Abstract  High time resolution measurements of fine particulate matter composition were a component of the St. Louis - Midwest Supersite in East St. Louis, IL. Measurements of fifteen particulate matter species (Al, As, Cd, Cr, Cu, Fe, Mn, Ni, Pb, Se, Zn, OC, EC, SO4=, and NO3-) were made using semi-continuous sampling and monitoring techniques. In this study, three weeks of the hourly species data have been combined with on-site surface winds data using conditional probability function (CPF) analysis and 1-D non-parametric regression (NPR) to identify the bearing of putative local emission sources. Typically there was good agreement between the CPF and NPR results and most (but not all) of the identified emission source bearings were consistent with the location of known emission sources. Differences between the CPF and NPR methods occurred when there were infrequent high concentration events, typically a single hour, which yielded a high expected concentration with NPR but a low conditional probability with CPF. Challenges to fully identifying the suite of local point sources impacting the monitoring site include the relatively poor representation of some wind directions in such a small data set, confounding by multiple emission sources at similar bearings, and for some elements high impacts from regional scale contributions. (C) Author(s) 2011. This work is distributed under the Creative Commons Attribution 3.0 License.

Abstract  The environmental protection conception increasing, the prediction of air quality is more and more important.The main Pollutant Standards Index (PSI) includes PM10, SO2, NO2, CO and O-3 etc... The PSI will be produced and changed when combining in the air. Due to the concentrations of CO, SO2, NO2, and PM10 have declined, the focus of health studies and control efforts has increasingly turned to PM10 and O-3 as the most important air pollutant species of concern. Correspondingly, the primary focus on the current understanding of the health is affected by PM10 and O-3 in the Taiwan. Therefore, this study uses O-3 attribute to evaluate air quality. This paper proposes an OWA based time series model to predict the air quality. Due to O-3 data is belong to time series pattern, and OWA operator can aggregate multiple lag periods into single aggregated value by different situation parameters alpha. Based on the advantages of TSM and OWA, the OWA based time series model can efficiently and accurately predict PSI. In verification, this paper collects a practical data to verify the proposed method. The dataset contains records of 1061 days with O-3 attribute from air qualities inspection station in Hsinchu city,Taiwan. From the results, the proposed method outperforms the listing methods.

Abstract  Ambient air pollution has been attributed with an increase in exacerbation frequencies among the cystic fibrosis (CF) population. This study correlates exacerbation frequency with proximity to roadways and two criteria air pollutants. Clinical data was extracted from the Cystic Fibrosis Foundation National Patient Registry and Electronic Medical Records at Children's Hospital Los Angeles (CHLA). Average annual air pollutant levels were obtained from selected US Environmental Protection Agency's monitoring stations. Geographic proximity to monitoring stations and roadways were analyzed using spatial mapping software. A total of 145 patients from the CHLA's CF center were characterized by a dichotomous exacerbation category. No significant association was determined between the frequency of exacerbations and exposure to fine particulate matter and ozone levels. Residential proximity to US-designated highways and freeways also did not achieve significance (p = 0.3777) but was noted to be correlated with major arterial roadways (p = 0.0420). Associations of environmental exposures may have important implications for future predictive models of CF clinical outcomes.

Abstract  Lanzhou is one of the most polluted cities in China. Sulfur dioxide (SO2) concentrations have shown evident seasonal variability. Pollution was generally within the second-level criterion (< 0.15 mg m(-3)) in spring, summer, and fall but was much higher than the second-level criterion and sometimes reaches mid-level pollution (API>200) in winter. Meteorological conditions (low winds, stable stratification) were found to be important for SO2 pollution. Observational and modeling studies conducted in the present study showed a close connection between static stability and SO2 pollution in Lanzhou, China, during winter. (C) 2008 Elsevier B.V. All rights reserved.

