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Surface ozone (O3) is the primary air pollutant threatening global vegetation. It typically reduces the photosynthetic rate and stomatal conductance, leading to changes in carbon, water, and energy cycles; vegetation structure and composition; and climate. Several parameterization schemes have been developed to integrate the photosynthetic and stomatal responses to O3 exposure in regional and global process-based models to simulate time- and space-varying O3 plant damage and its cascading dynamic influence. However, these schemes are calibrated based on limited observations and often fail to reproduce the response relationships in observations, impeding accurate assessments of the role of O3 plant damage in the Earth system. This study proposes a new parameterization scheme to utilize the extensive observations from O3 fumigation experiments to inform large-scale modeling. It is built on 4210 paired data points of photosynthetic and stomatal responses compiled from the peer-reviewed literature, more than 6 times larger than those employed in earlier schemes. Functions of phytotoxic O3 dose (POD) are found to accurately reproduce the statistically significant linear or nonlinear relationships observed between POD and either relative leaf photosynthetic rate or relative stomatal conductance for needleleaf trees, broadleaf trees, shrubs, grasses, and crops. These eliminate the practice in earlier schemes of setting response functions as constants and applying the response function from one vegetation type to another. It outperforms the old scheme in the Community Land Model (CLM), which skillfully reproduces the observed response for crop photosynthetic rate only. The nonlinear response functions we developed depict decreasing plant sensitivity with increases in POD, enabling models to implicitly capture the variability in plant ozone tolerance and the shift among plant species for both intra- and inter-PFTs (plant functional types) within a vegetation type observed in the real world. Then, the new scheme is incorporated into the Community Earth System Model version 2.2 (CESM2.2), specifically its land component CLM5, to quantify the global impacts of present-day O3 plant damage by comparing the simulations with and without O3 plant damage. Results show that O3 exposure reduces the global leaf photosynthetic rate by 8.5 % and stomatal conductance by 7.4 %, around half the estimates using the old scheme. Furthermore, the new scheme improves global gross primary productivity (GPP) simulations, decreasing RMSE by 11.1 % relative to simulations without O3 plant damage and by 11.7 % compared to the old scheme. These results underscore the importance of including O3 plant damage in large-scale process-based models and the effectiveness of the new scheme in assessing and projecting globally the role of O3 plant damage in the Earth system.

The present study describes the magnetic properties of nanotubes and nanowires of Permalloy through micromagnetic simulations. These properties are evaluated as a function of the external diameters of such one-dimensional nanostructures when the magnetic field applied is parallel and perpendicular to the easy axis of the nanostructures. In addition, the diameter of the nanostructures was also varied in order to discuss the similarities and differences in the magnetic properties as a function of their length.

Plant community composition influences carbon, water, and energy fluxes at regional to global scales. Vegetation demographic models (VDMs) allow investigation of the effects of changing climate and disturbance regimes on vegetation composition and fluxes. Such investigation requires that the models can accurately resolve these feedbacks to simulate realistic composition. Vegetation in VDMs is composed of plant functional types (PFTs), which are specified according to plant traits. Defining PFTs is challenging due to large variability in trait observations within and between plant types and a lack of understanding of model sensitivity to these traits. Here we present an approach for developing PFT parameterizations that are connected to the underlying ecological processes determining forest composition in the mixed-conifer forest of the Sierra Nevada of California, USA. We constrain multiple relative trait values between PFTs, as opposed to randomly sampling within the range of observations. An ensemble of PFT parameterizations are then filtered based on emergent forest properties meeting observation-based ecological criteria under alternate disturbance scenarios. A small ensemble of alternate PFT parameterizations is identified that produces plausible forest composition and demonstrates variability in response to disturbance frequency and regional environmental variation. Retaining multiple PFT parameterizations allows us to quantify the uncertainty in forest responses due to variability in trait observations. Vegetation composition is a key emergent outcome from VDMs and our methodology provides a foundation for robust PFT parameterization across ecosystems.

