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

Pollutant emission reductions deliver decreased PM₂.₅-caused mortality across China during 2015-2017

Air pollution is a serious environmental issue and leading contributor to the disease burden in China. Rapid reductions in fine particulate matter (PM2.5) concentrations and increased ozone concentrations have occurred across China, during 2015 to 2017. We used measurements of particulate matter with a diameter  1000 stations across China along with Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) regional air quality simulations, to explore the drivers and impacts of observed trends. The measured nationwide median PM2.5 trend of −3.4 µg m−3 year−1, was well simulated by the model (−3.5 µg m−3 year−1). With anthropogenic emissions fixed at 2015-levels, the simulated trend was much weaker (−0.6 µg m−3 year−1), demonstrating interannual variability in meteorology played a minor role in the observed PM2.5 trend. The model simulated increased ozone concentrations in line with the measurements, but underestimated the magnitude of the observed absolute trend by a factor of 2. We combined simulated trends in PM2.5 concentrations with an exposure-response function to estimate that reductions in PM2.5 concentrations over this period have reduced PM2.5-attribrutable premature morality across China by 150 000  deaths year−1

Large air quality and public health impacts due to Amazonian deforestation fires in 2019

Air pollution from Amazon fires has adverse impacts on human health. The number of fires in the Amazon has increased in recent years, but whether this increase was driven by deforestation or climate has not been assessed. We analyzed relationships between fire, deforestation, and climate for the period 2003 to 2019 among selected states across the Brazilian Legal Amazon (BLA). A statistical model including deforestation, precipitation and temperature explained ∼80% of the variability in dry season fire count across states when totaled across the BLA, with positive relationships between fire count and deforestation. We estimate that the increase in deforestation since 2012 increased the dry season fire count in 2019 by 39%. Using a regional chemistry-climate model combined with exposure-response associations, we estimate this increase in fire resulted in 3,400 (95UI: 3,300–3,550) additional deaths in 2019 due to increased exposure to particulate air pollution. If deforestation in 2019 had increased to the maximum recorded during 2003–2019, the number of active fire counts would have increased by an additional factor of 2 resulting in 7,900 (95UI: 7,600–8,200) additional premature deaths. Our analysis demonstrates the strong benefits of reduced deforestation on air quality and public health across the Amazon

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

Pollutant emission reductions deliver decreased PM2.5-caused mortality across China during 2015–2017

Air pollution is a serious environmental issue and leading contributor to disease burden in China. Rapid reductions in fine particulate matter (PM2.5) concentrations and increased ozone concentrations occurred across China during 2015 to 2017. We used measurements of particulate matter with a diameter <2.5 µm (PM2.5) and ozone (O3) from more than 1000 stations across China along with Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) regional air quality simulations, to explore the drivers and impacts of observed trends. The measured nationwide median PM2.5 trend of −3.4µgm−3yr−1 was well simulated by the model (−3.5µgm−3yr−1). With anthropogenic emissions fixed at 2015 levels, the simulated trend was much weaker (−0.6µgm−3yr−1), demonstrating that interannual variability in meteorology played a minor role in the observed PM2.5 trend. The model simulated increased ozone concentrations in line with the measurements but underestimated the magnitude of the observed absolute trend by a factor of 2. We combined simulated trends in PM2.5 concentrations with an exposure–response function to estimate that reductions in PM2.5 concentrations over this period have reduced PM2.5-attributable premature mortality across China by 150 000 deaths yr−1

Air Pollution from Forest and Vegetation Fires in Southeast Asia Disproportionately Impacts the Poor

Forest and vegetation fires, used as tools for agriculture and deforestation, are a major source of air pollutants and can cause serious air quality issues in many parts of Asia. Actions to reduce fire may offer considerable, yet largely unrecognized, options for rapid improvements in air quality. In this study, we used a combination of regional and global air quality models and observations to examine the impact of forest and vegetation fires on air quality degradation and public health in Southeast Asia (including Mainland Southeast Asia and south-eastern China). We found that eliminating fire could substantially improve regional air quality across Southeast Asia by reducing the population exposure to fine particulate matter (PM2.5) concentrations by 7% and surface ozone concentrations by 5%. These reductions in PM2.5 exposures would yield a considerable public health benefit across the region; averting 59,000 (95% uncertainty interval (95UI): 55,200–62,900) premature deaths annually. Analysis of subnational infant mortality rate data and PM2.5 exposure suggested that PM2.5 from fires disproportionately impacts poorer populations across Southeast Asia. We identified two key regions in northern Laos and western Myanmar where particularly high levels of poverty coincide with exposure to relatively high levels of PM2.5 from fires. Our results show that reducing forest and vegetation fires should be a public health priority for the Southeast Asia region

Assessing costs of Indonesian fires and the benefits of restoring peatland

Deforestation and drainage has made Indonesian peatlands susceptible to burning. Large fires occur regularly, destroying agricultural crops and forest, emitting large amounts of CO2 and air pollutants, resulting in adverse health effects. In order to reduce fire, the Indonesian government has committed to restore 2.49 Mha of degraded peatland, with an estimated cost of US$3.2-7 billion. Here we combine fire emissions and land cover data to estimate the 2015 fires, the largest in recent years, resulted in economic losses totalling US$28 billion, whilst the six largest fire events between 2004 and 2015 caused a total of US$93.9 billion in economic losses. We estimate that if restoration had already been completed, the area burned in 2015 would have been reduced by 6$8.4 billion for 2004–2015, making it a cost-effective strategy for reducing the impacts of peatland fires to the environment, climate and human health

Exploring the impacts of anthropogenic emission sectors on PM2.5 and human health in South and East Asia

To improve poor air quality in Asia and inform effective emission-reduction strategies, it is vital to understand the contributions of different pollution sources and their associated human health burdens. In this study, we use the WRF-Chem regional atmospheric model to explore the air quality and human health benefits of eliminating emissions from six different anthropogenic sectors (transport, industry, shipping, electricity generation, residential combustion, and open biomass burning) over South and East Asia in 2014. We evaluate WRF-Chem against measurements from air quality monitoring stations across the region and find the model captures the spatial distribution and magnitude of PM2.5 (particulate matter with an aerodynamic diameter of no greater than 2.5 µm). We find that eliminating emissions from residential energy use, industry, or open biomass burning yields the largest reductions in population-weighted PM2.5 concentrations across the region. The largest human health benefit is achieved by eliminating either residential or industrial emissions, averting 467 000 (95 % uncertainty interval (95UI): 409 000–542 000) or 283 000 (95UI: 226 000–358 000) annual premature mortalities, respectively, in India, China, and South-east Asia, with fire prevention averting 28 000 (95UI: 24 000–32 000) annual premature mortalities across the region. We compare our results to previous sector-specific emission studies. Across these studies, residential emissions are the dominant cause of particulate pollution in India, with a multi-model mean contribution of 42 % to population-weighted annual mean PM2.5. Residential and industrial emissions cause the dominant contributions in China, with multi-model mean contributions of 29 % for both sectors to population-weighted annual mean PM2.5. Future work should focus on identifying the most effective options within the residential, industrial, and open biomass-burning emission sectors to improve air quality across South and East Asia

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