Increase In PM10 Concentration Research Articles

Impact of Exposure to Environmental Particulate Matter on the Onset of Giant Cell Arteritis.

The aim of this study was to investigate the association between exposure to particulate matter with an aerodynamic diameter ≤10 μm (PM10) and the development of giant cell arteritis (GCA) and its ischemic complications. This was case-crossover study on consecutive patients who received a diagnosis of GCA in three hospitals in northern Italy between 2013 and 2021. The PM10 hourly and daily average concentrations, collected in the Italian monitoring network and archived by Istituto Superiore per la Protezione e la Ricerca Ambientale, were determined using European reference. We used a Bayesian hierarchical model to determine patients' daily exposures to them. We employed conditional logistic regression to estimate the effect of exposure on GCA symptoms onset or ischemic complications. We included 232 patients. A positive association was observed between exposure to PM10 and GCA risk, with an incremental odd of 27.1% (95% confidence interval 5.8-52.6) for every 10-μg/m3 increase in PM10 concentration within a 60-day period. We did not find any significant association for shorter periods or with ischemic complications. Subgroup analysis found a significantly higher incremental risk at a 60-day lag for patients ≥70 years old. Comparing patients who were chronically exposed to high PM10 levels (26.9 ± 13.8 μg/m3) to those who were not (11.9 ± 7.9 μg/m3) revealed that only in the former group was there an association between GCA onset and increased PM10 levels in the preceding 60 days. Exposure to environmental PM10 in the preceding 60 days seems to be associated with an increased risk of developing GCA, especially in older individuals with prolonged exposure to high levels of air pollution.

Long-range transport impact of a severe dust storm over the Yangtze River Basin region and its modeling sensitivity to dust emission scheme

Dust storms frequently occur in the spring over East Asia, affecting southern Mongolia and northeast China. An exceptionally powerful dust storm occurred in East Asia from March 14th to March 18th, 2021. To investigate the ability of climate models to simulate severe dust storms, we employed the Weather Research Forecast model coupled with chemistry (WRF-Chem) with Goddard Chemistry Aerosol Radiation and Transport (GOCART), SHAO and KOK dust emission schemes to simulate the evolution of this event and to characterize dust aerosols long-range transport. Results showed that this storm was caused by a Mongolian cyclone depicted at 850 hPa with a cold front, which swept dust aerosols southeastward across southern Mongolia to northeast China. Model evaluation with satellite-retrieved Aerosol Optical Depth (AOD) and observational PM10 concentrations revealed that the SHAO dust emission scheme performed better in simulating spatial and temporal distribution of AOD over the Gobi Desert (GD) but overestimated them over Taklimakan Desert (TD). In contrast, the GOCART dust emission scheme underestimated AOD over most areas except the Taklimakan Desert; the KOK dust emission scheme overestimated them over both TD and GD. Overall, the SHAO dust emission scheme had good performance in simulating the surface PM10 concentrations over the Yangtze River Basin (YRB) and depicted an increase in PM10 concentrations, which denoted the transport of dust aerosols over YRB. As a better description of the physical process of dust emission flux over the eastern region of the Gobi Desert, the SHAO dust emission scheme depicted well the spatial and temporal evolution of dust plume episodes, especially over northeast China and YRB. The significant differences in dust emission fluxes between the three dust emission schemes were attributed to the sensitivity of threshold friction velocity and erodibility factor. Thereunto, the SHAO dust emission scheme incorporated well soil particle size distribution and threshold velocity to produce the dust emission flux, which allowed higher dust emission flux over the eastern GD and under strong southwesterly transported dust aerosols to East Central China's region of North China Plain (NCP) and YRB. This study will help further the simulation of extreme dust events more accurately and the exploration of climate change's effect on dust events over East Asia.

