Inexpensive piezoelectric diaphragms can be used as sensors to facilitate both nozzle height setting and build platform leveling in FFF (Fused Filament Fabrication) 3D printers. Tests simulating nozzle contact are conducted to establish the available output and an output of greater than 8 Volts found at 20 ºC, a value which is readily detectable by simple electronic circuits. Tests are also conducted at a temperature of 80 ºC and, despite a reduction of greater than 80% in output voltage, this is still detectable. The reliability of piezoelectric diaphragms is investigated by mechanically stressing samples over 100,000 cycles at both 20 ºC and 80 ºC and little loss of output over the test duration is found. The development of a nozzle contact sensor using a single piezoelectric diaphragm is described.

In this study, we evaluated the physicochemical and microbial qualities of source and stored household waters in some communities in Southwestern Nigeria using standard methods. Compared parameters include physicochemical constituents; Temperature (T), pH, Total Dissolved Solids (TDS), Total Hardness (TH), Biological Oxygen Demand (BOD), Magnesium ion (Mg²⁺) and Calcium ion (Ca²⁺) and microbiological parameters included Total Coliform Counts (TC), Faecal Coliform Counts (FC), Fungal Counts (Fung C), Heterotrophic Plate Counts (HPC). Comparing Stored and Source samples, the mean values of some physicochemical parameters of most of the stored water samples significantly (P<0.05) exceeded that of Sources and ranged in the following order: T (15.3±0.3^oC - 28.3±0.5^oC), pH (6.4±0.1 - 7.6±0.1), TDS (192.1±11.1 ppm - 473.7±27.9 ppm), TH (10.6±1.7 mg/L - 248.6±18.6 mg/L), BOD (0.5±0.0 mg/L - 3.2±0.3 mg/L), Mg²⁺ (6.5±2.4 mg/L - 29.1±3.2 mg/L) and Ca²⁺ (6.5±2.4 mg/L - 51.6±4.4 mg/L). The mean microbial counts obtained from microbial comparison of different points (Stored and Source) of collection showed that most of the stored water had counts significantly exceeding (P<0.05) those of the source water samples (cfu/100 mL) which ranged as follows: TC (3.1±1.5 - 156.8±42.9), FC (0.0±0.0 - 64.3±14.2) and HPC (47.8±12.1 - 266.1±12.2) across all sampled communities. Also, the predominant isolates recovered from the samples were identified as Escherichia coli, Klebsiella pneumonia, Pseudomonas aeruginosa, Enterobacter aerogenes, Aspergillus spp, Mucor spp, Rhizopus spp and Candida spp. The presence of these pathogenic and potentially pathogenic organisms in the waters and the high counts of the indicator organisms suggest the waters to be a threat to public health.

The process of modelling energy systems is accompanied by challenges inherently connected with mathematical modelling. However, due to modern realities in the 21st century, existing challenges are gaining in magnitude and are supplemented with new ones. Modellers are confronted with a rising complexity of energy systems and high uncertainties on different levels. In addition, interdisciplinary modelling is necessary for getting insight in mechanisms of an integrated world. At the same time models need to meet scientific standards as public acceptance becomes increasingly important. In this intricate environment model application as well as result communication and interpretation is also getting more difficult. In this paper we present the open energy modelling framework (oemof) as a novel approach for energy system modelling and derive its contribution to existing challenges. Therefore, based on literature review, we outline challenges for energy system modelling as well as existing and emerging approaches. Based on a description of the philosophy and elementary structural elements of oemof, a qualitative analysis of the framework with regard to the challenges is undertaken. Inherent features of oemof such as the open source, open data, non-proprietary and collaborative modelling approach are preconditions to meet modern realities of energy modelling. Additionally, a generic basis with an object-oriented implementation allows to tackle challenges related to complexity of highly integrated future energy systems and sets the foundation to address uncertainty in the future. Experiences from the collaborative modelling approach can enrich interdisciplinary modelling activities. Our analysis concludes that there are remaining challenges that can neither be tackled by a model nor a modelling framework. Among these are problems connected to result communication and interpretation.

Loss of function of the hippocampus or frontal cortex is associated with reduced performance on memory tasks in which subjects are incidentally exposed to cues at specific places in the environment and are subsequently asked to recollect the location at which the cue was experienced. Here, we examined the roles of the rodent hippocampus and frontal cortex in cue-directed attention during encoding of memory for the location of a single incidentally experienced cue. During a spatial sensory preconditioning task, rats explored an elevated platform while an auditory cue was incidentally presented at one corner. The opposite corner acted as an unpaired control location. The rats demonstrated recollection of location by avoiding the paired corner after the auditory cue was in turn paired with shock. Damage to either the dorsal hippocampus or the frontal cortex impaired this memory ability. However, we also found that hippocampal lesions enhanced attention directed towards the cue during the encoding phase while frontal cortical lesions reduced cue-directed attention. These results suggest that the deficit in spatial sensory preconditioning caused by frontal cortical damage may be mediated by inattention to the location of cues during the latent encoding phase, while deficits following hippocampal damage must be related to other mechanisms such as generation of neural plasticity.

Rapid search and localization for nuclear sources can be an important aspect in preventing human harm from illicit material in dirty bombs or from contamination. In the case of a single mobile radiation detector, there are numerous challenges to overcome such as weak source intensity, multiple sources, background radiation, and the presence of obstructions, i.e., a non-convex environment. In this work, we investigate the sequential decision making capability of deep reinforcement learning in the nuclear source search context. A novel neural network architecture (RAD-A2C) based on the actor critic (A2C) framework and a particle filter gated recurrent unit for localization is proposed. Performance is studied in a randomized 20 x 20 m convex and non-convex environment across a range of signal-to-noise ratio (SNR)s for a single detector and single source. RAD-A2C performance is compared to both an information-driven controller that uses a bootstrap particle filter and to a gradient search (GS) algorithm. We find that the RAD-A2C has comparable performance to the information-driven controller across SNR in a convex environment and at lower computational complexity per action. The RAD-A2C far outperforms the GS algorithm in the non-convex environment with greater than 95% median completion rate for up to seven obstructions.

Low-cost personal exposure monitors (PEMs) to measure personal exposure to air pollution are potentially promising tools for health research. However, their adoption requires robust validation. This study evaluated the performance of twenty-one Plume Lab Flow2 (PLF) by comparing its air pollutant measurements, particulate matter with a diameter of 2.5 μm or less (PM2.5), 10 μm or less (PM10), and nitrogen dioxide (NO2), against several high-quality air pollution monitors under field conditions (at indoor, outdoor, and roadside locations). Correlation and regression analysis were used to evaluate measurements obtained by different PLFs against reference instrumentation. For all measured pollutants, the overall correlation coefficient between the PLFs and the reference instruments was often weak (r<0.4). Moderate correlation was observed for one PLF unit at indoor location and two units at roadside location, when measuring PM2.5, but not for PM10 and NO2 concentration. During periods of particularly higher pollution, 11 PLF tools showed stronger regression results (R2 values > 0.5) with one-hour and 9 PLF units with one-minute time interval. Results show that the PLF cannot be used robustly to determine high and low exposure to poor air. Therefore, the use of PLFs in research studies should be approached with caution if data quality is important to the research outputs.

Aero submarines (aerosubs) are vehicles that can both fly both in air and travel under water. The concept of dual aerial and aquatic vehicles emerged in 1939 when Russian engineer Boris Ushakov proposed the “flying submarine”[1], and this was followed by further developments including RFS1 [2], convair project in 1964[3] , etc. however, to date, limited attempt has been diverted towards the advanced development of such aircraft. This is heavily influenced by challenges associated with the design and operation of the same. Based on the review of literature the authors aim to introduce a theoretical design for an aerosub (QFS-20) with a view to address the design and operation issues including power, entry to and exit from water.

This paper describes a novel concept of producing energy efficient ”Maroon enriched natural gas “ and then Pink hydrogen” from any hydrocarbon base. The key idea is the extraction of hydrogen from water in addition to that from the hydrocarbon in an optimal fashion. This has the benefit of higher water vapor to CO2 exhaust ratio than conventional carbonaceous fuels when generating energy via combustion, a prudent step in achieving Netzero goals in a shorter time, and creating energy independence in most places.. The process of production makes concentrated CO₂ available for use and or sequestration. The process also maximizes use of renewable electricity in hydrogen generation, and maximizes use of existing infrastructure, with a minimum capital cost by energy recycle in the process. The process design applies sound thermodynamic principles which evolved during the nineteenth century, and mimics the geochemical processes going on in some of the natural 'colorless hydrogen'.

Fungi are ubiquitous and metabolically versatile. Their dispersion has important scientific, environmental, health, and economic implications. They can be dispersed through the air by the aerosolization of near surfaces or transported from distant sources. Here, we tested the contribution of local (scale of meters) versus regional (kilometers) sources by analyzing airborne fungal community by ITS sequencing around a copper mine in the North of Chile. The mine was the regional source, whereas soil and vegetal detritus were the local sources at each point. The airborne community was highly homogeneous in ca. 2,000 km2, impeding the detection of regional or local contributions. Ascomycota was the dominant phylum in the three communities. Soil and vegetal detritus communities had lower alpha-diversity, but some taxa had abundance patterns related to the distance to the mine and altitude. On the contrary, the air was compositionally even and unrelated to environmental or spatial factors, except for altitude. The presence of plant pathogens in the air suggests that other distant sources contribute to this region's airborne fungal community and reinforces the complexity of tracking the sources of air microbial communities in a real world where several natural and human activities coexist.

Fractal analysis of time series aims to extract the hidden or complex structures issued from the associated real data, such as scaling laws, non-stationary, dynamics, and so on. In the present work, the air quality index and its components are considered as time series owing fractal structures. To understand their underlying dynamics, wavelet multifractal approach is applied starting with a wavelet multifractal spectrum test to confirm the multifractality of the underlying data. Next, a new model is introduced improving the classical minmax one, provided with a statistical measure for the adequacy of the new model. The theoretical findings are applied to the north west Tabuk region of Saudi Arabia for environmental and climate data related to pollutants and factors involved in the estimation of the air quality index.

A single paragraph of about 200 words maximum. For research articles, abstracts should give a pertinent overview of the work. We strongly encourage authors to use the following style of structured abstracts, but without headings: (1) Background: place the question addressed in a broad context and highlight the purpose of the study; (2) Methods: describe briefly the main methods or treatments applied; (3) Results: summarize the article’s main findings; (4) Conclusions: indicate the main conclusions or interpretations. The abstract should be an objective representation of the article, it must not contain results which are not presented and substantiated in the main text and should not exaggerate the main conclusions.

The unquenchable demand for rock materials has attracted many companies within the building and construction sector to invest in stone quarrying. However, this has brought about the environmental impacts with health threats to people. There is a paucity of information about the magnitude of pollution on air and water and how it varies with quarry sites. This study therefore investigated the physical impacts of quarrying on air and water and explored the in-situ mitigations to undesirable effects due to stone quarrying. Four active quarry sites were identified. Field measurements of dust (particulate matter) was conducted within the four quarry sites and in the nearby community. Water samples were collected from quarry pits and nearby shallow wells for laboratory analysis of water quality. Statistical Analysis of Variance (ANOVA) was used to test for differences in pollution across the four studied sites. Results revealed that, amidst use of wet crushing and water sprinkling on bare surfaces, dust emission was higher than the recommended permissible standards levels with a significant variation across the quarry sites with ANOVA (P-value=0.003) for PM2.5 and (P-value=0.04366) for PM10. Water pollution was mainly contributed by the non-permissive levels of nitrates, chromium, and pH. Polluted air and water are associated with sparking off health threats to the users in the community. In conclusion, quarry companies should strengthen the already existing mitigation of dust suppression. The study recommends additional measures such as treating quarry pit water before discharging to the open environment

Social distancing policies put in place during COVID-19 epidemic in addition to helping to limit the spread of the disease also contributed to improving urban air quality. Here we show a decrease in air pollutant concentration as a consequence of mobility reduction in São Paulo during the containment measure which began on 22^nd March 2020. When comparing to foregoing weeks to equivalent periods of 2019, the concentration of most air pollutants sharply decreased in the first days of mobility restriction, to then increase again after government officials downplayed the threat of the disease. This trend is also followed by a decrease in hospital admissions by SARS-influenza. Therefore, despite the great economic and social unrest caused by the pandemic, this unique situation shows that large-scale mobility reduction policy had a significant impact on air quality, benefiting, directly and indirectly, the public health system.

Several methods have been tried to estimate air temperature using satellite imagery. In this paper, the results of two machine learning algorithms, Support Vector Machine and Random Forest, are compared with Multivariate Linear Regression, TVX and Ordinary kriging. Several geographic, remote sensing and time variables are used as predictors. The validation is carried out using four different statistics on a daily basis allowing the use of ANOVA to compare the results. The main conclusion is that Random Forest with residual kriging produces the best results (R$^2$=0.612 $\pm$ 0.019, NSE=0.578 $\pm$ 0.025, RMSE=1.068 $\pm$ 0.027, PBIAS=-0.172 $\pm$ 0.046), whereas TVX produces the least accurate results. The environmental conditions in the study area are not really suited to TVX, moreover this method only takes into account satellite data. On the other hand, regression methods (Support Vector Machine, Random Forest and Multivariate Linear Regression) use several parameters that are easily calculated from a Digital Elevation Model, adding very little difficulty to the use of satellite data alone. The most important variables in the Random Forest Model were satellite temperature, potential irradiation and cdayt, a cosine transformation of the julian day.

