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Type 2 diabetes causes early mortality worldwide. Air pollution's relationship with T2DM has been studied. The association between them is unclear because of inconsistent outcomes. Studies on this topic have been published since 2019, but not thoroughly evaluated. We conducted a systematic review and meta-analysis using relevant data. The study protocol was registered in PROSPIRO and conducted according to MOOSE guidelines. In total, 4510 manuscripts were found. After screening, 46 studies were assessed using the OHAT tool. This meta-analysis evaluated fine particles with T2DM using OR and HR effect estimates. Evaluation of publication bias was conducted by Egger's test, Begg's test, and funnel plot analysis. A sensitivity analysis was conducted to evaluate the influence of several studies on the total estimations. Results show a significant association between PM2.5 and PM10 exposure and T2DM. Long-term exposure to fine air particles may increase the prevalence and incidence of T2DM. Fine air pollution increases the chance of developing T2DM mainly via systemic inflammation, oxidative stress, and endoplasmic reticulum stress.

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The relevance of atmospheric particulate matter (PM) to health and the environment is widely known. Long-term studies are necessary for understanding current and future trends in air quality management. This study aimed to assess the long-term PM concentration in the Magdalena department (Colombia). It focused on the following aspects: i) spatiotemporal patterns, ii) correlation with meteorology, iii) compliance with standards, iv) temporal trends over time, v) impact on health, and vi) impact of policy management. Fifteen stations from 2003 to 2021 were analyzed. Spearman-Rho and Mann-Kendall methods were used to correlate concentration with meteorology. The temporal and five-year moving trends were determined, and the trend magnitude was calculated using Teil-Sen. Acute respiratory infection odd ratios and risk of cancer associated with PM concentration were used to assess the impact on health. The study found that the maximum PM10 concentration was 194.5 µg/m3, and the minimum was 3 µg/m3. In all stations, a negative correlation was observed between PM10 and atmospheric water content, while the wind speed and temperature showed a positive correlation. The global trends indicated an increasing value, with five fluctuations in five-year moving trends, consistent with PM sources and socio-economic behavior. PM concentrations were found to comply with national standard; however, the results showed a potential impact on population health. The management regulation had a limited impact on increasing concentration. Considering that national regulations tend to converge towards WHO standards, the study area must create a management program to ensure compliance.

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One of the primary causes of urban atmospheric particulate matter, which is harmful to human health in addition to affecting air quality and atmospheric visibility, is road dust. This study used online monitoring equipment to examine the characteristics of road dust emissions, the effects of temperature, humidity, and wind speed on road dust, as well as the correlation between road and high-space particulate matter concentrations. A section of a real road in Jinhua City, South China, was chosen for the study. The findings demonstrate that the concentration of road dust particles has a very clear bimodal single-valley distribution throughout the day, peaking between 8:00 and 11:00 and 19:00 and 21:00 and troughing between 14:00 and 16:00. Throughout the year, there is a noticeable seasonal change in the concentration of road dust particles, with the highest concentration in the winter and the lowest in the summer. Simultaneously, it has been discovered that temperature and wind speed have the most effects on particle concentration. The concentration of road dust particles reduces with increasing temperature and wind speed. The particle concentrations of road particles and those from urban environmental monitoring stations have a strong correlation, although the trend in the former is not entirely consistent, and the changes in the former occur approximately 1 h after the changes in the latter.

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Accurate prediction of Particulate Matter (PM 10) levels, an indicator of natural pollutants such as those resulting from dust storms, is crucial for public health and environmental planning. This study aims to provide accurate forecasts of PM 10 over Morocco for five days. The Analog Ensemble (AnEn) and the Bias Correction (AnEnBc) techniques were employed to post-process PM 10 forecasts produced by the Copernicus Atmosphere Monitoring Service (CAMS) global atmospheric composition forecasts, using CAMS reanalysis data as a reference. The results show substantial prediction improvements: the Root Mean Square Error (RMSE) decreased from 63.83 µg/m 3 in the original forecasts to 44.73 µg/m 3 with AnEn and AnEnBc, while the Mean Absolute Error (MAE) reduced from 36.70 µg/m 3 to 24.30 µg/m 3. Additionally, the coefficient of determination (R 2) increased more than twofold from 29.11% to 65.18%, and the Pearson correlation coefficient increased from 0.61 to 0.82. This is the first use of this approach for Morocco and the Middle East and North Africa and has the potential for translation into early and more accurate warnings of PM 10 pollution events. The application of such approaches in environmental policies and public health decision making can minimize air pollution health impacts.

