Largest Source Research Articles

Collaborative Governance Of Marine Plastic Waste Of Local Administrative Organizations In Thailand Case Study: Phuket City Municipality

This article aims to study the collaborative role of Phuket City Municipality in marine plastic waste management among public, private and social sector. Selection of key informants was done by a theoretical sampling method through Collaborative Governance theory. The sample group was divided into 3 groups: government, private and social sector. Since it was a case study, key informants were selected by purposive sampling. The tool used was semi-structured interview and analyzed data by content analysis and triangulation validation.
 The findings showed that Phuket City Municipality has created cooperation among government, private and social sector according to the legal authority, clear goals system to drive in every dimension as follows: 1.Government sector: Phuket City Municipality collects, transports, and disposes the waste according to its duty. Phuket Provincial Committee was established to be a driver and integrator in the cluster of local administrative organizations , local government agencies , international organizations and ministerial level. 2. Private sector creates cooperation with large waste sources to participate in the management of source waste through social networks. 3. Social sector by building cooperation through community leaders and the community of Phuket City Municipality, promoting the processing of recycled products, creating a provincial environmental foundation to reduce bureaucratic constraints, educating on waste management through municipal schools, creation of communication channels to solve problems with the people, and building cooperation with educational institutions to educate and build cooperation with the public. The cooperation of these 3 sectors is in line with the concept of Collaborative Governance

Graph-Regularized Tensor Regression: A Domain-Aware Framework for Interpretable Modeling of Multiway Data on Graphs.

Modern data analytics applications are increasingly characterized by exceedingly large and multidimensional data sources. This represents a challenge for traditional machine learning models, as the number of model parameters needed to process such data grows exponentially with the data dimensions, an effect known as the curse of dimensionality. Recently, tensor decomposition (TD) techniques have shown promising results in reducing the computational costs associated with large-dimensional models while achieving comparable performance. However, such tensor models are often unable to incorporate the underlying domain knowledge when compressing high-dimensional models. To this end, we introduce a novel graph-regularized tensor regression (GRTR) framework, whereby domain knowledge about intramodal relations is incorporated into the model in the form of a graph Laplacian matrix. This is then used as a regularization tool to promote a physically meaningful structure within the model parameters. By virtue of tensor algebra, the proposed framework is shown to be fully interpretable, both coefficient-wise and dimension-wise. The GRTR model is validated in a multiway regression setting and compared against competing models and is shown to achieve improved performance at reduced computational costs. Detailed visualizations are provided to help readers gain an intuitive understanding of the employed tensor operations.

Overlooked riverine contributions of dissolved neodymium and hafnium to the Amazon estuary and oceans

The Amazon River accounts for 20% of global freshwater runoff and supplies vital trace metals to the Atlantic Ocean. Suspended particles within its plume are thought to partially dissolve, constituting a large potential source of metals, which is, however, not well constrained. Here we used combined neodymium (Nd) and hafnium (Hf) isotopes to disprove the release of Nd and Hf from particles as the cause of the observed dissolved concentration increases and isotopic variability across the plume. Instead, the changes reflect admixture of nearby Pará River freshwater with exceptionally high dissolved Nd and Hf concentrations contributing 45–100% of the riverine fraction to the southern and outer estuary. This result led us to develop an empirical relationship between riverine Nd concentration and pH to revise the global dissolved riverine Nd flux, which accordingly is at least three times higher than commonly used estimates. Future work should focus on contributions of low-pH rivers to global metal fluxes.

Evaluation of the emission inventory for large point emission sources in South Korea by applying measured data from the NASA/NIER KORUS-AQ aircraft field campaign

