再生稻田温室气体排放特征及碳足迹

研究中国东南区域不同稻作方式对水稻生产过程中稻田温室气体排放特征及其碳足迹的影响,对促进水稻可持续生产有重要意义。本研究以当前推广的常规稻‘佳辐占'和杂交中稻‘甬优2640'为材料,构建4种适合福建不同生态类型区的稻作模式: 1) 双季稻,早稻和晚稻均种植佳辐占(D-J);2) 早熟再生稻,头季稻和再生季稻均种植佳辐占(R-J);3) 中熟再生稻,头季稻和再生季稻均种植甬优2640(R-Y);4) 单季晚稻,与中熟再生季稻同期抽穗的单季晚稻,种植甬优2640(S-Y)。采用密闭静态暗箱观测法和气相色谱法分别收集并检测稻田土壤温室气体排放量,借用生命周期法对不同稻作方式产生的直接和间接温室气体排放总量(即碳足迹)进行数据采集与比较分析。结果表明: 不同稻作方式稻田温室气体排放特征均表现为生育前期排放量较低,到孕穗期前后达到高峰后又下降,即全生育期呈前高后低的双峰曲线,其中早稻或头季稻达到的第1个峰值较相应晚稻或再生季稻的第2个峰值高。不同稻作模式稻田温室气体排放总量差异显著。各种植模式全球增温潜势(GWP)表现为:R-Y>D-J>S-Y>R-J,温室气体排放强度(GHGI)表现为:D-J>S-Y>R-Y>R-J;与双季稻模式相比,佳辐占再生稻模式GWP和GHGI分别降低26.1%和14.1%;与同期抽穗的单季晚稻相比,甬优2640再生季稻稻田GWP和GHGI分别降低74.3%和56.7%。不同稻作模式下水稻单位产量碳足迹为0.38~1.08 kg CO₂-eq.·kg^-1,其中双季稻模式下最高,再生稻模式下甬优2640的单位产量碳足迹最低。不同稻作模式产生的碳足迹主要来源于CH₄,其贡献率高达44.2%~71.5%。可见,再生稻种植模式能显著降低水稻全球增温潜势和碳排放强度。选用高产低碳排放的水稻优良品种并配套科学栽培技术,是有效降低稻田CH₄排放量和碳足迹、促进再生稻生产可持续发展的关键。     

Sensitivity of the carbon footprint of New Zealand milk to greenhouse gas metrics

Milk production is responsible for emitting a range of greenhouse gases (GHGs), mainly carbon dioxide (CO₂), nitrous oxide (N₂O) and methane (CH₄). In Life Cycle Assessments (LCA), the Global Warming Potential with a time horizon of 100 years (GWP100) is used almost universally to aggregate emissions of individual gases into so-called CO₂-equivalent emissions that are used to calculate the overall carbon footprint of milk production. However, there is growing awareness that, depending on the purpose of the LCA, metrics other than GWP100 could be justified and some would give a very different weighting for the short-lived gas CH₄ relative to the long-lived gases CO₂ and N₂O when calculating the carbon footprint. Pastoral dairy production systems at different levels of intensification differ in the balance of short- and long-lived GHGs associated with on- and off-farm emissions. Differences in the carbon footprint of different production systems could therefore be highly sensitive to the choice of GHG metric. Here we explore the extent to which alternative GHG metric choices would alter the carbon footprint of New Zealand milk production at different levels of intensification at national, regional and individual farm scales and compared to the carbon footprint of milk of selected European countries. We find that the ranking of different production systems and individual farms in terms of their carbon footprint is relatively robust against the choice of GHG metric, despite significant differences in their utilisation of pastures versus supplementary off-farm feed, fertiliser use and energy consumption at various stages of farm operations. However, there are instances where alternative GHG metric choices would fundamentally change the conclusions of LCA of different production systems, including whether a move towards higher or lower input systems would increase or decrease the average carbon footprint of milk production in New Zealand. Greater transparency about the implications of alternative GHG metrics for LCA, and the often inadvertent and implicit value judgements embedded in these metrics, would help ensure that policy decisions and consumer choices based on LCA indeed deliver the climate outcomes intended by end-users.     

