Carbon farming innovation and scale-up

Expected Outcome: Project results are expected to contribute to all of the following expected outcomes: models, methods and data needed for the quantification of carbon farming activities and results are available for integration in a single monitoring, reporting and verification (MRV) system, so that the costs and burden associated to carbon farming MRV are reduced to a minimum; use of carbon-removal and emission-reduction certification is facilitated at scale, and the EU Carbon Removals and Carbon Farming (CRCF) Regulation [1] becomes the basis for cost-effective certification of carbon farming in different contexts; carbon farming actors involved in CRCF implementation in different roles – including land managers and other market participants as well as certification and governance bodies – have access to relevant scientific knowledge and tailored technical support for the implementat… devamı

AgricultureCarbon capture and sequestrationCertification schemesClimate change mitigationEarth Observation / Services and applicationsForestryCRCF certification and registryCarbon Removals and Carbon Farming (CRCF) Regulationcarbon farmingcarbon farming innovationcertificationgreenhouse gas inventoriesmodels, methods and datamonitoring, reporting and verification (MRV) systemquantificationscale-up

1. %52
   ALİ DEVLET

   Doktor Öğretim ÜyesiBilecik Şeyh Edebali Üniversitesi

   Ortak konular: Soil Carbon and Nitrogen Dynamics

2. %43
   CAFER GENÇOĞLAN

   ProfesörKahramanmaraş Sütçü İmam Üniversitesi

   Ortak konular: Plant Water Relations and Carbon Dynamics

3. %43
   SAİT ÜSTÜN

   Doktor Öğretim ÜyesiKahramanmaraş Sütçü İmam Üniversitesi

   Ortak konular: Plant Water Relations and Carbon Dynamics

4. %40
   KADİR SALTALI

   ProfesörKahramanmaraş Sütçü İmam Üniversitesi

   Ortak konular: Soil Carbon and Nitrogen Dynamics

5. %40
   SAKİNE ÇETİN TANER

   Doktor Öğretim ÜyesiOndokuz Mayıs Üniversitesi

   Ortak konular: Plant Water Relations and Carbon Dynamics

Uyum oranı kodla, her istekte hesaplanır: çağrı metni (başlık, AB anahtar kelimeleri, resmi açıklamanın başı) ile akademisyenin YÖKSİS alanları, anahtar kelimeleri ve OpenAlex konuları arasındaki anlamsal yakınlık (%55) ve ortak ayırt edici terimler (%45; yaygın kelimeler düşük ağırlıklı). %40 altı gösterilmez. Bir konu önerisidir; başvuru uygunluğu, kapasite ya da başarı değerlendirmesi değildir. Gizli profiller listelenmez.