Domains and domain walls are critical in determining the response of ferroelectrics, and the ability to controllably create, annihilate, or move domains is essential to enable a range of ...next-generation devices. Whereas electric-field control has been demonstrated for ferroelectric 180° domain walls, similar control of ferroelastic domains has not been achieved. Here, using controlled composition and strain gradients, we demonstrate deterministic control of ferroelastic domains that are rendered highly mobile in a controlled and reversible manner. Through a combination of thin-film growth, transmission-electron-microscopy-based nanobeam diffraction and nanoscale band-excitation switching spectroscopy, we show that strain gradients in compositionally graded PbZr1-xTixO3 heterostructures stabilize needle-like ferroelastic domains that terminate inside the film. These needle-like domains are highly labile in the out-of-plane direction under applied electric fields, producing a locally enhanced piezoresponse. This work demonstrates the efficacy of novel modes of epitaxy in providing new modalities of domain engineering and potential for as-yet-unrealized nanoscale functional devices.
Soils have been identified as a major source (~15%) of global nitrogen oxide (NOx) emissions. Parameterizations of soil NOx emissions (SNOx) commonly used in the current generation of chemical ...transport models were designed to capture mean seasonal behaviour. These parameterizations do not, however, respond quantitatively to the meteorological triggers that are observed to result in pulsed SNOx. Here we present a new parameterization of SNOx implemented within a global chemical transport model (GEOS-Chem). The parameterization represents available nitrogen (N) in soils using biome specific emission factors, online wet- and dry-deposition of N, and fertilizer and manure N derived from a spatially explicit dataset, distributed using seasonality derived from data obtained by the Moderate Resolution Imaging Spectrometer. Moreover, it represents the functional form of emissions derived from point measurements and ecosystem scale experiments including pulsing following soil wetting by rain or irrigation, and emissions that are a smooth function of soil moisture as well as temperature between 0 and 30 °C. This parameterization yields global above-soil SNOx of 10.7 Tg N yr−1, including 1.8 Tg N yr−1 from fertilizer N input (1.5% of applied N) and 0.5 Tg N yr−1 from atmospheric N deposition. Over the United States (US) Great Plains region, SNOx are predicted to comprise 15–40% of the tropospheric NO2 column and increase column variability by a factor of 2–4 during the summer months due to chemical fertilizer application and warm temperatures. SNOx enhancements of 50–80% of the simulated NO2 column are predicted over the African Sahel during the monsoon onset (April–June). In this region the day-to-day variability of column NO2 is increased by a factor of 5 due to pulsed-N emissions. We evaluate the model by comparison with observations of NO2 column density from the Ozone Monitoring Instrument (OMI). We find that the model is able to reproduce the observed interannual variability of NO2 (induced by pulsed-N emissions) over the US Great Plains. We also show that the OMI mean (median) NO2 observed during the overpass following first rainfall over the Sahel is 49% (23%) higher than in the five days preceding. The measured NO2 on the day after rainfall is still 23% (5%) higher, providing a direct measure of the pulse's decay time of 1–2 days. This is consistent with the pulsing representation used in our parameterization and much shorter than 5–14 day pulse decay length used in current models.
Concern is growing about the effects of urbanization on air pollution and health. Nitrogen dioxide (NO2) released primarily from combustion processes, such as traffic, is a short-lived atmospheric ...pollutant that serves as an air-quality indicator and is itself a health concern. We derive a global distribution of ground-level NO2 concentrations from tropospheric NO2 columns retrieved from the Ozone Monitoring Instrument (OMI). Local scaling factors from a three-dimensional chemistry-transport model (GEOS-Chem) are used to relate the OMI NO2 columns to ground-level concentrations. The OMI-derived surface NO2 data are significantly correlated (r = 0.69) with in situ surface measurements. We examine how the OMI-derived ground-level NO2 concentrations, OMI NO2 columns, and bottom-up NO x emission inventories relate to urban population. Emission hot spots, such as power plants, are excluded to focus on urban relationships. The correlation of surface NO2 with population is significant for the three countries and one continent examined here: United States (r = 0.71), Europe (r = 0.67), China (r = 0.69), and India (r = 0.59). Urban NO2 pollution, like other urban properties, is a power law scaling function of the population size: NO2 concentration increases proportional to population raised to an exponent. The value of the exponent varies by region from 0.36 for India to 0.66 for China, reflecting regional differences in industrial development and per capita emissions. It has been generally established that energy efficiency increases and, therefore, per capita NO x emissions decrease with urban population; here, we show how outdoor ambient NO2 concentrations depend upon urban population in different global regions.