UK emissions of the greenhouse gas nitrous oxide

Signatories of the Kyoto Protocol are obliged to submit annual accounts of their anthropogenic greenhouse gas emissions, which include nitrous oxide (N(2)O). Emissions from the sectors industry (3.8 Gg), energy (14.4 Gg), agriculture (86.8 Gg), wastewater (4.4 Gg), land use, land-use change and forestry (2.1 Gg) can be calculated by multiplying activity data (i.e. amount of fertilizer applied, animal numbers) with simple emission factors (Tier 1 approach), which are generally applied across wide geographical regions. The agricultural sector is the largest anthropogenic source of N(2)O in many countries and responsible for 75 per cent of UK N(2)O emissions. Microbial N(2)O production in nitrogen-fertilized soils (27.6 Gg), nitrogen-enriched waters (24.2 Gg) and manure storage systems (6.4 Gg) dominate agricultural emission budgets. For the agricultural sector, the Tier 1 emission factor approach is too simplistic to reflect local variations in climate, ecosystems and management, and is unable to take into account some of the mitigation strategies applied. This paper reviews deviations of observed emissions from those calculated using the simple emission factor approach for all anthropogenic sectors, briefly discusses the need to adopt specific emission factors that reflect regional variability in climate, soil type and management, and explains how bottom-up emission inventories can be verified by top-down modelling.     

The greenhouse gas value of ecosystems

As society faces the urgent need to mitigate climate change, it is critical to understand how various ecosystems contribute to the climate, and to express these contributions in terms that are meaningful to policymakers, economists, land managers, and other nonscience interest holders. Efforts to mitigate climate change call for quantification of the full greenhouse gas (GHG) effects of land use decisions, yet we lack an appropriate metric of the full GHG implications of maintaining a given ecosystem over a multiple year time frame. Here, we propose the concept of greenhouse gas value (GHGV) of ecosystems, which accounts for potential GHG release upon clearing of stored organic matter, annual GHG flux, and probable GHG exchanges resulting from disturbance. It treats these ecosystem–atmosphere exchanges in a time‐sensitive manner, thereby providing an appropriate framework for computing of the GHG consequences of any land use decision. To illustrate this concept, we provide estimates of the GHGV of various biome types (based on data compiled from the literature), disturbance regimes, and decisions on the treatment of time. We show that natural ecosystems generally have high GHGV's, whereas managed ecosystems generally have lower or negative GHGV's; that GHGV decreases with increasing probability of disturbance, and that decisions on the treatment of time can be important, affecting some ecosystem types more strongly than others. In addition, we show how GHGV may be used to quantify the full GHG effects of land‐use or land‐cover change in a thorough and rigorous manner. Finally, we provide comparisons of GHGV to other major paradigms for valuing the GHG contributions of ecosystems, showing that – for many purposes –GHGV is the most appropriate method of quantifying the GHG services of ecosystems.     

