Simulation of PM<Subscript>10</Subscript> concentration patterns for a 2010 traffic scenario in Bologna,Italy

Three state of the art traffic–emission–dispersion models dealing with particulate matter have been tested and validated over the Bologna metropolitan area with 2001 data and a future scenario has been developed in order to estimate expected PM concentrations in 2010. The modelling system is composed by a traffic model (VISUM) evaluating vehicle fluxes as a function of mobility demand and road network in the area, an emission model (Trefic) estimating pollutants emitted in atmosphere as a function of vehicle fluxes amount and composition and of environmental conditions and a dispersion model (ADMS) evaluating PM concentrations on the area, given the meteorological variables. The three models compose a cascade sequence and results of the previous one feed the next one. PM concentrations computed by the model suite for the town of Bologna, in northern Italy, for the reference period (January 2001) have been compared with air quality stations measurements suggesting the modelling system being especially suitable for evaluating traffic induced PM. Qualitative and quantitative changes in the circulating vehicle fleet have been supposed in order to obtain a realistic scenario for year 2010. Forecasted concentrations have been then compared with limits fixed by current EU legislation for particulate matter.     

Air pollution exposure monitoring and estimation. Part IV. Urban exposure in children

In the winter of 1994, 2300 school-age children in Oslo participated in a panel study of the role of traffic pollution on the exacerbation of diseases of the respiratory system and other symptoms of reduced health and well being in children. The children filled out a diary daily with information for five time points over six weeks. In order to quantify exposure-effect relationships for the symptoms, individual exposure to NO2 and particulate matter (PM2.5) was estimated, using the DINEX method a combination of information from the diary as to the children's whereabouts during the five time points each day, coupled with continuous dispersion modelling. An individual exposure estimate for each time point for each child was defined. Individual exposure estimated using dispersion modelling can be used to examine patterns of exposure such as isolating geographic areas with higher concentrations or describing concentrations of pollution by time of day. The diary allowed the time-use of the children to be described.     

公路隧道可吸入颗粒物扩散模型研究

运用大气扩散理论,得到了隧道内自然通风和纵向通风状态下的可吸入颗粒物(PM10)扩散模型,并由隧道口PM10浓度、隧道截面积、隧道内风速,以及车流量和类型等参数,获得了整条隧道内的不同PM10浓度分布.模型表明,随着隧道深度的增加,PM10浓度逐渐增大.通过采用纵向通风的玄武湖隧道各参数,得到了3组不同条件下的PM10扩散模型,并用所得模型计算了隧道内不同深度处PM10的浓度.沿隧道不同深度测得的PM10浓度值的比较结果表明,实际测定值围绕计算值上下波动,两者之间具有良好的一致性.     

Dispersion in Urban Environments; Comparison of Field Measurements with Wind Tunnel Results

A wind tunnel study was performed to determine the dispersion characteristics of vehicle exhaust gases within the urban canopy layer. The results were compared with those from a field monitoring station located in a street canyon with heavy traffic load. The agreement found was fair. In the second part of the paper it is shown how wind tunnel data can be utilized to supplement and thereby enhance the value of field data for model validation purposes. Uncertainty ranges were quantified which are inherent to mean concentration values measured in urban streets.     

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.     

Assessing PM10 source reduction in urban agglomerations for air quality compliance

The objective of this work was to study PM(10) and PM(2.5) concentration data available from monitoring stations in two large urban agglomerations in Greece and to estimate the emissions reduction required for compliance with the EU Air Quality Standards (AQS) for particulate matter. The cities studied are namely the Athens and Thessaloniki Metropolitan Areas (AMA and TMA, respectively). PM(10) concentrations during the period 2001-2010 have been evaluated for 15 air quality monitoring stations in the two urban areas. It was found that the concentrations of PM(10) during the period studied constantly exceeded the threshold values at the traffic and industrial stations in TMA and most of the traffic sites in AMA. Most of the occurrences of non-attainment to the daily AQSs were observed during the winter period at all stations (more pronounced for TMA stations). The reduction in current emission source strength to meet the air quality goal was calculated by the rollback equation using PM(10) day-averaged concentrations over the selected period at each station. Among the lognormal and Weibull distributions, the lognormal distribution was found to best fit the frequency distributions of PM(10) concentrations at the selected stations. The results showed that the minimum reduction required in order to meet the AQS in the AMA ranges from approximately 20 to 38% and up to 11% for traffic and background stations, respectively. Reductions in the range of 31% for traffic and 44% for industrial areas in TMA are also required. The same methodology was applied to PM(2.5) concentrations in the AMA and showed that emission reductions up to 31% are necessary in order to meet the 2020 EU AQS. Finally, continuous concentration data of organic (OC) and elementary carbon (EC) in PM(2.5) were used to study the possibility of achieving specific emission attenuation objectives in AMA.     

