Analysis of energy consumption and change structure in major economic sectors of Pakistan.

Studying and analyzing energy consumption and structural changes in Pakistan's major economic sectors is crucial for developing targeted strategies to improve energy efficiency, support sustainable economic growth, and enhance energy security. The logarithmic mean Divisia index (LMDI) method is applied to find the factors' effects that change sector-wise energy consumption from 1990 to 2019. The results show that: (1) the change in mixed energy and sectorial income shows a negative influence, while energy intensity (EI) and population have an increasing trend over the study period. (2) The EI effects of the industrial, agriculture and transport sectors are continuously rising, which is lowering the income potential of each sector. (3) The cumulative values for the industrial, agricultural, and transport sectors increased by 57.3, 5.3, and 79.7 during 2019. Finally, predicted outcomes show that until 2035, the industrial, agriculture, and transport incomes would change by -0.97%, 13%, and 65% if the energy situation remained the same. Moreover, this sector effect is the most crucial contributor to increasing or decreasing energy consumption, and the EI effect plays the dominant role in boosting economic output. Renewable energy technologies and indigenous energy sources can be used to conserve energy and sectorial productivity.

The potential climate benefits of seaweed farming in temperate waters.

Seaweed farming is widely promoted as an approach to mitigating climate change despite limited data on carbon removal pathways and uncertainty around benefits and risks at operational scales. We explored the feasibility of climate change mitigation from seaweed farming by constructing five scenarios spanning a range of industry development in coastal British Columbia, Canada, a temperate region identified as highly suitable for seaweed farming. Depending on growth rates and the fate of farmed seaweed, our scenarios sequestered or avoided between 0.20 and 8.2 Tg CO2e year-1, equivalent to 0.3% and 13% of annual greenhouse gas emissions in BC, respectively. Realisation of climate benefits required seaweed-based products to replace existing, more emissions-intensive products, as marine sequestration was relatively inefficient. Such products were also key to reducing the monetary cost of climate benefits, with product values exceeding production costs in only one of the scenarios we examined. However, model estimates have large uncertainties dominated by seaweed production and emissions avoided, making these key priorities for future research. Our results show that seaweed farming could make an economically feasible contribute to Canada's climate goals if markets for value-added seaweed based products are developed. Moreover, our model demonstrates the possibility for farmers, regulators, and researchers to accurately quantify the climate benefits of seaweed farming in their regional contexts.

Co-designing sustainable biochar business models with sub-Saharan African communities for inclusive socio-economic transformation.

Smallholder farmers in sub-Saharan Africa (SSA) encounter multiple livelihood challenges. Embracing circular bioeconomy principles, particularly considering agricultural and food processing residues, could enable inclusive, locally led, sustainable development pathways within rural communities. Biochar products are one such example of a bio-based material that can be generated using circular principles and deployed for sustainable community development, including among smallholder farmers. This research leverages empirical evidence from four SSA regions to explore the potential of inclusive and sustainable biochar business models, namely: (i) Northern Region, Ghana, (ii) Yamoussoukro, Côte d'Ivoire, (iii) Casamance, Senegal, and (iv) Western Region, Uganda. Co-creation workshops using the Triple-Layered Business Model Canvas framework were carried out in each region with local stakeholders to evaluate the social, ecological, and economic implications of four locally relevant biochar applications: water filtration, biogas purification, soil amendment, and cooking fuel briquettes. Data was analysed at an aggregate level for all regions and applications. The study describes this consolidated biochar business model and examines the implications for SSA communities. The resulting sustainable bio-based business model can guide value chain actors and policymakers in SSA communities towards rural sustainable development with a better understanding of the needs, opportunities, challenges, and impacts of biochar-based value chain development.

Analysis of food system drivers of deforestation highlights foreign direct investments and urbanization as threats to tropical forests.

Approximately 90% of global forest cover changes between 2000 and 2018 were attributable to agricultural expansion, making food production the leading direct driver of deforestation. While previous studies have focused on the interaction between human and environmental systems, limited research has explored deforestation from a food system perspective. This study analyzes the drivers of deforestation in 40 tropical and subtropical countries (2004-2021) through the lenses of consumption/demand, production/supply and trade/distribution using Extreme Gradient Boosting (XGBoost) models. Our models explained a substantial portion of deforestation variability globally (R2 = 0.74) and in Asia (R2 = 0.81) and Latin America (R2 = 0.73). The results indicate that trade- and demand-side dynamics, specifically foreign direct investments and urban population growth, play key roles in influencing deforestation trends at these scales, suggesting that food system-based interventions could be effective in mitigating deforestation. Conversely, the model for Africa showed weaker explanatory power (R2 = 0.30), suggesting that factors beyond the food system may play a larger role in this region. Our findings highlight the importance of targeting trade- and demand-side dynamics to reduce deforestation and how interventions within the food system could synergistically contribute to achieving sustainable development goals, such as climate action, life on land and zero hunger.

