Agro-tactics for reducing carbon footprint in agricultural production systems: A review

Simple SummaryMinimizing the effects of climate change by reducing GHG emissions is crucial and can be accomplished by truly understanding the carbon footprint phenomenon. This study aims to improve the understanding of carbon footprint alteration due to agricultural management and fertility practices. It provides a detailed review of carbon footprint management under the impacts of environmental factors, land use, and agricultural practices. The results show that healthy soils have numerous benefits for the general public and especially farmers. These benefits include being stable and resilient, resistant to erosion, easily workable in cultivated systems, good habitat for soil micro-organisms, fertile and good structure, large carbon sinks, and hence lower carbon footprint. Intensive tillage is harmful to soil structure by oxidizing carbon and causing GHG emissions. If possible, no-till; if not, minimum tillage frequency and depth of tillage, and optimum moisture are recommended. The soil should be at an appropriate level of moisture when tillage takes place. Diverse cropping systems are better for the soil than monocultures. Minimizing machinery operations can help to avoid soil compaction. Building soil organic carbon in the most stable form is the most efficient practice of sustainable crop production.Global attention to climate change issues, especially air temperature changes, has drastically increased over the last half-century. Along with population growth, greater surface temperature, and higher greenhouse gas (GHG) emissions, there are growing concerns for ecosystem sustainability and other human existence on earth. The contribution of agriculture to GHG emissions indicates a level of 18% of total GHGs, mainly from carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O). Thus, minimizing the effects of climate change by reducing GHG emissions is crucial and can be accomplished by truly understanding the carbon footprint (CF) phenomenon. Therefore, the purposes of this study were to improve understanding of CF alteration due to agricultural management and fertility practices. CF is a popular concept in agro-environmental sciences due to its role in the environmental impact assessments related to alternative solutions and global climate change. Soil moisture content, soil temperature, porosity, and water-filled pore space are some of the soil properties directly related to GHG emissions. These properties raise the role of soil structure and soil health in the CF approach. These properties and GHG emissions are also affected by different land-use changes, soil types, and agricultural management practices. Soil management practices globally have the potential to alter atmospheric GHG emissions. Therefore, the relations between photosynthesis and GHG emissions as impacted by agricultural management practices, especially focusing on soil and related systems, must be considered. We conclude that environmental factors, land use, and agricultural practices should be considered in the management of CF when maximizing crop productivity.

