Urban Monitoring Sites Research Articles

Using structural equation modeling to construct calibration equations relating PM2.5 mass concentration samplers to the federal reference method sampler

The objective of this study was to remove systematic bias among fine particulate matter (PM2.5) mass concentration measurements made by different types of samplers used in the Pittsburgh Aerosol Research and Inhalation Epidemiology Study (PARIES). PARIES is a retrospective epidemiology study that aims to provide a comprehensive analysis of the associations between air quality and human health effects in the Pittsburgh, Pennsylvania, region from 1999 to 2008. Calibration was needed in order to minimize the amount of systematic error in PM2.5 exposure estimation as a result of including data from 97 different PM2.5 samplers at 47 monitoring sites. Ordinary regression often has been used for calibrating air quality measurements from pairs of measurement devices; however, this is only appropriate when one of the two devices (the “independent” variable) is free from random error, which is rarely the case. A group of methods known as “errors-in-variables” (e.g., Deming regression, reduced major axis regression) has been developed to handle calibration between two devices when both are subject to random error, but these methods require information on the relative sizes of the random errors for each device, which typically cannot be obtained from the observed data. When data from more than two devices (or repeats of the same device) are available, the additional information is not used to inform the calibration. A more general approach that often has been overlooked is the use of a measurement error structural equation model (SEM) that allows the simultaneous comparison of three or more devices (or repeats). The theoretical underpinnings of all of these approaches to calibration are described, and the pros and cons of each are discussed. In particular, it is shown that both ordinary regression (when used for calibration) and Deming regression are particular examples of SEMs but with substantial deficiencies. To illustrate the use of SEMs, the 7865 daily average PM2.5 mass concentration measurements made by seven collocated samplers at an urban monitoring site in Pittsburgh, Pennsylvania, were used. These samplers, which included three federal reference method (FRM) samplers, three speciation samplers, and a tapered element oscillating microbalance (TEOM), operated at various times during the 10-year PARIES study period. Because TEOM measurements are known to depend on temperature, the constructed SEM provided calibration equations relating the TEOM to the FRM and speciation samplers as a function of ambient temperature. It was shown that TEOM imprecision and TEOM bias (relative to the FRM) both decreased as temperature increased. It also was shown that the temperature dependency for bias was non-linear and followed a sigmoidal (logistic) pattern. The speciation samplers exhibited only small bias relative to the FRM samplers, although the FRM samplers were shown to be substantially more precise than both the TEOM and the speciation samplers. Comparison of the SEM results to pairwise simple linear regression results showed that the regression results can differ substantially from the correctly-derived calibration equations, especially if the less-precise device is used as the independent variable in the regression.

Ozone trends across the United States over a period of decreasing NOx and VOC emissions.

In this work, we evaluate ambient ozone trends at urban, suburban, and rural monitoring sites across the United States over a period of decreasing NOx and VOC emissions (1998-2013). We find that decreasing ozone trends generally occur in the summer, in less urbanized areas, and at the upper end of the ozone distribution. Conversely, increasing ozone trends generally occur in the winter, in more urbanized areas, and at the lower end of the ozone distribution. The 95(th) percentile ozone concentrations decreased at urban, suburban, and rural monitors by 1-2 ppb/yr in the summer and 0.5-1 ppb/yr in the winter. In the summer, there are both increasing and decreasing trends in fifth percentile ozone concentrations of less than 0.5 ppb/yr at urban and suburban monitors, while fifth percentile ozone concentrations at rural monitors decreased by up to 1 ppb/yr. In the winter, fifth percentile ozone concentrations generally increased by 0.1-1 ppb/yr. These results demonstrate the large scale success of U.S. control strategies targeted at decreasing peak ozone concentrations. In addition, they indicate that as anthropogenic NOx emissions have decreased, the ozone distribution has been compressed, leading to less spatial and temporal variability.

Personal day-time exposure to ultrafine particles in different microenvironments.

