Point Source Research Articles

Archetypes of Spatial Concentration Variability of Organic Contaminants in the Atmosphere: Implications for Identifying Sources and Mapping the Gaseous Outdoor Inhalation Exposome.

Whereas inhalation exposure to organic contaminants can negatively impact human health, knowledge of their spatial variability in the ambient atmosphere remains limited. We analyzed the extracts of passive air samplers deployed at 119 unique sites in Southern Canada between 2019 and 2022 for 353 organic vapors. Hierarchical clustering of the obtained data set revealed four archetypes of spatial concentration variability in the outdoor atmosphere, which are indicative of common sources and similar atmospheric dispersion behavior. "Point Source" signatures are characterized by elevated concentration in the vicinity of major release locations. A "Population" signature applies to compounds whose air concentrations are highly correlated with population density, and is associated with emissions from consumer products. The "Water Source" signature applies to substances with elevated levels in the vicinity of water bodies from which they evaporate. Another group of compounds displays a "Uniform" signature, indicative of a lack of major sources within the study area. We illustrate how such a data set, and the derived spatial patterns, can be applied to support the identification of sources, the quantification of atmospheric emissions, the modeling of air quality, and the investigation of potential inequities in inhalation exposure.

Development of a method to use standard hospital gamma cameras as triage whole body monitors in UK emergencies.

This paper outlines the process by which a medical gamma camera can be utilised to support assessment of internal radionuclides for the public. While hospital based gamma cameras are able to detect photopeaks, they are often limited to an energy range of 40-540 keV. However, radionuclides with photopeak energies above 540 keV can still be detected as the partial collection of photon energy increases the count rate at lower energies. By combining extensive mathematical modelling with empirical calibration of multiple gamma cameras it is possible to develop a linear correlation between the efficiency of counting point sources and the overall counting efficiency for the camera. Once established, a simple protocol can be used to characterise any gamma camera, using optimal system settings, and hence generate a system efficiency with sufficient accuracy to allow the camera to be used in a triage process to committed effective doses of 2 mSv.&#xD.

Field-scale gene flow of fungicide resistance in Pyrenophora teres f. teres and the effect of selection pressure on the population structure.

The effectiveness of fungicides to control foliar fungal crop diseases is being diminished by the increasing spread of resistances to fungicides. One approach that may help to maintain efficacy is remediation of resistant populations by sensitive ones. However, the success of such approaches can be compromised by re-incursion of resistance through aerial spore dispersal; although, knowledge of localized gene flow is lacking. Here, we report on a replicated mark-release-recapture field experiment with several treatments set up to study spore-dispersal-mediated gene flow of a mutated allele that confers demethylase inhibitor resistance in Pyrenophora teres f. teres (Ptt). Artificial inoculation of the host, barley (Hordeum vulgare), was successful across the 12-ha trial, where the introduced sensitive- and resistant-populations were, respectively, 6- and 13-fold the DNA concentration of the native Ptt population. Subsequent disease pressure remained low which hampered spread of the epidemic to such extent that gene flow was not detected at, or beyond 2.5 m from source points. In the absence of gene flow, plots were assessed for treatment effects; fungicide applied to populations that contained 14.3% of allele mutation increased in frequency to 24.5%, whereas sensitive populations had no change in structure. Untreated controls of native Ptt population remained genetically stable, yet untreated controls that were inoculated with sensitive Ptt had half the resistance frequency of the native population structure. The trial demonstrates the potential for management to remediate fungicide resistant pathogen populations, where localized gene flow is minimal; to safeguard chemical crop protection into the future.

