Local characteristics of and exposure to fine particulate matter (PM2.5) in four indian megacities

Public health in India is gravely threatened by severe PM2.5 exposure. This study presents an analysis of long-term PM2.5 exposure in four Indian megacities (Delhi, Chennai, Hyderabad and Mumbai) based on in-situ observations during 2015–2018, and quantifies the health risks of short-term exposure during Diwali Fest (usually lasting for ~5 days in October or November and celebrating with lots of fireworks) in Delhi for the first time. The population-weighted annual-mean PM2.5 across the four cities was 72 μg/m3, ~3.5 times the global level of 20 μg/m3 and 1.8 times the annual criterion defined in the Indian National Ambient Air Quality Standards (NAAQS). Delhi suffers the worst air quality among the four cities, with citizens exposed to ‘severely polluted’ air for 10% of the time and to unhealthy conditions for 70% of the time. Across the four cities, long-term PM2.5 exposure caused about 28,000 (95% confidence interval: 17,200–39,400) premature mortality and 670,000 (428,900–935,200) years of life lost each year. During Diwali Fest in Delhi, average PM2.5 increased by ~75% and hourly concentrations reached 1676 μg/m3. These high pollutant levels led to an additional 20 (13–25) daily premature mortality in Delhi, an increase of 56% compared to the average over October–November. Distinct seasonal and diurnal variations in PM2.5 were found in all cities. PM2.5 mass concentrations peak during the morning rush hour in all cities. This indicates local traffic could be an important source of PM2.5, the control of which would be essential to improve air quality. We report an interesting seasonal variation in the diurnal pattern of PM2.5 concentrations, which suggests a 1–2 h shift in the morning rush hour from 8 a.m. in pre-monsoon/summer to 9–10 a.m. in winter. The difference between PM2.5 concentrations on weekdays and weekend, namely weekend effect, is negligible in Delhi and Hyderabad, but noticeable in Mumbai and Chennai where ~10% higher PM2.5 concentrations were observed in morning rush hour on weekdays. These local characteristics provide essential information for air quality modelling studies and are critical for tailoring the design of effective mitigation strategies for each city

Sensitivity of air pollution exposure and disease burden to emission changes in China using machine learning emulation

Machine learning models can emulate chemical transport models, reducing computational costs and enabling more experimentation. We developed emulators to predict annual−mean fine particulate matter (PM(2.5)) and ozone (O(3)) concentrations and their associated chronic health impacts from changes in five major emission sectors (residential, industrial, land transport, agriculture, and power generation) in China. The emulators predicted 99.9% of the variance in PM(2.5) and O(3) concentrations. We used these emulators to estimate how emission reductions can attain air quality targets. In 2015, we estimate that PM(2.5) exposure was 47.4 μg m(−3) and O(3) exposure was 43.8 ppb, associated with 2,189,700 (95% uncertainty interval, 95UI: 1,948,000–2,427,300) premature deaths per year, primarily from PM(2.5) exposure (98%). PM(2.5) exposure and the associated disease burden were most sensitive to industry and residential emissions. We explore the sensitivity of exposure and health to different combinations of emission reductions. The National Air Quality Target (35 μg m(−3)) for PM(2.5) concentrations can be attained nationally with emission reductions of 72% in industrial, 57% in residential, 36% in land transport, 35% in agricultural, and 33% in power generation emissions. We show that complete removal of emissions from these five sectors does not enable the attainment of the WHO Annual Guideline (5 μg m(−3)) due to remaining air pollution from other sources. Our work provides the first assessment of how air pollution exposure and disease burden in China varies as emissions change across these five sectors and highlights the value of emulators in air quality research

