Changes in soil C with classic soil sample analysis require long ‐term monitoring of CS systems. A short‐term quanti ﬁcation of C dynamics can be achieved with the eddy covariance (EC) method, where the carbon ﬂux (Fc) is calculated as the mean covariance of atmospheric CO 2 density and the vertical wind scalar (Burba, 2013). The annual sum of F c is the net ecosystem production (NEP), that is, the sum of assimilated and respired carbon within the footprint of the EC system. With the additional knowledge of residue and grain C removal and organic fertilizer input, the net biome production (NBP) is calculated, which is a measure of the “apparent” change in soil C (Baker & Grifﬁs, 2005). Several studies have analyzed NEP and NBP in corn ‐soybean systems. Corn‐years have been identiﬁed as either C neutral or C source, while soybean‐years are a C source under conventional crop management in the Midwestern United States (Dold et al., 2017; Verma et al., 2005). There is little impact of irrigation on NEP, while ecosystem respiration increases with irri- gation (Verma et al., 2005). Reduced ‐till cover‐crop systems had substantially higher NEP during the off‐sea- son, probably owing to reduced mineralization of crop residues (Dold et al., 2019). However, Baker and Grif ﬁs (2005) found small differences in NEP in strip till compared to conventional CS. While the EC method has been widely used in studying carbondynamics, the method depends on several preconditions. This can affect the quality of Fc measurements, for example, by the underestimation of nighttime ﬂuxes (Burba, 2013). Yet only a few studies have assessed C dynamics using a combination of several methods, for example, deep ‐core soil analysis and EC ﬂux measurements (Abraha et al., 2016; Curtis et al., 2002; Ferster et al., 2015; Leifeld et al., 2011; Skinner & Dell, 2015; Stahl et al., 2017; Vaccari et al., 2012; Verma et al., 2005). Verma et al. (2005) found similar trends with both EC measurements and topsoil sampling in CS, but the study period was too short for a comprehensive analysis and did not include the subsoil. Abraha et al. (2016) compared CS in Michigan with both deep ‐core sampling and the EC method in a 6‐yr study. Zenone et al. (2011) reported both signi ﬁcant and not signiﬁcant relationships between NEE and soil C, depending on season and crop. Other studies focused on other cropping systems and biomes and comparison to CS is limited.
considered important sources, sinks and/or transformers of biologically vital elements in the coastal ecosystems (Tobias & Neubauer 2009). Element cycling in salt marshes involve many different ecological processes which are affected by a wide range of environmental factors. For example, as salt marshes form at the interface between land and sea, they often have a high rate of sedimentation. The sedimentation rate in salt marshes depends on suspended sediment concentrations, tidal range, vegetation, proximity to the sediment source, and hydroperiod (Friedrichs & Perry 2001). After deposition, sediment and associated organic carbon could be decomposed by microorganisms (Bianchi 2011), buried (Duarte et al. 2013, Lovelock et al. 2014) or even exported to adjacent ecosystems (Chen et al. 2015). The fate of organic carbon depends on many factors such as geological set up, hydrodynamics, microbial communities, and anthropogenic activities (Zhou et al. 2006, Macreadie et al. 2013, Saintilan et al. 2013, Ouyang & Lee 2014, Rosencranz et al. 2016). Those processes, however, have not been fully understood. The use of stable isotopes in salt marsh studies now enables us to determine the source of elements, as well as to track them as they cycle in ecosystems. Moreover, the advantages of stable isotope techniques nowadays allow us to study biogeochemical processes of salt marshes in greater detail and at different scales.