In order to assess the personal exposure to ultrafine particles (UFP) during individual day-time activities and to investigate the impact of different microenvironments on exposure, we measured personal exposure to particle number concentrations (PNC), a surrogate for UFP, among 112 non-smoking participants in Augsburg, Germany over a nearly two-year period from March 2007 to December 2008. We obtained 337 personal PNC measurements from 112 participants together with dairies of their activities and locations. The measurements lasted on average 5.5h and contained on average 330 observations. In addition, ambient PNC were measured at an urban background stationary monitoring site. Personal PNC were highly variable between measurements (IQR of mean: 11780-24650cm(-3)) and also within a single measurement. Outdoor personal PNC in traffic environments were about two times higher than in non-traffic environments. Higher indoor personal PNC were associated with activities like cooking, being in a bistro or exposure to passive smoking. Overall, personal and stationary PNC were weakly to moderately correlated (r<0.41). Personal PNC were much higher than stationary PNC in traffic (ratio: 1.5), when shopping (ratio: 2.4), and indoors with water vapor (ratio: 2.5). Additive mixed models were applied to predict personal PNC by participants' activities and locations. Traffic microenvironments were significant determinants for outdoor personal PNC. Being in a bistro, passive smoking, and cooking contributed significantly to an increased indoor personal PNC.

Elucidating multipollutant exposure across a complex metropolitan area by systematic deployment of a mobile laboratory

Abstract. This study evaluates a deployment strategy of a heavily instrumented mobile lab for characterizing multipollutant spatial patterns based upon a limited number of measurement days spread over different seasons. The measurements obtained through this deployment strategy are used to gain insight into average pollutant levels between routine monitoring sites and in relation to emission sources in the region, as well as to assess correlations between pollutant patterns to better understand the nature of urban air pollutant mixtures. A wide range of locations were part of the deployment in order to characterize the distribution of chronic exposures potentially allowing development of exposure models. Comparison of the mobile lab averages to the available adjacent air quality monitoring network stations to evaluate their representativeness showed that they were in reasonable agreement with the annual averages at the monitoring sites, thus providing some evidence that, through the deployment approach, the mobile lab is able to capture the main features of the average spatial patterns. The differences between mobile lab and network averages varied by pollutant with the best agreement for NO2 with a percentage difference of 20%. Sharp differences in the average spatial distribution were found to exist between different pollutants on multiple scales, particularly on the sub-urban scale, i.e., the neighborhood to street scales. For example, NO2 was observed to be 210–265% higher by the main highway in the study region compared to the nearby urban background monitoring site, while black carbon was higher by 180–200% and particle number concentration was 300% higher. The repeated measurements of near-roadway gradients showed that the rate of change differed by pollutant with elevated concentrations detected up to 600–700 m away for some pollutants. These results demonstrate that through systematic deployment mobile laboratory measurements can be used to characterize average or typical concentration patterns, thus providing data to assess monitoring site representativeness, spatial relationships between pollutants, and chronic multipollutant exposure patterns useful for evaluating and developing exposure models for outdoor concentrations in an urban environment.

Localized Climate and Surface Energy Flux Alterations across an Urban Gradient in the Central U.S.

Long-term urban and rural climate data spanning January 1995 through October 2013 were analyzed to investigate the Urban Heat Island (UHI) effect in a representative mid-sized city of the central US. Locally distributed climate data were also collected at nested low density urban, recently developed, and high density urban monitoring sites from June through September 2013 to improve mechanistic understanding of spatial variability of the UHI effect based upon urban land use intensity. Long-term analyses (1995–2013) indicate significant differences (p &lt; 0.001) between average air temperature (13.47 and 12.89 °C, at the urban and rural site respectively), relative humidity (69.11% and 72.51%, urban and rural respectively), and average wind speed (2.05 and 3.15 m/s urban and rural respectively). Significant differences (p &lt; 0.001) between urban monitoring sites indicate an urban microclimate gradient for all climate variables except precipitation. Results of analysis of net radiation and soil heat flux data suggest distinct localized alterations in urban energy budgets due to land use intensity. Study results hold important implications for urban planners and land managers seeking to improve and implement better urban management practices. Results also reinforce the need for distributed urban energy balance investigations.

