Effect of Biomass Burning, Diwali Fireworks, and Polluted Fog Events on the Oxidative Potential of Fine Ambient Particulate Matter in Delhi, India.

We investigated the influence of biomass burning (BURN), Diwali fireworks, and fog events on the ambient fine particulate matter (PM2.5) oxidative potential (OP) during the postmonsoon (PMON) and winter season in Delhi, India. The real-time hourly averaged OP (based on a dithiothreitol assay) and PM2.5 chemical composition were measured intermittently from October 2019 to January 2020. The peak extrinsic OP (OPv: normalized by the volume of air) was observed during the winter fog (WFOG) (5.23 ± 4.6 nmol·min-1·m-3), whereas the intrinsic OP (OPm; normalized by the PM2.5 mass) was the highest during the Diwali firework-influenced period (29.4 ± 18.48 pmol·min-1·µg-1). Source apportionment analysis using positive matrix factorization revealed that traffic + resuspended dust-related emissions (39%) and secondary sulfate + oxidized organic aerosols (38%) were driving the OPv during the PMON period, whereas BURN aerosols dominated (37%) the OPv during the WFOG period. Firework-related emissions became a significant contributor (∼32%) to the OPv during the Diwali period (4 day period from October 26 to 29), and its contribution peaked (72%) on the night of Diwali. Discerning the influence of seasonal and episodic sources on health-relevant properties of PM2.5, such as OP, could help better understand the causal relationships between PM2.5 and health effects in India.

Detection and Quantification of Enteric Pathogens in Aerosols Near Open Wastewater Canals in Cities with Poor Sanitation.

Urban sanitation infrastructure is inadequate in many low-income countries, leading to the presence of highly concentrated, uncontained fecal waste streams in densely populated areas. Combined with mechanisms of aerosolization, airborne transport of enteric microbes and their genetic material is possible in such settings but remains poorly characterized. We detected and quantified enteric pathogen-associated gene targets in aerosol samples near open wastewater canals (OWCs) or impacted (receiving sewage or wastewater) surface waters and control sites in La Paz, Bolivia; Kanpur, India; and Atlanta, USA, via multiplex reverse-transcription qPCR (37 targets) and ddPCR (13 targets). We detected a wide range of enteric targets, some not previously reported in extramural urban aerosols, with more frequent detections of all enteric targets at higher densities in La Paz and Kanpur near OWCs. We report density estimates ranging up to 4.7 × 102 gc per mair3 across all targets including heat-stable enterotoxigenic Escherichia coli, Campylobacter jejuni, enteroinvasive E. coli/Shigella spp., Salmonella spp., norovirus, and Cryptosporidium spp. Estimated 25, 76, and 0% of samples containing positive pathogen detects were accompanied by culturable E. coli in La Paz, Kanpur, and Atlanta, respectively, suggesting potential for viability of enteric microbes at the point of sampling. Airborne transmission of enteric pathogens merits further investigation in cities with poor sanitation.

Extended-spectrum beta-lactamase (ESBL)-positive Escherichia coli presence in urban aquatic environments in Kanpur, India.

In India, high rates of antibiotic consumption and poor sanitation infrastructure combine to pose a significant risk to the public through the environmental transmission of antimicrobial resistance (AMR). The WHO has declared extended-spectrum beta-lactamase (ESBL)-positive Escherichia coli a key indicator for the surveillance of AMR worldwide. In the current study, we measured the prevalence of AMR bacteria in an urban aquatic environment in India by detecting metabolically active ESBL-positive E. coli. Water samples were collected in duplicate from 16 representative environmental water sources including open canals, drains, and rivers around Kanpur, Uttar Pradesh. We detected culturable E. coli in environmental water at 11 (69%) of the sites. Out of the 11 sites that were positive for culturable E. coli, ESBL-producing E. coli was observed at 7 (64%). The prevalence of ESBL-producing E. coli detected in the urban aquatic environment suggests a threat of AMR bacteria to this region.

Validation of Low-Cost Sensors in Measuring Real-Time PM10 Concentrations at Two Sites in Delhi National Capital Region.

