Filter Samples Research Articles

Active noise control performance in the high-frequency range

Noise control for vehicle mainly uses a reduction method through sound absorbing and insulating materials but has disadvantages of increasing cost and weight. It is known that the noise reduction performance of Active Noise Control (ANC) technology that can be considered as an alternative is limited to the low frequency range. However, there could be a case when the use of active noise cancellation is required at higher frequency range. Therefore, the purpose of this paper is to find out how much high-frequency noise can be controlled by applying active noise cancellation and the performance of ANC according to the equipment used. For this end, an ANC experimental environment was installed at the passenger's seat interior vehicle. By using Filtered-x Least Mean Square (FxLMS) algorithm based on adaptive control, ANC was conducted to reduce the high frequency noise in the 2kHz~4kHz and its noise reduction performance was compared according to the following variables: Filter length, step size, sampling frequency, etc. As a result of selecting the audio DSP board as the control system and applying appropriate filter length, step size, and sampling frequency, noise reduction of up to 40 dB(A) was obtained at the position of both ears of the occupant.

Beyond common urban air quality assessment: Relationship between PM2.5 and black carbon during haze and non-haze periods in Bangkok

The atmospheric pollution burden in Bangkok, Thailand, is likely to be similar to that of other large urban agglomerations. Black carbon (BC) aerosol is one of the key components of PM2.5 (particulate matter with equivalent diameter ≤2.5 μm) pollutants; jointly they adversely affect humans and the environment. This study assessed the BC and PM2.5 ambient concentrations in Bangkok over nine months (November 1, 2020, to July 27, 2021), focusing on seasonal differences during the haze period (Hp; december 2020 to February 2021) and non-haze period (NHP; remaining months). PM2.5 data were measured optically, together with filter sampling of particles at heights of 30, 75, and 110 m above ground level (AGL). A thermal/optical carbon analysis method was used to determine the BC mass concentrations in the collected samples. The results showed that the vertically averaged BC concentration within PM2.5 increased more than 3-fold from 2.82 to 9.09 μg/m3 from the NHP to the HP. The vertical dependence of BC concentration was characterized by an increase in the height AGL in the NHP. In contrast, the opposite trend was observed for the HP. The average values of the PM2.5/BC ratio at all heights AGL showed a seasonal trend, with the BC mass concentration accounting for over 25% of PM2.5 concentration during the peak of the haze season.

Pathogenic bacteria and fungi in bioaerosols from specialized hospitals in Shandong province, East China

Bacteria and fungi are abundant and ubiquitous in bioaerosols in hospital environments. Understanding the distribution and diversity of microbial communities within bioaerosols is critical for mitigating their detrimental effects. Our knowledge on the composition of bacteria or fungi in bioaerosols is limited, especially the potential pathogens present in fine particulate matter (PM2.5) from specialized hospitals. Thirty p.m.2.5 filter samples were collected from five hospitals (i.e., oral, dermatology, chest, eye, and general hospitals) in Shandong Province, East China. The diversity of bacteria and fungi was analyzed at the species level using single-molecule real-time sequencing of the 16 S and internal transcribed spacer 1 (ITS) ribosomal genes, respectively. Significant differences were detected across sampling sites in terms of microbial diversity and community composition in PM2.5 as well as pollution concentrations. The range of PM2.5 concentrations observed in hospital halls was higher, ranging from 39.0 to 46.2 μg/m3, compared to the wards where the concentrations ranged from 10.7 to 25.2 μg/m3. Furthermore, microbial variations in PM2.5 bioaerosols were associated with hospital type. The most dominant pathogens identified were Vibrio metschnikovii, Staphylococcus epidermidis, Staphylococcus haemolyticus, Fusarium pseudensiforme, and Aspergillus ruber. Among these, A. ruber was identified as an opportunistic fungus in a hospital setting for the first time. Nine potentially novel strains of F. pseudensiforme, showing 84.5%–92.0% ITS sequence similarity to known Fusarium isolates, were identified in PM2.5 samples from all hospitals (excluding an eye hospital). This study highlights the importance of hospital environments in shaping microbial aerosol communities. To the best of our knowledge, this is the first study to provide insights into the bacterial and fungal biodiversity of PM2.5 in specialized hospitals, enriching research in healthcare environmental microbiology and carrying significant public health implications.