Short-Term Exposure to Ozone and Levels of Exhaled Nitric Oxide

Adverse effects of air pollution include respiratory inflammation. A few epidemiologic studies have shown elevations in the fraction of exhaled nitric oxide, a marker of airway inflammation, after exposure to traffic-related pollutants. We examined whether short-term exposures to ozone (O3), oxides of nitrogen (NOx), or particulate matter <10 μm (PM10) were associated with proximal and distal airway inflammation. The study included 5841 randomly selected Swedish adults from 25 to 75 years of age. Fraction of exhaled nitrogen was measured at two flow rates: 50 ml/s representing the proximal airways and 270 ml/s representing the distal airways. Air pollution data were obtained from an urban monitoring site. We applied linear regression to estimate short-term associations of O3, NOx, and PM10 with fractions of exhaled NO at 50 and 270 ml/s. An interquartile range increase in 120-hour average O3 levels was associated with a 5.1% (95% confidence interval = 1.7% to 8.5%) higher level of fraction of exhaled NO at 270 ml/s and 3.6% (-0.4% to 3.4%) higher level of the fraction of exhaled NO at 50 ml/s. For NOx, a small effect was seen for the 24-hour average on the fraction of exhaled NO at 270 ml/s, while for PM10 no clear effects were seen. There was a tendency for a weaker effect of ozone and a stronger effect of NOx in subjects with asthma. Exposure to O3 was associated with a marker of distal airway inflammation, while the association was less obvious for inflammation of the proximal airways.

Comparison of ozone pollution levels at various sites in Seoul, a megacity in Northeast Asia

Concentrations of ozone were continuously measured at four urban monitoring sites (Gu Ro (G); No Won (N); Song Pa (S); and Yong San (Y)) in Seoul, Korea from 2009 to 2011. The annual mean concentrations of ozone (in ppb) at these sites were found on the order of N (21.8±19.3)>S (21.4±20.14)>G (20.9±18.0)>Y (18.8±17.4). During peak hours (12–6pm), the ozone concentrations were significantly higher (75, 69, 67, and 64% at site S, Y, N, and G, respectively) than overall 24hour mean values. Seasonal variations of ozone have quite similar patterns at every site with systematic increases during spring (March–May) and summer (June–August) with the summer daytime mean (12–6pm) values of 40.7 (site Y)–49.3ppb (site S). The concentrations of ozone exhibited strong inverse correlations with other criteria pollutants (e.g., oxides of nitrogen and carbon monoxide), while a significant positive correlation was observed with some meteorological parameters (e.g., ultraviolet ray and solar radiation). Evidence collected in this study confirm that the spatio-temporal distribution of ozone in the study areas should be affected by the anthropogenic sources (e.g., vehicles, residential, and industrial sources) in concert with such well-known variables as the NOx–VOC chemistry and a number of natural parameters (e.g., wind speed, geographic position, and solar radiation).

The impact of low emission zone and heavy traffic ban in Munich on the reduction of PM10 in ambient air

Background: In Munich, Germany, a low emission zone (LEZ) and transit bans for heavy-duty vehicles have been introduced in 2008 to improve air quality and to meet policy targets. Aim: We investigated the effects of those measures on PM10 (particulate matter &lt; 10 µm) mass concentration levels in Munich. Methods: In our analysis we compared PM10 concentrations measured prior to the implementation of any air quality measures (January 06 – January 08) with the PM10 levels measured after the measures became effective (October 08 – June 10). A semiparametric regression model with a first-order autocorrelated error term was applied for modeling hourly PM10 concentrations depending on the time of day, day of the week, the presence of the measures, background pollution, public holidays and wind direction. The changes in PM10 were quantified relative to a reference station representing regional background concentrations. Results: The mean PM10 concentration decreased at the traffic site from 30.0 µg/m3 prior to the measures to 26.0 µg/m3 thereafter, and at the background site from 27.3 µg/m3 to 25.0 µg/m3. The adjusted reduction was 13.8% at the traffic site and 4.8% at the urban background monitoring site. The effect was stronger in the summer season at the traffic site, whereas this was not observed at the background site. The effect sizes were dependent on time of day and day of the week. Conclusion: Traffic regulating measures aiming at the improvement of ambient air quality in Munich resulted in a decrease of ambient PM10 concentrations. The observed changes were larger at a traffic site than at an urban background site. The magnitude of this effect was in the range predicted by means of dispersion modeling for Munich. As dispersion modeling predicted even higher decrease of black smoke concentrations, we concluded that the introduced measures have more significant effects on human health than was anticipated when considering only the reduction of PM10 mass concentrations.

