Study of ambient air pollutants over Rishikesh at foothills of north-western Indian Himalaya

49-60Air quality parameters measured over Rishikesh city of Uttarakhand, where a large number of visitors and pilgrimage stay and pass by throughout the year are analyzed and studied. Such intensive human activities lead to the impacts and its manifestation on regional scale environment. Due to consistent infrastructure development and the increased vehicular emission due to transport, a large amount of particulate matters is added to the ambient environment and affects the air quality adversely. Here an attempt is made to understand the growth in level of ambient air pollutants through available measurement. In this study particulate matter (PM10), suspended particulate matters (SPMs) and the concentration of gaseous pollutants (SO2 and NO2) from 2011 to 2014 are measured and analyzed. It is observed that concentrations of the pollutants increase during pre-monsoon season as compared to the winter and monsoon seasons. In addition, PM10 and SPM concentrations are found about two times higher than the prescribed national standard. SO2 and NO2 levels are found within the limits as proposed by the Central Pollution Control Board (CPCB) New Delhi, India. A detailed statistical analysis is carried out on the basis of monthly mean values of the observed pollutants. The PM10 exhibits a significant positive correlation with SO2 and NO2 concentrations. In addition, back trajectories show partly long-term transport from North Africa, Saudi Arabia and central Asian region in contributing over the region with local emission that is considered to be the main and direct cause of increasing trend of the pollutants

Effect of stem structural characteristics and cell wall components related to stem lodging resistance in a newly identified mutant of hexaploid wheat (Triticum aestivum L.)

In wheat, lodging is affected by anatomical and chemical characteristics of the stem cell wall. Plant characteristics determining the stem strength were measured in lodging tolerant mutant (PMW-2016-1) developed through mutation breeding utilizing hexaploid wheat cultivar, DPW-621-50. Various anatomical features, chemical composition, and mechanical strength of the culms of newly developed lodging-tolerant mutant (PMW-2016-1) and parent (DPW-621-50), were examined by light microscopy, the Klason method, prostate tester coupled with a Universal Tensile Machine, and Fourier Transform Infrared Spectroscopy. Significant changes in the anatomical features, including the outer radius of the stem, stem wall thickness, and the proportions of various tissues, and vascular bundles were noticed. Chemical analysis revealed that the lignin level in the PMW-2016-1 mutant was higher and exhibited superiority in stem strength compared to the DPW-621-50 parent line. The force (N) required to break the internodes of mutant PMW 2016-1 was higher than that of DPW-621-50. The results suggested that the outer stem radius, stem wall thickness, the proportion of sclerenchyma tissues, the number of large vascular bundles, and lignin content are important factors that affect the mechanical strength of wheat stems, which can be the key parameters for the selection of varieties having higher lodging tolerance. Preliminary studies on the newly identified mutant PMW-2016-1 suggested that this mutant may possess higher lodging tolerance because it has a higher stem strength than DPW-621-50 and can be used as a donor parent for the development of lodging-tolerant wheat varieties

Variations in the cloud-base height over the central Himalayas during GVAX: association with the monsoon rainfall

We present the measurements of cloud-base height variations over Aryabhatta Research Institute of Observational Science, Nainital (79.45 degrees E, 29.37 degrees N, 1958 m amsl) obtained from Vaisala Ceilometer, during the nearly year-long Ganges Valley Aerosol Experiment (GVAX). The cloud-base measurements are analysed in conjunction with collocated measurements of rainfall, to study the possible contributions from different cloud types to the observed monsoonal rainfall during June to September 2011. The summer monsoon of 2011 was a normal monsoon year with total accumulated rainfall of 1035.8 mm during June-September with a maximum during July (367.0 mm) and minimum during September (222.3 mm). The annual mean monsoon rainfall over Nainital is 1440 +/- 430 mm. The total rainfall measured during other months (October 2011-March 2012) was only 9% of that observed during the summer monsoon. The first cloud-base height varied from about 31 m above ground level (AGL) to a maximum of 7.6 km AGL during the summer monsoon period of 2011. It is found that about 70% of the total rain is observed only when the first cloud-base height varies between surface and 2 km AGL, indicating that most of the rainfall at high altitude stations such as Nainital is associated with stratiform low-level clouds. However, about 25% of the total rainfall is being contributed by clouds between 2 and 6 km. The occurrences of high-altitude cumulus clouds are observed to be only 2-4%. This study is an attempt to fill a major gap of measurements over the topographically complex and observationally sparse northern Indian region providing the evaluation data for atmospheric models and therefore, have implications towards the better predictions of monsoon rainfall and the weather components over this region