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Fine dust causes various disorders, including cardiovascular, neurological, renal, reproductive, motor, systemic, respiratory, and cancerous diseases. Therefore, it is essential to study functional materials to prevent these issues. This study investigated the beneficial effects of erucic acid against fine dust using methods such as miRNA profiling, quantitative PCR, flow cytometry, ELISA, and Alizarin O staining. Erucic acid effectively suppresses inflammation and upregulates osteogenic activators in fibroblasts exposed to fine dust. Additionally, erucic acid-induced exosomes (EIEs) strongly counteract the negative effects of fine dust on osteocytic differentiation and inflammation. Despite fine dust exposure, EIEs promoted osteocytic differentiation in adipose-derived stem cells (ASCs) and enhanced osteogenesis and phagocytosis in macrophages. The significant upregulation of RunX2 and BMP7 by EIEs indicates its strong role in osteocytic differentiation and protection against the effects of fine dust. EIEs also boosts immune activity and acts as an osteogenic trigger for macrophages. MicroRNA profiling revealed that EIEs dramatically upregulated miRNAs, including hsa-miRNA-1301-3p, hsa-miRNA-1908-5p, hsa-miRNA-423-5p, and hsa-miRNA-122-5p, which are associated with osteogenic differentiation and immunity. Therefore, EIEs show potential as biomaterials to prevent environment-borne diseases.

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In this contribution, we report the study of nuclear resonance magnetic spectroscopy techniques (1H-NMR, 13C-NMR, and 2D-NMR) efficiency in the characterisation of the functional composition of water-soluble organic compounds (WSOC) from atmospheric aerosols. The chosen site was our scientific and technical center of research (CRAPC) situated in Algerian Bou-Ismail city. where the concentrations of PM10 were found to be between 15.66 and 142.19 µg.m-3. As results, 1H-NMR analysis showed the coexistence of biological material and emissions from urban and biomass burning. The dominant source was identified by quantitative integration of each 1H NMR spectral region. By using the HSQC technique, many peaks are revealed in biogenic samples including biomass burning. On the other hand, the identification of the source of various organic compounds and their functional composition is possible through specific NMR spectra, which can also be used to adjust the surrounding organic aerosol sources.

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The article evaluates air pollution by particulate matter (PM) in indoor and outdoor air in one of the Polish health resorts, where children and adults with respiratory diseases are treated. The highest indoor PM concentrations were recorded during the winter season. Therefore, the maximum average daily concentration values in indoor air for the PM10, PM2.5, and PM1 fractions were 50, 42 and 23 µg/m3, respectively. In the case of outdoor air, the highest average daily concentrations of PM2.5 reached a value of 40 µg/m3. The analyses and backward trajectories of episodes of high PM concentrations showed the impact of supra-regional sources and the influx of pollutants from North Africa on the variability of PM concentrations. The correlation between selected meteorological parameters and PM concentrations shows the relationship between PM concentrations and wind speed. For example, the correlation coefficients between PM1(I) and PM1(O) concentrations and wind speed were - 0.8 and - 0.7 respectively. These factors determined episodes of high PM concentrations during winter periods in the outdoor air, which were then transferred to the indoor air. Elevated concentrations in indoor air during summer were also influenced by chimney/gravity ventilation and the appearance of reverse chimney effect.

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Prenatal and early life air pollution exposure has been linked with several adverse health outcomes. However, the mechanisms underlying these relationships are not yet fully understood. Therefore, this study utilizes fecal metabolomics to determine if pre- and postnatal exposure to ambient air pollutants (i.e., PM10, PM2.5, and NO2) is associated with the fecal metabolome in the first 2 years of life in a Latino cohort from Southern California. The aims of this analysis were to estimate associations between (1) prenatal air pollution exposure with fecal metabolic features at 1-month of age, (2) prior month postnatal air pollution exposure with fecal metabolites from 1-month to 2 years of age, and (3) how postnatal air pollution exposure impacts the change over time of fecal metabolites in the first 2 years of life. Prenatal exposure to air pollutants was associated with several Level-1 metabolites, including those involved in vitamin B6 and tyrosine metabolism. Prior month air pollution exposure in the postnatal period was associated with Level-1 metabolites involved in histidine metabolism. Lastly, we found that pre- and postnatal ambient air pollution exposure was associated with changes in metabolic features involved in metabolic pathways including amino acid metabolism, histidine metabolism, and fatty acid metabolism.