The land and ocean absorb on average just over half of the anthropogenic emissions of carbon dioxide (CO2) every year. These CO2 "sinks" are modulated by climate change and variability. Here we use a suite of nine dynamic global vegetation models (DGVMs) and four ocean biogeochemical general circulation models (OBGCMs) to estimate trends driven by global and regional climate and atmospheric CO2 in land and oceanic CO2 exchanges with the atmosphere over the period 1990–2009, to attribute these trends to underlying processes in the models, and to quantify the uncertainty and level of inter-model agreement. The models were forced with reconstructed climate fields and observed global atmospheric CO2; land use and land cover changes are not included for the DGVMs. Over the period 1990–2009, the DGVMs simulate a mean global land carbon sink of −2.4 ± 0.7 Pg C yr−1 with a small significant trend of −0.06 ± 0.03 Pg C yr−2 (increasing sink). Over the more limited period 1990–2004, the ocean models simulate a mean ocean sink of −2.2 ± 0.2 Pg C yr−1 with a trend in the net C uptake that is indistinguishable from zero (−0.01 ± 0.02 Pg C yr−2). The two ocean models that extended the simulations until 2009 suggest a slightly stronger, but still small, trend of −0.02 ± 0.01 Pg C yr−2. Trends from land and ocean models compare favourably to the land greenness trends from remote sensing, atmospheric inversion results, and the residual land sink required to close the global carbon budget. Trends in the land sink are driven by increasing net primary production (NPP), whose statistically significant trend of 0.22 ± 0.08 Pg C yr−2 exceeds a significant trend in heterotrophic respiration of 0.16 ± 0.05 Pg C yr−2 – primarily as a consequence of widespread CO2 fertilisation of plant production. Most of the land-based trend in simulated net carbon uptake originates from natural ecosystems in the tropics (−0.04 ± 0.01 Pg C yr−2), with almost no trend over the northern land region, where recent warming and reduced rainfall offsets the positive impact of elevated atmospheric CO2 and changes in growing season length on carbon storage. The small uptake trend in the ocean models emerges because climate variability and change, and in particular increasing sea surface temperatures, tend to counter\-act the trend in ocean uptake driven by the increase in atmospheric CO2. Large uncertainty remains in the magnitude and sign of modelled carbon trends in several regions, as well as regarding the influence of land use and land cover changes on regional trends.

The Community Land Model (CLM) can simulate planting and harvesting of crops but does not include effects of cultivation on soil carbon decomposition. The biogeochemistry model DayCent does account for cultivation and provides a baseline for evaluating the CLM. With the goal of representing cultivation effects on soil carbon decomposition, we implemented the DayCent cultivation parameterization in the CLM and compared CLM and DayCent simulations at eight Midwestern United States sites with and without the cultivation parameterization. Cultivation decreases soil carbon by about 1350 gC m−2 in the CLM and 1660 gC m−2 in DayCent across the eight sites from the first cultivation (early 1900s) to 2010. CLM crop simulations without cultivation have soil carbon gain, not loss, over this period, in contrast to the expected declining trends in agricultural soil carbon. A global cultivation simulation for 1973–2004 reduces ecosystem carbon by 0.4 Pg yr−1 over temperate corn, soybean, and cereal crop areas, which occupy approximately 1/3 of global crop area. Earth System Models may improve their atmospheric CO2 and soil carbon simulations by accounting for enhanced decomposition from cultivation.

Fire is the primary form of terrestrial ecosystem disturbance on a global scale. It affects the net carbon balance of terrestrial ecosystems by emitting carbon directly and immediately into the atmosphere from biomass burning (the fire direct effect), and by changing net ecosystem productivity and land-use carbon loss in post-fire regions due to biomass burning and fire-induced vegetation mortality (the fire indirect effect). Here, we provide the first quantitative assessment of the impact of fire on the net carbon balance of global terrestrial ecosystems during the 20th century, and investigate the roles of fire's direct and indirect effects. This is done by quantifying the difference between the 20th century fire-on and fire-off simulations with the NCAR Community Land Model CLM4.5 (prescribed vegetation cover and uncoupled from the atmospheric model) as a model platform. Results show that fire decreases the net carbon gain of global terrestrial ecosystems by 1.0 Pg C yr−1 averaged across the 20th century, as a result of the fire direct effect (1.9 Pg C yr−1) partly offset by the indirect effect (−0.9 Pg C yr−1). Post-fire regions generally experience decreased carbon gains, which is significant over tropical savannas and some North American and East Asian forests. This decrease is due to the direct effect usually exceeding the indirect effect, while they have similar spatial patterns and opposite sign. The effect of fire on the net carbon balance significantly declines until ∼1970 with a trend of 8 Tg C yr−1 due to an increasing indirect effect, and increases subsequently with a trend of 18 Tg C yr−1 due to an increasing direct effect. These results help constrain the global-scale dynamics of fire and the terrestrial carbon cycle.

