Alkaline air: changing perspectives on nitrogen and air pollution in an ammonia-rich world.

Ammonia and ammonium have received less attention than other forms of air pollution, with limited progress in controlling emissions at UK, European and global scales. By contrast, these compounds have been of significant past interest to science and society, the recollection of which can inform future strategies. Sal ammoniac (nushadir, nao sha) is found to have been extremely valuable in long-distance trade (ca AD 600-1150) from Egypt and China, where 6-8 kg N could purchase a human life, while air pollution associated with nushadir collection was attributed to this nitrogen form. Ammonia was one of the keys to alchemy-seen as an early experimental mesocosm to understand the world-and later became of interest as 'alkaline air' within the eighteenth century development of pneumatic chemistry. The same economic, chemical and environmental properties are found to make ammonia and ammonium of huge relevance today. Successful control of acidifying SO2 and NOx emissions leaves atmospheric NH3 in excess in many areas, contributing to particulate matter (PM2.5) formation, while leading to a new significance of alkaline air, with adverse impacts on natural ecosystems. Investigations of epiphytic lichens and bog ecosystems show how the alkalinity effect of NH3 may explain its having three to five times the adverse effect of ammonium and nitrate, respectively. It is concluded that future air pollution policy should no longer neglect ammonia. Progress is likely to be mobilized by emphasizing the lost economic value of global N emissions ($200 billion yr-1), as part of developing the circular economy for sustainable nitrogen management. This article is part of a discussion meeting issue 'Air quality, past present and future'.

A central neural pathway controlling odor tracking in Drosophila.

Chemotaxis is important for the survival of most animals. How the brain translates sensory input into motor output beyond higher olfactory processing centers is largely unknown. We describe a group of excitatory neurons, termed Odd neurons, which are important for Drosophila larval chemotaxis. Odd neurons receive synaptic input from projection neurons in the calyx of the mushroom body and project axons to the central brain. Functional imaging shows that some of the Odd neurons respond to odor. Larvae in which Odd neurons are silenced are less efficient at odor tracking than controls and sample the odor space more frequently. Larvae in which the excitability of Odd neurons is increased are better at odor intensity discrimination and odor tracking. Thus, the Odd neurons represent a distinct pathway that regulates the sensitivity of the olfactory system to odor concentrations, demonstrating that efficient chemotaxis depends on processing of odor strength downstream of higher olfactory centers.

Measurements of methane and nitrous oxide in human breath and the development of UK scale emissions.

Exhaled human breath can contain small, elevated concentrations of methane (CH4) and nitrous oxide (N2O), both of which contribute to global warming. These emissions from humans are not well understood and are rarely quantified in global greenhouse gas inventories. This study investigated emissions of CH4 and N2O in human breath from 104 volunteers in the UK population, to better understand what drives these emissions and to quantify national-scale estimates. A total of 328 breath samples were collected, and age, sex, dietary preference, and smoking habits were recorded for every participant. The percentage of methane producers (MPs) identified in this study was 31%. The percentage of MPs was higher in older age groups with 25% of people under the age of 30 classified as MPs compared to 40% in the 30+ age group. Females (38%) were more likely to be MPs than males (25%), though overall concentrations emitted from both MP groups were similar. All participants were found to emit N2O in breath, though none of the factors investigated explained the differences in emissions. Dietary preference was not found to affect CH4 or N2O emissions from breath in this study. We estimate a total emission of 1.04 (0.86-1.40) Gg of CH4 and 0.069 (0.066-0.072) Gg of N2O in human breath annually in the UK, the equivalent of 53.9 (47.8-60.0) Gg of CO2. In terms of magnitude, these values are approximately 0.05% and 0.1% of the total emissions of CH4 and N2O reported in the UK national greenhouse gas inventories.

The Terrestrial Biosphere Model Farm.

