Examining the carbon emissions and climate impacts on main agricultural crops production and land use: updated evidence from Pakistan

The effect of climate change on agricultural production in Iran

The issue of climate change caused by global warming has become a major concern and challenge around the world, requiring comprehensive countermeasures. Agriculture is the most affected part of climate change and Iran's agriculture economy is at risk because of hot and dry and damages due global climate changes. This study investigates the effects of climatic variables temperature, such as precipitation, carbon and dioxide emission on total crop production in Iran from 1971 to 2020 using a fully modified conventional least squares econometric model (FMOLS). Chemical fertilizer and crop area variables, as well as fixed capital in agricultural have machinery, also been used as indicators of technology. The results showed that all variables had a significant effect on production. The average annual temperature and total annual rainfall its had an inverse U-shaped relationship with production, and were significant. Fertilizer and crop area variables had a positive effect, while CO2 had a negative relationship on total crop production in Iran. The findings of this study can be used to provide strategic plans for policymakers in the face of climate change. It is suggested that the government invest more in the mechanization of the agricultural sector and provide facilities and credits with priority given to farmers' education and the use of temperature-resistant varieties, and also act regionally against climate change.

Do the asymmetric effects of eco-digitalization amidst energy transition make or mar the strides toward environmental sustainability in the USA?

The present era faces adverse effects of the strides recorded in economic advancements of the prior generations thus leading the present generation to growth dilemma. Consequently, there is a conscientious consideration for the ecological effects of economic growth. To resolve the preceding issue, due consideration must be given to harmless growth of which eco-digitalization, green financing, green technology, energy transition, and regularity quality are key determinants. Despite the aforesaid importance, empirical studies advancing this nexus are scarce. Hence, this study contributes to environment empirics by providing empirical evidence for the impacts of the highlighted indicators on sustainable environment in the USA. The study explores quarterly data from 1996Q1 to 2019Q4 based on the novel non-linear autoregressive distributed lag (ARDL) model. The pretests' outcomes show that long-run nexus exists among the variables, whereas the Zivot-Andrew uncovers breakpoint years in the observations. The main findings show that eco-digitalization, green financing, green technology, and renewable energy promote sustainable environment. On the flip side, non-renewable energy and regulatory quality hinder the pathways to sustaining the environment in the USA. Robustness analyses conducted based on FMOL, DOLS, and CCR provide substantial support and validity for the main results. Furthermore, the causality nexus lends empirical support for the existence of bidirectional and unidirectional causalities in the empirical model. Policy insights that drive the paths to sustainability in the US are suggested based on the findings.

Measuring climate change's impact on different sugarcane varieties production in the South of Goiás

A crucial aspect analysed during the last years, aiming to improve sugarcane production, is the impact of climate change on sugarcane productivity. One of the strategies to mitigate climate change's impact on sugarcane yield is the development of new varieties known to positively affect crop production. This paper analysed how climate change impacts sugarcane production regarding the different planted varieties. Data regarding sugarcane harvest were collected from a cooperative in the south of Goiás state-Brazil, the second biggest national sugarcane producer. Results indicate that climate impact on sugarcane yield is irrelevant when controlling for different varieties. Considering the results presented in this work, the Brazilian government should keep the incentives for the development of new sugarcane varieties and, at the same time, spur sugarcane producers to use the new sugarcane varieties. The results imply that if the variety is correctly chosen, sugarcane can be produced without harming the environment, contributing to reaching SDG 15. Moreover, it is less probable that an adverse climatic event will destroy the planted area, preventing sugarcane producers from severe loss and contributing to achieving SDGs number 1 and 2.

Bibliometrics of the nexus between food security and carbon emissions: hotspots and trends

With the growth of global food demand, agricultural carbon emissions caused by agricultural production have become a major challenge in controlling global warming. However, a systematic and visual literature review of food security and carbon emissions (FSCE) is still lacking, and there is a lack of exploration on the balanced path between ensuring food security and realizing carbon emission reduction. Based on 872 articles related to FSCE in the Web of Science (WOS) core database, this paper used CiteSpace and VOSviewer bibliometric software to analyze the relevant research focus and trends. This study found that developed countries dominated the research in this field, and the quantity, quality, and intensity of their authors, institutions, and cooperation among countries are higher than those of developing countries. Although the intensity of interdisciplinary cooperation has increased, it remains at a low level. Since 2007, the number of papers published in this field has increased significantly, and the research perspectives have diversified. Moreover, the research theme continues to expand with the core of "food security," involving the impact of climate change, crop production and food security, soil carbon sequestration, and farmers' livelihood sustainability. In addition, food production, food transportation, and food loss reduction are key paths that need to be balanced to ensure global food security and realize carbon emission reduction, and how to promote "economic growth" under the constraints of FSCE will be a future research hotspot.

