High CO2 Emissions Research Articles

Effect of CO[formula omitted] dilution on structures of premixed syngas/air flames in a gas turbine model combustor

The impact of CO2 dilution on combustion of syngas (a mixture of H2, CO, and CH4) was investigated in a lab-scale gas turbine model combustor at atmospheric pressure conditions. Two mild dilution levels of CO2, corresponding to 15% and 34% of CO2 mole fraction in the syngas/CO2 mixtures, were experimentally investigated to evaluate the effects of CO2 dilution on the flame structures and the emissions of CO and NOx. All experiments were performed at a constant Reynolds number (Re = 10000). High-speed flame luminescence, simultaneous planar laser-induced fluorescence (PLIF) measurements of the OH radicals and particle image velocimetry (PIV) were employed for qualitative and quantitative assessment of the resulting flame and flow structures. The main findings are: (a) the operability range of the syngas flames is significantly affected by the CO2 dilution, with both the lean blowoff (LBO) limit and the flashback limit shifting towards fuel-richer conditions as the CO2 dilution increases; (b) syngas flames exhibit flame-pocket structures with chemical reactions taking place in isolated pockets surrounded by non-reacting fuel/air mixture; (c) the inner recirculation zone tends to move closer to the burner axis at high CO2 dilution, and (d) the NOx emission becomes significantly lower with increasing CO2 dilution while the CO emission exhibits the opposite trend. The flame-pocket structure is more significant with increased CO2 dilution level. The low NOx emissions and high CO emissions are the results of the flame-pocket structures.

Investigation of the Bonding Mechanism between Overlapping Textile Layers for FRP Repair Based on Dry Textile Patches.

Lots of damaged fiber-reinforced plastic (FRP) components are replaced by new components instead of repairing. Furthermore, only very labor-intensive repair methods are available on the market to fully restore the integrity of the structure. This requires a high level of experience or, alternatively, very cost-intensive technology, such as the use of computer tomography and robotics. The high costs and CO2 emissions caused by the manufacture of FRP components then bear no relation to their service life. The research project IGF-21985 BR "FRP-Repair" aims to solve the named challenges. Using semiconductor oxide catalysts, the matrix can be locally depolymerized by ultraviolet (UV) radiation, and thus removed from the damaged area of the FRP component. Subsequently, the damaged fibers in this area can be detached. By using customized textile repair patches and local thermoset reinfiltration, the repair area is restored. With this process, the fiber structure can be repaired locally with new fibers on the textile level. The repair is similar to the original production of a fiber composite in an infusion process. No additional adhesive material is used. As a result, repaired FRP structures with restored mechanics and a near-original surface can be realized. This article provides an insight into the actual steps of the development of the FRP component repair process using dry textile patches. The empirical investigation of overlapped rovings and UD material showed the expected results. Residual fracture forces of up to 86% could be achieved. The most interesting approach on the roving level was splicing the overlapping fibers. The free ends of the fibers of the patch and part are mechanically bonded. This bond at the textile level is further strengthened by infusion with matrix.

Rice yield and carbon dioxide emissions in a paddy soil: A comparison of biochar and polystyrene microplastics

AbstractBiochar has been suggested as a soil supplement to improve soil fertility. The world is covered in microplastics (MPs). A pot greenhouse experiment was carried out to examine the effects of polystyrene (PS), sugarcane bagasse biochar (SBB), and their interactions (PS × SBB) on the CO2 emission and rice yield in a rice paddy calcareous soil. The largest CO2 emissions occurred 35–40 days following rice planting, which corresponds to the tillering stages of rice growth. Higher CO2 emissions were detected after SBB treatment. Our findings showed that applying PS increased CO2 emissions in our soil samples. Our research revealed that adding SBB can boosted the negative effects of PS in the soil. The co‐application of SBB and PS increased PS's stimulation of the CO2 emissions. We infer that PS‐SBB interactions have an impact on global warming potential, microbial community activity, and CO2 emissions. Both SBB rates resulted in a significant increase in biomass and rice grain. Our research indicates that PS has a detrimental effect on rice grain output and biomass, but that the addition of SBB can slightly lessen these effects.