PDF HTML阅读 XML下载 导出引用 引用提醒 基于生命周期评价的上海市水稻生产的碳足迹 DOI: 10.5846/stxb201304240794 作者: 作者单位: 上海市农业科学院,上海市农业科学院,上海市农业科学院,上海市农业科学院,江西农业大学 作者简介: 通讯作者: 中图分类号: 基金项目: 国家科技部支撑计划后世博专项资助项目（2010BAK69B18）；上海市科委崇明科技攻关专项资助项目（10DZ1960101） Life cycle assessment of carbon footprint for rice production in Shanghai Author: Affiliation: Shanghai Academy of Agricultural Sciences,Seed management station of Shanghai,,,Jiangxi Agricultural University Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:碳足迹是指由企业、组织或个人引起的碳排放的集合。参照PAS2050规范并结合生命周期评价方法对上海市水稻生产进行了碳足迹评估。结果表明：（1）目前上海市水稻生产的碳排放为11.8114 t CO2e/hm2，折合每吨水稻生产周期的碳足迹为1.2321 t CO2e；（2）稻田温室气体排放是水稻生产最主要的碳排放源，每吨水稻生产的总排放量为0.9507 t CO2e，占水稻生产全部碳排放的77.1%，其中甲烷（CH4）又是最主要的温室气体，对稻田温室气体碳排放的贡献率高达96.6%；（3）化学肥料的施用是第二大碳排放源，每吨水稻生产的总排放量为0.2044 t CO2e，占水稻生产总碳排放的16.5%，其中N最高，排放量为0.1159 t CO2e。因此，上海低碳水稻生产的关键在降低稻田甲烷的排放，另外可通过提高氮肥利用效率，减少氮肥施用等方法减少种植过程中碳排放。 Abstract:Global climate change has become an urgent issue of concern. Climate change will increasingly threaten our food production, security and even the survival of the human race. It also has a serious impact on natural ecosystems and the socioeconomic system. With the increasing scale and improvement in mechanization levels, the economic linkage between agricultural production and reduction of Greenhouse Gas (GHG) emissions is even closer in the agricultural production system. Therefore, the development of a low-carbon agricultural model is one of the long-term strategies for low-carbon economic growth throughout the country.This research of carbon footprint is introduced to measure the GHG emission over the rice production cycle. The carbon footprint can be defined as the total carbon emissions caused by an organization, event, product or person. At present, carbon footprints are used to measure GHG emissions in products, services, organizations, cities and countries and offer the decision basis for the formulation of GHG emission reduction schemes.Agricultural ecological systems, every year, also produce a lot of GHG emissions. The whole process of prenatal, intrapartum and postpartum agricultural production are closely related to energy consumption and GHG emission. In the process, all the agricultural inputs, such as chemical fertilizers, pesticides, seeds, cultivation, plant protection, agricultural machinery, irrigation and harvest also produce greenhouse gas emissions.The whole cultivation of rice involves methane (CH4) emission. This study shows that rice cultivation is one of the biggest sources of GHG emissions in crop cultivation. Rice paddies emit a large amount of methane in their water logged mode. Different irrigation modes have a great influence on the emission of GHG. Straw return is another factor that promotes GHG emissions. Soil organic content increases with the return of straw, with an increase in the soil methanogen activity, leading to increased methane emissions.The current carbon footprint research is the first time it has been used to measure the carbon emissions involved in rice production. The carbon footprint for rice production in Shanghai was assessed by the PAS2050 paradigm and life cycle assessment. The study area, located in Changjiang Farm, which belongs to the Guangming Group in Chongming County Shanghai City atlatitude 121°32'22' E, longitude31°40'23' N. Chongming County, in the Yangtze River Estuary, is a typical sub tropical monsoon climate with mild climate, abundant rainfall, annual average temperatures of 15.3 ℃, and annual precipitation of 1245 mm. It is the major grain production base for Shanghai city with winter wheat and summer rice forming their main planting patterns, which are typical for the middle and lower reaches of the Yangtze River rice-wheat rotation cropping pattern.The entire carbon emission of rice production in Shanghai was 11.8114 t CO2e (CO2-equivalents)/hm2, corresponding to a 1.2321 t CO2e/t rice grain yield. GHG emissions from paddy fields were the major source, which emitted 0.9507 t CO2e/t rice and accounted for 77.1% of total carbon emissions during rice production. Moreover, CH4 was the largest source for GHG emissions with a contribution rate of 96.6%.Chemical fertilizers were the second largest emission source in rice production. Chemical fertilizers emitted 0.2044 t CO2e for each ton of rice production, contributing 16.5% of total carbon emissions in rice production. N fertilizer was the biggest emission source, which released 0.1159 t CO2e/t rice.This research investigates the GHG emissions over the whole process of the Shanghai rice production cycle and reveals the energy consumption and GHG emissions in rice production. Thus, a rice carbon footprint is calculated by assessing the GHG emissions in Shanghai rice production. The results are beneficial for producing reduction plans of reducing GHG emissions in Shanghai rice production. Furthermore, the results will supply both practicable and theoretical foundations for drafting carbon footprint formulations in other industrial areas. 参考文献 相似文献 引证文献

For many developing countries, the land use sector, particularly agriculture and forestry, represents a large proportion of their greenhouse gas (GHG) emissions, making this sector a priority for GHG mitigation activities. Previous global surveys (e.g., IPCC 2000) as well as the most recent IPCC assessment report clearly indicate that the greatest technical potential for carbon sequestration and reductions of non-CO2 GHG emissions from the land use sector is in developing countries. Estimates that consider economic feasibility suggest that agriculture and forestry together provide among the greatest opportunities for short-term and low-cost mitigation measures across all sectors of the global economy1 (IPCC 2007). In addition, it is widely recognized that the ecosystem changes entailed by most mitigation practices, i.e., building soil organic matter, reducing losses and tightening nutrient cycles, more efficient production systems and preserving native vegetation, are well aligned with goals of increasing food security and rural development as well as buffering land use systems against climate change (Lal 2004). Hence, there is growing interest in jump-starting the capacity for broad-based engagement in agriculturally-based GHG mitigation projects in developing countries.

