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The impact of light intensity on the toxicity of pyrene, a 4-ring polycyclic aromatic hydrocarbon (PAH), was studied in Chlorella vulgaris and Scenedesmus acutus. Both species were cultured under low light, LL [50-60 µmol(photon) m-2 s-1], and high light, HL [100-110 µmol(photon) m-2 s-1] conditions to study the effects of pyrene (PYR) toxicity on growth parameters, the content of biomolecules, chlorophyll content, and photosynthetic efficiency. In the presence of PYR, S. acutus could grow well in LL and HL intensity. On the other hand, C. vulgaris showed a drastic decrease in growth and photosynthesis during HL conditions due to PYR toxicity. Regulation of nonphotochemical and photochemical quenching was responsible for the survival of S. acutus under PYR toxicity in LL and HL conditions. Thus, S. acutus seems to be a more promising candidate for pyrene degradation under varying light conditions.

In recent years, the Indian capital city of Delhi has been impacted by very high levels of air pollution, especially during winter. Comprehensive knowledge of the composition and sources of the organic aerosol (OA), which constitutes a substantial fraction of total particulate mass (PM) in Delhi, is central to formulating effective public health policies. Previous source apportionment studies in Delhi identified key sources of primary OA (POA) and showed that secondary OA (SOA) played a major role but were unable to resolve specific SOA sources. We address the latter through the first field deployment of an extractive electrospray ionization time-of-flight mass spectrometer (EESI-TOF) in Delhi, together with a high-resolution aerosol mass spectrometer (AMS). Measurements were conducted during the winter of 2018/19, and positive matrix factorization (PMF) was used separately on AMS and EESI-TOF datasets to apportion the sources of OA. AMS PMF analysis yielded three primary and two secondary factors which were attributed to hydrocarbon-like OA (HOA), biomass burning OA (BBOA-1 and BBOA-2), more oxidized oxygenated OA (MO-OOA), and less oxidized oxygenated OA (LO-OOA). On average, 40 % of the total OA mass was apportioned to the secondary factors. The SOA contribution to total OA mass varied greatly between the daytime (76.8 %, 10:00–16:00 local time (LT)) and nighttime (31.0 %, 21:00–04:00 LT). The higher chemical resolution of EESI-TOF data allowed identification of individual SOA sources. The EESI-TOF PMF analysis in total yielded six factors, two of which were primary factors (primary biomass burning and cooking-related OA). The remaining four factors were predominantly of secondary origin: aromatic SOA, biogenic SOA, aged biomass burning SOA, and mixed urban SOA. Due to the uncertainties in the EESI-TOF ion sensitivities, mass concentrations of EESI-TOF SOA-dominated factors were related to the total AMS SOA (i.e. MO-OOA + LO-OOA) by multiple linear regression (MLR). Aromatic SOA was the major SOA component during the daytime, with a 55.2 % contribution to total SOA mass (42.4 % contribution to total OA). Its contribution to total SOA, however, decreased to 25.4 % (7.9 % of total OA) during the nighttime. This factor was attributed to the oxidation of light aromatic compounds emitted mostly from traffic. Biogenic SOA accounted for 18.4 % of total SOA mass (14.2 % of total OA) during the daytime and 36.1 % of total SOA mass (11.2 % of total OA) during the nighttime. Aged biomass burning and mixed urban SOA accounted for 15.2 % and 11.0 % of total SOA mass (11.7 % and 8.5 % of total OA mass), respectively, during the daytime and 15.4 % and 22.9 % of total SOA mass (4.8 % and 7.1 % of total OA mass), respectively, during the nighttime. A simple dilution–partitioning model was applied on all EESI-TOF factors to estimate the fraction of observed daytime concentrations resulting from local photochemical production (SOA) or emissions (POA). Aromatic SOA, aged biomass burning, and mixed urban SOA were all found to be dominated by local photochemical production, likely from the oxidation of locally emitted volatile organic compounds (VOCs). In contrast, biogenic SOA was related to the oxidation of diffuse regional emissions of isoprene and monoterpenes. The findings of this study show that in Delhi, the nighttime high concentrations are caused by POA emissions led by traffic and biomass burning and the daytime OA is dominated by SOA, with aromatic SOA accounting for the largest fraction. Because aromatic SOA is possibly more toxic than biogenic SOA and primary OA, its dominance during the daytime suggests an increased OA toxicity and health-related consequences for the general public.

