Ambient PM2.5 exposure and expected premature mortality to 2100 in India under climate change scenarios

Enhanced Intrusion of Exogenous Airborne Fine Particles toward Eyes in Humans and Animals: Where Damaged Blood-Ocular Barrier Plays a Crucial Role

Emerging data suggest a close correlation between ambient fine particle (AFP) exposure and eye disorders and pinpoint potential threats of AFPs to eye health in humans. However, the possible passage (including direct intrusion) and the interactions of AFPs with the eye microenvironment in addition to morphological and physiological injuries remain elusive. To this end, the likely transport of AFPs into the eyes via blood-ocular barrier (BOB) in humans and animals was investigated herein. Exogenous particles were recognized inside human eyes with detailed structural and chemical fingerprints. Importantly, comparable AFPs were found in sera with constant structural and chemical fingerprints, hinting at the translocation pathway from blood circulation into the eye. Furthermore, we found that the particle concentrations in human eyes from patients with diabetic retinopathy were much higher than those from patients with no fundus pathological changes (i.e., myopia), indicating that the damaged BOB increased the possibility of particle entrance. Our diseased animal model further corroborated these findings. Collectively, our results offer a new piece of evidence on the intrusion of exogenous particles into human eyes and provide an explanation for AFP-induced eye disorders, with substantially increased risk in susceptible individuals with BOB injuries.

Continued Rise in Health Burden from Ambient PM2.5 in India under SSP Scenarios Until 2100 despite Decreasing Concentrations

Forecasting alterations in ambient air pollution and the consequent health implications is crucial for safeguarding public health, advancing environmental sustainability, informing economic decision making, and promoting appropriate policy and regulatory action. However, predicting such changes poses a substantial challenge, requiring accurate data, sophisticated modeling methodologies, and a meticulous evaluation of multiple drivers. In this study, we calculate premature deaths due to ambient fine particulate matter (PM2.5) exposure in India from the 2020s (2016-2020) to the 2100s (2095-2100) under four different socioeconomic and climate scenarios (SSPs) based on four CMIP6 models. PM2.5 concentrations decreased in all SSP scenarios except for SSP3-7.0, with the lowest concentration observed in SSP1-2.6. The results indicate an upward trend in the five-year average number of deaths across all scenarios, ranging from 1.01 million in the 2020s to 4.12-5.44 million in the 2100s. Further analysis revealed that the benefits of reducing PM2.5 concentrations under all scenarios are largely mitigated by population aging and growth. These findings underscore the importance of proactive measures and an integrated approach in India to improve atmospheric quality and reduce vulnerability to aging under changing climate conditions.

In-depth characterization of particulate matter in a highly polluted urban environment at the foothills of Himalaya-Karakorum Region

In recent years, the rising levels of atmospheric particulate matter (PM) have an impact on the earth's system, leading to undesirable consequences on various aspects like human health, visibility, and climate. The present work is carried out over an insufficiently studied but polluted urban area of Peshawar, which lies at the foothills of the famous Himalaya and Karakorum area, Northern Pakistan. The particulate matter with an aerodynamic diameter of less than 10 µm, i.e., PM10 are collected and analyzed for mineralogical, morphological, and chemical properties. Diverse techniques were used to examine the PM10 samples, for instance, Fourier transform infrared spectroscopy, x-ray diffraction, and scanning electron microscopy along with energy-dispersive x-ray spectroscopy, proton-induced x-ray emission, and an OC/EC carbon analyzer. The 24 h average PM10 mass concentration along with standard deviation was investigated to be 586.83 ± 217.70 µg/m3, which was around 13 times greater than the permissible limit of the world health organization (45 µg/m3) and 4 times the Pakistan national environmental quality standards for ambient PM10 (150 µg/m3). Minerals such as crystalline silicate, carbonate, asbestiform minerals, sulfate, and clay minerals were found using FTIR and XRD investigations. Microscopic examination revealed particles of various shapes, including angular, flaky, rod-like, crystalline, irregular, rounded, porous, chain, spherical, and agglomeration structures. This proved that the particles had geogenic, anthropogenic, and biological origins. The average value of organic carbon, elemental carbon, and total carbon is found to be 91.56 ± 43.17, 6.72 ± 1.99, and 102.41 ± 44.90 µg/m3, respectively. Water-soluble ions K+ and OC show a substantial association (R = 0.71). Prominent sources identified using Principle component analysis (PCA) are anthropogenic, crustal, industrial, and electronic combustion. This research paper identified the potential sources of PM10, which are vital for preparing an air quality management plan in the urban environment of Peshawar.

Interplay of Climate Change and Air Pollution- Projection of the under-5 mortality attributable to ambient particulate matter (PM2.5) in South Asia

Ambient fine particulate matter (PM2.5) pollution is a leading health risk factor for children under- 5 years, especially in developing countries. South Asia is a PM2.5 hotspot, where climate change, a potential factor affecting PM2.5 pollution, adds a major challenge. However, limited evidence is available on under-5 mortality attributable to PM2.5 under different climate change scenarios. This study aimed to project under-5 mortality attributable to long-term exposure to ambient PM2.5 under seven air pollution and climate change mitigation scenarios in South Asia. We used a concentration-risk function obtained from a previous review to project under-5 mortality attributable to ambient PM2.5. With a theoretical minimum risk exposure level of 2.4 μg/m3, this risk function was linked to gridded annual PM2.5 concentrations from atmospheric modeling to project under-5 mortality from 2010 to 2049 under different climate change mitigation scenarios. The scenarios were developed from the Aim/Endues global model based on end-of-pipe (removing the emission of air pollutants at the source, EoP) and 2 °C target measures. Our results showed that, in 2010-2014, about 306.8 thousand under-5 deaths attributable to PM2.5 occurred in South Asia under the Reference (business as usual) scenario. The number of deaths was projected to increase in 2045-2049 by 36.6% under the same scenario and 7.7% under the scenario where EoP measures would be partially implemented by developing countries (EoPmid), and was projected to decrease under other scenarios, with the most significant decrease (81.2%) under the scenario where EoP measures would be fully enhanced by all countries along with the measures to achieve 2 °C target (EoPmaxCCSBLD) across South Asia. Country-specific projections of under-5 mortality varied by country. The current emission control strategy would not be sufficient to reduce the number of deaths in South Asia. Robust climate change mitigation and air pollution control policy implementation is required.

Bicomponent core/sheath melt-blown fibers for air filtration with ultra-low resistance

With the escalating air pollution and frequent outbreaks of airborne diseases, there is a growing demand for personal protective filtration media. Melt-blown nonwovens have proven to be highly effective in capturing tiny particles, but their tightly packed fiber assemblages are more resistant to airflow and less comfortable to breathe. Here, we present a one-step melt-blown spinning process for the production of bicomponent core/sheath (BCS) crimped fibers and their application in high-efficiency, low-resistance air filtration. Fiber curl is caused by unbalanced internal stresses resulting from differences in the structure components, resulting in uneven shrinkage inside and outside the fibers. The resulting CM@S-2 filtration media features a uniform fiber curl and a porous fiber mesh structure, which reduces air filtration resistance. Under the same filtration conditions, the filtration efficiency of CM@S-2 (96.58% vs. 95.58%), filtration resistance (56.1 Pa vs. 108.0 Pa), quality factor (0.061 Pa-1vs. 0.029 Pa-1), and dust holding capacity (10.60 g m-2vs. 9.10 g m-2) were comparable to those of the single-component polypropylene filters. The filtration efficiency of the CM@S-2 remained above 94.0% after 30 days of indoor storage. Computational Fluid Dynamics (CFD) simulation demonstrated that crimped fibers effectively reduce pressure surges on the filter media caused by fiber accumulation. In comparative tests with commercial masks, the CM@S-2 cartridge masks demonstrated superior air permeability compared to commercial masks under similar filtration conditions. In conclusion, the bicomponent core/sheath melt-blown fibers significantly reduce air resistance and show excellent potential for application in protective masks.

Substantially reducing global PM2.5-related deaths under SDG3.9 requires better air pollution control and healthcare

The United Nations' Sustainable Development Goal (SDG) 3.9 calls for a substantial reduction in deaths attributable to PM2.5 pollution (DAPP). However, DAPP projections vary greatly and the likelihood of meeting SDG3.9 depends on complex interactions among environmental, socio-economic, and healthcare parameters. We project potential future trends in global DAPP considering the joint effects of each driver (PM2.5 concentration, death rate of diseases, population size, and age structure) and assess the likelihood of achieving SDG3.9 under the Shared Socioeconomic Pathways (SSPs) as quantified by the Scenario Model Intercomparison Project (ScenarioMIP) framework with simulated PM2.5 concentrations from 11 models. We find that a substantial reduction in DAPP would not be achieved under all but the most optimistic scenario settings. Even the development aligned with the Sustainability scenario (SSP1-2.6), in which DAPP was reduced by 19%, still falls just short of achieving a substantial (≥20%) reduction by 2030. Meeting SDG3.9 calls for additional efforts in air pollution control and healthcare to more aggressively reduce DAPP.