Dynamic characteristics of wind and PM10 over desert-oasis transition zone during dust events

Dust storm events generate aeolian dust as one of the main aerosols in the atmosphere, with significant impacts on air quality and human health. Further study is needed on the dust emission processes in source regions and the impacts of underlying surfaces with forested windbreaks on the transport of wind flow and PM10 to develop more accurate dust concentration forecasts. Synchronized monitoring of wind velocity and the PM10 concentration was performed along the dust transport pathway crossing the desert and oasis in Minqin County, Gansu Province, China. Results indicated that the PM10 concentration and flux responded quickly to wind velocity in the desert with both having obvious power function relationships. The addition of supra-regional transport of PM10 particles led to an abnormal increase in PM10 concentration and flux. Between desert and oasis, a positive linear function relationship of PM10 concentrations and quadratic function relationship of PM10 flux exist. The dynamic transfer process of PM10 in the oasis roughly depends on the condition of PM10 in the desert area. Forested windbreaks significantly reduced the mean wind velocity and PM10 flux by 65.02% and 67.63%, respectively. However, forests had a weak influence on the mean PM10 concentration. The effects of forested windbreaks on the PM10 concentration are related to the windward wind velocity. With increasing velocity, difference of PM10 concentration from desert to oasis turned from negative to positive, while the positive effects of the forested windbreak system can be enhanced by an increase in the windward wind velocity.

Arctic/North Atlantic atmospheric variability causes Severe PM10 events in South Korea

Severe PM10 (particulate matter with a diameter of <10 μm) events in South Korea are known to be caused by stable atmospheric circulation conditions related to high-pressure anomalies in the upper troposphere. However, research on why these atmospheric circulation patterns occur is unknown. In this study, we propose new large-scale teleconnection pathways that cause severe PM10 events during the midwinter in South Korea. This study investigated instances of extremely high (EH)-PM10 in South Korea during mid-winter and examined the corresponding atmospheric teleconnection patterns to identify the factors contributing to EH-PM10 events. K-means clustering analysis revealed that EH-PM10 instances were associated with two large-scale teleconnection patterns. Cluster 1 exhibited a wave train pattern originating in the North Atlantic that developed from Eurasia to the Korean Peninsula. Cluster 2 was associated with a wave-like teleconnection pattern from the Barents-Kara Sea to the Korean Peninsula. The Rossby waves, triggered by the North Atlantic and the Arctic, propagated and weakened the surface pressure system. This led to a high-pressure anomaly over the Korean Peninsula, reducing atmospheric ventilation and causing a rapid increase in PM10 concentration within a few days. Furthermore, an experiment involving a linear baroclinic model established that atmospheric forcing in upstream regions has the potential to induce large-scale atmospheric teleconnection patterns, resulting in EH-PM10 cases in South Korea. These findings emphasize the ventilation effect and transport of PM10 concentrations modulated by two large-scale teleconnection patterns originating from the Arctic and North Atlantic, leading to EH-PM10 events in South Korea. Understanding this combined phenomenon may assist in the implementation of emission reduction measures based on the results of short-term forecasts of severe PM10 events.

Variability of airborne microbiome at different urban sites across seasons: a case study in Rome

Introduction: Biogenic fraction of airborne PM10 dominated by bacteria and fungi, has been recognized as serious environmental and human health issues in cities.Methods: In the present study, we combined a high-throughput amplicon sequencing of the bacterial 16S rRNA gene and the fungal internal transcribed spacer (ITS) region, with elemental analysis of airborne particulate matter (PM10) to investigate the community compositions and structures of PM10-associated bacteria and fungi across four different seasons in three urban sites of Rome with differential pollution rate.Results: In this study, а clear seasonal shift of bacterial and fungal community structure driven by PM10 mass concentrations and environmental factors, such as temperature and precipitations, has been identified. In addition, the seasonal impact of local sources and long-range transported air masses on the community structures of the microbes has been also postulated. Our data revealed that the lack of precipitation and the subsequent resuspension of dust produced by vehicular traffic might contribute to the maximum abundance of soil-associated microbes in winter and summer. However, the increase of PM10 concentrations favoured also by climatic conditions, domestic heating and dust advection event from African desert further shaped the community structure of winter. Across three seasons, the pollutant removal-hydrogen oxidation bacteria and the opportunist-human pathogenic fungi progressively increased with pollution levels, in the sequence from green to residential and/or polluted area close to the traffic roads, with highest fraction during winter.Discussion: Hence, our results highlight a close interrelationship between pollution, climatic factors and abundance of certain bacterial and fungal predicted functional groups also with potential implications for human health.

