Emission Pathways Research Articles

Temperature, Water Depth, and Flow Velocity Are Important Drivers of Methane Ebullition in a Temperate Lowland Stream

AbstractStreams and rivers are a well‐recognized source of methane (CH4), with high spatiotemporal variability in fluxes. However, CH4 release in form of bubbles (ebullition) is rarely included in current global CH4 emission estimates from lotic ecosystems, due to the lack of reliable models to upscale ebullition. Our study aimed to determine the importance of individual emission pathways (diffusion and ebullition) for total CH4 emissions from a lowland stream with low sediment heterogeneity and explore the relations of ebullition to environmental variables to build a stream ebullition model for this simplified system. We measured CH4 and carbon dioxide (CO2) diffusive emissions and ebullition from a temperate lowland stream in Czech Republic (Central Europe) during the ice‐free season 2021. The studied stream was a significant source of CH4 (mean 260 ± 107 mg CH4 m−2 day−1), with ebullition as a prevailing pathway of CH4 emission (mean 74 ± 7%, range 55%–85%) throughout the whole monitored period. CH4 ebullition showed a high spatiotemporal heterogeneity, with sediment temperature and water depth as the strongest predictors, followed by the interaction between flow velocity and sediment temperature. Our model explained 81% of total variance of CH4 ebullition and suggests that it is possible to model ebullitive fluxes in lowland streams with homogeneous sediments. Since CH4 was an important part of the total CO2‐equivalent emissions from the examined stream, accounting for mean (±SD) 35 ± 7.4%, and ebullition the majority of the CH4 emission, the ability to adequately model ebullition is pertinent for lowland streams.

Bedroom Concentrations and Emissions of Volatile Organic Compounds during Sleep.

Because humans spend about one-third of their time asleep in their bedrooms and are themselves emission sources of volatile organic compounds (VOCs), it is important to specifically characterize the composition of the bedroom air that they experience during sleep. This work uses real-time indoor and outdoor measurements of volatile organic compounds (VOCs) to examine concentration enhancements in bedroom air during sleep and to calculate VOC emission rates associated with sleeping occupants. Gaseous VOCs were measured with proton-transfer reaction time-of-flight mass spectrometry during a multiweek residential monitoring campaign under normal occupancy conditions. Results indicate high emissions of nearly 100 VOCs and other species in the bedroom during sleeping periods as compared to the levels in other rooms of the same residence. Air change rates for the bedroom and, correspondingly, emission rates of sleeping-associated VOCs were determined for two bounding conditions: (1) air exchange between the bedroom and outdoors only and (2) air exchange between the bedroom and other indoor spaces only (as represented by measurements in the kitchen). VOCs from skin oil oxidation and personal care products were present, revealing that many emission pathways can be important occupant-associated emission factors affecting bedroom air composition in addition to direct emissions from building materials and furnishings.

Carbon budget concept and its deviation through the pulse response lens

Abstract. The carbon budget concept states that the global mean temperature (GMT) increase is roughly linearly dependent on cumulative emissions of CO2. The proportionality is measured as the transient climate response to cumulative emissions of carbon dioxide (TCRE). In this paper, the deviations of the carbon budget from the strict linear relationship implied by the TCRE are examined through the lens of a temperature response to an emission pulse (i.e., pulse response) and its relationship with a nonlinear TCRE. Hereby, two sources of deviation are distinguished: emission scenario and climate state dependence. The former stems from the scenario choice, i.e., the specific emission pathway for a given level of cumulative emissions and the latter from the change in TCRE with changing climatic conditions. Previous literature argues for scenario independence using a stylized set of emission scenarios, and offers a way to fit a nonlinear carbon budget equation. This paper shows how the pulse response, viewed as a Green's function, gives a unifying perspective on both scenario and state dependence. Moreover, it provides an optimization program that tests the scenario independence under the full range of emission pathways for a given set of constraints. In a setup chosen in this paper, the deviations stemming from emission pathway choices are less than 10 % of the overall temperature increase and gradually diminish. Moreover, using the pulse response as a Green's function, the scenario-dependent effects of a reduced-complexity climate model were replicated to a high degree, confirming that the behavior of scenario-dependent deviations can be explained and predicted by the shape of the pulse response. Additionally, it is shown that the pulse response changes with climatic conditions, through which the carbon budget state dependency is explained. Using a pulse response as an approximation for a state-dependent TCRE, an alternative method to derive a nonlinear carbon budget equation is provided. Finally, it is shown how different calibrations of a model can lead to different degrees of carbon budget nonlinearities. The analysis is done using FaIRv2.0.0, a simple climate emulator model that includes climate feedback modifying the carbon cycle, along with a one-box model used for comparison purposes. The Green's function approach can be used to diagnose both models' carbon budget scenario dependency, paving the way for future investigations and applications with other and more complex models.