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Air pollution exposure has been linked to detrimental health outcomes. While cross-sectional studies have demonstrated socioeconomic disparities in air pollution exposure, longitudinal evidence on these disparities remains limited. The current study investigates trends in residential air pollution exposure across socioeconomic groups in the Netherlands from 2014 to 2019. Our dataset includes over 12.5 million individuals, aged 18 years and above, who resided in the Netherlands between 2014 and 2019, using Statistics Netherlands data. The address-level air pollution concentrations were estimated by dispersion models of the National Institute of Public Health and the Environment. We linked the exposure estimations of particulate matter < 10 or <2.5 µm (PM10, PM2.5) and nitrogen dioxide (NO2) to household-level socioeconomic data. In highly urbanized areas, individuals from both the lowest and highest socioeconomic groups were exposed to higher air pollution concentrations. Individuals from the lowest socioeconomic group were disproportionally located in highly urbanized and more polluted areas. The air pollution concentrations of PM10, PM2.5, and NO2 decreased between 2014 and 2019 for all the socioeconomic groups. The decrease in the annual average air pollution concentrations was the strongest for the lowest socioeconomic group, although differences in exposure between the socioeconomic groups remain. Further research is needed to define the health and equity implications.

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Accumulating observational studies have linked particulate air pollutants to neurodegenerative diseases (NDDs). However, the causal links and the direction of their associations remain unclear. Therefore, we adopted a two-sample Mendelian randomization (TSMR) design using the GWAS-based genetic instruments of particulate air pollutants (PM2.5 and PM10) from the UK Biobank to explore their causal influence on four common neurodegenerative diseases. Estimates of causative relationships were generated by the Inverse variance weighted (IVW) method with multiple sensitive analyses. The heterogeneity and pleiotropy tests were additionally performed to verify whether our findings were robust. Genetically predicted PM2.5 and PM10 could elevate the occurrence of AD (odds ratio [OR] = 2.22, 95 % confidence interval [CI] 1.53-3.22, PIVW = 2.85×10-5, PFalsediscovery rate[FDR]= 2.85×10-4 and OR = 2.41, 95 % CI: 1.26-4.60, PIVW = 0.008, PFDR=0.039, respectively). The results were robust in sensitive analysis. However, no evidence of causality was found for other NDDs. Our present study suggests that PM2.5 and PM10 have a detrimental effect on AD, which indicates that improving air quality to prevent AD may have pivotal public health implications.

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Exposure to particulate matter and endotoxin can lead to acute and chronic respiratory problems in workers. A study was conducted to quantify particulate matter with an aerodynamic diameter of ≤10 µm (PM10) and endotoxin levels in rice mills in northeast India. Sixty-four PM10 dust samples were collected from eight rice mills at two locations: the feeding and polishing sections for two varieties of paddy: Ranjit and Hali. Endotoxin exposures were analyzed using the Limulus Amoebocyte Lysate (LAL) gel clot test. The results showed that the geometric mean of the 8-h time-weighted average (TWA) PM10 dust concentration and endotoxin level in the rice mills were 10.69 mg/m³ and 2.2 EU/m³, respectively. Dust and endotoxin exposure were higher in the feeding section than in the polishing section. Endotoxin exposure in the feeding section during the milling of the Hali variety of paddy was 56.0 % higher than the milling of the Ranjit variety. Additionally, endotoxin exposure during the milling of the Hali variety was 24.2 % higher than that of the milling of the Ranjit variety in the polishing section. The dust exposure in the rice mills was 194.5 % higher than the standards set up by the United States Environmental Protection Agency. However, the exposure to endotoxin in rice mills was approximately 40.10 times below the recommended limit of 90 EU/m3.

