Drivers of natural gas use in U.S. residential buildings

Natural gas is the primary fuel used in U.S. residences, yet little is known about its consumption patterns and drivers. We use daily county-level gas consumption data to assess the spatial patterns of the relationships and the sensitivities of gas consumption to outdoor air temperature across U.S. households. We fitted linear-plus-plateau functions to daily gas consumption data in 1000 counties, and derived two key coefficients: the heating temperature threshold (Tcrit) and the gas consumption rate change per 1°C temperature drop (Slope). We identified the main predictors of Tcrit and Slope (like income, employment rate, and building type) using interpretable machine learning models built on census data. Finally, we estimated a potential 2.47 million MtCO2 annual emission reduction in U.S. residences by gas savings due to household insulation improvements and hypothetical behavioral change toward reduced consumption by adopting a 1°C lower Tcrit than the current value.

Biosorption of rare earth elements from luminophores by G. sulphuraria (Cyanidiophytina, Rhodophyta)

Lanthanides are indispensable constituents of modern technologies and are often challenging to acquire from natural resources. The demand for REEs is so high that there is a clear need to develop efficient and eco-friendly recycling methods. In the present study, freeze-dried biomass of the polyextremophile Galdieria sulphuraria was employed to recover REEs from spent fluorescent lamps (FL) luminophores by pretreating the freeze-dried biomass with an acid solution to favour ion exchange and enhance the binding sites on the cell surface available for the metal ions. Lanthanides were extracted from the luminophores using sulfuric acid solutions according to standardised procedures, and the effect of biosorbent dosage (0.5-5 mg/ml) and biosorption time (5-60 min) were evaluated. The content of individual REEs in the luminophores and the resulting algal biomass were determined using inductively coupled plasma mass spectrometry (ICP-MS). The most abundant REE in the luminophores was yttrium (287.42 mg/g dm, 91.60% of all REEs), followed by europium (20.98 mg/g, 6.69%); cerium, gadolinium, terbium and lanthanum was in trace. The best biosorption performances were achieved after 5 min and at the lowest biosorbent dosage (0.5 mg/mL). The highest total metal amount corresponded to 41.61 mg/g dried mass, and yttrium was the most adsorbed metal (34.59 mg/g dm, 82.88%), followed by cerium (4.01 mg/g); all other metals were less than 2 mg/g. The rapidity of the biosorption process and the low biosorbent dosage required confirmed this microalga as a promising material for creating an eco-sustainable protocol for recycling REEs.

The global mismatch between equitable carbon dioxide removal liability and capacity

Limiting climate change to 1.5°C and achieving net-zero emissions would entail substantial carbon dioxide removal (CDR) from the atmosphere by the mid-century, but how much CDR is needed at country level over time is unclear. The purpose of this paper is to provide a detailed description of when and how much CDR is required at country level in order to achieve 1.5°C and how much CDR countries can carry out domestically. We allocate global CDR pathways among 170 countries according to 6 equity principles and assess these allocations with respect to countries' biophysical and geophysical capacity to deploy CDR. Allocating global CDR to countries based on these principles suggests that CDR will, on average, represent ∼4% of nations' total emissions in 2030, rising to ∼17% in 2040. Moreover, equitable allocations of CDR, in many cases, exceed implied land and carbon storage capacities. We estimate ∼15% of countries (25) would have insufficient land to contribute an equitable share of global CDR, and ∼40% of countries (71) would have insufficient geological storage capacity. Unless more diverse CDR technologies are developed, the mismatch between CDR liabilities and land-based CDR capacities will lead to global demand for six GtCO2 carbon credits from 2020 to 2050. This demonstrates an imperative demand for international carbon trading of CDR.

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.

Rebound effects could offset more than half of avoided food loss and waste

Reducing food loss and waste (FLW) could lessen the environmental impacts of food systems and improve food security. However, rebound effects-whereby efficiency improvements cause price decreases and consumption increases-may offset some avoided FLW. Here we model rebounds in food consumption under a scenario of costless FLW reduction. We project that consumption rebound could offset 53-71% of avoided FLW. Such rebounds would imply similar percentage reductions in environmental benefits (carbon emissions, land use, water use) and improvements in food security benefits (increased calorie availability), highlighting a tension between these two objectives. Evidence from energy systems suggests that indirect effects not included in our analysis could further increase rebounds. However, costs of reducing FLW would reduce rebounds. Rebound effects are therefore important to consider in efforts aimed at reducing FLW.

Carbon Monitor Europe near-real-time daily CO2 emissions for 27 EU countries and the United Kingdom

With the urgent need to implement the EU countries pledges and to monitor the effectiveness of Green Deal plan, Monitoring Reporting and Verification tools are needed to track how emissions are changing for all the sectors. Current official inventories only provide annual estimates of national CO₂ emissions with a lag of 1+ year which do not capture the variations of emissions due to recent shocks including COVID lockdowns and economic rebounds, war in Ukraine. Here we present a near-real-time country-level dataset of daily fossil fuel and cement emissions from January 2019 through December 2021 for 27 EU countries and UK, which called Carbon Monitor Europe. The data are calculated separately for six sectors: power, industry, ground transportation, domestic aviation, international aviation and residential. Daily CO₂ emissions are estimated from a large set of activity data compiled from different sources. The goal of this dataset is to improve the timeliness and temporal resolution of emissions for European countries, to inform the public and decision makers about current emissions changes in Europe.

