Showing papers on "Air pollutant concentrations published in 2009"

Use of a mobile laboratory to evaluate changes in on-road air pollutants during the Beijing 2008 Summer Olympics

Abstract: . China implemented systematic air pollution control measures during the 2008 Beijing Summer Olympics and Paralympics to improve air quality. This study used a versatile mobile laboratory to conduct in situ monitoring of on-road air pollutants along Beijing's Fourth Ring Road on 31 selected days before, during, and after the Olympics air pollution control period. A suite of instruments with response times of less than 30 s was used to measure temporal and spatial variations in traffic-related air pollutants, including NOx, CO, PM1.0 surface area (S(PM1)), black carbon (BC), and benzene, toluene, the sum of ethylbenzene, and m-, p-, and o-xylene (BTEX). During the Olympics (8–23 August, 2008), on-road air pollutant concentrations decreased significantly, by up to 54% for CO, 41% for NOx, 70% for SO2, 66% for BTEX, 12% for BC, and 18% for SPM1, compared with the pre-control period (before 20 July). Concentrations increased again after the control period ended (after 20 September), with average increases of 33% for CO, 42% for NOx, 60% for SO2, 40% for BTEX, 26% for BC, and 37% for S(PM1), relative to the control period. Variations in pollutants concentrations were correlated with changes in traffic speed and the number and types of vehicles on the road. Throughout the measurement periods, the concentrations of NOx, CO, and BTEX varied markedly with the numbers of light- and medium-duty vehicles (LDVs and MDVs, respectively) on the road. Only after 8 August was a noticeable relationship found between BC and S(PM1) and the number of heavy-duty vehicles (HDVs). Additionally, BC and S(PM1) showed a strong correlation with SO2 before the Olympics, indicating possible industrial sources from local emissions as well as regional transport activities in the Beijing area. Such factors were identified in measurements conducted on 6 August in an area southwest of Beijing. The ratio of benzene to toluene, a good indicator of traffic emissions, shifted suddenly from about 0.26 before the Olympics to approximately 0.48 after the Olympics began. This finding suggests that regulations on traffic volume and restrictions on the use of painting solvents were effective after the Olympics began. This study demonstrated the effectiveness of air pollution control measures and identified local and regional pollution sources within and surrounding the city of Beijing. The findings will be invaluable for emission inventory evaluations and model verifications.

Prediction of hourly air pollutant concentrations near urban arterials using artificial neural network approach

Abstract: This paper applies artificial neural network to predict hourly air pollutant concentrations near an arterial in Guangzhou, China. Factors that influence pollutant concentrations are classified into four categories: traffic-related, background concentration, meteorological and geographical. The hourly averages of these influential factors and concentrations of carbon monoxide, nitrogen dioxide, particular matter and ozone were measured at three selected sites near the arterial using vehicular automatic monitoring equipments. Models based on back-propagation neural network were trained, validated and tested using the collected data. It is demonstrated that the models are able to produce accurate prediction of hourly concentrations of the pollutants respectively more than 10 h in advance. A comparison study shows that the neural network models outperform multiple linear regression models and the California line source dispersion model.

Prev'air: An Operational Forecasting and Mapping System for Air Quality in Europe

Abstract: The current state of the art in three-dimensional chemistry-transport models allows them to be considered as mature and reliable enough to be combined with observations networks for implementing integrated air quality monitoring systems over large territories. A cooperative initiative of four research and operational organizations in France has led to the creation of an integrated air quality platform providing near-real-time and forecasted information using last model developments. Since summer 2003, this system, Previsions et Observations de la Qualite de l'Air en France et en Europe (PREV'AIR; available online at www.prevair.org), has been delivering daily air quality observations short-term (0-3 days) forecasts, and real-time analyses of ozone, nitrogen dioxide, and particulate matter (PM) at the global and European scales, with a focus over France. It has become a powerful scientific and communication tool to inform the public, sensitive population about the potential occurrence of air pollutant concentrations exceeding regulatory thresholds. The architecture of the operational system is described in this paper. Its setup allows the partners to cope with stringent operational constraints regarding the timely availability of the forecasts and the reliability and the quality of the products delivered. The system relies on a chain of numerical models and methods, and on real-time air quality observations. It uses National Centers for Environmental Predictions (NCEP) and Meteo-France weather forecasts. Methods used for producing air pollutant concentration forecasts and analyses are described, as well as the final products, with case examples. A synthesis of the operational system skill results obtained over three consecutive years of operation (2003-06) is given. Lessons learned are presented and issues related to the use of the PREV'AIR system as a complementary tool for air quality management are discussed.

