Outdoor Nitrogen Dioxide Research Articles

Environmental Conditions for Danish Storage Buildings: A Summary of 20 Years of Air Quality Surveys

ABSTRACT Air quality in 36 Danish storage buildings was investigated, ranging from naturally ventilated historical buildings to modern purpose-built storage facilities, some with full HVAC climate control systems. Most were able to maintain a humidity level within 40–60% RH. The main deviations were for older heated buildings without humidity control, resulting in dry winter periods. Many modern stores were un-heated, which resulted in an annual average temperature about 12–13°C, and a high (>80) time-weighted preservation index (TWPI). The older buildings often struggled to maintain a moderate temperature, but experienced summer levels of 20–30°C. This lowered the TWPI considerably, typically to index 40–80. Concentration of organic acids in air was below 50 ppb for 22 sites, and only high (>100 ppb) for a few sites due to off-gassing from heritage materials. The outdoor pollutants ozone and nitrogen dioxide were mainly found in low concentrations indoors (<5 ppb) except for a few locations with forced but unfiltered air intake. Low-energy storage had the lowest energy consumption of <3 kWh/m3 annually, while repositories with traditional climate control systems were in the range of 10–30 kWh/m3. Information on energy consumption in storage buildings is sparse, and the authors call for more research. The most optimal solutions were offered by the modern low-energy buildings, where the best conservation conditions as defined by TWPI (high), pollution levels (low), and energy consumption (low) were observed, and where sustainable operation such as sharing space between several institutions was often practiced.

Spatial variance and estimation of nitrogen dioxide levels as a contributing factor to asthma epidemiology in Rawalpindi, Pakistan.

Asthma prevalence and morbidity are increasing rapidly worldwide, especially in developing countries. Previous studies have shown nitrogen dioxide as an important contributor to asthma prevalence along with extreme temperatures, relative humidity, and land use change. The present study aimed to assess the asthma epidemiology and association of nitrogen dioxide, temperature, and land use as a contributing factor for increasing asthma prevalence in Rawalpindi, Pakistan. Secondary data related to the frequency of asthmatics hospital visits were analyzed to figure out the hotspots of asthma by using Getis ord Gi* statistics in ArcGIS 10.2. Moreover, intraurban variation of nitrogen dioxide concentration was analyzed by passive sampling method and its association with the rate of asthmatics hospital visits in Rawalpindi, Pakistan was also researched. Results revealed the random distribution of disease with significant hotspots along with spatial variability of nitrogen dioxide in urban and rural locations. Indoor and outdoor levels of nitrogen dioxide exceed the national and world health organization standards on asthma high risk areas especially in winter season. Congested housing with poor ventilation, unplanned urbanization, cold temperature, and unclean fuel use are revealed as strong determinants of asthma prevalence in Rawalpindi, Pakistan. Extensive monitoring and interventions are needed for the reduction of both indoor and outdoor nitrogen dioxide levels to overcome the increasing rate of asthma prevalence.

Simulation of outdoor air pollution in Southampton

The city of Southampton is committed to monitoring and reducing outdoor air pollution, in particular, Nitrogen Dioxide (NO2) and Particulate Matters (PM2.5/PM10), which have been linked with adverse health effects under short- or long-term exposure. This project investigates the air pollution contributed mainly by road sources, which consist of major and minor roads in Southampton, by using Atmospheric Dispersion Modelling Software (ADMSRoads), and provides further understanding on the air pollution contributions based on qualitative and quantitative analysis. The model was validated by comparing the modelled concentration with the observed data from the Southampton AURN pollution monitoring station. This study has found out that although the simulation exhibits a tendency to underpredict pollution concentrations, the dynamics of the model were relatively promising as it managed to capture the trends over time of the concentration of air pollutants relatively consistently. Therefore, future improvements to the model may be made by applying correction factors to overcome the bias offset to obtain more realistic predictions of air quality. The simulation has also correctly predicted poorer air quality within the Air Quality Management Areas (AQMA) declared by Southampton City Council (SCC), which implies that road sources have a notable contribution towards the air pollution. The advantages of this model are that it can be quickly altered to predict response to future policy actions and that it has sufficient resolution to be used for epidemiological studies linking air pollution with the prevalence of health conditions in the city. The findings so far indicate that further pollution control measures are still warranted as most of the pollutant concentrations from road sources exceed the latest (2021) WHO air quality guidelines developed to protect public health from effects of exposure to air pollutants.