Examining the U-shaped relationship between non-agricultural sources water pollution and the urban-rural income gap.

Determining how the economy and society interact with the environment of water quality is essential to determining the financial impact of green development. Based on China's provincial panel data from 2010 to 2021, this research considers non-agricultural sources of water pollution (NASWP) as a negative factor of production, investigates its influence on the urban-rural divide, and explains the mechanism of action. The empirical results show that there is a significant correlation between NASWP and the urban-rural gap, with a "U-shaped" relationship between the two. Water pollution first reduces and then increases the urban-rural income gap, and the results are robust after considering endogeneity. Mechanistic research demonstrates that NASWP cause a loss in food output, which in combination with changes in food prices and food subsidy programs impacts the incomes of rural dwellers, thereby having an influence on the urban-rural income gap. Using the threshold effect model, it is discovered that under the combined influence of agricultural mechanization and food subsidy policy, the relationship between NASWP and urban-rural income divide exhibits an U-shape in areas with high agricultural mechanization and an "inverted U" shape in areas with low agricultural mechanization.

Climate impacts of alternative beef production systems depend on the functional unit used: Weight or monetary value.

Beef production has been identified as a significant source of anthropogenic greenhouse gas (GHG) emissions in the agricultural sector. United States and Canada account for about a quarter of the world's beef supply. To compare the GHG emission contributions of alternative beef production systems, we conducted a meta-analysis of 32 studies that were conducted between 2001 and 2023. Results indicated that GHG emissions from beef production in North America varied almost fourfold from 10.2 to 37.6 with an average of 21.4 kg CO2e/kg carcass weight (CW). Studies that considered soil C sequestration (C-seq) reported the highest mitigation potential in GHG emissions (80%), followed by growth enhancement technology (16%), diet modification (6%), and grazing management improvement (7%). Our study highlights the implications of using carbon intensity per economic activity (i.e., GHG emissions per monetary unit), compared to the more common metric of intensity on per weight of product basis (GHG emissions per kg CW) for comparisons across differentiated beef cattle products. While a positive association was found between the proportion of lifespan on grassland and the conventional weight-based indicator, grass-finished beef was found to have lower carbon intensity per economic activity than feedlot-finished beef. Our study emphasizes the need to incorporate land use and management effects and soil C-seq as fundamental aspects of beef GHG emissions and mitigation assessments.

Can digital financial inclusion converge the regional agricultural carbon emissions intensity gap?

To explore whether digital finance can reduce agricultural carbon emissions, promote regional convergence, and foster inclusivity in rural revitalization and shared prosperity, this paper uses the provincial-level index of digital financial inclusion to analyze the impact of digital financial inclusion on the intensity of agricultural carbon emissions and the Degum Gini coefficient (D-Gini coefficient) of regional carbon emission intensity in 30 sample provinces from 2010 to 2020. It examines the mechanism of the impact of digital financial inclusion on both variables to understand the underlying factors better. The main conclusions are as follows: (1) Digital financial inclusion significantly reduces the intensity of agricultural carbon emissions and narrows the gap in carbon emission intensity between regions. (2) The unconditional quantile regression coefficients show that the negative coefficients of the digital financial inclusion index and the three-dimensional indices decrease with increasing quantiles. However, the significant effects vary significantly at different quantiles. (3) Technological progress and the government's ability to allocate financial resources play a significant mediating role, and the income gap between urban and rural areas can be further narrowed, as well as the carbon emission intensity gap between provinces. The empirical results are robust and proven by replacing the econometric analysis method, changing the core variables, and other methods.

Factors affecting onion production: An empirical study in the Raya Kobo district, Amhara regional state, Ethiopia.