The social distribution of neighborhood-scale air pollution and monitoring protection.

Abstract: The potential for inequities between population subgroups in air pollution exposures and in regulatory protection because of small-scale intraurban differences in outdoor air pollution and air quality monitoring are studied here. The focus subgroups are blacks, Hispanics, whites, and the population living below poverty, with Tampa, FL, used as the case study area for quantitative analyses. A geographical database is developed for the surrounding county that includes population demographics, source locations, monitor locations, and air pollutant concentrations. Data included are residential population demographics at the block-group spatial scale from the year 2000 U.S. Census, U.S. Environmental Protection Agency (EPA) Toxic Releases Inventory source locations and air source release amounts, EPA Air Quality System monitoring data, and Florida major highway source locations and roadway traffic data. This database is applied for analysis of the spatial relationships between residence locations of population subgroups and outdoor air pollution surrogates. A quantitative index to evaluate the inequity between subpopulations is developed and applied. Findings include that blacks, Hispanics, and people living in poverty are disproportionately living closer to sources of air pollution and further from regulatory air quality monitoring sites compared with the overall county population. Conversely, whites are disproportionately living away from sources and near monitoring sites. Analysis of the regulatory monitoring guidelines indicates that recent changes in those guidelines may exacerbate existent inequities. The results suggest disparities in exposures to air pollution, disparities in regulatory monitoring representation, and the need for more monitoring and analyses at smaller spatial scales.

Multi-year assessment of photochemical air quality simulation over Spain

Abstract: Ground-level ozone concentrations in the atmospheric boundary layer over Spain are still exceeding thresholds established in EU legislation to protect human health and prevent damage to ecosystems. The increasing role that air quality models play in air quality management requires comparison between model results and previous observations in order to determine the capacity of the model to reproduce past events. The CHIMERE chemistry-transport model has been used by several research groups to estimate air pollutant concentrations in different European countries. An evaluation of the model performance of the CHIMERE air quality model was carried out for the spring and summer periods of 2003-2005 in Spain, using EMEP emissions. This evaluation has demonstrated a fair agreement between observed and modelled ozone values for background stations, with a mean normalized absolute error below 15% for rural background air quality sites. This value lays inside the range proposed in EPA's guideline for an acceptable level of model performance. In spite of this acceptable model performance, further studies need to be carried out to explain some underestimation found over Madrid surroundings.

Air Pollution and Survival within the Washington University-EPRI Veterans Cohort : Risks Based on Modeled Estimates of Ambient Levels of Hazardous and Criteria Air Pollutants

