Density Functional Theory Studies of Catalytic Sites in Metal- Organic Frameworks

Theoretical methods have become indispensable tools in many fields of chemistry and materials research. Metal-organic frameworks (MOFs) are porous materials; they have been intensively developed due to their diverse properties suitable for a wide range of applications. Theoretical approaches have thus been frequently employed toward the design and characterization of MOFs. We focus here in particular on theoretical studies of single-site catalytic reactions that occur inside the cavities of MOFs. The density functional method (DFT) has been the main approach used for such studies. We briefly review the uses of DFT to examine the catalytic reactions in MOFs. We note that DFT methods are versatile and can be made to work for different purposes such as, e.g., force-field development for molecular simulations. We shall, however, cover this field only very succinctly to put it into context with our main topic

Сравнительный анализ алгоритма MCMC и нейронной сети с обучением при прогнозировании котировок высокотехнологических компаний

В работе представлен сравнительный анализ прогнозирования цен 10 высокотехнологичных компаний мира, определенных с помощью метода MCMC и работы обученной нейронной сети. Оценка качества прогнозирования учитывает скорость вычисления и точность прогнозирования.The article presents a comparative analysis of price forecasting of 10 high-tech companies in the world, determined using the MCMC method and the operation of a trained neural network. Evaluation of forecasting quality takes into account the calculation speed and forecasting accuracy

Sources, transport and deposition of iron in the global atmosphere

International audienceAtmospheric deposition of iron (Fe) plays an important role in controlling oceanic primary productivity. However, the sources of Fe in the atmosphere are not well understood. In particular, the combustion sources of Fe and the subsequent deposition to the oceans have been accounted for in only few ocean biogeochemical models of the carbon cycle. Here we used a mass-balance method to estimate the emissions of Fe from the combustion of fossil fuels and biomass by accounting for the Fe contents in fuel and the partitioning of Fe during combustion. The emissions of Fe attached to aerosols from combustion sources were estimated by particle size, and their uncertainties were quantified by a Monte Carlo simulation. The emissions of Fe from mineral sources were estimated using the latest soil mineralogical database to date. As a result, the total Fe emissions from combustion averaged for 1960–2007 were estimated to be 5.3 Tg yr−1 (90% confidence of 2.3 to 12.1). Of these emissions, 1, 27 and 72% were emitted in particles 10 μm (PM> 10), respectively, compared to a total Fe emission from mineral dust of 41.0 Tg yr−1 in a log-normal distribution with a mass median diameter of 2.5 μm and a geometric standard deviation of 2. For combustion sources, different temporal trends were found in fine and medium-to-coarse particles, with a notable increase in Fe emissions in PM1 since 2000 due to an increase in Fe emission from motor vehicles (from 0.008 to 0.0103 Tg yr−1 in 2000 and 2007, respectively). These emissions have been introduced in a global 3-D transport model run at a spatial resolution of 0.94° latitude by 1.28° longitude to evaluate our estimation of Fe emissions. The modelled Fe concentrations as monthly means were compared with the monthly (57 sites) or daily (768 sites) measured concentrations at a total of 825 sampling stations. The deviation between modelled and observed Fe concentrations attached to aerosols at the surface was within a factor of 2 at most sampling stations, and the deviation was within a factor of 1.5 at sampling stations dominated by combustion sources. We analysed the relative contribution of combustion sources to total Fe concentrations over different regions of the world. The new mineralogical database led to a modest improvement in the simulation relative to station data even in dust-dominated regions, but could provide useful information on the chemical forms of Fe in dust for coupling with ocean biota models. We estimated a total Fe deposition sink of 8.4 Tg yr−1 over global oceans, 7% of which originated from the combustion sources. Our central estimates of Fe emissions from fossil fuel combustion (mainly from coal) are generally higher than those in previous studies, although they are within the uncertainty range of our estimates. In particular, the higher than previously estimated Fe emission from coal combustion implies a larger atmospheric anthropogenic input of soluble Fe to the northern Atlantic and northern Pacific Oceans, which is expected to enhance the biological carbon pump in those regions

