Climate warming increases extreme daily wildfire growth risk in California.

California has experienced enhanced extreme wildfire behaviour in recent years1-3, leading to substantial loss of life and property4,5. Some portion of the change in wildfire behaviour is attributable to anthropogenic climate warming, but formally quantifying this contribution is difficult because of numerous confounding factors6,7 and because wildfires are below the grid scale of global climate models. Here we use machine learning to quantify empirical relationships between temperature (as well as the influence of temperature on aridity) and the risk of extreme daily wildfire growth (>10,000 acres) in California and find that the influence of temperature on the risk is primarily mediated through its influence on fuel moisture. We use the uncovered relationships to estimate the changes in extreme daily wildfire growth risk under anthropogenic warming by subjecting historical fires from 2003 to 2020 to differing background climatological temperatures and aridity conditions. We find that the influence of anthropogenic warming on the risk of extreme daily wildfire growth varies appreciably on a fire-by-fire and day-by-day basis, depending on whether or not climate warming pushes conditions over certain thresholds of aridity, such as 1.5 kPa of vapour-pressure deficit and 10% dead fuel moisture. So far, anthropogenic warming has enhanced the aggregate expected frequency of extreme daily wildfire growth by 25% (5-95 range of 14-36%), on average, relative to preindustrial conditions. But for some fires, there was approximately no change, and for other fires, the enhancement has been as much as 461%. When historical fires are subjected to a range of projected end-of-century conditions, the aggregate expected frequency of extreme daily wildfire growth events increases by 59% (5-95 range of 47-71%) under a low SSP1-2.6 emissions scenario compared with an increase of 172% (5-95 range of 156-188%) under a very high SSP5-8.5 emissions scenario, relative to preindustrial conditions.

Global and regional drivers of land-use emissions in 1961-2017.

Historically, human uses of land have transformed and fragmented ecosystems1,2, degraded biodiversity3,4, disrupted carbon and nitrogen cycles5,6 and added prodigious quantities of greenhouse gases (GHGs) to the atmosphere7,8. However, in contrast to fossil-fuel carbon dioxide (CO2) emissions, trends and drivers of GHG emissions from land management and land-use change (together referred to as 'land-use emissions') have not been as comprehensively and systematically assessed. Here we present country-, process-, GHG- and product-specific inventories of global land-use emissions from 1961 to 2017, we decompose key demographic, economic and technical drivers of emissions and we assess the uncertainties and the sensitivity of results to different accounting assumptions. Despite steady increases in population (+144 per cent) and agricultural production per capita (+58 per cent), as well as smaller increases in emissions per land area used (+8 per cent), decreases in land required per unit of agricultural production (-70 per cent) kept global annual land-use emissions relatively constant at about 11 gigatonnes CO2-equivalent until 2001. After 2001, driven by rising emissions per land area, emissions increased by 2.4 gigatonnes CO2-equivalent per decade to 14.6 gigatonnes CO2-equivalent in 2017 (about 25 per cent of total anthropogenic GHG emissions). Although emissions intensity decreased in all regions, large differences across regions persist over time. The three highest-emitting regions (Latin America, Southeast Asia and sub-Saharan Africa) dominate global emissions growth from 1961 to 2017, driven by rapid and extensive growth of agricultural production and related land-use change. In addition, disproportionate emissions are related to certain products: beef and a few other red meats supply only 1 per cent of calories worldwide, but account for 25 per cent of all land-use emissions. Even where land-use change emissions are negligible or negative, total per capita CO2-equivalent land-use emissions remain near 0.5 tonnes per capita, suggesting the current frontier of mitigation efforts. Our results are consistent with existing knowledge-for example, on the role of population and economic growth and dietary choice-but provide additional insight into regional and sectoral trends.

Committed emissions from existing energy infrastructure jeopardize 1.5 °C climate target.