Abstract  A microwave digestion method in a closed vessel was developed for the determination of trace metals in atmospheric aerosols using inductively coupled plasma mass spectrometry (ICP-MS). A recovery study for the elements V, Cr, Mn, Fe, Co, Ni, Cu, Zn, As, Se, Cd, Sb, and Pb was conducted using multi-elemental standard solutions, NIST 1633b Trace Elements in Coal Fly Ash, and NIST 1648 Urban Particulate Matter. A simple digestion method using only HNO3/H2O2 gave good recoveries (90%-108%) for all elements except Cr in SRM 1648, but yielded low recoveries for SRM 1633b. A more robust method using HNO3/H2O2/HF/H3BO3 yielded higher recoveries (82%-103%) for the lighter elements (V-Zn) in SRM 1633b, and improved the Cr recovery in SRM 1648, but decreased the Se recovery in both SRMs. A comparative analysis of aerosol samples obtained at a remote mountain location Nathiagali, Pakistan (2.5 km above mean sea level), and Mayville, New York, downwind from the highly industrialized Midwestern United States, was carried out using Instrumental Neutron Activation Analysis (INAA) for the elements Cr, Mn, Fe, Co, Zn, As, Se, and Sb. The simple digestion method yielded excellent agreement for Cr, Fe, Zn, As, Se, and Sb, with slopes of the ICP-MS vs. INAA regressions of 0.90-1.00 and R2 values of 0.96-1.00. The regressions for Mn and Co had slopes of 0.82 and 0.84 with R2 values of 0.83 and 0.82, respectively. Addition of HF/H3BO3 did not improve the correlation for any of the elements and degraded the precision somewhat. The technique provides sensitivity and accuracy for trace elements in relatively small aerosol samples used in atmospheric chemistry studies related to SO2 oxidation in cloud droplets. The ability to determine concentrations of a very large number of elements from a single analysis will permit source apportionment of various trace pollutants and hence strategies to control the sources of air pollution. This is particularly important as the health effects of particulate matter are increasingly recognized.

Abstract  This paper examines the health implications of global PM reduction accompanying greenhouse gas emissions reductions in the 180 national economies of the global macroeconomy. A human health effects module based on empirical data on GHG emissions, PM emissions, background PM concentrations, source apportionment and human health risk coefficients is used to estimate reductions in morbidity and mortality from PM exposures globally as co-reduction of GHG reductions. These results are compared against the "fuzzy bright line" that often underlies regulatory decisions for environmental toxics, and demonstrate that the risk reduction through PM reduction would usually be considered justified in traditional risk-based decisions for environmental toxics. It is shown that this risk reduction can be on the order of more than 4 × 10(-3) excess lifetime mortality risk, with global annual cost savings of slightly more than $10B, when uniform GHG reduction measures across all sectors of the economy form the basis for climate policy ($2.2B if only Annex I nations reduce). Consideration of co-reduction of PM-10 within a climate policy framework harmonized with other environmental policies can therefore be an effective driver of climate policy. An error analysis comparing results of the current model against those of significantly more spatially resolved models at city and national scales indicates errors caused by the low spatial resolution of the global model used here may be on the order of a factor of 2.

Abstract  A set of daily PM10 (n=281) samples collected from April 2001 to April 2002 at a rural site (Erdemli), located on the coast of the Eastern Mediterranean, were analyzed applying Mass Closure (MC), absolute principal factor analysis (APFA) and Positive Matrix Factorization (PMF) to determine source contributions. The results from the three techniques were compared to identify the similarities and differences in the sources and source contributions. Source apportionment analysis indicated that PM10 were mainly originated from natural sources (sea salt +crustal approximate to 60%) whilst secondary aerosols and residual oil burning accounted for approximately 20% and 10% of the total PM10 mass, respectively. Calculations for sulfate showed that on average 8% and 12% of its total concentration were originated from sea salt and biogenic emissions, respectively. However, the contribution by biogenic emissions may reach up to a maximum of similar to 40% in the summer Potential Source Contribution Function (PSCF) analysis for identification of source regions showed that the Saharan desert was the main source area for crustal components. For secondary aerosol components the analysis revealed one source region, (i.e. the south-Eastern Black Sea), whereas for residual oil, Western Europe and the western Balkans areas were found to be the main Source regions. (C) 2009 Elsevier B.V. All rights reserved.

Abstract  PURPOSE OF REVIEW: This overview highlights recent experimental and epidemiological evidence for the programming effects of outdoor air pollution exposures during early development on lung function and chronic respiratory disorders, such as asthma and related allergic disorders.

RECENT FINDINGS: Air pollutants may impact anatomy and/or physiological functioning of the lung and interrelated systems. Programming effects may result from pollutant-induced shifts in a number of molecular, cellular, and physiological states and their interacting systems. Specific key regulatory systems susceptible to programming may influence lung development and vulnerability to respiratory diseases, including both central and peripheral components of neuroendocrine pathways and autonomic nervous system (ANS) functioning which, in turn, influence the immune system. Starting in utero, environmental factors, including air pollutants, may permanently organize these systems toward trajectories of enhanced pediatric (e.g., asthma, allergy) as well as adult disease risk (e.g., chronic obstructive pulmonary disease). Evidence supports a central role of oxidative stress in the toxic effects of air pollution. Additional research suggests xenobiotic metabolism and subcellular components, such as mitochondria are targets of ambient air pollution and play a role in asthma and allergy programming. Mechanisms operating at the level of the placenta are being elucidated. Epigenetic mechanisms may be at the roots of adaptive developmental programming.

