Different exposure levels of fine particulate matter and preterm birth: a meta-analysis based on cohort studies

The previous studies estimated the association between PM_2.5 (particulate matter with aerodynamic diameter less than or equal to 2.5 μm) exposure during pregnancy and preterm birth, only considered and highlighted the hazard effects of high levels of air pollutant exposure, and underestimated that low levels of pollutant exposure might also affect pregnancy outcome. We conducted a meta-analysis of 11 cohort studies, a total of more than 1,500,000 subjects. The results of these studies were pooled by exposure levels and study periods. PM_2.5 exposure during pregnancy was positively associated with preterm birth (OR = 1.15, 95% CI = 1.07–1.23), and during the first trimester of pregnancy, low levels of PM_2.5 exposure were also positively associated with preterm birth (OR = 1.17, 95% CI = 1.04–1.30). It is important to protect pregnant women from PM_2.5 exposures, especially during their first trimester of pregnancy even when the ambient PM_2.5 concentration is relatively low. More relevant health policy should be carried out to prevent hazard effect of air pollutants.     

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.

     

Effects of Instrument Precision and Spatial Variability on the Assessment of the Temporal Variation of Ambient Air Pollution in Atlanta,Georgia

Abstract

Data from the U.S. Environmental Protection Agency Air Quality System, the Southeastern Aerosol Research and Characterization database, and the Assessment of Spatial Aerosol Composition in Atlanta database for 1999 through 2002 have been used to characterize error associated with instrument precision and spatial variability on the assessment of the temporal variation of ambient air pollution in Atlanta, GA. These data are being used in time series epidemiologic studies in which associations of acute respiratory and cardiovascular health outcomes and daily ambient air pollutant levels are assessed. Modified semivariograms are used to quantify the effects of instrument precision and spatial variability on the assessment of daily metrics of ambient gaseous pollutants (SO₂, CO, NO_x, and O₃) and fine particulate matter ([PM_2.5] PM_2.5 mass, sulfate, nitrate, ammonium, elemental carbon [EC], and organic carbon [OC]). Variation because of instrument imprecision represented 7–40% of the temporal variation in the daily pollutant measures and was largest for the PM_2.5 EC and OC. Spatial variability was greatest for primary pollutants (SO₂, CO, NO_x, and EC). Population–weighted variation in daily ambient air pollutant levels because of both instrument imprecision and spatial variability ranged from 20% of the temporal variation for O₃ to 70% of the temporal variation for SO₂ and EC. Wind rose plots, corrected for diurnal and seasonal pattern effects, are used to demonstrate the impacts of local sources on monitoring station data. The results presented are being used to quantify the impacts of instrument precision and spatial variability on the assessment of health effects of ambient air pollution in Atlanta and are relevant to the interpretation of results from time series health studies that use data from fixed monitors.     

Impact of Covid-19 partial lockdown on PM2.5, SO2, NO2, O3, and trace elements in PM2.5 in Hanoi,Vietnam

Covid-19 lockdowns have improved the ambient air quality across the world via reduced air pollutant levels. This article aims to investigate the effect of the partial lockdown on the main ambient air pollutants and their elemental concentrations bound to PM_2.5 in Hanoi. In addition to the PM_2.5 samples collected at three urban sites in Hanoi, the daily PM_2.5, NO₂, O₃, and SO₂ levels were collected from the automatic ambient air quality monitoring station at Nguyen Van Cu street to analyze the pollution level before (March 10th–March 31st) and during the partial lockdown (April 1st–April 22nd) with “current” data obtained in 2020 and “historical” data obtained in 2014, 2016, and 2017. The results showed that NO₂, PM_2.5, O₃, and SO₂ concentrations obtained from the automatic ambient air quality monitoring station were reduced by 75.8, 55.9, 21.4, and 60.7%, respectively, compared with historical data. Besides, the concentration of PM_2.5 at sampling sites declined by 41.8% during the partial lockdown. Furthermore, there was a drastic negative relationship between the boundary layer height (BLH) and the daily mean PM_2.5 in Hanoi. The concentrations of Cd, Se, As, Sr, Ba, Cu, Mn, Pb, K, Zn, Ca, Al, and Mg during the partial lockdown were lower than those before the partial lockdown. The results of enrichment factor (EF) values and principal component analysis (PCA) concluded that trace elements in PM_2.5 before the partial lockdown were more affected by industrial activities than those during the partial lockdown.