Paired Indoor and Outdoor Nitrogen Dioxide Associated With Childhood Asthma Outcomes in a Mixed Rural-Urban Setting: A Feasibility Study.

Nitrogen dioxide (NO2) is known to be a trigger for asthma exacerbation. However, little is known about the role of seasonal variation in indoor and outdoor NO2 levels in childhood asthma in a mixed rural-urban setting of North America. This prospective cohort study, as a feasibility study, included 62 families with children (5-17 years) that had diagnosed persistent asthma residing in Olmsted County, Minnesota. Indoor and outdoor NO2 concentrations were measured using passive air samples over 2 weeks in winter and 2 weeks in summer. We assessed seasonal variation in NO2 levels in urban and rural residential areas and the association with asthma control status collected from participants' asthma diaries during the study period. Outdoor NO2 levels were lower (median: 2.4 parts per billion (ppb) in summer, 3.9 ppb in winter) than the Environmental Protection Agency (EPA) annual standard (53 ppb). In winter, a higher level of outdoor NO2 was significantly associated with urban residential living area (P = .014) and lower socioeconomic status (SES) (P = .027). For both seasons, indoor NO2 was significantly higher (P < .05) in rural versus urban areas and in homes with gas versus electric stoves (P < .05). Asthma control status was not associated with level of indoor or outdoor NO2 in this cohort. NO2 levels were low in this mixed rural-urban community and not associated with asthma control status in this small feasibility study. Further research with a larger sample size is warranted for defining a lower threshold of NO2 concentration with health effect on asthma in mixed rural-urban settings.

Urban green spaces and suicide mortality in Belgium (2001–2011): A census-based longitudinal study

BackgroundExposure to green spaces is associated with improved mental health and may reduce risk of suicide. Here, we investigate the association between long-term exposure to residential surrounding greenness and suicide mortality. MethodsWe used data from the 2001 Belgian census linked to mortality register data (2001–2011). We included all registered individuals aged 18 years or older at baseline (2001) residing in the five largest urban areas in Belgium (n = 3,549,514). Suicide mortality was defined using the tenth revision of the World Health Organisation International Classification of Diseases (ICD-10) codes X60-X84, Y10–Y34, and Y870. Surrounding greenness was measured using the Normalized Difference Vegetation Index (NDVI) within a 300 m and 1,000 m buffer around the residential address at baseline. To assess the association between residential surrounding greenness and suicide mortality, we applied Cox proportional hazards models with age as the underlying time scale. Models were adjusted for age, sex, living arrangement, migrant background, educational attainment, neighbourhood socio-economic position. We additionally explored potential mediation by residential outdoor nitrogen dioxide (NO2) concentrations. Finally, we assessed potential effect modification by various socio-demographic characteristics of the population (sex, age, educational attainment, migrant background, and neighbourhood socio-economic position). Associations are expressed as hazard ratios and their 95% confidence intervals (CI) for an interquartile range (IQR) increase in residential surrounding greenness. ResultsWe observed a 7% (95%CI 0.89–0.97) and 6% (95%CI 0.90–0.98) risk reduction of suicide mortality for an IQR increase in residential surrounding greenness for buffers of 300 m and 1,000 m, respectively. Furthermore, this association was independent of exposure to NO2. After stratification, the inverse association was only apparent among women, and residents of Belgian origin, and that it was stronger among residents aged 36 or older, those with high level of education, and residents of most deprived neighbourhoods. ConclusionOur results suggest that urban green spaces may protect against suicide mortality, but this beneficial effect may not be equally distributed across all strata of the population.