Kraków is routinely affected by very high air pollution levels, especially during the winter months. Although a lot of effort has been made to characterize ambient aerosol, there is a lack of online and long-term measurements of non-refractory aerosol. Our measurements at the AGH University of Science and Technology provide the online long-term chemical composition of ambient submicron particulate matter (PM1) between January 2018 and April 2019. Here we report the chemical characterization of non-refractory submicron aerosol and source apportionment of the organic fraction by positive matrix factorization (PMF). In contrast to other long-term source apportionment studies, we let a small PMF window roll over the dataset instead of performing PMF over the full dataset or on separate seasons. In this way, the seasonal variation in the source profiles can be captured. The uncertainties in the PMF solutions are addressed by the bootstrap resampling strategy and the random a-value approach for constrained factors. We observe clear seasonal patterns in the concentration and composition of PM1, with high concentrations during the winter months and lower concentrations during the summer months. Organics are the dominant species throughout the campaign. Five organic aerosol (OA) factors are resolved, of which three are of a primary nature (hydrocarbon-like OA (HOA), biomass burning OA (BBOA) and coal combustion OA (CCOA)) and two are of a secondary nature (more oxidized oxygenated OA (MO-OOA) and less oxidized oxygenated OA (LO-OOA)). While HOA contributes on average 8.6 % ± 2.3 % throughout the campaign, the solid-fuel-combustion-related BBOA and CCOA show a clear seasonal trend with average contributions of 10.4 % ± 2.7 % and 14.1 %, ±2.1 %, respectively. Not only BBOA but also CCOA is associated with residential heating because of the pronounced yearly cycle where the highest contributions are observed during wintertime. Throughout the campaign, the OOA can be separated into MO-OOA and LO-OOA with average contributions of 38.4 % ± 8.4 % and 28.5 % ± 11.2 %, respectively.

In recent years, intense haze events in megacities such as Beijing have received significant attention. Although secondary organic aerosol (SOA) has been identified as a major contributor to such events, knowledge of its sources and formation mechanisms remains uncertain. We investigate this question through the first field deployment of the extractive electrospray ionisation time-of-flight mass spectrometer (EESI-TOF) in Beijing, together with an Aerodyne long-time-of-flight aerosol mass spectrometer (L-TOF AMS). Measurements were performed during autumn and winter 2017, capturing the transition from non-heating to heating seasons. Source apportionment resolved four factors related to primary organic aerosols (traffic, cooking, biomass burning, and coal combustion), as well as four related to SOA. Of the SOA factors, two were related to solid fuel combustion (SFC), one to SOA generated from aqueous chemistry, and one to mixed/indeterminate sources. The SFC factors were identified from spectral signatures corresponding to aromatic oxidation products, while the aqueous SOA factor was characterised by signatures of small organic acids and diacids and unusually low CO+/CO2+ fragment ratios measured by the AMS. Solid fuel combustion was the dominant source of SOA during the heating season. However, a comparably intense haze event was also observed in the non-heating season and was dominated by the aqueous SOA factor. During this event, aqueous chemistry was promoted by the combination of high relative humidity and air masses passing over high-NOx regions to the south and east of Beijing, leading to high particulate nitrate. The resulting high liquid water content was highly correlated with the concentration of the aqueous SOA factor. These results highlight the strong compositional variability between different haze events, indicating the need to consider multiple formation pathways and precursor sources to describe SOA during intense haze events in Beijing.

