Accelerating the energy transition towards photovoltaic and wind in China.

China's goal to achieve carbon (C) neutrality by 2060 requires scaling up photovoltaic (PV) and wind power from 1 to 10-15 PWh year-1 (refs. 1-5). Following the historical rates of renewable installation1, a recent high-resolution energy-system model6 and forecasts based on China's 14th Five-year Energy Development (CFED)7, however, only indicate that the capacity will reach 5-9.5 PWh year-1 by 2060. Here we show that, by individually optimizing the deployment of 3,844 new utility-scale PV and wind power plants coordinated with ultra-high-voltage (UHV) transmission and energy storage and accounting for power-load flexibility and learning dynamics, the capacity of PV and wind power can be increased from 9 PWh year-1 (corresponding to the CFED path) to 15 PWh year-1, accompanied by a reduction in the average abatement cost from US$97 to US$6 per tonne of carbon dioxide (tCO2). To achieve this, annualized investment in PV and wind power should ramp up from US$77 billion in 2020 (current level) to US$127 billion in the 2020s and further to US$426 billion year-1 in the 2050s. The large-scale deployment of PV and wind power increases income for residents in the poorest regions as co-benefits. Our results highlight the importance of upgrading power systems by building energy storage, expanding transmission capacity and adjusting power load at the demand side to reduce the economic cost of deploying PV and wind power to achieve carbon neutrality in China.

Delayed use of bioenergy crops might threaten climate and food security.

The potential of mitigation actions to limit global warming within 2 °C (ref. 1) might rely on the abundant supply of biomass for large-scale bioenergy with carbon capture and storage (BECCS) that is assumed to scale up markedly in the future2-5. However, the detrimental effects of climate change on crop yields may reduce the capacity of BECCS and threaten food security6-8, thus creating an unrecognized positive feedback loop on global warming. We quantified the strength of this feedback by implementing the responses of crop yields to increases in growing-season temperature, atmospheric CO2 concentration and intensity of nitrogen (N) fertilization in a compact Earth system model9. Exceeding a threshold of climate change would cause transformative changes in social-ecological systems by jeopardizing climate stability and threatening food security. If global mitigation alongside large-scale BECCS is delayed to 2060 when global warming exceeds about 2.5 °C, then the yields of agricultural residues for BECCS would be too low to meet the Paris goal of 2 °C by 2200. This risk of failure is amplified by the sustained demand for food, leading to an expansion of cropland or intensification of N fertilization to compensate for climate-induced yield losses. Our findings thereby reinforce the urgency of early mitigation, preferably by 2040, to avoid irreversible climate change and serious food crises unless other negative-emission technologies become available in the near future to compensate for the reduced capacity of BECCS.

The contributions of individual countries and regions to the global radiative forcing.

Knowing the historical relative contribution of greenhouse gases (GHGs) and short-lived climate forcers (SLCFs) to global radiative forcing (RF) at the regional level can help understand how future GHGs emission reductions and associated or independent reductions in SLCFs will affect the ultimate purpose of the Paris Agreement. In this study, we use a compact Earth system model to quantify the global RF and attribute global RF to individual countries and regions. As our evaluation, the United States, the first 15 European Union members, and China are the top three contributors, accounting for 21.9 ± 3.1%, 13.7 ± 1.6%, and 8.6 ± 7.0% of global RF in 2014, respectively. We also find a contrast between developed countries where GHGs dominate the RF and developing countries where SLCFs including aerosols and ozone are more dominant. In developing countries, negative RF caused by aerosols largely masks the positive RF from GHGs. As developing countries take measures to improve the air quality, their negative contributions from aerosols will likely be reduced in the future, which will in turn enhance global warming. This underlines the importance of reducing GHG emissions in parallel to avoid any detrimental consequences from air quality policies.

Predicting the effect of confinement on the COVID-19 spread using machine learning enriched with satellite air pollution observations.