Regionally differentiated promotion of electric vehicles in China considering environmental and human health impacts

Private passenger vehicles, with its high emissions of CO2 and air pollutants, poses a severe threat to global climate and human health, particularly for a large developing country like China. Although both energy efficiency improvement of internal combustion engine vehicles (ICEVs) and the wide adoption of electric vehicles (EVs) could contribute to reducing emissions, how they should be jointly implemented in provinces with a heterogeneous context to maximize their net benefits remains insufficiently explored. Here, based on an integrated modeling framework associated with one factual (REF) and four counterfactual scenarios to explore the priority and best-ranked ordering of both EVs’ penetration and high energy-efficient ICEVs in 31 Chinese provinces to achieve the most environmental and human health benefits from 2011 to 2018. The results demonstrate that electrification of the passenger fleet, which is charged by a slightly cleaner power source relative to 2011, yields significant co-benefits of CO2 reduction and air quality improvement. Compared with REF, the fleet electrification scenario would lead to 3167 cases of avoided mortality and attain US$4.269 billion of health benefits in 2018, accounting for 0.03% of China’s gross domestic product. Nonetheless, highly efficient ICEVs are found to harbor decarbonization potential and health benefits in northern China. Based on these results, Sichuan, Hebei and seven other provinces in east China should promote EVs imminently; conversely, eight provinces with a high share of thermal power must continually advance their implementation of ICEVs in the near future. Such prioritization of EVs and ICEV development at the provincial level provides timely insights for devising tailored policies regarding passenger car transition and for maximizing climate and health benefits based on regional heterogeneity.

DEM/CFD Simulation in Process Engineering

Thermal and chemical treatment of bulk solids and particle systems is a basic unit operation in many industrial sectors. The purpose of the treatment can be either to achieve well-defined product properties or to use solids in gasification processes to produce syngas, synthetic fuels, or to recycle waste products. Typical examples are the calcination of minerals as dolomite or magnesite in the basic materials industry, the direct iron ore reduction with hydrogen in steel industry, coffee bean roasting in the food processing industry, or catalytic reactors and fluidized bed spray coating of tablets in the chemical and medical industries, respectively. Many of these processes are operated at high temperatures and are, therefore, energy-intensive and often associated with high CO2 emissions; a careful layout of the systems is needed. Furthermore, target properties of the solids must be achieved concerning reactivity, specific surface area, calcination or roasting degree, etc. To meet all these challenges and requirements, a detailed knowledge of the underlying physical and chemical processes is needed for predictive design. Fundamental studies are first necessary to understand the properties of particulate flows, e.g., regarding turbulence modulation, collisions between particles and/or with surfaces, and particle dispersion, before going toward practical applications. Typical systems are highly loaded with particles, often passed by a reactive gas flow, and are operated at high temperatures. Therefore, measurements are very challenging in such systems. Hence, appropriate simulation methods are needed to support system and reactor layout. Such a method combines the discrete element method (DEM) with computational fluid dynamics (CFD). DEM/CFD allows to track individual particles and their interactions with other particles, surrounding walls, and the gas phase in-between the particles. Conversion of the particles including intra-particle processes can be described as well as size change or development of adhesive forces associated with the thermal treatment. The current focus issue of Chemical Engineering & Technology entitled “DEM/CFD Simulation in Process Engineering” gives a status on the description of particulate flows with a focus on reactive particle-gas systems using DEM/CFD and presents illustrative examples of its application. A review article on DEM/CFD for reacting systems sets the frame for the further contributions that concentrate on fundamental aspects, specific examples, and important methodological developments. Examples presented are shaft kilns (production of quicklime/production of spinel), waste incineration, combustion of wood pellets, and carbonate looping processes. Novel trends as the usage of machine learning in combination with DEM/CFD, the combination of resolved and unresolved DEM/CFD in one simulation domain, and new approaches regarding the immersed boundary method to describe particle-gas systems are presented. The contributions do not claim to cover all relevant aspects needed for DEM/CFD simulations of reactive particle-gas systems but can be seen as a first overview and starting point for interested readers. This focus issue and the corresponding workshop at the Conference on Modelling Fluid Flow in Budapest 2022 have been organized by the Collaborative Research Centre BULK-REACTION financed by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Project-ID 422037413 – TRR 287. Prof. Dr.-Ing. Viktor Scherer Ruhr-Universität Bochum, Faculty of Mechanical Engineering, Department of Energy Plant Technology Prof. Dr.-Ing. Dominique Thévenin Otto von Guericke University Magdeburg, The Laboratory of Fluid Dynamics and Technical Flows Viktor Scherer Dominique Thévenin

The Impact of COVID-19 Outbreak on CO2 Emissions in the Ten Countries with the Highest Carbon Dioxide Emissions.