Abstract: For this paper, we considered relationships between mortality, vehicular traffic density, and ambient levels of 12 hazardous air pollutants, elemental carbon (EC), oxides of nitrogen (NOx), sulfur dioxide (SO2), and sulfate (SO4(2-)). These pollutant species were selected as markers for specific types of emission sources, including vehicular traffic, coal combustion, smelters, and metal-working industries. Pollutant exposures were estimated using emissions inventories and atmospheric dispersion models. We analyzed associations between county ambient levels of these pollutants and survival patterns among approximately 70,000 U.S. male veterans by mortality period (1976-2001 and subsets), type of exposure model, and traffic density level. We found significant associations between all-cause mortality and traffic-related air quality indicators and with traffic density per se, with stronger associations for benzene, formaldehyde, diesel particulate, NOx, and EC. The maximum effect on mortality for all cohort subjects during the 26-yr follow-up period is approximately 10%, but most of the pollution-related deaths in this cohort occurred in the higher-traffic counties, where excess risks approach 20%. However, mortality associations with diesel particulates are similar in high- and low-traffic counties. Sensitivity analyses show risks decreasing slightly over time and minor differences between linear and logarithmic exposure models. Two-pollutant models show stronger risks associated with specific traffic-related pollutants than with traffic density per se, although traffic density retains statistical significance in most cases. We conclude that tailpipe emissions of both gases and particles are among the most significant and robust predictors of mortality in this cohort and that most of those associations have weakened over time. However, we have not evaluated possible contributions from road dust or traffic noise. Stratification by traffic density level suggests the presence of response thresholds, especially for gaseous pollutants. Because of their wider distributions of estimated exposures, risk estimates based on emissions and atmospheric dispersion models tend to be more precise than those based on local ambient measurements.

Using a sub-grid scale modeling approach to simulate the transport and fate of toxic air pollutants

Abstract: Several air toxics are emitted from mobile sources on roadways and these emissions account for a significant fraction of the health risks to the population. In addition, health effect studies are now becoming more comprehensive and some account for the spatial heterogeneities of air pollutant concentration fields (as is the case near roadways). Standard models can simulate either the near-source concentration fields or the urban background, but no model can handle both spatial scales in the vicinity of roadways in a coherent and scientifically correct manner. Here, we present a model that provides such an integrated treatment by combining a grid-based air quality model of the urban background with a plume-in-grid representation of roadway emissions. The model is applied to simulate near-roadway concentrations due to emissions from a busy interstate highway in New York City. Qualitative comparisons with typical measured concentration profiles show that the model captures the observed features of toxic air pollutant concentrations near roadways.

MODIS and OMI satellite observations supporting air quality monitoring.

Abstract: Within the framework of air quality monitoring, measurements by Earth-observing satellite sensors are combined here with regional meteorological and chemical transport models. Two satellite-derived products developed within the QUITSAT project, regarding significant pollutants including PM2.5 and NO2, are presented. Estimates of PM2.5 concentrations at ground level were obtained using moderate resolution imaging spectroradiometer (Terra-Aqua/NASA) aerosol optical properties. The semi-empirical approach adopted takes into account PM2.5 sampling and meteorological descriptions of the area studied, as simulated by MM5, to infer aerosol optical properties to PM projection coefficients. Daily maps of satellite-based PM2.5 concentrations over northern Italy are derived. Monthly average values were compared with in situ PM2.5 samplings showing good agreement. Ozone monitoring instrument (OMI) (Aura/NASA) NO2 tropospheric contents are merged using the GAMES chemical model simulations. The method employs a weighted rescaling of the model column in the troposphere according to the OMI observations. The weightings take into account measurement errors and model column variances within the satellite ground pixel. The obtained ground-level concentrations of NO2 show good agreement with the environmental agencies’ in situ. The capabilities of Earth observation satellites have greatly improved over the last few years, with gradual improvements in temporal and spatial resolutions and enhancements in radiometric accuracy, thus encouraging further studies on the use of satellite data to assess air quality (AQ). Within this context, the synoptic view and the daily repetition cycle of satellite-based measurements strengthen the potential for monitoring air pollution transport and directly evaluating the spatial distribution of various air pollutant concentrations. These evaluations are in compliance with the regulations of

Statistical analysis of meteorological factors and air pollution at winter months in elazig, turkey

Abstract: In the present study, relationship between monitored air pollutant concentrations such as SO2 and the total suspended particles (TSP) data and meteorological factors such as wind speed, temperature, relative humidity and atmospheric pressure was investigated in months of October, November, December, January, February, and March during the period of three years (2003, 2004 and 2005) for Elazig city. According to the results of linear and non-linear regression analysis, it was found that there is a moderate and weak level of relation between the air pollutant concentrations and the meteorological factors in Elazig city.