The greenhouse gas balance of European grasslands

The greenhouse gas (GHG) balance of European grasslands (EU‐28 plus Norway and Switzerland), including CO₂, CH₄ and N₂O, is estimated using the new process‐based biogeochemical model ORCHIDEE‐GM over the period 1961–2010. The model includes the following: (1) a mechanistic representation of the spatial distribution of management practice; (2) management intensity, going from intensively to extensively managed; (3) gridded simulation of the carbon balance at ecosystem and farm scale; and (4) gridded simulation of N₂O and CH₄ emissions by fertilized grassland soils and livestock. The external drivers of the model are changing animal numbers, nitrogen fertilization and deposition, land‐use change, and variable CO₂ and climate. The carbon balance of European grassland (NBP) is estimated to be a net sink of 15 ± 7 g C m^?2 year^?1 during 1961–2010, equivalent to a 50‐year continental cumulative soil carbon sequestration of 1.0 ± 0.4 Pg C. At the farm scale, which includes both ecosystem CO₂ fluxes and CO₂ emissions from the digestion of harvested forage, the net C balance is roughly halved, down to a small sink, or nearly neutral flux of 8 g C m^?2 year^?1. Adding CH₄ and N₂O emissions to net ecosystem exchange to define the ecosystem‐scale GHG balance, we found that grasslands remain a net GHG sink of 19 ± 10 g C‐CO₂ equiv. m^?2 year^?1, because the CO₂ sink offsets N₂O and grazing animal CH₄ emissions. However, when considering the farm scale, the GHG balance (NGB) becomes a net GHG source of ?50 g C‐CO₂ equiv. m^?2 year^?1. ORCHIDEE‐GM simulated an increase in European grassland NBP during the last five decades. This enhanced NBP reflects the combination of a positive trend of net primary production due to CO₂, climate and nitrogen fertilization and the diminishing requirement for grass forage due to the Europe‐wide reduction in livestock numbers.     

基于本土参数的流域生态足迹评估与不确定分析

产量因子和均衡因子是生态足迹模型的关键参数,评估其取值的不确定性对完善生态足迹核算模型具有重要意义。以牛栏江流域为例,应用生态足迹模型评估了2014年整个流域及流域内11个区县的生态足迹与生态承载力,通过计算本土产量因子并与国内外常用值对比,进行流域生态足迹不确定性分析。研究结果表明:2014年牛栏江流域生态足迹为3521404 ghm~2(全球公顷),可利用生物承载力为2338535 ghm~2,处于不可持续发展状态,其中官渡区生态超载率最高。不同研究中均衡因子、产量因子取值差异较大,其中耕地的均衡因子最大值是最小值的4.16倍,草地的产量因子最大值是最小值的4.16倍;采用均衡因子和产量因子最大值计算所得流域生态足迹、生态承载力,生态赤字分别是最小值的2.5倍、3.9倍、1.4倍。由于牛栏江流域特殊的气候和地形以及畜牧业、渔业发展程度低,因此计算生态足迹时需要进行详细的分类,不能简单的采用全球及全国的因子。     

Estimating the impact of clinical mastitis in dairy cows on greenhouse gas emissions using a dynamic stochastic simulation model: a case study

The increasing attention for global warming is likely to contribute to the introduction of policies or other incentives to reduce greenhouse gas (GHG) emissions related to livestock production, including dairy. The dairy sector is an important contributor to GHG emissions. Clinical mastitis (CM), an intramammary infection, results in reduced milk production and fertility, increases culling and mortality of cows and, therefore, has a negative impact on the efficiency (output/input) of milk production. This may increase GHG emissions per unit of product. Our objective was to estimate the impact of CM in dairy cows on GHG emissions of milk production for the Dutch situation. A dynamic stochastic simulation model was developed to simulate the dynamics and losses of CM for individual lactations. Cows receive a parity (1 to 5+), a milk production and a calving interval (CI). Based on the parity, cows have a risk of CM, with a maximum of three cases in a lactation. Pathogens causing CM were classified as gram-positive bacteria, gram-negative bacteria, or other. Based on the parity and pathogen combinations, cows had a reduced milk production, discarded milk, prolonged CI and a risk of removal (culling and mortality) that reduce productivity of dairy cows and therefore increase GHG emissions per unit of product. Using life cycle assessment, emissions of GHGs were estimated from cradle to farm gate for processes along the milk production chain that are affected by CM. Processes included were feed production, enteric fermentation, and manure management. Emissions of GHGs were expressed as kg CO₂ equivalents per ton of fat-and-protein-corrected milk (kg CO₂e/t FPCM). Emissions of cows with CM increased on average by 57.5 (6.2%) kg CO₂e/t FPCM compared with cows without CM. This increase was caused by removal (39%), discarded milk (38%), reduced milk production (17%) and prolonged CI (6%). The GHG emissions increased by 48 kg CO₂e/t FPCM for cows with one case of CM, by 69 kg CO₂e/t FPCM for cows with two cases of CM and by 92 kg CO₂e/t FPCM for cows with three cases of CM compared with cows without CM. Preventing CM can be an effective strategy for farmers to reduce GHG emissions and can contribute to sustainable development of the dairy sector, because this also can improve the income of farmers and the welfare of cows. The impact of CM on GHG emissions, however, will vary between farms due to environmental conditions and management practices.     