Analysis of water-soluble ions and their precursor gases over diurnal cycle

A detailed description of an interactive relationship is made between water-soluble ionic components in PM2.5 and their precursor gases using the hourly resolution data measured at an urban monitoring site in Seoul during the year of 2010. Their diurnal variability was found to be correlated with their precursor gases (HNO3 and NH3). In the case of NO3− and NH4+, a close similarity was seen in their diurnal trends, especially during spring. There were no noticeable differences in the formation pathway of NO3−, SO42−, and NH4+ aerosols between day and night. For NO3− formation, heterogeneous hydrolysis of N2O5 might play a significant role in the nighttime enhancement of the oxidation rate. In addition, the concentrations of major anions (e.g. NO3−, SO42−, and Cl−) exhibited highly diverse seasonal patterns with their maximum values occurring in spring, summer, and winter, respectively. The overall results of this study suggest that the formation pathway of NO3− and SO42− aerosols should be regulated by a competing relationship between the NH3-lean (spring and winter) and NH3-rich conditions (summer and fall).

Variation trends and influencing factors of total gaseous mercury in the Pearl River Delta—A highly industrialised region in South China influenced by seasonal monsoons

Studies on atmospheric mercury in the Pearl River Delta (PRD) region are important because of the economic relevance of this region to China, because of its economic developmental pattern and because it is a highly industrialised area influenced by the strong seasonal monsoons. Total gaseous mercury (TGM), meteorological parameters and criteria pollutant concentrations were measured at Mt. Dinghu (DH, a regional monitoring site) and Guangzhou (GZ, an urban monitoring site) in the PRD region from October 2009 to April 2010 and from November 2010 to November 2011, respectively. The ranges of daily average TGM concentrations at the DH and GZ sites were 1.87–29.9 ng m−3 (5.07 ± 2.89 ng m−3) and 2.66–11.1 ng m−3 (4.60 ± 1.36 ng m−3), respectively, which were far more significant than the background values in the Northern Hemisphere (1.5–1.7 ng m−3), suggesting that the atmosphere in the PRD has suffered from mercury pollution. Similar TGM seasonal distributions at the two sites were observed, with a descending order of spring, winter, autumn and summer. The different seasonal monsoons were the dominant factor controlling the seasonal variability of the TGM, with variations in the boundary layer and oxidation also possibly partially contributing. Different diurnal patterns of the TGM at two sites were observed. TGM levels during the daytime were higher than those during the nighttime and were predominantly influenced by mountain and valley winds at the DH site, whereas the opposite trend was evident at the GZ site, which was primarily influenced by the boundary-layer height and O3 concentration. During the monitoring period, the correlations between the daily TGM levels and the SO2 and NO2 levels at the DH site were significant (r = 0.36, p < 0.001; r = 0.29, p < 0.001), suggesting that coal-fired emission is an important source of mercury for this regional monitoring site. At the GZ site, the correlations between the daily TGM level and the NO, NO2, CO levels were significant (r = 0.501, p < 0.001; r = 0.579, p < 0.001; r = 0.358, p < 0.001). However, TGM was partially correlated with SO2, suggesting that the combined vehicle emissions and coal combustion were the dominant mercury sources for this urban monitoring site. The TGM distribution figure, which related to the wind-rose pattern and the distribution figure of emission sources, indicated significant contributions from anthropogenic emission sources.

Simultaneous monitoring of total gaseous mercury at four urban monitoring stations in Seoul, Korea

The monitoring of total gaseous mercury (TGM) concentrations together with other trace gases and meteorological parameters was made at hourly intervals over 2-year period (1 January 2010 to 31 December 2011) at four urban monitoring sites: Guro-gu (G), Nowon-gu (N), Songpa-gu (S), and Yongsan-gu (Y) in Seoul, Korea. The mean concentrations of TGM at these sites were found to span the range of 3.28 (Y) to 3.47ngm−3 (N). Inspection of the seasonal patterns indicates that the maximum concentrations (ngm−3) occur at different times of year across the four sites: winter at N (3.67±1.77), fall at S (3.64±1.12), summer at G (3.61±1.51), and spring at Y (3.40±1.26). The long-term trend in Hg concentrations, when also considering data sets from previous studies, suggests modest reductions in concentrations at all four sites, from 2.89 to 4.49ngm−3 in 2004 and from 2.49 to 3.42ngm−3 in 2011.