CarbonMonitor-Power near-real-time monitoring of global power generation on hourly to daily scales

We constructed a frequently updated, near-real-time global power generation dataset: CarbonMonitor-Power since January, 2016 at national levels with near-global coverage and hourly-to-daily time resolution. The data presented here are collected from 37 countries across all continents for eight source groups, including three types of fossil sources (coal, gas, and oil), nuclear energy and four groups of renewable energy sources (solar energy, wind energy, hydro energy and other renewables including biomass, geothermal, etc.). The global near-real-time power dataset shows the dynamics of the global power system, including its hourly, daily, weekly and seasonal patterns as influenced by daily periodical activities, weekends, seasonal cycles, regular and irregular events (i.e., holidays) and extreme events (i.e., the COVID-19 pandemic). The CarbonMonitor-Power dataset reveals that the COVID-19 pandemic caused strong disruptions in some countries (i.e., China and India), leading to a temporary or long-lasting shift to low carbon intensity, while it had only little impact in some other countries (i.e., Australia). This dataset offers a large range of opportunities for power-related scientific research and policy-making.

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.

Singlet Molecular Oxygen: from COIL Lasers to Photodynamic Cancer Therapy

Translation of experimental techniques from one scientific discipline to another is often difficult but rewarding. Knowledge gained from the new area can lead to long lasting and fruitful collaborations with concomitant development of new ideas and studies. In this Review Article, we describe how early work on the chemically pumped atomic iodine laser (COIL) led to the development of a key diagnostic for a promising cancer treatment known as photodynamic therapy (PDT). The highly metastable excited state of molecular oxygen, a¹Δ_g, also known as singlet oxygen, is the link between these disparate fields. It powers the COIL laser and is the active species that kills cancer cells during PDT. We describe the fundamentals of both COIL and PDT and trace the development path of an ultrasensitive dosimeter for singlet oxygen. The path from COIL lasers to cancer research was relatively long and required medical and engineering expertise from numerous collaborations. As we show below, the knowledge gained in the COIL research, combined with these extensive collaborations, has resulted in our being able to show a strong correlation between cancer cell death and the singlet oxygen measured during PDT treatments of mice. This progress is a key step in the eventual development of a singlet oxygen dosimeter that could be used to guide PDT treatments and improve outcomes.

Record-high CO2 emissions from boreal fires in 2021

Extreme wildfires are becoming more common and increasingly affecting Earth's climate. Wildfires in boreal forests have attracted much less attention than those in tropical forests, although boreal forests are one of the most extensive biomes on Earth and are experiencing the fastest warming. We used a satellite-based atmospheric inversion system to monitor fire emissions in boreal forests. Wildfires are rapidly expanding into boreal forests with emerging warmer and drier fire seasons. Boreal fires, typically accounting for 10% of global fire carbon dioxide emissions, contributed 23% (0.48 billion metric tons of carbon) in 2021, by far the highest fraction since 2000. 2021 was an abnormal year because North American and Eurasian boreal forests synchronously experienced their greatest water deficit. Increasing numbers of extreme boreal fires and stronger climate-fire feedbacks challenge climate mitigation efforts.

Selective biosorption of lanthanides onto Galdieria sulphuraria

The recovering of trivalent Lanthanides from aqueous solutions, by biosorption process onto Galdieria sulphuraria lifeless cells, was investigated. Potentiometry, UV-Vis, FTIR-ATR spectroscopy and SEM-EDS analysis were used. All the experiments were performed at 25 °C, in 0.5 M NaCl. Ln³⁺ biosorption is greater in the 5-6 pH range with values ranging from 80 μmol/g to 130 μmol/g (dry weight). The adsorbed Ln³⁺ ions can be recovered at higher acidity (pH<1) and the biosorbent can be reused. Specific molecular interactions between Ln³⁺ ions and the functional groups on G. sulphuraria surface were highlighted. Particularly, proteins are involved if Ln³⁺=Pr³⁺, Sm³⁺, Eu³⁺, Tb³⁺, Dy³⁺, Tm³⁺, while Ce³⁺, Ho³⁺, Er³⁺ form bonds with carbohydrates. Finally, both proteins and carbohydrates are involved if Gd³⁺ and Yb³⁺. A Surface Complexation approach, with a good graphical fitting to potentiometric experimental collected data, was used to describe the biosorption mechanism. This study could be of great applicative utility for removing of trivalent actinides, from waste aqueous solutions, by biosorption. As well known the lanthanides were used as model to simulate the chemical behaviour of actinides in the same oxidation state.