Root proliferation adaptation strategy improved maize productivity in the US Great Plains: Insights from crop simulation model under future climate change

Adaptation measures are essential for reducing the impact of future climate risks on agricultural production systems. The present study focuses on implementing an adaptation strategy to mitigate the impact of future climate change on rainfed maize production in the Eastern Kansas River Basin (EKSRB), an important rainfed maize-producing region in the US Great Plains, which faces potential challenges of future climate risks due to a significant east-to-west aridity gradient. We used a calibrated CERES-Maize crop model to evaluate the impacts of baseline climate conditions (1985–2014), late-term future climate scenarios (under the SSP245 emission pathway and CMIP6 models), and a novel root proliferation adaptation strategy on regional maize yield and rainfall productivity. Changes in the plant root system by increasing the root density could lead to yield benefits, especially under drought conditions. Therefore, we modified the governing equation of soil root growth in the CERES-Maize model to reflect the genetic influence of a maize cultivar to improve root density by proliferation. Under baseline conditions, maize yield values ranged from 6522 to 12,849 kgha−1, with a regional average value of 9270 kgha−1. Projections for the late-term scenario indicate a substantial decline in maize yield (36 % to 50 %) and rainfall productivity (25 % to 42 %). Introducing a hypothetical maize cultivar by employing root proliferation as an adaptation strategy resulted in a 27 % increase in regional maize yield, and a 28 % increase in rainfall productivity compared to the reference cultivar without adaptation. We observed an indication of spatial dependency of maize yield and rainfall productivity on the regional precipitation gradient, with counties towards the east having an implicit advantage over those in the west. These findings offer valuable insights for the US Great Plains maize growers and breeders, guiding strategic decisions to adapt rainfed maize production to the region's impending challenges posed by climate change.

Least-cost and 2 °C-compliant mitigation pathways robust to physical uncertainty, economic paradigms, and intergenerational cost distribution

Each run of an integrated assessment models produces a single mitigation pathway consistent with stated objectives (e.g. maximum temperature) and optimizing some objective function (e.g. minimizing total discounted costs of mitigation). Even though models can be run thousands of times, it is unclear how built-in assumptions constrain the final set of pathways. Here we aim at broadly exploring the space of possible mitigation scenarios for a given mitigation target, and at characterizing the sets of pathways that are (near-)optimal, taking uncertainties into account. We produce an extensive set of CO2 emission pathways that stay below 2 °C of warming using a reduced-form climate-carbon model with a 1000 different physical states. We then identify 18 sets of quasi ‘least-cost’ mitigation pathways, under six assumptions about cost functions and three different cost minimization functions embarking different visions of intergenerational cost distribution. A first key outcome is that the absence or presence of inertia in the cost function plays a pivotal role in the resulting set of least-cost pathways. Second, despite inherent structural differences, we find common pathways across the 18 combinations in 96% of the physical states studied. Interpreting these common pathways as robust economically and in terms of intergenerational distribution, we shed light on some of their characteristics, even though these robust pathways differ for each physical state.

Global Projection of Flood Risk With a Bivariate Framework Under 1.5–3.0°C Warming Levels

