Low Levels Of PM2 Research Articles

Pollutants-mediated viral hepatitis in different types: assessment of different algorithms and time series models

The escalating frequency of environmental pollution incidents has raised significant concerns regarding the potential health impacts of pollutant fluctuations. Consequently, a comprehensive study on the role of pollutants in the prevalence of viral hepatitis is indispensable for the advancement of innovative prevention strategies. Monthly incidence rates of viral hepatitis from 2005 to 2020 were sourced from the Chinese Center for Disease Control and Prevention Infectious Disease Surveillance Information System. Pollution data spanning 2014–2020 were obtained from the National Oceanic and Atmospheric Administration (NOAA), encompassing pollutants such as CO, NO2, and O3. Time series analysis models, including seasonal auto-regressive integrated moving average (SARIMA), Holt-Winters model, and Generalized Additive Model (GAM), were employed to explore prediction and synergistic effects related to viral hepatitis. Spearman correlation analysis was utilized to identify pollutants suitable for inclusion in these models. Concurrently, machine learning (ML) algorithms were leveraged to refine the prediction of environmental pollutant levels. Finally, a weighted quantile sum (WQS) regression framework was developed to evaluate the singular and combined impacts of pollutants on viral hepatitis cases across different demographics, age groups, and environmental strata. The incidence of viral hepatitis in Beijing exhibited a declining trend, primarily characterized by HBV and HCV types. In predicting hepatitis prevalence trends, the Holt-Winters additive seasonal model outperformed the SARIMA multiplicative model ((1,1,0) (2,1,0) [12]). In the prediction of environmental pollutants, the SVM model demonstrated superior performance over the GPR model, particularly with Polynomial and Besseldot kernel functions. The combined pollutant risk effect on viral hepatitis was quantified as βWQS (95% CI) = 0.066 (0.018, 0.114). Among different groups, PM2.5 emerged as the most sensitive risk factor, notably impacting patients with HCV and HEV, as well as individuals aged 35–64. CO predominantly affected HAV patients, showing a risk effect of βWQS (95% CI) = − 0.0355 (− 0.0695, − 0.0016). Lower levels of PM2.5 and PM10 were associated with heightened risk of viral hepatitis incidence with a lag of five months, whereas elevated levels of PM2.5 (100–120 μg/m3) and CO correlated with increased hepatitis incidence risk with a lag of six months. The Holt-Winters model outperformed the SARIMA model in predicting the incidence of viral hepatitis. Among machine learning algorithms, SVM and GPR models demonstrated superior performance for analyzing pollutant data. Patients infected with HAV and HEV were primarily influenced by PM10 and CO, whereas SO2 and PM2.5 significantly impacted others. Individuals aged 35–64 years appeared particularly susceptible to these pollutants. Mixed pollutant exposures were found to affect the development of viral hepatitis with a notable lag of 5–6 months. These findings underscore the importance of long-term monitoring of pollutants in relation to viral hepatitis incidence.

Ambient air pollution and survival in childhood cancer: A nationwide survival analysis.

Particulate matter consisting of fine particles measuring 2.5 microns or less in diameter (PM2.5), a component of air pollution, has been linked to adverse health outcomes. The objective of this study was to assess the association between ambient PM2.5 exposure and survival in children with cancer in the United States. Individuals aged birth to 19 years who were diagnosed with cancer between January 1, 2004, and December 31, 2019, were selected from the National Cancer Database. The association between the annual PM2.5 level at the patient's zip code of residence at the time of diagnosis and overall survival was evaluated using time-varying Cox proportional hazards models (crude and adjusted for diagnosis year and age). To address concerns that exposure to air pollution is correlated with other social determinants of health, the authors tested the association between PM2.5 levels and survival among sociodemographic subgroups. Of the 172,550 patients included, 27,456 (15.9%) resided in areas with annual PM2.5 concentrations above the US Environmental Protection Agency (EPA) annual PM2.5 standard of 12 μg/m3. Residing in these high-pollution areas was associated with worse overall survival (adjusted hazard ratio [aHR], 1.06; 95% confidence interval [CI], 1.012-1.10). Similarly, when PM2.5 was evaluated as a linear measure, each unit increase in PM2.5 exposure was associated with worse survival (aHR, 1.011; CI, 1.005-1.017). Exposure to PM2.5 at levels above the EPA standards was also significantly associated with worse overall survival among sociodemographic subgroups. Exposure to PM2.5 was significantly associated with worse overall survival among children with cancer, even at levels below EPA air quality standards. These results underscore the importance of setting appropriate air quality standards to protect the health of this sensitive population. The authors investigated how living in areas with high air pollution (defined as particulate matter consisting of fine particles measuring 2.5 microns or less in diameter; PM2.5) affects the overall survival of children with cancer in the United States. The results indicated that children living in areas with higher PM2.5 levels, and even at levels below prior and current US Environmental Protection Agency standards, had lower survival rates than children living in areas with lower levels of PM2.5. This finding emphasizes the need for stricter air quality standards to better protect children, particularly those with serious health conditions like childhood cancer.