contour tillage by a chisel, following Van Muysen et al. (2000). For SOC redistribution and modelling of vertical C fluxes, the most important model inputs were yields and ma- nure application, a topsoil SOC map (12.5 m x 12.5 m; Sinowski et al., 1997) and as- sumptions regarding the allocation of C to different texture classes and in different aggregates. As texture and aggregate C allocation was not measured, we took measured data from Doetterl et al. (2012a) and scaled these measurements according to the available bulk SOC (see Section 4.2.3: Representation of grain-size-specific soil and SOC). The parameters for the C turnover model are taken from Dlugoß et al. (2012), who worked under similar environmental conditions with loess-derived soils in a small catchment in western Germany. The C turnover decline with depth was determined by an inverse mod- elling approach and found a mean turnover rate of 0.268 year -1 for the young pool and 0.002 year -1 for the old pool over the 1 m soil profile. Further details regarding the mon- itoring data are given in Fiener and Auerswald (2003, 2007b) and Fiener et al. (2008). As indicated above, it is difficult, if not impossible, to identify erosion-induced changes in SOC and vertical C fluxes if measurements or modelling efforts do not cover decadal time spans. Therefore, a 50-year synthetic input data set and parameter set was created for MCST-C in order to analyse C dynamics. This data set is based on the 8 years of measured data used to validate the erosion component of the model. First, a time series of precipitation was established by randomly choosing the data of one of the eight meas- ured years (see Section 4.2.5: Model validation) and applying it for the first 42 years of the time series. This was followed by the original 8 measured years to reach the total of 50 years. Next, this precipitation time series was combined with synthetic land use and soil management data representing two full crop rotations (1994 to 2001), which were repeatedly used for all 50 years. This combination leads to a wide variety of precipitation events (time step 1 min) occurring for different daily soil covers by vegetation as a major driver of soil erosion. In contrast to the erosion dynamics, C inputs via plants and manure are repeated every 8 years, which ignores any potential change in management and yields within the modelling period. The synthetic input data were applied for both catchments for the purpose of comparability.
The soil microbial community as a major driver of most grassland ecosystem functions is directly affected by digestate application. According to current knowledge, digestates increase soil microbial biomass and activity after application on bare and planted soils (Ernst et al., 2008; Odlare et al., 2008; Terhoeven–Urselmans et al., 2009; Bachmann et al., 2011). Arthurson (2009) reviewed that the amount of metabolically active microorganisms increase after digestate application compared to unfertilized soils due to the input of mineral nutrients and organic material. In particular, the quantity and quality of carbon added to the soil with digestates affect the microbial soil community metabolism (Ernst et al., 2008). The N metabolism of soil microorganism was found to be affected by digestate application. Peters and Jensen (2011) found in an incubation experiment a significant negative correlation between net N mineralization and C:N org ratio of solid fractions from animal slurry separation. Furthermore, soil microorganisms may compete with plants for N (Bardgett et al., 1999; Geisseler et al., 2010) and the N immobilization process is likewise related to the amount and decomposability of C for the microorganisms (Geisseler et al., 2010), and thus may be influenced by digestate composition. Therefore, it might be expected that, because of its reduced C content, the IFBB digestate differs in the effects on soil microbial organisms and their functioning compared to the C richer conventional whole crop digestates.
Saltwater coastal wetlands are generally found in sheltered waters and include mangrove forests, seagrass meadows and tidal salt marshes. These wetlands host highly productive plant communities, which take up substantial amounts of carbon via photosynthesis (Mcleod et al. 2011). The carbon stored in these coastal ecosystems has been coined “blue carbon” (Laffoley and Grimsditch 2009) and mangroves, being a blue carbon sink, are among the most carbon-rich ecosystems on earth (Mcleod 2011). It has been estimated that mangrove forests sequester and store carbon at rate 50 times higher than tropical rainforests (Laffoley and Grimsditch 2009). They not only photosynthesize to acquire carbon from the atmosphere but are also very efficient in trapping suspended matter and associated organic carbon during tidal inundation due to their complex root systems (Furukawa et al., 1996). Carbon can be stored within the aboveground living biomass (leaves, branches, trunks), the belowground living biomass (roots) and the non-living biomass (litter and dead wood) over the short term (decennial) (Howard et al. 2014) or can be stored for longer time scales within the sediments (Brevik et al. 2004). Compared to terrestrial ecosystems, mangrove sediments are saturated with water keeping them in an anaerobic state and thus preventing aerobic microbial carbon oxidation and carbon release into the atmosphere through respiration. Carbon located within mangrove sediment represents the majority of the ecosystem carbon stock within mangrove forests (Donato et al. 2011; Adame et al. 2013) but significant amounts of the captured carbon are exported as organic and inorganic carbon to the coastal zone (Odum 1968; Lee 1995). The coastal zone reflects another important carbon sink. The tidally induced export of dissolved inorganic carbon (DIC) may account for more than 50% of the total net primary production in mangroves (Maher et al. 2013; Sippo et al. 2016; Ray et al. 2018). Due to their high carbon sink potential they can effectively contribute to climate change mitigation strategies on a national scale for tropical and subtropical countries with extensive coastlines (Murdiyarso et al. 2015).