中国湿地温室气体清单编制研究进展

湿地是重要的土地利用类型之一,在陆地生态系统碳循环中起重要作用。在缔约国向《联合国气候变化框架公约》提交的温室气体国家清单报告中,湿地作为“农业、林业及其他土地利用(AFOLU)”的一部分,因其不确定性较高而备受关注。自2006年以来,IPCC先后发布了《2006 IPCC国家温室气体清单指南》、《2013 IPCC 2006国家温室气体清单指南的增补：湿地》和《IPCC 2006年国家温室气体清单指南2019精细化》,为缔约国提供了清单编制的参考方法学。然而,IPCC指南中对湿地的定义和分类与中国现行的土地利用类型和并不统一,其提供的缺省参数对中国的研究亦未充分整合。因此,亟需在IPCC框架下开发适合中国的湿地温室气体清单方法学及参数库,以降低清单编制的不确定性。综述了IPCC湿地清单编制的方法学与中国湿地清单的研究进展,主要包括(1)比较了IPCC三部指南中的湿地清单的方法学,梳理了后两部对《2006 IPCC国家温室气体清单指南》在湿地类型、评估方法和缺省参数的更新内容;(2)比较了中国湿地清单编制与其他湿地温室气体研究结果的差异并探讨原因;(3)梳理了IPCC三部清单指南中湿地...     

Variability in greenhouse gas footprints of the global wind farm fleet

While technological characteristics largely determine the greenhouse gas (GHG) emissions during the construction of a wind farm and meteorological circumstances the actual electricity production, a thorough analysis to quantify the GHG footprint variability (in g CO₂eq/kWh electricity produced) between wind farms is still lacking at the global scale. Here, we quantified the GHG footprint of 26,821 wind farms located across the globe, combining turbine-specific technological parameters, life-cycle inventory data, and location- and temporal-specific meteorological information. These wind farms represent 79% of the 651 global wind (GW) capacity installed in 2019. Our results indicate a median GHG footprint for global wind electricity of 10 g CO₂eq/kWh, ranging from 4 to 56 g CO₂eq/kWh (2.5th and 97.5th percentiles). Differences in the GHG footprint of wind farms are mainly explained by spatial variability in wind speed, followed by whether the wind farm is located onshore or offshore, the turbine diameter, and the number of turbines in a wind farm. We also provided a metamodel based on these four predictors for users to be able to easily obtain a first indication of GHG footprints of new wind farms considered. Our results can be used to compare the GHG footprint of wind farms to one another and to other sources of electricity in a location-specific manner.     

Progress in the studies on the greenhouse gas emissions from reservoirs

The green credentials of hydroelectricity in terms of greenhouse-gas (GHG) emissions have been tarnished with the finding of the researches on GHG emissions from hydroelectric reservoirs in the last two decades. Substantial amounts of GHGs release from the tropical reservoirs, especially methane (CH₄) from Brazil’s Amazonian areas. CH₄ contributes strongly to climate change because it has a global warming potential (GWP) 24 times higher than carbon dioxide (CO₂) on a per molecule basis over a 100-year time horizon. GHGs may emit from reservoirs through four different pathways to the atmosphere: (1) diffusive flux at the reservoir surface, (2) gas bubble flux in the shallow zones of a reservoir, (3) water degassing flux at the outlet of the powerhouse downstream of turbines and spillways, and (4) flux across the air–water interface in the rivers downstream of the dams. This paper reviewed the productions and emissions of CH₄, CO₂, and N₂O in reservoirs, and the environmental variables influencing CH₄ and CO₂ emissions were also summarized. Moreover, the paper combined with the progress of GHG emissions from Three Gorges Reservoir and proposed three crucial problems to be resolved on GHG emissions from reservoirs at present, which would be benefit to estimate the total GHG emissions from Three Gorges Reservoir accurately.     