Model Intercomparison Projects (MIPs) are fundamental to our understanding of how the land surface responds to changes in climate. However, MIPs are challenging to conduct, requiring the organization of multiple, decentralized modeling teams throughout the world running common protocols. We explored centralizing these models on a single supercomputing system. We ran nine offline terrestrial biosphere models through the Terrestrial Biosphere Model Farm: CABLE, CENTURY, HyLand, ISAM, JULES, LPJ-GUESS, ORCHIDEE, SiB-3, and SiB-CASA. All models were wrapped in a software framework driven with common forcing data, spin-up, and run protocols specified by the Multi-scale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP) for years 1901-2100. We ran more than a dozen model experiments. We identify three major benefits and three major challenges. The benefits include: (a) processing multiple models through a MIP is relatively straightforward, (b) MIP protocols are run consistently across models, which may reduce some model output variability, and (c) unique multimodel experiments can provide novel output for analysis. The challenges are: (a) technological demand is large, particularly for data and output storage and transfer; (b) model versions lag those from the core model development teams; and (c) there is still a need for intellectual input from the core model development teams for insight into model results. A merger with the open-source, cloud-based Predictive Ecosystem Analyzer (PEcAn) ecoinformatics system may be a path forward to overcoming these challenges.

Spin Hall effect induced by resonant scattering on impurities in metals.

The spin Hall effect is a promising way for transforming charge currents into spin currents in spintronic devices. Large values of the spin Hall angle, the characteristic parameter of the yield of this transformation, have been recently found in noble metals doped with nonmagnetic impurities. We show that this can be explained by resonant scattering off impurity states split by the spin-orbit interaction. By using as an example copper doped with 5d impurities we describe the general conditions and provide a guide for experimentalists for obtaining the largest effects.

Multiple mechanisms of Amazonian forest biomass losses in three dynamic global vegetation models under climate change.

*The large-scale loss of Amazonian rainforest under some future climate scenarios has generally been considered to be driven by increased drying over Amazonia predicted by some general circulation models (GCMs). However, the importance of rainfall relative to other drivers has never been formally examined. *Here, we conducted factorial simulations to ascertain the contributions of four environmental drivers (precipitation, temperature, humidity and CO(2)) to simulated changes in Amazonian vegetation carbon (C(veg)), in three dynamic global vegetation models (DGVMs) forced with climate data based on HadCM3 for four SRES scenarios. *Increased temperature was found to be more important than precipitation reduction in causing losses of Amazonian C(veg) in two DGVMs (Hyland and TRIFFID), and as important as precipitation reduction in a third DGVM (LPJ). Increases in plant respiration, direct declines in photosynthesis and increases in vapour pressure deficit (VPD) all contributed to reduce C(veg) under high temperature, but the contribution of each mechanism varied greatly across models. Rising CO(2) mitigated much of the climate-driven biomass losses in the models. *Additional work is required to constrain model behaviour with experimental data under conditions of high temperature and drought. Current models may be overly sensitive to long-term elevated temperatures as they do not account for physiological acclimation.

Effect of 7 yr of experimental drought on vegetation dynamics and biomass storage of an eastern Amazonian rainforest.

*At least one climate model predicts severe reductions of rainfall over Amazonia during this century. Long-term throughfall exclusion (TFE) experiments represent the best available means to investigate the resilience of the Amazon rainforest to such droughts. *Results are presented from a 7 yr TFE study at Caxiuanã National Forest, eastern Amazonia. We focus on the impacts of the drought on tree mortality, wood production and above-ground biomass. *Tree mortality in the TFE plot over the experimental period was 2.5% yr(-1), compared with 1.25% yr(-1) in a nearby control plot experiencing normal rainfall. Differences in stem mortality between plots were greatest in the largest (> 40 cm diameter at breast height (dbh)) size class (4.1% yr(-1) in the TFE and 1.4% yr(-1) in the control). Wood production in the TFE plot was c. 30% lower than in the control plot. Together, these changes resulted in a loss of 37.8 +/- 2.0 Mg carbon (C) ha(-1) in the TFE plot (2002-2008), compared with no change in the control. *These results are remarkably consistent with those from another TFE (at Tapajós National Forest), suggesting that eastern Amazonian forests may respond to prolonged drought in a predictable manner.

Nitrous oxide emission factors of mineral fertilisers in the UK and Ireland: A Bayesian analysis of 20 years of experimental data.