Smoke-weather interaction affects extreme wildfires in diverse coastal regions

Extreme wildfires threaten human lives, air quality, and ecosystems. Meteorology plays a vital role in wildfire behaviors, and the links between wildfires and climate have been widely studied. However, it is not fully clear how fire-weather feedback affects short-term wildfire variability, which undermines our ability to mitigate fire disasters. Here, we show the primacy of synoptic-scale feedback in driving extreme fires in Mediterranean and monsoon climate regimes in the West Coast of the United States and Southeastern Asia. We found that radiative effects of smoke aerosols can modify near-surface wind, air dryness, and rainfall and thus worsen air pollution by enhancing fire emissions and weakening dispersion. The intricate interactions among wildfires, smoke, and weather form a positive feedback loop that substantially increases air pollution exposure.

Near-real-time global gridded daily CO2 emissions 2021

We present a near-real-time global gridded daily CO₂ emissions dataset (GRACED) throughout 2021. GRACED provides gridded CO₂ emissions at a 0.1° × 0.1° spatial resolution and 1-day temporal resolution from cement production and fossil fuel combustion over seven sectors, including industry, power, residential consumption, ground transportation, international aviation, domestic aviation, and international shipping. GRACED is prepared from the near-real-time daily national CO₂ emissions estimates (Carbon Monitor), multi-source spatial activity data emissions and satellite NO₂ data for time variations of those spatial activity data. GRACED provides the most timely overview of emissions distribution changes, which enables more accurate and timely identification of when and where fossil CO₂ emissions have rebounded and decreased. Uncertainty analysis of GRACED gives a grid-level two-sigma uncertainty of value of ±19.9% in 2021, indicating the reliability of GRACED was not sacrificed for the sake of higher spatiotemporal resolution that GRACED provides. Continuing to update GRACED in a timely manner could help policymakers monitor energy and climate policies' effectiveness and make adjustments quickly.

Economic and biophysical limits to seaweed farming for climate change mitigation

Net-zero greenhouse gas (GHG) emissions targets are driving interest in opportunities for biomass-based negative emissions and bioenergy, including from marine sources such as seaweed. Yet the biophysical and economic limits to farming seaweed at scales relevant to the global carbon budget have not been assessed in detail. We use coupled seaweed growth and technoeconomic models to estimate the costs of global seaweed production and related climate benefits, systematically testing the relative importance of model parameters. Under our most optimistic assumptions, sinking farmed seaweed to the deep sea to sequester a gigaton of CO₂ per year costs as little as US$480 per tCO₂ on average, while using farmed seaweed for products that avoid a gigaton of CO₂-equivalent GHG emissions annually could return a profit of $50 per tCO₂-eq. However, these costs depend on low farming costs, high seaweed yields, and assumptions that almost all carbon in seaweed is removed from the atmosphere (that is, competition between phytoplankton and seaweed is negligible) and that seaweed products can displace products with substantial embodied non-CO₂ GHG emissions. Moreover, the gigaton-scale climate benefits we model would require farming very large areas (>90,000 km²)-a >30-fold increase in the area currently farmed. Our results therefore suggest that seaweed-based climate benefits may be feasible, but targeted research and demonstrations are needed to further reduce economic and biophysical uncertainties.

Global mitigation efforts cannot neglect emerging emitters

International efforts to avoid dangerous climate change have historically focused on reducing energy-related CO₂ emissions from countries with either the largest economies (e.g. the EU and the USA) and/or the largest populations (e.g. China and India). However, in recent years, emissions have surged among a different and much less-examined group of countries, raising concerns that a next generation of high-emitting economies will obviate current mitigation targets. Here, we analyse the trends and drivers of emissions in each of the 59 countries where emissions in 2010-2018 grew faster than the global average (excluding China and India), project their emissions under a range of longer-term energy scenarios and estimate the costs of decarbonization pathways. Total emissions from these 'emerging emitters' reach as much as 7.5 GtCO₂/year in the baseline 2.5° scenario-substantially greater than the emissions from these regions in previously published scenarios that would limit warming to 1.5°C or even 2°C. Such unanticipated emissions would in turn require non-emitting energy deployment from all sectors within these emerging emitters, and faster and deeper reductions in emissions from other countries to meet international climate goals. Moreover, the annual costs of keeping emissions at the low level are in many cases 0.2%-4.1% of countries' gross domestic production, pointing to potential trade-offs with poverty-reduction goals and/or the need for economic support and low-carbon technology transfer from historically high-emitting countries. Our results thus highlight the critical importance of ramping up mitigation efforts in countries that to this point have been largely ignored.

