Low emission zones reduce PM10 mass concentrations and diesel soot in German cities

In many European cities mass concentrations of PM₁₀ (particles less than 10 μm in size) are still exceeding air quality standards as set by the European Commission in 1999. As a consequence, many cities introduced low emission zones (LEZs) to improve air quality and to meet the limit values. In Germany currently 48 LEZs are in operation. By means of dispersion modeling, PM₁₀ concentrations were estimated to decrease up to 10%. Analysis of PM₁₀ levels conducted for Cologne, Berlin, and Munich some time after the LEZs were introduced showed reduction of PM₁₀ mass concentration in the estimated range. The PM₁₀ particle fraction is, however, composed of particles with varying toxicity, of which diesel soot is highly health relevant. An evaluation of air quality data conducted in Berlin showed that in 2010 traffic-related soot concentrations measured along major roads decreased by 52% compared to 2007. Diesel particle emissions in Berlin were reduced in 2012 by 63% compared to a business-as-usual scenario (reference year 2007). A strong reduction of the traffic-related particle fraction of PM_2.5 was also reported for Munich. Therefore, it is likely that the effects of LEZs are considerably more significant to human health than was anticipated when only considering the reduction of PM₁₀ mass concentrations.

Implications: The implementation of low emission zones in German cities might result in a reduction of PM₁₀ levels concentrations by up to 10%. However, it is difficult to show a reduction of PM₁₀ annual averages in this order of magnitude as meteorology has a large impact on the year-to-year variation of PM mass concentrations. Monitoring of other PM metrics such as black smoke (BS) or elemental carbon (EC) might be a better strategy for evaluating LEZs effects. The benefit of low emission zones on human health is far greater than is presently visible from routine measurements of PM₁₀.     

Estimation of Ambient PM2.5 Concentrations in Maryland and Verification by Measured Values

Abstract

In 1997, Maryland had no available ambient Federal Reference Method data on particulate matter less than 2.5 μm in aerodynamic diameter (PM_2.5), but did have annual ambient data for PM smaller than 10 μm (PM₁₀) at 24 sites. The PM₁₀ data were analyzed in conjunction with local annual and seasonal zip-code-level emission inventories and with speciated PM_2.5 data from four nearby monitors in the IMPROVE network (located in the national parks, wildlife refuges, and wilderness areas) in an effort to estimate annual average and seasonal high PM_2.5 concentrations at the 24 PM₁₀ monitor sites operating from 1992 to 1996. All seasonal high concentrations were estimated to be below the 24-hr PM_2.5 National Ambient Air Quality Standards (NAAQS) at the sites operating in Maryland between 1992 and 1996. The estimates also indicated that 12 monitor sites might exceed the 3-year annual average PM_2.5 NAAQS of 15 ug/m³, but Maryland’s air quality shows signs that it has been improving since 1992. The estimates also were compared with actual measurements after the PM_2.5 monitor network was installed. The estimates were adequate for describing the chemical composition of the PM_2.5, forecasting compliance status with the 24-hr and annual standards, and determining the spatial variations in PM_2.5 across central Maryland.     

Characterization of Particulate Matter in California

ABSTRACT

The size, composition, and concentration of particulate matter (PM) vary with location and time. Several monitoring/sampling programs are operated in California to characterize PM less than 2.5 and 10 µm in aerodynamic diameter (PM_2.5 and PM₁₀). This paper presents a broad summary of the spatial and temporal variations observed in ambient PM_2.5 and PM₁₀ concentrations in California. Many areas that have high PM₁₀ concentrations also have relatively high PM_2.5 concentrations, and data indicate that a significant portion of the PM₁₀ air quality problem is caused by PM_2.5. To develop effective plans for attaining the ambient PM standards, improved understanding of these unique problems is needed. Since 1989, pollution control efforts—whether specifically targeted for particulate matter or indirectly via controls on gaseous emissions—have caused annual average PM_2.5 and PM₁₀ concentrations to decline at most sites in California.     

