Using clustering, statistical modeling, and climate change projections to analyze recent and future region‐specific compound ozone and temperature burden over Europe

High ground‐level ozone concentrations and high air temperatures present two health‐relevant natural hazards. The most severe health outcomes are generally associated with concurrent elevated levels of both variables, representing so‐called compound ozone and temperature (o‐t‐) events. These o‐t‐events, their relationship with identified main meteorological and synoptic drivers, as well as ozone and temperature levels themselves and the linkage between both variables, vary temporally and with the location of sites. Due to the serious health burden and its spatiotemporal variations, the analysis of o‐t‐events across the European domain represents the focus of the current work. The main objective is to model and project present and future o‐t‐events, taking region‐specific differences into account. Thus, a division of the European domain into six o‐t‐regions with homogeneous, similar ground‐level ozone and temperature characteristics and patterns built the basis of the study. In order to assess region‐specific main meteorological and synoptic drivers of o‐t‐events, statistical downscaling models were developed for selected representative stations per o‐t‐region. Statistical climate change projections for all central European o‐t‐regions were generated to assess potential frequency shifts of o‐t‐events until the end of the 21st century. The output of eight Earth System Models from the sixth phase of the Coupled Model Intercomparison Project considering SSP245 and SSP370 scenario assumptions was applied. By comparing midcentury (2041–2060) and late century (2081–2100) time slice differences with respect to a historical base period (1995–2014), substantial increases of the health‐relevant compound o‐t‐events were projected across all central European regions

Temperature projections over the Indus River Basin of Pakistan using statistical downscaling

We assessed maximum (Tmax) and minimum (Tmin) temperatures over Pakistan’s Indus basin during the 21st century using statistical downscaling. A particular focus was given to spatiotemporal heterogeneity, reference and General Circulation Model (GCM) uncertainties, and statistical skills of regression models using an observational profile that could significantly be improved by recent high-altitude observatories. First, we characterized the basin into homogeneous climate regions using K-means clustering. Predictors from ERA-Interim reanalysis were then used to model observed temperatures skillfully and quantify reference and GCM uncertainties. Thermodynamical (dynamical) variables mainly governed reference (GCM) uncertainties. The GCM predictors under RCP4.5 and RCP8.5 scenarios were used as “new” predictors in statistical models to project ensemble temperature changes. Our analysis projected non-uniform warming but could not validate elevation-dependent warming (EDW) at the basin scale. We obtained more significant warming during the westerly-dominated seasons, with maximum heating during the winter season through Tmin changes. The most striking feature is a low-warming monsoon (with the possibility of no change to slight cooling) over the Upper Indus Basin (UIB). Therefore, the likelihood of continuing the anomalous UIB behavior during the primary melt season may not entirely be ruled out at the end of the 21st century under RCP8.5

Development of air quality boxes based on low-cost sensor technology for ambient air quality monitoring

Analyses of the relationships between climate, air substances and health usually concentrate on urban environments because of increased urban temperatures, high levels of air pollution and the exposure of a large number of people compared to rural environments. Ongoing urbanization, demographic ageing and climate change lead to an increased vulnerability with respect to climate-related extremes and air pollution. However, systematic analyses of the specific local-scale characteristics of health-relevant atmospheric conditions and compositions in urban environments are still scarce because of the lack of high-resolution monitoring networks. In recent years, low-cost sensors (LCS) became available, which potentially provide the opportunity to monitor atmospheric conditions with a high spatial resolution and which allow monitoring directly at vulnerable people. In this study, we present the atmospheric exposure low-cost monitoring (AELCM) system for several air substances like ozone, nitrogen dioxide, carbon monoxide and particulate matter, as well as meteorological variables developed by our research group. The measurement equipment is calibrated using multiple linear regression and extensively tested based on a field evaluation approach at an urban background site using the high-quality measurement unit, the atmospheric exposure monitoring station (AEMS) for meteorology and air substances, of our research group. The field evaluation took place over a time span of 4 to 8 months. The electrochemical ozone sensors (SPEC DGS-O3: R(2): 0.71–0.95, RMSE: 3.31–7.79 ppb) and particulate matter sensors (SPS30 PM1/PM2.5: R(2): 0.96–0.97/0.90–0.94, RMSE: 0.77–1.07 µg/m(3)/1.27–1.96 µg/m(3)) showed the best performances at the urban background site, while the other sensors underperformed tremendously (SPEC DGS-NO2, SPEC DGS-CO, MQ131, MiCS-2714 and MiCS-4514). The results of our study show that meaningful local-scale measurements are possible with the former sensors deployed in an AELCM unit

Blessing and curse of bioclimatic variables: a comparison of different calculation schemes and datasets for species distribution modeling within the extended Mediterranean area