Carbon Monitor Cities near-real-time daily estimates of CO2 emissions from 1500 cities worldwide

Building on near-real-time and spatially explicit estimates of daily carbon dioxide (CO2) emissions, here we present and analyze a new city-level dataset of fossil fuel and cement emissions, Carbon Monitor Cities, which provides daily estimates of emissions from January 2019 through December 2021 for 1500 cities in 46 countries, and disaggregates five sectors: power generation, residential (buildings), industry, ground transportation, and aviation. The goal of this dataset is to improve the timeliness and temporal resolution of city-level emission inventories and includes estimates for both functional urban areas and city administrative areas that are consistent with global and regional totals. Comparisons with other datasets (i.e. CEADs, MEIC, Vulcan, and CDP-ICLEI Track) were performed, and we estimate the overall annual uncertainty range to be ±21.7%. Carbon Monitor Cities is a near-real-time, city-level emission dataset that includes cities around the world, including the first estimates for many cities in low-income countries.

Land-use emissions embodied in international trade

International trade separates consumption of goods from related environmental impacts, including greenhouse gas emissions from agriculture and land-use change (together referred to as "land-use emissions"). Through use of new emissions estimates and a multiregional input-output model, we evaluated land-use emissions embodied in global trade from 2004 to 2017. Annually, 27% of land-use emissions and 22% of agricultural land are related to agricultural products ultimately consumed in a different region from where they were produced. Roughly three-quarters of embodied emissions are from land-use change, with the largest transfers from lower-income countries such as Brazil, Indonesia, and Argentina to more industrialized regions such as Europe, the United States, and China. Mitigation of global land-use emissions and sustainable development may thus depend on improving the transparency of supply chains.

Role of climate goals and clean-air policies on reducing future air pollution deaths in China: a modelling study

BACKGROUND

Over 3 million people die every year from diseases caused by exposure to outdoor PM_2·5 air pollution, and more than a quarter of these premature deaths occur in China. In addition to clean-air policies that target pollution emissions, climate policies aimed at reducing fossil-fuel CO₂ emissions (eg, to avoid 1·5°C of warming) might also greatly improve air quality and public health. However, no comprehensive accounting of public health outcomes has been done under different energy pathways and local clean-air management decisions in China. We aimed to develop an integrated method for quantifying the health co-benefits from different climate, energy, and clean-air policy scenarios and to assess the relationship between climate and clean-air policies and future health burdens in China, where an ageing population will further exacerbate the effects of air pollution.

METHODS

For this modelling study, we used a China-focused integrated assessment model and a dynamic emission projection model to project future Chinese air quality in scenarios spanning a range of global climate targets (1·5°C, 2°C, national determined contributions [NDC], unambitious, baseline, and 4·5°C) and national clean-air actions (termed 2015-pollution, current-pollution, and ambitious-pollution). We then evaluated the health effects of PM_2·5 air pollution in the scenario matrix using the air quality model and the latest epidemiological concentration-response functions from the 2019 Global Burden of Diseases, Injuries, and Risk Factors Study.

FINDINGS

We found that, without ambitious climate mitigation (eg, under current NDC pledge), Chinese deaths related to PM_2·5 air pollution might not always decrease-and might often grow-by 2050 compared with the base year of 2015, regardless of clean-air policies and air quality improvements. For example, in the scenario that tracks China's current NDC pledge and uses the best available pollution control technologies (the ambitious-pollution and NDC goals scenario), PM_2·5-related deaths in China would decrease slightly by 2030 to 1·23 million per year (95% CI 0·95-1·51) from 1·25 million (1·04-1·46) in 2015, but would not decrease further by 2050 (1·21 million, 0·86-1·60) despite substantial and continuous improvements in population-weighted air quality (from 27·2 μg/m³ in 2030 to 16·0 μg/m³ in 2050). The contrary trends of improving air quality and increasing PM_2·5-related deaths in many of our scenarios revealed the extent to which extra efforts are needed to compensate for the increasing age of China's population in the future. With the scenarios that included ambitious clean-air policies and met international climate goals to avoid 1·5°C and 2°C of warming (the ambitious-pollution-2°C goals scenario and the ambitious-pollution-1·5°C goals scenario), we observed substantial decreases in China's PM_2·5-related deaths of 0·32-0·55 million deaths compared with NDC goals in 2050, and age-standardised death rates decreased by 10·2-14·2 deaths per 100 000 population per year.

INTERPRETATION

Our results show that ambitious climate policies (ie, limiting global average temperature rise to well below 2°C) and low-carbon energy transitions coupled with stringent clean-air policies are necessary to substantially reduce the human health effects from air pollution in China, regardless of socioeconomic assumptions. Our findings could help policy makers understand the crucial links between climate policy and public health.

FUNDING

The National Natural Science Foundation of China.