Global awareness of climate change issues, particularly changes in air temperature, has increased dramatically over the last half a century.Concerns regarding ecosystem sustainability and human existence on Earth arise due to population expansion, rising surface temperatures and increased greenhouse gas (GHG) emissions.Agriculture accounts for approximately 18% of the total GHG emissions, largely in the form of carbon dioxide, methane and nitrous oxide.As a result, limiting GHG emissions is critical to alleviating the consequences of climate change, which is attainable if the concept of carbon footprint is understood.Cereal production produces more GHG emissions than other farming methods, including vegetables and fruits.'Carbon footprint' is a popular term in agriculture and environmental research due to its involvement in environmental impact assessments and global climate change.GHG emissions are influenced by changes in land use, soil type and agricultural management approaches.Therefore, it is important to consider how agricultural management practices, particularly those involving the soil and related systems, affect the relationships between photosynthesis and GHG emissions.This study deals with the concept of carbon footprint in agriculture and various mitigation measures for its management.

Better information on greenhouse gas (GHG) emissions and mitigation potential in the agricultural sector is necessary to manage these emissions and identify responses that are consistent with the food security and economic development priorities of countries. Critical activity data (what crops or livestock are managed in what way) are poor or lacking for many agricultural systems, especially in developing countries. In addition, the currently available methods for quantifying emissions and mitigation are often too expensive or complex or not sufficiently user friendly for widespread use.The purpose of this focus issue is to capture the state of the art in quantifying greenhouse gases from agricultural systems, with the goal of better understanding our current capabilities and near-term potential for improvement, with particular attention to quantification issues relevant to smallholders in developing countries. This work is timely in light of international discussions and negotiations around how agriculture should be included in efforts to reduce and adapt to climate change impacts, and considering that significant climate financing to developing countries in post-2012 agreements may be linked to their increased ability to identify and report GHG emissions (Murphy et al 2010, CCAFS 2011, FAO 2011).

A wide range of calculators have been developed to assess the greenhouse gas (GHG) emissions of agricultural products, including biomass for bioenergy production. However, these calculators often fail in their ability to take into account the differences in pedoclimatic conditions, agricultural management practices and characteristics of perennial crops and crop rotations. As a result, the predictions of GHG emissions by these calculators are characterized by a high level of uncertainty, and calculators may fail in their ability to detect mitigation options along the production chain. The aim of this study was to analyze the available calculators for calculating GHG emissions from energy crop cultivation based on Carbon Footprint (CFP) approaches according to the goal and scope of the calculator, the methodology used to account for GHG emissions from energy crop cultivation, energy crop cultivation management practices and the ability to model crop rotation. Out of 44 environmental assessment calculators for agricultural products, we identified 18 calculators which are capable of assessing GHG emissions from energy crop cultivation. These calculators differ in their goal and scope and which farming operations related to crop management are taken into account; this makes it difficult to compare and interpret the results from these CFP assessments. Only seven calculators out of 18 can calculate GHG emissions from energy crop rotations. At the moment, none of these calculators are able to consider actual effects from energy crops in rotation in the context of nutrient shifts, reductions in the use of agricultural operating needs, or the sequence and composition of crop rotations. However, by expanding the system boundaries of the CFP study, by taking the whole energy crop rotation and local agricultural management practices into account, the opportunity to identify more GHG mitigation options increases.

Agricultural lands make up approximately 37% of the global land surface, and agriculture is a significant source of greenhouse gas (GHG) emissions, including carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O). Those GHGs are responsible for the majority of the anthropogenic global warming effect. Agricultural GHG emissions are associated with agricultural soil management (e.g. tillage), use of both synthetic and organic fertilisers, livestock management, burning of fossil fuel for agricultural operations, and burning of agricultural residues and land use change. When natural ecosystems such as grasslands are converted to agricultural production, 20–40% of the soil organic carbon (SOC) is lost over time, following cultivation. We thus need to develop management practices that can maintain or even increase SOCstorage in and reduce GHG emissions from agricultural ecosystems. We need to design systematic approaches and agricultural strategies that can ensure sustainable food production under predicted climate change scenarios, approaches that are being called climate‐smart agriculture (CSA). Climate‐smart agricultural management practices, including conservation tillage, use of cover crops and biochar application to agricultural fields, and strategic application of synthetic and organic fertilisers have been considered a way to reduce GHG emission from agriculture. Agricultural management practices can be improved to decreasing disturbance to the soil by decreasing the frequency and extent of cultivation as a way to minimise soil C loss and/or to increase soil C storage. Fertiliser nitrogen (N) use efficiency can be improved to reduce fertilizer N application and N loss. Management measures can also be taken to minimise agricultural biomass burning. This chapter reviews the current literature on CSA practices that are available to reduce GHG emissions and increase soil Csequestration and develops a guideline on best management practices to reduce GHG emissions, increase C sequestration, and enhance crop productivity in agricultural production systems.