Net anthropogenic emissions of carbon dioxide (CO2) must approach zero by mid-century (2050) in order to stabilize the global mean temperature at the level targeted by international efforts1-5. Yet continued expansion of fossil-fuel-burning energy infrastructure implies already 'committed' future CO2 emissions6-13. Here we use detailed datasets of existing fossil-fuel energy infrastructure in 2018 to estimate regional and sectoral patterns of committed CO2 emissions, the sensitivity of such emissions to assumed operating lifetimes and schedules, and the economic value of the associated infrastructure. We estimate that, if operated as historically, existing infrastructure will cumulatively emit about 658 gigatonnes of CO2 (with a range of 226 to 1,479 gigatonnes CO2, depending on the lifetimes and utilization rates assumed). More than half of these emissions are predicted to come from the electricity sector; infrastructure in China, the USA and the 28 member states of the European Union represents approximately 41 per cent, 9 per cent and 7 per cent of the total, respectively. If built, proposed power plants (planned, permitted or under construction) would emit roughly an extra 188 (range 37-427) gigatonnes CO2. Committed emissions from existing and proposed energy infrastructure (about 846 gigatonnes CO2) thus represent more than the entire carbon budget that remains if mean warming is to be limited to 1.5 degrees Celsius (°C) with a probability of 66 to 50 per cent (420-580 gigatonnes CO2)5, and perhaps two-thirds of the remaining carbon budget if mean warming is to be limited to less than 2 °C (1,170-1,500 gigatonnes CO2)5. The remaining carbon budget estimates are varied and nuanced14,15, and depend on the climate target and the availability of large-scale negative emissions16. Nevertheless, our estimates suggest that little or no new CO2-emitting infrastructure can be commissioned, and that existing infrastructure may need to be retired early (or be retrofitted with carbon capture and storage technology) in order to meet the Paris Agreement climate goals17. Given the asset value per tonne of committed emissions, we suggest that the most cost-effective premature infrastructure retirements will be in the electricity and industry sectors, if non-emitting alternatives are available and affordable4,18.

Kinetics of Metastable Argon Optical Excitation and Gain in Ar/He Microplasmas.

The optically pumped rare-gas metastable laser is capable of high-intensity lasing on a broad range of near-infrared transitions for excited-state rare gas atoms (Ar*, Kr*, Ne*, Xe*) diluted in flowing He. The lasing action is generated by photoexcitation of the metastable atom to an upper state, followed by collisional energy transfer with He to a neighboring state and lasing back to the metastable state. The metastables are generated in a high-efficiency electric discharge at pressures of ∼0.4 to 1 atm. The diode-pumped rare-gas laser (DPRGL) is a chemically inert analogue to diode-pumped alkali laser (DPAL) systems, with similar optical and power scaling characteristics for high-energy laser applications. We used a continuous-wave linear microplasma array in Ar/He mixtures to produce Ar(1s5) (Paschen notation) metastables at number densities exceeding 1013 cm-3. The gain medium was optically pumped by both a narrow-line 1 W titanium-sapphire laser and a 30 W diode laser. Tunable diode laser absorption and gain spectroscopy determined Ar(1s5) number densities and small-signal gains up to ∼2.5 cm-1. Continuous-wave lasing was observed using the diode pump laser. The results were analyzed with a steady-state kinetics model relating the gain and the Ar(1s5) number density.

Transboundary health impacts of transported global air pollution and international trade.

Millions of people die every year from diseases caused by exposure to outdoor air pollution. Some studies have estimated premature mortality related to local sources of air pollution, but local air quality can also be affected by atmospheric transport of pollution from distant sources. International trade is contributing to the globalization of emission and pollution as a result of the production of goods (and their associated emissions) in one region for consumption in another region. The effects of international trade on air pollutant emissions, air quality and health have been investigated regionally, but a combined, global assessment of the health impacts related to international trade and the transport of atmospheric air pollution is lacking. Here we combine four global models to estimate premature mortality caused by fine particulate matter (PM2.5) pollution as a result of atmospheric transport and the production and consumption of goods and services in different world regions. We find that, of the 3.45 million premature deaths related to PM2.5 pollution in 2007 worldwide, about 12 per cent (411,100 deaths) were related to air pollutants emitted in a region of the world other than that in which the death occurred, and about 22 per cent (762,400 deaths) were associated with goods and services produced in one region for consumption in another. For example, PM2.5 pollution produced in China in 2007 is linked to more than 64,800 premature deaths in regions other than China, including more than 3,100 premature deaths in western Europe and the USA; on the other hand, consumption in western Europe and the USA is linked to more than 108,600 premature deaths in China. Our results reveal that the transboundary health impacts of PM2.5 pollution associated with international trade are greater than those associated with long-distance atmospheric pollutant transport.

Economic carbon cycle feedbacks may offset additional warming from natural feedbacks.

