Sürdürülebilir Kalkınma Amaçları

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• MakaleAçık Erişim2026Scopus SJRQ2/r/munzur/913
  Risk Assessment via Hazard Scenario in Cereal Production Under Rising CO

  Susam, Selim Orhun; Peker, Ayse Esra; Hudaverdi, Burcu

  Global food security has been seriously threatened by air pollution and climate change. The impact of CO on crop output is complicated because of its interactions with temperature, nutrient availability, and other pollutants, even though it is necessary for photosynthesis. This study develops a copula-based hazard modeling framework to assess how increasing CO concentrations affect cereal production risk across multiple crops. By integrating hazard scenario analysis with localized dependence measures, we estimate both failure probabilities and dynamic associations between CO emissions and cereal yields. A novel localized version of Kendall’s implemented via a Bernstein copula approximation, enables flexible modeling of heterogeneous and nonlinear dependence structures. As the relationship between CO emissions and crop-specific yields changes in both density and direction, it may indicate asymmetries or nonlinearities that are missed by measures of global dependence. Empirical results reveal distinct crop-specific responses. While CO levels enhance yields for rice, millet, and sugar beet, they reduce or destabilize production for rye and lentil, indicating asymmetric sensitivities. Failure probabilities increase with the time horizon, reflecting the accumulation of climate-related production risk. The findings emphasize the significance of integrating probabilistic hazard modeling into climate-resilient agricultural planning and food security policies, as crop-specific risk exposure has increased in recent time periods.

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  AtıfWoS1·OpenAlex1

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• MakaleYalnız künye2025Scopus SJRQ2/r/munzur/1252
  Exploring the Grazing Land Footprint’s Stochastic Behavior in the Top Dairy and Meat-Producing Nations

  Adali, Zafer; Yeter, Fatih; Çoban, Mustafa Necati; Sarı, Sacit

  The Sustainable Development Goals (SDGs) are a set of influential and easily understood sustainability principles. SDG2 defines Zero Hunger, which is once again a key goal in the SDGs. A sustainable food system depends on the grazing land footprint, one of the elements of the ecological footprint. For food security to be maintained, the grazing land footprint has to be taken into consideration. In order to provide adequate global food systems and mitigate climate change, research on the stochastic features of grazing land footprint is crucial. The goal of this research is to look at the stochastic characteristics of the grazing land footprint in 13 nations that produce almost two-thirds of the world’s milk and meat. The study includes data for 13 nations over the years 1961–2022. Several unit root tests are conducted to provide more precise data about the effectiveness of the policy shocks, including whether or not they allow for repeated, smooth structural breakdowns. The results show that because the series is prone to following its long-term trends, shocks cannot lead it to diverge from those trends. Thus, any shocks brought on by policies cannot have a lasting effect on the series. However, the series includes a unit root. The unit root tests have made it clear that any policy shocks would have a long-lasting effect on the series and that policymakers may set a goal for the series. Policy suggestions have been provided for the investigated nations in conjunction with these results.

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  AtıfScopus2·WoS2·OpenAlex8

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