Quantifying metallic components in aerosol filter samples using micro-synchrotron radiation X-ray fluorescence: With quartz filter as an example

Metals in atmospheric fine particulate matter (PM2.5) are presumed to have toxic effects. For environmental epidemiological studies, measuring the metallic components of PM2.5 collected by personal samplers and quartz fiber filters (QFF) has two key advantages: reducing exposure misclassification and enabling analyses of multiple (organic and inorganic) components on a single filter. We developed a sensitive, low-sample-consumption method to quantify the metallic components of PM2.5 collected on QFFs using micro-synchrotron radiation X-ray fluorescence (μ-SRXRF). Teflon filter is used here as a reference to test the substrate applicability of QFF. This method requires only a 5-mm-diameter portion of a QFF and can simultaneously quantify 15 metals with atomic numbers Z = 19–34 (i.e., K–Se, excluding Sc). The analysis time for each sample was 120–360 s, and the method detection limits were 0.04–36.6 ng/m3. We validated this method by performing cross-comparisons with two external methods: offline inductively coupled plasma mass spectrometry (ICP-MS) and online X-ray fluorescence (XRF). The slopes of the linear fits between the μ-SRXRF and offline ICP-MS methods varied from 0.40 to 1, with R2 values ranging from 0.62 to 0.98. The slopes of the linear fits between the μ-SRXRF and online XRF methods were between 0.29 and 0.89, with R2 values ranging from 0.39 to 0.80. We applied the proposed method to analyze 391 personal PM2.5 samples collected in an epidemiological study conducted in urban Beijing. By comparing the results with the ambient concentrations from a fixed monitoring site, we found that the concentrations of some metallic components in personal PM2.5 samples were significantly different from those in the corresponding fixed-site samples, with up to an order of magnitude difference. Because personal sampling can reduce the potential for exposure misclassifications, the high-resolution temporal analysis of metallic components in personal samples using the μ-SRXRF method could be a useful approach for exploring the health risks and identifying the sources of metallic components of PM2.5.

МОЯ ЖИЗНЬ С ИНСТИТУТОМ

The article is dedicated to the 90th anniversary of Irina Nikolaevna Sukhanova – phytoplanktonologist, biologist, Candidate of Biological Sciences. I. N. Sukhanova, a veteran of Russian oceanology, has worked at the Institute of Oceanology of the Academy of Sciences (IO RAS) since 1958, participated in 18 major marine expeditions of the Institute, dealt with a wide range of problems related to the structure and functioning of phytocenoses in various regions of the World Ocean, as well as the Black, Baltic and Bering Seas. She studied phytoplankton blooms and the life cycles of mass phytoplankton species with the possibility of changing autotrophic and heterotrophic types of nutrition during the development of populations. She is the first phytoplanktonologist to develop and introduce into the practice of marine research a method of soft reverse filtration of samples using nuclear filters. In this article, Irina Nikolaevna recalls her fellow scientists and her teachers, the expeditions in which she had a chance to participate and talks about her work as a phytoplanktonologist.

Aerosol and dynamical contributions to cloud droplet formation in Arctic low-level clouds