Onion is a vital vegetable crop in Ethiopia, with significant economic and health benefits. However, its production trend is not consistent, with periods of increase and decrease; and its productivity in the country falls far below its potential. As a result, farmers are not yet fully benefited from onion production. Thus, this study was initiated to identify the factors influencing onion production in the Raya Kobo District of Amhara Regional State of Ethiopia. Data was collected from 189 onion-producing farmers through household surveys, and both descriptive and econometric techniques were used for analysis. The study found significant variation in onion production among farmers, with lower levels compared to national and international averages. Factors such as gender, education level, experience, labor force, land size, access to extension services, irrigation water, land plough frequency, and fertilizer availability positively impact onion production. However, excessive fertilizer use was found to have a negative effect. The study also identified challenges faced by farmers, including input shortages, high costs, diseases, labor issues, soil infertility, and storage knowledge gaps. The study recommends policymakers and stakeholders to utilize these findings to develop effective policies and interventions that can enhance onion production, benefiting farmers and improving the overall onion production.

Accelerating agricultural innovation in Latin America and the Caribbean: The crucial role of public investment data in science.

In the face of rapid global changes, the agricultural sector in Latin America and the Caribbean (LAC) stands at a crossroads. The region, known for its rich biodiversity and considerable agricultural output, is increasingly challenged by climate change, political and economic pressures, and the need for efficient and effective innovations to sustain the transformation of agrifood systems toward more sustainable practices.

Sensor based precise nitrogen application augmented productivity and profitability of mustard (Brassica juncea L.).

Unremitting decline in crop productivity and nutrient recovery are resulted due to dearth of need based fertilizer recommendation over blanket application apart from nitrogen pollution in several means. An advance nutrient management tactic, GreenSeeker (GS) has developed and used in many field crops following the principle of four "R" (right source, right amount at right time, and place) nutrients stewardship technologies. But no studies have been conducted for evaluation of GS in mustard for improving productivity, profitability and nutrient use efficiency (NUE) while minimizing environmental risks. With this objective, a study was planned to conduct an experiment in rabi season of 2021-22 and 2022-23 to assess optical sensor based nitrogen management in mustard over blanket recommendation. The experiment was comprised of ten N treatments including control in randomized block design in triplicates. Research findings indicated that application of GreenSeeker based N significantly improved all growth traits and yield parameters in Brassica juncea L. Per cent enhancement in seed yield, net monetary returns and benefit-cost ratio was higher as 19.3 and 64.5%, 125.1 & 36.2% and 58.8 & 24.4%, respectively under GS based multi split N application over RDF and control. Further, real time N management with GS acquired higher crop production efficiency (CPE) (19.9 kg/day) with lesser cost/kg production (Rs 15.7/kg). Split application of N using GS increased oil yield by 79.9 and 26% over control and recommended dose of fertilizer (RDF) with maximum oil content (42.3%), and increases soil organic carbon (SOC) content by 16.1% from its initial value. Moreover, GS crop sensor could be the probable solution to minimize the crop nitrogen requirement by 15-20% with a yield enhancement of about 18.7% over RDF.

Impact of economic indicators on rice production: A machine learning approach in Sri Lanka.

Rice is a crucial crop in Sri Lanka, influencing both its agricultural and economic landscapes. This study delves into the complex interplay between economic indicators and rice production, aiming to uncover correlations and build prediction models using machine learning techniques. The dataset, spanning from 1960 to 2020, includes key economic variables such as GDP, inflation rate, manufacturing output, population, population growth rate, imports, arable land area, military expenditure, and rice production. The study's findings reveal the significant influence of economic factors on rice production in Sri Lanka. Machine learning models, including Linear Regression, Support Vector Machines, Ensemble methods, and Gaussian Process Regression, demonstrate strong predictive accuracy in forecasting rice production based on economic indicators. These results underscore the importance of economic indicators in shaping rice production outcomes and highlight the potential of machine learning in predicting agricultural trends. The study suggests avenues for future research, such as exploring regional variations and refining models based on ongoing data collection.

Unlocking sustainable livestock production potential in the Colombian Amazon through paddock division and gender inclusivity.