Two impact related air quality indices as tools to assess the daily and long-term air pollution

Abstract: The methodology of the recently developed Daily Air Quality Index (DAQx) and Long-term Air Quality Index (LAQx) is explained. Both indices consider air pollutants frequently monitored at long-term stations within official air pollution control networks. Therefore, they enable an assessment of the integral air pollution, which reflects the ambient air consisting of a mixture of air pollutants more realistic. Both air quality indices are impact related with respect to people. On the basis of results of extensive investigations in environmental medicine and toxicology, they quantify the impacts of a mixture of air pollutants, which is typical of the ambient air, on well-being and health of people in the form of six index classes and ranges of index values, respectively. To analyse the sensitivity of DAQx and LAQx, air pollutant data for the period 1995-2003 were used. They originate from selected stations within the official air pollution monitoring network in the South-West of Germany, which are characterised by different emission conditions.

Measuring public health accountability of air quality management

Abstract: Accountability of air quality management is often measured by tracking ambient pollution concentrations over time. These changes in ambient air quality are rarely linked to changes in public health, a major driver for such programs. We propose a method to assess the accountability of air quality management programs with respect to improvements in public health by estimating national temporal trends in health risk attributable to air pollution. The air health indicator (AHI) is a function of two temporal functions, annual air pollutant concentrations and annual estimates of health risk obtained by time series statistical methods, to indicate the trend in annual percent attributable risk (the product of concentration and risk times 100). Random effects models are used to obtain a distribution of risk over space. The model is illustrated by examining the association between daily nonaccidental deaths in 24 of Canada’s largest cities and daily concentrations of ozone and nitrogen dioxide over the 17-year period 1984–2000. Our analysis demonstrates that examining trends in exposure alone, which has typically been the approach to air quality indicators, provides an incomplete picture of trends in the impact of air pollution. The AHI appears to provide a more informative measure of the population burden of illness associated with air pollution over time.

Seasonal variations of air pollutant concentrations within Krasnoyarsk City.

Abstract: This paper examines the significant differences in seasonal variations of criteria pollutant concentrations in various parts of a large urban area. These differences are caused by the microclimatic heterogeneity of the city and show the influence of breeze and orographic-type circulations on urban air pollution. The temperature heterogeneity of Krasnoyarsk territory during the winter leads to an increase of 150% in CO air pollution levels in the central part of city. During the summer the orographical heterogeneity of Krasnoyarsk City leads to increases of up to 400% in air pollution for different areas.

Can traffic-related air pollution cause asthma?

Abstract: Traffic-generated pollution contains particles and gases (eg, oxides of nitrogen) that are known to have health effects.1 Concentrations of pollutants emitted by motor vehicles are highest within 150 m of roadways and remain raised up to 300 m from roadways, but fall off markedly beyond that range.2 3 Exposure to the mixture of traffic-generated pollutants may be more relevant to human health than exposure to any single ambient air pollutant, making epidemiological investigations of traffic effects a key component of research into the public health impact of air pollution. However, assessment of exposure to traffic-related air pollution can be problematic. Exposure to traffic can be estimated with complex dispersion models of pollutants from local freeway and non-freeway sources, but the data inputs required for such modelling are not always available. A frequently used simpler approach has been to estimate residential distance to roadways. A number …

Mobile monitoring system for gaseous air pollution

Abstract: The concept of a mobile monitoring system for chemical agents control in the air is presented. The proposed system can be applied to measure industrial and car traffic air pollution. A monitoring station is relatively small and can be placed on cars or public transportation vehicles. Measured concent rations of air pollutants are collected and transferred via the GSM network to a central data base. Exemplary results from a measurement series in Gda ńsk are also presented.