Nanopatterning of beaded poly(lactic acid) nanofibers for highly electroactive, breathable, UV-shielding and antibacterial protective membranes

Despite great potential in fabrication of biodegradable protective membranes by electrospinning of poly(lactic acid) (PLA) nanofibers, it is still thwarted by smooth surfaces and poor electroactivity that challenge the promotion of electret properties and long-term air filtration performance. Here, a microwave-assisted synthetic method was used to customize dielectric TiO2 nanocrystals of ultrasmall and uniform dimensions (∼30 nm), which were homogeneously embedded at beaded PLA nanofibers (PLA@TiO2, diameter of around 280 nm) by the combined "electrospinning-electrospray" approach. With small amounts of TiO2 (2, 4 and 6 wt%), the nanopatterned PLA@TiO2 nanofibrous membranes (NFMs) were characterized by largely increased dielectric constants (nearly 1.9), surface potential (up to 1.63 kV) and triboelectric properties (output voltage of 12.2 V). Arising from the improved electroactivity and self-charging mechanisms, the nanopatterned PLA@TiO2 NFMs exhibited remarkable PM0.3 filtration properties (97.9 %, 254.6 Pa) even at the highest airflow rate of 85 L/min, surpassing those of pure PLA membranes (86.2 %, 483.7 Pa). This was moreover accompanied by inhibition rates of 100 % against both E. coli and S. aureus, as well as excellent UV-blocking properties (UPF as high as 3.8, TUVA of 50.9 % and TUVB of 20.1 %). The breathable and electroactive nanopatterned PLA NFMs permit promising applications in multifunctional protective membranes toward excellent UV shielding and high-efficiency removal of both PMs and pathogens.

A district-level emission inventory of anthropogenic PM2.5 from the primary sources over the Indian Indo Gangetic Plain: Identification of the emission hotspots

A district-wise emission inventory was made for the states and union territories (UTs) of the Indian Indo-Gangetic Plain for the base year of 2018 to estimate the emissions of PM2.5 from various sectors. In addition to conventional sectors, emissions from road dust, fossil-fuelled irrigation pumps, and construction dust were also taken into account. Total primary anthropogenic PM2.5 emission was estimated to be 3157.3 Gg (or kilo-tones) for the year 2018 of which 32 % originated from the industrial sector, 27 % from domestic fuel consumption, 23 % from open burning, 14 % from road dust, 2 % from vehicular and 2 % from various unorganized sectors. The highest emissions were observed during the premonsoon (1013 Gg/year) followed by postmonsoon (802Gg/year), winter (788 Gg/year), and lowest during the monsoon (554Gg/year). Among the states and UTs, Uttar Pradesh contributes the most in total emissions (39 %), followed by Punjab (19 %), Bihar (17 %), West Bengal (13 %), Haryana (11 %), Delhi (0.9 %) and Chandigarh (0.1 %). Emission for per capita and for billion-rupee of state gross domestic product (GDP) were the highest for Punjab and Haryana. Results have identified the districts of Punjab (Firozpur, Ludhiana, Jalandhar), scattered pockets of Uttar Pradesh (Sonbhadra, Agra, Varanasi, Kanpur, Lucknow, Prayagraj) and lower Gangetic delta (Gaya, Muzaffarpur, Burdwan, both 24-parganas and Murshidabad) as potent hotspots of cumulative PM2.5 emissions. On the other hand, the districts of Punjab (Faridkot, Mansa, Muktsar, Fatehgarh) were found to be the hotspots for per capita emissions. High emissions were observed from the domestic sector, brick kilns, and micro and small-scale industries, and regulating norms should be more stringent for these sectors. Such a study will be a value add for the policymakers and health experts to assess emission hot spots, pollution simulation, and associated mortality analysis of the region.

Association between sea-land breeze and particulate matter in five coastal urban locations in India

Particulate matter less than 2.5 μm particle diameter (PM2.5) is the most significant environmental issue globally. PM2.5 is an integral component of air quality monitoring and management, human health, weather, climate, and epidemiological research. In this work, we investigate the seasonal variation in PM2.5 mass concentrations and the association between the sea-land breeze system and particulate matter in five coastal urban locations in India (Kolkata, Visakhapatnam, Chennai, Thiruvananthapuram, and Mumbai). The relative occurrence of high PM2.5 mass concentrations was the greatest during the winter season (December through February) while the relative occurrence of low PM2.5 mass concentrations was the greatest during the monsoon season (June through September). Amongst locations, Kolkata experiences the highest PM2.5 loading in winter while Thiruvananthapuram experiences the lowest PM2.5 loading in monsoon. Indo-Gangetic Plain (IGP) outflow onto the Bay of Bengal significantly impacts locations along the eastern coast of India with reduced impact from north (Kolkata) to south (Chennai). The sea-breeze component analysis revealed daily cycles of the sea-land breeze with varying magnitudes of the breeze between the different seasons. Overall, we found a negative association between the sea-land breeze magnitude and PM2.5 mass concentrations, implying that the weakened sea-land breeze may deteriorate air quality in coastal locations due to poor ventilation. The vertical profiles of aerosol extinction showed elevated aerosol layers within 1 km from the surface in almost all locations. The decreasing trend in the land-sea temperature contrast in coastal locations is expected to deteriorate air quality in coastal locations in the warming future. Nevertheless, critical analyses using ground-based remote sensing techniques are required for a better understanding the impact of sea-land breeze dynamics on air quality in coastal locations.

Size-segregated characteristics of water-soluble oxidative potential in urban Xiamen: Potential driving factors and implications for human health

Oxidative potential (OP), defined as the ability of particulate matter (PM) to generate reactive oxygen species (ROS), has been considered as a potential health-related metric for PM. Particles with different sizes have different OP and deposition efficiencies in the respiratory tract and pose different health risks. In this study, size-segregated PM samples were collected at a coastal urban site in Xiamen, a port city in southeastern China, between August 2020 and September 2021. The water-soluble constituents, including inorganic ions, elements and organic carbon, were determined. Total volume-normalized OP based on the dithiothreitol assay was highest in spring (0.241 ± 0.033 nmol min-1 m-3) and lowest in summer (0.073 ± 0.006 nmol min-1 m-3). OP had a biomodal distribution with peaks at 0.25-0.44 μm and 1.0-1.4 μm in spring, summer, and winter and a unimodal pattern with peak at 0.25-0.44 μm in fall, which were different from the patterns of redox-active species. Variations in the seasonality of fine and coarse mode OP and their correlations with water-soluble constituents showed that the size distribution patterns of OP could be attributed to the combined effects of the size distributions of transition metals and redox-active organics and the interactions between them which varied with emissions, meteorological conditions and atmospheric processes. Respiratory tract deposition model indicated that the deposited OP and the toxic elements accounted for 47.9 % and 36.8 % of their measured concentrations, respectively. The highest OP doses and the excess lifetime carcinogenic risk (ELCR) were found in the head airway (>70 %). However, the size distributions of OP deposition and ELCR in the respiratory tract were different, with 63.9 % and 49.4 % of deposited ELCR and OP, respectively, coming from PM2.5. Therefore, attention must be paid to coarse particles from non-exhaust emissions and road dust resuspension.

Health effects of carbonaceous PM2.5 compounds from residential fuel combustion and road transport in Europe

Exposure to fine particulate matter (PM2.5) is associated with an increased risk of morbidity and mortality. In Europe, residential fuel combustion and road transport emissions contribute significantly to PM2.5. Toxicological studies indicate that PM2.5 from these sources is relatively more hazardous, owing to its high content of black and organic carbon. Here, we study the contribution of the emissions from these sectors to long-term exposure and excess mortality in Europe. We quantified the impact of anthropogenic carbonaceous aerosols on excess mortality and performed a sensitivity analysis assuming that they are twice as toxic as inorganic particles. We find that total PM2.5 from residential combustion leads to 72,000 (95% confidence interval: 48,000-99,000) excess deaths per year, with about 40% attributed to carbonaceous aerosols. Similarly, road transport leads to about 35,000 (CI 23,000-47,000) excess deaths per year, with 6000 (CI 4000-9000) due to carbonaceous particles. Assuming that carbonaceous aerosols are twice as toxic as other PM2.5 components, they contribute 80% and 37%, respectively, to residential fuel combustion and road transport-related deaths. We uncover robust national variations in the contribution of each sector to excess mortality and emphasize the importance of country-specific emission reduction policies based on national characteristics and sectoral shares.

