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We describe a novel scanning microwave limb sounder (SMLS) instrument that performs rapid and broad azimuth conical scans of Earth's limb while simultaneously scanning the limb in the vertical. This azimuthal scanning capability gives dramatic improvement in temporal and spatial coverage over that of previous limb sounding instruments. In a 1500-kilometer altitude, 52°-inclination Earth orbit, SMLS provides 6–8 vertical profile measurements separated by 1.9 hours every 24 hours everywhere between ±65° latitude, and 2–4 such measurements everywhere between ±(65–82°). Horizontal resolution is ∼50×50 km. Vertical resolution is ∼2 km for water vapor and cloud ice and ∼1–3 km for chemical species. In an equatorial orbit, emphasizing the tropics and subtropics, SMLS produces profile measurements every 1.9 hours everywhere between ±35° latitude. SMLS measurements address scientific issues of relevance to the upper troposphere, stratosphere, mesosphere, and lower thermosphere regions of the atmosphere (heights from ∼10 km to ∼100 km).

Abstract Aerosol-cloud interactions (aerosol indirect effects) play an important role in regional meteorological variations, which could further induce feedback on regional air quality. While the impact of aerosol-cloud interactions on meteorology and climate has been extensively studied, their feedback on air quality remains unclear. Using a fully coupled meteorology-chemistry model, we find that increased aerosol loading due to anthropogenic activities in China substantially increases column cloud droplet number concentration and liquid water path (LWP), which further leads to a reduction in the downward shortwave radiation at surface, surface air temperature and planetary boundary layer (PBL) height. The shallower PBL and accelerated cloud chemistry due to larger LWP in turn enhance the concentrations of particulate matter with diameter less than 2.5 μm (PM2.5) by up to 33.2 μg m−3 (25.1%) and 11.0 μg m−3 (12.5%) in January and July, respectively. Such a positive feedback amplifies the changes in PM2.5 concentrations, indicating an additional air quality benefit under effective pollution control policies but a penalty for a region with a deterioration in PM2.5 pollution. Additionally, we show that the cloud processing of aerosols, including wet scavenging and cloud chemistry, could also have substantial effects on PM2.5 concentrations.

This article presents and characterizes an Open Application Repository for Federated Learning (OARF), a benchmark suite for federated machine learning systems. Previously available benchmarks for federated learning (FL) have focused mainly on synthetic datasets and use a limited number of applications. OARF mimics more realistic application scenarios with publicly available datasets as different data silos in image, text, and structured data. Our characterization shows that the benchmark suite is diverse in data size, distribution, feature distribution, and learning task complexity. The extensive evaluations with reference implementations show the future research opportunities for important aspects of FL systems. We have developed reference implementations, and evaluated the important aspects of FL, including model accuracy, communication cost, throughput, and convergence time. Through these evaluations, we discovered some interesting findings such as FL can effectively increase end-to-end throughput. The code of OARF is publicly available on GitHub.1 [ABSTRACT FROM AUTHOR]

In this study, the novel tin-based catalysts (Sn(II)/PN@AC) were prepared using the phosphorus and nitrogen dual-modified activated carbon as support and SnCl2 as active compounds, as well as then evaluated in acetylene hydrochlorination. Under the reaction temperature of 180 °C and an acetylene gas hourly space velocity (GHSV-C2H2) of 30 h-1, the 15%Sn(II)/PN@AC-550 showed the initial acetylene conversion of 100% and vinyl chloride selectivity over 98.5%. Additionally, the deactivation rate of 15%Sn(II)/PN@AC-550 reached 0.47% h-1, which was lower than that of 15%Sn(II)/AC-550 (1.02% h-1), suggesting that PN@AC-550 as novel support can retarded the deactivation of Sn(II)/AC-550 catalysts during acetylene hydrochlorination. Based on the catalytic tests and characterization results (XRD, Raman, BET surface area, TEM, C2H2-TPD, H2-TPR, XPS, FT-IR, TGA, and ICP), it demonstrated that PN@AC-550 as support could effectively improve the dispersion of tin species, retard the formation of coke deposition, lessen the oxidation of SnCl2 during the preparation process, as well as relatively inhibit the leach of tin species during the reaction. By combing the FTIR results and Rideal-Eley mechanism, we proposed that that HSnCl3 was transition state of SnCl2 in catalysis acetylene hydrochlorination and then adsorbed the acetylene to produce the vinyl chloride. [ABSTRACT FROM AUTHOR]