The present work aimed to validate a low-cost passive monitoring procedure. For its validation, the monitoring of atmospheric organic pollutants - polycyclic aromatic hydrocarbons (PAH) was carried out in a capital of the central-western region of Brazil. The sensors were fixed on poles intended for electrification during the dry season. After 15 days, samples were extracted by solvent extraction and analysed by High-Resolution Gas Chromatography with Flame Ionization Detector (HRGC-FID). For the validation of the procedure, PAHs monitored and standardised by the American Environmental Agency (EPA), a benchmark for environmental monitoring of air quality by several countries, were analysed. The results demonstrated that the low-cost passive monitoring method was effective in the quantification of PAH in the environment-air, capable of being used by countries that do not have many resources for monitoring air quality.

The air quality monitoring network in Alaska is currently limited to ground-based observations in urban areas and national parks leaving a large proportion of the state unmonitored. The use of MODIS aerosol optical depth (AOD) to estimate ground-level particulate pollution concentrations has been successfully demonstrated around the world, and could potentially be used in Alaska. In this work, MODIS AOD measurements at 550 nm were validated against AOD derived from AERONET ground-based sunphotometers in Barrow and Bonanza Creek to determine if MODIS AOD from the Terra and Aqua satellites could be used to estimate ground-level particulate pollution concentrations. The MODIS AOD was obtained from MODIS collection 6 using the dark target Land and Ocean algorithms from 2000 to 2014. MODIS data could only be obtained between the months of April and October; therefore, it could only be validated for those months. Individual and combined Terra and Aqua MODIS data were considered. The results showed that MODIS collection 6 products at 10 km resolution for Terra and Aqua combined are not valid over land but are valid over the ocean. On the other hand, the individual Terra and Aqua MODIS collection 6 AOD products at 10 km resolution are valid over land individually but not when combined. Results also suggest the MODIS collection 6 AOD products at 3 km resolution are valid over land and ocean and perform better over land than the 10-km product. These findings indicate that MODIS collection 6 AOD products can be used quantitatively in air quality applications in Alaska during the summer months.

Local air quality is a major concern for the population regularly exposed to high levels of air pollution. The airport, mainly due to its aircraft engines activities during taxiing and take off, is often submitted to heterogeneous but important concentrations of NOx and PM. The study suggests an innovative approach to determine the air traffic impact on air quality at the scale of the airport, its runways and terminals, in order to be able to locate the persistent high concentrations spots. The pollutants concentrations at 10 m resolution and 1 s time step are calculated in order to identify the most affected areas of an airport platform. A real day of air traffic on a regional airport is simulated, using real data as aircraft trajectories (from radar streams). In order to estimate the aircraft emissions, the Air Transport Systems Evaluation Infrastructure (IESTA) is used. Regarding local air quality, IESTA relies on the non-hydrostatic meso-scale atmospheric model Meso-NH using grid-nesting capabilities with 3 domains, for this study. The detailed cartography of the airport distinguishes between grassland, parking and terminals, allowing to compute exchanges of heat, water and momentum between the different types of surfaces and the atmosphere as well as the interactions with the building using a drag force. The dynamic parameters like wind, temperature, turbulent kinetic energy and pollutants concentration are computed at 10 m resolution over the 2 × 4 km airport domain. The pollutants are considered in this preliminary study as passive tracers, without chemical reactions. This preliminary study aims at proving the feasibility of high scale modelling over an airport with state of the art physical models.

When it comes to air pollution complaints, odours are often the most significant contributor. Sources of odour emissions range from natural to anthropogenic. Mitigation of odour can be challenging, multifaceted, site-specific, and is often confounded by its complexity—defined by existing (or non-existing) environmental laws, public ordinances, and socio-economic considerations. The objective of this paper is to review and summarize odour legislation in selected European countries (France, Germany, Austria, Hungary, United Kingdom, Spain, The Netherlands, Italy, Belgium), North America (USA and Canada), South America (Chile and Colombia), as well as Oceania (Australia and New Zealand) and Asia (Japan, China). Many countries have incorporated odour controls into their legislation. However, odour-related assessment criteria tend to be highly variable between countries, individual states, provinces and even counties and towns. Legislation ranges from (1) no specific mention in environmental legislation that regulates pollutants which are known to have an odour impact to (2) extensive details about odour source testing, odour dispersion modeling, ambient odour monitoring, (3) setback distances, (4) process operations, and (5) odour control technologies and procedures. Agricultural operations are one specific source of odour emissions in rural and suburban areas and a model example of such complexities. Management of agricultural odour emissions is important because of the dense consolidation of animal feeding operations and the advance of housing development into rural areas. Overall, there is a need for continued survey, review, development, and adjustment of odour legislation that considers sustainable development, environmental stewardship, and socio-economic realities, all of which are amenable to a just, site-specific, and sector-specific application.

This study investigates the impact of climate change on the efficiency of organic honey production in Türkiye using a machine learning approach. The eXtreme Gradient Boosting (XGBoost) algorithm is employed for the Machine Learning (ML) modelling. The analysis includes data on organic honey production performance from 2004 to 2023, spanning a period of 20 years, and 8 different climate variables (16 variables depending on daytime and nighttime values). The dataset created to investigate the impact of climate change on organic honey yield comprises 28 columns and 120,960 rows. The study aimed to determine the significance of different climatic variables on the efficiency of organic honey production. The study found that, in addition to daytime solar radiation and temperature, wind speed and direction were also important factors. The sensitivity analysis has shown that minor alterations in the variables have a significant impact on the model's predictions. Additionally, non-linear relationships between the variables and honey production were identified. These findings suggest that it may be beneficial to consider implementing climate change adaptation and mitigation strategies in agricultural policies and beekeeping practices. The study suggests that machine learning has the potential to provide valuable insights into the complex relationship between climate change and agricultural production. This could aid in the sustainability and economic optimization of the sector.

This work introduces a new architecture for a time-domain feedback-based beamformer designed to meet real-time processing demands. The primary goal of this design is to locate reflective sources by estimating their direction of arrival (DOA) and signal range. Incorporating a feedback mechanism in this architecture is a unique aspect that refines localization precision. We conduct an in-depth analysis highlighting their respective benefits and limitations to compare the effectiveness of time-domain feedback beamforming against conventional time-domain methods. Our evaluation of the proposed architecture, based on critical performance indicators such as peak-to-sidelobe ratio, mainlobe width, and directivity factor, demonstrates its ability to improve beamformer effectiveness significantly.

Commonly, professors, students and researchers from universities around the world use software distributed under a license agreement for computer simulation purposes, which requires a computer with considerable hardware capabilities. Consequently, this implies a high cost to conduct simulations that require implementing numerical methods in all areas of engineering, particularly in the field of robotics and nonlinear control. This paper presents the design and results analysis of a low-cost and open-source frugal computer simulation tool with applications to robotic nonlinear control, for instance, for numerical simulations of manipulator robot control based on dynamic models. Using a single board minicomputer with with reduced computing power, Raspberry Pi, together with free software, GNU-Octave, trajectory tracking control simulations in the joint space of a Selective Conformal Assembly Robot Arm (SCARA) are achieved by solving a system of nonlinear differential equations, represented in matrix form, which includes the control law and the system model. The results of the proposed alternative are compared by running the same simulation code on a laptop computer using MATLAB and GNU Octave, which show minimal deviations and reasonable time complexity. Moreover, considering the frugality curve calculated for this approach, in addition to the low acquisition cost of the simulation software tool, it would allow the creation of a simulation laboratory in some universities with budgetary constraints for educational and research purposes.

River monitoring has the potential to grow substantially with present-day available affordable and locally sourced hardware. Yet river monitoring networks are still under pressure due to lack of resources, difficulties with maintenance, and rapidly changing conditions which in part may be due to climate change. We advocate that to turn around this trend, monitoring stations must rely on local people, work with locally available devices, work without contact with water and operate through openly available knowledge. River observations with camera videos have this potential. IP cameras, drones or smartphones are widely available as observation platforms. The scientific methods are well established in literature. Yet current attempts to establish scalable open-source software solutions that can be operated anywhere are lacking. In fact, currently available software is either research-oriented, more aimed at incidental observations, is restricted to single-use licenses, entirely proprietary, or restricted to operations through a third-party Software as a Service. To overcome this obstacle, we present OpenRiverCam, a free and open-source software ecosystem for river observations that can fulfill a wide variety of use cases and business cases through a well-documented and simple to use Application Programming Interface, service workflows, cloud scalability and interoperability, and options to extend to several applications within the hydrological, hydrodynamic, environmental and geospatial domains. We demonstrate its current technical abilities through three different case studies that all originate from a user perspective. We discuss the future developments to meet further requirements, which include documentation, widely available training materials and embedding in curricula, and further hardware and software developments.

This paper discusses a means of making an extremely bright path entangled source. An initial laser source is preferred but any source of light: LED, sub-critical laser, coherent or thermal can be used. The light is dimmed by a beam expander until the relative number of |1> or |2> photons increases compared to higher photon states. The expanded beam is then passed through a 1:1 beamsplitter to generate path entanglement on the |1> and |2> photons. A further stage of “purification” can remove the non-entangled higher states by passing the output beams from the beamsplitter through one another, such that the correlated entangled photon electrical fields cancel in some region. In the said region, the uncorrelated non-entangled fields can be Faraday rotated and then absorbed by a polariser. The entangled photons pass through the region without rotation and attenuation. The output from the device then has copious quantities of 1 and 2 photon path entangled suitable for use in telecommunications engineering, secure transmission of data and quantum metrology. The wide beams can be beam-contracted to a thin bright beam and will keep the path entanglement of individual photons, as photons are bosons and so don’t interact, furthermore, all operations are unitary and linear, as by Maxwell’s equations.

In order to better understand the source-sink flow and relationships of Zinc (Zn) and other nutrients in wheat (Triticum aestivum L.) plants for biofortification and improving grain nutritional quality, effects of reducing photoassimilate source (through the flag leaf removal and spike shading) or sink (through 50% spikelets removal) in the field on accumulation of Zn and other nutrients in wheat grains of two cultivars (Jimai 22 and Jimai 44) were investigated under two soil Zn application levels. The single panicle weight (SPW), kernel number per spike (KNPS), thousand kernel weight (TKW), total grain weight (TGW), concentrations and yields of various nutrient elements (Zn, Fe, Mn, Cu, N, P, K, Ca and Mg), phytate phosphorus (phytate-P), phytic acid (PA) and phytohormones (ABA: abscisic acid, and the ethylene precursor ACC: 1-aminocylopropane-1-carboxylic acid), and C/N ratios were determined. Soil Zn application significantly increased concentrations of grain Zn, N and K. Cultivars showing higher grain yields had lower grain protein and micronutrient nutritional quality. SPW, KNPS, TKW (with an exception of TKW in half spikelets removal), TGW, and nutrient yields in wheat grains were most severely reduced by half spiklets removal, secondly by spike shading, and slightly by flag leaf removal. Grain concentrations of Zn, N and Mg consistently showed negative correlations with SPW, KNPS and TGW, but positively with TKW. There were general positive correlations among grain concentrations of Zn, Fe, Mn, Cu, N and Mg, and bioavailability of Zn and Fe (estimated by molar ratios of PA/Zn, PA × Ca/Zn, PA/Fe, or PA × Ca/Fe). Although concentrations of Zn and Fe were increased and Ca was decreased in treatments of half spikelets removal and spike shading, the simultaneously increased PA limited the increase in bioavailability of Zn and Fe. In general, different nutrient elements interact with each other and are affected to different degrees by source-sink manipulations. Elevated endogenous ABA levels and ABA/ACC ratios were associated with increased TKW and grain-filling of Zn, Mn, Ca and Mg, and inhibited K in wheat grains. However, effects of ACC were diametrically opposite. These results provide basis for wheat grain biofortification to alleviate human malnutrition.

Characterization of flying insects in-situ measurement using remote sensing spectroscopy is an emerging research field. Also, most analysis techniques in remote sensing spectroscopy are based on the use of an intensity threshold which introduces indeterminacies in the number of detected specimens. In this manuscript, we investigated the possibility of analysing passive remote sensing spectroscopy measurement data using the maximum noise fraction method. The results obtained show that this analysis technique can help to overcome the measurement of background noise in spectroscopic measurements.

Three-dimensional (3D) bioprinting promises to be essential in tissue engineering for solving the rising demand for organs and tissues. Some bioprinters are commercially available, but their impact on the field of TE is still limited due to their cost or difficulty to tune. Herein, we present a low-cost easy-to-build printhead for microextrusion-based bioprinting (MEBB) that can be installed in many desktop 3D printers to transform them into 3D bioprinters. We can extrude bioinks with precise control of print temperature between 2 - 60 ºC. We validated the versatility of the printhead, by assembling it in three low-cost open-source desktop 3D printers. Multiple units of the printhead can also be easily put together in a single printer carriage for building a multi-material 3D bioprinter. Print resolution was evaluated by creating representative calibration models at different temperatures using natural hydrogels such as gelatin and alginate, and synthetic ones like poloxamer. Using one of the three modified low-cost 3D printers, we successfully printed cell-laden lattice constructs with cell viabilities higher than 90% after 24h post printing. Controlling temperature and pressure according to the rheological properties of the bioinks was essential in achieving optimal printability and great cell viability. The cost per unit of our device, which can be used with syringes of different volume, is less expensive than any other commercially available product. These data demonstrate an affordable open-source printhead with the potential to become a reliable alternative to commercial bioprinters for any laboratory.

