Carbon Footprint Model Research Articles

Carbon footprint of wheat-summer direct-seeding peanut planting system in Shandong Pro-vince, China

Clarifying the carbon emissions in wheat-summer direct-seeding peanut planting (W-P) system could help realize the synergistic effects of high yield and low carbon emissions. Based on whole life cycle method, we constructed a carbon footprint model to calculate the carbon emissions of W-P system. We found that the net income of W-P system was 71.2%-88.3% higher than that of wheat-maize rotation (W-M) system. The carbon emissions per unit area under W-P system was 6977.9-8018.5 kg·hm-2, being 6.2% higher than that of W-M system. The carbon emission of per net income under W-P system was 0.23-0.28 kg CO2-eq·yuan-1, which was 37.4%-44.1% lower than that of W-M system. Combining the net income and carbon emissions of per net income, W-P system could achieve synergistic effects of high yield and low carbon emissions, which would fulfill the targets of agricultural supply-side structural reform with optimizing supply, enhancing quality and efficiency, and increasing income of peasants.

A deterministic carbon footprint modelling across the supply chain of electricity

The electricity sector is one of the major contributors to climate change and global warming. Hence, decarbonisation of electricity which is generated by current technologies is inevitable. For a better policy implementation in energy portfolio, this paper presents a deterministic carbon footprint model for a frame F fossil fuel power plant from a raw material until the product is delivered to the end user. The model has been designed to cover the effect of investigated parameters. Controlling the investigated parameters can reduce carbon footprint of electricity through its life phases. The distinguished feature of the proposed model is the integration of raw material, operation of the power plant and transmission and distribution phases. The result shows good agreement between statistical data and the proposed model.

A deterministic carbon footprint modelling across the supply chain of electricity

A deterministic carbon footprint modelling across the supply chain of electricity

Carbon Footprinting and Mitigation Strategies for the USP Marine Campus

The quest for a low carbon footprint (CF) has prompted many institutions around the world, such as universities, among others, to take stock of their greenhouse gas (GHG) emissions. The CF assessment and its reporting are seen as a first step towards sustainability through planning for anthropogenic carbon emissions reduction. Carbon emissions–related activities of The University of the South Pacific (USP) Marine Campus) were investigated and then evaluated for potential reduction opportunities. A CF model for the campus’s CO2e emissions was developed. The results from the model estimated the USP Lower Campus CO2e emissions to be 2665.8 tCO2e. The Lower Campus per capita emissions for 2015 amount to about 1.1 tCO2e per equivalent full-time student (EFTS) and 0.07 tCO2e per square meter. Scope 3 emissions held the largest share of the emissions (96%). The emissions within scope 3 were largely from student and staff commuting. Besides commuting category, the largest contributor to the overall campus emission was electricity consumption and was recognized as an important source category. A 50kWp Photovoltaic (PV) rooftop system is proposed as an emission reduction strategy for the base case. This would make the campus electricity 100% renewable and entail an annual emission reduction of 12.9 tCO2e. Other strategies that support environmental and GHG management within the campus are also proposed in this paper.

A well to wire LCA model development and sensitivity analysis for carbon footprint of combined cycle power plants in Iranian electricity network

ABSTRACTThe present research introduces a well to wire pseudo comprehensive carbon footprint model for combined cycle power plants. The mentioned model integrates land use change model, operational model and transmission and distribution model into one comprehensive model. The parameters which their effects are considered in the integrated model are: fuel type, fuel transmission type, emission for fuel extraction and processing, own consumption of the plant, degradation, site ambient condition, transmission and distribution losses. For quantifying the effectiveness of each parameter, sensitivity analyses based on different life cycle scenarios are performed. The result shows that the effect of land use change is negligible. The carbon footprint of electrical energy produced in combined cycle plant until it is delivered to the end users varies from 321 to 522 g CO2 eq/kWh.

The Sustainable Infrastructure through the Construction Supply Chain Carbon Footprint Approach

The sustainable development concept is an important issue in construction industry, which becomes important mainly because of its role in infrastructure provision. Infrastructure availability will affect economic growth and increase a country's competitiveness. Indonesia as a developing country still needs to build a lot of physical infrastructure. The concept of sustainable infrastructure development is in line with the Indonesian government's development plans for the period of 2014-2015 called Nawa Cita. Carbon footprint modelling is one of the methods that contributes to the realization of sustainable infrastructure development. This paper describes the approach of sustainable infrastructure development through carbon footprinting in the construction supply chain. In the construction industry, carbon footprinting gives information in total emission of carbon dioxide (CO2) in every stage of a construction project's supply chain activities. In creating a carbon footprint model, life cycle analysis (LCA) is used as a supporting instrument to estimate the carbon dioxide (CO2) emissions in each stage of the supply chain activities. It is shown that the implementation of sustainable infrastructure development needs a synergy from all parties involved in the construction supply chain.