The real-time monitoring of reductions of economic activity by containment measures and its effect on the transmission of the coronavirus (COVID-19) is a critical unanswered question. We inferred 5,642 weekly activity anomalies from the meteorology-adjusted differences in spaceborne tropospheric NO2 column concentrations after the 2020 COVID-19 outbreak relative to the baseline from 2016 to 2019. Two satellite observations reveal reincreasing economic activity associated with lifting control measures that comes together with accelerating COVID-19 cases before the winter of 2020/2021. Application of the near-real-time satellite NO2 observations produces a much better prediction of the deceleration of COVID-19 cases than applying the Oxford Government Response Tracker, the Public Health and Social Measures, or human mobility data as alternative predictors. A convergent cross-mapping suggests that economic activity reduction inferred from NO2 is a driver of case deceleration in most of the territories. This effect, however, is not linear, while further activity reductions were associated with weaker deceleration. Over the winter of 2020/2021, nearly 1 million daily COVID-19 cases could have been avoided by optimizing the timing and strength of activity reduction relative to a scenario based on the real distribution. Our study shows how satellite observations can provide surrogate data for activity reduction during the COVID-19 pandemic and monitor the effectiveness of containment to the pandemic before vaccines become widely available.

Atmospheric phosphorus deposition amplifies carbon sinks in simulations of a tropical forest in Central Africa.

Spatial redistribution of nutrients by atmospheric transport and deposition could theoretically act as a continental-scale mechanism which counteracts declines in soil fertility caused by nutrient lock-up in accumulating biomass in tropical forests in Central Africa. However, to what extent it affects carbon sinks in forests remains elusive. Here we use a terrestrial biosphere model to quantify the impact of changes in atmospheric nitrogen and phosphorus deposition on plant nutrition and biomass carbon sink at a typical lowland forest site in Central Africa. We find that the increase in nutrient deposition since the 1980s could have contributed to the carbon sink over the past four decades up to an extent which is similar to that from the combined effects of increasing atmospheric carbon dioxide and climate change. Furthermore, we find that the modelled carbon sink responds to changes in phosphorus deposition, but less so to nitrogen deposition. The pronounced response of ecosystem productivity to changes in nutrient deposition illustrates a potential mechanism that could control carbon sinks in Central Africa. Monitoring the quantity and quality of nutrient deposition is needed in this region, given the changes in nutrient deposition due to human land use.

Stringent Emission Controls Are Needed to Reach Clean Air Targets for Cities in China under a Warming Climate.

Quantifying the threat that climate change poses to fine particle (PM2.5) pollution is hampered by large uncertainties in the relationship between PM2.5 and meteorology. To constrain the impact of climate change on PM2.5, statistical models are often employed in a different manner than physical-chemical models to reduce the requirement of input data. A majority of statistical models predict PM2.5 concentration (often log-transformed) as a simple function of meteorology, which could be biased due to the conversion of precursor gases to PM2.5. We reduced this bias by developing a unique statistic model where the sum of PM2.5 and the weighted precursor gases, rather than the PM2.5 alone, was predicted as a function of meteorology and a proxy of primary emissions, where the input data of PM10, CO, O3, NOx, and SO2 were obtained from routine measurements. This modification, without losing the simplicity of statistical models, reduced the mean-square error from 27 to 17% and increased the coefficient of determination from 47 to 67% in the model cross-validation using daily PM2.5 observations during 2013-2018 for 74 cities over China. We found a previously unrecognized mechanism that synoptic climate change in the past half-century might have increased low quantiles of PM2.5 more strenuously than the upper quantiles in large cities over China. Climate change during 1971-2018 was projected to increase the annual mean concentration of PM2.5 at a degree that could be comparable with the toughest-ever clean air policy during 2013-2018 had counteracted it, as inferred from the decline in the daily concentration of carbon monoxide as an inert gas. Our estimate of the impact of climate change on PM2.5 is higher than previous statistical models, suggesting that aerosol chemistry might play a more important role than previously thought in the interaction between climate change and air pollution. Our result indicated that air quality might degrade if the future synoptic climate change could continue interacting with aerosol chemistry as it had occurred in the past half-century.

The contribution of China's emissions to global climate forcing.

