Aerosol forcing regulating recent decadal change of summer water vapor budget over the Tibetan Plateau.

The Tibetan Plateau (TP), known as the Asian water tower, has been getting wetter since the 1970s. However, the primary drivers behind this phenomenon are still highly controversial. Here, we isolate the impacts of greenhouse gases (GHG), aerosols, natural forcings and internal climate variability on the decadal change of summer water vapor budget (WVB) over the TP using multi-model ensemble simulations. We show that an anomalous Rossby wave train in the upper troposphere travelling eastward from central Europe and equatorward temperature gradient in eastern China due to the inhomogeneous aerosol forcing in Eurasia jointly contribute to anomalous easterly winds over the eastern TP. Such anomalous easterly winds result in a significant decrease in water vapor export from the eastern boundary of the TP and dominate the enhanced summer WVB over the TP during 1979-2014. Our results highlight that spatial variation of aerosol forcing can be used as an important indicator to project future WVB over the TP.

Global population exposure to landscape fire air pollution from 2000 to 2019.

Wildfires are thought to be increasing in severity and frequency as a result of climate change1-5. Air pollution from landscape fires can negatively affect human health4-6, but human exposure to landscape fire-sourced (LFS) air pollution has not been well characterized at the global scale7-23. Here, we estimate global daily LFS outdoor fine particulate matter (PM2.5) and surface ozone concentrations at 0.25° × 0.25° resolution during the period 2000-2019 with the help of machine learning and chemical transport models. We found that overall population-weighted average LFS PM2.5 and ozone concentrations were 2.5 µg m-3 (6.1% of all-source PM2.5) and 3.2 µg m-3 (3.6% of all-source ozone), respectively, in 2010-2019, with a slight increase for PM2.5, but not for ozone, compared with 2000-2009. Central Africa, Southeast Asia, South America and Siberia experienced the highest LFS PM2.5 and ozone concentrations. The concentrations of LFS PM2.5 and ozone were about four times higher in low-income countries than in high-income countries. During the period 2010-2019, 2.18 billion people were exposed to at least 1 day of substantial LFS air pollution per year, with each person in the world having, on average, 9.9 days of exposure per year. These two metrics increased by 6.8% and 2.1%, respectively, compared with 2000-2009. Overall, we find that the global population is increasingly exposed to LFS air pollution, with socioeconomic disparities.

Global estimates of daily ambient fine particulate matter concentrations and unequal spatiotemporal distribution of population exposure: a machine learning modelling study.

BACKGROUND: Short-term exposure to ambient PM2·5 is a leading contributor to the global burden of diseases and mortality. However, few studies have provided the global spatiotemporal variations of daily PM2·5 concentrations over recent decades. METHODS: In this modelling study, we implemented deep ensemble machine learning (DEML) to estimate global daily ambient PM2·5 concentrations at 0·1° × 0·1° spatial resolution between Jan 1, 2000, and Dec 31, 2019. In the DEML framework, ground-based PM2·5 measurements from 5446 monitoring stations in 65 countries worldwide were combined with GEOS-Chem chemical transport model simulations of PM2·5 concentration, meteorological data, and geographical features. At the global and regional levels, we investigated annual population-weighted PM2·5 concentrations and annual population-weighted exposed days to PM2·5 concentrations higher than 15 µg/m3 (2021 WHO daily limit) to assess spatiotemporal exposure in 2000, 2010, and 2019. Land area and population exposures to PM2·5 above 5 µg/m3 (2021 WHO annual limit) were also assessed for the year 2019. PM2·5 concentrations for each calendar month were averaged across the 20-year period to investigate global seasonal patterns. FINDINGS: Our DEML model showed good performance in capturing the global variability in ground-measured daily PM2·5, with a cross-validation R2 of 0·91 and root mean square error of 7·86 µg/m3. Globally, across 175 countries, the mean annual population-weighted PM2·5 concentration for the period 2000-19 was estimated at 32·8 µg/m3 (SD 0·6). During the two decades, population-weighted PM2·5 concentration and annual population-weighted exposed days (PM2·5 >15 µg/m3) decreased in Europe and northern America, whereas exposures increased in southern Asia, Australia and New Zealand, and Latin America and the Caribbean. In 2019, only 0·18% of the global land area and 0·001% of the global population had an annual exposure to PM2·5 at concentrations lower than 5 µg/m3, with more than 70% of days having daily PM2·5 concentrations higher than 15 µg/m3. Distinct seasonal patterns were indicated in many regions of the world. INTERPRETATION: The high-resolution estimates of daily PM2·5 provide the first global view of the unequal spatiotemporal distribution of PM2·5 exposure for a recent 20-year period, which is of value for assessing short-term and long-term health effects of PM2·5, especially for areas where monitoring station data are not available. FUNDING: Australian Research Council, Australian Medical Research Future Fund, and the Australian National Health and Medical Research Council.

