30 research outputs found
ECLAIRE third periodic report
The ÉCLAIRE project (Effects of Climate Change on Air Pollution Impacts and Response Strategies for European Ecosystems) is a four year (2011-2015) project funded by the EU's Seventh Framework Programme for Research and Technological Development (FP7)
ECLAIRE: Effects of Climate Change on Air Pollution Impacts and Response Strategies for European Ecosystems. Project final report
The central goal of ECLAIRE is to assess how climate change will alter the extent to which air pollutants threaten terrestrial ecosystems. Particular attention has been given to nitrogen compounds, especially nitrogen oxides (NOx) and ammonia (NH3), as well as Biogenic Volatile Organic Compounds (BVOCs) in relation to tropospheric ozone (O3) formation, including their interactions with aerosol components. ECLAIRE has combined a broad program of field and laboratory experimentation and modelling of pollution fluxes and ecosystem impacts, advancing both mechanistic understanding and providing support to European policy makers.
The central finding of ECLAIRE is that future climate change is expected to worsen the threat of air pollutants on Europe’s ecosystems.
Firstly, climate warming is expected to increase the emissions of many trace gases, such as agricultural NH3, the soil component of NOx emissions and key BVOCs. Experimental data and numerical models show how these effects will tend to increase atmospheric N deposition in future. By contrast, the net effect on tropospheric O3 is less clear. This is because parallel increases in atmospheric CO2 concentrations will offset the temperature-driven increase for some BVOCs, such as isoprene. By contrast, there is currently insufficient evidence to be confident that CO2 will offset anticipated climate increases in monoterpene emissions.
Secondly, climate warming is found to be likely to increase the vulnerability of ecosystems towards air pollutant exposure or atmospheric deposition. Such effects may occur as a consequence of combined perturbation, as well as through specific interactions, such as between drought, O3, N and aerosol exposure.
These combined effects of climate change are expected to offset part of the benefit of current emissions control policies. Unless decisive mitigation actions are taken, it is anticipated that ongoing climate warming will increase agricultural and other biogenic emissions, posing a challenge for national emissions ceilings and air quality objectives related to nitrogen and ozone pollution. The O3 effects will be further worsened if progress is not made to curb increases in methane (CH4) emissions in the northern hemisphere.
Other key findings of ECLAIRE are that: 1) N deposition and O3 have adverse synergistic effects. Exposure to ambient O3 concentrations was shown to reduce the Nitrogen Use Efficiency of plants, both decreasing agricultural production and posing an increased risk of other forms of nitrogen pollution, such as nitrate leaching (NO3-) and the greenhouse gas nitrous oxide (N2O); 2) within-canopy dynamics for volatile aerosol can increase dry deposition and shorten atmospheric lifetimes; 3) ambient aerosol levels reduce the ability of plants to conserve water under drought conditions; 4) low-resolution mapping studies tend to underestimate the extent of local critical loads exceedance; 5) new dose-response functions can be used to improve the assessment of costs, including estimation of the value of damage due to air pollution effects on ecosystems, 6) scenarios can be constructed that combine technical mitigation measures with dietary change options (reducing livestock products in food down to recommended levels for health criteria), with the balance between the two strategies being a matter for future societal discussion. ECLAIRE has supported the revision process for the National Emissions Ceilings Directive and will continue to deliver scientific underpinning into the future for the UNECE Convention on Long-range Transboundary Air Pollution
ÉCLAIRE - Effects of Climate Change on Air Pollution Impacts and Response Strategies for European Ecosytems - second periodic report 01/04/2013 to 30/09/2014
Invited talk: Uplift and long range transport of anthropogenic SO2
info:eu-repo/semantics/nonPublishe
Satellite-based detection of potential land grabs
International audienceLarge scale land acquisitions (LSLAs), often referred as “land grabbing”, are highly dynamic and complex land use systems that are rapidly transforming ecosystems and societies in many low-income countries of the world, bringing on one hand sustainability challenges and, on the other hand, undermining the right of peoples to self-determination over natural resources. As such, monitoring of those large-scale agricultural expansions has appeared to be of paramount importance. In response to that need, the Land Matrix international initiative has emerged to promote the creation of an open access database on world land transactions. This open tool enables the collection and visualization of data on land deals based on publicly available sources (i.e. from governments, corporations, medias, citizen). However, because information on those acquisitions is often opaque and scarce, systems allowing near real-time LSLAs detection, characterization and monitoring are needed. In this context, the increasing availability of free-of-cost global satellite data products has shown great potential for providing insights into land dynamics, particularly of large and remote areas. While LSLAs are not directly observable from remote sensing images (no one-to-one relation between land cover and functionality), they may be inferred from observable land cover and spatio-temporal characteristics at different scales, and structural elements in the landscape. At a pixel level, land use and land cover (LULC) changes are often detected using change detection algorithms applied on temporally-dense satellite image time series (SITS) of vegetation indices. So far, most of the LULC change studies have focused on forested land covers where significant deviations (anomalies) from the mean are relatively easy to detect. However, LULC changes, and in particular human-driven ones such as those induced by LSLAs, often imply a change in (seasonal) interannual