Long-term Quantification Research Articles

Long-term quantification of springtime aerosols over Saudi Arabia using multi-satellite remotely sensed data.

A comprehensive analysis of aerosol characteristics over Saudi Arabia from 2005 to 2022, utilizing high-resolution satellite-based observations and reanalysis datasets, examining the distribution of aerosols and their subtypes across the three dimensions (temporal, spatial, and altitude based) for March, April, and May. This study focuses on the analysis of parameters such as aerosol optical depth (AOD), angstrom exponent (AE), absorption aerosol optical depth (AAOD), and Ultraviolet Aerosol Index (UVAI), revealing significant spatial disparities, with elevated aerosol concentrations in the central and eastern regions and comparatively lower concentrations along the western coastal areas. In this study, the spatial patterns and temporal trends are analyzed through trajectory modeling. The study also investigates the composition of aerosols in various Saudi cities. Aerosols prevailing in a dozen Saudi Arabian cities were systematically categorized into six sub-types, considering their particle size and UV-absorbing properties. Notably, two major aerosol sub-types, absorbing coarse (AC) aerosols (UVAI > 0.25, AE < 0.70) treated as mineral dust and absorbing mixed (AM) aerosols (0.70 < AE < 1.25) along with neutral fine (NF) particles (- 0.5 < UVAI < 0.25, AE > 1.25) treated as urban, predominate across the Kingdom of Saudi Arabia.

Mice with deficiency in Pcdh15, a gene associated with bipolar disorders, exhibit significantly elevated diurnal amplitudes of locomotion and body temperature

Genetic factors significantly affect the pathogenesis of psychiatric disorders. However, the specific pathogenic mechanisms underlying these effects are not fully understood. Recent extensive genomic studies have implicated the protocadherin-related 15 (PCDH15) gene in the onset of psychiatric disorders, such as bipolar disorder (BD). To further investigate the pathogenesis of these psychiatric disorders, we developed a mouse model lacking Pcdh15. Notably, although PCDH15 is primarily identified as the causative gene of Usher syndrome, which presents with visual and auditory impairments, our mice with Pcdh15 homozygous deletion (Pcdh15-null) did not exhibit observable structural abnormalities in either the retina or the inner ear. The Pcdh15-null mice showed very high levels of spontaneous motor activity which was too disturbed to perform standard behavioral testing. However, the Pcdh15 heterozygous deletion mice (Pcdh15-het) exhibited enhanced spontaneous locomotor activity, reduced prepulse inhibition, and diminished cliff avoidance behavior. These observations agreed with the symptoms observed in patients with various psychiatric disorders and several mouse models of psychiatric diseases. Specifically, the hyperactivity may mirror the manic episodes in BD. To obtain a more physiological, long-term quantification of the hyperactive phenotype, we implanted nano tag® sensor chips in the animals, to enable the continuous monitoring of both activity and body temperature. During the light-off period, Pcdh15-null exhibited elevated activity and body temperature compared with wild-type (WT) mice. However, we observed a decreased body temperature during the light-on period. Comprehensive brain activity was visualized using c-Fos mapping, which was assessed during the activity and temperature peak and trough. There was a stark contrast between the distribution of c-Fos expression in Pcdh15-null and WT brains during both the light-on and light-off periods. These results provide valuable insights into the neural basis of the behavioral and thermal characteristics of Pcdh15-deletion mice. Therefore, Pcdh15-deletion mice can be a novel model for BD with mania and other psychiatric disorders, with a strong genetic component that satisfies both construct and surface validity.

Scaling of stochastic growth and division dynamics: A comparative study of individual rod-shaped cells in the Mother Machine and SChemostat platforms.

Microfluidic platforms enable long-term quantification of stochastic behaviors of individual bacterial cells under precisely controlled growth conditions. Yet, quantitative comparisons of physiological parameters and cell behaviors of different microorganisms in different experimental and device modalities is not available due to experiment-specific details affecting cell physiology. To rigorously assess the effects of mechanical confinement, we designed, engineered, and performed side-by-side experiments under otherwise identical conditions in the Mother Machine (with confinement) and the SChemostat (without confinement), using the latter as the ideal comparator. We established a protocol to cultivate a suitably engineered rod-shaped mutant of Caulobacter crescentus in the Mother Machine and benchmarked the differences in stochastic growth and division dynamics with respect to the SChemostat. While the single-cell growth rate distributions are remarkably similar, the mechanically confined cells in the Mother Machine experience a substantial increase in interdivision times. However, we find that the division ratio distribution precisely compensates for this increase, which in turn reflects identical emergent simplicities governing stochastic intergenerational homeostasis of cell sizes across device and experimental configurations, provided the cell sizes are appropriately mean-rescaled in each condition. Our results provide insights into the nature of the robustness of the bacterial growth and division machinery.