Abstract. The Arctic is one of the most rapidly warming regions of the globe. Low-level clouds and fog modify the energy transfer from and to space and play a key role in the observed strong Arctic surface warming, a phenomenon commonly termed “Arctic amplification”. The response of low-level clouds to changing aerosol characteristics throughout the year is therefore an important driver of Arctic change that currently lacks sufficient constraints. As such, during the NASCENT campaign (Ny-Ålesund AeroSol Cloud ExperimeNT) extending over a full year from October 2019 to October 2020, microphysical properties of aerosols and clouds were studied at the Zeppelin station (475 m a.s.l.), Ny-Ålesund, Svalbard, Norway. Particle number size distributions obtained from differential mobility particle sizers as well as chemical composition derived from filter samples and an aerosol chemical speciation monitor were analyzed together with meteorological data, in particular vertical wind velocity. The results were used as input to a state-of-the-art cloud droplet formation parameterization to investigate the particle sizes that can activate to cloud droplets, the levels of supersaturation that can develop, the droplet susceptibility to aerosol and the role of vertical velocity. We evaluate the parameterization and the droplet numbers calculated through a droplet closure with in-cloud in situ measurements taken during nine flights over 4 d. A remarkable finding is that, for the clouds sampled in situ, closure is successful in mixed-phase cloud conditions regardless of the cloud glaciation fraction. This suggests that ice production through ice–ice collisions or droplet shattering may have explained the high ice fraction, as opposed to rime splintering that would have significantly reduced the cloud droplet number below levels predicted by warm-cloud activation theory. We also show that pristine-like conditions during fall led to clouds that formed over an aerosol-limited regime, with high levels of supersaturation (generally around 1 %, although highly variable) that activate particles smaller than 20 nm in diameter. Clouds formed in the same regime in late spring and summer, but aerosol activation diameters were much larger due to lower cloud supersaturations (ca. 0.5 %) that develop because of higher aerosol concentrations and lower vertical velocities. The contribution of new particle formation to cloud formation was therefore strongly limited, at least until these newly formed particles started growing. However, clouds forming during the Arctic haze period (winter and early spring) can be limited by updraft velocity, although rarely, with supersaturation levels dropping below 0.1 % and generally activating larger particles (20 to 200 nm), including pollution transported over a long range. The relationship between updraft velocity and the limiting cloud droplet number agrees with previous observations of various types of clouds worldwide, which supports the universality of this relationship.

Characterising microplastics in indoor air: Insights from Raman imaging analysis of air filter samples

We are directly exposed to microplastic contamination via indoor air that we breathe daily, for which the characterisation of microplastics is still a challenge. Herein, two typical air filter samples were collected, one from an air-conditioner and another from a personal computer, both of which have been working for around half a year to collect and accumulate microplastics in the indoor air, like microplastic banks. After the sample preparation to remove the mineral dusts, Raman imaging was employed to directly and simultaneously identify and visualise microplastics of polyethylene terephthalate (PET) fibres, distinguish them from other fibres such as cellulose and cross-check them with a scanning electron microscope (SEM). To count the microplastics and to avoid the quantification bias, several areas were randomly scanned and imaged to statistically estimate the percentage of microplastic fibres in the analysed samples. The microplastics amount, which has been estimated at 73–88,000 fibers per filter per half a year, varies and depends on the indoor environment so that the air filter can work as a good indicator to monitor the quality of the indoor air from the microplastic perspective. Overall, human are directly exposed to this emerging contamination every day, raising environmental concerns. Raman imaging characterisation and its corresponding statistical information can help pursue further research on microplastics.

Desain Eksperimen TUF Dalam Peningkatan Kualitas Garam Olahan Limbah Produksi Es dengan Metode Taguchi di PT. Putra Maesa Persada

Indonesia has salt resources in seawater along the Java Sea coast. However, the high salt content in seawater causes difficulties for various industries that use seawater as their raw material. A Taguchi experimental design using TUF filters was carried out to determine the best TUF filter composition in producing high-quality salt. The factors considered were the compositions of three materials, namely crushed coral, charcoal, and palm fibers. The results obtained for the sample filters were analyzed using one-way ANOVA, Minitab, and the Signal-to-Noise Ratio (SNR) method. The optimal TUF filter composition was found to be 450g finely crushed coral, 350g finely crushed charcoal, and 30g palm fibers. The study results revealed that the best factor for improving salt quality was crushed coral, with a contribution of 65.63842% and an F-value of 109.3333. Charcoal also provided a significant contribution of 24.40453% with an F-value of 40.65041. However, palm fibers did not contribute significantly to improving salt quality. The optimal TUF filter composition can help improve salt quality and increase productivity while reducing costs for various industries such as food production and preservation. The optimal composition of 450g of crushed coral, 350g of charcoal, and 30g of palm fibers can significantly improve the quality of salt production. In conclusion, the use of TUF filters with the optimal composition of 450g crushed coral, 350g charcoal, and 30g palm fibers can significantly improve salt quality. This study provides insight into the potential applications of TUF filters and should encourage further exploration of the technology's potential in various industries.

