13 research outputs found
Variability and quasi-decadal changes in the methane budget overthe period 2000–2012
Following the recent Global Carbon Project (GCP)
synthesis of the decadal methane (CH4/ budget over 2000–
2012 (Saunois et al., 2016), we analyse here the same dataset
with a focus on quasi-decadal and inter-annual variability in
CH4 emissions. The GCP dataset integrates results from topdown
studies (exploiting atmospheric observations within an
atmospheric inverse-modelling framework) and bottom-up
models (including process-based models for estimating land
surface emissions and atmospheric chemistry), inventories of
anthropogenic emissions, and data-driven approaches.The annual global methane emissions from top-down studies,
which by construction match the observed methane
growth rate within their uncertainties, all show an increase in
total methane emissions over the period 2000–2012, but this
increase is not linear over the 13 years. Despite differences
between individual studies, the mean emission anomaly of the top-down ensemble shows no significant trend in total
methane emissions over the period 2000–2006, during
the plateau of atmospheric methane mole fractions, and also
over the period 2008–2012, during the renewed atmospheric
methane increase. However, the top-down ensemble mean
produces an emission shift between 2006 and 2008, leading
to 22 [16–32] Tg CH4 yr1 higher methane emissions
over the period 2008–2012 compared to 2002–2006. This
emission increase mostly originated from the tropics, with
a smaller contribution from mid-latitudes and no significant
change from boreal regions.
The regional contributions remain uncertain in top-down
studies. Tropical South America and South and East Asia
seem to contribute the most to the emission increase in the
tropics. However, these two regions have only limited atmospheric
measurements and remain therefore poorly constrained.
The sectorial partitioning of this emission increase between
the periods 2002–2006 and 2008–2012 differs from
one atmospheric inversion study to another. However, all topdown
studies suggest smaller changes in fossil fuel emissions
(from oil, gas, and coal industries) compared to the
mean of the bottom-up inventories included in this study.
This difference is partly driven by a smaller emission change
in China from the top-down studies compared to the estimate
in the Emission Database for Global Atmospheric Research
(EDGARv4.2) inventory, which should be revised to smaller
values in a near future. We apply isotopic signatures to the
emission changes estimated for individual studies based on
five emission sectors and find that for six individual top-down
studies (out of eight) the average isotopic signature of the
emission changes is not consistent with the observed change
in atmospheric 13CH4. However, the partitioning in emission
change derived from the ensemble mean is consistent with
this isotopic constraint. At the global scale, the top-down ensemble
mean suggests that the dominant contribution to the
resumed atmospheric CH4 growth after 2006 comes from microbial
sources (more from agriculture and waste sectors than
from natural wetlands), with an uncertain but smaller contribution
from fossil CH4 emissions. In addition, a decrease in
biomass burning emissions (in agreement with the biomass
burning emission databases) makes the balance of sources
consistent with atmospheric 13CH4 observations.
In most of the top-down studies included here, OH concentrations
are considered constant over the years (seasonal variations
but without any inter-annual variability). As a result,
the methane loss (in particular through OH oxidation) varies
mainly through the change in methane concentrations and not
its oxidants. For these reasons, changes in the methane loss
could not be properly investigated in this study, although it
may play a significant role in the recent atmospheric methane
changes as briefly discussed at the end of the paper.Published11135–111616A. Geochimica per l'ambienteJCR Journa
The global methane budget 2000–2017
Understanding and quantifying the global methane (CH4) budget is important for assessing realistic pathways to mitigate climate change. Atmospheric emissions and concentrations of CH4 continue to increase, making CH4 the second most important human-influenced greenhouse gas in terms of climate forcing, after carbon dioxide (CO2). The relative importance of CH4 compared to CO2 depends on its shorter atmospheric lifetime, stronger warming potential, and variations in atmospheric growth rate over the past decade, the causes of which are still debated. Two major challenges in reducing uncertainties in the atmospheric growth rate arise from the variety of geographically overlapping CH4 sources and from the destruction of CH4 by short-lived hydroxyl radicals (OH). To address these challenges, we have established a consortium of multidisciplinary scientists under the umbrella of the Global Carbon Project to synthesize and stimulate new research aimed at improving and regularly updating the global methane budget. Following Saunois et al. (2016), we present here the second version of the living review paper dedicated to the decadal methane budget, integrating results of top-down studies (atmospheric observations within an atmospheric inverse-modelling framework) and bottom-up estimates (including process-based models for estimating land surface emissions and atmospheric chemistry, inventories of anthropogenic emissions, and data-driven extrapolations).