Carbon footprint of main crop production in China: Magnitude, spatial-temporal pattern and attribution

Health Care and Climate Change: Challenges and Pathways to Sustainable Health Care.

The rapid growth of crop yield in China was maintained by more fossil fuel inputs in the past years, causing concern about the greenhouse gas (GHG) emissions related to crop production. Therefore, this study analyzed historical dynamics of carbon footprint (CF) of 11 major crops in China during 2000–2016 and estimated possible GHG emissions of the system in 2020 under different scenarios. Results indicated that the GHG emissions of the Chinese crop system increased by 20.07% from 2000 to 2016, in which the grain crops contributed to more than 80% of the total emissions. The GHG emissions from grain crops including maize, wheat, and rice as well as sugar crops including sugarcane and sugar beet were increased by 28.07% and 14.27% in the study period, respectively, making up the primary factor of increased GHG emissions of crop system in China. Moreover, if the cropping pattern and agricultural practices is not improved in the future, the GHG emissions from Chinese crop system are estimated to increase by 346.19 million tons in 2020. If advanced agricultural policies and practices are implemented, the GHGs emissions of crop system in China in 2020 are estimated to be 2.92–12.62% lower than that in 2016. Overall, this study illustrated that the crop system in China contributed to the growth of GHG emissions in China over the past decades. Improving utilization efficiency of fertilizers and crop structure in China are the most important ways to reduce GHG emissions from the Chinese crop system.

Identifying effective agricultural management practices for climate change adaptation and mitigation: A win-win strategy in South-Eastern Australia

Aktualnie ważnym wyzwaniem dla sektora rolniczego jest redukcja emisji gazów cieplarnianych (GHG) w celu złagodzenia skutków zmian klimatycznych. Istnieje potrzeba dokładnej identyfikacji źródeł emisji oraz upowszechnienia praktyk rolniczych, które przyczyniałyby się do zmniejszenia emisji we wszystkich ogniwach produkcji roślinnej. Do przeprowadzenia obiektywnych porównań i wyboru najlepszych rozwiązań technologicznych według kryterium emisyjności potrzebna jest szczegółowa ocena ilościowa emisji GHG. W opracowaniu przedstawiono ocenę emisji GHG w produkcji roślinnej za pomocą śladu węglowego (CF). Udział operacji technologicznych w powstawaniu CF scharakteryzowano na przykładzie rzepaku ozimego. Wyniki badań wskazują, że największe znaczenie w kształtowaniu CF ma proces nawożenia mineralnego. Wpływ pozostałych procesów na CF jest wielokrotnie mniejszy. Miejscem głównych emisji GHG w nawożeniu mineralnym rzepaku są emisje bezpośrednie i pośrednie GHG z pól. Po emisjach GHG z pól, produkcja nawozów stanowi drugie źródło emisji z nawożenia. Zmiany praktyk rolniczych polegających na zwiększeniu efektywności nawożenia azotowego oraz stosowaniu nawozów o niskich współczynnikach emisji stwarzają obecnie możliwość redukcji emisji GHG i przez to, tym samym mogą przyczynić się do zmniejszenia CF produktów roślinnych.

