A Comparison of Carbon Footprint and Production Cost of Different Pasta Products Based on Whole Egg and Pea Flour

Maize production is critical in tropical/subtropical regions, especially in developing countries where maize is a staple food. However, its environmental costs remain unclear. Southwest China is a tropical/subtropical region with large-scale maize production in each of its sub-regions. In the present study, we used Southwest China as a case study to evaluate the greenhouse gas (GHG) emissions and carbon footprint (CF) of maize production during 1996-2015 using life cycle assessment to identify the driving factors behind the GHG emissions and CF and to propose potential mitigation strategies. The mean GHG emissions of maize production per year during 1996-2015 was 4132 kg CO2-eq·ha-1, and the CF during this period was 961 kg CO2-eq·Mg-1. The GHG emissions and CF in Southwest China were 2-4 times higher than those of other major maize-producing regions worldwide. The GHG emissions and CF were both significantly correlated with the N surplus. The N surplus was also linearly correlated with annual precipitation, annual temperature and growing degree days, but not significantly related with soil pH. Scenario testing showed that the CF of maize production in Southwest China could be reduced by 41%, i.e. to 437 kg CO2-eq·Mg-1, by farmers adopting a comprehensive strategy including recommended fertiliser application rates, innovative fertilisers, and crop management to decrease GHG emissions and achieve the yield potential in the region. Integrated soil and crop management is essential for sustainable maize production in tropical/subtropical regions with complex and changeable ecological conditions, especially in developing countries where maize is a staple food.

The achievement of the targets of reducing greenhouse gas emissions is ensured, among other things, through direct price regulation measures, for the implementation of which a necessary condition is the calculation of the carbon footprint of products. At the same time, carbon footprint targets can be used as driving parameters to set industry targets for reducing greenhouse gas emissions, as well as to provide government support measures for enterprises. The aim of the work is to develop a methodological approach to the use of the «carbon footprint of products» indicator as a parameter for assessing the current and forecast values of greenhouse gas emissions from enterprises in industries that are subject to carbon regulation. The hypothesis of the study is to justify the use of target values of the indicator «carbon footprint of products» for strategic estimates of greenhouse gas emissions in the process of industrial decarbonization. For this purpose, the paper considers the organizational and economic mechanism of the European emissions trading system. A methodical approach to determining the carbon footprint of metallurgical products is described, and calculations of the carbon footprint of metallurgical enterprises in the Sverdlovsk region are performed. Calculations based on average indicators of the carbon intensity of products of Russian metallurgical enterprises showed that the total carbon footprint of the metallurgical sector of the Sverdlovsk region in 2021 is 21.8 million tons of CO2-eq; its target value may be 16.7 million tons of CO2-eq . Differences in values are due to the existing structure of manufactured products and applied technologies. The development of standard metrics for assessing greenhouse gas emissions at the enterprise level, regularly conducting such an assessment and its verification by an independent organization may constitute a preparatory stage that makes it possible to launch a mechanism for trading greenhouse gas emissions at the regional or country level. Additionally, the carbon footprint of products can act as a control parameter while establishing quantitative values for the volume of greenhouse gas emission reductions. The proposed methodological approach can be used by decision makers to shape regional decarbonization policies.

Smallholder dairy farms face enormous challenges in increasing milk production while mitigating greenhouse gas (GHG) emissions, thereby enhancing climate resilience. The carbon footprint (CF) of smallholder milk production is expected to increase with increasing demand for dairy products under the business-as-usual scenario. This study estimates the carbon footprint of smallholder milk production and examines variation across farms using data from 480 households to identify viable options for mitigating GHG emissions. We applied a cradle to farm-gate life cycle assessment (LCA) approach to examine the effects of farming systems on GHG emission intensities across intensification gradients of smallholder farms (SHF) from four potential dairy districts in the central highlands of Ethiopia. According to our findings, enteric fermentation was the primary source of GHG emissions, and methane(CH4) emissions from enteric fermentation and manure management accounted for the majority of total emissions across farms. The estimated average CF varies depending on farming systems, global warming potential (GWP), and allocation methods used. When GHG emissions were allocated to multiple products using economic allocation and based on IPCC (2007)and IPCC (2014)GWPs, the overall average CF of milk production was 1.91 and 2.35kg CO2e/kg fat and protein-corrected milk (FPCM), respectively. On average, milk accounted for 72% of total greenhouse gas emissions. In terms of farm typology, rural SHF systems produced significantly more CF per kg of milk than urban and peri-urban SHF systems. Variations in milk yield explained more than half of the variation in GHG emissions intensity at the farm level. Feed digestibility and feed efficiency had a negative and significant (P < 0.01) association with CF of SHF. Our findings suggested that improving feed digestibility and feed efficiency by increasing the proportion of concentrate and improved forage as well as chemically upgrading straw and crop residue could provide an opportunity to both increase milk yield and reduce the CF of milk production of SHF in the study area. Supporting SHF to realize strategies contributing to climate-resilient dairy development require interventions at several levels in the dairy value chain.