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BACKGROUND: Cardiovascular disease (CVD) is the leading cause of death worldwide, with air pollution posing significant risks to cardiovascular health. The effect of air quality on heart failure (HF) readmission in acute myocardial infarction (AMI) patients is unclear.The aim of this study was to evaluate the role of a single measure of air pollution exposure collected on the day of first hospitalization. METHODS: We retrospectively analyzed data from 12,857 acute coronary syndrome (ACS) patients (January 2015-March 2023). After multiple screenings, 4023 AMI patients were included. The air pollution data is updated by the automatic monitoring data of the national urban air quality monitoring stations in real time and synchronized to the China Environmental Monitoring Station. Cox proportional hazards regression assessed the impact of air quality indicators on admission and outcomes in 4013 AMI patients. A decision tree model identified the most susceptible groups. RESULTS: After adjusting for confounders, NO2 (HR 1.009, 95% CI 1.004-1.015, P = 0.00066) and PM10 (HR 1.006, 95% CI 1.002-1.011, P = 0.00751) increased the risk of HF readmission in ST-segment elevation myocardial infarction (STEMI) patients. No significant effect was observed in non-STEMI (NSTEMI) patients (P > 0.05). STEMI patients had a 2.8-fold higher risk of HF readmission with NO2 > 13 µg/m3 (HR 2.857, 95% CI 1.439-5.670, P = 0.00269) and a 1.65-fold higher risk with PM10 > 55 µg/m3 (HR 1.654, 95% CI 1.124-2.434, P = 0.01064). CONCLUSION: NO2 and PM10 are linked to increased HF readmission risk in STEMI patients, particularly when NO2 exceeds 13 µg/m3 and PM10 exceeds 55 µg/m3. Younger, less symptomatic male STEMI patients with fewer underlying conditions are more vulnerable to these pollutants.

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Air pollution is affected by the atmospheric dynamics. This study aims to determine that air pollution concentration values in Istanbul increased significantly and reached peak values due to atmospheric blocking between the 30th of December 2022 and the 5th of January 2023. In this study, hourly pollutant data was obtained from 16 air quality monitoring stations (AQMS), the exact reanalysis data was extracted from ERA5 database, and inversion levels and meteorological and synoptic analyses were used to determine the effects of atmospheric blocking on air pollution. Also, cloud base heights and vertical visibility measurements were taken with a ceilometer. Statistical calculations and data visualizations were performed using the R and Grads program. Omega-type blocking, which started in Istanbul on December 30, 2022, had a significant impact on the 1st and 2nd of January 2023, and PM10 and PM2.5 concentration values reached their peak values at 572.8 and 254.20 µg/m3, respectively. In addition, it was found that the average concentration values in the examined period in almost all stations were higher than the averages for January and February. As a result, air quality in Istanbul was determined as "poor" between these calendar dates. It was found that the blocking did not affect the ozone (µg/m3) concentration. It was also found that the concentrations of particulate matter (PM) 10 µm or less in diameter (PM10) and PM 2.5 µm or less in diameter (PM2.5) were increased by the blocking effect in the Istanbul area. Finally, according to the data obtained using the ceilometer, cloud base heights decreased to 30 m and vertical visibility to 10 m.

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A comprehensive chemical characterization (water-soluble ions, organic and elemental carbon, water- and methanol-soluble organic carbon, levoglucosan, and major and trace metals) of PM10 samples collected in a rural area located in the southeast of the Iberian Peninsula was performed. Additionally, the oxidative potential of the samples, used as an indicator of aerosol toxicity, was determined by the ascorbic acid (OPAA) and dithiothreitol (OPDTT) assays. The average concentration of PM10 during the study period, spanning from late winter to early spring, was 20.2 ± 10.8 µg m-3. Nitrate, carbonate and calcium (accounting for 20% of the average PM10 mass concentration) and organic matter (with a contribution of 28%) were the main chemical components of PM10. Average concentrations of traffic tracers such as elemental carbon, copper and zinc (0.31 µg m-3, 3 ng m-3, and 9 ng m-3, respectively) were low compared with those obtained at an urban site in the same region, due to the almost total absence of traffic in the surrounding of the sampling site. Regarding levoglucosan and K+, which can be considered as tracers of biomass burning, their concentrations (0.12 µg m-3 and 55 ng m-3, respectively) were in the lower range of values reported for other rural areas in Europe, suggesting a moderate contribution form this source to PM10 levels. The results of the Pearson's correlation analysis showed that volume-normalised OPAA and OPDTT levels (average values of 0.11 and 0.32 nmol min-1 m-3, respectively) were sensitive to different PM10 chemical components. Whereas OPAA was not strongly correlated with any of the species measured, good correlation coefficients of OPDTT with water-soluble organic carbon (r = 0.81) and K+ (r = 0.73) were obtained, which points to biomass burning as an important driver of the DTT activity.

