Spatial analysis of energy use and GHG emissions from cereal production in India

Assessing the influence of land use, agricultural, industrialization, CO2 emissions, and energy intensity on cereal production

In light of the growing global demand for food and the urgent need to address environmental challenges, it is essential to understand the factors that influence cereal production. This research set out to examine the intricate relationships between land use practices, agricultural methods, industrialization, energy intensity, carbon emissions, urban population growth, gross domestic savings, and cereal production across fifteen key cereal-producing states in the Americas. The study employs a Panel VAR/GMM model with data spanning from 2000 to 2021. The findings indicate that the lag of all variables exerts a strong, positive, and statistically significant effect on their current values. However, the lag of cereal production on other variables reveals a mixed and weaker effect, with cereal production showing a slight negative impact on land use and carbon dioxide (CO2) emissions. Conversely, the lag of land use positively influences cereal production, underscoring land management's crucial role. Meanwhile, the lag of agricultural practices, while mostly insignificant on other variables including cereal production, negatively affects urban population growth, suggesting that agricultural activities may slow urbanization. Additionally, industrialization has no significant effect on cereal production, except a weak negative influence on CO2 emissions and energy intensity. In contrast, Carbon dioxide emissions, exhibit a significant negative effect on cereal production, highlighting their detrimental impact on agricultural output. Moreover, the lag of energy intensity negatively affects CO2 emissions, suggesting more efficient energy use could help reduce emissions. Meanwhile, Urban population growth also has a significant negative impact on cereal production, indicating that urbanization may harm food security. The effect of gross domestic savings is generally weak and statistically insignificant across variables, though it shows some negative influence on both cereal production and urban population growth. Lastly, Granger causality tests show significant bidirectional causality between land use and cereal production, as well as between CO2 emissions and cereal production. The stability tests indicate that the model remains stable with impulse response functions. Based on these findings, the study offers practical policy implications, acknowledges limitations, and suggests future research directions, providing valuable insights for balancing agricultural productivity, environmental sustainability, and urban development.

Hydrologic variability governs GHG emissions in rice-based cropping systems of Eastern India

Reducing methane (CH4) emissions is increasingly recognized as an urgent greenhouse gas mitigation priority for avoiding ecosystem 'tipping points' that will accelerate global warming. Agricultural systems, namely ruminant livestock and rice cultivation are dominant sources of CH4 emissions. Efforts to reduce methane from rice typically focus on water management strategies that implicitly assume that irrigated rice systems are consistently flooded and that farmers exert a high level of control over the field water balance. In India most rice is cultivated during the monsoon season and hydrologic variability is common, particularly in the Eastern Gangetic Plains (EGP) where high but variable rainfall, shallow groundwater, and subtle differences in topography interact to create complex mosaics of field water conditions. Here, we characterize the hydrologic variability of monsoon season rice fields (n = 207) in the Indian EGP ('Eastern India') across two contrasting climate years (2021, 2022) and use the Denitrification Decomposition (DNDC) model to estimate GHG emissions for the observed hydrologic conditions. Five distinct clusters of field hydrology patterns were evident in each year, but cluster characteristics were not stable across years. In 2021, average GHG emissions (8.14 mt CO2-eq ha-1) were twice as high as in 2022 (3.81 mt CO2-eq ha-1). Importantly, intra-annual variability between fields was also high, underlining the need to characterize representative emission distributions across the landscape and across seasons to appropriately target GHG mitigation strategies and generate accurate baseline values. Simulation results were also analyzed to identify main drivers of emissions, with readily identified factors such as flooding period and hydrologic interactions with crop residues and nitrogen management practices emerging as important. These insights provide a foundation for understanding landscape variability in GHG emissions from rice in Eastern India and suggest priorities for mitigation that honor the hydrologic complexity of the region.

