IoT-based monitoring system and air quality prediction using machine learning for a healthy environment in Cameroon.

This paper is aimed at developing an air quality monitoring system using machine learning (ML), Internet of Things (IoT), and other elements to predict the level of particulate matter and gases in the air based on the air quality index (AQI). It is an air quality assessor and therefore a means of achieving the Sustainable Development Goals (SDGs), in particular, SDG 3.9 (substantial reduction of the health impacts of hazardous substances) and SDG 11.6 (reduction of negative impacts on cities and populations). AQI quantifies and informs the public about air pollutants and their adverse effects on public health. The proposed air quality monitoring device is low-cost and operates in real-time. It consists of a hardware unit that detects various pollutants to assess air quality as well as other airborne particles such as carbon dioxide (CO2), methane (CH4), volatile organic compounds (VOCs), nitrogen dioxide (NO2), carbon monoxide (CO), and particulate matter with an aerodynamic diameter of 2.5 microns or less (PM2.5). To predict air quality, the device was deployed from November 1, 2022, to February 4, 2023, in certain bauxite-rich areas of Adamawa and certain volcanic sites in western Cameroon. Therefore, machine learning algorithm models, namely, multiple linear regression (MLR), support vector regression (SVR), random forest regression (RFR), XGBoost (XGB), and K-nearest neighbors (KNN) were applied to analyze the collected concentrations and predict the future state of air quality. The performance of these models was evaluated using mean absolute error (MAE), coefficient of determination (R-square), and root mean square error (RMSE). The obtained data in this study show that these pollutants are present in selected localities albeit to different extents. Moreover, the AQI values obtained range from 10 to 530, with a mean of 132.380 ± 63.705, corresponding to moderate air quality state but may induce an adverse effect on sensitive members of the population. This study revealed that XGB regression performed better in air quality forecasting with the highest R-squared (test score of 0.9991 and train score of 0.9999) and lowest RMSE (test score of 1.5748 and train score of 0. 0073) and MAE (test score of 0.0872 and train score of 0.0020), while the KNN model had the worst prediction (lowest R-squared and highest RMSE and MAE). This embryonic work is a prototype for projects in Cameroon as measurements are underway for a national spread over a longer period of time.

Using CO2 and oxidants for in situ regeneration of permeable reactive barriers for leachate-contaminated groundwater.

Groundwater contamination near landfills is commonly caused by leachate leakage, and permeable reactive barriers (PRBs) are widely used for groundwater remediation. However, the deactivation and blockage of the reactive medium in PRBs limit their long-term effectiveness. In the current study, a new methodology was proposed for the in situ regeneration of PRB to remediate leachate-contaminated groundwater. CO2 coupled with oxidants was applied for the dispersion and regeneration of the fillers; by injecting CO2 to disperse the fillers, the permeability of the PRB was increased and the oxidants could flow evenly into the PRB. The results indicate that the optimum filler proportion was zero-valent iron (ZVI)/zeolites/activated carbon (AC) = 3:8:10 and the optimum oxidant proportion was COD/Na2S2O8/H2O2/Fe2+ = 1:5:6:5; the oxidation system of Fe2+/H2O2/S2O82- has a high oxidation efficiency and persistence. The average regeneration rate of zeolites was 72.71%, and the average regeneration rate of AC was 68.40%; the permeability of PRB also increased. This technology is effective for the remediation of landfills in China that have large contaminated areas, an uneven pollutant concentration distribution, and a long pollution duration. The purification mode of long-term adsorption and short-time in situ oxidation can be applied to the remediation of long-term high-concentration organically polluted groundwater, where pollution sources are difficult to cut off.

Can China's carbon generalized system of preferences reduce urban residents' carbon emissions? Evidence from a quasi-natural experiment.