The utility of ICTs for providing market information to rural smallholder farmers is growing rapidly, and access to reliable information and sources is considered crucial for beneficial market interaction. This study explored critical factors contributing to usage of electronic sources for market information search among rural smallholder livestock farmers. Using data collected from 129 respondents through a non-random sampling technique; descriptive and regression analysis was applied to identify key factors responsible for their awareness and use of ICT-based market information sources. Level of education was found to be a driver of awareness of ICT-based sources, and use of these sources was influenced by farmer-specific characteristics such as household size, education, income, membership of cooperatives and herd-size. The key ICT tools used was radio and mobile phones, widely available in the study area. Identified constraints to use of these ICTs include cost and patchy network signals in some areas. Policy interventions to reduce cost of mobile phone services and expansion of base stations; including practical recommendations for improved programming in radio and television offerings, are considered indispensable for greater uptake of e-information sources among smallholder livestock farmers.

This research work deals with the modeling and control of hybrid photovoltaic (PV) - Wind micro-grid using Quasi Z-Source inverter. This inverter provides better buck/boost characteristics, able to regulate the phase angle output, less harmonic content, no requirement of the filter and has high power performance characteristics over conventional inverter as major benefits. A SEPIC converter as dc-dc switched power apparatus is employed for maximum power point tracking (MPPT) functions which provides high voltage gain throughout the process. Moreover, a modified power ratio variable step (MPRVS) based perturb & observe (P&O) method has been proposed in the PV MPPT action which forces the operating point close to maximum power point (MPP). Practical responses justify the performance of hybrid PV-Wind micro-grid with Quasi Z-Source inverter structure.

Every day around 93% of children under the age of 15 (1.8 billion children) breathe outdoor air that is so polluted it puts their health and development at serious risk. Due to the pandemic, however, ventilation of buildings using outdoor air has become an important safety technique to prevent the spread of COVID-19. With the mounting ev-idence suggesting that air pollution is impactful to human health and educational out-comes, this contradictory guidance may be problematic in schools with higher air pol-lution levels, but keeping kids COVID-19 free and in school to receive their education is now more pressing than ever. To understand if all schools in an urban area are ex-posed to similar outdoor air quality and if school infrastructure protects children equally indoors, we installed research grade sensors to observe PM2.5 concentrations in indoor and outdoor settings to understand how unequal exposure to indoor and out-door air pollution impacts indoor air quality among high- and low-income schools in Salt Lake City, Utah. Based on this approach, we found that during atmospheric inver-sions and dust events, there was a lag ranging between 35 to 73 minutes for the out-door PM2.5 concentrations to follow a similar temporal pattern as the indoor PM2.5. This lag has policy and health implications and may help to explain the rising concerns re-garding reduced educational outcomes related to air pollution in urban areas. These data and resulting analysis show that poor air quality may impact school settings, and the potential implications with respect to environmental inequality.

The provision requirement of 10% openings of the total floor area stated in the Uniform Building by Law 1984 Malaysia has been practiced by designers for building plan submission approval. However, the effectiveness of thermal performance in landed residential buildings, despite the imposition by the by-law, has never been empirically measured and proven. Although terraced houses in Malaysia have dominated 40.9% of the total property transaction in 2019, such mass production with typical designs hardly provides its occupants with thermal comfort due to the static outdoor air condition and lack of external windows, where the conventional ventilation technique does not work well, even for houses with an air well system. Consequently, the occupants need to rely on mechanical cooling, which is a high energy-consuming component contributing to outdoor heat dissipation and therefore urban heat island effect. Thus, encouraging more effective natural ventilation to eliminate excessive heat from the indoor environment is critical. Since most of the research focuses on simulation modelling lacking sufficient empirical validation, this paper drawing on field measurement investigates natural ventilation performance in terraced housing with an air well system. More importantly, the key concern as to what extent the current air well system serving as a ventilator is effective to provide better thermal performance in the single storey terraced house is to be addressed. By adopting an existing single storey air welled terrace house, the existing indoor environmental conditions and thermal performance were monitored and measured using scientific equipment, namely HOBO U12 air temperature and air humidity, the HOBO U12 anemometer and the Delta Ohm HD32.3 Wet Bulb Globe Temperature meter for a six-month duration. The findings show that the air temperature of the air well ranged from 27.48°C to 30.92°C, while the mean relative humidity were from 72.67% to 79.25%. The mean air temperature for a test room (single sided ventilation room) ranged from 28.04°C to 30.92°C with a relative humidity of 70.16% to 76%. These empirical findings are of importance, offering novel policy insights and suggestions to potentially revising the existing building code standard and by laws; since the minimum provision of 10% openings has been revealed to be less effective to provide a desired thermal performance and comfort, mandatory compliance with, and the necessity for, the bylaw requirement should be revisited and further studied.

The aim of this work is to provide a full description of how air temperature and solar radiation induce changes in the land cover over an Antarctic site. We use shortwave broadband albedo (albedo integrated in the range 300-3000 nm) from a spaceborne sensor and from field surveys to calculate the monthly relative abundance of landscape units. Field albedo data were collected using a portable albedometer over seven landscape units: clean fresh snow; clean old snow; rugged landscape composed of dirty snow with disperse pyroclasts and rocky outcrops; dirty snow; stripes of bare soil and snow; shallow snow with small bare soil patches; bare soil. MODIS MCD43A3 daily albedo product was downloaded using the Google Earth Engine API from the 2000-2001 season to the 2020-2021 season. Each landscape unit was characterized by an albedo normal distribution. The monthly relative abundance of the landscape units were calculated by fitting a linear combination of the normal distributions to the histogram of the MODIS monthly mean albedo. The monthly relative abundance of the landscape unit consisting of rugged landscape composed of dirty snow, with dispersed clasts and small rocky outcrops exhibits a high linear positive correlation with the monthly mean albedo (R2=0.87) and a high linear negative correlation with the monthly mean air temperature (R2= 0.69). The increase of the solar radiation energy flux from September to December coincides with the decrease of the relative abundance of the landscape unit composed of dirty snow with dispersed clasts and small rocky outcrops. We propose a mechanism to describe the evolution of the landscape: uncovered pyroclasts act as melting centres favouring the melting of surrounding snow. Ash does not play a decisive role in the melting of the snow. The results also explain the observed decreasing of the thaw depth of the permafrost on the island in the period 2006-2014, resulting from an increase in the snow cover over the whole island.

Different coffee drying technologies face complex task in ensuring an acceptable final seed moisture content. Drying technology of agricultural commodities aims to maintain and improve the quality of the agricultural products themselves. In addition to maintaining quality, especially from other bacterial attacks, it can last for a long time before further processing. Coffee commodities are promising for the welfare of coffee farmers. Drying technology plays a major role in determining the quality of coffee. Various drying models are applied including the traditional model that until now is still applied, direct drying under solar radiation. However, this drying process is less hygienic and requires a large area. Thus, one of the drying technologies that can accelerate drying time is to vary the air flow in the drying chamber so that the coffee can be determined to reduce the water content with a certain temperature. In this study, it was found that the moisture content of coffee beans dried using a dryer on air flow with variations of velocity in solar collector 1 (DB1) air velocity of 1.0m/s obtained the final mass = 732.249 gr, solar collector 2 (DB2) with air velocity 1.5 m/s obtained the final mass = 774.70 gr, solar collector 3 (DB3) with air velocity 2.0 m/s obtained the final mass = 855.10 gr, solar collector 4 (DB4) with air velocity 2.5 m/s obtained the final mass = 745.79 gr, and solar collector 5 (DB5) with air velocity 3.0 m/s obtained the final mass = 786.40 gr. Water Content DB1=12.0%, DB2=13.6%, DB3=18.5%, DB4=12.9% and DB5=15.2%. The time required for 25 hours with a maximum radiation of 586.9 w/m2, total heat utilized from solar radiation in 3 days =16.663128 MJ/m2. from the initial weight of 1500gr coffee bean samples and dried in five solar collectors with parallel simultaneously. The evaporated water content DB1=51.18%, DB2=48.35%, DB3=42.96%, DB4=50.28% and DB5=47.57%. Based on this research, it was found that the most optimum quality of coffee was by using solar collector 2 (DB2), namely with air flow of 1.5 m/s with average temperature in the drying box DB2=43.68°C, with the quality content of the coffee, Protein content=12.2%, Carbohydrate=22.8% and Free Fatty Acid (ALB) content=0.05%.

TiO2-based building materials have air purification, auto-cleaning and sterilization functions, and these innovative green building materials have great potential for energy-saving and emission reduction applications in the future. However, there are still great challenges in improving photocatalytic efficiency and stability from laboratory to practical applications. In recent years, researchers have done a lot of work to improve the efficiency and stability of TiO2-based building materials. This paper briefly discussed the air purification principle by photocatalytic building, and the preparation techniques of TiO2-based building materials and the strategies to improve the efficiency of TiO2. Moreover, this paper has outlined the key factors that affect the photocatalytic building performance in practical applications, and analyzed the limitations and future development trends. Finally, we proposed some suggestions for further research on photocatalytic buildings and its application in practice, aiming to provide an efficient reference for developing highly efficient and stable photocatalytic building materials. The aim of this paper is to provide effective guidance for the application of TiO2-based photo-catalysts in the field of green buildings, helping to develop more efficient and stable low-carbon buildings for the development of sustainable cities.

The outbreak of the COVID-19 pandemic has raised concerns about potential environmental factors that could influence the spread and severity of the SARS-CoV-2 virus. Atmospheric pollution, particularly particulate matter (PM), has been suggested as a contributing factor to viral infections and respiratory complications. This two-year observational study aimed to investigate the relation between air pollution and the spread of COVID-19, focusing on PM2.5. Unlike previous studies limited to specific cities or countries, inevitable to use temporal data. Our research analyzed data from various states across the United States, considering both spatial and temporal correlation. The analysis considered the number and geographic distribution of COVID-19 cases along with daily PM2.5 exposure levels, accounting for monthly average PM2.5 exposure, from March 2020 to December 2021. The observed conflicting results of the temporal and spatial correlation present challenges for researchers in understanding the true nature of the relationship between PM2.5 air pollution and COVID-19 cases. The correlation between various factors, such as population density, PM2.5, temperature, and wind speed, and COVID-19 refers to an association or statistical relationship, not causation. Moreover, the intricate interplay of these variables makes it difficult to establish a clear cause-and-effect relationship.

The research considers creating a network of moss-based biotechnological purification filters in the Smart City concept. The extent of absorption of heavy metals and gases by Sphagnopsida moss under different conditions was investigated. The efficiency of air purification with biotechnological filters was also investigated using the example of the city of Almaty, Republic of Kazakhstan, where an excess of the permissible concentration of harmful substances in the air, according to the WHO air quality guidelines, is recorded throughout the year. Data on the level of pollution recorded by sensors located in the biggest Kazakhstani cities from 06/21/2020 to 06/04/2023 were selected as the basis for calculating the efficiency. In total, there are two hundred twenty sensors in 73 settlements of the Republic of Kazakhstan, with 80 such sensors located in the city of Almaty. Since creating a single biotechnological filter is expensive, the task was to calculate the air purification effect in the case of increasing the number of filters placed in polluted areas. As a result, it is shown that ten filters provide an air purification efficiency of 0.77%, 100 filters 5.72%, and 500 filters 23.11%. A biotechnological filter for air purification based on moss was designed at Astana IT University, considering the climatic features, distribution, and types of pollution in the Republic of Kazakhstan. The obtained results are essential for ensuring compliance with the ISO 37120:2018 standard for environmental comfort in the Republic of Kazakhstan. Additionally, the research findings and the experience of implementing a moss-based biotechnological filter can be applied to designing similar air purification systems in other cities. This is of great importance for the advancement of the field of urban science.

Air pollution is a man-made environmental-related problem and has importance globally among all environmental issues. It is described as an atmospheric situation in which several components appear at high attention above their ambient level and generate a quantifiable effect on vegetation, animals, and people. Air pollution and its control are a universal problem and have become an issue of great trouble for us in current years. However, monitoring and measurement of the concentration of air pollutants are most difficult in assessment to monitoring other components in the environment. Air pollutants are transported to polar regions by different mechanisms such as long-range atmospheric transport or grasshopper effects and via anthropogenic activities. After reaching the polar regions, they settle down and remain as such for a long-time due to their persistent nature. They can distress the environment and wildlife of the polar regions. Generally, dangerous chemicals may cause a risk of well-being effects, whereas lethal pollutants focus on one physiological reaction. We reviewed the available information on air pollution (occurrence, sources, and harmful effects) in the polar regions.

Rationale: The possible effect of Particulate Matter (PM10 and PM2.5 of diameter 10 and 2.5 µm respectively) levels on Covid-19 mortality is now well established. However, time-evolution of Covid-19 mortality according to PM2.5 levels has been scarcely investigated. Aim: To understand this relationship at the European level for the period 2020 (beginning) - 2022 (end). Methods: 16 representative locations in Europe (81 million people) with heterogeneous levels of PM2.5 (µg.m-3), from low to high. PM2.5 levels were assessed by various methods, and Covid-19 mortality was reported by Johns Hopkins University. Results: The trend of Covid-19 mortality vs. PM2.5 levels varied among locations. Overall, the estimated mean value was of a 40±20% mortality increase per 1 µg.m-3 PM2.5 increase. The stronger the positive gradient of the PM peak, the stronger the positive gradient of the Covid-19 mortality. Exposure to several PM peaks during about a 2-month period was the main contributor to Covid-19 mortality increases. Conclusion: Our data confirm a temporal relation between PM2.5 exposure and Covid-19 mortality, considering a 2-month integration-time for pollution events. Number-concentrations of PM should be used in the future rather than the PM2.5 mass-concentrations (µg.m-3) with the consideration of PM composition to better explain this finding.