Low-emissions livestock production can be achieved through scaling production systems integrating trees, forages, and livestock within the same area. Such systems are known as silvopastoral production systems (SPS). However, despite SPS reported benefits, adoption rates globally remain low. This paper, therefore, aims to inform land use policy oriented towards increasing SPS adoption. This study intends to capture this by assessing SPS adoption benefits, identifying determinants of SPS adoption, and thus to contribute to policy for scaling low-emissions livestock production. Data was collected on socioeconomic status, livestock farming technical and economic indicators, and farm and paddock practices through farm-level surveys in four municipalities in the Amazon Piedmont of Colombia. Unlike previous studies that assume homogeneous farm management, when in fact, it is heterogeneous, this study assessed SPS adoption determinants using the paddock (n = 2819) as the unit of analysis. This methodological approach is consistent with paddock-level land use decisions taken by farmers based on socioeconomic and biophysical factors such as soil financial resources, type, and topography. The methodological approach allows us to provide new insights into the determinant of adopting SPS and an understanding of intra-farm level land use decisions. The results show that the adoption of SPS at both paddocks and farm levels in Caquetá is low. The main factors associated with higher SPS adoption levels at the paddock level are framed in gender, resources, and knowledge. We observe that women are more motivated to conserve the environment. Cattle paddocks managed by women, smaller in size, and those with more SPS-related projects show a tendency for medium or high SPS adoption. Furthermore, the positive relationship between access to credit and SPS adoption emphasizes the importance of financial resources tailored to SPS projects. Enhancing gender roles, improving access to finance in land use, and providing training programs on SPS systems can contribute to low-emission livestock production in Colombia. This research paper highlights the significance of implementing diverse management strategies and reaching out to farmers not involved in SPS projects. It emphasizes investments in low-emission livestock production, especially for female heads of households. This approach recognizes the broader benefits of SPS, beyond production and financial gains, promoting the division of paddocks and the adoption of SPS.

How can the digital economy reduce carbon emissions? Empirical evidence from China.

China is transitioning into the digital economy era. The advancement of the digital economy could offer a fresh mechanism to attain carbon peak and carbon neutrality objectives. Applications of the digital economy, such as smart energy management, intelligent transport systems, and digital agricultural technologies, have significantly reduced carbon emissions by optimizing resource use, reducing energy waste, and improving production efficiency. This research does so by devising a theoretical model that looks into the multi-faceted power of the digital economy under a two-sector paradigm. Utilising a panel model, a mediation effect model and a spatial Durbin model to assess the digital economy's power on carbon emissions. This research has determined that the digital economy can significantly diminish carbon emissions, with green tech innovations and industrial transformation being key contributors. The spatial spillover effect was used for the digital economy to aid in lowering carbon emissions in adjacent districts and upgrading better environmental stewardship. The influence of the digital economy has better performance in lowering carbon emissions in mid-western China than in the eastern area. This paper deepens understanding of the drivers of low-carbon growth and the significance, mechanism and regional disparities of the digital economy's effect on reducing carbon emissions. It offers valuable policy insights and guidance for globally achieving digital economy growth, reducing carbon emissions and reaching carbon peak and neutrality goals.

Landscape features support natural pest control and farm income when pesticide application is reduced.

Future trajectories of agricultural productivity need to incorporate environmental targets, including the reduction of pesticides use. Landscape features supporting natural pest control (LF-NPC) offer a nature-based solution that can serve as a partial substitute for synthetic pesticides, thereby supporting future productivity levels. Here, we introduce a novel approach to quantify the contribution of LF-NPC to agricultural yields and its associated economic value to crop production in a broad-scale context. Using the European Union as case study, we combine granular farm-level data, a spatially explicit map of LF-NPC potential, and a regional agro-economic supply and market model. The results reveal that farms located in areas characterized by higher LF-NPC potential experience lower productivity losses in a context of reduced synthetic pesticides use. Our analysis suggests that LF-NPC reduces yield gaps on average by four percentage points, and increases income by a similar magnitude. These results highlight the significance of LF-NPC for agricultural production and income, and provide a valuable reference point for farmers and policymakers aiming to successfully invest in landscape features to achieve pesticides reduction targets.

Cocoa, livelihoods, and deforestation within the Tridom landscape in the Congo Basin: A spatial analysis.

In the context of emerging international trade regulations on deforestation-free commodities, the drivers of households' deforestation in conservation landscapes are of interest. The role of households' livelihood strategies including cocoa production, and the effects of human-elephant conflict are investigated. Using a unique dataset from a survey of 1035 households in the Tridom landscape in the Congo basin, the spatial autoregressive model shows that: (1) Households imitate the deforestation decisions of their neighbors; (2) A marginally higher income from cocoa production-based livelihood portfolios is associated with six to seven times higher deforestation compared to other livelihood strategies with a significant spillover effect on neighboring households' deforestation. The increase in income, mainly from cocoa production-based livelihoods in open-access systems can have a negative effect on forests. Households with a higher share of auto-consumption are associated with lower deforestation. If economic development brings better market access and lower auto-consumption shares, this is likely to positively influence deforestation. Without proper land use planning/zoning associated with incentives, promoting sustainable agriculture, such as complex cocoa agroforestry systems, may lead to forest degradation and deforestation.

Alternative crop residue management practices to mitigate the environmental and economic impacts of open burning of agricultural residues.