Performance evaluation of the portable MiniVOL particulate matter sampler

The MiniVOL sampler is a popular choice for use in air quality assessments because it is portable and inexpensive relative to fixed site monitors. However, little data exist on the performance characteristics of the sampler. The reliability, precision, and comparability of the portable MiniVOL PM₁₀ and PM_2.5 sampler under typical ambient conditions are described in this paper. Results indicate that the MiniVOL (a) operated reliably and (b) yielded statistically similar concentration measurements when co-located with another MiniVOL (r²=0.96 for PM₁₀ measurements and r²=0.95 for PM_2.5 measurements). Thus, the characterization of spatial distributions of PM₁₀ and PM_2.5 mass concentrations with the MiniVOL can be accomplished with a high level of confidence. The MiniVOL also produced statistically comparable results when co-located with a Dichotomous Sampler (r²=0.83 for PM₁₀ measurements and r²=0.85 for PM_2.5 measurements) and a continuous mass sampling system (r²=0.90 for PM₁₀ measurements). Environmental factors such as ambient concentration, wind speed, temperature, and humidity may influence the relative measurement comparability between these sampling systems.     

Evaluation of PM10 forecasting based on the artificial neural network model and intake fraction in an urban area: A case study in Taiyuan City,China

Primary fine particulate matters with a diameter of less than 10 µm (PM₁₀) are important air emissions causing human health damage. PM₁₀ concentration forecast is important and necessary to perform in order to assess the impact of air on the health of living beings. To better understand the PM₁₀ pollution health risk in Taiyuan City, China, this paper forecasted the temporal and spatial distribution of PM₁₀ yearly average concentration, using Back Propagation Artificial Neural Network (BPANN) model with various air quality parameters. The predicted results of the models were consistent with the observations with a correlation coefficient of 0.72. The PM₁₀ yearly average concentrations combined with the population data from 2002 to 2008 were given into the Intake Fraction (IF) model to calculate the IFs, which are defined as the integrated incremental intake of a pollutant released from a source category or a region over all exposed individuals. The results in this study are only for main stationary sources of the research area, and the traffic sources have not been included. The computed IFs results are therefore under-estimations. The IFs of PM₁₀ from Taiyuan with a mean of 8.5 per million were relatively high compared with other IFs of the United States, Northern Europe and other cities in China. The results of this study indicate that the artificial neural network is an effective method for PM₁₀ pollution modeling, and the Intake Fraction model provides a rapid population risk estimate for pollutant emission reduction strategies and policies.

Implications The PM₁₀ (particulate matter with an aerodynamic diameter ≤10 μm) yearly average concentration of Taiyuan, with a mean of 0.176 mg/m³, was higher than the 65 μg/m³ recommended by the U.S. Environmental Protection Agency (EPA). The spatial distribution of PM₁₀ yearly average concentrations showed that wind direction and wind speed played an important role, whereas temperature and humidity had a lower effect than expected. Intake fraction estimates of Taiyuan were relatively high compared with those observed in other cities. Population density was the major factor influencing PM₁₀ spatial distribution. The results indicated that the artificial neural network was an effective method for PM₁₀ pollution modeling.     

Evaluation of Human Exposure to Ambient PM10 in the Metropolitan Area of Mexico City Using a GIS-Based Methodology

ABSTRACT

The main goal of this study was to evaluate the magnitude of outdoor exposure to fine particulate matter (PM₁₀) potentially experienced by the population of metropolitan Mexico City. With the use of a geographic information system (GIS), spatially resolved PM₁₀ distributions were generated and linked to the local population. The PM₁₀ concentration exceeded the 24-hr air quality standard of 150 μg/m³ on 16% of the days, and the annual air quality standard of 50 μg/m³ was exceeded by almost twice its value in some places. The basic methodology described in this paper integrates spatial demographic and air quality databases, allowing the evaluation of various air pollution reduction scenarios. Achieving the annual air quality standard would represent a reduction in the annual arithmetic average concentration of 14 μg/m³ for the typical inhabitant. Human exposure to particulate matter (PM) has been associated with mortality and morbidity in Mexico City; reducing the concentration levels of this pollutant would represent a reduction in mortality and morbidity and the associated cost of such impacts. This methodology is critical to assessing the potential benefits of the current initiative to improve air quality implemented by the Environmental Metropolitan Commission of Mexico City.     