广州市空气可吸入性颗粒物的污染水平

报告了中美合作“广州市大气污染对儿童肺功能影响研究”课题可吸入性颗粒物的两年监测结果。用安德森双道采样器、Ｔｅｆｌｏｎ膜采集细颗粒物（＜２５μｍ,ＰＭ２５）和粗颗粒物（２５≤＜１０μｍ,ＰＭ２５１０）,两者之和为ＰＭ１０,每季度采１５天,每天采一个２４小时样品。结果表明,广州市城区大气可吸入性颗粒物的污染相当严重,尤其是细颗粒物（ＰＭ２５）的污染,应引起公众和政府有关部门的重视。     

System Dynamics Modeling and Policy Simulation for Urban Traffic: a Case Study in Beijing

This paper constructs a system dynamics model for simulating the impact of different strategies on urban traffic’s energy consumption and carbon emissions. Based on a case study in Beijing, the model includes three subsystems: (1) urban traffic, (2) population and economy, and (3) energy consumption and carbon emissions. First, the model is used to decompose the impact of different vehicles on energy consumption and carbon emissions. Decomposition results show that private cars have the most significant impact on urban traffic’s energy consumption and carbon emissions; however, total vehicle kilometers traveled by private cars are the smallest among four trip modes. Then, the model is used to simulate different urban traffic policies. Policies are categorized as follows: (a) driving restrictions on vehicle registration numbers, (b) a scheme for vehicle registrations via a lottery system, and (c) development of public transportation infrastructures. Scenario simulation results show that all those measures can reduce energy consumption and carbon emissions. Though the last strategy (c) contains several delays, its effect is more stable and far-reaching. Finally, some recommendations about easing traffic pressure and reducing traffic emissions are given.     

A land use regression model for predicting ambient fine particulate matter across Los Angeles, CA

Land use regression (LUR) models have been used successfully for predicting local variation in traffic pollution, but few studies have explored this method for deriving fine particle exposure surfaces. The primary purpose of this method is to develop a LUR model for predicting fine particle or PM(2.5) mass over the five county metropolitan statistical area (MSA) of Los Angeles. PM(2.5) includes all particles with diameter less than or equal to 2.5 microns. In the Los Angeles MSA, 23 monitors of PM(2.5) were available in the year 2000. This study uses GIS to integrate data regarding land use, transportation and physical geography to derive a PM(2.5) dataset covering Los Angeles. Multiple linear regression was used to create the model for predicting the PM(2.5) surface. Our parsimonious model explained 69% of the variance in PM(2.5) with three predictors: (1) traffic density within 300 m, (2) industrial land area within 5000 m, and (3) government land area within 5000 m of the monitoring site. These results suggest the LUR method can refine exposure models for epidemiologic studies in a North American context.     

Indoor and outdoor concentrations of fine particles, particle-bound PAHs and volatile organic compounds in Kaunas, Lithuania

This complex study presents indoor and outdoor levels of air-borne fine particles, particle-bound PAHs and VOCs at two urban locations in the city of Kaunas, Lithuania, and considers possible sources of pollution. Two sampling campaigns were performed in January-February and March-April 2009. The mean outdoor PM(2.5) concentration at Location 1 in winter was 34.5 ± 15.2 μg m(-3) while in spring it was 24.7 ± 12.2 μg m(-3); at Location 2 the corresponding values were 36.7 ± 21.7 and 22.4 ± 19.4 μg m(-3), respectively. In general there was little difference between the PM concentrations at Locations 1 and 2. PM(2.5) concentrations were lower during the spring sampling campaign. These PM concentrations were similar to those in many other European cities; however, the levels of most PAHs analysed were notably higher. The mean sum PAH concentrations at Locations 1 and 2 in the winter campaign were 75.1 ± 32.7 and 32.7 ± 11.8 ng m(-3), respectively. These differences are greater than expected from the difference in traffic intensity at the two sites, suggesting that there is another significant source of PAH emissions at Location 1 in addition to the traffic. The low observed indoor/outdoor (I/O) ratios indicate that PAH emissions at the locations studied arise primarily from outdoor sources. The buildings at both locations have old windows with wooden frames that are fairly permissive in terms of air circulation. VOC concentrations were mostly low and comparable to those reported from Sweden. The mean outdoor concentrations of VOC's were: 0.7 ± 0.2, 3.0 ± 0.8, 0.5 ± 0.2, 3.5 ± 0.3, and 0.2 ± 0.1 μg m(-3), for benzene, toluene, ethylbenzene, sum of m-, p-, o-xylenes, and naphthalene, respectively. Higher concentrations of VOCs were observed during the winter campaign, possibly due to slower dispersion, slower chemical transformations and/or the lengthy "cold start" period required by vehicles in the wintertime. A trajectory analysis showed that air masses coming from Eastern Europe carried significantly higher levels of PM(2.5) compared to masses from other regions, but the PAHs within the PM(2.5) are of local origin. It has been suggested that street dust, widely used for winter sanding activities in Eastern and Central European countries, may act not only as a source of PM, but also as source of particle-bound PAHs. Other potential sources include vehicle exhaust, domestic heating and long-range transport.     