With power conversion efficiencies of perovskite-on-silicon and all-perovskite tandem solar cells increasing at rapid pace, wide bandgap (>1.7 eV) metal-halide perovskites (MHPs) are becoming a major ...focus of academic and industrial photovoltaic research. Compared to their lower bandgap (≤1.6 eV) counterparts, these types of perovskites suffer from higher levels of non-radiative losses in both the bulk material and in device configurations, constraining their efficiencies far below their thermodynamic potential. In this work, we investigate the energy losses in methylammonium (MA) free high-Br-content wide bandgap perovskites by using a combination of THz spectroscopy, steady-state and time-resolved photoluminescence, coupled with drift-diffusion simulations. The investigation of this system allows us to study charge-carrier recombination in these materials and devices in the absence of halide segregation due to the photostabilty of formamidinium-cesium based lead halide perovskites. We find that these perovskites are characterised by large non-radiative recombination losses in the bulk material and that the interfaces with transport layers in solar cell devices strongly limit their open-circuit voltage. In particular, we discover that the interface with the hole transport layer performs particularly poorly, in contrast to 1.6 eV bandgap MHPs which are generally limited by the interface with the electron-transport layer. To overcome these losses, we incorporate and investigate the recombination mechanisms present with perovskites treated with the ionic additive 1-butyl-1-methylpipiderinium tetrafluoroborate. We find that this additive not only improves the radiative efficiency of the bulk perovskite, but also reduces the non-radiative recombination at both the hole and electron transport layer interfaces of full photovoltaic devices. In addition to unravelling the beneficial effect of this specific treatment, we further optimise our solar cells by introducing an additional LiF interface treatment at the electron transport layer interface. Together these treatments enable MA-free 1.79 eV bandgap perovskite solar cells with open-circuit voltages of 1.22 V and power conversion efficiencies approaching 17%, which is among the highest reported for this material system.
We identify the limiting factors of wide bandgap metal halide perovskite solar cells. To overcome these losses, we developed an efficient optimisation strategy and outline the necessary steps for the continued development of these perovskites.
Ambient fine particulate matter (PM2.5) is a leading environmental risk factor for premature mortality. We use aerosol optical depth (AOD) retrieved from two satellite instruments, MISR and SeaWiFS, ...to produce a unified 15-year global time series (1998–2012) of ground-level PM2.5 concentration at a resolution of 1° x 1°. The GEOS-Chem chemical transport model (CTM) is used to relate each individual AOD retrieval to ground-level PM2.5. Four broad areas showing significant, spatially coherent, annual trends are examined in detail: the Eastern U.S. (−0.39 ± 0.10 μg m–3 yr–1), the Arabian Peninsula (0.81 ± 0.21 μg m–3 yr–1), South Asia (0.93 ± 0.22 μg m–3 yr–1) and East Asia (0.79 ± 0.27 μg m–3 yr–1). Over the period of dense in situ observation (1999–2012), the linear tendency for the Eastern U.S. (−0.37 ± 0.13 μg m–3 yr–1) agrees well with that from in situ measurements (−0.38 ± 0.06 μg m–3 yr–1). A GEOS-Chem simulation reveals that secondary inorganic aerosols largely explain the observed PM2.5 trend over the Eastern U.S., South Asia, and East Asia, while mineral dust largely explains the observed trend over the Arabian Peninsula.