Estimating the environmental Kuznets curve for ecological footprint at the global level: A spatial econometric approach

The national ecological footprint of both consumption and production are significantly spatially autocorrelated at global level. This violates the assumption of independently distributed errors of most conventional estimation techniques. Using a spatial econometric approach, this paper re-examine the relationship between economic growth and environmental impact for indicator of ecological footprint. The results do not show evidence of inverted U-shape Environmental Kuznets Curve. The domestic ecological footprint of consumption (or production) was obviously influenced by the ecological footprint of consumption (or production), income and biocapacity in neighborhood countries. We also found that the consumption footprint is more sensitive to domestic income, while production footprint is more sensitive to domestic biocapacity, which is often unnoticed in EKC hypothesis analyses that focus exclusively on the consumption-based or production-based indictors.     

Using LCA to examine greenhouse gas abatement policy

The site-generic approach currently adopted by the Life Cycle Assessment (LCA) methodology introduces uncertainties into the impact assessment phase of an LCA study. These uncertainties are greatest for localised and short-lived problems but are less significant for long lasting, cumulative environmental effects. Indeed, the reliability of LCA results is high for problems that manifest at a global scale. Nevertheless, even though these results are considered accurate, it is still often unclear as to their relevance in terms of policy development and decision-making. Therefore, this paper demonstrates how LCA can be used to determine the efficacy of policies aimed at reducing a product system’s contribution to global environmental problems. We accomplish this aim by presenting a case study that evaluates the greenhouse gas contributions of each stage in the life cycle of containerboard packaging and the potential impact on emissions of various policy options available to decision makers. Our analysis showed that in general the most useful strategy was to recycle the used packaging. However, our analysis also indicated that when measures are taken to eliminate sources of methane emissions and encourage the use of plantation timber then recycling is no longer beneficial from a greenhouse perspective. This is because the process energy required in the form of gas and electricity is substantially greater for containerboard manufactured from recycled material than it is for virgin fibre.     

Reducing greenhouse gas emissions of a heterogeneous vehicle fleet

Recent research on the vehicle routing problem attempts to integrate so-called “green” aspects into classical planning models. The minimization of transport-related emissions (especially CO₂) instead of driving distances is an important integration approach. Within this paper, we propose an approach which is focusing on the reduction of CO₂ emissions caused by transportation. Based on the observation that vehicles with different maximal payload values have different payload-dependent fuel consumption characteristics, we integrate into Dantzig’s classical vehicle routing model the option of choosing vehicles of different size for route fulfillment. Then, the Emission Minimization Vehicle Routing Problem with Vehicle Categories (EVRP-VC) is introduced. It aims at minimizing the fuel consumption, respectively CO₂ emissions instead of the driving distances. Comprehensive computational experiments with CPLEX are conducted to evaluate the EVRP-VC. A major finding is that the quantity of fuel needed to serve a given request portfolio can be reduced tremendously by using an inhomogeneous fleet with vehicles of different size.     

Estimation of greenhouse gas emissions from sewer pipeline system

Purpose

The aim of this study was to estimate the total greenhouse gas (GHG) emissions generated from whole life cycle stages of a sewer pipeline system and suggest the strategies to mitigate GHG emissions from the system.

Methods

The process-based life cycle assessment (LCA) with a city-scale inventory database of a sewer pipeline system was conducted. The GHG emissions (direct, indirect, and embodied) generated from a sewer pipeline system in Daejeon Metropolitan City (DMC), South Korea, were estimated for a case study. The potential improvement actions which can mitigate GHG emissions were evaluated through a scenario analysis based on a sensitivity analysis.