patterns (not always with significant shifts from the mean), that are less well detected by change detection algorithms. Accurate and automatic detection of those type of changes would thus pave the way for the development of generic and unsupervised approaches to LULC change detection.This study deals with the detection of agricultural LSLAs under different environmental conditions. Focus is given on Senegal for which we have ground-truth data. In addition, its strong north-south gradient of rainfall from dry to semi-humid climate, and relatively small sizes of its deals make Senegal an interesting and difficult study case study for the detection of LSLAs. The detection method proposed here is based on a two-step approach: 1- the detection of (if any) breakpoints in dense MODIS 2000-2020 Vegetation Index (NDVI) time series using the very fast BFAST monitor algorithm. Because BFAST monitor algorithm is subject to a high false positive rate, we implemented a second step to select the breakpoint most likely related to the desired land use change (biggest pattern change), 2- the selection, for each pixel, of the breakpoint associated to the biggest phenological change, based on a time series distance computed between the subsamples before and after each breakpoint. Results consist of change-intensity maps, date-of-change maps, and a comparison of the change detection maps obtained using our method vs. using the biggest BFAST-magnitude change detected. Areas potentially related to agricultural LSLAs are identified and qualitatively/quantitatively characterized (e.g. year of change, spatial expansion) and evaluated against field data (when available) and high spatial resolution spatial imagery (Landsat/ Google Earth). The method was also tested over different more humid and forested specific areas found in the literature (e.g. Laos and Mozambique), where agricultural LSLAs have been reported and characterized. For these areas we produced maps of deforested areas, with associated date-of-change, that could be assessed qualitatively. The results indicate that our method has a high potential for detecting LSLAs even in humid regions, and thus for mapping the extent and dynamics of deforestation driven by different types of commodities. Future efforts will focus on a finer assessment of the driving factor of the detected LULC changes (e.g. fire, forest management, commodities cropping etc.) through the application of image analysis techniques (clustering and object-based image analysis)
Retrieval of sulphur dioxide from the infrared atmospheric sounding interferometer (IASI)
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BFASTm-L2, an unsupervised LULCC detection based on seasonal change detection – An application to large-scale land acquisitions in Senegal
In the context of Global Change Research, detection, monitoring and characterization of land use/land cover (LULC) changes are of prime importance. The increasing availability of dense satellite image time series (SITS) has led to a shift in the change detection paradigm, with algorithms able to exploit the full temporal information laid down in SITS. So far, most of these algorithms have focused on the detection of abrupt and gradual changes, and thus developed breakpoint detection based on significant deviations from the mean. However, LULC changes may manifest themselves in other patterns, particularly changes in seasonality (amplitude, number and length of the growing seasons) that are harder to detect. In this paper, we propose a simple method to automatically select the breakpoint linked to the biggest seasonal change in long and dense SITS with multiple breakpoints. This approach - BFASTm-L2 - relies on linking a high-speed algorithm (BFAST monitor) with a time series similarity metric (Euclidian distance L2) sensitive to seasonal changes. The capacity of BFASTm-L2 to identify the date of change in different situations was tested on two data sets, and compared to the performances of three other algorithms (BFAST monitor, BFAST lite, and Edyn). The data sets are 1. a published benchmark data set composed of 25 200 simulated SITS with different change types and change magnitudes, and 2. the 2000–2020 MODIS NDVI SITS over a 200x200 pixels area in Senegal including different study sites which have undergone recent LULC changes due to agricultural large-scale land acquisitions (LSLAs) (as reported in the ground field database used in this study). The results show that BFASTm-L2 is efficient in accurately detecting in time most of the changes, and, in contrast with BFAST Lite and BFASTmonitor, to spatially highlight LSLAs-induced changes without the need of any prior knowledge. The automatic proposed approach, faster than BFAST Lite and Edyn, and with very few tuneable parameters, may thus be easily implemented in unsupervised pipelines to map and analyse generic LULC changes at regional scale
Neural network approach to identify NH3 emissions from biomass burning
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Exceptional emissions of NH and HCOOH in the 2010 Russian wildfires
In July 2010, several hundred forest and peat fires broke out across central Russia during its hottest summer on record. Here, we analyze these wildfires using observations of the Infrared Atmospheric Sounding Interferometer (IASI). Carbon monoxide (CO), ammonia (NH3) and formic acid (HCOOH) total columns are presented for the year 2010. Maximum total columns were found to be one order (for CO and HCOOH) and two orders (for NH3) of magnitude larger than typical background values. The temporal evolution of NH3 and HCOOH enhancement ratios relative to CO are presented. Evidence of secondary formation of HCOOH is found, with enhancement ratios exceeding reported emission ratios in fresh plumes. We estimate the total emitted masses for the period July-August 2010 over the center of western Russia; they are 19-33 Tg (CO), 0.7-2.6 Tg (NH3) and 0.9-3.9 Tg (HCOOH). For NH3 and HCOOH, these quantities are comparable to what is emitted in the course of a whole year by all extratropical forest fires. © Author(s) 2013.SCOPUS: ar.jinfo:eu-repo/semantics/publishe
Infrared satellite observations of HCN and C2H2 in biomass burning plumes
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