Characterization of summertime coarse particulate matter in the Desert Southwest—Arizona, USA

A year-long study was conducted in Pinal County, AZ, to characterize coarse (2.5 – 10 μm aerodynamic diameter, AD) and fine (< 2.5 μm AD) particulate matter (PMc and PMf, respectively) to further understand spatial and temporal variations in ambient PM concentrations and composition in rural, arid environments. Measurements of PMc and PMf mass, ions, elements, and carbon concentrations at one-in-six day resolution were obtained at three sites within the region. Results from the summer of 2009 and specifically the local monsoon period are presented. The summer monsoon season (July – September) and associated rain and/or high wind events, has historically had the largest number of PM10 NAAQS exceedances within a year. Rain events served to clean the atmosphere, decreasing PMc concentrations resulting in a more uniform spatial gradient among the sites. The monsoon period also is characterized by high wind events, increasing PMc mass concentrations, possibly due to increased local wind-driven soil erosion or transport. Two PM10 NAAQS exceedances at the urban monitoring site were explained by high wind events and can likely be excluded from PM10 compliance calculations as exceptional events. At the more rural Cowtown site, PM10 NAAQS exceedances were more frequent, likely due to the impact from local dust sources. PM mass concentrations at the Cowtown site were typically higher than at the Pinal County Housing and Casa Grande sites. Crustal material was equal to 52-63% of the PMc mass concentration on average. High concentrations of phosphate and organic carbon found at the rural Cowtown were associated with local cattle feeding operations. A relatively high correlation between PMc and PMf (R2 = 0.63) indicated that the lower tail of the coarse particle fraction often impacts the fine particle fraction, increasing the PMf concentrations. Therefore, reductions in PMc sources will likely also reduce PMf concentrations, which also are near the value of the 24-hr PM2.5 NAAQS. Implications: In the desert southwest, summer monsoons are often associated with above average PM10 (<10 μm AD) mass concentrations. Competing influences of monsoon rain and wind events showed that rain suppresses ambient concentrations while high wind increase them. In this region, the PMc fraction dominates PM10 and crustal sources contribute 52-63% to local PMc mass concentrations on average. Cattle feedlot emissions are also an important source and a unique chemical signature was identified for this source. Observations suggest monsoon wind events alone cannot explain PM10 NAAQS exceedances, thus requiring these values to remain in compliance calculations rather than being removed as exceptional wind events.

Multifractal analysis of ground–level ozone concentrations at urban, suburban and rural background monitoring sites in Southwestern Iberian Peninsula

This paper seeks to enhance understanding of the data distribution of ground–level ozone time series by analysing their multifractal spectra. Emphasis is placed on the suitability of the box–counting and moments methods for characterizing scaling properties of ozone concentration, enabling us to describe similarities and differences inferred from the multifractal spectra by analysing various types of monitoring stations (urban, suburban and rural monitoring sites) under identical atmospheric conditions. It is herein demonstrated that that multifractal features are to a considerable extent similar for each type of monitoring station under warm atmospheric conditions and high solar radiation, owing to the fact that these weather characteristics homogenize the scaling behaviour of ozone. On the contrary, location and chemical precursors play a more prominent role under low temperatures and solar radiation, highlighting differences among multifractal features of ozone concentrations in the monitoring sites. At rural stations, the absence of anthropogenic emissions promotes less variability in ozone data and homogenization of multifractal behaviour throughout the year. Furthermore, a data shuffling procedure was performed in order to analyse changes occurring in multifractal spectra as time series are subjected to varying degrees of data position disturbance. Results indicate that multifractal analysis is a useful tool for describing the temporal scaling behaviour of ozone time series at different monitoring sites which refines results that have been traditionally provided by statistical analyses on ozone pollution.