In the present study, we assessed for the first time the performance of our custom-designed low-cost Particulate Matter (PM) monitoring devices (Atmos) in measuring PM10 concentrations. We examined the ambient PM10 levels during an intense measurement campaign at two sites in the Delhi National Capital Region (NCR), India. In this study, we validated the un-calibrated Atmos for measuring ambient PM10 concentrations at highly polluted monitoring sites. PM10 concentration from Atmos, containing laser scattering-based Plantower PM sensor, was comparable with that measured from research-grade scanning mobility particle sizers (SMPS) in combination with optical particle sizers (OPS) and aerodynamic particle sizers (APS). The un-calibrated sensors often provided accurate PM10 measurements, particularly in capturing real-time hourly concentrations variations. Quantile-Quantile plots (QQ-plots) for data collected during the selected deployment period showed positively skewed PM10 datasets. Strong Spearman's rank-order correlations (rs = 0.64-0.83) between the studied instruments indicated the utility of low-cost Plantower PM sensors in measuring PM10 in the real-world context. Additionally, the heat map for weekly datasets demonstrated high R2 values, establishing the efficacy of PM sensor in PM10 measurement in highly polluted environmental conditions.

Intensive allochthonous inputs along the Ganges River and their effect on microbial community composition and dynamics.

Little is known about microbial communities in the Ganges River, India and how they respond to intensive anthropogenic inputs. Here we applied shotgun metagenomics sequencing to study microbial community dynamics and function in planktonic samples collected along an approximately 700 km river transect, including urban cities and rural settings in upstream waters, before and after the monsoon rainy season. Our results showed that 11%-32% of the microbes represented terrestrial, sewage and human inputs (allochthonous). Sewage inputs significantly contributed to the higher abundance, by 13-fold of human gut microbiome (HG) associated sequences and 2-fold of antibiotic resistance genes (ARGs) in the Ganges relative to other riverine ecosystems in Europe, North and South America. Metagenome-assembled genome sequences (MAGs) representing allochthonous populations were detectable and tractable across the river after 1-2 days of (downstream) transport (> 200 km apart). Only approximately 8% of these MAGs were abundant in U.S. freshwater ecosystems, revealing distinct biodiversity for the Ganges. Microbial communities in the rainy season exhibited increased alpha-diversity and spatial heterogeneity and showed significantly weaker distance-decay patterns compared with the dry season. These results advance our understanding of the Ganges microbial communities and how they respond to anthropogenic pollution.

Access to Household Water Quality Information Leads to Safer Water: A Cluster Randomized Controlled Trial in india.

Household-specific feedback on the microbiological safety of drinking water may result in changes to water management practices that reduce exposure risks. We conducted a randomized, controlled trial in India to determine if information on household drinking water quality could change behavior and improve microbiological quality as indicated by Escherichia coli counts. We randomly assigned 589 participating households to one of three arms: (1) a messaging-only arm receiving messaging on safe water management ( n = 237); (2) a standard testing arm receiving the same messaging plus laboratory E. coli testing results specific to that household's drinking water ( n = 173); and (3) a test kit arm receiving messaging plus low-cost E. coli tests that could be used at the household's discretion ( n = 179). Self-reported water treatment increased significantly in both the standard testing arm and the test kit arm between baseline and follow-up one month later. Mean log10 E. coli counts per 100 mL in household stored drinking water increased in the messaging-only arm from 1.42 to 1.87, while decreasing in the standard testing arm (1.38 to 0.89, 65% relative reduction) and the test kit arm (1.08 to 0.65, 76% relative reduction). Findings indicate that household-specific water quality information can improve both behaviors and drinking water quality.

Leveraging Unsupervised Data and Domain Adaptation for Deep Regression in Low-Cost Sensor Calibration.

Air quality monitoring is becoming an essential task with rising awareness about air quality. Low-cost air quality sensors are easy to deploy but are not as reliable as the costly and bulky reference monitors. The low-quality sensors can be calibrated against the reference monitors with the help of deep learning. In this article, we translate the task of sensor calibration into a semi-supervised domain adaptation problem and propose a novel solution for the same. The problem is challenging, because it is a regression problem with a covariate shift and label gap. We use histogram loss instead of mean-squared or mean absolute error (MAE), which is commonly used for regression, and find it useful against covariate shift. To handle the label gap, we propose the weighting of samples for adversarial entropy optimization. In experimental evaluations, the proposed scheme outperforms many competitive baselines, which are based on semi-supervised and supervised domain adaptation, in terms of R2 score and MAE. Ablation studies show the relevance of each proposed component in the entire scheme.

Inter-continental variability in the relationship of oxidative potential and cytotoxicity with PM2.5 mass.