The environmental pollution during the COVID-19 crisis has declined dramatically due to quarantines that have severely reduced transport and industry but has had little effect on the steady rise in CO2 concentrations in the atmosphere. Through the Paris Agreement, countries are working to reduce the emissions of these pollutants, for example, by burning fossil fuels. These greenhouse gases trap heat near the earth's surface and raise the temperature. This global warming threatens global food resources. In times of corona crisis and environmental pollution, especially in countries with the highest CO2 emissions, governance is a key factor that explains the poor economic, social, and environmental performance of many countries. Governance plays an important role in controlling these crises. In this study, the World Bank's governance indicators have been used to examine the relationship between governance and economic performance and its impact on CO2 emissions during the COVID-19 outbreak period. Also, the Tobit panel model with a limited-dependent model from 2011 to 2020 has been used. Several economic factors and governance variables are also considered. Given the negative relationship between governance and CO2 emissions during the COVID-19 outbreak, the role of governance in reducing environmental pollution is emphasized, and it is shown that policymakers can take appropriate measures by implementing good governance and enforcing the right laws to control the corona epidemic and also reduce carbon emissions in the long run.

Negative CO2 emissions in the lime production using an indirectly heated carbonate looping process

Lime is an essential raw material for iron and steel production, in construction and agriculture, in civil engineering, in environmental protection, and in manifold chemical manufacturing processes. To address the problem of unavoidable process CO2 emissions associated with the production of lime, efficient capture technologies need to be developed and implemented. The indirectly heated carbonate looping (IHCaL) process is an efficient candidate for this application because it utilizes lime as the sorbent for the CO2 capture. In this work, a retrofit configuration of this process is presented and analyzed for net negative CO2 emissions. This is done considering different fuels that provide the heat required for the regeneration of the sorbent. The different scenarios were simulated with an AspenPlus® model, key performance indicators were calculated, and the process was compared with other post-combustion capture methods. The results show that net negative CO2 emissions as high as −1805 kgCO2/tCaO, calculated with a state-of-the-art coal power plant energy scenario (ηe = 44.2 %; eref,el = 770 kgCO2/MWhel), can be obtained. This represents an equivalent CO2 avoidance of more than 230% with respect to the reference plant without capture (1368 kgCO2/tCaO). A specific primary energy consumption for CO2 avoided (SPECCA) lower than 1.5 MJLHV/kgCO2,av was achieved for the same energy scenario. Particularly promising results can be accomplished when applying fuels with high biogenic fraction and low specific CO2 emissions, such as solid recovered fuels (SRFs) with a high calorific value.

NOx and N2O emissions from Ca-rich fuel conversion in oxyfuel circulating fluidized bed combustion

A part of Estonia’s power generation is based on oil shale combustion in thermal power plants, resulting in high CO2 and pollutant emissions. The presented paper is a part of long-term experimental work to investigate the combustion of Ca-rich oil shale for air and oxyfuel combustion environments. The experiments were performed in a 60 kWth circulating fluidized bed (CFB) test facility under air, O2/CO2, and O2 with the recycled flue gas (RFG) modes of inlet O2 as vol.% ranging from 21% to 52%, and with RFG of 50% and 87%. The influence of different combustion atmospheres, excess oxygen volumetric ratios in the primary oxidizer (λPr), and dense bed temperatures (TDB), on the total NOx and N2O formations, have been studied in detail.The results show that specific concentrations of NOx (per MJ) were reduced by 14% in O2/CO2 mode, and 22% in O2/RFG compared to air combustion. N2O emissions were increased in OXY21 mode and reduced significantly from 20 mg/MJ to 4 mg/MJ with increasing inlet O2% to 52% under O2/CO2. NOx and N2O emissions were the lowest of all combustion experiments at high inlet O2% with RFG application (OXY87 + RFG). Under all tested atmospheres, NOx emissions were increasing with increasing excess oxygen in the primary oxidizer. N2O enhanced with excess oxygen, accounted for the homogenous gas-phase reaction of volatile-N and the heterogenous reaction of char-N. NOx emissions at low operating TDB were decreasing with increasing bed temperatures and increased at higher TDB > 770 °C in air combustion and TDB > 850 °C in OXY30. N2O emissions were slightly decreased at higher bed temperatures under air and O2/CO2 modes. Combustion efficiency enhanced at higher inlet O2% resulting in lower CO concentrations with reduced fuel burnout, and increased NOx and N2O emissions.Overall, NOx and N2O formations were more affected by the condition of operating parameters under both air and oxyfuel combustion experiments, and the obtained results are giving confidence that oxyfuel technology does not influence the release of nitrogen emissions from oil shale combustion. To lower the cost of CO2 impurities removal, the optimal operating conditions during oil shale CFB combustion can be confirmed after considering the discussed parameters. However, further CO2 purification resulting from oil shale oxyfuel flue gas stream is possibly required.