Measuring the urban-rural and spatiotemporal heterogeneity of the drivers of PM2.5-attributed health burdens in China from 2008 to 2021 using high-resolution dataset

Urbanization has been considered a driver of PM2.5 pollution and the attributed health burden. This study systematically measured the spatiotemporal and urban-rural heterogeneity of PM2.5-attributed health burden drivers, including income, population, baseline mortality rate, and PM2.5 level. The results reveal the significantly positive contribution of disposable income and the periodical and urban-rural differentiation of population contribution to PM2.5-attributed health burden. The difference in driver performance due to socioeconomic development and urbanization stages might be an important determinant for different or even opposite results of previous studies. Policymaking for mitigating PM2.5-attributed health risk could incorporate the re-assessment and driver determination for PM2.5-attributed health burden into the construction and development plan from the overall urbanization perspective. The urbanization-perspective driver decomposition could be synergized with the flow analysis, equality evaluation, and policy benefit estimation to achieve further direction-determining and quantitative assessment of the urban-rural PM2.5 health risk management strategies.

Impact of Glasgow Climate Pact and Updated Nationally Determined Contribution on Mercury Mitigation Abiding by the Minamata Convention in India

India is one of the largest emitters of atmospheric anthropogenic mercury (Hg) and the third-largest emitter of greenhouse gases in the world. In the past decade, India has been committed to the Minamata Convention (2017) in addition to the Paris Climate Change Agreement (2015) and the Glasgow Pact (2021). More than 70% to 80% of India's mercury and carbon dioxide emissions occur because of anthropogenic activities from coal usage. This study explores nine policy scenarios, the nationally determined contribution (NDC) scenario, and two deep decarbonization pathways (DDP) with and without mercury control technologies in the energy and carbon-intensive sectors using a bottom-up, techno-economic model, AIM/Enduse India. It is estimated that NDC scenarios reduce mercury emissions by 4%-10% by 2070; while coal intensive (DDP-CCS) pathways and focus on renewables (DDP-R) reduce emissions by 10%-54% and 15%-59%, respectively. Increase in the renewables share (power sector) can result in a significant reduction in the costs of additional pollution-abating technologies in the DDP-R scenario when compared with the coal intensive DDP-CCS scenario. However, the industry sector, especially iron and steel and metal production, will require stringent policies to encourage installation of pollution-abating technologies to mitigate mercury emissions under all the scenarios.

Climate change and mortality rates of COPD and asthma: A global analysis from 2000 to 2018

BACKGROUND

Climate change plays a significant role in global health threats, particularly with respiratory diseases such as chronic obstructive pulmonary disease (COPD) and asthma, but the long-term global-scale impact of climate change on these diseases' mortality remains unclear.

OBJECTIVE

This study aims to investigate the impact of climate change on the age-standardized mortality rates (ASMR) of COPD and asthma at national levels.

METHODS

We used Global Burden of Disease (GBD) data of ASMR of COPD and asthma from 2000 to 2018. The climate change index was represented as the deviance percentage of temperature (DPT) and relative humidity (DPRH), calculated based on 19-year temperature and humidity averages. Annual temperature, RH, and fine particulate matter (PM2.5) levels in 185 countries/regions were obtained from ERA5 and the OECD's environmental statistics database. General linear mixed-effect regression models were used to examine the associations between climate change with the log of ASMR (LASMR) of COPD and asthma.

RESULTS

After adjusting for annual PM2.5, SDI level, smoking prevalence, and geographical regions, a 0.26% increase in DPT was associated with decreases of 0.016, 0.017, and 0.014 per 100,000 people in LASMR of COPD and 0.042, 0.046, and 0.040 per 100,000 people in LASMR of asthma for both genders, males, and females. A 2.68% increase in DPRH was associated with increases of 0.009 and 0.011 per 100,000 people in LASMR of COPD. We observed a negative association of DPT with LASMR for COPD in countries/regions with temperatures ranging from 3.8 to 29.9 °C and with LASMR for asthma ranging from -5.3-29.9 °C. However, we observed a positive association of DPRH with LASMR for both COPD and asthma in the RH range of 41.2-67.2%.

CONCLUSION

Climate change adaptation and mitigation could be crucial in reducing the associated COPD and asthma mortality rates, particularly in regions most vulnerable to temperature and humidity fluctuations.

The challenge of population aging for mitigating deaths from PM2.5 air pollution in China

Estimating the health burden of air pollution against the background of population aging is of great significance for achieving the Sustainable Development Goal 3.9 which aims to substantially reduce the deaths and illnesses from air pollution. Here, we estimated spatiotemporal changes in deaths attributable to PM2.5 air pollution in China from 2000 to 2035 and examined the drivers. The results show that from 2019 to 2035, deaths were projected to decease 15.4% (6.6%-20.7%, 95% CI) and 8.4% (0.6%-13.5%) under the SSP1-2.6 and SSP5-8.5 scenario, respectively, but increase 10.4% (5.1%-20.5%) and 18.1% (13.0%-28.3%) under SSP2-4.5 and SSP3-7.0 scenarios. Population aging will be the leading contributor to increased deaths attributable to PM2.5 air pollution, which will counter the positive gains achieved by improvements in air pollution and healthcare. Region-specific measures are required to mitigate the health burden of air pollution and this requires long-term efforts and mutual cooperation among regions in China.

The Air Pollution Human Health Burden in Different Future Scenarios That Involve the Mitigation of Near-Term Climate Forcers, Climate and Land-Use

Elevated surface concentrations of ozone and fine particulate matter (PM2.5) can lead to poor air quality and detrimental impacts on human health. These pollutants are also termed Near-Term Climate Forcers (NTCFs) as they can also influence the Earth's radiative balance on timescales shorter than long-lived greenhouse gases. Here we use the Earth system model, UKESM1, to simulate the change in surface ozone and PM2.5 concentrations from different NTCF mitigation scenarios, conducted as part of the Aerosol and Chemistry Model Intercomparison Project (AerChemMIP). These are then combined with relative risk estimates and projected changes in population demographics, to estimate the mortality burden attributable to long-term exposure to ambient air pollution. Scenarios that involve the strong mitigation of air pollutant emissions yield large future benefits to human health (25%), particularly across Asia for black carbon (7%), when compared to the future reference pathway. However, if anthropogenic emissions follow the reference pathway, then impacts to human health worsen over South Asia in the short term (11%) and across Africa (20%) in the longer term. Future climate change impacts on air pollutants can offset some of the health benefits achieved by emission mitigation measures over Europe for PM2.5 and East Asia for ozone. In addition, differences in the future chemical environment over regions are important considerations for mitigation measures to achieve the largest benefit to human health. Future policy measures to mitigate climate warming need to also consider the impact on air quality and human health across different regions to achieve the maximum co-benefits.

Effects of Ambient Air Pollutants on Hospital Admissions among Children Due to Asthma and Wheezing-Associated Lower Respiratory Infections in Mysore, India: A Time Series Study

Air pollutants are known to trigger asthma and wheezing-associated lower respiratory infections in children, but evidence regarding their effect on hospital admissions in India is limited. We conducted a time-series study over a period of five years to assess the role of ambient air pollutants in daily asthma-related hospital admissions in children in Mysore, India. Daily asthma and wheeze (associated with lower respiratory infections) admissions were modelled using a generalised additive model (GAM) to examine the non-linear effects and generalised linear models (GLM) for linear effects, if any. Models were adjusted by day of the week and lag days, with smooth terms for time, maximum temperature, and relative humidity, and they were stratified by sex and age group. Of the 362 children admitted, more than 50% were boys, and the mean age was 5.34 years (±4.66). The GAMs showed non-linear associations between NO2, PM2.5, and NH3. For example, a 10 µgm-3 (or 10%) increase in NO2 increased admissions by 2.42. These non-linear effects were more pronounced in boys. A linear effect was detected for PM10 with a relative risk (95% CI) of 1.028, 1.013, and 1.043 with admission. Further research is needed to explore whether these findings can be replicated in different cities in India. Air pollution needs to be controlled, and policies that focus on lower cut-off levels for vulnerable populations are necessary.

Global PM2.5 Prediction and Associated Mortality to 2100 under Different Climate Change Scenarios

Ambient fine particulate matter (PM_2.5) has severe adverse health impacts, making it crucial to reduce PM_2.5 exposure for public health. Meteorological and emissions factors, which considerably affect the PM_2.5 concentrations in the atmosphere, vary substantially under different climate change scenarios. In this work, global PM_2.5 concentrations from 2021 to 2100 were generated by combining the deep learning technique, reanalysis data, emission data, and bias-corrected CMIP6 future climate scenario data. Based on the estimated PM_2.5 concentrations, the future premature mortality burden was assessed using the Global Exposure Mortality Model. Our results reveal that SSP3-7.0 scenario is associated with the highest PM_2.5 exposure, with a global concentration of 34.5 μg/m³ in 2100, while SSP1-2.6 scenario has the lowest exposure, with an estimated of 15.7 μg/m³ in 2100. PM_2.5-related deaths for individuals under 75 years will decrease by 16.3 and 10.5% under SSP1-2.6 and SSP5-8.5, respectively, from 2030s to 2090s. However, premature mortality for elderly individuals (>75 years) will increase, causing the contrary trends of improved air quality and increased total PM_2.5-related deaths in the four SSPs. Our results emphasize the need for stronger air pollution mitigation measures to offset the future burden posed by population age.