Assessing agricultural greenhouse gas emission mitigation by scaling up farm size: An empirical analysis based on rural household survey data

Agriculture is a major contributor to greenhouse gas (GHG) emissions. Farm size affects agricultural production inputs and thus has impacts on agricultural GHG emissions. However, the effects and mechanisms behind this are still unclear. In this paper, we identified the effects and mechanisms of farm size on agricultural GHG emissions, based on survey data about over 20,000 rural households in China from 2009 to 2016. Firstly, we calculated the agricultural CO2, CH4, and N2O emissions using the life-cycle analysis (LCA). Secondly, the impacts of farm size on GHG emissions intensity were explored with a fixed effect model, based on the long-term rural household survey data. Finally, the mechanisms were tested by the mediation effect model. The results showed that a 1 % increase in farm size, on average, could reduce the GHG emissions intensity of rural households by 0.245 % from 2009 to 2016. The mechanism analysis showed that the larger farm size reduced GHG emissions intensity mainly by reducing the non-fixed input intensity and raising fixed input investment. By identifying the impacts and mechanisms of farm size on agricultural GHG emissions, this paper aims to provide insights for policymakers to achieve China's goal of reaching carbon neutrality by 2060.

Do rainfed production systems have lower environmental impact over irrigated production systems?: On -farm mitigation strategies

The intensive agriculture practices improved the crop productivity but escalated energy inputs (EI) and carbon foot print (CF) which contributes to global warming. Hence designing productive, profitable crop management practices under different production systems with low environmental impact (EI and CF) is the need of the hour. To identify the practices, quantification of baseline emissions and the major sources of emissions are required. Indian agriculture has diversified crops and production systems but there is dearth of information on both EI and CF of these production systems and crops. Hence the present study was an attempt to find hot spots and identify suitable strategies with high productivity, energy use efficiency (EUE) and carbon use efficiency (CUE). Energy and carbon balance of castor, cotton, chickpea, groundnut, maize, rice (both rainfed and irrigated), wheat, sugarcane (only irrigated), pigeon pea, soybean, sorghum, pearl millet (only rainfed) in different production systems was assessed. Field specific data on different crop management practices as well as grain and biomass yields were considered. Rainfed production systems had lower EI and CF than irrigated system. The nonrenewable sources of energy like fertilizer (64 %), irrigation (78 %), diesel fuel (75 %) and electricity (67 %) are the major source of energy input. Rainfed crops recorded higher CUE over irrigated condition. Adoption of technologies like efficient irrigation strategies (micro irrigation), enhancing fertilizer use efficiency (site specific nutrient management or slow release fertilizer), conservation agriculture (conservation or reduced tillage) rice cultivation methods (SRI or Direct seeded rice) were the mitigation strategies. These results will help policy makers and stake holders in adoption of suitable strategies for sustainable intensification.

Environmental imprints of agricultural and livestock produce: A scoping review from South Asian countries

BACKGROUND

Agricultural activities in 2020 have resulted in 5.5 billion tons of CO2 equivalent globally, which is expected to rise because the food system would have to grow 70% more food for the population in 2050. Research suggests that agricultural productivity in South Asian countries, will increase food security; however, the role of their food crops and livestock products in environmental imprints is uncertain. This review aimed to assess the environmental impacts resulting from pre- and post-production agricultural activities related to edible food crops and livestock products consumed in eight South Asian countries.

METHODS

Studies were retrieved using three databases (PubMed, Google Scholar and Science Direct) from 2011 to 2022. The protocol for this scoping review was not registered.

RESULTS

Twenty-seven studies met the inclusion criteria. Most studies were conducted in India. Twenty-four articles assessed greenhouse gases (GHG) emissions, followed by water footprints (n = 5), nitrogen and phosphorus (N&P) emissions (n = 4), and land requirements (n = 4). The production of rice and wheat was identified as a significant contributor to GHG emissions. In India, Bangladesh and Sri Lanka, the production of livestock (meat/bovine/shrimp and milk) was reported to be harmful to the environment. Inconclusive data were retrieved for other environment variables.

