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Climate change has significantly affected agricultural production. As one of China's most important agricultural production regions, the North China Plain (NCP) is subject to climate change. This paper examines the influence of climate change on the wheat and maize yields at household and village levels, using the multilevel model based on a large panel survey dataset in the NCP. The results show that: (i) Extreme weather events (drought and flood) would significantly reduce the wheat and maize yields. So, the governments should establish and improve the emergency service system of disaster warning and encourage farmers to mitigate the adverse effects of disasters. (ii) Over the past three decades, the NCP has experienced climate change that affects its grain production. Therefore, it is imperative to build the farmers' adaptive capacity to climate change. (iii) Spatial variations in crop yield are significantly influenced by the household characteristics and the heterogeneity of village economic conditions. Therefore, in addition to promoting household production, it is necessary to strengthen and promote China's development of the rural collective economy, especially the construction of rural irrigation and drainage infrastructures.

Weather, trade restrictions, rising oil prices, a lack of financial support for farmers, and other factors have contributed to the destabilization of South Asian food security. The purpose of this study is to determine the long-run and short-run relationships between climate change, agricultural credit, renewable energy, and food security for a sample of South Asian countries between 1990 and 2021. The Dynamic Common Correlated technique is utilized for empirical analysis since it directly addresses the issue of cross-sectional dependency while delivering accurate cointegration findings. The study's empirical findings show that climate change reduces food availability and increases the incidence of food insecurity in South Asia. In contrast, the use of renewable energy sources has a positive effect on food security in the short-run but not in the long-run, while the availability of credit to farmers has a positive effect on food security. Findings suggest that South Asian countries may reduce climate change's negative effect on food security by investing in climate services, climate-resilient infrastructure, growing drought-resistant crops, using supplemental reinforced agricultural practices, and improving their weather forecasting capabilities. [ABSTRACT FROM AUTHOR]

Carbon dioxide emission and climatic variation have a detrimental influence on the atmosphere as well as on agriculture production. The key aim of the present study was to investigate the influence of carbon dioxide emission on livestock, cereal crops production, rainfall and temperature in China by utilizing the vector autoregressive model and Granger causality test for the period 1988–2017. Variables stationarity was verified by using ADF, P-P and KPSS unit root tests. The outcomes through long-run dynamics exposed that agriculture value added and rainfall have a positive influence on carbon dioxide emission, while cereal crops production, livestock production and temperature have an adverse interaction with carbon dioxide emission. Similarly, the results of the short-run analysis also demonstrate that agriculture value added, cereal crops production, livestock production, rainfall and temperature have a significant influence on carbon dioxide emission with their p-values (0.0488), (0.0885), (0.0263), (0.0096) and (0.5141) respectively. Furthermore, the Granger causality test outcomes also exposed a unidirectional linkage amid the variables. In order to improve agricultural productivity, the Chinese government should take potential steps to minimize the carbon dioxide emission from various industries that trigger climate change. [ABSTRACT FROM AUTHOR]

Carbon dioxide emission and greenhouse gas emissions are considered core issue in the world that influence agricultural production and also cause climate change. The present study seeks to investigate the linkage of methane emissions, nitrous oxide emissions, carbon dioxide emission, and greenhouse gas emissions with agricultural gross domestic product in China. The long-term association was checked by using an autoregressive distributed lag (ARDL) bounds testing approach, fully modified least squares method, and canonical cointegrating regression analysis. The results from long-run analysis exposed that carbon dioxide emission and greenhouse gas emissions have positive coefficients that demonstrate the long-run linkage with the agricultural gross domestic product having p values of 0.5709 and 0.3751, respectively. Similarly, results also revealed that agricultural methane emissions and agricultural nitrous oxide emissions have a negative association with the agricultural gross domestic product having p values of 0.1737 and 0.0559. China is a huge emitter of CO2 emission and greenhouse gas emissions. Possible conservative policies are required to form the Chinese government to tackle this challenge to decrease CO2 emission in order to increase agricultural production. [ABSTRACT FROM AUTHOR]