The turbulent future brings a breath of fresh air

Ventilation of health hazardous aerosol pollution within the planetary boundary layer (PBL) - the lowest layer of the atmosphere - is dependent upon turbulent mixing, which again is closely linked to the height of the PBL. Here we show that emissions of both CO2 and absorbing aerosols such as black carbon influence the number of severe air pollution episodes through impacts on turbulence and PBL height. While absorbing aerosols cause increased boundary layer stability and reduced turbulence through atmospheric heating, CO2 has the opposite effect over land through surface warming. In future scenarios with increasing CO2 concentrations and reduced aerosol emissions, we find that around 10% of the world's population currently living in regions with high pollution levels are likely to experience a particularly strong increase in turbulence and PBL height, and thus a reduction in intense pollution events. Our results highlight how these boundary layer processes provide an added positive impact of black carbon mitigation to human health.

Mortality and morbidity assessment attributed to short- and long-term exposure to fine particles in ambient air of Agadir city, Morocco: The AirQ model approach

It is well established that respiratory mortality and morbidity are associated with high concentrations of fine particles such as PM2.5. The aim of this study was to evaluate the long- and short-term impacts of PM2.5 on the population of Agadir, Morocco, using AirQ 2.1.1 software. The mean PM2.5 values were obtained from data collected at three sites. Baseline incidence data were obtained from the literature, and relative risk (RR) values were referenced from the World Health Organization. This study quantified long-term total mortality (LT-TM), lung cancer mortality (LT-LC), morbidity from acute lower respiratory tract infections (LT-ALRI), and morbidity from chronic obstructive pulmonary disease (LT-COPD), as well as short-term total mortality (ST-TM). The attributable proportions (AP) of LT-TM and LT-LC were estimated to 14.19% and 18.42%, respectively. Their excess deaths were estimated to 279 and 11 persons, respectively, and their RRs to 1.16 (95% CI: 1.10-1.22) and 1.23 (95% CI: 1.12-1.37), respectively. Furthermore, the AP of LT-ALRI and LT-COPD were estimated to 14.36% and 15.68%, respectively, their excess deaths to 33 and 4, and their RRs to 1.17 (95% CI: 1.11-1.31) and 1.19 (95% CI: 1.00-1.02), respectively. In comparison, the AP of ST-TM was estimated to 1.27%, with a 25-person excess death rate. This study was conducted to inform decision-making and to promote local policies on ambient air quality.

Future Health Risk Assessment of Exposure to PM2.5 in Different Age Groups of Children in Northern Thailand

Particulate matter with a diameter less than 2.5 (PM_2.5) is one of the major threats posed by air pollution to human health. It penetrates the respiratory system, particularly the lungs. In northern Thailand, the PM_2.5 concentrations have significantly increased in the past decade, becoming a major concern for the health of children. This study aimed to assess the health risk of PM_2.5 in different age groups of children in northern Thailand between 2020 and 2029. Based on the PM_2.5 data from the simulation of the Nested Regional Climate Model with Chemistry (NRCM-Chem), the hazard quotient (HQ) was used to estimate the possible risk from PM_2.5 exposure in children. In general, all age groups of children in northern Thailand will tend to experience the threat of PM_2.5 in the future. In the context of age-related development periods, infants are at a higher risk than other groups (toddlers, young children, school age and adolescents), but adolescents also have a lower risk of exposure to PM_2.5, albeit maintaining a high HQ value (>1). Moreover, the analysis of risk assessment in different age groups of children revealed that PM_2.5 exposure might indeed affect adolescent risk differently depending on gender, with males generally at a heightened risk than females in adolescence.

Future air quality and premature mortality in Korea

We simulate air quality in Korea for the present, the near-term, and the long-term future conditions under the Shared Socioeconomic Pathways (SSP1: most sustainable pathway with strong emissions control, SSP3: most challenging pathway with mild emissions control) using a chemical transport model. Simulated future concentrations of NO₂, SO₂, and fine particulate matter (PM_2.5), show, in general, lower values compared to the present with varying degrees depending on SSP scenarios. Significant reductions in precursor emissions result in a decrease in O₃ concentrations under a NO_x-limited environment in the long-term future under SSP1. Under SSP3, O₃ increases in the future under a VOC-limited regime, driven by increased CH₄ levels and biogenic VOC emissions under the warming climate. Concentrations of PM_2.5 and its components, including sulfate, nitrate, ammonium, and organic aerosols (OA), generally decrease in the long-term future under both scenarios. However, the contribution of biogenic secondary OA (BSOA) to PM_2.5 will increase in the future. Simulated results are used to estimate cardiorespiratory mortality changes with concentration-response factors from epidemiologic studies in Korea based on national health surveys and Korean cohorts, using projected population structures from the SSP database. The cardiorespiratory health burden of long-term exposure to O₃, NO₂, SO₂, and PM_2.5 is estimated to be 10,419 (95 % confidence interval: 1271-17,142), 8630 (0-18,713), 3958 (0-9272), and 10,431 (1411-20,643) deaths in 2019. We find that the total cardiorespiratory excess mortality due to air pollutants under SSP1 decreases by 8 % and 95 % in 2045 and 2095, respectively. Under SSP3, excess mortality increases by 80 % in 2045, and decreases by 22 % in 2095, resulting in a substantial difference in the health outcomes depending on the emission scenario. We also find that the BSOA contribution to total PM_2.5 will differ by region, emphasizing the potential health impact of BSOA on a local scale in the future.

Fabrication of Laminated Micro/Nano Filter and Its Application for Inhalable PM Removal

Particulate matter (PM) with a diameter of 0.3 µm is inhalable and brings great threats to human health. Traditional meltblown nonwovens used for air filtration need to be treated by high voltage corona charging, which has the problem of electrostatic dissipation and thus reduces the filtration efficiency. In this work, a kind of composite air-filter with high efficiency and low resistance was fabricated by alternating lamination of ultrathin electronspun nano-layer and melt-blown layer without corona charging treatment. The effects of fiber diameter, pore size, porosity, layer number, and weight on filtration performance were investigated. Meanwhile, the surface hydrophobicity, loading capacity, and storage stability of the composite filter were studied. The results indicate that the filters (18.5 gsm) laminated by 10 layers fiber-webs present excellent filtration efficiency (97.94%), low pressure drop (53.2 Pa), high quality factor (QF 0.073 Pa−1), and high dust holding capacity (9.72 g/m2) for NaCl aerosol particles. Increasing the layers and reducing individual layer weight can significantly improve filtration efficiency and reduce pressure drop of the filter. The filtration efficiency decayed slightly from 97.94% to 96.48% after 80 days storage. The alternate arrangement of ultra-thin nano and melt-blown layers constructed a layer-by-layer interception and collaborative filtering effect in the composite filter, realizing the high filtration efficiency and low resistance without high voltage corona charging. These results provided new insights for the application of nonwoven fabrics in air filtration.

Dual-Network Structured Nanofibrous Membranes with Superelevated Interception Probability for Extrafine Particles

Airborne particulate matter (PM) pollution has caused a public health threat, including nanoscale particles, especially with emerging infectious diseases and indoor and vehicular environmental pollution. However, most existing indoor air filtration units are expensive, energy-intensive, and bulky, and there is an unavoidable trade-off between low-efficiency PM_0.3/pathogen interception, PM removal, and air resistance. Herein, we designed and synthesized a two-dimensional continuous cellulose-sheath/net with a unique dual-network corrugated architecture to manufacture high-efficiency air filters and even N95 particulate face mask. Combined with its sheath/net structured pores (size 100-200 nm) consisting of a cellulose framework (1-100 nm diameter), the cellulose sheath/net filter offers high-efficiency air filtration (>99.5338%, Extrafine particles; >99.9999%, PM_2.5), low-pressure drops, and a robustness quality factor of >0.14 Pa^-1, utilizing their ultralight weight of 30 mg/m² and physical adhesion and sieving behaviors. Simultaneously, masks prepared with cellulose-sheath/net filters are more likely to capture and block smaller particles than the N95 standard. The synthesis of such materials with their nanoscale features and designed macrostructures may suggest new design criteria for a novel generation of high-efficiency air filter media for different applications such as personal protection products and industrial dust removal.