A case study predicting environmental impacts of urban transport planning in China

Predicting environmental impacts is essential when performing an environmental assessment on urban transport planning. System dynamics (SD) is usually used to solve complex nonlinear problems. In this study, we utilized system dynamics (SD) to evaluate the environmental impacts associated with urban transport planning in Jilin City, China with respect to the local economy, society, transport, the environment and resources. To accomplish this, we generated simulation models comprising interrelated subsystems designed to utilize changes in the economy, society, road construction, changes in the number of vehicles, the capacity of the road network capacity, nitrogen oxides emission, traffic noise, land used for road construction and fuel consumption associated with traffic to estimate dynamic trends in the environmental impacts associated with Jilin's transport planning. Two simulation scenarios were then analyzed comparatively. The results of this study indicated that implementation of Jilin transport planning would improve the current urban traffic conditions and boost the local economy and development while benefiting the environment in Jilin City. In addition, comparative analysis of the two scenarios provided additional information that can be used to aid in scientific decision-making regarding which aspects of the transport planning to implement in Jilin City. This study demonstrates that our application of the SD method, which is referred to as the Strategic Environmental Assessment (SEA), is feasible for use in urban transport planning.     

Measurement and Interpretation of Concentrations of Urban Atmospheric Organic Compounds

The presence of volatile organic compounds (VOCs) from traffic and other sources in urban areas is a cause for concern about public health. Canister, chemical derivatisation, particulate sampling and adsorption sampling techniques were used to measure VOC concentrations of a wide range of compounds (C6-C40) during a four day campaign in south London with subsequent laboratory analysis of the samples. Compounds quantified included alkanes, mono- and poly-nuclear aromatic hydrocarbons. Also the first sequential measurements of carbonyl compounds (C1-C8) in a UK urban area are presented. Results from canister and adsorption sampling methods are compared. A comparison of the results with other urban data is presented and the temporal variations in VOC concentrations were interpreted with reference to the prevalent wind speeds and directions. The CALINE4 line source dispersion model was generally successful in reproducing the daytime 12 hour average concentrations of selected VOCs.     

百色市冬季PM2.5传输路径及来源分析

通过采用后向轨迹结合聚类分析方法计算2015—2016年百色市PM2.5潜在源贡献因子(PSCF)和浓度权重轨迹(CWT),分析影响该市冬季PM2.5质量浓度的潜在源区,并探讨不同源区对PM2.5的贡献率。同时,使用CAMx模式模拟百色市各县区及周边区域对该市大气传输的影响。结果表明,影响百色市PM2.5浓度潜在源主要集中在该市和临近的河池、南宁、崇左,以及北部的贵州省;CAMx模式模拟对百色市冬季大气污染物传输的地区来源与该市大气污染物的PSCF分析和CWT分析权重较大的区域较为一致,这些区域对百色市PM2.5的贡献率达73%。     

Integrated Traffic and Emission Simulation: a Model Calibration Approach Using Aggregate Information

Environmental impacts of road traffic have attracted increasing attention in project-level traffic planning and management. The conventional approach considers emission impact analysis as a separate process in addition to traffic modeling. This paper first introduces our research effort to integrate traffic, emission, and dispersion processes into a common distributed computational framework, which makes it efficient to quantify and analyze correlations among dynamic traffic conditions, emission impacts, and air quality consequences. A model calibration approach is particularly proposed when on-road or in-lab instantaneous emission measurements are not directly available. Microscopic traffic simulation is applied to generate dynamic vehicle states at the second-by-second level. Using aggregate emission estimation as standard reference, a numerical optimization scheme on the basis of a stochastic gradient approximation algorithm is applied to find optimal parameters for the dynamic emission model. The calibrated model has been validated on several road networks with traffic states generated by the same simulation model. The results show that with proper formulation of the optimization objective function, the estimated dynamic emission model can capture the trends of aggregate emission patterns of traffic fleets and predict local emission and air quality at higher temporal and spatial resolutions.     