PM2.5 diminution and haze events over Delhi during the COVID-19 lockdown period: an interplay between the baseline pollution and meteorology

Abstract Delhi, a tropical Indian megacity, experiences one of the most severe air pollution in the world, linked with diverse anthropogenic and biomass burning emissions. First phase of COVID-19 lockdown in India, implemented during 25 March to 14 April 2020 resulted in a dramatic near-zeroing of various activities (e.g. traffic, industries, constructions), except the “essential services”. Here, we analysed variations in the fine particulate matter (PM2.5) over the Delhi-National Capital Region. Measurements revealed large reductions (by 40–70%) in PM2.5 during the first week of lockdown (25–31 March 2020) as compared to the pre-lockdown conditions. However, O3 pollution remained high during the lockdown due to non-linear chemistry and dynamics under low aerosol loading. Notably, events of enhanced PM2.5 levels (300–400 µg m−3) were observed during night and early morning hours in the first week of April after air temperatures fell close to the dew-point (~ 15–17 °C). A haze formation mechanism is suggested through uplifting of fine particles, which is reinforced by condensation of moisture following the sunrise. The study highlights a highly complex interplay between the baseline pollution and meteorology leading to counter intuitive enhancements in pollution, besides an overall improvement in air quality during the COVID-19 lockdown in this part of the world

Comprehensive meta-QTL analysis for dissecting the genetic architecture of stripe rust resistance in bread wheat

Abstract Background Yellow or stripe rust, caused by the fungus Puccinia striiformis f. sp. tritici (Pst) is an important disease of wheat that threatens wheat production. Since developing resistant cultivars offers a viable solution for disease management, it is essential to understand the genetic basis of stripe rust resistance. In recent years, meta-QTL analysis of identified QTLs has gained popularity as a way to dissect the genetic architecture underpinning quantitative traits, including disease resistance. Results Systematic meta-QTL analysis involving 505 QTLs from 101 linkage-based interval mapping studies was conducted for stripe rust resistance in wheat. For this purpose, publicly available high-quality genetic maps were used to create a consensus linkage map involving 138,574 markers. This map was used to project the QTLs and conduct meta-QTL analysis. A total of 67 important meta-QTLs (MQTLs) were identified which were refined to 29 high-confidence MQTLs. The confidence interval (CI) of MQTLs ranged from 0 to 11.68 cM with a mean of 1.97 cM. The mean physical CI of MQTLs was 24.01 Mb, ranging from 0.0749 to 216.23 Mb per MQTL. As many as 44 MQTLs colocalized with marker–trait associations or SNP peaks associated with stripe rust resistance in wheat. Some MQTLs also included the following major genes- Yr5, Yr7, Yr16, Yr26, Yr30, Yr43, Yr44, Yr64, YrCH52, and YrH52. Candidate gene mining in high-confidence MQTLs identified 1,562 gene models. Examining these gene models for differential expressions yielded 123 differentially expressed genes, including the 59 most promising CGs. We also studied how these genes were expressed in wheat tissues at different phases of development. Conclusion The most promising MQTLs identified in this study may facilitate marker-assisted breeding for stripe rust resistance in wheat. Information on markers flanking the MQTLs can be utilized in genomic selection models to increase the prediction accuracy for stripe rust resistance. The candidate genes identified can also be utilized for enhancing the wheat resistance against stripe rust after in vivo confirmation/validation using one or more of the following methods: gene cloning, reverse genetic methods, and omics approaches

Very high particulate pollution over northwest India captured by a high-density in situ sensor network

Abstract Exposure to particulate matter less than 2.5 µm in diameter (PM2.5) is a cause of concern in cities and major emission regions of northern India. An intensive field campaign involving the states of Punjab, Haryana and Delhi national capital region (NCR) was conducted in 2022 using 29 Compact and Useful PM2.5 Instrument with Gas sensors (CUPI-Gs). Continuous observations show that the PM2.5 in the region increased gradually from < 60 µg m−3 in 6–10 October to up to 500 µg m−3 on 5–9 November, which subsequently decreased to about 100 µg m−3 in 20–30 November. Two distinct plumes of PM2.5 over 500 µg m−3 are tracked from crop residue burning in Punjab to Delhi NCR on 2–3 November and 10–11 November with delays of 1 and 3 days, respectively. Experimental campaign demonstrates the advantages of source region observations to link agricultural waste burning and air pollution at local to regional scales