Figures 1 - 4 give overviews of the properties of the stands considered. First, consider case 1 and the scenario without harvesting and tree planting (Figure 1). At time t = 0; assuming that harvesting has not yet taken place, the stand’s total carbon stock is 108.1 tC, including 44.3 tC stored in living biomass, 3.9 tC stored in natural deadwood and 60 tC stored in the soil layer. In the tree planting scenario (Figure 2), stems of living trees together with 25 per cent of other living biomass (residues) are removed after clear cutting of the stand at time t = 0: Throughout it is assumed that stems constitute 48 per cent of total living biomass. This means that 27.0 tC is removed from that stand with subsequent combustion giving rise to a corresponding pulse of carbon. It follows that after clear-cutting and harvesting the stand stores 77.2 tC (Figure 2).
Shen et al. [ 7 ] tested 54 different spectral pretreatments to preprocess soil spectral data acquired in the laboratory for an improved SOM prediction using partial least squares regression (PLSR) techniques. These spectral pretreatments consisted of three denoising methods, six data transformations, and three dimensionality reduction methods. Over- all, the denoising caused a strong reduction of overfitting and increased accuracy. The pretreatment will become ever more important as remote sensing platforms evolve from multispectral to hyperspectral instruments. On the one hand, multispectral satellite data are now readily available and their frequency of overflight allows the establishment of time series. On the other hand, multispectral and hyperspectral UAV systems are affordable options for acquiring images at the field scale under ideal conditions, as the operators can quickly launch a campaign at low costs. Žížala et al. [ 8 ] compared the performance of SOC prediction models in a large cropland field for multispectral satellite and UAV sensors with different spatial and spectral resolution against a baseline using an airborne hyperspectral sensor. A moderately strong spatial correlation was obtained between the baseline SOC maps and the maps produced by all other sensors. Wehrhahn and Sommer [ 9 ] provide an example of high-resolution UAV-based SOC mapping in a number of cropland fields in hummocky terrain where tillage erosion creates high spatially-distributed SOC dynamics. Multiple linear regression models including both spectral and topographic variables already produce robust SOC prediction models. For mapping of large areas using satellite imagery, the consistent analysis of calibration samples becomes a bottleneck. Ward et al. [ 10 ] used a two-step approach to predict the SOC contents for airborne HySpex and simulated EnMAP imagery acquired in northeastern Germany, based on the local PLSR method for model building. First, the local PLSR uses the European LUCAS soil spectral database to quantify the SOC content for soil samples from the study site, and second, a remote sensing model is calibrated based on the local PLSR SOC results and the corresponding image spectra.
In aquatic ecosystems, phytoplankton primary production, zooplankton grazing, and pelagic respiration are important processes of carbondynamics. The aim of this study is to quantify the annual dynamics of pelagic primary production, zooplankton grazing, and respiration in a shallow coastal system and to investigate possible benthic impacts. Pelagic primary production, zooplankton grazing, and respiration were investigated as weekly/monthly time series over a one year period in the northern Wadden Sea. Studies were related to the Sylt long term time series, providing data on temperature, salinity, inorganic and organic nutrients, chlorophyll a and suspended matter concentrations (e.g. M ARTENS & E LBRÄCHTER 1998). This study was conducted in the framework of the European Research Project COSA (Coastal Sands as Biocatalytical Filters) to relate the temporal dynamics of pelagic carbondynamics with benthic processes.
reduced by 21%. FirmIndir, the cheapest carbon policy regime for the world as an entity is, thus, not riddled by severe distributional dilemmas.