Near-real-time global gridded daily CO2 emissions

Precise and high-resolution carbon dioxide (CO₂) emission data is of great importance in achieving carbon neutrality around the world. Here we present for the first time the near-real-time Global Gridded Daily CO₂ Emissions Dataset (GRACED) from fossil fuel and cement production with a global spatial resolution of 0.1° by 0.1° and a temporal resolution of 1 day. Gridded fossil emissions are computed for different sectors based on the daily national CO₂ emissions from near-real-time dataset (Carbon Monitor), the spatial patterns of point source emission dataset Global Energy Infrastructure Emissions Database (GID), Emission Database for Global Atmospheric Research (EDGAR), and spatiotemporal patters of satellite nitrogen dioxide (NO₂) retrievals. Our study on the global CO₂ emissions responds to the growing and urgent need for high-quality, fine-grained, near-real-time CO₂ emissions estimates to support global emissions monitoring across various spatial scales. We show the spatial patterns of emission changes for power, industry, residential consumption, ground transportation, domestic and international aviation, and international shipping sectors from January 1, 2019, to December 31, 2020. This gives thorough insights into the relative contributions from each sector. Furthermore, it provides the most up-to-date and fine-grained overview of where and when fossil CO₂ emissions have decreased and rebounded in response to emergencies (e.g., coronavirus disease 2019 [COVID-19]) and other disturbances of human activities of any previously published dataset. As the world recovers from the pandemic and decarbonizes its energy systems, regular updates of this dataset will enable policymakers to more closely monitor the effectiveness of climate and energy policies and quickly adapt.

Monitoring global carbon emissions in 2021

Following record-level declines in 2020, near-real-time data indicate that global CO₂ emissions rebounded by 4.8% in 2021, reaching 34.9 GtCO₂. These 2021 emissions consumed 8.7% of the remaining carbon budget for limiting anthropogenic warming to 1.5 °C, which if current trajectories continue, might be used up in 9.5 years at 67% likelihood.

Stock Prices and Economic Activity in the Time of Coronavirus

Stock prices and workplace mobility trace out striking clockwise paths in daily data from mid-February to late May 2020. Global stock prices fell 30% from 17 February to 12 March, before mobility declined. Over the next 11 days, stocks fell another 10 percentage points as mobility dropped 40%. From 23 March to 9 April, stocks recovered half their losses and mobility fell further. From 9 April to late May, both stocks and mobility rose modestly. This dynamic plays out across the 35 countries in our sample, with notable departures in China, South Korea and Taiwan. The size of the global stock market crash in reaction to the pandemic is many times larger than a standard asset-pricing model implies. Looking more closely at the world’s two largest economies, the pandemic had greater effects on stock market levels and volatilities in the USA than in China even before it became evident that early US containment efforts would flounder. Newspaper-based narrative evidence confirms the dominant—and historically unprecedented—role of pandemic-related developments in the stock market behavior of both countries.

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)'.

Regional impacts of COVID-19 on carbon dioxide detected worldwide from space

Activity reductions in early 2020 due to the coronavirus disease 2019 pandemic led to unprecedented decreases in carbon dioxide (CO₂) emissions. Despite their record size, the resulting atmospheric signals are smaller than and obscured by climate variability in atmospheric transport and biospheric fluxes, notably that related to the 2019–2020 Indian Ocean Dipole. Monitoring CO₂ anomalies and distinguishing human and climatic causes thus remain a new frontier in Earth system science. We show that the impact of short-term regional changes in fossil fuel emissions on CO₂ concentrations was observable from space. Starting in February and continuing through May, column CO₂ over many of the world’s largest emitting regions was 0.14 to 0.62 parts per million less than expected in a pandemic-free scenario, consistent with reductions of 3 to 13% in annual global emissions. Current spaceborne technologies are therefore approaching levels of accuracy and precision needed to support climate mitigation strategies with future missions expected to meet those needs.

High optical-throughput spectroscopic singlet oxygen and photosensitizer luminescence dosimeter for monitoring of photodynamic therapy

We report a high light-throughput spectroscopic dosimeter system that is able to noninvasively measure luminescence signals of singlet oxygen (¹ O₂ ) produced during photodynamic therapy (PDT) using a CW (continuous wave) light source. The system is based on a compact, fiber-coupled, high collection efficiency spectrometer (>50% transmittance) designed to maximize optical throughput but with sufficient spectral resolution (~7 nm). This is adequate to detect ¹ O₂ phosphorescence in the presence of strong luminescence background in vivo. This system provides simultaneous acquisition of multiple spectral data points, allowing for more accurate determination of luminescence baseline via spectral fitting and thus the extraction of ¹ O₂ phosphorescence signal based solely on spectroscopic decomposition, without the need for time-gating. Simultaneous collection of photons at different wavelengths improves the quantum efficiency of the system when compared to sequential spectral measurements such as filter-wheel or tunable-filter based systems. A prototype system was tested during in vivo PDT tumor regression experiments using benzoporphyrin derivative (BPD) photosensitizer. It was found that the treatment efficacy (tumor growth inhibition rate) correlated more strongly with ¹ O₂ phosphorescence than with PS fluorescence. These results indicate that this high photon-collection efficiency spectrometer instrument may offer a viable option for real-time ¹ O₂ dosimetry during PDT treatment using CW light.