碳限额与交易机制下供应链网络设计

本文结合碳足迹及经典的供应链网络模型等相关理论，在传统的三级供应链网络模型中加入了碳限额与交易机制，全面分析了碳限额与交易机制对运营成本和供应链网络的影响。在经典供应链网络模型基础上运用0-1混合整数规划的方法构建了考虑碳限额与交易机制的供应链网络优化模型。从消费者、供应商和生产商三个角度对模型进行数值模拟对比分析，综合考虑了在碳限额与交易机制下各影响因子的变动对企业运营成本和供应链网络的影响。进一步验证了企业可以运用构建的模型来制定出合理的供应链网络，实现减排的同时降低企业的运输成本和运营成本。 This paper combines the theory of carbon footprint and basic supply chain model, add the carbon cap and trade mechanism into the basic supply chain model. And a comprehensive analysis of the impact of carbon cap and trade mechanism on operational costs and network flow has been made. Based upon basic transportation model, and taking into consideration of carbon cap and trade mechanism, we construct an optimized transportation network model applying 0-1 mixed integer programming method. Through the numerical simulation analysis of the model, we consider the influence on the enterprise’s operational cost and strategy under the cap and trade policy from three aspects, such as consumers, suppliers, manufactures. The industry can use the model to develop a reasonable transportation route to reduce carbon emissions and operational costs.

Sensitivity analysis of parameters affecting carbon footprint of fossil fuel power plants based on life cycle assessment scenarios

In this study a pseudo comprehensive carbon footprint model for fossil fuel power plants is presented. Parameters which their effects are considered in this study include: plant type, fuel type, fuel transmission type, internal consumption of the plant, degradation, site ambient condition, transmission and distribution losses. Investigating internal consumption, degradation and site ambient condition effect on carbon footprint assessment of fossil fuel power plant is the specific feature of the proposed model. To evaluate the model, a sensitivity analysis is performed under different scenarios covering all possible choices for investigated parameters. The results show that carbon footprint of fossil fuel electrical energy that is produced, transmitted and distributed, varies from 321 g CO2 eq/kWh to 980 g CO2 equivalent /kWh. Carbon footprint of combined cycle with natural gas as main fuel is the minimum carbon footprint. Other factors can also cause indicative variation. Fuel type causes a variation of 28%. Ambient condition may change the result up to 13%. Transmission makes the carbon footprint larger by 4%. Internal consumption and degradation influence the result by 2 and 2.5%, respectively. Therefore, to minimize the carbon footprint of fossil fuel electricity, it is recommended to construct natural gas ignited combined cycles in low lands where the temperature is low and relative humidity is high. And the internal consumption is as least as possible and the maintenance and overhaul is as regular as possible.

Carbon Footprint Analysis of Fibre Reinforced Composite Recycling Processes

Global rise of composite material demand has led to major legacy problems of manufacturing and end of life waste. The heterogeneous nature of composite material is the main challenge for recycling. In the European Union, tighter legislation on landfill, increasing landfill tax and loss of valuable material are driving the need for development of composite recycling technology. However, the recycling environmental benefits may not be optimised due to lack of high integrity environmental datasets. This study considered mechanical, high voltage fragmentation (HVF) and chemical recycling methods. New carbon footprint models were developed for each process. Experimental modelling was used to provide detailed process data associated with the processes. The Environmental Product Declaration (EPD) of the processes were evaluated through life cycle assessment studies. This work identifies that the electrical energy demand dominates the overall resource footprint in mechanical and HVF recycling methods. For both processes, extended tool life and optimised processing rate could significantly reduce the carbon footprint per unit of weight of waste processed. Environmental impact of the chemical recycling method was highly dominated by acetone used as the solvent. The refined datasets generated in this study enable better resource analysis to minimise carbon footprint of composite recycling processes. This is hoped to help increase market value of the recyclates by highlighting the environmental benefits gained through potential reuse applications.