Exposure to air pollution have detrimental effects on the elderly, women, people with pre-existing medical conditions, people living in poverty and children. The aim of the study was to investigate the extent of community awareness and knowledge on the health risks associated with exposure to air pollution. A cross-sectional study design was used for the study, using self-administered questionnaires. A simple random sampling technique was used to select 376 respondents. Systematic sampling method was applied to select the households. SPSS version 26 was used to analyze data. Of 376 respondents, 221 were males and 154 females. 113 were aged between 23-47years and 353 were aware that if they don’t protect themselves against polluted air, they may get sick, with age and educational status associated with their awareness (p &lt; 0.05). About 361 knew what air pollution is and 188 think the air they breathe in Annadale is moderate. A total number of 278 said they feel sick/uncomfortable when the quality of air is bad. About 293 knew that people are exposed to air pollution by breathing contaminated air and 237 identified sewage smell as the main cause of air pollution. Respondents who identified internet and television as the main source of information were 199 and 177 respectively. Those who were not aware of actions implemented to reduce air pollution were 180. Based on the results of the study, respondents are aware of the dangers of exposure to polluted air, and it is necessary that air pollution risk communication strategies be implemented to empower residents.

The representation of aerosols in climate-chemistry models is important for air quality and climate change research, but it can require significant computational resources. To overcome this, simpler modules such as modal aerosol modules with three lognormal modes (MAM3) can be used. In this study, the coupling of the Carbon Bond Mechanism, version Z (CBMZ), and MAM3 chemistry modules in WRF-CAM5 was improved by adding biomass-burning emissions to both gas- and particle-phase chemistry and incorporating a conversion mechanism between volatile organic compounds (VOCs) and secondary organic carbons (SOCs). The study conducted six simulations over the western U.S. and northeastern Pacific region and compared the model’s performance with observational benchmarks such as reanalysis, ground-based, and satellite data. The results showed that the model with enhanced chemistry capabilities had a 31% and 58% reduction in root-mean-square errors (RMSE) for black carbon (BC) and organic carbon (OC) surface concentrations, respectively. The earlier release of the WRF-CAM5 version had two deficiencies that were addressed in this study. This research highlights the importance of accurate aerosol representation in climate-chemistry models for improving accuracy and reducing errors in simulations.

Hot air frying is a new method of frying food, where the use of a small amount of oil is optional but recommended. The objective of this review was to know the state of the art of hot air frying technology, focusing on trends, and thus obtain new ideas for future work in this area of food. In conclusion, the availability of advanced devices will increase the demand for hot air fryers as demonstrated by the trend generating a great economic and social impact. This new technology not only provides health benefits, but also has environmental advantages. In addition, work focusing on food (i.e. tortilla chips, plantain chips, eggs and meats) is recommended, since there are not enough studies on the subject. Currently, research is being conducted on home fryers, so the use of fryers and their impact at the industrial level is a developing area that will require further research.

This document serves as supplemental information to Shapero et al. (2023), which is itself a comment on Nowell et al. (2022). Environmental Health Perspective’s publishing standards for article comments have strict word counts and do not allow the addition of new primary data analyses; therefore, this document provides an additional level of detail and supporting analyses that serve as an important backup to and expansion of Shapero et al. (2023) and that also respond to some comments within the author’s reply to our comments (Holmes and Nowell, 2023). Nowell et al. (2022) evaluated potential PM_2.5 community impacts from sugarcane harvesting. However, their analysis is flawed by erroneous assumptions and misapplied technical approaches, as discussed in Shapero et al. (2023) and as detailed in this supplemental information document. Additionally, the authors ended their analysis with 2018 data, but later data shows no marginal increase in PM_2.5 during sugarcane harvest following 2019 even using the authors’ approach (Holmes and Nowell, 2023). Therefore, the authors’ evaluations have no relevance to current conditions. Nonetheless, even their evaluation and conclusions regarding PM_2.5 concentrations purportedly attributable to sugarcane harvesting prior to 2019 are unsupported and technically unsound as detailed below.

The climate change impacts on some regions of the planet faster and stronger. These areas are known as the hot spots for climate change and Cyprus (Nicosia) in the Mediterranean is one of these spots. This paper aims to analyze the significant changes of atmospheric aerosol characteristics in 2019 and during the extreme event of 25 April 2019. We study the aerosol optical thickness (AOT), Ångström exponent, single scattering albedo, refractive index (imaginary and real parts), size, and vertical distribution of aerosol particles during the event of a high atmospheric aerosol contamination over Nicosia in details. For this purpose, we used the ground-based lidar, observations of the sun-photometer AERONET Nicosia station, satellite products from the Moderate Resolution Imaging Spectroradiometer (MODIS), and back trajectories of air movements calculated using the Hybrid Single Particle Lagrangian Integrated Trajectory Model (HYSPLIT). On 23–25 April, according to lidar and sun-photometer observations, strong aerosol pollution over Nicosia was detected. On April 25, 2019, the AOT value exceeds 1.0 at λ = 440 nm. Analysis of the optical and microphysical characteristics supported that the pollution consists of mainly Saharan dust and partly urban aerosols. This assumption was confirmed by HYSPLIT backward trajectories and MODIS images where air masses containing dust particles came from North Africa and from the Eastern part of Europe.

Air pollution is a serious global issue, responsible for approximately one in every nine deaths each year, ranking it among the greatest environmental hazards to human health. It is of particular concern in urban areas, where elevated pollutant concentrations and potential sufferers converge. Over one half of the world’s population presently lives in urban areas, and the urban population ratio is expected to reach 68% by 2050. Common air pollutants include particulate matter (PM), sulphur dioxide (SO2), ground-level ozone (O3), nitrogen oxide (NOx) and carbon monoxide (CO). While elevated rates of air pollution pose serious health risks for humans, outdoor plants can help reduce the harmful effects of air pollution by filtering and purifying the air around us.In this project Common Ivy, Aster and Miniature Andromeda plants were evaluated for air pollutant mitigation. In this study we developed a vegetation barrier model with the plant located in the middle of the greenhouse box, and air pollutant was sprayed on one side of the plant. Dispersion patterns of sprayed pollutants were tested with and without vegetation barrier. Measurements of carbon dioxide (CO2), Formaldehyde (HCHO), Total Volatile Organic Compounds (TVOC), and Particulate Matter (PM2.5/PM10) were taken before spraying, then at 0 and 30 minutes after spraying, using both monitors.The results show mitigation rates (in 177 ft3 of air after 30 min): for TVOC the minimum reduction is 5 mg/m3; for HCHO, 1 mg/m3; for CO2, 2000 ppm; for PM2.5, 2000 ug/m3; and for PM10 it was 1000 ug/m3.

The mass composition of Particulate Matter (PM) with an aerodynamic diameter of 2.5 microns (PM2.5) in San Joaquin Valley (SJV) is dominated by ammonium nitrate (NH4NO3) which is a secondary pollutant. The goal of this research was the investigation of the relationship between emissions, meteorology and PM2.5 concentrations in Fresno for the winter season. It was found that the location of sites near emission sources such as freeways compared with residential sites strongly affected measured PM2.5 concentrations. It was found that although long-term trends showed declines in both emissions and PM2.5 concentrations there was substantial variability between the years in the PM2.5/emissions relationship. Much of the yearly variation in the relationship between emissions and PM2.5 concentrations can be attributed to yearly variations in weather, such as atmospheric stability, precipitation frequency and average wind speed. There are moderate correlations between PM2.5 concentrations and temperature differences between nearby surface stations at varying elevations which explains some of the daily and seasonal variation in PM2.5. Occurrence of precipitation was related to low PM¬2.5 although the higher wind speeds and lower atmospheric stability associated with precipitation likely explain some of the low PM2.5 as well as washout of PM.

International literature data report that the increase of infectious risk may be due to heating, ventilation and air conditioning (HVAC) systems contaminated by airborne pathogens. Moreover, the presence of complex rotating dehumidification wheels (RDWs) may complicate the cleaning and disinfection procedures of the HVAC systems. We evaluated the efficacy of a disinfection strategy applied to the RDW of two hospitals HVAC systems. Hospitals have 4 RDW systems related to the surgical areas (SA1 and SA2) and to the intensive and sub-intensive cares (IC and sIC). Microbiological air and surfaces analysis were performed in HVAC systems, before and after the disinfection treatment. Hydrogen peroxide (12%) with silver ions (10 mg/L) was aerosolized in all the air sampling points, located close to the RDW device. After the air disinfection procedure, reductions of total microbial counts at 22°C and fungi were achieved in SA2 and IC HVAC systems. An Aspergillus fumigatus contamination (6 CFU/500L), detected in one air sample collected in the IC HVAC system, was eradicated after the disinfection. Surface samples proved a good microbiological quality. Results suggest the need of a disinfection procedure aimed to improve the microbiological quality of the complex HVAC systems, mostly in surgical and intensive care areas.

The Cosmic-Ray Extremely Distributed Observatory (CREDO) is a project dedicated to global studies of extremely extended cosmic-ray phenomena, the cosmic-ray ensembles (CRE), beyond the capabilities of existing detectors and observatories. Up to date cosmic-ray research has been focused on detecting single air showers, while the search for ensembles of cosmic-rays, which may overspread a significant fraction of the Earth, is a scientific terra incognita. Instead of developing and commissioning a completely new global detector infrastructure, CREDO proposes approaching the global cosmic-ray analysis objectives with all types of available detectors, from professional to pocket size, merged into a worldwide network. With such a network it is possible to search for evidences of correlated cosmic-ray ensembles. One of the observables that can be investigated in CREDO is a number of spatially isolated events collected in a small time window which could shed light on fundamental physics issues. The CREDO mission and strategy requires active engagement of a large number of participants, also non-experts, who will contribute to the project by using common electronic devices (e.g. smartphones). In this note the status and perspectives of the project is presented.

Livestock farming is a major source of greenhouse gas and ammonia emissions. In this study, we estimate methane, nitrous oxide and ammonia emission from livestock sector in the Red River Delta region from 2000 to 2015 and projection to 2030 using IPCC 2006 methodologies with the integration of local emission factors and provincial statistic livestock database. Methane, nitrous oxide and ammonia emissions in 2030 are estimated at 132 kt, 8.3 kt and 34.2 kt, respectively. Total global warming potential is 9.7 MtCO_2eq in 2030, accounts for 33% greenhouse gas emissions from livestock in Vietnam. Pig farming is responsible for half of both greenhouse gases and ammonia emissions in the studied region. Other major livestock for greenhouse gas emission is cattle and for ammonia emission is poultry. Hanoi contributes for the largest emissions in the region in 2015 but will be caught up and surpassed by other provinces in 2030.

Air pollution has become a growing invisible killer in recent years and is major cause of morbidity and mortality globally. India stands 10th among the highly polluted countries with an average PM10 level of 134μg/m3 per year. It is also reported that 99% of India's population comes across air pollution level that exceed the World Health Organization Air Quality Guideline (AQG), PM2.5 permissible levels of 10 μg/m3. Maternal exposure to air pollution has a serious health outcome to the offspring because it can affect embryonic phases of development during the gestation period. Fetus is more prone to air pollution effect during embryonic developmental phases due to oxidative stress as antioxidant mechanisms are lacking at that stage. Any injury during this vulnerable period (embryonic phase) will have long-term impact on offspring health both in early and later in life. Epidemiological studies have revealed that maternal exposure to air pollution increases the risk of developing airways disease in offspring due to impaired lung development in utero. In this review, we discuss cellular mechanisms involved in maternal exposure to air pollution and how it can impact development of airways disease in offspring. Better understanding of these mechanisms in context of maternal exposure to air pollution can offer newer avenue to prevent development of airways disease in offspring.

Abstract: Air-polishing with low abrasiveness powders is fats arising as a valid and mini-invasive instrument for the management of biofilm colonizing dental implants. The reported advantage is the efficient removal of plaque with respect of the titanium integrity. In the present study, we evaluated the in-situ plaque-removal and continual the post-treatment anti-bacterial efficacy of an innovative erythritol/chlorhexidine air-polishing powder and compared it with sodium bicarbonate. Two peri-implantitis-linked biofilm formers strains Staphylococcus aureus and Aggregatibacter actinomycetemcomitans were selected and used to infect titanium disks before and after the air-polishing treatment. Cells number and viability were assayed by colonies forming units (CFUs) count and metabolic-colorimetric (2,3-Bis-(2-Methoxy-4-Nitro-5-Sulfophenyl)-2H-Tetrazolium-5-Carboxanilide) (XTT) assay. Air-polishing performed with either sodium bicarbonate or erythritol/chlorhexidine was effective in reducing bacteria biofilm viability and number onto pre-infected specimens, while erythritol/ chlorhexidine showed a higher post-treatment biofilm re-growth inhibition. Surface analysis via mechanical profilometry failed to show an increase in titanium roughness, regardless of the powder selected.

The ambient air quality data for particulate matter as well as criteria of gaseous pollutants were assembled during December 2013 to December 2015 from the Continuous Air Quality Monitoring Station (CAMS) located at Agrabad, Chittagong. The observation showed that during April- October, 24 hour average concentration of PM10 and PM2.5 were within the National Ambient Air Quality Standard (NAAQS) level but it increased occasionally by more than two and a half times during the whole non-monsoon period (November-March). The highest values found of PM2.5 were 321.1 µg/m³ in January, 2013 and 220.34 µg/m³ in December 2015. Whether, the highest alarming concentration of PM10 was reported as 474 µg/m3 in January 2007. The other gaseous pollutants such as SO₂, NO₂, O₃, CO and Hydrocarbons remain well within the permissible limit except dry non-monsoon period. The yearly average increase of Air Quality Index (AQI) value indicates the growth rate of air pollution in Chittagong city. The main responsible pollutant for air pollution is found PM_2.5.