SUMMARY: Optimal coordinated functioning of many complex processes and their networks of interaction are necessary for normal lung development and the maintenance of respiratory health. Outdoor air pollution may play an important role in early programming of respiratory health and is potentially amenable to intervention.

Abstract  TSP samples and gas phase air samples were collected by an improved high volume active air sampler during domestic heating season in Xi'an, and the concentrations of polycyclic aromatic hydrocarbons (PAHs) were analyzed via GC-MS. The results showed that average concentrations of sigma 16 PAHs in TSP and gas phase were (108.15 +/- 41.44) ng/m3, (260.14 +/- 99.84) ng/m3, respectively. Two and three ring PAHs dominated in the gas phase, while more than four ring PAHs were mainly adsorbed on the particle phase. Good correlation was found between gas-particle partition coefficient and the respective sub-cooled vapor pressures of PAHs. A significant correlation was also found between partition coefficient and temperature, and the regression equation was put forward by stepwise linear regression method. Ratio analysis illustrated that coal burning and vehicle exhaust were the main source of PAHs in Xi' an. Contribution of each source was calculated by factor analysis and multiple linear regression. Partial correlation analysis was applied to study the relationship between air pollution indexes and some representative PAHs of individual factors, which indicated some PAH had same source to SO2 and NO2.

Abstract  Since the U.S. Environmental Protection Agency began widespread monitoring of PM2.5 (particulate matter <2.5 mu in diameter) concentration levels in the late 1990s, the epidemiological community has performed several observational studies directly relating PM2.5 concentration to various health endpoints including mortality and morbidity. However, recent research suggests that human exposure to the constituents of PM2.5 may differ significantly from ambient (or outdoor) PM2.5 concentration measured by monitors because people spend a great deal of time in environments, such as various indoor environments, where they are partially shielded from ambient sources of PM and are exposed to nonambient sources of PM. Recent research has provided some ways to include exposure information, but little has been done to determine the impact of including such information in a statistical model. To address this concern, we develop a three-stage Bayesian hierarchical model based on the Poisson regression model that is traditionally used to characterize the relationship between PM2.5 concentration and health endpoints. Our approach includes a spatial model relating monitor readings to average county PM2.5 concentration and an exposure simulator that links average ambient PM2.5 concentration to average personal exposure using activity pattern data. We apply our model to a study population in North Carolina and explore the impact of various exposure modeling assumptions on the conclusions that can be drawn about the link between PM2.5 exposure and cardiovascular mortality.

Abstract  Multiple environmental factors including hormones, dietary factors, infections, and exposure to tobacco smoke, as well as gene-environment interactions, have been associated with increased risk for rheumatoid arthritis (RA). The growing understanding of the prolonged period before the first onset of symptoms of RA suggests that these environmental and genetic factors are likely acting to drive the development of RA-related autoimmunity long before the appearance of the first joint symptoms and clinical findings that are characteristic of RA. This article reviews these factors and interactions, especially those that have been investigated in a prospective fashion before the symptomatic onset of RA.

Abstract  Outdoor air pollution poses risks to human health in communities around the world, and research on populations who are most susceptible continues to reveal new insights. Human susceptibility to adverse health effects from exposure to air pollution can be related to underlying disease; demographic or anthropometric characteristics; genetic profile; race and ethnicity; lifestyle, behaviors, and socioeconomic position; and location of residence or daily activities. In health research, an individual or group may have an enhanced responsiveness to a given, identical level of pollution exposure compared to those who are less susceptible. Or, people in these different groups may experience varying levels of exposure (for example, a theoretically homogeneous population whose members differ only by proximity to a road). Often the information available for health research may relate to both exposure and enhanced response to a given dose of pollution. This paper discusses the general direction of research on susceptibility to air pollution, with a general though not an exclusive focus on particulate matter, with specific examples of research on susceptibility related to cardiovascular disease, diabetes, asthma, and genetic and epigenetic features. We conclude by commenting how emerging knowledge of susceptibility can inform policy for controlling pollution sources and exposures to yield maximal health benefit and discuss two areas of emerging interest: studying air pollution and its connection to perinatal health, as well as land use and urban infrastructure design.