Interval-Based Air Quality Index Optimization Model for Regional Environmental Management Under Uncertainty

Abstract: In this study, an interval-based air quality index optimization (IAQO) method was developed for the planning of regional air quality management systems. The developed IAQO method introduced an air quality index (AQI) concept into an interval mathematical programming (IMP) framework to handle uncertainties expressed as interval values in the model's left- and right-hand sides and objective function over a multipollutant environmental management for its capacity of integrated evaluation and health risk analysis with ambient concentrations. A management problem for controlling total air pollutant concentrations was studied to illustrate applicability of the proposed IAQO approach. A number of scenarios based on different ambient air quality management policies were analyzed. Results indicate that reasonable solutions have been generated under different levels of violating AQI risk. They can help decision makers to identify desired alternatives for mitigating air pollution with cost minimization and ...

An Evaluation of the Performance of the CHIMERE Model over Spain Using Meteorology from MM5 and WRF Models

Abstract: The presence of high pollution levels in the atmosphere can produce damages to human health and ecosystems. Because of this reason, the prediction of air pollutant concentration is important to prevent any potential damage. Chemistry-transport models constitute a useful tool to quantify the presence of pollutants in the atmosphere. Input information, such as meteorology and emissions, has a strong influence on model results. Many research activities are focused on trying to reduce errors affecting input information. In this paper we have applied the CHIMERE photochemical model to simulate ozone, NO2 and SO2 in Spain for two sets of meteorological fields obtained with the MM5 and WRF meteorological models. An evaluation of the performance of the CHIMERE model for both meteorological data sets is presented. Very similar air pollutant concentrations were found for the three pollutants and for the two sets of meteorological information.

Climate variability of cold surge and its impact on the air quality of Taiwan

Abstract: Climate change has been receiving wide attention in the last few decades. In order to quantify the climate variability of extreme weather events and their possible impacts on weather parameters and air quality, cold surge events in the past 45 years and the difference in characteristics of air pollutants before and after frontal passage has been examined after December 1993 in Taiwan. The potential impact of climate change on air pollutant concentration and its health implication were presented and discussed. In the past 45 years, the cold surge days (about 18.7 days, or 0.42 day/year) decreased significantly and the average lowest daily temperature for winter in northern Taiwan increased nearly 3°C (0.067°C/year). Based on the definition of cold surge in Taiwan and excluding the stagnation frontal passage, 21 cold surge frontal passage (CSFP) cases and 89 common frontal passage (CFP) events in winter (December–February) were identified in the past 12 years (1993–2005). We take the frontal passage day as the baseline and the differences in air pollutant concentrations and weather-related parameters between the two days before and after the frontal passage days were examined for each case. The averages of the above-mentioned differences during CSFP were compared to the corresponding differences during CFP. During CSFP, the air temperatures after the frontal passage were nearly 4–6°C lower than before the passage at both the background windward stations and urban stations. The average wind speed was about 4–5 m/s higher at the windward stations and less than 2 m/s higher in the major urban areas in Taiwan. During CFP, there was a 2°C increase in temperature but 1 m/s decrease in wind speeds on the day after frontal passage. Because of these meteorological differences, the concentration change of air pollutants during CSFP is significantly greater than that during CFP, especially for PM10 concentration. The difference of PM10 concentration during CSFP can be as large as 20–40 μg/m3 while that during CFP is only about 10 μg/m3. The differences in the other air pollutants such as CO, SO2, and O3 during CSFP are greater than those during CFP, but the difference is insignificant. Under the warming trend, less frequent CSFP’s are expected; the impacts on deterioration of air quality and human health are noteworthy.