Detection and long-term quantification of methane emissions from an active landfill

Abstract. Landfills are a significant source of fugitive methane (CH4) emissions, which should be precisely and regularly monitored to reduce and mitigate net greenhouse gas emissions. In this study, we present long-term, in situ, near-surface, mobile atmospheric CH4 mole fraction measurements (complemented by meteorological measurements from a fixed station) from 21 campaigns that cover approximately 4 years from September 2016 to December 2020. These campaigns were utilized to regularly quantify the total CH4 emissions from an active landfill in France. We use a simple atmospheric inversion approach based on a Gaussian plume dispersion model to derive CH4 emissions. Together with the measurements near the soil surface, mainly dedicated to the identification of sources within the landfill, measurements of CH4 made on the landfill perimeter (near-field) helped us to identify the main emission areas and to provide some qualitative insights about the rank of their contributions to total emissions from the landfill. The two main area sources correspond, respectively, to a covered waste sector with infrastructure with sporadic leakages (such as wells, tanks, pipes, etc.) and to the last active sector receiving waste during most of the measurement campaigns. However, we hardly managed to extract a signal representative of the overall landfill emissions from the near-field measurements, which limited our ability to derive robust estimates of the emissions when assimilating them in the atmospheric inversions. The analysis shows that the inversions based on the measurements from a remote road further away from the landfill (far-field) yielded reliable estimates of the total emissions but provided less information on the spatial variability of emissions within the landfill. This demonstrates the complementarity between the near- and far-field measurements. According to these inversions, the total CH4 emissions have a large temporal variability and range from ∼ 0.4 to ∼ 7 t CH4 d−1, with an average value of ∼ 2.1 t CH4 d−1. We find a weak negative correlation between these estimates of the CH4 emissions and atmospheric pressure for the active landfill. However, this weak emission–pressure relationship is based on a relatively small sample of reliable emission estimates with large sampling gaps. More frequent robust estimations are required to better understand this relationship for an active landfill.

Long-term quantification of pre and post-monsoon surface water area of Bangladesh

Since the 1990s, about 70 percent of the world's wetland ecosystem have been lost, despite the acknowledged contribution of surface waters to human well-being. Surface water is a prerequisite for agriculture, fisheries, and other human activities. It also significantly impacts the groundwater reserve, soil conditions, the environment, and the surrounding area's ecology. Bangladesh's population and economic expansion have increased the need for water resources. Therefore, monitoring the spatial and temporal distribution of surface water resources is essential. The present study used more than 2700 Landsat scenes from 1990 to 2020 to quantify the total surface water area utilizing the strength of cloud computing in the Google Earth Engine platform. Mann-Kendall trend analysis was performed to understand the trend of the surface water area. In 1990 the total pre-monsoon and post-monsoon surface water areas were 7994.91 km2 and 11453.43 km2 which is 5.38% and 7.71% of the total countries area, respectively. In 2010 and 2020, the water area was 10748.61 km2 (7.24%) and 10313.49 km2 (6.94%), respectively, in the pre-monsoon; and 10794.05 km2 (7.27%) and 15570.36 km2 (10.48%) respectively in the post-monsoon season. The overall change between 2020 and 1990 is 7994.91 km2 (1.89%) in the pre-monsoon season and 4116.93 (2.77%) in the post-monsoon season. The maximum average surface water area in the post-monsoon season was found in Sylhet (22.68%), followed by Khulna (14.52%). Rangpur was found to have the least average surface water area in both seasons (2.85% and 3.57%). Coastal regions showed a significant increasing trend in the surface water area in the pre-monsoon and post-monsoon seasons. These findings have significant implications for sustainable surface water management decisions, priority interventions, legal frameworks, and public policies to conserve valuable surface water resources in Bangladesh.

