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.     

Seasonal variation of air pollution index: Hong Kong case study

Air pollution is an important and popular topic in Hong Kong as concerns have been raised about the health impacts caused by vehicle exhausts in recent years. In Hong Kong, sulphur dioxide SO2, nitrogen dioxide (NO2), nitric oxide (NO), carbon monoxide (CO), and respirable suspended particulates (RSP) are major air pollutants caused by the dominant usage of diesel fuel by goods vehicles and buses. These major pollutants and the related secondary pollutant, e.g., ozone (O3), become and impose harmful impact on human health in Hong Kong area after the northern shifting of major industries to Mainland China. The air pollution index (API), a referential parameter describing air pollution levels, provides information to enhance the public awareness of air pollutions in time series since 1995. In this study, the varying trends of API and the levels of related air pollutants are analyzed based on the database monitored at a selected roadside air quality monitoring station, i.e., Causeway Bay, during 1999-2003. Firstly, the original measured pollutant data and the resultant APIs are analyzed statistically in different time series including daily, monthly, seasonal patterns. It is found that the daily mean APIs in seasonal period can be regarded as stationary time series. Secondly, the auto-regressive moving average (ARMA) method, implemented by Box-Jenkins model, is used to forecast the API time series in different seasonal specifications. The performance evaluations of the adopted models are also carried out and discussed according to Bayesian information criteria (BIC) and root mean square error (RMSE). The results indicate that the ARMA model can provide reliable, satisfactory predictions for the problem interested and is expecting to be an alternative tool for practical assessment and justification.     

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.     

The Association between Ambient Carbon Monoxide Levels and Daily Mortality in Toronto,Canada

ABSTRACT

The role of ambient levels of carbon monoxide (CO) in the exacerbation of heart problems in individuals with both cardiac and other diseases was examined by comparing daily variations in CO levels and daily fluctuations in nonaccidental mortality in metropolitan Toronto for the 15-year period 1980–1994. After adjusting the mortality time series for day-of-the-week effects, nonparametic smoothed functions of day of study and weather variables, statistically significant positive associations were observed between daily fluctuations in mortality and ambient levels of carbon monoxide, nitrogen dioxide, sulfur dioxide, coefficient of haze, total suspended particulate matter, sulfates, and estimated PM_2.5 and PM₁₀. However, the effects of this complex mixture of air pollutants could be almost completely explained by the levels of CO and total suspended particulates (TSP). Of the 40 daily nonaccidental deaths in metropolitan Toronto, 4.7% (95% confidence interval of 3.4%–6.1%) could be attributable to CO while TSP contributed an additional 1.0% (95% confidence interval of 0.2–1.9%), based on changes in CO and TSP equivalent to their average concentrations. Statistically significant positive associations were observed between CO and mortality in all seasons, age, and disease groupings examined. Carbon monoxide should be considered as a potential public health risk to urban populations at current ambient exposure levels.     

Analysis of the air pollution climate at a central urban background site

Measurements of air pollutants from a background site in central London are analysed. These comprise hourly data for CO, NO, NO₂, O₃, SO₂ and PM₁₀ from 1996 to 2008 and particle number count from 2001 to 2008. The data are analysed in terms of long-term trends, annual, weekly and diurnal cycles, and autocorrelation and cross-correlation functions. CO, NO and NO₂ show a typical traffic-associated pattern with two daily peaks and lesser concentrations at the weekend. Particle number count and PM₁₀ show a similar cycle, but with smaller amplitude. Ozone has an annual cycle with a maximum in May, influenced by the spring maximum in background ozone, but the diurnal and weekly cycles are dominated by losses through reaction with nitric oxide. Particle number count shows a minimum corresponding with maximum air temperatures in August, whereas the CO, NO NO₂ and SO₂ show a minimum in June/July. There is a lower particle count to NO_x ratio at the background site compared to a central London kerbside site (Marylebone Road) and a seasonal pattern in particle count to NO_x and PM₁₀ ratios consistent with loss of nanoparticles by evaporation during atmospheric transport. Sulphur dioxide peaks in the morning in summer, but at midday in winter consistent with emissions from elevated sources mixing down from aloft as the diurnal mixed layer deepens. Implications for epidemiological studies of air quality and health are discussed. Sulphur dioxide, carbon monoxide, nitric oxide and nitrogen dioxide show clear downward trends over the measurement period, PM₁₀ declines initially before levels stabilised, and ozone concentrations increased.     