Estimating the infection risks in indoor environments comprises the assessment of the behavior of virus-laden aerosols, i.e. spreading, mixing, removal by air purifiers etc. A promising experimental approach is based on using non-hazardous surrogate aerosols of similar size, e.g. salt particles, to mimic the virus aerosol behavior. This manuscript addresses the issue how a successful transfer of such experiments can be accomplished. Corresponding experiments in two very different environments, a large community hall and a seminar room, with optional use of air purifiers in various constellations were conducted. While high particle concentrations are advantageous in terms of avoiding influence of background aerosol concentrations, it is shown that appropriate consideration of aggregation and settling are vital to theoretically describe the experimentally determined course of particle concentrations. A corresponding model equation for a well-mixed situation is derived and the required parameters are thoroughly determined in separate experiments independently. It is demonstrated that clean air delivery rates (CADR) of air purifiers determined with this approach may differ substantially from common approaches not explicitly taking into account aggregation.

A millimeter-wave (mmWave) gallium nitride (GaN) high-power amplifier (PA) monolithic microwave-integrated circuit (MMIC) was implemented, considering a source via effect. In this paper, we introduce guidelines for designing GaN high PA MMICs, from device sizing to meeting high-power specifications, power matching considering source via effects, schematic design of three-stage amplifier structures, and electromagnetic (EM) simulation. Based on the results of load pull simulation and small-signal maximum stable gain (MSG) simulation, the GaN high electron-mobility transistor (HEMT) size was selected to be 8×70 μm. However, since the source via model provided by the foundry was significantly different from the EM results, it was necessary to readjust the power matching considering this. Additionally, when selecting the source via size, the larger the size, the easier the matching, but since the layout of the peripheral bias circuit is not possible, a compromise was required considering the actual layout. To prevent in-band oscillation, an RC parallel circuit was added to the input matching circuit, and low-frequency oscillation was solved by adding a gate resistor on the PCB module. The proposed PA was fabricated with a commercial 0.1 μm GaN HEMT MMIC process. It exhibited 38.56 to 39.71 dBm output power (Pout), 14.2 to 16.7 dB linear gain, and 14.1% to 18.2% power-added efficiency (PAE) between 34 and 36 GHz. The fabricated GaN power amplifier MMIC shows competitive Pout in the Ka upper band above 33 GHz

The NP method was used to elucidate the contributions of vehicles and coal combustion to seasonal and long-term atmospheric PM-bound Pyr and 1-NP concentrations in Kanazawa, Kitakyushu, Shenyang, and Shanghai in the Western Pacific region from 1997 to 2021. Among the four cities, Kanazawa demonstrated the lowest Pyr concentration. The contribution of vehicles to Pyr before and after 2010 were 35% and 5%, respectively. The 1-NP concentration reduced by a factor of more than 1/10. These changes can be attributed to the emission control from vehicles. Kitakyushu revealed the second lowest Pyr and the lowest 1-NP concentrations. Coal combustion was found to be the main contributor to Pyr, while its contribution to 1-NP increased from 9% to 19%. The large contribution of coal combustion is attributed to iron manufactures. Shenyang demonstrated the highest atmospheric Pyr concentration with its largest seasonal change. Vehicles are the largest contributors to 1-NP. However, coal combustion, including winter coal heating, contributed 97% or more to Pyr and more than 14% to 1-NP. Shanghai revealed the second highest Pyr and 1-NP concentrations, but the former was substantially lower than in Shenyang. Coal combustion was the major contributor, but the contribution of vehicles to Pyr was larger before 2010 similar to Kanazawa.

The objective of the present study was to develop and optimize an efficient growth media for Lactobacillus delbrueckii ssp. bulgaricus, an essential dairy starter culture, uses plant-based nitrogen sources. The composition of the de Man, Rogosa, and Sharpe (MRS) culture medium was modified, and the nitrogen content was replaced by alternative nitrogen sources X-Seed N7 and N5 in various blends of 3% and 1.5%. Results showed that bacterial growth was higher with the N7 and N5 nitrogen source blends at 3% and 1.5%. Similarly, the optical densities of the L. bulgaricus strains were higher in the N7 and N5 blends (1.5/3%) compared to the MRS medium. Although there was no significance in bacterial counts for both the MRS and the N7 and N5 media, a significant difference between the control medium and the optimized growth media was noted. Our results thus suggest that the alternative nitrogen sources X-Seed N7 and N5 can substantially support the growth of lactic acid bacteria as shown with L. bulgaricus. Moreover, the presence of complex nitrogen sources rich in free nucleotides, amino acids, and peptides enhanced L. bulgaricus growth. Our results support the development of cost-effective and plant-based growth media for LAB cultures and potential benefits to the food and dairy industries. Additional research is warranted to improve buffering capacity for higher cell counts.

Static and dynamic analysis of website security risks is generally used for website security meas-urements. The website security measurements method recently proposed includes similarity hash-based website security risk analysis and machine learning-based website security risk anal-ysis. In this study, a method that can be performed through information disclosed on the Internet was proposed to measure the risk of a website. DNS information, IP information, and website history information are required to measure the risk of a website. In addition, global traffic rank-ing, malicious code distribution history, and HTTP access status can be checked in the website history information. In this study, information related to the security risk of websites in a total of 2,000 domains was collected and analyzed in 1,000 normal and malicious domains. Through the experiment results, 11 open information collection items were selected to measure the security risk of the website. This study presented the possibility of using public information collection to measure website security risk.

Multi-source image registration often suffered from great radiation and geometric differences. Specifically, gray scale and texture from similar landforms in different source images often show significantly different visual features. And these differences disturb the corresponding point extraction in the following image registration process. Considering that edges between heterogeneous images can provide homogeneous information and more consistent features can be extracted based on image edges, an edge consistency radiation-change insensitive feature transform (EC-RIFT) method is proposed in this paper. Firstly, the noise and texture interference are reduced by preprocessing according to the image characteristics. Secondly, image edges are extracted based on phase congruency, and an orthogonal Log-Gabor filter is performed to replace the global algorithm. Finally, the descriptors are built with logarithmic partition of the feature point neighborhood, which improves the robustness of descriptors. Comparative experiments on datasets containing multi-source remote sensing image pairs show that the proposed EC-RIFT method outperforms other registration methods in terms of precision and effectiveness.

In this paper, a fuzzy logic-based energy management system and multi-port quasi-z-source converter are proposed that utilizes hybrid renewable energy sources. The system ensures that each energy source module can be used individually by employing fuzzy logic to define power modes. This approach also helps prevent switching losses resulting from extra switching of the source modules. Also, the proposed energy management does not have a mathematical model, so applicability is simple and it is suitable for different multiple input topologies. The Mamdani fuzzy inference system can be designed to capture the nonlinear behavior of the system because of the linguistic rules. Moreover, by adopting the quasi-z-source network to the end of the multi-port converter, the switching losses of the multi-port modules have been significantly reduced. The simulation results are obtained using MATLAB Simulink, and the experimental results are obtained by connecting the circuit to MATLAB Simulink via an Arduino Due.

Heavy metals are toxic, persistent and non-degradable. After sedimentation and adsorption, they accumulate in water sediments. The aim of this study was to understand the heavy metal pollution of Qinjiang River sediments on the ecological environment and apportioning sources. The mean total concentrations of Mn, Zn, Cr, Cu, and Pb are 3.14, 2.33, 1.39, 5.79, and 1.33 times higher than the background values, respectively, except for the Co, Ni, and Cd, which are lower than the background values; Fe, Co, Ni, Cd, Cr, Cu, and Pb are all primarily in the residual state, while Mn and Zn are primarily in the acid-soluble and oxidizable states, respectively. Igeo, RI, SQGs and RAC together indicate that the pollution status and ecological risk of heavy metals in Qinjiang River sediments are generally moderate; among them, Fe, Co, Ni, Cd, Cr, and Pb are not harmful to the ecological environment of the Qinjiang River. Cu is not readily released because of its higher residual composition, depicting that Cu is less harmful to the ecological environment. Mn and Zn, as the primary pollution factors of the Qinjiang River, are harmful to the ecological environment. This heavy metal pollution in surface sediments of the Qinjiang River primarily comes from manganese and zinc ore mining. Manganese carbonate and its weathered secondary manganese oxide are frequently associated with a significant amount of residual copper and Cd, as a higher pH is suitable for the deposition and enrichment of these heavy metals. Lead-zinc ore and its weathering products form organic compounds with residual Fe, Co, Cr, and Ni, and their content is related to salinity. The risk assessment results of heavy metals in sediments provide an important theoretical basis for the prevention and control of heavy metal pollution in Qinjiang River.

Beach sand may act as a reservoir for numerous micro-organisms, including enteric pathogens. Several of these pathogens originate in human or animal feces, which may pose a public health risk. In August 2019, high levels of fecal indicator bacteria (FIB) were detected in the sand of the Azorean beach Prainha, Terceira Island, Portugal. Remediation measures were promptly implemented, including sand removal and the spraying of chlorine to restore the beach sand quality. To determine the biological source of the contamination, during the first campaign, supratidal sand samples were collected from several sites along the beach, followed by microbial source tracking (MST) analyses of Bacteroides markers for five animal species, including humans. Some of the sampling sites revealed the presence of marker genes from dogs, seagulls, and ruminants. Making use of the information on biological sources originating partially from dogs, the municipality enforced restrictive measures for dog-walking at the beach. Subsequent sampling campaigns detected low FIB contamination due to the mitigation and remediation measures that were undertaken, thereby no longer requiring MST marker-gene analysis. This is the first case study where the MST approach was used to determine the contamination sources in the supratidal sand of a coastal beach. Our results show that MST can be an essential approach to determine sources of fecal contamination in the sand. This study shows the importance of holistic management of beaches that should go beyond water quality monitoring for FIB, putting forth evidence for the need for sands also to be monitored.

The problem of reliable function computation is extended by imposing privacy, secrecy, and storage constraints on a remote source whose noisy measurements are observed by multiple parties. The main additions to the classic function computation problem include 1) privacy leakage to an eavesdropper is measured with respect to the remote source rather than the transmitting terminals’ observed sequences; 2) the information leakage to a fusion center with respect to the remote source is considered as a new privacy leakage metric; 3) the function computed is allowed to be a distorted version of the target function, which allows to reduce the storage rate as compared to a reliable function computation scenario in addition to reducing secrecy and privacy leakages; 4) two transmitting node observations are used to compute a function. Inner and outer bounds on the rate regions are derived for lossless and lossy single-function computation with two transmitting nodes, which recover previous results in the literature. For special cases that include invertible and partially-invertible functions, and degraded measurement channels, exact lossless and lossy rate regions are characterized, and one exact region is evaluated for an example scenario.

In the present study, the polysaccharide-hydrolyzing secretomes of Irpex lacteus BCC104, Pycnoporus coccineus BCC310, and Schizophyllum commune BCC632 were analyzed in submerged fermentation conditions to elucidate the effect of chemically and structurally different carbon sources on the expression of cellulases and xylanase. Among polymeric substrates, crystalline cellulose appeared to be the best carbon source providing the highest endoglucanase, total cellulase, and xylanase activities. Mandarin pomace as a growth substrate for S. commune allowed to achieve comparatively high volumetric activities of all target enzymes while wheat straw induced a significant secretion of cellulase and xylanase activities of I. lacteus and P. coccineus. A synergistic effect on the secretion of cellulases and xylanases by the tested fungi was observed when crystalline cellulose was combined with mandarin pomace. In I. lacteus the cellulase and xylanase production is inducible in the presence of cellulose-rich substrates but is suppressed in the presence of an excess of easily metabolizable carbon source. These enzymes are expressed in a coordinated manner under all conditions studied. It was shown that the substitution of glucose in the inoculum medium with Avicel provides accelerated enzyme production by I. lacteus and higher cellulase and xylanase activities of the fungus. These results add new knowledge to the physiology of basidiomycetes to improve cellulase production.

Background: The human mind is multimodal. Yet most behavioral studies rely on century-old measures such as task accuracy and latency. To create a better understanding of human behavior and brain functionality, we should introduce other measures and analyze behavior from various aspects. However, it is technically complex and costly to design and implement the experiments that record multiple measures. To address this issue, a platform that allows synchronizing multiple measures from human behavior is needed. Method: This paper introduces an opensource platform named OpenSync, which can be used to synchronize multiple measures in neuroscience experiments. This platform helps to automatically integrate, synchronize and record physiological measures (e.g., electroencephalogram (EEG), galvanic skin response (GSR), eye-tracking, body motion, etc.), user input response (e.g., from mouse, keyboard, joystick, etc.), and task-related information (stimulus markers). In this paper, we explain the structure and details of OpenSync, provide two case studies in PsychoPy and Unity. Comparison with existing tools: Unlike proprietary systems (e.g., iMotions), OpenSync is free and it can be used inside any opensource experiment design software (e.g., PsychoPy, OpenSesame, Unity, etc., https://pypi.org/project/OpenSync/ and https://github.com/moeinrazavi/OpenSync_Unity). Results: Our experimental results show that the OpenSync platform is able to synchronize multiple measures with microsecond resolution.

Machine learning applications often need large amounts of training data to perform well. Whereas unlabeled data can be easily gathered, the labeling process is difficult, time-consuming, or expensive in most applications. Active learning can help solve this problem by querying labels for those data points that will improve the performance the most. Thereby, the goal is that the learning algorithm performs sufficiently well with fewer labels. We provide a library called scikit-activeml that covers the most relevant query strategies and implements tools to work with partially labeled data. It is programmed in Python and builds on top of scikit-learn.

