Global trends in visibility: implications for dust sources

International audienceThere is a large uncertainty in the relative roles of human land use, climate change and carbon dioxide fertilization in changing desert dust source strength over the past 100 years, and the overall sign of human impacts on dust is not known. We used visibility data from meteorological stations in dusty regions to assess the anthropogenic impact on long term trends in desert dust emissions. Visibility data are available at thousands of stations globally from 1900 to the present, but we focused on 359 stations with more than 30 years of data in regions where mineral aerosols play a dominant role in visibility observations. We evaluated the 1974 to 2003 time period because most of these stations have reliable records only during this time. We first evaluated the visibility data against AERONET aerosol optical depth data, and found that only in dusty regions are the two moderately correlated. Correlation coefficients between visibility derived variables and AERONET optical depths indicate a moderate correlation (~0.47), consistent with capturing about 20% of the variability in optical depths. Two visibility derived variables appear to compare the best with AERONET observations: the fraction of observations with visibility less than 5 km (VIS5) and the surface extinction (EXT). Regional trends show that in many dusty places, VIS5 and EXT are statistically significantly correlated with the palmer drought severity index (based on precipitation and temperature) or surface wind speeds, consistent with dust temporal variability being largely driven by meteorology. This is especially true for North African and Chinese dust sources, but less true in the Middle East, Australia or South America, where there are not consistent patterns in the correlations. Climate indices such as El Nino or the North Atlantic Oscillation are not correlated with visibility derived variables in this analysis. There are few stations where visibility measures are correlated with cultivation or grazing estimates on a temporal basis, although this may be a function of the very coarse temporal resolution of the land use datasets. On the other hand, spatial analysis of the visibility data suggests that natural topographic lows are not correlated with visibility, but land use is correlated at a moderate level. This analysis is consistent with land use being important in some regions, but meteorology driving interannual variability during 1974?2003

Global trends in visibility: implications for dust sources

There is a large uncertainty in the relative roles of human land use, climate change and carbon dioxide fertilization in changing desert dust source strength over the past 100 years, and the overall sign of human impacts on dust is not known. We used visibility data from meteorological stations in dusty regions to assess the anthropogenic impact on long term trends in desert dust emissions. We did this by looking at time series of visibility derived variables and their correlations with precipitation, drought, winds, land use and grazing. Visibility data are available at thousands of stations globally from 1900 to the present, but we focused on 357 stations with more than 30 years of data in regions where mineral aerosols play a dominant role in visibility observations. We evaluated the 1974 to 2003 time period because most of these stations have reliable records only during this time. We first evaluated the visibility data against AERONET aerosol optical depth data, and found that only in dusty regions are the two moderately correlated. Correlation coefficients between visibility-derived variables and AERONET optical depths indicate a moderate correlation (0.47), consistent with capturing about 20% of the variability in optical depths. Two visibility-derived variables appear to compare the best with AERONET observations: the fraction of observations with visibility less than 5 km (VIS5) and the surface extinction (EXT). Regional trends show that in many dusty places, VIS5 and EXT are statistically significantly correlated with the Palmer drought severity index (based on precipitation and temperature) or surface wind speeds, consistent with dust temporal variability being largely driven by meteorology. This is especially true for North African and Chinese dust sources, but less true in the Middle East, Australia or South America, where there are not consistent patterns in the correlations. Climate indices such as El Nino or the North Atlantic Oscillation are not correlated with visibility-derived variables in this analysis. There are few stations where visibility measures are correlated with cultivation or grazing estimates on a temporal basis, although this may be a function of the very coarse temporal resolution of the land use datasets. On the other hand, spatial analysis of the visibility data suggests that natural topographic lows are not correlated with VIS5 or EXT, but land use is correlated at a moderate level. This analysis is consistent with land use being important in some regions, but meteorology driving interannual variability during 1974–2003

Urban agriculture: a global analysis of the space constraint to meet urban vegetable demand

Urban agriculture (UA) has been drawing a lot of attention recently for several reasons: the majority of the world population has shifted from living in rural to urban areas; the environmental impact of agriculture is a matter of rising concern; and food insecurity, especially the accessibility of food, remains a major challenge. UA has often been proposed as a solution to some of these issues, for example by producing food in places where population density is highest, reducing transportation costs, connecting people directly to food systems and using urban areas efficiently. However, to date no study has examined how much food could actually be produced in urban areas at the global scale. Here we use a simple approach, based on different global-scale datasets, to assess to what extent UA is constrained by the existing amount of urban space. Our results suggest that UA would require roughly one third of the total global urban area to meet the global vegetable consumption of urban dwellers. This estimate does not consider how much urban area may actually be suitable and available for UA, which likely varies substantially around the world and according to the type of UA performed. Further, this global average value masks variations of more than two orders of magnitude among individual countries. The variations in the space required across countries derive mostly from variations in urban population density, and much less from variations in yields or per capita consumption. Overall, the space required is regrettably the highest where UA is most needed, i.e., in more food insecure countries. We also show that smaller urban clusters (i.e., <100 km2 each) together represent about two thirds of the global urban extent; thus UA discourse and policies should not focus on large cities exclusively, but should also target smaller urban areas that offer the greatest potential in terms of physical space

