Urban-rural disparity in global estimation of PM2·5 household air pollution and its attributable health burden.

BACKGROUND: Polluting fuels and inefficient stove technologies are still a leading cause of premature deaths worldwide, particularly in low-income and middle-income countries. Previous studies of global household air pollution (HAP) have neither considered the estimation of PM2·5 at national level nor the corresponding attributable mortality burden. Additionally, the effects of climate and ambient air pollution on the global estimation of HAP-PM2·5 exposure for different urban and rural settings remain largely unknown. In this study, we include climatic effects to estimate the HAP-PM2·5 exposure from different fuel types and stove technologies in rural and urban settings separately and the related attributable global mortality burden. METHODS: Bayesian hierarchical models were developed to estimate an annual average HAP-PM2·5 personal exposure and HAP-PM2·5 indoor concentration (including both outdoor and indoor sources). Model variables were selected from sample data in 282 peer-reviewed studies drawn and updated from the WHO Global HAP dataset. The PM2·5 exposure coefficients from the developed model were applied to the external datasets to predict the HAP-PM2·5 exposure globally (personal exposure in 62 countries and indoor concentration in 69 countries). Attributable mortality rate was estimated using a comparative risk assessment approach. Using weighted averages, the national level 24 h average HAP-PM2·5 exposure due to polluting and clean fuels and related death rate per 100 000 population were estimated. FINDINGS: In 2020, household use of polluting solid fuels for cooking and heating led to a national-level average personal exposure of 151 µg/m3 (95% CI 133-169), with rural households having an average of 171 µg/m3 (153-189) and urban households an average of 92 µg/m3 (77-106). Use of clean fuels gave rise to a national-level average personal exposure of 69 µg/m3 (62-76), with a rural average of 76 µg/m3 (69-83) and an urban average of 49 µg/m3 (46-53). Personal exposure-attributable premature mortality (per 100 000 population) from the use of polluting solid fuels at national level was on average 78 (95% CI 69-87), with a rural average of 82 (73-90) and an urban average of 66 (57-75). The average attributable premature mortality (per 100 000 population) from the use of clean fuels at the national level is 62 (54-70), with a rural average of 66 (58-74) and an urban average of 52 (47-57). The estimated HAP-PM2·5 indoor concentration shows that the use of polluting solid fuels resulted in a national-level average of 412 µg/m3 (95% CI 353-471), with a rural average of 514 µg/m3 (446-582) and an urban average of 149 µg/m3 (126-173). The use of clean fuels (gas and electricity) led to an average PM2·5 indoor concentration of 135 µg/m3 (117-153), with a rural average of 174 µg/m3 (154-195) and an urban average of 71 µg/m3 (63-80). Using time-weighted HAP-PM2·5 indoor concentrations, the attributable premature death rate (per 100 000 population) from the use of polluting solid fuels at the national level is on average 78 (95% CI 72-84), the rural average being 84 (78-91) and the urban average 60 (54-66). From the use of clean fuels, the average attributable premature death rate (per 100 000 population) at the national level is 59 (53-64), the rural average being 68 (62-74) and the urban average 45 (41-50). INTERPRETATION: A shift from polluting to clean fuels can reduce the average PM2·5 personal exposure by 53% and thereby lower the death rate. For all fuel types, the estimated average HAP-PM2·5 personal exposure and indoor concentrations exceed the WHO's Interim Target-1 average annual threshold. Policy interventions are urgently needed to greatly increase the use of clean fuels and stove technologies by 2030 to achieve the goal of affordable clean energy access, as set by the UN in 2015, and address health inequities in urban-rural settings. FUNDING: Wellcome Trust, The Lancet Countdown, the Engineering and Physical Sciences Research Council, and the Natural Environment Research Council.

Covid-19 mobility restrictions: impacts on urban air quality and health.

In 2020, Covid-19-related mobility restrictions resulted in the most extensive human-made air-quality changes ever recorded. The changes in mobility are quantified in terms of outdoor air pollution (concentrations of PM2.5 and NO2) and the associated health impacts in four UK cities (Greater London, Cardiff, Edinburgh and Belfast). After applying a weather-corrected machine learning (ML) technique, all four cities show NO2 and PM2.5 concentration anomalies in 2020 when compared with the ML-predicted values for that year. The NO2 anomalies are -21% for Greater London, -19% for Cardiff, -27% for Belfast and -41% for Edinburgh. The PM2.5 anomalies are 7% for Greater London, -1% for Cardiff, -15% for Edinburgh, -14% for Belfast. All the negative anomalies, which indicate air pollution at a lower level than expected from the weather conditions, are attributable to the mobility restrictions imposed by the Covid-19 lockdowns. Spearman rank-order correlations show a significant correlation between the lowering of NO2 levels and reduction in public transport (p < 0.05) and driving (p < 0.05), which is associated with a decline in NO2-attributable mortality. These positive effects of the mobility restrictions on public health can be used to evaluate policies for improved outdoor air quality. POLICY RELEVANCE: Finding the means to curb air pollution is very important for public health. Empirical evidence at a city scale reveals significant correlations between the reduction in vehicular transport and in ambient NO2 concentrations. The results provide justification for city-level initiatives to reduce vehicular traffic. Well-designed and effective policy interventions (e.g. the promotion of walking and cycling, remote working, local availability of services) can substantially reduce long-term air pollution and have positive health impacts.

