A blind hierarchical coherent search for gravitational-wave signals from coalescing compact binaries in a network of interferometric detectors

We describe a hierarchical data analysis pipeline for coherently searching for gravitational wave (GW) signals from non-spinning compact binary coalescences (CBCs) in the data of multiple earth-based detectors. It assumes no prior information on the sky position of the source or the time of occurrence of its transient signals and, hence, is termed "blind". The pipeline computes the coherent network search statistic that is optimal in stationary, Gaussian noise, and allows for the computation of a suite of alternative statistics and signal-based discriminators that can improve its performance in real data. Unlike the coincident multi-detector search statistics employed so far, the coherent statistics are different in the sense that they check for the consistency of the signal amplitudes and phases in the different detectors with their different orientations and with the signal arrival times in them. The first stage of the hierarchical pipeline constructs coincidences of triggers from the multiple interferometers, by requiring their proximity in time and component masses. The second stage follows up on these coincident triggers by computing the coherent statistics. The performance of the hierarchical coherent pipeline on Gaussian data is shown to be better than the pipeline with just the first (coincidence) stage.Comment: 12 pages, 3 figures, accepted for publication in Classical and Quantum Gravit

Aerosol single scattering albedo dependence on biomass combustion efficiency: Laboratory and field studies

Single scattering albedo (ω) of fresh biomass burning (BB) aerosols produced from 92 controlled laboratory combustion experiments of 20 different woods and grasses was analyzed to determine the factors that control the variability in ω. Results show that ω varies strongly with fire-integrated modified combustion efficiency (MCEFI)—higher MCEFI results in lower ω values and greater spectral dependence of ω. A parameterization of ω as a function of MCEFI for fresh BB aerosols is derived from the laboratory data and is evaluated by field observations from two wildfires. The parameterization suggests that MCEFI explains 60% of the variability in ω, while the 40% unexplained variability could be accounted for by other parameters such as fuel type. Our parameterization provides a promising framework that requires further validation and is amenable for refinements to predict ω with greater confidence, which is critical for estimating the radiative forcing of BB aerosols

Nepal Ambient Monitoring and Source Testing Experiment (NAMaSTE): Emissions of particulate matter and sulfur dioxide from vehicles and brick kilns and their impacts on air quality in the Kathmandu Valley, Nepal

Air pollution is one of the most pressing environmental issues in the Kathmandu Valley, where the capital city of Nepal is located. We estimated emissions from two of the major source types in the valley (vehicles and brick kilns) and analyzed the corresponding impacts on regional air quality. First, we estimated the on-road vehicle emissions in the valley using the International Vehicle Emissions (IVE) model with local emissions factors and the latest available data for vehicle registration. We also identified the locations of the brick kilns in the Kathmandu Valley and developed an emissions inventory for these kilns using emissions factors measured during the Nepal Ambient Monitoring and Source Testing Experiment (NAMaSTE) field campaign in April 2015. Our results indicate that the commonly used global emissions inventory, the Hemispheric Transport of Air Pollution (HTAP_v2.2), underestimates particulate matter emissions from vehicles in the Kathmandu Valley by a factor greater than 100. HTAP_v2.2 does not include the brick sector and we found that our sulfur dioxide (SO2) emissions estimates from brick kilns are comparable to 70 % of the total SO2 emissions considered in HTAP_v2.2. Next, we simulated air quality using the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) for April 2015 based on three different emissions scenarios: HTAP only, HTAP with updated vehicle emissions, and HTAP with both updated vehicle and brick kilns emissions. Comparisons between simulated results and observations indicate that the model underestimates observed surface elemental carbon (EC) and SO2 concentrations under all emissions scenarios. However, our updated estimates of vehicle emissions significantly reduced model bias for EC, while updated emissions from brick kilns improved model performance in simulating SO2. These results highlight the importance of improving local emissions estimates for air quality modeling. We further find that model overestimation of surface wind leads to underestimated air pollutant concentrations in the Kathmandu Valley. Future work should focus on improving local emissions estimates for other major and underrepresented sources (e.g., crop residue burning and garbage burning) with a high spatial resolution, as well as the model\u27s boundary layer representation, to capture strong spatial gradients of air pollutant concentrations