Carbon footprint of Canadian dairy products: Calculations and issues

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

Accounting methane and nitrous oxide emissions, and carbon footprints of livestock food products in different states of India

The purpose of this study was to quantify the spatial and technological variability in life cycle greenhouse gas (GHG) emissions, also called the carbon footprint, of durum wheat production in Iran. The calculations were based on information gathered from 90 farms, each with an area ranging from 1 to 150 ha (average 16 ha). The carbon footprint of durum wheat was calculated by quantifying the biogenic GHG emissions of carbon loss from soil and biomass, as well as the GHG emissions from fertilizer application and machinery use, irrigation, transportation, and production of inputs (e.g., fertilizers, seeds, and pesticides). We used Spearman’s rank correlation to quantify the relative influence of technological variability (in crop yields, fossil GHG emissions, and N2O emissions from fertilizer application) and spatial variability (in biogenic GHG emissions) on the variation of the carbon footprint of durum wheat. The average carbon footprint of 1 kg of durum wheat produced was 1.6 kg CO2-equivalents with a minimum of 0.8 kg and a maximum of 3.0 kg CO2-equivalents. The correlation analysis showed that variation in crop yield and fertilizer application, representing technological variability, accounted for the majority of the variation in the carbon footprint, respectively 76 and 21%. Spatial variation in biogenic GHG emissions, mainly resulting from differences in natural soil carbon stocks, accounted for 3% of the variation in the carbon footprint. We also observed a non-linear relationship between the carbon footprint and the yield of durum wheat that featured a scaling factor of −2/3. This indicates that the carbon footprint of durum wheat production (in kg CO2-eq kg−1) typically decreases by 67% with a 100% increase in yield (in kg ha−1 year−1). Various sources of variability, including variation between locations and technologies, can influence the results of life cycle assessments. We demonstrated that technological variability exerts a relatively large influence on the carbon footprint of durum wheat produced in Iran with respect to spatial variability. To increase the durum wheat yield at farms with relatively large carbon footprints, technologies such as site-specific nutrient application, combined tillage, and mechanized irrigation techniques should be promoted.

Indian dairy enterprise is dominated by smallholder dairy farms that contribute 72% of the country's total milk production. These smallholder dairy farms are often considered to emit substantial greenhouse gases (GHG) but are poor in productive performances. Therefore, it is crucial to estimate the carbon footprint (CF) of milk production of the smallholder Indian dairy farms. The primary objectives of the study were (1) Assessing the CF of milk production of smallholder dairy farms through life cycle analysis in south-interior Karnataka, India; (2) Identifying the hotspots of GHG emissions and significant factors influencing the CF of milk production in smallholder dairy production system. The study accounted GHG emissions from different sources and considered multiple functions of the smallholder production system. Estimations were made based on primary data collected from 47 farms and associated secondary data. For estimating the CF of milk production, the emissions of carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) on a CO2-equivalent (CO2-eq) basis from feed production, enteric fermentation, manure management, transport and energy usage were allocated to fat- and protein-corrected milk (FPCM) based on mass balance, price (crop byproducts and residues) and feed digestibility. Principal component analysis and stepwise linear regression analysis were performed to identify the major factors influencing the CF. The average total GHG emissions (kg CO2-eq yr-1 farm-1) attributable to milk production based on mass, economic, and digestibility allocations were 8,936, 8,641, and 8,759, respectively. The contributions of CH4, N2O, and CO2 to the total farm GHG emission were 70.6%, 20.5%, and 7.69%, respectively. The major emission hotspots were CH4 emission from enteric fermentation (66.8%) and GHG emission from feed production (23.0%). The average CF of cradle-to-dairy cooperative milk production varied from 1.45 to 1.81 kg CO2-eq kg FPCM-1. The CF of milk production was more than 2-fold greater, when milk yield was below 3,500 kg lactating cow-1 yr-1. The FPCM yield 100 kg body weight-1, dry matter intake, and CH4 emission from manure management were the strongest determinants of the CF and explained 83.4% of the observed variation. The study emphasized the importance of considering multiple functions of a mixed crop-livestock-based dairy production system for estimating CF per unit of product. The results suggest that maintaining high-yielding dairy animals and adopting appropriate feeding strategies for better feed utilization are the possible effective interventions for reducing the CF of milk production.