Global ensemble projections reveal trophic amplification of ocean biomass declines with climate change

While the physical dimensions of climate change are now routinely assessed through multimodel intercomparisons, projected impacts on the global ocean ecosystem generally rely on individual models with a specific set of assumptions. To address these single-model limitations, we present standardized ensemble projections from six global marine ecosystem models forced with two Earth system models and four emission scenarios with and without fishing. We derive average biomass trends and associated uncertainties across the marine food web. Without fishing, mean global animal biomass decreased by 5% (±4% SD) under low emissions and 17% (±11% SD) under high emissions by 2100, with an average 5% decline for every 1 °C of warming. Projected biomass declines were primarily driven by increasing temperature and decreasing primary production, and were more pronounced at higher trophic levels, a process known as trophic amplification. Fishing did not substantially alter the effects of climate change. Considerable regional variation featured strong biomass increases at high latitudes and decreases at middle to low latitudes, with good model agreement on the direction of change but variable magnitude. Uncertainties due to variations in marine ecosystem and Earth system models were similar. Ensemble projections performed well compared with empirical data, emphasizing the benefits of multimodel inference to project future outcomes. Our results indicate that global ocean animal biomass consistently declines with climate change, and that these impacts are amplified at higher trophic levels. Next steps for model development include dynamic scenarios of fishing, cumulative human impacts, and the effects of management measures on future ocean biomass trends

Trends in the sources and sinks of carbon dioxide

Efforts to control climate change require the stabilization of atmospheric CO2 concentrations. This can only be achieved through a drastic reduction of global CO2 emissions. Yet fossil fuel emissions increased by 29% between 2000 and 2008, in conjunction with increased contributions from emerging economies, from the production and international trade of goods and services, and from the use of coal as a fuel source. In contrast, emissions from land-use changes were nearly constant. Between 1959 and 2008, 43% of each year's CO2 emissions remained in the atmosphere on average; the rest was absorbed by carbon sinks on land and in the oceans. In the past 50 years, the fraction of CO2 emissions that remains in the atmosphere each year has likely increased, from about 40% to 45%, and models suggest that this trend was caused by a decrease in the uptake of CO2 by the carbon sinks in response to climate change and variability. Changes in the CO2 sinks are highly uncertain, but they could have a significant influence on future atmospheric CO2 levels. It is therefore crucial to reduce the uncertainties

Global carbon budget 2022

Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere in a changing climate is critical to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe and synthesize data sets and methodologies to quantify the five major components of the global carbon budget and their uncertainties. Fossil CO2 emissions (EFOS) are based on energy statistics and cement production data, while emissions from land-use change (ELUC), mainly deforestation, are based on land use and land-use change data and bookkeeping models. Atmospheric CO2 concentration is measured directly, and its growth rate (GATM) is computed from the annual changes in concentration. The ocean CO2 sink (SOCEAN) is estimated with global ocean biogeochemistry models and observation-based data products. The terrestrial CO2 sink (SLAND) is estimated with dynamic global vegetation models. The resulting carbon budget imbalance (BIM), the difference between the estimated total emissions and the estimated changes in the atmosphere, ocean, and terrestrial biosphere, is a measure of imperfect data and understanding of the contemporary carbon cycle. All uncertainties are reported as ±1σ. For the year 2021, EFOS increased by 5.1% relative to 2020, with fossil emissions at 10.1±0.5GtCyr-1 (9.9±0.5GtCyr-1 when the cement carbonation sink is included), and ELUC was 1.1±0.7GtCyr-1, for a total anthropogenic CO2 emission (including the cement carbonation sink) of 10.9±0.8GtCyr-1 (40.0±2.9GtCO2). Also, for 2021, GATM was 5.2±0.2GtCyr-1 (2.5±0.1ppmyr-1), SOCEAN was 2.9 ±0.4GtCyr-1, and SLAND was 3.5±0.9GtCyr-1, with a BIM of -0.6GtCyr-1 (i.e. the total estimated sources were too low or sinks were too high). The global atmospheric CO2 concentration averaged over 2021 reached 414.71±0.1ppm. Preliminary data for 2022 suggest an increase in EFOS relative to 2021 of +1.0% (0.1% to 1.9%) globally and atmospheric CO2 concentration reaching 417.2ppm, more than 50% above pre-industrial levels (around 278ppm). Overall, the mean and trend in the components of the global carbon budget are consistently estimated over the period 1959-2021, but discrepancies of up to 1GtCyr-1 persist for the representation of annual to semi-decadal variability in CO2 fluxes. Comparison of estimates from multiple approaches and observations shows (1) a persistent large uncertainty in the estimate of land-use change emissions, (2) a low agreement between the different methods on the magnitude of the land CO2 flux in the northern extratropics, and (3) a discrepancy between the different methods on the strength of the ocean sink over the last decade. This living data update documents changes in the methods and data sets used in this new global carbon budget and the progress in understanding of the global carbon cycle compared with previous publications of this data set. The data presented in this work are available at 10.18160/GCP-2022 (Friedlingstein et al., 2022b)