The carbon generalized system of preferences (CGSP) is an innovative incentive mechanism implemented by the Chinese government, which has also become an important part of carbon emission reduction at the living end, and it is of great significance to study whether the Pilot Policy can reduce the carbon emissions of residents. This study firstly accounts for the total carbon emissions and per capita carbon emissions of the residents of 284 cities in China, and on this basis, adopts the SCM method to quantitatively study and analyze the overall and local implementation effects of CGSP in China by taking the first batch of CGSP pilots in China as an example, and further applies the mediation effect model to test the pathways of the role of CGSP. The main findings of the study are as follows: (1) During the period of 2010-2020, the total carbon emissions from urban residents' living in China showed a yearly growth trend, from 36,623.98 ×10-2Mt in 2010-85,241.20 ×10-2Mt in 2020, an increase of 8.83%. Total carbon emissions present a structural difference of "electricity consumption > central heating > private transport > gas (oil, natural gas) consumption". (2) Overall, the implementation of the CGSP had a robust positive impact on the overall carbon emission reduction in the pilot cities, with an average annual emission reduction effect value of 36.53 ×10-2Mt. Locally, the annual net policy effect values of Dongguan, Zhongshan, Heyuan, and Guangzhou are 6169.79 ×10-2, 26,600.17 ×10-2, 17,081.34 ×10-2 and 9393.36 ×10-2Mt respectively. (3) CGSP has a good carbon emission reduction effect by suppressing the impact on residents' carbon emissions through enhancing the city's innovation capacity and promoting electricity saving and consumption reduction, while the mediating effect played by the promotion of green and low-carbon travel in the pilot policy is not significant. Finally, based on the research findings, relevant suggestions are targeted.

Standard vs. carbone dioxide adapted kidney replacement therapy in hypercapnic ARDS patients: a randomized controlled pilot trial (BigBIC).

BACKGROUND: Current continuous kidney replacement therapy (CKRT) protocols ignore physiological renal compensation for hypercapnia. This study aimed to explore feasibility, safety, and clinical benefits of pCO2-adapted CKRT for hypercapnic acute respiratory distress syndrome (ARDS) patients with indication for CKRT. METHODS: We enrolled mechanically ventilated hypercapnic ARDS patients (pCO2 > 7.33 kPa) receiving regional citrate anticoagulation (RCA) based CKRT in a prospective, randomized-controlled pilot-study across five intensive care units at the Charité-Universitätsmedizin Berlin, Germany. Patients were randomly assigned 1:1 to the control group with bicarbonate targeted to 24 mmol/l or pCO2-adapted-CKRT with target bicarbonate corresponding to physiological renal compensation. Study duration was six days. Primary outcome was bicarbonate after 72 h. Secondary endpoints included safety and clinical endpoints. Endpoints were assessed in all patients receiving treatment. RESULTS: From September 2021 to May 2023 40 patients (80% male) were enrolled. 19 patients were randomized to the control group, 21 patients were randomized to pCO2-adapted-CKRT. Five patients were excluded before receiving treatment: three in the control group (consent withdrawal, lack of inclusion criteria fulfillment (n = 2)) and two in the intervention group (lack of inclusion criteria fulfillment, sudden unexpected death) and were therefore not included in the analysis. Median plasma bicarbonate 72 h after randomization was significantly higher in the intervention group (30.70 mmol/l (IQR 29.48; 31.93)) than in the control group (26.40 mmol/l (IQR 25.63; 26.88); p < 0.0001). More patients in the intervention group received lung protective ventilation defined as tidal volume < 8 ml/kg predicted body weight. Thirty-day mortality was 10/16 (63%) in the control group vs. 8/19 (42%) in the intervention group (p = 0.26). CONCLUSION: Tailoring CKRT to physiological renal compensation of respiratory acidosis appears feasible and safe with the potential to improve patient care in hypercapnic ARDS. TRIAL REGISTRATION: The trial was registered in the German Clinical Trials Register (DRKS00026177) on September 9, 2021 and is now closed.