Knowledge of the contribution that individual countries have made to global radiative forcing is important to the implementation of the agreement on "common but differentiated responsibilities" reached by the United Nations Framework Convention on Climate Change. Over the past three decades, China has experienced rapid economic development, accompanied by increased emission of greenhouse gases, ozone precursors and aerosols, but the magnitude of the associated radiative forcing has remained unclear. Here we use a global coupled biogeochemistry-climate model and a chemistry and transport model to quantify China's present-day contribution to global radiative forcing due to well-mixed greenhouse gases, short-lived atmospheric climate forcers and land-use-induced regional surface albedo changes. We find that China contributes 10% ± 4% of the current global radiative forcing. China's relative contribution to the positive (warming) component of global radiative forcing, mainly induced by well-mixed greenhouse gases and black carbon aerosols, is 12% ± 2%. Its relative contribution to the negative (cooling) component is 15% ± 6%, dominated by the effect of sulfate and nitrate aerosols. China's strongest contributions are 0.16 ± 0.02 watts per square metre for CO2 from fossil fuel burning, 0.13 ± 0.05 watts per square metre for CH4, -0.11 ± 0.05 watts per square metre for sulfate aerosols, and 0.09 ± 0.06 watts per square metre for black carbon aerosols. China's eventual goal of improving air quality will result in changes in radiative forcing in the coming years: a reduction of sulfur dioxide emissions would drive a faster future warming, unless offset by larger reductions of radiative forcing from well-mixed greenhouse gases and black carbon.

Spatial Representativeness Error in the Ground-Level Observation Networks for Black Carbon Radiation Absorption.

There is high uncertainty in the direct radiative forcing of black carbon (BC), an aerosol that strongly absorbs solar radiation. The observation-constrained estimate, which is several times larger than the bottom-up estimate, is influenced by the spatial representativeness error due to the mesoscale inhomogeneity of the aerosol fields and the relatively low resolution of global chemistry-transport models. Here we evaluated the spatial representativeness error for two widely used observational networks (AErosol RObotic NETwork and Global Atmosphere Watch) by downscaling the geospatial grid in a global model of BC aerosol absorption optical depth to 0.1° × 0.1°. Comparing the models at a spatial resolution of 2° × 2° with BC aerosol absorption at AErosol RObotic NETwork sites (which are commonly located near emission hot spots) tends to cause a global spatial representativeness error of 30%, as a positive bias for the current top-down estimate of global BC direct radiative forcing. By contrast, the global spatial representativeness error will be 7% for the Global Atmosphere Watch network, because the sites are located in such a way that there are almost an equal number of sites with positive or negative representativeness error.

Global forest carbon uptake due to nitrogen and phosphorus deposition from 1850 to 2100.

Spatial patterns and temporal trends of nitrogen (N) and phosphorus (P) deposition are important for quantifying their impact on forest carbon (C) uptake. In a first step, we modeled historical and future change in the global distributions of the atmospheric deposition of N and P from the dry and wet deposition of aerosols and gases containing N and P. Future projections were compared between two scenarios with contrasting aerosol emissions. Modeled fields of N and P deposition and P concentration were evaluated using globally distributed in situ measurements. N deposition peaked around 1990 in European forests and around 2010 in East Asian forests, and both increased sevenfold relative to 1850. P deposition peaked around 2010 in South Asian forests and increased 3.5-fold relative to 1850. In a second step, we estimated the change in C storage in forests due to the fertilization by deposited N and P (∆Cν dep ), based on the retention of deposited nutrients, their allocation within plants, and C:N and C:P stoichiometry. ∆Cν dep for 1997-2013 was estimated to be 0.27 ± 0.13 Pg C year-1 from N and 0.054 ± 0.10 Pg C year-1 from P, contributing 9% and 2% of the terrestrial C sink, respectively. Sensitivity tests show that uncertainty of ∆Cν dep was larger from P than from N, mainly due to uncertainty in the fraction of deposited P that is fixed by soil. ∆CPdep was exceeded by ∆CNdep over 1960-2007 in a large area of East Asian and West European forests due to a faster growth in N deposition than P. Our results suggest a significant contribution of anthropogenic P deposition to C storage, and additional sources of N are needed to support C storage by P in some Asian tropical forests where the deposition rate increased even faster for P than for N.