As the Earth warms, carbon sinks on land and in the ocean will weaken, thereby increasing the rate of warming. Although natural mechanisms contributing to this positive climate-carbon feedback have been evaluated using Earth system models, analogous feedbacks involving human activities have not been systematically quantified. Here we conceptualize and estimate the magnitude of several economic mechanisms that generate a carbon-climate feedback, using the Kaya identity to separate a net economic feedback into components associated with population, GDP, heating and cooling, and the carbon intensity of energy production and transportation. We find that climate-driven decreases in economic activity (GDP) may in turn decrease human energy use and thus fossil fuel CO2 emissions. In a high radiative forcing scenario, such decreases in economic activity reduce fossil fuel emissions by 13% this century, lowering atmospheric CO2 by over 100 ppm in 2100. The natural carbon-climate feedback, in contrast, increases atmospheric CO2 over this period by a similar amount, and thus, the net effect including both feedbacks is nearly zero. Our work highlights the importance of improving the representation of climate-economic feedbacks in scenarios of future change. Although the effects of climate warming on the economy may offset weakening land and ocean carbon sinks, a loss of economic productivity will have high societal costs, potentially increasing wealth inequity and limiting resources available for effective adaptation.

Impacts of climate change on future air quality and human health in China.

In recent years, air pollution has caused more than 1 million deaths per year in China, making it a major focus of public health efforts. However, future climate change may exacerbate such human health impacts by increasing the frequency and duration of weather conditions that enhance air pollution exposure. Here, we use a combination of climate, air quality, and epidemiological models to assess future air pollution deaths in a changing climate under Representative Concentration Pathway 4.5 (RCP4.5). We find that, assuming pollution emissions and population are held constant at current levels, climate change would adversely affect future air quality for >85% of China's population (∼55% of land area) by the middle of the century, and would increase by 3% and 4% the population-weighted average concentrations of fine particulate matter (PM2.5) and ozone, respectively. As a result, we estimate an additional 12,100 and 8,900 Chinese (95% confidence interval: 10,300 to 13,800 and 2,300 to 14,700, respectively) will die per year from PM2.5 and ozone exposure, respectively. The important underlying climate mechanisms are changes in extreme conditions such as atmospheric stagnation and heat waves (contributing 39% and 6%, respectively, to the increase in mortality). Additionally, greater vulnerability of China's aging population will further increase the estimated deaths from PM2.5 and ozone in 2050 by factors of 1 and 3, respectively. Our results indicate that climate change and more intense extremes are likely to increase the risk of severe pollution events in China. Managing air quality in China in a changing climate will thus become more challenging.

Atmospheric methane removal: a research agenda.

Atmospheric methane removal (e.g. in situ methane oxidation to carbon dioxide) may be needed to offset continued methane release and limit the global warming contribution of this potent greenhouse gas. Because mitigating most anthropogenic emissions of methane is uncertain this century, and sudden methane releases from the Arctic or elsewhere cannot be excluded, technologies for methane removal or oxidation may be required. Carbon dioxide removal has an increasingly well-established research agenda and technological foundation. No similar framework exists for methane removal. We believe that a research agenda for negative methane emissions-'removal' or atmospheric methane oxidation-is needed. We outline some considerations for such an agenda here, including a proposed Methane Removal Model Intercomparison Project (MR-MIP). This article is part of a discussion meeting issue 'Rising methane: is warming feeding warming? (part 1)'.

Reduced carbon emission estimates from fossil fuel combustion and cement production in China.

Nearly three-quarters of the growth in global carbon emissions from the burning of fossil fuels and cement production between 2010 and 2012 occurred in China. Yet estimates of Chinese emissions remain subject to large uncertainty; inventories of China's total fossil fuel carbon emissions in 2008 differ by 0.3 gigatonnes of carbon, or 15 per cent. The primary sources of this uncertainty are conflicting estimates of energy consumption and emission factors, the latter being uncertain because of very few actual measurements representative of the mix of Chinese fuels. Here we re-evaluate China's carbon emissions using updated and harmonized energy consumption and clinker production data and two new and comprehensive sets of measured emission factors for Chinese coal. We find that total energy consumption in China was 10 per cent higher in 2000-2012 than the value reported by China's national statistics, that emission factors for Chinese coal are on average 40 per cent lower than the default values recommended by the Intergovernmental Panel on Climate Change, and that emissions from China's cement production are 45 per cent less than recent estimates. Altogether, our revised estimate of China's CO2 emissions from fossil fuel combustion and cement production is 2.49 gigatonnes of carbon (2 standard deviations = ±7.3 per cent) in 2013, which is 14 per cent lower than the emissions reported by other prominent inventories. Over the full period 2000 to 2013, our revised estimates are 2.9 gigatonnes of carbon less than previous estimates of China's cumulative carbon emissions. Our findings suggest that overestimation of China's emissions in 2000-2013 may be larger than China's estimated total forest sink in 1990-2007 (2.66 gigatonnes of carbon) or China's land carbon sink in 2000-2009 (2.6 gigatonnes of carbon).

Optimizing Emissions Reductions from the U.S. Power Sector for Climate and Health Benefits.