Analysis of Photorespiratory Intermediates Under Transient Conditions by Mass Spectrometry.

Photorespiration is an essential process of phototropic organisms caused by the limited ability of rubisco to distinguish between CO2 and O2. To understand the metabolic flux through the photorespiratory pathway, we combined a mass spectrometry-based approach with a shift experiment from elevated CO2 (3000 ppm) to ambient CO2 (390 ppm). Here, we describe a protocol for quantifying photorespiratory intermediates, starting from plant cultivation through extraction and evaluation.

Combining Gas Exchange and Rapid Quenching of Leaf Tissue for Mass Spectrometry Analysis Directly in Gas Exchange Cuvette.

Isotopically nonstationary metabolic flux analysis (INST-MFA) is a powerful technique for studying plant central metabolism, which involves introducing a 13CO2 tracer to plant leaves and sampling the labeled metabolic intermediates during the transient period before reaching an isotopic steady state. The metabolic intermediates involved in the C3 cycle have exceptionally fast turnover rates, with some intermediates turning over many times a second. As a result, it is necessary to rapidly introduce the label and then rapidly quench the plant tissue to determine concentrations in the light or capture the labeling kinetics of these intermediates at early labeling time points. Here, we describe a rapid quenching (0.1-0.5 s) system for 13CO2 labeling experiments in plant leaves to minimize metabolic changes during labeling and quenching experiments. This system is integrated into a commercially available gas exchange analyzer to measure initial rates of gas exchange, precisely control ambient conditions, and monitor the conversion from 12CO2 to 13CO2.

Combining Gas Exchange and Rapid Quenching of Leaf Tissue for Mass Spectrometry and NMR Analysis Using an External Chamber.

We describe here a method to study and manipulate photorespiration in intact illuminated leaves. When the CO2/O2 mole fraction ratio changes, instant sampling is critical, to quench leaf metabolism and thus trace rapid metabolic modification due to gaseous conditions. To do so, we combine 13CO2 labeling and gas exchange, using a large custom leaf chamber to facilitate fast sampling by direct liquid nitrogen spraying. Moreover, the use of a high chamber surface area (about 130 cm2) allows one to sample a large amount of leaf material to carry out 13C-nuclear magnetic resonance (NMR) analysis and complementary analyses, such as isotopic analyses by high-resolution mass spectrometry (by both GC and LC-MS). 13C-NMR gives access to absolute 13C amounts at the specific carbon atom position in the labeled molecules and thereby provides an estimate of 13C-flux of photorespiratory intermediates. Since NMR analysis is not very sensitive and can miss minor metabolites, GC or LC-MS analyses are useful to monitor metabolites at low concentrations. Furthermore, 13C-NMR and high-resolution LC-MS allow to estimate isotopologue distribution in response to 13CO2 labeling while modifying photorespiration activity.

Recent advances on greenhouse gas emissions from wetlands: Mechanism, global warming potential, and environmental drivers.

Greenhouse gas (GHG) emissions from wetlands have exacerbated global warming, attracting worldwide attention. However, the research process and development trends in this field remain unknown. Herein, 1865 papers related to wetlands GHG emissions published from January 2000 to December 2023 were selected, and CiteSpace and VOSviewer were used for bibliometric analysis to visually analyze the publications distribution, research authors, organizations and countries, core journal and keywords, and discussed the research progress, trends and hotspots in the fields. Over the past 24 years, the research has gone through three phases: the "embryonic" stage (2000-2006), the accumulation stage (2007-2014), and the acceleration stage (2015-2023). China has played a pivotal role in this domain, publishing the most papers and working closely with the United States, United Kingdom, Canada, Germany, and Australia. In addition, this study synthesized 311 field observations from 123 publications to analyze the variability in GHG emissions and their driving factors in four different types of natural wetlands. The results suggested that the average carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) fluxes in different wetlands were significantly different. River wetlands exhibited the highest GHG fluxes, while marsh wetlands demonstrated greater global warming potential (GWP). The average CO2, CH4 and N2O fluxes were 60.41 mg m-2·h-1, 2.52 mg m-2·h-1 and 0.05 mg m-2·h-1, respectively. The GWP of Chinese natural wetlands was estimated as 648.72 Tg·CO2-eq·yr-1, and CH4 contributed the largest warming effect, accounting for 57.43%. Correlation analysis showed that geographical location, climate factors, and soil conditions collectively regulated GHG emissions from wetlands. The findings provide a new perspective on sustainable wetland management and reducing GHG emissions.