Time series analysis of ambient air pollution effects on daily mortality

Although the growths of ambient pollutants have been attracting public concern, the characteristic of the associations between air pollutants and mortality remains elusive. Time series analysis with a generalized additive model was performed to estimate the associations between ambient air pollutants and mortality outcomes in Shenzhen City for the period of 2012–2014. The results showed that nitrogen dioxide (NO₂)-induced excess risks (ER) of total non-accidental mortality and cardiovascular mortality were significantly increased (6.05% (95% CI 3.38%, 8.78%); 6.88% (95% CI 2.98%, 10.93%), respectively) in interquartile range (IQR) increase analysis. Also, these associations were strengthened after adjusting for other pollutants. Moreover, similar associations were estimated for sulfur dioxide (SO₂), particulate matter with an aerodynamic diameter of <10 μm (PM₁₀), and total non-accidental mortality. There were significant higher ERs of associations between PM₁₀ and mortality for men than women; while there were significant higher ERs of associations between PM₁₀/NO₂ and mortality for elders (65 or elder) than youngers (64 or younger). Season analyses showed that associations between NO₂ and total non-accidental mortality were more pronounced in hot seasons than in warm seasons. Taken together, NO₂ was positively associated with total non-accidental mortality and cardiovascular mortality in Shenzhen even when the concentrations were below the ambient air quality standard. Policy measures should aim at reducing residents’ exposure to anthropogenic NO₂ emissions.     

The short-term effects of air pollution on adolescent lung function in Taiwan

A mass screening of lung function associated with air pollutants for children is limited. This study assessed the association between air pollutants exposure and the lung function of junior high school students in a mass screening program in Taipei city, Taiwan. Among 10,396 students with completed asthma screening questionnaires and anthropometric measures, 2919 students aged 12-16 received the spirometry test. Forced vital capacity (FVC) and forced expiratory flow in 1 s (FEV₁) in association with daily ambient concentrations of particulate matter with diameter of 10 μm or less (PM₁₀), sulfur dioxide (SO₂), carbon monoxide (CO), nitrogen dioxide (NO₂), and ozone (O₃) were assessed by regression models controlling for the age, gender, height, weight, student living districts, rainfall and temperature. FVC, had a significant negative association with short-term exposure to O₃ and PM₁₀ measured on the day of spirometry testing. FVC values also were reversely associated with means of SO₂, O₃, NO₂, PM₁₀ and CO exposed 1 d earlier. An increase of 1-ppm CO was associated with the reduction in FVC for 69.8 mL (95% CI: −115, −24.4 mL) or in FEV₁ for 73.7 mL (95% CI: −118, −29.7 mL). An increase in SO₂ for 1 ppb was associated with the reductions in FVC and FEV₁ for 12.9 mL (95% CI: −20.7, −5.09 mL) and 11.7 mL (95% CI: −19.3, −4.16 mL), respectively. In conclusion, the short-term exposure to O₃ and PM₁₀ was associated with reducing FVC and FEV₁. CO and SO₂ exposure had a strong 1-d lag effect on FVC and FEV₁.     

The impact of airborne particulate matter on pediatric hospital admissions for pneumonia among children in Jinan,China: A case-crossover study

This study aims to examine the effect of short-term changes in the concentration of particulate matter of diameter ≤2.5 µm (PM_2.5) and ≤10 µm (PM₁₀) on pediatric hospital admissions for pneumonia in Jinan, China. It explores confoundings factors of weather, season, and chemical pollutants. Information on pediatric hospital admissions for pneumonia in 2014 was extracted from the database of Jinan Qilu Hospital. The relative risk of pediatric hospital admissions for pneumonia was assessed using a case-crossover approach, controlling weather variables, day of the week, and seasonality. The single-pollutant model demonstrated that increased risk of pediatric hospital admissions for pneumonia was significantly associated with elevated PM_2.5 concentrations the day before hospital admission and elevated PM₁₀ concentrations 2 days before hospital admission. An increment of 10 μg/m³ in PM_2.5 and PM₁₀ was correlated with a 6% (95% CI 1.02–-1.10) and 4% (95% CI 1.00–1.08) rise in number of admissions for pneumonia, respectively. In two pollutant models, PM_2.5 and PM₁₀ remained significant after inclusion of sulfur dioxide or nitrogen dioxide but not carbon monoxide. This study demonstrated that short-term exposure to atmospheric particulate matter (PM_2.5/PM₁₀) may be an important determinant of pediatric hospital admissions for pneumonia in Jinan, China.