One of the major issues in determining a region’s air quality is the uncertainty of large point sources (LPSs) emissions, which significantly affect the local-regional air quality. In this study, the SO2 and NOx emissions of 5 major LPSs in South Korea were evaluated by comparing the emissions-based concentrations employing a Gaussian dispersion model with aircraft-based measurements from DC-8 “around-the-stack” flights through the National Aeronautics and Space Administration (NASA)/National Institute of Environmental Research (NIER) KORea-U.S. Cooperative Domestic Air Quality (KORUS-AQ) aircraft field campaign. The ratio between modeled and measured concentrations for all 5 LPSs ranged between 0.42 and 1.30 and 0.39 and 1.01 for NOx and SO2, respectively. The results for the Boryeong, Dangjin, and Seocheon power plants (PPs), where the locations and sizes of stacks are easier to specify than industrial complexes (Hyundai Steel and Hankook Glass), yielded better performance, which ranged between 0.82 and 1.30 and 0.79 and 1.01 for NOx and SO2. This level of agreement was very encouraging, considering that the modeled concentrations were based on 30-min averaged emissions compared to less-than-a-minute DC-8 around-the-stack measurements. Based on our analysis, the uncertainty of LPS emissions, at least for NOx and SO2, appears to be small, which implies that the point sources inventory emissions are reasonably accurate. The Dangjin PP’s analysis reveals that the actual measured emissions should be considered in addition to “the official” inventory amounts to reduce emission uncertainty. This detailed comparative analysis verified the method used for this study. The findings of this study are expected to enhance the performance of future LPS emission inventory assessments. In terms of recommendations, the data from the raw emission inventory should include more clear information about the locations of measured stacks to obtain more accurate emission estimates. In addition, the flight measurement duration should be long enough to fly around several times to reduce uncertainties, and the flight positions and altitudes should be varied. By improving LPS inventories through accurate evaluations, more accurate air quality forecasts and better policies could be made. As a result, it is expected that public health can be improved by reducing the time people are exposed to high concentrations of air pollutants.

Research on a New Method for Intermittent Production of Horizontal Wells in Low-Permeability Gas Field

With the development of drilling technology in recent years, an increasing number of horizontal wells have been widely used in low-permeability gas fields. Although horizontal wells are much more productive than vertical wells, fluid accumulation can occur when the formation energy drops and the gas flow rate in the wellbore is not sufficient to remove the loaded fluid from the wellbore. Intermittent production is a good method for preventing liquid loading, but thus far, there is no difference between the open and closed working system of horizontal wells and that of vertical wells, and there is a certain misunderstanding here. In this work, experiments were conducted on the opening process and closing process of a horizontal well, and it was found that the loaded fluid in the horizontal wellbore is a large source of water. It enters the vertical section during the opening process, thereby raising the liquid level and storing the fluid loaded in the vertical section during the closing process, which is difficult to unload. Combined with the experimental results, the production dynamics of a horizontal well with intermittent production was analyzed, and the well opening process and well closing process were divided into four stages. On this basis, a new multifrequency well opening method for intermittent production of horizontal wells was proposed to unload the liquid in horizontal wellbore. The field application case shows that this method can effectively eliminate the drawbacks caused by using conventional methods and increase the average gas production in one cycle by 46%.

Controlled-release testing of the static chamber methodology for direct measurements of methane emissions

Abstract. Direct measurements of methane emissions at the component level provide the level of detail necessary for the development of actionable mitigation strategies. As such, there is a need to understand the magnitude of component-level methane emission sources and to test methane quantification methods that can capture methane emissions at the component level used in national inventories. The static chamber method is a direct measurement technique that has been applied to measure large and complex methane sources, such as oil and gas infrastructure. In this work, we compile methane emission factors from the Intergovernmental Panel on Climate Change (IPCC) Emission Factor Database in order to understand the magnitude of component-level methane flow rates, review the tested flow rates and measurement techniques from 40 controlled-release experiments, and perform 64 controlled-release tests of the static chamber methodology with mass flow rates of 1.02, 10.2, 102, and 512 g h−1 of methane. We vary the leak properties, chamber shapes, chamber sizes, and use of fans to evaluate how these factors affect the accuracy of the static chamber method. We find that 99 % of the component-level methane emission rates from the IPCC Emission Factor Database are below 100 g h−1 and that 77 % of the previously available controlled-release experiments did not test for methane mass flow rates below 100 g h−1. We also find that the static chamber method quantified methane flow rates with an overall accuracy of +14/-14 % and that optimal chamber configurations (i.e., chamber shape, volume, and use of fans) can improve accuracy to below ±5 %. We note that smaller chambers (≤20 L) performed better than larger-volume chambers (≥20 L), regardless of the chamber shape or use of fans. However, we found that the use of fans can substantially increase the accuracy of larger chambers, especially at higher methane mass flow rates (≥100 g h−1). Overall, our findings can be used to engineer static chamber systems for future direct measurement campaigns targeting a wide range of sources, including landfills, sewerage utility holes, and oil and natural gas infrastructure.