Performance of wastewater treatment plants in emission of greenhouse gases.

The present work has estimated greenhouse gas emissions in aerobic and anaerobic Wastewater Treatment Plants in Southern Italy. Greenhouse gases emissions from each treatment unit were calculated based on emission factors related to Chemical Oxygen Demand removal for biogenic CO2 and CH4 assessment and on Nitrogen removal for N2O. N2O, biogenic CO2, and CH4 emissions vary for aerobic and anaerobic-based WWTPs respectively from 73 kgCO2eq/PE*y for anaerobic plants to 91 kgCO2eq/PE*y for aerobic plants. In aerobic and anaerobic digestion systems WWTPs the contributions to CO2eq total emissions from N2O, CH4, biogenic CO2, and fossil CO2 are 30 %-33 %, 20 %-29 %, 22 %-25 %, and 26 %-16 %, respectively. N2O emissions from biological processes were found the most contributing sources of greenhouse gases while in the physical processes higher contribution is indirect carbon dioxide related to energy consumption. Compensatory measures are reported to reduce greenhouse gases emissions.

The role of renewable energy and total factor productivity in reducing carbon emissions: A case of top-ranked nations in the renewable energy country attractiveness index.

On the one hand, economies, particularly developing ones, need to grow. On the other hand, climate change is the most pressing issue globally, and nations should take the necessary measures. Such a complex task requires new theoretical and empirical models to capture this complexity and provide new insights. Our study uses a newly developed theoretical framework that involves renewable energy consumption (REC) and total factor productivity (TFP) alongside traditional factors of CO2 emissions. It provides policymakers with border information compared to traditional models, such as the Environmental Kuznets Curve (EKC), being limited to income and population. Advanced panel time series methods are also employed, addressing panel data issues while producing not only pooled but also country-specific results. 20 Renewable Energy Country Attractiveness Index (RECAI) nations are considered in this study. The results show that REC, TFP, and exports reduce CO2 emissions with elasticities of 0.3, 0.4, and 0.3, respectively. Oppositely, income and imports increase emissions with elasticities of 0.8 and 0.3. Additionally, we show that RECAI countries are commonly affected by global and regional factors. Moreover, we find that shocks can create permanent changes in the levels of the factors but only temporary changes in their growth rates. The main policy implication of the findings is that authorities should implement measures boosting TFP and REC. These factors are driven mainly by technological progress, innovation, and efficiency gains. Thus, they can simultaneously reduce emissions while promoting long-run green economic growth, which addresses the complexity mentioned above to some extent.

Path to pollution and carbon reduction synergy from the perspective of the digital economy: Fresh evidence from 292 prefecture-level cities in China.

The digital economy is a crucial focus for realizing the transformation of old and new kinetic energy in China. It is widely integrated with various fields of the economy and society, constantly providing a new dynamic mechanism with synergetic control of environmental pollution and carbon emissions (SCEPCE). Based on panel data from 292 prefecture-level cities in China from 2011 to 2021, this study discusses the spatial effects and mechanisms of the digital economy on the coordinated control of pollutants and carbon emissions. The study found that: (1) The digital economy has direct and indirect influences on the coordinated control of pollutants and carbon emissions. The digital economy can drive reductions in pollutants and carbon dioxide emissions by upgrading industrial structures and transforming energy structures. (2) Green innovation plays an active regulatory role in the digital economy and structural optimization, particularly in the context of SCEPCE. This interference helps mitigate the impact of the digital economy on pollution and carbon emissions. (3) The digital economy has a significant spatial spillover effect on the coordinated control of pollutants and carbon emissions. (4) The influence mechanism of the digital economy on pollution reduction and carbon reduction synergy exhibits geographical heterogeneity, resource endowment heterogeneity. To enhance the synergy of pollution reduction and carbon reduction, it is essential to bolster support and optimise the digital economy at various levels. This includes reinforcing regional balance, considering spatial spillover effects, and enhancing the leading role of developed cities in the region.