Effects of stubble burning and firecrackers on the air quality of Delhi.

Every year at the onset of winter season (October-November), crop residue/parali/stubble burning starts in Punjab and Haryana, leading to heavy air pollution in Delhi, and adversely affecting human and environmental health. During this time, the combination of unfavourable meteorological conditions, additional emissions from stubble burning, and firework activities in this area causes the air quality to furtherdeteriorate. In this study, we have attempted to understand the influence of parali and firecracker incidents on air pollutants' variability over Delhi during the last three years (2020 to 2022). For this purpose, daily average particulate matter and gaseous pollutants data were fetched from the Central Pollution Control Board (CPCB), and daily total fire counts and fire radiative power (FRP) data were retrieved from NASA's Fire Information for Resource Management System (FIRMS). A bigger area of severe burning is suggested by higher FRP values and higher fire counts in the middle of November in all the years considered. Three years satellite-based FIRMS data over Punjab and Haryana show the highest number of active fire counts in 2021 (n = 80,505) followed by 2020 (n = 75,428), and 2022 (n = 49,194). More than 90% parali burning incidents were observed in Punjab state only despite the considerable variability in numbers among the years. The significant effect of parali burning was seen on pollutant concentration variability. As the number of fire count increases or decreases in Punjab and Haryana, there is a corresponding increase or decrease in the particulate matter concentration with a time lag of few days (1 to 2days). The trend in backward air mass trajectories suggests that the variable response time of pollutants' concentration is due to local and distant sources with different air mass speeds. Our estimates suggest that stubble burning contributes 50-75% increment in PM2.5 and 40 to 45% increase in PM10 concentration between October and November. A good positive correlation between PM2.5, PM10, NOX, and CO and fire counts (up to 0.8) suggests a strong influence of stubble burning on air quality over Delhi. Furthermore, the firecracker activities significantly increase the concentration of particulate matter with ~100% increment in PM2.5 and ~55% increment in PM10 mass concentrations for a relatively shorter period (1 to 2days).

Intense Desert Dust Event in the Northern Adriatic (March 2020); Insights From the Numerical Model Application and Chemical Characterization Results

AbstractThe uncharacteristically extreme outbreak of particulate matter took place over the Balkan region from 27 to 30 March 2020. Observations at air quality stations in Croatia recorded hourly PM10 concentrations up to 412 μgm−3. The meteorological analysis shows that the increase in PM10 concentrations was primarily due to the advection of dust from the deserts east of the Caspian Sea. The anticyclone north of Croatia and the cyclone over Anatolia formed a strong pressure gradient driving transport from the east. Both back trajectories and satellite products pointed to the dry Aral Sea as the main source of dust. A dust plume influenced the PM10 increase observed in Croatia, starting at the easternmost air quality stations. The modeling study shows that the vertical extent of the dust plume was up to ∼2 km. However, the chemical and morphological (scanning electron microscope analysis) composition of PM10 at the sites in the northeastern Adriatic Sea showed mainly the presence of Saharan dust. Prior to the advection of the Asian dust, the transport of Saharan dust, driven by Sharav cyclone, was observed in the PM10 values at several stations in the Adriatic Sea and on the Croatian mainland on 26 March 2020. Modeling results showed that the Saharan dust transport occurred at altitudes below ∼8 km. The mixing of the Asian and Saharan dust plumes over the Balkans was favored by the subsidence due to anticyclonic high‐pressure conditions and is the most likely explanation for the observed PM chemical and morphological results.

Ambient air pollution and emergency department visits and hospitalisation for cardiac arrest: a population-based case–crossover study in Reykjavik, Iceland

ObjectivesTo assess the association between traffic-related ambient air pollution and emergency hospital visits for cardiac arrest.DesignCase–crossover design was used with a lag time to 4 days.SettingThe Reykjavik capital area and...

The impact of monthly air pollution exposure and its interaction with individual factors: Insight from a large cohort study of comprehensive hospitalizations in Guangzhou area.