Accurate assessments of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere is important to better understand the global carbon cycle, support the climate policy process, and project future climate change. Present-day analysis requires the combination of a range of data, algorithms, statistics and model estimates and their interpretation by a broad scientific community. Here we describe datasets and a methodology developed by the global carbon cycle science community to quantify all major components of the global carbon budget, including their uncertainties. We discuss changes compared to previous estimates, consistency within and among components, and methodology and data limitations. CO2 emissions from fossil fuel combustion and cement production (EFF) are based on energy statistics, while emissions from Land-Use Change (ELUC), including deforestation, are based on combined evidence from land cover change data, fire activity in regions undergoing deforestation, and models. The global atmospheric CO2 concentration is measured directly and its rate of growth (GATM) is computed from the concentration. The mean ocean CO2 sink (SOCEAN) is based on observations from the 1990s, while the annual anomalies and trends are estimated with ocean models. Finally, the global residual terrestrial CO2 sink (SLAND) is estimated by the difference of the other terms. For the last decade available (2002–2011), EFF was 8.3 ± 0.4 PgC yr−1, ELUC 1.0 ± 0.5 PgC yr−1, GATM 4.3 ± 0.1PgC yr−1, SOCEAN 2.5 ± 0.5 PgC yr−1, and SLAND 2.6 ± 0.8 PgC yr−1. For year 2011 alone, EFF was 9.5 ± 0.5 PgC yr−1, 3.0 percent above 2010, reflecting a continued trend in these emissions; ELUC was 0.9 ± 0.5 PgC yr−1, approximately constant throughout the decade; GATM was 3.6 ± 0.2 PgC yr−1, SOCEAN was 2.7 ± 0.5 PgC yr−1, and SLAND was 4.1 ± 0.9 PgC yr−1. GATM was low in 2011 compared to the 2002–2011 average because of a high uptake by the land probably in response to natural climate variability associated to La Niña conditions in the Pacific Ocean. The global atmospheric CO2 concentration reached 391.31 ± 0.13 ppm at the end of year 2011. We estimate that EFF will have increased by 2.6% (1.9–3.5%) in 2012 based on projections of gross world product and recent changes in the carbon intensity of the economy. All uncertainties are reported as ±1 sigma (68% confidence assuming Gaussian error distributions that the real value lies within the given interval), reflecting the current capacity to characterise the annual estimates of each component of the global carbon budget. This paper is intended to provide a baseline to keep track of annual carbon budgets in the future. All data presented here can be downloaded from the Carbon Dioxide Information Analysis Center (doi:10.3334/CDIAC/GCP_V2013).

Modeling fire as an integral part of an Earth system model (ESM) is vital for quantifying and understanding fire–climate–vegetation interactions on a global scale and from an Earth system perspective. In this study, we introduce to the Community Earth System Model (CESM) the new global fire parameterization proposed by Li et al. (2012a, b), now with a more realistic representation of the anthropogenic impacts on fires, with a parameterization of peat fires, and with other minor modifications. The improved representation of the anthropogenic dimension includes the first attempt to parameterize agricultural fires, the economic influence on fire occurrence, and the socioeconomic influence on fire spread in a global fire model – also an alternative scheme for deforestation fires. The global fire parameterization has been tested in CESM1's land component model CLM4 in a 1850–2004 transient simulation, and evaluated against the satellite-based Global Fire Emission Database version 3 (GFED3) for 1997–2004. The simulated 1997–2004 average global totals for the burned area and fire carbon emissions in the new fire scheme are 338 Mha yr−1 and 2.1 Pg C yr−1. Its simulations on multi-year average burned area, fire seasonality, fire interannual variability, and fire carbon emissions are reasonable, and show better agreement with GFED3 than the current fire scheme in CESM1 and modified CTEM-FIRE. Moreover, the new fire scheme also estimates the contributions of global fire carbon emissions from different sources. During 1997–2004, the contributions are 8% from agricultural biomass burning, 24% from tropical deforestation and degradation fires, 6% from global peat fires (3.8% from tropical peat fires), and 62% from other fires, which are close to previous assessments based on satellite data, government statistics, or other information sources. In addition, we investigate the importance of direct anthropogenic influence (anthropogenic ignitions and fire suppression) on global fire regimes during 1850–2004, using CESM1 with the new fire scheme. Results show that the direct anthropogenic impact is the main driver for the long-term trend of global burned area, but hardly contributes to the long-term trend of the global total of fire carbon emissions.