We decompose factors affecting China's energy-related air pollutant (NOx, PM2.5, and SO2) emission changes into different effects using structural decomposition analysis (SDA). We find that, from 2005 to 2012, investment increased NOx, PM2.5, and SO2 emissions by 14.04, 7.82 and 15.59 Mt respectively, and consumption increased these emissions by 11.09, 7.98, and 12.09 Mt respectively. Export and import slightly increased the emissions on the whole, but the rate of the increase has slowed down, possibly reflecting the shift in China's foreign trade structure. Energy intensity largely reduced NOx, PM2.5, and SO2 emissions by 12.49, 14.33 and 23.06 Mt respectively, followed by emission efficiency that reduces these emissions by 4.57, 9.08, and 17.25 Mt respectively. Input-output efficiency slightly reduces the emissions. At sectoral and sub-sectoral levels, consumption is a great driving factor in agriculture and commerce, whereas investment is a great driving factor in transport, construction, and some industrial subsectors such as iron and steel, nonferrous metals, building materials, coking, and power and heating supply. Energy intensity increases emissions in transport, chemical products and manufacturing, but decreases emissions in all other sectors and subsectors. Some policies arising from our study results are discussed. [ABSTRACT FROM AUTHOR]

Abstract. We systematically investigate the effects of Wegener-Bergeron-Findeisen process (hereafter WBF) on black carbon (BC) scavenging efficiency, surface BCair, deposition flux, concentration in snow (BCsnow, ng g-1), and washout ratio using a global 3-D chemical transport model (GEOS-Chem). We differentiate riming- versus WBF-dominated in-cloud scavenging based on liquid water content (LWC) and temperature. Specifically, we implement an implied WBF parameterization using either temperature or ice mass fraction (IMF) in mixed-phase clouds based on field measurements. We find that at Jungfraujoch, Switzerland, and Abisko, Sweden, where WBF dominates in-cloud scavenging, including the WBF effect strongly reduces the discrepancies of simulated BC scavenging efficiency and washout ratio against observations (from a factor of 3 to 10% and from a factor of 4-5 to a factor of 2). However, at Zeppelin, Norway, where riming dominates, simulation of BC scavenging efficiency, BCair, and washout ratio become worse (relative to observations) when WBF is included. There is thus an urgent need for extensive observations to distinguish and characterize riming- versus WBF-dominated aerosol scavenging in mixed-phase clouds and the associated BC scavenging efficiency. Our model results show that including the WBF effect lowers global BC scavenging efficiency, with a higher reduction at higher latitudes (8% in the tropics and up to 76%in the Arctic). The resulting annual mean BCair increases by up to 156% at high altitudes and at northern high latitudes because of lower temperature and higher IMF. Overall, WBF halves the model-observation discrepancy (from -65 to -30 %) of BCair across North America, Europe, China and the Arctic. Globally WBF increases BC burden from 0.22 to 0.29-0.35 mg m-2 yr-1, which partially explains the gap between observed and previous model-simulated BC burdens over land. In addition, WBF significantly increases BC lifetime from 5.7 to ~8 days. Additionally, WBF results in a significant redistribution of BC deposition in source and remote regions. Specifically, it lowers BC wet deposition (by 37-63%at northern mid-latitudes and by 21-29% in the Arctic), while it increases dry deposition (by 3-16% at mid-latitudes and by 81-159% in the Arctic). The resulting total BC deposition is lower at mid-latitudes (by 12-34 %) but higher in the Arctic (by 2-29 %). We find that WBF decreases BCsnow at mid-latitudes (by ~15 %) but increases it in the Arctic (by 26 %) while improving model comparisons with observations. In addition, WBF dramatically reduces the model-observation discrepancy of washout ratios in winter (from a factor of 16 to 4). The remaining discrepancies in BCair, BCsnow and BC washout ratios suggest that in-cloud removal in mixed-phased clouds is likely still excessive over land. [ABSTRACT FROM AUTHOR]