A large-scale personal monitoring of air pollution during pregnancy in the BiSC cohort

Background and aim: Large-scale monitoring of personal exposure to air pollution remains scarce, especially for pregnant women. We present the results of one of the largest monitoring campaigns of personal, home-indoor, and home-outdoor air pollution on pregnant women. Methods: The Barcelona Life Study Cohort (BiSC) is an ongoing cohort of 1086 mother-child pairs in Barcelona, Spain (2018 onwards). We monitored personal exposure to particulate matter &amp;#x2264; 2.5 µm (PM2.5; filter samples for chemical characterisation), Black Carbon (BC; MicroAeth AE51), and personal, home indoor and outdoor nitrogen dioxide (NO2; Gradko passive tubes) at first (week 12, w12) and third trimester (w32) of pregnancy. The Covid pandemic forced us to stop data collection on PM2.5 and BC. Results: Weekly averaged concentrations (for both w12 and w32) for NO2 were 28.5 &amp;#xb1; 12.0, 24.2 &amp;#xb1; 11.7, and 38.9 &amp;#xb1; 15.8 µg/m3 for personal exposure (N = 1680), indoors (N = 1685) and outdoors (N = 1570), respectively. Personal 48h average concentration was 21.0 &amp;#xb1; 15.7 µg/m3 for PM2.5 (N = 498) and 1.63 &amp;#xb1; 0.78 µg/m3 for BC (N = 374). Compared to current WHO 24-h outdoor air quality guidelines, 55.5% of PM2.5 samples and 89 % (outdoor) and 58.6% (personal) NO2 samples were above the recommendations (15 and 25 µg/m3, respectively). Correlations were higher between personal and indoor NO2 (spearman coefficient, r, &amp;#x3e;0.74) than between personal and outdoor (r &amp;#x3c;0.42) in both w12 and w32, due to a larger time spent at home (indoors). Moderate correlations between indoor and outdoor NO2 may be explained by potential indoor sources and indoor consumption of NO2 in gas-phase reactions. Conclusions: BiSC is one of the largest studies on air pollution exposure measurements on pregnant women. Participants were exposed to a wide range of air pollutants’ concentrations. Keywords: Pregnant women, Personal exposure assessment, Air Pollution

Exploring early life exposome related to low birth weight through machine learning methods

BACKGROUND AND AIM: Regarding the multifactorial etiology of low birth weight (LBW), the contribution of environmental hazards is increasing. Exposome refer to totality of a life’s exposure including multiple pollutants, lifestyle and sociodemographic factors should provide a holistic view on LBW. This study aims to explore early life exposome related to LBW and identify important factors through machine learning methods. METHODS We recruited 486 mother-infant pairs from Taiwan Birth Panel Study, with LBW defined as birth body weight below 2500 gm. Early life factors included 27 environmental pollutants measured in cord blood or maternal urine, estimated outdoor air pollutants (particulate matter 2.5 (PM2.5), nitrogen dioxide (NO2) and greenness (Normalized Difference Vegetation Index (NDVI)) and questionnaires on socioeconomic levels, health behaviors and diet during pregnancy. The association between exposome and LBW were examined by five machine learning methods including Naïve bayes, Support vector machine (SVM), Random forest, XGBoost (eXtreme gradient boosting) and Ensemble learning. Model performance was evaluated by area under Receiver operator characteristic (ROC) curve. And, features selection was used to identify important features. RESULTS SVM method and Random forest provided the best prediction based on AUC= 0.73 and 0.74, respectively. The top five important features selected from best model prediction of Random forest include: perfluorooctyl sulfonate (PFOS) in cord blood, uranium and zinc in maternal urine, maternal pre-pregnancy body mass index, maternal gestational weight gain. CONCLUSIONS Machine learning approaches could be useful tools for modeling early life exposome associated with LBW. Environmental pollutants and maternal weight status are critical for LBW risk. KEYWORDS exposome, machine learning, environmental pollutants, low birth weight