Abstract  Ambient air pollution has been associated with increased mortality and morbidity; however, few studies have examined the short-term effect of air pollution specifically on chronic obstructive pulmonary disease (COPD), which is an important cause of mortality and morbidity world wide. In this analysis, we examined the associations between daily air pollution levels [particulate matter less than 10 microns in aerodynamic diameter (PM10), sulfur dioxide (SO2) and nitrogen dioxide (NO2)] and COPD mortality in four Chinese cities. We used Poisson regression models with natural spline smoothing functions to adjust for long-term and seasonal trends of COPD mortality, as well as other time-varying covariates. We did a meta-analysis to obtain the 4-city average estimates. Air pollution (PM10, SO2, and NO2) was found to be associated with increased risk of COPD mortality in these four cities. Using the random-effects model, an increase of 10 mu g m(-3) of 2-day moving average concentrations of PM10, SO2 and NO2 corresponded to a 0.78% (95% CI, 0.13-1.42), 1.30% (95% CI, 0.61-1.99), and 1.78% (95% CI, 1.10-2.46) increase of COPD mortality, respectively. The concentration response curves indicated linear associations without threshold. Only NO2 remained significant in the multi-pollutant models. To our knowledge, this is the first multi-city study in Asian developing region to report the short-term effect of air pollution on COPD mortality. Our results contribute to very limited data on the effects of air pollution on COPD mortality for high exposure settings typical in developing countries. (C) 2013 Elsevier Ltd. All rights reserved.

Abstract  Exposures to airborne metals are known to cause physiological responses in organisms and wide-ranging health effects in humans. Hence determination of metals in particulate matter is important from a toxicological perspective. In the current study heavy metals associated with respirable (RSPM) and nonrespirable (NRSPM) fractions of suspended particulate matter were estimated in air samples from six stations in Coimbatore, India, during March 1999 to February 2001. The mean quantity of heavy metals in RSPM was in the order Zn > Cu > Pb > Ni > Cr > Cd. Concentrations of these heavy metals were in the range of BDL (below detectable level) to 2,147 ng/m3 in RSPM. The highest level of lead (2,147 ng/m(3)) was recorded at an industrial station. The station also had the highest mean value (481 +/- 544.3 ng/m(3)), suggesting the importance of industrial operations in determining the ambient concentrations of lead. Significant positive correlation among metals excepting lead and copper suggests that they originate mostly from a common source. Air samples of urban and industrial areas showed higher concentrations than residential (Urban) and suburban areas.

Abstract  The health burden of environmental exposures, including ambient air pollution and climate-change-related health impacts, is not equally distributed between or within regions and countries. These inequalities are currently receiving increased attention in environmental research as well as enhanced appreciation in environmental policy, where calls for environmental equity are more frequently heard. The World Health Organization (WHO) 2006 Global Update of the Air Quality Guidelines attempted to address the global-scale inequalities in exposures to air pollution and the burden of diseases due to air pollution. The guidelines stop short, however, of addressing explicitly the inequalities in exposure and adverse health effects within countries and urban areas due to differential distribution of sources of air pollution such as motor vehicles and local industry, and differences in susceptibility to the adverse health effects attributed to air pollution. These inequalities, may, however, be addressed in local air quality and land use management decisions. Locally, community-based participatory research can play an important role in documenting potential inequities and fostering corrective action. Research on environmental inequities will also benefit from current efforts to (1) better understand social determinants of health and (2) apply research evidence to reduce health disparities. Similarly, future research and policy action will benefit from stronger linkages between equity concerns related to health consequences of both air pollution exposure and climate change, since combustion products are important contributors to both of these environmental problems.

