Deconstruction of annoyance due to air pollution by multiple correspondence analyses

Annoyance caused by air pollution is a matter of public health as it can cause stress and ill-health and affect quality of life, among other burdens. The aim of this study is to apply the multiple correspondence analyses (MCA) technique as a differential tooling to explore relationships between variables that can influence peoples’ behaviour concerning annoyance caused by air pollution. Data were collected through a survey on air pollution, environmental issues and quality of life. Face-to-face survey studies were conducted in two industrialized urban areas (Vitoria in Brazil and Dunkirk in France). These two regions were chosen as their inhabitants often report feeling annoyed by air pollution, and both regions have similar industrial characteristics. The results showed a progressive correspondence between levels of annoyance and other active variables in the “air pollution” factor group: as the levels of annoyance increased, the levels of the other qualitative variables (importance of air quality, perceived exposure to industrial risk, assessment of air quality, perceived air pollution) also increased. Respondents who reported feeling annoyed by air pollution also thought that air quality was very important and were very concerned about exposure to industrial risks. Furthermore, they often assessed air quality as horrible, and they could frequently perceive air pollution by dust, odours and decreased visibility. The results also showed a statistically significant association between occurrence of allergies and high levels of annoyance.

     

Validity of Ambient Levels of Fine Particles as Surrogate for Personal Exposure to Outdoor Air Pollution—Results of the European EXPOLIS-EAS Study (Swiss Center Basel)

ABSTRACT

To evaluate the validity of fixed-site fine particle levels as exposure surrogates in air pollution epidemiology, we considered four indicator groups: (1) PM₂₅ total mass concentrations, (2) sulfur and potassium for regional air pollution, (3) lead and bromine for traffic-related particles, and (4) calcium for crustal particles. Using data from the European EXPOLIS (Air Pollution Exposure Distribution within Adult Urban Populations in Europe) study, we assessed the associations between 48-hr personal exposures and home outdoor levels of the indicators. Furthermore, within-city variability of fine particle levels was evaluated.

Personal exposures to PM_2.5 mass were not correlated to corresponding home outdoor levels (n = 44, r_{S (S)} =r o v ' Spearman (Sp) 0.07). In the group reporting neither relevant indoor sources nor relevant activities, personal exposures and home outdoor levels of sulfur were highly correlated (n = 40, r_Sp = 0.85). In contrast, the associations were weaker for traffic (Pb: n = 44, r_Sp = 0.53; Br: n = 44, r_Sp = 0.21) and crustal (Ca: n = 44, r_Sp = 0.12) indicators. This contrast is consistent with spatially homogeneous regional pollution and higher spatial variability of traffic and crustal indicators observed in Basel, Switzerland.

We conclude that for regional air pollution, fixed-site fine particle levels are valid exposure surrogates. For source-specific exposures, however, fixed-site data are probably not the optimal measure. Still, in air pollution epidemiology, ambient PM_2.5 levels may be more appropriate exposure estimates than total personal PM_2.5 exposure, since the latter reflects a mixture of indoor and outdoor sources.     

Fine Particle (PM25) Measurement Methodology,Quality Assurance Procedures,and Pilot Results of the EXPOLIS Study

ABSTRACT

EXPOLIS is a European multicenter (Athens, Basel, Grenoble, Helsinki, Milan, and Prague) air pollution exposure study. It is the first international, population-based, large-scale study, where personal exposures to PM_{2 5} aerosol particles (together with volatile organic compounds and carbon monoxide) are being monitored. EXPOLIS is performed in six different centers across Europe, the sampled aerosol concentrations vary greatly, and the mi-croenvironmental samples are not collected with the same equipment as the personal samples. Therefore careful equipment selection, methods development and testing, and thorough quality assurance and quality control (QA & QC) procedures are essential for producing reliable and comparable PM_2.5 data. This paper introduces the equipment, the laboratory test results, the pilot results, the standard operating procedures, and the QA & QC procedures of EXPOLIS. Test results show good comparability and repeatability between personal and microenvironmen-tal monitors for PM2.5 at different concentration levels measured across Europe in EXPOLIS centers.     