Using artificial intelligence for global solar radiation modeling from meteorological variables

Long-term quantification of solar energy variables at ground level is not easily achievable in many locations. In order to overcome this limitation, use of artificial intelligence such as the application of machine learning methods is commonly used for solar irradiance prediction.In this context, this study proposes the implementation of artificial neural networks as deep learning and the XGBoost algorithm as a machine learning method for modeling the hourly global solar radiation for a humid climate such as the Rabat region. For this purpose, hourly meteorological data from the city of Rabat in Morocco are chosen in order of importance using the random forests method, for training and testing the models, namely date and time, sunshine duration, temperature, relative humidity, wind speed/direction and pressure. Subsequently, models are selected after the validation phase for testing, whose performance is evaluated using relevant statistical indicators. As a result, we retain 2 ANN and 1 XGBoost models which are eventually very close in terms of performance with a coefficient of determination value equal to 98% and 97% respectively. However, statistical indicators have proven to be effective in assessing the accuracy and fidelity of each model.Ultimately, the intent of the modeling in terms of accuracy, simplicity or fidelity is a crucial factor in the selection of the model algorithm to adopt.

In-Depth Method Investigation for Determination of Boron in Silicate Samples Using an Improved Boron-Mannitol Complex Digestion Method by Inductively Coupled Plasma Mass Spectrometry.

In this paper, a boron-mannitol complex wet acid digestion method proposed for the accurate determination of boron in silicate samples by inductively coupled plasma mass spectrometry (ICP-MS) was investigated in detail for the first time. With the addition of 50 μL of mannitol (2% wt.) into the mixture of 0.6 mL of concentrated HF and 30 μL of concentrated HNO3, the 50 mg of silicate sample was effectively decomposed after being heated overnight with optional pre-ultrasonic treatment. Following fluoride formation prevention by 8% HNO3 (wt.) and fluoride decomposition using 6% HCl (wt.), the samples were fluxed in 2.0 mL of 40% HNO3 (wt.) for 4 h and aged overnight. By diluting 1000-fold using 2% HNO3 (wt.) solution, the samples were directly quantified by an ICP-MS, showing boron recoveries of the standard materials including diabase W-2, basalt JB-2a, and rhyolite JR-2 in the range of 95.5-105.5% (n = 5). For this wet acid method, it was found that the contents of boron had no obvious difference under digestion temperatures of 65, 100, and 140 °C. It was also found that the ICP-MS quantification accuracy deteriorated at the mass of 11B when boron content was about 7250 ng yielding positive bias with average recoveries of 115.5-119.8% (n = 5), while the determination results remained unaffected at the mass of 10B. Furthermore, the digestion efficiency of boron by laboratory high-pressure closed digestion method was assessed. The boron recoveries with samples treated by the high-pressure closed digestion method were found to vary within 49.5-98.0% (n = 5) and even lowered down to 31.1% when skipping pressure relief procedure. The long-term quantification stability study showed that the boron content generally declined in one month for the high-pressure closed digestion method and exhibited no significant changes for the proposed method. By applying such an improved boron-mannitol complex digestion method, the boron concentration in the studied silicate standard materials were accurately determined, providing critical data for further boron isotope analyses and associated geochemical studies. This in-depth method investigation for silicate boron determination demonstrates the feasibility of this boron-mannitol complex strategy under a wide digestion temperature of 65-140 °C, and also sheds light on the extensive applications of boron as a geological tracer.

Long-term quantification of the intensity of clay-sized particles transfers due to earthworm bioturbation and eluviation/illuviation in a cultivated Luvisol

As a result of the limited knowledge on eluviation/illuviation and bioturbation rates, these two processes of soil particles translocation are qualitatively described either as synergic or competing processes. Here we take the opportunity of the recent development of an image analysis procedure to quantify illuvial clay and earthworm’s porosity to quantify the intensity of illuviation and bioturbation cumulated over soil formation in a temperate cultivated Luvisol. The key objectives of the study are i) to quantify the total intensity of illuviation and bioturbation and their depth distributions and ii) to assess the possibility for bioturbation to limit or compensate the depletion of the clay-sized fraction in topsoil horizons due to eluviation. The total quantity of illuvial clay is 1,100 t.ha−1 while the estimated annual amount of clay-sized fraction translocated by eluviation is between 0.08 and 1 t ha−1 yr−1. This is comparable to the annual loss of land by water erosion (between 1 and 5 t ha−1 yr−1) or by arable erosion (3.3 t ha−1 yr−1). Eluviation/illuviation is thus a discrete and active form of soil loss. With approximately 1,900 t.ha−1 of clay-sized fraction, the amount of fine particles displaced at least once by bioturbation is higher than the one related to eluviation/illuviation. At first sight, it therefore seems possible for biological activity to compensate for vertical transfers of the clay-sized fraction by eluviation/illuviation. However, our study shows that a considerable amount of the clay-sized fraction will never be brought up by the bioturbation and will remain definitively lost for the surface horizons as bioturbation decreases non-linearly with depth. Consequently, a preventive management of the depletion of the clay-sized fraction in topsoil horizons by eluviation/illuviation should be preferred to the curative management of its consequences by bioturbation.

