Protective Effects and Mechanisms of Melatonin on Stress Myocardial Injury in Rats.

ABSTRACT: Prolonged and intense stress can exceed the body's normal self-regulation and limited compensatory and repair capacity, resulting in pathological damage to the body. In this study, we established a rat stress myocardial injury (SMI) model to explore the protective effect of melatonin (MLT) on SMI and its possible mechanisms of action. Adult female Sprague Dawley (SD) rats were randomly divided into 5 groups: blank control group (NC), SMI group, MLT low-dose group, MLT medium-dose group, and MLT high-dose group, and 10 rats in each group were used to establish a SMI model by the water immersion restraint method. We observed the changes in body weight and tail vein glucose of each group. Serum levels of corticosterone (Cort), creatine kinase isoenzyme (CK-MB), and Troponin Ⅰ (Tn-Ⅰ) and activity of lactic acid dehydrogenase were measured by ELISA. Transcriptome sequencing was used to find differentially expressed genes in the control and model groups, and the results were verified by real-time fluorescence quantitative polymerase chain reaction (RT-qPCR). HE staining was used to visualize the pathological changes in the heart tissue of each group, and Western blot was used to study the differences in protein expression in the cardiomyocytes of each group to further corroborate the results. The body weight growth rate of rats in the SMI group was significantly lower than that of the NC group ( P < 0.01), and the body weight growth rate of rats in the MLT high-dose group was significantly higher than that of the SMI group ( P < 0.05) with no significant difference compared with the NC group rats. The mean blood glucose of rats in the SMI group was significantly higher compared with the NC group ( P < 0.001), while the mean blood glucose of rats in the MLT administration groups was dose-dependently reduced compared with the SMI group. By RNA-seq and bioinformatics tools such as KEGG and Gene ontology, we found that the circadian clock-related genes Ciart , Arnt1 , Per1 , and Dbp were significantly downregulated in the SMI group during water immersion stress, and differentially expressed genes were enriched in the p38MAPK signaling pathway and p53 signaling pathway. Moreover, genes related to inflammation and apoptosis were differentially expressed. ELISA results showed that Cort, CK-MB, and Tn-Ⅰ levels were significantly higher in the SMI group compared with the NC group ( P < 0.01) and melatonin reduced the levels of Cort, CK-MB, and Tn-Ⅰ and decreased lactic acid dehydrogenase activity in rat serum. HE staining results showed that melatonin could attenuate stress-generated myocardial injury. Western blot showed that melatonin reduced the expression of p38MAPK, p53, Bax, and caspase-3 and increased the expression of Bcl-2 protein in rat heart. Melatonin can inhibit myocardial injury caused by water immersion, and its mechanism of action may be related to the regulation of the expression of circadian clock genes such as Ciart , Arnt1 , Per1 , and Dbp ; the inhibition of the expression of proapoptotic proteins such as p38MAPK, p53, Bax, and caspase-3; and the increase of the expression of Bcl-2 antiapoptotic protein.

CALIOP retrieval of droplet effective radius accounting for cloud vertical homogeneity.

Monitoring cloud droplet effective radius (re) is of great significance for studying aerosol-cloud interactions (ACI). Passive satellite retrieval, e.g., MODIS (Moderate Resolution Imaging Spectroradiometer), requires sunlight. This requirement prompted developing re retrieval using active sensors, e.g., CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization). Given the highest sensitivity of vertically homogeneous clouds to aerosols that feed to cloud base, here CALIOP profile measurements were used for the first time to quantify cloud vertical homogeneity and estimate cloud re during both day and night. Comparison using simultaneous Aqua-MODIS measurements demonstrates that CALIOP retrieval has the highest accuracy for vertically homogeneous clouds, with R2 (MAE, RMSE) of 0.72 (1.75 µm, 2.25 µm), while the accuracy is lowest for non-homogeneous clouds, with R2 (MAE, RMSE) of 0.60 (2.90 µm, 3.70 µm). The improved re retrieval in vertically homogeneous clouds provides a basis for possible breakthrough insights in ACI by CALIOP since re in such clouds reflects most directly aerosol effects on cloud properties. Global day-night maps of cloud vertical homogeneity and respective re are presented.