Exposure of population and microenvironmental distributions of volatile organic compound concentrations in the EXPOLIS study

Determination of volatile organic compounds (VOCs) formed one part of the EU-EXPOLIS project in which the exposure of European urban populations to particles and gaseous pollutants was studied. The EXPOLIS study concentrated on 30 target VOCs selected on the basis of environmental and health significance and usability of the compounds as markers of pollution sources. In the project, 201 subjects in Helsinki, 50 in Athens, 50 in Basel, 50 in Milan and, 50 in Oxford and 50 in Prague were selected for the final exposure sample. The microenvironmental and personal exposure concentrations of VOCs were the lowest in Helsinki and Basel, while the highest concentrations were measured in Athens and Milan; Oxford and Prague were in between. In all cities, home indoor air was the most significant exposure agent. Workplace indoor air concentrations measured in this study were generally lower than the home indoor concentrations and home outdoor air played a minor role as an exposure agent. When estimating the measured personal exposure concentrations using the measured concentrations and time fractions spent at home indoors, at home outdoors, and at the workplace, it could be concluded that these three microenvironments do not fully explain the personal exposure. Other important sources for personal exposure must be encountered, the most important being traffic/transportation and other indoor environments not measured in this study.     

Extended effects of air pollution on cardiopulmonary mortality in Vienna

BackgroundCurrent standards for fine particulates and nitrogen dioxide are under revision. Patients with cardiovascular disease have been identified as the largest group which need to be protected from effects of urban air pollution.MethodsWe sought to estimate associations between indicators of urban air pollution and daily mortality using time series of daily TSP, PM₁₀, PM_2.5, NO₂, SO₂, O₃ and nontrauma deaths in Vienna (Austria) 2000–2004. We used polynomial distributed lag analysis adjusted for seasonality, daily temperature, relative humidity, atmospheric pressure and incidence of influenza as registered by sentinels.ResultsAll three particulate measures and NO₂ were associated with mortality from all causes and from ischemic heart disease and COPD at all ages and in the elderly. The magnitude of the effect was largest for PM_2.5 and NO₂. Best predictor of mortality increase lagged 0–7 days was PM_2.5 (for ischemic heart disease and COPD) and NO₂ (for other heart disease and all causes). Total mortality increase, lagged 0–14 days, per 10 μg m⁻³ was 2.6% for PM_2.5 and 2.9% for NO₂, mainly due to cardiopulmonary and cerebrovascular causes.ConclusionAcute and subacute lethal effects of urban air pollution are predicted by PM_2.5 and NO₂ increase even at relatively low levels of these pollutants. This is consistent with results on hospital admissions and the lack of a threshold. While harvesting (reduction of mortality after short increase due to premature deaths of most sensitive persons) seems to be of minor importance, deaths accumulate during 14 days after an increase of air pollutants. The limit values for PM_2.5 and NO₂ proposed for 2010 in the European Union are unable to prevent serious health effects.     

Personal exposures to NO2 in the EXPOLIS-study: relation to residential indoor,outdoor and workplace concentrations in Basel,Helsinki and Prague

Personal exposures, residential indoor, outdoor and workplace levels of nitrogen dioxide (NO₂) were measured for 262 urban adult (25–55 years) participants in three EXPOLIS centres (Basel; Switzerland, Helsinki; Finland, and Prague; Czech Republic) using passive samplers for 48-h sampling periods during 1996–1997. The average residential outdoor and indoor NO₂ levels were lowest in Helsinki (24±12 and 18±11 μg m⁻³, respectively), highest in Prague (61±20 and 43±23 μg m⁻³), with Basel in between (36±13 and 27±13 μg m⁻³). Average workplace NO₂ levels, however, were highest in Basel (36±24 μg m⁻³), lowest in Helsinki (27±15 μg m⁻³), with Prague in between (30±18 μg m⁻³). A time-weighted microenvironmental exposure model explained 74% of the personal NO₂ exposure variation in all centres and in average 88% of the exposures. Log-linear regression models, using residential outdoor measurements (fixed site monitoring) combined with residential and work characteristics (i.e. work location, using gas appliances and keeping windows open), explained 48% (37%) of the personal NO₂ exposure variation. Regression models based on ambient fixed site concentrations alone explained only 11–19% of personal NO₂ exposure variation. Thus, ambient fixed site monitoring alone was a poor predictor for personal NO₂ exposure variation, but adding personal questionnaire information can significantly improve the predicting power.     