AbstractGlobal warming increases the atmospheric water‐holding capacity, consequently altering the frequency, and intensity of extreme hydrological events. River floods characterized by large peak flow or prolonged duration can amplify the risk of social disruption and affect ecosystem stability. However, previous studies have mostly focused on univariate flood magnitude characteristics, such as flood peak or volume, and there is still limited understanding of how these joint flood characteristics (i.e., magnitude and duration) might co‐evolve under different warming levels. Here, we develop a systematical bivariate framework to project future flood risk in 11,528 catchments across the globe. By constructing the joint distribution of flood peak and duration with copulas, we examine global flood risk with a bivariate framework under varying levels of global warming (i.e., within a range of 1.5–3.0°C above pre‐industrial levels). The flood projections are produced by driving five calibrated lumped hydrological models (HMs) using the simulations with bias adjustment of five global climate models (GCMs) under three shared socioeconomic pathways (SSP126, SSP370, and SSP585). On average, global warming from 1.5 to 3.0°C tends to amplify flood peak and lengthen flood duration across almost all continents, but changes are not unidirectional and vary regionally around the globe. The joint return period (JRP) of the historical (1985–2014) 50‐year flood event is projected to decrease to a median with 36 years under a medium emission pathway at the 1.5°C warming level. Finally, we evaluate the drivers of these JRP changes in the future climate and quantify the uncertainty arising from the different GCMs, SSPs, and HMs. Our findings highlight the importance of limiting greenhouse gas emission to slow down global warming and developing climate adaptation strategies to address future flood hazards.

Regional carbon emission pathways under central-local coordination: Objective constraints and collaborative incentives

The commitment of carbon peak and carbon neutrality in China has attracted global attention. In high-emission countries, the coordination between the central and local governments will inevitably influence climate governance. This study establishes the Regional Collaborations Dynamic Integrated model of Climate and Economy, predicting carbon emission pathways and social cost of carbon for regions within China. The design of six scenarios incorporates objective constraints and collaborative incentives to identify the impact of central-local coordination on climate governance. Results indicate that objective constraints will mitigate 0.17–0.60 Gt carbon emissions in all regions, reaching carbon peak 5–10 years earlier. Collaborative incentives will contribute to achieving carbon neutrality for regions in the long term, especially the Yangtze River Economic Belt advancing 7 years. The combination of objective constraints and collaborative incentives will facilitate China reaching carbon peak in 2029 and achieving carbon neutrality in 2057. The social cost of carbon will vary across regions due to socioeconomic conditions, initiative choices, and mitigation efforts. Moreover, the analysis of structural uncertainty can help China to undertake timely climate actions and avoid excessive mitigation costs. Based on these findings, this study proposes policy suggestions to improve climate governance by dynamic objective management, innovative collaborative forms, enhancing synergistic effects.

Warming-Induced Stimulation of Soil N2O Emissions Counteracted by Elevated CO2 from Nine-Year Agroecosystem Temperature and Free Air Carbon Dioxide Enrichment.

Globally, agricultural soils account for approximately one-third of anthropogenic emissions of the potent greenhouse gas and stratospheric ozone-depleting substance nitrous oxide (N2O). Emissions of N2O from agricultural soils are affected by a number of global change factors, such as elevated air temperatures and elevated atmospheric carbon dioxide (CO2). Yet, a mechanistic understanding of how these climatic factors affect N2O emissions in agricultural soils remains largely unresolved. Here, we investigate the soil N2O emission pathway using a 15N tracing approach in a nine-year field experiment using a combined temperature and free air carbon dioxide enrichment (T-FACE). We show that the effect of CO2 enrichment completely counteracts warming-induced stimulation of both nitrification- and denitrification-derived N2O emissions. The elevated CO2 induced decrease in pH and labile organic nitrogen (N) masked the stimulation of organic carbon and N by warming. Unexpectedly, both elevated CO2 and warming had little effect on the abundances of the nitrifying and denitrifying genes. Overall, our study confirms the importance of multifactorial experiments to understand N2O emission pathways from agricultural soils under climate change. This better understanding is a prerequisite for more accurate models and the development of effective options to combat climate change.

Exploring the temporal dynamics of methane ebullition in a subtropical freshwater reservoir.

The transport of methane from sediments to the atmosphere by rising gas bubbles (ebullition) can be the dominant, yet highly variable emission pathway from shallow aquatic ecosystems. Ebullition fluxes have been reported to vary in space and time, as methane production, accumulation, and bubble release from the sediment matrix is affected by several physical and bio-geochemical processes acting at different timescales. Time-series analysis and empirical models have been used for investigating the temporal dynamics of ebullition and its controls. In this study, we analyzed the factors governing the temporal dynamics of ebullition and evaluated the application of empirical models to reproduce these dynamics across different timescales and across different aquatic systems. The analysis is based on continuous high frequency measurements of ebullition fluxes and environmental variables in a mesotrophic subtropical and polymictic freshwater reservoir. The synchronization of ebullition events across different monitoring sites, and the extent to which ebullition was correlated to environmental variables varied throughout the three years of observations and were affected by thermal stratification in the reservoir. Empirical models developed for other aquatic systems could reproduce a limited fraction of the variability in observed ebullition fluxes (R2 < 0.3), however the predictions could be improved by considering additional environmental variables. The model performance depended on the timescale. For daily and weekly time intervals, a generalized additive model could reproduce 70 and 96% of ebullition variability but could not resolve hourly flux variations (R2 = 0.19). Lastly, we discuss the potential application of empirical models for filling gaps in ebullition measurements and for reproducing the main temporal dynamics of the fluxes. The results provide crucial information for emission estimates, and for the development and implementation of strategies targeting at a reduction of methane emissions from inland waters.