Interpretation of air quality in relation to monitoring station's surroundings

This study explores the appropriateness of the locality of air monitoring stations which are meant to indicate air quality in the area. Daily variations in NO₂ and PM₁₀ concentrations at 14 monitoring stations in Hong Kong are examined. The daily variations in NO₂ at a number of background monitoring stations exhibit patterns similar to variations in traffic volume while variations in PM₁₀ concentration exhibit less discernible pattern. Principal component analysis (PCA) and cluster analysis (CA) are applied to analyse NO₂ and PM₁₀ measurements between January 2001 and December 2005. The results show that NO₂ concentrations at background stations within the urban area are highly influenced by vehicle emissions. The effect vehicle emission has on NO₂ at stations within new towns is smaller. CA results also show that variations in PM₁₀ concentrations are distinguished by the area the station is located in. PCA results show that there are two principal components (PC's) associated with variations in roadside concentration of PM₁₀. The strong influence of roadside emissions towards concentrations of NO₂ and PM₁₀ at a number of urban background stations may be due to their close proximity to busy roadways and the high density of surrounding tall buildings, which creates an enclosure that hinders dispersion of roadside emissions and results in air pollution behaviour that reflects variation in traffic.     

Indoor particulate matter in urban residences of Alexandria,Egypt

Indoor particulate matter samples were collected in 17 homes in an urban area in Alexandria during the summer season. During air measurement in all selected homes, parallel outdoor air samples were taken in the balconies of the domestic residences. It was found that the mean indoor PM_2.5 and PM₁₀ (particulate matter with an aerodynamic diameter ≤2.5 and ≤10 μm, respectively) concentrations were 53.5 ± 15.2 and 77.2 ± 15.1 µg/m³, respectively. The corresponding mean outdoor levels were 66.2 ± 16.5 and 123.8 ± 32.1 µg/m³, respectively. PM_2.5 concentrations accounted, on average, for 68.8 ± 12.8% of the total PM₁₀ concentrations indoors, whereas PM_2.5 contributed to 53.7 ± 4.9% of the total outdoor PM₁₀ concentrations. The median indoor/outdoor mass concentration (I/O) ratios were 0.81 (range: 0.43–1.45) and 0.65 (range: 0.4–1.07) for PM_2.5 and PM₁₀, respectively. Only four homes were found with I/O ratios above 1, indicating significant contribution from indoor sources. Poor correlation was seen between the indoor PM₁₀ and PM_2.5 levels and the corresponding outdoor concentrations. PM₁₀ levels were significantly correlated with PM_2.5 loadings indoors and outdoors and this might be related to PM₁₀ and PM_2.5 originating from similar particulate matter emission sources. Smoking, cooking using gas stoves, and cleaning were the major indoor sources contributed to elevated indoor levels of PM₁₀ and PM_2.5.

Implications: The current study presents results of the first PM_2.5 and PM₁₀ study in homes located in the city of Alexandria, Egypt. Scarce data are available on indoor air quality in Egypt. Poor correlation was seen between the indoor and outdoor particulate matter concentrations. Indoor sources such as smoking, cooking, and cleaning were found to be the major contributors to elevated indoor levels of PM₁₀ and PM_2.5.     