The Isotopic Composition of Selected Phosphate Sources (δ18O-PO4) from the Area of the Vistula and Bug Interfluve (Poland)

Phosphorus belongs to the crucial bioelements that cause eutrophication, and phosphates, easily assimilated by organisms, are widespread in the environment. Phosphates can be of natural or anthropogenic origin and can derive from various point or non-point sources. Knowledge about the origin of nutrients is necessary to effectively manage, protect, and revitalize water resources. To recognize various phosphate sources in the study area of our research, i.e., the Vistula and Bug interfluve (SE Poland), we used the oxygen isotopic signature of phosphate ions (δ18O-PO4), which has been successfully used in recent decades as a tracer of phosphorus cycling in water studies. We measured the δ18O-PO4 of dissolved inorganic phosphates (DIPs) extracted from various phosphate sources. The obtained results are as follows: For springs, the δ18O-PO4 value varied from +14.8‰ to +18.5‰; for riverine samples, from +10.3‰ to +18.6‰, which were significantly location-dependent; while waste water treatment plant effluents ranged from +12.4‰ to +15.6‰. Two tested drainage water samples had similar isotopic compositions (+16.7‰ and +17.3‰). In the case of two analyzed bedrock samples, the δ18O-PO4 values, which were similar (+20.5‰ and +21.7‰), are close to the existing data on sedimentary bedrocks derived from similar geological periods. The obtained results can be helpful in future research aimed at identifying phosphate sources and P cycling in the studied area.

Development and deployment of a mid-cost CO2 sensor monitoring network to support atmospheric inverse modeling for quantifying urban CO2 emissions in Paris

Abstract. To effectively monitor highly heterogeneous urban CO2 emissions using atmospheric observations, there is a need to deploy cost-effective CO2 sensors at multiple locations within the city with sufficient accuracy to capture the concentration gradients in urban environments. These dense measurements could be used as input of an atmospheric inversion system for the quantification of emissions at the sub-city scale or to separate specific sectors. Such quantification would offer valuable insights into the efficacy of local initiatives and could also identify unknown emission hotspots that require attention. Here we present the development and evaluation of a mid-cost CO2 instrument designed for continuous monitoring of atmospheric CO2 concentrations with a target accuracy of 1 ppm for hourly mean measurements. We assess the sensor sensitivity in relation to environmental factors such as humidity, pressure, temperature and CO2 signal, which leads to the development of an effective calibration algorithm. Since July 2020, eight mid-cost instruments have been installed within the city of Paris and its vicinity to provide continuous CO2 measurements, complementing the seven high-precision cavity ring-down spectroscopy (CRDS) stations that have been in operation since 2016. A data processing system, called CO2calqual, has been implemented to automatically handle data quality control, calibration and storage, which enables the management of extensive real-time CO2 measurements from the monitoring network. Colocation assessments with the high-precision instrument show that the accuracies of the eight mid-cost instruments are within the range of 1.0 to 2.4 ppm for hourly afternoon (12:00–17:00 UTC) measurements. The long-term stability issues require manual data checks and instrument maintenance. The analyses show that CO2 measurements can provide evidence for underestimations of CO2 emissions in the Paris region and a lack of several emission point sources in the emission inventory. Our study demonstrates promising prospects for integrating mid-cost measurements along with high-precision data into the subsequent atmospheric inverse modeling to improve the accuracy of quantifying the fine-scale CO2 emissions in the Paris metropolitan area.

Effect of ambisonic order on spatial release from masking.

In two experiments, spatial release from masking (SRM) was measured using an ambisonic reproduction system for a range of different ambisonic orders. The first experiment used ambisonic panning while the second experiment used impulse responses recorded from a sixth-order ambisonic microphone. Both experiments found a progressive increase in SRM with increasing ambisonic order for speech presented against a single speech-shaped-noise interferer. SRM increased progressively up to at least fourth order and continued to asymptotically improve at higher-ambisonic orders toward the level achieved with point sources. The second experiment found that this effect was robust for different acoustic environments.

Search for GeV gamma-ray emission from SPT-CL J2012-5649 with six years of DAMPE data

We search for gamma-ray emission from the galaxy cluster SPT-CL J2012-5649 in the energy range from 3 GeV to 1 TeV using the DArk Matter Particle Explorer (DAMPE) telescope. For our analysis, we use three different templates: point source, radial disk, and radial Gaussian. We do not detect a signal with significance >3σ for any of these templates at any location within R200 of the cluster center. We obtain 95% C.L. upper limit on the energy flux ranging between ∼10−6 and 10−4MeVcm−2s−1 depending on the energy range. These upper limits are consistent with a previously reported non-zero flux detected by Fermi-LAT at 6σ significance. This work represents the first proof of principle search for gamma-ray emission from a single galaxy cluster using DAMPE data.