This REgional Carbon Cycle Assessment and Processes regional study provides a synthesis of the carbon balance of terrestrial ecosystems in East Asia, a region comprised of China, Japan, North and South Korea, and Mongolia. We estimate the current terrestrial carbon balance of East Asia and its driving mechanisms during 1990–2009 using three different approaches: inventories combined with satellite greenness measurements, terrestrial ecosystem carbon cycle models and atmospheric inversion models. The magnitudes of East Asia's terrestrial carbon sink from these three approaches are comparable: −0.293±0.033 PgC yr−1 from inventory–remote sensing model–data fusion approach, −0.413±0.141 PgC yr−1 (not considering biofuel emissions) or −0.224±0.141 PgC yr−1 (considering biofuel emissions) for carbon cycle models, and −0.270±0.507 PgC yr−1 for atmospheric inverse models. Here and in the following, the numbers behind ± signs are standard deviations. The ensemble of ecosystem modeling based analyses further suggests that at the regional scale, climate change and rising atmospheric CO2 together resulted in a carbon sink of −0.289±0.135 PgC yr−1, while land-use change and nitrogen deposition had a contribution of −0.013±0.029 PgC yr−1 and −0.107±0.025 PgC yr−1, respectively. Although the magnitude of climate change effects on the carbon balance varies among different models, all models agree that in response to climate change alone, southern China experienced an increase in carbon storage from 1990 to 2009, while northern East Asia including Mongolia and north China showed a decrease in carbon storage. Overall, our results suggest that about 13–27% of East Asia's CO2 emissions from fossil fuel burning have been offset by carbon accumulation in its terrestrial territory over the period from 1990 to 2009. The underlying mechanisms of carbon sink over East Asia still remain largely uncertain, given the diversity and intensity of land management processes, and the regional conjunction of many drivers such as nutrient deposition, climate, atmospheric pollution and CO2 changes, which cannot be considered as independent for their effects on carbon storage.

Plants exchange greenhouse gases carbon dioxide and water with the atmosphere through the processes of photosynthesis and transpiration, making them essential in climate regulation. Carbon dioxide and water exchange are typically coupled through the control of stomatal conductance, and the parameterization in many models often predict conductance based on photosynthesis values. Some environmental conditions, like exposure to high ozone (O3) concentrations, alter photosynthesis independent of stomatal conductance, so models that couple these processes cannot accurately predict both. The goals of this study were to test direct and indirect photosynthesis and stomatal conductance modifications based on O3 damage to tulip poplar (Liriodendron tulipifera) in a coupled Farquhar/Ball-Berry model. The same modifications were then tested in the Community Land Model (CLM) to determine the impacts on gross primary productivity (GPP) and transpiration at a constant O3 concentration of 100 parts per billion (ppb). Modifying the Vcmax parameter and directly modifying stomatal conductance best predicts photosynthesis and stomatal conductance responses to chronic O3 over a range of environmental conditions. On a global scale, directly modifying conductance reduces the effect of O3 on both transpiration and GPP compared to indirectly modifying conductance, particularly in the tropics. The results of this study suggest that independently modifying stomatal conductance can improve the ability of models to predict hydrologic cycling, and therefore improve future climate predictions.

