Food systems-encompassing activities in food production, land-use change, supply chains and waste management-contribute significantly to climate change. Recent estimates indicate that food systems produce over 30% of annual anthropogenic greenhouse gas (GHG) emissions (about 20% of CO2, 50% of CH4, and 75% of N2O), with the Intergovernmental Panel on Climate Change (IPCC) estimating a notably broad range of 23%-42% of global GHG emissions. This paper synthesizes current research on the contributions of food systems to climate change, highlights challenges in quantifying their impact and proposes a harmonized accounting framework for more effective climate action. We recommend that an expert committee aligned with the IPCC develop guidance for food systems emissions accounting in four key areas, including: (1) defining system boundaries and nomenclature; (2) developing protocols to allocate broader sectoral emissions to food systems; (3) prioritizing critical areas for research into activity data and emissions factors; and (4) developing a balanced framework for evaluating the impact of mitigation interventions in light of other food systems imperatives. The committee should be integrated into two key international policy processes-the United Nations Framework Convention on Climate Change and the United Nations Food Systems Summit-to support coordinated action towards global net-zero goals. Guidance from the committee could significantly improve the ability of governments, companies, and researchers to estimate, report, monitor and ultimately reduce the climate impacts of food systems.

Cooling degree days provide a simple indicator to represent how temperature drives energy demand for cooling. We investigate, at country level, the changes in cooling degree days worldwide in a recent twenty-one-year period starting in 2000. A new database, jointly generated by CMCC and IEA based on ERA5 reanalysis’ global gridded data, is used for the analysis. In contrast to the existent literature, the factors of population-weighting and humidity are considered, which affect the magnitude and the spatial distribution of these changes. Annual tendencies show a general increase of cooling degree days over the different countries, fostering more energy consumption for cooling demand, as confirmed by some regional studies. We also focus on the temporal clustering, to measure if peaks occur evenly random or tend to cluster in shorter periods. We stress that including humidity is important both for general tendencies and clustering. India, Cambodia, Thailand and Vietnam represent the emerging countries where this effect is stronger.

We present results from the FAOSTAT emissions shares database, covering emissions from agri-food systems and their shares to total anthropogenic emissions for 196 countries and 40 territories for the period 1990–2019. We find that in 2019, global agri-food system emissions were 16.5 (95 %; CI range: 11–22) billion metric tonnes (Gt CO2 eq. yr−1), corresponding to 31 % (range: 19 %–43 %) of total anthropogenic emissions. Of the agri-food system total, global emissions within the farm gate – from crop and livestock production processes including on-farm energy use – were 7.2 Gt CO2 eq. yr−1; emissions from land use change, due to deforestation and peatland degradation, were 3.5 Gt CO2 eq. yr−1; and emissions from pre- and post-production processes – manufacturing of fertilizers, food processing, packaging, transport, retail, household consumption and food waste disposal – were 5.8 Gt CO2 eq. yr−1. Over the study period 1990–2019, agri-food system emissions increased in total by 17 %, largely driven by a doubling of emissions from pre- and post-production processes. Conversely, the FAOSTAT data show that since 1990 land use emissions decreased by 25 %, while emissions within the farm gate increased 9 %. In 2019, in terms of individual greenhouse gases (GHGs), pre- and post-production processes emitted the most CO2 (3.9 Gt CO2 yr−1), preceding land use change (3.3 Gt CO2 yr−1) and farm gate (1.2 Gt CO2 yr−1) emissions. Conversely, farm gate activities were by far the major emitter of methane (140 Mt CH4 yr−1) and of nitrous oxide (7.8 Mt N2O yr−1). Pre- and post-production processes were also significant emitters of methane (49 Mt CH4 yr−1), mostly generated from the decay of solid food waste in landfills and open dumps. One key trend over the 30-year period since 1990 highlighted by our analysis is the increasingly important role of food-related emissions generated outside of agricultural land, in pre- and post-production processes along the agri-food system, at global, regional and national scales. In fact, our data show that by 2019, pre- and post-production processes had overtaken farm gate processes to become the largest GHG component of agri-food system emissions in Annex I parties (2.2 Gt CO2 eq. yr−1). They also more than doubled in non-Annex I parties (to 3.5 Gt CO2 eq. yr−1), becoming larger than emissions from land use change. By 2019 food supply chains had become the largest agri-food system component in China (1100 Mt CO2 eq. yr−1), the USA (700 Mt CO2 eq. yr−1) and the EU-27 (600 Mt CO2 eq. yr−1). This has important repercussions for food-relevant national mitigation strategies, considering that until recently these have focused mainly on reductions of non-CO2 gases within the farm gate and on CO2 mitigation from land use change. The information used in this work is available as open data with DOI https://doi.org/10.5281/zenodo.5615082 (Tubiello et al., 2021d). It is also available to users via the FAOSTAT database (https://www.fao.org/faostat/en/#data/EM; FAO, 2021a), with annual updates.