Mortality Attributable to Ambient Air Pollution: A Review of Global Estimates

Since the publication of the first epidemiological study to establish the connection between long-term exposure to atmospheric pollution and effects on human health, major efforts have been dedicated to estimate the attributable mortality burden, especially in the context of the Global Burden of Disease (GBD). In this work, we review the estimates of excess mortality attributable to outdoor air pollution at the global scale, by comparing studies available in the literature. We find large differences between the estimates, which are related to the exposure response functions as well as the number of health outcomes included in the calculations, aspects where further improvements are necessary. Furthermore, we show that despite the considerable advancements in our understanding of health impacts of air pollution and the consequent improvement in the accuracy of the global estimates, their precision has not increased in the last decades. We offer recommendations for future measurements and research directions, which will help to improve our understanding and quantification of air pollution-health relationships.

High contribution from outdoor air to personal exposure and potential inhaled dose of PM2.5 for indoor-active university students

People spend most of their time indoors, isolated from the outdoor environment where serious air pollution usually occurs. To what extent outdoor air pollution contributes to their daily personal exposure and inhaled dose? To fill this knowledge gap, an exposure assessment study was conducted for indoor-active university students during a wintertime period of hazy and non-hazy (clear) days in Beijing. Indoor and outdoor fine particulate matter (PM_2.5) samples were collected at six indoor microenvironments, and two outdoor environments representing traffic and ambient exposure in the university, respectively, to estimate the personal exposure of students. The average daily personal exposure and poteantial inhaled dose on hazy days (124.8 ± 72.3 μg m^-3 and 2.74 ± 1.53 mg) were much higher than that on clear days (57.5 ± 31.9 μg m^-3 and 1.26 ± 0.59 mg), indicating a significant influence from the ambient air quality. The indoor PM_2.5 concentrations were significantly and positively correlated with the outdoor ones (r = 0.67-0.96) with an F_INF (infiltration factor) range of 0.44-0.81 during sampling periods. The outdoor-origin air contributed 68%-95% to the total indoor PM_2.5, the average of which was higher during haze events (87%) than clear periods (73%). Correspondingly, outdoor-origin PM_2.5 contributed around 105.4 μg m^-3 and 2.41 mg (85% and 89%) to the daily exposure and inhaled dose of college students on hazy days, respectively, compared to just 39.2 μg m^-3 and 0.95 mg (68% and 75%) on clear days. Our results highlight the significant contribution of outdoor-origin PM_2.5 occurred indoor to both the daily personal exposure and inhaled dose due to air pollution filtration between outdoor and indoor environments. These also suggest a continuous effort not only on ambient air quality improvements, but also on environmental friendly building for public health protection with lower exposure.

Air quality impacts of crop residue burning in India and mitigation alternatives

Crop residue burning contributes to poor air quality and imposes a health burden on India. Despite government bans and other interventions, this practice remains widespread. Here we estimate the impact of changes in agricultural emissions on air quality across India and quantify the potential benefit of district-level actions using an adjoint modeling approach. From 2003 to 2019, we find that agricultural residue burning caused 44,000-98,000 particulate matter exposure-related premature deaths annually, of which Punjab, Haryana, and Uttar Pradesh contribute 67-90%. Due to a combination of relatively high downwind population density, agricultural output, and cultivation of residue-intensive crops, six districts in Punjab alone contribute to 40% of India-wide annual air quality impacts from residue burning. Burning two hours earlier in Punjab alone could avert premature deaths up to 9600 (95% CI: 8000-11,000) each year, valued at 3.2 (95% CI: 0.49-7.3) billion US dollars. Our findings support the use of targeted and potentially low-cost interventions to mitigate crop residue burning in India, pending further research regarding cost-effectiveness and feasibility.

Projecting future health burden associated with exposure to ambient PM2.5 and ozone in China under different climate scenarios

Projecting future air pollution and related health burdens remains challenging because of the complex interactions among future emissions, population, and climate change. In this study, we estimated the premature deaths attributed to ambient fine particulate matter (PM_2.5) and ozone (O₃) from 2015 to 2100 under four socioeconomic climate scenarios based on an age-stratified assessment method. We found that PM_2.5 will decrease in all shared socioeconomic pathway (SSP) scenarios and O₃ will decrease in the SSP1-2.6 and SSP2-4.5 scenarios, contributing to a decrease in premature mortality together with the declining total population in China. However, the benefits of a decline in population size and PM_2.5 and O₃ concentrations over time will be largely offset by population aging, and premature death caused by PM_2.5 and O₃ will continue to rise till 2060-2080. This impact was greater for the O₃-related deaths than those for PM_2.5. Our study highlights the importance of future prevention strategies that must jointly improve air quality and susceptibility to aging.

Compositional Constraints are Vital for Atmospheric PM2.5 Source Attribution over India

India experiences some of the highest levels of ambient PM_2.5 aerosol pollution in the world. However, due to the historical dearth of in situ measurements, chemical transport models that are often used to estimate PM_2.5 exposure over the region are rarely evaluated. Here, we conduct a novel model comparison with speciated airborne measurements of fine aerosol, revealing large biases in the ammonium and nitrate simulations. To address this, we incorporate process-level changes to the model and use satellite observations from the Cross-track Infrared Sounder (CrIS) and the TROPOspheric Monitoring Instrument (TROPOMI) to constrain ammonia and nitrogen oxide emissions. The resulting simulation demonstrates significantly lower bias (NMB_Modified: 0.19; NMB_Base: 0.61) when validated against the airborne aerosol measurements, particularly for the nitrate (NMB_Modified: 0.08; NMB_Base: 1.64) and ammonium simulation (NMB_Modified: 0.49; NMB_Base: 0.90). We use this validated simulation to estimate a population-weighted annual PM_2.5 exposure of 61.4 μg m^-3, with the RCO (residential, commercial, and other) and energy sectors contributing 21% and 19%, respectively, resulting in an estimated 961,000 annual PM_2.5-attributable deaths. Regional exposure and sectoral source contributions differ meaningfully in the improved simulation (compared to the baseline simulation). Our work highlights the critical role of speciated observational constraints in developing accurate model-based PM_2.5 aerosol source attribution for health assessments and air quality management in India.

Seasonal variations in aerosol acidity and its driving factors in the eastern Indo-Gangetic Plain: A quantitative analysis

This study employs ISORROPIA-II for the evaluation of aerosol acidity and quantification of contributions from chemical species and meteorological parameters to acidity variation in the Indian context. PM_2.5 samples collected during summer (April-July 2018), post-monsoon (September-November 2018), and winter (December 2018-January 2019) from a rural receptor location in the eastern Indo-Gangetic Plain (IGP) were analyzed for ionic species, water-soluble organic carbon (WSOC), and organic and elemental carbon (OC, EC) fractions. This was followed by estimation of the in situ aerosol pH and liquid water content (LWC) using the forward mode of ISORROPIA-II, which is less sensitive to measurement uncertainty compared to the reverse mode, for a K⁺-Ca²⁺-Mg²⁺-NH₄⁺-Na⁺-SO₄^2--NO₃^--Cl^--H₂O system. Aerosol pH was moderately acidic (summer: 2.93 ± 0.67; post-monsoon: 2.67 ± 0.23; winter: 3.15 ± 0.34) and was most sensitive to SO₄^2- and total ammonium (TNH₃) variation. The LWC of aerosol showed an increasing trend from summer (16.6 ± 13.6 μg m^-3) through winter (32.9 ± 10.4 μg m^-3). With summer as the baseline, the largest changes in aerosol pH during the other seasons was driven by SO₄^2- (ΔpH: -0.70 to -0.82 units), followed by TNH₃ (ΔpH: +0.25 to +0.38 units) with K⁺ and temperature being significant only during winter (ΔpH: +0.51 and + 0.46 units, respectively). The prevalent acidity regime provided three major insights: i) positive summertime Cl^- depletion (49 ± 20%) as a consequence of SO₄^2- substitution increased aerosol pH by 0.03 ± 0.20 units and decreased LWC by 2.4 ± 5.9 μg m^-3; ii) the rate of strong acidity (H⁺_str) neutralization and the [H⁺_str]/[SO₄^2-] molar ratio suggested the existence of bounded acidity in ammonium-rich (winter) conditions; and iii) significant correlations between LWC, WSOC, and secondary organics during post-monsoon and winter pointed towards a possible indirect role of WSOC in enhancing LWC of aerosol, thereby increasing pH. Given the inability of proxies such as H⁺_str and charge ratios to accurately represent aerosol pH as demonstrated here, this study emphasizes the need for rigorous thermodynamic model-based evaluation of aerosol acidity in the Indian scenario.