In this study, we analysed datasets of N2O emission factors (EFs) from 21 separate studies carried out on arable and managed grasslands across the UK and Ireland over the past 20 years. A total of 641 separate events were collated from 40 experimental field sites. Individual EFs ranged over an order of magnitude (0-12% of applied N) for each fertiliser type, following a log-normal distribution in all cases. Our study shows that a Bayesian approach can provide a robust statistical method that is capable of performing uncertainty analysis on log-normal distributed data in a more defensible manner than conventional statistical methods allow. This method allowed for a national scale comparison of EFs between the most commonly applied mineral fertilisers based solely on previously published data (UK and Ireland in this case). The study shows that ammonium nitrate (AN) and Calcium ammonium nitrate (CAN) are the largest emitting fertiliser types by mass across the British Isles (temperate climate zone), with EFs of 1.1 (1.0-1.2) % and 1.0 (0.7-1.3) % for all recorded events, respectively; however, emissions from AN applications were significantly lower for applications to arable fields (0.6%) than to grasslands (1.3%). EFs associated with urea (CO(NH2)2) were significantly lower than AN for grasslands with an EF of 0.6 (0.5-0.7) %, but slightly higher for arable fields with an EF of 0.7 (0.4-1.4) %. The study highlights the potential effectiveness of microbial inhibitors at reducing emissions of N2O from mineral fertilisers, with Dicyandiamide (DCD) treated AN reducing emissions by approximately 28% and urea treated with either DCD or N-(n)-butyl) thiophosphorictriamide (NBTP) reducing emissions by approximately 40%. Although limited by a relatively small sample size (n = 11), urea treated with both DCD and NBPT appeared to have the lowest EF of all treatments at 0.13 (0.08-0.21) %, highlighting the potential to significantly reduce N2O emissions at regional scales if applied instead of conventional nitrogen fertilisers.

Quantifying gross vs. net agricultural land use change in Great Britain using the Integrated Administration and Control System.

Land use change has impacts upon many natural processes, and is one of the key measures of anthropogenic disturbance on ecosystems. Agricultural land covers 70% of Great Britain's (GB) land surface and annually undergoes disturbance and change through farming practices such as crop rotation, ploughing and the planting and subsequent logging of forestry. It is important to quantify how much of GB's agricultural land undergoes such changes and what those changes are at an annual temporal resolution. Integrated Administration and Control System (IACS) data give annual snapshots of agricultural land use at the field level, allowing for high resolution spatiotemporal land use change studies at the national scale. Crucially, not only do the data allow for simple net change studies (total area change of a land use, in a specific areal unit) but also for gross change calculations (summation of all changes to and from a land use), meaning that both gains and losses to and from each land use category can be defined. In this study we analysed IACS data for GB from 2005 to 2013, and quantified gross change for over 90% of the agricultural area in GB for the first time. It was found that gross change totalled 63,500 km2 in GB compared to 20,600 km2 of net change, i.e. the real year-on-year change is, on average, three times larger than net change. This detailed information on nature of land use change allows for increased accuracy in modelling the impact of land use change on ecosystem processes and is directly applicable across EU member states, where collection of such survey data is a requirement. The modelled carbon flux associated with gross land use change was at times >100 Gg C y-1 larger than that based on net land use change for some land use transitions.

Ambient concentrations and deposition rates of selected reactive nitrogen species and their contribution to PM2.5 aerosols at three locations with contrasting land use in southwest China.

The fast economic development of southwest China has resulted in significant increases in the concentrations of reactive nitrogen (Nr) in the atmosphere. In this study, an urban (Chengdu, CD), suburban (Shifang, SF) and agriculture (Yanting, YT) - dominated location in the Sichuan Province, southwest China, were selected to investigate the atmospheric composition of Nr, their concentrations and deposition rates. We measured Nr concentrations in precipitation (NH4+, NO3- and organic N (DON)), the gas phase (NH3 and NO2), and the aerosol particles (PM2.5), and calculated their fluxes over a two year period (2014-2016). Total annual N deposition rates were 49.2, 44.7 and 19.8 kg N ha-1 yr-1 at CD, SF and YT, respectively. Ammonia concentrations were larger at the urban and suburban sites than the agricultural site (12.2, 14.9, and 4.9 µg N m-3 at CD, SF and YT, respectively). This is consistent with the multitude of larger sources of NH3, including city garbage, livestock and traffic, in the urban and suburban areas. Monthly NO2 concentrations were lower in warmer compared to the colder months, but seasonal differences were insignificant. Daily PM2.5 concentrations ranged from 7.7 to 236.0, 5.0-210.4 and 4.2-128.4 µg m-3 at CD, SF and YT, respectively, and showed significant correlations with fine particulate NH4+ and NO3- concentrations. Ratios of reduced to oxidized N were in the range of 1.6-2.7. This implies that the control of reduced Nr especially in urban environments is needed to improve local air quality.