Long-term associations of morbidity with air pollution: A catalog and synthesis

I searched the National Institutes of Health MEDLINE database through January 2017 for long-term studies of morbidity and air pollution and cataloged them with respect to cardiovascular, respiratory, cancer, diabetes, hospitalization, neurological, and pregnancy-birth endpoints. The catalog is presented as an online appendix. Associations with PM_2.5 (particulate matter with an aerodynamic diameter <2.5 μm), PM₁₀ (PM with an aerodynamic diameter <10 μm), and nitrogen dioxide (NO₂) were evaluated most frequently among the 417 ambient air quality studies identified. Associations with total suspended particles (TSP), carbon, ozone, sulfur, vehicular traffic, radon, and indoor air quality were also reported. I evaluated each study in terms of pollutant significance (yes, no), duration of exposure, and publication date. I found statistically significant pollutant relationships (P < 0.05) in 224 studies; 220 studies indicated adverse effects. Among 795 individual pollutant effect estimates, 396 are statistically significant. Pollutant associations with cardiovascular indicators, lung function, respiratory symptoms, and low birth weight are more likely to be significant than with disease incidence, heart attacks, diabetes, or neurological endpoints. Elemental carbon (EC), traffic, and PM_2.5 are most likely to be significant for cardiovascular outcomes; TSP, EC, and ozone (O₃) for respiratory outcomes; NO₂ for neurological outcomes; and PM₁₀ for birth/pregnancy outcomes. Durations of exposure range from 60 days to 35 yr, but I found no consistent relationships with the likelihood of statistical significance. Respiratory studies began ca. 1975; studies of diabetes, cardiovascular, and neurological effects increased after about 2005. I found 72 studies of occupational air pollution exposures; 40 reported statistically significant adverse health effects, especially for respiratory conditions. I conclude that the aggregate of these studies supports the existence of nonlethal physiological effects of various pollutants, more so for non–life-threatening endpoints and for noncriteria pollutants (TSP, EC, PM_2.5 metals). However, most studies were cross-sectional analyses over limited time spans with no consideration of lag or disease latency. Further longitudinal studies are thus needed to investigate the progress of disease incidence in association with air pollution exposure.

Implications: Relationships of air pollution with excess mortality are better known than with long-term antecedent morbidity. I cataloged 489 studies of cardiovascular, respiratory, cancer, and neurological effects, diabetes, and birth outcomes with respect to 12 air pollutants. About half of the studies reported statistically significant relationships, more frequently with noncriteria than with criteria pollutants. Indoor and cumulative exposures, coarse or ultrafine particles, and organic carbon were seldom considered. Significant relationships were more likely with less-severe endpoints such as blood pressure, lung function, or respiratory symptoms than with incidence of cancer, chronic obstructive pulmonary disease (COPD), heart failure, or diabetes. Most long-term studies are based on spatial relationships; longitudinal studies are needed to link the progression of pollution-related morbidity to mortality, especially for the cardiovascular system.     

Ambient air pollution and term birth weight in Texas from 1998 to 2004

Previous studies have explored the association between air pollution levels and adverse birth outcomes such as lower birth weight. Existing literature suggests an association, although results across studies are not consistent. Additional research is needed to confirm the effect, investigate the exposure window of importance, and distinguish which pollutants cause harm.

We assessed the association between ambient pollutant concentrations and term birth weight for 1,548,904 births in TX from 1998 to 2004. Assignment of prenatal exposure to air pollutants was based on maternal county of residence at the time of delivery. Pollutants examined included particulate matter with aerodynamic diameter ≤10 and ≤2.5 µm (PM₁₀ and PM_2.5), sulfur dioxide (SO₂), nitrogen dioxide (NO₂), carbon monoxide (CO), and ozone (O₃). We applied a linear model with birth weight as a continuous variable. The model was adjusted for known risk factors and region. We assessed pollutant effects by trimester to identify biological exposure window of concern, and explored interaction due to race/ethnicity.