Long term detection and quantification of SARS-CoV-2 RNA in wastewater in Bahrain

Wastewater-based epidemiology is a corroborated environmental surveillance tool in the global fight against SARS-CoV-2. The analysis of wastewater for detection of SARS-CoV-2 RNA may assist policymakers to survey a specific infectious community. Herein, we report on a long-term quantification study in Bahrain to investigate the incidence of the SARS-CoV-2 RNA in wastewater during the COVID-19 pandemic. The ∼260,000 population of Muharraq Island in Bahrain is served by a discrete sewerage catchment, and all wastewater flows to a single large Sewage Treatment Plant (STP) with a capacity of 100,000 m3/day. The catchment is predominately domestic, but also serves several hospitals and Bahrain's international airport. Flow-weighted 24-h composite wastewater samples for the period February 2020 to October 2021 were analyzed for the presence of SARS-CoV-2 N1, N2 and E genes. A Spearman rank correlation demonstrated a moderate correlation between the concentration of SARS-CoV-2 N1, N2 and E genes in the wastewater samples and the number of COVID-19 cases reported on the same day of the sampling.SARS-CoV-2 viral genes were detected in wastewater samples shortly after the first cases of COVID-19 were reported by the health authorities in Bahrain by reverse transcription–polymerase chain reaction (RT-qPCR). The viral genes were detected in 55 of 65 samples (84.62%) during the whole study period and the concentration range was found to be between 0 and 11,508 RNA copies/mL across the viral genes tested (in average N1: 518.4, N2: 366.8 and E: 649.3 copies/mL). Furthermore, wastewater samples from two COVID-19-dedicated quarantine facilities were analysed and detected higher SARS-CoV-2 gene concentrations (range 27-19,105 copies/mL; in average N1: 5044, N2: 4833 and E: 8663 copies/mL). Our results highlight the potential use of RT-qPCR for SARS-CoV-2 detection and quantification in wastewater and present the moderate correlation between concentration of SARS-CoV-2 genes with reported COVID-19 cases for a specified population. Indeed, this study identifies this technique as a mechanism for long term monitoring of SARS-CoV-2 infection levels and hence provides public health and policymakers with a useful environmental surveillance tool during and after the current pandemic.

Long-term tracking and quantification of individual behavior in bumble bee colonies

Social insects are ecologically dominant and provide vital ecosystem services. It is critical to understand collective responses of social insects such as bees to ecological perturbations. However, studying behavior of individual insects across entire colonies and across timescales relevant for colony performance (i.e., days or weeks) remains a central challenge. Here, we describe an approach for long-term monitoring of individuals within multiple bumble bee (Bombus spp.) colonies that combines the complementary strengths of multiple existing methods. Specifically, we combine (a) automated monitoring, (b) fiducial tag tracking, and (c) pose estimation to quantify behavior across multiple colonies over a 48 h period. Finally, we demonstrate the benefits of this approach by quantifying an important but subtle behavior (antennal activity) in bumble bee colonies, and how this behavior is impacted by a common environmental stressor (a neonicotinoid pesticide).

Long-term quantification and characterisation of wind farm noise amplitude modulation

The large-scale expansion of wind farms has prompted community debate regarding adverse impacts of wind farm noise (WFN). One of the most annoying and potentially sleep disturbing components of WFN is amplitude modulation (AM). Here we quantified and characterised AM over one year using acoustical and meteorological data measured at three locations near three wind farms. We found that the diurnal variation of outdoor AM prevalence was substantial, whereby the nighttime prevalence was approximately 2 to 5 times higher than the daytime prevalence. On average, indoor AM occurred during the nighttime from 1.1 to 1.7 times less often than outdoor AM, but the indoor AM depth was higher than that measured outdoors. We observed an association between AM prevalence and sunset and sunrise. AM occurred more often during downwind and crosswind conditions. These findings provide important insights into long term WFN characteristics that will help to inform future WFN assessment guidelines.