Symptomatic intracranial hemorrhage in patients with admission hyperglycemia and diabetes after mechanical thrombectomy: A systematic review and meta-analysis.

OBJECTIVES: Symptomatic intracranial hemorrhage (sICH) is a severe complication of revascularization therapy. We aimed to investigate the association of admission hyperglycemia and sICH after mechanical thrombectomy in patients with acute ischemic stroke. METHODS: We systematically searched PubMed, EMBASE and Cochrane Library to identify studies that reported incidence of sICH in patients with admission hyperglycemia and normoglycemia, or with and without a history of diabetes, or glucose level in patients with sICH and non-sICH from inception to December 10, 2019. The estimate effects were pooled by random-effects model. RESULTS: Twelve eligible studies were included with 4892 patients enrolled. The risk of sICH was significantly higher in admission hyperglycemia patients than that in normoglycemia (OR 2.93, 95% CI 1.34-6.42, p = 0.007; adjusted OR1.95, 95% CI 1.22-3.13; p = 0.006). The admission glucose level was significantly higher in sICH patients than that in non-sICH with a mean difference of 37.49 (95% CI 3.03-71.94, p = 0.03). The risk of sICH increased with elevating glucose level (adjusted OR 1.06, 95% CI 1.01-1.11; p = 0.02). The risk of sICH was not significantly increased in patients with a history of diabetes than that of those without (OR 1.74, 95% CI 1.00-3.03, p = 0.05; adjusted OR 2.26, 95% CI 0.97-5.28; p = 0.06). CONCLUSIONS: In patients of acute ischemic stroke treated with mechanical thrombectomy, the risk of sICH was associated with admission hyperglycemia but possibly not with a history of diabetes.

Absorption mechanism of oxymatrine in cultured Madin-Darby canine kidney cell monolayers.

Context Oxymatrine (OMT) is beneficial to human health by exerting various biological effects. Objective To investigate the absorption mechanism of OMT and discover absorption enhancers using Madin-Darby canine kidney (MDCK) cell monolayers. Materials and methods Concentration effects on the transport of OMT were measured in the range of 1.0 × 10(-5)-1.0 × 10(-3) M in 2 h. Then, the effect of time, direction, temperature and pH on the transport of OMT at 10(-4) M was studied. Moreover, Papp of OMT was determined in the absence/presence of cyclosporine and surfactants at 100 µM to further confirm the relative transport mechanism. Results The Papp AP→BL ranged from (3.040 ± 0.23) × 10(-6) to (3.697 ± 0.19) × 10(-6 )cm/s as the concentration varied from 10(-5) to 10(-3) M. OMT showed similar Papp at 4 and 37 °C (p > 0.05). Increasing the apical pH 7.4 and 8.0 resulted in Papp versus pH 5.0 (p < 0.01). Furthermore, in the presence of cyclosporine and surfactants including sodium citrate, sodium dodecyl sulphate (SDS) and deoxysodium cholate, Papp was (0.318 ± 0.033) × 10(-5), (0.464 ± 0.048) × 10(-5), (0.897 ± 0.115) × 10(-5) and (1.341 ± 0.122) × 10(-5 )cm/s, respectively. In the presence of surfactants, Papp significantly increased up to 1.5-4.3-fold (p < 0.05). Discussion and conclusion OMT transport across MDCK cell monolayers was by passive diffusion. Sodium citrate, SDS and deoxysodium cholate serve as excellent absorption enhancers which are useful for the related research improving the oral bioavailability of OMT.

[Absolute bioavailability of caffeic acid in rats and its intestinal absorption properties].

OBJECTIVE: To investigate the absolute bioavailability of caffeic acid in rats and its intestinal absorption properties. METHOD: The absolute bioavailability (Fabs) of caffeic acid was obtained after iv (2 mg x kg(-1)) or ig (10 mg x kg(-1)) administration to rats. The intestinal absorption of caffeic acid was explored by the recirculating vascularly perfused rat intestinal preparation. Caco-2 cell model was applied to measure the permeability of caffeic acid from apical to basolateral said (A-B) and from basolateral to apical said (B-A). RESULT: A two-compartment pharmacokinetic model was best to describe the pharmacokinetics of caffeic acid following iv or ig administration. The Fabs of caffeic acid was 14. 7% , and its intestinal absorption was 12.4%. The values of Papp A-->B and Papp B-->A of caffeic acid were retained stable while its concentration was changed. The efflux ratio values in this study surveyed were above 2.0, and suggesting caffeic acid was active transport. CONCLUSION: Caffeic acid was shown to have poor permeability across the Caco-2 cells, low intestinal absorption and low oral bioavailability in rats.