Influence of rice husk ash and hybrid fiber on engineering properties of densified high-performance fiber-reinforced concrete

Conventional concrete significantly affects the environment due to high CO2 emission into the atmosphere during the production process. In order to improve concrete performance and arrest the incidence of global warming, the use of additive materials for cement replacement has been promoted worldwide. This study was designed to investigate the mechanical properties of high-performance fiber-reinforced concrete (HFRC) produced using rice husk ash (RHA) and hybrid fiber (HF) in accordance with the densified mixture design algorithm (DMDA) mix design method. Samples were produced using RHA as a direct replacement for cement at 10%, 20%, and 30%. HF, comprising steel and polypropylene fibers, was added (by volume) to the 20% RHA group mixture to improve the HFRC sample properties. Based on the experimental results, higher RHA contents had a generally negative effect on the fresh properties of the HFRC mixtures. Compressive strength values ranged from 53 to 72 MPa with various RHA and HF content. RHA replacement levels up to 20% had an insignificant effect on the strength development and dynamic modulus of the HFRC samples. However, the addition of HF improved splitting tensile strength, flexural strength, and dynamic modulus remarkably at all curing ages. Furthermore, the 91-day drying shrinkage was in the ranges of 0.032%–0.039% and 0.023%–0.034% using different RHA and HF levels, respectively. Increasing both RHA and HF contents significantly reduced drying shrinkage in the samples. Multivariable regression was also performed, clarifying that all tested results were consistent and had good correlations. The results of this study also provide a potentially effective use for abundantly available industrial waste products such as fly ash (FA) and RHA to promote the production of greener and more sustainable concrete.

Permafrost Effect on the Spatial Distribution of CO2 Emission in the North of Western Siberia (Russia)

The landscapes in the discontinuous permafrost area of Western Siberia are unique objects for assessing the direct and indirect impact of permafrost on greenhouse gas fluxes. The aim of this study was to identify the influence of permafrost on the CO2 emission at the landscape and local levels. The CO2 emission from the soil surface with the removed vegetation cover was measured by the closed chamber method, with simultaneous measurements of topsoil temperature and moisture and thawing depth in forest, palsa, and bog ecosystems in August 2022. The CO2 emissions from the soils of the forest ecosystems averaged 485 mg CO2 m−2 h−1 and was 3–3.5 times higher than those from the peat soils of the palsa mound and adjacent bog (on average, 150 mg CO2 m−2 h−1). The high CO2 emission in the forest was due to the mild soil temperature regime, high root biomass, and good water–air permeability of soils in the absence of permafrost. A considerable warming of bog soils, and the redistribution of CO2 between the elevated palsa and the bog depression with water flows above the permafrost table, equalized the values of CO2 emissions from the palsa and bog soils. Soil moisture was a significant factor of the spatial variability in the CO2 emission at all levels. The temperature affected the CO2 emission only at the sites with a shallow thawing depth.

Modelling the compressive strength of high-performance concrete containing metakaolin using distinctive statistical techniques