Exposure to ambient black carbon derived from a unique inventory and high-resolution model.

Black carbon (BC) is increasingly recognized as a significant air pollutant with harmful effects on human health, either in its own right or as a carrier of other chemicals. The adverse impact is of particular concern in those developing regions with high emissions and a growing population density. The results of recent studies indicate that BC emissions could be underestimated by a factor of 2-3 and this is particularly true for the hot-spot Asian region. Here we present a unique inventory at 10-km resolution based on a recently published global fuel consumption data product and updated emission factor measurements. The unique inventory is coupled to an Asia-nested (∼50 km) atmospheric model and used to calculate the global population exposure to BC with fully quantified uncertainty. Evaluating the modeled surface BC concentrations against observations reveals great improvement. The bias is reduced from -88% to -35% in Asia when the unique inventory and higher-resolution model replace a previous inventory combined with a coarse-resolution model. The bias can be further reduced to -12% by downscaling to 10 km using emission as a proxy. Our estimated global population-weighted BC exposure concentration constrained by observations is 2.14 µg⋅m(-3); 130% higher than that obtained using less detailed inventories and low-resolution models.

Influence of anthropogenic aerosol deposition on the relationship between oceanic productivity and warming.

Satellite data and models suggest that oceanic productivity is reduced in response to less nutrient supply under warming. In contrast, anthropogenic aerosols provide nutrients and exert a fertilizing effect, but its contribution to evolution of oceanic productivity is unknown. We simulate the response of oceanic biogeochemistry to anthropogenic aerosols deposition under varying climate from 1850 to 2010. We find a positive response of observed chlorophyll to deposition of anthropogenic aerosols. Our results suggest that anthropogenic aerosols reduce the sensitivity of oceanic productivity to warming from -15.2 ± 1.8 to -13.3 ± 1.6 Pg C yr-1 °C-1 in global stratified oceans during 1948-2007. The reducing percentage over the North Atlantic, North Pacific, and Indian Oceans reaches 40, 24, and 25%, respectively. We hypothesize that inevitable reduction of aerosol emissions in response to higher air quality standards in the future might accelerate the decline of oceanic productivity per unit warming.

Trend in global black carbon emissions from 1960 to 2007.

Black carbon (BC) plays an important role in both climate change and health impact. Still, BC emissions as well as the historical trends are associated with high uncertainties in existing inventories. In the present study, global BC emissions from 1960 to 2007 were estimated for 64 sources, by using recompiled fuel consumption and emission factor data sets. Annual BC emissions had increased from 5.3 (3.4-8.5 as an interquartile range) to 9.1 (5.6-14.4) teragrams during this period. Our estimations are 11-16% higher than those in previous inventories. Over the period, we found that the BC emission intensity, defined as the amount of BC emitted per unit of energy production, had decreased for all the regions, especially China and India. Improvements in combustion technology and changes in fuel composition had led to an increase in energy use efficiency, and subsequently a decline of BC emission intensities in power plants, the residential sector, and transportation. On the other hand, the BC emission intensities had increased in the industrial and agricultural sectors, mainly due to an expansion of low-efficiency industry (coke and brick production) in developing countries and to an increasing usage of diesel in agriculture in developed countries.

Global transport and deposition of 137Cs following the Fukushima nuclear power plant accident in Japan: emphasis on Europe and Asia using high-resolution model versions and radiological impact assessment of the human population and the environment using interactive tools.