Evaluation of sequential filtration and centrifugation to capture environmental DNA and survey microbial eukaryotic communities in aquatic environments.

Sequential membrane filtration of water samples is commonly used to monitor the diversity of aquatic microbial eukaryotes. This capture method is efficient to focus on specific taxonomic groups within a size fraction, but it is time-consuming. Centrifugation, often used to collect microorganisms from pure culture, could be seen as an alternative to capture microbial eukaryotic communities from environmental samples. Here, we compared the two capture methods to assess diversity and ecological patterns of eukaryotic communities in the Thau lagoon, France. Water samples were taken twice a month over a full year and sequential filtration targeting the picoplankton (0.2-3 μm) and larger organisms (>3 μm) was used in parallel to centrifugation. The microbial eukaryotic community in the samples was described using an environmental DNA approach targeting the V4 region of the 18S rRNA gene. The most abundant divisions in the filtration fractions and the centrifugation pellet were Dinoflagellata, Metazoa, Ochrophyta, Cryptophyta. Chlorophyta were dominant in the centrifugation pellet and the picoplankton fraction but not in the larger fraction. Diversity indices and structuring patterns of the community in the two size fractions and the centrifugation pellet were comparable. Twenty amplicon sequence variants were significantly differentially abundant between the two size fractions and the centrifugation pellet, and their temporal patterns of abundance in the two fractions combined were similar to those obtained with centrifugation. Overall, centrifugation led to similar ecological conclusions as the two filtrated fractions combined, thus making it an attractive time-efficient alternative to sequential filtration.

Radon decay product particle radioactivity and oxidative stress biomarkers in patients with COPD

Radon decay products include α-radiation emitting radionuclides that attach to airborne particles that have potential to promote oxidative tissue damage after inhalation. To assess associations between α-particle radioactivity (α-PR) with urinary biomarkers of oxidative tissue damage, 140 patients with chronic obstructive pulmonary disease (COPD) had up to four 1-week seasonal assessments (N = 413) of indoor (home) and ambient (central site) PM2.5 and black carbon (BC). Following environmental sampling, urine samples were analyzed for total and free malondialdehyde (MDA), biomarkers of lipid oxidation, and 8-hydroxyl-2′-deoxyguanosine (8-OHdG), a biomarker of DNA oxidative damage. Particle radioactivity was measured as α-activity on PM2.5 filter samples. Linear mixed-effects regression models adjusted for urinary creatinine and other personal characteristics were used to assess associations. Indoor α-PR was associated with an increase in 8-OhdG (8.53%; 95% CI: 3.12, 14.23); total MDA (5.59%; 95% CI: 0.20, 11.71); and free MDA (2.17%; 95% CI: 2.75, 7.35) per interquartile range (IQR) of α-PR [median 1.25 mBq/m3; IQR 0.64], similar adjusting for PM2.5 or BC. The ratio of indoor/ambient α-PR was positively associated with each biomarker and associations with ambient α-PR were positive but weaker than with indoor concentrations. These findings are consistent with a contribution of radon decay products as measured by α-PR to oxidative stress in patients with COPD, with a greater contribution of indoor radon decay products.

Investigating the gas-phase reaction mechanism of catechol with ozone: Product analysis and insights

Volatile aromatic compounds (VOCs) are ubiquitous in the environment, they can be emitted from biogenic and anthropogenic sources. They can contribute to the formation of many products leading to the formation of secondary organic aerosols (SOA). The products of the gas phase reaction of 1,2-benzenediol (catechol) with ozone were studied in a simulation chamber at atmospheric pressure and 294 ± 2 K in presence of different levels of relative humidity (0–60%). The gas phase products were monitored continuously by a PTR-ToF-MS for 2 h, whereas filters samples were collected directly from the reaction chamber and analyzed by thermo-desorption gas chromatography; TD-GC-MS. This study shows the different potential chemical pathways that catechol could follow to form a variety of products under dry, low and high humidity conditions. The molecular mass 98 was found to be distinctive and appears in the gas phase when humidity in the reaction chamber is between 20 and 60%. Other new masses (m/z) such as 176, 154, 116, 68, 72, 80, 96, 108, and 124 were also detected under different experimental conditions. Furthermore, the catechol concentration has been monitored continuously by a PTR-ToF-MS from low to high humidity conditions (RH = 7.5−78.8%). The purpose of the latter is to suggest that the formation of catechol-H2O clusters occurs in the gas phase of the reaction chamber causing a decrease in catechol reactivity towards ozone and other gases and subsequently a decrease in the rate constant.