For the 2008–2017 decade, global methane emissions are estimated by atmospheric inversions (a top-down approach) to be 576 Tg CH4 yr−1 (range 550–594, corresponding to the minimum and maximum estimates of the model ensemble). Of this total, 359 Tg CH4 yr−1 or ∼ 60 % is attributed to anthropogenic sources, that is emissions caused by direct human activity (i.e. anthropogenic emissions; range 336–376 Tg CH4 yr−1 or 50 %–65 %). The mean annual total emission for the new decade (2008–2017) is 29 Tg CH4 yr−1 larger than our estimate for the previous decade (2000–2009), and 24 Tg CH4 yr−1 larger than the one reported in the previous budget for 2003–2012 (Saunois et al., 2016). Since 2012, global CH4 emissions have been tracking the warmest scenarios assessed by the Intergovernmental Panel on Climate Change. Bottom-up methods suggest almost 30 % larger global emissions (737 Tg CH4 yr−1, range 594–881) than top-down inversion methods. Indeed, bottom-up estimates for natural sources such as natural wetlands, other inland water systems, and geological sources are higher than top-down estimates. The atmospheric constraints on the top-down budget suggest that at least some of these bottom-up emissions are overestimated. The latitudinal distribution of atmospheric observation-based emissions indicates a predominance of tropical emissions (∼ 65 % of the global budget, < 30∘ N) compared to mid-latitudes (∼ 30 %, 30–60∘ N) and high northern latitudes (∼ 4 %, 60–90∘ N). The most important source of uncertainty in the methane budget is attributable to natural emissions, especially those from wetlands and other inland waters.
Some of our global source estimates are smaller than those in previously published budgets (Saunois et al., 2016; Kirschke et al., 2013). In particular wetland emissions are about 35 Tg CH4 yr−1 lower due to improved partition wetlands and other inland waters. Emissions from geological sources and wild animals are also found to be smaller by 7 Tg CH4 yr−1 by 8 Tg CH4 yr−1, respectively. However, the overall discrepancy between bottom-up and top-down estimates has been reduced by only 5 % compared to Saunois et al. (2016), due to a higher estimate of emissions from inland waters, highlighting the need for more detailed research on emissions factors. Priorities for improving the methane budget include (i) a global, high-resolution map of water-saturated soils and inundated areas emitting methane based on a robust classification of different types of emitting habitats; (ii) further development of process-based models for inland-water emissions; (iii) intensification of methane observations at local scales (e.g., FLUXNET-CH4 measurements) and urban-scale monitoring to constrain bottom-up land surface models, and at regional scales (surface networks and satellites) to constrain atmospheric inversions; (iv) improvements of transport models and the representation of photochemical sinks in top-down inversions; and (v) development of a 3D variational inversion system using isotopic and/or co-emitted species such as ethane to improve source partitioning
Developing climate change impact metrics for agriculture
We propose a framework for the analysis of the benefits of climate change policies on the agricultural sector, identifying biophysical factors, agricultural system characteristics, socio-economic data, and climate policy as key categories for analysis, and relating them to vulnerability criteria of agricultural systems in terms of their exposure, sensitivity, adaptive capacity, and synergy with mitigation strategies under climate change. Based on such a framework, a set of metrics is developed, comprised of variables that can be easily extracted from current impact assessment models and used to obtain consistent and comparable information on climate change impacts and benefits, in both monetary and non-monetary terms. Specifically, this work focuses on development of metrics for regional, national, and global scales, characterizing the short-term (20-30 years) and long-term (80-100 years) impacts of climate change on agriculture. The metrics, which include crop yield and variability, water stress indicators, production and land value, as well as a nutrition index for the number of people at risk of hunger, can help to identify risk thresholds and to evaluate policies related to adaptation. Finally, a number of improvements needed within current agronomic and economic models to address key uncertainties in assessing benefits of climate policies are discussed, with attention to the representation of the effects of climate extremes (heat waves, droughts, and floods), pest and disease interactions, and elevated CO2 on crops
Food system emissions: a review of trends, drivers, and policy approaches, 1990–2018