An interquartile increase in ambient pollutant concentrations of SO₂ and O₃ was associated with a 4.99-g (95% confidence interval [CI], 1.87–8.11) and 2.72-g (95% CI, 1.11–4.33) decrease in birth weight, respectively. Lower birth weight was associated with exposure to O₃ in the first and second trimester, whereas results were not significant for other pollutants by trimester. A positive association was exhibited for PM_2.5 in the first trimester. Effects estimates for PM₁₀ and PM_2.5 were inconsistent across race/ethnic groups.

Current ambient air pollution levels may be increasing the risk of lower birth weight for some pollutants. These risks may be increased for certain racial/ethnic groups. Additional research including consideration of improved methodology is needed to investigate these findings. Future studies should examine the influence of residual confounding.

Implications: This is one of the most comprehensive studies examining criteria air pollutants and lower birth weight in Texas. Our findings confirm results found previously for adverse effects of the air pollutant SO₂ on lower birth weight. Results from our study suggest that adverse pregnancy outcomes such as lower birth weight can occur even while maintaining air pollution levels below regulatory standards. Future studies should incorporate the assessment of differential pollutant exposure as well as effect estimates by race/ethnicity with individual and community-level social factors in order to enhance our understanding of how physical, social, and host factors influence birth outcomes.

Supplemental Materials: Supplementary information relating to characteristics of excluded births, distribution of air pollutant monitors by pollutant, and correlation coefficients of the air pollutants is available in the publisher's online edition of the Journal of the Air & Waste Management Association.     

Validity of ambient levels of fine particles as surrogate for personal exposure to outdoor air pollution--results of the European EXPOLIS-EAS Study (Swiss Center Basel)

To evaluate the validity of fixed-site fine particle levels as exposure surrogates in air pollution epidemiology, we considered four indicator groups: (1) PM2.5 total mass concentrations, (2) sulfur and potassium for regional air pollution, (3) lead and bromine for traffic-related particles, and (4) calcium for crustal particles. Using data from the European EXPOLIS (Air Pollution Exposure Distribution within Adult Urban Populations in Europe) study, we assessed the associations between 48-hr personal exposures and home outdoor levels of the indicators. Furthermore, within-city variability of fine particle levels was evaluated. Personal exposures to PM2.5 mass were not correlated to corresponding home outdoor levels (n = 44, rSpearman (Sp) = 0.07). In the group reporting neither relevant indoor sources nor relevant activities, personal exposures and home outdoor levels of sulfur were highly correlated (n = 40, rSp = 0.85). In contrast, the associations were weaker for traffic (Pb: n = 44, rSp = 0.53; Br: n = 44, rSp = 0.21) and crustal (Ca: n = 44, rSp = 0.12) indicators. This contrast is consistent with spatially homogeneous regional pollution and higher spatial variability of traffic and crustal indicators observed in Basel, Switzerland. We conclude that for regional air pollution, fixed-site fine particle levels are valid exposure surrogates. For source-specific exposures, however, fixed-site data are probably not the optimal measure. Still, in air pollution epidemiology, ambient PM2.5 levels may be more appropriate exposure estimates than total personal PM2.5 exposure, since the latter reflects a mixture of indoor and outdoor sources.     

Predicting residential indoor concentrations of nitrogen dioxide,fine particulate matter,and elemental carbon using questionnaire and geographic information system based data

Previous studies have identified associations between traffic-related air pollution and adverse health effects. Most have used measurements from a few central ambient monitors and/or some measure of traffic as indicators of exposure, disregarding spatial variability and factors influencing personal exposure-ambient concentration relationships. This study seeks to utilize publicly available data (i.e., central site monitors, geographic information system, and property assessment data) and questionnaire responses to predict residential indoor concentrations of traffic-related air pollutants for lower socioeconomic status (SES) urban households.As part of a prospective birth cohort study in urban Boston, we collected indoor and outdoor 3–4 day samples of nitrogen dioxide (NO₂) and fine particulate matter (PM_2.5) in 43 low SES residences across multiple seasons from 2003 to 2005. Elemental carbon (EC) concentrations were determined via reflectance analysis. Multiple traffic indicators were derived using Massachusetts Highway Department data and traffic counts collected outside sampling homes. Home characteristics and occupant behaviors were collected via a standardized questionnaire. Additional housing information was collected through property tax records, and ambient concentrations were collected from a centrally located ambient monitor.The contributions of ambient concentrations, local traffic and indoor sources to indoor concentrations were quantified with regression analyses. PM_2.5 was influenced less by local traffic but had significant indoor sources, while EC was associated with traffic and NO₂ with both traffic and indoor sources. Comparing models based on covariate selection using p-values or a Bayesian approach yielded similar results, with traffic density within a 50 m buffer of a home and distance from a truck route as important contributors to indoor levels of NO₂ and EC, respectively. The Bayesian approach also highlighted the uncertanity in the models. We conclude that by utilizing public databases and focused questionnaire data we can identify important predictors of indoor concentrations for multiple air pollutants in a high-risk population.     