Fossil-fuel-based energy use in agriculture leads to CO2 and non-CO2 emissions. We focus on emissions generated within the farm gate and from fisheries, providing information relative to the period 1970–2019, for both energy use, as input activity data and the associated greenhouse gas (GHG) emissions. Country-level information is generated from United Nations Statistics Division (UNSD) and International Energy Agency (IEA) data on energy in agriculture (including forestry and fisheries), relative to use of gas/diesel oil, motor gasoline, liquefied petroleum gas (LPG), natural gas, fuel oil and coal. Electricity used within the farm gate is also quantified, while recognizing that the associated emissions are generated elsewhere. We find that, in 2019, annual emissions from energy use in agriculture were about 523 million tonnes (Mt CO2eq yr−1​​​​​​​), while when including electricity they were 1029 Mt CO2eq yr−1, having increased 7 % from 1990. The largest emission increase from on-farm fuel combustion was from LPG (32 %), whereas significant decreases were observed for coal (−55 %), natural gas (−50 %), motor gasoline (−42 %) and fuel oil (−37 %). Conversely, the use of electricity and the associated indirect emissions increased 3-fold over the 1990–2019 period, thus becoming the largest emission source from energy use in agriculture since 2005. Overall, the global trends were a result of counterbalancing effects: marked decreases in developed countries in 2019 compared to 1990 (−273 Mt CO2eq yr−1) were masked by slightly larger increases in developing and emerging economies (+339 Mt CO2eq yr−1). The information used in this work is available as open data at https://doi.org/10.5281/zenodo.5153241 (Tubiello and Pan, 2021). The relevant Food and Agriculture Organization Corporate Statistical Database (FAOSTAT) (FAO, 2021b) on emissions is maintained and updated annually by FAO.

New estimates of greenhouse gas (GHG) emissions from the food system were developed at the country level, for the period 1990–2018, integrating data from crop and livestock production, on-farm energy use, land use and land use change, domestic food transport and food waste disposal. With these new country-level components in place, and by adding global and regional estimates of energy use in food supply chains, we estimate that total GHG emissions from the food system were about 16 CO2eq yr−1 in 2018, or one-third of the global anthropogenic total. Three quarters of these emissions, 13 Gt CO2eq yr−1, were generated either within the farm gate or in pre- and post-production activities, such as manufacturing, transport, processing, and waste disposal. The remainder was generated through land use change at the conversion boundaries of natural ecosystems to agricultural land. Results further indicate that pre- and post-production emissions were proportionally more important in developed than in developing countries, and that during 1990–2018, land use change emissions decreased while pre- and post-production emissions increased. We also report results on a per capita basis, showing world total food systems per capita emissions decreasing during 1990–2018 from 2.9 to 2.2 t CO2eq cap−1, with per capita emissions in developed countries about twice those in developing countries in 2018. Our findings also highlight that conventional IPCC categories, used by countries to report emissions in the National GHG inventory, systematically underestimate the contribution of the food system to total anthropogenic emissions. We provide a comparative mapping of food system categories and activities in order to better quantify food-related emissions in national reporting and identify mitigation opportunities across the entire food system.

This paper develops a methodology for the estimation of Energy Physical Supply and Use Tables (E-PSUTs) based on the IEA’s World Energy Balances (WEB). The tables are similar to those proposed by the United Nations System of Environmental Economic Accounting. However, they fully exploit, and are consistent, with the information on fuel transformation processes available in the WEB. The E-PSUTs can be used to derive energy indicators in physical units. Additionally, they can be used in a hybrid methodological approach to link global energy production and consumption in physical units with global production and consumption in monetary units, allowing the development of indicators to better understand the multiple links between energy and the economy, contributing to climate change discussions. Furthermore, complementary analyses can be undertaken by linking the MF-IO model with variables such as industry value added and employment data. And, used to estimate energy-related CO2 emissions indicators.