Most fine ambient particulate matter (PM2.5)-based epidemiological models use globalized concentration-response (CR) functions assuming that the toxicity of PM2.5 is solely mass-dependent without considering its chemical composition. Although oxidative potential (OP) has emerged as an alternate metric of PM2.5 toxicity, the association between PM2.5 mass and OP on a large spatial extent has not been investigated. In this study, we evaluate this relationship using 385 PM2.5 samples collected from 14 different sites across 4 different continents and using 5 different OP (and cytotoxicity) endpoints. Our results show that the relationship between PM2.5 mass vs. OP (and cytotoxicity) is largely non-linear due to significant differences in the intrinsic toxicity, resulting from a spatially heterogeneous chemical composition of PM2.5. These results emphasize the need to develop localized CR functions incorporating other measures of PM2.5 properties (e.g., OP) to better predict the PM2.5-attributed health burdens.

Local incomplete combustion emissions define the PM2.5 oxidative potential in Northern India.

The oxidative potential (OP) of particulate matter (PM) is a major driver of PM-associated health effects. In India, the emission sources defining PM-OP, and their local/regional nature, are yet to be established. Here, to address this gap we determine the geographical origin, sources of PM, and its OP at five Indo-Gangetic Plain sites inside and outside Delhi. Our findings reveal that although uniformly high PM concentrations are recorded across the entire region, local emission sources and formation processes dominate PM pollution. Specifically, ammonium chloride, and organic aerosols (OA) from traffic exhaust, residential heating, and oxidation of unsaturated vapors from fossil fuels are the dominant PM sources inside Delhi. Ammonium sulfate and nitrate, and secondary OA from biomass burning vapors, are produced outside Delhi. Nevertheless, PM-OP is overwhelmingly driven by OA from incomplete combustion of biomass and fossil fuels, including traffic. These findings suggest that addressing local inefficient combustion processes can effectively mitigate PM health exposure in northern India.

Proliferation of Lung Epithelial Cells Is Regulated by the Mechanisms of Autophagy Upon Exposure of Soots.

BACKGROUND: Soots are known to cause many diseases in humans, but their underlying mechanisms of toxicity are still not known. Here, we report that soots induce cell proliferation of lung epithelial cells via modulating autophagy pathways. RESULTS: Fullerene soot and diesel exhaust particles (DEP) induced cell proliferation of lung epithelial, A549 cells via distinct autophagic mechanisms and did not cause cell death. Exposure of fullerene soot protected the cell death of A549 cells, caused by hydrogen peroxide, and inhibited LPS-induced autophagy. Fullerene soot co-localized with the autophagic proteins and inhibited starvation-induced autophagy (downregulated ATG-5, beclin-1, p62, and LC3 expressions) independent of its antioxidant properties. Similarly, it decreased the expression profile of autophagic genes and upregulated the proliferation-responsive gene, Ki-67, in mice. We observed that expressions of fullerene soot-responsive genes (Beclin-1, ATG-5, and p62) were reverted by Akt Inhibitor X, indicating an important role of the Akt pathway. At an elemental level, we found that elemental carbon of fullerene soot may be converted into organic carbon, as measured by OCEC, which may point fullerene soot as a source of carbon. On the other hand, DEP upregulated the expressions of autophagy genes. Akt Inhibitor X did not attenuate DEP-induced cell proliferation and autophagic response. However, an autophagic inhibitor, chloroquine, and significantly inhibited DEP-induced cell proliferation. CONCLUSION: It can be said that distinct autophagic mechanisms are operational in cell proliferation of lung epithelial cells due to soots, which may be responsible for different diseases. Understanding the mechanism of these pathways provides some important targets, which can be utilized for the development of future therapeutics.

Variations in Black Carbon concentration and sources during COVID-19 lockdown in Delhi.

A nationwide lockdown was imposed in India due to COVID-19 pandemic in five phases from 25th March to May 31, 2020. The lockdown restricted major anthropogenic activities, primarily vehicular and industrial, thereby reducing the particulate matter concentration. This work investigates the variation in Black Carbon (BC) concentration and its sources (primarily Fossil Fuel (ff) burning and Biomass Burning (bb)) over Delhi from 18th February to July 31, 2020, covering one month of pre-lockdown phase, all the lockdown phases, and two months of successive lockdown relaxations. The daily average BC concentration varied from 0.22 to 16.92 µg/m3, with a mean value of 3.62 ± 2.93 µg/m3. During Pre-Lockdown (PL, 18th Feb-24th March 2020), Lockdown-1 (L1, 25th March-14th April 2020), Lockdown-2 (L2, 15th April-3rd May 2020), Lockdown-3 (L3, 4th-17th May 2020), Lockdown-4 (L4, 18th-31st May 2020), Unlock-1 (UN1, June 2020), and Unlock-2 (UN2, July 2020) the average BC concentrations were 7.93, 1.73, 2.59, 3.76, 3.26, 2.07, and 2.70 µg/m3, respectively. During the lockdown and unlock phases, BC decreased up to 78% compared to the PL period. The BC source apportionment studies show that fossil fuel burning was the dominant BC source during the entire sampling period. From L1 to UN2 an increasing trend in BCff contribution was observed (except L3) due to the successive relaxations given to anthropogenic activities. BCff contribution dipped briefly during L3 due to the intensive crop residue burning events in neighboring states. CWT analysis showed that local emission sources were the dominant contributors to BC concentration over Delhi.