Elevated CO2 exacerbates the risk of methylmercury exposure in consuming aquatic products: Evidence from a complex paddy wetland ecosystem.

Elevated CO2 levels and methylmercury (MeHg) pollution are important environmental issues faced across the globe. However, the impact of elevated CO2 on MeHg production and its biological utilization remains to be fully understood, particularly in realistic complex systems with biotic interactions. Here, a complete paddy wetland microcosm, namely, the rice-fish-snail co-culture system, was constructed to investigate the impacts of elevated CO2 (600 ppm) on MeHg formation, bioaccumulation, and possible health risks, in multiple environmental and biological media. The results revealed that elevated CO2 significantly increased MeHg concentrations in the overlying water, periphyton, snails and fish, by 135.5%, 66.9%, 45.5%, and 52.1%, respectively. A high MeHg concentration in periphyton, the main diet of snails and fish, was the key factor influencing the enhanced MeHg in aquatic products. Furthermore, elevated CO2 alleviated the carbon limitation in the overlying water and proliferated green algae, with subsequent changes in physico-chemical properties and nutrient concentrations in the overlying water. More algal-derived organic matter promoted an enriched abundance of Archaea-hgcA and Deltaproteobacteria-hgcA genes. This consequently increased the MeHg in the overlying water and food chain. However, MeHg concentrations in rice and soil did not increase under elevated CO2, nor did hgcA gene abundance in soil. The results reveal that elevated CO2 exacerbated the risk of MeHg intake from aquatic products in paddy wetland, indicating an intensified MeHg threat under future elevated CO2 levels.

Governance effects of pollution reduction and carbon mitigation of carbon emission trading policy in China.

China's carbon emission trading policy plays a crucial role in achieving both its "3060" dual carbon objectives and the United Nations Sustainable Development Goal 13 (SDG 13) on climate action. The policy's effectiveness in reducing pollution and mitigating carbon emissions holds significant importance. This paper investigated whether China's carbon emission trading policy affects pollution reduction (PM2.5 and SO2) and carbon mitigation (CO2) in pilot regions, using panel data from 30 provinces and municipalities in China from 2005 to 2019 and employing a multi-period difference-in-differences (DID) model. Furthermore, it analyzed the heterogeneity of carbon market mechanisms and regional variations. Finally, it examined the governance pathways for pollution reduction and carbon mitigation from a holistic perspective. The results indicate that: (1) China's carbon emission trading policy has reduced CO2 emissions by 18% and SO2 emissions by 36% in pilot areas, with an immediate impact on the "carbon mitigation" effect, while the "pollution reduction" effect exhibits a time lag. (2) Higher carbon trading prices lead to stronger "carbon mitigation" effect, and larger carbon market scales are associated with greater "pollution reduction" effects on PM2.5. Governance effects on pollution reduction and carbon mitigation vary among pilot regions: Carbon markets of Beijing, Chongqing, Shanghai, and Tianjin show significant governance effects in both "pollution reduction" and "carbon mitigation", whereas Guangdong's carbon market exhibits only a "pollution reduction" effect, and Hubei's carbon market demonstrates only a "carbon mitigation" effect. (3) Currently, China's carbon emission trading policy achieves pollution reduction and carbon mitigation through "process management" and "end-of-pipe treatment". This study could provide empirical insights and policy implications for pollution reduction and carbon mitigation, as well as for the development of China's carbon emission trading market.