Bulk deposition of organic and inorganic nitrogen in southwest China from 2008 to 2013.

China is regarded as one of the nitrogen deposition hotspots in the world. Measurements to-date have focused mainly on the North China Plain, ignoring the fact that atmospheric chemical and physical properties vary across the country and that there may be other hotspots regions that should be investigated. For this reason we have conducted a six year study, measuring the bulk deposition of reduced (NH4-N), oxidized (NO3-N), and dissolved organic nitrogen (DON) at three contrasting sites in the Sichuan province, southwest China. The study sites were a high altitude forest in the Gongga Mountains (GG), an agriculture dominated region in Yanting (YT) and an urban site in the mega city Chengdu (CD). The annual average bulk deposition fluxes of total dissolved nitrogen (TDN) were 7.4, 23.1 and 36.6 kg N ha-1 yr-1 at GG, YT and CD sites, respectively, during the study period 2008 to 2013. The contributions of NH4-N, NO3-N and DON to the TDN were in the range of 48.4-57.8%, 28.8-43.7%, and 8.0-15.6%, respectively. DON bulk deposition was mainly dominated by agricultural activities. TDN bulk deposition fluxes showed increasing trends at the agricultural and urban sites from 2008 to 2013, but there was little change at the remote forest (GG) site. While reduced N dominated bulk N deposition at all the three sites, its contribution showed a decreasing trend, suggesting a gradual increase in the importance of oxidized N. These results reveal the value of long term monitoring in detecting changes in the atmospheric chemical composition of this rapidly changing region, and their inclusion in the policy debate regarding which sources should be controlled in order to reduce the long term impacts of N deposition, especially for southwest China, where there are few measurements of N deposition.

Completing the FACE of elevated CO2 research.

We appraise the present geographical extent and inherent knowledge limits, following two decades of research on elevated CO2 responses in plant communities, and ask whether such research has answered the key question in quantifying the limits of compensatory CO2 uptake in the major biomes. Our synthesis of all ecosystem-scale (between 10 m(2) and 3000 m(2) total experimental plot area) elevated CO2 (eCO2) experiments in natural ecosystems conducted worldwide since 1987 (n=151) demonstrates that the locations of these eCO2 experiments have been spatially biased, targeting primarily the temperate ecosystems of northern America and Europe. We consider the consequences, suggesting fundamentally that this limits the capacity of the research to understand how the world's major plant communities will respond to eCO2. Most notably, our synthesis shows that this research lacks understanding of impacts on tropical forests and boreal regions, which are potentially the most significant biomes for C sink and storage activity, respectively. Using a meta-analysis of the available data across all biomes, we show equivocal increases in net primary productivity (NPP) from eCO2 studies, suggesting that global validation is needed, especially in the most important biomes for C processing. Further, our meta-analysis identifies that few research programs have addressed eCO2 effects on below-ground C storage, such that at the global scale, no overall responses are discernable. Given the disparity highlighted in the distribution of eCO2 experiments globally, we suggest opportunities for newly-industrialized or developing nations to become involved in further research, particularly as these countries host some of the most important regions for tropical or sub-tropical forest systems. Modeling approaches that thus far have attempted to understand the biological response to eCO2 are constrained with respect to collective predictions, suggesting that further work is needed, which will link models to in situ eCO2 experiments, in order to understand how the world's most important regions for terrestrial C uptake and storage will respond to a future eCO2 atmosphere.

Evidence for a weakening relationship between interannual temperature variability and northern vegetation activity.