Particulate matter sources on an hourly timescale in a rural community during the winter

Particulate matter (PM) sources at four different monitoring sites in Alexandra, New Zealand, were investigated on an hourly timescale. Three of the sites were located on a horizontal transect, upwind, central, and downwind of the general katabatic flow pathway. The fourth monitoring site was located at the central site, but at a height of 26 m, using a knuckleboom, when wind conditions permitted. Average hourly PM₁₀ (PM with an aerodynamic diameter <10 μm) concentrations in Alexandra showed slightly different diurnal profiles depending on the sampling site location. Each location did, however, feature a large evening peak and smaller morning peak in PM₁₀ concentrations. The central site in Alexandra experienced the highest PM₁₀ concentrations as a result of PM transport along a number of katabatic flow pathways. A significant difference in PM₁₀ concentrations between the central and elevated sites indicated that a shallow inversion layer formed below the elevated site, limiting the vertical dispersion of pollutants. Four PM₁₀ sources were identified at each of the sites: biomass combustion, vehicles, crustal matter, and marine aerosol. Biomass combustion was identified as the most significant source of PM₁₀, contributing up to 91% of the measured PM₁₀. Plots of the average hourly source contributions to each site revealed that biomass combustion was responsible for both the evening and morning peaks in PM₁₀ concentrations observed at each of the sites, suggesting that Alexandra residents were relighting their fires when they rose in the morning. The identification of PM sources on an hourly timescale can have significant implications for air quality management.

Implications: Monitoring the sources of PM₁₀ on an hourly timescale at multiple sites within an airshed provides extremely useful information for air quality management. Sources responsible for observed peaks in measured diurnal PM₁₀ concentration profiles can be easily identified and targeted for reduction. Also, hourly PM₁₀ sampling can provide crucial information on the role meteorology plays in the development of elevated PM₁₀ concentrations.     

Comment on “Measuring Air Quality Levels Inexpensively at Multiple Locations by Random Sampling”

ABSTRACT

In order to evaluate the spatial variation of aerosol (particulate matter with aerodynamic diameter ≤10 μm [PM₁₀]) and ozone (O₃) concentrations and characterize the atmospheric conditions that lead to O₃ and PM₁₀-rich episodes in southern Italy during summer 2007, an intensive sampling campaign was simultaneously performed, from middle of July to the end of August, at three ground-based sites (marine, urban, and high-altitude monitoring stations) in Calabria region. A cluster analysis, based on the prevailing air mass backward trajectories, was performed, allowing to discriminate the contribution of different air masses origin and paths. Results showed that both PM₁₀ and O₃ levels reached similar high values when air masses originated from the industrialized continental Europe as well as under the influence of wildfire emissions. Among natural sources, dust intrusion and wildfire events seem to involve a marked impact on the recorded data. Typical fair weather of Mediterranean summer and persisting anticyclone system at synoptic scale were indeed favorable conditions to the arrival of heavily dust-loaded air masses over three periods of consecutive days and more than half of the observed PM₁₀ daily exceedances have been attributed to Saharan dust events. During the identified dust outbreaks, a consistent increase in PM₁₀ levels with a concurrent decrease in O₃ values was also observed and discussed.

IMPLICATIONS In the summertime, the central-southern Mediterranean Basin is heavily affected by Saharan dust outbreaks and wildfire events. A focus on their significant influence on either oxidizing capacity of the atmosphere and air quality over Calabria, southern Italy, was here presented. Similar studies for most regions surrounding the Mediterranean Basin are needed to implement effective emission reduction measures, to prevent apparent air quality parameter exceedances and to define an appropriate health alert system. Because the frequency of these events is expected to increase due to climate change, these studies could even be a valid effort to better understand and characterize such atmospheric variations.     