Modeling traffic air pollution in street canyons in New York City for intra-urban exposure assessment in the US Multi-Ethnic Study of atherosclerosis and air pollution

We evaluated the Danish AirGIS air quality and exposure model system using air quality measurement data from New York City in the Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air). Measurements were used from three US EPA Air Quality System (AQS) monitoring stations and a comprehensive MESA Air measurement campaign including about 150 different locations and about 650 samples of about 2 week measurements of NO_x, NO₂ and PM_2.5. AirGIS is a deterministic exposure model system based on the dispersion models Operational Street Pollution Model (OSPM) and the Urban Background Model (UBM). The UBM model reproduced the annual levels within 1–26% depending on station and pollutant at the three urban background EPA monitor stations, and generally reproduced well the seasonal and diurnal variation. The full model with OSPM and UBM reproduced the MESA Air measurements with a correlation coefficient of r² = 0.51 for NO_x, r² = 0.28 for NO₂ and r² = 0.73 for PM_2.5.     

Personal Exposure to Fine Particulate Matter in Elderly Subjects: Relation between Personal,Indoor, and Outdoor Concentrations

ABSTRACT

The time-series correlation between ambient levels, indoor levels, and personal exposure to PM_2.5 was assessed in panels of elderly subjects with cardiovascular disease in Amsterdam, the Netherlands, and Helsinki, Finland. Subjects were followed for 6 months with biweekly clinical visits. Each subject's indoor and personal exposure to PM_2.5 was measured biweekly, during the 24-hr period preceding the clinical visits. Outdoor PM_2.5 concentrations were measured at fixed sites. The absorption coefficients of all PM_2.5 filters were measured as a marker for elemental carbon (EC). Regression analyses were conducted for each subject separately, and the distribution of the individual regression and correlation coefficients was investigated. Personal, indoor, and ambient concentrations were highly correlated within subjects over time. Median Pearson's R between personal and outdoor PM_2.5 was 0.79 in Amsterdam and 0.76 in Helsinki. For absorption, these values were 0.93 and 0.81 for Amsterdam and Helsinki, respectively. The findings of this study provide further support for using fixed-site measurements as a measure of exposure to PM_2.5 in epidemiological time-series studies.     

Estimated long-term outdoor air pollution concentrations in a cohort study

Several recent studies associated long-term exposure to air pollution with increased mortality. An ongoing cohort study, the Netherlands Cohort Study on Diet and Cancer (NLCS), was used to study the association between long-term exposure to traffic-related air pollution and mortality. Following on a previous exposure assessment study in the NLCS, we improved the exposure assessment methods.Long-term exposure to nitrogen dioxide (NO₂), nitrogen oxide (NO), black smoke (BS), and sulphur dioxide (SO₂) was estimated. Exposure at each home address (N=21 868) was considered as a function of a regional, an urban and a local component. The regional component was estimated using inverse distance weighed interpolation of measurement data from regional background sites in a national monitoring network. Regression models with urban concentrations as dependent variables, and number of inhabitants in different buffers and land use variables, derived with a Geographic Information System (GIS), as predictor variables were used to estimate the urban component. The local component was assessed using a GIS and a digital road network with linked traffic intensities. Traffic intensity on the nearest road and on the nearest major road, and the sum of traffic intensity in a buffer of 100 m around each home address were assessed. Further, a quantitative estimate of the local component was estimated.The regression models to estimate the urban component explained 67%, 46%, 49% and 35% of the variances of NO₂, NO, BS, and SO₂ concentrations, respectively. Overall regression models which incorporated the regional, urban and local component explained 84%, 44%, 59% and 56% of the variability in concentrations for NO₂, NO, BS and SO₂, respectively.We were able to develop an exposure assessment model using GIS methods and traffic intensities that explained a large part of the variations in outdoor air pollution concentrations.     