Cement consumption is rapidly increasing around the world causing environmental concerns over higher CO2 emissions. Metakaolin obtained through the calcination of kaolinite clay is an eco-friendly substitution for clinker in portland cement production. The raw materials required to produce metakaolin are easily accessible and cheap. Addition of metakaolin in concrete alters mechanical properties, notably compressive strength. Prior knowledge of the strength characteristics of concrete play a vital role in determining the design aspects of the buildings. Robust prediction models that can effectively predict the compressive strength of pozzolan-based concrete are highly essential in the field of concrete technology in order to save time and reduce laboratory testing samples. In this regard, A total of 152 experimental datasets from the literature were collected and evaluated. Influencing parameters such as binder content (385–600 kg/m3), water to cementitious material ratio (0.25–0.45), metakaolin replacement levels (0%–50%) and SiO 2/Al2O3 ratio in the cement paste (1.05–12) were chosen as independent variables. The present study was aimed at developing prediction models using different statistical techniques such as Linear regression (LR), Multi-logistic regression (MLR), Nonlinear regression (NLR) and Response surface methodology (RSM) to predict the 28-day compressive strength of High-performance concrete containing metakaolin. Also, the performance of the proposed models was examined using different statistical metrics such as coefficient of correlation (R), root mean squared error (RMSE), mean absolute error (MAE) and scatter index (SI). The quadratic RSM model outperforms all the proposed models in the present study with R, RMSE, MAE and SI of 0.92, 6.5 MPa, 5.2 MPa and 0.08. The models were evaluated in strength ranges other than HPC, and the QRSM model showed a maximum residual error of ±20%. Furthermore, the results of sensitivity analysis indicate that binder content, w/b ratio and SiO2/Al2O3 are the most influential parameters controlling the compressive strength of concrete.

Machine learning using magnetic stochastic synapses

The impressive performance of artificial neural networks has come at the cost of high energy usage and CO2 emissions. Unconventional computing architectures, with magnetic systems as a candidate, have potential as alternative energy-efficient hardware, but, still face challenges, such as stochastic behaviour, in implementation. Here, we present a methodology for exploiting the traditionally detrimental stochastic effects in magnetic domain-wall motion in nanowires. We demonstrate functional binary stochastic synapses alongside a gradient learning rule that allows their training with applicability to a range of stochastic systems. The rule, utilising the mean and variance of the neuronal output distribution, finds a trade-off between synaptic stochasticity and energy efficiency depending on the number of measurements of each synapse. For single measurements, the rule results in binary synapses with minimal stochasticity, sacrificing potential performance for robustness. For multiple measurements, synaptic distributions are broad, approximating better-performing continuous synapses. This observation allows us to choose design principles depending on the desired performance and the device’s operational speed and energy cost. We verify performance on physical hardware, showing it is comparable to a standard neural network.

An overview of motivators and challenges of passive design strategies

Growing concerns over high energy consumption and CO2 emissions from residential buildings have boosted the adoption of passive design strategies (PDS) globally, for their promising solution to address these issues, and also positively influencing occupant productivity. As such, many governments and organizations have developed relevant codes and procedures to encourage and enforce the adoption of PDS. Despite the increased focus, the adoption of PDS is still trailing behind in developing countries, particularly in a hot, dry and humid climate zone. This paper examines the current state of PDS adoption in such climates, and extracts relevant motivators, and challenges. The data was gathered through a structured review of literature. Initial results show the extraction of thirty-five motivators and forty-six challenges to PDS adoption. The key motivators include reduction in energy consumption and energy bills, while key challenges include high initial investment and lack of awareness. These are expected to generate a general awareness among stakeholders and allow a better understanding of the underlying issues for non-adoption of PDS. Future research will examine the extracted sets of motivators and challenges through a questionnaire survey in a hot, dry and humid climate zone.

Carbon Dioxide Capture and Product Characteristics Using Steel Slag in a Mineral Carbonation Plant

Carbon capture and storage (CCS) technology can reduce CO2 emissions by 85 to 95% for power plants and kilns with high CO2 emissions. Among CCS technologies, carbon dioxide capture using steel slag is a method of carbonating minerals by combining oxidized metals in the slag, such as CaO, MgO, and SiO2, with CO2. This study assessed the amount of CO2 captured and the sequestration efficiency in operating a mineral carbonation plant with a CO2 capture capacity of 5 tons/day by treating the exhaust gas from a municipal waste incinerator and identified the characteristics of the mineral carbonation products. As a result, the average concentration of CO2 in the inflow and outflow gas during the reaction time was 10.0% and 1.1%, respectively, and the average CO2 sequestration efficiency was 89.7%. This resulted in a conversion rate of CaO of > 90%. This study manifested that mineral carbonation products are more stable than steel slag as a construction material and are effective at sequestering CO2 by forming chemically stable CaCO3.