All these tariff regimes reduce global welfare costs of EUR’s carbon policies compared to Bench; the most effective, FirmIndir, by as much as 18%. This is a larger benefit of carbon tariffs than in the previous studies listed above.The reason is that this carbon tariff regime is based on firm-specific information and account for indirect emissions. As shown in the theoretical section, such carbon tariffs are more targeted than previously studied designs, because they motivate unit emission reductions in the firms (both directly and indirectly) involved in exporting to EUR. While introducing region- specific tariffs based on the direct emissions (RegDir) reduces global welfare loss by merely 4%, going from RegDir to FirmDir implies an additional 3 percentage points reduction in welfare costs (see Figure 6). Further, also including indirect emissions in FirmIndir saves another 11 percentage points of the welfare costs – in total 18% – compared to Bench.
Over the last decade, a large number of computable general equilibrium (CGE) studies of BCAs have been carried out. The majority of the studies focus on carbon tariffs on imports, only; i.e. they do not consider simultaneous export subsidies. They confirm that carbon tariffs reduce the carbon leakage problem of unilateral policies. Also, the coalition’s efficiency costs of its carbon policies, as well as the competitiveness losses of its emission-intensive industries, decline, while the opposite is true for non-coalition countries. See Branger and Quirion (2014), Böhringer et al. (2012a), and Zhang (2012) for recent overviews. The numerical studies have increased our knowledge of the role of various factors like coalition size, the coverage of the carbon tariffs, and how embodied emissions are calculated. Many studies include indirect emissions in the the tariff calculations. Only rarely are all embodied emissions accounted for (e.g., Böhringer et al., 2012b), but rather often are the emissions arising from the use of electricity accounted for (e.g. Mattoo et al. 2009, Winchester 2011, Böhringer et al. 2012a).
Institute of Statics and Dynamics in Aerospace Structures, University of Stuttgart, Pfaffenwaldring 27, D- 70550 Stuttgart
SUMMARY: The major process for manufacturing carbon/carbon composites is the carboni-
zation of carbon fibre reinforced plastics (CFRP). In this process, the shrinkage of the matrix is hindered by the fibres and leads to a high amount of cracks resulting in a microscopic open porosity. To control this process, it is necessary to gain knowledge about its essential parame- ters, in which the crack microstructure plays an important role. Micrographs (SEM) revealed that the cracks can be distinguished in three different types: fibre-matrix debonding, segmenta- tion cracks and micro-delaminations. Fibre-matrix bonding determines which crack type domi- nates the structure of the final carbon/carbon composite. The evolution of the cracks during pyrolysis (temperature, sequence and importance of the crack types) was investigated by means of acoustic emission and microscopy in combination with a heating stage. By comparing these results with those of thermogravimetric analysis and dilatometer experiments, the devel- opment of the cracks can be explained.
Although the DICE model, which is used widely in the integrated assessment literature (Nordhaus, 2008; 2014), allows for a negative impact of pricing carbon on fossil fuel use, it does not allow for scarce fossil fuel and for forward-looking expectations and thus does not shed much light on the issue of expectations and timing of optimal energy transitions. Furthermore, integrated assessment studies based on DICE and the tractable general equilibrium model of growth and climate change developed by Golosov et al. (2014), denoted by GHKT from hereon, do not allow for fossil fuel extraction costs that rise as fossil fuel reserves are depleted and more costly fields or deposits have to be explored. These studies thus do not give an answer to the question how the prices of carbon and its energy alternatives and expectations of the future prices affect the optimal amount of abandoned fossil fuel reserves (also known as stranded assets). This is a major shortcoming, since much of the debate among climate scientists is about the crucial importance of limiting cumulative carbon emissions and thereby increasing the size of stranded assets. Clearly, this has a big negative impact on fossil fuel producers. Our objective is to address these issues in a modified version of the GHKT model and obtain a tractable solution and simple rule for both the optimal SCC and SBL. 2 We extend the GHKT model in five directions. First, we allow for stock-dependent fossil fuel extraction costs and partial exhaustion of fossil fuel reserves. Carbon taxation thus has to be designed to bring forward the carbon-free era but also to leave more fossil fuel abandoned in the crust of the earth. Second, we take account of the empirical findings of Dell et al. (2013) and allow global warming to negatively affect both the level and growth rate of total factor productivity. Empirical evidence suggests that this negative growth effect is substantial for low-income countries. Growth is driven by steady labour-augmenting technical progress. Third, we allow for a direct effect of atmospheric carbon on welfare. Fourth, we allow for population growth and explore its effects on the social cost of carbon under utilitarian welfare. Fifth, we allow for specific green innovations bringing down the cost of renewable production via learning by doing. We thus derive a simple rule for the subsidy for renewable energy given endogenous technical progress in renewable energy production.