In-situ spectroscopy of intrinsic Bi2Te3 topological insulator thin films and impact of extrinsic defects

Combined in-situ x-ray photoemission spectroscopy, scanning tunnelling spectroscopy and angle resolved photoemission spectroscopy of molecular beam epitaxy grown Bi2Te3 on lattice mismatched substrates reveal high quality stoichiometric thin films with topological surface states without a contribution from the bulk bands at the Fermi energy. The absence of bulk states at the Fermi energy is achieved without counter doping. We observe that the surface morphology and electronic band structure of Bi2Te3 are not affected by in-vacuo storage and exposure to oxygen, whereas major changes are observed when exposed to ambient conditions. These films help define a pathway towards intrinsic topological devices.Comment: 8 pages, 5 figure

Mapping Asian Cropping Intensity With MODIS

Agricultural systems are geographically extensive, have profound significance to society, and affect regional energy, climate, and water cycles. Since most suitable lands worldwide have been cultivated, there is a growing pressure to increase yields on existing agricultural lands. In tropical and subtropical regions, multicropping is widely used to increase food production, but regional-to-global information related to multicropping practices is poor. The high temporal resolution and moderate spatial resolution of the MODIS sensors provide an ideal source of information for characterizing cropping practices over large areas. Relative to studies that document agricultural extensification, however, systematic assessment of agricultural intensification via multicropping has received relatively little attention. The goal of this work was to help close this information gap by developing methods that use multitemporal remote sensing to map multicropping systems in Asia. Image time-series analysis is especially challenging in this part of the world because atmospheric conditions including clouds and aerosols lead to high frequencies of missing or low-quality observations, especially during the Asian Monsoon. The methodology that we developed builds upon the algorithm used to produce the MODIS Land Cover Dynamics product (MCD12Q2), but uses an improved methodology optimized for crops. We assessed our results at the aggregate scale using state, district, and provincial level inventory statistics reporting total cropped and harvested areas, and at the field scale using survey results for 191 field sites in Bangladesh. While the algorithm highlighted the dominant continental-scale patterns in agricultural practices throughout Asia, and produced reasonable estimates of state and provincial level total harvested areas, field-scale assessment revealed significant challenges in mapping high cropping intensity due to abundant missing data

Urban agriculture: a global analysis of the space constraint to meet urban vegetable demand

Urban agriculture (UA) has been drawing a lot of attention recently for several reasons: the majority of the world population has shifted from living in rural to urban areas; the environmental impact of agriculture is a matter of rising concern; and food insecurity, especially the accessibility of food, remains a major challenge. UA has often been proposed as a solution to some of these issues, for example by producing food in places where population density is highest, reducing transportation costs, connecting people directly to food systems and using urban areas efficiently. However, to date no study has examined how much food could actually be produced in urban areas at the global scale. Here we use a simple approach, based on different global-scale datasets, to assess to what extent UA is constrained by the existing amount of urban space. Our results suggest that UA would require roughly one third of the total global urban area to meet the global vegetable consumption of urban dwellers. This estimate does not consider how much urban area may actually be suitable and available for UA, which likely varies substantially around the world and according to the type of UA performed. Further, this global average value masks variations of more than two orders of magnitude among individual countries. The variations in the space required across countries derive mostly from variations in urban population density, and much less from variations in yields or per capita consumption. Overall, the space required is regrettably the highest where UA is most needed, i.e., in more food insecure countries. We also show that smaller urban clusters (i.e., <100 km2 each) together represent about two thirds of the global urban extent; thus UA discourse and policies should not focus on large cities exclusively, but should also target smaller urban areas that offer the greatest potential in terms of physical space

The effects of CO2, climate and land-use on terrestrial carbon balance, 1920-1992: An analysis with four process-based ecosystem models