Improved air quality and human health are often discussed as "co-benefits" of mitigating climate change, yet they are rarely considered when designing or implementing climate policies. We analyze the implications of integrating health and climate when determining the best locations for replacing power plants with new wind, solar, or natural gas to meet a CO2 reduction target in the United States. We employ a capacity expansion model with integrated assessment of climate and health damages, comparing portfolios optimized for benefits to climate alone or both health and climate. The model estimates county-level health damages and accounts for uncertainty by using a range of air quality models (AP3, EASIUR, and InMAP) and concentration-response functions (American Cancer Society and Harvard Six Cities). We find that reducing CO2 by 30% yields $21-68 billion in annual health benefits, with an additional $9-36 billion possible when co-optimizing for climate and health benefits. Additional benefits accrue from prioritizing emissions reductions in counties with high population exposure. Total health benefits equal or exceed climate benefits across a wide range of modeling assumptions. Our results demonstrate the value of considering health in climate policy design and the need for interstate cooperation to achieve additional health benefits equitably.

Local Anomalies in the Column-Averaged Dry Air Mole Fractions of Carbon Dioxide Across the Globe During the First Months of the Coronavirus Recession.

We use a global transport model and satellite retrievals of the carbon dioxide (CO2) column average to explore the impact of CO2 emissions reductions that occurred during the economic downturn at the start of the Covid-19 pandemic. The changes in the column averages are substantial in a few places of the model global grid, but the induced gradients are most often less than the random errors of the retrievals. The current necessity to restrict the quality-assured column retrievals to almost cloud-free areas appears to be a major obstacle in identifying changes in CO2 emissions. Indeed, large changes have occurred in the presence of clouds, and in places that were cloud free in 2020, the comparison with previous years is hampered by different cloud conditions during these years. We therefore recommend to favor all-weather CO2 monitoring systems, at least in situ, to support international efforts to reduce emissions.

Evaluation of a proposal for reliable low-cost grid power with 100% wind, water, and solar.

A number of analyses, meta-analyses, and assessments, including those performed by the Intergovernmental Panel on Climate Change, the National Oceanic and Atmospheric Administration, the National Renewable Energy Laboratory, and the International Energy Agency, have concluded that deployment of a diverse portfolio of clean energy technologies makes a transition to a low-carbon-emission energy system both more feasible and less costly than other pathways. In contrast, Jacobson et al. [Jacobson MZ, Delucchi MA, Cameron MA, Frew BA (2015) Proc Natl Acad Sci USA 112(49):15060-15065] argue that it is feasible to provide "low-cost solutions to the grid reliability problem with 100% penetration of WWS [wind, water and solar power] across all energy sectors in the continental United States between 2050 and 2055", with only electricity and hydrogen as energy carriers. In this paper, we evaluate that study and find significant shortcomings in the analysis. In particular, we point out that this work used invalid modeling tools, contained modeling errors, and made implausible and inadequately supported assumptions. Policy makers should treat with caution any visions of a rapid, reliable, and low-cost transition to entire energy systems that relies almost exclusively on wind, solar, and hydroelectric power.

Economic uncertainty before and during the COVID-19 pandemic.

We consider several economic uncertainty indicators for the US and UK before and during the COVID-19 pandemic: implied stock market volatility, newspaper-based policy uncertainty, Twitter chatter about economic uncertainty, subjective uncertainty about business growth, forecaster disagreement about future GDP growth, and a model-based measure of macro uncertainty. Four results emerge. First, all indicators show huge uncertainty jumps in reaction to the pandemic and its economic fallout. Indeed, most indicators reach their highest values on record. Second, peak amplitudes differ greatly - from a 35% rise for the model-based measure of US economic uncertainty (relative to January 2020) to a 20-fold rise in forecaster disagreement about UK growth. Third, time paths also differ: Implied volatility rose rapidly from late February, peaked in mid-March, and fell back by late March as stock prices began to recover. In contrast, broader measures of uncertainty peaked later and then plateaued, as job losses mounted, highlighting differences between Wall Street and Main Street uncertainty measures. Fourth, in Cholesky-identified VAR models fit to monthly U.S. data, a COVID-size uncertainty shock foreshadows peak drops in industrial production of 12-19%.

Infrastructure Shapes Differences in the Carbon Intensities of Chinese Cities.