Urban green spaces and suicide mortality in Belgium (2001-2011): a census-based longitudinal study

BACKGROUND Exposure to green spaces is associated with improved mental health and may reduce the risk of suicide. Here, we investigate the association between long-term exposure to residential surrounding greenness and suicide mortality. METHODS We used data from the 2001 Belgian census linked to mortality register data (2001-2011). We included individuals aged 18 years or older at baseline (2001) and residing in the five largest urban areas in Belgium (n=3,549,514). Suicide mortality was defined using ICD-10 codes X60-X84, Y10-Y34, and Y870. Surrounding greenness was measured using the Normalized Difference Vegetation Index (NDVI) within 300m and 1,000m buffers around the residential address at baseline. To assess the association between residential surrounding greenness and suicide mortality, we applied Cox proportional hazards models with age as the underlying time scale. Models were adjusted for age, sex, marital status, migrant background, educational attainment, neighbourhood socio-economic position. We additionally explored potential mediation with residential outdoor nitrogen dioxide (NO2) concentrations. Associations are expressed as hazard ratios (HR) and their 95% confidence intervals (CI) for an interquartile range (IQR) increase in residential surrounding greenness. RESULTS Between 2001 and 2011, 8,577 suicide deaths were registered. We observed a 7% (95%CI 0.89-0.97) and 6% (95%CI 0.90-0.98) risk reduction of suicide mortality for an IQR increase in residential surrounding greenness for buffers of 300m and 1,000m, respectively. Furthermore, this association was independent of exposure to NO2. After stratification, the inverse association was only apparent among females, and residents of Belgian origin, and that it was stronger among residents aged 36 or older, those with high level of education, and residents living in socio-economic deprived neighborhoods. CONCLUSION Our results suggest that urban green spaces may protect against suicide mortality, but this beneficial effect may not be equally distributed across all strata of the population. KEYWORDS Suicide mortality; surrounding greenness; longitudinal study

Exposure to road traffic noise and cognitive development in schoolchildren in Barcelona, Spain: A population-based cohort study.

BackgroundRoad traffic noise is a prevalent and known health hazard. However, little is known yet about its effect on children’s cognition. We aimed to study the association between exposure to road traffic noise and the development of working memory and attention in primary school children, considering school-outdoor and school-indoor annual average noise levels and noise fluctuation characteristics, as well as home-outdoor noise exposure.Methods and findingsWe followed up a population-based sample of 2,680 children aged 7 to 10 years from 38 schools in Barcelona (Catalonia, Spain) between January 2012 to March 2013. Children underwent computerised cognitive tests 4 times (n = 10,112), for working memory (2-back task, detectability), complex working memory (3-back task, detectability), and inattentiveness (Attention Network Task, hit reaction time standard error, in milliseconds). Road traffic noise was measured indoors and outdoors at schools, at the start of the school year, using standard protocols to obtain A-weighted equivalent sound pressure levels, i.e., annual average levels scaled to human hearing, for the daytime (daytime LAeq, in dB). We also derived fluctuation indicators out of the measurements (noise intermittency ratio, %; and number of noise events) and obtained individual estimated indoor noise levels (LAeq) correcting for classroom orientation and classroom change between years. Home-outdoor noise exposure at home (Lden, i.e., EU indicator for the 24-hour annual average levels) was estimated using Barcelona’s noise map for year 2012, according to the European Noise Directive (2002). We used linear mixed models to evaluate the association between exposure to noise and cognitive development adjusting for age, sex, maternal education, socioeconomical vulnerability index at home, indoor or outdoor traffic-related air pollution (TRAP) for corresponding school models or outdoor nitrogen dioxide (NO2) for home models. Child and school were included as nested random effects.The median age (percentile 25, percentile 75) of children in visit 1 was 8.5 (7.8; 9.3) years, 49.9% were girls, and 50% of the schools were public. School-outdoor exposure to road traffic noise was associated with a slower development in working memory (2-back and 3-back) and greater inattentiveness over 1 year in children, both for the average noise level (e.g., ‒4.83 points [95% CI: ‒7.21, ‒2.45], p-value < 0.001, in 2-back detectability per 5 dB in street levels) and noise fluctuation (e.g., ‒4.38 [‒7.08, ‒1.67], p-value = 0.002, per 50 noise events at street level). Individual exposure to the road traffic average noise level in classrooms was only associated with inattentiveness (2.49 ms [0, 4.81], p-value = 0.050, per 5 dB), whereas indoor noise fluctuation was consistently associated with all outcomes. Home-outdoor noise exposure was not associated with the outcomes. Study limitations include a potential lack of generalizability (58% of mothers with university degree in our study versus 50% in the region) and the lack of past noise exposure assessment.ConclusionsWe observed that exposure to road traffic noise at school, but not at home, was associated with slower development of working memory, complex working memory, and attention in schoolchildren over 1 year. Associations with noise fluctuation indicators were more evident than with average noise levels in classrooms.