Energy systems in scenarios at net-zero CO2 emissions

Achieving net-zero CO2 emissions has become the explicitgoal of many climate-energy policies around the world. Although many studies have assessed net-zero emissions pathways, the common features and tradeoffs of energy systems across global scenarios at the point of net-zero CO2 emissions have not yet been evaluated. Here, we examine the energy systems of 177 net-zero scenarios and discuss their long-term technological and regional characteristics in the context of current energy policies. We find that, on average, renewable energy sources account for 60% of primary energy at net-zero (compared to ∼14% today), with slightly less than half of that renewable energy derived from biomass. Meanwhile, electricity makes up approximately half of final energy consumed (compared to ∼20% today), highlighting the extent to which solid, liquid, and gaseous fuels remain prevalent in the scenarios even when emissions reach net-zero. Finally, residual emissions and offsetting negative emissions are not evenly distributed across world regions, which may have important implications for negotiations on burden-sharing, human development, and equity.

Pathways of China's PM2.5 air quality 2015–2060 in the context of carbon neutrality

Clean air policies in China have substantially reduced particulate matter (PM_2.5) air pollution in recent years, primarily by curbing end-of-pipe emissions. However, reaching the level of the World Health Organization (WHO) guidelines may instead depend upon the air quality co-benefits of ambitious climate action. Here, we assess pathways of Chinese PM_2.5 air quality from 2015 to 2060 under a combination of scenarios that link global and Chinese climate mitigation pathways (i.e. global 2°C- and 1.5°C-pathways, National Determined Contributions (NDC) pledges and carbon neutrality goals) to local clean air policies. We find that China can achieve both its near-term climate goals (peak emissions) and PM_2.5 air quality annual standard (35 μg/m³) by 2030 by fulfilling its NDC pledges and continuing air pollution control policies. However, the benefits of end-of-pipe control reductions are mostly exhausted by 2030, and reducing PM_2.5 exposure of the majority of the Chinese population to below 10 μg/m³ by 2060 will likely require more ambitious climate mitigation efforts such as China's carbon neutrality goals and global 1.5°C-pathways. Our results thus highlight that China's carbon neutrality goals will play a critical role in reducing air pollution exposure to the level of the WHO guidelines and protecting public health.

Enhanced secondary pollution offset reduction of primary emissions during COVID-19 lockdown in China

To control the spread of the 2019 novel coronavirus (COVID-19), China imposed nationwide restrictions on the movement of its population (lockdown) after the Chinese New Year of 2020, leading to large reductions in economic activities and associated emissions. Despite such large decreases in primary pollution, there were nonetheless several periods of heavy haze pollution in eastern China, raising questions about the well-established relationship between human activities and air quality. Here, using comprehensive measurements and modeling, we show that the haze during the COVID lockdown was driven by enhancements of secondary pollution. In particular, large decreases in NO_x emissions from transportation increased ozone and nighttime NO₃ radical formation, and these increases in atmospheric oxidizing capacity in turn facilitated the formation of secondary particulate matter. Our results, afforded by the tragic natural experiment of the COVID-19 pandemic, indicate that haze mitigation depends upon a coordinated and balanced strategy for controlling multiple pollutants.

Satellite-based estimates of decline and rebound in China's CO2 emissions during COVID-19 pandemic

Changes in CO₂ emissions during the COVID-19 pandemic have been estimated from indicators on activities like transportation and electricity generation. Here, we instead use satellite observations together with bottom-up information to track the daily dynamics of CO₂ emissions during the pandemic. Unlike activity data, our observation-based analysis deploys independent measurement of pollutant concentrations in the atmosphere to correct misrepresentation in the bottom-up data and can provide more detailed insights into spatially explicit changes. Specifically, we use TROPOMI observations of NO₂ to deduce 10-day moving averages of NO _x and CO₂ emissions over China, differentiating emissions by sector and province. Between January and April 2020, China's CO₂ emissions fell by 11.5% compared to the same period in 2019, but emissions have since rebounded to pre-pandemic levels before the coronavirus outbreak at the beginning of January 2020 owing to the fast economic recovery in provinces where industrial activity is concentrated.

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.

Carbon Monitor, a near-real-time daily dataset of global CO2 emission from fossil fuel and cement production

We constructed a near-real-time daily CO2 emission dataset, the Carbon Monitor, to monitor the variations in CO2 emissions from fossil fuel combustion and cement production since January 1, 2019, at the national level, with near-global coverage on a daily basis and the potential to be frequently updated. Daily CO2 emissions are estimated from a diverse range of activity data, including the hourly to daily electrical power generation data of 31 countries, monthly production data and production indices of industry processes of 62 countries/regions, and daily mobility data and mobility indices for the ground transportation of 416 cities worldwide. Individual flight location data and monthly data were utilized for aviation and maritime transportation sector estimates. In addition, monthly fuel consumption data corrected for the daily air temperature of 206 countries were used to estimate the emissions from commercial and residential buildings. This Carbon Monitor dataset manifests the dynamic nature of CO2 emissions through daily, weekly and seasonal variations as influenced by workdays and holidays, as well as by the unfolding impacts of the COVID-19 pandemic. The Carbon Monitor near-real-time CO2 emission dataset shows a 8.8% decline in CO2 emissions globally from January 1st to June 30th in 2020 when compared with the same period in 2019 and detects a regrowth of CO2 emissions by late April, which is mainly attributed to the recovery of economic activities in China and a partial easing of lockdowns in other countries. This daily updated CO2 emission dataset could offer a range of opportunities for related scientific research and policy making.

