Concentration Maps Research Articles

The health Loss Distribution of Coal-fired Power Plants and the relationship to Air Pollution Charges

In this study, the regional health loss due to the air pollution of a coal-fired power plant is analyzed by using the atmospheric dispersion model. AERMOD was used to simulate the increment concentration map of point source emission, and the GIS geographic information system was used to displace the distribution of air pollution concentration and regional health loss in grid receptors. The data of the continuous automatic monitoring facilities and the source of pollution sources were analyzed. Moreover, the effects of emissions, seasons, population, and distance on the simulated concentration were evaluated. The various influencing factors of air pollution concentration were evaluated.the R2 value of the empty product prediction map in summer has a better correlation with the concentration from monitor station, between 0.38 and 0.83, and the sulphur dioxide correlation has the best R2 value of 0.83. AERMOD was used to combined with pollutant emissions, weather, and terrain data, to simulate the distribution of rising concentration values due to coal-fired power plant emissions within the research area, and the study used the simulated rising concentration values to calculate the health loss. [1] The study used health loss of 25,647,291,161 NTD/year and medical loss of 319,153,198 NTD/year.

Spatially resolved refractometry, fluorophore-concentration, axial-position, and orientational imaging using an evanescent Bessel beam

Simultaneous field- and aperture-plane (back-focal plane, BFP) imaging enriches the information content of fluorescence microscopy. In addition to the usual density and concentration maps of sample-plane images, BFP images provide information on the surface proximity and orientation of molecular fluorophores. They also give access to the refractive index of the fluorophore-embedding medium. However, in the high-NA, wide-field detection geometry commonly used in single-molecule localisation microscopies, such measurements are averaged over all fluorophores present in the objective’s field of view, thus limiting spatial resolution and specificity. We here solve this problem and demonstrate how an oblique, variable-angle, coherent ring illumination can be used to generate a Bessel beam that - for supercritical excitation angles - produces an evanescent needle of light. Scanning the sample through the this evanescent needle enables us to acquire combined sample-plane and BFP images with sub-diffraction resolution and axial localisation precision. Background, resolution and polarisation considerations will be discussed.

DISTRIBUTION OF GERMANIUM IN THE COAL OF THE LVIV-VOLYN BASIN

Germanium – rare element, it is a raw material of multipurpose usage and it is included in the list of “critically important minerals” confirmed by the European Commission. The mineral base of Ukraine is characterized by considerable reserves of accompanying germanium and prospects of its development during the complex mining development of coal deposits. Purpose of the work is to study the origin of germanium in the course of the geological history of the formation of coalbearing deposits and to establish the law-governed nature of its distribution as the element-admixture in coal of the Lviv-Volyn Basin. Germanium in coal of Lviv-Volyn Basin is present in samples of the coal ash in all coal seams the Lower and Middle Carboniferous. The concentration of germanium for the seams v6, n7, n8, n8в, n9 was analyzed in the Chervonohrad geologicalindustrial region (Mezhyrichanske and Zabuzke fields). The article analyzes and constructs a map of germanium concentrations for coal of the seam v6 for the Chervonohrad geological-industrial region of Lviv-Volyn Basin. Along the lateral of the seam one can fix the rise in the concentration in the edge zones of paleopeatbog. Such distribution is explained by the mechanism of sorption accumulation of Ge in the organic mass of peats in the areas of increased water-mineral supplying. Data received while executing prospecting in the Lyubelske field of Lviv-Volyn Basin were analyzed. Coal of the seams п7 в, п8 в, п9, b1 of the Lyubelska-3 site that is planned from burning with the energy purposes, simultaneously may be used as source of germanium. At stratigraphic interval of the upper alluvial-lacustrine-marshy-lagoonal subformation of the Carboniferous formation of the Lviv-Volyn Basin (Bashkirian stages) the coal of the South-Western coal-bearing region (the Lyubelske field) is more germanium-bearing than coal from the Chervonohrad geological-industrial region (Mezhyrichanske and Zabuzke fields). The uneven distribution of germanium concentration is characteristic of the coal seams of the Lviv-Volyn Basin. The wave-like character of the distribution of concentrations is caused by the process of sedimentation which is subordinated to consedimentary movements that influenced the water regime of paleopeatsbogs, lithological and facies changing of the coalbearing deposits as a whole.