Impact of weather types on UK ambient particulate matter concentrations

Each year more than 29,000 premature deaths in the UK are linked to long term-exposure to ambient particulate matter (PM) with a diameter less than 2.5 μm (PM2.5). Many studies have focused on the long-term impacts of exposure to PM, but short-term increases in pollution can also exacerbate health effects, leading to deaths brought forward within exposed populations. This study investigates the impact of different atmospheric circulation patterns on UK PM2.5 concentrations and the relative contribution of local and transboundary pollutants to variations in PM2.5 concentrations. Daily mean PM2.5 observations from 42 UK background sites indicate that easterly, south-easterly and southerly wind directions and anticyclonic circulation patterns enhance background concentrations of PM2.5 at all UK sites by up to 12 μg m-3. Results from back trajectory analysis and the European Monitoring and Evaluation Programme for UK model (EMEP4UK) show this is due to the transboundary transport of pollutants from continental Europe. While back trajectories indicate under easterly, south-easterly and southerly flow 25–50% of the total accumulated primary PM2.5 emissions originate outside of the UK, with a very polluted footprint (0.25–0.35 μg m-2). Anticyclonic conditions, which occur frequently (21%), also lead to increases in PM2.5 concentrations (UK multi-annual mean 14.7 μg m-3). EMEP4UK results indicate this is likely due the build-up of local emissions due to slack winds. Under westerly and north-westerly flow 15–30% of the total accumulated primary PM2.5 emissions originate outside of the UK, and are much less polluted (0.1 μg m-2) with model results indicating transport of clean maritime air masses from the Atlantic. Results indicate that both wind-direction and stability under anticyclonic conditions are important in controlling ambient PM2.5 concentrations across the UK. There is also a strong dependence of high PM2.5 Daily Air Quality Index (DAQI) values on easterly, south-easterly and southerly wind-directions, with >70% of occurrences of observed 48–71+ μg m-3 concentrations occurring under these wind directions. While north-westerly and cyclonic conditions reduce PM2.5 concentrations at all sites by up to 8 μg m-3. PM2.5 DAQI values are also lowest under these conditions, with >80% of 0–11 μg m-3 concentrations and >50% of 12–23 μg m-3 concentrations observed during westerly, north-westerly and northerly wind directions. Indicating that these conditions are likely to be associated with a reduction in the potential health effects from exposure to ambient levels of PM2.5

Phase 1, pharmacogenomic, dose-expansion study of pegargiminase plus pemetrexed and cisplatin in patients with ASS1-deficient non-squamous non-small cell lung cancer

Introduction We evaluated the arginine-depleting enzyme pegargiminase (ADI-PEG20; ADI) with pemetrexed (Pem) and cisplatin (Cis) (ADIPemCis) in ASS1-deficient non-squamous non-small cell lung cancer (NSCLC) via a phase 1 dose-expansion trial with exploratory biomarker analysis. Methods Sixty-seven chemonaïve patients with advanced non-squamous NSCLC were screened, enrolling 21 ASS1-deficient subjects from March 2015 to July 2017 onto weekly pegargiminase (36 mg/m2) with Pem (500 mg/m2) and Cis (75 mg/m2), every 3 weeks (four cycles maximum), with maintenance Pem or pegargiminase. Safety, pharmacodynamics, immunogenicity, and efficacy were determined; molecular biomarkers were annotated by next-generation sequencing and PD-L1 immunohistochemistry. Results ADIPemCis was well-tolerated. Plasma arginine and citrulline were differentially modulated; pegargiminase antibodies plateaued by week 10. The disease control rate was 85.7% (n = 18/21; 95% CI 63.7%–97%), with a partial response rate of 47.6% (n = 10/21; 95% CI 25.7%–70.2%). The median progression-free and overall survivals were 4.2 (95% CI 2.9–4.8) and 7.2 (95% CI 5.1–18.4) months, respectively. Two PD-L1-expressing (≥1%) patients are alive following subsequent pembrolizumab immunotherapy (9.5%). Tumoral ASS1 deficiency enriched for p53 (64.7%) mutations, and numerically worse median overall survival as compared to ASS1-proficient disease (10.2 months; n = 29). There was no apparent increase in KRAS mutations (35.3%) and PD-L1 (<1%) expression (55.6%). Re-expression of tumoral ASS1 was detected in one patient at progression (n = 1/3). Conclusions ADIPemCis was safe and highly active in patients with ASS1-deficient non-squamous NSCLC, however, survival was poor overall. ASS1 loss was co-associated with p53 mutations. Therapies incorporating pegargiminase merit further evaluation in ASS1-deficient and treatment-refractory NSCLC