LCA Frameworks integration in Carbon Footprint Modeling of Simple Cycle and Combined Cycle Power Plant for Sustainable Planning in Iran

The present research introduces a pseudo comprehensive carbon footprint model for simple cycle and combined cycle power plants based on Life Cycle Assessment frameworks for sustainable planning in Iran. For this purpose, parameters which their effects are considered distinguishable have been investigated. The mentioned parameters include: plant type, fuel type, fuel transmission type, own consumption of the plant, degradation, site ambient condition, transmission and distribution losses. Investigating power plant operational phase and transmission and distribution effect on carbon footprint assessment of power plant is the specific feature of the proposed model. Afterward, a sensitivity analysis is performed under different cases covering all the possible choices for investigated parameters. The results show that carbon footprint of fossil fuel (simple and combined cycle) varies remarkably due to the parameters affecting the carbon footprint. Results of sensitivity analyses show that by controlling the effective parameters carbon footprint of power plants can be reduced by 142%.

基于土地利用变化的四川省碳排放与碳足迹效应及时空格局

PDF HTML阅读 XML下载 导出引用 引用提醒 基于土地利用变化的四川省碳排放与碳足迹效应及时空格局 DOI: 10.5846/stxb201506111188 作者: 作者单位: 地理与资源科学学院,地理与资源科学学院,中国科学院资源环境科学数据中心,地理与资源科学学院,地理与资源科学学院,地理与资源科学学院 作者简介: 通讯作者: 中图分类号: 基金项目: 国家自然科学基金资助项目（41371125） Effect of land use changes on the temporal and spatial patterns of carbon emissions and carbon footprints in the Sichuan Province of Western China, from 1990 to 2010 Author: Affiliation: Key Lab of Land Resources Evaluation and Monitoring in Southwest,Ministry of Education,Sichuan Normal University,Key Lab of Land Resources Evaluation and Monitoring in Southwest,Ministry of Education,Sichuan Normal University,Data Center for Resources and Environmental Sciences,Chinese Academy of Sciences RESDC,Key Lab of Land Resources Evaluation and Monitoring in Southwest,Ministry of Education,Sichuan Normal University,Key Lab of Land Resources Evaluation and Monitoring in Southwest,Ministry of Education,Sichuan Normal University,Key Lab of Land Resources Evaluation and Monitoring in Southwest,Ministry of Education,Sichuan Normal 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:土地利用变化的碳排放与碳足迹研究对了解人类活动对生态环境的扰动程度及其机理、制定有效的碳排放政策具有重要意义。采用1990-2010年四川省能源消费数据和土地利用数据，通过构建碳排放模型、碳足迹及其压力指数模型，对研究区20年来土地利用的碳排放及碳足迹进行了定量分析。结果表明：（1）土地利用变化的碳排放和能源消费碳的足迹呈显著增加趋势。碳排放增加5407.839×104 t，增长率达143%；能源消费的碳足迹增加1566.622×104 hm2，四川全省的生态赤字达1563.598×104 hm2。（2）建设用地和林地分别为四川省最大的碳源与碳汇。20年间建设用地的碳排放增加5407.072×104 t，增长率达126.27%，占碳排放总量的88%以上；林地的碳汇减少10.351×104 t，但仍占四川省碳汇的96%以上。（3）土地利用碳排放、碳足迹和生态赤字存在明显区域差异。成都平原区碳排放、碳足迹压力最大，生态赤字严重，西部高山高原区和盆周山区碳排放、碳足迹最小，未出现生态赤字；成都、德阳、资阳和内江等地的碳排放、碳足迹压力最大，生态赤字最严重，甘孜、阿坝等地的碳排放、碳足迹最小，未出现生态赤字。（4）土地利用结构与碳排放、碳足迹存在一定的相互关系，趋高的碳源、碳汇比导致土地利用的碳源效应远大于碳汇效应。因此，四川省减排的重点应该在保持或增加现有的林地的同时，主要以降低建设用地的碳排放、碳足迹为主。 Abstract:Land use changes significantly affect the carbon dynamics of terrestrial ecosystems, and are one of the main factors influencing climate change on a global scale. Analyzing the effects of land use on carbon emissions is important for understanding the mechanisms of carbon emissions and the success of carbon reduction and climate change mitigation efforts. In this study, we developed carbon emission, pressure index, and carbon footprint models to evaluate a carbon budget, and carried out research in the Sichuan Province of western China to estimate carbon sinks and carbon sources, based on energy consumption and land use change data from 1990 to 2010 (obtained from remote sensing technologies). The results showed that:(1) Changes in land use and energy consumption from 1990 to 2010 significantly increased carbon emissions (5407.839×104 t, or 143%), with an average annual rate of increase of 7.151% (1566.622×104 hm2). During the same period, the carbon footprint for energy consumption increased, and the area of ecological deficit reached 1563.598×104 hm2. Overall, the increase in carbon emissions was associated with a rapid increase in fossil fuel consumption as well as land use changes; (2) Land under construction (carbon source) and forests (carbon sink) were the largest carbon pools in the carbon budget. Higher carbon emissions were noted for built-up land than for other land use types. Between 1990 and 2010, there was a continuous increase in carbon sources, and a slight decrease in carbon sinks. Carbon emissions from built-up land increased by 126.27%, which was the largest percentage increase in carbon emissions; (3) There were considerable regional differences in carbon emissions and carbon footprints. The Chengdu plain, and its surroundings regions (e.g., Chengdu, Deyang, Ziyang, and Neijiang), had higher carbon emissions, carbon footprints, and ecological deficits in 2010 than in 1990. In contrast, the west, northwest, and southwest mountainous regions and plateau areas (e.g., the Ganzhi, Aba, and Liangshan autonomous prefectures) had lower carbon emissions in 2010 than in 1990. In general, these regions had low carbon footprints and ecological deficits because of their widespread coverage by forests and grasslands. Compared to the Chengdu plain (and its surroundings regions), these regions had relatively low fossil fuel consumption, slow urbanization rates, and limited industrial development and transportation corridors. Overall, in Sichuan, there was an increase from 1990 to 2010 in the spatial distribution and severity of carbon emissions, carbon footprints, and ecological deficits; and (4) Land use had a greater effect on carbon sources than on carbon sinks. Forests, grasslands, water areas, and unused land were the main carbon sinks, while land under construction and cultivated land were the main carbon sources. The rapid increase in carbon sources and slow decrease in carbon sinks resulted in a substantial increase in carbon emissions in Sichuan from 1990 to 2010, with the ratio of sources to sinks increasing from 4.002 in 1990 to 9.739 in 2010. In conclusion, one key focus of future carbon emission reduction efforts in Sichuan should be to maintain or increase forest areas. It would also be worthwhile to reduce carbon emissions from land under construction. Through targeted land use and land management activities, ecosystems can be managed to enhance carbon sequestration and mitigate fluxes of greenhouse gases. 参考文献 相似文献 引证文献