Graphic Organizers are visual and graphic display that illustrates the correlations between facts, terms, and ideas with a learning task. Integrating Graphic Organizers can enhance the efficiency of the teacher's delivery of lessons and students' learning. However, no study had been conducted in using graphic organizers in the process of teaching and learning. Therefore, this explanatory mixed-method study aimed to investigate the effectiveness of Graphic Organizers in teaching Chemical Bonding to grade nine (n=98) students in Samtse Dzongkhag, Bhutan. The study's main objective was to compare the academic achievement of the control group (n=53) and experimental group (n=45) and also to investigate students' and teachers' (n=6) perceptions of using Graphic Organizers in teaching and learning Chemistry over four weeks. Learning achievement tests (pre-test and post-test), semi structured interviews, and survey questionnaires were used to collect the quantitative data and qualitative data. The independent sample t-test analysis of the post-test scores revealed a statistically significant difference between the control group and the experimental group with a mean difference value of 1.17 (p=0.017), indicating that the use of Graphic Organizers improved the students' learning achievement which was also reflected in the qualitative data gathered through interview and survey questionnaire. As a result, this study strongly suggests the use of graphic Organizers as a teaching and learning tool to improve students' academic performance in Chemistry.

In Indian society, caste is assigned to us before birth. Caste positions individuals in a social, economic, and political hierarchy. This study explores the meaning of caste discrimination from the perspectives of individuals who experience it in their everyday lives. Many studies have focused on the causes and consequences of caste discrimination and the nature of caste discrimination in different settings. Still, very few have dealt with the "meaning" of caste discrimination and how that meaning-making occurs in the context of present-day academia.This paper adopts an ecological systems approach to explore individuals' interactions with different social settings. Grounded in the epistemological standpoint of social constructionism, the study explored the meaning of caste discrimination through semi-structured interviews and focus group discussions conducted with 22 students who belonged to reserved categories. Constructivist grounded theory was used for analysis to understand the process of meaning formation along with the meaning of caste discrimination. We found that students conceive caste discrimination as the maintenance of the social hierarchy, imposition of rigid identity, and invalidation of caste discriminatory practices. This conception of the meaning was influenced by multiple factors, such as interactions with peers, local cultural ideologies, and treatment received in the academia by teaching and non-teaching staff. The study's findings indicate the need for an integrative indigenous theory of caste discrimination to ensure equitable higher education.

We present highly time-resolved (30 to 120 min) measurements of size-fractionated (PM10 and PM2.5) elements in two cities in Asia (Delhi and Beijing) and Europe (Krakow and London). For most elements, the mean concentrations in PM10 and PM2.5 are higher in the Asian cities (up to 24 and 28 times, respectively) than in Krakow and often higher in Delhi than in Beijing. Among European cities, Krakow shows higher elemental concentrations (up to 20 and 27 times, respectively) than London. Hourly maximum concentrations of Pb and Zn reach up to 1 µg m−3 in Delhi, substantially higher than at the other sites. The enrichment factor of an element together with the size distribution allows for a rough classification of elements by major source. We define five groups: (1) dust emissions, (2) non-exhaust traffic emissions, (3) solid fuel combustion, (4) mixed traffic/industrial emissions, and (5) industrial/coal/waste burning emissions, with the last group exhibiting the most site-to-site variability. We demonstrate that the high time resolution and size-segregated elemental dataset can be a powerful tool to assess aerosol composition and sources in urban environments. Our results highlight the need to consider the size distributions of toxic elements, diurnal patterns of targeted emissions, and local vs. regional effects in formulating effective environmental policies to protect public health.