The organization of double-stranded RNA in the chikungunya virus replication organelle

Alphaviruses are mosquito-borne, positive-sense single-stranded RNA viruses. Amongst the alphaviruses, chikungunya virus is notable as a large source of human illness, especially in tropical and subtropical regions. When they invade a cell, alphaviruses generate dedicated organelles for viral genome replication, so-called spherules. Spherules form as outward-facing buds at the plasma membrane, and it has recently been shown that the thin membrane neck that connects this membrane bud with the cytoplasm is guarded by a two-megadalton protein complex that contains all the enzymatic functions necessary for RNA replication. The lumen of the spherules contains a single copy of the negative-strand template RNA, present in a duplex with newly synthesized positive-sense RNA. Less is known about the organization of this double-stranded RNA as compared to the protein components of the spherule. Here, we analyzed cryo-electron tomograms of chikungunya virus spherules in terms of the organization of the double-stranded RNA replication intermediate. We find that the double-stranded RNA has a shortened apparent persistence length as compared to unconstrained double-stranded RNA. Around half of the genome is present in either of five conformations identified by subtomogram classification, each representing a relatively straight segment of ~25–32 nm. Finally, the RNA occupies the spherule lumen at a homogeneous density, but has a preferred orientation to be perpendicular to a vector pointing from the membrane neck towards the spherule center. Taken together, this analysis lays another piece of the puzzle of the highly coordinated alphavirus genome replication.

Magnetotelluric Power Line Noise Removal Using Temporally Varying Sinusoidal Subtraction of the Grid Utility Frequency

The magnetotelluric method relies on variations of natural electromagnetic fields, which in the vicinity of human settlements are persistently distorted by anthropogenic electromagnetic noise. A large source of noise to the magnetotelluric response is caused by the harmonic oscillations of the power network utility frequency centered on 50/60 Hz along with the associated higher harmonics. Removing this type of noise is essential for high frequency magnetotelluric measurements used for shallow surveys. There are a large number of approaches for how to treat power line noise in magnetotelluric signals, however, commonly used methods do not take into account time variations/instabilities of the utility frequency. That is not serious problem in vicinity of well balanced grid networks, but can cause issues in regions with larger utility frequency variations. Under such conditions, commonly used methods loose more of the natural signal, which is undesirable especially in case of very noisy datasets. Hence, we adopted approach for removing of power line noise with respect to time variations of the utility frequency and applied it to magnetotelluric signals to preserve more of natural signal. The method is based on modelling of the grid network harmonic oscillations by the optimum utility frequency and its integer multiples. The resulting sum of sinusoidal signals is subsequently subtracted from recorded data and only particular noise frequencies are removed from the original signal with high precision, while frequency ranges around power line harmonics are cleaned.

Testing the Blazar Sequence with Spectra of Recently Discovered Dim Blazars from the Fermi Unassociated Catalog

Recent works have developed samples of blazars from among the Fermi Large Area Telescope unassociated sources via machine-learning comparisons with known blazar samples. Continued analysis of these new blazars tests the predictions of the blazar sequence and enables more flux-complete samples of blazars as a population. Using Fermi, Swift, Wide-field Infrared Survey Explorer, and archival radio data, we construct broadband spectral energy distributions for 106 recently identified blazars. Drawn from the unassociated 4FGL source sample, this new sample has a lower median flux than the overall sample of gamma-ray blazars. By measuring the synchrotron peak frequency, we compare our sample of new blazars with known blazars from the 4LAC catalog. We find that the bulk of the new blazars are similar to high-synchrotron-peaked BL Lac objects, with a higher median synchrotron peak; the sample has a median via BLaST peak estimation, compared to for the 4LAC BL Lacs. Finally, we conduct synchrotron self-Compton leptonic modeling, comparing fitted physical and phenomenological properties to brighter blazars. We find that the new blazars have smaller characteristic Lorentz factors γ boost and fitted magnetic fields B, in agreement with blazar sequence predictions. The new blazars have slightly higher Compton dominance ratios than expected, which may point to alternative emission models for these dim blazars. Our results extend the predictions of the blazar sequence to a sample of dimmer blazars, confirming the broad predictions of that theory.

Predictive algorithms in dynamical sampling for burst-like forcing terms

In this paper, we consider the problem of recovery of a burst-like forcing term in an initial value problem (IVP) in the framework of dynamical sampling. We introduce an idea of using two particular classes of samplers that allow one to predict the solution of the IVP over a time interval without a burst. This leads to two different algorithms that stably and accurately approximate the burst-like forcing term even in the presence of a measurement acquisition error and a large background source.