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%.

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%.

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%.

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%.

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.

Effects of Deep Reductions in Energy Storage Costs on Highly Reliable Wind and Solar Electricity Systems

We use 36 years (1980-2015) of hourly weather data over the contiguous United States (CONUS) to assess the impact of low-cost energy storage on highly reliable electricity systems that use only variable renewable energy (VRE; wind and solar photovoltaics). Even assuming perfect transmission of wind and solar generation aggregated over CONUS, energy storage costs would need to decrease several hundred-fold from current costs (to ∼$1/kWh) in fully VRE electricity systems to yield highly reliable electricity without extensive curtailment of VRE generation. The role of energy storage changes from high-cost storage competing with curtailment to fill short-term gaps between VRE generation and hourly demand to near-free storage serving as seasonal storage for VRE resources. Energy storage faces "double penalties" in VRE/storage systems: with increasing capacity, (1) the additional storage is used less frequently and (2) hourly electricity costs would become less volatile, thus reducing price arbitrage opportunities for the additional storage.

The Unprecedented Stock Market Reaction to COVID-19

No previous infectious disease outbreak, including the Spanish Flu, has affected the stock market as forcefully as the COVID-19 pandemic. In fact, previous pandemics left only mild traces on the U.S. stock market. We use text-based methods to develop these points with respect to large daily stock market moves back to 1900 and with respect to overall stock market volatility back to 1985. We also evaluate potential explanations for the unprecedented stock market reaction to the COVID-19 pandemic. The evidence we amass suggests that government restrictions on commercial activity and voluntary social distancing, operating with powerful effects in a service-oriented economy, are the main reasons the U.S. stock market reacted so much more forcefully to COVID-19 than to previous pandemics in 1918–1919, 1957–1958, and 1968.

Enhanced secondary pollution offset reduction of primary emissions during COVID-19 lockdown in China

To control the spread of the 2019 novel coronavirus (COVID-19), China imposed nationwide restrictions on the movement of its population (lockdown) after the Chinese New Year of 2020, leading to large reductions in economic activities and associated emissions. Despite such large decreases in primary pollution, there were nonetheless several periods of heavy haze pollution in eastern China, raising questions about the well-established relationship between human activities and air quality. Here, using comprehensive measurements and modeling, we show that the haze during the COVID lockdown was driven by enhancements of secondary pollution. In particular, large decreases in NO_x emissions from transportation increased ozone and nighttime NO₃ radical formation, and these increases in atmospheric oxidizing capacity in turn facilitated the formation of secondary particulate matter. Our results, afforded by the tragic natural experiment of the COVID-19 pandemic, indicate that haze mitigation depends upon a coordinated and balanced strategy for controlling multiple pollutants.

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.

Global supply-chain effects of COVID-19 control measures

Countries have sought to stop the spread of coronavirus disease 2019 (COVID-19) by severely restricting travel and in-person commercial activities. Here, we analyse the supply-chain effects of a set of idealized lockdown scenarios, using the latest global trade modelling framework. We find that supply-chain losses that are related to initial COVID-19 lockdowns are largely dependent on the number of countries imposing restrictions and that losses are more sensitive to the duration of a lockdown than its strictness. However, a longer containment that can eradicate the disease imposes a smaller loss than shorter ones. Earlier, stricter and shorter lockdowns can minimize overall losses. A 'go-slow' approach to lifting restrictions may reduce overall damages if it avoids the need for further lockdowns. Regardless of the strategy, the complexity of global supply chains will magnify losses beyond the direct effects of COVID-19. Thus, pandemic control is a public good that requires collective efforts and support to lower-capacity countries.

Climate adaptation by crop migration

Many studies have estimated the adverse effects of climate change on crop yields, however, this literature almost universally assumes a constant geographic distribution of crops in the future. Movement of growing areas to limit exposure to adverse climate conditions has been discussed as a theoretical adaptive response but has not previously been quantified or demonstrated at a global scale. Here, we assess how changes in rainfed crop area have already mediated growing season temperature trends for rainfed maize, wheat, rice, and soybean using spatially-explicit climate and crop area data from 1973 to 2012. Our results suggest that the most damaging impacts of warming on rainfed maize, wheat, and rice have been substantially moderated by the migration of these crops over time and the expansion of irrigation. However, continued migration may incur substantial environmental costs and will depend on socio-economic and political factors in addition to land suitability and climate.