Satellite-derived Normalized Difference Vegetation Index (NDVI), a proxy of vegetation productivity, is known to be correlated with temperature in northern ecosystems. This relationship, however, may change over time following alternations in other environmental factors. Here we show that above 30°N, the strength of the relationship between the interannual variability of growing season NDVI and temperature (partial correlation coefficient RNDVI-GT) declined substantially between 1982 and 2011. This decrease in RNDVI-GT is mainly observed in temperate and arctic ecosystems, and is also partly reproduced by process-based ecosystem model results. In the temperate ecosystem, the decrease in RNDVI-GT coincides with an increase in drought. In the arctic ecosystem, it may be related to a nonlinear response of photosynthesis to temperature, increase of hot extreme days and shrub expansion over grass-dominated tundra. Our results caution the use of results from interannual time scales to constrain the decadal response of plants to ongoing warming.

Odd-skipped labels a group of distinct neurons associated with the mushroom body and optic lobe in the adult Drosophila brain.

Olfactory processing has been intensively studied in Drosophila melanogaster. However, we still know little about the descending neural pathways from the higher order processing centers and how these connect with other neural circuits. Here we describe, in detail, the adult projections patterns that arise from a cluster of 78 neurons, defined by the expression of the Odd-skipped transcription factor. We term these neurons Odd neurons. By using expression of genetically encoded axonal and dendritic markers, we show that a subset of the Odd neurons projects dendrites into the calyx of the mushroom body (MB) and axons into the inferior protocerebrum. We exclude the possibility that the Odd neurons are part of the well-known Kenyon cells whose projections form the MB and conclude that the Odd neurons belong to a previously not described class of extrinsic MB neurons. In addition, three of the Odd neurons project into the lobula plate of the optic lobe, and two of these cells extend axons ipsi- and contralaterally in the brain. Anatomically, these cells do not resemble any previously described lobula plate tangential cells (LPTCs) in Drosophila. We show that the Odd neurons are predominantly cholinergic but also include a small number of γ-aminobutyric acid (GABA)ergic neurons. Finally, we provide evidence that the Odd neurons are a hemilineage, suggesting they are born from a defined set of neuroblasts. Our anatomical analysis hints at the possibility that subgroups of Odd neurons could be involved in olfactory and visual processing.

Methane indicator values for peatlands: a comparison of species and functional groups.

Previous studies have shown a correspondence between the abundance of particular plant species and methane flux. Here, we apply multivariate analyses, and weighted averaging, to assess the suitability of vegetation composition as a predictor of methane flux. We developed a functional classification of the vegetation, in terms of a number of plant traits expected to influence methane production and transport, and compared this with a purely taxonomic classification at species level and higher. We applied weighted averaging and indirect and direct ordination approaches to six sites in the United Kingdom, and found good relationships between methane flux and vegetation composition (classified both taxonomically and functionally). Plant species and functional groups also showed meaningful responses to management and experimental treatments. In addition to the United Kingdom, we applied the functional group classification across different geographical regions (Canada and the Netherlands) to assess the generality of the method. Again, the relationship appeared good at the site level, suggesting some general applicability of the functional classification. The method seems to have the potential for incorporation into large-scale (national) greenhouse gas accounting programmes (in relation to peatland condition/management) using vegetation mapping schemes. The results presented here strongly suggest that robust predictive models can be derived using plant species data (for use in national-scale studies). For trans-national-scale studies, where the taxonomic assemblage of vegetation differs widely between study sites, a functional classification of plant species data provides an appropriate basis for predictive models of methane flux.

African tropical rainforest net carbon dioxide fluxes in the twentieth century.

The African humid tropical biome constitutes the second largest rainforest region, significantly impacts global carbon cycling and climate, and has undergone major changes in functioning owing to climate and land-use change over the past century. We assess changes and trends in CO2 fluxes from 1901 to 2010 using nine land surface models forced with common driving data, and depict the inter-model variability as the uncertainty in fluxes. The biome is estimated to be a natural (no disturbance) net carbon sink (-0.02 kg C m⁻² yr⁻¹ or -0.04 Pg C yr⁻¹, p < 0.05) with increasing strength fourfold in the second half of the century. The models were in close agreement on net CO2 flux at the beginning of the century (σ1901 = 0.02 kg C m⁻² yr⁻¹), but diverged exponentially throughout the century (σ2010 = 0.03 kg C m⁻² yr⁻¹). The increasing uncertainty is due to differences in sensitivity to increasing atmospheric CO2, but not increasing water stress, despite a decrease in precipitation and increase in air temperature. However, the largest uncertainties were associated with the most extreme drought events of the century. These results highlight the need to constrain modelled CO2 fluxes with increasing atmospheric CO2 concentrations and extreme climatic events, as the uncertainties will only amplify in the next century.