Groundwater springs formed during glacial retreat are a large source of methane in the high Arctic

Permafrost and glaciers in the high Arctic form an impermeable ‘cryospheric cap’ that traps a large reservoir of subsurface methane, preventing it from reaching the atmosphere. Cryospheric vulnerability to climate warming is making releases of this methane possible. On Svalbard, where air temperatures are rising more than two times faster than the average for the Arctic, glaciers are retreating and leaving behind exposed forefields that enable rapid methane escape. Here we document how methane-rich groundwater springs have formed in recently revealed forefields of 78 land-terminating glaciers across central Svalbard, bringing deep-seated methane gas to the surface. Waters collected from these springs during February–May of 2021 and 2022 are supersaturated with methane up to 600,000 times greater than atmospheric equilibration. Spatial sampling reveals a geological dependency on the extent of methane supersaturation, with isotopic evidence of a thermogenic source. We estimate annual methane emissions from proglacial groundwaters to be up to 2.31 kt across the Svalbard archipelago. Further investigations into marine-terminating glaciers indicate future methane emission sources as these glaciers transition into fully land-based systems. Our findings reveal that climate-driven glacial retreat facilitates widespread release of methane, a positive feedback loop that is probably prevalent across other regions of the rapidly warming Arctic.

Modeling and Simulation of CO2 Capture Unit using Mixed Solvent of Aqueous Methyldiethanolamine and Piperazine for 6.4 MWe Power Plant

Carbon dioxide emissions are the largest greenhouse gases contributor, which is attributed to global warming. Therefore, the capture of CO2 is necessary, especially from large point sources. Post-combustion capture using chemical solvents is the most matured capture technology. In this paper, mixed solvents of methyldiethanolamine (MDEA) and piperazine (PZ) were studied to potentially address some issues related to the use of conventional monoethanolamine (MEA). Steady-state modeling and simulation of the post-combustion carbon capture using the mixed solvents for a typical 6.4 MWe power plant were done. The model developed was validated against experimented data with relative error between 1 – 4.73% for the absorber on CO2 capture efficiency and between 2.93 – 10.2% relative errors on CO2 regeneration efficiency. The model was scaled up to capture CO2 from the flue gas of a typical 6.4 MWe power plant. The scaled-up results showed packing height and diameter of absorber to be 5.5 m and 1.5 m; while that of the stripper was 5.08 m and 1.45 m respectively. Effect of flue gas temperature on the capture efficiency was studied, it was observed that as the temperature increased from 20 ºC, the capture efficiency increased, but at 70 ºC, the efficiency showed no significant increase which could be associated with the existence of a temperature bulge. Capture efficiency increases with an increase in PZ concentration due to increase in the rate of reaction with concentration. The absorption and regeneration results suggest that an aqueous MDEA/PZ blend could be a prospective absorbent for CO2 capture.

Groundwater pollution source identification and health risk assessment in the North Anhui Plain, eastern China: Insights from positive matrix factorization and Monte Carlo simulation

Groundwater contaminants from natural and anthropogenic sources pose a serious threat to the ecological environment and public health. In this study, 30 groundwater samples were collected from shallow wells at a large central water source in the North Anhui Plain, eastern China. Hydrogeochemical methods, positive matrix factorization (PMF) model, and Monte Carlo simulation were used to determine the characteristics, sources, and human health risks of inorganic and organic analytes in groundwater. The groundwater was weakly alkaline with high total hardness and was dominated by HCO3-Mg·Ca, HCO3-Ca·Mg, and HCO3-Ca·Mg·Na hydrochemical facies. The concentration of naphthalene was at a safe level, while the concentrations of F−, NO3− and Mn in 16.7 %, 26.7 % and 40 % of the samples, respectively, exceeded threshold risk-based values based on Chinese groundwater quality standards. Hydrogeochemical methods revealed that water-rock interactions (including weathering of silicate minerals, dissolution of carbonates, and cation exchange), acidity, and runoff conditions control the migration and enrichment of these analytes in groundwater. The PMF model indicated that local geogenic processes, hydrogeochemical evolution, agricultural activities, and petroleum-related industrial sources were the main factors affecting groundwater quality, with contributions of 38.2 %, 33.7 %, 17.8 %, and 10.3 %, respectively. A health risk evaluation model based on Monte Carlo simulation indicated that 77.9 % of children were exposed to a total noncarcinogenic risk above safe thresholds, about 3.4 times higher than the risk to adults. The main contributor to human health risk was F− originating from geogenic processes; thus, F− was identified as a priority for control. This study demonstrates the feasibility and reliability of combining source apportionment techniques and health risk assessment to evaluate groundwater quality.