LoVoCCS. II. Weak Lensing Mass Distributions, Red-sequence Galaxy Distributions, and Their Alignment with the Brightest Cluster Galaxy in 58 Nearby X-Ray-luminous Galaxy Clusters

The Local Volume Complete Cluster Survey is an ongoing program to observe nearly a hundred low-redshift X-ray-luminous galaxy clusters (redshifts 0.03 < z < 0.12 and X-ray luminosities in the 0.1–2.4 keV band L X500c > 1044 erg s−1) with the Dark Energy Camera, capturing data in the u, g, r, i, z bands with a 5σ point source depth of approximately 25th–26th AB magnitudes. Here, we map the aperture masses in 58 galaxy cluster fields using weak gravitational lensing. These clusters span a variety of dynamical states, from nearly relaxed to merging systems, and approximately half of them have not been subject to detailed weak lensing analysis before. In each cluster field, we analyze the alignment between the 2D mass distribution described by the aperture mass map, the 2D red-sequence (RS) galaxy distribution, and the brightest cluster galaxy (BCG). We find that the orientations of the BCG and the RS distribution are strongly aligned throughout the interiors of the clusters: the median misalignment angle is 19° within 2 Mpc. We also observe the alignment between the orientations of the RS distribution and the overall cluster mass distribution (by a median difference of 32° within 1 Mpc), although this is constrained by galaxy shape noise and the limitations of our cluster sample size. These types of alignment suggest long-term dynamical evolution within the clusters over cosmic timescales.

A Deeper Look into eFEDS AGN Candidates in Dwarf Galaxies with Chandra

The ability to accurately discern active massive black holes (BHs) in nearby dwarf galaxies is paramount to understanding the origins and processes of “seed” BHs in the early Universe. We present Chandra X-ray Observatory observations of a sample of three local dwarf galaxies (M * ≤ 3 × 109 M ⊙, z ≤ 0.15) previously identified as candidates for hosting active galactic nuclei (AGN). The galaxies were selected from the NASA-Sloan Atlas with spatially coincident X-ray detections in the eROSITA Final Equatorial Depth Survey. Our new Chandra data reveal three X-ray point sources in two of the target galaxies with luminosities between log(L 2−10 keV [erg s−1]) = 39.1 and 40.4. Our results support the presence of an AGN in these two galaxies and an ultraluminous X-ray source (ULX) in one of them. For the AGNs, we estimate BH masses of M BH ∼ 105−6 M ⊙ and Eddington ratios on the order of ∼10−3.

Maximum Lateral Expansion of Wetting Bulbs from Buried and Surface Point Sources: Implications for Drip Irrigation Design

Maximum Lateral Expansion of Wetting Bulbs from Buried and Surface Point Sources: Implications for Drip Irrigation Design

Identifying Pulsar Candidates in Interferometric Radio Images Using Scintillation

Pulsars have been primarily detected by their narrow pulses or periodicity in time domain data. Interferometric surveys for pulsars are challenging due to the trade-off between beam sensitivity and beam size and the corresponding tradeoff between survey sensitivity (depth), sky coverage, and computational efforts. The detection sensitivity of time domain searches for pulsars is affected by dispersion smearing, scattering, and rapid orbital motion of pulsars in binaries. We have developed a new technique to select pulsar candidates in interferometric radio images by identifying scintillating sources and measuring their scintillation bandwidth and timescale. Identifying likely candidates allows sensitive, focused time-domain searches, saving computational effort. Pulsar scintillation is independent of its timing properties and hence offers a different selection of pulsars compared to time-domain searches. Candidates identified from this method could allow us to find hard-to-detect pulsars, such as submillisecond pulsars and pulsars in very compact, highly accelerated binary orbits. We use upgraded Giant Metrewave Radio Telescope (uGMRT) observations in the fields of PSR B1508+55, PSR J0437−4715, and PSR B0031−07 as test cases for our technique. We demonstrate that the technique correctly differentiates between the pulsar and other nonscintillating point sources and show that the extracted dynamic spectrum of the pulsar is equivalent to that extracted from the uGMRT phased array beam. We show the results from our analysis of known pulsar fields and discuss challenges in dealing with interference and instrumental effects.

