77 for a linear regression model based only on aerosol. Hence, the ventilation control system should not solely be based on aerosol measurements. Since NO2 is the hazardous polluter, modelling NO2 concentration rather than NO should be preferred in any further optimising of the ventilation control.