Although the association between short-term air pollution exposure and certain hospitalizations has been well documented, evidence on the effect of longer-term (e. g., monthly) air pollution on a comprehensive set of outcomes is still limited. A total of 68,416 people in South China were enrolled and followed up during 2019-2020. Monthly air pollution level was estimated using a validated ordinary Kriging method and assigned to individuals. Time-dependent Cox models were developed to estimate the relationship between monthly PM10 and O3 exposures and the all-cause and cause-specific hospitalizations after adjusting for confounders. The interaction between air pollution and individual factors was also investigated. Overall, each 10 μg/m3 increase in PM10 concentration was associated with a 3.1% (95%CI: 1.3%-4.9%) increment in the risk of all-cause hospitalization. The estimate was even greater following O3 exposure (6.8%, 5.5%-8.2%). Furthermore, each 10 μg/m3 increase in PM10 was associated with a 2.3%-9.1% elevation in all the cause-specific hospitalizations except for those related to respiratory and digestive diseases. The same increment in O3 was relevant to a 4.7%-22.8% elevation in the risk except for respiratory diseases. Additionally, the older individuals tended to be more vulnerable to PM10 exposure (P interaction: 0.002), while the alcohol abused and those with an abnormal BMI were more vulnerable to the impact of O3 (P interaction: 0.052 and 0.011). However, the heavy smokers were less vulnerable to O3 exposure (P interaction: 0.032). We provide comprehensive evidence on the hospitalization hazard of monthly PM10 and O3 exposure and their interaction with individual factors.

An analysis of particulate pollution using urban aerosol pollution island intensity over Delhi, India.

The accent of the present study is determination of Urban Aerosol Pollution Island (UAPI) intensity and spatial variability in particulate matter concentration (PM10 and PM2.5) over Delhi. For analysis, the hourly concentration dataset of PM2.5 and PM10 from January 2019 to December 2020 was obtained from ten air quality monitoring stations of Delhi. Additionally, UAPI Index has been calculated to assess the intensity of particulate pollution. The daily, monthly, and annual variations in the trends of PM10, PM2.5, and UAPI index along with related meteorological parameters have been analyzed. Particulate pollution peaked majorly during two seasons, i.e., summer and winter. The highest concentration of PM10 was observed to be 426.77 µg/m3 while that of PM2.5 was observed to be 301.91 µg/m3 in January 2019 for traffic-affected regions. During winters, higher PM2.5 concentration was observed which can be ascribed to increased local emissions and enhanced secondary particle formations. While the increase in PM10 concentrations led to an increment in pollution episodes during summers over most of the sites in Delhi. The UAPI index was found to be declining in 2020 over traffic affected regions (77.92 and 27.22 for 2019 and 2020, respectively) as well as in the background regions (64.91 and 19.80 for 2019 and 2020, respectively) of Delhi. Low traffic intensity and reduced pollutant emission could have been responsible for the reduction of UAPI intensity in the year 2020. The result indicates that lockdown implemented to control the COVID-19 outbreak led to an unexpected decrease in the PM10 pollution over Delhi.

Air quality affects house prices — Analysis based on RD of the Huai River policy

Based on the quasi-natural experiment of the Huai River policy in China, this research attempts to demonstrate the causal relationship between the Huai River policy, air quality and house prices, as well as the underlying logical mechanism. This paper's findings suggest that the Huai River policy leads to higher concentrations of air pollutants such as PM10, SO2and PM2.5 in cities north of the Huai River than in the south, and lower real estate prices in cities north of the Huai River than in the south. Secondly, air quality significantly affects house prices.For every 1 unit increase in PM10 concentration, house prices will decrease by 0.24%; for every 1 unit increase in PM2.5 concentration, house prices will decrease by 0.37%; and for every 1 unit increase in SO2 concentration, house prices will decrease by 0.24%. Finally, by tracing the potential mechanisms, the results SO2 show that the Huai River policy reduces the air quality in the northern region, and then has a restraining effect on the northern housing price level, and there is no alternative path for the Huai River policy to affect house prices.