Projections of fire emissions and the consequent impacts on air quality under 1.5 °C and 2 °C global warming.

Fire is a major source of atmospheric aerosols and trace gases. Projection of future fire activities is challenging due to the joint impacts of climate, vegetation, and human activities. Here, we project global changes of fire-induced particulate matter smaller than 2.5 µm (PM2.5) and ozone (O3) under 1.5 °C/2 °C warming using a climate-chemistry-vegetation coupled model in combination with site-level and satellite-based observations. Compared to the present day, fire emissions of varied air pollutants increase by 10.0%-15.4% at the 1.5 °C warming period and 15.1%-22.5% at the 2 °C warming period, with the most significant enhancements in Amazon, southern Africa, and boreal Eurasia. The warmer climate promotes fuel dryness and the higher leaf area index increases fuel availability, leading to escalated fire flammability globally. However, moderate declines in fire emissions are predicted over the Sahel region, because the higher population density increases fire suppressions and consequently inhibits fire activities over central Africa. Following the changes in fire emissions, the population-weighted exposure to fire PM2.5 increases by 5.1% under 1.5 °C warming and 13.0% under 2 °C warming. Meanwhile, the exposure to fire O3 enhances by 10.2% and 16.0% in response to global warming of 1.5 °C and 2 °C, respectively. As a result, limiting global temperature increase to 1.5 °C can greatly reduce the risks of exposure to fire-induced air pollution compared to 2 °C.

Effect of vegetation seasonal cycle alterations to aerosol dry deposition on PM2.5 concentrations in China.

The effect of vegetation seasonal cycle alterations to aerosol dry deposition on PM2.5 concentrations (hereafter referred as the VSC effect) in China was investigated using a numerical modelling system (WRF/CUACE). Two simulation experiments using the vegetation parameters in particle dry deposition schemes typical for January and July revealed an absolute increase in surface PM2.5 concentrations of about 2.4 µg/m3 and a 5.5% relative increase in China (within model domain 2). The effect in non-urban areas was more significant than that in urban areas. The increases in PM2.5 concentrations in Beijing-Tianjin-Hebei (BTH), Yangtze River Delta (YRD), Pearl River Delta (PRD), Sichuan Basin (SCB), and Central China (CC) were calculated as 1.9 µg/m3, 3.4 µg/m3, 3.1 µg/m3, 4.3 µg/m3, and 4.9 µg/m3, respectively, corresponding to relative increases of 2.9%, 4.5%, 5.4%, 5.8%, and 5.9%. These results demonstrate that the effect of decreased particle dry deposition due to reduced vegetation in southern areas was stronger, which was partially attributed to the increased vegetation cover and more significant seasonal changes in those regions. Furthermore, the increased PM2.5 concentrations caused by the VSC effect were transported from north to south via the winter northerly winds, which weakened the effect in North China Plain and enhanced the effect in parts of central and southern China, such as the south of CC. Although the surface PM2.5 concentration was relatively high in North China Plain, the effects of the northerly wind and relatively small dry deposition velocity meant that the removal of PM2.5 in that region was relatively less than in southern areas of China. These results will contribute to understanding of the underlying mechanisms of PM2.5 enhancement during winter in China.

Global Perspective of Drought Impacts on Ozone Pollution Episodes.

Ozone (O3) pollution threatens global public health and damages ecosystem productivity. Droughts modulate surface O3 through meteorological processes and vegetation feedbacks. Unraveling these influences is difficult with traditional chemical transport models. Here, using an atmospheric chemistry-vegetation coupled model in combination with a suite of existing measurements, we investigate the drought impacts on global surface O3 and explore the main driving processes. Relative to the mean state, accelerated photochemical rates dominate the surface O3 enhancement during droughts except for eastern U.S. and western Europe, where reduced stomatal uptakes make comparable contributions. During 1990-2012, the simulated frequency of O3 pollution episodes in western Europe decreases greatly with a negative trend of -5.5 ± 6.6 days per decade following the reductions in anthropogenic emissions if meteorology is fixed. However, such decreased trend is weakened to -2.1 ± 3.8 days per decade, which is closer to the observed trend of -2.9 ± 1.1 days per decade when year-to-year meteorology is applied because increased droughts alone offset 43% of the effects from air pollution control. Our results highlight that more stringent controls of O3 precursors are necessary to mitigate the higher risks of O3 pollution episodes by more droughts in a warming world.