A Reliable U-trough Runoff Collection Method for Quantifying the Migration Loads of Nutrients at Different Soil Layers under Natural Rainfall

Long-term quantification of the migration loads of subsurface runoff (SSR) and its collateral soil nutrients among different soil layers are still restricted by the runoff collection method. This study tested the reliability of the U-trough collection methods (UCM), compared with the seepage plate collection method (SPM), in monitoring the runoff, sediment and nutrient migration loads from different soil layers (L1: 0–20 cm depth; L2: 20–40 cm depth; L3: 40–60 cm depth) for two calendar years under natural rainfall events. The results suggested that the U-trough could collect nearly 10 times the SSR sample volume of the seepage plate and keep the sampling probability more than 95% at each soil layer. The annual SSR flux from L1 to L3 was 403.4 mm, 271.9 mm, and 237.4 mm under the UCM, 14.35%, 10.56%, and 8.41% lower than those under the SPM, respectively. The annual net migration loads of sediment, TN, and TP from the L1 layer under the UCM were 49.562 t/km2, 19.113 t/km2 and 0.291 t/km2, and 86.62%, 41.21% and 81.78% of them were intercepted by the subsoil layers (L2 and L3), respectively. While their migration loads under the SPM were 48.708 t/km2, 22.342 t/km2 and 0.291 t/km2, and 88.24%, 53.06% and 80.42% of them were intercepted, respectively. Under both methods, the average leached total n (TN), total p (TP) concentrations per rainfall event and their annual migrated loads at each soil layer showed no significant difference. In conclusion, the UCM was a reliable quantitative method for subsurface runoff, sediment, and soil nutrient migration loads from diverse soil layers of purple soil sloping cultivated lands. Further studies are needed to testify the availability in other lands.

Examining the utility of continuously quantified Darcy fluxes through the use of periodic temperature time series

Fluxes across the groundwater-surface water interface are spatially and temporally variable, difficult to observe and measure, and play a major role in regulating ecological habitat distributions, water quality, and water quantity. The long-term quantification of these fluxes is difficult as field conditions dictate when data can be collected. Ultimately there is a pressing necessity to quantify these long-term flow regimes, as impacts from a changing climate are altering the timing and extent of key groundwater-surface water interactions. The use of periodic temperature time series data is one method that can be utilized to capture these fluxes over long periods of time. Long term deployment of temperature sensors, continuously logging temperature time series data, can be leveraged into time-varying Darcy fluxes via time series analysis and the advection–dispersion equation. However, as hydrologic boundary conditions change, fluxes transition in both magnitude and direction and these temperature time series-based methods are less capable of accurately quantifying fluxes. Real world data taken from five existing United States Geological Survey paired stream gages and riparian groundwater wells sites were used as boundary conditions to inform a one-dimensional heat and mass transport model, with the simulated temperatures used to quantify Darcy fluxes through time. Comparing the Darcy fluxes found using Darcy's Law and the estimated Darcy fluxes from the use of heat as an environmental tracer, periodic temperature time series derived fluxes accurately matched those derived from Darcy's law at three of the sites. For the remaining two sites, hydrologic conditions resulted in erroneous flux estimates, allowing for the identification of specific conditions where temperature time series methods relying on a periodic signal cannot be applied.

Immune-Endocrine Links to Gregariousness in Wild House Mice.

Social interactions are critically important for survival and impact overall-health, but also impose costs on animals, such as exposure to contagious agents. The immune system can play a critical role in modulating social behavior when animals are sick, as has been demonstrated within the context of “sickness behaviors.” Can immune molecules affect or be affected by social interactions even when animals are not sick, therefore serving a role in mediating pathogen exposure? We tested whether markers of immune function in both the blood and the brain are associated with gregariousness, quantified as number of animals interacted with per day. To do this, we used remote tracking of social interactions of a wild population of house mice (Mus musculus domesticus) to categorize animals in terms of gregariousness. Blood, hair, brain and other tissue samples from animals with extreme gregariousness phenotypes were collected. We then tested whether the levels of three important cytokines (TNF-α, IFN-γ and IL-1β) in the serum, cortex and hypothalamus of these animals could be explained by the gregariousness phenotype and/or sex of the mice. Using the hair as a long-term quantification of steroid hormones, we also tested whether corticosterone, progesterone and testosterone differed by social phenotype. We found main effects of gregariousness and sex on the serum levels of TNF-α, but not on IFN-γ or IL-1β. Brain gene expression levels were not different between phenotypes. All hair steroids tended to be elevated in animals of high gregariousness phenotype, independent of sex. In sum, elements of the immune system may be associated with gregariousness, even outside of major disease events. These results extend our knowledge of the role that immune signals have in contributing to the regulation of social behaviors outside periods of illness.