In 1985, the Rockefeller Foundation published Good health at low cost to discuss why some countries or regions achieve better health and social outcomes than do others at a similar level of income ...and to show the role of political will and socially progressive policies. 25 years on, the Good Health at Low Cost project revisited these places but looked anew at Bangladesh, Ethiopia, Kyrgyzstan, Thailand, and the Indian state of Tamil Nadu, which have all either achieved substantial improvements in health or access to services or implemented innovative health policies relative to their neighbours. A series of comparative case studies (2009–11) looked at how and why each region accomplished these changes. Attributes of success included good governance and political commitment, effective bureaucracies that preserve institutional memory and can learn from experience, and the ability to innovate and adapt to resource limitations. Furthermore, the capacity to respond to population needs and build resilience into health systems in the face of political unrest, economic crises, and natural disasters was important. Transport infrastructure, female empowerment, and education also played a part. Health systems are complex and no simple recipe exists for success. Yet in the countries and regions studied, progress has been assisted by institutional stability, with continuity of reforms despite political and economic turmoil, learning lessons from experience, seizing windows of opportunity, and ensuring sensitivity to context. These experiences show that improvements in health can still be achieved in countries with relatively few resources, though strategic investment is necessary to address new challenges such as complex chronic diseases and growing population expectations.
Retrievals of tropospheric nitrogen dioxide (NO2) from the Ozone Monitoring Instrument (OMI) are subject to errors in the treatments of aerosols, surface reflectance anisotropy, and vertical profile ...of NO2. Here we quantify the influences over China via an improved retrieval process. We explicitly account for aerosol optical effects (simulated by nested GEOS-Chem at 0.667 degree long. 0.5 degree lat. and constrained by aerosol measurements), surface reflectance anisotropy, and high-resolution vertical profiles of NO2 (simulated by GEOS-Chem). Prior to the NO2 retrieval, we derive the cloud information using consistent ancillary assumptions. We compare our retrieval to the widely used DOMINO v2 product, using MAX-DOAS measurements at three urban/suburban sites in East China as reference and focusing the analysis on the 127 OMI pixels (in 30 days) closest to the MAX-DOAS sites. We find that our retrieval reduces the interference of aerosols on the retrieved cloud properties, thus enhancing the number of valid OMI pixels by about 25%. Compared to DOMINO v2, our retrieval better captures the day-to-day variability in MAX-DOAS NO2 data (R2 = 0.96 versus 0.72), due to pixel-specific radiative transfer calculations rather than the use of a look-up table, explicit inclusion of aerosols, and consideration of surface reflectance anisotropy. Our retrieved NO2 columns are 54% of the MAX-DOAS data on average, reflecting the inevitable spatial inconsistency between the two types of measurement, errors in MAX-DOAS data, and uncertainties in our OMI retrieval related to aerosols and vertical profile of NO2. Sensitivity tests show that excluding aerosol optical effects can either increase or decrease the retrieved NO2 for individual OMI pixels with an average increase by 14%. Excluding aerosols also complexly affects the retrievals of cloud fraction and particularly cloud pressure. Employing various surface albedo data sets slightly affects the retrieved NO2 on average (within 10%). The retrieved NO2 columns increase when the NO2 profiles are taken from MAX-DOAS retrievals (by 19% on average) or TM4 simulations (by 13%) instead of GEOS-Chem simulations. Our findings are also relevant to retrievals of other pollutants (e.g., sulfur dioxide, ormaldehyde, glyoxal) from UV-visible backscatter satellite instruments.
Postpartum Depression Disorder (PPDD) is a prevalent mental health condition and results in severe depression and suicide attempts in the social community. Prompt actions are crucial in tackling ...PPDD, which requires a quick recognition and accurate analysis of the probability factors associated with this condition. This concern requires attention. The primary aim of our research is to investigate the feasibility of anticipating an individual's mental state by categorizing individuals with depression from those without depression using a dataset consisting of text along with audio recordings from patients diagnosed with PPDD. This research proposes a hybrid PPDD framework that combines Improved Bi-directional Long Short-Term Memory (IBi-LSTM) with Transfer Learning (TL) based on two Convolutional Neural Network (CNN) architectures, respectively CNN-text and CNN audio. In the proposed model, the CNN section efficiently utilizes TL to obtain crucial knowledge from text and audio characteristics, whereas the improved Bi-LSTM module combines written material and sound data to obtain intricate chronological interpersonal relationships. The proposed model incorporates an attention technique to augment the effectiveness of the Bi-LSTM scheme. An experimental analysis is conducted on the PPDD online textual and speech audio dataset collected from UCI. It includes textual features such as age, women's health tracks, medical histories, demographic information, daily life metrics, psychological evaluations, and 'speech records' of PPDD patients. Data pre-processing is applied to maintain the data integrity and achieve reliable model performance. The proposed model demonstrates a great performance in better precision, recall, accuracy, and F1-score over existing deep learning models, including VGG-16, Base-CNN, and CNN-LSTM. These metrics indicate the model's ability to differentiate among women at risk of PPDD vs. non-PPDD. In addition, the feature importance analysis demonstrates that specific risk factors substantially impact the prediction of PPDD. The findings of this research establish a basis for improved precision and promptness in assessing the risk of PPDD, which may ultimately result in earlier implementation of interventions and the establishment of support networks for women who are susceptible to PPDD.