Expanding NEON biodiversity surveys with new instrumentation and machine learning approaches

A core goal of the National Ecological Observatory Network (NEON) is to measure changes in biodiversity across the 30-yr horizon of the network. In contrast to NEON’s extensive use of automated instruments to collect environmental data, NEON’s biodiversity surveys are almost entirely conducted using traditional human-centric field methods. We believe that the combination of instrumentation for remote data collection and machine learning models to process such data represents an important opportunity for NEON to expand the scope, scale, and usability of its biodiversity data collection while potentially reducing long-term costs. In this manuscript, we first review the current status of instrument-based biodiversity surveys within the NEON project and previous research at the intersection of biodiversity, instrumentation, and machine learning at NEON sites. We then survey methods that have been developed at other locations but could potentially be employed at NEON sites in future. Finally, we expand on these ideas in five case studies that we believe suggest particularly fruitful future paths for automated biodiversity measurement at NEON sites: acoustic recorders for sound-producing taxa, camera traps for medium and large mammals, hydroacoustic and remote imagery for aquatic diversity, expanded remote and ground-based measurements for plant biodiversity, and laboratory-based imaging for physical specimens and samples in the NEON biorepository. Through its data science-literate staff and user community, NEON has a unique role to play in supporting the growth of such automated biodiversity survey methods, as well as demonstrating their ability to help answer key ecological questions that cannot be answered at the more limited spatiotemporal scales of human-driven surveys

Speciated online PM1 from South Asian combustion sources-Part 1: Fuel-based emission factors and size distributions

Combustion of biomass, garbage, and fossil fuels in South Asia has led to poor air quality in the region and has uncertain climate forcing impacts. Online measurements of submicron aerosol (PM1) emissions were conducted as part of the Nepal Ambient Monitoring and Source Testing Experiment (NAMaSTE) to investigate and report emission factors (EFs) and vacuum aerodynamic diameter (dva) size distributions from prevalent but poorly characterized combustion sources. The online aerosol instrumentation included a qmini aerosol mass spectrometer (mAMS) and a dual-spot eight-channel aethalometer (AE33). The mAMS measured non-refractory PM1 mass, composition, and size. The AE33-measured black carbon (BC) mass and estimated light absorption at 370 nm due to organic aerosol or brown carbon. Complementary gas-phase measurements of carbon dioxide (CO2), carbon monoxide (CO), and methane (CH4) were collected using a Picarro Inc. cavity ring-down spectrometer (CRDS) to calculate fuel-based EFs using the carbon mass balance approach. The investigated emission sources include open garbage burning, diesel-powered irrigation pumps, idling motorcycles, traditional cookstoves fueled with dung and wood, agricultural residue fires, and coal-fired brick-making kilns, all of which were tested in the field. Open-garbage-burning emissions, which included mixed refuse and segregated plastics, were found to have some of the largest PM1 EFs (3.77-19.8 g k-1) and the highest variability of the investigated emission sources. Non-refractory organic aerosol (OA) size distributions measured by the mAMS from garbage-burning emissions were observed to have lognormal mode dva values ranging from 145 to 380 nm. Particle-phase hydrogen chloride (HCl) was observed from open garbage burning and was attributed to the burning of chlorinated plastics. Emissions from two diesel-powered irrigation pumps with different operational ages were tested during NAMaSTE. Organic aerosol and BC were the primary components of the emissions and the OA size distributions were centered at ∼ 80 nm dva. The older pump was observed to have significantly larger EFOA than the newer pump (5.18 g k-1 compared to 0.45 g k-1) and similar EFBC. Emissions from two distinct types of coal-fired brick-making kilns were investigated. The less advanced, intermittently fired clamp kiln was observed to have relatively large EFs of inorganic aerosol, including sulfate (0.48 g k-1) and ammonium (0.17 g k-1), compared to the other investigated emission sources. The clamp kiln was also observed to have the largest absorption Ångström exponent (AAE Combining double low line 4) and organic carbon (OC) to BC ratio (OC: BC Combining double low line 52). The continuously fired zigzag kiln was observed to have the largest fraction of sulfate emissions with an EFSO4 of 0.96 g k-1. Non-refractory aerosol size distributions for the brick kilns were centered at ∼ 400 nm dva. The biomass burning samples were all observed to have significant fractions of OA and non-refractory chloride; based on the size distribution results, the chloride was mostly externally mixed from the OA. The dung-fueled traditional cookstoves were observed to emit ammonium, suggesting that the chloride emissions were partially neutralized. In addition to reporting EFs and size distributions, aerosol optical properties and mass ratios of OC to BC were investigated to make comparisons with other NAMaSTE results (i.e., online photoacoustic extinctiometer (PAX) and off-line filter based) and the existing literature. This work provides critical field measurements of aerosol emissions from important yet under-characterized combustion sources common to South Asia and the developing world

