Journal Paper Digests

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Journal Paper Digests 2017 #9

Greenhouse gas emissions intensity of global croplands

Online Link Authors: Carlson, KM; Gerber, JS; Mueller, ND; Herrero, M; MacDonald, GK; Brauman, KA; Havlik, P; O’Connell, CS; Johnson, JA; Saatchi, S; West, PC

Source: NATURE CLIMATE CHANGE, 7 (1):63-+; JAN 2017

Abstract: Stabilizing greenhouse gas (GHG) emissions fromcroplands as agricultural demand grows is a critical component of climate change mitigation(1-3). Emissions intensity metrics-including carbon dioxide equivalent emissions per kilocalorie produced (‘production intensity’)-can highlight regions, management practices, and crops as potential foci for mitigation(4-7). Yet the spatial and crop-wise distribution of emissions intensity has been uncertain. Here, we develop global crop-specific circa 2000 estimates of GHG emissions and GHG intensity in high spatial detail, reporting the effects of rice paddy management, peatland draining, and nitrogen (N) fertilizer on CH4, CO2 and N-2O emissions. Global mean production intensity is 0.16 Mg CO(2)e M kcal(-1), yet certain cropping practices contribute disproportionately to emissions. Peatland drainage (3.7 Mg CO(2)e M kcal(-1))-concentrated in Europe and Indonesia-accounts for 32% of these cropland emissions despite peatlands producing just 1.1% of total crop kilocalories. Methane emissions fromrice (0.58 Mg CO(2)e M kcal(-1)), a crucial food staple supplying 15% of total crop kilocalories, contribute 48% of cropland emissions, with outsized production intensity in Vietnam. In contrast, N2O emissions from N fertilizer application (0.033 Mg CO(2)e M kcal(-1)) generate only 20% of cropland emissions. We find that current total GHG emissions are largely unrelated to production intensity across crops and countries. Climate mitigation policies should therefore be directed to locations where crops have both high emissions and high intensities.

Mitigation potential and global health impacts from emissions pricing of food commodities

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Authors: Springmann, M; Mason-D’Croz, D; Robinson, S; Wiebe, K; Godfray, HCJ; Rayner, M; Scarborough, P

Source: NATURE CLIMATE CHANGE, 7 (1):69-+; JAN 2017

Abstract: The projected rise in food-related greenhouse gas emissions could seriously impede efforts to limit global warming to acceptable levels. Despite that, food production and consumption have long been excluded from climate policies, in part due to concerns about the potential impact on food security. Using a coupled agriculture and health modelling framework, we show that the global climate change mitigation potential of emissions pricing of food commodities could be substantial, and that levying greenhouse gas taxes on food commodities could, if appropriately designed, be a health-promoting climate policy in high-income countries, as well as in most low-and middle-income countries. Sparing food groups known to be beneficial for health from taxation, selectively compensating for income losses associated with tax-related price increases, and using a portion of tax revenues for health promotion are potential policy options that could help avert most of the negative health impacts experienced by vulnerable groups, whilst still promoting changes towards diets which are more environmentally sustainable.

The changing pore size distribution of swelling and shrinking soil revealed by nuclear magnetic resonance relaxometry

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Authors: Shi, FG; Zhang, CZ; Zhang, JB; Zhang, XN; Yao, J