Mann–Kendall trend of pollutants,temperature and humidity over an urban station of India with forecast verification using different ARIMA models

The purpose of the present research is to identify the trends in the concentrations of few atmospheric pollutants and meteorological parameters over an urban station Kolkata (22° 32′ N; 88° 20′ E), India, during the period from 2002 to 2011 and subsequently develop models for precise forecast of the concentration of the pollutants and the meteorological parameters over the station Kolkata. The pollutants considered in this study are sulphur dioxide (SO₂), nitrogen dioxide (NO₂), particulates of size 10-μm diameters (PM₁₀), carbon monoxide (CO) and tropospheric ozone (O3). The meteorological parameters considered are the surface temperature and relative humidity. The Mann–Kendall, non-parametric statistical analysis is implemented to observe the trends in the data series of the selected parameters. A time series approach with autoregressive integrated moving average (ARIMA) modelling is used to provide daily forecast of the parameters with precision. ARIMA models of different categories; ARIMA (1, 1, 1), ARIMA (0, 2, 2) and ARIMA (2, 1, 2) are considered and the skill of each model is estimated and compared in forecasting the concentration of the atmospheric pollutants and meteorological parameters. The results of the study reveal that the ARIMA (0, 2, 2) is the best statistical model for forecasting the daily concentration of pollutants as well as the meteorological parameters over Kolkata. The result is validated with the observation of 2012.     

Air quality of Prague: traffic as a main pollution source

Political and economical transition in the Central and Eastern Europe at the end of eighties significantly influenced all aspects of life as well as technological infrastructure. Collapse of outdated energy demanding industry and adoption of environmental legislation resulted in seeming improvements of urban environmental quality. Hand in hand with modernization the newly adopted regulations also helped to phase out low quality coal frequently used for domestic heating. However, at the same time, the number of vehicles registered in the city increased. The two processes interestingly acted as parallel but antagonistic forces. To interpret the trends in urban air quality of Prague, Czech capital, monthly averages of PM(10), SO(2), NO(2), NO, O(3) and CO concentrations from the national network of automated monitoring stations were analyzed together with long term trends in fuel consumption and number of vehicles registered in Prague within a period of 1992-2005. The results showed that concentrations of SO(2) (a pollutant strongly related to fossil fuel burning) dropped significantly during the period of concern. Similarly NO(X) and PM(10) concentrations decreased significantly in the first half of the nineties (as a result of solid fuel use drop), but remained rather stable or increased after 2000, presumably reflecting rapid increase of traffic density. In conclusion, infrastructural changes in early nineties had a strong positive effect on Prague air quality namely in the first half of the period studied, nevertheless, the current trend in concentrations of automotive exhaust related pollutants (such as PM(10), NO(X)) needs adoption of stricter measures.     

A Statistical Analysis of Particulate Data Sets for Jawaharlal Nehru Port and Surrounding Harbour Region in India

The concentrations of total suspended particulate matter (TSP) and particulate matter less than 10 microns (PM10) were measured at various locations in a Jawaharlal Nehru port and surrounding harbour region. Meteorological data was also collected to establish the correlation with air pollutant concentration. The results are analysed from the standpoint of monthly and seasonal variations, annual trends as well as meteorological effects. The monthly mean concentration of TSP was in the range of 88.2 to 199.3 microg m(-3). The maximum and minimum-recorded value of PM10 was 135.8 and 20.3 microg m(-3), respectively. The annual average concentration of PM10 was 66.1 microg m(-3). There are clear associations between TSP and PM10 data set at all the measured three sites with a correlation coefficient of 0.89, 0.69 and 0.81, respectively. PM10 data appears to be a constant fraction of the TSP data throughout the year, indicating common influences of meteorology and sources. Particle size analysis showed PM10 to be 47% of the total TSP concentration, which is lower than reported for industrial area and traffic junctions in Mumbai. Anthropogenic sources contribute significantly to the PM10 fraction in an industrial region, while contributions from natural sources are more in a port and harbour area. Statistical analysis of air quality data shows that TSP is strongly correlated with wind speed but weakly correlated with temperature. There appears to be a simple inverse relationship between TSP and wind speed data, indicating the dilution and transport by winds.     