Risk assessment of soil and wheat pollution by heavy metals around Zanjan cement factory, Northwest Iran

ABSTRACT This study aimed to evaluate the extent of the risk of lead (Pb) and cadmium (Cd) in the soil and wheat plants grown around the Zanjan cement factory in Northwest Iran and to assess the accuracy of soil regulatory standards in reflecting the potential risk of these pollutants. A total of 73 surface (0–20 cm) soil samples and 31 wheat plant samples were collected and analyzed for their Pb and Cd contents. Statistical analyses revealed that the soil Pb and Cd concentrations varied from 1.2 to 240.0 milligram per kilogram (mg kg−1) and below the detection limit to 27.5 mg kg−1, respectively. Additionally, the wheat grain content of these metallic pollutants ranged from below the detection limit to 3.5 and 1.6 mg kg−1, respectively, indicating that certain wheat samples were polluted with Pb, Cd, or both. Spatial analyses highlighted the significant role of the cement factory in spreading substantial amounts of HMs into the soil. By comparing the soil Pb and Cd total concentrations to their respective national regulatory standards, it was observed that 26.3% and 37.2% of the study area, respectively, were classified as polluted. Integrating the interpolated maps of soil Pb and Cd concentrations and identifying sites in which at least one pollutant exceeded its regulatory standard showed that a greater proportion of the area (42.3%) should be considered polluted. Finally, after accounting for sites in which either the soil was polluted and/or wheat grain content of Pb or Cd exceeded the threshold value of 0.2 mg kg−1, 67.4% of the area was classified as polluted. The findings suggest that thematic maps prepared for individual pollutants are inadequate for pinpointing the potential risk of soil pollution with HMs. Therefore, it is crucial to consider both the soil and plant aspects when assessing the risk of HM pollution in agricultural lands.

Assignment of the biological value of solid breast masses based on quantitative evaluations of spectral CT examinations using electron density mapping, Zeffective mapping and iodine mapping

ObjectiveWe aimed to asses, in a clinical setting, whether the newly available quantitative evaluation of electron density (ED) in spectral CT examinations of the breast provide information on the biological identity of solid breast masses and whether ED maps yield added value to the diagnostic information of iodine maps and Zeff maps calculated from the same CT image datasets. MethodsAll patients at the University Breast Cancer Center who underwent a clinically indicated Dual Layer Computed Tomography (DLCT) examination for staging of invasive breast cancer from 2018 to 2020 were prospectively included. Iodine concentration maps, Zeff maps and ED maps were automatically reconstructed from the DLCT datasets. Region of interest (ROI) based evaluations in the breast target lesions and in the aorta were performed semi-automatically in identical anatomical positions using dedicated evaluation software. Case-by-case evaluations were carried independently by 2 of 4 radiologists for each examination, respectively. Statistical analysis derived from the ROIs was done by calculating ROC/AUC curves and Youden indices. ResultsThe evaluations comprised 166 DLCT examinations. In the ED maps the measurements in the breast target lesions yielded Youden cutpoints of 104.0% (reader 1) and 103.8% (reader 2) resulting in AUCs of 0.63 and 0.67 at the empirical cutpoints. The variables “Zeff” and “iodine content” derived from the target lesions showed superior diagnostical results, with a Youden cutpoint of 8.0 mg/ml in the iodine maps and cutpoints of 1.1/1.2 in the Zeff maps the AUCs ranging from 0.84 to 0.85 (p = 0.023 to <0.000). The computational combination of Zeff and ED measurements in the target lesions yielded a slight AUC increase (readers 1: 0.85–0.87; readers 2: 0.84–0.94). The ratios of the measured values in the target lesions normalized to the values measured in the aorta showed comparable results. The AUCs of ED derived from the cutpoints showed inferior results to those derived from the Zeff maps and iodine maps (ED: 0.64 and 0.66 for reader 1 and 2; Zeff: 0.86 for both readers; iodine content: 0.89 and 0.86 for reader 1 and 2, respectively). The computational combination of the ED results and the Zeff measurements did not lead to a clinically relevant diagnostic gain with AUCs ranging from 0.86 to 0.88. ConclusionsQuantitative assessments of Zeff, iodine content and ED all targeting the physical and chemical aspects of iodine uptake in solid breast masses confirmed diagnostically robust cutpoints for the differentiation of benign and malignant findings (Zeff < 7.7, iodine content of <0.8 mg/ml). The evaluations of the ED did not indicate any added diagnostic value beyond the quantitative assessments of Zeff and iodine content. Further research is warranted to develop suitable clinical indications for the use of ED maps.