The Effects of Traffic Air Pollution in and around Schools on Executive Function and Academic Performance in Children: A Rapid Review.

This review summarises the extant literature investigating the relation between traffic-related air pollution levels in and around schools and executive functioning in primary-school-aged children. An electronic search was conducted using Web of Science, Scopus, and Education Literature Datasets databases (February 2020). Review articles were also searched, and forwards and backwards searches of identified studies were performed. Included papers were assessed for quality. We included 9 separate studies (published in 13 papers). Findings suggest that indoor and outdoor particulate matter with a diameter of 2.5 μm or less (PM2.5) negatively influences executive function and academic achievement and that indoor and outdoor nitrogen dioxide (NO2) adversely affects working memory. Evidence for the effects of particulate matter with a diameter of 10 μm or less (PM10) is limited but suggests potential wide-ranging negative effects on attention, reasoning, and academic test scores. Air pollution in and around schools influences executive function and appears to impede the developmental trajectory of working memory. Further research is required to establish the extent of these effects, reproducibility, consequences for future attainment, and place within the wider context of cognitive development.

Invited Perspective: Moving from Characterizing to Addressing Racial/Ethnic Disparities in Air Pollution Exposure.

Invited Perspective: Moving from Characterizing to Addressing Racial/Ethnic Disparities in Air Pollution Exposure.

Land use regression modelling of NO2 in São Paulo, Brazil

BackgroundAir pollution is a major global public health problem. The situation is most severe in low- and middle-income countries, where pollution control measures and monitoring systems are largely lacking. Data to quantify the exposure to air pollution in low-income settings are scarce. MethodsIn this study, land use regression models (LUR) were developed to predict the outdoor nitrogen dioxide (NO2) concentration in the study area of the Western Region Birth Cohort in São Paulo. NO2 measurements were performed for one week in winter and summer at eighty locations. Additionally, weekly measurements at one regional background location were performed over a full one-year period to create an annual prediction. ResultsThree LUR models were developed (annual, summer, winter) by using a supervised stepwise linear regression method. The winter, summer and annual models explained 52 %, 75 % and 66 % of the variance (R2) respectively. Cross-holdout validation tests suggest robust models. NO2 levels ranged from 43.2 μg/m3 to 93.4 μg/m3 in the winter and between 28.1 μg/m3 and 72.8 μg/m3 in summer. Based on our annual prediction, about 67 % of the population living in the study area is exposed to NO2 values over the WHO suggested annual guideline of 40 μg/m3 annual average. ConclusionIn this study we were able to develop robust models to predict NO2 residential exposure. We could show that average measures, and therefore the predictions of NO2, in such a complex urban area are substantially high and that a major variability within the area and especially within the season is present. These findings also suggest that in general a high proportion of the population is exposed to high NO2 levels.

Systematic review and meta-analysis of cohort studies of long term outdoor nitrogen dioxide exposure and mortality.