Variation in chemical composition and sources of PM2.5 during the COVID-19 lockdown in Delhi.

The Government of India (GOI) announced a nationwide lockdown starting 25th March 2020 to contain the spread of COVID-19, leading to an unprecedented decline in anthropogenic activities and, in turn, improvements in ambient air quality. This is the first study to focus on highly time-resolved chemical speciation and source apportionment of PM2.5 to assess the impact of the lockdown and subsequent relaxations on the sources of ambient PM2.5 in Delhi, India. The elemental, organic, and black carbon fractions of PM2.5 were measured at the IIT Delhi campus from February 2020 to May 2020. We report source apportionment results using positive matrix factorization (PMF) of organic and elemental fractions of PM2.5 during the different phases of the lockdown. The resolved sources such as vehicular emissions, domestic coal combustion, and semi-volatile oxygenated organic aerosol (SVOOA) were found to decrease by 96%, 95%, and 86%, respectively, during lockdown phase-1 as compared to pre-lockdown. An unforeseen rise in O3 concentrations with declining NOx levels was observed, similar to other parts of the globe, leading to the low-volatility oxygenated organic aerosols (LVOOA) increasing to almost double the pre-lockdown concentrations during the last phase of the lockdown. The effect of the lockdown was found to be less pronounced on other resolved sources like secondary chloride, power plants, dust-related, hydrocarbon-like organic aerosols (HOA), and biomass burning related emissions, which were also swayed by the changing meteorological conditions during the four lockdown phases. The results presented in this study provide a basis for future emission control strategies, quantifying the extent to which constraining certain anthropogenic activities can ameliorate the ambient air. These results have direct relevance to not only Delhi but the entire Indo-Gangetic plain (IGP), citing similar geographical and meteorological conditions common to the region along with overlapping regional emission sources. SUMMARY OF MAIN FINDINGS: We identify sources like vehicular emissions, domestic coal combustion, and semi-volatile oxygenated organic aerosol (SVOOA) to be severely impacted by the lockdown, whereas ozone levels and, in turn, low-volatility oxygenated organic aerosols (LVOOA) rise by more than 95% compared to the pre-lockdown concentrations during the last phase of the lockdown. However, other sources resolved in this study, like secondary chloride, power plants, dust-related, hydrocarbon-like organic aerosols (HOA), and biomass burning related emissions, were mainly driven by the changes in the meteorological conditions rather than the lockdown.

Application of National Aerosol Facility (NAF) in Designing of a Ventilation System for Isolation Rooms to Minimize Interpersonal Exposure of Sneezing/Coughing.

With the outbreak of pandemic COVID-19, protection of public and health workers has become a national priority. In this regard, it is desirable to study the coughing- and sneezing-generated pathogen aerosols, its dispersion and transportation in isolation rooms, clinics, confined spaces and other general public places to evolve efficient ventilation system along with suitable protective measures to limit the spread of the virus. The present paper describes the overall experimental scheme supported with computational fluid dynamics evaluation to address this problem for evolution of optimal ventilation system using the National Aerosol Facility at IIT Kanpur set up in collaboration with BARC Trombay. The outcome of this study is aimed to evolve a national standard for optimum isolation rooms that would provide adequate protection to health workers.

Climatological trends in satellite-derived aerosol optical depth over North India and its relationship with crop residue burning: Rural-urban contrast.