Membraneless Ionic Liquid Droplet Nanoprobe for Vapor Sensing and Gas Phase Scanning Electrochemical Microscopy

Gas phase sensing of volatile chemicals is a critical area of research relevant to biomedical diagnosis and environmental hazard assessment. Among various types of sensors, electrochemical sensors garnered attention as cost-effective and portable methods. Most electrochemical sensors needed the membrane to prevent solvent evaporation for detecting the gaseous species. However, the presence of the membrane induced slow response time due to the penetration of gas molecules through the membrane. To improve the systems, a membraneless ionic liquid droplet nanoprobe was developed. Gaseous species can permeate the thin ionic liquid layer, which was also used as the electrolytes, and react on the electrode in extremely fast response. Furthermore, nano-sized electrode makes available to detect sensitively with low charging capacitance. Using the probe type form factor, application to gas phase scanning electrochemical microscopy (SECM) was attempted with high spatial resolution. Oxygen detection, the most commonly studied, was implemented for the first application of the ionic liquid nanoprobe. The limit of detection of this probe was 13 ppm, which is extremely good for electrochemical oxygen sensors. Also, the fast response (< 0.1 s) made the mapping of oxygen concentration using SECM. The nanoprobe showed more than a hundred times better spatial resolution (several micrometer scale) than the previous gas phase SECM study mapping the oxygen. As the application of this oxygen probe, Li-air battery analysis can be conducted. Oxygen was used in the reaction at the cathode of the Li-air battery. As mapping the oxygen concentration above the cathode, It is expected that structural causes for the irreversibility at the cathode can also be found. As oxygen sensing, other electrochemical active gaseous species can be detected with the electrochemical sensor. Trinitrotoluene is a well-known explosive compound, and it can be detected in electrochemistry. Due to its low vapor pressure, di-nitroaromatic compounds, like dinitrotoluene (DNT), dinitrobenzene (DNB), and dinitrophenol (DNP), were used as explosive footprints, which have higher vapor pressure and have often been identified as marker molecules. Using our ionic liquid nanoprobe, we developed the nitroaromatic compounds (NACs) sensor for real-time detection of trace vapors, without any sample pre-treatment and at room temperature. Furthermore, in a simulated airport carousel, real-time and preemptive NACs detection was demonstrated with fast response time. As oxygen detection, gas phase SECM was conducted and 3D mapping capability of the differential vapor pressure was demonstrated, exercising the potential of the NACs nanoprobe in locating the source of an explosive risk. With the sensitive sensing performance of nanoprobe, it can be used as breath analysis. There are several biomarkers to indicate certain diseases. For example, acetone is a representative biomarker of diabetes. Using this sensing platform, acetone sensing was implemented, and it may be used for the initial detection of diabetes.