We quantify source contributions to springtime (April 2008) surface black carbon (BC) in the Arctic by interpreting surface observations of BC at five receptor sites (Denali, Barrow, Alert, Zeppelin, and Summit) using a global chemical transport model (GEOS-Chem) and its adjoint. Contributions to BC at Barrow, Alert, and Zeppelin are dominated by Asian anthropogenic sources (40-43 %) before April 18 and by Siberian open biomass burning emissions (29-41 %) afterward. In contrast, Summit, a mostly free tropospheric site, has predominantly an Asian anthropogenic source contribution (24-68 %, with an average of 45 %). We compute the adjoint sensitivity of BC concentrations at the five sites during a pollution episode (April 20-25) to global emissions from March 1 to April 25. The associated contributions are the combined results of these sensitivities and BC emissions. Local and regional anthropogenic sources in Alaska are the largest anthropogenic sources of BC at Denali (63 %), and natural gas flaring emissions in the Western Extreme North of Russia (WENR) are the largest anthropogenic sources of BC at Zeppelin (26 %) and Alert (13 %). We find that long-range transport of emissions from Beijing-Tianjin-Hebei (also known as Jing-Jin-Ji), the biggest urbanized region in Northern China, contribute significantly (~ 10 %) to surface BC across the Arctic. On average it takes ~ 12 days for Asian anthropogenic emissions and Siberian biomass burning emissions to reach Arctic lower troposphere, supporting earlier studies. Natural gas flaring emissions from the WENR reach Zeppelin in about a week. We find that episodic, direct transport events dominate BC at Denali (87 %), a site outside the Arctic front, a strong transport barrier. The relative contribution of direct transport to surface BC within the Arctic front is much smaller (~ 50 % at Barrow and Zeppelin and ~ 10 % at Alert). The large contributions from Asian anthropogenic sources are predominately in the form of 'chronic' pollution (~ 40 % at Barrow and 65 % at Alert and 57 % at Zeppelin) on 1-2 month timescales. As such, it is likely that previous studies using 5- or 10-day trajectory analyses strongly underestimated the contribution from Asia to surface BC in the Arctic. Both finer temporal resolution of biomass burning emissions and accounting for the Wegener-Bergeron-Findeisen (WBF) process in wet scavenging improve the source attribution estimates. [ABSTRACT FROM AUTHOR]

We investigate the sensitivity of black carbon (BC) in the Arctic, including BC concentration in snow (BCsnow, ng g−1) and surface air (BCair, ng m−3), as well as emissions, dry deposition, and wet scavenging using the global three-dimensional (3-D) chemical transport model (CTM) GEOS-Chem. We find that the model underestimates BCsnow in the Arctic by 40 % on average (median  =  11.8 ng g−1). Natural gas flaring substantially increases total BC emissions in the Arctic (by ∼ 70 %). The flaring emissions lead to up to 49 % increases (0.1–8.5 ng g−1) in Arctic BCsnow, dramatically improving model comparison with observations (50 % reduction in discrepancy) near flaring source regions (the western side of the extreme north of Russia). Ample observations suggest that BC dry deposition velocities over snow and ice in current CTMs (0.03 cm s−1 in the GEOS-Chem) are too small. We apply the resistance-in-series method to compute a dry deposition velocity (vd) that varies with local meteorological and surface conditions. The resulting velocity is significantly larger and varies by a factor of 8 in the Arctic (0.03–0.24 cm s−1), which increases the fraction of dry to total BC deposition (16 to 25 %) yet leaves the total BC deposition and BCsnow in the Arctic unchanged. This is largely explained by the offsetting higher dry and lower wet deposition fluxes. Additionally, we account for the effect of the Wegener–Bergeron–Findeisen (WBF) process in mixed-phase clouds, which releases BC particles from condensed phases (water drops and ice crystals) back to the interstitial air and thereby substantially reduces the scavenging efficiency of clouds for BC (by 43–76 % in the Arctic). The resulting BCsnow is up to 80 % higher, BC loading is considerably larger (from 0.25 to 0.43 mg m−2), and BC lifetime is markedly prolonged (from 9 to 16 days) in the Arctic. Overall, flaring emissions increase BCair in the Arctic (by ∼ 20 ng m−3), the updated vd more than halves BCair (by ∼ 20 ng m−3), and the WBF effect increases BCair by 25–70 % during winter and early spring. The resulting model simulation of BCsnow is substantially improved (within 10 % of the observations) and the discrepancies of BCair are much smaller during the snow season at Barrow, Alert, and Summit (from −67–−47 % to −46–3 %). Our results point toward an urgent need for better characterization of flaring emissions of BC (e.g., the emission factors, temporal, and spatial distribution), extensive measurements of both the dry deposition of BC over snow and ice, and the scavenging efficiency of BC in mixed-phase clouds. In addition, we find that the poorly constrained precipitation in the Arctic may introduce large uncertainties in estimating BCsnow. Doubling precipitation introduces a positive bias approximately as large as the overall effects of flaring emissions and the WBF effect; halving precipitation produces a similarly large negative bias. [ABSTRACT FROM AUTHOR]