We present a generic and open-source framework for the numerical modeling of the expected transport and storage mechanisms in unconventional gas reservoirs. These unconventional reservoirs typically contain natural fractures at multiple scales. Considering the importance of these fractures in shale gas production, we perform a rigorous study on the accuracy of different fracture models. The framework is validated against an industrial simulator and is used to perform a history-matching study on the Barnett shale. This work presents an open-source code that leverages cutting-edge numerical modeling capabilities like automatic differentiation, stochastic fracture modeling, multi-continuum modeling and other explicit and discrete fracture models. We modified the conventional mass balance equation to account for the physical mechanisms that are unique to organic-rich source rocks. Some of these include the use of an adsorption isotherm, a dynamic permeability-correction function, and an embedded discrete fracture model (EDFM) with fracture-well connectivity. We explore the accuracy of the EDFM for modeling hydraulically-fractured shale-gas wells, which could be connected to natural fractures of finite or infinite conductivity, and could deform during production. Simulation results indicates that although the EDFM provides a computationally efficient model for describing flow in natural and hydraulic fractures, it could be inaccurate under these three conditions: 1. when the fracture conductivity is very low. 2. when the fractures are not orthogonal to the underlying Cartesian grid blocks, and 3. when sharp pressure drops occur in large grid blocks with insufficient mesh refinement. Each of these results are very significant considering that most of the fluids in these ultra-low matrix permeability reservoirs get produced through the interconnected natural fractures, which are expected to have very low fracture conductivities. We also expect sharp pressure drops near the fractures in these shale gas reservoirs, and it is very unrealistic to expect the hydraulic fractures or complex fracture networks to be orthogonal to any structured grid. In conclusion, this paper presents an open-source numerical framework to facilitate the modeling of the expected physical mechanisms in shale-gas reservoirs. The code was validated against published results and a commercial simulator. We also performed a history-matching study on a naturally-fractured Barnett shale-gas well considering adsorption, gas slippage & diffusion and fracture closure as well as proppant embedment, using the framework presented. This work provides the first open-source code that can be used to facilitate the modeling and optimization of fractured shale-gas reservoirs. To provide the numerical flexibility to accurately model stochastic natural fractures that are connected to hydraulically-fractured wells, it is built atop other related open-source codes. We also present the first rigorous study on the accuracy of using EDFM to model both hydraulic fractures and natural fractures that may or may not be interconnected.

Despite increased awareness of and attention to the need for sustainable agriculture, fertilizers and compost application in excess of crop requirements remain common agricultural practices in South Korea, causing eutrophication of freshwater and coastal ecosystems. In this study, a phosphorus (P) budget was developed to quantify P inputs, outputs, and retention in a forested- agricultural watershed. The P budget showed that chemical fertilizers and organic compost were the largest source of P (97.6% of the total) followed by atmospheric deposition (2.1% of the total P), whereas forest export (0.2% of the total) and sewage treatment plants (STPs) (0.1% of the total) were negligible. The dominant P outputs were crop harvesting and hydrologic export to surface water. The P balance showed a significant accumulation of P in the watershed; approximately 87% of the total P input was retained in the soils within the watershed. However, P concentrations in drainage water were still high enough to cause eutrophication of downstream reservoirs. The results provide useful information on the proportion of P export and retention in soils and will help support efforts to improve water quality and design better management of agricultural non-point source pollution.

This paper presents a novel approach for indoor acoustic source localization using microphone arrays and based on a Convolutional Neural Network (CNN). The proposed solution is, to the best of our knowledge, the first published work in which the CNN is designed to directly estimate the three dimensional position of an acoustic source, using the raw audio signal as the input information avoiding the use of hand crafted audio features. Given the limited amount of available localization data, we propose in this paper a training strategy based on two steps. We first train our network using semi-synthetic data, generated from close talk speech recordings, and where we simulate the time delays and distortion suffered in the signal that propagates from the source to the array of microphones. We then fine tune this network using a small amount of real data. Our experimental results show that this strategy is able to produce networks that significantly improve existing localization methods based on SRP-PHAT strategies. In addition, our experiments show that our CNN method exhibits better resistance against varying gender of the speaker and different window sizes compared with the other methods.

The Agricultural Policy/Environmental eXtender (APEX) model is widely used for evaluating agricultural conservation efforts and their effects on soil and water. A key component of APEX application in Korea is simulating water quality impacts of rice paddies because rice agriculture claims the largest cropland area in the country. In this study, a computational module called APEX-Paddy is developed to simulate water quality with considering pertinent paddy management practices such as puddling, flood irrigation management. Data collected at two experimental paddy sites in Korea were used to calibrate and validate the model. Results indicate that APEX-Paddy performs well in predicting runoff discharge rate and nitrogen yield while the original APEX highly overestimates runoff rates and nitrogen yields on large storm events. With APEX-Paddy, simulated and observed flow and mineral nitrogen yield (QN) are found to be highly correlated after calibration (Nash & Sutcliffe Efficiency (NSE) = 0.87 and Percent Bias (PBIAS) = −14.6% for flow; NSE = 0.68 and PBIAS = 2.1% for QN). Consequently, the APEX-Paddy showed a greater accuracy in flow and QN prediction than the original APEX modeling practice using the SCS-CN method.

Given a stream of depth images with a known cuboid reference object present in the scene, we propose a novel approach for accurate camera tracking and volumetric surface reconstruction in real-time. Our contribution in this paper is threefold: (a) utilizing a priori knowledge of the cuboid reference object, we keep drift-free camera tracking without explicit global optimization; (b) we improve the fineness of the volumetric surface representation by proposing a prediction-corrected data fusion strategy rather than simple moving average, which enables accurate reconstruction of high-frequency details such as sharp edges of objects and geometries of high curvature; (c) we introduce a benchmark dataset CU3D containing both synthetic and real-world scanning sequences with ground-truth camera trajectories and surface models for quantitative evaluation of 3D reconstruction algorithms. We test our algorithm on our dataset and demonstrate its accuracy compared with other state-of-the-art algorithms. We release both our dataset and code as opensource1 for other researchers to reproduce and verify our results.

In this paper, the methods and their analysis for estimating the location of three dimension (3-D) single source buried in lossy medium are presented with uniform circular array (UCA). The mathematical model of the signal in the lossy medium is proposed. Using location information in the covariance matrix obtained by sensors’ output, the equations of the source location (azimuth angle, elevation angle and range) are obtained. The phase and amplitude of the covariance matrix function are used to process these equations respectively. Then, the phase and amplitude of the covariance matrix function are used to process the source localization in the conductive medium together. By analyzing the characteristics of the proposed methods and MUSIC method, the computational complexity and the valid range of these methods are given. From the results, whether the loss is known, we can choose the appropriate method to process the issues (localization in lossless medium or lossy medium).

Societies around the world face serious energy problems related to the consumption of fossil fuels and the emission of dangerous radiation. To solve these problems, a new superconductor exhibiting a critical temperature higher than room temperature has been pursued but not achieved. This paper proposes a new energy generation system based on a circuit approach. Secondary to this process, a new type of superconductivity without refrigeration is demonstrated. In our previous paper [1], this system was proposed, but it did not describe the underlying theory in detail and did not mention an actual method to generate energy from the system. The present paper describes the theory of the existence of divergent current density and new superconductivity with no refrigeration. Moreover, the present paper proposes a method for extracting energy from the system by employing a voltage-controlled current source (i.e., a voltage–current converting method).The principle of the system is based on a circuit of two loops and independent current sources. First, the two electric loops are prepared, each with 4 diodes, where the diodes are oriented in the same direction within each loop, but their direction is opposite from loop to loop; four independent current sources connect the loops. In this circuit system, current is added iteratively as it flows along the loop according to Kirchhoff’s circuit law. As a result, a large current and electric potential are present along the loop. To confirm that this system works properly, it is necessary to demonstrate the presence of divergent currents in the transient state, and to do this, the present paper employs the Dirac equation and Lorentz conservation. Electric circuit software is employed to demonstrate that the presented method generates energy actually from our system.Our results confirm the presence of divergent current at a connected point of an independent current source in the transient state. Moreover, in the steady state, the theory demonstrates the Meissner effect (i.e., a London equation) and a new type of macroscopic wave function and condensation. For an initial small input current of 0.1 μA, the simulation reveals a large generating current of 7 kA and electric power of 10¹¹ W, which is much larger than unit of power from an average thermal power station; moreover, the system presents with superconducting electrical transport conditions.The present study is significant because it demonstrates theoretically the existence of divergent current density and a new type of superconductivity requiring no refrigeration. Secondly, the simulations show the generation of a large energy density that can be obtained in a small laboratory room with minimal cost.

Observing air quality from sensors onboard light rail cars in Salt Lake County, Utah began as a pilot study in 2014 and has now evolved into a five-year state-funded program. This metropolitan region suffers from both elevated ozone levels during summer and high PM2.5 events during winter. Pollution episodes result predominantly from local anthropogenic emissions but are also impacted by regional transport of dust, chemical precursors to ozone, and wildfire smoke as well as being exacerbated by the topographical features surrounding the city. Two electric light-rail train cars from the Utah Transit Authority light-rail Transit Express (“TRAX”) system were outfitted with PM2.5 and ozone sensors to measure air quality at high spatial and temporal resolution in this region. Pollutant concentration data underwent quality control procedures to determine whether the train motion affected the readings and how the sensors compared against regulatory sensors. Quality assurance results from data obtained over the past year show that TRAX Observation Project sensors are reliable, which corroborates earlier preliminary validation work. Two case studies from summer 2019 are presented to illustrate the strength of the finely-resolved air quality observations: 1) an elevated ozone event and 2) elevated particulate pollution resulting from 4th of July fireworks. The mobile observations were able to capture spatial gradients as well as pollutant hotspots during both of these episodes. Sensors have been recently added to a third light rail train car, which travels on a north-south oriented rail line along which we were unable to monitor air quality previously. The TRAX Observation Project is currently being used to provide reliable pollutant data for health studies and inform urban planning efforts. Links to real-time data displays and updated information on the quality-controlled data from this study are available at https://atmos.utah.edu/air_quality/trax/.

This paper presents a symmetrical topology for the design of solid-state transformer, made up of power switching converters, to replace conventional bulky transformers. The proposed circuitry not only reduces the overall size but also provides power flow control with the ability to be interfaced with renewable energy resources (RESs) to fulfill the future grid requirements at consumer end. Solid state transformer provides bidirectional power flow with variable voltage and frequency operation and has the ability to maintain unity power factor, and current total harmonic distortion (THD) for any type of load within defined limits of IEEE standard. Solid State Transformer offers much smaller size as compared to that of the conventional iron core transformer. MATLAB/Simulink platform is adopted to test the validity of the proposed circuit for different scenarios by providing the simulation results evaluated at 25 kHz switching frequency.

Retiring coal power plants can reduce air pollution and health damages. However, the spatial distribution of those impacts remains unclear due to complex power system adjustments and pollution chemistry and transport. Focusing on coal retirements in Pennsylvania (PA), we analyze six counterfactual scenarios for 2019 that differ in retirement targets (e.g., reducing 50% of coal-based installed capacity vs. generation) and priorities (e.g., closing plants with higher cost, closer to Environmental Justice Areas, or with higher CO₂ emissions). Using a power system model of the PJM Interconnection, we find that coal retirements in PA shift power generation across PA and the Rest of PJM region leading to scenario-varying changes in the plant-level release of several air pollutants. Due to air pollution chemistry and transport and socio-demographics, these changes in turn give rise to a reduction of 10 to 182 PM_2.5-attributable deaths in PJM across the six scenarios, with most reductions occurring in PA. Scenarios that reduce more coal power generation yield greater aggregate health benefits due to air quality improvements in PA and adjacent downwind regions. In addition, vulnerable populations—in both PA and Rest of PJM—benefit most in scenarios that prioritize plant closures in PA near Environmental Justice Areas. These results demonstrate the importance of considering cross-regional linkages and socio-demographics in designing equitable retirement strategies.

It is concerning that Cameroon's urban centers are experiencing an alarming rise in air pollution as a result of urbanization, population growth, industrial activity, and transportation emissions. We examined the causes, health impacts, research methodology, case studies, and government measures to address the urgent issue of air pollution in Cameroon's urban regions. We have emphasized how Cameroon's air pollution levels have significantly increased as a result of causes like population expansion, urbanization, industrial emissions, and automobile exhaust A thorough discussion of the negative health impacts of extended exposure to air pollution is included, with special attention to the sensitivity of the old and young. These effects include respiratory disorders, cardiovascular ailments, and early mortality. We emphasized the pressing need for all-encompassing strategies to address air pollution, such as increased public awareness campaigns, stronger emissions regulations, the development of renewable energy sources, and better waste management. The techniques employed in studies on air pollution, like as epidemiological research and air quality monitoring, are also explained to provide light on the unique health dangers that Cameroonian urban dwellers must contend with. We emphasized in our conclusion the significance of joint efforts by legislators, medical professionals, and the general people to reduce air pollution and protect public health in Cameroon in order to create a cleaner and healthier future. In order to protect public health in the future, it is imperative that Cameroon's air pollution be addressed.

The primary sources of particulate matter are linked to human activity. Certain particulate emissions, particularly those of a finer nature, can significantly impact human health, making them one of the most concerning pollutants. Ultrafine particles (UFP), which have a diameter of less than 100 nm, are of particular concern due to their impact on human health and the difficulty in controlling them. The concentration of ultrafine particles (UFP) in the workplace is a growing concern and is classified as an emerging risk. Workers may be exposed to UFP through inhalation, skin absorption, ingestion, or a combination of these routes. This study aims to determine the levels of UFP exposure among workers in environments with varying direct particle emission patterns. Measurements were conducted to compare the results with the levels recommended by the WHO. The study monitored industrial workplaces with direct particulate matter emissions, such as a carpentry and a bakery, as well as social sector sites without or almost without direct particle emissions, such as a school and a health clinic. One conclusion drawn from this study is that all tasks and occupations are susceptible to high levels of UFP, exceeding WHO recommended values in virtually all monitored environments. Therefore, monitoring and controlling UFP is crucial. Further in-depth studies on this subject are also necessary..