Incorporating meander to account for the impact of low winds in area source Modeling; AERMOD as a case study

ABSTRACT A variety of sources of pollutant emissions can be represented as area sources. These include manure lagoons, landfills, wastewater treatment ponds, and highways. A group of point sources can also be treated as an area source. The impact of an area source is usually computed by representing the area source as a set of line sources perpendicular to the wind direction. As for point sources, the Gaussian horizontal concentration distribution used to compute the contributions of the line sources is likely to overestimate ground-level concentrations when the wind speed is comparable to the standard deviation of the horizontal velocity fluctuations. A variety of methods are used to mitigate this overestimation under these conditions, referred to as meander. As an example of one these approaches, we examine that of AERMOD, EPA’s regulatory model. AERMOD includes meander in modeling the impact of point and volume sources, but has not yet incorporated it into AERMOD’s area source algorithm. This paper describes an approach to including meander in AERMOD’s area source algorithm and demonstrates its impact on concentrations associated with area sources. Implication Statement Inclusion of wind direction meander in modeling dispersion when the wind speed is low is important in ensuring that AERMOD does not overestimate concentrations under these conditions. In view of the importance of area sources of pollution, the results presented in this paper represent a potential enhancement of AERMOD’s ability to estimate the upper end of the concentration distribution, which forms the basis of the regulatory acceptance of the model.

Analysis of the Distribution and Influencing Factors of Antibiotic Partition Coefficients in the Fenhe River Basin

Affected by point and non-point source pollution, the Fenhe River Basin faces significant environmental challenges. This study aimed to analyze the distribution characteristics and influencing factors of antibiotics in the water and sediments of the Fenhe River Basin. Samples were collected from 23 sites within the basin, and 26 antibiotics from five different classes were detected and analyzed using high-performance liquid chromatography–tandem mass spectrometry (HPLC-MS/MS). The water–sediment partition coefficient (Kp) was calculated, and spatial analysis was conducted using geographic information system (GIS) technology. The results showed that 25 antibiotics were detected in the water, with concentrations ranging from 130 to 1615 ng/L, and 17 antibiotics were detected in the sediments, with concentrations ranging from 121 to 426 μg/kg. For quinolones (QNs), except for ofloxacin, all others could be calculated with overall high values of Kp ranging from 692 to 16,106 L/kg. The Kp values for QNs were generally higher in the midstream, with considerable point source pollution from industries and non-point source pollution from developed agriculture. The distribution of Kp is closely associated with risk. This study found that the Kp values of the antibiotics were influenced by various factors such as temperature, water flow, and the physicochemical properties of sediments. Correlation analysis revealed significant relationships between Kp and parameters such as river width, water depth, water quality (total nitrogen, total phosphorus, and chemical oxygen demand), and sediment pH and clay content.

Quantifying the relative importance of agricultural land use as a predictor of catchment nitrogen and phosphorus concentrations