The concurrent effects of increasing atmospheric CO2 concentration, climate variability, and cropland establishment and abandonment on terrestrial carbon storage between 1920 and 1992 were assessed using a standard simulation protocol with four process-based terrestrial biosphere models. Over the long-term(1920–1992), the simulations yielded a time history of terrestrial uptake that is consistent (within the uncertainty) with a long-term analysis based on ice core and atmospheric CO2 data. Up to 1958, three of four analyses indicated a net release of carbon from terrestrial ecosystems to the atmosphere caused by cropland establishment. After 1958, all analyses indicate a net uptake of carbon by terrestrial ecosystems, primarily because of the physiological effects of rapidly rising atmospheric CO2. During the 1980s the simulations indicate that terrestrial ecosystems stored between 0.3 and 1.5 Pg C yr−1, which is within the uncertainty of analysis based on CO2 and O2 budgets. Three of the four models indicated (in accordance with O2 evidence) that the tropics were approximately neutral while a net sink existed in ecosystems north of the tropics. Although all of the models agree that the long-term effect of climate on carbon storage has been small relative to the effects of increasing atmospheric CO2 and land use, the models disagree as to whether climate variability and change in the twentieth century has promoted carbon storage or release. Simulated interannual variability from 1958 generally reproduced the El Niño/Southern Oscillation (ENSO)-scale variability in the atmospheric CO2 increase, but there were substantial differences in the magnitude of interannual variability simulated by the models. The analysis of the ability of the models to simulate the changing amplitude of the seasonal cycle of atmospheric CO2 suggested that the observed trend may be a consequence of CO2 effects, climate variability, land use changes, or a combination of these effects. The next steps for improving the process-based simulation of historical terrestrial carbon include (1) the transfer of insight gained from stand-level process studies to improve the sensitivity of simulated carbon storage responses to changes in CO2 and climate, (2) improvements in the data sets used to drive the models so that they incorporate the timing, extent, and types of major disturbances, (3) the enhancement of the models so that they consider major crop types and management schemes, (4) development of data sets that identify the spatial extent of major crop types and management schemes through time, and (5) the consideration of the effects of anthropogenic nitrogen deposition. The evaluation of the performance of the models in the context of a more complete consideration of the factors influencing historical terrestrial carbon dynamics is important for reducing uncertainties in representing the role of terrestrial ecosystems in future projections of the Earth system

Global-scale climate impact functions: the relationship between climate forcing and impact

Although there is a strong policy interest in the impacts of climate change corresponding to different degrees of climate change, there is so far little consistent empirical evidence of the relationship between climate forcing and impact. This is because the vast majority of impact assessments use emissions-based scenarios with associated socio-economic assumptions, and it is not feasible to infer impacts at other temperature changes by interpolation. This paper presents an assessment of the global-scale impacts of climate change in 2050 corresponding to defined increases in global mean temperature, using spatially-explicit impacts models representing impacts in the water resources, river flooding, coastal, agriculture, ecosystem and built environment sectors. Pattern-scaling is used to construct climate scenarios associated with specific changes in global mean surface temperature, and a relationship between temperature and sea level used to construct sea level rise scenarios. Climate scenarios are constructed from 21 climate models to give an indication of the uncertainty between forcing and response. The analysis shows that there is considerable uncertainty in the impacts associated with a given increase in global mean temperature, due largely to uncertainty in the projected regional change in precipitation. This has important policy implications. There is evidence for some sectors of a non-linear relationship between global mean temperature change and impact, due to the changing relative importance of temperature and precipitation change. In the socio-economic sectors considered here, the relationships are reasonably consistent between socio-economic scenarios if impacts are expressed in proportional terms, but there can be large differences in absolute terms. There are a number of caveats with the approach, including the use of pattern-scaling to construct scenarios, the use of one impacts model per sector, and the sensitivity of the shape of the relationships between forcing and response to the definition of the impact indicator

The AVOID programme’s new simulations of the global benefits of stringent climate change mitigation

Quantitative simulations of the global-scale benefits of climate change mitigation are presented, using a harmonised, self-consistent approach based on a single set of climate change scenarios. The approach draws on a synthesis of output from both physically-based and economics-based models, and incorporates uncertainty analyses. Previous studies have projected global and regional climate change and its impacts over the 21st century but have generally focused on analysis of business-as-usual scenarios, with no explicit mitigation policy included. This study finds that both the economics-based and physically-based models indicate that early, stringent mitigation would avoid a large proportion of the impacts of climate change projected for the 2080s. However, it also shows that not all the impacts can now be avoided, so that adaptation would also therefore be needed to avoid some of the potential damage. Delay in mitigation substantially reduces the percentage of impacts that can be avoided, providing strong new quantitative evidence for the need for stringent and prompt global mitigation action on greenhouse gas emissions, combined with effective adaptation, if large, widespread climate change impacts are to be avoided. Energy technology models suggest that such stringent and prompt mitigation action is technologically feasible, although the estimated costs vary depending on the specific modelling approach and assumptions