High CO2 Emissions Research Articles

Designing Retirement Strategies for Coal-Fired Power Plants To Mitigate Air Pollution and Health Impacts.

Retiring coal power plants can reduce air pollution and health damages. However, the spatial distribution of those impacts remains unclear due to complex power system operations and pollution chemistry and transport. Focusing on coal retirements in Pennsylvania (PA), we analyze six counterfactual scenarios for 2019 that differ in retirement targets (e.g., reducing 50% of coal-based installed capacity vs generation) and priorities (e.g., closing plants with higher cost, closer to Environmental Justice Areas, or with higher CO2 emissions). Using a power system model of the PJM Interconnection, we find that coal retirements in PA shift power generation across PA and Rest of PJM, leading to scenario-varying changes in the plant-level release of air pollutants. Considering pollution transport and the size of the exposed population, these emissions changes, in turn, give rise to a reduction of 6-136 PM2.5-attributable deaths in PJM across the six scenarios, with most reductions occurring in PA. Among our designed scenarios, those that reduce more coal power generation yield greater aggregate health benefits due to air quality improvements in PA and adjacent downwind regions. In addition, comparing across the six scenarios evaluated in this study, vulnerable populations─in both PA and Rest of PJM─benefit most in scenarios that prioritize plant closures near Environmental Justice Areas in PA. These results demonstrate the importance of considering cross-regional linkages and sociodemographics in designing equitable retirement strategies.

Effects of flame impingement on the stability and NO/CO emissions of laminar premixed methane-ammonia impinging flame

This study investigates the stable combustion range and CO/NO emissions of laminar premixed CH4-NH3 impinging flames experimentally. Effects of flame impingement on the flame stability and CO/NO formations are analyzed quantitatively. The result shows that the flame impingement improves the flame stability considerably through decelerating the unburned gases velocity in the stagnation region, with smaller nozzle-to-wall distance (H) exerting stronger improvement on the flame stability. The NO emission is increased initially but dropped finally with the increased H. This trend is ascribed to the suppressed NO productions at both small and large H due to the intensive cooling effects of cold wall and ambient air entrainment respectively in consideration of the relatively inferior reactivity of NH3. Additionally, due to the insufficient oxidizer in the fuel-rich flame, the more NH3 molecule can also facilitate the NO destruction via the DeNOx pathways at small or large H. In contrast, the CO emissions show similar variation trends with H like the NO emission for the fuel-lean and stoichiometric flames, while the CO emission has a “N” type variation trend with H for the fuel-rich flames. Since the CH4 reactivity can be improved by the NH3 addition at low temperatures, a low-temperature environment at small H due to the strong cooling effect, as well as more available NH3 in the flame, can effectively highlight the improvement of NH3 on the CH4 reactivity in the fuel-rich flame. This makes for the CO production at small H combined with the insufficient oxidizer and eventually results in the higher CO emission of the fuel-rich flame at small H. Additionally, the decreased CO emission at large H results from the improved CO oxidation that is caused by the increased residence time and more oxidizer from ambient air.

CDP (carbon disclosure project) emissions of CO2 and environmental disclosure quality: the mediating role of media legitimacy and governance

ABSTRACT The paper assesses the relation between firms’ CO2 emissions as per the CDP (formerly known as Carbon Disclosure Project) platform and their environmental disclosure quality, as mediated by two monitoring mechanisms: media legitimacy (external) and firm governance (internal). Legitimacy theory as well as the monitoring dimension of agency theory underlie the empirical investigation. The sample comprises Canadian and U.S. firms, for which a governance disclosure score and media legitimacy information are available from Bloomberg. Relying on structural equations modelling, results are the following. First, CDP disclosing firms exhibit an environmental disclosure score that is twice as high as non-disclosing firms. Second, media legitimacy, expressed by the Janis-Fadner index, is significantly lower for CDP disclosing firms. This may explain why high CO2 emission firms are less inclined to disclose CDP emission data. Third, the direct effect of the decision to disclose CDP emissions of CO2 (full sample) on environmental disclosure quality is positive and significant. Consistent with our hypotheses, we observe an indirect (mediating) effect on this relationship of media legitimacy (external monitoring) and corporate governance (internal monitoring). This suggests that media legitimacy and corporate governance enhance the positive impact of the decision to disclose CDP emissions of CO2 on environmental disclosure quality. Fourth, the direct effect of CDP emissions of CO2 (reduced sample) and environmental disclosure quality is positive and significant. Also consistent with our hypotheses, we observe an indirect effect on this relationship from media legitimacy and corporate governance.