Diffusion Simulation on Mammograms: A Technique for Analyzing and Monitoring Breast Tumors

We have developed an imaging biomarker for quantitatively monitoring the response to clinical treatment in cancer patients. Similar to other diffusion-weighted imaging DWI techniques, our method allows for the monitoring of breast cancer progression based on the diffusion coefficient values in the affected area. Our technique has the advantage of using images from mammograms and mesoscopic multiparticle collision MPC simulation, making it more affordable and easier to implement compared to other DWI techniques, such as diffusion-weighted MRI. To create our simulation, we start with the region of interest from a mammogram where the lesion is located and build a flat simulation box with impenetrable cylindrical obstacles of varying diameters to represent the tissue’s heterogeneity. The volume of each obstacle is based on the intensity of the mammogram pixels, and the diffusion coefficient is calculated by simulating the behavior of a point particle fluid inside the box using MPC. We tested our technique on two mammograms of a male patient with a moderately differentiated breast ductal carcinoma lesion, taken before and after the first cycle of four chemotherapy sessions. As seen in other DWI studies, our technique demonstrated significant changes in the fluid concentration map of the tumor lesion, and the relative values of the diffusion coefficient showed a clear difference before and after chemotherapy.

How do emission reductions of individual national and local measures impact street-level air quality in a neighbourhood of Madrid, Spain?

AbstractThis paper aims to assess the impact of individual measures for NOx emission reduction on NO2 concentrations at very high spatial resolution in an urban district of Madrid City (Spain). A methodology based on a set of Computational Fluid Dynamics simulations for 16 meteorological scenarios combined with the CHIMERE model for background pollution is used to obtain annual NO2 concentration maps. Two scenarios included in the Spanish National Air Pollution Control Programme are investigated: NOx emission reductions from the installation of more efficient boilers for domestic heating (ECOBOIL) and from the partly substitution of passenger cars with combustion engines by electric cars (EC). This analysis is extended to 9 additional scenarios of more ambitious implementation of electric vehicles in order to determine what the NOx emission reduction required for the annual mean NO2 concentration EU limit value not being exceeded is. The ECOBOIL scenario has a very weak impact on the NO2 concentrations. However, the EC scenario implies a more significant reduction of the NO2 concentrations, but not enough to fully remove NO2 limit value exceedances in the study area. A small additional (compared with the EC scenario) implementation of electric vehicles seems to fulfil that the spatially averaged NO2 concentration be lower than the EU limit value, but the area with exceedances is still very large. However, stronger traffic emission reductions (80%) corresponding to the most ambitious scenarios are needed in order to reach that at least 95% of the domain is free of EU limit value exceedances.

Smart placement of depolluting panels in urban areas as regards of the airflow using adjoint framework and district digital twin

A two-step numerical strategy based on a district digital twin is presented to efficiently deploy a limited number of depolluting panels in urban areas. In a diagnosis stage, a detailed pollutant concentration map is computed using CFD to identify critical highly polluted areas. Then, in a remediation stage, the optimal placement of depolluting panels as regards of urban airflow is determined to locally mitigate the air pollution in the exposed areas. For this purpose, a spatial sensitivity indicator calculated from an adjoint framework is proposed. The approach is applied to two real case studies: the full-scale laboratory district “Sense-City” under controlled conditions and a district area in Paris using realistic NOx traffic emission and wind conditions. In both case studies, it is shown that depolluting panels should be placed on a part of the sidewalks, the building facades and the roads adjacent to the sidewalks to reduce the high NOx concentration on some sidewalks and on first-floor building windows, thus preventing outdoor/indoor pollutant transfer. It is also proven that the proposed strategy is more efficient than a non-smart massive deployment of depolluting panels to improve the air quality in exposed areas. In addition to practical recommendations, this numerical strategy can provide a help-decision tool for city managers to design depolluting panels-based mitigation actions.

Inclusion of trans-cinnamaldehyde and caprylic acid in feed results in detectable concentrations in the chicken gut and reduces foodborne pathogen carriage