Source: JOURNAL OF SOILS AND SEDIMENTS, 17 (1):61-69; JAN 2017

Abstract: Purpose Determining soil pore size distribution is difficult and time-consuming using traditional methods. Additionally, for swelling and shrinking soil, the specific volume of soil changes with soil moisture conditions. Nuclear magnetic resonance (NMR) relaxometry allows observation of pore size distribution changes during the process of dehydration and soil shrinkage.Materials and methods Naturally structured soil cores of a Vertisol with characteristic swelling and shrinking behavior were collected from the Huang-Huai-Hai Plain of China. The samples were saturated with water and dehydrated gradually at room temperature and relaxometry tests conducted at different moisture contents as they air-dried. Then, the soil cores were oven-dried at 105 degrees C and saturated with n-octane, which prevented clay swelling. The pore size distribution of soil cores at the end of the shrinking process was determined through the description of n-octane-filled pores. The shrinkage characteristic curves were determined as naturally structured soil cores were air-dried from moisture content at full expansion to constant volume, indicating the relationship between the volume of bulk soil and moisture content.Results and discussion The transverse relaxation time (T-2) distribution deduced from NMR relaxometry gives a good description of the size distribution of pores filled with protons (contained in water or n-octane). The T-2 distribution curves of soil cores at saturation were trimodal, due to the presence of interlayer, interparticular, and interaggregate pores. Combined with the shrinkage characteristic curves, it was deduced that the structural pores were evacuated during the structural shrinkage period. The normal and residual shrinkage was accompanied by the narrowing and closure of the interlayer spaces. During the residual shrinkage period, the frame structure of the soil particles prevented further shrinkage of the bulk soil. The shrinkage process was accompanied by the closure of interlayer spaces and the formation of large cracks between aggregates.Conclusions H-1 NMR relaxometry was especially suited to studying the changing pore size distribution of swelling and shrinking soils. When the soil cores began shrinking, almost all remaining water was retained in interlayer spaces. The volume change of the interlayer space was the main cause of swelling and shrinking. The swelling limit could be estimated from the T-2 distributions of soils at full expansion.

Magnetic signature and source identification of heavy metal contamination in urban soils of steel industrial city, Northeast China

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Authors: Zong, YT; Xiao, Q; Lu, SG

Source: JOURNAL OF SOILS AND SEDIMENTS, 17 (1):190-203; JAN 2017

Abstract: Purpose Identifying the spatial distribution and degree of heavy metal contamination in the soils is required for urban environmental management. Magnetic measurement provides a rapidmeans of determining spatial distribution and degree of soil pollution and identifying various anthropogenic sources of heavy metals. The purpose of this study was to characterize the magnetic signature of heavy metal contamination and identify the sources of heavy metals in urban soils from steel industrial city.Materials and methods A total of 115 urban topsoils from Anshan city, Northeast China, were collected and determined for magnetic properties and heavy metal concentration. Magnetic susceptibility (chi lf) and saturation isothermal remanent magnetization (SIRM) were determined as proxy for ferrimagnetic mineral concentration. Magnetic minerals were identified by using Curie temperature, X-ray diffraction (XRD), and scanning electron microscope (SEM) equipped with an energy-dispersive X-ray spectrometer (EDS). The Pearson’ correlation and matrix cluster analyses were used to establish the relationship between magnetic parameters and heavy metal concentrations.Results and discussion Urban topsoils exhibit characteristic magnetic enhancement. The magnetic measurement in particle size fractions indicates that 50-2 mu m fraction has the highest low-field magnetic susceptibility (chi lf), while < 2 mu m has the highest frequency-dependent magnetic susceptibility (chi fd) value. The soil.lf and SIRM values are significantly correlated with the contents of metals (Fe, Pb, Zn, Cu, and Cr) and Tomlinson pollution load index (PLI), which indicates that.lf and SIRM could be served as better indicators for the pollution of heavy metals in the urban topsoil. Spatial distribution maps of.lf, SIRM, and PLI indicate that the pollution hotspots tend to associate with the regions within and close to steel industrial zones. XRD and Curie temperature analyses indicate that the main magnetic minerals of urban topsoils are magnetite (Fe3O4), hematite (alpha-Fe2O3), and metallic iron. Magnetic minerals mostly occur in the pseudosingle- domain/multidomain (PSD/MD) grain size range, which is the dominant contributor to the magnetic enhancement of topsoils. SEM observation reveals that magnetic particles in soils exist in irregular-shaped particles and spherule. Results reveal that heavy metals from industrially derived and traffic emissions coexist with coarse-grained magnetic phases.Conclusions It is concluded that the magnetic measurement could be regarded as a proxy tool to detect the level of heavy metal pollution and identify the source of heavy metals in urban soils. Magnetic properties provide a fast and inexpensive method to map the spatial distribution of long-term pollution from steel industrial origin on region scale.