Results and discussion

The amount of GHG emissions varied with the size (150, 300, 450, 700, and 900 mm) and materials (polyvinyl chloride (PVC), polyethylene (PE), concrete, and cast iron) of the pipeline. Pipes with smaller diameter emitted less GHG, and the concrete pipe generated lower amount of GHG than pipes made from other materials. The case study demonstrated that the operation (OP) stage (3.67 × 10⁴ t CO₂eq year^?1, 64.9%) is the most significant for total GHG emissions (5.65 × 10⁴ t CO₂eq year^?1) because a huge amount of CH₄ (3.51 × 10⁴ t CO₂eq year^?1) can be generated at the stage due to biofilm reaction in the inner surface of pipeline. Mitigation of CH₄ emissions by reducing hydraulic retention time (HRT), optimizing surface area-to-volume (A/V) ratio of pipes, and lowering biofilm reaction during the OP stage could be effective ways to reduce total GHG emissions from the sewer pipeline system. For the rehabilitation of sewer pipeline system in DMC, the use of small diameter pipe, combination of pipe materials, and periodic maintenance activities are suggested as suitable strategies that could mitigate GHG emissions.

Conclusions

This study demonstrated the usability and appropriateness of the process-based LCA providing effective GHG mitigation strategies at a city-scale sewer pipeline system. The results obtained from this study could be applied to the development of comprehensive models which can precisely estimate all GHG emissions generated from sewer pipeline and other urban environmental systems.

     

城市温室气体排放清单编制研究进展

温室气体排放清单是目前最常用的城市碳排放核算方法,有助于在大尺度上了解城市不同行业或部门的温室气体排放情况.然而,中国城市温室气体清单研究刚刚起步,研究成果还不多,尚缺乏系统、规范的城市温室气体研究方法和指标体系.概述了城市温室气体排放清单的主要参考编制方法,介绍了国内外城市温室气体清单的编制情况,对目前城市温室气体清单编制的特点进行了分析,总结了城市温室气体清单与国家温室气体清单在关键排放源、编制模式、方法体系等方面的差异;在此基础上结合我国城市实际,对适合中国城市的温室气体清单编制方法进行了探索,并针对清单编制过程中存在的具体问题提出了建议;最后对未来城市温室气体清单的发展趋势进行了展望,以期为中国温室气体清单编制及研究提供借鉴.     

A meta-analysis of the life cycle greenhouse gas balances of microalgae biodiesel

Purpose

Microalgae biodiesel has attracted considerable attention as a potential substitute for fossil fuels and biodiesel from food crops. Nevertheless, its reported climate impacts in the scientific literature vary significantly. This article describes and synthesizes the range of results found in the life cycle assessment (LCA) literature regarding microalgae biodiesel studies to investigate whether particular parameters, e.g. technologies, were associated with higher or lower greenhouse gas (GHG) emissions so that a best practice can be inferred from currently available LCA data and thereby recommended.

Methods

A systematic literature review and meta-regression analysis (MRA) of 36 LCA studies that report on the GHG emissions of microalgae biodiesel was conducted. An assessment of key aspects, including modelling choices and technologies, was performed. Furthermore, MRA models were formulated considering several variables of interest describing both technical and modelling choices to identify the main causes for the variability in GHG emissions per MJ of biodiesel. Variables chosen include: microalgae species; culture medium; cultivation system; source of CO₂; extraction technology; conversion technology; system boundary; geographical scope; inclusion or exclusion of capital goods; and how multifunctionality was handled.

Results and discussion

The reviewed studies altogether reported 308 results ranging from ?0.7 to 3.8 kg CO₂ eq. MJ^?1_biodiesel, portraying 19 different system configurations. Despite the comprehensive range of variables assessed, the models generated could not plausibly explain that the variability in GHG emissions depends either on the technologies considered or on the methodological choices adopted. However, the following relationships could be observed: location in Europe and high oil productivity were associated with lower emissions, whilst dry extraction should be avoided for leading to higher GHG emissions, on average.