The bulk of empirical analysis on the implications of carbon tariffs, therefore, comes up with two central findings (for summaries see e.g., Böhringer et al., 2012; Branger and Quirion, 2014): (i) carbon tariffs are potent in reducing emission leakage but gains in global cost- effectiveness remain rather modest, and (ii) carbon tariffs shift the economic burden of emission reductions from regulating developed regions to unregulated developing regions. Empirical analyses so far have been based on pointwise assessments for specific base-years without accounting for the fact that embodied carbon in trade has increased significantly over time. While industrialized OECD countries for example, have become large net importers, developing Non-OECD countries are mostly large net exporters of embodied carbon (Caldeira and Davis, 2011; Peters and Hertwich, 2008; Peters et al., 2011). This raises the policy-relevant question on the performance of carbon tariffs if one considers the increasing relevance of embodied carbon in trade. Clearly, if there was no carbon in trade at all, the implementation of carbon tariffs would have no effect. In turn, it seems plausible at first glance that the potential of carbon tariffs to reduce leakage and increase global cost- effectiveness of unilateral emission pricing augments as trade in carbon sharply increases. And what about the burden shifting effect of carbon tariffs over time?
public and financial markets. This explains why most of the carbon intensive companies seem not to be affected by increasing carbon prices with respect to their credit risk in the early period. Hence, the awareness of carbon risk seems to increase with time, which also holds for the contract’s maturity. Concentrating on the five years maturity regression results we find that most of the heavy emitters suffer from carbon risk and the less carbon intensive panels benefit from increasing EUA futures prices. We conclude that carbon risk is a longer-term phenomenon. From a policy perspective this seems reasonable, be- cause carbon risk incorporates policy risk. However, policy decisions and implementations rather face time horizons of years than months. A main reason for this is the security of investment. Thus, companies should be able to plan their investments assuming regulatory stability. In Germany and the European Union emission reduction targets are well com- municated and the regulatory rules within an EU ETS trading periods are transparent. Nevertheless, the somewhat sudden implementation of a driving ban in German cities, such as Essen, Frankfurt, Stuttgart and Berlin, for diesel vehicles with Euro4 or Euro5 engines signals an increase in policy uncertainty. This could lead to an increase in carbon risk perception, because regulatory stability is weakened. This explains the explanatory power of the five years maturity regression results.
In summary, a series of low condensed carbon nitride materials based on heptazine units were synthesized showing photocatalytic activity for the hydrogen evolution reaction. Though we were not able to unambiguously elucidate the composition and structure of the melamine samples calcined for an increasing period of time, we have accumulated evidence that the calcined samples are mixtures of melem and melem oligomers. TEM analysis of the samples calcined for a short period of time as well as for intermediate times invariably shows the presence of melem in the samples. However, another crystalline phase was observed which likely is another modification of melem, possibly a planar structure. The melem oligomers presumably resemble melon on a local level as well as with respect to their planar layered structure, but seem to be essentially amorphous. Nevertheless, the solubility of the calcined samples is quite low. Three kinds of solvents (non-polar, polar aprotic and polar protic solvents) were tested, but only DMSO slightly dissolves parts of the samples which contain melem. The photocatalytic activities of these calcined melamine samples in the hydrogen evolution reaction are smaller than that of melon.