The global distribution and dynamics of surface soil moisture

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Authors: McColl, KA; Alemohammad, SH; Akbar, R; Konings, AG; Yueh, S; Entekhabi, D

Source: NATURE GEOSCIENCE, 10 (2):100-+; FEB 2017

Abstract: Surface soil moisture has a direct impact on food security, human health and ecosystem function. It also plays a key role in the climate system, and the development and persistence of extreme weather events such as droughts, floods and heatwaves. However, sparse and uneven observations have made it difficult to quantify the global distribution and dynamics of surface soil moisture. Here we introduce a metric of soil moisture memory and use a full year of global observations from NASA’s Soil Moisture Active Passive mission to show that surface soil moisture-a storage believed to make up less than 0.001% of the global freshwater budget by volume, and equivalent to an, on average, 8-mm thin layer of water covering all land surfaces-plays a significant role in the water cycle. Specifically, we find that surface soil moisture retains a median 14% of precipitation falling on land after three days. Furthermore, the retained fraction of the surface soil moisture storage after three days is highest over arid regions, and in regions where drainage to groundwater storage is lowest. We conclude that lower groundwater storage in these regions is due not only to lower precipitation, but also to the complex partitioning of the water cycle by the surface soil moisture storage layer at the land surface.

Soil Survey: Pedotransfer Function of Linear Extensibility Percent for Soils of the United States

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Authors: Seybold, CA; Libohova, Z

Source: SOIL SCIENCE, 182 (1):1-8; JAN 2017

Abstract: Soil survey is an ongoing process from initial soil mapping through soil survey updates. A national model of linear extensibility percent (LEP) is needed to improve this process. The objective of this work was to develop and validate models for estimating LEP using general linear models and readily available soil survey properties. Measured data from the Kellogg National Soil Survey Laboratory database (Lincoln, Nebraska) were used to develop the prediction models. Twenty LEP prediction equations were developed based on pH and major mineralogy classes. Noncarbonate clay and, depending on the soil pH, either cation-exchange capacity or effective cation-exchange capacity explained between 42% and 86% of the total variation in LEP. Model equations using cation-exchange capacity as a predictive variable collectively produced a prediction root mean square error (RMSEp) of 1.44% and mean error (ME) of -0.16%. For low pH soils, the model equations using effective cation-exchange capacity as a predictive variable collectively produced an RMSEp of 1.29% and ME of -0.034%. The small negative MEs indicate an overall underestimation of LEP. Breaking down the validation results further among the different mineralogy groups produced a range of RMSEp from 0.42% to 1.80%. The smectitic group had the largest and the siliceous group had the lowest RMSEp. The prediction accuracy is considered adequate for soil survey purposes, and it is expected that LEP estimates will ultimately enhance soil survey interpretations. The models will be added to the soil survey database for soil scientists to use when measured data are not available.

Land management: data availability and process understanding for global change studies

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Authors: Erb, KH; Luyssaert, S; Meyfroidt, P; Pongratz, J; Don, A; Kloster, S; Kuemmerle, T; Fetzel, T; Fuchs, R; Herold, M; Haberl, H; Jones, CD; Marin-Spiotta, E; McCallum, I; Robertson, E; Seufert, V; Fritz, S; Valade, A; Wiltshire, A; Dolman, AJ

Source: GLOBAL CHANGE BIOLOGY, 23 (2):512-533; FEB 2017

Abstract: In the light of daunting global sustainability challenges such as climate change, biodiversity loss and food security, improving our understanding of the complex dynamics of the Earth system is crucial. However, large knowledge gaps related to the effects of land management persist, in particular those human-induced changes in terrestrial ecosystems that do not result in land-cover conversions. Here, we review the current state of knowledge of ten common land management activities for their biogeochemical and biophysical impacts, the level of process understanding and data availability. Our review shows that ca. one-tenth of the ice-free land surface is under intense human management, half under medium and one-fifth under extensive management. Based on our review, we cluster these ten management activities into three groups: (i) management activities for which data sets are available, and for which a good knowledge base exists (cropland harvest and irrigation); (ii) management activities for which sufficient knowledge on biogeochemical and biophysical effects exists but robust global data sets are lacking (forest harvest, tree species selection, grazing and mowing harvest, N fertilization); and (iii) land management practices with severe data gaps concomitant with an unsatisfactory level of process understanding (crop species selection, artificial wetland drainage, tillage and fire management and crop residue management, an element of crop harvest). Although we identify multiple impediments to progress, we conclude that the current status of process understanding and data availability is sufficient to advance with incorporating management in, for example, Earth system or dynamic vegetation models in order to provide a systematic assessment of their role in the Earth system. This review contributes to a strategic prioritization of research efforts across multiple disciplines, including land system research, ecological research and Earth system modelling.