     

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.     

Assessing the Relationship between Personal Particulate and Gaseous Exposures of Senior Citizens Living in Baltimore,MD

ABSTRACT

We conducted a multi-pollutant exposure study in Baltimore, MD, in which 15 non-smoking older adult subjects (>64 years old) wore a multi-pollutant sampler for 12 days during the summer of 1998 and the winter of 1999. The sampler measured simultaneous 24-hr integrated personal exposures to PM₂₅, PM₁₀, SO₄ ^2-, O₃, NO₂, SO₂, and exhaust-related VOCs.

Results of this study showed that longitudinal associations between ambient PM_2.5 concentrations and corresponding personal exposures tended to be high in the summer (median Spearman's r = 0.74) and low in the winter (median Spearman's r = 0.25). Indoor ventilation was an important determinant of personal PM_2.5 exposures and resulting personal-ambient associations. Associations between personal PM₂₅ exposures and corresponding ambient concentrations were strongest for well-ventilated indoor environments and decreased with ventilation. This decrease was attributed to the increasing influence of indoor PM_{2 5} sources. Evidence for this was provided by SO₄ ^2-measurements, which can be thought of as a tracer for ambient PM₂₅. For SO₄ ^2-, personal-ambient associations were strong even in poorly ventilated indoor environments, suggesting that personal exposures to PM_2.5 of ambient origin are strongly associated with corresponding ambient concentrations. The results also indicated that the contribution of indoor PM_2.5 sources to personal PM_2.5 exposures was lowest when individuals spent the majority of their time in well-ventilated indoor environments.

Results also indicate that the potential for confounding by PM_2.5 co-pollutants is limited, despite significant correlations among ambient pollutant concentrations. In contrast to ambient concentrations, PM_2.5 exposures were not significantly correlated with personal exposures to PM_2.5-10, PM_2.5 of non-ambient origin, O₃, NO₂, and SO₂. Since a confounder must be associated with the exposure of interest, these results provide evidence that the effects observed in the PM_2.5 epidemiologic studies are unlikely to be due to confounding by the PM_2.5 co-pollutants measured in this study.     

A general method for evaluating the effects of air pollutants on lung cancer prevalence

ABSTRACT

It is widely accepted that some air pollutants are related to lung cancer prevalence. An effective method is proposed to quantitatively evaluate the effects of air pollutants and the interactions between them. The method consisted of three parts: data decomposition, comparable data generation and relationship inference. Firstly, very limited monitoring data published by Geographic Information System were applied to calculate the inhalable air pollution of relatively massive patient samples. Then the investigated area was partitioned into a number of districts, and the comparable data containing air pollutant concentrations and lung cancer prevalence in all districts were generated. Finally, the relationships between pollutants and lung cancer prevalence were concluded by an information fusion tool: Choquet integral. As an example, the proposed method was applied in the investigation of air pollution in Tianjin, China. Overall, SO₂, O₃ and PM_2.5 were the top three factors for lung cancer. And there was obvious positive interaction between O₃ and PM_2.5 and negative interaction among SO₂, O₃ and PM₁₀. The effect of SO₂ on men was larger than on women. O₃ and SO₂ were the most important factors for the adenocarcinoma and squamous cell carcinoma, respectively. The effect of SO₂ or NO₂ on squamous cell carcinoma is obviously larger than that on adenocarcinoma, while the effect of O₃ or PM_2.5 on adenocarcinoma is obviously larger than that on squamous cell carcinoma. The results provide important suggestions for management of pollutants and improvement of environmental quality. The proposed method without any parameter is general and easily realized, and it sets the foundation for further researches in other cities/countries.

Implications: For total lung cancer prevalence, male and female lung cancer prevalence, and adenocarcinoma and squamous cell carcinoma prevalence, the proposed method not only quantify the effect of single pollutant (SO₂, NO₂, CO, O₃, PM_2.5, and PM₁₀) but also reveals the correlations between different pollutants such as positive interaction or negative interaction. The proposed method without any geographic predictor and parameter is much easier to realize, and it sets the foundation for further research in other cities/countries. The study results provide important suggestions for the targeted management of different pollutants and the improvement of human lung health.     