Spatiotemporal characterization of PM2.5, O3, and trace gases associated with East Asian continental outflows via drone sounding

East Asian continental outflows with PM2.5, O3, and other species may determine the baseline conditions and affect the air quality in downwind areas via long-range transport (LRT). To gain insight into the impact and spatiotemporal characteristics of airborne pollutants in East Asian continental outflows, a versatile multicopter drone sounding platform was used to simultaneously observe PM2.5, O3, CO2, and meteorological variables (temperature, specific humidity, pressure, and wind vector) above the northern tip of Taiwan, Cape Fuiguei, which often encounters continental outflows during winter monsoon periods. By coordinating hourly high-spatial-resolution profiles provided by drone soundings, WRF/CMAQ model air quality predictions, HYSPLIT-simulated backward trajectories, and MERRA-2 reanalysis data, we analyzed two prominent phenomena of airborne pollutants in continental outflows to better understand their physical/chemical characteristics. First, we found that pollutants were well mixed within a sounding height of 500 m when continental outflows passed through and completely enveloped Cape Fuiguei. Eddies induced by significant fluctuations in wind speeds coupled with minimal temperature inversion and LRT facilitated vertical mixing, possibly resulting in high homogeneity of pollutants within the outflow layer. Second, the drone soundings indicated exceptionally high O3 concentrations (70–100 ppbv) but relatively low concentrations of PM2.5 (10–20 μg/m3), CO2 (420–425 ppmv), and VOCs in some air masses. The low levels of PM2.5, CO2, and VOCs ruled out photochemistry as the cause of the formation of high-level O3. Further coordination of spatiotemporal data with air mass trajectories and O3 cross sections provided by MERRA-2 suggested that the high O3 concentrations could be attributed to stratospheric intrusion and advection via continental outflows. High-level O3 concentrations persisted in the lower troposphere, even reaching the surface, suggesting that stratospheric intrusion O3 may be involved in the rising trend in O3 concentrations in parts of East Asia in recent years in addition to surface photochemical factors.

Seasonal changes in water-soluble brown carbon (BrC) at Nanling background station in South China

Brown carbon (BrC) is an important light-absorbing component of organic carbon (OC), causing large uncertainty in aerosol radiative forcing evaluation and being related to health issues as well. Knowledge of BrC in an atmospheric background station is beneficial to understand its role in a changing climate. A year-long sampling campaign was conducted at Nanling background station to get a comprehensive knowledge of WS-BrC, a total of seventy-two PM2.5 samples throughout a year were used. Light absorption and fluorescence spectra of WSOC were analyzed synchronously using a fluorescence spectrophotometer. The low levels of PM2.5, OC, and elemental carbon (EC) conferred a background site. The optical properties of WS-BrC were characterized using excitation-emission matrix (EEM) fluorescence spectroscopy. The WS-BrC made a significant contribution (365 nm, 18% ± 10%) to total carbonaceous aerosol absorption. The mass absorption efficiency (MAE) of WS-BrC is 0.81 ± 0.34 m2 gC–1, and varies among seasons due to the different sources or atmospheric processing. Three EEM fluorescent components were identified by parallel factor (PAFAFAC) analysis, including two humic-like substances (HULIS, C1, C2), and one phenolic-like component. The HULIS components accounted for approximately 70% of the total fluorescence intensities. Primary combustion emissions showed enhanced activity during the winter and spring seasons, but there were no significant influences on WS-BrC in spring. Secondary sources contributed significantly to WS-BrC during winter, summer, and autumn (all exceeding 50%), except for spring. Photooxidation is a significant process in the formation of secondary WS-BrC in winter and autumn, but there may be another formation pathway in summer, i.e., the ammonia pathway. This study contributes to our understanding of BrC in the background atmosphere.

