Globally, economies are highly concerned about the balance between climatic issues and attaining agricultural sustainability. However, empirical evidence regarding the nexus of agricultural sustainability, emissions, land use, and agricultural trade is scarce and requires appropriate policy-level attention. The current study examines the influence of land-use resources, agricultural exports, and foreign direct investment on agriculture-related greenhouse gas emissions in Brazil. Using various time series diagnostic measures on quarterly data from 1990Q1 to 2020Q4 reveals non-normality and a mixed order of stationarity in variables. The autoregressive distributed lag (ARDL) model and quantile ARDL approach are employed for comprehensive empirical analysis. The results assert that land resources and foreign investments are harmful to environmental sustainability, as they significantly enhance agricultural greenhouse gas emissions. Additionally, agricultural exports and green energy significantly contribute to emissions mitigation by tackling land-use and agricultural emissions in the short and long run. The results are robust across the ARDL and quantile regressions and pairwise granger causality. The study concludes that agricultural exports and land use are key factors inducing agricultural sustainability by inducing emissions. The study recommends increased spending on research and development, solar-based irrigation, and promotion of green energy projects. The study discusses novel findings and implications apropos land resources, foreign investments, agricultural exports, and emissions in the lens of COP 28.

In the contemporary world, achieving sustainable food production has become an urgent task for the international community and policymakers due to the rapidly growing social challenges of mankind. Sustainable food production practices aid countries in adapting to the challenges posed by climate change, thereby ensuring a better and more sustainable future for all. This study examines the impact of land use, energy efficiency (ENE), water productivity (WP), renewable energy consumption (REC), and gross domestic product (GDP) on sustainable food production in G20 nations over the period of 1998–2020. We use quantile regression approaches to capture potential heterogeneity across various food value-added distribution quantiles. The results show that arable land, WP, GDP, ENE, and REC are important factors affecting food value added in G20 nations. However, the nature of the relationship varies across different quantiles, suggesting heterogeneity in the relationships. The results show that ENE, renewable energies, and GDP are positively related to food production. However, arable land and WP are negatively related to food production. The findings can assist policymakers and stakeholders in making informed decisions to increase value added in the agricultural sector while promoting resilience and sustainability.

The current study establishes theoretical and empirical linkages among urbanization, economic growth, land use, and greenhouse gas (GHG) emissions. The prime objective of this article is to draw novel conclusions and policies for the different income levels of countries regarding the urbanization and agriculture sector land on environmental pollution. Employing panel data of 50 countries for the period 1990 to 2019, this study uses the lasso regression and non-parametric regression panel data methods to investigate the impacts of land use (arable, permanent pastures, and cropland), urbanization growth, and economic progress on the pollution levels. After estimating a Lasso regression to find the best auto-regressive predictive specification, we used an auto-regressive partially linear regression where each of the drivers’ effects was modelled non-parametrically. The elasticity effect of the urban population on emissions is significantly positive and sizable. In addition, the effect distribution shows a non-negligible share of observations with an elasticity higher than one. Urban population growth is a serious threat to climate change, as it seems to increase sharply CO2 emissions (although with an elasticity pace smaller than one). The elasticity effect of GDP is significantly negative, which implies that the scale of production, by triggering efficiency, can have a positive effect on emissions reduction. The results argue that agglomeration negative effects put in place by larger urban population can partly explain this finding. Overall, the study argues that urbanization growth and economic activities lead to GHG emissions, whereas the study also discusses novel implications and the role of agricultural land use apropos Sustainable Development Goals (SDGs). The empirical findings allow us to draw novel conclusions and guidelines in line with SDGs. The agricultural reforms might include irrigation and farming techniques such as spin farming, solar tube wells, tunnel farming, technology use agreements, plant double helix, etc.