Bioclimatic variables (BCVs) are the most widely used predictors within the field of species distribution modeling, but recent studies imply that BCVs alone are not sufficient to describe these limits. Unfortunately, the most popular database, WorldClim, offers only a limited selection of bioclimatological predictors; thus, other climatological datasets should be considered, and, for data consistency, the BCVs should also be derived from the respective datasets. Here, we investigate how well the BCVs are represented by different datasets for the extended Mediterranean area within the period 1970–2020, how different calculation schemes affect the representation of BCVs, and how deviations among the datasets differ regionally. We consider different calculation schemes for quarters/months, the annual mean temperature (BCV-1), and the maximum temperature of the warmest month (BCV-5). Additionally, we analyzed the effect of different temporal resolutions for BCV-1 and BCV-5. Differences resulting from different calculation schemes are presented for ERA5-Land. Selected BCVs are analyzed to show differences between WorldClim, ERA5-Land, E-OBS, and CRU. Our results show that (a) differences between the two calculation schemes for BCV-1 diminish as the temporal resolution decreases, while the differences for BCV-5 increase; (b) with respect to the definition of the respective month/quarter, intra-annual shifts induced by the calculation schemes can have substantially different effects on the BCVs; (c) all datasets represent the different BCVs similarly, but with partly large differences in some subregions; and (d) the largest differences occur when specific month/quarters are defined by precipitation. In summary, (a) since the definition of BCVs matches different calculation schemes, transparent communication of the BCVs calculation schemes is required; (b) the calculation, integration, or elimination of BCVs has to be examined carefully for each dataset, region, period, or species; and (c) the evaluated datasets provide, except in some areas, a consistent representation of BCVs within the extended Mediterranean region

Impact of climate change on non-communicable diseases due to increased ambient air pollution

Background: The impacts of air pollutants on health range from short-term health impairments to hospital admissions and deaths. Climate change is leading to an increase in air pollution. Methods: This article addresses, based on selected literature, the relationship between climate change and air pollutants, the health effects of air pollutants and their modification by air temperature, with a focus on Germany. Results: Poor air quality increases the risk of many diseases. Climate change is causing, among other things, more periods of extreme heat with simultaneously increased concentrations of air pollutants. The interactions between air temperature and air pollutants, as well as their combined effects on human health, have not yet been sufficiently studied. Limit, target, and guideline values are of particular importance for health protection. Conclusions: Measures to reduce air pollutants and greenhouse gases must be more strictly implemented. An essential step towards improving air quality is setting stricter air quality limit values in Europe. Prevention and adaptation measures should be accelerated in Germany, as they contribute to climate-resilient and sustainable healthcare systems. This is part of a series of articles that constitute the German Status Report on Climate Change and Health 2023

Impact of climate change on non-communicable diseases due to increased ambient air pollution

Background: The impacts of air pollutants on health range from short-term health impairments to hospital admissions and deaths. Climate change is leading to an increase in air pollution. Methods: This article addresses, based on selected literature, the relationship between climate change and air pollutants, the health effects of air pollutants and their modification by air temperature, with a focus on Germany. Results: Poor air quality increases the risk of many diseases. Climate change is causing, among other things, more periods of extreme heat with simultaneously increased concentrations of air pollutants. The interactions between air temperature and air pollutants, as well as their combined effects on human health, have not yet been sufficiently studied. Limit, target, and guideline values are of particular importance for health protection. Conclusions: Measures to reduce air pollutants and greenhouse gases must be more strictly implemented. An essential step towards improving air quality is setting stricter air quality limit values in Europe. Prevention and adaptation measures should be accelerated in Germany, as they contribute to climate-resilient and sustainable healthcare systems. This is part of a series of articles that constitute the German Status Report on Climate Change and Health 2023

Impact of climate change on non-communicable diseases due to increased ambient air pollution

Background: The impacts of air pollutants on health range from short-term health impairments to hospital admissions and deaths. Climate change is leading to an increase in air pollution. Methods: This article addresses, based on selected literature, the relationship between climate change and air pollutants, the health effects of air pollutants and their modification by air temperature, with a focus on Germany. Results: Poor air quality increases the risk of many diseases. Climate change is causing, among other things, more periods of extreme heat with simultaneously increased concentrations of air pollutants. The interactions between air temperature and air pollutants, as well as their combined effects on human health, have not yet been sufficiently studied. Limit, target, and guideline values are of particular importance for health protection. Conclusions: Measures to reduce air pollutants and greenhouse gases must be more strictly implemented. An essential step towards improving air quality is setting stricter air quality limit values in Europe. Prevention and adaptation measures should be accelerated in Germany, as they contribute to climate-resilient and sustainable healthcare systems. This is part of a series of articles that constitute the German Status Report on Climate Change and Health 2023