Mortality risk attributable to wildfire-related PM2·5 pollution: a global time series study in 749 locations.

BACKGROUND: Many regions of the world are now facing more frequent and unprecedentedly large wildfires. However, the association between wildfire-related PM2·5 and mortality has not been well characterised. We aimed to comprehensively assess the association between short-term exposure to wildfire-related PM2·5 and mortality across various regions of the world. METHODS: For this time series study, data on daily counts of deaths for all causes, cardiovascular causes, and respiratory causes were collected from 749 cities in 43 countries and regions during 2000-16. Daily concentrations of wildfire-related PM2·5 were estimated using the three-dimensional chemical transport model GEOS-Chem at a 0·25°â€ˆ× 0·25° resolution. The association between wildfire-related PM2·5 exposure and mortality was examined using a quasi-Poisson time series model in each city considering both the current-day and lag effects, and the effect estimates were then pooled using a random-effects meta-analysis. Based on these pooled effect estimates, the population attributable fraction and relative risk (RR) of annual mortality due to acute wildfire-related PM2·5 exposure was calculated. FINDINGS: 65·6 million all-cause deaths, 15·1 million cardiovascular deaths, and 6·8 million respiratory deaths were included in our analyses. The pooled RRs of mortality associated with each 10 µg/m3 increase in the 3-day moving average (lag 0-2 days) of wildfire-related PM2·5 exposure were 1·019 (95% CI 1·016-1·022) for all-cause mortality, 1·017 (1·012-1·021) for cardiovascular mortality, and 1·019 (1·013-1·025) for respiratory mortality. Overall, 0·62% (95% CI 0·48-0·75) of all-cause deaths, 0·55% (0·43-0·67) of cardiovascular deaths, and 0·64% (0·50-0·78) of respiratory deaths were annually attributable to the acute impacts of wildfire-related PM2·5 exposure during the study period. INTERPRETATION: Short-term exposure to wildfire-related PM2·5 was associated with increased risk of mortality. Urgent action is needed to reduce health risks from the increasing wildfires. FUNDING: Australian Research Council, Australian National Health & Medical Research Council.

Identifying the dominant climate-driven uncertainties in modeling gross primary productivity.

Accurate simulation of gross primary productivity (GPP) is essential for estimating the global carbon budget. However, GPP modeling is subject to various sources of uncertainties, among which the impacts of biases in climate forcing data have not been well quantified. Here, using a well-validated vegetation model, we compare site-level simulations using either ground-based meteorology or assimilated reanalyses to identify climate-driven uncertainties in the predicted GPP at 91 FLUXNET sites. Simulations yield the lowest root mean square errors (RMSE) in GPP relative to observations when all site-level meteorology and CO2 concentrations are used. Sensitivity tests conducted with Modern-Era Retrospective Analysis (MERRA) reanalyses increase GPP RMSE by 30%. Replacement of site-level CO2 with global annual average values provides limited contributions to these changes. In contrast, GPP uncertainties increase almost linearly with the biases in meteorology. Among all factors, photosynthetically active radiation (PAR), especially diffuse PAR, plays dominant roles in modulating GPP uncertainties. Simulations using all MERRA forcings but with site-level diffuse PAR help reduce over 50% of the climate-driven biases in GPP. Our study reveals that biases in meteorological forcings, especially the variabilities at diurnal to seasonal time scales, can induce significant uncertainties in the simulated GPP at FLUXET sites. We suggest cautions in simulating global GPP using climate reanalyses for dynamic global vegetation models and urgent improvements in climatic variability in reanalyses data, especially for diffuse radiation.

Author Correction: Near-real-time monitoring of global CO2 emissions reveals the effects of the COVID-19 pandemic.

A Correction to this paper has been published: https://doi.org/10.1038/s41467-020-20254-5.

Near-real-time monitoring of global CO2 emissions reveals the effects of the COVID-19 pandemic.

The COVID-19 pandemic is impacting human activities, and in turn energy use and carbon dioxide (CO2) emissions. Here we present daily estimates of country-level CO2 emissions for different sectors based on near-real-time activity data. The key result is an abrupt 8.8% decrease in global CO2 emissions (-1551 Mt CO2) in the first half of 2020 compared to the same period in 2019. The magnitude of this decrease is larger than during previous economic downturns or World War II. The timing of emissions decreases corresponds to lockdown measures in each country. By July 1st, the pandemic's effects on global emissions diminished as lockdown restrictions relaxed and some economic activities restarted, especially in China and several European countries, but substantial differences persist between countries, with continuing emission declines in the U.S. where coronavirus cases are still increasing substantially.