Atmospheric PM2.5 before and After Lockdown in Relation to COVID-19 Evolution and Daily Viral Counts: Could Viral Natural Selection Have Occurred due to Changes in the Airborne Pollutant PM2.5?

Background: Genes coding for SARS-CoV-2 have been detected on the microscopic airborne pollutant particulate matter, which has been suggested as a vector and co-factor for COVID-19 transmission. Lockdown in China has been shown to be associated with significant reduction in pollution including the particulate matter component which coincided with the appearance of a viral mutant (Clade G) which steadily displaced the original Clade D after lockdown. The reason why Clade G developed a fitness advantage is as yet unknown. This paper examines the possible role of airborne particulate matter PM2.5 as selective pressure determining viral Clade predominance and further shedding light on the mode of SARS-CoV-2 transmission. Methods: The average levels of PM2.5 of a number of cities were obtained from the Air Quality Index (AQI), a real-time assessment of atmospheric pollution. The daily average PM2.5 levels were assessed between January 23rd and April 29th 2020 determined by the timeline when viral counts in Beijing and other cities were available. Daily viral counts of Clades D and G were available starting from the 12th February as determined by the scientific literature published in August 2020. The cities chosen were Beijing, Sheffield, Nottingham, Sydney and Cambridge because of their substantially elevated viral counts compared to other cities. Cities as opposed to vaster areas/nations were chosen as PM2.5 levels vary across regions and countries. Results: For the time period assessed, the Beijing PM2.5 pattern initiated with highly elevated mean PM2.5 levels of 147.5µg/ m3 (SD+/-70.5) during high viral counts, followed by 98.5µg/m3 (SD+/-50.7) (p<0.007) when the viral counts decreased. In all the other cities assessed, the pattern differed whereby the PM2.5 levels increased significantly over the preceding baseline contemporaneously with the viral count rise. The changes in these cities’ PM2.5 levels were on average 34.4µg/m3 before viral counts rose and 46.0µg/m3 contemporaneous with viral count rise. As regards the viral counts from data retrieved from Beijing, the latter part of the bell-shaped curve and a subsequent smaller curve of the viral count was available for evaluation. The average viral count for Clade D in Beijing was 11.1(SD+/-13.5) followed by a mean viral count for Clade G was 13.8(SD+/- 9.2). Conversely in all the other cities besides Beijing, the viral counts averaged 45.8 for Clade D and 161 for Clade G. The variation in viral counts between cities suggests the strong possibility of variation in the availability of sampling between cities. The newer variant, Clade G demonstrated viral counts initially appearing in mid-February in Beijing to later displace Clade D as the dominant viral Clade. The appearance of Clade G coincided with the decreasing gradient of PM2.5 levels. A number of significant correlations were obtained between PM2.5 levels and the viral count in all the cities reviewed. Conclusion: COVID-19 viral counts appear to increase concomitant with increasing PM2.5 levels. Viral counts of both Clades correlated differentially with PM2.5 levels in all the cities assessed. The significantly highly elevated PM2.5 levels in Beijing resulted in correlating mainly with Clade D, however Clade G began to appear with decreasing PM2.5 levels, suggesting the beginnings for the initial SARS-CoV-2 Clade evolution. Clade G, the newer variant was able to flourish at lower levels of PM2.5 than Clade D. Clade G may possibly have utilized other sources of particulate matter as a viral vector, and co-factor such as that derived from tobacco smoking, whereby 66% of Chinese males are smokers and 70% of the Chinese non-smoking population are exposed to 2nd hand smoking.