Controls on hourly variations in urban background air pollutant concentrations

Average 21st century concentrations of urban air pollutants linked to cardiorespiratory disease are not declining, and commonly exceed legal limits. Even below such limits, health effects are being observed and may be related to transient daytime peaks in pollutant concentrations. With this in mind, we analyse >52,000 hourly urban background readings of PM₁₀ and pollutant gases throughout 2007 at a European town with legal annual average concentrations of common pollutants, but with a documented air pollution-related cardiorespiratory health problem, and demonstrate the hourly variations in PM₁₀, SO₂, NO_x, CO and O₃. Back-trajectory analysis was applied to track the arrival of exotic PM₁₀ intrusions, the main controls on air pollutants were identified, and the typical hourly pattern on ambient concentrations during 2007 was profiled. Emphasis was placed on “worst case” data (>90th percentile), when health effects are likely to be greatest. The data show marked daytime variations in pollutants result from rush-hour traffic-related pollution spikes, midday industrial SO₂ maxima, and afternoon O₃ peaks. African dust intrusions enhance PM₁₀ levels at whatever hour, whereas European PM incursions produce pronounced evening peaks due to their transport direction (across an industrial traffic corridor). Transient peak profiling moves us closer to the reality of personal outdoor exposure to inhalable pollutants in a given urban area. We argue that such an approach to monitoring data potentially offers more to air pollution health effect studies than using only 24 h or annual averages.     

Association between Levels of Fine Particulate and Emergency Visits for Pneumonia and other Respiratory Illnesses among Children in Santiago,Chile

ABSTRACT

Recent evidence has implicated the fine fraction of particulate as the major contributor to the increase in mortality and morbidity related to particulate ambient levels. We therefore evaluated the impact of daily variation of ambient PM_2.5 and other pollutants on the number of daily respiratory-related emergency visits (REVs) to a large pediatric hospital of Santiago, Chile. The study was conducted from February 1995 to August 1996. Four monitoring stations from the network of Santiago provided air pollution data. The PM2.5 24-hr average ranged from 10 to 111 μg/m³ during September to April (warm months) and from 10 to 156 μg/m³ during May to August (cold months). Other contaminants (ozone (O₃), nitrogen dioxide (NO₂), and sulfur dioxide (SO₂)) were, in general, low during the study period. The increase in REVs was significantly related to PM₁₀ and PM_2.5 ambient levels, with the relationship between PM_2.5 levels and the number of REVs the stronger. During the cold months, an increase of 45 ìg/m³ in the PM_2.5 24-hr average was related to a 2.7% increase in the number of REVs (95% CI, 1.1–4.4%) with a two-day lag, and to an increase of 6.7% (95% CI, 1.7–12.0%) in the number of visits for pneumonia with a three-day lag. SO₂ and NO₂ were also related to REVs. We conclude that urban air pollutant mixture, particularly fine particulates, adversely affect the respiratory health of children residing in Santiago.     

Infant Mortality and Air Pollution: A Comprehensive Analysis of U.S. Data for 1990

ABSTRACT

This paper uses U.S. linked birth and death records to explore associations between infant mortality and environmental factors, based on spatial relationships. The analysis considers a range of infant mortality end points, regression models, and environmental and socioeconomic variables. The basic analysis involves logistic regression modeling of individuals; the cohort comprises all infants born in the United States in 1990 for whom the required data are available from the matched birth and death records. These individual data include sex, race, month of birth, and birth weight of the infant, and personal data on the mother, including age, adequacy of prenatal care, and smoking and education in most instances. Ecological variables from Census and other sources are matched on the county of usual residence and include ambient air quality, elevation above sea level, climate, number of physicians per capita, median income, racial and ethnic distribution, unemployment, and population density. The air quality variables considered were 1990 annual averages of PM₁₀, CO, SO₂, SO₄ ^2-, and “non-sulfate PM₁₀” (NSPM₁₀—obtained by subtracting the estimated SO₄ ^2-mass from PM₁₀). Because all variables were not available for all counties (especially maternal smoking), it was necessary to consider various subsets of the total cohort.