The relationship between environmental degradation, agricultural crops, and livestock production in Somalia

Climate change is an imminent threat to both developing and developed countries. Various determinants of climate change have been discovered in the literature including, inter alia, the agriculture sector. To this end, this study models the role of agricultural crops - maize, sesame, sorghum, and wheat productions - and livestock production in environmental degradation in Somalia for the period of 1985 to 2017. The study applied the autoregressive distributed lag model (ARDL) for the long-run cointegration between the variables, and vector error correction modeling (VECM) for short- and long-run causalities among the variables. The empirical result revealed the presence of a long-run cointegration between environmental degradation, agricultural crops, and livestock production. All the crops and livestock production increase environmental degradation except wheat production which has a constructive role in reducing environmental degradation in the long run. In contrast, the VECM results detected a short-run causality from sorghum to livestock production. Environmental degradation, sesame, sorghum, and wheat productions cause maize production significantly in the short run as well as in the long run. Moreover, sesame production causes sorghum production in the short run. Likewise, a long-run causality is established from environmental degradation, maize, sesame, livestock, and wheat production to sorghum production. However, Somalia policymakers should institute agricultural policies that are not only sustainable for agricultural production practices to meet the growing food demand but also sustainable to the environment.

Impact of Tree Cover Loss on Carbon Emission: A Learning-Based Analysis

Describing the processes leading to deforestation is essential for the development and implementation of the forest policies. In this work, two different learning models were developed in order to identify the best possible model for the assessment of the deforestation causes and trends. We developed autoregressive integrated moving average (ARIMA) model and long short-term memory (LSTM) independently in order to see the trend between tree cover loss and carbon dioxide emission. This study includes the twenty-year data of Pakistan on tree cover loss and carbon emission from the Global Forest Watch (GFW) platform, a known platform to get numerical data. Minimum mean absolute error (MAE) for the prediction of tree cover loss and carbon emission obtained through ARIMA model is 0.89 and 0.95, respectively. The minimum MAE given by LSTM model is 0.33 and 0.43, respectively. There is no such kind of study conducted in order to identify the increase in carbon emission due to tree cover loss most specifically in Pakistan. The results endorsed that one of the main causes of increase in the pollution in the environment in terms of carbon emission is due to tree cover loss.

Spatial-Temporal Characteristics and Influence Factors of Carbon Emission from Livestock Industry in China

Animal husbandry is an important source of carbon emissions. As a large country, China must measure the carbon emissions from animal husbandry to reveal the spatial and temporal characteristics and determine the influencing factors to realize low-carbon animal husbandry and carbon emission reduction. In this paper, the carbon emissions of the livestock industry in each province of China were calculated with the emission coefficient method, considering the temperature change factor. The spatial and temporal characteristics and influencing factors of livestock industry carbon emissions were analyzed using the kernel density model, the spatial autocorrelation model, and the Tobit model. The results indicated that: (1) From 2000 to 2020, carbon emissions from the livestock industry in China experienced four stages: rapid rise, rapid decline, slow rise, and fluctuating decline, with an overall downward trend. Carbon emissions in the eastern and central regions showed a downward trend, while carbon emissions in the western regions showed an upward trend. (2) In terms of time, the relative gap in carbon emissions among the provinces narrowed first and then widened; the spatial agglomeration of carbon emissions from livestock farming in China increased, gradually forming the characteristics of "high agglomeration, low agglomeration", and showing a gradually decreasing pattern from northwest to southeast. (3) Nationwide, industrial structure, population, and farmers' income levels have had significantly promoting effects on animal husbandry carbon emissions, and the urbanization and agricultural mechanization levels have had significant inhibitory effects on carbon emissions. Finally, based on the above factors, it can be concluded that recognizing the location conditions, promoting the upgrading of industrial structures, and adopting differentiated strategies will help to promote the reduction in carbon emissions in animal husbandry and achieve its high-quality development.