Abstract. We present results from the FAOSTAT agri-food systems emissions database, relative to 236 countries and territories and over the period 1990–2019. We find that in 2019, world-total food systems emissions were 16.5 billion metric tonnes (Gt CO2eq yr−1), corresponding to 31 % of total anthropogenic emissions. Of the agri-food systems total, global emissions within the farm gate –from crop and livestock production processes including on-farm energy use—were 7.2 Gt CO2eq yr−1; emissions from land use change, due to deforestation and peatland degradation, were 3.5 Gt CO2eq yr−1; and emissions from pre- and post-production processes –manufacturing of fertilizers, food processing, packaging, transport, retail, household consumption and food waste disposal—were 5.8 Gt CO2eq yr−1. Over the study period 1990–2019, agri-food systems emissions increased in total by 17 %, largely driven by a doubling of emissions from pre- and post-production processes. Conversely, the FAO data show that since 1990 land use emissions decreased by 25 %, while emissions within the farm gate increased only 9 %. In 2019, in terms of single GHG, pre- and post- production processes emitted the most CO2 (3.9 Gt CO2 yr−1), preceding land use change (3.3 Gt CO2 yr−1) and farm-gate (1.2 Gt CO2 yr−1) emissions. Conversely, farm-gate activities were by far the major emitter of methane (140 Mt CH4 yr−1) and of nitrous oxide (7.8 Mt N2O yr−1). Pre-and post- processes were also significant emitters of methane (49 Mt CH4 yr−1), mostly generated from the decay of solid food waste in landfills and open-dumps. The most important trend over the 30-year period since 1990 highlighted by our analysis is the increasingly important role of food-related emissions generated outside of agricultural land, in pre- and post-production processes along food supply chains, at all scales from global, regional and national, from 1990 to 2019. In fact, our data show that by 2019, food supply chains had overtaken farm-gate processes to become the largest GHG component of agri-food systems emissions in Annex I parties (2.2 Gt CO2eq yr−1). They also more than doubled in non-Annex I parties (to 3.5 Gt CO2eq yr−1), becoming larger than emissions from land-use change. By 2019 food supply chains had become the largest agri-food system component in China (1100 Mt CO2eq yr−1); USA (700 Mt CO2eq yr−1) and EU-27 (600 Mt CO2eq yr−1). This has important repercussions for food-relevant national mitigation strategies, considering that until recently these have focused mainly on reductions of non-CO2 gases within the farm gate and on CO2 mitigation from land use change. The information used in this work is available as open data at: https://zenodo.org/record/5615082 (Tubiello et al., 2021d). It is also available to users via the FAOSTAT database (FAO, 2021a), with annual updates.

The UN Sustainable Development Goal 7 aims to deliver affordable, reliable, sustainable and modern energy for all. Tracking progress towards the targets under this goal can spur better energy statistics and data gathering capacity, and will require new indicators that also consider the interplay with other goals.

Fossil fuel combustion is the single largest human influence on climate, accounting for 80% of anthropogenic greenhouse gas emissions. This paper presents trends in world carbon dioxide (CO2) emissions from fossil fuel combustion worldwide, based on the estimates of the International Energy Agency (IEA) [IEA, 2006a. CO2 Emissions from Fuel Combustion 1971-2004. International Energy Agency, Paris, France]. Analyzing the drivers of CO2 emissions, the paper considers regions, types of fuel, sectors, and socioeconomic indicators. The paper then examines the growing body of climate change mitigation policies and measures, both multinational and federal. Policies discussed include the Kyoto Protocol, the European Union Emissions Trading Scheme, and the potential measures to be implemented in 2012 and beyond.CO2 emissions of recent years have grown at the highest rates ever recorded, an observed trend incompatible with stabilizing atmospheric concentrations of greenhouse gases and avoiding long-term climate change. Within this aggregate upward trend, a comparison of emissions sources proves dynamic: while industrialized countries have so far dominated historical emissions, rapid growth in energy demand of developing economies, led by China, may soon spur their absolute emissions beyond those of industrialized countries.To provide context for the drivers of CO2 emissions, the paper examines fuel sources, from coal to biofuels, and fuel use in the production of heat and electricity, in transport, in industrial production and in households. The sectoral analysis illustrates the primacy, in terms of emissions growth and absolute emissions, of two sectors: electricity and heat generation, and transport.A discussion of several socio-economic emissions drivers complements the paper's analysis of mitigation mechanisms. As illustrated, emissions per capita and emissions per unit of economic production, as measured in gross domestic product (GDP), vary widely between regions. In this context, the paper examines the constraints and choices of energy use in two prominent developing economies: China and Brazil.This analysis of long-term trends in CO2 emissions from fuel combustion will prove useful for policyrnakers and energy policy analysts alike. Understanding the sources and drivers of greenhouse gas emissions is essential to their worldwide management and to the mitigation of climate change. (C) 2007 OECD/IEA. Published by Elsevier Ltd. All rights reserved.