Wildfire smoke reduces Little Eagle (Hieraaetus morphnoides) flight activity

ABSTRACT There have been few empirical studies of the sensitivity of birds to the effect of air pollutants. In late 2019 and early 2020 the Australian Capital Territory (ACT) and much of south-eastern Australia were affected by extreme wildfire events and smoke extended to surrounding areas. Prior to this event, GPS transmitters had been fitted to a sample of Little Eagles Hieraaetus morphnoides in the ACT as part of a study of their movement behaviour. Three of these birds carried transmitters in the breeding season during the fires and in the previous breeding season. This offered opportunistic analysis of data from both periods to test for effects of smoke on the birds’ flight behaviour. The effects of particulate matter in the air of ≤2.5 microns in diameter (PM2.5) and covariates on flight status were investigated with a binomial generalised linear model with logistic link. The birds were more likely to fly when there were low levels of PM2.5 and the odds of flying decreased as density of PM2.5 increased at a rate of 0.202% per ug/m3. None of the sample birds died during or after smoke exposure, although their respiratory system might have been affected.

Sulfur isotope-based source apportionment and control mechanisms of PM2.5 sulfate in Seoul, South Korea during winter and early spring (2017–2020)

High level of particulate matter (PM) concentrations are a major environmental concern in Seoul, South Korea, especially during winter and early spring. Sulfate is a major component of PM and induces severe environmental pollution, such as acid precipitation. Previous studies have used numerical models to constrain the relative contributions of domestic and trans-boundary sources to PM2.5 sulfate concentration in South Korea. Because of the scarce measurement result of δ34S for PM2.5 sulfate in South Korea, poorly defined δ34S value of domestic sulfur sources, and no application of sulfur isotope fractionation during sulfate formation in previous observation-based studies, source apportionment results conducted by model studies have not been corroborated from independent chemical observations. Here, we examined the δ34S of PM2.5 in Seoul and domestic sulfur sources, and considered the sulfur isotope fractionation for accurate source apportionment constraint. Accordingly, domestic and trans-boundary sulfur sources accounted for approximately (16–32) % and (68–84) % of the sulfate aerosols in Seoul, respectively, throughout the winter and early spring of 2017–2020. Air masses passing through north-eastern China had relatively low sulfate concentrations, enriched δ34S, and a low domestic source contribution. Those passing through south-eastern China had relatively a high sulfate concentrations, depleted δ34S, and high domestic source contribution. Furthermore, elevated PM2.5 sulfate concentrations (>10 μg m−3) were exclusively associated with a weak westerly wind speed of <3 m s−1. From December 2019 to March 2020, Seoul experienced relatively low levels of PM2.5 sulfate, which might be attributed to favorable weather conditions rather than the effects of COVID-19 containment measures. Our results demonstrate the potential use of δ34S for accurate source apportionment and for identifying the crucial role of regional air mass transport and meteorological conditions in PM2.5 sulfate concentration. Furthermore, the data provided can be essential for relevant studies and policy-making in East Asia.

Facial Expressions of Urban Forest Visitors Jointly Exposed to Air Pollution and Regional Climate

Urban forests have important functions to alleviate air pollution, adjust the regional climate, and promote visitors’ mental health and well-being. Humans’ perceptions towards both atmospheric particulate matter (PM) and meteorological factors can be a gauge for assessing the functional services of urban forests. The geographical locations of host cities experiencing urbanization could take part in effects on emotional states of forest visitors. In this study, a total of 6309 facial photos of urban forest visitors were obtained from social networks in 42 cities of mainland China. Happy, sad, and neutral emotions were rated as percent scores in 2020, when the same-day air pollutants, meteorological factors, and socioeconomic indicators were recorded. The positive emotional index (PEI) was calculated as the difference between happy scores and sad scores. The results reveal that severe air pollutants (jointly PM2.5 &gt; 75 μg/m3, PM10 &gt; 150 μg/m3, and AQI &gt; 150) were more frequently found in cities in the northeastern and northern areas of China. The forest visitors in the northeastern cities showed higher happiness scores compared to the visitors in other regions. The Quasi-Poisson regression suggested that high scores of happiness were frequently disclosed in weathers with low PM10. High scores of sadness were regressed on exposure to cities with a low GDP per capita and low total retail sales but with a high GDP at low-longitudinal and high-latitudinal locations with low levels of PM2.5 pollution, relative humidity, and wind velocity and a high temperature. The happiness score and PEI showed high-value aggregations in mega-sized cities (population over 10 million), such as Beijing and Zhengzhou, and in a metro-sized city (population of 5–10 million in Langfang) from climate regions of China.