Towards a sustainable food production: modelling the impacts of climate change on maize and soybean production in Ghana

The Ghanaian economy relies heavily on maize and soybean production. The entire maize and soybean production system is low-tech, making it extremely susceptible to environmental factors. As a result, climate change and variability have an influence on agricultural production, such as maize and soybean yields. Therefore, the study's ultimate purpose was to analyze the influence of CO2 emissions, precipitation, domestic credit, and fertilizer consumption on maize and soybean productivity in Ghana by utilizing the newly constructed dynamic simulated autoregressive distributed lag (ARDL) model for the period 1990 to 2020. The findings indicated that climate change enhances maize and soybean yields in Ghana in both the short run and long run. Also, the results from the frequency domain causality showed that climate change causes maize and soybean yield in the long-run. These outcomes were robust to the use of the ordinary least squares estimator and the impulse response technique. The findings show that crop and water management strategies, as well as information availability, should be considered in food production to improve resistance to climate change and adverse climatic circumstances.

Transportation moderation in agricultural sector sustainability - a robust global perspective

The agriculture sector creates nearly a quarter of the total GHG emissions globally as production and transportation activities in the agriculture sector mostly use fossil fuels, creating carbon emissions. In this regard, it is highly important to study the environmental sustainability of agriculture sector growth by using the theory of environmental Kuznets curve (EKC). Furthermore, this research study is aimed to assess the moderation role of transportation competitiveness in determining the carbon emissions of transportation sector by using agriculture sector value addition. The study uses panel quantile regression technique for data analysis of 121 countries by covering time period from 2008 to 2018. The study results validated the agricultural EKC across four different quantile groups based on carbon emissions of transport sector. The moderation of transportation competitiveness is observed in changing the turning point and flattening of agricultural EKC indicating the early achievement of maturity. The quality of institutions and planned increase of population can help reduce carbon emissions of transportation sector. The moderation of transportation competitiveness implicates the importance of planning and efficiently operating the transportation sector to mitigate carbon emissions.

The nexuses between carbon emissions, agriculture production efficiency, research and development, and government effectiveness: evidence from major agriculture-producing countries

Agriculture production efficiency and carbon emissions have become the challenge for the sustainable world. Therefore, this study explores the relationships between agriculture production and carbon emissions in major (seventeen) agriculture-producing countries over the time period of 1996-2018. Data envelopment analysis is applied to estimate the efficiency of agriculture sector production. The results suggested that the USA, Russia, Korea, Japan, and Italy were efficient agriculture production. Among BRICS countries, China (0.183), India (0.378), and Brazil (0.382) are far off to Russia in Agriculture production efficiency. Growth of research and development investment by 1% increases agriculture production efficiency by 0.0773 (full panel), 0.119 (developing), and 0.0245(developed), respectively. Carbon emissions are also significantly decreased by research and development investment. However, the effectiveness of the government on carbon emissions can be both positive and negative in developed and developing countries' cases. Nevertheless, both developed and developing governments are concerned about increasing agriculture production efficiency. The shape validity of the environmental Kuznets curve is also varied between the developed and developing groups. From the policy perspective, it is suggested that the government should reform its policies to avoid carbon activities and enhance the agricultural sector on a priority basis to increase the efficiency of current raw resources, generate jobs, and reap a variety of other advantages.

People's attitude towards willingness-to-pay for environmental protection in Pakistan