We examined all infant deaths and deaths by age (neonatal and postneonatal), by birth weight (normal and low [<2500 g]), and by specific causes within these categories. Special attention was given to sudden infant death syndrome (SIDS). For comparable modeling assumptions, the results for PM₁₀ agreed with previously published estimates; however, the associations with PM₁₀ were not specific to probable exposures or causes of death and were not robust to changes in the model and/or the locations considered. Significant negative mortality associations were found for SO₄ ^2-. There was no indication of a role for outdoor PM_2.5, but possible contributions from indoor air pollution sources cannot be ruled out, given higher SIDS rates in winter, in the north and west, and outside of large cities.     

Daily Mortality in the Philadelphia Metropolitan Area and Size-Classified Particulate Matter

ABSTRACT

Time-series of daily mortality data from May 1992 to September 1995 for various portions of the seven-county Philadelphia, PA, metropolitan area were analyzed in relation to weather and a variety of ambient air quality parameters. The air quality data included measurements of size-classified PM, SO₄ ^2-, and H+ that had been collected by the Harvard School of Public Health, as well as routine air pollution monitoring data. Because the various pollutants of interest were measured at different locations within the metropolitan area, it was necessary to test for spatial sensitivity by comparing results for different combinations of locations. Estimates are presented for single pollutants and for multiple-pollutant models, including gaseous pollutants and mutually exclusive components of PM (PM_2.5 and coarse particles, SO₄ ^2- and non-SO₄ ^2- portions of total suspended particulate [TSP] and PM₁₀), measured on the day of death and the previous day.

We concluded that associations between air quality and mortality were not limited to data collected in the same part of the metropolitan area; that is, mortality for one part may be associated with air quality data from another, not necessarily neighboring, part. Significant associations were found for a wide variety of gaseous and particulate pollutants, especially for peak O₃. Using joint regressions on peak O₃ with various other pollutants, we found that the combined responses were insensitive to the specific other pollutant selected. We saw no systematic differences according to particle size or chemistry. In general, the associations between daily mortality and air pollution depended on the pollutant or the PM metric, the type of collection filter used, and the location of sampling. Although peak O₃ seemed to exhibit the most consistent mortality responses, this finding should be confirmed by analyzing separate seasons and other time periods.     

Daily Mortality and Air Pollution in the Netherlands

ABSTRACT

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

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

Ambient air quality changes after stubble burning in rice–wheat system in an agricultural state of India

Ground-based ambient air monitoring was conducted to assess the contribution of crop residue burning of wheat (Triticum aestivum) and rice (Oriza sativa) at different locations in three districts (Kaithal, Kurukshetra, and Karnal) of the agricultural state of Haryana in India for two successive years (2016 and 2017). The Air Quality Index (AQI) and concentration of primary pollutants (SO_x, NO_x, and PM_2.5) were determined in rice and wheat crop season, for burning and non-burning periods. During crop residue burning periods, concentrations of SO_x, NO_x, and PM_2.5 were exceeded the NAAQS values by 78%, 71%, and 53%, respectively. A significant increase in SO_x (4.5 times), NO_x (3.8 times), and PM_2.5 concentration (3.5 times) was observed in stubble burning periods as compared to pre-burning (p < 0.05). A positive and significant correlation among the three pollutant concentrations was observed (p < 0.01). The AQI of KA site in Karnal district fell in severely polluted category during 2016 for rice as well as wheat residue burning period, and of KK site in Kaithal during wheat residue burning in year 2017. Results of present study indicate a remarkable increase in pollutant concentration (SO_x, NO_x, and PM_2.5) during the crop residue burning periods. To the best of our knowledge, the outcomes of present study in this region have not been reported in earlier reports. Hence, there is an urgent need to curb air pollution by adopting sustainable harvesting technologies and management of residues.

     

Exposure of Chronic Obstructive Pulmonary Disease Patients to Particulate Matter: Relationships between Personal and Ambient Air Concentrations

ABSTRACT

Most time-series studies of particulate air pollution and acute health outcomes assess exposure of the study population using fixed-site outdoor measurements. To address the issue of exposure misclassification, we evaluate the relationship between ambient particle concentrations and personal exposures of a population expected to be at risk of particle health effects.

Sampling was conducted within the Vancouver metropolitan area during April-September 1998. Sixteen subjects (non-smoking, ages 54-86) with physician-diagnosed chronic obstructive pulmonary disease (COPD) wore personal PM_{2 5} monitors for seven 24-hr periods, randomly spaced approximately 1.5 weeks apart. Time-activity logs and dwelling characteristics data were also obtained for each subject. Daily 24-hr ambient PM₁₀ and PM_2.5 concentrations were measured at five fixed sites spaced throughout the study region. SO₄ ^2-, which is found almost exclusively in the fine particle fraction and which does not have major indoor sources, was measured in all PM_{2 5} samples as an indicator of accumulation mode particu-late matter of ambient origin.     