Empirical Filtering-Based Artificial Intelligence Learning Diagnosis of Series DC Arc Faults in Time Domains

Direct current (DC) networks play a pivotal role in the growing integration of renewable energy sources. However, the occurrence of DC arc faults can introduce disruptions and pose fire hazards within these networks. In order to ensure both safety and optimal functionality, it becomes imperative to comprehend the characteristics of DC arc faults and implement a dependable detection system. This paper introduces an innovative arc fault detection algorithm that leverages current filtering based on the empirical rule in conjunction with intelligent machine learning techniques. The core of this approach involves the sampling and subsequent filtration of current using the empirical rule. This filtering process effectively amplifies the distinctions between normal and arcing states, thereby enhancing the overall performance of the intelligent learning techniques integrated into the system. Furthermore, this proposed diagnosis scheme requires only the signal from the current sensor, which reduces the complexity of the diagnosis scheme. The results obtained from the detection process serve to affirm the effectiveness and reliability of the proposed DC arc fault diagnosis scheme.

Characterising a mobile reference station (MoRS) to quantify personal exposure to air quality

There is increasing clinical, epidemiological, and toxicological evidence linking exposure to air pollution with multiple health outcomes that lead to increased mortality and morbidity. Traditionally, fixed air quality monitors have been used to provide ambient air pollution measurements, but they have spatial and temporal limitations. Rapid advances in instrument miniaturisation have made novel sensing technologies more accessible but these are prone to high sensitivity and inaccuracies. To bridge the gap between fixed monitors and small sensors we have developed a Mobile Reference Station (MoRS) – a portable platform delivering high quality measurements of air pollutants using smaller, low power reference grade instruments at high time resolutions. MoRS enables the simultaneous measurement of a broad aerosol size distribution (10 nm–35 μm), gaseous pollutant concentrations (nitrogen dioxide (NO2) and ozone (O3)), environmental parameters (noise, relatively humidity (RH) and temperature) as well as collecting filter samples for laboratory analysis. The MoRS instrumentation is described and the major challenges in ensuring that high data quality standards are maintained are discussed. Laboratory and field tests were used to derive scaling factors for all the MoRSinstrumentation. Field testing of MoRS showed excellent intercomparability against reference instrumentation (R2 > 0.98) and good agreement with reference instruments in the ultrafine aerosol range, although there was an overestimation of fine particle aerosols. Measurements taken during example mainline train and London Underground (LU) journeys are displayed showing the value of the high-quality data derived from MoRS and how this can help to disentangle multiple confounding environmental pollutants and enrich epidemiological studies.

Ferrous determination in ground and brackish water by high-resolution electrospray ionization mass spectrometry

Generally, methods using nebulizers such as in Electrospray Ionization Mass Spectrometry (ESI-MS) or Induced Coupled Plasma Mass Spectrometry(ICP-MS) for the determination of Fe(II) in seawater are difficult because of the high concentration of salt. In earlier studies, we determined Fe(II) in river water with 1,10-phenanthroline (phen) and measured the complexed species by ESI-MS, but a method to reduce the interference of salts in seawater is lacking. After filtration of water samples with a 0.45 µm membrane on site, the sample was immediately added into a previously prepared solution containing sodium perchlorate (NaClO4) and phen in nitrobenzene (NB). After shaking for 20 min, Fe(II) was extracted into nitrobenzene (NB) with the perchlorate ions. The NB was introduced to an ESI-MS, using a syringe. The Fe(II)-phen complex and perchlorate ions in NB were more stable than in the aqueous solution.Approximately 99.6 % of Fe(II) was extracted into the organic phase. In our previously presented data, Fe(II) was complexed with 1,10-phenanthroline in aqueous solution, and measured by HR-ESI-MS, a standard addition method was used, and a calibration curve was obtained. In this method, the samples were added to 0.025, 0.05, 0.1 and 0.2 Fe(II)/µmol/L and a calibration curve (R2 = 0.993) of the peak intensity was determined by HR-ESI-MS from the total peak areas of [Fe(phen)₂-NB]2+m/z 269.5 and [Fe(phen)3]2+m/z 298.2. In the present study, the concentration of Fe(II) in brackish water containing 1 % salt was determined to be 0.184 ± 0.05 µM, and the total iron concentration was determined by ICP-MS and found to be 0.70 µM. Fe(II)/Fetotal was 26 %, the groundwater sample contained Fe(II) 0.146 ± 0.002 µM, Fetotal was 0.23 ± 0.02 µM, and Fe(II)/Fetotal was 63 %. Groundwater is less sensitive to oxygen and therefore has a higher proportion of Fe(II) to total iron. In brackish water, on the other hand, the proportion of Fe(II) can be higher or lower because it is affected by oxygen supply from the surface and reduction from the bottom sediment. Therefore, the Fe(II) concentration was relatively high, but in brackish water, Fe(II) was low, but Fetotal was high.