Particulate Air Pollution in Mexico City: A Collaborative Research Project

ABSTRACT

PM₁₀, PM₂₅, precursor gas, and upper-air meteorological measurements were taken in Mexico City, Mexico, from February 23 to March 22, 1997, to understand concentrations and chemical compositions of the city's particulate matter (PM). Average 24-hr PM₁₀ concentrations over the period of study at the core sites in the city were 75 H g/m³. The 24-hr standard of 150 μ g/m³ was exceeded for seven samples taken during the study period; the maximum 24-hr concentration measured was 542 μ g/m³. Nearly half of the PM₁₀ was composed of fugitive dust from roadways, construction, and bare land. About 50% of the PM₁₀ consisted of PM_2.5, with higher percentages during the morning hours. Organic and black carbon constituted up to half of the PM_2.5. PM concentrations were highest during the early morning and after sunset, when the mixed layers were shallow. Meteorological measurements taken during the field campaign show that on most days air was transported out of the Mexico City basin during the afternoon with little day-to-day carryover.     

A Statistical Assessment of Saturation and Mobile Sampling Strategies to Estimate Long-Term Average Concentrations across Urban Areast

Abstract

The objectives of this study were: (1) to quantify the errors associated with saturation air quality monitoring in estimating the long-term (i.e., annual and 5 yr) mean at a given site from four 2-week measurements, once per season; and (2) to develop a sampling strategy to guide the deployment of mobile air quality facilities for characterizing intraurban gradients of air pollutants, that is, to determine how often a given location should be visited to obtain relatively accurate estimates of the mean air pollutant concentrations. Computer simulations were conducted by randomly sampling ambient monitoring data collected in six Canadian cities at a variety of settings (e.g., population-based sites, near-roadway sites). The 5-yr (1998–2002) dataset consisted of hourly measurements of nitric oxide (NO), nitrogen dioxide (NO₂), oxides of nitrogen (NO_x), sulfur dioxide (SO₂), coarse particulate matter (PM₁₀), fine particulate matter (PM_2.5)_, and CO. The strategy of randomly selecting one 2-week measurement per season to determine the annual or long-term average concentration yields estimates within 30% of the true value 95% of the time for NO₂, PM₁₀ and NO_x. Larger errors, up to 50%, are expected for NO, SO₂, PM_2.5, and CO. Combining concentrations from 85 random 1-hr visits per season provides annual and 5-yr average estimates within 30% of the true value with good confidence. Overall, the magnitude of error in the estimates was strongly correlated with the variability of the pollutant. A better estimation can be expected for pollutants known to be less temporally variable and/or over geographic areas where concentrations are less variable. By using multiple sites located in different settings, the relationships determined for estimation error versus number of measurement periods used to determine long-term average are expected to realistically portray the true distribution. Thus, the results should be a good indication of the potential errors one could expect in a variety of different cities, particularly in more northern latitudes.     

Outdoor and indoor factors influencing particulate matter and carbon dioxide levels in naturally ventilated urban homes

ABSTRACT

The present study investigated indoor and outdoor concentrations of two particulate matter size fractions (PM₁₀ and PM_2.5) and CO₂ in 20 urban homes ventilated naturally and located in one congested residential and commercial area in the city of Alexandria, Egypt. The results indicate that the daily mean PM_2.5 concentrations measured in the ambient air, living rooms, and kitchens of all sampling sites exceeded the WHO guideline by 100%, 65%, and 95%, respectively. The daily mean outdoor and indoor PM₁₀ levels in all sampling sites were found to exceed the WHO guideline by 100% and 80%, respectively. The indoor PM₁₀ and PM_2.5 concentrations were significantly correlated with their corresponding outdoor levels, as natural ventilation through opening doors and windows allowed direct transfer of outdoor airborne particles into the indoor air. Most of the kitchens investigated had higher indoor concentrations of PM_2.5 and CO₂ than in living rooms. The elevated levels of PM_2.5 and CO₂ in domestic kitchens were probably related to inadequate ventilation. The current study attempted to understand the sources and the various indoor and outdoor factors that affect indoor PM₁₀, PM_2.5 and CO₂ concentrations. Several domestic activities, such as smoking, cooking, and cleaning, were found to constitute important sources of indoor air pollution. The indoor pollution caused by PM_2.5 was also found to be more serious in the domestic kitchens than in the living rooms and the results suggest that exposure to PM_2.5 is high and highlights the need for more effective control measures.