Estimation of Atmospheric PM10 Concentration in China Using an Interpretable Deep Learning Model and Top‐of‐the‐Atmosphere Reflectance Data From China’s New Generation Geostationary Meteorological Satellite, FY‐4A

AbstractThe rapid urbanization in China and the long‐range transport dust (LRTD) from arid and semi‐arid areas has resulted in an increase of PM10 concentration. In this study, an interpretable deep learning model [deep forest (DF)] with FY‐4A top‐of‐the‐atmosphere reflectance (TOAR) data were used to obtain the hourly PM10 in China. The optimal hourly average R2 of 10‐fold cross validation can achieve 0.85 (13:00 Beijing time); The R2 (RMSE, μg/m³) of the daily, monthly, and annual averages were 0.82 (24.16), 0.97 (6.53), and 0.99 (2.30), respectively. Using TOAR data, the DF model performed better than other machine learning models. The feature importance of the TOAR‐PM10 model showed that TOAR and meteorological elements both contributed significantly to the model. In spring, the PM10 in northern China was greater than that in southern China, which may be related to the LRTD. Excluding the dust weather periods, the areas with high PM10 values in China were mainly in cities and their suburbs, where were correlated with human activities. During a dust weather process, LRTD increased PM10 in northern China by 80.4%. During a mixture haze and dust weather process, the PM10 increased by 130.2% in northern China, of which LRTD led to an increase of 73.7%. The sources (from the Taklimakan Desert in China) and transmission paths of these two LRTD processes were similar. The contribution of LRTD to PM10 was related to dust intensity and meteorological conditions. The results showed that LRTD and local pollution to PM10 was both important in haze periods.

Maternal air pollution exposure during the first trimester of pregnancy and markers of inflammation and endothelial dysfunction

BackgroundMaternal exposure to air pollutants has been associated with pregnancy complications and adverse birth outcomes. Endothelial dysfunction, an imbalance in vascular function, during pregnancy is considered a key element in the development of pre-eclampsia. Environmental exposure to particulate matter (PM) during the first trimester of pregnancy might increase maternal inflammatory status thus affecting fetal growth, possibly leading to preterm delivery. ObjectivesThe purpose of the study was to evaluate possible effects of PM10 and PM2.5 exposure on fetal growth in healthy pregnant women at the end of the first trimester of pregnancy by investigating the relationship between circulating biomarkers of inflammation (IL-6), early systemic prothrombotic effects (CRP, plasma fibrinogen, PAI-1) and endothelial dysfunction (sICAM-1 and sVCAM-1). Methods295 pregnant women were recruited. Individual PM exposure was assigned to each subject by calculating the mean of PM10 and PM2.5 daily values observed during the 30, 60, and 90 days preceding enrolment (long-term) and single lag days back to fourteen days (short-term), and circulating plasma biomarkers were determined. ResultsFor long-term exposure, we observed an increase in sVCAM-1 and a decrease of PAI-1 levels for each 10 μg/m3 increase in PM10 concentration. Decreases in IL-6 and CRP levels were associated with each 10 μg/m3 PM2.5 increase. For short-term exposure, the levels of sVCAM-1 and PAI-1 were found to be associated with PM10 exposure, whereas fibrinogen levels were associated with PM2.5 exposure. Maternal plasmatic fibrinogen levels were negatively associated with the crown-rump length (p-value = 0.008). DiscussionThe present study showed that both long- and short-term exposures to PM are associated with changes in circulating levels of biomarkers in pregnant women reflecting systemic inflammation and endothelial dysfunction/activation. Our findings support the hypothesis that inflammation and endothelial dysfunction might have a central role in modulating the detrimental effects of air pollution exposure during pregnancy.