Green Concept of Kulon Progo Airport Development Using UMI Simulation

High energy consumption on the airport becomes a very crucial issue nowadays. Uninterruptable energy supply is required to support airline’s activity and keep the passenger convenience. Regarding the mentioned problem, there is a need to enhance the current plan of the airport with green airport concept. Green airport concept also known as eco-airport is an airport that adopted green and sustainable ecosystem concept to integrate community and environment that lead to reduction of energy consumption. The blueprint of Kulon Progo airport with green concept located in D.I. Yogyakarta, Indonesia has been made and the construction will be start in the mid of 2016. The airport has a FAR of 0.16 with 637 hectares land area. This study is simulating the plan to assess the energy consumption and CO2 emission in each part of the building in Kulon Progo Airport by using Urban Modeling Interface simulator. From the results, it can be seen that the passenger terminal building is responsible for the highest share with 1,351,861.01 Kwh while second floor of ATC building has the highest CO2 emission 2,679.77 kgCO2/m

TEMPORAL DYNAMICS OF CO2 EFFLUX AND LITTER DEPOSITION IN A DRY TROPICAL FOREST IN THE BRAZILIAN SEMIARID REGION

The study of the dynamics of the Caatinga ecosystem, which includes the process of nutrient cycling through the contribution and litter decomposition, and the microbial activity measured through CO2 efflux, can contribute to a better understanding of the ecological processes in this ecosystem. Thus, the present study sought to quantify the contribution of the litter forming material and its chemical composition, and CO2 efflux from soil respiration in an area of shrubby-tree caatinga. A transect with 3 arborescent stratum sampling points and 3 shrubby strata, totaling 6 sampling points (2 environments x 3 points per environment x 3 replications per point) was drawn. The litter production was collected monthly (October 2017 to October 2018), using 6 collectors. The monthly CO2 emission was evaluated by the static closed chamber method. The influence of rainfall, soil moisture and temperature on the studied variables was evaluated. The annual litter production was estimated at 590 kg ha-1 for arboreal species and 767 kg ha-1 for shrubby species, and this layer is responsible for 23% more in the supply of plant material in the area. The highest CO2 emissions were found in the environment of shrubby vegetation with one annual total of 21.2 μmol m-2s-1 in relation to the area of arboreal vegetation that obtained 17.6 μmol m-2s-1. Spatial and temporal variability were observed in all analyzed variables and the strong influence of climatic factors such as precipitation, humidity and soil temperature.

Effects of Extreme Temperature and Precipitation Events on Daily CO2 Fluxes in the Tropics

The effects of anomalous weather conditions (such as extreme temperatures and precipitation) on CO2 flux variability in different tropical ecosystems were assessed using available reanalysis data, as well as information about daily net CO2 fluxes from the global FLUXNET database. A working hypothesis of the study suggests that the response of tropical vegetation can differ depending on local geographical conditions and intensity of temperature and precipitation anomalies. The results highlighted the large diversity of CO2 flux responses to the fluctuations of temperature and precipitation in tropical ecosystems that may differ significantly from some previously documented relationships (e.g., higher CO2 emission under the drier and hotter weather, higher CO2 uptake under colder and wetter weather conditions). They showed that heavy precipitation mainly leads to the strong intensification of mean daily CO2 release into the atmosphere at almost all stations and in all types of study biomes. For the majority of considered tropical ecosystems, the intensification of daily CO2 emission during cold and wet weather was found, whereas the ecosystems were predominantly served as CO2 sinks from the atmosphere under hot/dry conditions. Such disparate responses suggested that positive and negative temperature and precipitation anomalies influence Gross Primary Production (GPP) and Ecosystem Respiration (ER) rates differently that may result in various responses of Net Ecosystem Exchanges (NEE) of CO2 to external impacts. Their responses may also depend on various local biotic and abiotic factors, including plant canopy age and structure, plant biodiversity and plasticity, soil organic carbon and water availability, surface topography, solar radiation fluctuation, etc.