We systematically investigate the effects of Wegener-Bergeron-Findeisen (WBF) on BC scavenging efficiency, surface BCair, deposition flux, concentration in snow (BCsnow, ng g-1), and washout ratio using a global 3D chemical transport model (GEOS-Chem). We differentiate riming- versus WBF-dominated in-cloud scavenging based on liquid water content (LWC) and temperature. Specifically, we relate WBF to either temperature or ice mass fraction (IMF) in mixed-phase clouds. We find that at Jungfraujoch, Switzerland and Abisko, Sweden, where WBF dominates, the discrepancies of simulated BC scavenging efficiency and washout ratio are significantly reduced (from a factor of 3 to 10% and from a factor of 4-5 to a factor of two). However, at Zeppelin, Norway, where riming dominates, simulation of BC scavenging efficiency, BCair, and washout ratio become worse (relative to observations) when WBF is included. There is thus an urgent need for extensive observations to distinguish and characterize riming- versus WBF-dominated aerosol scavenging in mixed-phase clouds and the associated BC scavenging efficiency. We find the reduction resulting from WBF to global BC scavenging efficiency varies substantially, from 8% in the tropics to 76% in the Arctic. The resulting annual mean BCair increases by up to 156% at high altitudes and at northern high latitudes because of lower temperature and higher IMF. Overall, WBF halves the model-observation discrepancy (from -65% to -30%) of BCair across North America, Europe, China and the Arctic. Globally WBF increases BC burden from 0.22 to 0.29-0.35 mg m-2 yr-1, which partially explains the gap between observed and previous model simulated BC burdens over land. In addition, WBF significantly increases BC lifetime from 5.7 days to ~8 days. Additionally, WBF results in a significant redistribution of BC deposition in source and remote regions. Specifically, it lowers BC wet deposition (by 37-63% at northern mid-latitudes and by 21-29% in the Arctic) while increases dry deposition (by 3-16% at mid-latitudes and by 81-159% in the Arctic). The resulting total BC deposition is lower at mid-latitudes (by 12-34%) but higher in the Arctic (by 2-29%). We find that WBF decreases BCsnow at mid-latitudes (by ~15%) but increases it in the Arctic (by 26%) while improving model comparisons with observations. In addition, WBF dramatically reduces the model-observation discrepancy of washout ratios in winter (from a factor of 16 to 4). The remaining discrepancies in BCair, BCsnow and BC washout ratios suggest that in-cloud removal in mixed-phased clouds is likely still excessive over land. [ABSTRACT FROM AUTHOR]