Identification of haze-creating sources from fine particulate matter in Dhaka aerosol using carbon fractions

Fine particulate matter (PM2.5) samples were simultaneously collected on Teflon and quartz filters between February 2010 and February 2011 at an urban monitoring site (CAMS2) in Dhaka, Bangladesh. The samples were collected using AirMetrics MiniVol samplers. The samples on Teflon filters were analyzed for their elemental composition by PIXE and PESA. Particulate carbon on quartz filters was analyzed using the IMPROVE thermal optical reflectance (TOR) method that divides carbon into four organic carbons (OC), pyrolized organic carbon (OP), and three elemental carbon (EC) fractions. The data were analyzed by positive matrix factorization using the PMF2 program. Initially, only total OC and total EC were included in the analysis and five sources, including road dust, sea salt and Zn, soil dust, motor vehicles, and brick kilns, were obtained. In the second analysis, the eight carbon fractions (OC1, OC2, OC3, OC4, OP, EC1, EC2, EC3) were included in order to ascertain whether additional source information could be extracted from the data. In this case, it is possible to identify more sources than with only total OC and EC. The motor vehicle source was separated into gasoline and diesel emissions and a fugitive Pb source was identified. Brick kilns contribute 7.9 μg/m3 and 6.0 μg/m3 of OC and EC, respectively, to the fine particulate matter based on the two results. From the estimated mass extinction coefficients and the apportioned source contributions, soil dust, brick kiln, diesel, gasoline, and the Pb sources were found to contribute most strongly to visibility degradation, particularly in the winter. Implications: Fine particle concentrations in Dhaka, Bangladesh, are very high and cause significant degradation of urban visibility. This work shows that using carbon fraction data from the IMPROVE OC/EC protocol provides improved source apportionment. Soil dust, brick kiln, diesel, gasoline, and the Pb sources contribute strongly to haze, particularly in the winter.

One-Day Prediction of Biometeorological Conditions in a Mediterranean Urban Environment Using Artificial Neural Networks Modeling

The present study, deals with the 24-hour prognosis of the outdoor biometeorological conditions in an urban monitoring site within the Greater Athens area, Greece. For this purpose, artificial neural networks (ANNs) modelling techniques are applied in order to predict the maximum and the minimum value of the physiologically equivalent temperature (PET) one day ahead as well as the persistence of the hours with extreme human biometeorological conditions. The findings of the analysis showed that extreme heat stress appears to be 10.0&#x25; of the examined hours within the warm period of the year, against extreme cold stress for 22.8&#x25; of the hours during the cold period of the year. Finally, human thermal comfort sensation accounts for 81.8&#x25; of the hours during the year. Concerning the PET prognosis, ANNs have a remarkable forecasting ability to predict the extreme daily PET values one day ahead, as well as the persistence of extreme conditions during the day, at a significant statistical level of <svg style="vertical-align:-0.1638pt;width:58.712502px;" id="M1" height="11.375" version="1.1" viewBox="0 0 58.712502 11.375" width="58.712502" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg"> <g transform="matrix(.017,-0,0,-.017,.062,11.112)"><path id="x1D443" d="M619 482q0 -69 -40.5 -119t-96 -72.5t-118.5 -26.5h-44l-70 20l-31 -151q-14 -67 0.5 -83t89.5 -22l-5 -28h-287l8 28q65 7 81.5 22t29.5 83l79 398q12 56 0.5 70.5t-78.5 20.5l7 28h255q108 0 164 -43t56 -125zM524 478q0 141 -146 141q-25 0 -47 -8q-16 -6 -20.5 -13.5&#xA;t-10.5 -39.5l-43 -241q37 -13 83 -13q67 0 125.5 45t58.5 129z" /></g><g transform="matrix(.017,-0,0,-.017,15.582,11.112)"><path id="x3C" d="M512 -3l-437 233v51l437 233v-58l-378 -200v-2l378 -199v-58z" /></g><g transform="matrix(.017,-0,0,-.017,30.286,11.112)"><path id="x30" d="M241 635q53 0 94 -28.5t63.5 -76t33.5 -102.5t11 -116q0 -58 -11 -112.5t-34 -103.5t-63.5 -78.5t-94.5 -29.5t-95 28t-64.5 75t-34.5 102.5t-11 118.5q0 58 11.5 112.5t34.5 103t64.5 78t95.5 29.5zM238 602q-32 0 -55.5 -25t-35.5 -68t-17.5 -91t-5.5 -105&#xA;q0 -76 10 -138.5t37 -107.5t69 -45q32 0 55.5 25t35.5 68.5t17.5 91.5t5.5 105t-5.5 105.5t-18 92t-36 68t-56.5 24.5z" /></g><g transform="matrix(.017,-0,0,-.017,38.446,11.112)"><path id="x2E" d="M113 -12q-24 0 -39.5 16t-15.5 42q0 24 16 40.5t40 16.5t40 -16.5t16 -40.5q0 -26 -16 -42t-41 -16z" /></g><g transform="matrix(.017,-0,0,-.017,42.321,11.112)"><use xlink:href="#x30"/></g><g transform="matrix(.017,-0,0,-.017,50.481,11.112)"><path id="x31" d="M384 0h-275v27q67 5 81.5 18.5t14.5 68.5v385q0 38 -7.5 47.5t-40.5 10.5l-48 2v24q85 15 178 52v-521q0 -55 14.5 -68.5t82.5 -18.5v-27z" /></g> </svg>.