Deliberate open burning of crop residues emits greenhouse gases and toxic pollutants into the atmosphere. This study investigates the environmental impacts (global warming potential, GWP) and economic impacts (net cash flow) of nine agricultural residue management schemes, including open burning, fertilizer production, and biochar production for corn residue, rice straw, and sugarcane leaves. The environmental assessment shows that, except the open burning schemes, fossil fuel consumption is the main contributor of the GWP impact. The fertilizer and biochar schemes reduce the GWP impact including black carbon by 1.88-1.96 and 2.46-3.22 times compared to open burning. The biochar schemes have the lowest GWP (- 1833.19 to - 1473.21 kg CO2-eq/ton). The economic assessment outcomes reveal that the biochar schemes have the highest net cash flow (222.72-889.31 US$2022/ton or 1258.15-13409.16 US$2022/ha). The expenditures of open burning are practically zero, while the biochar schemes are the most costly to operate. The most preferable agricultural residue management type is the biochar production, given the lowest GWP impact and the highest net cash flow. To discourage open burning, the government should tailor the government assistance programs to the needs of the farmers and make the financial assistance more accessible.

Cover crops support the climate change mitigation potential of agroecosystems.

Cover crops have the potential to mitigate climate change by reducing negative impacts of agriculture on ecosystems. This study is first to quantify the net climate change mitigation impact of cover crops including land-use effects. A systematic literature and data review was conducted to identify major drivers for climate benefits and costs of cover crops in maize (Zea maize L.) production systems. The results indicate that cover crops lead to a net climate change mitigation impact (NCCMI) of 3.30 Mg CO2e ha-1 a-1. We created four scenarios with different impact weights of the drivers and all of them showing a positive NCCMI. Carbon land benefit, the carbon opportunity costs based on maize yield gains following cover crops, is the major contributor to the NCCMI (34.5% of all benefits). Carbon sequestration is the second largest contributor (33.8%). The climate costs of cover crops are mainly dominated by emissions from their seed production and foregone benefits due to land use for cover crops seeds. However, these two costs account for only 15.8% of the benefits. Extrapolating these results, planting cover crops before all maize acreage in the EU results in a climate change mitigation of 49.80 million Mg CO2e a-1, which is equivalent to 13.0% of the EU's agricultural emissions. This study highlights the importance of incorporating cover crops into sustainable cropping systems to minimize the agricultural impact to climate change.

Cost-competitive decentralized ammonia fertilizer production can increase food security.

The current centralized configuration of the ammonia industry makes the production of nitrogen fertilizers susceptible to the volatility of fossil fuel prices and involves complex supply chains with long-distance transport costs. An alternative consists of on-site decentralized ammonia production using small modular technologies, such as electric Haber-Bosch or electrocatalytic reduction. Here we evaluate the cost-competitiveness of producing low-carbon ammonia at the farm scale, from a solar agrivoltaic system, or using electricity from the grid, within a novel global fertilizer industry. Projected costs for decentralized ammonia production are compared with historical market prices from centralized production. We find that the cost-competitiveness of decentralized production relies on transport costs and supply chain disruptions. Taking both factors into account, decentralized production could achieve cost-competitiveness for up to 96% of the global ammonia demand by 2030. These results show the potential of decentralized ammonia technologies in revolutionizing the fertilizer industry, particularly in regions facing food insecurity.

Characteristics and prediction of agricultural ecological efficiency for coordination between economy and environment.

Agricultural ecological efficiency is an important tool with which to measure the coordination of the sustainable development of agricultural economies and ecological environments. In this paper, a super-efficiency slacks-based measures model was used to measure the agricultural ecological efficiency in Hebei Province. The characteristics of spatial and temporal evolution patterns were explored using a spatial Markov transfer matrix. The results showed that (i) based on measurements, the agricultural ecological efficiency in Hebei Province showed regional differences in four regions (eastern, northern, central and southern Hebei) and 141 counties; (ii) from the perspective of evolutionary characteristics of agricultural ecological efficiency, the overall development of in Hebei Province was good, with more concentrated spatial distribution and more obvious direction, while the type of transfer of agricultural ecological efficiency in Hebei Province showed strong stability that was significantly affected by geographical neighborhood conditions and the club convergence phenomenon; (iii) from the perspective of the long-term evolutionary trend of agricultural ecological efficiency, the areas adjacent to counties with low efficiency had limited potential for improvement, and the areas adjacent to counties with high grade had great potential. However, it was difficult to achieve large-scale improvement in agricultural ecological efficiency in Hebei Province, whether the impact of geospatial backgrounds was considered or not.