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The PM2.5 and PM10 particles were characterized in terms of morphology (size and shape) and surface elemental composition at two different (traffic and industrial) locations in urban region of India and further linked to different morphological defining parameters. The overall PM2.5 and PM10 showed significant daily variability indicating higher PM10 as compared to PM2.5. PM2.5/PM10 ratio was found to be 0.58 ± 0.10 indicating the abundance of PM2.5. Soot aggregates, aluminosilicates, and brochosomes particles were classified based on morphology, aspect ratio (AR), and surface elemental composition of single particles. The linear regression analysis indicates the significant correlation between area equivalent (Daeq) and feret diameter (Dfd) (R2 0.86-0.98). Higher aspect ratio (1.48 ± 0.87-1.43 ± 0.50) was noted at traffic site as compared to industrial site (1.33 ± 0.58-1.29 ± 0.30), while circularity showed the opposite trend. Fractal dimension (Df) of soot aggregates estimated by the soot parameters method (SPM) were found to be 1.70, 1.72, and 1.88, mainly attributed to vehicular emissions, biomass, and industrial emission/coal burning, respectively. This further inferred that freshly emitted soot particles exhibited lacey in nature with spherical shape (Df 1.70) at traffic site, while at industrial location, they were different with compact shapes (Df 1.88) due to particle aging processes. This study inferred the synoptic changes in mass, chemical characteristics, and morphology of aerosol particles which provide the new insights into individual atmospheric particle and their dynamic nature.

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Exposure to particulate matter (PM10) can induce respiratory diseases that are closely related to bronchial hyperresponsiveness. However, the involved mechanism remains to be fully elucidated. This study aimed to demonstrate the effects of PM10 on the acetylcholine muscarinic 3 receptor (CHRM3) expression and the role of the ERK1/2 pathway in rat bronchial smooth muscle. A whole-body PM10 exposure system was used to stimulate bronchial hyperresponsiveness in rats for 2 and 4 months, accompanied by MEK1/2 inhibitor U0126 injection. The whole-body plethysmography system and myography were used to detect the pulmonary and bronchoconstrictor function, respectively. The mRNA and protein levels were determined by Western blotting, qPCR, and immunofluorescence. Enzyme-linked immunosorbent assay was used to detect the inflammatory cytokines. Compared with the filtered air group, 4 months of PM10 exposure significantly increased CHRM3-mediated pulmonary function and bronchial constriction, elevated CHRM3 mRNA and protein expression levels on bronchial smooth muscle, then induced bronchial hyperreactivity. Additionally, 4 months of PM10 exposure caused an increase in ERK1/2 phosphorylation and increased the secretion of inflammatory factors in bronchoalveolar lavage fluid. Treatment with the MEK1/2 inhibitor, U0126 inhibited the PM10 exposure-induced phosphorylation of the ERK1/2 pathway, thereby reducing the PM10 exposure-induced upregulation of CHRM3 in bronchial smooth muscle and CHRM3-mediated bronchoconstriction. U0126 could rescue PM10 exposure-induced pathological changes in the bronchus. In conclusion, PM10 exposure can induce bronchial hyperresponsiveness in rats by upregulating CHRM3, and the ERK1/2 pathway may be involved in this process. These findings could reveal a potential therapeutic target for air pollution induced respiratory diseases.

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In this study, we have examined the air quality within a revitalized, post-industrial urban area in Lódz, Poland. The use of Dron technology with mobile measurement equipment allowed for accurate assessment of air quality (particulate matter and gaseous pollutants) and factors influencing air quality (wind speed and direction) on a local scale in an area of 0.18 km2 and altitudes from 2 to 50 m. The results show that the revitalization carried out in the Lodz special economic zone area contributed to eliminate internal air pollution emitters through the use of ecological and effective heat sources. The exceedances permissible concentration values were local, and concerned mainly the higher measurement zones of the troposphere (more than 30 m above ground level). In the case of gaseous pollutants, higher wind speeds were associated with a decrease in the concentration of SO2 and an increase in H2S concentration. In both cases, the wind contributed to the occurrence of local areas of accumulation of these gaseous pollutants in the spaces between buildings or wooded areas.