Evaluation of the urban/rural particle-bound PAH and PCB levels in the northern Spain (Cantabria region)

The aim of the present study was to evaluate the polycyclic aromatic hydrocarbon (PAH) and polychlorinated biphenyl (PCB) levels in PM(10) and PM(2.5), at one rural and three urban sites in the Cantabria region (northern Spain). From all of these pollutants, benzo(a)pyrene is regulated by the EU air quality directives; its target value (1?ng/m(3)) was not exceeded. The concentration values of the studied organic pollutants at the studied sites are in the range of those obtained at other European sites. A comparison between the rural-urban stations was developed: (a) PAH concentration values were lower in the rural site (except for fluorene). Therefore, the contribution of local sources to the urban levels of PAHs seems relevant. Results from the coefficient of divergence show that the urban PAH levels are influenced by different local emission sources. (b) PCB rural concentration values were higher than those found at urban sites. Because no local sources of PCBs were identified in the rural site, the contribution of more distant emission sources (about 40?km) to the PCB levels is considered to be the most important; the long-range transport of PCBs does not seem to be significant. Additionally, local PAH tracers were identified by a triangular diagram: higher molecular weight PAHs in Reinosa, naphthalene in Santander and anthracene/pyrene in Castro Urdiales. A preliminary PAH source apportionment study in the urban sites was conducted by means of diagnostic ratios. The ratios are similar to those reported in areas affected by traffic emissions; they also suggest an industrial emission source at Reinosa.     

Speciation and sources of atmospheric aerosols in a highly industrialised emerging mega-city in central China

Monitoring air quality in large urban agglomerations is the key to the prevention of air pollution-related problems in emerging mega-cities. The city of Wuhan is a highly industrialised city with >9 million inhabitants in Central China. Simultaneous PM10 sampling was performed during 1 year at one urban and one industrial site. Mean PM10 daily levels (156 microg m(-3) at the urban site and 197 microg m(-3) at the industrial hotspot) exceed the US-EPA or EU annual limit values by 3-4 times. A detailed study of daily speciation showed that the mean chemical composition of PM10 presents minimal differences between peak and low PM episodes. This implies that PM10 aerosols in the study area result from local emissions, and air quality management and abatement strategies in Wuhan should thus focus on local anthropogenic sources. The levels of some elements of environmental concern are relatively high (409-615 ngPb m(-3), 66-70 ngAs m(-3), 116-227 ngMn m(-3), 10-12 ngCd m(-3)) due to industrial, but also urban emissions. Principal component analysis identified a mineral source (probably cement and steel manufacture) and smelting as the main contributors to PM10 levels at the industrial site (34%), followed by a coal fired power plant (20%) and the anthropogenic regional background (16%). At the urban site the major PM10 source is a mixed coal combustion source (31%), followed by the anthropogenic regional background (28%) and traffic (16%).     

Spatiotemporal analysis of the PM10 concentration over the Taranto area

In this paper, an analysis of air quality data is provided for the municipal area of Taranto (southern Italy) characterized by high environmental risks as formally decreed by the Italian government in the 1990s with two administrative measures. This is due to the massive presence of industrial sites with elevated environmental impact activities along the NW boundary of the city conurbation. The aforementioned activities have effects on the environment and on public health, as a number of epidemiological researches concerning this area reconfirm. The present study is focused on particulate matter as measured by PM10 concentrations at 13 monitoring stations, equipped with analogous instruments based on the Beta absorption technology, either reporting hourly, two-hourly, or daily measurements. Daily estimates of the PM10 concentration surfaces are obtained in order to identify areas of higher concentration (hot spots), possibly related to specific anthropic activities. Preliminary analysis involved addressing several data problems: (1) due to the use of two different validation techniques, a calibration procedure was devised to allow for data comparability; (2) imputation techniques were considered to cope with the large number of missing data, due to both different working periods and occasional malfunctions of PM10 sensors; and (3) reliable weather covariates (wind speed and direction, pressure, temperature, etc.) were obtained and considered within the analysis. Spatiotemporal modelling was addressed by a Bayesian kriging-based model proposed by Le and Zidek (2006) characterized by the use of time varying covariates and a semiparametric covariance structure. Advantages and disadvantages of the model are highlighted and assessed in terms of fit and performance. Estimated daily PM10 concentration surfaces are suitable for the interpretation of time trends and for identifying concentration peaks within the urban area.