Fine particulate matter (PM₂.₅) has been recognized as a key air pollutant that can influence population health risk, especially during extreme cases such as wildfires. Previous studies have applied geospatial techniques such as land use regression to map the ground-level PM₂.₅, while some recent studies have found that Aerosol Optical Depth (AOD) derived from satellite images and machine learning techniques may be two elements that can improve spatiotemporal prediction. However, there has been a lack of studies evaluating use of different machine learning techniques with AOD datasets for mapping PM₂.₅, especially in areas with high spatiotemporal variability of PM₂.₅.In this study, we compared the performance of eight predictive algorithms with the use of multiple remote sensing datasets, including satellite-derived AOD data, for the prediction of ground-level PM2.5 concentration. Based on the results, Cubist, random forest and eXtreme Gradient Boosting were the algorithms with better performance, while Cubist was the best (CV-RMSE = 2.64 μg/m3, CV-R² = 0.48). Variable importance analysis indicated that the predictors with the highest contributions in modelling were monthly AOD and elevation.In conclusion, appropriate selection of machine learning algorithms can improve ground-level PM2.5 estimation, especially for areas with nonlinear relationships between PM2.5 and predictors caused by complex terrain. Satellite-derived data such as AOD and land surface temperature (LST) can also be substitutes for traditional datasets retrieved from weather stations, especially for areas with sparse and uneven distribution of stations.

Water Soluble Bulk Deposition (WSBD) and Water Soluble Leaching (WSL) from Pseudevernia furfuracea thalli transplanted in a anthropized zone were separately collected in four locations where weather stations were set up for monitoring rainfalls rate and daily temperature.The thalli were exposed for three months during which 13 major rainfalls took place. The concentrations of 15 elements (Al, V, Cr, Mn, Co, Ni, Cu, Zn, Mo, Pb, As, Cd, Ti, Sn, Sb) were measured as well in WSBD and WSL as in the lichen thalli at the end of the exposure period. The total bioaccumulation of each element was significantly correlated with its % representation in both the lichen input (WSBD) and output (WSL). Elements with a small water-soluble input-pool were mostly taken up by the thalli (output/input < 1). Among the elements with a high input-pool, Zn was nearly systematically taken up while Al and Mn were lost (output/input > 1). Al showed a significant direct correlation with the increase in mm and hours of rainfall (i.e. transition from net loss to net uptake) while Mn showed an inverse correlation (transition from net uptake to net loss), which may be due to element competition modulated by water-stimulated lichen physiology. Al was strongly bioaccumulated while Mn showed a slight increase in exposed thalli. This suggests that rainfall-induced loss can result in an underestimation by lichen biomonitoring of element concentrations in atmospheric deposition and an increase in the bioavailability of potential toxic elements for other environmental compartments.

We aimed to understand relationships of the weather as biometeorological and hospital admissions due to diseases of arteries and veins by subtypes, which have been scarcely studied, in a national setting in recent years. This is an ecological study. Ten percent of daily hospital admissions from the included hospitals (n = 1,618) across Germany that were available between 1 January 2009 and 31 December 2011 (n = 5,235,600) were extracted from Statistisches Bundesamt, Germany. We identified I70-I79 Diseases of arteries, arterioles and capillaries and I80-I89 Diseases of veins, lymphatic vessels and lymph nodes by International Classification of Diseases version 10 as the study outcomes. Daily weather data from 64 weather stations that covered 13 German states including air temperature, humidity, wind speed, cloud cover, radiation flux and vapour pressure were obtained and generated into physiologically equivalent temperature (PET). Two-way fractional-polynomial prediction was plotted with 95 % confidence intervals. For most of the subtypes from diseases of arteries and veins, hospital admissions slightly peaked in spring and dropped when PET was at 10 °C. There were no other large differences across 12 months. Admissions of peripheral vascular diseases, arterial embolism and thrombosis, phlebitis and thrombophlebitis, oesophageal varices and nonspecific lymphadenitis peaked when PET was between 0 and −10 °C, while others peaked when PET was between 0 and 10 °C. More medical resources could have been needed on days when PETs were at −10 to 10 °C than on other days. Adaptation to such weather change for health professionals and the general public would seem to be imperative.

We aimed to understand relationships of the weather as biometeorological and hospital admissions due to other forms of heart disease by subtypes, which have been paid less attention, in a national setting in recent years. This is an ecological study. Ten percent of daily hospital admissions of the included hospitals (n = 1618) across Germany that were available between 1 January 2009 and 31 December 2011 (n = 5,235,600) were extracted from Statistisches Bundesamt, Germany. We identified I30–I51 other forms of heart disease by the International Classification of Diseases version 10 as the study outcomes. Daily weather data from 64 weather stations that have covered 13 German states, including air temperature, humidity, wind speed, cloud cover, radiation flux and vapour pressure, were obtained and generated into physiologically equivalent temperature (PET). Admissions due to other diseases of pericardium, nonrheumatic mitral valve disorders, nonrheumatic aortic valve disorders, cardiomyopathy, atrioventricular and left bundle-branch block, other conduction disorders, atrial fibrillation and flutter, and other cardiac arrhythmias peaked when PET was between 0 and 10 °C. Complications and ill-defined descriptions of heart disease admissions peaked at PET 0 °C. Cardiac arrest and heart failure admissions peaked when PET was between 0 and −10 °C while the rest did not vary significantly. A common drop of admissions was found when PET was above 10 °C. More medical resources could have been needed for heart health on days when PETs were <10 °C than on other days. Adaptation to such weather change for medical professionals and the general public would seem to be imperative.

We aimed to understand and to provide evidence on relationships of the weather as biometeorological and hospital admissions due to hypertension, angina, myocardial infarction and ischemic heart disease in a national setting in recent years that might help indicate when to expect more admissions for health professionals and the general public. This is an ecological study. Ten percent of daily hospital admissions from the included hospitals (n = 1618) across Germany that were available between 1 January 2009 and 31 December 2011 (n = 5,235,600) were extracted from Statistisches Bundesamt, Germany. We identified I11 hypertensive heart disease, I13 hypertensive heart and renal disease, I15 secondary hypertension, I20 angina pectoris, I21 acute myocardial infarction and I25 chronic ischemic heart disease by International Classification of Diseases version 10 as the study outcomes. Daily weather data from 64 weather stations that covered 13 German States including air temperature, humidity, wind speed, cloud cover, radiation flux and vapour pressure were obtained and generated into physiologically equivalent temperature (PET). Two-way fractional-polynomial prediction was plotted with 95 % confidence intervals. Hospital admissions of hypertension, angina, myocardial infarction, heart disease peaked in winter and early spring when PETs were around 0 °C. Admissions had an apparent drop when PETs reached 10 °C. More medical resources could have been needed on days when PETs were around 0 °C than on other days. While adaptation to such weather change for health professionals and the general public would seem to be imperative, future research with a longitudinal monitoring would still be needed.