Spatio-temporal association mining of intercity PM2.5 pollution: Hubei Province in China as an example.

The complex interaction between emissions, meteorology, and atmospheric chemistry makes accurate predictions of particulate pollution difficult. Advanced data mining techniques can reveal potential laws, providing new possibilities for understanding the evolution and causes of air pollution. Based on the Granger method and block modeling analysis, this paper explored the intercity spillover effects of hourly PM2.5 in Hubei Province, China, to determine the specific role (i.e., overflow, limited overflow, bilateral, inflow, and limited inflow) of each city on regional pollution formation. Furthermore, a dynamic Apriori algorithm considering time-lag effects was used to mine the spatio-temporal associations of extreme PM2.5 pollution events among different cities. Results suggest that the northern and central cities with high-level PM2.5 concentration in Hubei have a significant spillover effect, whereas the eastern and southern cities generally play a role as the sink of pollutants. Based on the association rules of extreme PM2.5 pollution, four main pollutant transport channels were excavated and well matched with the trajectories extracted by the atmospheric model. This paper provides new insights for exploring the interaction of intercity particulate pollution, which is a supplement and cross-validation of the model results.

Diversity and function of mountain and polar supraglacial DNA viruses.

Mountain and polar glaciers cover 10% of the Earth's surface and are typically extreme environments that challenge life of all forms. Viruses are abundant and active in supraglacial ecosystems and play a crucial role in controlling the supraglacial microbial communities. However, our understanding of virus ecology on glacier surfaces and their potential impacts on downstream ecosystems remains limited. Here, we present the supraglacial virus genome (SgVG) catalog, a 15-fold expanded genomic inventory of 10,840 DNA-virus species from 38 mountain and polar glaciers, spanning habitats such as snow, ice, meltwater, and cryoconite. Supraglacial DNA-viruses were highly specific compared to viruses in other ecosystems yet exhibited low public health risks. Supraglacial viral communities were primarily constrained by habitat, with cryoconite displaying the highest viral activity levels. We observed a prevalence of lytic viruses in all habitats, especially in cryoconite, but a high level of lysogenic viruses in snow and ice. Additionally, we found that supraglacial viruses could be linked to ∼83% of obtained prokaryotic phyla/classes and possessed the genetic potential to promote metabolism and increase cold adaptation, cell mobility, and phenolic carbon use of hosts in hostile environmental conditions using diverse auxiliary metabolic genes. Our results provide the first systematic characterization of the diversity, function, and public health risks evaluation of mountain and polar supraglacial DNA viruses. This understanding of glacial viruses is crucial for function assessments and ecological modeling of glacier ecosystems, especially for the Tibetan Plateau's Mountain glaciers, which support ∼20% of the human populations on Earth.

Midpalatal Suture CBCT Image Quantitive Characteristics Analysis Based on Machine Learning Algorithm Construction and Optimization.

BACKGROUND: Midpalatal suture maturation and ossification status is the basis for appraising maxillary transverse developmental status. METHODS: We established a midpalatal suture cone-beam computed tomography (CBCT) normalized database of the growth population, including 1006 CBCT files from 690 participants younger than 24 years old. The midpalatal suture region of interest (ROI) labeling was completed by two experienced clinical experts. The CBCT image fusion algorithm and image texture feature analysis algorithm were constructed and optimized. The age range prediction convolutional neural network (CNN) was conducted and tested. RESULTS: The midpalatal suture fusion images contain complete semantic information for appraising midpalatal suture maturation and ossification status during the fast growth and development period. Correlation and homogeneity are the two texture features with the strongest relevance to chronological age. The overall performance of the age range prediction CNN model is satisfactory, especially in the 4 to 10 years range and the 17 to 23 years range, while for the 13 to 14 years range, the model performance is compromised. CONCLUSIONS: The image fusion algorithm can help show the overall perspective of the midpalatal suture in one fused image effectively. Furthermore, clinical decisions for maxillary transverse deficiency should be appraised by midpalatal suture image features directly rather than by age, especially in the 13 to 14 years range.