Size distributions of fractures, dykes, and eruptions on Etna, Italy: Implications for magma-chamber volume and eruption potential.

The main magma source for eruptions on Etna (Italy) is poorly constrained. Here we use data on the size distributions of volcanic fissures/feeder-dykes, crater cones, dyke thicknesses, and lava flows to estimate the average magma volume flowing out of the chamber during eruptions and the volume of the chamber. For the past four centuries the average magma volume leaving the chamber during each eruption is estimated at 0.064 km3. From the theory of poroelasticity the estimated chamber volume is then between 69 and 206 km3. For comparison, a sill-like, circular chamber (an oblate ellipsoid) 1 km thick and 14 km in diameter would have a volume of about 154 km3. The elastic strain energy stored in the host rock during inflation of such a chamber is about 2.8 × 1014 J. Estimating the surface energy of a typical dyke-fracture as about 107 J m-2, the results suggest that the stored strain energy is sufficient to generate a dyke-fracture with an area of about 28 km2. The average strike-dimension of volcanic fissures/feeder-dykes in Etna is about 2.7 km. It follows that the estimated strain energy is sufficient to generate a feeder-dyke with a strike-dimension of 2-3 km and with a dip-dimension as great as 10 km, agreeing with the maximum estimated depth of the magma chamber.

Forecasting magma-chamber rupture at Santorini volcano, Greece.

How much magma needs to be added to a shallow magma chamber to cause rupture, dyke injection, and a potential eruption? Models that yield reliable answers to this question are needed in order to facilitate eruption forecasting. Development of a long-lived shallow magma chamber requires periodic influx of magmas from a parental body at depth. This redistribution process does not necessarily cause an eruption but produces a net volume change that can be measured geodetically by inversion techniques. Using continuum-mechanics and fracture-mechanics principles, we calculate the amount of magma contained at shallow depth beneath Santorini volcano, Greece. We demonstrate through structural analysis of dykes exposed within the Santorini caldera, previously published data on the volume of recent eruptions, and geodetic measurements of the 2011-2012 unrest period, that the measured 0.02% increase in volume of Santorini's shallow magma chamber was associated with magmatic excess pressure increase of around 1.1 MPa. This excess pressure was high enough to bring the chamber roof close to rupture and dyke injection. For volcanoes with known typical extrusion and intrusion (dyke) volumes, the new methodology presented here makes it possible to forecast the conditions for magma-chamber failure and dyke injection at any geodetically well-monitored volcano.

Entropy and order in urban street networks.

Many complex networks erase parts of their geometry as they develop, so that their evolution is difficult to quantify and trace. Here we introduce entropy measures for quantifying the complexity of street orientations and length variations within planar networks and apply them to the street networks of 41 British cities, whose geometric evolution over centuries can be explored. The results show that the street networks of the old central parts of the cities have lower orientation/length entropies - the streets are more tightly ordered and form denser networks - than the outer and more recent parts. Entropy and street length increase, because of spreading, with distance from the network centre. Tracing the 400-year evolution of one network indicates growth through densification (streets are added within the existing network) and expansion (streets are added at the margin of the network) and a gradual increase in entropy over time.

Depth of origin of magma in eruptions.

Many volcanic hazard factors--such as the likelihood and duration of an eruption, the eruption style, and the probability of its triggering large landslides or caldera collapses--relate to the depth of the magma source. Yet, the magma source depths are commonly poorly known, even in frequently erupting volcanoes such as Hekla in Iceland and Etna in Italy. Here we show how the length-thickness ratios of feeder dykes can be used to estimate the depth to the source magma chamber. Using this method, accurately measured volcanic fissures/feeder-dykes in El Hierro (Canary Islands) indicate a source depth of 11-15 km, which coincides with the main cloud of earthquake foci surrounding the magma chamber associated with the 2011-2012 eruption of El Hierro. The method can be used on widely available GPS and InSAR data to calculate the depths to the source magma chambers of active volcanoes worldwide.