A regional assessment of marine vessel PM2.5 impacts in the U.S. Pacific Northwest using a receptor-based source apportionment method

This work reports results from a receptor-based source apportionment analysis using the Positive Matrix Factorization (PMF) model on chemically speciated PM2.5 data from 36 urban and rural monitoring sites within the U.S. Pacific Northwest. The approach taken is to model each site independently, treats monitor datasets with a common data preparation protocol, and uses a common modeling protocol. Complementary data from two monitoring networks, the urban Chemical Speciation Network (CSN) and rural Interagency Monitoring of Protected Visual Environments (IMPROVE) Network, was modeled for the period of 2007–2011. 15 different factor types were found for CSN sites and 17 for IMPROVE sites, however many factors occurred at only a few locations. Only 3 factor types were common in both networks: sulfate/sulfur rich, nitrate rich, and soil. However, for coastal and near coastal monitoring sites there were three additional factors common in both networks: sea salt, aged sea salt, and residual fuel oil combustion (RFO). This work presents annual average PM2.5 mass impacts for all sites and factors found and the results for RFO are explored in greater depth. The association between RFO results and commercial marine vessel emissions is made based on similarities between factor chemical profiles and published emissions profiles, comparisons with emissions inventories, and the similarity in the spatial extent of RFO factor locations to that of the other marine aerosols identified in this study, sea salt and aged sea salt. All 14 monitoring sites with marine vessel RFO factors showed a seasonal cycle of mass impacts, with lower impacts in winter months (monthly average PM2.5 between 0.1 μg m−3 and 0.9 μg m−3 in January) and higher impacts in summer months (monthly average PM2.5 between 0.3 μg m−3 and 2.7 μg m−3 in August). These results set a baseline to measure progress in emissions reductions that are expected from implementation of the North American Emissions Control Area (ECA) beginning in August 2012.

Volatile Organic Compounds in Ambient Air at Four Residential Locations in Seoul, Korea

To investigate the environmental behavior of volatile organic compounds (VOCs) in urban areas, their concentrations were measured at four urban monitoring sites (namely, N, S, E, and W) in Seoul, Korea (February to December 2009). A total of 27 compounds were quantified that consist of four chemical groups: aromatic (AR), halogenated aromatic, halogenated paraffin, and halogenated olefin. Results were evaluated by focusing on these four functional groups just mentioned and their summation term as total VOC (TVOC) along with several individual species (mainly AR species, that is, benzene, toluene, ethylbenzene, and xylene). The highest concentration of chemical groups was found from AR (71.1±42.1 ppbC), while that for individual species confirmed the dominance of toluene (7.48±3.88 ppb). The analysis of spatial distribution indicated that high TVOC levels were recorded at sites N and W, while it was not so significant such as S and E in terms of TVOC budget. Seasonal variation of these VOCs was characterized by the peak values in December to reflect the combined effects of pronounced source activities and meteorological conditions. Analysis of spatial variations in VOC levels between the four urban sites indicated that their distributions are tightly affected by local source processes in each area.