Implications: This study demonstrated that short-term exposure to atmospheric particulate matter (PM_2.5/PM₁₀) may be an important determinant of pediatric hospital admissions for pneumonia in Jinan, China, and suggested the relevance of pollutant exposure levels and their effects. As a specific group, children are sensitive to airborne particulate matter. This study estimated the short-term effects attribute to other air pollutants to provide references for relevant studies.     

A new multipollutant, no-threshold air quality health index based on short-term associations observed in daily time-series analyses

Air quality indices currently in use have been criticized because they do not capture additive effects of multiple pollutants, or reflect the apparent no-threshold concentration-response relationship between air pollution and health. We propose a new air quality health index (AQHI), constructed as the sum of excess mortality risk associated with individual pollutants from a time-series analysis of air pollution and mortality in Canadian cities, adjusted to a 0-10 scale, and calculated hourly on the basis of trailing 3-hr average pollutant concentrations. Extensive sensitivity analyses were conducted using alternative combinations of pollutants from single and multipollutant models. All formulations considered produced frequency distributions of the daily maximum AQHI that were right-skewed, with modal values of 3 or 4, and less than 10% of values at 7 or above on the 10-point scale. In the absence of a gold standard and given the uncertainty in how to best reflect the mix of pollutants, we recommend a formulation based on associations of nitrogen dioxide, ozone, and particulate matter of median aerodynamic diameter less than 2.5 microm with mortality from single-pollutant models. Further sensitivity analyses revealed good agreement of this formulation with others based on alternative sources of coefficients drawn from published studies of mortality and morbidity. These analyses provide evidence that the AQHI represents a valid approach to formulating an index with the objective of allowing people to judge the relative probability of experiencing adverse health effects from day to day. Together with health messages and a graphic display, the AQHI scale appears promising as an air quality risk communication tool.     

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.

     

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.     

A New Multipollutant,No-Threshold Air Quality Health Index Based on Short-Term Associations Observed in Daily Time-Series Analyses

Abstract

Air quality indices currently in use have been criticized because they do not capture additive effects of multiple pollutants, or reflect the apparent no-threshold concentration-response relationship between air pollution and health. We propose a new air quality health index (AQHI), constructed as the sum of excess mortality risk associated with individual pollutants from a time-series analysis of air pollution and mortality in Canadian cities, adjusted to a 0–10 scale, and calculated hourly on the basis of trailing 3-hr average pollutant concentrations. Extensive sensitivity analyses were conducted using alternative combinations of pollutants from single and multi-pollutant models. All formulations considered produced frequency distributions of the daily maximum AQHI that were right-skewed, with modal values of 3 or 4, and less than 10% of values at 7 or above on the 10-point scale. In the absence of a gold standard and given the uncertainty in how to best reflect the mix of pollutants, we recommend a formulation based on associations of nitrogen dioxide, ozone, and particulate matter of median aerodynamic diameter less than 2.5 µm with mortality from single-pollutant models. Further sensitivity analyses revealed good agreement of this formulation with others based on alternative sources of coefficients drawn from published studies of mortality and morbidity. These analyses provide evidence that the AQHI represents a valid approach to formulating an index with the objective of allowing people to judge the relative probability of experiencing adverse health effects from day to day. Together with health messages and a graphic display, the AQHI scale appears promising as an air quality risk communication tool.     

Predicting hourly air pollutant levels using artificial neural networks coupled with uncertainty analysis by Monte Carlo simulations