30 bar. 86 Higher temperatures require other electrical technologies, e.g. resistance furnaces, induction heating, microwave heating or non-fossil fuels. 87
The production of hydrogen is assumed to switch from steam methane reforming to water splitting via electrolysis. Furthermore, ammonia is no longer produced by the Haber– Bosch but by electrochemical conversion, rendering the steam methane reforming step in ammonia synthesis obsolete. 88 Other chemical processes, including the direct oxidation of ethylene to ethylene oxide can be substituted by carbon capture and utilization technologies or bio-based processes. In consequence, steam crackers with naphtha as a major fossil feedstock for the chemical industry can be decommissioned. 7,89–92
CESifo Forum 2/2011
gin). For example, Figure 2 decomposes Chinese exports of virtual carbon by destination. More than half of China’s virtual carbon is exported to the EU15, Japan and the United States. But carbon- intensive products are delivered to other emerging economies such as Mexico, India and Russia. In the two lower maps in Figure 1, the data is adjust- ed for the size of the economy and its population. The general picture remains, however some changes can be observed. In both intensity illustrations, South Africa becomes a large net exporter, whereas the net exports of ‘Other middle income’ countries take a more moderate level. The Latin American counties which are part of this group now range in the same category as Brazil. In the bottom map, after adjusting for population, Canada becomes a large net exporter and China a small net exporter. This reflects that Canada in contrast to China is not a very populous country.
In this paper we focus on the economic implications of carbon tariffs for EITE industries. Contrary to previous findings, we show that carbon tariffs can worsen rather than ameliorate adverse impacts for unilaterally regulated EITE industries. The key impact drivers are the amount and composition of embodied emissions in EITE production (consisting of direct emissions from fossil fuel inputs, indirect emissions embodied in domestically produced intermediate inputs, and indirect emissions embodied in imported intermediate inputs) and the share of EITE production that is supplied to the export market. If the carbon embodied in an EITE good stems predominantly from imported inputs, then this industry can rather suffer than benefit from the imposition of carbon tariffs. Likewise, industries exporting larger shares of their output suffer more, since carbon tariffs level the playing field only in domestic markets but lead to a further cost- disadvantage in foreign markets. Export-oriented EITE industries that are relatively clean in terms of direct emissions but rather dirty in terms of the imported carbon run the risk to shoot themselves in the foot if they lobby for carbon tariffs. We draw our conclusions from combined multi-region input-output (MRIO) and computable general equilibrium (CGE) analyses. In our numerical simulations we focus on Switzerland and the United States of America as prime examples of how carbon tariffs can affect the performance of EITE industries in opposing ways. While we find that carbon tariffs reduce the adverse EITE production impacts of unilateral emission pricing in the case of the US, they exacerbate the negative EITE production effects in the case of Switzerland.
Empirical studies were carried out to reveal the impact of carbon tax on industries and society. Research by Lin and Li (2011) comprehensively estimated the real mitigation effects of the five north European countries who were the first adopters of carbon tax. They found that mitigation effect of carbon tax differs from country to country. For example, the carbon tax on Finland actually exerts a negative and significant impact on CO2 emission. In addition, research by Hübler (2012) found that the mitigation effect of carbon tariff on emission appears small through analyze China’s commodities trade by the CGE model. Besides, many recent climate- policy proposals contain provisions for carbon tariff, such as the Waxman-Markey Bill and the Kerry-Boxer in the US, the revised directive of the EU ETS and so on (Springmann, 2012).
In the Paris Agreement, all countries committed to transitioning towards low-carbon, climate- resilient economies. Several policy instruments have been proposed to finance this transition, including green bonds and carbon pricing. Often these instruments are perceived as alternative choices, but this paper finds there are important gains from deploying them jointly, provided countries have sufficient fiscal space. Debt levels are rising in many low-income countries (Essl et al. 2019), and in such circumstances it is preferable for climate policy to be financed by taxation or budget reallocation instead of deficit spending (Forni et al. 2019). However, for advanced econo- mies, Blanchard (2019) observes that sovereign debt is, in contrast to corporate debt, not rising that much, so there may be space for pursuing climate policies by green bonds and carbon pricing. Carbon pricing improves the performance of green bonds, which in turn improve inter-genera- tional equity, political feasibility, and help address multiple market failures. Yet, not all carbon pricing is the same: the synergies with green bonds are greater for carbon taxation than for emissions trading.