Abstract: Recent years demonstrate the increased attention to radon from two scientific directions. After neglecting radon as earthquake precursors in 1990-th it becomes again the subject of earthquake-forecast papers discussions due to growing networks of the radon monitoring in different countries, especially, the technologies of real-time radon measurements where the gamma-spectrometers become the leader of interest as the sources of 222Rn identification. The second fast developing direction is including the radon in the Lithosphere-Atmosphere-Ionosphere Coupling (LAIC) models as a source of the boundary layer ionization. And here we encounter with second direction which is not connected with the earthquake forecast problems. It is the role of air ionization by radon as a source of the Global Electric Circuit (GEC) modification. In this publication we try to unite all these problems to present more complex view on radon as important element of our environment.

DNA extraction for downstream molecular diagnostic applications can be an expensive, time-consuming process. We devised a method to quickly extract genomic DNA from environmental samples based on sodium hydroxide lysis of cells with or without capture by magnetic beads, for subsequent PCR or quantitative PCR. The final DNA extraction method using NaOH is extremely low-cost and can be completed in 10 minutes at room temperature. NaOH extraction was effective for Gram-negative and Gram-positive bacteria in samples from air, soil, sewage, food, laboratory surfaces, and chicken cloacal swabs. The NaOH extraction method was comparable to commercial kits for extraction of DNA from pig fecal samples for 16S amplicon sequencing analyses. We demonstrate that an impinger and portable pump can efficiently capture bacteria in poultry facilities for rapid DNA extraction for quantification of total bacteria and for detection of specific species using qPCR. The air sampling and NaOH extraction procedures are well-suited for routine, high throughput screening, and for metagenomic analyses for specific pathogens, even in resource-limited situations.

The air is a fundamental element for the life on Earth. Rapid urbanization and industrialization release large amounts of pollutants (harmful gases, microorganisms, and particulate matter, among others) into the atmosphere, leading to health hazards. Air filtration is still the most used and promising technique for protecting air against pollutants. The quality and efficiency of filtering process are dependent of material used for the filter and other filter’s properties. Several methods can be used for manufacturing filters, one of them uses fibrous membranes obtained through electrospinning from polymeric solutions. Electrospinning is a technique that combines the application of an electrostatic field to a moving fluid which results in the fibers formation. Electrospun membranes are constituted by fibers that the sizes spread on submicro and or nanometric scales. This review focuses on fiber membranes obtained by electrospinning for filtration of particulate matter. It is addressed the effect of solution, processing and ambient parameters on the morphology and dimensional characteristics of fiber membranes. The basic principles of air filtration and test and characterization of filter performance are presented. The research progress on electrospun nanofibers as air filters in recent years is summarized and examined. Finally, conclusion and future perspectives in electrospun fibers for air filtration are provided and discussed.

This research investigates the compatibility of conventional air conditioning with the principles of green building, highlighting the need for systems that enhance indoor comfort while aligning with environmental sustainability. Conventional cooling systems, though proficient in regulating indoor temperatures, encounter several issues when incorporated into green buildings. These include energy waste, high running costs, and a misalignment with eco-friendly practices, which may also lead to detrimental environmental effects and potentially reduce occupant comfort, particularly in retrofit situations. Given the emphasis on sustainability and energy conservation in green buildings, there is a pressing demand for heating, ventilation, and air conditioning (HVAC) solutions that support these goals. This study emphasizes the critical need to reconsider traditional HVAC strategies in the face of green building advances. It advocates for the adoption of innovative HVAC technologies designed for eco-efficiency and enhanced comfort. These technologies should integrate seamlessly with sustainable construction, use greener refrigerants, and uphold environmental integrity, driving progress towards a sustainable and occupant-friendly built environment.

A study was conducted on the power system of a forklift equipped with PEM fuel cells. A fuel cell assembly relies on several components for proper functioning, and among these, the air compressor holds paramount importance due to its significant energy consumption when compared to other Balance of Plant components. The air supply system, in turn, plays a critical role in ensuring the stable and efficient operation of the entire fuel cell system. To enhance system efficiency, we delved into the impact of varying the stoichiometric ratio of air and air pressure on the validated and optimized power module model. This investigation was carried out under real loading conditions, replicating the conditions experienced by the power module when fuel cells are in use within a forklift. The air compressor, being a pivotal component of a PEM fuel cell system, can be oper-ated at different excess air and pressure ratios, which in turn influence both the fuel cell's performance and the overall efficiency of the power module system. Our research focused on assessing the performance of polymer electrolyte membrane (PEM) fuel cells under different load cycles, adhering to the VDI60 requirements for forklift applications. This comprehensive examination encompassed the system's minimum and maximum load scenarios, with the primary goal of optimizing excess air and pressure ratio parameters, especially under dynamic load conditions. The results revealed that higher air pressures and lower excess air ratios were con-ducive to increasing system efficiency, shedding light on potential avenues for enhancing the performance of PEM fuel cell systems in forklift applications.

In Bangkok, the capital city of Thailand, air pollution is a significant problem, and efforts are needed to define organisms that may be used as bioindicators of air pollution. Epiphytic subaerial algae, which grow on the surface of trees, may have a potential as bioindicators of urban air quality. Algae were collected from randomly selected tree trunks in five parks in Bangkok, and the air pollutants CO, NO2, O3, SO2, PM2.5, and PM10 were measured. Analysis of the subaerial algal communities was performed by metagenomics. Diversity indexes were determined for the algal taxa detected, which were separated into groups corresponding to different collection sites by cluster analysis. Relationships between taxa and air pollutants were analyzed by PCA and the Pearson correlation coefficient (r). The results showed a high diversity of epiphytic subaerial al-gae. We recorded 101 taxa belonging to the Cyanophyta (70 taxa), Chlorophyta (21 taxa), Char-ophyta (5 taxa), Bacillariophyta (3 taxa), and Eustigmatophyta (2 taxa). The most abundant taxon was Chroococcidiopsis sp. 1, for which up to 13,254 individuals/cm2 were recorded. The Shan-non–Weaver index ranged between 1.37 and 2.51, the Margalef index between 3.84 and 4.75, and the Pielou index between 0.30 and 0.54. The similarity index was between 8.00% and 64.82% ac-cording to the cluster analysis results for three groups. The PCA indicated that all air pollutants affected the diversity and abundance of the epiphytic subaerial algae. Cyanothece sp. 2 is consid-ered a potential bioindicator of air pollution. It was negatively related to O3 and positively related to NO2 and CO

Numerical simulations and experiments on evaporative condensers in air conditioning systems using R744 were performed. Two configurations were given to study the feasibility of operating the subcritical R744 cycle. It indicated the capable of evaporative cooling condensing R744 to liquify by analyzing the outlet temperature at the end of the condenser reached from 28.7oC to 30.3oC with the operating pressure from 72.6 bar to 68.5 bar. The mass flow rate in the study increases from 14.34 kg/h to 46.08 kg/h, the pressure drop also increases from 0.23 bar to 0.47 bar for the simulation and 0.4 bar to 0.5 bar for the experiment, respectively. This study indicates that a 5-layers of copper tubes configuration causes a higher pressure drop and lower COP when compared to an 8-layers of copper tubes that split into 2 sets for smaller pressure drop. In this study, the evaporative condensers using mini tubes that are flooded in the cooling water tank are suitable for the subcritical R744 air conditioning system. The results obtained from the experimental data are in good agreement with those obtained from the numerical results, with the deviation less than 5%.

During the second half of August 2022, a dust intrusion event occurred, when dust that originated from the dry regions of Kalmyk steppe and the Precaspian plain was transported over the eastern region of Romania. The dry soil in these regions was the result of the severe drought over a long period of time, accentuated by early heat waves in May and June 2022. The dust event was captured by MODIS images. Smoke trains originating from fires in the north of the Azov were also detected, but these did not reach Romania. Optical parametres from AERONET was used to confirm the dust event. To determine the trajectory of the particles, the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model was used in this paper. The Ensemble median model was used to highlight the presence and concentration of dust in eastern part of Romania. Aerosols were detected between 0 and 4 km, according to radar and ceilometer data of the REXDAN cloud remote sensing facility in Galați, Romania. This dust intrusion event was the result of the dominant easterly cir-culation caused by the extension of East European High to the northeast of the continent, which transported the dust towards eastern part of Romania for more than 2 days. Moreover, the tor-rential rains between August 22nd and 24th did not clear the atmosphere of dust, since the intense easterly circulation kept carrying the dust into the Moldavian area.

The close proximity of different buildings heights can cause disturbances in the working of the smoke and ventilation ducts of lower buildings, threatening the health and even the lives of residents. To define the influence of high-rise building on the work of the ducts of the neighbouring double-storied building, experimental investigations in the wind tunnel were conducted. On this basis, empirical equations and graphs were developed leading to determining the aerodynamic coefficients considering different wind directions and the height of ducts. The direction of the wind reveals a greater influence than the height of the ducts. Properly using deflectors or increasing the height of the duct ensures maintaining static rarefaction in the area of smoke and ventilation ducts. The creation of rarefaction ensures the reliability of the natural ventilation system and the safety of the health of residents.

The cornea is an avascular tissue which has attracted much attention by the uniqueness of its anatomical characteristics, it has, in proportion, an enormous size, in relation to the number of vessels, because on average few cells in the organism are away more than 30 microns of a blood vessel. However, the cornea, with a diameter of between 11 and 12 mm, is a unique example. It has been tried to explain the notable absence of blood vessels in the cornea, arguing that corneal tissues are able to take oxygen directly from the air. In this article we are explaining that based on the physicochemical characteristics of molecular oxygen and the cell membrane, cytoplasm, water, and cellular metabolism, it is not possible that epithelial corneal cells directly take oxygen from the air, instead, corneal cells have molecules that can dissociate the water molecules thereby these cells, like any other eukaryotic cells, take the oxygen from the intracell water, like plants.

Aerosol Optical Thickness (AOT) is one of the critical factors for global atmospheric conditions, climate change, and air pollution. AOT has been exposed as a major component of air pollution in Bangladesh. This paper aims to map the seasonal distribution of AOT from 2002-2022 and to explore the internal relationship between AOT and ten air pollutants using remote sensing and machine learning tools. These ten air pollutants are Particulate matter (PM2.5), Methane (CH4), Carbon monoxide (CO), Nitrogen dioxide (NO2), Formaldehyde (HCHO), Ozone (O3), Sulfur dioxide (SO2), Aerosol Particulate Radius (APR), Nitrogen oxide (NOx) and Black carbon (BC). The results show that the concentrations of AOT were higher in December-January-February (mean value 0.50) and March-April-May (mean value 0.50) seasons, mostly in the central, western, and southern parts of Dhaka, Narayanganj, and Munshiganj districts. AOT was a bit less in June-July-August (mean value 0.33) and September-October-November (mean value 0.37). This paper also revealed that the AOT was correlated positively with PM2.5 (0.60), CH4 (0.80), NO (0.76), and BC (0.83) while correlated negatively with CO (-0.66), HCHO (-0.16), SO2 (-0.41), APR (-0.48), and NOx (-0.20). From the machine learning, the Rational quadratic GPR (RME-0.0024, MAE-0.0015, R2-0.96), Matern 5/2 GPR (RMSE-0.0023, MAE-0.0015, R2-0.96), and Squared Exponential GPR (RMSE-0.0015, MAE-0.0015, R2-0.96) were found good classifiers to predict AOT. UN agencies, government line departments, and local and regional development councils for air pollution mitigation and long-term protective measures may use the paper's key results.

Cigarette smoking and air pollution (particulate matter) are recognized as two major etiological factors for lung cancer. Of all the risk factors, cigarette smoking is significantly associated with lung carcinogenesis. The main mechanism lies in the metabolically activated carcinogens (majorly polycyclic aromatic hydrocarbons and nitrosamines), which could covalently bind with DNA molecules and lead to irreversible mutations in pivotal cancer genes, such as TP53 and KRAS. Another major etiological factor for lung cancer is air pollution, which is with complex compositions and ubiquitous in daily life, especially in developing countries as China and India. The latest literatures on lung cancer epidemiology and etiology have been briefly summarized and reviewed in this work.

Chronic obstructive pulmonary disease (COPD) is a multifactorial lung inflammatory disease affecting 174 million people worldwide, with a recently reported increased incidence in female patients. Patients with COPD are especially vulnerable to the detrimental effects of environmental exposures, especially from air particulate and gaseous pollutants. Exposure to air pollution severely influences COPD outcomes, resulting in acute exacerbations, hospitalizations, and death. In the current study, we conducted a review of the literature addressing air pollution induced acute exacerbations of COPD (AECOPD) in order to determine whether air pollution affects COPD patients in a sex-specific manner. We found that while the majority of studies enrolled both male and female patients, only a few reported results disaggregated by sex. Most studies had a higher enrollment of male patients, only four compared AECOPD outcomes between sexes, and only one study identified sex differences in AECOPD, with females displaying higher rates. Overall, our analysis of the literature confirmed that air pollution exposure is a trigger for AECOPD hospitalizations and revealed a significant gap in our knowledge of sex-specific effects of air pollutants on COPD outcomes, highlighting the need for more studies considering sex as a biological variable.