Next-generation ice-nucleating particle sampling on board aircraft: characterization of the High-volume flow aERosol particle filter sAmpler (HERA)

Abstract. Atmospheric ice-nucleating particle (INP) concentration data from the free troposphere are sparse but urgently needed to understand vertical transport processes of INPs and their influence on cloud formation and properties. Here, we introduce the new High-volume flow aERosol particle filter sAmpler (HERA) which was specially developed for installation on research aircraft and subsequent offline INP analysis. HERA is a modular system consisting of a sampling unit and a powerful pump unit, and it has several features which were integrated specifically for INP sampling. Firstly, the pump unit enables sampling at flow rates exceeding 100 L min−1, which is well above typical flow rates of aircraft INP sampling systems described in the literature (∼ 10 L min−1). Consequently, required sampling times to capture rare, high-temperature INPs (≥ −15 ∘C) are reduced in comparison to other systems, and potential source regions of INPs can be confined more precisely. Secondly, the sampling unit is designed as a seven-way valve, enabling switching between six filter holders and a bypass with one filter being sampled at a time. In contrast to other aircraft INP sampling systems, the valve position is remote-controlled via software so that manual filter changes during flight are eliminated and the potential for sample contamination is decreased. This design is compatible with a high degree of automation, i.e., triggering filter changes depending on parameters like flight altitude, geographical location, temperature, or time. In addition to presenting the design and principle of operation of HERA, this paper describes laboratory characterization experiments with size-selected test substances, i.e., SNOMAX® and Arizona Test Dust. The particles were sampled on filters with HERA, varying either particle diameter (300 to 800 nm) or flow rate (10 to 100 L min−1) between experiments. The subsequent offline INP analysis showed good agreement with literature data and comparable sampling efficiencies for all investigated particle sizes and flow rates. Furthermore, the collection efficiency of atmospheric INPs in HERA was compared to a straightforward filter sampler and good agreement was found. Finally, results from the first campaign of HERA on the High Altitude and LOng range research aircraft (HALO) demonstrate the functionality of the new system in the context of aircraft application.

Air quality impacts of a large waste fire in Stockholm, Sweden

Fires in waste facilities are a common occurrence. Since many waste facilities are located adjacent to densely populated areas, these fires could potentially expose large populations to the emitted pollutants. However, at the moment there are only few field studies investigating the impact of waste fire emissions on air quality since the unpredictable nature of these events makes them challenging to capture.This study investigated the impact of a large and persistent un-prescribed fire in a waste storage facility in Stockholm county, Sweden, on the local air quality of two residential areas in close proximity to the fire. In-situ measurements of particulate matter, black carbon and nitrogen oxide concentrations were conducted both during open burning and after the fire was fully covered. In addition, filter samples were collected for offline analysis of organic composition, metal content and toxicity.Strongly increased concentrations of PM10, PM2.5 and black carbon were found during the open burning period, especially when the wind was coming from the direction of the fire. In addition, elevated concentrations of particulate heavy metals and polycyclic aromatic hydrocarbons were observed in the air during the open burning period. These results show that waste fires can have a strong impact on the air quality of nearby residential areas.