Source emissions with high covariance degrade the performance of multivariate models, and often highly-time resolved data is needed to accurately extract the contribution of different emissions. Here, we use highly time-resolved size segregated elemental composition data to apportion the sources of the elemental fraction of PM in Zürich (May 2019–May 2020). For data collection, we have used an ambient metals monitor, Xact 625i, equipped with a sampling inlet alternating between PM2.5 and PM10. By implementing interpolation and a newly proposed uncertainty estimation methodology, it was possible to obtain and use in PMF a combined dataset of PM2.5 and PMcoarse (PM10-2.5) having data from only one instrument. The combination of the inlet switching system, the instrument's high time resolution, and the use of advanced source apportionment approaches yielded improved source apportionment results in terms of the number of identified sources, as the model, additionally to the diurnal and seasonal variation of the dataset, also utilizes the variation from the size segregated data. Thirteen sources of elements were identified, i.e., sea salt (5.4%), biomass burning (7.2%), construction (4.3%), industrial (3.3%), light-duty vehicles (5.4%), Pb (0.7%), Zn (0.7%), dust (22.1%), transported dust (9.5%), sulfates (15.4%), heavy-duty vehicles (17%), railway (6.6%) and fireworks (2.4%). The Covid-19 lockdown effect in PM sources in the area was also quantified. High-intensity events disproportionally affect the PMF solution, and in many cases, they are getting discarded before analysis, removing thus valuable information from the dataset. In this study, a three-step source apportionment approach was used to get a well-resolved unmixed solution when firework data points were included in the analysis. This approach can also be used for other sources and/or events with very high contributions that distort source apportionment analysis. Optimized source apportionment techniques are necessary for effective air pollution monitoring.

Characteristics and sources of volatile organic compounds (VOCs) were investigated with highly time-resolved simultaneous measurements by two proton-transfer-reaction time-of-flight mass spectrometers (PTR-ToF-MS) at an urban and a suburban site in New Delhi, India, from January to March 2018. During the measurement period, high mixing ratios of VOCs and trace gases were observed, with high nocturnal mixing ratios and strong day–night variations. The positive matrix factorization (PMF) receptor model was applied separately to the two sites, and six major factors of VOCs were identified at both sites, i.e., two factors related to traffic emissions, two to solid fuel combustion, and two secondary factors. At the urban site, traffic-related emissions comprising mostly mono-aromatic compounds were the dominant sources, contributing 56.6 % of the total mixing ratio, compared to 36.0 % at the suburban site. Emissions from various solid fuel combustion processes, particularly in the night, were identified as a significant source of aromatics, phenols and furans at both sites. The secondary factors accounted for 15.9 % of the total VOC concentration at the urban site and for 33.6 % at the suburban site. They were dominated by oxygenated VOCs and exhibited substantially higher contributions during daytime.

The measurement of elements in PM10 was performed with 1 h time resolution at a rural freeway site during summer 2015 in Switzerland using the Xact1 625 Ambient Metals Monitor. On average the Xact elements (without accounting for oxygen and other associated elements) make up about 20 % of the total PM10 mass (14.6 µg m−3). We conducted source apportionment by positive matrix factorisation (PMF) of the elemental mass measurable by the Xact (i.e. major elements heavier than Al), defined here as PM10el. Eight different sources were identified in PM10el (elemental PM10) mass driven by the sum of 14 elements (notable elements in brackets): Fireworks-I (K, S, Ba and Cl), Fireworks-II (K), sea salt (Cl), secondary sulfate (S), background dust (Si, Ti), road dust (Ca), non-exhaust traffic-related elements (Fe) and industrial elements (Zn and Pb). The major components were secondary sulfate and non-exhaust traffic-related elements followed by background dust and road dust factors, explaining 21 %, 20 %, 18 % and 16 % of the analysed PM10 elemental mass, respectively, with the factor mass not corrected for oxygen content. Further, there were minor contributions (on the order of a few percent) of sea salt and industrial sources. The regionally influenced secondary sulfate factor showed negligible resuspension, and concentrations were similar throughout the day. The significant loads of the non-exhaust traffic-related and road dust factors with strong diurnal variations highlight the continuing importance of vehicle-related air pollutants at this site. Enhanced control of PMF implemented via the SourceFinder software (SoFi Pro version 6.2, PSI, Switzerland) allowed for a successful apportionment of transient sources such as the two firework factors and sea salt, which remained mixed when analysed by unconstrained PMF.