Ambient air quality in the Kathmandu Valley, Nepal, during the pre-monsoon: Concentrations and sources of particulate matter and trace gases

The Kathmandu Valley in Nepal is a bowl-shaped urban basin that experiences severe air pollution that poses health risks to its 3.5 million inhabitants. As part of the Nepal Ambient Monitoring and Source Testing Experiment (NAMaSTE), ambient air quality in the Kathmandu Valley was investigated from 11 to 24 April 2015, during the premonsoon season. Ambient concentrations of fine and coarse particulate matter (PM2:5 and PM10, respectively), online PM1, inorganic trace gases (NH3, HNO3, SO2, and HCl), and carbon-containing gases (CO2, CO, CH4, and 93 nonmethane volatile organic compounds; NMVOCs) were quantified at a semi-urban location near the center of the valley. Concentrations and ratios of NMVOC indicated origins primarily from poorly maintained vehicle emissions, biomass burning, and solvent/gasoline evaporation. During those 2 weeks, daily average PM2:5 concentrations ranged from 30 to 207 μ g m-3, which exceeded the World Health Organization 24 h guideline by factors of 1.2 to 8.3. On average, the nonwater mass of PM2:5 was composed of organic matter (48 %), elemental carbon (13 %), sulfate (16 %), nitrate (4 %), ammonium (9 %), chloride (2 %), calcium (1 %), magnesium (0.05 %), and potassium (1 %). Large diurnal variability in temperature and relative humidity drove corresponding variability in aerosol liquid water content, the gas-aerosol phase partitioning of NH3, HNO3, and HCl, and aerosol solution pH. The observed levels of gas-phase halogens suggest that multiphase halogen-radical chemistry involving both Cl and Br impacted regional air quality. To gain insight into the origins of organic carbon (OC), molecular markers for primary and secondary sources were quantified. Levoglucosan (averaging 1230±1154 ng m-3), 1,3,5-triphenylbenzene (0:8± 0:6 ng m-3), cholesterol (2:9±6:6 ng m-3), stigmastanol (1.0 ±0:8 ng m-3), and cis-pinonic acid (4:5 ± 1:9 ng m-3) indicate contributions from biomass burning, garbage burning, food cooking, cow dung burning, and monoterpene secondary organic aerosol, respectively. Drawing on source profiles developed in NAMaSTE, chemical mass balance (CMB) source apportionment modeling was used to estimate contributions to OC from major primary sources including garbage burning (18 ± 5 %), biomass burning (17 ± 10 %) inclusive of open burning and biomass-fueled cooking stoves, and internal-combustion (gasoline and diesel) engines (18±9 %). Model sensitivity tests with newly developed source profiles indicated contributions from biomass burning within a factor of 2 of previous estimates but greater contributions from garbage burning (up to three times), indicating large potential impacts of garbage burning on regional air quality and the need for further evaluation of this source. Contributions of secondary organic carbon (SOC) to PM2:5 OC included those originating from anthropogenic precursors such as naphthalene (10 ± 4 %) and methylnaphthalene (0:3 ± 0:1 %) and biogenic precursors for monoterpenes (0:13 ± 0:07 %) and sesquiterpenes (5 ± 2 %). An average of 25 % of the PM2.5 OC was unapportioned, indicating the presence of additional sources (e.g., evaporative and/or industrial emissions such as brick kilns, food cooking, and other types of SOC) and/or underestimation of the contributions from the identified source types. The source apportionment results indicate that anthropogenic combustion sources (including biomass burning, garbage burning, and fossil fuel combustion) were the greatest contributors to PM2:5 and, as such, should be considered primary targets for controlling ambient PM pollution