Recent progress in developing artificial neural network (ANN) metamodels has paved the way for reliable use of these models in the prediction of air pollutant concentrations in urban atmosphere. However, improvement of prediction performance, proper selection of input parameters and model architecture, and quantification of model uncertainties remain key challenges to their practical use. This study has three main objectives: to select an ensemble of input parameters for ANN metamodels consisting of meteorological variables that are predictable by conventional weather forecast models and variables that properly describe the complex nature of pollutant source conditions in a major city, to optimize the ANN models to achieve the most accurate hourly prediction for a case study (city of Tehran), and to examine a methodology to analyze uncertainties based on ANN and Monte Carlo simulations (MCS). In the current study, the ANNs were constructed to predict criteria pollutants of nitrogen oxides (NO_x), nitrogen dioxide (NO₂), nitrogen monoxide (NO), ozone (O₃), carbon monoxide (CO), and particulate matter with aerodynamic diameter of less than 10 μm (PM₁₀) in Tehran based on the data collected at a monitoring station in the densely populated central area of the city. The best combination of input variables was comprehensively investigated taking into account the predictability of meteorological input variables and the study of model performance, correlation coefficients, and spectral analysis. Among numerous meteorological variables, wind speed, air temperature, relative humidity and wind direction were chosen as input variables for the ANN models. The complex nature of pollutant source conditions was reflected through the use of hour of the day and month of the year as input variables and the development of different models for each day of the week. After that, ANN models were constructed and validated, and a methodology of computing prediction intervals (PI) and probability of exceeding air quality thresholds was developed by combining ANNs and MCSs based on Latin Hypercube Sampling (LHS). The results showed that proper ANN models can be used as reliable metamodels for the prediction of hourly air pollutants in urban environments. High correlations were obtained with R ² of more than 0.82 between modeled and observed hourly pollutant levels for CO, NO_x, NO₂, NO, and PM₁₀. However, predicted O₃ levels were less accurate. The combined use of ANNs and MCSs seems very promising in analyzing air pollution prediction uncertainties. Replacing deterministic predictions with probabilistic PIs can enhance the reliability of ANN models and provide a means of quantifying prediction uncertainties.     

Concentrations of mobile source air pollutants in urban microenvironments

Human exposures to criteria and hazardous air pollutants (HAPs) in urban areas vary greatly due to temporal-spatial variations in emissions, changing meteorology, varying proximity to sources, as well as due to building, vehicle, and other environmental characteristics that influence the amounts of ambient pollutants that penetrate or infiltrate into these microenvironments. Consequently, the exposure estimates derived from central-site ambient measurements are uncertain and tend to underestimate actual exposures. The Exposure Classification Project (ECP) was conducted to measure pollutant concentrations for common urban microenvironments (MEs) for use in evaluating the results of regulatory human exposure models. Nearly 500 sets of measurements were made in three Los Angeles County communities during fall 2008, winter 2009, and summer 2009. MEs included in-vehicle, near-road, outdoor, and indoor locations accessible to the general public. Contemporaneous 1- to 15-min average personal breathing zone concentrations of carbon monoxide (CO), carbon dioxide (CO₂), volatile organic compounds (VOCs), nitric oxide (NO), nitrogen oxides (NO_x), particulate matter (<2.5 μm diameter; PM_2.5) mass, ultrafine particle (UFP; <100 nm diameter) number, black carbon (BC), speciated HAPs (e.g., benzene, toluene, ethylbenzene, xylenes [BTEX], 1,3-butadiene), and ozone (O₃) were measured continuously. In-vehicle and inside/outside measurements were made in various passenger vehicle types and in public buildings to estimate penetration or infiltration factors. A large fraction of the observed pollutant concentrations for on-road MEs, especially near diesel trucks, was unrelated to ambient measurements at nearby monitors. Comparisons of ME concentrations estimated using the median ME/ambient ratio versus regression slopes and intercepts indicate that the regression approach may be more accurate for on-road MEs. Ranges in the ME/ambient ratios among ME categories were generally greater than differences among the three communities for the same ME category, suggesting that the ME proximity factors may be more broadly applicable to urban MEs.

Implications:Estimates of population exposure to air pollutants extrapolated from ambient measurements at ambient fixed site monitors or exposure surrogates are prone to uncertainty. This study measured concentrations of mobile source air toxics (MSAT) and related criteria pollutants within in-vehicle, outdoor near-road, and indoor urban MEs to provide multipollutant ME measurements that can be used to calibrate regulatory exposure models.     

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.     