Application of the wildland fire emissions inventory system to estimate fire emissions on forest lands of the United States

BackgroundForests are significant terrestrial biomes for carbon storage, and annual carbon accumulation of forest biomass contributes offsets affecting net greenhouse gases in the atmosphere. The immediate loss of stored carbon through fire on forest lands reduces the annual offsets provided by forests. As such, the United States reporting includes annual estimates of direct fire emissions in conjunction with the overall forest stock and change estimates as a part of national greenhouse gas inventories within the United Nations Framework Convention on Climate Change. Forest fire emissions reported for the United States, such as the 129 Tg CO2 reported for 2022, are based on the Wildland Fire Emissions Inventory System (WFEIS). Current WFEIS estimates are included in the Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2022 published in 2024 by the United States Environmental Protection Agency. Here, we describe WFEIS the fire emissions inventory system we used to address current information needs, and an analysis to confirm compatibility of carbon mass between estimated forest fire emissions and carbon in forest stocks.ResultsThe summaries of emissions from forests are consistent with previous reports that show rates and interannual variability in emissions and forest land area burned are generally greater in recent years relative to the 1990s. Both emissions and interannual variability are greater in the western United States. The years with the highest CO2 emissions from forest fires on the 48 conterminous states plus Alaska were 2004, 2005, and 2015. In some years, Alaska emissions exceed those of the 48 conterminous states, such as in 2022, for example. Comparison of forest fire emission to forest carbon stocks indicate there is unlikely any serious disconnect between inventory and fire emissions estimates.ConclusionsThe WFEIS system is a user-driven approach made available via a web browser. Model results are compatible with the scope and reporting needs of the annual national greenhouse gas inventories.

Data-Driven Predictive Modeling of Steel Slag Concrete Strength for Sustainable Construction

Conventional concrete causes significant environmental problems, including resource depletion, high CO2 emissions, and high energy consumption. Steel slag aggregate (SSA), a by-product of the steelmaking industry, offers a sustainable alternative due to its environmental benefits and improved mechanical properties. This study examined the predictive power of four modeling techniques—Gene Expression Programming (GEP), an Artificial Neural Network (ANN), Random Forest Regression (RFR), and Gradient Boosting (GB)—to predict the compressive strength (CS) of SSA concrete. Using 367 datasets from the literature, six input variables (cement, water, granulated furnace slag, superplasticizer, coarse aggregate, fine aggregate, and age) were utilized to predict compressive strength. The models’ performance was evaluated using statistical measures such as the mean absolute error (MAE), root mean squared error (RMSE), mean values, and coefficient of determination (R2). Results indicated that the GB model consistently outperformed RFR, GEP, and the ANN, achieving the highest R2 values of 0.99 and 0.96 for the training and testing dataset, respectively, followed by RFR with R2 values of 0.97 (training) and 0.93 (testing), GEP with R2 values of 0.85 (training) and 0.87 (testing), and ANN with R2 values of 0.61 (training) and 0.82 (testing). Additionally, the GB model had the lowest MAE values of 0.79 MPa (training) and 2.61 MPa (testing) and RMSE values of 1.90 MPa (training) and 3.95 MPa (testing). This research aims to advance predictive modeling in sustainable construction through thorough analysis and well-defined conclusions.

Conceptual design and life-cycle environmental and economic assessment of low-carbon cement manufacturing processes

Cement manufacturing, a fundamental process industry characterized by high CO2 emissions, sees over 58% of its emissions stemming from the limestone calcination process. However, this significant source of CO2 has not yet been adequately addressed by most existing cement decarbonization processes. As such, systematic environmental and economic comparisons between different cement processes are essential. This paper proposes a new cement process (NCP) that uses natural gas to react with limestone to reduce CO2 emissions and simultaneously produce high-value-added chemical products (methanol). To explore strategies for further improving the performance of the CO2 emission reduction, two processes are developed, integrating the organic Rankine cycle (ORC) and carbon capture and storage (CCS) units with the traditional cement process (TCP) and the NCP, namely TCP-ORC-CCS and NCP-ORC-CCS respectively. Life cycle assessment (LCA) and economic analysis were performed on the TCP, NCP, TCP-ORC-CCS, and NCP-ORC-CCS processes, revealing their advantages and limitations in different scenarios. LCA adopts the "cradle to gate" system boundary, which includes the whole cement process from ore mining to clinker generation and other processes used for carbon reduction. The LCA results show that four cement processes exhibit different environmental performances when choosing different allocation methods. Under economic allocation, the global warming potential (GWP) of TCP, NCP, TCP-ORC-CCS, and NCP-ORC-CCS are 933, 300, 432, and 194 kgCO2eq/ton·clinker, respectively. The comprehensive analysis indicates that NCP has the best comprehensive economic and environmental performance when natural gas and methanol prices are 332 and 319 $/ton, respectively. The price fluctuation of natural gas and methanol is found to greatly impact the levelized cost of clinker (LCOC) of NCP through sensitivity analysis. NCP is economically preferred over TCP when the price of methanol (MeOH) is at least $76 above approximately two-thirds of the price of methane (CH4). Similarly, NCP-ORC-CCS is more advantageous than TCP-ORC-CCS when the price of MeOH is at least $87 above nearly two-thirds of the price of CH4. This study provides a comprehensive analysis for low-carbon cement process design to achieve CO2 emissions reduction.