The carbon intensity of economic activity, or CO2 emissions per unit GDP, is a key indicator of the climate impacts of a given activity, business, or region. Although it is well-known that the carbon intensity of countries varies widely according to their level of economic development and dominant industries, few studies have assessed disparities in carbon intensity at the level of cities due to limited availability of data. Here, we present a detailed new inventory of emissions for 337 Chinese cities (every city in mainland China including 333 prefecture-level divisions and 4 province-level cities, Beijing, Tianjin, Shanghai, and Chongqing) in 2013, which we use to evaluate differences of carbon intensity between cities and the causes of those differences. We find that cities' average carbon intensity is 0.84 kg of CO2 per dollar of gross domestic product (kgCO2 per $GDP), but individual cities span a large range: from 0.09 to 7.86 kgCO2 per $GDP (coefficient of variation of 25%). Further analysis of economic and technological drivers of variations in cities' carbon intensity reveals that the differences are largely due to disparities in cities' economic structure that can in turn be traced to past investment-led growth. These patterns suggest that "carbon lock-in" via socio-economic and infrastructural inertia may slow China's efforts to reduce emissions from activities in urban areas. Policy instruments targeted to accelerate the transition of urban economies from investment-led to consumption-led growth may thus be crucial to China meeting both its economic and climate targets.

Climatic Responses to Future Trans-Arctic Shipping.

As global temperatures increase, sea ice loss will increasingly enable commercial shipping traffic to cross the Arctic Ocean, where the ships' gas and particulate emissions may have strong regional effects. Here we investigate impacts of shipping emissions on Arctic climate using a fully coupled Earth system model (CESM 1.2.2) and a suite of newly developed projections of 21st-century trans-Arctic shipping emissions. We find that trans-Arctic shipping will reduce Arctic warming by nearly 1 °C by 2099, due to sulfate-driven liquid water cloud formation. Cloud fraction and liquid water path exhibit significant positive trends, cooling the lower atmosphere and surface. Positive feedbacks from sea ice growth-induced albedo increases and decreased downwelling longwave radiation due to reduced water vapor content amplify the cooling relative to the shipping-free Arctic. Our findings thus point to the complexity in Arctic climate responses to increased shipping traffic, justifying further study and policy considerations as trade routes open.

China's international trade and air pollution in the United States.

China is the world's largest emitter of anthropogenic air pollutants, and measurable amounts of Chinese pollution are transported via the atmosphere to other countries, including the United States. However, a large fraction of Chinese emissions is due to manufacture of goods for foreign consumption. Here, we analyze the impacts of trade-related Chinese air pollutant emissions on the global atmospheric environment, linking an economic-emission analysis and atmospheric chemical transport modeling. We find that in 2006, 36% of anthropogenic sulfur dioxide, 27% of nitrogen oxides, 22% of carbon monoxide, and 17% of black carbon emitted in China were associated with production of goods for export. For each of these pollutants, about 21% of export-related Chinese emissions were attributed to China-to-US export. Atmospheric modeling shows that transport of the export-related Chinese pollution contributed 3-10% of annual mean surface sulfate concentrations and 0.5-1.5% of ozone over the western United States in 2006. This Chinese pollution also resulted in one extra day or more of noncompliance with the US ozone standard in 2006 over the Los Angeles area and many regions in the eastern United States. On a daily basis, the export-related Chinese pollution contributed, at a maximum, 12-24% of sulfate concentrations over the western United States. As the United States outsourced manufacturing to China, sulfate pollution in 2006 increased in the western United States but decreased in the eastern United States, reflecting the competing effect between enhanced transport of Chinese pollution and reduced US emissions. Our findings are relevant to international efforts to reduce transboundary air pollution.

Outsourcing CO2 within China.

Recent studies have shown that the high standard of living enjoyed by people in the richest countries often comes at the expense of CO2 emissions produced with technologies of low efficiency in less affluent, developing countries. Less apparent is that this relationship between developed and developing can exist within a single country's borders, with rich regions consuming and exporting high-value goods and services that depend upon production of low-cost and emission-intensive goods and services from poorer regions in the same country. As the world's largest emitter of CO2, China is a prominent and important example, struggling to balance rapid economic growth and environmental sustainability across provinces that are in very different stages of development. In this study, we track CO2 emissions embodied in products traded among Chinese provinces and internationally. We find that 57% of China's emissions are related to goods that are consumed outside of the province where they are produced. For instance, up to 80% of the emissions related to goods consumed in the highly developed coastal provinces are imported from less developed provinces in central and western China where many low-value-added but high-carbon-intensive goods are produced. Without policy attention to this sort of interprovincial carbon leakage, the less developed provinces will struggle to meet their emissions intensity targets, whereas the more developed provinces might achieve their own targets by further outsourcing. Consumption-based accounting of emissions can thus inform effective and equitable climate policy within China.