CONCLUSIONS

Diversification in food production and cultivating additional coarse cereals (millets) offer opportunities for GHG reduction. Nevertheless, more comprehensive and longitudinal studies for South Asian countries are essential to make precise conclusions and validate the present review.

Adherence to EAT-Lancet dietary recommendations for health and sustainability in the Gambia

Facilitating dietary change is pivotal to improving population health, increasing food system resilience, and minimizing adverse impacts on the environment, but assessment of the current 'status-quo' and identification of bottlenecks for improvement has been lacking to date. We assessed deviation of the Gambian diet from the EAT-Lancet guidelines for healthy and sustainable diets and identified leverage points to improve nutritional and planetary health. We analysed the 2015/16 Gambian Integrated Household Survey dataset comprising food consumption data from 12 713 households. Consumption of different food groups was compared against the EAT-Lancet reference diet targets to assess deviation from the guidelines. We computed a 'sustainable and healthy diet index (SHDI)' based on deviation of different food groups from the EAT-Lancet recommendations and modelled the socio-economic and geographic determinants of households that achieved higher scores on this index, using multivariable mixed effects regression. The average Gambian diet had very low adherence to EAT-Lancet recommendations. The diet was dominated by refined grains and added sugars which exceeded the recommendations. SHDI scores for nutritionally important food groups such as fruits, vegetables, nuts, dairy, poultry, and beef and lamb were low. Household characteristics associated with higher SHDI scores included: being a female-headed household, having a relatively small household size, having a schooled head of the household, having a high wealth index, and residing in an urban settlement. Furthermore, diets reported in the dry season and households with high crop production diversity showed increased adherence to the targets. While average Gambian diets include lower amounts of food groups with harmful environmental footprint, they are also inadequate in healthy food groups and are high in sugar. There are opportunities to improve diets without increasing their environmental footprint by focusing on the substitution of refined grains by wholegrains, reducing sugar and increasing fruit and vegetables consumption.

Examining the carbon footprint of rice production and consumption in Hubei, China: A life cycle assessment and uncertainty analysis approach

This study aimed to quantify greenhouse gas emissions derived from the production-consumption of rice in Hubei-a major rice-producing province in central China. This research employed primary and secondary data collection methods. Primary data sources included interviews and experimental observations from seven counties in Hubei collected from June 2016 to December 2016. Secondary data sources-including national datasets, inter-governmental reports, and peer-reviewed articles-were used to extract relevant data, such as emission factors, and national and provincial rice output. Life Cycle Assessment was employed to build a comprehensive inventory and map of the rice carbon footprint, including the following five stages: production inputs, farm management, growth period, processing and sale, and consumption. Uncertainty analysis was performed to validate the reliability of carbon footprint estimations. Results showed that the carbon footprint for every 1 ton of polished rice in Hubei ranged between 4.19-6.81 t CO₂e/t and was 5.39 t CO₂e/t on average. Greenhouse gas emissions were primarily produced from rice fields during the growth stage (over 60% of greenhouse gas emissions of the whole life cycle of rice), followed by the consumption stage, and the production and transportation of agricultural inputs. Uncertainty analysis estimations indicated acceptable levels of reliability. This study's results indicate that the production and consumption of rice is a significant contributor to agricultural carbon emissions in Hubei-consistent with national estimates that place China as the largest carbon dioxide emitter globally. This research provides further insight into future policies and targeted initiatives for the efficient use of low-carbon agricultural inputs for rice production and consumption stages in China.

A Framework for Modelling Consumption-Based Energy Demand and Emission Pathways

Energy demand in global climate scenarios is typically derived for sectors - such as buildings, transportation, and industry - rather than from underlying services that could drive energy use in all sectors. This limits the potential to model household consumption and lifestyles as mitigation options through their impact on economy-wide energy demand. We present a framework to estimate the economy-wide energy requirements and carbon emissions associated with future household consumption, by linking Industrial Ecology tools and Integrated Assessment Models (IAM). We apply the framework to assess final energy and emission pathways for meeting three essential and energy-intensive dimensions of basic well-being in India: food, housing and mobility. We show, for example, that nutrition-enhancing dietary changes can reduce emissions by a similar amount as meeting future basic mobility in Indian cities with public transportation. The relative impact of energy demand reduction measures compared to decarbonization differs across these services, with housing having the lowest and food the highest. This framework provides complementary insights to those obtained from IAM by considering a broader set of consumption and well-being-related interventions, and illustrating trade-offs between demand and supply-side options in climate stabilization scenarios.