Recent spatial gradients and time trends in Dhaka,Bangladesh, air pollution and their human health implications

Dhaka, the capital of Bangladesh, is among the most polluted cities in the world. This research evaluates seasonal patterns, day-of-week patterns, spatial gradients, and trends in PM_2.5 (<2.5 µm in aerodynamic diameter), PM₁₀ (<10 µm in aerodynamic diameter), and gaseous pollutants concentrations (SO₂, NO₂, CO, and O₃) monitored in Dhaka from 2013 to 2017. It expands on past work by considering multiple monitoring sites and air pollutants. Except for ozone, the average concentrations of these pollutants showed strong seasonal variation, with maximum during winter and minimum during monsoon, with the pollution concentration of PM_2.5 and PM₁₀ being roughly five- to sixfold higher during winter versus monsoon. Our comparisons of the pollutant concentrations with Bangladesh NAAQS and U.S. NAAQS limits analysis indicate particulate matter (PM_2.5 and PM₁₀) as the air pollutants of greatest concern, as they frequently exceeded the Bangladesh NAAQS and U.S. NAAQS, especially during nonmonsoon time. In contrast, gaseous pollutants reported far fewer exceedances throughout the study period. During the study period, the highest number of exceedances of NAAQS limits in Dhaka City (Darus-Salam site) were found for PM_2.5 (72% of total study days), followed by PM₁₀ (40% of total study days), O₃ (1.7% of total study days), SO₂ (0.38% of total study days), and CO (0.25% of total study days). The trend analyses results showed statistically significant positive slopes over time for SO₂ (5.6 ppb yr^?1, 95% confidence interval [CI]: 0.7, 10.5) and CO (0.32 ppm yr^?1, 95% CI: 0.01, 0.56), which suggest increase in brick kilns operation and high-sulfur diesel use. Though statistically nonsignificant annual decreasing slopes for PM_2.5 (?4.6 µg/m³ yr^?1, 95% CI: ?12.7, 3.6) and PM₁₀ (?2.7 µg/m³ yr^?1, 95% CI: ?7.9, 2.5) were observed during this study period, the PM_2.5 concentration is still too high (~ 82.0 µg/m³) and can cause severe impact on human health.

Implications: This study revealed key insights into air quality challenges across Dhaka, Bangladesh, indicating particulate matter (PM) as Dhaka’s most serious air pollutant threat to human health. The results of these analyses indicate that there is a need for immediate further investigations, and action based on those investigations, including the conduct local epidemiological PM exposure-human health effects studies for this city, in order to determine the most public health effective interventions.     

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

Abstract

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

Air pollution and hospital visits for acute upper and lower respiratory infections among children in Ningbo,China: A time-series analysis

Acute upper and lower respiratory infections are main causes of mortality and morbidity in children. Air pollution has been recognized as an important contributor to development and exacerbation of respiratory infections. However, few studies are available in China. In this study, we investigated the short-term effect of air pollution on hospital visits for acute upper and lower respiratory infections among children under 15 years in Ningbo, China. Poisson generalized models were used to estimate the associations between air pollution and hospital visits for acute upper and lower respiratory infections adjusted for temporal, seasonal, and meteorological effects. We found that four pollutants (PM_2.5, PM₁₀, NO₂, and SO₂) were significantly associated with hospital visits for acute upper and lower respiratory infections. The effect estimates for acute upper respiratory infections tended to be higher (PM_2.5 ER = 3.46, 95% CI 2.18, 4.76; PM₁₀ ER = 2.81, 95% CI 1.93, 3.69; NO₂ ER = 11.27, 95% CI 8.70, 13.89; SO₂ ER = 15.17, 95% CI 11.29, 19.19). Significant associations for gaseous pollutants (NO₂ and SO₂) were observed after adjustment for particular matter. Stronger associations were observed among older children and in the cold period. Our study suggested that short-term exposure to outdoor air pollution was associated with hospital visits for acute upper and lower respiratory infections in Ningbo.     

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.