Subgroups exposed to systematically different elemental compositions of PM2.5

Identification of exposure subgroups is important for both health-based assessments where health effects are linked to the elemental composition of PM_2.5 mixture to which participants are exposed, and for development of population exposure models where population exposures to PM_2.5 mass are modeled generally using fixed site ambient monitoring. Here we demonstrate that workplace sources dominate PM_2.5 mass in the upper end of the distribution for EXPOLIS participants in Athens, Basel, Helsinki and Oxford, resulting in poor performance of models that use ambient concentrations to predict exposures when predicting higher exposures, where adverse health impacts would be more likely. Further, since different microenvironments reflect differing contributions from local PM_2.5 sources, personal PM_2.5 exposures for participants whose exposures are dominated by different microenvironments show systematically different elemental personal compositions. Perhaps a more significant complication for epidemiologic associations is that the proportion of participants whose exposures are dominated by each microenvironment varies across the exposure distribution to PM_2.5. Participants exposed predominantly in the outdoor or personal microenvironments are a greater fraction of the lower end of the PM_2.5 exposure distribution while participants with dominant workplace environments are a greater fraction of the upper end of the distribution, with corresponding differences in elemental compositions of PM_2.5 exposures across the exposure distribution.     

Personal exposure to particulate air pollution in transport microenvironments

Personal measurements of exposure to particulate air pollution (PM₁₀, PM_2.5, PM₁) were simultaneously made during walking and in-car journeys on two suburban routes in Northampton, UK, during the winter of 1999/2000. Comparisons were made between concentrations found in each transport mode by particle fraction, between different particle fractions by transport mode, and between transport microenvironments and a fixed-site monitor located within the study area. High levels of correlation were seen between walking and in-car concentrations for each of the particle fractions (PM₁₀: r²=0.82; PM_2.5: r²=0.98; PM₁: r²=0.99). On an average, PM₁₀ concentrations were 16% higher inside the car than for the walker, but there were no difference in average PM_2.5 and PM₁ concentrations between the two modes. High PM_2.5:PM₁₀ ratios (0.6–0.73) were found to be associated with elevated sulphate levels. The PM_2.5:PM₁₀ and PM₁:PM_2.5 ratios were shown to be similar between walking and in-car concentrations. Concentrations of PM₁₀ were found to be more closely related between transport mode than either mode was with concentrations recorded at the fixed-site (roadside) monitor. The fixed-site monitor was shown to be a poor marker for PM₁₀ concentrations recorded during walking and in-car on a route over 1 km away.     

Development of an individual exposure model for application to the Southern California children's health study

The Southern California Children's Health Study (CHS) investigated the relationship between air pollution and children's chronic respiratory health outcomes. Ambient air pollutant measurements from a single CHS monitoring station in each community were used as surrogates for personal exposures of all children in that community. To improve exposure estimates for the CHS children, we developed an Individual Exposure Model (IEM) to retrospectively estimate the long-term average exposure of the individual CHS children to CO, NO₂, PM₁₀, PM_2.5, and elemental carbon (EC) of ambient origin. In the IEM, pollutant concentrations due to both local mobile source emissions (LMSE) and meteorologically transported pollutants were taken into account by combining a line source model (CALINE4) with a regional air quality model (SMOG). To avoid double counting, local mobile sources were removed from SMOG and added back by CALINE4. Limited information from the CHS survey was used to group each child into a specific time-activity category, for which corresponding Consolidated Human Activity Database (CHAD) time-activity profiles were sampled. We found local traffic significantly increased within-community variability of exposure to vehicle-related pollutants. PM-associated exposures were influenced more by meteorologically transported pollutants and local non-mobile source emissions than by LMSE. The overall within-community variability of personal exposures was highest for NO₂ (±20–40%), followed by EC (±17–27%), PM₁₀ (±15–25%), PM_2.5 (±15–20%), and CO (±9–14%). Between-community exposure differences were affected by community location, traffic density, and locations of residences and schools in each community. Proper siting of air monitoring stations relative to emission sources is important to capture community mean exposures.     