What is the role of particulate matter 2.5 (PM2.5) on excess weight? A cross-sectional study in young Spanish people aged 2─14 years

PurposeTo assess the relationship between particulate matter 2.5 (PM2.5) levels and the prevalence of excess weight in a representative sample of Spanish young people aged 2─14 years. MethodsThis was an ecological cross-sectional study using data from the 2017 wave of the Encuesta Nacional de Salud Española (ENSE), a nationally representative survey of the Spanish young and adult population. The final sample included 4378 young Spanish people (51.0% boys). The weight (kg) and height (cm) of the study participants were proxy-reported by parents or guardians. Excess weight was determined according to the age- and sex-criteria of the International Obesity Task Force. The PM2.5 level was calculated as the annual monitoring data indicator for 2017 among the different regions in Spain. Logistic regression models were performed to estimate the relationships between PM2.5 and weight. ResultsCompared to young people located in regions with low levels of PM2.5, those reporting greater odds for excess weight were found in regions with medium PM2.5 (OR = 1.23; 95% CI, 1.02–1.49) and high PM2.5 (OR = 1.35; 95% CI, 1.11–1.64) after adjusting for several sociodemographic, lifestyle and environmental covariates. ConclusionsThe prevalence of excess weight in young people was positively associated with PM2.5 levels in Spain. This finding supports the hypothesis that air pollution exposure can result in excess weight in the young population, which, in turn, might lead to the development of metabolic disorders. From a socioecological perspective, a practical need to take environmental factors into consideration is important to address unhealthy weight in Spanish young people.

PM2.5, and soot measurements in Gqeberha municipality, South Africa

Background and aim: Air pollution is a major risk factor in Africa. Air pollution exposure assessment studies are lacking in South Africa and Africa, especially on fine particulate matter (PM2.5) and its chemical composition. The aim of this study was to assess the PM2.5 and soot levels in Gqeberha municipality, Eastern Cape province, South Africa Method: The study was conducted in an urban area located in Gqeberha municipality. Gravimetric analysis was used to determine PM2.5 levels from May 2021 to January 2022. Soot measurements were done using a smoke stain reflectometer. All analysis was done in the air quality laboratory at the School of Health Systems and Public Health (SHSPH) at the University of Pretoria. Results: The average PM2.5 level during the study period was 4.97&amp;#xb1; 2.99 µg/m3 which was lower than the annual WHO air quality guideline (5 µg/m3) and lower than the annual South African air quality standard (20 µg/m3). The mean soot level was 1.07 10-7m-1. Conclusion: This baseline study shows that background level PM2.5 levels in Gqeberha municipality. Although these levels are relatively low, further studies in the area are still needed. Especially that evidence shows that low levels of PM2.5 can lead to adverse health effects. Keywords: Air pollution, PM2.5, South Africa, black carbon, soot

Technical note: Understanding the effect of COVID-19 on particle pollution using a low-cost sensor network

The 2020 coronavirus pandemic and the following quarantine measures have led to significant changes in daily life worldwide. Preliminary research indicates that air quality has improved in many urban areas as a result of these measures. This study takes a neighborhood-scale approach to quantifying this change in pollution. Using data from a network of citizen-hosted, low-cost particulate matter (PM) sensors, called Air Quality & yoU (AQ&U), we obtained high-spatial resolution measurements compared to the relatively sparse state monitoring stations. We compared monthly average estimated PM2.5 concentrations from February 11 to May 11, 2019 at 71 unique locations in Salt Lake County, UT, USA with the same (71) sensors’ measurements during the same timeframe in 2020. A paired t-test showed significant reductions (71.1% and 21.3%) in estimated monthly PM2.5 concentrations from 2019 to 2020 for the periods from March 11-April 10 and April 11-May 10, respectively. The March time period corresponded to the most stringent COVID-19 related restrictions in this region. Significant decreases in PM2.5 were also reported by state monitoring sites during March (p < 0.001 compared to the previous 5-year average). While we observed decreases in PM2.5 concentrations across the valley in 2020, it is important to note that the PM2.5 concentrations did not improve equally in all locations. We observed the greatest reductions at lower elevation, more urbanized areas, likely because of the already low levels of PM2.5 at the higher elevation, more residential areas, which were generally below 2 μg/m3 in both 2019 and 2020. Although many of measurements during March and April were near or below the estimated detection limit of the low-cost PM sensors and the federal equivalent measurements, every low-cost sensor (51) showed a reduction in PM2.5 concentration in March of 2020 compared to 2019. These results suggest that the air quality improvement seen after March 11, 2020 is due to quarantine measures reducing traffic and decreasing pollutant emissions in the region.