Purpose: With the increasing incidence of a novel coronavirus SARS-CoV-2 causing COVID-19 cases, accurate and early detection infection is need of the hour for effective prevention and management. Therefore, the aim of this study was to develop a colorimetric reverse transcriptional loop-mediated isothermal amplification for rapid detection of SARS-CoV-2. Methods & Materials: Inactivated SARS-CoV-2 virus samples were procured from the National Institute of Virology, Pune, India. Various genes were targeted for primer design, such as nucleocapsid, spike, RNA dependent RNA polymerase, and envelop genes region of SARS-CoV-2. In-vitro synthesised viral RNA was used for the standardisation of the RT-LAMP. RT-LAMP products were visualised by the naked eye using hydroxy naphthol blue dye. The sensitivity of RT-LAMP assay was performed by diluting in-vitro synthesised viral RNA at a different concentration such as 5 ng/µl, 25 ng/µl, 50 ng/µl, 200 ng/µl. Additionally, the RNA copy number was estimated and tested with RT-LAMP. In-silico analysis was carried to calculating the percentage of mismatch using various viral sequences, including SARS-CoV-2, other coronaviruses, and other related RNA virus sequences available at GenBank. Results: RT-LAMP assay was standardised using in-vitro synthesised viral RNA. Temperature and time standardisation revealed, all the targets i.e., E, S, N, and RdRp gene regions had an optimum temperature of 63°C and time, 60 min. The sensitivity of all the target genes were ten copies of viral RNA. RT-LAMP amplified products were visualised by the naked eye using hydroxy naphthol blue dye and verified by agarose gel electrophoresis. All the primers used for the RT-LAMP assay showed a zero percent mismatch with SARS-CoV-2 sequences available at GenBank. Conclusion: Colorimetric reverse transcriptional loop-mediated isothermal amplification assay developed in this study could provide a visual and faster alternative to the RT-qPCR assays.

Purpose: Testing of SARS-CoV-2 for large populations is crucial for diagnosis, epidemiology, and surveillance of COVID-19. Currently, reverse transcription (RT) qPCR (RT-qPCR) is being performed worldwide and considered as a gold standard. As an alternative nucleic acid amplification test (NAAT)-based method, RT- polymerase spiral reaction (RT-PSR) assay can be a rapid, robust, and cost-effective point-of-care detection of SARS-CoV-2. Methods & Materials: Inactivated SARS-CoV-2 virus samples were provided by the National Institute of Virology, India for this study. Specific primers targeting Nucleocapsid (N) gene, and RNA-dependent RNA polymerase (RdRp) genes of SARS-CoV-2 were designed for RT-PSR assay. Purified RNA was used for the standardisation of the RT-PSR using in vitro synthesised viral RNA. A simple visual detection of SARS-CoV-2 by the naked eye was optimised using hydroxy naphthol blue dye. The sensitivity of the assay was performed by diluting viral RNA at various concentrations. The limit of detection was estimated and tested with RT-PSR. Computational analysis was performed to determine the specificity of the primers by calculating the percentage of mismatch using various novel coronavirus sequences, other coronaviruses, and other related RNA virus sequences. Results: Temperature and time for RT-PSR assay were found to be optimum at 63°C and 60 min, respectively, for both the gene targets. RT-PSR assay amplified even at a concentration of 5 ng/µl and could detect ten copies and one copy of RNA targeting RdRp and N gene, respectively. RT-PSR amplified products were visually detected by the naked eye and further verified by agarose gel electrophoresis. Primers used for the RT-PSR assay showed zero percent mismatch with SARS-CoV-2 sequences and mismatch with other viruses. Conclusion: The RT-PSR assay developed in this study could be considered a good alternative to the RT-qPCR assays.

Background: The aim of this feasibility study was to adapt and model a behavioural intervention for anxiety with autistic adults with moderate to severe intellectual disabilities. Method: Twenty-eight autistic adults with moderate or severe intellectual disabilities, 37 carers, and 40 therapists took part in this single-group non-randomised feasibility study designed to test intervention feasibility and acceptability, outcome measures, and research processes. Results: The intervention was judged as feasible and acceptable by autistic adults with intellectual disabilities, carers, and therapists. Minor intervention revisions were suggested. Carers completed 100% of outcome measures and the missing data rate was low. Complying with legislation governing the inclusion of participants who lack capacity to decide whether they wanted to take part in this study led to an average 5-week enrolment delay. Conclusion: The intervention and associated study processes were judged to be feasible and acceptable and should now be tested within a larger randomised trial.