A comprehensive continental-scale analysis of carbon footprint of food production: Comparing continents around the world

Carbon footprint of a typical pomelo production region in China based on farm survey data

Coupling life-cycle assessment and the RothC model to estimate the carbon footprint of green manure-based wheat production in China

A comparative life cycle assessment highlighting the trade-offs of a liquid manure separator-composter in a Canadian dairy farm system

While the environmental impacts of livestock production, such as greenhouse gas emissions and water usage, have been studied for a variety of US livestock production systems, the environmental impact of US sheep production is still unknown. A cradle-to-farm gate life cycle assessment (LCA) was conducted according to international standards (ISO 14040/44), analyzing the impacts of CS representing five different meat sheep production systems in California, and focusing on carbon footprint (carbon dioxide equivalents, CO2e) and irrigated water usage (metric ton, MT). This study is the first to look specifically at the carbon footprint of the California sheep industry and consider both wool and meat production across the diverse sheep production systems within California. This study also explicitly examined the carbon footprint of hair sheep as compared with wooled sheep production. Data were derived from producer interviews and literature values, and California-specific emission factors were used wherever possible. Flock outputs studied included market lamb meat, breeding stock, 2-d-old lambs, cull adult meat, and wool. Four different methane prediction models were examined, including the current IPCC tier 1 and 2 equations, and an additional sensitivity analysis was conducted to examine the effect of a fixed vs. flexible coefficient of gain (kg) in mature ewes on carbon footprint per ewe. Mass, economic, and protein mass allocation were used to examine the impact of allocation method on carbon footprint and water usage, while sensitivity analyses were used to examine the impact of ewe replacement rate (% of ewe flock per year) and lamb crop (lambs born per ewe bred) on carbon footprint per kilogram market lamb. The carbon footprint of market lamb production ranged from 13.9 to 30.6 kg CO2e/kg market lamb production on a mass basis, 10.4 to 18.1 kg CO2e/kg market lamb on an economic basis, and 6.6 to 10.1 kg CO2e/kg market lamb on a protein mass basis. Enteric methane (CH4) production was the largest single source of emissions for all CS, averaging 72% of total emissions. Emissions from feed production averaged 22% in total, primarily from manure emissions credited to feed. Whole-ranch water usage ranged from 2.1 to 44.8 MT/kg market lamb, almost entirely from feed production. Overall results were in agreement with those from meat-focused sheep systems in the United Kingdom as well as beef raised under similar conditions in California.

The impact of various parameters on the carbon footprint of milk production in New Zealand and Sweden

Simple SummaryA spring calving herd (~350 beef cows) over two production cycles was used to compare the whole-farm greenhouse gas (GHG) emissions among calf-fed vs. yearling-fed production systems, with and without growth implants. Farm GHG emissions initially included enteric CH4, manure CH4 and N2O, cropping N2O, and energy use CO2. The carbon footprint ranged from 19.9–22.5 kg CO2e per kg carcass weight. Including soil organic carbon loss from annual cropping and carbon sequestration from perennial pastures and haylands further reduced the carbon footprint by 11–16%. The carbon footprint of beef was reduced by growth promotants (4.9–5.1%) and by calf-fed beef production (6.3–7.5%).A spring calving herd consisting of about 350 beef cows, 14–16 breeding bulls, 60 replacement heifers and 112 steers were used to compare the whole-farm GHG emissions among calf-fed vs. yearling-fed production systems with and without growth implants. Carbon footprint ranged from 11.63 to 13.22 kg CO2e per kg live weight (19.87–22.52 kg CO2e per kg carcass weight). Enteric CH4 was the largest source of GHG emissions (53–54%), followed by manure N2O (20–22%), cropping N2O (11%), energy use CO2 (9–9.5%), and manure CH4 (4–6%). Beef cow accounted for 77% and 58% of the GHG emissions in the calf-fed and yearling-fed. Feeders accounted for the second highest GHG emissions (15% calf-fed; 35–36% yearling-fed). Implants reduced the carbon footprint by 4.9–5.1% compared with hormone-free. Calf-fed reduced the carbon footprint by 6.3–7.5% compared with yearling-fed. When expressed as kg CO2e per kg carcass weight per year the carbon footprint of calf-fed production was 73.9–76.1% lower than yearling-fed production, and calf-fed implanted was 85% lower than hormone-free yearling-fed. Reducing GHG emissions from beef production may be accomplished by improving the feed efficiency of the cow herd, decreasing the days on low quality feeds, and reducing the age at harvest of youthful cattle.