Ambient fine particulate matter in Latin American cities: Levels, population exposure, and associated urban factors

BackgroundExposure to particulate matter (PM2.5) is a major risk factor for morbidity and mortality. Yet few studies have examined patterns of population exposure and investigated the predictors of PM2.5 across the rapidly growing cities in lower- and middle-income countries. ObjectivesCharacterize PM2.5 levels, describe patterns of population exposure, and investigate urban factors as predictors of PM2.5 levels. MethodsWe used data from the Salud Urbana en America Latina/Urban Health in Latin America (SALURBAL) study, a multi-country assessment of the determinants of urban health in Latin America, to characterize PM2.5 levels in 366 cities comprising over 100,000 residents using satellite-derived estimates. Factors related to urban form and transportation were explored. ResultsWe found that about 172 million or 58% of the population studied lived in areas with air pollution levels above the defined WHO-AQG of 10 μg/m3 annual average. We also found that larger cities, cities with higher GDP, higher motorization rate and higher congestion tended to have higher PM2.5. In contrast cities with higher population density had lower levels of PM2.5. In addition, at the sub-city level, higher intersection density was associated with higher PM2.5 and more green space was associated with lower PM2.5. When all exposures were examined adjusted for each other, higher city per capita GDP and higher sub-city intersection density remained associated with higher PM2.5 levels, while higher city population density remained associated with lower levels. The presence of mass transit was also associated with lower PM2.5 after adjustment. The motorization rate also remained associated with PM2.5 and its inclusion attenuated the effect of population density. DiscussionThese results show that PM2.5 exposures remain a major health risk in Latin American cities and suggest that urban planning and transportation policies could have a major impact on ambient levels.

The profile of fine particulate matter (PM2.5) using Beta Attenuator Monitor (BAM) in Addis Ababa, Ethiopia

The profile of fine particulate matter (PM2.5) using Beta Attenuator Monitor (BAM) in AddisAbaba, EthiopiaAuthor List: Abera Kumie1, Alemayehu Worku1, Zelalem Tazu1, Worku Tefera1, Getu Boja1, MollaMekashaw1, Solomon Teferra2, Jonathan Patz3, Jonathan Samet4, Kiros Berhane51Addis Ababa University (Ethiopia); 2Air Quality Management District (USA), 3University of Wisconsin–Madison (USA), 4University of Colorado (USA), 5University of Southern California (USA).AbstractBackground: Ambient air pollution is currently a global agenda. The concentration of fine particulatematter (PM2.5) is one of the indicators for the air quality monitoring. The monitoring of air qualityindicators is very limited in African countries including Ethiopia.Objectives: The objective of this study is to describe the current level of air pollution in Addis Ababa anddetermine its patterns over time, days of the week and seasons.Material and Methods: MetOne® Beta Attenuator Monitor (BAM) instrument for measuring the hourlyaverage level of PM2.5 was installed at one of the referral hospital in Addis Ababa, capital city ofEthiopia. A two-year data (April 1st, 2017 to March 31st, 2019) was generated to describe the profile ofPM for this study. The raw data from the monitor was periodically downloaded and cleaned usingstandard operative procedures. R-software was used for data management and analysis.Results: The average PM2.5 concentration over the two years was found to be 43.3µg/m3. There wereunusual peaks of PM concentration that greatly exceeded the daily averages. There were differences inlevels of PM2.5 across the days of the week and week days. Sunday’s had on average low PM2.5concentration relative to other days. We also observed variations in levels of PM2.5 across the Ethiopianseasons. Generally, wet seasons exhibited high levels of PM2.5 while low levels of PM2.5 were during thedry season. These findings highlighted the need of interventions related to public transportation and urbanplanning in controlling the ambient air pollution.Keywords: Ambient air pollution, PM2.5, Status, Beta Attenuator Monitor, variation

