This current study addresses the knowledge gap regarding the influence of seasons, months, and THI on milk yield, composition, somatic cell counts (SCC), and total bacterial counts (TBC) of dairy farms in northeastern regions of Iran. For this purpose, ten dairy herds were randomly chosen, and daily milk production records were obtained. Milk samples were systematically collected from individual herds upon delivery to the dairy processing facility for subsequent analysis, including fat, protein, solids-not-fat (SNF), pH, SCC, and TBC. The effects of seasons, months, and THI on milk yield, composition, SCC, and TBC were assessed using an analysis of variance. To account for these effects, a mixed-effects model was utilized with a restricted maximum likelihood approach, treating month and THI as fixed factors. Our investigation revealed noteworthy correlations between key milk parameters and seasonal, monthly, and THI variations. Winter showed the highest milk yield, fat, protein, SNF, and pH (p < 0.01), whereas both SCC and TBC reached their lowest values in winter (p < 0.01). The highest values for milk yield, fat, and pH were recorded in January (p < 0.01), while the highest protein and SNF levels were observed in March (p < 0.01). December marked the lowest SCC and TBC values (p < 0.01). Across the THI spectrum, spanning from −3.6 to 37.7, distinct trends were evident. Quadratic regression models accounted for 34.59%, 21.33%, 4.78%, 20.22%, 1.34%, 15.42%, and 13.16% of the variance in milk yield, fat, protein, SNF, pH, SCC, and TBC, respectively. In conclusion, our findings underscore the significant impact of THI on milk production, composition, SCC, and TBC, offering valuable insights for dairy management strategies. In the face of persistent challenges posed by climate change, these results provide crucial guidance for enhancing production efficiency and upholding milk quality standards.

This study examined the impacts of climate change on okra and tomato yields. Fertilizer consumption and credit to the crop sector were considered as covariates in the analysis. Time-series data, spanning a period of 40 years, were obtained from various sources. An autoregressive distributed lag model was applied to analyze short- and long-term impacts of climate change and agricultural inputs on okra and tomato yields. Not all variables were stationary at levels (order zero), but they were all significant at first difference, indicating the presence of cointegration. The Bound’s test F-ratio was statistically significant and implied the presence of long- and short-term relationships among the variables studied. The mean temperatures had negative impacts on okra and tomato yields in both the short and long terms. Credit guaranteed to the crop sector had positive short- and long-term impacts on tomato yield; fertilizer consumption had a negative long-term impact on okra yield. Our study concludes that climate change, particularly rising temperature, impacts herbaceous fruit crop production in Nigeria. Therefore, we recommend that breeding and disseminating climate-smart tomato and okra varieties will help fruit crop farmers respond to rising temperatures.

The livestock industry significantly contributes to greenhouse gas emissions, with ruminant animals, including cows, sheep, and goats, being responsible for a substantial share of these emissions due to methane production. Reducing methane emissions from ruminants is crucial for mitigating the environmental impact of livestock production. Additionally, there has been a growing interest in improving the nutritional quality of ruminant products through modifying their profile of fatty acids. The current study aimed to investigate the potential of sage (SAG), pine (PIN), and clove (CLO) essential oils as natural additives for modulating in vitro ruminal fermentation characteristics and biohydrogenation of polyunsaturated fatty acids (PUFA). Within the current experiment, three dose levels (300, 600, and 900 mg/L) of essential oils were evaluated using rumen inoculum from three mature Dalagh ewes (58 ± 2.84 kg body weight). The results revealed that the essential oils had a significant impact on gas production, methane and carbon dioxide production, ruminal fermentation parameters, and ruminal biohydrogenation of dietary PUFAs. The essential oil treatments resulted in reduced gas production compared with the control group. Methane production was significantly reduced by all doses of the essential oils, with the highest dose of CLO resulting in the lowest methane production. In addition, the essential oils affected ruminal fermentation parameters, including pH, ammonia concentration, and production of total volatile fatty acids. Promising modifications in ruminal biohydrogenation of PUFAs and the profile of fatty acids were also observed in the current study. These findings suggest that SAG, Pin, and CLO hold promise in mitigating methane emissions and improve the nutritional value of ruminant products. Further investigation is required to evaluate their effectiveness in practical feeding strategies for livestock.

This study presents a novel approach that will address escalating demands for water and cooling in regions vulnerable to climate change through the proposal of an optimal integrated cooling–freshwater cogeneration system powered by renewable energy sources. Comprising three subsystems (integrated multi-effect evaporation distillation, absorption heat pump, and vapor compression refrigeration (MAV); renewable energy unit incorporating solar panels, wind turbines, batteries, and hydrogen facilities (RHP/BH); and combined heat and power (CHP)), the system aims to produce both cooling and freshwater. By recovering cooling from combined desalination and refrigeration subsystems to chill the air taken into the gas turbine compressor, the system maximizes efficiency. Through the recovery of waste heat and employing an integrated thermo-environ-economic framework, a novel objective function, termed modified total annual cost (MTAC), is introduced for optimization. Using a genetic algorithm, parametric iterative optimization minimizes the MTAC. The results reveal that under optimum conditions, the MAV, RHP/BH, and CHP subsystems account for 67%, 58%, and 100% of total annual, exergy destruction, and environmental costs, respectively. Notably, the system exhibits lower sensitivity to fuel prices than renewable energy sources, suggesting a need for future research that will incorporate dynamic product prices and greater fuel consumption to produce enhanced operational robustness.

Household energy consumption is influenced by a variety of factors, including climate, demographics, and socio-economic conditions. This study is a review based on clustering analysis of data from the 2019 Household Budget Survey in Turkey, and explores the role of dwelling structure, household habits, and possessions as indicators of energy patterns and preferences within distinct household groups contributing to Sustainable Development Goals 1, 7, and 12. The data analysis identifies three distinct clusters with specific features that set them apart. The Urban Majority cluster represents densely populated urban areas where natural gas is a preferred fuel source, and parquet and ceramic tiles are common flooring materials. The Deprived-like Remote Residents cluster portrays areas with less access to natural gas, where wood and coal are frequently used for heating, and the Urban Comfort-Seekers cluster highlights urban areas with high comfort levels, featuring natural gas, floor heating, and various amenities. These clusters reflect energy consumption patterns and social aspects related to poverty and habits. They indicate that Turkey’s energy preferences are closely linked to accessibility, user-friendliness, and affordability. Urban households prioritize comfort, while rural areas are more resource-constrained, and contextual factors like location and possessions play a vital role in energy preferences.