Evaluation of terrestrial carbon cycle models for their response to climate variability and to CO2 trends.

The purpose of this study was to evaluate 10 process-based terrestrial biosphere models that were used for the IPCC fifth Assessment Report. The simulated gross primary productivity (GPP) is compared with flux-tower-based estimates by Jung et al. [Journal of Geophysical Research 116 (2011) G00J07] (JU11). The net primary productivity (NPP) apparent sensitivity to climate variability and atmospheric CO2 trends is diagnosed from each model output, using statistical functions. The temperature sensitivity is compared against ecosystem field warming experiments results. The CO2 sensitivity of NPP is compared to the results from four Free-Air CO2 Enrichment (FACE) experiments. The simulated global net biome productivity (NBP) is compared with the residual land sink (RLS) of the global carbon budget from Friedlingstein et al. [Nature Geoscience 3 (2010) 811] (FR10). We found that models produce a higher GPP (133 ± 15 Pg C yr(-1) ) than JU11 (118 ± 6 Pg C yr(-1) ). In response to rising atmospheric CO2 concentration, modeled NPP increases on average by 16% (5-20%) per 100 ppm, a slightly larger apparent sensitivity of NPP to CO2 than that measured at the FACE experiment locations (13% per 100 ppm). Global NBP differs markedly among individual models, although the mean value of 2.0 ± 0.8 Pg C yr(-1) is remarkably close to the mean value of RLS (2.1 ± 1.2 Pg C yr(-1) ). The interannual variability in modeled NBP is significantly correlated with that of RLS for the period 1980-2009. Both model-to-model and interannual variation in model GPP is larger than that in model NBP due to the strong coupling causing a positive correlation between ecosystem respiration and GPP in the model. The average linear regression slope of global NBP vs. temperature across the 10 models is -3.0 ± 1.5 Pg C yr(-1) °C(-1) , within the uncertainty of what derived from RLS (-3.9 ± 1.1 Pg C yr(-1) °C(-1) ). However, 9 of 10 models overestimate the regression slope of NBP vs. precipitation, compared with the slope of the observed RLS vs. precipitation. With most models lacking processes that control GPP and NBP in addition to CO2 and climate, the agreement between modeled and observation-based GPP and NBP can be fortuitous. Carbon-nitrogen interactions (only separable in one model) significantly influence the simulated response of carbon cycle to temperature and atmospheric CO2 concentration, suggesting that nutrients limitations should be included in the next generation of terrestrial biosphere models.

Electrical control of the direction of spin accumulation.

We are able to continuously change the direction of polarization of spin accumulation in a nonmagnetic metal by varying the currents injected by two ferromagnetic spin injectors. From measurements made at a distance from the injection area, we find a cosvarphi variation of the spin signal. This confirms that the angle of polarization of the nonlocal spin polarization with respect to the magnetization of the fixed spin detector is continuously varied as we change the injection currents. We give an explanation for the origin of this simple cosvarphi variation of the spin signal.

Spin transfer in magnetic tunnel junctions with hot electrons.

Recent data on the bias dependence of the spin transfer effect in magnetic tunnel junctions have shown that torque remains intact at bias voltages for which the tunneling magnetoresistance has been strongly reduced. We show that the current induced excitations due to hot electrons, while reducing the magnetoresistance, enhance both the charge current and the spin transfer in magnetic tunnel junctions in such a manner that the ratio of the torque to the charge current does not significantly change.

Identification of transverse spin currents in noncollinear magnetic structures.

In this Letter we construct a spinor transport theory and derive the equations of motion for the distribution functions for currents in noncollinear magnetic multilayers. We find the length scale which characterizes the transverse spin current is of the order of 3 nm for a ferromagnetic 3d transition metal such as Co; this alters one's prediction of the spin torque generated for free magnetic layers less than 3 nm. In the limit of large exchange splitting we reproduce the results previously found for spin currents across noncollinear multilayers inasmuch as there are no transverse spin currents in the layers themselves in this limit.