Adaptation of the Product Structure-based Integrated Life cycle Analysis (PSILA) technique for carbon footprint modelling and analysis of closed-loop production systems

In a previous work, the Product Structure-based Integrated Life cycle Analysis (PSILA) technique was developed to conduct cost modelling and analysis of closed-loop production systems. In this paper, we expand the utility of this technique into carbon footprint (CFP) modelling and analysis of closed-loop production systems – enabling companies to make informed decisions on whether to adopt closed-loop production based not only on economic but also environmental performance. A description of the PSILA technique applied for carbon footprint modelling and analysis is explained, followed by a case study of closed-loop production of a flat-panel display (FPD) monitor to validate the technique. We verified the CFP result simulated by the model built through the PSILA technique, or PSILA-CFP model in short, against the result generated by a model built through the conventional Life Cycle Assessment (LCA) method. A benchmarking analysis was then conducted to compare the closed-loop production system against the linear production system. Through this analysis, we demonstrated how the CFP result can be broken down based on the product structure, thus enabling us to granularise the result and trace the impact of implementing a closed-loop production system to the individual modules, components and materials that are recovered, reutilised or treated in the system. The results were able to show that the implementation of the closed-loop production system for the FPD monitor can potentially result in an overall CFP reduction of 39.91 million kg CO2e, of which 90.03% is contributed by the closed-loop recycling of ABS. The other significant contributors of CFP reduction are from the closed-loop material recycling of the aluminium, which accounts for 8.13 million kg CO2e or 20.37% of the total CFP reduction. A sensitivity analysis was also carried out to investigate the effects of data uncertainties, which may invalidate assumptions made in the case study. In summary, we have successfully adapted the PSILA technique so as to provide decision support in the form of analytical insights on how a closed-loop production system will perform in terms of carbon footprint, why it performs this way and what to look out for if the decision is made to implement such a system.