Assessing the sustainability of post-Green Revolution cereals in India

Substantial growth in food production has occurred from a narrowing diversity of crops over the last 50 y. Agricultural policies have largely focused on the single objective of maximizing production with less attention given to nutrition, climate, and environment. Decisions about sustainable food systems require quantifying and assessing multiple dimensions together. In India, diversifying crop production to include more coarse cereals, such as millets and sorghum, can make food supply more nutritious, reduce resource demand and greenhouse gas emissions, and enhance climate resilience without reducing calorie production or requiring more land. Similar multidimensional approaches to food production challenges in other parts of the world can identify win–win scenarios where food systems meet multiple nutritional, environmental, and climate resilience goals.

Sustainable food systems aim to provide sufficient and nutritious food, while maximizing climate resilience and minimizing resource demands as well as negative environmental impacts. Historical practices, notably the Green Revolution, prioritized the single objective to maximize production over other nutritional and environmental dimensions. We quantitatively assess outcomes of alternative production decisions across multiple objectives using India’s rice-dominated monsoon cereal production as an example. We perform a series of optimizations to maximize nutrient production (i.e., protein and iron), minimize greenhouse gas (GHG) emissions and resource use (i.e., water and energy), or maximize resilience to climate extremes. We find that increasing the area under coarse cereals (i.e., millets, sorghum) improves nutritional supply (on average, +1% to +5% protein and +5% to +49% iron), increases climate resilience (1% to 13% fewer calories lost during an extreme dry year), and reduces GHGs (−2% to −13%) and demand for irrigation water (−3% to −21%) and energy (−2% to −12%) while maintaining calorie production and cropped area. The extent of these benefits partly depends on the feasibility of switching cropped area from rice to coarse cereals. Based on current production practices in 2 states, supporting these cobenefits could require greater manure and draft power but similar or less labor, fertilizer, and machinery. National- and state-level strategies considering multiple objectives in decisions about cereal production can move beyond many shortcomings of the Green Revolution while reinforcing the benefits. This ability to realistically incorporate multiple dimensions into intervention planning and implementation is the crux of sustainable food production systems worldwide.

Integrated Solutions for the Water-Energy-Land Nexus: Are Global Models Rising to the Challenge?

Increasing human demands for water, energy, food and materials, are expected to accentuate resource supply challenges over the coming decades. Experience suggests that long-term strategies for a single sector could yield both trade-offs and synergies for other sectors. Thus, long-term transition pathways for linked resource systems should be informed using nexus approaches. Global integrated assessment models can represent the synergies and trade-offs inherent in the exploitation of water, energy and land (WEL) resources, including the impacts of international trade and climate policies. In this study, we review the current state-of-the-science in global integrated assessment modeling with an emphasis on how models have incorporated integrated WEL solutions. A large-scale assessment of the relevant literature was performed using online databases and structured keyword search queries. The results point to the following main opportunities for future research and model development: (1) improving the temporal and spatial resolution of economic models for the energy and water sectors; (2) balancing energy and land requirements across sectors; (3) integrated representation of the role of distribution infrastructure in alleviating resource challenges; (4) modeling of solution impacts on downstream environmental quality; (5) improved representation of the implementation challenges stemming from regional financial and institutional capacity; (6) enabling dynamic multi-sectoral vulnerability and adaptation needs assessment; and (7) the development of fully-coupled assessment frameworks based on consistent, scalable, and regionally-transferable platforms. Improved database management and computational power are needed to address many of these modeling challenges at a global-scale.