Agriculture is a major source of nitrogen (N) and phosphorus (P) in freshwater ecosystems, and different management strategies exist to reduce farmland nutrient losses and thus mitigate freshwater eutrophication. The importance of agricultural sources of N and P as drivers of water quality is known to vary spatially, but quantification of the relative importance of the nutrient sources shaping this variability remains challenging, especially with reference to inputs from waste water treatment works. Addressing this knowledge gap is key for targeting management strategies to where they are likely to have the greatest effect. To advance our understanding in this area, this study assesses the impact of population density as a driver of the relative importance of agricultural land use for predicting mean Total Oxidised Nitrogen (TON) and Reactive Phosphorus (RP) concentrations in rivers in England, using two different data-driven, statistical approaches: a generalised linear model and random forest. Our results show that agricultural N and P sources dominate in catchments with low population density, where stream water concentrations are lower and waste water treatment works are numerous, but smaller in terms of the population equivalent served. Agricultural N and P sources are not important predictors of N and P in catchments with high population density, where contributions from waste water treatment works dominate. These results require cautious interpretation, as model validation outcomes show that high TON and RP concentrations are consistently underpredicted. Altogether, our results suggest that the relative contribution of agricultural sources may be overestimated in densely populated catchments, relative to point sources from waste water treatment works, and that management strategies to reduce the contribution of agriculture to N and P in rivers may be better targeted towards catchments with lower population density, as this is where agricultural land use is the primary source of N and P.

Numerical Simulation Study of Gas–Liquid–Solid Triphase Coupling in Fully Mechanized Excavation Faces with Variation in Dust Source Points

In view of the current situation where research on the dust diffusion laws of different dust source points is limited and the gap with the actual field situation is too large; this study employs an innovative gas–liquid–solid triphase coupling method to investigate how dust moves and spreads in the fully mechanized excavation face 431305 at the Liangshuijing Mine; focusing on both the dust field and the dust–fog coupled field. The results indicate that using the long-pressure short-suction ventilation method; dust movement in the roadway is primarily influenced by the airflow; which can be classified into vortex; jet; and return flow regions. The analysis reveals that different dust source points affect dust distribution patterns. Dust source 1 generates the highest dust concentration; primarily accumulating on the duct side and return air side of the roadway. By contrast; dust source 2’s dust mainly gathers at the heading and the front of the cutting head. Dust sources 3 and 4 show lower dust concentrations near the top of the roadway. Dust source 5 achieves the most effective dust removal; aided by airflow and a suction fan; showcasing superior dust performance. A comprehensive comparison indicates that dust source 1 has the highest overall dust concentration. Therefore; further simulation of the distribution law of dust generated at dust source 1 under the action of water mist reveals that the dust concentration near the heading face is reduced from 2000 mg/m3 under the action of single air flow to about 1100 mg/m3. At t = 5 s; the spray droplets almost cover the entire tunneling face; leading to a significant decrease in dust concentration within 10–25 m from the tunneling face. Within 40 s; both coal dust and spray droplets are significantly reduced. The field measurement results verify the accuracy of the simulation results and provide certain guidance for promoting the sustainable development of the coal industry.

Deciphering the point source carbon footprint puzzle: Land use dynamics and socio-economic drivers

Point source carbon emissions account for approximately 80 % of total emissions. Investigating the influence of land use and socio-economic indicators on these emissions is crucial for achieving sustainable development goals. Existing research faces challenges such as focusing on specific regions, mixing variables that may exhibit multicollinearity, and lacking sufficient land use information. This study takes China, the largest emitting country, as a case study, utilizing geospatial big data to subdivide land use into 11 categories based on emission sectors. The impacts of land use and socio-economic indicators on different emission sectors are discussed from the perspectives of bivariate and spatial statistical analysis, with spatial hotspots identified. Hierarchical regression is used to evaluate the explanatory power of the indicators and to establish models, and potential carbon reduction strategies are further explored. Key findings reveal: (1) Significant multicollinearity between land use and socio-economic indicators was demonstrated, with land use explaining 57.1 % of emissions compared to 37.4 % explained by socio-economic indicators. The spatial consistency between land use and emissions exceeds 80 %, and the spatiotemporal variability is relatively low, making land use a more advantageous factor in explaining point source carbon emissions. (2) Agricultural mechanization increases emission intensity, but this efficient farming method helps convert surplus plowland, the largest influencing factor (Coefficient = 0.717), into carbon sinks, thereby controlling agricultural emissions. (3) Land intensification helps control industrial land, the main factor influencing industrial emissions (Coefficient = 0.392). It also contributes to the efficient use of carbon reduction technologies and industrial supporting land. (4) Mixed commercial and residential land has the greatest impact on commercial, service, and household emissions. However, its relationship with the economy (Correlation = 0.479) is stronger than its relationship with emissions (Correlation = 0.182), making it more applicable to cities that serve as economic growth hubs.