Dissolved organic carbon dynamics and fluxes in Mississippi-Atchafalaya deltaic system impacted by an extreme flood event and hurricanes: a multi-satellite approach using Sentinel-2/3 and Landsat-8/9 data

Transport of riverine and wetland-derived dissolved organic carbon (DOC) spanning tidal wetlands, estuaries, and continental shelf waters functionally connects terrestrial and aquatic carbon reservoirs, yet the magnitude and ecological significance of this variable and its spatiotemporal linkage remains uncertain for coastal deltaic regions, such as Mississippi River Delta Plain, which includes Mississippi (MR) and Atchafalaya (AR) rivers and estuaries with vast expanses of wetlands and coastal forests. We examined DOC dynamics and fluxes in this large river-dominated wetland-estuarine system for the period between 2019 and 2021 that included an extreme river flood event in 2019, two major hurricanes (Barry in 2019 and Ida in 2021), and cold front passage using an improved adaptive quasi-analytical algorithm (QAA-AD) applied to multi-satellite sensors (Sentinel 3A/B OLCI, Landsat-8/OLI and Sentinel-2A/B MSI) with varying spectral and spatial (10/30/300 m) resolutions. The DOC estimates from multi-satellite sensors in combination with water fluxes were used to assess DOC fluxes from two large rivers (MR and AR) and small channels across the delta plain. Overall, this system delivered a total of 6.7 Tg C yr-1(1 Tg = 1012g) into the estuarine zone and the northern Gulf of Mexico (nGoM) during 2019. High DOC fluxes from the AR (1.3 Tg C yr-1) and MR (4.5 Tg C yr-1) were associated with the extreme flood event in 2019. Hurricanes that occurred in the study period also contributed to the wetland and estuarine DOC fluxes into continental shelf waters; for example, the passage of Hurricane Barry in July 2019, delivered over a 3-day period ~1.33 ×109g DOC from Barataria Basin into the nGoM. Sentinel 2-MSI land and water classification revealed that Hurricane Ida eroded a total of 1.34×108m2of marshes in middle Barataria Basin, converting those habitats into open water with 3.0 m inundation depth and high DOC concentrations (16.4 mg L-1), a potentially large DOC source to the coastal waters. Overall, storms and flood events are major sources of DOC flux that facilitate transport of upstream carbon as well as transformation of carbon in the wetlands, through the conversion of vegetated wetland to open water.

Agricultural ditches are hotspots of greenhouse gas emissions controlled by nutrient input

Agricultural ditches are pervasive in agricultural areas and are potential greenhouse gas (GHG) hotspots, since they directly receive abundant nutrients from neighboring farmlands. However, few studies measure GHG concentrations or fluxes in this particular water course, likely resulting in underestimations of GHG emissions from agricultural regions. Here we conducted a one-year field study to investigate the GHG concentrations and fluxes from typical agricultural ditch systems, which included four different types of ditches in an irrigation district located in the North China Plain. The results showed that almost all the ditches were large GHG sources. The mean fluxes were 333 μmol m-2 h-1 for CH4, 7.1 mmol m-2 h-1 for CO2, and 2.4 μmol m-2 h-1 for N2O, which were approximately 12, 5, and 2 times higher, respectively, than that in the river connecting to the ditch systems. Nutrient input was the primary driver stimulating GHG production and emissions, resulting in GHG concentrations and fluxes increasing from the river to ditches adjacent to farmlands, which potentially received more nutrients. Nevertheless, the ditches directly connected to farmlands showed lower GHG concentrations and fluxes compared to the ditches adjacent to farmlands, possibly due to seasonal dryness and occasional drainage. All the ditches covered approximately 3.3% of the 312 km2 farmland area in the study district, and the total GHG emission from the ditches in this area was estimated to be 26.6 Gg CO2-eq yr−1, with 17.5 Gg CO2, 0.27 Gg CH4, and 0.006 Gg N2O emitted annually. Overall, this study demonstrated that agricultural ditches were hotspots of GHG emissions, and future GHG estimations should incorporate this ubiquitous but underrepresented water course.