Winter Mass Concentrations of Carbon Species in PM10, PM2.5 and PM1 in Zagreb Air, Croatia

The purpose of our investigation was to examine the mass concentrations of EC, OC and TC (EC + OC) in PM(10), PM(2.5) and PM(1) particle fractions. Daily PM(10), PM(2.5) and PM(1) samples were collected at an urban background monitoring site in Zagreb during winter 2009. Average OC and EC mass concentrations were 11.9 and 1.8 μg m(-3) in PM(10), 9.0 and 1.4 μg m(-3) in PM(2.5), and 5.5 and 1.1 μg m(-3) in PM(1). Average OC/EC ratios in PM(10), PM(2.5), and PM(1) were 7.4, 6.9 and 5.4, respectively.

Selection of key ambient particulate variables for epidemiological studies — Applying cluster and heatmap analyses as tools for data reduction

The success of epidemiological studies depends on the use of appropriate exposure variables. The purpose of this study is to extract a relatively small selection of variables characterizing ambient particulate matter from a large measurement data set. The original data set comprised a total of 96 particulate matter variables that have been continuously measured since 2004 at an urban background aerosol monitoring site in the city of Augsburg, Germany. Many of the original variables were derived from measured particle size distribution (PSD) across the particle diameter range 3nm to 10μm, including size-segregated particle number concentration, particle length concentration, particle surface concentration and particle mass concentration. The data set was complemented by integral aerosol variables. These variables were measured by independent instruments, including black carbon, sulfate, particle active surface concentration and particle length concentration. It is obvious that such a large number of measured variables cannot be used in health effect analyses simultaneously. The aim of this study is a pre-screening and a selection of the key variables that will be used as input in forthcoming epidemiological studies.In this study, we present two methods of parameter selection and apply them to data from a two-year period from 2007 to 2008. We used the agglomerative hierarchical cluster method to find groups of similar variables. In total, we selected 15 key variables from 9 clusters which are recommended for epidemiological analyses. We also applied a two-dimensional visualization technique called “heatmap” analysis to the Spearman correlation matrix. 12 key variables were selected using this method. Moreover, the positive matrix factorization (PMF) method was applied to the PSD data to characterize the possible particle sources. Correlations between the variables and PMF factors were used to interpret the meaning of the cluster and the heatmap analyses.

Evaluation of the changes in the Madrid metropolitan area influencing air quality: Analysis of 1999–2008 temporal trend of particulate matter

During the 1999–2008 period a statistically significant downward trend in the concentrations of SO2, NOx, CO and PM2.5 was determined at most of the urban and urban-background monitoring sites in the Madrid metropolitan area. However, no statistically significant trend was detected in PM10 concentrations at any urban and rural site and in NO2 concentrations at the urban sites. The reduction in the annual coal consumption and in the number of gasoline vehicles and the use of particle filters for diesel engines in this area, have contributed to this reduction of SO2, CO and fine PM concentrations, but the increase of the diesel fleet is probably the cause of an increase of the NO2/NOx ratio and the lack of a decreasing trend of NO2 concentrations. Chemical characterisation and receptor modelling analysis results showed that mean contributions to PM10 and PM2.5 levels attributed to anthropogenic sources throughout the 1999–2008 period, decreased at the Madrid urban areas mainly by reductions in their carbonaceous and SO42− contents. However, the contribution of mineral dust to PM10 bulk levels did not significantly decrease at the urban sites. Thus, strategies aimed at reducing levels of PM10 and PM2.5 concentrations focussing mainly on road traffic and coal consumption, can be insufficient to reduce the number of days exceeding the PM10 Daily Limit Value (50 μg m−3) at some metropolitan areas, such as Madrid, where crustal content due to anthropogenic activities and natural phenomena is elevated even when the African dust contribution during episodic days is excluded. Changes in the structure of the metropolitan area such as the increase of the Madrid car fleet and of its proportion of diesel vehicles, could also contribute to keep or increase the concentration of other pollutants (NO2) which resulted in increases of the NO3− contribution to PM10 and PM2.5 levels.