Case Study of the Evidence of PM1&amp; PM2.5 Contribution on PM10 from Podul De Piatra– Iasi City

Abstract The importance of air quality monitoring has been strongly demonstrated in numerous scientific studies. This study, carried out in an intense circular intersection, brings additional arguments that the monitoring of the fine particles like PM1 and PM2.5 that influence in more than 80% the concentration of PM10 particles must be measured at several points. Few were the cases [approx. 20%] in which the increase of PM10 concentrations is given by particles with diameters from 2.5 to 10 μm, most likely caused by the re-suspension of dust particles. Grimm Aerosol Technik Germany and SC INOESY SRL conducted a campaign for monitoring the air quality [PM1, PM2.5, PM10] in Iasi, Stone Bridge area, from 8 to 22 February 2018. The monitoring point was located close (150 m) to the APMIS-01 station of the National Environmental Protection Agency.

Association between long-term exposure to air pollution and immune-mediated diseases: a population-based cohort study

ObjectiveEnvironmental air pollution has been associated with disruption of the immune system at a molecular level. The primary aim of the present study was to describe the association between long-term...

Association between atmospheric particulate matter and emergency room visits for cerebrovascular disease in Beijing, China.

The association between atmospheric particulate matter and emergency room visits for cerebrovascular disease were evaluated in Beijing. A generalized additive model was used to evaluate the associations between particulate matter and cerebrovascular disease, based on the daily data of meteorological elements, PM concentrations, and emergency room (ER) visits for cerebrovascular disease in Beijing from 2009 to 2012. Long-term trends and the effects of holidays, the day of the week, and confounding factors were controlled to determine the lag effect at 0-6days. Single- and double-pollutant models were employed for different age and sex groups. The effect of PM2.5 concentration on the number of daily ER visits for cerebrovascular disease was much stronger than that of PM10 concentration. PM2.5 and PM10 had maximum RR values of 1.096 and 1.054 at lag 6 for patients aged 61-75years. For each inter-quartile range (IQR) increase in PM10 concentration, the maximum RR values for the total, males, females, aged 15-60years, aged 61-75years, and aged > 75years were 1.024, 1.044, 1.043, 1.038, 1.054, and 1.032, respectively. For each IQR increase in PM2.5 concentration, the maximum RR values for the total, males, females, aged 15-60years, aged 61-75years, and aged > 75years were 1.038, 1.064, 1.076, 1.054, 1.096, and 1.049, respectively. The RR values of the double-pollutant models were lower than those of the single-pollutant models. This study showed that the effects of PM pollution on cerebrovascular disease were different among different gender and age groups, and aged 61-75years were mostly sensitive to particulate matters. The effects of PM2.5 on cerebrovascular disease were stronger than those of PM10. Our results can provide scientific evidence for the local government to take effective measures to improve air quality and the health of residents. The online version contains supplementary material available at 10.1007/s40201-021-00776-w.

Dust storm simulation over the Sahara Desert (Moroccan and Mauritanian regions) using HYSPLIT

AbstractSaharan dust storms are major events that occur normally in the summer and affect the air quality in various regions of the world. In particular, Saharan regions in Morocco and Mauritania actively contribute to dust storms. The Saharan outbreak that took place between 14 and 19 of June 2020 was one of the most severe Saharan dust storms in recent years. This paper investigates the PM10 emissions and concentrations during the 4 days of the dust storm in the region of Western Sahara of Morocco and Mauritania and the transport of the PM10 from the area of study to the Caribbean Sea and the Gulf of Mexico using Hybrid Single‐Particle Lagrangian Integrated Trajectory Model (HYSPLIT) software with PM10 emission model and cluster analysis. We also analyse the effect of the transported PM10 particles on the concentration level in the Southern parts of the United States and the Martinique islands. The results showed that the average PM10 concentration below the altitude of 100 m during the dust storm was higher than 100 μg/m3 in most of the regions such as Dakhla in Morocco, Nouakchott, Adrar and Tiris Zemmour in Mauritania. This is confirmed by Aerosol Optical Depth (AOD) values between 0.7 and 1 retrieved by MODIS‐Aqua for those areas. Furthermore, PM10 particles transported across the Atlantic Ocean affected the concentrations observed in the Caribbean Basin, where hourly PM10 reached 372 μg/m3 and the dust top layer was found between 4 and 4.5 km above ground level. In addition, HYSPLIT cluster analysis results revealed several PM10 particle source areas in Western Sahara such as Bir Anzerane in Morocco, Nouakchott and Tichit in Mauritania that contributed to the increase of PM10 concentrations to an Unhealthy level in the Texas and Florida States in the United States.