Nepal Ambient Monitoring and Source Testing Experiment (NAMaSTE): Emissions of trace gases and light-absorbing carbon from wood and dung cooking fires, garbage and crop residue burning, brick kilns, and other sources

The Nepal Ambient Monitoring and Source Testing Experiment (NAMaSTE) campaign took place in and around the Kathmandu Valley and in the Indo-Gangetic Plain (IGP) of southern Nepal during April 2015. The source characterization phase targeted numerous important but undersampled (and often inefficient) combustion sources that are widespread in the developing world such as cooking with a variety of stoves and solid fuels, brick kilns, open burning of municipal solid waste (a.k.a. trash or garbage burning), crop residue burning, generators, irrigation pumps, and motorcycles. NAMaSTE produced the first, or rare, measurements of aerosol optical properties, aerosol mass, and detailed trace gas chemistry for the emissions from many of the sources. This paper reports the trace gas and aerosol measurements obtained by Fourier transform infrared (FTIR) spectroscopy, whole-air sampling (WAS), and photoacoustic extinctiometers (PAX; 405 and 870nm) based on field work with a moveable lab sampling authentic sources. The primary aerosol optical properties reported include emission factors (EFs) for scattering and absorption coefficients (EF Bscat, EF Babs, inm2kg-1 fuel burned), single scattering albedos (SSAs), and absorption Ångström exponents (AAEs). From these data we estimate black and brown carbon (BC, BrC) emission factors (gkg-1 fuel burned). The trace gas measurements provide EFs (gkg-1) for CO2, CO, CH4, selected non-methane hydrocarbons up to C10, a large suite of oxygenated organic compounds, NH3, HCN, NOx, SO2, HCl, HF, etc. (up to ∼ 80 gases in all). The emissions varied significantly by source, and light absorption by both BrC and BC was important for many sources. The AAE for dung-fuel cooking fires (4.63±0.68) was significantly higher than for wood-fuel cooking fires (3.01±0.10). Dung-fuel cooking fires also emitted high levels of NH3 (3.00±1.33gkg-1), organic acids (7.66±6.90gkg-1), and HCN (2.01±1.25gkg-1), where the latter could contribute to satellite observations of high levels of HCN in the lower stratosphere above the Asian monsoon. HCN was also emitted in significant quantities by several non-biomass burning sources. BTEX compounds (benzene, toluene, ethylbenzene, xylenes) were major emissions from both dung- (∼4.5gkg-1) and wood-fuel (∼1.5gkg-1) cooking fires, and a simple method to estimate indoor exposure to the many measured important air toxics is described. Biogas emerged as the cleanest cooking technology of approximately a dozen stove-fuel combinations measured. Crop residue burning produced relatively high emissions of oxygenated organic compounds (∼12gkg-1) and SO2 (2.54±1.09gkg-1). Two brick kilns co-firing different amounts of biomass with coal as the primary fuel produced contrasting results. A zigzag kiln burning mostly coal at high efficiency produced larger amounts of BC, HF, HCl, and NOx, with the halogenated emissions likely coming from the clay. The clamp kiln (with relatively more biomass fuel) produced much greater quantities of most individual organic gases, about twice as much BrC, and significantly more known and likely organic aerosol precursors. Both kilns were significant SO2 sources with their emission factors averaging 12.8±0.2gkg-1. Mixed-garbage burning produced significantly more BC (3.3±3.88gkg-1) and BTEX (∼4.5gkg-1) emissions than in previous measurements. For all fossil fuel sources, diesel burned more efficiently than gasoline but produced larger NOx and aerosol emission factors. Among the least efficient sources sampled were gasoline-fueled motorcycles during start-up and idling for which the CO EF was on the order of ∼700gkg-1 - or about 10 times that of a typical biomass fire. Minor motorcycle servicing led to minimal if any reduction in gaseous pollutants but reduced particulate emissions, as detailed in a companion paper (Jayarathne et al., 2016). A small gasoline-powered generator and an insect repellent fire were also among the sources with the highest emission factors for pollutants. These measurements begin to address the critical data gap for these important, undersampled sources, but due to their diversity and abundance, more work is needed