Characterizing water-soluble brown carbon in fine particles in four typical cities in northwestern China during wintertime: integrating optical properties with chemical processes

Abstract. Brown carbon (BrC) aerosol could impact atmospheric radiative forcing and play a crucial role in atmospheric photochemistry. In this study, fine particulate matter (PM2.5) filter samples were collected synchronously in four major cities in northwestern China during the winter season (December 2019–January 2020): Lanzhou (LZ), Xining (XN), Yinchuan (YC), and Ürümqi (UR), which are represented as energy-producing and heavy manufacturing cities in China. The primary aim of the study is to explore the optical properties, sources, and chemical processes of water-soluble BrC (WS-BrC). The average mass absorption efficiency at 365 nm (MAE365) of WS-BrC at these four cities was 1.24 ± 0.19 m2 g−1 (XN), 1.19 ± 0.12 m2 g−1 (LZ), 1.07 ± 0.23 m2 g−1 (YC), and 0.78 ± 0.16 m2 g−1 (UR). The properties of WS-BrC were further investigated by an acid–base titration experiment. The results showed that the MAE365 values in all cities increased with higher pH values (2–11), while the fluorescence intensities of water extracts fluctuated with pH values, being stronger under both highly acidic and basic conditions. The sensitivity to pH variation was most pronounced in the WS-BrC samples from YC and LZ, indicating the important contribution of acid or base functional group compounds in these locations. Additionally, the study revealed significant photo-enhancement (LZ) or photo-bleaching (YC and UR) phenomena of WS-BrC in different cities. These results suggest that the sources and/or chemical processes of WS-BrC varied among the cities. The sources and chemical processes of WS-BrC were further explored by a combination of parallel factor analysis (PARAFAC) on excitation–emission matrix (EEM) spectra of WS-BrC and positive matrix factorization analysis (PMF) on high-resolution mass spectra of water-soluble organic aerosol (WSOA). Six PARAFAC components were identified, including three humic-like substances (HULIS; two less oxygenated (LO) HULIS and one highly oxygenated (HO) HULIS), two protein-like or phenol-like substances (PLS), and one undefined substance. Four PMF factors were identified, including a water-soluble primary OA (WS-POA), a less oxidized oxygenated OA associated with coal combustion-induced WSOA (LO-OOA), and two highly oxidized oxygenated OAs resulting from photochemical oxidation and aqueous-phase oxidation transformations (HO-OOA1 and HO-OOA2). WS-POA was determined to be the most significant source of light absorption, accounting for 30 %–60 % based on multiple linear regression models, and it showed a significant correlation with PLS and LO-HULIS components. The loss of light absorption of WS-POA was found to occur through its conversion to LO-OOA and HO-OOAs through photochemical or aqueous reactions, with HO-OOAs being significantly correlated with the HO-HULIS component. These processes can be clearly illustrated by integrating optical properties and chemical composition using a Van Krevelen diagram and an EEM plot.

Cascaded Control System Design for Quadrotor UAV through Relay with Embedded Integrator-Based Automatic Tuning Approach

Due to their enormous characteristics and applicability, quadrotor unmanned aerial vehicles (UAVs) have enjoyed much popularity lately. However, designing a stable control strategy for quadrotors still remains one of the major concerns mainly due to the requirement of an accurate system model. They are naturally underactuated systems, with complex and nonlinear dynamics as well as interaxes couplings. Considering the dynamical complexities of these vehicles, one of the efficient methods is to utilize the relay feedback experiments and automatic tuning approach to tackle these issues. This paper investigates the employment of the relay with embedded integrator approach, wherein the quadrotor dynamics are estimated effectively with minimal parameters as compared to previously utilized relay with hysteresis technique. Frequency sampling filter (FSF) is further utilized for the extraction of the needful data through the signals obtained using the relay experiments, followed by the estimation of the plant dynamics. PID controllers have then been developed using the approximated quadrotor models. Which are used in the proposed cascade control structure for the quadrotor. The demonstrated results and analysis present the efficacy of designed control system technique for the quadrotor UAV.