Recent environmental research has found that people with higher incomes and in more developed countries are more willing to pay (WTP) to protect their environment than people in developing countries. Based on this assumption, the study investigated Pakistani citizens' attitudes toward environmental protection, precisely their willingness to pay higher prices and taxes to preserve the natural environment. The research was carried out in three Punjab cities (Hasan Abdal, Wah, and Taxila) and four KPK cities (Abbottabad, Havelian, Mansehra, and Haripur). The selected cities are home to knowledgeable people who work in various universities, schools, hospitals, medical colleges, and nearby industrial estates and have a sense of environmental protection and can understand the healthcare issues related to environmental damages. The survey was divided into two sections: one about the participants' socio-demographic information and the other about people's willingness to pay higher prices and taxes to protect the environment. Four hundred and sixty-two people took part in the survey, and the data were analyzed using the bootstrap regression approach. The results show that gender has a detrimental impact, although population density and education positively impact a country's willingness to pay for environmental protection (WTPEP). Women are more likely to engage in pro-environmental behavior than men, resulting in disparities in their perceptions of male and female respondents in the study. People who live in crowded places tend to pay for environmental protection because of population density, healthcare difficulties, and air pollution. The respondents are well-versed in the externalities of environmental pollution; they are hopeful about paying for a better healthcare environment. Other criteria, such as the respondent's income, health status, total pollution level in the country, and per capita income, enable respondents to pay for environmental preservation to achieve long-term sustainable growth. The government must embrace air quality regulations and empower its citizens by offering better healthcare services since they are enthusiastic about paying higher taxes and fees to protect the environment.

Do Agriculture Technologies Influence Carbon Emissions in Pakistan? Evidence based on ARDL technique

Pakistan is an agrarian country, and the usage of agriculture technologies has increased in this country over the period of time. Extensive use of agriculture technologies may have detrimental impact of environment quality through an increase in carbon dioxide emissions. This study examines the impact of agriculture technologies on carbon emissions in Pakistan by using the annual time series data for the period 1973-2018. For long-run and short-run analysis, autoregressive distributed lag model is applied and the results reveal that cointegration exists among the variables. Long-run results show a significant positive impact of pesticide and economic growth on carbon emission, whereas short-run results confirm the positive effect of economic growth on carbon emissions in Pakistan. This study has important policy implications, such as to increase sustainable economic growth through agriculture sector; there is a need to introduce green technologies that produce less carbon emissions.

Tracking the effect of climatic and non-climatic elements on rice production in Pakistan using the ARDL approach

The present study aims to investigate the effect of climatic and non-climatic factors on rice production by employing an annual time series data from the period of 1970 to 2018. The study employed an ARDL (Autoregressive Distributed Lag) approach, and the long-term equilibrium linkages between the variables have been discovered. Additionally, the study also used a regression model to determine the robustness for the authentication of results. The Fully Modified Ordinary Least Squares (FMOLS), Canonical Cointegration Regression (CCR) methods, and the VECM (Vector Error Correction Model) technique confirmed the long-run causal relationships amid the variables. The empirical results further revealed that climatic factors including annual temperature negatively affect the rice crop production, while carbon dioxide emission positively influenced via long-run. Similarly, non-climatic factors like area under rice crop, fertilizer consumption, labor force, and water availability affect the rice production positively in the long-run analysis. Finally, the pairwise Granger causality test revealed that both climatic and non-climatic variables had a substantial impact on rice yield in Pakistan. Based on the study's findings, the government and policy makers should formulate alleviation polices to tackle with harsh effects of climate change and consistent adoption of measures to secure overall agricultural production including rice crop because it is a country stable food.

Global warming and export competitiveness of agriculture sector: evidence from heterogeneous econometric analysis of Pakistan

The increase in average annual temperature due to greenhouse gases emission is posing threat to the agriculture sector across the globe. Pakistan is labor abundant agrarian country that heavily depends on the agriculture sector for food, employment, and raw material for industries. This study is a preliminary investigation that explores the effect of increasing average annual temperature on the competitiveness of 24 major agricultural exports from 2003 to 2020. The revealed export advantage (RXA) is used to explore the competitive performance of selected agricultural exports, which is then normalized to examine the effect of increasing average annual temperature along with official exchange rate, urbanization, and globalization. The panel fixed-effect model with heteroscedasticity consistent robust standard error recommended by White (Econometrica 48(4):817-838, 1980) is used to explore model estimates, whereas the robustness check has been performed by using heteroscedasticity and multicollinearity consistent robust standard error model of Driscoll and Kaary (Rev Econ Stat 80(4):549-559, 1998). The estimated result reveals that the increasing average annual temperature has a negative but insignificant impact on the export competitiveness of selected agricultural exports. While, urbanization and exchange rate deprecation show a significant negative effect of higher intensity, respectively. Globalization, however, reveals a significant positive impact on the competitiveness of selected agricultural exports. This study, therefore, urges for the development of the agriculture sector by adopting SDGs proposed by the United Nations for sustainable economic growth and development.