A Perspective on Electrochemical Point Source Utilization of CO2 and Other Flue Gas Components to Value Added Chemicals.

Electrochemical CO2 reduction reaction (eCO2RR) has been explored extensively for mitigation of noxious CO2 gas generating C1 and C2+ hydrocarbons and oxygenates as value-added fuels and chemicals with remarkable selectivity. The source of CO2 being a pure CO2 feed, it does not fully satisfy the real-time digestion of industrial exhausts. Besides the detrimental effect of noxious gas mixture leading to global warming, there is a huge capital investment in purifying the flue gas mixtures from industries. The presence of other impurity gases affects the eCO2RR mechanism and its activity and selectivity toward C2+ products dwindle drastically. Impurities like NOx, SOx, O2, N2, and halide ions present in flue gas mixture reduce the conversion and selectivity of eCO2RR significantly. Instead of wiping out these impurities via separation processes, new strategies from material chemistry and electrochemistry can open new avenues for turning foes to friends! In this perspective, the co-electroreduction will vividly discussed and supporting role of different heteroatom-containing impurity gases with CO2, generating highly stable C─N, C─S, C─X bonds, and highlight the existing limitations and providing probable solutions for attaining further success in this field and translating this to industrial exhaust streams.

An analytical model for point source pollutants in an urban area with mesoscale wind and wet deposition

An analytical model for point source pollutants in an urban area with mesoscale wind and wet deposition

A Comparative Review of Post-Combustion Capture and Direct Air Capture of CO2

Mitigating anthropogenic CO2 emissions has been a subject of incredible urgency in recent years. Carbon capture and storage (CCS) has emerged as a promising means of cutting emissions, with post-combustion capture and direct air capture (DAC) both gaining traction as methods of offsetting emissions from point sources and the ambient atmosphere. Each of these carbon capture methods rely on absorbent or adsorbent materials to function, whose properties can vastly impact capture performance. In this work, 14 materials are analyzed, with qualitative descriptions and performance data of each material based on existing review papers and representative case studies being presented. The review highlights limitations in the field in standardizing the reporting of experimental data, complicating the direct comparison of different materials’ efficacies. While no single CCS technology is found to be unequivocally superior, the promising performances of certain materials in earlier stages of development emphasize the importance of investing further in emerging post-combustion capture materials. This study concludes that CCS technologies are a necessary tool in ultimately reaching net zero emissions due to their role in neutralizing sectors resistant to decarbonization, but they should not be relied upon to substitute the transition to renewable energy, as the prevention of emissions should take priority over the abatement of emissions.

Capability of Searching for Kilonova Associated with a Short Gamma-ray Burst by SVOM

Abstract In spite of the importance of studying the cosmic generation of heavy elements&amp;#xD;through the r-process, the detection of kilonova resulted from a merger of neutron star&amp;#xD;binaries is still a challenge task. In this paper, we show that the Visible Telescope (VT)&amp;#xD;onboard the on-going SVOM space mission is powerful for identifying kilonova candi-&amp;#xD;dates associated with short gamma-ray bursts (SGRBs) up to a distance of 600Mpc. A&amp;#xD;significant color variation, turn blue and then turn red, is revealed by calculating the light&amp;#xD;curves in both red and blue channels of the VT by a linear combination of an afterglow&amp;#xD;and an assocaited kilonova. The maximum color variation is as high as ∼ 0.5 − 1 mag,&amp;#xD;which is far larger than the small photometry error of ∼ 0.2 mag of VT for a point source&amp;#xD;with a brightness of 23 mag. Up to a distance of 600Mpc, ∼ 1 − 2 kilonova candidates&amp;#xD;per year are predicted to be identified by VT.