To determine whether long term exposure to outdoor nitrogen dioxide (NO2) is associated with all-cause or cause-specific mortality. MEDLINE, Embase, CENTRAL, Global Health and Toxline databases were searched using terms developed by a librarian. Screening, data extraction and risk of bias assessment were completed independently by two reviewers. Conflicts were resolved through consensus and/or involvement of a third reviewer. Pooling of results across studies was conducted using random effects models, heterogeneity among included studies was assessed using Cochran's Q and I2 measures, and sources of heterogeneity were evaluated using meta-regression. Sensitivity of pooled estimates to individual studies was examined and publication bias was evaluated using Funnel plots, Begg's and Egger's tests, and trim and fill. Seventy-nine studies based on 47 cohorts, plus one set of pooled analyses of multiple European cohorts, met inclusion criteria. There was a consistently high degree of heterogeneity. After excluding studies with probably high or high risk of bias in the confounding domain (n = 12), pooled hazard ratios (HR) indicated that long term exposure to NO2 was significantly associated with mortality from all/ natural causes (pooled HR 1.047, 95% confidence interval (CI), 1.023-1.072 per 10 ppb), cardiovascular disease (pooled HR 1.058, 95%CI 1.026-1.091), lung cancer (pooled HR 1.083, 95%CI 1.041-1.126), respiratory disease (pooled HR 1.062, 95%CI1.035-1.089), and ischemic heart disease (pooled HR 1.111, 95%CI 1.079-1.144). Pooled estimates based on multi-pollutant models were consistently smaller than those from single pollutant models and mostly non-significant. For all causes of death other than cerebrovascular disease, the overall quality of the evidence is moderate, and the strength of evidence is limited, while for cerebrovascular disease, overall quality is low and strength of evidence is inadequate. Important uncertainties remain, including potential confounding by co-pollutants or other concomitant exposures, and limited supporting mechanistic evidence. (PROSPERO registration number CRD42018084497).

A national cross-sectional study of exposure to outdoor nitrogen dioxide and aeroallergen sensitization in Australian children aged 7-11 years.

The prevalence of allergic diseases in Australian children is high, but few studies have assessed the potential role of outdoor air pollution in allergic sensitization. We investigated the association between outdoor air pollution and the prevalence of aeroallergen sensitization in a national cross-sectional study of Australian children aged 7-11 years. Children were recruited from 55 participating schools in 12 Australian cities during 2007-2008. Parents completed a detailed (70-item) questionnaire. Outdoor nitrogen dioxide (NO2), as a proxy for exposure to traffic-related emissions, was estimated using measurements from regulatory monitors near each school and a national land-use regression (LUR) model. Three averaging periods were assessed, using information on duration of residence at the address, including lifetime, previous (lifetime, excluding the last year), and recent (the last year only). The LUR model was used as an additional source of recent exposure estimates at school and home addresses. Skin prick tests (SPTs) were performed to measure sensitization to eight common aeroallergens. Multilevel logistic regression estimated the association between NO2 and sensitization (by individual allergens, indoor and outdoor allergens, and all allergens combined), after adjustment for individual- and area-level covariates. In total, 2226 children had a completed questionnaire and SPT. The prevalence of sensitization to any allergen was 44.4%. Sensitization to house dust mites (HDMs) was the most common (36.1%), while sensitization to Aspergillus was the least common (3.4%). Measured mean (±s.d.) NO2 exposure was between 9 (±2.9) ppb and 9.5 (±3.2) ppb, depending on the averaging period. An IQR (4ppb) increase in measured previous NO2 exposure was associated with greater odds of sensitization to HDMs (OR: 1.21, 95% CI: 1.01-1.43, P=0.035). We found evidence of an association between relatively low outdoor NO2 concentrations and sensitization to HDMs, but not other aeroallergens, in Australian children aged 7-11 years.

