Background: Temperature, precipitation, and humidity are important factors that can influence the spread, reproduction, and survival of pathogens. Climate change affects these factors, resulting in higher air and water temperatures, increased precipitation, or water scarcity. Climate change may thus have an increasing impact on many infectious diseases.
Methods: The present review considers those foodborne pathogens and toxins in animal and plant foods that are most relevant in Germany, on the basis of a selective literature review: the bacterial pathogens of the genera and , parasites of the genera and , and marine biotoxins.
Results: As climate change continues to progress, all infections and intoxications discussed here can be expected to increase in Germany.
Conclusions: The expected increase in foodborne infections and intoxications presents a growing public health risk in Germany.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10278375 | PMC |
http://dx.doi.org/10.25646/11403 | DOI Listing |
Sci Rep
January 2025
School of Civil Engineering, Vellore Institute of Technology, Chennai, Tamil Nadu, 600127, India.
The carbon footprint associated with cement production, coupled with depletion of natural resources and climate change, underscores the need for sustainable alternatives. This study explores the effect of metakaolin (MK) and nano-silica (NS) on concrete's engineering performance and environmental impact. Initially, compressive, tensile, and flexural strength tests, along with durability assessments like water absorption, sorptivity, rapid chloride permeability, and resistance to acid and sulphate attacks, were conducted.
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January 2025
Institute of Crop Science and Resource Conservation, University of Bonn, Katzenburgweg 5, D-53115, Bonn, Germany.
Climate change significantly challenges smallholder mixed crop-livestock (MCL) systems in sub-Saharan Africa (SSA), affecting food and feed production. This study enhances the SIMPLACE modeling framework by incorporating crop-vegetation-livestock models, which contribute to the development of sustainable agricultural practices in response to climate change. Applying such a framework in a domain in West Africa (786,500 km) allowed us to estimate the changes in crop (Maize, Millet, and Sorghum) yield, grass biomass, livestock numbers, and greenhouse gas emission in response to future climate scenarios.
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January 2025
University of Antwerp - imec - IDLab, Department of Mathematics, Antwerp, 2000, Belgium.
As global fertilizer application rates increase, high-quality datasets are paramount for comprehensive analyses to support informed decision-making and policy formulation in crucial areas such as food security or climate change. This study aims to fill existing data gaps by employing two machine learning models, eXtreme Gradient Boosting and HistGradientBoosting algorithms to produce precise country-level predictions of nitrogen (N), phosphorus pentoxide (PO), and potassium oxide (KO) application rates. Subsequently, we created a comprehensive dataset of 5-arcmin resolution maps depicting the application rates of each fertilizer for 13 major crop groups from 1961 to 2019.
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January 2025
Jozef Stefan Institute, Ljubljana, 1000, Slovenia.
Due to growing population and technological advances, global electricity consumption is increasing. Although CO emissions are projected to plateau or slightly decrease by 2025 due to the adoption of clean energy sources, they are still not decreasing enough to mitigate climate change. The residential sector makes up 25% of global electricity consumption and has potential to improve efficiency and reduce CO footprint without sacrificing comfort.
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January 2025
Department of Economics, Vienna University of Economics and Business (WU), Vienna, Austria.
The quantitative assessment of policies aimed at climate change mitigation requires rigorously identifying abnormal changes in greenhouse gas emissions. We present a new dataset of robust level changes in greenhouse gas emissions that cannot be explained by aggregate socioeconomic fluctuations. Modern methods of structural break identification based on two-way fixed effects models are employed to estimate the size of significant level changes in emissions.
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