Implications: Indoor air pollution is a complex problem that involves many determinant factors. Understanding the relationships and the influence of various indoor and outdoor factors on indoor air quality is very important to prioritize control measures and mitigation action plans. There is currently a lack of research studies in Egypt to investigate determinant factors controlling indoor air quality for urban homes. The present study characterizes the indoor and outdoor concentrations of PM₁₀, PM_2.5, and CO₂ in residential buildings in Alexandria city. The study also determines the indoor and outdoor factors which influence the indoor PM and CO₂ concentrations as well as it evaluates the potential indoor sources in the selected homes. This research will help in the development of future indoor air quality standards for Egypt.     

An enhanced PM2.5 air quality forecast model based on nonlinear regression and back-trajectory concentrations

An enhanced PM_2.5 air quality forecast model based on nonlinear regression (NLR) and back-trajectory concentrations has been developed for use in the Louisville, Kentucky metropolitan area. The PM_2.5 air quality forecast model is designed for use in the warm season, from May through September, when PM_2.5 air quality is more likely to be critical for human health. The enhanced PM_2.5 model consists of a basic NLR model, developed for use with an automated air quality forecast system, and an additional parameter based on upwind PM_2.5 concentration, called PM24. The PM24 parameter is designed to be determined manually, by synthesizing backward air trajectory and regional air quality information to compute 24-h back-trajectory concentrations. The PM24 parameter may be used by air quality forecasters to adjust the forecast provided by the automated forecast system. In this study of the 2007 and 2008 forecast seasons, the enhanced model performed well using forecasted meteorological data and PM24 as input. The enhanced PM_2.5 model was compared with three alternative models, including the basic NLR model, the basic NLR model with a persistence parameter added, and the NLR model with persistence and PM24. The two models that included PM24 were of comparable accuracy. The two models incorporating back-trajectory concentrations had lower mean absolute errors and higher rates of detecting unhealthy PM2.5 concentrations compared to the other models.     

Source Apportionment of PM10 and PM25 in Five Chilean Cities Using Factor Analysis

ABSTRACT

Chile is a fast-growing country with important industrial activities near urban areas. In this study, the mass and elemental concentrations of PM₁₀ and PM_2.5 were measured in five major Chilean urban areas. Samples of particles with diameter less than 10 um (PM₁₀) and 2.5 um (PM_2.5) were collected in 1998 in Iquique (northern Chile), Valparaiso, Vina del Mar, Rancagua (central Chile), and Temuco (southern Chile). Both PM₁₀ and PM₂₅ annual mean concentrations (PM₁₀: 56.9-77.6 u,g/m³; PM₂₅: 22.4-42.6 u.g/m³) were significantly higher than the corresponding European Union (EU) and U.S. Environmental Protection Agency (EPA) air quality standards. Moreover, the 24-hr PM₁₀ and PM₂₅ U.S. standards were exceeded infrequently for some of the cities (Rancagua and Valparaiso).     

Daily Mortality and Air Pollution in the Netherlands

ABSTRACT

We studied the association of daily mortality with short-term variations in the ambient concentrations of major gaseous pollutants and PM in the Netherlands. The magnitude of the association in the four major urban areas was compared with that in the remainder of the country. Daily cause-specific mortality counts, air quality, temperature, relative humidity, and influenza data were obtained from 1986 to 1994. The relationship between daily mortality and air pollution was modeled using Poisson regression analysis. We adjusted for potential confounding due to long-term and seasonal trends, influenza epidemics, ambient temperature and relative humidity, day of the week, and holidays, using generalized additive models.