The earthquake and the subsequent tsunami that occurred offshore of Japan resulted in an important loss of life and a serious accident at the nuclear facility of Fukushima. The "hot spots" of the release are evaluated here applying the model LMDZORINCA for (137)Cs. Moreover, an assessment is attempted for the population and the environment using the dosimetric scheme of the WHO and the interactive tool ERICA, respectively. Cesium-137 was deposited mostly in Pacific and Atlantic Oceans and North Pole (80%), whereas the rest in the continental areas of North America and Eurasia contributed slightly to the natural background (0.5-5.0 kBq m(-2)). The effective dose from (137)Cs and (134)Cs (radiocesium) irradiation during the first 3 months was estimated between 1-5 mSv in Fukushima and the neighboring prefectures. In the rest of Japan, the respective doses were found to be less than 0.5 mSv, whereas in the rest of the world it was less than 0.1 mSv. Such doses are equivalent with the obtained dose from a simple X-ray; for the highly contaminated regions, they are close to the dose limit for exposure due to radon inhalation (10 mSv). The calculated dose rates from radiocesium exposure on reference organisms ranged from 0.03 to 0.18 µGy h(-1), which are 2 orders of magnitude below the screening dose limit (10 µGy h(-1)) that could result in obvious effects on the population. However, these results may underestimate the real situation, since stable soil density was used in the calculations, a zero radiocesium background was assumed, and dose only from two radionuclides was estimated, while more that 40 radionuclides have been deposited in the vicinity of the facility. When monitoring data applied, much higher dose rates were estimated certifying ecological risk for small mammals and reptiles in terms of cytogenetic damage and reproduction.

Satellites reveal Earth's seasonally shifting dust emission sources.

Establishing mineral dust impacts on Earth's systems requires numerical models of the dust cycle. Differences between dust optical depth (DOD) measurements and modelling the cycle of dust emission, atmospheric transport, and deposition of dust indicate large model uncertainty due partially to unrealistic model assumptions about dust emission frequency. Calibrating dust cycle models to DOD measurements typically in North Africa, are routinely used to reduce dust model magnitude. This calibration forces modelled dust emissions to match atmospheric DOD but may hide the correct magnitude and frequency of dust emission events at source, compensating biases in other modelled processes of the dust cycle. Therefore, it is essential to improve physically based dust emission modules. Here we use a global collation of satellite observations from previous studies of dust emission point source (DPS) dichotomous frequency data. We show that these DPS data have little-to-no relation with MODIS DOD frequency. We calibrate the albedo-based dust emission model using the frequency distribution of those DPS data. The global dust emission uncertainty constrained by DPS data (±3.8 kg m-2 y-1) provides a benchmark for dust emission model development. Our calibrated model results reveal much less global dust emission (29.1 ± 14.9 Tg y-1) than previous estimates, and show seasonally shifting dust emission predominance within and between hemispheres, as opposed to a persistent North African dust emission primacy widely interpreted from DOD measurements. Earth's largest dust emissions, proceed seasonally from East Asian deserts in boreal spring, to Middle Eastern and North African deserts in boreal summer and then Australian shrublands in boreal autumn-winter. This new analysis of dust emissions, from global sources of varying geochemical properties, have far-reaching implications for current and future dust-climate effects. For more reliable coupled representation of dust-climate projections, our findings suggest the need to re-evaluate dust cycle modelling and benefit from the albedo-based parameterisation.

Improved representation of the global dust cycle using observational constraints on dust properties and abundance.

Even though desert dust is the most abundant aerosol by mass in Earth's atmosphere, atmospheric models struggle to accurately represent its spatial and temporal distribution. These model errors are partially caused by fundamental difficulties in simulating dust emission in coarse-resolution models and in accurately representing dust microphysical properties. Here we mitigate these problems by developing a new methodology that yields an improved representation of the global dust cycle. We present an analytical framework that uses inverse modeling to integrate an ensemble of global model simulations with observational constraints on the dust size distribution, extinction efficiency, and regional dust aerosol optical depth. We then compare the inverse model results against independent measurements of dust surface concentration and deposition flux and find that errors are reduced by approximately a factor of two relative to current model simulations of the Northern Hemisphere dust cycle. The inverse model results show smaller improvements in the less dusty Southern Hemisphere, most likely because both the model simulations and the observational constraints used in the inverse model are less accurate. On a global basis, we find that the emission flux of dust with geometric diameter up to 20 µm (PM20) is approximately 5,000 Tg/year, which is greater than most models account for. This larger PM20 dust flux is needed to match observational constraints showing a large atmospheric loading of coarse dust. We obtain gridded data sets of dust emission, vertically integrated loading, dust aerosol optical depth, (surface) concentration, and wet and dry deposition fluxes that are resolved by season and particle size. As our results indicate that this data set is more accurate than current model simulations and the MERRA-2 dust reanalysis product, it can be used to improve quantifications of dust impacts on the Earth system.