Late-spring and summertime tropospheric ozone and NO2 in western Siberia and the Russian Arctic : regional model evaluation and sensitivities

We use a regional chemistry transport model (Weather Research and Forecasting model coupled with chemistry, WRF-Chem) in conjunction with surface observations of tropospheric ozone and Ozone Monitoring Instrument (OMI) satellite retrievals of tropospheric column NO2 to evaluate processes controlling the regional distribution of tropospheric ozone over western Siberia for late spring and summer in 2011. This region hosts a range of anthropogenic and natural ozone precursor sources, and it serves as a gateway for near-surface transport of Eurasian pollution to the Arctic. However, there is a severe lack of in situ observations to constrain tropospheric ozone sources and sinks in the region. We show widespread negative bias in WRF-Chem tropospheric column NO2 when compared to OMI satellite observations from May-August, which is reduced when using ECLIPSE (Evaluating the Climate and Air Quality Impacts of Short-Lived Pollutants) v5a emissions (fractional mean bias (FMB) = -0.82 to -0.73) compared with the EDGAR (Emissions Database for Global Atmospheric Research)-HTAP (Hemispheric Transport of Air Pollution) v2.2 emissions data (FMB = -0.80 to -0.70). Despite the large negative bias, the spatial correlations between model and observed NO2 columns suggest that the spatial pattern of NOx sources in the region is well represented. Scaling trans-port and energy emissions in the ECLIPSE v5a inventory by a factor of 2 reduces column NO2 bias (FMB = -0.66 to -0.35), but with overestimates in some urban regions and little change to a persistent underestimate in background regions. Based on the scaled ECLIPSE v5a emissions, we assess the influence of the two dominant anthropogenic emission sectors (transport and energy) and vegetation fires on surface NOx and ozone over Siberia and the Russian Arctic. Our results suggest regional ozone is more sensitive to anthropogenic emissions, particularly from the transport sector, and the contribution from fire emissions maximises in June and is largely confined to latitudes south of 60 degrees N. Ozone dry deposition fluxes from the model simulations show that the dominant ozone dry deposition sink in the region is to forest vegetation, averaging 8.0 Tg of ozone per month, peaking at 10.3 Tg of ozone deposition during June. The impact of fires on ozone dry deposition within the domain is small compared to anthropogenic emissions and is negligible north of 60 degrees N. Overall, our results suggest that surface ozone in the region is controlled by an interplay between seasonality in atmospheric transport patterns, vegetation dry deposition, and a dominance of transport and energy sector emissions.Peer reviewe

Cross-reactive memory T cells associate with protection against SARS-CoV-2 infection in COVID-19 contacts

Cross-reactive immune responses to SARS-CoV-2 have been observed in pre-pandemic cohorts and proposed to contribute to host protection. Here we assess 52 COVID-19 household contacts to capture immune responses at the earliest timepoints after SARS-CoV-2 exposure. Using a dual cytokine FLISpot assay on peripheral blood mononuclear cells, we enumerate the frequency of T cells specific for spike, nucleocapsid, membrane, envelope and ORF1 SARS-CoV-2 epitopes that cross-react with human endemic coronaviruses. We observe higher frequencies of cross-reactive (p=0.0139), and nucleocapsid-specific (p=0.0355) IL-2-secreting memory T cells in contacts who remained PCR-negative despite exposure (n=26), when compared with those who convert to PCR-positive (n=26); no significant difference in the frequency of responses to spike is observed, hinting at a limited protective function of spike-cross-reactive T cells. Our results are thus consistent with pre-existing non-spike cross-reactive memory T cells protecting SARS-CoV-2-naïve contacts from infection, thereby supporting the inclusion of non-spike antigens in second-generation vaccines

Onset and window of SARS-CoV-2 infectiousness and temporal correlation with symptom onset: a prospective, longitudinal, community cohort study.