Drivers of PM2.5 in the urban agglomeration on the northern slope of the Tianshan Mountains, China

Fine particulate matter (PM_2.5) is a major source of air pollution in China. Although there have been many studies of the drivers of PM_2.5 pollution in the megacities clustered in eastern China, the behavior of PM_2.5 in the northwestern urban agglomeration is not well understood. This study used near-surface observation data for 2015-2019 obtained from the national air environmental monitoring network to examine variation in PM_2.5 in the urban agglomeration on the northern slopes of the Tianshan Mountains (UANSTM). Two-factor interaction provided new insights into the dominant factors of PM_2.5 in the study region. The annual average PM_2.5 concentrations over the study period was 54.3 μg/m³, with an exceedance rate of 23.3%. Wavelet analysis showed two dominant cycles of 320-370 d and 150-200 d with high pollution events occurring in winter. The generalized additive model (GAM) contained linear functions of pressure, non-linear functions of SO₂, NO₂, relative humidity, sunshine duration and temperature. The two most primary variables, NO₂ and SO₂, represent 20.65% and 19.54% of the total deviance explained, respectively, while the meteorological factors account for 36.1% of the total deviance explained. In addition, the interaction between NO₂ and other factors had the strongest effect on PM_2.5. The deviance explained in the two factor interaction model (88.5%) was higher than that in the single factor model (78.4%). Our study emphasized that interaction between meteorological factors and pollutant emissions enhanced the impact on PM_2.5 compared with individual factors, which can provide a scientific basis for developing effective emission reduction strategies in UANSTM.

Decadal changes in PM2.5-related health impacts in China from 1990 to 2019 and implications for current and future emission controls

In China, the rapid development of the economy and implementation of multiple emission control policies in recent decades have been accompanied by dramatic changes in air quality. In this study, PM_2.5 concentrations estimated by using MERRA-2 reanalysis data were integrated into the Global Exposure Mortality Model (GEMM) to explore the spatiotemporal variation of nationwide PM_2.5-related premature mortality from 1990 to 2019, and the driving factors behind decadal changes were evaluated. Since 2000, as a result of PM_2.5 pollution, air quality in China has deteriorated substantially, especially in the fast-developing eastern and southern parts. In 2009, the nationwide population-weighted (PW) PM_2.5 concentration peaked at 41.4 μg/m³ (95% confidence interval [CI], 36.7-46.2). Simultaneously, the GEMM results revealed that nationwide PM_2.5-related deaths increased remarkably from 1089 (95% CI, 965-1210) thousand in 1990 to 1795 (1597-1986) thousand in 2009. The implementation of the toughest-ever Air Pollution Prevention and Control Action Plan (APPCAP) in 2013 effectively controlled PM_2.5 pollution in China. By 2018, the nationwide PW PM_2.5 concentration had decreased to 34.0 (29.2-38.9) μg/m³. Dynamic trend prediction revealed that, although the APPCAP achieved substantial health benefits, the policy did not result in further remarkable reductions in PM_2.5-related deaths; in 2019, deaths peaked at 1932 (1716-2140) thousand. PM_2.5-related deaths in 2030 were projected for each of four emission control scenarios. The results of the driving factor analysis and the future projections indicated that the health benefits from improving air quality are likely to be counterbalanced by changes in the population age structure. Because population ageing is becoming more and more rapid in China and the challenge of climate change is increasing, the results of this study imply that policymakers need to implement more stringent measures and set more ambitious emission control targets to reduce nationwide PM_2.5-related premature mortality in the future.

Environmentally vulnerable or sensitive groups exhibiting varying concerns toward air pollution can drive government response to improve air quality

Air pollution seriously threatens human health, and its consequences are particularly prevalent among environmentally vulnerable or sensitive groups. However, whether the concerns among these groups are different and how they affect air pollution governance remain unclear. Here, we extract 3.8 million haze-related posts from China’s Sina Weibo and analyze the concerns raised by these groups by constructing an air pollution notability index. The results show that protection is the key theme for women aged 20–35 years, while elderly individuals are easily influenced by haze-related product ads yet lack awareness of scientific-based protection. Concerns shared by young individuals are more effective in pressuring the government in cities that experience higher levels of pollution. Concerns shared by women are more effective in cities that experience lower levels of pollution. This study evidences the influence of the public concerns conveyed via social media on air pollution governance in China.

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Online haze concerns from environmentally vulnerable groups can drive air clean

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Government response to their concern plays the key role in improving air quality

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When PM2.5 exceeds 200 μg/m³, their concern shifts from self-protection to governance

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Elders are easily drawn by haze-related ads yet lack aware of scientific protection

Local mortality impacts due to future air pollution under climate change scenarios

The health impacts of global climate change mitigation will affect local populations differently. However, most co-benefits analyses have been done at a global level, with relatively few studies providing local level results. We aimed to quantify the local health impacts due to fine particles (PM_2.5) under the governance arrangements embedded in the Shared Socioeconomic Pathways (SSPs1-5) under two greenhouse gas concentration scenarios (Representative Concentration Pathways (RCPs) 2.6 and 8.5) in local populations of Mozambique, India, and Spain. We simulated the SSP-RCP scenarios using the Global Change Analysis Model, which was linked to the TM5-FASST model to estimate PM_2.5 levels. PM_2.5 levels were calibrated with local measurements. We used comparative risk assessment methods to estimate attributable premature deaths due to PM_2.5 linking local population and mortality data with PM_2.5-mortality relationships from the literature, and incorporating population projections under the SSPs. PM_2.5 attributable burdens in 2050 differed across SSP-RCP scenarios, and sensitivity of results across scenarios varied across populations. Future attributable mortality burden of PM_2.5 was highly sensitive to assumptions about how populations will change according to SSP. SSPs reflecting high challenges for adaptation (SSPs 3 and 4) consistently resulted in the highest PM_2.5 attributable burdens mid-century. Our analysis of local PM_2.5 attributable premature deaths under SSP-RCP scenarios in three local populations highlights the importance of both socioeconomic development and climate policy in reducing the health burden from air pollution. Sensitivity of future PM_2.5 mortality burden to SSPs was particularly evident in low- and middle- income country settings due either to high air pollution levels or dynamic populations.

Multi-layered micro/nanofibrous nonwovens for functional face mask filter

The worldwide COVID-19 pandemic has led to an attention on the usage of personal protective face masks. However, the longevity and safety of the commercial face masks are limited due to the charge dissipation of the electret meltblown nonwovens, which are dominate in the face mask filters. Herein, we design a type of multi-layer structured nonwovens using meltblowing and electrospinning technologies. The complex nonwovens involving meltblown and electrospun fibers are designed to possess multilevel fiber diameters and pore sizes. The micro/nanofibers with porous and wrinkled surface morphologies can well capture particulate matters (PMs), and the multilevel pore sizes contribute to low air resistance under high filtration efficiency. Airflow field simulation was carried out to understand the pressure distribution within the nonwovens in the filtration process. Meanwhile, by adding Ag nanoparticles (AgNPs) as additives, the nonwovens exhibit excellent antibacterial performance. The resultant nonwovens exhibit filtration efficiency of 99.1% for PM_0.3 and low pressure drop of 105 Pa under the 10.67 cm/s inlet air velocity, and antibacterial rate of > 99.99% for Escherichia coli. These performances and functions make the designed complex nonwovens a promising filter core for face masks.

ELECTRONIC SUPPLEMENTARY MATERIAL

Supplementary material (Fig. S1. The filtration efficiencies of a brand of surgical mask changes with the storage time under the condition of 100% humidity. Fig. S2. The FE-SEM images of the fibers after blocking PMs. Fig. S3. Illustration of 3D structure models of the nonwovens. Fig. S4. Diameter distribution of AgNPs. Table S1. The structure parameters and filtration performances of the PP-M fibers with and without pores and wrinkles. Table S2. Filtration performance of PP-M/PLA-M/PLA-N nonwovens and commercial face masks. Table S3. The structural parameters for the nonwovens. Table S4. The filtration efficiencies and pressure drops of the PP, PE spunbonded nonwovens, and PP-M/PLA-M/PLA-N@AgNPs nonwovens) is available in the online version of this article at 10.1007/s12274-022-4350-2.

The decay of airborne bacteria and fungi in a constant temperature and humidity test chamber

Despite substantial research to profile the microbial characteristics in the atmosphere, the changing metabolism underpinning microbial successional dynamics remains ambiguous. Herein, we applied qPCR, high-throughput sequencing of the genes encoding 16S and ITS rRNA to render the bacterial/fungal dynamics of ambient PM_2.5 filters maintained at constant conditions of temperature (20 ± 2 °C) and humidity (50 ± 5%). The incubation experiments which lasted for 50 days aim to simulate a metabolic process of microbe in two types PM_2.5 (polluted and non-polluted). The results show that microbial community species in polluted PM_2.5 had faster decay rates, more bacterial diversity and less fungal community compared to the non-polluted ones. For bacteria, the proportion of anaerobic species is higher than aerobic ones, and their performance of contain mobile elements, form-biofilms, and pathogenic risks declined rapidly as times went by. Whereas for fungi, saprotroph species occupied about 70% of the population, resulting in a specified peak of abundance due to the adequacy nutrients supplied by the apoptosis cells. Combining the classified microbial species, we found stable community structure and the volatile ones related to the various metabolic survival strategies during different time. Without the input of peripheral environment, the health risks of airborne microbe descend to a healthy level after 20 days, implying their biologic effectiveness was about 20 days no matter the air is polluted or not. This study provided new insights into the different metabolic survival of airborne microorganisms in ideal and stable conditions.