The Efficacy of Needle-Warming Moxibustion Combined with Hyperbaric Oxygen Therapy for Ischemic Stroke and Its Effect on Neurological Function.

OBJECTIVE: To elucidate the therapeutic efficacy of needle-warming moxibustion (NWM) combined with hyperbaric oxygen therapy (HBOT) in the treatment of patients with ischemic stroke and its effect on neurological function. METHODS: One hundred patients with ischemic stroke admitted to the Xuzhou Medical University Affiliated Hospital of Lianyungang from January 2019 to July 2021 were enrolled. Among them, 45 patients treated with NWM were set as the control group, and the rest 55 patients treated by NWM combined with HBOT were included in the research group. The curative effect, neurological deficit score, activity of daily living (ADL), balance ability, and the levels of serum proinflammatory factors in both groups were observed and recorded. Of them, the neurological deficit of patients was evaluated by the National Institutes of Health Stroke Scale (NHISS), the ADL ability was determined by the Barthel index score, and the balance ability was assessed by the Berg balance scale. RESULTS: The total effective rate of the research group was higher than that of the control group. Better ADL and balance ability and milder neurologic impairment were determined in the research group compared with the control group. After treatment, the secretion levels of proinflammatory factors such as C-reactive protein (CRP), tumor necrosis factor-α (TNF-α), and interleukin-8 (IL-8) in the serum of patients in the research group were statistically lower than those before treatment and the control group. CONCLUSIONS: NWM combined with HBOT is effective in the treatment of patients with ischemic stroke, which can not only improve patients' neurological function, ADL, and balance ability but also inhibit serum inflammatory reactions.

Improving PM2.5 predictions during COVID-19 lockdown by assimilating multi-source observations and adjusting emissions.

The Coronavirus Disease 2019 (COVID-19) outbreak caused a suspension of almost all non-essential human activities, leading to a significant reduction of anthropogenic emissions. However, the emission inventory of the chemistry transport model cannot be updated in time, resulting in large uncertainty in PM2.5 predictions. This study adopted a three-dimensional variational approach to assimilate multi-source PM2.5 data from satellite and ground observations and jointly adjusted emissions to improve PM2.5 predictions of the WRF-Chem model. Experiments were conducted to verify the method over Hubei Province, China, during the COVID-19 epidemic from Jan 21st to Mar 20th, 2020. The results showed that PM2.5 predictions were improved at almost all the validation sites, and the benefit of data assimilation (DA) can last for 48 h. However, the benefits of DA diminished quickly with the increase of the forecast time. By adjusting emissions, the PM2.5 predictions showed a much slower error accumulation along forecast time. At 48Z, the RMSE still has an 8.85 µg/m3 (19.49%) improvement, suggesting the effectiveness of emissions adjustment based on the improved initial conditions via DA.

Coarse sea spray inhibits lightning.

The known effects of thermodynamics and aerosols can well explain the thunderstorm activity over land, but fail over oceans. Here, tracking the full lifecycle of tropical deep convective cloud clusters shows that adding fine aerosols significantly increases the lightning density for a given rainfall amount over both ocean and land. In contrast, adding coarse sea salt (dry radius > 1 µm), known as sea spray, weakens the cloud vigor and lightning by producing fewer but larger cloud drops, which accelerate warm rain at the expense of mixed-phase precipitation. Adding coarse sea spray can reduce the lightning by 90% regardless of fine aerosol loading. These findings reconcile long outstanding questions about the differences between continental and marine thunderstorms, and help to understand lightning and underlying aerosol-cloud-precipitation interaction mechanisms and their climatic effects.

Outcomes of mechanical thrombectomy with pre-intravenous thrombolysis: a systematic review and meta-analysis.