Standardized NEON organismal data for biodiversity research

Understanding patterns and drivers of species distribution and abundance, and thus biodiversity, is a core goal of ecology. Despite advances in recent decades, research into these patterns and processes is currently limited by a lack of standardized, high-quality, empirical data that span large spatial scales and long time periods. The NEON fills this gap by providing freely available observational data that are generated during robust and consistent organismal sampling of several sentinel taxonomic groups within 81 sites distributed across the United States and will be collected for at least 30 years. The breadth and scope of these data provide a unique resource for advancing biodiversity research. To maximize the potential of this opportunity, however, it is critical that NEON data be maximally accessible and easily integrated into investigators\u27 workflows and analyses. To facilitate its use for biodiversity research and synthesis, we created a workflow to process and format NEON organismal data into the ecocomDP (ecological community data design pattern) format that were available through the ecocomDP R package; we then provided the standardized data as an R data package (neonDivData). We briefly summarize sampling designs and data wrangling decisions for the major taxonomic groups included in this effort. Our workflows are open-source so the biodiversity community may: add additional taxonomic groups; modify the workflow to produce datasets appropriate for their own analytical needs; and regularly update the data packages as more observations become available. Finally, we provide two simple examples of how the standardized data may be used for biodiversity research. By providing a standardized data package, we hope to enhance the utility of NEON organismal data in advancing biodiversity research and encourage the use of the harmonized ecocomDP data design pattern for community ecology data from other ecological observatory networks

A survey on MAC protocols for complex self-organizing cognitive radio networks

Complex self-organizing cognitive radio (CR) networks serve as a framework for accessing the spectrum allocation dynamically where the vacant channels can be used by CR nodes opportunistically. CR devices must be capable of exploiting spectrum opportunities and exchanging control information over a control channel. Moreover, CR nodes should intelligently coordinate their access between different cognitive radios to avoid collisions on the available spectrum channels and to vacate the channel for the licensed user in timely manner. Since inception of CR technology, several MAC protocols have been designed and developed. This paper surveys the state of the art on tools, technologies and taxonomy of complex self-organizing CR networks. A detailed analysis on CR MAC protocols form part of this paper. We group existing approaches for development of CR MAC protocols and classify them into different categories and provide performance analysis and comparison of different protocols. With our categorization, an easy and concise view of underlying models for development of a CR MAC protocol is provided

Urbanisation generates multiple trait syndromes for terrestrial animal taxa worldwide

Cities can host significant biological diversity. Yet, urbanisation leads to the loss of habitats, species, and functional groups. Understanding how multiple taxa respond to urbanisation globally is essential to promote and conserve biodiversity in cities. Using a dataset encompassing six terrestrial faunal taxa (amphibians, bats, bees, birds, carabid beetles and reptiles) across 379 cities on 6 continents, we show that urbanisation produces taxon-specific changes in trait composition, with traits related to reproductive strategy showing the strongest response. Our findings suggest that urbanisation results in four trait syndromes (mobile generalists, site specialists, central place foragers, and mobile specialists), with resources associated with reproduction and diet likely driving patterns in traits associated with mobility and body size. Functional diversity measures showed varied responses, leading to shifts in trait space likely driven by critical resource distribution and abundance, and taxon-specific trait syndromes. Maximising opportunities to support taxa with different urban trait syndromes should be pivotal in conservation and management programmes within and among cities. This will reduce the likelihood of biotic homogenisation and helps ensure that urban environments have the capacity to respond to future challenges. These actions are critical to reframe the role of cities in global biodiversity loss.info:eu-repo/semantics/publishedVersio