Outdoor air pollution and terminal duct lobular involution of the normal breast

BackgroundExposure to certain outdoor air pollutants may be associated with a higher risk of breast cancer, though potential underlying mechanisms are poorly understood. We examined whether outdoor air pollution was associated with involution of terminal duct lobular units (TDLUs), the histologic site where most cancers arise and an intermediate marker of breast cancer risk.MethodsPathologist-enumerated TDLUs were assessed in H&E (hematoxylin and eosin)-stained breast tissue sections from 1904 US women ages 18–75 who donated to the Susan G. Komen Tissue Bank (2009–2012). The 2009 annual fine particulate matter < 2.5 μm in diameter (PM2.5) total mass (μg/m3) at each woman’s residential address was estimated from the Environmental Protection Agency’s Downscaler Model combining Community Multiscale Air Quality (CMAQ) System modeling with air quality monitoring data. We secondarily considered CMAQ-modeled components of PM2.5 and gaseous pollutants. We used K-means clustering to identify groups of individuals with similar levels of PM2.5 components, selecting groups via cluster stability analysis. Relative rates (RRs) and 95% confidence intervals (95% CIs) for the association between air pollutants and TDLU counts were estimated from a zero-inflated negative binomial regression model adjusted for potential confounders.ResultsPM2.5 total mass was associated with higher TDLU counts among all women (interquartile range (IQR) increase, RR = 1.06; 95% CI: 1.01–1.11). This association was evident among both premenopausal and postmenopausal women (premenopausal RR = 1.05, 95% CI: 1.00–1.11; postmenopausal RR = 1.11, 95% CI: 1.00–1.23). We identified 3 groups corresponding to clusters that varied geographically and roughly represented high, medium, and low levels of PM2.5 components relative to population mean levels. Compared to the cluster with low levels, the clusters with both high (RR = 1.74; 95% CI: 1.08–2.80) and medium (RR = 1.82; 95% CI: 1.13–2.93) levels were associated with higher TDLU counts; although not significantly different, the magnitude of the associations was stronger among postmenopausal women.ConclusionsHigher PM2.5 levels were associated with reduced TDLU involution as measured by TDLU counts. Air pollution exposure may influence the histologic characteristics of normal tissue which could in turn affect breast cancer risk.

The role of local meteorology on ambient particulate and gaseous species at an urban site of western India

Dependencies of ambient concentrations of PM2.5, PM10, CO and O3 on meteorology in Udaipur of India have been discussed based on the measurements from April 2011 to March 2012. PM2.5 and CO were highest in winter due to lower PBL depth and calm winds while PM10 and O3 were highest in the pre-monsoon season due to convective activities. Lower wind regimes (<2 km hr−1), highest PM2.5 and CO were 47 ± 20 μg m−3 and 441 ± 170 μg m−3 indicating the accumulation of pollutants while lower levels of PM2.5 (36 ± 16 μg m−3) and CO (317 ± 114 μg m−3) indicated the impact of dispersion at higher wind regimes. A positive slope of ∆PM10/∆WS = 4.4 μg m−3/km hr−1 indicates predominance of natural sources of coarser particles. Higher concentrations of PM2.5 and CO with correlation coefficient (0.42 and 0.52) under high RH and low temperature during winter season indicate the strong temperature inversion. Negative correlation between PM10 and RH (r = −0.70) during monsoon indicates the role of rainfall in wetting the soil reducing its aerosolization and particle washout. Rainfall was significant for PM10 (~53% reduction) than those observed for PM2.5 and CO. Overall, this study suggests the strong influence of meteorology in the variation of air pollutants.

Effects of long-term exposure to CO and PM2.5 on microalbuminuria in type 2 diabetes

No study has examined the effects of air pollutants on albuminuria in type 2 diabetes. Therefore, the present study investigated this association. This follow-up study enrolled 812 patients with type 2 diabetes between 2003 and 2012. The urinary albumin-to-creatinine ratio (ACR) was recorded annually. Exposure to the air pollutants CO, NO2, O3, SO2, and PM2.5 was interpolated from 72 air-quality monitoring stations to residences by using the kriging method. The association between air pollutants and ACR increase was assessed using mixed-effect model with random intercepts for 36 clinics. The study objects (mean age: 55.4 years) were followed for 3 or more years (average period: 5.4 years). ACR increase was found to be positively associated with the male sex, baseline hemoglobin A1c, and exposure to CO and PM2.5, and negatively associated with waist circumference through multiple linear regression. Annually urine albumin/creatinine ratio increase was estimated by the final model, Patients exposed to higher levels of CO (e.g., third quartile, 1025 ppb) and lower levels of CO (e.g., first quartile, 850 ppb) had an annual ACR increase of 3.73 and 3.54 mg/g, respectively. Patients exposed to higher levels of PM2.5 (e.g., third quartile, 38.8 μg/M3) and lower levels of PM2.5 (e.g., first quartile, 27.7 μg/M3) had an annual ACR increase of 3.96 and 3.17 mg/g, respectively. Exposure to high CO and PM2.5 levels increased albuminuria in type 2 diabetes.