High-performance anti-haze window screen based on multiscale structured polyvinylidene fluoride nanofibers

Indoor air quality (IAQ) has assumed new significance given the extensive amount of time spent indoor due to the coronavirus pandemic and particulate matter (PM) pollution. Accordingly, the development of window air filters to effectively intercept PM from outdoor air under natural ventilation conditions is an important research topic. However, most existing filters inevitably suffer from the compromise among filtration capability, transparency, and air permeability. In this study, we fabricate a high-performance transparent air filter to improve IAQ via natural ventilation. polyvinylidene fluoride (PVDF) superfine nanofibers of size 20-35 nm are prepared using extremely dilute solution electrospinning; a multi-scale nanofiber structure is then designed. By adjusting the ratio of PVDF superfine nanofibers (SNs) to PVDF coarse fibers (CNs), we balance the structure-performance relationship. Benefiting from the multiscale structural features that include a small pore size (0.72 μm) and high porosity (92.22%), the resulting filters exhibit excellent performance including high interception efficiency (99.92%) for PM_0.3, low air resistance (69 Pa), high transparency (∼80%) and stable filtration after 100 h of UV irradiation. This work describes a new strategy for the fabrication of nanofibers with true-nanoscale diameters and the design of high-performance air filters.

Particulate Matter and Premature Mortality: A Bayesian Meta-Analysis

BACKGROUND

We present a systematic review of studies assessing the association between ambient particulate matter (PM) and premature mortality and the results of a Bayesian hierarchical meta-analysis while accounting for population differences of the included studies.

METHODS

The review protocol was registered in the PROSPERO systematic review registry. Medline, CINAHL and Global Health databases were systematically searched. Bayesian hierarchical meta-analysis was conducted using a non-informative prior to assess whether the regression coefficients differed across observations due to the heterogeneity among studies.

RESULTS

We identified 3248 records for title and abstract review, of which 309 underwent full text screening. Thirty-six studies were included, based on the inclusion criteria. Most of the studies were from China (n = 14), India (n = 6) and the USA (n = 3). PM_2.5 was the most frequently reported pollutant. PM was estimated using modelling techniques (22 studies), satellite-based measures (four studies) and direct measurements (ten studies). Mortality data were sourced from country-specific mortality statistics for 17 studies, Global Burden of Disease data for 16 studies, WHO data for two studies and life tables for one study. Sixteen studies were included in the Bayesian hierarchical meta-analysis. The meta-analysis revealed that the annual estimate of premature mortality attributed to PM_2.5 was 253 per 1,000,000 population (95% CI: 90, 643) and 587 per 1,000,000 population (95% CI: 1, 39,746) for PM₁₀.

CONCLUSION

253 premature deaths per million population are associated with exposure to ambient PM_2.5. We observed an unstable estimate for PM₁₀, most likely due to heterogeneity among the studies. Future research efforts should focus on the effects of ambient PM₁₀ and premature mortality, as well as include populations outside Asia. Key messages: Ambient PM_2.5 is associated with premature mortality. Given that rapid urbanization may increase this burden in the coming decades, our study highlights the urgency of implementing air pollution mitigation strategies to reduce the risk to population and planetary health.

Estimation of ambient PM2.5-related mortality burden in China by 2030 under climate and population change scenarios: A modeling study

BACKGROUND

Fine particulate matter (PM_2.5) pollution is one of the most critical environmental and public health problems in China and has caused an enormous disease burden, especially long-term PM_2.5 exposure. Global climate change represents another environmental challenge in the coming decades and is also an essential factor affecting PM_2.5 pollution. Moreover, China has an aging population with a changing population size and falling age-standardized mortality rates. However, little evidence exists evaluating the potential impacts from climate change and population aging on the long-term PM_2.5 exposure-related disease burden. This study quantifies the impacts of climate and population changes on changes in the disease burden attributed to long-term PM_2.5 exposure from 2015 to 2030 in mainland China, which could add evidence for the revision of relevant environmental standards and health policies.

METHODS

This modeling study investigated long-term PM_2.5 exposure-related mortality across China based on PM_2.5 projections under Intergovernmental Panel on Climate Change Representative Concentration Pathways (RCPs) and population scenarios from shared socioeconomic pathways (SSPs). PM_2.5 concentrations were simulated by the Weather Research and Forecasting (WRF) and Community Multiscale Air Quality (CMAQ) modeling systems. In addition, three types of population projections in 2030 relative to 2015 were set up as follows: (i) the population remained the same as that in 2015; (ii) the population size changed under SSPs, but the age structure remained the same; (iii) both the population size and age structure changed under SSPs. The global exposure mortality model (GEMM) was adopted to estimate PM_2.5-related premature deaths.

RESULTS

Ambient PM_2.5 concentrations decreased from 2015 to 2030 under the two climate and emission scenarios. Estimates of related premature mortality in 2030 declined compared with that in 2015 due to lower PM_2.5 concentrations (RCP4.5: -16.8%; RCP8.5: -16.4%). If the age structure of the population remained unchanged and the population size changed under SSPs, the nonaccidental premature mortality also showed a decrease ranging from -18.6% to -14.9%. When both population size and age structure changed under SSPs, the population in China would become older. Nonaccidental premature mortality would sharply increase by 35.7-52.3% (with a net increase of 666-977 thousand) in 2030.

CONCLUSION

The PM_2.5 pollution in 2030 under both RCP4.5 and RCP8.5 would slightly improve. The population sizes in 2030 projected by SSPs are relatively stable compared with that in 2015. However, the modest decrease due to air pollution improvement and stable population size would be offset by population aging.

Regional Features of Long-Term Exposure to PM2.5 Air Quality over Asia under SSP Scenarios Based on CMIP6 Models

This study investigates changes in fine particulate matter (PM_2.5) concentration and air-quality index (AQI) in Asia using nine different Coupled Model Inter-Comparison Project 6 (CMIP6) climate model ensembles from historical and future scenarios under shared socioeconomic pathways (SSPs). The results indicated that the estimated present-day PM_2.5 concentrations were comparable to satellite-derived data. Overall, the PM_2.5 concentrations of the analyzed regions exceeded the WHO air-quality guidelines, particularly in East Asia and South Asia. In future SSP scenarios that consider the implementation of significant air-quality controls (SSP1-2.6, SSP5-8.5) and medium air-quality controls (SSP2-4.5), the annual PM_2.5 levels were predicted to substantially reduce (by 46% to around 66% of the present-day levels) in East Asia, resulting in a significant improvement in the AQI values in the mid-future. Conversely, weak air pollution controls considered in the SSP3-7.0 scenario resulted in poor AQI values in China and India. Moreover, a predicted increase in the percentage of aged populations (>65 years) in these regions, coupled with high AQI values, may increase the risk of premature deaths in the future. This study also examined the regional impact of PM_2.5 mitigations on downward shortwave energy and surface air temperature. Our results revealed that, although significant air pollution controls can reduce long-term exposure to PM_2.5, it may also contribute to the warming of near- and mid-future climates.

Impact of Air Pollution (PM2.5) on Child Mortality: Evidence from Sixteen Asian Countries

Air pollution in Asian countries represents one of the biggest health threats given the varied levels of economic and population growth in the recent past. The quantification of air pollution (PM_2.5) vis à vis health problems has important policy implications in tackling its health effects. This paper investigates the relationship between air pollution (PM_2.5) and child mortality in sixteen Asian countries using panel data from 2000 to 2017. We adopt a two-stage least squares approach that exploits variations in PM_2.5 attributable to economic growth in estimating the effect on child mortality. We find that a one-unit annual increase in PM_2.5 leads to a nearly 14.5% increase in the number of children dying before the age of five, suggesting the severity of the effects of particulate matter (PM_2.5) on health outcomes in sixteen Asian countries considered in this study. The results of this study suggest the need for strict policy interventions by governments in Asian countries to reduce PM_2.5 concentration alongside environment-friendly policies for economic growth.

Impacts of Industrial Restructuring and Technological Progress on PM2.5 Pollution: Evidence from Prefecture-Level Cities in China

PM_2.5 pollution has produced adverse effects all over the world, especially in fast-developing China. PM_2.5 pollution in China is widespread and serious, which has aroused widespread concern of the government, the public and scholars. This paper evaluates the evolution trend and spatial pattern of PM_2.5 pollution in China based on the data of 281 prefecture-level cities in China from 2007 to 2017, and reveals the pollution situation of PM_2.5 and its relationship with industrial restructuring and technological progress by using spatial dynamic panel model. The results show that China's PM_2.5 pollution has significant path dependence and spatial correlation, and the industrial restructuring and technological progress have significant positive effects on alleviating PM_2.5 pollution. As a decomposition item of technological progress, technical change effectively alleviates PM_2.5 pollution. Another important discovery is that the interaction between industrial restructuring and technological progress will aggravate PM_2.5 pollution. Finally, in order to effectively improve China's air quality, while advocating the Chinese government to pursue high-quality development, this paper puts forward a regional joint prevention mechanism.