Mechanistic insights and kinetics of torrefaction of pine wood biomasses using solid-state NMR

The purpose of this study is to investigate the potential use of torrefied biomass of the genus Pinus, in the form of wood bark (CC), chips (CV) and wood pellets (PP), as substitutes for metallurgical coke to reduce the high CO2 emissions from the use of metallurgical coke in blast furnaces. Thermogravimetric analysis were used to optimize the torrefaction temperature (250 °C or 290 °C), residence time (30 or 60 min) under inert atmosphere. All of the torrefied biomasses were analyzed to determine physical and chemical characteristics (proximate analyses, ultimate analyses, higher calorific value (HHV), Fourier transform infrared spectroscopy (FTIR) and ss-NMR. The composition of condensable and non-condensable gases formed during torrefaction process were also measured. The results showed that the two most promising biomasses were CV and PP torrefied at a temperature of 290 °C at a residence time of 30 min. The kinetics of torrefaction was analyzed by solid state ss-NMR characterization of the torrefied biomass at different time reactions and temperature (250–290 °C) under inert atmosphere, and followed a pseudo-first order kinetic model. The kinetics of evolution of ss-NMR signals related to C-1 of cellulose; C-4 of cellulose in ordered cellulose; C-4 of cellulose in disordered/amorphous cellulose; C-6 of cellulose, and carbon atoms of methoxyl groups in lignins, at different temperatures were used to estimate the activation energy, and values in the range 11–25 kJ mol−1 were obtained.

An integrated view of correlated emissions of greenhouse gases and air pollutants in China

BackgroundAir pollution in China has raised great concerns due to its adverse effects on air quality, human health, and climate. Emissions of air pollutants (APs) are inherently linked with CO2 emissions through fossil-energy consumption. Knowledge of the characteristics of APs and CO2 emissions and their relationships is fundamentally important in the pursuit of co-benefits in addressing air quality and climate issues in China. However, the linkages and interactions between APs and CO2 in China are not well understood.ResultsHere, we conducted an ensemble study of six bottom-up inventories to identify the underlying drivers of APs and CO2 emissions growth and to explore their linkages in China. The results showed that, during 1980–2015, the power and industry sectors contributed 61–79% to China’s overall emissions of CO2, NOx, and SO2. In addition, the residential and industrial sectors were large emitters (77–85%) of PM10, PM2.5, CO, BC, and OC. The emissions of CH4, N2O and NH3 were dominated by the agriculture sector (46–82%) during 1980–2015, while the share of CH4 emissions in the energy sector increased since 2010. During 1980–2015, APs and greenhouse gases (GHGs) emissions from residential sources generally decreased over time, while the transportation sector increased its impact on recent emissions, particularly for NOx and NMVOC. Since implementation of stringent pollution control measures and accompanying technological improvements in 2013, China has effectively limited pollution emissions (e.g., growth rates of –10% per year for PM and –20% for SO2) and slowed down the increasing trend of carbon emissions from the power and industrial sectors. We also found that areas with high emissions of CO, NOx, NMVOC, and SO2 also emitted large amounts of CO2, which demonstrates the possible common sources of APs and GHGs. Moreover, we found significant correlations between CO2 and APs (e.g., NOx, CO, SO2, and PM) emissions in the top 5% high-emitting grid cells, with more than 60% common grid cells during 2010–2015.ConclusionsWe found significant correlation in spatial and temporal aspects for CO2, and NOx, CO, SO2, and PM emissions in China. We targeted sectorial and spatial APs and GHGs emission hot-spots, which help for management and policy-making of collaborative reductions of them. This comprehensive analysis over 6 datasets improves our understanding of APs and GHGs emissions in China during the period of rapid industrialization from 1980 to 2015. This study helps elucidate the linkages between APs and CO2 from an integrated perspective, and provides insights for future synergistic emissions reduction.

The effect of automation on firms’ carbon dioxide emissions of China

This paper empirically analyzes the impact of automation upon firms’ carbon dioxide emissions (CO2 emissions) of China by using data for the period 1998–2009. Our research yields a few findings. First, we find that automation as measured by the robot density can reduce firms’ CO2 emissions intensity. Specifically, 1% increase in the robot density leads to a 0.018% decrease in CO2 emissions intensity. Second, we find that automation reduces firms’ CO2 emissions intensity by promoting firms’ technological innovation and improving management efficiency. Finally, we find that automation exerts a greater impact on reducing CO2 emissions intensity for firms in industries with high CO2 emissions intensity rather than low CO2 emissions intensity, and for firms in capital-intensive industries rather than non-capital-intensive industries, as well as firms in industries with high servitization of manufacturing rather than low servitization of manufacturing. Moreover, the mitigating effects of automation have been given greater play on firms’ CO2 emissions intensity after the global financial crisis.