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

The previous studies estimated the association between PM2.5 (particulate matter with aerodynamic diameter less than or equal to 2.5μm) 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. PM2.5 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 PM2.5 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 PM2.5 exposures, especially during their first trimester of pregnancy even when the ambient PM2.5 concentration is relatively low. More relevant health policy should be carried out to prevent hazard effect of air pollutants.

Cancer incidence attributable to air pollution in Alberta in 2012.

The International Agency for Research on Cancer has classified outdoor air pollution (fine particulate matter [PM2.5]) as a Group 1 lung carcinogen in humans. We aimed to estimate the proportion of lung cancer cases attributable to PM2.5 exposure in Alberta in 2012. Annual average concentrations of PM2.5 in 2011 for 22 communities across Alberta were extracted from the Clean Air Strategic Alliance Data Warehouse and were population-weighted across the province. Using 7.5 µg/m3 and 3.18 µg/m3 as the annual average theoretical minimum risk concentrations of PM2.5, we estimated the proportion of the population above this cut-off to determine the population attributable risk of lung cancer due to PM2.5 exposure. The mean population-weighted concentration of PM2.5 for Alberta in 2011 was 10.03 µg/m3. We estimated relative risks of 1.02 and 1.06 for theoretical minimum risk PM2.5 concentration thresholds of 7.5 µg/m3 and 3.18 µg/m3, respectively. About 1.87%-5.69% of incident lung cancer cases in Alberta were estimated to be attributable to PM2.5 exposure. Our estimate of attributable burden is low compared to that reported in studies in other areas of the world owing to the relatively low levels of PM2.5 recorded in Alberta. Reducing PM2.5 emissions in Alberta should continue to be a priority to help decrease the burden of lung cancer in the population.

A case study using remote sensing data to compare biophysical properties of a forest and an urban area in Northern Alabama, USA

ABSTRACTThe quantification of major biophysical features of forest and urban areas is important for assessing ecological service from land use change and is necessary for sustainable regional planning. This study compares biophysical indicators related to local climate, air quality, and hydrology using remote sensing and derived data at a representative forest area to a nearby urban area located in Huntsville, Alabama. Results indicate that (a) there was a higher albedo, a lower average air temperature, and 10% more annual precipitation in the forest area; the assumed air conditioner working time was about 7 days more per year in the urban area; (b) there was better air quality in the forest area based on lower levels of PM2.5, PM10, and SO2; and (c) there was a higher latent heat, more runoff per year (both aboveground and belowground runoff), and a greater soil water content at the forest area. Although Huntsville is a small city, there were some profound biophysical differences in this urban area compared to the nearby forest. These results are useful for analyzing sustainability, planning regional resources (e.g., energy, air, and water), and estimating ecological services from forests.

Urban, traffic- related particles and lung tumors in urethane treated mice

OBJECTIVE:The present study was designed to evaluate the effects of urban, traffic-related, fine particulate matter (PM2.5) on mice lung tumorigenesis under controlled exposure conditions.METHODS:Four groups of female Swiss mice were treated with intraperitonial injections of urethane and saline solution. Urethane was used to start the carcinogenesis process. The animals were housed in two chambers receiving filtered and polluted air. In the polluted air chamber, pollutant levels were low. After two months of exposure, the animals were euthanized and lung tumoral nodules were counted.RESULTS:Saline-treated animals showed no nodules. Urethane-treated animals showed 2.0+2.0 and 4.0+3.0 nodules respectively, in the filtered and non-filtered chambers (p = 0.02), thus showing experimental evidence of increased carcinogenic-induced lung cancer with increasing PM2.5 exposure.CONCLUSION:Our data support the concept that low levels of PM2.5 may increase the risk of developing lung tumors.