The impacts of decarbonization pathways on Sustainable Development Goals in the European Union

Climate action to achieve the Paris Agreement should respect the United Nations Sustainable Development Goals. Here, we use an integrated assessment modelling framework comprising nine climate policy models and quantify the impacts of decarbonisation pathways on Sustainable Development Goals in the European Union at regional and national levels. We show that scenario-consistent assumptions of future socio-economic trends and current climate policies would improve energy- and carbon-related aspects of sustainability and reduce inequalities. Ambitious net-zero emissions pathways would further improve health and agricultural productivity. Furthermore, countries currently lagging in achieving sustainable development goals would see the greatest benefits from ambitious climate action. Negative socio-economic impacts from climate action on poverty, hunger, and economic growth will require specific corrective policies. While our analysis does not quantify the negative effects of less ambitious climate policy, it demonstrates where co-benefits and trade-offs of greenhouse gas mitigation and sustainable development agenda exist and can guide policy formulation.

A harmonized Danube basin-wide multi-compartment concentration database to support inventories of micropollutant emissions to surface waters

BackgroundThe European Water Framework Directive foresees the establishment of emission inventories for micropollutants (MP) to facilitate an evidence-based development of mitigation measures. Regionalized pathway analysis constitutes a moderately data-intensive approach to quantify the contribution of different pathways to the total pollution of surface waters. So far, only few European member states have created an inventory that includes diffuse pathways. The fundamental basis to enable it is an accessible, well-structured and harmonized database with data on the concentration of MPs in multiple compartments, such as soils, groundwater, atmospheric deposition and urban systems. Combined with the water and suspended substance balance in river basins, such data enables the estimation of emission loads via specific pathways. In the Danube River Basin, but in general in Europe, a public data management platform with such scope and criteria is still lacking.ResultsWe collected and harmonized MP measurements across multiple compartments and countries together with key metadata, harmonized and combined them into a new database. The resulting tool, available for download, facilitates the assessment of current data availability, in terms of quantity and quality. For example, while the majority of available data stems from groundwater and surface water, other highly relevant compartments are scarcely represented. By examining differences in MP concentration level across compartments, the database can lead to understand the relevance of specific emission pathways and thus to prioritize data-retrieval and calculation efforts in modelling applications. Selected examples show how to exploit the metadata associated to the measurements to extrapolate the results to regions not covered by specific monitoring programmes. For example, PFAS concentrations in treated wastewater show significant dependence on the design capacity of the treatment plant.ConclusionsThis study showcases how such database can support the setup of emission inventories, guide data providers and national authorities in prioritizing the allocation of resources for new surveys and in optimizing their national data collection and management systems. The process tested showed a great need for enhanced data literacy across countries and institutions to increase data availability and quality to secure the exploitation of the full information potential generated via monitoring programmes.

Ignoring Plant Physiological Responses to Elevated CO2 Will Overestimate Terrestrial Vertebrate Biodiversity Loss Under Global Climate Change