We investigate the sensitivity of black carbon (BC) in the Arctic, including BC in snow (BCsnow, ng g-1) and surface air (BCair, μg m-3), to emissions, dry deposition and wet scavenging using a global 3-D chemical transport model (CTM) GEOS-Chem. We find that the model underestimates BCsnow in the Arctic by 40% on average (median = 11.8 ng g-1). Natural gas flaring substantially increases total BC emissions in the Arctic (by ~ 70%). The flaring emissions lead to up to 49% increases (0.1-8.5 ng g-1) in Arctic BCsnow, dramatically improving model comparison with observations (50% reduction in discrepancy) near flaring source regions (Western Extreme North of Russia). Ample observations suggest that BC dry deposition velocities over snow and ice in current CTMs (0.03 cm s-1 in GEOS-Chem) are exceedingly small. We apply the resistance-in-series method to compute the dry deposition velocity that varies with local meteorological and surface conditions. The resulting velocity is significantly larger and varies by a factor of eight in the Arctic (0.03-0.24 cm s-1), increases the fraction of dry to total BC deposition (16% to 25%), yet leaves the total BC deposition and BCsnow in the Arctic unchanged. This is largely explained by the offsetting higher dry and lower wet deposition fluxes. Additionally, we account for the effect of the Wegener-Bergeron-Findeisen (WBF) process in mixed-phase clouds, which releases BC particles from condensed phases (water drops and ice crystals) back to the interstitial air and thereby substantially reduces the scavenging efficiency of BC (by 43-76% in the Arctic). The resulting BCsnow is up to 80% higher, BC loading is considerably larger (from 0.25 to 0.43 mg m-2), and BC lifetime is markedly prolonged (from 9 to 16 days) in the Arctic. Over all, flaring emissions increase BCair in the Arctic (by ~ 20 ng m-3), the updated dry deposition velocity more than halves BCair (by ~ 20 ng m-3), and the WBF effect increases BCair by 25-70% during winter and early spring. The resulting model simulation of BCsnow is substantially improved (within 10% of the observations) and the discrepancies of BCair are much smaller during snow season at Barrow, Alert and Summit (from -67%--47% to -46%-3%). Our results point toward an urgent need for better characterization of flaring emissions of BC (e.g. the emission factors, temporal and spatial distribution), extensive measurements of both the dry deposition of BC over snow and ice, and the scavenging efficiency of BC in mixed-phase clouds. [ABSTRACT FROM AUTHOR]

The rugged surface of an urban area due to varying buildings can interact with solar beams and affect both the magnitude and spatiotemporal distribution of surface solar fluxes. Here we systematically examine the impact of buildings on downward surface solar fluxes over urban Beijing by using a 3-D radiation parameterization that accounts for 3-D building structures vs. the conventional plane-parallel scheme. We find that the resulting downward surface solar flux deviations between the 3-D and the plane-parallel schemes are generally ±1-10Wm-2 at 800m grid resolution and within ±1Wm-2 at 4 km resolution. Pairs of positive-negative flux deviations on different sides of buildings are resolved at 800m resolution, while they offset each other at 4 km resolution. Flux deviations from the unobstructed horizontal surface at 4 km resolution are positive around noon but negative in the early morning and late afternoon. The corresponding deviations at 800m resolution, in contrast, show diurnal variations that are strongly dependent on the location of the grids relative to the buildings. Both the magnitude and spatiotemporal variations of flux deviations are largely dominated by the direct flux. Furthermore, we find that flux deviations can potentially be an order of magnitude larger by using a finer grid resolution. Atmospheric aerosols can reduce the magnitude of downward surface solar flux deviations by 10-65%, while the surface albedo generally has a rather moderate impact on flux deviations. The results imply that the effect of buildings on downward surface solar fluxes may not be critically significant in mesoscale atmospheric models with a grid resolution of 4 km or coarser. However, the effect can play a crucial role in meso-urban atmospheric models as well as microscale urban dispersion models with resolutions of 1m to 1 km. [ABSTRACT FROM AUTHOR]

Using in situ measurements, we find a semiannual oscillation (SAO) in the midtropospheric and surface C(X Chemistry transport models (2-D Caltech/JPL model, 3-D GEOS-Chem, and 3-D N40ZART-2) arc used to investigate possible sources for the SAO signal in the midtropospheric and surface CO2. From model sensitivity studies, it is revealed that the SAO signal in the midtropospheric CO2 originates mainly from surface CO2 with a small contribution from transport fields. It is also found that the source for the SAO signal in surface CO2 is mostly related to the CO2 exchange between the biosphere and the atmosphere. By comparing model CO2 with in situ CO2 measurements at the surface, we find that models are able to capture both annual and semiannual cycles well at the surface. Model simulations of the annual and semiannual cycles of CO2 in the iropical middle troposphere agree reasonably well with aircraft measurements [ABSTRACT FROM AUTHOR]