This study investigates the response of wintertime North Atlantic Oscillation (NAO) to increasing concentrations of atmospheric carbon dioxide (CO2) as simulated by 18 global coupled general circulation models that participated in phase 2 of the Coupled Model Intercomparison Project (CMIP2). NAO has been assessed in control and transient 80-year simulations produced by each model under constant forcing, and 1% per year increasing concentrations of CO2, respectively. Although generally able to simulate the main features of NAO, the majority of models overestimate the observed mean wintertime NAO index of 8 hPa by 5–10 hPa. Furthermore, none of the models, in either the control or perturbed simulations, are able to reproduce decadal trends as strong as that seen in the observed NAO index from 1970–1995. Of the 15 models able to simulate the NAO pressure dipole, 13 predict a positive increase in NAO with increasing CO2 concentrations. The magnitude of the response is generally small and highly model-dependent, which leads to large uncertainty in multi-model estimates such as the median estimate of 0.0061±0.0036 hPa per %CO2. Although an increase of 0.61 hPa in NAO for a doubling in CO2 represents only a relatively small shift of 0.18 standard deviations in the probability distribution of winter mean NAO, this can cause large relative increases in the probabilities of extreme values of NAO associated with damaging impacts. Despite the large differences in NAO responses, the models robustly predict similar statistically significant changes in winter mean temperature (warmer over most of Europe) and precipitation (an increase over Northern Europe). Although these changes present a pattern similar to that expected due to an increase in the NAO index, linear regression is used to show that the response is much greater than can be attributed to small increases in NAO. NAO trends are not the key contributor to model-predicted climate change in wintertime mean temperature and precipitation over Europe and the Mediterranean region. However, the models’ inability to capture the observed decadal variability in NAO might also signify a major deficiency in their ability to simulate the NAO-related responses to climate change.

Abstract A perturbation analysis is carried out to quantify the eigenvector errors due to the mixing with other eigenvectors that occur when empirical orthogonal functions (EOFs) are computed for a finite-size data sample. Explicit forms are provided for the second-order eigenvalue error and first-order eigenvector error. The eigenvector sampling error depends monotonically on the ratio of the lower to the higher eigenvalues that mix. The relationship to the eigenvalue separation criterion of North et al. is discussed. The eigenvector error formula is applied to quantify sampling errors for the leading EOF of the Northern Hemisphere wintertime geopotential height at various pressure levels, and it is found that the smallest sampling error in the troposphere occurs for the sea level pressure EOF. The errors in the 500-hPa height EOFs are almost twice as large.

The low-frequency (>day period) variability observed within four different subsets of the climatology (H1, L1, H2, and L2) as defined by the high and low index polarities of the two leading principal components (PCs) of the sea level pressure field is compared, with emphasis on distinctive flow configurations and teleconnection patterns. The analysis is based on wintertime 500-hPa height, sea level pressure, and 1000-500-hPa thickness fields derived from the NCEP-NCAR reanalyses for the period of record, 1958-99."Spaghetti diagrams'' display specified contours for ensembles of individual 10-day mean charts extracted from the four different subsets of the climatology. In L1, 10-day mean maps (weak zonal flow at latitudes similar to55degreesN) exhibit larger undulations in the barotropic component of the flow than those in H1, implying larger particle displacements and deeper penetration of Arctic air masses, particularly into Europe and the eastern United States. Maps in H2 and L2, separated in accordance with the Pacific-North American (PNA)-like second mode, exhibit quite different kinds of planetary wave patterns. The L2 subset (characterized by a retracted Pacific jet) exhibits greater variability over the Gulf of Alaska and over northern Europe.Cold air outbreaks in Europe occur more frequently in L1 than H1, and over western North America, they occur more frequently in L2 than H2. The cold anomalies associated with low polarities of both PCs are observed more frequently than expected based on linear correlation; within the individual subsets of the climatology there are suggestions of multiple circulation regimes; teleconnection patterns for the subsets of the climatology are also discernibly different. These results constitute evidence of nonnormal or nonlinear behavior of 5- and 10-day mean fields and provide indications of how the intraseasonal variability depends on the mean state of the flow in which it is embedded.