BACKGROUND: Knowledge of the window of SARS-CoV-2 infectiousness is crucial in developing policies to curb transmission. Mathematical modelling based on scarce empirical evidence and key assumptions has driven isolation and testing policy, but real-world data are needed. We aimed to characterise infectiousness across the full course of infection in a real-world community setting. METHODS: The Assessment of Transmission and Contagiousness of COVID-19 in Contacts (ATACCC) study was a UK prospective, longitudinal, community cohort of contacts of newly diagnosed, PCR-confirmed SARS-CoV-2 index cases. Household and non-household exposed contacts aged 5 years or older were eligible for recruitment if they could provide informed consent and agree to self-swabbing of the upper respiratory tract. The primary objective was to define the window of SARS-CoV-2 infectiousness and its temporal correlation with symptom onset. We quantified viral RNA load by RT-PCR and infectious viral shedding by enumerating cultivable virus daily across the course of infection. Participants completed a daily diary to track the emergence of symptoms. Outcomes were assessed with empirical data and a phenomenological Bayesian hierarchical model. FINDINGS: Between Sept 13, 2020, and March 31, 2021, we enrolled 393 contacts from 327 households (the SARS-CoV-2 pre-alpha and alpha variant waves); and between May 24, 2021, and Oct 28, 2021, we enrolled 345 contacts from 215 households (the delta variant wave). 173 of these 738 contacts were PCR positive for more than one timepoint, 57 of which were at the start of infection and comprised the final study population. The onset and end of infectious viral shedding were captured in 42 cases and the median duration of infectiousness was 5 (IQR 3-7) days. Although 24 (63%) of 38 cases had PCR-detectable virus before symptom onset, only seven (20%) of 35 shed infectious virus presymptomatically. Symptom onset was a median of 3 days before both peak viral RNA and peak infectious viral load (viral RNA IQR 3-5 days, n=38; plaque-forming units IQR 3-6 days, n=35). Notably, 22 (65%) of 34 cases and eight (24%) of 34 cases continued to shed infectious virus 5 days and 7 days post-symptom onset, respectively (survival probabilities 67% and 35%). Correlation of lateral flow device (LFD) results with infectious viral shedding was poor during the viral growth phase (sensitivity 67% [95% CI 59-75]), but high during the decline phase (92% [86-96]). Infectious virus kinetic modelling suggested that the initial rate of viral replication determines the course of infection and infectiousness. INTERPRETATION: Less than a quarter of COVID-19 cases shed infectious virus before symptom onset; under a crude 5-day self-isolation period from symptom onset, two-thirds of cases released into the community would still be infectious, but with reduced infectious viral shedding. Our findings support a role for LFDs to safely accelerate deisolation but not for early diagnosis, unless used daily. These high-resolution, community-based data provide evidence to inform infection control guidance. FUNDING: National Institute for Health and Care Research

Large air quality and human health impacts due to Amazon forest and vegetation fires

Vegetation fires across the tropics emit fine particulate matter (PM2.5) to the atmosphere, degrading regional air quality and impacting human health. Extensive vegetation fires occur regularly across the Amazon basin, but there have been no detailed assessments of the impacts on air quality or human health. We used updated exposure-response relationships and a regional climate-chemistry model, evaluated against a comprehensive set of observational data, to provide the first in-depth assessment of the potential public health benefits due to fire prevention across the Amazon Basin. We focused on 2012, a year with emissions similar to the 11-year average (2008 to 2018). Vegetation fires contributed >80% of simulated dry season mean surface PM2.5 in the western Amazon region particularly in Bolivia and Brazilian states of Rondônia, Acre, and Mato Grosso. We estimate that the prevention of vegetation fires would have averted 16 800 (95UI: 16 300–17 400) premature deaths and 641 000 (95UI: 551 900–741 300) disability adjusted life years (DALYs) across South America, with 26% of the avoided health burden located within the Amazon Basin. The health benefits of fire prevention in the Amazon are comparable to those found in Equatorial Asia