INWERSJA TEMPERATURY POWIETRZA W TATRACH W LATACH 1995–2020

This paper concerns the characteristics of the multi-annual, seasonal and daily variability of thermal inversion in the Tatra Mountains in 1995–2020. The analysis was performed on the basis of hourly measurements taken at the Institute of Meteorology and Water Management National Research Institute (IMGW-PIB) station in Kasprowy Wierch and Zakopane. The types of atmosphere circulation were determined found when the inversion was most frequent. The concentration of PM10 during the inversion and its intensity were analyzed and indicated that the number of inversion cases was growing. The analysis confirmed that inversions were most frequent in the cold season in the evening hours during anticyclonic circulation. Strong inversions occurred in the cold season. Winter inversions were associated with an increase in PM10 concentration.

Years of life lost due to premature deaths associated with air pollution: an ecological time-series study.

Exposure to air pollutants is associated with hospital admissions due to cardiovascular diseases and premature deaths. To estimate years of life lost (YLL) due to premature deaths and their financial costs. Ecological time-series study carried out in São José dos Campos, Brazil, in 2016. Data on deaths among residents of this city in 2016 were assessed to estimate the financial cost of premature deaths associated with air pollution. The diagnoses studied were ischemic heart disease, congestive heart failure and cerebrovascular disease, according to YLL. The fractions attributable to deaths associated with air pollutant exposure and to each potential year of life lost were calculated using negative binomial regression with lags of 0-7 days between exposure and outcome. Nitrogen dioxide, particulate matter (PM10) and ozone concentrations were included in the model and adjusted for temperature, humidity and seasonality. Exposure to particulate matter was significant at lag 3 days. There were 2177 hospitalizations over the study period, with 201 deaths (9.2%). Premature deaths led to 2035.69 years of life lost. A 10 μg/m3 increase in PM10 concentrations was correlated with 8.0% of the hospitalizations, which corresponded to 152.67 YLL (81.67 for males and 71.00 for females). The cost generated was approximately US$ 9.1 million in 2016. In this first study conducted in a medium-sized Brazilian city, using the YLL methodology, we identified an excess expense attributable to air pollution.

Clinical outcomes associated with long-term exposure to airborne particulate pollution in kidney transplant recipients

BackgroundResearchers have yet to investigate the specific association between 10-μm particulate matter (PM10) levels and the risk of graft failure, kidney disease, or the functional decline of transplanted kidneys, in kidney transplant recipients (KTRs). Furthermore, we know very little about the association between PM10 levels and the development of allograft rejection in transplanted kidneys. Identification of air pollution as a potential contributor to kidney disease could help reduce future disease burden, stimulate policy discussions on the importance of reducing air pollution with respect to health and disease, and increase public awareness of the hazards of air pollution. We aimed to evaluate the relationship of PM10 with the risk of graft failure, mortality, and decline of graft function in KTRs.MethodsAir pollutant data were obtained from the Korean National Institute of Environmental Research. We then investigated potential associations between these data and the clinical outcomes of 1532 KTRs who underwent kidney transplantation in a tertiary hospital between 2001 and 2015. Survival models were used to evaluate the association between PM10 concentrations and the risk of death-censored graft failure (DCGF), all-cause mortality, and biopsy-proven rejection (BPR), over a median follow-up period of 6.31 years.ResultsThe annual mean PM10 exposure after kidney transplantation was 27.1 ± 8.0 μg/m3. Based on 1-year baseline exposure, 1 μg/m3 increase in PM10 concentration was associated with an increased risk of DCGF (hazard ratio (HR): 1.049; 95% confidence interval (CI): 1.014–1.084) and BPR (HR: 1.053; 95% CI: 1.042–1.063). Fully adjusted models showed that all-cause mortality was significantly associated with 1-year average PM10 concentrations (HR, 1.09; 95% CI, 1.043 to 1.140).ConclusionsLong-term PM10 exposure is significantly associated with BPR, DCGF, and all-cause mortality in KTRs.