BACKGROUND AND PURPOSE: Whether pre-intravenous thrombolysis (IVT) provides any extra benefits to mechanical thrombectomy (MT) remains controversial. We conducted a systematic review and meta-analysis to compare MT with pre-IVT (IVT + MT) and MT without pre-IVT (MT) for acute ischemic stroke of large vessel occlusion. METHODS: We systematically searched PubMed, EMBASE and Cochrane Library to identify studies comparing outcomes between IVT + MT and MT from inception to Jan 24, 2019. Random effects mode was used to pool relative risk (RR) with confidence intervals (CI) to compare functional independence in terms of modified Rankin Scale (mRS) 0-2, favorable outcome (mRS 0-1) and mortality at three-months, symptomatic intracerebral hemorrhage, successful reperfusion, and complete reperfusion between the two treatments groups. RESULTS: We included 30 studies enrolling 8970 patients with acute ischemic stroke of large vessel occlusion. Compared with MT, IVT + MT significantly increased the rate of 3-month functional independence (RR 1.20, 95% CI 1.12-1.30; P < 0.0001) and favorable outcome (RR 1.28; 95% CI 1.16-1.40; P < 0.0001), increased the rate of successful reperfusion (RR 1.04,95% CI 1.01-1.08; P = 0.013) and complete reperfusion (RR 1.10; 95% CI 1.01-1.19; P = 0.024), reduced the rate of mortality (RR 0.74, 95% CI 0.67-0.82; P < 0.0001), without significantly increasing the rate of symptomatic intracerebral hemorrhage (RR 0.98,95% CI 0.82-1.17; P = 0.833). The results remained stable in sensitivity analyses and adjusting for publication bias. CONCLUSIONS: Pre-IVT provides extra benefits to MT on clinical and imaging outcomes without increasing symptomatic intracerebral hemorrhage in acute ischemic stroke of large vessel occlusion.

Unique T4-like phages in high-altitude lakes above 4500 m on the Tibetan Plateau.

Viruses are the most abundant biological entities in the biosphere; however, little is known about viral ecology in high altitude lakes. Here, we characterized viruses from 13 lakes, nine of which located ≥4500 m above sea level, on the Tibetan Plateau, the highest plateau on Earth. The abundance of virus-like particle (VLP) in Tibetan lakes ranged from 4.8 ± 0.2 × 105 VLPs mL-1 to 6.0 ± 0.2 × 107 VLPs mL-1 and the virus-to-bacterium ratio was in the lower range of values reported for other lakes. The viral population size was positively correlated with turbidity and negatively correlated with particulate organic carbon concentration. Highly diverse VLP morphologies, including large (~300 nm) morphotypes, were observed. Phylogenetic analysis of T4-like bacteriophages based on major capsid gene (g23) identified a novel viral group, which were detected in abundance in hyposaline and mesosaline Tibetan lakes. Adaptation to lake evolution, water source (glacier-fed or non-glacier-fed) and environmental conditions (e.g., salinity, phosphorus concentration and productivity) are likely responsible for the variation in T4-like myovirus community composition in contrasting Tibetan lakes. This first investigation of viruses in high-altitude alpine lakes above 4500 m could contribute to our understanding of viral ecology in global alpine lakes.

Estimating hourly full-coverage PM2.5 over China based on TOA reflectance data from the Fengyun-4A satellite.

It is challenging to retrieve hourly ground-level PM2.5 on a national scale in China due to the sparse site measurements and the limited coverage of Low Earth Orbit (LEO) satellite observations. The new geostationary meteorological satellite of China, Fengyun-4A (FY-4A), provides a unique opportunity to fill this gap. In this study, the Random Forest (RF) algorithm was applied to retrieve hourly PM2.5 of China directly from FY-4A Top-of-Atmosphere (TOA) reflectance data. A one-year PM2.5 retrieval shows a strong agreement to ground-based measurements, with the averaged R2 approaching 0.92, while the RMSE was only 10.0 µg/m³. An analysis of the regional differences of the performance and the dependency on satellite Viewing Zenith Angle (VZA) show that sparse measurements, high VZA, and solar zenith angle (SZA) are the primary sources of the uncertainty. The use of the FY-4A improved 17% spatial coverage compared to the Himawari-8-based PM2.5 retrievals, enabling full-coverage, hourly PM2.5 monitoring over China, and potentially could improve PM2.5 predictions from air quality models after data assimilation.

Estimation of hourly PM1 concentration in China and its application in population exposure analysis.