Influenza episodes were associated with increased mortality up to 3 weeks later. Daily mortality was significantly associated with the concentration of all air pollutants. An increase in the PM₁₀ concentration by 100 u.g/m³ was associated with a relative risk (RR) of 1.02 for total mortality. The largest RRs were found for pneumonia deaths. Ozone had the most consistent, independent association with mortality. Particulate air pollution (e.g., PM₁₀, black smoke [BS]) was not more consistently associated with mortality than were the gaseous pollutants SO₂ and NO₂. Aerosol SO₄ ^-2, NO₃ ^-, and BS were more consistently associated with total mortality than was PM₁₀. The RRs for all pollutants were substantially larger in the summer months than in the winter months. The RR of total mortality for PM₁₀ was 1.10 for the summer and 1.03 for the winter. There was no consistent difference between RRs in the four major urban areas and the more rural areas.     

Determination of air quality zones in Turkey

In this study, the particulate matter (with an aerodynamic diameter <10 μm; PM₁₀) profile of Turkey with data from the air quality monitoring stations located throughout the country was used. The number of stations (119) was reduced to 55 after a missing data treatment for statistical analyses. First, a classification method was developed based on ongoing national and international (European Commission directives) legislations to categorize air zones into six groups, from a “Very Clear Air Zone” to a “Polluted Air Zone.” Then, a Geographic Information System (GIS)-based interpolation technique and statistical analyses (correlation analysis and factor analysis) were used to generate PM₁₀ pollution profiles of the annual heating time and nonheating time periods. Finally, the coherent air pollution management zones of Turkey, based on air quality criteria and measured data using a GIS-based model supported by statistical analyses, were suggested. Based on the analysis, four hot spots were identified: (i) the eastern part of the Black Sea region; (ii) the northeastern part of inland Anatolia; (iii) the western part of Northeastern Anatolia; and (vi) the eastern part of Turkey. The possible reasons for the elevated PM₁₀ levels are discussed using topographic, climatologic, land use, and energy utilization parameters. Finally, the suggested air zones were compared with the administrative air zones, which were newly developed by the Turkish Ministry of Environment and Forestry, to evaluate the level of agreement between the two.

Implications: The evaluation of air quality profiles of specific regions is important in the development and/or application of an effective air quality management strategy. Factor analysis (FA), together with correlation analysis (CA), provides useful information to classify air pollution management areas over regional networks that have historical time-series air quality data. In this study, which relied on a FA- and CA-based methodology, the coherent air pollution management zones of Turkey after using a GIS-based model were suggested. Policy makers and scientist can use these suggested zones to construct better air quality management strategies.     

Demolition of High-Rise Public Housing Increases Particulate Matter Air Pollution in Communities of High-Risk Asthmatics

Abstract

Public housing developments across the United States are being demolished, potentially increasing local concentrations of particulate matter (PM) in communities with high burdens of severe asthma. Little is known about the impact of demolition on local air quality. At three public housing developments in Chicago, IL, PM with an aerodynamic diameter <10 μm (PM₁₀) and <2.5 μm were measured before and during high-rise demolition. Additionally, size-selective sampling and real-time monitoring were concurrently performed upwind and downwind of one demolition site. The concentration of particulates attributable to demolition was estimated after accounting for background urban air pollution. Particle microscopy was performed on a small number of samples. Substantial increases of PM₁₀ occurred during demolition, with the magnitude of that increase varying based on sampler distance, wind direction, and averaging time. During structural demolition, local concentrations of PM₁₀ 42 m downwind of a demolition site increased 4- to 9-fold above upwind concentrations (6-hr averaging time). After adjusting for background PM₁₀, the presence of dusty conditions was associated with a 74% increase in PM₁₀ 100 m downwind of demolition sites (24-hr averaging times). During structural demolition, short-term peaks in real-time PM₁₀ (30-sec averaging time) occasionally exceeded 500 μg/m³. The median particle size downwind of a demolition site (17.3 μm) was significantly larger than background (3 μm). Specific activities are associated with real-time particulate measures. Microscopy did not identify asbestos or high concentrations of mold spores. In conclusion, individuals living near sites of public housing demolition are at risk for exposure to high particulate concentrations. This increase is characterized by relatively large particles and high short-term peaks in PM concentration.     