Combining citizen science and deep learning for large-scale estimation of outdoor nitrogen dioxide concentrations

Reliable estimates of outdoor air pollution concentrations are needed to support global actions to improve public health. We developed a new approach to estimating annual average outdoor nitrogen dioxide (NO2) concentrations using approximately 20,000 ground-level measurements in Flanders, Belgium combined with aerial images and deep neural networks. Our final model explained 79% of the spatial variability in NO2 (root mean square error of 10-fold cross-validation = 3.58 μg/m3) using only images as model inputs. This novel approach offers an alternative means of estimating large-scale spatial variations in ambient air quality and may be particularly useful for regions of the world without detailed emissions data or land use information typically used to estimate outdoor air pollution concentrations.

Spatial decomposition analysis of NO2 and PM2.5 air pollution in the United States

Background: Length scales for spatial variability of air pollution concentrations depend on the pollutant and the location, from meters to 100s or 1000s of km. Spatial patterns of the concentration at a location could reveal information on pollution sources. Methods: Here, we develop a readily scalable algorithm based on “spatial-increment”, to decompose the air pollution concentration into four spatial components: long-range, mid-range, neighborhood, and near-source. We apply the algorithm to annual-average predicted concentrations of outdoor nitrogen dioxide (NO2) and fine particulate matter (PM2.5) for all (n ≈ 6 million) census blocks in the contiguous US, from national empirical models. We analyze the within-city patterns of the decomposed concentrations and summarize the national decomposition results by state, geographic region, and urban area size. We also calculate how much each empirical regression component contributes to the spatial decomposition results. Results: Our results show that for NO2, “neighborhood” and “mid-range” components dominate both with-city and inter-city concentration differences (both are ~5-fold larger in large urbanized areas than rural areas). Urban area size plays a more important role in the component concentrations than geographic regions. For PM2.5, the “long-range” component dominates; this component varies by region (e.g., three times greater in the Midwest [7 μg/m3] than in the West [2.3 μg/m3]), whereas variation by urban area size is relatively minor. Conclusions: Our study provides the first nation-level fine-scale decomposed pollution surfaces to date, that can be used to estimate, at least to a zeroth order, the contribution of sources at different distances from the receptor to the annual average pollution in the location of interest.

Gestational exposures to outdoor air pollutants in relation to low birth weight: A retrospective observational study

Findings for impacts of outdoor air pollutants on birth outcomes were controversial. We performed a retrospective observational study in 2527 preschoolers of Shanghai, China and investigated associations of duration-averaged concentrations of outdoor sulphur dioxide (SO2), nitrogen dioxide (NO2), and particulate matter with an aerodynamic diameter ≤ 10 μm (PM10) in different months and trimesters of gestation, with preterm birth (PB), low birth weight (LBW), term low birth weight (T-LBW), and small for gestational age (SGA). Daily concentrations of outdoor air pollutants were collected in each residence-located district. Parents reported health information. In the multivariate logistic regression analyses, exposures to outdoor NO2 were consistently associated with the higher odds of LBW and T-LBW. These associations were generally stronger for early months than for later months of the gestation. Adjusted odds ratios generally were larger in multi-pollutant model than in single-pollutant model. Exposure to NO2 in the first month of the gestation was significantly associated with T-LBW (adjusted OR, 95%CI: 1.91, 1.02–3.58 for increment of interquartile range (18.5 μg/m3); p-value = 0.044) in multi-pollutant model. This association was stronger in girls, renters, and children whose mothers ≥30 years-old, with household dampness-related exposures, and with parental smoking during pregnancy. Our results indicate that exposure to NO2 during gestation perhaps is a risk factor for LBW and T-LBW, and effects of NO2 exposures could be greater during early periods than during later periods of gestation.