Low-carbon conceptual design based on product life cycle assessment

Greenhouse gas emission becomes a recent global concern for manufacturing. As product design has a profound effect on a product’s carbon footprint in its life cycle, recent research efforts of low-carbon design provided valuable insights and contributions. Yet, most of the research is about detailed design instead of the conceptual stage. Conceptual design of a product determines over 70 % of its life cycle costs. The decisions made during the conceptual design also have extensive impacts on the environment. Therefore, it is important to estimate the carbon footprint of a product at its conceptual design stage. In this paper, we present a carbon footprint model and a low-carbon conceptual design framework where the environmental impacts throughout the life cycle of a product can be assessed. In the carbon footprint model, the amount of carbon emission is estimated at the five stages of the entire product life cycle. The carbon footprint analysis is based on product life cycle assessment. Sensitivity analysis for design parameters is also performed to measure the effects of design parameters on the estimation of product carbon footprint quantitatively. The conceptual design of a cold heading machine is used to demonstrate the proposed methodology.

Application of the Crop Carbon Progress Calculator in a ‘farm to ship’ cotton production case study in Australia

The various initiatives in the market place to quantify the sustainability levels of products are putting pressure on farmers to demonstrate a reduction in the environmental impacts of their crop management practices, and in particular with the lowering of the carbon footprints of their crops. At present there is no internationally accredited common method or carbon footprint model which generates site specific and LCA aligned emission estimates. The application of the Crop Carbon Progress Calculator (CCAP) is demonstrated for an irrigated cotton ‘farm to ship’ case study in Australia where we determine that the progress made in the 2011 crop against a 2002 crop base year amounts to 44% reduction in GHG emission levels.We estimate that for this particular case study the total carbon footprint of producing a bale of cotton up to ship's side or point of export is 323 kg CO2e. This includes 182 kg CO2e from the farm production phase, 73.1 kg CO2e from the gin to port supply chain, and 68.1 kg CO2e that results from emission from the stock piled gin trash at the gins. It appears that a feasible option to avoid these trash emissions is to incorporate the waste at farm level. Our analysis shows that this could generate an emissions credit of 48.8 kg CO2e per bale at farm level, which will amount to a 27% reduction in the farm emissions footprint and a 15% reduction in the whole farm to ship carbon footprint. Due to a number of site specific environmental and crop management factors, there can be significant variances in crop carbon footprint outcomes.

Application of unascertained number for the integration of carbon footprint in conceptual design

Carbon footprint has become a recent global concern for the environment. The product carbon footprint is typically calculated with activity data and corresponding carbon emission factors in the product life cycle. However, due to the uncertainty of product information in conceptual design, all the existing carbon footprint models fail in conceptual design. As the decisions made during the conceptual design have extensive impacts on carbon footprint, it is a crucial issue to estimate product carbon footprint in conceptual design. This article is devoted to model carbon footprint in conceptual design. After the introduction of unascertained mathematics theory, the modeling process of carbon footprint in conceptual design based on unascertained number is proposed. The carbon footprint in conceptual design of an automatic pipe handling manipulator is used to demonstrate the proposed methodology.

Investigation of Carbon Footprint on Campus - A Case Study of Tajen University

This study investigates and analysis the carbon dioxide emissions focus on student’s campus activities in the Tajen University during the school year. Survey queries includes commute distance, using means of transport, means of transport emissions, food consumption survey, the amount of waste, recycling and electricity consumption. The collected information was integrated into the carbon footprint calculation. This study investigated a total of 70 college students with 60 valid questionnaires in 85.7% recovery rate. Using descriptive statistics analysis quantitatively describing the students’ basic attributes and utilize analysis of variance to analyze the differences between students’ differences and their associated on carbon dioxide emissions. In this study, the result showed Tajen University students’ carbon footprint averaged 2.31±0.37 kg/person-day. Carbon footprint analysis results indicate that student age, grade, and gender difference between latent variables have different scenarios on carbon footprint model, such as, different genders no significant difference by measuring the carbon footprint, but of different ages and grade under test carbon footprint had a significant difference.

