Energy implications of the 21st century agrarian transition

The Green Revolution, marked by the adoption of fossil-fuel-based industrial fertilizers, new cultivars, and machinery, overcame historical limitations in traditional agriculture related to soil fertility, water, and energy. While increasing crop production threefold in the last 50 years, this intensification has led to significant environmental impacts. A key challenge is sustainably meeting future food demands while minimizing agriculture's environmental footprint. Strategies often involve dietary shifts, reducing food waste, and closing yield gaps through intensification. However, agricultural intensification rarely creates win-win scenarios; benefits to global health and land use may not translate to local hunger alleviation or reduced pressure on local resources. The recent surge in large-scale land acquisitions (LSLAs) globally has exacerbated controversies surrounding agricultural intensification. LSLAs, involving long-term, large-scale land acquisitions by domestic and foreign actors, are driven by factors such as food security concerns and the resurgence of agriculture as a key investment sector. The Land Matrix estimates 90 million hectares of land have been acquired globally since 2000. While some studies highlight potential benefits like yield increases and economic gains, others criticize LSLAs as land grabs causing adverse impacts on local communities, including land dispossession and livelihood loss. LSLAs might paradoxically increase overall crop production while undermining local food security through the export of energy-rich but nutrient-poor crops. Though the political, social, economic, and environmental implications of LSLAs have been studied extensively, their energy implications remain largely unexplored. Considering that food systems account for a significant portion of global primary energy use (15–30%) and greenhouse gas emissions (25–34%), this study addresses the critical gap in understanding the energy implications of the agrarian transition driven by LSLAs.

Existing literature extensively examines the impact of large-scale land acquisitions (LSLAs) on various aspects, including their political implications, effects on property systems, rural livelihoods, crop yields, water use and redistribution, food security, environmental impacts, and carbon emissions. However, with a few exceptions, the energy implications of LSLAs remain poorly understood. Studies have analyzed the Green Revolution's impact on energy consumption in agriculture, highlighting increased efficiency but not necessarily input savings. The potential benefits and drawbacks of LSLAs are also debated; some studies point to potential yield increases and economic benefits, while others emphasize the negative effects on local communities and food security. Previous research has estimated the GHG emissions associated with deforestation and land-use change resulting from LSLAs, but the energy consumption associated with the shift from traditional to intensive farming practices has received less attention.

This study evaluates the energy and fossil fuel implications of the agricultural transition driven by LSLAs, focusing on the changes from low-input, labor-intensive systems to high-input, intensified production. The study uses data from various sources to estimate pre- and post-LSLA energy inputs in crop production. A sample of 197 land deals from the Land Matrix dataset (deals larger than 200 hectares) was analyzed. The study assesses energy intensity under low- and high-input scenarios for various crops, including staple crops (rice, wheat, maize, soybean) and others like oil palm, jatropha, and cotton. Pre-LSLA agricultural productivity is assessed using fertilizer application rates and yield gap closure levels. The energy intensity of irrigation is also evaluated considering different irrigation technologies (sprinkler and surface irrigation) and the WATNEEDS crop water model. The study calculates aggregate fossil fuel energy requirements and related carbon emissions for the intended crops under low- and high-input scenarios. Greenhouse gas (GHG) emissions are assessed by considering emissions from oil combustion and upstream emissions during crude oil production, as well as N2O emissions from synthetic nitrogen fertilizer application. Sensitivity analyses are conducted by varying assumptions about land cultivation, attainable yield, and the proportion of energy from fossil fuels versus renewable sources.

The analysis reveals that 80% of the land deals considered involved areas previously characterized by low-input agriculture, indicating a significant potential for increased energy consumption following LSLAs. High-input agriculture requires approximately five times more fossil fuel-based energy than low-input agriculture. For example, a transition to high-input agriculture across the 4.07 million hectares of land deals analyzed would require an estimated 15 million barrels of oil equivalent per year, compared to 3 million barrels for low-input agriculture. This would lead to an additional 6 million tons of CO2 emissions per year (a business-as-usual scenario). A more conservative estimate, accounting for lower attainable yields, partial cultivation, and some renewable energy use, reduces this to 3 million tons of CO2 per year. Oil palm is the most prevalent crop in these LSLAs, and its processing for biodiesel adds further energy demands. The study also found that 20% of land deals are located in regions with insufficient water resources to sustainably support irrigation, with high energy requirements for irrigation, particularly in Africa due to climate and crop choice (oil palm and sugarcane). Sprinkler irrigation is significantly more energy-intensive than surface irrigation. Synthetic nitrogen fertilizer application in high-input farming contributes substantially to GHG emissions (1.3 million tons of CO2 equivalent per year from the analyzed LSLAs). The combined energy demands for crop production and irrigation (under a high-input scenario) could reach 26 million GJ annually.

This research highlights the significant energy implications of the agrarian transition associated with LSLAs, particularly the substantial increase in fossil fuel energy consumption and GHG emissions resulting from the shift to high-input agriculture. The findings underscore the need to consider the energy dimension in evaluating the sustainability and distributional effects of LSLAs. The increased energy demand could exacerbate energy poverty and competition for scarce local energy resources in rural communities. The study's results demonstrate the importance of adopting a nexus approach that considers the integrated interactions among food, water, and energy systems, focusing on local resource access and social equity. The higher energy intensity of high-input agriculture is not merely an environmental concern but also affects access to energy for marginalized communities.

This study reveals the substantial and often overlooked energy implications of the global agrarian transition, particularly concerning large-scale land acquisitions. The shift towards high-input agriculture significantly increases fossil fuel dependency, carbon emissions, and competition for local energy resources. The research emphasizes the need for integrated assessments of LSLAs, considering the food-energy-water nexus and prioritizing local resource access and social justice. Future research should explore sustainable alternatives to intensive agriculture, including agroecological practices and renewable energy solutions for irrigation and fertilizer production. Policies supporting LSLAs must incorporate energy-intensity analyses to promote sustainable and equitable outcomes.

The study's analysis relies on data from the Land Matrix database, which may have limitations in data completeness and accuracy. The energy intensity estimates are based on existing data and may not capture all nuances of energy use in various agricultural contexts. The sensitivity analysis addresses some uncertainty but acknowledges simplifications in the estimations. Extrapolating the findings to the global scale requires considering the heterogeneity of agricultural systems and practices worldwide.