Background: Exposure in utero to particulate matter (PM2.5 and PM10) is associated with maladaptive health outcomes. Although exposure to prenatal PM2.5 and PM10 have cord blood DNA methylation signatures at birth, signature persistence into childhood and saliva cross-tissue applicability has not been tested. Methods: In the Fragile Families and Child Wellbeing Study, a United States 20-city birth cohort, average residential PM2.5 and PM10 during pregnancy was estimated using air quality monitors with inverse distance weighting. Saliva DNA methylation at ages 9 (n=749) and 15 (n=793) was measured using the Illumina HumanMethylation 450k BeadArray. Cumulative DNA methylation scores for particulate matter were estimated by weighting participant DNA methylation at each site by meta-analysis effect estimates from Gruzieva et al. 2019 and standardizing the sums. Using mixed effects regression analysis, we tested the associations between cumulative DNA methylation scores at ages 9 and 15 and PM exposure during pregnancy, adjusted for child sex, age, race/ethnicity, maternal income to needs ratio, nonmartial birth status, and saliva cell type proportions. Results: Our study sample was 50.5% male, 56.3% non-Hispanic Black, and 19.8% Hispanic, with median income to needs ratio of 1.4. In the third trimester, mean PM2.5 exposure levels were 27.9 ug/m3/day (standard deviation: 7.0, 23.7% of observations exceeded safety standards) and PM10 were 15.0 ug/m3/day (standard deviation: 3.1). An interquartile range increase in PM2.5 exposure (10.73 g/m3/day) was associated with -0.0287 standard deviation lower cumulative DNA methylation score for PM2.5 (95% CI: -0.0732, 0.0158, p=0.20) across all participants. An interquartile range increase in PM10 exposure (3.20 g/m3/day) was associated with -0.1472 standard deviation lower cumulative DNA methylation score for PM10 (95% CI: -0.3038, 0.0095, p=0.06) across all participants. The PM10 findings were driven by the age 15 subset where an interquartile range increase in PM10 exposure was associated with -0.024 standard deviation lower cumulative DNA methylation score for PM10 (95% CI: -0.043, -0.005, p=0.012). Findings were robust to adjustment for PM exposure at ages 1 and 3. Conclusion: In utero PM10 associated DNA methylation differences persist until age 15 and can be detected in saliva. Benchmarking the persistence and cell type generalizability is critical for epigenetic exposure biomarker assessment.

After the arrival of a new airborne virus to the world, science is aiming to develop solutions to withstand the spread and contagion of the SARS-CoV-2 coronavirus. The most severe among the adopted measures is to remain in home isolation for a significant number of hours per day, in order to avoid the spreading of the infection in an uncontrolled way through public spaces. Recent literature showed that the major route of transmission is via aerosols produced especially in poorly ventilated inner spaces. With regard to contagion rates, accumulated incidence or number of hospitalizations due to COVID-19, Spain has reached very high levels, therefore this article develops a quantitative and qualitative analysis of the requirements established in Spain with respect to the European framework in reference to ventilation parameters indoors. For this, a case study has been analyzed, representing a common residence in current Spanish residential developments. Results show that the criteria established in the applicable regulations are not sufficient to ensure health as well as to avoid contagion by aerosols indoors.

Three genera of very large volant birds existed for most of the Pliocene: the Pelagornithidae seabirds; the large North American Teratornithidae and the stork Leptoptilos falconeri in Africa and Asia. All became extinct around 3 Ma. The reasons for their demise are puzzling, as the Pelagornithidae had a world-wide evolutionary history of more than 50 Ma, smaller teratorns were still extant in the Holocene and smaller stork species are still globally extant. Extant large birds have a common critical takeoff airspeed suggesting a biomechanical limit in terms of power, risk and launch speed, and simulations of the flight of these extinct species suggest that at 1 bar they would have exceeded this value. Estimates for the Late Pliocene atmospheric density are derived from marine and terrestrial isotopes as well as resin chemistry, both approaches suggesting a value of about 1.2 bar, which drops to present levels during the period 3.3 to 2.6 Ma, thus a loss in atmospheric density may have caused biomechanical and ecological stress contributing to their extinction and/or development of smaller forms. This hypothesis is examined in terms of a possible mechanism of atmospheric mass loss and how this would be seen in the geological record. At 1.2 bar all the extinct species present takeoff airspeeds similar to large extant volant birds and which match the expected power and kinetic energy levels.

Concerns about China’s air quality, and its impact on the important tourism industry have been on the debate in recent years. This article aims to investigate the potential effect of air pollution on direct economic impact of tourism, using the case of Beijing and Shanghai. The results indicate that air pollution negatively affects China's inbound tourism, resulting in huge loss of tourist arrivals and receipts, and Beijing suffers a greater loss in comparison with Shanghai, its loss in tourist number amounts to 1569,700 persons, equal to CNY 10264.268 million in tourism receipts, and the GDP losses ranges from CNY 20528.536 to 41057.072 across major source countries. This study provides a quantification of the impact helpful to generate a social awareness of air pollution detrimental impacts on inbound tourism and hence the economy.

In this study, we test the performance of a compact gas chromatograph with photoionization detector (GC-PID) and optimize the configuration to detect ambient (sub-ppb) levels of benzene, toluene, ethylbenzene, and xylene isomers (BTEX). The GC-PID system was designed to serve as a relatively inexpensive (~$10k) and field-deployable air toxic screening tool alternative to conventional benchtop GCs. The instrument uses ambient air as a carrier gas, and consists of a Tenax-GR trap preconcentrator, a gas sample valve, two capillary columns, and a photoionization detector (PID) with a small footprint and low power requirement. The performance of the GC-PID has been evaluated in terms of system linearity and sensitivity in field conditions. The BTEX-GC system demonstrated the capacity to detect BTEX at levels as high as 500 ppb with a linear calibration range of 0-100 ppb. A detection limit lower than 1 ppb was found for all BTEX compounds with a sampling volume of 1 L. No significant drift in the instrument was observed. A time-varying calibration technique was established that requires minimal equipment for field operations and optimizes the sampling procedure for field measurements. With an analysis time of less than 15 minutes, the compact GC-PID is ideal for field deployment of background and polluted atmospheres for near-real time measurements of BTEX. The results highlight the application of the compact and portable GC-PID for community monitoring and screening of air toxics.

Market air quality is very important to the economic lives of the people which is rarely researched, however, market activities particularly pedestrian traffic releases particulates which is detrimental to the health of the users and stakeholders. Thermo scientific MIE pDR-1500 particulate was used to monitor the quality of air within the market for eight (8) weeks, air pollutant of concern is PM2.5. ten (10) sample points were located in the market which covers ten (10) sample points for pedestrian traffic to represent the entire market environment spectrum. The analysis of PM2.5 measured daily during dry and wet season shows a clear seasonal variation of this particular pollutant as elevated concentration was measured during the dry season than the wet season. The assessment of PM2.5 concentration shows exceedances of the standards stated by WHO and NAAQS during the dry season which ranges from 47.9 μg/m3- 231.88 μg/m3 in the morning and 65.17 μg/m3- 1806.33 μg/m3 in the afternoon. From the findings, pedestrian traffic contributes immensely to air pollution in an open market, with this elevated concentration, prolonged exposure is highly detrimental to health. This study creates awareness to the pedestrians in an open market about air pollution and informs policy changes.

In the past two decades, acoustic metamaterials have garnered much attention owing to their unique functional characteristics, which is difficult to be found in naturally available materials. The acoustic metamaterials have demonstrated to exhibit excellent acoustical characteristics that paved a new pathway for researchers to develop effective solutions for a wide variety of multifunctional applications such as low-frequency sound attenuation, sound wave manipulation, energy harvesting, acoustic focusing, acoustic cloaking, biomedical acoustics, and topological acoustics. This review provides an update on the acoustic metamaterials' recent progress for simultaneous sound attenuation and air ventilation performances. Several variants of acoustic metamaterials, such as locally resonant structures, space-coiling, holey and labyrinthine metamaterials, and Fano resonant materials, are discussed briefly. Finally, the current challenges and future outlook in this emerging field is discussed as well.

The literature, aimed at understanding the income-price elasticity of air passenger demand, bases its analysis on airport movement. The diversity of studies regarding the casualty between air transportation and economic growth are examples. Some studies covering this link, estimate the income-price relationship with the demand considering international traffic. Considering a domestic setting, where this traffic is significant in Brazil, studies related to remote regions are scarce, and the existing ones focus on governmental policies and subsidies. In addition, empirical studies on the theme consenter themselves in developed regions, such as Europe, North America, and Australia. For Brazil, where we find the Amazon region, there are no empirical researches. This paper analyses the price-income elasticity of the demand regarding domestic passengers in air links from remote cities of the Brazilian Amazon. This study uses panel data regression analysis method on a database of domestic scheduled flights of Brazil´s National Civil Aviation Agency. The results show that air passengers involving remote region flights present a lower sensitiveness regarding local income and airline´s price variations than those in flights among capitals. The higher difference is in income-elasticity of the remote city of origin, which is lower than that of the air traffic among capitals.

Population concentration in cities brings new risks as an increase in pollution, which causes urban health problems. In order to address this problem, traffic reduction measures are being implemented, as pedestrianization areas and the definition of Low Emissions Zones (LEZ). When the effectiveness of these types of measures is in doubt, smart city tools provide data that can be used to scientifically asses their impact. This article analyzes the situation of Madrid Central (Spain), a LEZ subject to controversy. We apply statistical and regression analyses to evaluate the effectiveness of this measure to reduce air pollution and outdoor noise. According to the results, this LEZ was able to significantly reduce NO$_2$, PM$_{2.5}$, and PM$_{10}$ concentration locally, having the same positive impact in the rest of the city. In terms of noise, this measure is able to mitigate background noise levels generated by the road traffic.

Background: Covid-19 was first reported in Wuhan, China in Dec 2019. Since then, it has been transmitted rapidly in China and the rest of the world. While Covid-19 transmission rate has been declining in China, it is increasing exponentially in Europe and America. Although there are numerous studies examining Covid-19 infection, including an archived paper looking into the meteorological effect, the role of outdoor air pollution has yet to be explored rigorously. It has been shown that air pollution will weaken the immune system, and increase the rate of respiratory virus infection. We postulate that outdoor air pollution concentrations will have a negative effect on Covid-19 infections in China, whilst lockdowns, characterized by strong social distancing and home isolation measures, will help to moderate such negative effect. Methods: We will collect the number of daily confirmed Covid-19 cases in 31 provincial capital cities in China during the period of 1 Dec 2019 to 20 Mar 2020 (from a popular Chinese online platform which aggregates all cases reported by the Chinese national/provincial health authorities). We will also collect daily air pollution and meteorology data at the city-level (from the Chinese National Environmental Monitoring Center and the US National Climatic Data Center), daily inter-city migration flows and intra-city movements (from Baidu). City-level demographics including age distribution and gender, education, and median household income can be obtained from the statistical yearbooks. City-level co-morbidity indicators including rates of chronic disease and co-infection can be obtained from related research articles. A regression model is developed to model the relationship between the infection rate of Covid-19 (number of confirmed cases/population at the city level) and outdoor air pollution at the city level, after taking into account confounding factors such as meteorology, inter- and intra-city movements, demographics, and co-morbidity and co-infection rates. In particular, we shall study how air pollution affects infection rates across different cities, including Wuhan. Our model will also study air pollution would affect infection rates in Wuhan before and after the lockdown. Expected findings: We expect there be a correlation between Covid-19 infection rate and outdoor air pollution. We also expect that reduced intra-city movement after the lockdowns in Wuhan and the rest of China will play an important role in reducing the infection rate. Interpretation: Infection rate is growing exponentially in major cities worldwide. We expect Covid-19 infection rate is related to the air pollution concentration, and is strongly dependent on inter- and intra-city movements. To reduce the infection rate, the international community may deploy effective air pollution reduction plans and social distancing policies.

Two isotropic pitches were prepared by air blowing and nitrogen distillation method using ethylene tar (ET) as a raw material. And correspondent carbon fibers were obtained through conventional melt spinning, stabilization and carbonization. The structures and properties of resultant pitches and fibers were characterized and their differences were discussed in this work. The results showed that introduction of the oxygen by air blowing method could quickly increase the yield and softening point of pitch. Moreover, the air blown pitch (ABP) composed of linear methylene chains of aromatic molecules while the nitrogen distilled pitch (NDP) mainly contained polycondensed aromatic rings, which was due to the oxygen containing functional groups existed in ABP could impede order stack of pitch molecules and form methylene bridge structure, instead of aromatic condensed structure like NDP. Meanwhile, the spinnability of ABP was not decreased even containing 2.31 wt% oxygen. In contrast, ABP had narrower molecular weight distribution, which contributed to better stabilization properties and higher tensile strength of carbon fiber. The tensile strength of carbon fibers from ABP was reached to 860 MPa with fiber diameter of about 10 μm, which was higher than that of NDP-derived carbon fibers of 640 MPa.

Ultraviolet (UV) light with a wavelength of 254 nm has proven to be effective at inactivating microorganisms, and thus has been increasingly employed as a method of disinfection for indoor environments. Solar UV wavelengths (300 to 400 nm) are known to initiate the formation of secondary organic aerosol (SOA) particles from photo-oxidation of volatile organic compounds in the atmosphere, but germicidal wavelengths have not been extensively studied for indoor environments. In this work, toluene was exposed to 254 nm UV light in a laboratory photoreactor, with varying conditions of the air, the duration of UV exposure, and the duration of post-UV time. The number of particles formed in the fine particulate matter (PM2.5) size range was measured, and significant levels of particle formation were observed for UV exposure periods of as short as 5 minutes. The particle formation ranged from 2.4x10⁶ particles/m³ for 5 minutes of UV exposure, to 1449.8x10⁶ particles/m³ for 15 minutes of UV exposure. Particle formation was found to increase with increasing concentrations of gas phase toluene, and at relative humidity of approximately 20% and higher. Variations in the initial number of particles present did not appear to have a significant effect on the particle formation, suggesting that nucleation was not a controlling factor. However, tests in a commercial environment showed no significant detectable PM2.5 formation, indicating that SOA formation during the intermittent use of germicidal UV may not significantly affect indoor air quality.