AbstractRising CO2 is accelerating Earth warming and drying by altering the radiation budget (CO2 radiative effect), and it is commonly thought that future biodiversity will be greatly threatened. However, elevated CO2 also modifies plant physiology including photosynthesis rate and water use efficiency (CO2 physiological effect), the impacts of which have been usually ignored. By coupling machine learning techniques and Earth system models, this study considered both of the two effects and simulated terrestrial vertebrate biodiversity changes under moderate CO2 emission pathway. Our results show that the CO2 radiative effect positively impacts terrestrial vertebrate biodiversity at high latitudes but has a negative impact at low latitudes, whereas the physiological effect generally has a positive impact that peaks near the equator. Between 45°N and 45°S, 15% of areas with diminishing terrestrial vertebrate biodiversity due to radiative effect experience a reversal in trend when physiological effect is also considered; species migration pressure is also mitigated. Additionally, the protection priority rankings of 36 biodiversity hotspots need to be readjusted with the consideration of CO2 physiological effect, for which the impacts on terrestrial vertebrate biodiversity are important and varied greatly over space. Overall, our findings highlight the critical impacts of vegetation physiology on terrestrial vertebrate biodiversity in response to elevated atmospheric CO2, which can provide a reference for resource allocation and biodiversity conservation policymaking.

Assessing the impact of climate change on a coastal karst aquifer in a semi-arid area

This study investigates the potential future state of a coastal karst aquifer located in the Salento peninsula of southern Italy, examining the impact of climate change. After a historical and future overview of the climate in the study area, an analysis of meteorological indices (SPIs and SPEIs) and groundwater levels (GWLs) during the historical period revealed a strong correlation between them. Then, straightforward linear regression models were applied to establish relationships between SPIs/SPEIs and GWLs for the analysed wells. To estimate future SPIs and SPEIs, an ensemble of regional climate models was used, and estimates of GWLs until the end of the century were obtained by incorporating these projections into the regression models. Two emission pathways, the RCP4.5 and the RCP8.5, were considered in the analysis. The results based on SPIs suggest no significant changes in future GWLs across all wells. However, when considering also temperature through the use of SPEIs, a general decline in groundwater levels is expected, with the decrease being more pronounced under the RCP8.5.

Identification on the common supply chain paths of CO2 and NOx emissions from the manufacturing industry in China

ABSTRACT Since the ‘Made in China 2025’ initiative was proposed, the transformation and upgrading of China’s manufacturing industry towards a high-end, intelligent, and green status has been accelerated, and the climate change and air pollution issues draw immediate attention. This paper investigated the simultaneous control paths of CO2 and NOx emissions throughout the manufacturing transition in China. Based on environmental input-output analysis, the production- and consumption-based CO2 and NOx emissions in 2015 and 2020 were evaluated, indicating that over 70% of production-side emissions were caused by medium-technology manufacturing, and over 50% of consumption-side emissions came from high-technology manufacturing. Then, the structural path analysis was introduced to extract the synergistic emission pathways of CO2 and NOx. The ‘smelting and pressing of metal sector → construction → investment’ pathway, which produced emissions of 347.71 Mt CO2 and 639.9 Kt NOx in 2015, was identified as the most critical path to achieve manufacturing synergistic reduction. Additionally, investment demand in the construction sector seriously affected the collaborative reduction of CO2 and NOx emissions in supply chains of medium-technology manufacturing. The critical supply chain of high-technology manufacturing for achieving coordinated emission reduction was mainly driven by export demand for chemical products.

Simulated responses and feedbacks of permafrost carbon under future emissions pathways and idealized solar geoengineering scenarios

The carbon-rich northern high-latitude permafrost is a potential climate tipping point. Once triggered, its thawing and release of carbon dioxide and methane might unleash irreversible changes in the Earth’s climate system. We investigate the response of permafrost under three Shared Socioeconomic Pathways (SSPs) with no mitigation (SSP5-8.5), moderate mitigation (SSP2-4.5) and delayed mitigation (SSP5-3.4-OS), and three solar geoengineering scenarios applied to each experiment to prevent global warming from exceeding 2 °C above pre-industrial. The long-term negative emissions in SSP5-3.4-OS preserves much more frozen soil than SSP5-8.5, but shows nearly as much permafrost carbon loss this century as SSP2-4.5 due to its mid-century temperature overshoot. Solar geoengineering to meet the 2 °C target above pre-industrial effectively suppresses permafrost thawing and reduces subsequent carbon release from the soil. However, the carbon emission from permafrost still continues after the temperature is stabilized, due to the decomposition of thawed permafrost carbon. More solar insolation reduction is required to compensate the positive permafrost carbon feedback, which exerts greater impacts on the efficiency of solar geoengineering under a scenario with strong climate policy and lower carbon emissions.