The food system, spanning from pre-production processes to post-production stages, is responsible for about one third of global greenhouse gas emissions and requires significant mitigation efforts to prevent dangerous levels of global warming. This article summarises trends and drivers of global food system emissions from 1990 to 2018. We highlight regional diversity in patterns of food system emissions and identify the highest global emitters. While food system emissions have stabilised in some regions and countries, global emissions are increasing, with growth in certain sectors and countries outweighing the handful of cases where sustained emissions reductions have been realised. Emissions from livestock rearing account for a large portion of global emissions, and the contribution of post-production emissions is steadily increasing in all regions. We also provide an overview of food system policies at the national level, mapping them to each emissions segment. This highlights the significant shortfall in policy activity required to address the challenge of climate change mitigation in general, and the impacts of livestock and post-production emissions in particular. Our work lays the groundwork for addressing specific country-level questions on optimal policy pathways to achieve emission reductions
Downy mildew outbreaks on grapevine under climate change: elaboration and application of an empirical-statistical model
The global climate is changing. Much research has already been carried out to assess the potential
impacts of climate change on plant physiology. However, effects on plant disease have not yet
been deeply studied. In this paper, an empirical disease model for primary infection of downy
mildew on grapevine was elaborated and used to project future disease dynamics under climate
change. The disease model was run under the outputs of the General Circulation Model (GCM)
and future scenarios of downy mildew primary outbreaks were generated at several sites all over
the word for three future dates: 2030, 2050, 2080. Results suggested a potential general advance
of first disease outbreaks, both in the Northern and Southern Hemispheres, for all three future
decades considered. The advance is predicted to be from about a minimum of one day in South
Africa in 2030 to a maximum of 28 days in Chile and China in 2080. The advance in the outbreak
time could lead to more severe infections, due to the polycyclic nature of the pathogen. Therefore,
changes in the timing and frequency of fungicide treatments could be expected in the future, with
a possible increase in the costs of disease management
Downy mildew (Plasmopara viticola) epidemics on grapevine under climate change
As climate is a key agro-ecosystem driving force, climate change could have a severe
impact on agriculture. Many assessments have been carried out to date on the possible
effects of climate change (temperature, precipitation and carbon dioxide concentration
changes) on plant physiology. At present however, likely effects on plant pathogens have
not been investigated deeply. The aim of this work was to simulate future scenarios of
downy mildew (Plasmopara viticola) epidemics on grape under climate change, by
combining a disease model to output from two general circulation models (GCMs).
Model runs corresponding to the SRES-A2 emissions scenario, characterized by high
projections of both population and greenhouse gas emissions from present to 2100, were
chosen in order to investigate impacts of worst-case scenarios, among those currently
available from IPCC. Three future decades were simulated (2030, 2050, 2080), using as
baseline historical series of meteorological data collected from 1955 to 2001 in Acqui
Terme, an important grape-growing area in the north-west of Italy. Both GCMs predicted
increase of temperature and decrease of precipitation in this region. The simulations
obtained by combining the disease model to the two GCM outputs predicted an increase
of the disease pressure in each decade: more severe epidemics were a direct consequence
of more favourable temperature conditions during the months of May and June. These
negative effects of increasing temperatures more than counterbalanced the effects of
precipitation reductions, which alone would have diminished disease pressure. Results
suggested that, as adaptation response to future climate change, more attention would
have to be paid in the management of early downy mildew infections; two more
fungicide sprays were necessary under the most negative climate scenario, compared
with present management regimes. At the same time, increased knowledge on the effects
of climate change on host–pathogen interactions will be necessary to improve current
prediction
Adaptation and mitigation strategies in agriculture: an analysis of potential synergies
Adaptation, Agriculture, Climate change impacts, Mitigation, Regional disparities, Synergies, Tradeoffs,