Particulate pollution is closely related to public health. PM1 (particles with an aerodynamic size not larger than 1 µm) is much more harmful than particles with larger sizes because it goes deeper into the body and hence arouses social concern. However, the sparse and unevenly distributed ground-based observations limit the understanding of spatio-temporal distributions of PM1 in China. In this study, hourly PM1 concentrations in central and eastern China were retrieved based on a random forest model using hourly aerosol optical depth (AOD) from Himawari-8, meteorological and geographic information as inputs. Here the spatiotemporal autocorrelation of PM1 was also considered in the model. Experimental results indicate that although the performance of the proposed model shows diurnal, seasonal and spatial variations, it is relatively better than others, with a determination coefficient (R2) of 0.83 calculated based on the 10-fold cross validation method. Geographical map implies that PM1 pollution level in Beijing-Tianjin-Hebei is much higher than in other regions, with the mean value of ∼55 µg/m3. Based on the exposure analysis, we found about 75% of the population lives in an environment with PM1 higher than 35 µg/m3 in the whole study area. The retrieval dataset in this study is of great significance for further exploring the impact of PM1 on public health.

Roles of Relative Humidity in Aerosol Pollution Aggravation over Central China during Wintertime.

Aerosol pollution elicits considerable public concern due to the adverse influence on air quality, climate change, and human health. Outside of emissions, haze formation is closely related to meteorological conditions, especially relative humidity (RH). Partly due to insufficient investigations on the aerosol hygroscopicity, the accuracy of pollution prediction in Central China is limited. In this study, taking Wuhan as a sample city, we investigated the response of aerosol pollution to RH during wintertime based on in-situ measurements. The results show that, aerosol pollution in Wuhan is dominated by PM2.5 (aerodynamic particle size not larger than 2.5 µm) on wet days (RH ≥ 60%), with the averaged mass fraction of 0.62 for PM10. Based on the RH dependence of aerosol light scattering (f (RH)), aerosol hygroscopicity was evaluated and shows the high dependence on the particle size distribution and chemical compositions. f (RH = 80%) in Wuhan was 2.18 (±0.73), which is comparable to that measured in the Pearl River Delta and Yangtze River Delta regions for urban aerosols, and generally greater than values in Beijing. Ammonium (NH4+), sulfate (SO42-), and nitrate (NO3-) were enhanced by approximately 2.5-, 2-, and 1.5-fold respectively under wet conditions, and the ammonia-rich conditions in wintertime efficiently promoted the formation of SO42- and NO3-, especially at high RH. These secondary ions play an important role in aggravating the pollution level and aerosol light scattering. This study has important implications for understanding the roles of RH in aerosol pollution aggravation over Central China, and the fitted equation between f (RH) and RH may be helpful for pollution forecasting in this region.

Stacking machine learning model for estimating hourly PM2.5 in China based on Himawari 8 aerosol optical depth data.

Aerosol optical depth (AOD) from polar orbit satellites and meteorological factors have been widely used to estimate concentrations of surface particulate matter with an aerodynamic diameter <2.5 µm (PM2.5). However, estimations with high temporal resolution remain lacking because of the limitations of satellite observations. Here, we used AOD data with a temporal resolution of 1 h provided by a geostationary satellite called Himawari 8 to overcome this problem. We developed a stacking model, which contained three submodels of machine learning, namely, AdaBoost, XGBoost and random forest, stacked through a multiple linear regression model. Then, we estimated the hourly concentrations of PM2.5 in Central and Eastern China. The accuracy evaluation showed that the proposed stacking model performed better than the single models when applied to the test set, with an average coefficient of determination (R2) of 0.85 and a root-mean-square error (RMSE) of 17.3 µg/m3. Model precision reached its peak at 14:00 (local time), with an R2 (RMSE) of 0.92 (12.9 µg/m3). In addition, the spatial and temporal distributions of PM2.5 in Central and Eastern China were plotted in this study. The North China Plain was determined to be the most polluted area in China, with an annual mean PM2.5 concentration of 58 µg/m3 during daytime. Moreover, the pollution level of PM2.5 was the highest in winter, with an average concentration of 73 µg/m3.

Ground-level PM2.5 estimation over urban agglomerations in China with high spatiotemporal resolution based on Himawari-8.