We use in situ observations from the Interagency Monitoring of PROtected Visual Environments (IMPROVE) network, the Midwest Ammonia Monitoring Project, 11 surface site campaigns as well as Infrared ...Atmospheric Sounding Interferometer (IASI) satellite measurements with the GEOS-Chem model to investigate inorganic aerosol loading and atmospheric ammonia concentrations over the United States. IASI observations suggest that current ammonia emissions are underestimated in California and in the springtime in the Midwest. In California this underestimate likely drives the underestimate in nitrate formation in the GEOS-Chem model. However in the remaining continental United States we find that the nitrate simulation is biased high (normalized mean bias > = 1.0) year-round, except in Spring (due to the underestimate in ammonia in this season). None of the uncertainties in precursor emissions, the uptake efficiency of N2O5 on aerosols, OH concentrations, the reaction rate for the formation of nitric acid, or the dry deposition velocity of nitric acid are able to explain this bias. We find that reducing nitric acid concentrations to 75% of their simulated values corrects the bias in nitrate (as well as ammonium) in the US. However the mechanism for this potential reduction is unclear and may be a combination of errors in chemistry, deposition and sub-grid near-surface gradients. This "updated" simulation reproduces PM and ammonia loading and captures the strong seasonal and spatial gradients in gas-particle partitioning across the United States. We estimate that nitrogen makes up 15−35% of inorganic fine PM mass over the US, and that this fraction is likely to increase in the coming decade, both with decreases in sulfur emissions and increases in ammonia emissions.
We present an approach to infer ground‐level nitrogen dioxide (NO2) concentrations by applying local scaling factors from a global three‐dimensional model (GEOS‐Chem) to tropospheric NO2 columns ...retrieved from the Ozone Monitoring Instrument (OMI) onboard the Aura satellite. Seasonal mean OMI surface NO2 derived from the standard tropospheric NO2 data product (Version 1.0.5, Collection 3) varies by more than two orders of magnitude (<0.1–>10 ppbv) over North America. Two ground‐based data sets are used to validate the surface NO2 estimate and indirectly validate the OMI tropospheric NO2 retrieval: photochemical steady‐state (PSS) calculations of NO2 based on in situ NO and O3 measurements, and measurements from a commercial chemiluminescent NO2 analyzer equipped with a molybdenum converter. An interference correction algorithm for the latter is developed using laboratory and field measurements and applied using modeled concentrations of the interfering species. The OMI‐derived surface NO2 mixing ratios are compared with an in situ surface NO2 data obtained from the U.S. Environmental Protection Agency's Air Quality System (AQS) and Environment Canada's National Air Pollution Surveillance (NAPS) network for 2005 after correcting for the interference in the in situ data. The overall agreement of the OMI‐derived surface NO2 with the corrected in situ measurements and PSS‐NO2 is −11–36%. A larger difference in winter/spring than in summer/fall implies a seasonal bias in the OMI NO2 retrieval. The correlation between the OMI‐derived surface NO2 and the ground‐based measurements is significant (correlation coefficient up to 0.86) with a tendency for higher correlations in polluted areas. The satellite‐derived data base of ground level NO2 concentrations could be valuable for assessing exposures of humans and vegetation to NO2, supplementing the capabilities of the ground‐based networks, and evaluating air quality models and the effectiveness of air quality control strategies.
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