Global carbon budget 2019

Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere – the “global carbon budget” – is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe data sets and methodology to quantify the five major components of the global carbon budget and their uncertainties. Fossil CO2 emissions (EFF) are based on energy statistics and cement production data, while emissions from land use change (ELUC), mainly deforestation, are based on land use and land use change data and bookkeeping models. Atmospheric CO2 concentration is measured directly and its growth rate (GATM) is computed from the annual changes in concentration. The ocean CO2 sink (SOCEAN) and terrestrial CO2 sink (SLAND) are estimated with global process models constrained by observations. The resulting carbon budget imbalance (BIM), the difference between the estimated total emissions and the estimated changes in the atmosphere, ocean, and terrestrial biosphere, is a measure of imperfect data and understanding of the contemporary carbon cycle. All uncertainties are reported as ±1σ. For the last decade available (2009–2018), EFF was 9.5±0.5 GtC yr−1, ELUC 1.5±0.7 GtC yr−1, GATM 4.9±0.02 GtC yr−1 (2.3±0.01 ppm yr−1), SOCEAN 2.5±0.6 GtC yr−1, and SLAND 3.2±0.6 GtC yr−1, with a budget imbalance BIM of 0.4 GtC yr−1 indicating overestimated emissions and/or underestimated sinks. For the year 2018 alone, the growth in EFF was about 2.1 % and fossil emissions increased to 10.0±0.5 GtC yr−1, reaching 10 GtC yr−1 for the first time in history, ELUC was 1.5±0.7 GtC yr−1, for total anthropogenic CO2 emissions of 11.5±0.9 GtC yr−1 (42.5±3.3 GtCO2). Also for 2018, GATM was 5.1±0.2 GtC yr−1 (2.4±0.1 ppm yr−1), SOCEAN was 2.6±0.6 GtC yr−1, and SLAND was 3.5±0.7 GtC yr−1, with a BIM of 0.3 GtC. The global atmospheric CO2 concentration reached 407.38±0.1 ppm averaged over 2018. For 2019, preliminary data for the first 6–10 months indicate a reduced growth in EFF of +0.6 % (range of −0.2 % to 1.5 %) based on national emissions projections for China, the USA, the EU, and India and projections of gross domestic product corrected for recent changes in the carbon intensity of the economy for the rest of the world. Overall, the mean and trend in the five components of the global carbon budget are consistently estimated over the period 1959–2018, but discrepancies of up to 1 GtC yr−1 persist for the representation of semi-decadal variability in CO2 fluxes. A detailed comparison among individual estimates and the introduction of a broad range of observations shows (1) no consensus in the mean and trend in land use change emissions over the last decade, (2) a persistent low agreement between the different methods on the magnitude of the land CO2 flux in the northern extra-tropics, and (3) an apparent underestimation of the CO2 variability by ocean models outside the tropics. This living data update documents changes in the methods and data sets used in this new global carbon budget and the progress in understanding of the global carbon cycle compared with previous publications of this data set (Le Quéré et al., 2018a, b, 2016, 2015a, b, 2014, 2013). The data generated by this work are available at https://doi.org/10.18160/gcp-2019 (Friedlingstein et al., 2019)