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The contents of water-soluble major's ions (MSA, Cl-, NO3-, SO42-, Na+, NH4+, K+, Mg2+, and Ca2+) in the PM10 particle fraction were investigated thanks to detailed measurements of the main chemical constituents of PM10 in remote coastal areas in Bou-Ismail; in the South-West of the Mediterranean Sea (Algeria), during a 2-year period; from July 2011 to August 2013, under the framework of the ChArMEx project (Chemistry-Aerosol Mediterranean Experiment, http://charmex.lsce.ipsl.fr ). The total water-soluble ion concentrations in PM10 at the Bou-Ismail measurement station varied from 3.3 µg/m3 (July 2011) to 49.6 µg/m3 (March 2012). The annual mean mass concentrations of ions in the PM10 particulate fraction were Cl- > Na+ > SO42- > Mg2+ > NO3- > Ca2+ > K+ > NH4+ > Oxalate. The change in potassium nss-K + concentrations in PM10 over the course of a year reveals that biomass burning (BB) has an effect on three separate seasons: the beginning of winter (February and March), the end of summer (August), and the autumn (September and October). The origin periods of biomass burning BB identified employing the mapping of hotspots and fires during periods of August and September 2011, 2012, and 2013 underlined the important fires in the surrounding areas of the Mediterranean Sea (Sardinia Islands from Italy, Corsica from France).

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This study investigates river dust episodes along the Choshui and Kaoping Rivers in Taiwan, focusing on their spatiotemporal distribution and correlation with hydrometeorological factors (temperature, precipitation, relative humidity, and wind speed). Using the Improved Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (ICEEMDAN) algorithm and time-dependent intrinsic correlation (TDIC) analysis, we identified significant annual and diurnal correlations between PM10 concentrations and these factors. The analysis revealed that wind speed at Lunbei station had a positive annual correlation with PM10, while other factors exhibited significant negative correlations. Seasonal variations in PM10 correlations with temperature, relative humidity, and wind speed were observed, aligning with the prevailing seasons of river dust episodes. Wind motion analysis highlighted diurnal associations with land-sea breezes and annual correlations with the winter monsoon. Specifically, the Choshui River's dust events coincided with the northeast monsoon, whereas the Kaoping River's events occurred during the northwest and southwest monsoons. The study also uncovered that downstream stations (Lunbei and Daliao) were more prone to severe dust events than upstream stations (Douliu and Pingtung). These findings enhance our understanding of the dynamics and environmental impacts of river dust episodes, providing valuable insights for air quality management and health risk mitigation.

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Current evidence suggests that airborne pollutants have a detrimental effect on fetal growth through the emergence of small for gestational age (SGA) or term low birth weight (TLBW). The study's objective was to critically evaluate the available literature on the association between environmental pollution and the incidence of SGA or TLBW occurrence. A comprehensive literature search was conducted across Pubmed/MEDLINE, Web of Science, Cochrane Library, EMBASE, and Google Scholar using predefined inclusion and exclusion criteria. The methodology adhered to the PRISMA guidelines. The systematic review protocol was registered in PROSPERO with ID number: CRD42022329624. As a result, 69 selected papers described the influence of environmental pollutants on SGA and TLBW occurrence with an Odds Ratios (ORs) of 1.138 for particulate matter ≤ 10 µm (PM10), 1.338 for particulate matter ≤ 2.5 µm (PM2.5), 1.173 for ozone (O3), 1.287 for sulfur dioxide (SO2), and 1.226 for carbon monoxide (CO). All eight studies analyzed validated that exposure to volatile organic compounds (VOCs) is a risk factor for SGA or TLBW. Pregnant women in the high-risk group of SGA occurrence, i.e., those living in urban areas or close to sources of pollution, are at an increased risk of complications. Understanding the exact exposure time of pregnant women could help improve prenatal care and timely intervention for fetuses with SGA. Nevertheless, the pervasive air pollution underscored in our findings suggests a pressing need for adaptive measures in everyday life to mitigate worldwide environmental pollution.