Poultry act as a major reservoir host for Salmonella and Campylobacter spp., the 2 leading causes of foodborne illnesses globally and in the United States. Preharvest stage interventions to reduce foodborne pathogen carriage in poultry are increasingly informed by consumer preference for antibiotic-free poultry production. The in-feed inclusion of plant-derived antimicrobial compounds is a promising antibiotic alternative strategy to reduce foodborne pathogen load in the broiler chicken gut. Yet, the fate of these phytochemicals through the broiler chicken gastrointestinal tract is unknown. Likewise, while in-feed phytochemicals have been widely demonstrated in challenge models to reduce foodborne pathogen carriage, little is known regarding efficacy to curb natural routes of infection. As such, the aim of the present study was 2-fold. We sought to determine the concentrations of 2 phytochemicals, trans-cinnamaldehyde and caprylic acid, in each region of the chicken gastrointestinal tract following their in-feed inclusion over a 6-wk production period. In addition, we investigated how the in-feed provision of these phytochemicals may protect against environmental acquisition of Campylobacter jejuni and Salmonella spp. Trans-cinnamaldehyde and caprylic acid were detected in crop, gizzard, duodenal, jejunal, and ileal contents. Crop and gizzard concentrations were not significantly (P > 0.05) different. A significant (P < 0.05) decrease in phytochemical concentration was observed in intestinal regions compared to crop and gizzard. Trans-cinnamaldehyde was consistently identified in cecal and colon contents, while caprylic acid was not detectable in these regions. Trans-cinnamaldehyde and caprylic acid were found to reduce (P < 0.05) Salmonella load. Together, our data establish that the in-feed addition of trans-cinnamaldehyde and caprylic acid, 2 phytochemicals that have previously been shown to exert antimicrobial activity against poultry-associated foodborne pathogens, results in detectable concentrations in the broiler chicken gastrointestinal tract. By providing researchers with a gastrointestinal region-by-region map of phytochemical concentrations, the present study is expected to inform the choice of in-feed phytochemicals targeting foodborne pathogen carriage in the broiler chicken gastrointestinal tract.

Addressing Nitrate Contamination in Groundwater: The Importance of Spatial and Temporal Understandings and Interpolation Methods

Iranian water security is threatened by groundwater (GW) degradation. The excessive use of GW for agriculture in Iran is degrading these resources. Livestock waste disposal and sewage irrigation are also major contributors. Nitrate (NO3) contamination in GW is a growing global concern, posing serious health and environmental risks. Soil can easily leach NO3 into GW, causing long-term contamination. Understanding the temporal and spatial patterns of NO3 pollution is vital in protecting human health and establishing safe drinking water limits. Choosing an appropriate interpolation method is crucial for creating a reliable spatial variability map, which is essential for environmental research and decision-making. This study used 85 GW samples collected over four periods to create interpolated maps and examine the spatial variability of NO3 levels. Spatial interpolation methods were performed using the geostatistical tool within ArcGIS Software. The results showed that Empirical Bayesian Kriging (EBK) was the most effective of the five evaluated interpolation methods, although the performance of each method varied depending on the period sampled. Therefore, the choice of interpolation method should be tailored to the study’s specific needs and the characteristics of the data being interpolated. The EBK method produced interpolation maps that illustrated the spatial distribution of NO3 concentrations, both within and exceeding the recommended guidelines. Interpolation methods can assist in creating spatial maps of NO3 concentrations, identifying pollution sources, and developing targeted management strategies. These maps demonstrate the potential impact of human activities on the observed patterns. A thorough understanding of Iran’s current GW quality is very important and valuable for management and policymakers.

A new two-step particle tracking and channels model method for preferential 3-D flow and transport in large DFNs of fractured aquifers