Abstract  In the last years numerous epidemiological studies were carried out about particulate matter effects on human health. Even if there is no agreement among the epidemiological and toxicological studies about the importance of total particle concentrations in terms of number, area or mass having the major negative effects on human health, it seems that the aerosol number concentrations plays a predominant role. For this reason, international standards move the attention from PM(10) to PM(2.5) even if the number concentration is still not considered. In industrialized areas, the highest contribution to the fine and ultrafine particles comes from anthropogenic activities, namely from emissions of industrial combustion processes and traffic-related emissions (Cass et al., 2000). For this reason it is important to estimate the total particle number emission for each anthropogenic source and to understand the evolution of the particle size distribution (PSD) near these emission points. Zhu et al. (2004) have characterized the PSD evolution near major highway in Los Angeles showing the PSD seasonal trends and PSD evolution at different distances from the highways. Similar analysis were conducted by Kittelson on Minnesota highways (Kittelson et al., 2004). Fine et al., 2004 have obtained an ultrafine particle source apportionment in Los Angeles' industrial area. In this study the authors evaluate the PSD spatial and temporal variations in the San Vittore del Lazio industrialized area in Italy in which there are two main sources of emission: an highway and a municipal waste incinerator (MWI) plant. The main aim is to comprehend how these two sources can influence the background aerosol PSD of the area. In particular, an experimental campaign was carried out by means of a TSI 3936 Scanning Mobility Particle Sizer (R) (SMPS) and a TSI 3321 Aerodynamic Particle Sizer (R) (APS) Spectrometers.

Abstract  The aim of the study was to determine whether the area of Tanggu, Tianjin Binhai New Economic Developing Area, China, is subject to similar effects of ambient particulate matter less than 10 micrometres in aerodynamic diameter (PM10) similar to other areas of China. This study was designed to investigate cause-specific mortality risks associated with air pollution in this geographical region. The present study used a time-series analysis to explore the relationship between PM10 and the cause-specific mortalities for non-accidental, cardiovascular, and cardiopulmonary mortality from 1 January 2006 to 31 December 2010. A 10 μg/m(3) increment of PM10 was associated with a 1.02% (95% confidence interval (CI): 0.48, 1.56) increase in cardiovascular mortality, and a 0.88% (95% CI: 0.36, 1.39) increase in cardiopulmonary mortality. In addition, the effects from PM10 appear to be consistent with multi-pollutant models. The results show that there are strong associations between daily cardiovascular and cardiopulmonary mortality and ambient PM10 exposure.

Abstract  Under Executive Order 12898, the U.S. Environmental Protection Agency (EPA) must perform environmental justice (EJ) reviews of its rules and regulations. EJ analyses address the hypothesis that environmental disamenities are experienced disproportionately by poor and/or minority subgroups. Such analyses typically use communities as the unit of analysis. While community-based approaches make sense when considering where polluting sources locate, they are less appropriate for national air quality rules affecting many sources and pollutants that can travel thousands of miles. We compare exposures and health risks of EJ-identified individuals rather than communities to analyze EPA's Heavy Duty Diesel (HDD) rule as an example national air quality rule. Air pollutant exposures are estimated within grid cells by air quality models; all individuals in the same grid cell are assigned the same exposure. Using an inequality index, we find that inequality within racial/ethnic subgroups far outweighs inequality between them. We find, moreover, that the HDD rule leaves between-subgroup inequality essentially unchanged. Changes in health risks depend also on subgroups' baseline incidence rates, which differ across subgroups. Thus, health risk reductions may not follow the same pattern as reductions in exposure. These results are likely representative of other national air quality rules as well.

Abstract  An air quality index (AQI) is proposed for the City of Kanpur, India, for simplified public information and data interpretation. A maximum operator concept is used to determine the overall AQI; maximum value of sub-indices (of each pollutant) is taken as the overall AQI. The mathematical functions for calculating sub-indices are proposed based on health criteria of the USEPA and Indian air quality standards. The pollutants included in the AQI are: SO2, SPM (suspended particulate matter), O-3, NO2, PM10 (particulate matter with a diameter of 10 mum or less), and CO. The investigations into data interpretation using the AQI for Kanpur city have shown that air quality worsens (very poor to severe) in winter months and also during the early summer months (March, April, and part of May). These months are characterized by dusty winds resulting in high SPM. The air quality generally improves in monsoon and post-monsoon period (good to moderate) as rain washes out the pollutants. Over 95% of the time, sub-index values corresponding to SPM levels were responsible for overall AQI.