Agriculture and environment: friends or foes? Conceptualising agri-environmental discourses under the European Union’s Common Agricultural Policy

The European Union’s common agricultural policy (CAP), in addition to its primary production and farm income goals, is a large source of funding for environmentally friendly agricultural practices. However, its schemes have variable success and uptake across member states (MS) and regions. This study tries to explain these differences by demonstrating differences between policy levels in the understanding of the relationship between nature and farming. To compare constructs and values of the respective policy communities, their discursive construction as it appears in the main strategic EU and MS agricultural policy documents is analysed. The theoretical framework integrates elements from existing frameworks of CAP and environmental discourse analysis; specific agri-environmental discourses, their elements and interplay, are identified. The six discourses suggested here are ‘Productivism’, ‘Classical neoliberal’, ‘Ecological modernisation’, ‘Administrative’, ‘Multifunctionality’ and ‘Radical green’. The discourse analysis of selected documents reveals that there are indeed differences in how farming and the environment are generally conceptualised at different levels of CAP decision-making. At EU level, farming is primarily understood as a sector whose main task is to produce food (‘Productivism’), and the environment is used as a justification for CAP payments (‘Multifunctionality’). At the national/regional level, Rural Development Programmes reflect different value systems: in England, environmental protection is mainly seen as sound management of natural capital (‘Classical neoliberal’); in Finland, a benefit for producers and conscious consumers (‘Ecological modernisation’); in Croatia, a necessity limiting productivity (‘Productivism’) and imposed by an external authority (‘Administrative’ discourse). This diversity shows that differences can visibly manifest despite the Commission constraining the discursive space, helping to explain the differential implementation and success of environmental measures.

Integrating carbon capture and utilization into the glass industry: Economic analysis of emissions reduction through CO2 mineralization

Glass production contributes significantly to global CO2 emissions due to high thermal energy requirements and raw material consumption. As a difficult-to-abate industry, carbon capture and utilization or storage (CCU/CCS) will be necessary to achieve emission targets. Among various options, CO2 mineralization shows promise to simultaneously capture CO2 and convert it to valuable products. When caustic (NaOH) is used as the absorbent, a portion of the resulting sodium carbonate (Na2CO3) can be fed back to the glass process to replace soda ash, a major component of glass and a large source of indirect emissions. Although a combination of glass manufacturing and CO2 mineralization presents a novel opportunity for drastic CO2 emissions reduction, such a process has yet to be studied. This work uses detailed, optimized process models to perform economic and CO2 emission analyses of three cases for such a highly integrated CCU system. In each case, CO2 is captured and directly converted to NaHCO3 and/or Na2CO3 by absorption into a NaOH solution. The NaOH is produced via the electrolysis of sodium chloride, which generates the valuable byproducts chlorine and hydrogen. The results are compared to glass production with amine-based CCS. The mineralization cases are shown to have net negative CO2 emissions, between −152 and −528 kg CO2/ton glass, relative to the unabated glass process and Solvay process for Na2CO3. The discounted payback periods for the mineralization cases range from 3.8 to 6.0 years, while the CCS case has reduced emissions of 353 kg CO2/ton glass and a negative net present value at the end of 20 years.

Quantification of methane emissions in Hamburg using a network of FTIR spectrometers and an inverse modeling approach