The principal patterns of variability of the extratropical Northern Hemisphere (NH) wintertime circulation are examined, based on 42 yr of data from the NCAR-NCEP reanalyses. The two-dimensional phase space defined by the two leading PCs of the monthly mean sea level pressure (SLP) field poleward of 20degreesN is used as a basis for surveying the structure of the geopotential height and surface air temperature ( SAT) fields. Together these two patterns account for roughly half the variance of SLP on interannual time scales and longer, and virtually all the planetary-scale SLP trends over the 42-yr period of record. The leading EOF corresponds to the NH annular mode (NAM), and the second EOF resembles the Pacific - North America (PNA) pattern.The leading EOF of the monthly mean geopotential height field at various levels throughout the troposphere and lower stratosphere is well represented by linear combinations of these two SLP patterns, as are the intra-seasonal and interannual SLP fields, the NAM, the North Atlantic Oscillation (NAO), the PNA pattern, the pattern corresponding to the North Pacific index (NP), the cold ocean - warm land ( COWL) pattern, the seasaw between the depths of the Aleutian and Icelandic lows (AIS), and the leading EOFs of lower-tropospheric temperature and midtropospheric wind. The combined influence of these patterns on temperature and rainfall and other variables can be represented in terms of compact vectorial plots.Interesting differences emerge when the EOF analysis is performed separately on the intraseasonal and interannual components of the NH SLP field. The former patterns appear to be hemispherically trapped, whereas the latter appear to be reflections of global structures, with ENSO clearly dominating the structure of interannual EOF2.

[1] The structure of the Northern Hemisphere annular mode (NAM) is shown to be significantly different during warm and cold winters of the ENSO cycle. During warm winters the Arctic center of action of the annular mode is more prominent and extends deeper into Siberia, its related surface air temperature signal is stronger, and the compensating outer ring in the sea-level pressure field is much broader, encompassing the entire tropics. During cold winters the NAM signature is much more pronounced over the Pacific sector: the sea-level pressure pattern exhibits a North Pacific center of action, positively correlated with the Atlantic center, and pronounced deflections of the storm track are also evident. It is suggested that the former features are associated with the equatorward displacement of the jet stream and the storm tracks during warm winters of the ENSO cycle and the latter is related to the the more pronounced break in the subtropical jet stream over the Pacific sector during cold winters.

The winter precipitation variability over the Alpine region is described by a standard principal component analysis (PCA), performed starting from monthly precipitation anomalies for the 1971-1992 winters. With respect to the temporal variability, significant trends are found over some areas within the domain. In particular, the Alpine orography signature enables identification of 2 major sectors, located north and south of the chain, which exhibit an increase and a more significant decrease, respectively, in precipitation during the period examined. The relationship between surface and upper air data is then investigated by means of covariance maps of the precipitation prin- cipal components (PCs) with the 500 hPa geopotential height monthly anomalies and also by study- ing the correlation between the same PCs and some indices of large-scale circulation patterns, such as the North Atlantic Oscillation (NAO) and the Northern Hemisphere blocking frequency. The 2 leading precipitation patterns are characterized by significant relationships with large-scale anom- alies: the NAO explains most of the Alpine precipitation variance, and a strong link is also found with Euro-Atlantic blocking. No significant connection is found between winter Alpine precipitation vari- ability and the El Nino signature as deduced by sea-surface temperature anomalies.

A standard principal component analysis has been performed over the Mediterranean and over the larger European region on monthly precipitation anomalies for the winters between 1979 and 1995. The main centres of action of the associated EOFs are very similar for the two regions and the two sets of PCs are highly correlated with each other. Focusing on the Mediterranean region, the same analysis has been performed using 500 hPa geopotential height monthly anomalies taken from the operational NCEP analysis. Comparing the two sets of PCs associated with upper-air and surface data, a strong correlation has been found suggesting the presence of a two-way link between regional precipitation patterns and large-scale circulation anomalies. For both fields, the largest fraction of variance is explained by the North Atlantic Oscillation, while smaller but still substantial fractions are explained by other known patterns of large-scale variability such as the Eastern Atlantic pattern and the Euro-Atlantic blocking. No detectable connection has been found between Mediterranean precipitation patterns and El Niño SST anomalies during winter. With respect to temporal variability, significant trends have been found over most European areas during the winters considered. The associated pattern is characterised by a substantial increase of precipitation over western Scandinavia and a general decrease over southern Europe. This result is confirmed by analysing data from stations located in northern Italy.