Installation of platform screen doors and their impact on indoor air quality: Seoul subway trains

In this study, variations of particulate matter (PM) concentrations in subway trains following installation of platform screen doors (PSDs) in the Seoul subway system were investigated. PM samples were collected in the trains on subway lines 1–8 before and after installation of PSDs. It was found that the mean PM₁₀ concentration in the trains after PSDs installation increased significantly by 29.9% compared to that before installation. In particular, the increase of PM₁₀ in line 6 was the highest at 103%. When the relationship between PM₁₀ and PM_2.5 was compared, coefficients of determination (r²) before and after PSDs installations were 0.696 and 0.169, respectively. This suggests that air mixing between the platform and the tunnel after PSDs installation was extremely restricted. In addition, the indoor/outdoor PM₁₀ ratio following PSDs installation increased from 1.32 to 2.97 relative to the period with no installed PSDs. Furthermore, this study revealed that PM levels in subway trains increased significantly after all underground PSDs were put in use. Several potential factors were examined that could result in this PM increase, such as train ventilation systems, operational conditions, passenger volume, subway depth, and the length of underground segments.

ImplicationsPM₁₀ concentrations inside the subway trains increased after PSDs installation. This indicates that air quality in trains was very seriously impacted by PSDs. PM₁₀ levels were also influenced by the tunnel depth and length of the underground segments. To prevent the adverse effect on human health by PM₁₀ emitted from the tunnel, an applicable ventilation system to reduce PM₁₀ is required inside trains and tunnels.     

Concentration and size distribution of particulate matter in a new aviary system for laying hens in China

ABSTRACT

Particulate matter (PM) from poultry production facilities may strongly affect the health of animals and workers in the houses, and PM emitted to the ambient air is an important pollution source to the surrounding areas. Aviary system is considered as a welfare friendly production system for laying hens. However, its air quality is typically worse as compared with conventional cage systems, because of the higher PM concentration of indoor air and other airborne contaminants. Furthermore, PM’s physical property, which has a direct impact on the penetration depth into the lungs of the birds and humans, is largely unknown for the aviary system. Therefore, a systematic method was utilized to investigate the characteristics of particles in the aviary house with large cage aviary unit system (LCAU) in Beijing, China. For the field measurements, three measuring locations were selected with two inside and one outside the house with LCAU to continuously monitor PM concentrations and collect the samples for particle size distribution (PSD) analysis. Results showed that PM_2.5, PM₁₀, and total suspended particulate (TSP) concentrations averaged at 0.037 ± 0.025 mg/m³, 0.42 ± 0.10 mg/m³, and 1.92 ± 1.91 mg/m³, respectively. Particle concentrations increased from October to December due to less ventilation as the weather got colder, and were generally affected by stocking density, ventilation rate, birds’ activities, and housing system. Meanwhile, indoor PM_2.5 concentration was easily impacted by the ambient air quality. Mass median diameter (MMD) and mass geometric standard deviation (MGSD) of the TSP during the measurement were 18.92 ± 7.08 μm and 3.11 ± 0.31, respectively. Count median diameter (CMD) and count geometric standard deviation (CGSD) were 1.94 ± 0.14 μm and 1.48 ± 0.08, respectively. Results indicated that the aviary system can attain a good indoor condition by suitable system design and environment control strategy.

Implications: Indoor PM_2.5 concentration of the layer house can be significantly affected by ambient air quality when the air quality index (AQI) was larger than 100. PM_2.5 and PM₁₀ concentrations of the layer house with a LCAU system were comparable to the cage system. TSP concentration was higher, and PM size was larger than most of the cage system. System design, larger space volume, and higher ventilation rate were the main influence factors. Good indoor environment of the aviary system can be achieved through the reasonable design of the production system and appropriate environment control strategy.