A new two-step method has been developed for predicting three-dimensional (3-D) pollutant plumes and breakthrough curves (BTC) in fractured aquifers. Predicting fluid motion fields and pollutant concentrations in groundwater is a challenging task, due to the difficulties in building a 3-D discrete fracture network (DFN) with the same geometry of fractures and interconnections as in the studied aquifer and the computational complexity of the problem being modeled. To improve the representation of DFN, geological characterization of fracture apertures was performed using field well-pumping data as the prerequisite for the modeling approach. The modeling was performed in two steps: first, 3-D particle tracking following streamline (PTFS) simulations in DFN backbones, and second, a 3-D channels model (CM) analytical solution. The PTFS simulations captured the mean properties of the 3-D velocity field relevant to spatial and temporal transport along preferential flow pathways of a fractured aquifer. The 3-D CM solution yielded the exact BTC of concentrations accounting for the slowest flow pathways typically excluded from DFN backbones extraction methods. The PTFS/CM simulations were initially performed at the lab scale on a 3-D 20 m rock block from the Bari (South Italy) fractured aquifer. Results were consistent with the chlorophyll-A BTC obtained from a well-to-well tracer experiment. Subsequently, the capability of the new method was tested by increasing the scale of simulations to a larger 3-D DFN of 200 m with 2,200 fractures. The resultant BTC was obtained in 32 min, showing the proposed PTFS/CM technique can rapidly determine complex 3-D solutions in heterogeneous fracture-dominated aquifers. The applied Lagrangian and Eulerian techniques can provide quasi-deterministic BTCs and 3-D maps of pollutant concentrations, avoiding extensive computations required for conforming mesh methods. Moreover, the solution does not require multiple randomly arranged DFN realizations, as in particle tracking-based stochastic methods. These results have significant implications in modeling transport at the aquifer scale, where DFNs are composed of thousands of fractures.

Air quality forecasting of along-route ship emissions in realistic meteo-marine scenarios

This study introduces a novel framework of metocean prediction and ship performance models that integrate multiple layers of modeling to evaluate the environmental impact of ship emissions. It enables scenario simulations that assess a ship’s performance, estimates pollutant emissions, and simulate the fate of these pollutants in the atmosphere. The study analyzes the fate of NOx, SO2, and PM10 pollutants in the atmosphere using spatially distributed concentration maps. It provides a comprehensive approach to assessing the environmental effects of ships and their emissions and contributes to the field of environmental impact assessment. Case studies are presented to demonstrate the framework’s functionalities, evaluating the interrelationships between adverse meteo-marine conditions, pollutant emissions, and resulting atmospheric diffusion characteristics.

A statistical analysis of exhaled respiratory droplet trajectory distribution in view of assessing the risk of infectious disease transmission

In the present work an analytical model of exhaled droplet trajectory and evaporation is employed to perform a preliminary statistical analysis of the droplet spatial distribution. The analysis is carried out for a set of over twenty thousand droplets distributed in the range of diameters from 0.1 μm to 1 mm. The type of respiratory events modelled are mouth breathing and speaking. The analytical model employed has been recently developed by the authors. It implements the fundamental laws of fluid dynamics and convection-diffusion, and features a 2D empirical numerical model of buoyant intermittent jet modelling the exhaled breath cloud. A discrete random walk turbulent dispersion model is also included allowing statistical analysis of the droplet trajectory to be performed. With proper boundary conditions any type of respiratory event can be simulated making the model particularly versatile. From the analysis, spatial virus concentration maps are derived for the largest droplets falling to the ground, and for the smaller droplets remaining airborne in the area in front of an infected emitter and successively uniformly dispersed in the ambient. This allows to estimate the risk of infection by fomite, direct inhalation and indirect inhalation routes, and provide a better understanding of infectious disease transmission risks.

Mapping of Chl-a in Indonesia’s Five Priority Lakes uSing Linear Regression (Case Studies: Lake Singkarak, Toba, Maninjau, Matano, and Towuti)

In Indonesia, 15 priority lakes need to be monitored regularly. Model algorithm development is the answer to accelerating lake water quality monitoring through chlorophyll-a concentration monitoring. This research aims to evaluate, develop, and find the most accurate global model algorithm for chlorophyll-a concentration mapping on Lake Singkarak, Toba, Maninjau, Matano, and Towuti. Algorithm development was made based on the existing 22-band ratio algorithm. Leave One Out Cross Validation (LOOCV) was used to evaluate the performance of all tested algorithms through the R2, NMAE, and RMSE accuracy results using 42 in-situ sample points of chlorophyll-a collected on five lakes. Lake Singkarak has an RMSE of 0.1 mg/m3, NMAE of 29.9%, R of 0.7, and R2 of 1.0. Lake Toba in the dry season has RMSE of 0.7 mg/m3, NMAE of 22.5%, R of 0.7 and R2 of 0.3. In the rainy season, Lake Toba has an RMSE of 0.1 mg/m3, NMAE of 7.1%, R of 0.5, and R2 of 0.3. Lake Maninjau has an RMSE of 0.6 mg/m3, NMAE of 32.5%, R of 0.5, and R2 of 0.3. Lake Matano has RMSE of 0.0 mg/m3, NMAE of 4.2%, R of 1.0 and R2 of 1.0. Lake Towuti has an RMSE of 0.0 mg/m3, NMAE of 3.4%, R of 1.0, and R2 of 1.0. The most accurate algorithm for Lake Singkarak, Toba (dry season), Toba (rainy season), Maninjau, Matano, and Towuti are C6, C6, C2, A2, C10, and B3, respectively