“Seeing” Beneath the Clouds—Machine‐Learning‐Based Reconstruction of North African Dust Plumes

AbstractMineral dust is one of the most abundant atmospheric aerosol species and has various far‐reaching effects on the climate system and adverse impacts on air quality. Satellite observations can provide spatio‐temporal information on dust emission and transport pathways. However, satellite observations of dust plumes are frequently obscured by clouds. We use a method based on established, machine‐learning‐based image in‐painting techniques to restore the spatial extent of dust plumes for the first time. We train an artificial neural net (ANN) on modern reanalysis data paired with satellite‐derived cloud masks. The trained ANN is applied to cloud‐masked, gray‐scaled images, which were derived from false color images indicating elevated dust plumes in bright magenta. The images were obtained from the Spinning Enhanced Visible and Infrared Imager instrument onboard the Meteosat Second Generation satellite. We find up to 15% of summertime observations in West Africa and 10% of summertime observations in Nubia by satellite images miss dust plumes due to cloud cover. We use the new dust‐plume data to demonstrate a novel approach for validating spatial patterns of the operational forecasts provided by the World Meteorological Organization Dust Regional Center in Barcelona. The comparison elucidates often similar dust plume patterns in the forecasts and the satellite‐based reconstruction, but once trained, the reconstruction is computationally inexpensive. Our proposed reconstruction provides a new opportunity for validating dust aerosol transport in numerical weather models and Earth system models. It can be adapted to other aerosol species and trace gases.

Scenarios for Adoption of Low-Carbon Household Cooking Fuels in Biomass-Dependent Informal Settlements of Urban Sub-Saharan Africa: A Critical Analysis of Kisumu City

The use of unclean cooking fuels is widespread in urban informal settlements in Africa, while the adoption of clean fuels is largely done by stacking with traditional biomass fuels. Rapid urbanisation has aggravated the situation since it hampers effective planning for climate action and the provision of clean and affordable cooking fuels. It is, therefore, essential to deploy effective household carbon emissions (HCE) reduction strategies that are cognizant of the fuel use patterns and household dynamics of households in urban informal settlements. This study highlights the status of HCE in Kisumu City’s informal settlements and subsequently explores possible pathways for reducing emissions through the adoption of low-carbon cooking fuels. The paper features existing and plausible emissions scenarios in the informal settlements of Kisumu City. The study adopts a descriptive correlation research design targeting a sample 419 households drawn from seven informal settlements of Kisumu City. Binary logistic regression is used to establish the relationships that exist between household characteristics and the adoption of clean fuels. Multiple linear regression analysis reveals existing and probable emission pathways, informed by varying household characteristics and adjusting fuel-stacking scenarios. Household income has a positive correlation with adoption of clean fuel combinations (p&lt;0.01), while household size does not have a significant relationship with adoption of clean fuels. The annual HCE attributable to cooking in Kisumu City’s informal settlements is 976 KgCO2. Fuel stacking nuances are vital considerations in choosing practical emission reduction pathways for these households. Emission reduction scenario that contemplates transitioning households that use charcoal in their fuel stacks to using LPG has the highest emission reduction potential of 72%. Although an emission scenario that includes LPG in the fuel mix of households that do not use it has an emission reduction potential of just 9%, it is the most realistic option since it accommodates the phenomenon of fuel stacking

Methane dynamics in vegetated habitats in inland waters: quantification, regulation, and global significance

Freshwater ecosystems, including lakes, wetlands, and running waters, are estimated to contribute over half the natural emissions of methane (CH4) globally, yet large uncertainties remain in the inland water CH4 budget. These are related to the highly heterogeneous nature and the complex regulation of the CH4 emission pathways, which involve diffusion, ebullition, and plant-associated transport. The latter, in particular, represents a major source of uncertainty in our understanding of inland water CH4 dynamics. Many freshwater ecosystems harbor habitats colonized by submerged and emergent plants, which transport highly variable amounts of CH4 to the atmosphere but whose presence may also profoundly influence local CH4 dynamics. Yet, CH4 dynamics of vegetated habitats and their potential contribution to emission budgets of inland waters remain understudied and poorly quantified. Here we present a synthesis of literature pertaining CH4 dynamics in vegetated habitats, and we (i) provide an overview of the different ways the presence of aquatic vegetation can influence CH4 dynamics (i.e., production, oxidation, and transport) in freshwater ecosystems, (ii) summarize the methods applied to study CH4 fluxes from vegetated habitats, and (iii) summarize the existing data on CH4 fluxes associated to different types of aquatic vegetation and vegetated habitats in inland waters. Finally, we discuss the implications of CH4 fluxes associated with aquatic vegetated habitats for current estimates of aquatic CH4 emissions at the global scale. The fluxes associated to different plant types and from vegetated areas varied widely, ranging from−8.6 to over 2835.8 mg CH4 m−2 d−1, but were on average high relative to fluxes in non-vegetated habitats. We conclude that, based on average vegetation coverage and average flux intensities of plant-associated fluxes, the exclusion of these habitats in lake CH4 balances may lead to a major underestimation of global lake CH4 emissions. This synthesis highlights the need to incorporate vegetated habitats into CH4 emission budgets from natural freshwater ecosystems and further identifies understudied research aspects and relevant future research directions.