Conclusions

There is a large degree of variability within the technologies considered, as well as the methodological choices adopted, so that no robust conclusions could be drawn from the MRA. Notwithstanding, average GHG emissions reported were more than twice as high as fossil diesel and, while there are some studies showing large benefits, none of the various algae technologies performed consistently better than fossil diesel, questioning the climate-mitigation potential of microalgae biodiesel.

     

氮沉降对森林土壤主要温室气体通量的影响

大气氮沉降已经并将继续对森林土壤主要温室气体(CO2、CH4和N2O)通量产生影响.综述了国内外氮沉降对森林土壤主要温室气体通量影响及其机理的研究现状.由于森林类型、土壤N状况、氮沉降量及沉降类型等不同,氮沉降对森林土壤主要温室气体通量的影响主要表现为抑制、促进和不显著3种效果.在N限制的森林中,氮沉降对土壤主要温室气体通量无显著影响,或促进土壤CO2排放;在"N饱和"的森林中,氮沉降可减少土壤CO2排放,抑制对大气CH4的吸收,增加N2O排放.分析了产生以上影响效果的作用机理,介绍了氮沉降对森林土壤主要温室气体通量影响的研究方法,探讨了该领域存在的问题及未来研究的方向.     

Effects of nitrogen deposition on the greenhouse gas fluxes from forest soils

Nitrogen (N) deposition can alter the rates of microbial N- and C- turnover, and thus can affect the fluxes of greenhouse gases (GHG, e.g., CO₂, CH₄, and N₂O) from forest soils. The effects of N deposition on the GHG fluxes from forest soils were reviewed in this paper. N deposition to forest soils have shown variable effects on the soil GHG fluxes from forest, including increases, decreases or unchanged rates depending on forest type, N status of the soil, and the rate and type of atmospheric N deposition. In forest ecosystems where biological processes are limited by N supply, N additions either stimulate soil respiration or have no significant effect, whereas in “N saturated” forest ecosystems, N additions decrease CO₂ emission, reduce CH₄ oxidation and elevate N₂O flux from the soil. The mechanisms and research methods about the effects of N deposition on GHG fluxes from forest soils were also reviewed in this paper. Finally, the present and future research needs about the effects of N deposition on the GHG fluxes from forest soils were discussed.     

Accounting for greenhouse gas emissions from the degradation of chemicals in the environment

The International Journal of Life Cycle Assessment - The degradation of chemicals in the environment is often excluded from life cycle assessment (LCA) studies. This paper describes a method to...     

Spatial greenhouse gas emissions from US county corn production

Purpose

Stakeholders from across supply chains have been prompted to explore ways to reduce the environmental burdens of corn production. To effectively manage these environmental impacts, spatially explicit information accounting for the differences in growing conditions and production practices across the production landscape is essential, allowing for high impact intensity corn to be identified and prioritized for improvement. To support these sustainability efforts, this study examines the spatially explicit life cycle greenhouse gas emissions of US county corn production, providing the most comprehensive assessment to date.

Methods

A streamlined spatial life cycle assessment is conducted, focusing on the three key hotspots of corn production for spatial differentiation at the county scale across the contiguous USA, accounting for almost 60% of total average cradle-to-farm gate impacts. Variations in nitrogen fertilization types and rates, N₂O emission rates, and irrigation emission rates are specifically revealed. Spatially distinguished hotspot inputs and related emissions are combined with static national average emission estimates from all other inputs used in corn production to gain a full picture and understand the relative contributions to total cradle-to gate impacts.

Results and discussion

Results show significant variation across corn producing counties, states, and regions. High impact priority locations are highlighted and key contributors of impact for each location are illuminated, providing critical information on the spatially explicit levers to reduce impacts. Results increase the generalizability of emission estimates using expected yields to characterize emission intensity, enabling more practical integration into company supply chain sustainability assessments to align with the time horizons in which decisions are made.

Conclusions

Streamlined life cycle assessment methods are an effective way to characterize spatial heterogeneity around key contributors of impact, helping deliver the necessary information for companies, stakeholders, and policy makers to target their influence to reduce these emissions through various engagement efforts.