The Long-Term Detection of Suspended Particulate Matter Concentration and Water Colour in Gravel and Sand Pit Lakes through Landsat and Sentinel-2 Imagery

Over the past half century, the demand for sand and gravel has led to extensive quarrying activities, creating many pit lakes (PLs) which now dot floodplains and urbanized regions globally. Despite the potential importance of these environments, systematic data on their location, morphology and water quality remain limited. In this study, we present an extensive assessment of the physical and optical properties in a large sample of PLs located in the Po River basin (Italy) from 1990 to 2021, utilizing a combined approach of remote sensing (Landsat constellation and Sentinel-2) and traditional limnological techniques. Specifically, we focused on the concentration of Suspended Particulate Matter (SPM) and the dominant wavelength (λdom, i.e., water colour). This study aims to contribute to the analysis of PLs at a basin scale as an opportunity for environmental rehabilitation and river floodplain management. ACOLITE v.2022, a neural network particularly suitable for the analysis of turbid waters and small inland water bodies, was used to atmospherically correct satellite images and to obtain SPM concentration maps and the λdom. The results show a very strong correlation between SPM concentrations obtained in situ and those obtained from satellite images, both for data derived from Landsat (R2 = 0.85) and Sentinel-2 images (R2 = 0.82). A strong correlation also emerged from the comparison of spectral signatures obtained in situ via WISP-3 and those derived from ACOLITE, especially in the visible spectrum (443–705 nm, SA = 10.8°). In general, it appeared that PLs with the highest mean SPM concentrations and the highest mean λdom are located along the main Po River, and more generally near rivers. The results also show that active PLs exhibit a poor water quality status, especially those of small sizes (&lt;5 ha) and directly connected to a river. Seasonal comparison shows the same trend for both SPM concentration and λdom: higher values in winter gradually decreasing until spring–summer, then increasing again. Finally, it emerged that the end of quarrying activity led to a reduction in SPM concentration from a minimum of 43% to a maximum of 72%. In this context, the combined use of Landsat and Sentinel-2 imagery allowed for the evaluation of the temporal evolution of the physical and optical properties of the PLs in a vast area such as the Po River basin (74,000 km2). In particular, the Sentinel-2 images consistently proved to be a reliable resource for capturing episodic and recurring quarrying events and portraying the ever-changing dynamics of these ecosystems.

High‐Resolution Mapping of Regional NMVOCs Using the Fast Space‐Time Light Gradient Boosting Machine (LightGBM)

AbstractAccurate spatiotemporal estimation of non‐methane volatile organic compounds (NMVOCs) plays a pivotal role in establishing sophisticated early warning systems and formulating strategies to combat air pollution. Despite these critical applications, robust estimation of high spatiotemporal resolution NMVOCs concentrations remains a challenge. In this study, we develop a space‐time Light Gradient Boosting Machine (STLGB) model, which successfully renders hourly maps of NMVOCs concentrations across Shanghai from 2019 to 2022 by integrating spatiotemporal information. After extensive training, the STLGB model demonstrates remarkable estimation performance for NMVOCs, accounting for multiple spatiotemporal variables (R2 = 0.92, RMSE = 34.52 ppb). With the developed model, we provide first high‐resolution (1 km) hourly NMVOCs concentration maps, uncovering previously overlooked spatiotemporal variations. Further, SHapley Additive exPlanation (SHAP) regression values reveal significant local interpretation capabilities of the STLGB model, emphasizing the strong influence of emissions on NMVOCs estimation, whilst acknowledging the important contribution of space and time term. Our study of the pandemic lockdown further showcases the model's adaptability to unique events influenced by policy changes. The superior performance of the STLGB model, with its minimal computational memory requirements and faster speed, makes it an ideal tool for air pollutant estimation, adaptable to any region with NMVOCs monitoring capabilities.