Forecast of the outlet turbidity and filtered volume in different microirrigation filters and filtration media by using machine learning techniques

Different media filters and filtration media are used to eliminate suspended particles in microirrigation and therefore prevent clogging in the emitter. The water volume by filtration cycle is a parameter related to the filter and media capacity to retain particles, while turbidity is a variable related to particles in suspension in the water. Since turbidity can be measured easily and quickly, it is commonly mentioned in recommendations for the reuse of effluents in microirrigation. There are currently no models that are reliable enough to predict the filtered volume in each irrigation filter and outlet turbidity when using different filter types and media configurations. The object of this work was to propose a model that can detect early the filtered volume and the turbidity at the outlet values. This investigation presents an effective machine learning method, the Random Forest regression (RFR) in combination with the population-inspired metaheuristic optimization algorithm, called Differential Evolution (DE), for estimating the output turbidity and the filtered volume from a dataset with 1,016 samples of distinct media filters that use reclaimed effluent. The same experimental dataset was also fitted with Elastic-net, Lasso and Ridge regression machine learning methods also in combination with DE optimizer for comparison. This optimization performs the parameter tuning in the RFR using the training dataset, which considerably improves the accuracy of the regression. To achieve this, the most relevant operation input variables are tracked and analyzed: the kind of medium and filter, filtration velocity (v), height of the filter bed (H), cycle duration and the electrical conductivity for the filter inlet (ECi), pHi, dissolved oxygen (DOi), water temperature (Ti) and the input turbidity (Turbi). There are two kinds of results. Firstly, the importance ranking of the input variables on the outlet turbidity and filtered volume is presented using the DE/RFR model. Secondly, an innovative model for the prediction of the outlet turbidity and filtered volume was built and a regression with optimized parameters was done and coefficients of determination of 0.9331 and 0.8712 for filtered volume and outlet turbidity were obtained with this DE/RFR–based model, respectively. Additionally, the outcomes from the Elastic-net, Lasso and Ridge models are worse than DE/RFR–relied model estimations. The DE/RFR-based model’s strong performance was confirmed by the agreement between experimental data and the latter results.

Response of organic aerosol to Delhi's pollution control measures over the period 2011–2018

Some of the world's highest air pollution episodes occur in Delhi, India and studies have shown particulate matter (PM) is the leading air pollutant to cause adverse health effects on Delhi's population. It is therefore vital to chart sources of PM over long time periods to effectively identify trends, particularly as multiple air quality mitigation measures have been implemented in Delhi over the past 10 years but remain unevaluated. An automated offline aerosol mass spectrometry (AMS) method has been developed which has enabled high-throughput analysis of PM filters. This novel offline-AMS method uses an organic solvent mix of acetone and water to deliver high extraction recoveries of organic aerosol (OA) (95.4 ± 8.3%). Positive matrix factorisation (PMF) source apportionment was performed on the OA fraction extracted from PM10 filter samples collected in Delhi in 2011, 2015 and 2018 to provide snapshots of the responses of OA to changes in sources in Delhi. The nine factors of OA resolved by PMF group into four primary source categories: traffic, cooking, coal-combustion and burning-related (solid fuel or open burning). Burning-related OA made the largest contribution during the winter and post-monsoon, when total OA concentrations were at their highest. Annual mean burning-related OA concentrations declined by 47% between 2015 and 2018, likely associated with the 2015 ban on open waste burning and controls and incentives to reduce crop-residue burning. Compositional analysis of OA factors shows municipal waste burning tracers still present in 2018, indicating further scope to reduce burning-related OA. The closure of the two coal power stations, along with initiatives to decrease coal use in industry, businesses, and residential homes, resulted in a significant decrease (87%) in coal-combustion OA. This corresponds to a 17% reduction in total OA, which shows the effectiveness of these measures in reducing PM10. Increases in traffic OA appear to have been offset by the introduction of the Bharat stage emissions standards for vehicles as the increases do not reflect the rapid increase in registered vehicles. However, daytime restrictions on heavy goods vehicles (HGVs) entering the city is linked to large increases in PM10 during the winter and post-monsoon, likely because the large influx of diesel-engine HGVs during the early mornings and evenings is timed with a particularly low planetary boundary layer height that enhances surface concentrations.