A process-based fire parameterization of intermediate complexity has been developed for global simulations in the framework of a Dynamic Global Vegetation Model (DGVM) in an Earth System Model (ESM). Burned area in a grid cell is estimated by the product of fire counts and average burned area of a fire. The scheme comprises three parts: fire occurrence, fire spread, and fire impact. In the fire occurrence part, fire counts rather than fire occurrence probability are calculated in order to capture the observed high burned area fraction in areas of high fire frequency and realize parameter calibration based on MODIS fire counts product. In the fire spread part, post-fire region of a fire is assumed to be elliptical in shape. Mathematical properties of ellipses and some mathematical derivations are applied to improve the equation and assumptions of an existing fire spread parameterization. In the fire impact part, trace gas and aerosol emissions due to biomass burning are estimated, which offers an interface with atmospheric chemistry and aerosol models in ESMs. In addition, flexible time-step length makes the new fire parameterization easily applied to various DGVMs. Global performance of the new fire parameterization is assessed by using an improved version of the Community Land Model version 3 with the Dynamic Global Vegetation Model (CLM-DGVM). Simulations are compared against the latest satellite-based Global Fire Emission Database version 3 (GFED3) for 1997–2004. Results show that simulated global totals and spatial patterns of burned area and fire carbon emissions, regional totals and spreads of burned area, global annual burned area fractions for various vegetation types, and interannual variability of burned area are reasonable, and closer to GFED3 than CLM-DGVM simulations with the commonly used Glob-FIRM fire parameterization and the old fire module of CLM-DGVM. Furthermore, average error of simulated trace gas and aerosol emissions due to biomass burning is 7% relative to GFED3. Results suggest that the new fire parameterization may improve the global performance of ESMs and help to quantify fire-vegetation-climate interactions on a global scale and from an Earth system perspective.

Fire is an integral Earth System process that interacts with climate in multiple ways. Here we assessed the parametrization of fires in the Community Land Model (CLM-CN) and improved the ability of the model to reproduce contemporary global patterns of burned areas and fire emissions. In addition to wildfires we extended CLM-CN to account for fires related to deforestation. We compared contemporary fire carbon emissions predicted by the model to satellite-based estimates in terms of magnitude and spatial extent as well as interannual and seasonal variability. Long-term trends during the 20th century were compared with historical estimates. Overall we found the best agreement between simulation and observations for the fire parametrization based on the work by Arora and Boer (2005). We obtained substantial improvement when we explicitly considered human caused ignition and fire suppression as a function of population density. Simulated fire carbon emissions ranged between 2.0 and 2.4 Pg C/year for the period 1997–2004. Regionally the simulations had a low bias over Africa and a high bias over South America when compared to satellite-based products. The net terrestrial carbon source due to land use change for the 1990s was 1.2 Pg C/year with 11% stemming from deforestation fires. During 2000–2004 this flux decreased to 0.85 Pg C/year with a similar relative contribution from deforestation fires. Between 1900 and 1960 we predicted a slight downward trend in global fire emissions caused by reduced fuels as a consequence of wood harvesting and also by increases in fire suppression. The model predicted an upward trend during the last three decades of the 20th century as a result of climate variations and large burning events associated with ENSO-induced drought conditions.

Using two climate-vegetation model simulations from the Fast Ocean Atmosphere Model (FOAM) and the Community Climate System Model (CCSM, version 2), we investigate vegetation-precipitation feedbacks across North Africa during the mid-Holocene. From mid-Holocene snapshot runs of FOAM and CCSM2, we detect a negative feedback at the annual timescale with our statistical analysis. Using the Monte-Carlo bootstrap method, the annual negative feedback is further confirmed to be significant in both simulations. Additional analysis shows that this negative interaction is partially caused by the competition between evaporation and transpiration in North African grasslands. Furthermore, we find the feedbacks decrease with increasing timescales, and change signs from positive to negative at increasing timescales in FOAM. The proposed mechanism for this sign switch is associated with the different persistent timescales of upper and lower soil water contents, and their interactions with vegetation and atmospheric precipitation.

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Over the last ten years, the number of new psychoactive substances (NPS) reported to UNODC has increased significantly to over 1,200 individual substances, reported by 141 countries and territories worldwide. Countries have addressed the challenges they face with proactive and innovative responses including a variety of national legislative responses. While these measures have to a large extent contributed to a reduction of these harmful substances and an overall stabilization of the NPS market, significant challenges remain, such as the continued presence of synthetic opioids, as well as new types of benzodiazepines and synthetic cannabinoids. Therefore, strong international collaboration among all actors is needed to detect, identify, monitor, analyse and share information on the use and risks of these substances. The UNODC early warning advisory and national and regional early warning mechanisms are key to generating the scientific evidence necessary to identify emerging harmful substances and develop appropriate responses at the national and international level. Translating trends into a threat analysis to communicate potential risks and raise awareness is key to reducing risks to public health and for effective policy design and programme interventions.