Author Correction: Greenhouse gas emissions from global production and use of nitrogen synthetic fertilisers in agriculture.
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ABSTRACT:
SUBMITTER: Menegat S
PROVIDER: S-EPMC9671884 | biostudies-literature | 2022 Nov
REPOSITORIES: biostudies-literature
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Author Correction: Greenhouse gas emissions from global production and use of nitrogen synthetic fertilisers in agriculture.
Menegat Stefano S Ledo Alicia A Tirado Reyes R
Scientific reports 20221117 1
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Project description:The global agri-food system relies on synthetic nitrogen (N) fertilisation to increase crop yields, yet the use of synthetic N fertiliser is unsustainable. In this study we estimate global greenhouse (GHG) emissions due to synthetic N fertiliser manufacture, transportation, and field use in agricultural systems. By developing the largest field-level dataset available on N2O soil emissions we estimate national, regional and global N2O direct emission factors (EFs), while we retrieve from the literature the EFs for indirect N2O soil emissions, and for N fertiliser manufacturing and transportation. We find that the synthetic N fertiliser supply chain was responsible for estimated emissions of 1.13 GtCO2e in 2018, representing 10.6% of agricultural emissions and 2.1% of global GHG emissions. Synthetic N fertiliser production accounted for 38.8% of total synthetic N fertiliser-associated emissions, while field emissions accounted for 58.6% and transportation accounted for the remaining 2.6%. The top four emitters together, China, India, USA and EU28 accounted for 62% of the total. Historical trends reveal the great disparity in total and per capita N use in regional food production. Reducing overall production and use of synthetic N fertilisers offers large mitigation potential and in many cases realisable potential to reduce emissions.
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Project description:Agriculture serves as both a source and a sink of global greenhouse gases (GHGs), with agricultural intensification continuing to contribute to GHG emissions. Climate-smart agriculture, encompassing both nature- and technology-based actions, offers promising solutions to mitigate GHG emissions. We synthesized global data, between 1990 and 2021, from the Food and Agriculture Organization (FAO) of the United Nations to analyze the impacts of agricultural activities on global GHG emissions from agricultural land, using structural equation modeling. We then obtained predictive estimates of agricultural GHG emissions for the future period of 2022-2050 using deep-learning models. The FAO data show that, from 1990 to 2021, global livestock numbers, inorganic nitrogen (N) fertilizer use, crop residue, and irrigation area increased by 27%, 47%, 49%, and 37%, respectively. The increased livestock numbers contributed to the increases in CH4 and N2O emissions, while inorganic N fertilizer, crop residue, and irrigation mainly contributed to the increases in N2O emissions. Emissions of CO2 decreased because of a 29% reduction in net forest loss. As a result of the reduced deforestation emissions, the overall agricultural GHG emissions declined from 11.50 to 10.89 GtCO2eq from 1990 to 2021 despite the increases in livestock numbers, inorganic N fertilizer, crop residue, and irrigation. Looking ahead, our model predicts that if current agricultural trends persist, GHG emissions will rise to 11.82 ± 0.07 GtCO2eq in 2050. However, maintaining agricultural GHG emissions at the 2021 level through 2050 is possible if the rate of reduction in net forest loss is doubled. Furthermore, if the rate is tripled, agricultural GHG emissions can be limited to 9.85 ± 0.07 GtCO2eq in 2050. Our findings suggest that reductions in agricultural GHG emissions, alongside sustainable agricultural intensification and climate-smart agricultural practices, can be achieved through parallel efforts emphasizing accelerated forest conservation.
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Project description: Not available
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Project description:[This corrects the article DOI: 10.1371/journal.pone.0062228.].
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Project description:In an effort to mitigate anthropogenic effects on the global climate system, industrialised countries are required to quantify and report, for various economic sectors, the annual emissions of greenhouse gases from their several sources and the absorption of the same in different sinks. These estimates are uncertain, and this uncertainty must be communicated effectively, if government bodies, research scientists or members of the public are to draw sound conclusions. Our interest is in communicating the uncertainty in estimates of greenhouse gas emissions from agriculture to those who might directly use the results from the inventory. We tested six methods of communication. These were: a verbal scale using the IPCC calibrated phrases such as 'likely' and 'very unlikely'; probabilities that emissions are within a defined range of values; confidence intervals for the expected value; histograms; box plots; and shaded arrays that depict the probability density of the uncertain quantity. In a formal trial we used these methods to communicate uncertainty about four specific inferences about greenhouse gas emissions in the UK. Sixty four individuals who use results from the greenhouse gas inventory professionally participated in the trial, and we tested how effectively the uncertainty about these inferences was communicated by means of a questionnaire. Our results showed differences in the efficacy of the methods of communication, and interactions with the nature of the target audience. We found that, although the verbal scale was thought to be a good method of communication it did not convey enough information and was open to misinterpretation. Shaded arrays were similarly criticised for being open to misinterpretation, but proved to give the best impression of uncertainty when participants were asked to interpret results from the greenhouse gas inventory. Box plots were most favoured by our participants largely because they were particularly favoured by those who worked in research or had a stronger mathematical background. We propose a combination of methods should be used to convey uncertainty in emissions and that this combination should be tailored to the professional group.