<p>Reducing greenhouse gas (GHG) emissions in to the atmosphere to limit global warming is the big challenge of the coming decades. The focus lies on negative emission technologies to remove GHGs from the atmosphere from different sectors. Agriculture produces around a quarter of all the anthropogenic GHGs globally (including land use change and afforestation). Reducing these net emissions can be achieved through techniques that increase the soil organic carbon (SOC) stocks. These techniques include improved management practices in agriculture and grassland systems, which increase the organic carbon (C) input or reduce soil disturbances. The C sequestration potential differs among soils depending on climate, soil properties and management, with the highest potential for poor soils (SOC stock farthest from saturation).</p><p>Modelling can be used to estimate the technical potential to sequester C of agricultural land under different mitigation practices for the next decades under different climate scenarios. The ECOSSE model was developed to simulate soil C dynamics and GHG emissions in mineral and organic soils. A spatial version of the model (GlobalECOSSE) was adapted to simulate agricultural soils around the world to calculate the SOC change under changing management and climate.</p><p>Practices like different tillage management, crop rotations and residue incorporation showed regional differences and the importance of adapting mitigation practices under an increased changing climate. A fast adoption of practices that increase SOC has its own challenges, as the potential to sequester C is high until the soil reached a new C equilibrium. Therefore, the potential to use soil C sequestration to reduce overall GHG emissions is limited. The results showed a high potential to sequester C until 2050 but much lower rates in the second half of the century, highlighting the importance of using soil C sequestration in the coming decades to reach net zero by 2050.</p>

Carbon sequestration is a natural process that removes carbon dioxide from the atmosphere and stores it in plant biomass, soils, oceans, and geological formations- a very important process for reducing greenhouse gas concentrations, mitigating climate change and improving soil health. This study explores the environmental impact of implementing Nature Based Solutions (NBSs) in peach orchards and olive groves in Greece, using a cradle-to-farm-gate Life Cycle Assessment (LCA) approach. It specifically examines the chemical, physical, and soil conditions necessary for humification and organic carbon accumulation. The objectives are to: (1) assess the effectiveness NBSs in enhancing soil carbon sequestration within different agricultural management practices, (2) quantify the impact of cultivation transitions on soil carbon storage capacity and greenhouse gas (GHG) emissions, (3) integrate soil carbon stock dynamics into LCA methodologies to improve accuracy in carbon footprint assessments, and (4) highlight the importance of soil organic carbon (SOC) pools and soil properties in refining LCA interpretations for sustainable land management. By Implementing NBSs at pilot sites and using the Monitoring, Reporting and Verification system to track GHG emissions and SOC changes in the field, carbon stocks increased: −179.2 kg CO₂ eq in the peach orchard and −186.3 kg CO₂ eq in the olive grove. GHG emissions reduced by 16.4% in peach cultivation and 51.1% per hectare in olive grove. Main emission sources included crop protection and field energy use; in olives, residue management also played a significant role. This study provides empirical evidence on how NBSs can enhance soil carbon sequestration and reduce GHG emissions, contributing to both climate change mitigation and sustainable agricultural management. These findings demonstrate the value of integrating SOC dynamics into LCA for more reliable carbon assessments, offering a more accurate representation of carbon sequestration potential. The study can support policymakers, farmers, and stakeholders in adopting strategies that maximize environmental benefits and promote soil health. More long- term research on the implementation of Nature Based Solutions is required to properly assess their impact across cultivations, soil types and pedoclimatic zones.

Food processing is a major thriving industry globally and provides livelihood to millions of workers. Food processing is an energy intensive process and often has an impact on the environment which remains undiagnosed and hence not quantified. Food processing industry comprises the organized as well as unorganized sector with varying levels of energy requirement and therefore the carbon foot prints also significantly vary. Higher energy use is often related to higher greenhouse gas (GHG) emission which is responsible for global warming and climate change. Carbon footprint (CFP) of food industry is an estimate of the energy use and GHG emissions caused due to the processing and delivery of food items to the consumer and also disposal of packaging. Recently there is a growing interest in estimating the carbon footprint of food industries to know how improved technologies can be used to make food processing less energy and carbon intensive. In this book chapter we would like to provide an overview of energy use and carbon footprint of different types of food industries. Quantification of CFP is generally done using Life Cycle Assessment (LCA) in which GHG emissions are measured from the very beginning of the production process to its final use and disposal. GHG emission from a food industry will include both direct emissions as well as indirect emissions. The CFP of different sectors like fruit and beverage industry, sugar production, dairy sector, fisheries, meat and poultry supply chains are presented. Apart from this, research gaps and possible steps to minimize the carbon footprint will be mentioned. Assessing the CFP of food industries can help in identifying the GHG sources and can be useful in developing alternative technologies which are more energy efficient and reduces GHG emission. Further, change in dietary pattern also contributes immensely to reduce the environmental impact of food consumption.