Predicting intraurban PM2.5 concentrations using enhanced machine learning approaches and incorporating human activity patterns

Urban areas contribute substantially to human exposure to ambient air pollution. Numerous statistical prediction models have been used to estimate ambient concentrations of fine particulate matter (PM_2.5) and other pollutants in urban environments, with some incorporating machine learning (ML) algorithms to improve predictive power. However, many ML approaches for predicting ambient pollutant concentrations to date have used principal component analysis (PCA) with traditional regression algorithms to explore linear correlations between variables and to reduce the dimensionality of the data. Moreover, while most urban air quality prediction models have traditionally incorporated explanatory variables such as meteorological, land use, transportation/mobility, and/or co-pollutant factors, recent research has shown that local emissions from building infrastructure may also be useful factors to consider in estimating urban pollutant concentrations. Here we propose an enhanced ML approach for predicting urban ambient PM_2.5 concentrations that hybridizes cascade and PCA methods to reduce the dimensionality of the data-space and explore nonlinear effects between variables. We test the approach using different durations of time series air quality datasets of hourly PM_2.5 concentrations from three air quality monitoring sites in different urban neighborhoods in Chicago, IL to explore the influence of dynamic human-related factors, including mobility (i.e., traffic) and building occupancy patterns, on model performance. We test 9 state-of-the-art ML algorithms to find the most effective algorithm for modeling intraurban PM_2.5 variations and we explore the relative importance of all sets of factors on intraurban air quality model performance. Results demonstrate that Gaussian-kernel support vector regression (SVR) was the most effective ML algorithm tested, improving accuracy by 118% compared to a traditional multiple linear regression (MLR) approach. Incorporating the enhanced approach with SVR algorithm increased model performance up to 18.4% for yearlong and 98.7% for month-long hourly datasets, respectively. Incorporating assumptions for human occupancy patterns in dominant building typologies resulted in improvements in model performance by between 4% and 37%. Combined, these innovations can be used to improve the performance and accuracy of urban air quality prediction models compared to conventional approaches.

Improved air quality during COVID-19 at an urban megacity over the Indo-Gangetic Basin: From stringent to relaxed lockdown phases

The enforced lockdown amid COVID-19 pandemic eased anthropogenic activities across India. The satellite-derived aerosol optical depth (AOD) and absorption AOD showed a significant reduction of ~30% over the Indo-Gangetic Basin (IGB) in north India during the lockdown period in 2020 with respect to the previous year 2019, when no such lockdown was in effect. Further, near-surface air pollutants were investigated at an urban megacity Delhi during 01 March to 31 May 2020. Except O₃, a drastic reduction in PM₁₀, PM_2.5, NO, NO₂ and CO concentrations were observed by ~58%, 47%, 76%, 68% and 58%, respectively during the lockdown period of 2020 as compared to 2019. While, O₃ was low in the initial phase and gradually increased with progression of lockdown phases, the mean O₃ during the entire lockdown period was nearly similar in both the years. Though, all the measured pollutants showed significant reduction during the entire lockdown, a phase-wise enhancement, associated with the conditional relaxations was observed in their concentrations. Thus, the present results may help, not only to assess the impact of outbreak on air quality, but also in designing the mitigation policies in urban megacities in more efficient ways to combat the air pollution problems.

Quantitative Structure-Activity Relationship of Nanowire Adsorption to SO2 Revealed by In Situ TEM Technique

A quantitative structure-activity relationship (QSAR) is revealed based on the real-time sulfurization processes of ZnO nanowires observed via gas-cell in situ transmission electron microscopy (in situ TEM). According to the in situ TEM observations, the ZnO nanowires with a diameter of 100 nm (ZnO-100 nm) gradually transform into a core-shell nanostructure under SO₂ atmosphere, and the shell formation kinetics are quantitatively determined. However, only sparse nanoparticles can be observed on the surface of the ZnO-500 nm sample, which implies a weak solid-gas interaction between SO₂ and ZnO-500 nm. The QSAR model is verified with heat of adsorption (-ΔH°) and aberration-corrected TEM characterization. With the guidance of the QSAR model, the following adsorbing/sensing applications of ZnO nanomaterials are explored: (i) breakthrough experiment demonstrates the application potential of the ZnO-100 nm sample for SO₂ capture/storage; (ii) the ZnO-500 nm sample features good reversibility (RSD = 1.5%, n = 3) for SO₂ sensing, and the detection limit reaches 70 ppb.

The mortality impacts of current and planned coal-fired power plants in India

We examine the health implications of electricity generation from the 2018 stock of coal-fired power plants in India, as well as the health impacts of the expansion in coal-fired generation capacity expected to occur by 2030. We estimate emissions of SO₂, NO_X, and particulate matter 2.5 μm (PM_2.5) for each plant and use a chemical transport model to estimate the impact of power plant emissions on ambient PM_2.5 Concentration-response functions from the 2019 Global Burden of Disease (GBD) are used to project the impacts of changes in PM_2.5 on mortality. Current plus planned plants will contribute, on average, 13% of ambient PM_2.5 in India. This reflects large absolute contributions to PM_2.5 in central India and parts of the Indo-Gangetic plain (up to 20 μg/m³). In the south of India, coal-fired power plants account for 20-25% of ambient PM_2.5 We estimate 112,000 deaths are attributable annually to current plus planned coal-fired power plants. Not building planned plants would avoid at least 844,000 premature deaths over the life of these plants. Imposing a tax on electricity that reflects these local health benefits would incentivize the adoption of renewable energy.

The Association Between Ambient PM2.5 Exposure and Anemia Outcomes Among Children Under Five Years of Age in India

Anemia is highly prevalent in India, especially in children. Exposure to ambient fine particulate matter (PM2.5) is a potential risk factor for anemia via. systemic inflammation. Using health data from the National Family and Health Survey 2015-2016, we examined the association between ambient PM2.5 exposure and anemia in children under five across India through district-level ecological and individual-level analyses.

METHODS

The ecological analysis assessed average hemoglobin levels and anemia prevalence (hemoglobin < 11 g/dL considered anemic) by district using multiple linear regression models. The individual-level analysis assessed average individual hemoglobin level and anemia status (yes/no) using generalized linear mixed models to account for clustering by district. Ambient PM2.5 exposure data were derived from the Multiangle Imaging SpectroRadiometer (MISR) level 2 aerosol optical depth (AOD) data and averaged from birth date to date of interview.

RESULTS

The district-level ecological analysis found that, for every 10 μg m-3 increase in ambient PM2.5 exposure, average anemia prevalence increased by 1.90% (95% CI = 1.43, 2.36) and average hemoglobin decreased by 0.07 g/dL (95% CI = 0.09, 0.05). At the individual level, for every 10 μg m-3 increase in ambient PM2.5 exposure, average hemoglobin decreased by 0.14 g/dL (95% CI = 0.12, 0.16). The odds ratio associated with a 10-μg m-3 increase in ambient PM2.5 exposure was 1.09 (95% CI = 1.06, 1.11). There was evidence of effect modification by wealth index, maternal anemia status, and child BMI.

CONCLUSION

Our results suggest that ambient PM2.5 exposure could be linked to anemia in Indian children, although additional research on the underlying biologic mechanisms is needed. Future studies on this association should specifically consider interactions with dietary iron deficiency, maternal anemia status, and child BMI.Keywords: Anemia; Children; Ambient PM2.5 exposure; India; Association.

Evolution of Urban Transportation Policies in India: A Review and Analysis

India’s rising population and vehicular ownership have led to problems such as traffic congestion, pollution, and road accidents. The transportation sector is a crucial player in the country’s economy, but at the same time, it is also a significant contributor to climate change. Since climate change is a global threat, most transportation policies eventually lead to solving the climate change problem to achieve sustainable transportation. Despite commitments from various countries, the carbon emissions are still to come down and require the implementation of ambitious policies. Globally, countries are increasingly putting more effort towards sustainable transportation through various policy initiatives, and so does India. Given the growing transport-related externalities, the policy stance of India towards urban transportation is also gradually shifting to a systems approach from supply-oriented to demand-oriented policies. This paper highlights the significant transportation problems faced in India and how the Government of India’s transportation sector policy interventions for cities have evolved since its independence. The challenges and gaps in the existing policies are discussed, and possible ways to frame the policies are presented. This study finds that most government policy initiatives are still to see the intended level of success. This is majorly due to lack of monitoring, complex institutional capacities and urban governance, irregular zoning of land and inefficient comprehensive development and mobility plans.