Assessing uncertainties in land cover projections

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Authors: Alexander, P; Prestele, R; Verburg, PH; Arneth, A; Baranzelli, C; Silva, FBE; Brown, C; Butler, A; Calvin, K; Dendoncker, N; Doelman, JC; Dunford, R; Engstrom, K; Eitelberg, D; Fujimori, S; Harrison, PA; Hasegawa, T; Havlik, P; Holzhauer, S; Humpenoder, F; Jacobs-Crisioni, C; Jain, AK; Krisztin, T; Kyle, P; Lavalle, C; Lenton, T; Liu, JY; Meiyappan, P; Popp, A; Powell, T; Sands, RD; Schaldach, R; Stehfest, E; Steinbuks, J; Tabeau, A; van Meijl, H; Wise, MA; Rounsevell, MDA

Source: GLOBAL CHANGE BIOLOGY, 23 (2):767-781; FEB 2017

Abstract: Understanding uncertainties in land cover projections is critical to investigating land-based climate mitigation policies, assessing the potential of climate adaptation strategies and quantifying the impacts of land cover change on the climate system. Here, we identify and quantify uncertainties in global and European land cover projections over a diverse range of model types and scenarios, extending the analysis beyond the agro-economic models included in previous comparisons. The results from 75 simulations over 18 models are analysed and show a large range in land cover area projections, with the highest variability occurring in future cropland areas. We demonstrate systematic differences in land cover areas associated with the characteristics of the modelling approach, which is at least as great as the differences attributed to the scenario variations. The results lead us to conclude that a higher degree of uncertainty exists in land use projections than currently included in climate or earth system projections. To account for land use uncertainty, it is recommended to use a diverse set of models and approaches when assessing the potential impacts of land cover change on future climate. Additionally, further work is needed to better understand the assumptions driving land use model results and reveal the causes of uncertainty in more depth, to help reduce model uncertainty and improve the projections of land cover.

Land-use contrasts reveal instability of subsoil organic carbon

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Authors: Hobley, E; Baldock, J; Hua, Q; Wilson, B

Source: GLOBAL CHANGE BIOLOGY, 23 (2):955-965; FEB 2017

Abstract: Subsoils contain large amounts of organic carbon which is generally believed to be highly stable when compared with surface soils. We investigated subsurface organic carbon storage and dynamics by analysing organic carbon concentrations, fractions and isotopic values in 78 samples from 12 sites under different land-uses and climates in eastern Australia. Despite radiocarbon ages of several millennia in subsoils, contrasting native systems with agriculturally managed systems revealed that subsurface organic carbon is reactive on decadal timeframes to land-use change, which leads to large losses of young carbon down the entire soil profile. Our results indicate that organic carbon storage in soils is input driven down the whole profile, challenging the concept of subsoils as a repository of stable organic carbon.

Application of spectroscopic techniques for monitoring microbial diversity and bioremediation

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Microbes are the most fascinating group, with huge diversity devising myriad functional applications in the field of medicine, pharmaceuticals, environmental remediation, and industries. Quantitative and qualitative determination of biomolecules and microbial assisted phenomena by spectroscopy is a pioneer approach. It facilitates the study of atomic and molecular geometries, energy levels, chemical bonds, and interactions between molecules and microbes. It produces fingerprints of the microbial species serving to characterize, differentiate, and identify microorganisms, in both the environment and at single-cell level. Spectroscopy-based bioremediation techniques like Fourier transform infrared spectroscopy, mass spectroscopy, force spectroscopy, Raman spectroscopy, photoemission spectroscopy, and laser-induced breakdown spectroscopy have been very well represented and linked with the microbial applications. This review summarizes the traditional spectroscopic techniques used for the study of microbes and microbial-assisted products as well as illustrates its application in the field of microbial diversity and remediation. This will provide an outlook for the intricate characterization and dimension of microbes to be used for effective application in bioremediation.

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