Understanding of regional air pollution over China using CMAQ,part I performance evaluation and seasonal variation

The U.S. EPA Models-3 Community Multiscale Air Quality (CMAQ) modeling system with the process analysis tool is applied to China to study the seasonal variations and formation mechanisms of major air pollutants. Simulations show distinct seasonal variations, with higher surface concentrations of sulfur dioxide (SO₂), nitrogen dioxide (NO₂), and particulate matter with aerodynamic diameter less than or equal to 10 μm (PM₁₀), column mass of carbon monoxide (CO) and NO₂, and aerosol optical depth (AOD) in winter and fall than other seasons, and higher 1-h O₃ and troposphere ozone residual (TOR) in spring and summer than other seasons. Higher concentrations of most species occur over the eastern China, where the air pollutant emissions are the highest in China. Compared with surface observations, the simulated SO₂, NO₂, and PM₁₀ concentrations are underpredicted throughout the year with NMBs of up to ?51.8%, ?32.0%, and ?54.2%, respectively. Such large discrepancies can be attributed to the uncertainties in emissions, simulated meteorology, and deviation of observations based on air pollution index. Max. 1-h O₃ concentrations in Jan. and Jul. at 36-km are overpredicted with NMBs of 12.0% and 19.3% and agree well in Apr. and Oct. Simulated column variables can capture the high concentrations over the eastern China and low values in the central and western China. Underpredictions occur over the northeastern China for column CO in Apr., TOR in Jul., and AODs in both Apr. and Jul.; and overpredictions occur over the eastern China for column CO in Oct., NO₂ in Jan. and Oct., and AODs in Jan. and Oct. The simulations at 12-km show a finer structure in simulated concentrations than that at 36-km over higher polluted areas, but do not always give better performance than 36-km. Surface concentrations are more sensitive to grid resolution than column variables except for column NO₂, with higher sensitivity over mountain and coastal areas than other regions.     

Association between particulate matter air pollution and cardiovascular disease mortality in Lanzhou,China

Ambient particulate matter (PM) pollution has been linked to elevated mortality, especially from cardiovascular diseases. However, evidence on the effects of particulate matter pollution on cardiovascular mortality is still limited in Lanzhou, China. This research aimed to examine the associations of daily mean concentrations of ambient air pollutants (PM_2.5, PM_C, and PM₁₀) and cardiovascular mortality due to overall and cause-specific diseases in Lanzhou. Data representing daily cardiovascular mortality rates, meteorological factors (daily average temperature, daily average humidity, and atmospheric pressure), and air pollutants (PM_2.5, PM₁₀, SO₂, NO₂) were collected from January 1, 2014, to December 31, 2017, in Lanzhou. A quasi-Poisson regression model combined with a distributed lag non-linear model (DLNM) was used to estimate the associations. Stratified analyses were also performed by different cause-specific diseases, including cerebrovascular disease (CD), ischemic heart disease (IHD), heart rhythm disturbances (HRD), and heart failure (HF). The results showed that elevated concentration of PM_2.5, PM_C, and PM₁₀ had different effects on mortality of different cardiovascular diseases. Only cerebrovascular disease showed a significant positive association with elevated PM_2.5. Positive associations were identified between PM_C and daily mortality rates from total cardiovascular diseases, cerebrovascular diseases, and ischemic heart diseases. Besides, increased concentration of PM₁₀ was correlated with increased death of cerebrovascular diseases and ischemic heart diseases. For cerebrovascular disease, each 10 μg/m³ increase in PM_2.5 at lag4 was associated with increments of 1.22% (95% CI 0.11–2.35%). The largest significant effects for PM_C on cardiovascular diseases and ischemic heart diseases were both observed at lag0, and a 10 μg/m³ increment in concentration of PM_C was associated with 0.47% (95% CI 0.06–0.88%) and 0.85% (95% CI 0.18–1.52%) increases in cardiovascular mortality and ischemic heart diseases. In addition, it exhibited a lag effect on cerebrovascular mortality as well, which was most significant at lag6d, and an increase of 10 μg/m³ in PM_C was associated with a 0.76% (95% CI 0.16–1.37%) increase in cerebrovascular mortality. The estimates of percentage change in daily mortality rates per 10 μg/m³ increase in PM₁₀ were 0.52% (95% CI 0.05–1.02%) for cerebrovascular disease at lag6 and 0.53% (95% CI 0.01–1.05%) for ischemic heart disease at lag0, respectively. Our study suggests that elevated concentration of atmospheric PM (PM_2.5, PM_C, and PM₁₀) in Lanzhou is associated with increased mortality of cardiovascular diseases and that the health effect of elevated concentration of PM_2.5 is more significant than that of PM_C and PM₁₀.

     

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.     

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.