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This study aims to examine the impact of coal energy consumption on the economic progress in Pakistan by using annual time series data during 1972–2019. Three-unit root tests were employed to rectify the variables' stationarity. The quantile regression approach with the extension of cointegration regression test was utilized to check the variables interaction with the economic progress. The outcomes of the quantile regression uncover that coal energy consumption in power sector and coal energy consumption in brick kilns have adverse influence to the economic progress, while total coal energy consumption has a productive association with the economic progress. Similarly, the findings of cointegration regression analysis uncover that via FMOLS (Fully Modified Least Squares) and DOLS (Dynamic Least Squares) that variables coal energy consumption in power sector and brick kilns have an adverse connection with the economic progress, while total coal energy consumption uncover a productive linkage to the economic progress in Pakistan. Pakistan is still facing a deep energy crisis because of the lack of energy production from cheap sources. New possible policies are required in this direction to improve the energy sector by paying more attention to the alternative energy sources to foster the economic progress. [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 accumulation of carbon dioxide in the atmosphere has surged over the years as a consequence of diverse humans activities such as deforestation and farming, in particular. The rapidly growing agriculture and farm mechanization have contributed to substantial increases in energy use and carbon dioxide emissions across the globe. It is hypothesized that agriculture significantly contributes to a country's economy to which China is no exception. Hence, the main intention of the current study was to explore the asymmetrical influences of cereal crop production, forestry production, and economic progress on CO 2 emissions in China between 1970 and 2017. The non-linear ARDL (Autoregressive Distributed Lag) bounds testing method was used to determine the short- and long-run dynamics linked with positive and negative shocks to the explanatory variables. The findings indicate that positive shocks to cereal crop production deteriorate the atmospheric quality by intensifying carbon dioxide emissions only in the long run, while the impacts of negative shocks in this regard are statistically insignificant. Ironically, shocks to forestry do not exhibit any significant impact on China's carbon dioxide emission levels. Moreover, carbon dioxide emissions demonstrate a strong progressive association with the positive shocks to energy resources utilized within the Chinese economy. Additionally, positive and negative shocks to economic progress are evidenced to boost and reduce the carbon dioxide emission figures in the long run. Lastly, negative shocks to livestock production are witnessed to increase carbon dioxide emissions only in the short run. Hence, for achieving the Chinese carbon-neutrality agenda, it is recommended to prioritize the use of renewable energy resources, particularly for producing cereal crops, in order to curb carbon dioxide emissions in China. Simultaneously, the Chinese economic growth policies should integrate environmentally-friendly schemes to counter the adversative environmental influences related to the economic progress in China. • The environmental impacts of cereal crops and forestry production are assessed. • The environmental impacts of livestock production are assessed. • Positive shocks to cereal crops production boost CO 2 emissions. • Negative and positive shocks to economic progress reduce and boost CO 2 emissions. • Positive shocks to energy use boost CO 2 emissions. [ABSTRACT FROM AUTHOR]