Multispectral singlet oxygen and photosensitizer luminescence dosimeter for continuous photodynamic therapy dose assessment during treatment

SIGNIFICANCE

Photodynamic therapy (PDT) involves complex light-drug-pathophysiology interactions that can be affected by multiple parameters and often leads to large variations in treatment outcome from patient to patient. Direct PDT dosimetry technologies have been sought to optimize the control variables (e.g., light dose, drug administration, tissue oxygenation, and patient conditioning) for best patient outcomes. In comparison, singlet oxygen (O21) dosimetry has been tested in various forms to provide an accurate and perhaps comprehensive prediction of the treatment efficacy.

AIM

We discuss an advanced version of this approach provided by a noninvasive, continuous wave dosimeter that can measure near-infrared spectrally resolved luminescence of both photosensitizer (PS) and O21 generated during PDT cancer treatment.

APPROACH

This dosimetry technology uses an amplified, high quantum efficiency InGaAs detector with spectroscopic decomposition during the light treatment to continuously extract the maximum signal of O21 phosphorescence while suppressing the strong PS luminescence background by spectrally fitting the data points across nine narrow band wavelengths. O21 and PS luminescence signals were measured in vivo in FaDu xenograft tumors grown in mice during PDT treatment using Verteporfin as the PS and a continuous laser treatment at 690 nm wavelength.

RESULTS

A cohort of 19 mice was used and observations indicate that the tumor growth rate inhibition showed a stronger correlation with O21 than with just the PS signal.

CONCLUSIONS

These results suggest that O21 measurement may be a more direct dosimeter of PDT damage, and it has potential value as a definitive diagnostic for PDT treatment, especially with spectral separation of the background luminescence and online estimation of the PS concentration.

Global urban expansion offsets climate-driven increases in terrestrial net primary productivity

The global urbanization rate is accelerating; however, data limitations have far prevented robust estimations of either global urban expansion or its effects on terrestrial net primary productivity (NPP). Here, using a high resolution dataset of global land use/cover (GlobeLand30), we show that global urban areas expanded by an average of 5694 km² per year between 2000 and 2010. The rapid urban expansion in the past decade has in turn reduced global terrestrial NPP, with a net loss of 22.4 Tg Carbon per year (Tg C year⁻¹). Although small compared to total terrestrial NPP and fossil fuel carbon emissions worldwide, the urbanization-induced decrease in NPP offset 30% of the climate-driven increase (73.6 Tg C year⁻¹) over the same period. Our findings highlight the urgent need for global strategies to address urban expansion, enhance natural carbon sinks, and increase agricultural productivity.

Robust estimates of either urban expansion worldwide or the effects of such phenomenon on terrestrial net primary productivity (NPP) are lacking. Here the authors used the new dataset of global land use to show that the global urban areas expanded largely between 2000 and 2010, which in turn reduced terrestrial NPP globally.

Inequality of household consumption and air pollution-related deaths in China

Substantial quantities of air pollution and related health impacts are ultimately attributable to household consumption. However, how consumption pattern affects air pollution impacts remains unclear. Here we show, of the 1.08 (0.74–1.42) million premature deaths due to anthropogenic PM_2.5 exposure in China in 2012, 20% are related to household direct emissions through fuel use and 24% are related to household indirect emissions embodied in consumption of goods and services. Income is strongly associated with air pollution-related deaths for urban residents in which health impacts are dominated by indirect emissions. Despite a larger and wealthier urban population, the number of deaths related to rural consumption is higher than that related to urban consumption, largely due to direct emissions from solid fuel combustion in rural China. Our results provide quantitative insight to consumption-based accounting of air pollution and related deaths and may inform more effective and equitable clean air policies in China.

Considering air pollution-induced health risks from a consumption perspective is important. Here the authors evaluated the premature deaths resulting from household consumption across 30 Chinese provinces and find that rural households can cause a similar number of pollution-induced deaths as urban households despite a larger and wealthier urban population, due to the combustion of solid fuel.

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.

Decreases in global beer supply due to extreme drought and heat

Beer is the most popular alcoholic beverage in the world by volume consumed, and yields of its main ingredient, barley, decline sharply in periods of extreme drought and heat. Although the frequency and severity of drought and heat extremes increase substantially in range of future climate scenarios by five Earth System Models, the vulnerability of beer supply to such extremes has never been assessed. We couple a process-based crop model (decision support system for agrotechnology transfer) and a global economic model (Global Trade Analysis Project model) to evaluate the effects of concurrent drought and heat extremes projected under a range of future climate scenarios. We find that these extreme events may cause substantial decreases in barley yields worldwide. Average yield losses range from 3% to 17% depending on the severity of the conditions. Decreases in the global supply of barley lead to proportionally larger decreases in barley used to make beer and ultimately result in dramatic regional decreases in beer consumption (for example, -32% in Argentina) and increases in beer prices (for example, +193% in Ireland). Although not the most concerning impact of future climate change, climate-related weather extremes may threaten the availability and economic accessibility of beer.