Abstract. Methane (CH4) is a potent greenhouse gas, and anthropogenic CH4 emissions contribute significantly to global warming. In this study, the CH4 emissions of the second most populated city in Germany, Hamburg, were quantified with measurements from four solar-viewing Fourier transform infrared (FTIR) spectrometers, mobile in situ measurements, and an inversion framework. For source type attribution, an isotope ratio mass spectrometer was deployed in the city. The urban district hosts an extensive industrial and port area in the south as well as a large conglomerate of residential areas north of the Elbe River. For emission modeling, the TNO GHGco (Netherlands Organisation for Applied Scientific Research greenhouse gas and co-emitted species emission database) inventory was used as a prior for the inversion. In order to improve the inventory, two approaches were followed: (1) the addition of a large natural CH4 source, the Elbe River, which was previously not included in the inventory, and (2) mobile measurements were carried out to update the spatial distribution of emissions in the TNO GHGco gridded inventory and derive two updated versions of the inventory. The addition of the river emissions improved model performance, whereas the correction of the spatial distribution with mobile measurements did not have a significant effect on the total emission estimates for the campaign period. A comparison of the updated inventories with emission estimates from a Gaussian plume model (GPM) showed that the updated versions of the inventory match the GPM emissions estimates well in several cases, revealing the potential of mobile measurements to update the spatial distribution of emission inventories. The mobile measurement survey also revealed a large and, at the time of the study, unknown point source of thermogenic origin with a magnitude of 7.9 ± 5.3 kg h−1 located in a refinery. The isotopic measurements show strong indications that there is a large biogenic CH4 source in Hamburg that produced repeated enhancements of over 1 ppm which correlated with the rising tide of the river estuary. The CH4 emissions (anthropogenic and natural) of the city of Hamburg were quantified as 1600 ± 920 kg h−1, 900 ± 510 kg h−1 of which is of anthropogenic origin. This study reveals that mobile street-level measurements may miss the majority of total methane emissions, potentially due to sources located within buildings, including stoves and boilers operating on natural gas. Similarly, the CH4 enhancements recorded during the mobile survey from large-area sources, such as the Alster lakes, were too small to generate GPM emission estimates with confidence, but they could nevertheless influence the emission estimates based on total column measurements.

Center-environment deep transfer machine learning across crystal structures: from spinel oxides to perovskite oxides

In data-driven materials design where the target materials have limited data, the transfer machine learning from large known source materials, becomes a demanding strategy especially across different crystal structures. In this work, we proposed a deep transfer learning approach to predict thermodynamically stable perovskite oxides based on a large computational dataset of spinel oxides. The deep neural network (DNN) source domain model with “Center-Environment” (CE) features was first developed using the formation energy of 5329 spinel oxide structures and then was fine-tuned by learning a small dataset of 855 perovskite oxide structures, leading to a transfer learning model with good transferability in the target domain of perovskite oxides. Based on the transferred model, we further predicted the formation energy of potential 5329 perovskite structures with combination of 73 elements. Combining the criteria of formation energy and structure factors including tolerance factor (0.7 < t ≤ 1.1) and octahedron factor (0.45 < μ < 0.7), we predicted 1314 thermodynamically stable perovskite oxides, among which 144 oxides were reported to be synthesized experimentally, 10 oxides were predicted computationally by other literatures, 301 oxides were recorded in the Materials Project database, and 859 oxides have been first reported. Combing with the structure-informed features the transfer machine learning approach in this work takes the advantage of existing data to predict new structures at a lower cost, providing an effective acceleration strategy for the expensive high-throughput computational screening in materials design. The predicted stable novel perovskite oxides serve as a rich platform for exploring potential renewable energy and electronic materials applications.

Effectiveness of emission controls implemented since 2000 on ambient ozone concentrations in multiple timescales in Japan: An emission inventory development and simulation study

It has been reported that ambient ozone concentrations in Japan have not been effectively suppressed by precursor emission controls. In this study, we developed an unprecedented long-term emission inventory of ozone precursors, including nitrogen oxide (NOX) and volatile organic compounds (VOCs), in Japan. The developed emission inventory, which explicitly represents changes in emissions caused by emission controls and variation in activities from 2000 to 2019, revealed that emission controls implemented for vehicles, large point sources, and fugitive VOC sources effectively reduced precursor emissions. The impact of emission changes on ozone concentrations at six different timescales was evaluated using air quality simulations. Three of them corresponded to annual mean values of daily ozone concentrations, and the others corresponded to annual high ozone concentrations. The simulations performed better at higher ozone concentrations. The simulation results suggested that emission controls have helped suppress annual high ozone concentrations, whereas the annual mean values of daily ozone concentrations may have increased in populated urban areas because reduced NOX emissions weakened the titration of ozone. Overall changes in the simulated ozone concentrations over different timescales were generally consistent with those in the observed ozone concentrations. These findings highlight the importance of evaluating the impact of emission controls on ozone concentrations over multiple timescales. The differences in the sensitivities of ozone concentrations to emission controls were clearly explained by the ozone sensitivity regimes implied by the ratios of formaldehyde to nitrogen dioxide. The outcomes of this study could assist countries beyond Japan in developing effective strategies to manage ozone pollution.