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Project description:Agricultural production is strongly affected by and a major contributor to climate change. Agriculture and land-use change account for a quarter of total global emissions of greenhouse gases (GHG). Agriculture receives around US$600 billion per year worldwide in government support. No rigorous quantification of the impact of this support on GHG emissions has been available. This article helps fill the void. Here, we find that, while over the years the government support has incentivized the development of high-emission farming systems, at present, the support only has a small impact in terms of inducing additional global GHG emissions from agricultural production; partly because support is not systematically biased towards high-emission products, and partly because support generated by trade protection reduces demand for some high-emission products by raising their consumer prices. Substantially reducing GHG emissions from agriculture while safeguarding food security requires a more comprehensive revamping of existing support to agriculture and food consumption.
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Project description:Global aquaculture makes an important contribution to food security directly (by increasing food availability and accessibility) and indirectly (as a driver of economic development). In order to enable sustainable expansion of aquaculture, we need to understand aquaculture's contribution to global greenhouse gas (GHG) emissions and how it can be mitigated. This study quantifies the global GHG emissions from aquaculture (excluding the farming of aquatic plants), with a focus on using modern, commercial feed formulations for the main species groups and geographic regions. Here we show that global aquaculture accounted for approximately 0.49% of anthropogenic GHG emissions in 2017, which is similar in magnitude to the emissions from sheep production. The modest emissions reflect the low emissions intensity of aquaculture, compared to terrestrial livestock (in particular cattle, sheep and goats), which is due largely to the absence of enteric CH4 in aquaculture, combined with the high fertility and low feed conversion ratios of finfish and shellfish.
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Project description:Unvegetated, intertidal sandflats play a critical role in estuarine carbon and nutrient dynamics. However, these ecosystems are under increasing threat from anthropogenic stressors, especially nitrogen enrichment. While research in this area typically focuses on sediment-water exchanges of carbon and nutrients during tidal inundation, there remain significant gaps in our understanding of GHG (Greenhouse Gas) fluxes during tidal emergence. Here we use in situ benthic chambers to quantify GHG fluxes during tidal emergence and investigate the impact of nitrogen enrichment on these fluxes. Our results demonstrate significant differences in magnitude and direction of GHG fluxes between emerged and submerged flats, demonstrating the importance of considering tidal state when estimating GHG emissions from intertidal flats. These responses were related to differences in microphytobenthic and macrofaunal activity, illustrating the important role of ecology in mediating fluxes from intertidal flats. Our results further demonstrate that nitrogen enrichment of 600 gN m-2 was associated with, on average, a 1.65x increase in CO2 uptake under light (photosynthetically active) conditions and a 1.35x increase in CO2 emission under dark conditions, a 3.8x increase in CH4 emission and a 15x increase in N2O emission overall. This is particularly significant given the large area intertidal flats cover globally, and their increasing exposure to anthropogenic stressors.
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Project description:Greenhouse gas emissions from wetlands are significantly promoted by global nitrogen input for changing the rate of soil carbon and nitrogen cycling, and are substantially affected by soil labile carbon and nitrogen conversely. However, the driving mechanism by which soil labile carbon and nitrogen affect greenhouse gas emissions from wetland ecosystems under global nitrogen input is not well understood. Working out the driving factor of nitrogen input on greenhouse gas emissions from wetlands is critical to reducing global warming from nitrogen input. Thus, we synthesized 72 published studies (2144 paired observations) of greenhouse gas fluxes and soil labile compounds of carbon and nitrogen (ammonium, nitrate, dissolved organic carbon, soil microbial biomass nitrogen and carbon), to understand the effects of labile carbon and nitrogen on greenhouse gas emissions under global nitrogen input. Across the data set, nitrogen input significantly promoted carbon dioxide, methane and nitrous oxide emissions from wetlands. In particular, at lower nitrogen rates (<100 kg ha-1·yr-1) and with added ammonium compounds, freshwater wetland significantly promoted carbon dioxide and methane emissions. Peatland was the largest nitrous oxide source under these conditions. This meta-analysis also revealed that nitrogen input stimulated dissolved organic carbon, ammonium, nitrate, microbial biomass carbon and microbial biomass nitrogen accumulation in the wetland ecosystem. The variation-partitioning analysis and structural equation model were used to analyze the relationship between the greenhouse gas and labile carbon and nitrogen further. These results revealed that dissolved organic carbon (DOC) is the primary factor driving greenhouse gas emission from wetlands under global nitrogen input, whereas microbial biomass carbon (MBC) more directly affects greenhouse gas emission than other labile carbon and nitrogen.
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Project description:Climate change represents a serious threat to life in earth. Agriculture releases significant emissions of greenhouse gases (GHG), but also offers low-cost opportunities to mitigate GHG emissions. This paper assesses agricultural GHG emissions in Aragon, one important and representative region for agriculture in Spain. The Marginal Abatement Cost Curve (MACC) approach is used to analyze the abatement potential and cost-efficiency of mitigation measures under several scenarios, with and without taking into account the interaction among measures and their transaction costs. The assessment identifies the environmental and economic outcomes of different combinations of measures, including crop, livestock and forest measures. Some of these measures are win-win, with pollution abatement at negative costs to farmers. Moreover, we develop future mitigation scenarios for agriculture toward the year 2050. Results highlight the trade-offs and synergies between the economic and environmental outcomes of mitigation measures. The biophysical processes underlying mitigation efforts are assessed taking into account the significant effects of interactions between measures. Interactions reduce the abatement potential and worsen the cost-efficiency of measures. The inclusion of transaction costs provides a better ranking of measures and a more accurate estimation of implementation costs. The scenario analysis shows how the combinations of measures could reduce emissions by up to 75% and promote sustainable agriculture in the future.
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