Globalization has contributed to several advances in technology including linking people around the globe and driving us to modern economies. With fast economic growth and industrialization progress, the negative impact of globalization on biodiversity can be easily ignored. Globalization is an undeniable factor in our planetary devastation from pollution to global warming and climate change. The major intention of our recent analysis was to examine the globalization, energy consumption, trade, economic growth, and fuel importation to determine the ecological footprint in Pakistan by taking the annual data variables from 1974–2017. A linear ARDL (autoregressive distributed lag) technique with limited information maximum likelihood and linear Gaussian model estimation were utilized to check the variables association. Outcomes show that in the long run, globalization, energy usage, trade, and GDP growth have consistently productive interactions with the ecological footprint, while an examination of fuel importation uncovers an adversative linkage to impacts on the ecological footprint in Pakistan. Similarly, the findings of short-run interactions also reveal that globalization, energy usage, trade, and GDP growth have constructive linkages; however, an examination of fuel importation also uncovers an adversative linkage to impacts on the ecological footprint. The outcomes of limited information maximum likelihood also expose that the variables of globalization, energy usage, trade, and fuel importation have productive linkages, while an examination the GDP growth uncovers an adversative linkage to the ecological footprint. Furthermore, the outcomes of the linear Gaussian model estimation also uncover that globalization and energy usage demonstrate a constructive linkage, while other variables reveal an adverse linkage to the ecological footprint. Environmental pollution is now an emerging issue which causes the climatic variations associated with greenhouse gases emissions. The Pakistani government must adopt new strategies to ensure that CO2 emissions are reduced in order to stimulate economic growth. [ABSTRACT FROM AUTHOR]

[Display omitted] • Devolving the CO 2 emission influence on climatic change, forestry, livestock and crops production. • Forestry, rainfall and temperature exposed a positive effect on CO 2 emission in the long-run analysis. • Forestry, crops production, livestock, population growth, rainfall and temperature also showed a positive effect on CO 2 emission in the short-run dynamics. Global warming is an important issue from the last few decades and causing climate change due to carbon dioxide emission and greenhouse gases emission. The present study's key aim is to decouple the carbon dioxide emission influence on forestry production, crops production, livestock production, energy usage, population growth, temperature and rainfall in Pakistan. Time series data was utilized ranging from 1970 to 2017, and stationarity of the data was verified by using the unit root tests, while vector autoregressive model was applied to demonstrate the dynamic interaction amid study variables. Furthermore, the Granger causality test was applied to check the causal relation amid variables. The long-run dynamics results through the vector autoregressive model show that forestry production, rainfall, and temperature have a constructive effect on carbon dioxide emission, while crops production, livestock production, energy use, and population growth have a negative effect on carbon dioxide emission. Short-run analysis outcomes also demonstrate that forestry production, crops production, livestock production, population growth, rainfall, and the temperature have a positive effect on carbon dioxide emission, while energy usage has an adverse impact on carbon dioxide emission in Pakistan. Similarly, Granger causality test results also exposed that all variables have a unidirectional association. The Pakistani government needs to take the requisite measures to curb carbon dioxide emission in order to improve agricultural production. [ABSTRACT FROM AUTHOR]

The mixed crop–livestock system is a primary source of livelihood in developing countries. Erratic climate changes are severely affecting the livelihoods of people who depend upon mixed crop–livestock production. By employing the livelihood vulnerability index (LVI), the Intergovernmental Panel on Climate Change LVI (LVIIPCC), and the livelihood effect index (LEI), this study evaluated livelihood vulnerability in southern Punjab, Pakistan. The study provides a range of indicators for national and local policy makers to improve resilience in the face of livelihood vulnerability. By incorporating more major components and subcomponents, this study identifies more specific challenges of livelihood vulnerability for future policy directions. It is interesting to find that credit and cash used for crop inputs are critical financial constraints for farmers. From the estimated indicators, this study also provides some specific policy recommendations for the four study districts of Punjab Province. These results are helpful in identifying and highlighting vulnerability determinants and indicators. Initiating and promoting better adaptive capacity and starting resilience projects for households are urgent actions required by donors and governments to reduce the livelihood vulnerability of mixed crop–livestock households in arid and semiarid areas. [ABSTRACT FROM AUTHOR]