Real-time emulation of future global warming reveals realistic impacts on the phenological response and quality deterioration in rice.

Decreased production of crops due to climate change has been predicted scientifically. While climate-resilient crops are necessary to ensure food security and support sustainable agriculture, predicting crop growth under future global warming is challenging. Therefore, we aimed to assess the impact of realistic global warming conditions on rice cultivation. We developed a crop evaluation platform, the agro-environment (AE) emulator, which generates diverse environments by implementing the complexity of natural environmental fluctuations in customized, fully artificial lighting growth chambers. We confirmed that the environmental responsiveness of rice obtained in the fluctuation of artificial environments is similar to those exhibited in natural environments by validating our AE emulator using publicly available meteorological data from multiple years at the same location and multiple locations in the same year. Based on the representative concentration pathway, real-time emulation of severe global warming unveiled dramatic advances in the rice life cycle, accompanied by a 35% decrease in grain yield and an 85% increase in quality deterioration, which is higher than the recently reported projections. The transcriptome dynamism showed that increasing temperature and CO2 concentrations synergistically changed the expression of various genes and strengthened the induction of flowering, heat stress adaptation, and CO2 response genes. The predicted severe global warming greatly alters rice environmental adaptability and negatively impacts rice production. Our findings offer innovative applications of artificial environments and insights for enhancing varietal potential and cultivation methods in the future.

A novel method for gas mixing and distribution in multi-chamber embryo incubators.

BACKGROUND: High-quality control of the gas environment in incubators is crucial for in vitro embryo development, which requires high accuracy, fast recovery, and low gas consumption. OBJECTIVE: In this study, we propose a novel gas mixing and distribution system and method as an alternative solution for multi-chamber embryo incubators. METHODS: The system-based embryo incubator enables a controllable gas circulation process and a quantitative supply of CO2 and N2. To determine the optimal parameters for the mixing time and flow rate of the circulated gases, we conducted contrast experiments on the system-based incubator. To evaluate the performance of the gas system in the incubator, we conducted tests under four different initial conditions, simulating various practical application scenarios. Furthermore, we performed a mouse embryo assay to assess the system's effectiveness. RESULTS: The results show that the system achieved a gas concentration accuracy of ± 0.2% (volume fraction) after stabilization, a minimum recovery time of 5 minutes, an average consumption of 8.9 L/d for N2 and 0.83 L/d for CO2 during routine operation, and a blastocyst rate exceeding 90% observed after 96 hours of culture in the incubator. CONCLUSION: The system and method demonstrate a significant advantage in terms of low gas consumption compared to existing incubators, while still maintaining high accuracy and fast recovery.

Abiotic processes control carbon dioxide dynamics in temperate karst lakes.