Experimental and numerical estimation of velocity and concentration distributions in partially vegetated open channels

Transport phenomena are crucial components of the biological and chemical processes that govern fluvial environments. The presence of vegetation along rivers plays a significant role in affecting the flow velocity, which becomes unevenly distributed, and consequently is an important factor that can affect longitudinal and transversal dispersion and mixing of pollutants. Therefore, in this study, to provide a better understanding and further insights of the velocity field and the pollutant dispersion in open channels partially covered by sparse vegetation and dense vegetation, an experimental campaign is presented to compare them with the no-vegetation scenario. Novel datasets are produced by applying the Particle Image Velocity (PIV) and the Planar Concentration Analysis (PCA) technologies, which were used to measure simultaneously the surface velocity field and pollutant concentration map within the open channel tested. Results obtained have been used to calibrate and validate a numerical model designed to simulate velocity fields (via Discrete Boltzmann Model D2Q16) and pollutant concentration maps (via the Lattice Boltzmann model D2Q9). Results have shown that as the density of vegetation increases, the flow velocity in the vegetation zone decreases while the velocity in the no-vegetation zone increases. So, the velocity gradient in the transition zone increases accordingly. Besides, the water surface difference between inlet and outlet is higher as the density increases. Finally, the simulated results have been compared with corresponding experimental data and good agreements have been achieved, which indicates that the model developed can accurately predict features that were observed and measured within the experimental facility.

Ground-Level Particulate Matter (PM2.5) Concentration Mapping in the Central and South Zones of Peninsular Malaysia Using a Geostatistical Approach

Fine particulate matter is one of the atmospheric contaminants that exist in the atmosphere. The purpose of this study is to evaluate spatial–temporal changes in PM2.5 concentrations in the central and south zones of Peninsular Malaysia from 2019 to 2020. The study area involves twenty-one monitoring stations in the central and south zones of Peninsular Malaysia, using monthly and annual means of PM2.5 concentrations. The spatial autocorrelation of PM2.5 is calculated using Moran’s I, while three semi-variogram models are used to measure the spatial variability of PM2.5. Three kriging methods, ordinary kriging (OK), simple kriging (SK), and universal kriging (UK), were used for interpolation and comparison. The results showed that the Gaussian model was more appropriate for the central zone (MSE = 14.76) in 2019, while the stable model was more suitable in 2020 (MSE = 19.83). In addition, the stable model is more appropriate for both 2019 (MSE = 12.68) and 2020 (8.87) for the south zone. Based on the performance indicator, universal kriging was chosen as the best interpolation method in 2019 and 2020 for both the central and south zone. In conclusion, the findings provide a complete map of the variations in PM2.5 for two different zones, and show that interpolation methods such as universal kriging are beneficial and could be extended to the investigation of air pollution distributions in other areas of Peninsular Malaysia.

Unmixing-based cleaning methods evaluation for re-polychromated plasterwork

The cleaning of re-polychromated plaster is a rather challenging task for Conservators. The optimal choice of solvents and its application instruments may depend on the original polychromy (binder and pigment) that aims to be revealed and the overlay polychromy (binder and pigment) as well. We present a new image-processing based method that uses hyperspectral imaging to obtain a non-invasive quantitative evaluation of cleaning procedures. It is based on the application of unmixing techniques for this problem. The method computes three quality indices: efficiency, destructivity, and alteration, that are based on the residual amounts of overlay pigment, the detection of excessive abrasion in the sample and the change in color that the cleaning produces. It produces as well pixel-by-pixel concentration maps and presence maps for plaster and overlay pigment, and it can self-evaluate by computing the error map comparing the modelled spectral reflectance with the measured spectral reflectance from the samples.