Columnar Aerosol Optical Depths (AOD) over an urban area (Chandigarh) and a rural area (Khera, Fatehgarh Sahib district) situated in the Indo-Gangetic Plains (IGP) of India were analysed to study their temporal heterogeneity in terms of interannual, seasonal and monthly variations. Over the last few decades, IGP has become one of the global hotspots of air pollution due to the increased anthropogenic activities such as traffic, industries, agricultural waste burning etc. Level-2 AODs (550 nm) were retrieved from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensors onboard NASA's Terra and Aqua satellites, for a period of 14 years (2005-2018). The climatological mean Terra-MODIS (Aqua-MODIS) AOD over the urban location was ~0.497 ± 0.238 (0.474 ± 0.228), whereas over the rural location it was 0.542 ± 0.269 (0.534 ± 0.282). Linear trend analysis estimated an increase in annual mean Terra-MODIS (Aqua-MODIS) AOD at a rate of ~0.009 (0.013) per year over the urban site; whereas over the rural location the rate of increase was ~0.003 (0.004) per year. Results show that the observed increase is ~1.49% (2.41%) of climatological mean AOD over the urban location for Terra-MODIS (Aqua-MODIS), whereas, over the rural location, it was ~0.50% (0.67%). Using the HYSPLIT trajectory model, it was concluded that, during post-monsoon, the observed high AODs can be related to massive crop residue burning in the IGP region. These AOD trends can also be used to track the regional anthropogenic air-pollution changes. An empirical relation between AOD and PM10 was established, which can be used to estimate PM10 over the urban and rural areas of IGP (using MODIS AODs), complementing the sparse ground-based monitoring. Further, satellite-based air pollution data can be used for baseline assessment and understanding the impact of control policies such as National Clean Air Programme and to support formulate evidence-based pollution control strategies.

Real-time measurement and source apportionment of elements in Delhi's atmosphere.

Delhi, the capital of India, suffers from heavy local emissions as well as regional transport of air pollutants, resulting in severe aerosol loadings. To determine the sources of these pollutants, we have quantified the mass concentrations of 26 elements in airborne particles, measured by an online X-ray fluorescence spectrometer with time resolution between 30 min and 1 h. Measurements of PM10 and PM2.5 (particulate matter <10 µm and < 2.5 µm) were conducted during two consecutive winters (2018 and 2019) in Delhi. On average, 26 elements from Al to Pb made up ~25% and ~19% of the total PM10 mass (271 µg m-3 and 300 µg m-3) in 2018 and 2019, respectively. Nine different aerosol sources were identified during both winters using positive matrix factorization (PMF), including dust, non-exhaust, an S-rich factor, two solid fuel combustion (SFC) factors and four industrial/combustion factors related to plume events (Cr-Ni-Mn, Cu-Cd-Pb, Pb-Sn-Se and Cl-Br-Se). All factors were resolved in both size ranges (but varying relative concentrations), comprising the following contributions to the elemental PM10 mass (in % average for 2018 and 2019): Cl-Br-Se (41.5%, 36.9%), dust (27.6%, 28.7%), non-exhaust (16.2%, 13.7%), S-rich (6.9%, 9.2%), SFC1 + SFC2 (4%, 7%), Pb-Sn-Se (2.3%, 1.66%), Cu-Cd-Pb (0.67%, 2.2%) and Cr-Ni-Mn (0.57%, 0.47%). Most of these sources had the highest relative contributions during late night (22:00 local time (LT)) and early morning hours (between 03:00 to 08:00 LT), which is consistent with enhanced emissions into a shallow boundary layer. Modelling of airmass source geography revealed that the Pb-Sn-Se, Cl-Br-Se and SFC2 factors prevailed for northwest winds (Pakistan, Punjab, Haryana and Delhi), while the Cu-Cd-Pb and S-rich factors originated from east (Nepal and Uttar Pradesh) and the Cr-Ni-Mn factor from northeast (Uttar Pradesh). In contrast, SFC1, dust and non-exhaust were not associated with any specific wind direction.

Loss of crop yields in India due to surface ozone: an estimation based on a network of observations.

Surface ozone is mainly produced by photochemical reactions involving various anthropogenic pollutants, whose emissions are increasing rapidly in India due to fast-growing anthropogenic activities. This study estimates the losses of wheat and rice crop yields using surface ozone observations from a group of 17 sites, for the first time, covering different parts of India. We used the mean ozone for 7 h during the day (M7) and accumulated ozone over a threshold of 40 ppbv (AOT40) metrics for the calculation of crop losses for the northern, eastern, western and southern regions of India. Our estimates show the highest annual loss of wheat (about 9 million ton) in the northern India, one of the most polluted regions in India, and that of rice (about 2.6 million ton) in the eastern region. The total all India annual loss of 4.0-14.2 million ton (4.2-15.0%) for wheat and 0.3-6.7 million ton (0.3-6.3%) for rice are estimated. The results show lower crop loss for rice than that of wheat mainly due to lower surface ozone levels during the cropping season after the Indian summer monsoon. These estimates based on a network of observation sites show lower losses than earlier estimates based on limited observations and much lower losses compared to global model estimates. However, these losses are slightly higher compared to a regional model estimate. Further, the results show large differences in the loss rates of both the two crops using the M7 and AOT40 metrics. This study also confirms that AOT40 cannot be fit with a linear relation over the Indian region and suggests for the need of new metrics that are based on factors suitable for this region.