Modulation of Deep-Red to Near-Infrared Room-Temperature Charge-Transfer Phosphorescence of Crystalline "Pyrene Box" Cages by Coupled Ion/Guest Structural Self-Assembly.

Organic cocrystals obtained from multicomponent self-assembly have garnered considerable attention due to their distinct phosphorescence properties and broad applications. Yet, there have been limited reports on cocrystal systems that showcase efficient deep-red to near-infrared (NIR) charge-transfer (CT) phosphorescence. Furthermore, effective strategies to modulate the emission pathways of both fluorescence and phosphorescence remain underexplored. In this work, we dedicated our work to four distinct self-assembled cocrystals called "pyrene box" cages using 1,3,6,8-pyrenetetrasulfonate anions (PTS4-), 4-iodoaniline (1), guanidinium (G+), diaminoguanidinium (A2G+), and hydrated K+ countercations. The binding of such cations to PTS4- platforms adaptively modulates their supramolecular stacking self-assembly with guest molecules 1, allowing to steer the fluorescence and phosphorescence pathways. Notably, the confinement of guest molecule 1 within "pyrene box" PTSK{1} and PTSG{1} cages leads to an efficient deep-red to NIR CT phosphorescence emission. The addition of fuming gases like triethylamine and HCl allows reversible pH modulations of guest binding, which in turn induce a reversible transition of the "pyrene box" cage between fluorescence and phosphorescence states. This capability was further illustrated through a proof-of-concept demonstration in shrimp freshness detection. Our findings not only lay a foundation for future supramolecular designs leveraging weak intermolecular host-guest interactions to engineer excited states in interacting chromophores but also broaden the prospective applications of room-temperature phosphorescence materials in food safety detection.

PM2.5 air quality and health gains in the quest for carbon peaking: A case study of Fujian Province, China

China faces a dual challenge of improving air quality and reducing greenhouse gas (GHG) emissions. Stringent clean air actions gradually narrow the end-of-pipe (EOP) pollution control potential. Meanwhile, pursuing carbon peaking will reduce air pollution and health risks. However, the impact on air quality and health gains in individual Chinese provinces has not been assessed with a specific focus on local policies. Here, typical shared socio-economic pathways (SSPs) and local policies (i.e., business as usual, BAU; end-of-pipe controls, EOP; co-control mitigation, CCM) are combined to set three scenarios (i.e., BAU-SSP3, EOP-SSP4, CCM-SSP1). Under these three scenarios, we couple the Low Emissions Analysis Platform (LEAP) model, an air quality model and health risk assessment methodology to evaluate the characteristics of carbon peaking in Fujian Province. PM2.5 air quality and impacts on public health are assessed, using the metric of the deaths attributable to PM2.5 pollution (DAPP). The results show that energy-related CO2 emissions will only peak before 2030 in the CCM-SSP1 scenario. In this context, air pollutant emission pathways reveal that mitigation is limited under the EOP-SSP4 scenario, necessitating further mitigation under the CCM-SSP1 scenario. The annual average PM2.5 level is projected to be 16.5 μg·m−3 in 2035 with a corresponding decrease in DAPP of 297 (95 % confidence intervals: 217–308) compared with that of 2020. Despite the significant improvements in PM2.5 air quality and health gains under the CCM-SSP1 scenario, reaching the 5 μg·m−3 target of the World Health Organization (WHO) remains difficult. Furthermore, population aging will require stronger PM2.5 mitigation to enhance health gains. This study provides a valuable reference for other developing regions to co-control air pollution and GHGs.