Carbon Footprint and Order Quantity in Logistics

Purpose: Even without economic factors and government regulations, the pressure and motivation of corporation to reduce emission are still increasing. This is because the key factors for corporation to reduce emissions have become corporate social responsibility and identification of low-carbon value by consumer and society from economic trade-off and government regulations. So, the purpose of this paper is to provide quantity methods for the logistics organizations with wish of voluntary reduction and social responsibility. Design/methodology/approach: Being difference from the traditional research that takes economic value as object, this paper takes carbon footprint as object directly, order quantity as decision variable. By referring to the traditional economic order quantity model, the paper creates logistics carbon footprint model which takes transport and inventory into account. Then it solves the model by calculating the values of order quantity, carbon footprint and revenue using the method of optimization. Findings and Originality/value: By solving and comparing the two models of economic order quantity model and carbon footprint model, it gets some results, such as carbon optimization order quantity, the effects order quantity deviating from economic order quantity or carbon order quantity having on economic or carbon footprint values, which can give some meaningful insight for corporation to search out reduction opportunities by operations adjustment. Originality/value: The study takes carbon footprint as object directly and creates the corresponding quantity model. By comparing with the traditional economic order quantity model, the paper provides quantity methods and obtains some meaningful insights for the logistics organizations with wish of voluntary reduction and social responsibility to reduce emissions by operations adjustment.

Low-carbon scheduling and estimating for a flexible job shop based on carbon footprint and carbon efficiency of multi-job processing

With the enhancement of people’s environmental awareness, low-carbon and energy efficiency in manufacturing industry have been drawing much attention due to the huge consumption of raw materials and energy during machining processes. But as one of the approaches to reduce carbon emission, manufacturing shop scheduling strategies have historically emphasized the makespan, machine workload, and so on and neglected energy and environmental factors in most cases. This article presents a model of low-carbon scheduling of the flexible job shop, which considers both factors of production (i.e. makespan and machine workload) and environmental influence (i.e. carbon emission). A carbon footprint model of multi-job processing is established to quantify the carbon emission of different scheduling plans, and three carbon efficiency indicators are put forward to estimate the carbon emission of parts and machine tools, that is, processing carbon efficiency, part carbon efficiency, and machine tool carbon efficiency. To solve the proposed model, a hybrid non-dominated sorting genetic algorithm II which combines the original non-dominated sorting genetic algorithm II with a local search algorithm based on neighborhood search is proposed. Finally, test of some well-known benchmark instances is carried out to verify the effectiveness of the proposed algorithm, and an actual case is studied to demonstrate the feasibility and applicability of the proposed model.

Income-carbon footprint relationships for urban and rural households of Iskandar Malaysia

Iskandar Malaysia has a vision to achieve sustainable development and a low carbon society status by decreasing the amount of CO2 emission as much as 60% by 2025. As the case is in other parts of the world, households are suspected to be a major source of carbon emission in Iskandar Malaysia. At the global level, 72% of greenhouse gas emission is a consequence of household activities, which is influenced by lifestyle. Income is the most important indicator of lifestyle and consequently may influence the amount of households' carbon footprint. The main objective of this paper is to illustrate the carbon-income relationships in Iskandar Malaysia's urban and rural areas. Data were gathered through a questionnaire survey of 420 households. The households were classified into six categories based on their residential area status. Both direct and indirect carbon footprints of respondents were calculated using a carbon footprint model. Direct carbon footprint includes domestic energy use, personal travel, flight and public transportation while indirect carbon footprint is the total secondary carbon emission measurement such as housing operations, transportation operations, food, clothes, education, cultural and recreational services. Analysis of the results shows a wide range of carbon footprint values and a significance correlation between income and carbon footprint. The carbon footprints vary in urban and rural areas, and also across different urban areas. These identified carbon footprint values can help the authority target its carbon reduction programs.

Carbon Footprint of Spring Maize Production System on State-Operated Farm in Northeast China Plain

In order to calculate the carbon footprint of agricultural production on farm, this paper, based on the investigation data of the farmers production, applying carbon footprint model, evaluated the carbon footprint (CF) of spring maize production systems (SMPS) on farm and its production teams in Northeast China Plain. The results were as follows: the CF of SMPS was 863.14.42±104.17 kg CO2e ha-1, in which chemical fertilizer accounted for 44.60%, mechanical operation accounted for 42.96%, seed accounted for 9.96%, and pesticides accounted for about 2.48%, respectively. The CF of SMPS in different production teams were significantly different (P<0.01), 18th production teams was the highest (958.37±81.73 kg CO2e ha-1) and 19th team was the lowest (767.84±45.98 kg CO2e ha-1). The differences of the CF of SMPSR among production teams almost was resulted from nitrous fertilizer using. Therefore, it had the potentiality of emission reduction in the production teams with higher CF. Using a fertilizer-saving way to build a low-carbon agricultural cropping pattern, that is an important way to realize agricultural energy saving and emission reduction of farm in the Northeast China Plain.