In vivo monitoring of tissue regeneration using a ratiometric lysosomal AIE probe.

Tissue regeneration is a crucial self-renewal capability involving many complex biological processes. Although transgenic techniques and fluorescence immunohistochemical staining have promoted our understanding of tissue regeneration, simultaneous quantification and visualization of tissue regeneration processes is not easy to achieve. Herein, we developed a simple and quantitative method for the real-time and non-invasive observation of the process of tissue regeneration. The synthesized ratiometric aggregation-induced-emission (AIE) probe exhibits high selectivity and reversibility for pH responses, good ability to map lysosomal pH both in vitro and in vivo, good biocompatibility and excellent photostability. The caudal fin regeneration of a fish model (medaka larvae) was monitored by tracking the lysosomal pH change. It was found that the mean lysosomal pH is reduced during 24–48 hpa to promote the autophagic activity for cell debris degradation. Our research can quantify the changes in mean lysosomal pH and also exhibit its distribution during the caudal fin regeneration. We believe that the AIE-active lysosomal pH probe can also be potentially used for long-term tracking of various lysosome-involved biological processes, such as tracking the stress responses of tissue, tracking the inflammatory responses, and so on.

Robust Longitudinal Ankle Edema Assessment Using Wearable Bioimpedance Spectroscopy.

We present a robust methodology for tracking ankle edema longitudinally based on bioimpedance spectroscopy (BIS). We designed a miniaturized BIS measurement system and employed a novel calibration method that enables accurate, high-resolution measurements with substantially lower power consumption than conventional approaches. Using this state-of-the-art wearable BIS measurement system, we developed a differential measurement technique for robust assessment of ankle edema. This technique addresses many of the major challenges in longitudinal BIS-based edema assessment, including day-to-day variability in electrode placement, positional/postural variability, and intersubject variability. We first evaluated the hardware in bench-top testing, and determined the error of the bioimpedance measurements to be 0.4 Ω for the real components and 0.54 Ω for the imaginary components with a resolution of 0.2 Ω. We then validated the hardware and differential measurement technique in: 1) an ex vivo, fresh-frozen, cadaveric limb model, and 2) a cohort of 11 human subjects for proof of concept (eight healthy controls and five subjects with recently acquired acute unilateral ankle injury). The hardware design, with novel calibration methodology, and differential measurement technique can potentially enable long-term quantification of ankle edema throughout the course of rehabilitation following acute ankle injuries. This could lead to better-informed decision making regarding readiness to return to activities and/or tailoring of rehabilitation activities to an individual's changing needs.

A database of atmospheric nitrogen concentration and deposition from the nationwide monitoring network in China

Atmospheric nitrogen (N) deposition has increased substantially across China since 1980; however, data for N deposition fluxes since the 2000s has been very limited. Understanding and mitigating the impacts of N deposition requires long-term quantification of dry as well as wet deposition of key reactive nitrogen (Nr) species. Here we present a dataset for inorganic N concentrations and deposition for the period 2010–2015 in China, compiled from the nationwide deposition monitoring network. The dataset comprises information from 32 monitoring sites on concentrations and bulk deposition (wet plus part of dry deposition) fluxes of NH4+-N and NO3−-N, air concentrations and dry deposition fluxes of the major Nr species NH3, NO2, HNO3, and particulate NH4+ and NO3−. This unique database is available inter alia to advance understanding of the spatial patterns of inorganic N concentrations and deposition in China and its associated effects, constrain primary Nr (e.g., NH3, NOx) emission inventories, and validate outputs of atmospheric chemistry and transport models.