The California Institute of Technology/Jet Propulsion Laboratory two-dimensional (2-D), three-dimensional (3-D) GEOS-Chem, and 3-D MOZART-2 chemistry and transport models (CTMs), driven respectively by NCEP2, GEOS-4, and NCEP1 reanalysis data, have been used to simulate upper tropospheric CO2 from 2000 to 2004. Model results of CO2 mixing ratios agree well with monthly mean aircraft observations at altitudes between 8 and 13 km (Matsueda et al., 2002) in the tropics. The upper tropospheric CO2 seasonal cycle phases are well captured by the CTMs. Model results have smaller seasonal cycle amplitudes in the Southern Hemisphere compared with those in the Northern Hemisphere, which are consistent with the aircraft data. Some discrepancies are evident between the model and aircraft data in the midlatitudes, where models tend to underestimate the amplitude of CO2 seasonal cycle. Comparison of the simulated vertical profiles of CO2 between the different models reveals that the convection in the 3-D models is likely too weak in boreal winter and spring. Model sensitivity studies suggest that convection mass flux is important for the correct simulation of upper tropospheric CO2. [ABSTRACT FROM AUTHOR]

We carried out a systematic study of the seasonal cycle and its latitudinal variation in the nitrous oxide (N2O) data collected by National Oceanic and Atmospheric Administration-Global Monitoring Division (NOAA-GMD) and the Advanced Global Atmospheric Gases Experiment (AGAGE). In order to confirm the weak seasonal signal in the observations, we applied the multitaper method for the spectrum analysis and studied the stations with significant seasonal cycle. In addition, the measurement errors must be small compared with the seasonal cycle. The N2O seasonal cycles from seven stations satisfied these criteria and were analyzed in detail. The stations are Alert (82°N, 62°W), Barrow (71°N, 157°W), Mace Head (53°N, 10°W), Cape Kumukahi (19°N, 155°W), Cape Matatula (14°S, 171°W), Cape Grim (41°S, 145°E) and South Pole (90°S, 102°W). The amplitude (peak to peak) of the seasonal cycle of N2O varies from 0.29 ppb (parts-per-billion by mole fraction in dry air) at the South Pole to 1.15 ppb at Alert. The month at which the seasonal cycle is at a minimum varies monotonically from April (South Pole) to September (Alert). The seasonal cycle in the Northern Hemisphere shows the influence of the stratosphere; the seasonal cycle of N2O in the Southern Hemisphere suggests greater influence from surface sources. Preliminary estimates are obtained for the magnitude of the seasonally varying sources needed to account for the observations. [ABSTRACT FROM AUTHOR]

Support Vector Machines (SVMs) are classic supervised learning models for classification, regression and distribution estimation. A survey conducted by Kaggle in 2017 shows that 26% of the data mining and machine learning practitioners are users of SVMs. However, SVM training and prediction are very expensive computationally for large and complex problems. This paper presents an efficient and open source SVM software toolkit called ThunderSVM which exploits the high-performance of Graphics Processing Units (GPUs) and multi-core CPUs. ThunderSVM supports all the functionalities|including classification (SVC), regression (SVR) and one-class SVMs|of LibSVM and uses identical command line options, such that existing LibSVM users can easily apply our toolkit. ThunderSVM can be used through multiple language interfaces including C/C++, Python, R and MAT- LAB. Our experimental results show that ThunderSVM is generally an order of magnitude faster than LibSVM while producing identical SVMs. In addition to the high efficiency, we design our convex optimization solver in a general way such that SVC, SVR, and one-class SVMs share the same solver for the ease of maintenance. Documentation, examples, and more about ThunderSVM are available at https://github.com/zeyiwen/thundersvm. [ABSTRACT FROM AUTHOR]

Gradient Boosting Decision Trees (GBDTs) and Random Forests (RFs) have been used in many real-world applications. They are often a standard recipe for building state-of-the-art solutions to machine learning and data mining problems. However, training and prediction are very expensive computationally for large and high dimensional problems. This article presents an efficient and open source software toolkit called ThunderGBM which exploits the high-performance Graphics Processing Units (GPUs) for GBDTs and RFs. ThunderGBM supports classification, regression and ranking, and can run on single or multiple GPUs of a machine. Our experimental results show that ThunderGBM outperforms the existing libraries while producing similar models, and can handle high dimensional problems where existing GPU-based libraries fail. Documentation, examples, and more details about ThunderGBM are available at https://github.com/xtra-computing/thundergbm. [ABSTRACT FROM AUTHOR]