The agricultural sector is seriously impacted by climate change, leading to potential risks to food security. In terms of global food production, maize ranks third. As a result, crop production and food security depend critically on assessing the effects of climate change and developing measures to adapt maize. Regarding adaptability, changing planting dates and using different agrochemicals are more effective than other management. Crop models are part of a global decision support system to help farmers maximize yields despite unpredictable weather patterns. To mitigate yield loss and protect the ecosystem, it is essential to use efficient maize-sowing practices in the field. This experiment was carried out to identify the most favorable sowing dates that maximize yield while ensuring the crop’s productivity and the integrity of the surrounding ecosystem remain intact. The main aim of this experiment was to mitigate the different climatic conditions by exogenous application of salicylic acid (SA) and sodium nitroprusside (SNP) on pigments and sugar content in maize under different sowing dates. A field experiment was carried out in the School of Agriculture, Lovely Professional University, Punjab, India, during the spring season of 2022. The experiment dealt with various maize crops, PMH-10, sourced from the Punjab Agricultural University (PAU), Punjab. The experiment was conducted in an open-air environment. The experimental setup was laid out in a split-plot design. The results stated that foliar application of salicylic acid and sodium nitroprusside successfully influenced high-temperature tolerance and low temperature at the reproductive phase and initial vegetative stages with other growing climatic conditions of maize in early and late sowings when controlled by increasing the chlorophyll index, carotenoids content, and sugar content of maize.

The Philippines has been listed as the topmost affected country by climate change. One of the sectors affected by this climatic change is the agricultural sector. This study aimed to document the knowledge, attitude, and practices (KAPs) on climate change among rice farmers as a baseline study in disseminating the practices on disaster risk reduction management to rice farmers in Central Luzon to reduce risks and improve the rice yield and income of rice farmers. A total of 969 respondents were randomly sampled from the seven provinces of Central Luzon. A survey questionnaire and an unstructured questionnaire were used as instruments in gathering the needed data. Descriptive and thematic analysis were used in analyzing the data. Results revealed that rice farmers are knowledgeable and have favorable attitudes toward the impact of climate change on farming. They sometimes practice climate-smart agricultural practices. Generally, the farmers are affected by weather and climatic conditions as well as the hazards that cause a reduction in rice yield. Climate change has affected farmers in their social well-being, economic aspect, and rice production. In terms of climate change disaster adaptation measures, the farmers sometimes adopt measures in terms of flood and drought and seldom adopt measures in typhoons, erosion, and volcanic eruptions. The study recommends the conduct of capability training on disaster risk reduction in rice production (such as early planting and planting of high-yielding varieties) based on the specific needs of each province.

Energy security and stable supply are the most important aspects for any nation. The rising need for energy, caused by both population growth and economic activity, is a problem for many nations throughout the world. Consequently, they have to find a way to meet energy demand while also making sure it is inexpensive and sustainable. The use of renewable energy has gradually become one that is being given a lot of attention since it does not cause any harm to the environment. On the other hand, renewable energy is gaining popularity for a variety of different reasons. A paradigm shift toward renewable resources is relevant, as they have the ability to lessen reliance on fossil fuels and decrease environmental consequences; this article will provide several reasons why renewable energy is attracting attention on a global scale. Indeed, renewable energy is plentiful, clean, and might one day provide all of our energy needs. A country's carbon footprint and reliance on fossil fuels may be reduced by investing in renewable energy sources. In addition, there are several health and environmental problems associated with air and water pollution; nevertheless, renewable energy may assist decrease these problems.

In this study, the AquaCrop model was employed to analyze the impact of projected future climate changes on the water usage and biomass production of potato crops in Babylon, Iraq, under varying irrigation methods. The irrigation techniques evaluated included sprinkler irrigation, surface drip irrigation, and subsurface drip irrigation at depths of 10 cm and 20 cm. The study involved simulating and forecasting conditions for the year 2050, comparing them to current conditions. The model measured and predicted the evapotranspiration (ETa) and actual biomass of potato crops for 2050 using the RCP 8.5 scenarios, which outline different trajectories for greenhouse gas emissions. The AquaCrop model was calibrated and validated using statistical measures such as the R2, RMSE, CV, EF, and D, achieving a 99% accuracy level in its performance. The findings suggest that using drip irrigation systems and applying the AquaCrop model significantly mitigates the adverse effects of environmental stress on desert soils and enhances sustainable agricultural practices in arid regions.

The present study attempted to observe the perception and adaptation strategies of farmers in the context of climate change. It observes that the majority of the farmers are aware of climate change and understand that they are facing problems due to it. The major problems faced by the farmers are the long duration of dryness due to lack of rainfall, weed pressure, very high temperatures, and crop disease. However, farmers are not very aware of technological adaptation and have changed the cropping time due to changes in the time of monsoon. The study recommends that there is a need for intensive micro and macro policy initiatives in terms of modern green sustainable technology along with awareness and skill development of the farmers. The government should also focus more on policy initiatives for sustainable agricultural practices in line with sustainable development goals.

The relationship between trade and climate change is not a simple linear relationship. In this paper, using the threshold regression model, we estimated the effect of trade on climate change in South Africa. The paper applied the LM test to examine the nonlinear inference approach to test whether nonlinearity existed and if the threshold model was relevant to the study. The results show that when energy use is set as the threshold variable, the relationship between trade and climate change measured as methane is U-shaped. Also, in other models of GHG as climate change indicators, the results show that the effect of trade on climate change is not dynamic. This result supports the idea that high and low trade effects may have different impacts on climate change indicators. It is, therefore, recommended that all exporters in South Africa resort to more innovative environmental mechanisms to reduce the contribution to climate. The suggestion for future studies is to consider exports of different sectors to climate change. This approach will avoid the generalization of exporting firms as the worst emitters.

The important source of carbon dioxide (CO2) emission is identified to be energy usage, which the demand is gradually increasing. Currently, many people are exposed to increasing temperatures, which affects to health, environment, and quality of life. Moreover, there are many worries about its continuously increasing trend. This work is interested in studying the association between the annual CO2 emission and the annual mean temperature in Thailand. At a confidence interval of 90%, a statistically significant association between the annual CO2 emission and the annual mean temperature was observed. The appropriate predictive equation represented that the CO2 emission at 0.481 M ton increased the annual mean temperature by about 1°C. The results are useful for planning the reduction of CO2 emissions in Thailand. Fascinatingly, the largest source comes from electricity production, and the most significant energy type is finished oil. Therefore, they should be controlled as the priority. Integrated methods are considered as more efficient strategies for the CO2 crisis.