Inland waters are crucial in the carbon cycle, contributing significantly to the global CO2 fluxes. Carbonate lakes may act as both sources and sinks of CO2 depending on the interactions between the amount of dissolved inorganic carbon (DIC) inputs, lake metabolisms, and geochemical processes. It is often difficult to distinguish the dominant mechanisms driving CO2 dynamics and their effects on CO2 emissions. This study was undertaken in three groundwater-fed carbonate-rich lakes in central Spain (Ruidera Lakes), severely polluted with nitrates from agricultural overfertilization. Diel and seasonal (summer and winter) changes in CO2 concentration (CCO2) DIC, and CO2 emissions-(FCO2)-, as well as physical and chemical variables, including primary production and phytoplanktonic chlorophyll-a were measured. In addition, δ13C-DIC, δ13C-CO2 in lake waters, and δ13C of the sedimentary organic matter were measured seasonally to identify the primary CO2 sources and processes. While the lakes were consistently CCO2 supersaturated and FCO2 was released to the atmosphere during both seasons, the highest CCO2 and DIC were in summer (0.36-2.26 µmol L-1). Our results support a strong phosphorus limitation for primary production in these lakes, which impinges on CO2 dynamics. External DIC inputs to the lake waters primarily drive the CCO2 and, therefore, the FCO2. The δ13C-DIC signatures below -12‰  confirmed the primary geogenic influence on DIC. As also suggested by the high values on the calcite saturation index, the Miller-Tans plot revealed that the CO2 source in the lakes was close to the signature provided by the fractionation of δ13C-CO2 from calcite precipitation. Therefore, the main contribution behind the CCO2 values found in these karst lakes should be attributed to the calcite precipitation process, which is temperature-dependent according to the seasonal change observed in δ13C-DIC values. Finally, co-precipitation of phosphate with calcite could partly explain the observed low phytoplankton production in these lakes and the impact on the contribution to increasing greenhouse gas emissions. However, as eutrophication increases and the soluble reactive phosphorus (SRP) content increases, the co-precipitation of phosphate is expected to be progressively inhibited. These thresholds must be assessed to understand how the CO32- ions drive lake co-precipitation dynamics. Carbonate regions extend over 15% of the Earth's surface but seem essential in the CO2 dynamics at a global scale.

Climate warming accelerates carbon release from foliar litter-A global synthesis.

With over one-third of terrestrial net primary productivity transferring to the litter layer annually, the carbon release from litter serves as a crucial valve in atmospheric carbon dioxide concentrations. However, few quantitative global projections of litter carbon release rate in response to climate change exist. Here, we combined a global foliar litter carbon release dataset (8973 samples) to generate spatially explicitly estimates of the response of their residence time (τ) to climate change. Results show a global mean litter carbon release rate ( k $$ k $$ ) of 0.69 year-1 (ranging from 0.09-5.6 year-1). Under future climate scenarios, global mean τ is projected to decrease by a mean of 2.7% (SSP 1-2.6) and 5.9% (SSP 5-8.5) during 2071-2100 period. Locally, the alleviation of temperature and moisture restrictions corresponded to obvious decreases in τ in cold and arid regions, respectively. In contract, τ in tropical humid broadleaf forests increased by 4.6% under SSP 5-8.5. Our findings highlight the vegetation type as a powerful proxy for explaining global patterns in foliar litter carbon release rates and the role of climate conditions in predicting responses of carbon release to climate change. Our observation-based estimates could refine carbon cycle parameterization, improving projections of carbon cycle-climate feedbacks.

Rising plant demand strengthens nitrogen limitation in tidal marsh.

Nitrogen (N) is a limiting nutrient for primary productivity in most terrestrial ecosystems, but whether N limitation is strengthening or weakening remains controversial because both N sources and sinks are increasing in magnitude globally. Temperate marshes are exposed to greater amounts of external N inputs than most terrestrial ecosystems and more than in preindustrial times owing to their position downstream of major sources of human-derived N runoff along river mouths and estuaries. Simultaneously, ecosystem N demand may also be increasing owing to other global changes such as rising atmospheric [CO2]. Here, we used interannual variability in external drivers and variables related to exogenous supply of N, along with detailed assessments of plant growth and porewater biogeochemistry, to assess the severity of N-limitation, and to determine its causes, in a 14-year N-addition × elevated CO2 experiment. We found substantial interannual variability in porewater [N], plant growth, and experimental N effects on plant growth, but the magnitude of N pools through time varied independently of the strength of N limitation. Sea level, and secondarily salinity, related closely to interannual variability in growth of the dominant plant functional groups which drove patterns in N limitation and in porewater [N]. Experimental exposure of plants to elevated CO2 and years with high flooding strengthened N limitation for the sedge. Abiotic variables controlled plant growth, which determined the strength of N limitation for each plant species and for ecosystem productivity as a whole. We conclude that in this ecosystem, which has an open N cycle and where N inputs are likely greater than in preindustrial times, plant N demand has increased more than supply.