High concentrations of particulate matter with diameter of <2.5 µm (PM2.5) demonstrate severe effects on human health, especially in the metropolitan agglomerations of China. Estimating PM2.5 based on satellite aerosol optical depth (AOD) is a widely used method. AOD data from Himawari-8, a geostationary satellite, enable improvement of the temporal resolution of PM2.5 estimates to the hourly level, thereby reflecting diurnal variations of pollutants compared with AOD products from polar orbit satellites, which only have one value per day. In this study, PM2.5 concentrations are estimated based on Himawari-8 AOD and other ancillary data by constructing spatiotemporal linear mixed effects model in Central China (CCH), Beijing-Tianjin-Henan (BTH), Yangtze River Delta (YRD) and Pearl River Delta (PRD) regions, respectively. The determination coefficient (R2) between the measurements and estimates of PM2.5 calculated with the tenfold cross-validation method are 0.82, 0.84, 0.80 and 0.74 in CCH, BTH, YRD and PRD, respectively. The spatial distributions of PM2.5 present large regional variation, which is highly correlated with land-use type. Heavily polluted zones are mainly located in urban or rural areas, which have dense population and high anthropogenic emissions. Comparisons among different seasons show that particle pollution during the cold seasons (autumn and winter) is relatively severe with an average PM2.5 of >60 µg/m3 in CCH, BTH and YRD, whereas the level does not greatly change throughout the year in the PRD region. During the daytime, particulate pollution levels are generally high in the morning.

Two-stage model for estimating the spatiotemporal distribution of hourly PM1.0 concentrations over central and east China.

Widespread and severe PM1.0 (particulate matter ≤1.0 µm) pollution in China has a significant negative influence on human health. However, knowledge of the regional spatiotemporal distribution of PM1.0 has been hindered by sparsely distributed PM1.0 concentration data. In this work, a two-stage model (linear mixed effect-bagged tree model) was proposed for estimating hourly PM1.0 pollution levels from July 2015 to June 2017 over central and east China by using Himawari-8 aerosol products and coincident geographic data, meteorology, and site-based PM1.0 concentrations from ground monitoring network. The cross-validation for the developed model displayed R2 and mean absolute error value of 0.80 and 9.3 µg/m3, respectively. Validation demonstrated that the model accurately estimated hourly PM1.0 concentrations with high R2 of 0.63-0.85 and low bias of 8.7-10.1 µg/m3. The estimated PM1.0 concentrations on daily scale showed peaks with PM1.0 of 36.9 ±â€¯8.4 µg/m3 at rush hours during daytime. Seasonal distribution displayed that summer was cleanest with an average PM1.0 of 20.9 ±â€¯6.8 µg/m3 and winter was the most polluted season with an average PM1.0 of 45.6 ±â€¯16.8 µg/m3. These results indicated that the proposed satellite-based model can estimate reliable spatial distribution of PM1.0 concentrations over a large-scale region.

Estimation of spatiotemporal PM1.0 distributions in China by combining PM2.5 observations with satellite aerosol optical depth.

Particulates smaller than 1.0 µm (PM1.0) have strong associations with public health and environment, and considerable exposure data should be obtained to understand the actual environmental burden. This study presented a PM1.0 estimation strategy based on the generalised regression neural network model. The proposed strategy combined ground-based observations of PM2.5 and satellite-derived aerosol optical depth (AOD) to estimate PM1.0 concentrations in China from July 2015 to June 2017. Results indicated that the PM1.0 estimates agreed well with the ground-based measurements with an R2 of 0.74, root mean square error of 19.0 µg/m3 and mean absolute error of 11.4 µg/m3 as calculated with the tenfold cross-validation method. The diurnal estimation performance displayed remarkable single-peak variation with the highest R2 of 0.80 at noon, and the seasonal estimation performance showed that the proposed method could effectively capture high-pollution events of PM1.0 in winter. Spatially, the most polluted areas were clustered in the North China Plain, where the average estimates presented a bimodal distribution during daytime. In addition, the quality of satellite-derived AOD, the robustness of the interpolation algorithm and the proportion of PM1.0 in PM2.5 were confirmed to affect the estimation accuracy of the proposed model.