How climate change is impacting the major yield crops of Pakistan? an exploration from long- and short-run estimation

This research attempts to evaluate the linkage among climatic change factors such as average temperature and rainfall patterns and non-climatic factors such as the area under major yield crops, fertilizer consumption, and formal credit on major food crop yield from 1985 to 2016 in Pakistan. For the first step, we checked the stationarity of the series by utilizing the unit root tests. An autoregressive distributed lag (ARDL) model was employed to identify the linkages between variables after verifying the properties over a specific period of time. The consequences of this study confirmed the long-run association between climatic and non-climatic factors to the major food crop yield in Pakistan. Furthermore, the outcomes of the study revealed that temperature has a diverse impact on major food crop yields. Whereas, the area under major food crops, average rainfall, fertilizer consumption, and formal credit have a positive impact on major food crop yield in Pakistan. For the second step, we used the Granger causality test to verify the causal linkage for the variables. The outcomes reveal a significant effect of climatic and non-climatic factors on major food crop yield. The bidirectional causality causal associations are found to be significant among variables including average temperature, fertilizer consumption, and formal credit disbursement. The empirical results further indicated that major food crop yields are more affected by climatic factors such as average temperature as compared to non-climatic factors. Based on the study findings, few recommendations are made to cope with factors of climate change. Invent such agricultural-specific adaptation policies for farmers which possess the ability and resilience to tackle climate change. Research and development in agriculture should focus on major varieties of food crops that can endure high temperatures. The agriculture industry will be able to sustain long-term production and distribution efficiency attributable to these strategies.

A change is gonna come: will traditional meat production end?

Recently, the world has faced environmental disasters mainly due to global warming. One of the main reasons for global temperature imbalances is the greenhouse gases (GHG) that soar the atmosphere's heat. The major aim of the current study is to explore whether the livestock population is the main contributor to GHG emission through econometric estimations. In this study, we examine the impact of livestock population with other explanatory variables-GDP per capita, Economic Complexity Index (ECI), ecological balance, and total patent applications-over GHG emission of 25 countries responsible for 76% of GHG emission between 1990 and 2017. To investigate the relationship of variables, Fully modified ordinary least squares (FMOLS) and dynamic ordinary least squares (DOLS) are used, as well as panel causality. Also, the relationship is examined by using the responsiveness scores (RS) approach. The empirical results reveal that all variables have a causal relationship with GHG emission. GDP per capita, ECI, and livestock population enhance the GHG emission whereas square of GDP per capita and ecological balance decline the environmental degradation. The paper demonstrates that the environmental Kuznets curve is valid and supports the literature. Lastly, the RS estimation results reveal that the livestock population is causing higher GHG emissions for all countries in the analysis, contrary to other independent variables. Governments should promote carbon-neutral meat production facilities instead of traditional beef farms to live in a more sustainable world. In the future, countries that invest in research and development (R&D) for less emission meat production will have a comparative advantage in the sustainable international meat market.

The cyclical impact of green and sustainable technology research on carbon dioxide emissions in BRICS economies

This paper explored the asymmetrical relationships between green and sustainable technology research and environmental sustainability among the BRICS states from 1990 to 2018. The data was analyzed by second- and third-generation economic techniques such as slope heterogeneity and cross-section independence test, unit root test, structural break unit root test, panel cointegration with structural breaks cointegration tests, cross-section autoregressive distributed lags technique, augmented mean group, and Dumitrescu-Hurlin panel causality test. First, the results validated a long-run cointegration among variables. Second, the results showed that renewable energy consumption and positive shocks to green and sustainable technology research are proper to mitigate carbon dioxide emissions (short- and long-run). Third, gross domestic product, foreign direct investment, exports, and negative shocks to green and sustainable technology research increase carbon dioxide emissions. Fourth, the nexus between green and sustainable technology research and carbon dioxide emissions was counter-cyclical during economic expansion and contraction periods. Fifth, the impact of positive shocks to green and sustainable technology research on carbon dioxide emissions was more than the impact of negative shocks to green and sustainable technology research on carbon dioxide emissions.