Prenatal and postnatal exposures to ambient air pollutants associated with allergies and airway diseases in childhood: A retrospective observational study

It’s inconsistent about associations of early exposures to outdoor air pollutants with allergies and airway diseases in childhood. Here, we investigated associations of prenatal and postnatal exposures to outdoor nitrogen dioxide (NO2), sulphur dioxide (SO2), and PM10 (particulate matter with an aerodynamic diameter ≤ 10 μm) with asthma, wheeze, hay fever, rhinitis, pneumonia, and eczema in childhood. We surveyed 3,177 preschoolers who never change residences since birth in Shanghai, China. Parents reported information regarding children’s health status. Daily-averaged concentrations of these pollutants in the children’s gestation and in the first year of lifetime for district where children lived were collected by Shanghai Environmental Monitoring Center. After adjusting for covariates, exposures to higher level of NO2 during different trimesters of gestation and of the first year of lifetime had significant associations with the increased odds of asthma, hay fever, rhinitis, pneumonia, and eczema in childhood. Associations of NO2 exposures in the early trimesters of gestation and of the first year of lifetime with pneumonia were stronger than in the later trimesters, whereas associations of NO2 exposures in the early trimesters with hay fever and eczema were weaker than in the later trimesters. Our results indicated that prenatal and postnatal exposures to outdoor NO2 could be risk factors for allergies and airway diseases in childhood. Both dose and duration were related with the influence degree of early NO2 exposure on childhood allergies and airway diseases.

Spatial decomposition analysis of NO2 and PM2.5 air pollution in the United States

Abstract Length scales for spatial variability of air pollution concentrations depend on the pollutant and the location. In this paper, we develop a readily scalable algorithm based on “spatial-increment”, to decompose the air pollution concentration into four spatial components: long-range, mid-range, neighborhood, and near-source. We apply the algorithm to annual-average concentrations of outdoor nitrogen dioxide (NO2) and fine particulate matter (PM2.5) for all census blocks in the contiguous US. For NO2, “neighborhood” and “mid-range” components dominate both within-city and between-city concentration differences (both components are ~5-fold larger in large urbanized areas than rural areas). For PM2.5, the “long-range” component dominates; this component varies by region (e.g., is three times greater in the Midwest [7 μg/m3] than in the West [2.3 μg/m3]), whereas variation by urban area size is relatively minor. Our study provides the first nation-level fine-scale decomposed pollution surfaces to date; this dataset is publicly available. Results can be used to estimate, at least to a zeroth order, the contribution of sources at different distances from the receptor to the annual average pollution in a location of interest.

Outdoor air pollution and the burden of childhood asthma across Europe.

Emerging evidence suggests that air pollution may contribute to childhood asthma development. We estimated the burden of incident childhood asthma that may be attributable to outdoor nitrogen dioxide (NO2), particulate matter ≤2.5 µm in diameter (PM2.5) and black carbon (BC) in Europe. We combined country-level childhood incidence rates and pooled exposure-response functions with childhood (age 1-14 years) population counts, and exposure estimates at 1 540 386 1 km×1 km cells, across 18 European countries and 63 442 419 children. Annual average pollutant concentrations were obtained from a validated and harmonised European land-use regression model. We investigated two exposure reduction scenarios. For the first, we used recommended annual World Health Organization (WHO) air quality guideline values. For the second, we used the minimum air pollution levels recorded across 41 studies in the underlying meta-analysis. NO2 ranged from 1.4 to 70.0 µg·m-3, with a mean of 11.8 µg·m-3. PM2.5 ranged from 2.0 to 41.1 µg·m-3, with a mean of 11.6 µg·m-3. BC ranged from 0.003 to 3.7×10-5 m-1, with a mean of 1.0×10-5 m-1. Compliance with the NO2 and PM2.5 WHO guidelines was estimated to prevent 2434 (0.4%) and 66 567 (11%) incident cases, respectively. Meeting the minimum air pollution levels for NO2 (1.5 µg·m-3), PM2.5 (0.4 µg·m-3) and BC (0.4×10-5 m-1) was estimated to prevent 135 257 (23%), 191 883 (33%) and 89 191 (15%) incident cases, respectively. A significant proportion of childhood asthma cases may be attributable to outdoor air pollution and these cases could be prevented. Our estimates underline an urgent need to reduce children's exposure to air pollution.