Spatially explicit analysis identifies significant potential for bioenergy with carbon capture and storage in China.

As China ramped-up coal power capacities rapidly while CO2 emissions need to decline, these capacities would turn into stranded assets. To deal with this risk, a promising option is to retrofit these capacities to co-fire with biomass and eventually upgrade to CCS operation (BECCS), but the feasibility is debated with respect to negative impacts on broader sustainability issues. Here we present a data-rich spatially explicit approach to estimate the marginal cost curve for decarbonizing the power sector in China with BECCS. We identify a potential of 222 GW of power capacities in 2836 counties generated by co-firing 0.9 Gt of biomass from the same county, with half being agricultural residues. Our spatially explicit method helps to reduce uncertainty in the economic costs and emissions of BECCS, identify the best opportunities for bioenergy and show the limitations by logistical challenges to achieve carbon neutrality in the power sector with large-scale BECCS in China.

Missed atmospheric organic phosphorus emitted by terrestrial plants, part 2: Experiment of volatile phosphorus.

The emission and deposition of global atmospheric phosphorus (P) have long been considered unbalanced, and primary biogenic aerosol particles (PBAP) and phosphine (PH3) are considered to be the only atmospheric P sources from the ecosystem. In this work, we found and quantified volatile organic phosphorus (VOP) emissions from plants unaccounted for in previous studies. In a greenhouse in which lemons were cultivated, the atmospheric total phosphorus (TP) concentration of particulate matter (PM) was 41.8% higher than that in a greenhouse containing only soil, and the proportion of organic phosphorus (OP) in TP was doubled. 31P nuclear magnetic resonance tests (31P-NMR) of PM showed that phosphate monoesters were the main components contributed by plants in both the greenhouse and at an outside observation site. Atmospheric gaseous P was directly measured to be 1-2 orders of magnitude lower than P in PM but appeared to double during plant growing seasons relative to other months. Bag-sampling and gas chromatography mass spectrometry (GCMS) tests showed that the gaseous P emitted by plants in the greenhouse was triethyl phosphate. VOP might be an important component of atmospheric P that has been underestimated in previous studies.

Daily CO2 Emission Reduction Indicates the Control of Activities to Contain COVID-19 in China.

Lockdown measures are essential to containing the spread of coronavirus disease 2019 (COVID-19), but they will slow down economic growth by reducing industrial and commercial activities. However, the benefits of activity control from containing the pandemic have not been examined and assessed. Here we use daily carbon dioxide (CO2) emission reduction in China estimated from statistical data for energy consumption and satellite data for nitrogen dioxide (NO2) measured by the Ozone Monitoring Instrument (OMI) as an indicator for reduced activities consecutive to a lockdown. We perform a correlation analysis to show that a 1% day-1 decrease in the rate of COVID-19 cases is associated with a reduction in daily CO2 emissions of 0.22% ± 0.02% using statistical data for energy consumption relative to emissions without COVID-19, or 0.20% ± 0.02% using satellite data for atmospheric column NO2. We estimate that swift action in China is effective in limiting the number of COVID-19 cases <100,000 with a reduction in CO2 emissions of up to 23% by the end of February 2020, whereas a 1-week delay would have required greater containment and a doubling of the emission reduction to meet the same goal. By analyzing the costs of health care and fatalities, we find that the benefits on public health due to reduced activities in China are 10-fold larger than the loss of gross domestic product. Our findings suggest an unprecedentedly high cost of maintaining activities and CO2 emissions during the COVID-19 pandemic and stress substantial benefits of containment in public health by taking early actions to reduce activities during the outbreak of COVID-19.