Association between air pollution exposure and gestational diabetes mellitus in pregnant women: a retrospective cohort study

The global prevalence of gestational diabetes mellitus (GDM) is increasing annually, and previous research reports on the relationship between exposure to air pollutants and GDM are not completely consistent. We investigated the association between air pollutant exposure and GDM in pregnant women in a retrospective cohort study in Guangzhou. We found that in the first trimester, exposure to PM_2.5 and CO showed a significant association with GDM. In the second trimester, exposure to PM₁₀ was significantly associated with GDM. In the third trimester, exposure to PM_2.5, PM₁₀, NO₂, SO₂, and CO at IQR4 (odds ratio [OR]?=?1.271, 95% confidence interval [CI]: 1.179–1.370; OR?=?1.283, 95% CI: 1.191–1.383; OR?=?1.230, 95% CI: 1.145–1.322; OR?=?1.408, 95% CI: 1.303–1.522; OR?=?1.150, 95% CI: 1.067–1.240, respectively) compared with IQR1 was positively associated with GDM. However, exposure to NO₂ was negatively associated with GDM in the first and second trimesters, and O₃ was negatively associated with GDM in the second and third trimesters. We found that the correlation between air pollutants and GDM in different trimesters of pregnancy was not completely consistent in this retrospective cohort study. During pregnancy, there may be an interaction between air pollutant exposure and other factors, such as pregnant women’s age, occupation, anemia status, pregnancy-induced hypertension status, and pregnancy season.

     

A reanalysis of fine particulate matter air pollution versus life expectancy in the United States

A reduction in population exposure to fine particulate matter air pollution (PM2.5) has been associated with improvements in life expectancy. This article presents a reanalysis of this relationship and comments on the results from a study on the reduction of ambient air PM_2.5 concentrations versus life expectancy in metropolitan areas of the United States. The results of the reanalysis show that the statistical significance of the correlation is lost after removing one of the metropolitan areas from the regression analysis, suggesting that the results may not be suitable for a meaningful and reliable inference.

Implications: The observed loss of statistical significance in the correlation between the reduction of ambient air PM_2.5 concentrations and life expectancy in metropolitan areas of the United States, after removing one of the metropolitan areas from the regression analysis, may raise concern for the policymakers in decisions regarding further reductions in permitted levels of air pollution emissions.     

Major air pollutants in Bursa,Turkey: their levels,temporal changes,interactions, and sources

Bursa is one of the largest cities of Turkey and it hosts 17 organized industrial zones. Parallel to the increase in population, rapidly growing energy consumption, and increased numbers of transport vehicles have impacts on the air quality of the city. In this study, regularly calibrated automatic samplers were employed to get the levels of air pollution in Bursa. The concentrations of CH₄ and N-CH₄ as well as the major air pollutants including PM₁₀, PM_2.5, NO, NO₂, NO_x, SO₂, CO, and O₃, were determined for 2016 and 2017 calendar years. Their levels were 1641.62?±?718.25, 33.11?±?5.45, 42.10?±?10.09, 26.41?±?9.01, 19.47?±?16.51, 46.73?±?16.56, 66.23?±?32.265, 7.60?±?3.43, 659.397?±?192.73, and 51.92?±?25.63 µg/m³ for 2016, respectively. Except for O₃, seasonal concentrations were higher in winter and autumn for both years. O₃, CO, and SO₂ had never exceeded the limit values specified in the regulations yet PM₁₀, PM_2.5, and NO₂ had violated the limits in some days. The ratios of CO/NO_x, SO₂/NO_x, and PM_2.5/PM₁₀ were examined to characterize the emission sources. Generally, domestic and industrial emissions were dominated in the fall and winter seasons, yet traffic emissions were effective in spring and summer seasons. As a result of the correlation process between O_x and NO_x, it was concluded that the most important source of O_x concentrations in winter was NO_x and O₃ was in summer.