A long-term source apportionment of PM2.5 in New York State during 2005–2016

The development and implementation of effective policies for controlling PM2.5 mass concentrations and protecting human health depend upon the identification and apportionment of its sources. In this study, the PM2.5 sources affecting 6 urban and 2 rural sites across New York State during the period 2005–2016 were determined. The extracted profiles were compared to identify state-wide common profiles. The source contributions provide detailed, long-term quantification of the emission sources across the state during the investigated period (2005–2016). Seven factors were common to all sites: secondary sulfate, secondary nitrate, spark-ignition emissions, diesel emissions, road dust, biomass burning, and pyrolyzed organic (OP) rich. The largest contributors were secondary sulfate, secondary nitrate, spark-ignition (gasoline), diesel, and OP-rich. Secondary sulfate concentrations ranged from 2.3 μg m−3 at Whiteface to 3.2 μg m−3 at Buffalo and the Bronx. The highest secondary sulfate fractional contributions were found at the rural sites (∼46% of PM2.5 mass) also showed the highest OP-rich contributions (∼19%). Secondary nitrate showed the highest concentrations at the urban sites representing ∼17% of PM2.5 mass (1.6 ± 0.3 μg m−3 on average). Urban sites also showed the highest average spark-ignition concentrations (1.7 ± 0.2 μg m−3, ∼18%) and diesel emissions (1.0 ± 0.2 μg m−3, ∼10%). During this period, secondary sulfate concentrations declined likely related to the implementation of mitigation strategies for controlling SO2 emissions and the changing economics of electricity generation. Similarly, diesel and secondary nitrate showed decreases in concentrations likely associated with the introduction of emissions controls and improved quality fuels for heavy-duty diesel on-road trucks and buses. Spark-ignition concentrations showed an increase across the state during 2014–2016 associated with the increase of registered vehicles in New York State.

Reversible and long-term immobilization in a hydrogel-microbead matrix for high-resolution imaging of Caenorhabditis elegans and other small organisms.

The nematode Caenorhabditis elegans is an important model organism for biomedical research and genetic studies relevant to human biology and disease. Such studies are often based on high-resolution imaging of dynamic biological processes in the worm body tissues, requiring well-immobilized and physiologically active animals in order to avoid movement-related artifacts and to obtain meaningful biological information. However, existing immobilization methods employ the application of either anesthetics or servere physical constraints, by using glue or specific microfluidic on-chip mechanical structures, which in some cases may strongly affect physiological processes of the animals. Here, we immobilize C. elegans nematodes by taking advantage of a biocompatible and temperature-responsive hydrogel-microbead matrix. Our gel-based immobilization technique does not require a specific chip design and enables fast and reversible immobilization, thereby allowing successive imaging of the same single worm or of small worm populations at all development stages for several days. We successfully demonstrated the applicability of this method in challenging worm imaging contexts, in particular by applying it for high-resolution confocal imaging of the mitochondrial morphology in worm body wall muscle cells and for the long-term quantification of number and size of specific protein aggregates in different C. elegans neurodegenerative disease models. Our approach was also suitable for immobilizing other small organisms, such as the larvae of the fruit fly Drosophila melanogaster and the unicellular parasite Trypanosoma brucei. We anticipate that this versatile technique will significantly simplify biological assay-based longitudinal studies and long-term observation of small model organisms.

Ongoing changes in migration phenology and winter residency at Bracken Bat Cave.

Bats play an important role in agroecology and are effective bioindicators of environmental conditions, but little is known about their fundamental migration ecology, much less how these systems are responding to global change. Some of the world's largest bat populations occur during the summer in the south-central United States, when millions of pregnant females migrate from lower latitudes to give birth in communal maternity colonies. Despite a relatively large volume of research into these colonies, many fundamental questions regarding their abundance-including their intra- and interseasonal variability-remain unanswered, and even estimating the size of individual populations has been a long-running challenge. Overall, monitoring these bat populations at high temporal resolution (e.g., nightly) and across long time spans (e.g., decades) has been impossible. Here, we show 22 continuous years of nightly population counts at Bracken Cave, a large bat colony in south-central Texas, enabling the first climate-scale phenological analysis. Using quantitative radar monitoring, we found that spring migration and the summer reproductive cycle have advanced by approximately 2weeks over the study period. Furthermore, we quantify the ongoing growth of a newly-established overwintering population that indicates a system-wide response to changing environmental conditions. Our observations reveal behavioral plasticity in bats' ability to adapt to changing resource availability, and provide the first long-term quantification of their response to a changing climate. As aerial insectivores, these changes in bat phenology and propensity for overwintering indicate probable shifts in prey availability, with clear implications for pest management across wider regional agrisystems.