Abstract  In this study, a source-oriented version of the Community Multiscale Air Quality (CMAQ) model was developed and used to quantify the contributions of five major local emission source types in Southeast Texas (vehicles, industry, natural gas combustion, wildfires, biogenic sources), as well as upwind sources, to regional primary and secondary formaldehyde (HCHO) concentrations. Predicted HCHO concentrations agree well with observations at two urban sites (the Moody Tower [MT] site at the University of Houston and the Haden Road #3 [HRM-3] site operated by Texas Commission on Environmental Quality). However, the model underestimates concentrations at an industrial site (Lynchburg Ferry). Throughout most of Southeast Texas, primary HCHO accounts for approximately 20-30% of total HCHO, while the remaining portion is due to secondary HCHO (30-50%) and upwind sources (20-50%). Biogenic sources, natural gas combustion, and vehicles are important sources of primary HCHO in the urban Houston area, respectively, accounting for 10-20%, 10-30%, and 20-60% of total primary HCHO. Biogenic sources, industry, and vehicles are the top three sources of secondary HCHO, respectively, accounting for 30-50%, 10-30%, and 5-15% of overall secondary HCHO. It was also found that over 70% of PAN in the Houston area is due to upwind sources, and only 30% is formed locally. The model-predicted source contributions to HCHO at the MT generally agree with source apportionment results obtained from the Positive Matrix Factorization (PMF) technique. Citation: Zhang, H., J. Li, Q. Ying, B. B. Guven, and E. P. Olaguer (2013), Source apportionment of formaldehyde during TexAQS 2006 using a source-oriented chemical transport model, J. Geophys. Res. Atmos., 118, 1525-1535, doi:10.1002/jgrd.50197.

Abstract  The aim of this study is to obtain the characteristic inorganic chemical profile of important particle sources identified in the integrated iron and steel process: sintering, blast furnace, steelmaking and desulfurization slag processing. A complete chemical and physical characterization program was developed: particle size distribution, chemical analysis, XRD, SEM-EDX and TGA/DTA. The sample collected from the sinter stack showed high levels of K and Cl-, followed by Fe, NH4+, Ca, Na and Pb. The profile of the dust samples taken from the sinter cake discharge zone was quite different, showing higher amounts of Fe, Ca and Al, and lower amounts of K, Cl-, Na and Pb. Dust samples collected from the blast furnace (BF) and steelmaking cast house may be distinguished from each other based on the higher levels of Fe (hematite and magnetite) and lower levels of Ca, Zn and C (graphite) found in BF dust. High levels of Ca and Fe were found in samples taken from the desulfurization slag processing area. Such information can be useful for source apportionment studies at receptor sites that could be influenced by iron and steelmaking plant emissions. (C) 2013 Elsevier B.V. All rights reserved.

Abstract  One year of high-volume PM2.5 filter samples were collected from 2004 to 2005 at one rural site and three urban sites in the Southeastern Aerosol Research and Characterization (SEARCH) network. These filters were analyzed for both organic tracers and carbon isotopes. Sources for primary carbon were previously apportioned based on molecular marker-based chemical mass balance modeling (CMB-MM). In this study, these primary sources were further classified into two categories as having fossil and contemporary origins. 14C data were used to estimate the relative contributions of fossil and contemporary contents in total carbon (TC). Combined these two sets of independent results, fossil and contemporary contributions to secondary carbon source, which was estimated by the unexplained OC in CMB-MM, were calculated. The fossil secondary organic carbon (SOCF) and the contemporary secondary organic carbon (SOCC) ranged from 0.56 to 3.20 microgC/m3 and 0.82 to 4.09 microgC/m3, respectively. SOCF was higher at urban sites and exhibited small seasonal variation at all sites, probably resulting from higher fossil precursor emissions in urban areas. In contrast, SOCC was higher at the rural site and exhibited obvious seasonal variation at all sites. During the whole year SOCF was the major secondary organic carbon (SOC) contributor at the urban sites, while SOCC dominated SOC at the rural site. In summer isoprene-derived SOC showed a large contribution to SOCC and exhibited significant positive correlation with SOCC, indicating the importance of isoprene-derived secondary organic aerosol (SOA) formation during summer. It is interesting to note that the secondary items, including SOCF, SOCC, secondary sulfate, and secondary ammonium, exhibited significant correlations between the monitoring sites, suggesting the regional impact of secondary aerosol in the southeastern United States.

Abstract  This study aims to analyze the short-term association between concentration of atmospheric pollutants and the mortality of elderly in the city of Curitiba (Brazil). The data comprised the period from 2003 to 2008. The relationships between the pollutants sulfur dioxide (SO2), ozone (O-3) and total suspended particles (TSP) and the number of total deaths (ObT) and deaths due to respiratory deceases (ObR) of people aged over 60 years were investigated with simple correlation and multiple regression analyses, using a generalized additive model (GAM). The results showed a positive and statistically significant relationship between TSP concentrations and elderly mortality from all causes (ObT), even considering that TSP concentrations met the air quality standards during the period of study.