Prevision of industrial SO 2 pollutant concentration applying ANNs

Abstract: Air pollution is one of the most important environmental problems Sulphur Dioxide (SO 2 ) and Suspended Particles are considered the most important atmospheric pollutants The prevision of industrial SO 2 air pollutant concentrations would allow us to take preventive measures such as reducing the pollutant emission to the atmosphere In This work we apply Feed Forward Artificial Neural Network to predict the air pollution concentrations in Salamanca, Mexico The work focuses on the daily maximum concentration of SO 2 A database used to train the neural network corresponds to historical time series of meteorological variables (wind speed, wind direction, temperature and relative humidity) and concentrations of SO 2 along a year Results of the experiments with the proposed system show the importance of the meteorological variable set on the prediction of SO 2 concentrations and the neural network efficiency The performance estimation is determined using the Root Mean Square Error (RMSE) and Mean Absolute Error (MAE)

Chapter 5:Human Exposure: Indoor and Outdoor

Abstract: Human exposure to air pollution is highly variable, reflecting the strong spatial and temporal variability of air pollutant concentrations in urban environments. A wide variety of outdoor and indoor sources contribute to acute and chronic exposures to respirable particles, carbon monoxide, nitrogen oxides, sulfur dioxide, ozone, volatile organic compounds and polycyclic aromatic hydrocarbons. Ambient air quality measurements and dispersion model simulations are commonly used to estimate population exposure to air pollutants in cities. In addition, time-activity micro-environmental and other dynamic time-space models can be used to characterise the personal exposure of individuals or population subgroups. People in developed countries typically spend 90% of their time indoors, and impact of indoor sources, such as tobacco smoking, gas cooking, construction and furnishing materials, and household chemicals (e.g. paints, adhesives, cleaning products, etc.), on personal exposure can become dominant. Recent exposure surveys have shown that personal exposure is typically higher than both indoor and outdoor concentrations of traffic-related pollutants such as benzene. In most cases, this is due to peak personal exposures occurring within transient (e.g. commuting) and other highly polluted micro-environments (e.g. petrol stations, garages, etc.). In developing countries, domestic fuel combustion (e.g. biomass burning for cooking and heating) has been identified as a major factor contributing to elevated exposure of the population to respirable particles, carbon monoxide, polycyclic aromatic hydrocarbons, nitrogen oxides and sulfur dioxide.

Development of Exposure Characterization Regions for Priority Ambient Air Pollutants

Abstract: To evaluate the relationship between air pollution and morbidity and mortality in epidemiological studies, the exposure of populations must be defined. Generally, ambient air monitoring networks are the source of the exposure data for these studies. In this study, we developed methods to define population exposure regions that represent minimal variation in air pollutant concentrations. We evaluated the spatial and temporal variation in concentrations for particulate matter less than 2.5 μm (PM2.5) and 10 μm (PM10) and ozone (O3) across New York State. The results from the PM2.5 and ozone analysis indicate a significant degree of regional transport and showed regions of consistent concentrations of 100 and 50 miles, respectively, around each monitor. PM10 analysis indicated little temporal and spatial variation for this pollutant and larger regions were adopted. The exposure characterization regions for PM2.5, PM10, and ozone have been used in ecological epidemiological investigations by the New ...

Air quality impact of sponge iron industries in central India.

Abstract: Emission load of particulate matter from 42 sponge iron industrial units located in clusters in the Indian State of Chhattisgarh was estimated to be 1,361 TPD. US EPA air pollution dispersion model ISCST-3 applied to predict the impact of the sponge iron industry emissions on ambient air quality showed contribution up to 546 microg/m(3) to the surrounding air basin causing the air quality exceeding the national ambient air quality standards. Electrostatic precipitator (ESP) has been suggested to all the above industrial units that would bring down the contribution to as low as 27 microg/m(3).

STATISTICAL ANALYSIS OF METEOROLOGICAL FACTORS AND AIR POLLUTION AT WINTER MONTHS IN ELAZIĞ, TURKEY (doi: 10.4090/juee.2009.v3n1.007016)

Abstract: In the present study, relationship between monitored air pollutant concentrations such as SO2 and the total suspended particles (TSP) data and meteorological factors such as wind speed, temperature, relative humidity and atmospheric pressure was investigated in months of October, November, December, January, February, and March during the period of three years (2003, 2004 and 2005) for Elazig city. According to the results of linear and non-linear regression analysis, it was found that there is a moderate and weak level of relation between the air pollutant concentrations and the meteorological factors in Elazig city.