We can't find the internet
Attempting to reconnect
Something went wrong!
Hang in there while we get back on track
65marcos/PDKP-v1.0.0---Initial-Release: PDKP v1.0.0 - Initial Release
AI summary Read the abstract
Scientists built a computer model that predicts how quickly microplastics break down in farm soil, based on factors like temperature. This matters because microplastics in soil can end up in our food and water, and understanding how fast they degrade (or don't) helps researchers figure out how much plastic contamination we're really exposed to over time. Note that this is a modeling tool released alongside a not-yet-published study, so its real-world accuracy still needs to be confirmed through peer review.
PDKP v1.0.0 Process-Based Kinetic Model for Microplastic Degradation in Agricultural Soils. Features Core kinetic model with Arrhenius temperature correction Lambda (λ) parameter calibration via NLS and MLE Monte Carlo uncertainty propagation Experimental validation against 6 literature datasets Fragmentation modeling via Weibull distribution Citation If you use this software, please cite: [seu artigo quando publicado]
More Papers Like This
65marcos/PDKP-v1.0.0---Initial-Release: PDKP v1.0.0 - Initial Release
AI summary Read the abstract
Scientists built a computer model (a set of software tools, not a lab experiment) that predicts how quickly microplastics break down in farm soil, based on factors like temperature. This matters because microplastics in soil can end up in the crops we eat, so better predictions of how long they stick around could help researchers and farmers figure out where contamination risks are highest. Note that this release is the modeling tool itself, tested against existing published data—it doesn't report new findings about health effects.
65marcos/soil-microplastics: PDKP v1.0.0 - Initial Release2
AI summary Read the abstract
Scientists built a computer model that predicts how plastic mulch used in farm fields breaks down over time and releases chemical additives—like plasticizers and other potentially harmful compounds—into the soil. Tested on real farmland data over several years, the model could reasonably track how these chemicals move and build up, which matters because it helps researchers estimate how much of these substances might end up in soil, water, and eventually the food we eat. This is a modeling tool rather than a direct health study, but it lays groundwork for better predicting chemical exposure risks tied to agricultural plastics.
65marcos/soil-microplastics: PDKP v1.0.0 - Initial Release2
AI summary Read the abstract
Scientists built a computer model that predicts how plastic mulch used in farm fields breaks down over time and releases chemical additives—like plasticizers and BPA-related compounds—into the soil. Tested against real farmland data in China, the model could help farmers and regulators anticipate when and how much of these chemicals might leach into soil and potentially into crops or groundwater. This matters because many of these additives are linked to hormone disruption and other health concerns, so better prediction tools could guide safer farming practices before contamination becomes widespread.
Microplastics in farmlands: A model of conditional fragmentation and source estimation
AI summary Read the abstract
Scientists built a model tracking how microplastics build up and break down in farm soil, using data from nearly 100 studies worldwide. They found that plastic mulch films (the thin sheets farmers use to cover soil) contribute the most microplastic pollution by weight, while compost and organic fertilizers add the highest number of tiny plastic particles—and even after farmers stop using new plastics, old ones keep breaking down into smaller pieces for years. This matters because these smaller, more numerous plastic particles are the ones most likely to end up in our food and water, so understanding where they come from can help guide better farming practices to reduce our
Degradable and Non-degradable Microplastics Regulate Soil Greenhouse Gas Emissions: Multi-factor Insights and Key Monitoring Factors from a Kolmogorov–Arnold Network Ensemble Model
AI summary Read the abstract
Scientists used advanced computer models to figure out what really drives greenhouse gas emissions from soil, and surprisingly, tiny plastic particles (microplastics) turned out to be a minor player compared to factors like soil moisture, temperature, and natural carbon content. This matters because it suggests that while microplastic pollution is still a health and environmental concern worth addressing, it's not a major direct driver of climate-warming gases from soil, so cleanup efforts and regulations might get more bang for their buck focusing on soil management practices alongside reducing plastic waste.
Research digests by email
When a large batch of papers lands in the Atlas, we read through it and send a short write-up of what stood out.