Exploring high-emission driving behaviors of heavy-duty diesel vehicles based on engine principles under different road grade levels

To reveal the outstanding high-emission problems that occur when heavy-duty diesel vehicles (HDDV) pass uphill and downhill, this study proposes a method to depict the nitrogen oxides (NOx) and carbon dioxide (CO2) high-emission driving behaviors caused by slopes from the perspective of engine principles. By calculating emission and grade data of HDDV based on on-board diagnostic (OBD) data and digital elevation model (DEM) data, the 262 short trips including uphill, flat-road and downhill are firstly obtained through the rule-based short trip segmentation method, and the significant correlation between the road grade and emissions of the short trips is verified by Kendall's Tau and K-means clustering. Secondly, by comparing the distribution changes of three speed categories (acceleration state, constant speed state and deceleration state), the differences in HDDV operating states under different grade levels are discussed. Finally, the machine learning models (Random Forest, XGBoost and Elastic Net), are used to develop the NOx and CO2 emission estimation model, identifying high-emission driving behaviors, particularly during uphill driving, which showed the highest proportion of high-emission. Explained by the feature importance and SHapley Additive exPlanations (SHAP) model that large accelerator pedal opening, frequent aggressive acceleration, and high engine load have positive effects both on NOx and CO2 emissions. The difference is in the air-fuel ratio that the engine in the rich or slightly lean burning state will increase CO2 emissions and the lean burning state will increase NOx emissions. In addition, due to the uncertainty of the actual uphill, drivers often undergo a rapid “deceleration-uniform-acceleration” process, which significantly contributes to high NOx and CO2 emissions from the engine perspective. The findings provide insights for designing driving strategies in slope scenarios and offer a novel perspective on depicting driving behaviors.

Electrocatalytic Synthesis of Urea

Many industrial chemical processes involve a high-energy demand (often still derived from fossil fuels). Urea is an important chemical for the agricultural industry, which accounts for 70% of the global nitrogen-containing fertilizer usage. Currently, urea is produced by the reaction of liquid NH3 and CO2 [1] in a process known as the Haber-Meiser process. Despite its importance, this process suffers from high energy demand and CO2 emissions, mainly due to the NH3 synthesis step (Haber- Bosch process), which relies on fossil fuel resources. Making urea with electrochemical methods has recently gained interest from the scientific community as this approach provides a way to reduce the high CO2 emissions currently associated with urea production. Among the various nitrogen sources explored for urea electrosynthesis, nitrate (NO3-) is attractive because of its high solubility in water, low dissociation energy and potential to mitigate NO3 − contaminations in water. Even though the mechanism of urea synthesis via CO2 and NO3 - coupling is still controversial and not broadly studied, most reports implicate CO* and NH2* surface intermediates in urea synthesis.[2] Cu is an attractive electrocatalyst as it can reduce CO2 to CO and further products and it is also an active catalyst for the reduction of nitrate to ammonia Previous reports on Cu and Cu-based materials showed that urea can be obtained from NO2 -.[3,4] Early research by Shibata et al. with various catalysts demonstrated that the highest faradaic efficiency towards urea from NO3 - was achieved with a Zn catalyst.[5] In this presentation, I will show our latest results on the development of Cu bimetallic catalysts ( CuRh) for urea electrosysnthesis from CO2 and NO3 -[6,7].

The Impact of Nuclear Energy Consumption, Green Technological Innovation, and Trade Openness on the Sustainable Environment in the USA

Nuclear energy, renewable energy, and alternative energy sources are all crucial for sustainable green energy. However, the existing literature often needs to pay more attention to the role of nuclear energy in achieving sustainable development goals. This study analyzes the impact of green technological innovation, nuclear energy consumption, and trade openness on environmental quality in the US. The authors used the ARDL bounds to identify cointegration relationships, which is appropriate for this study’s dataset as it works well with smaller samples. They also used the Toda–Yamamoto causality test to examine causal links. The ARDL cointegration results indicate a significant long-term relationship between CO2 emissions, green technological innovation, nuclear energy consumption, and trade openness. Green technological innovation has a negative impact on CO2 emissions. Higher nuclear energy consumption is associated with lower CO2 emissions, while greater trade openness is associated with higher CO2 emissions, although these effects are less certain. The results suggest promoting green technological innovation and nuclear energy can be effective strategies for reducing CO2 emissions, while the impact of trade openness requires careful consideration due to its potential to increase emissions.

Impacts of Sea‐Level Rise on Coastal Groundwater Table Simulated by an Earth System Model With a Land‐Ocean Coupling Scheme

AbstractSea‐level rise (SLR) poses a severe threat to the coastal environment through seawater intrusion into freshwater aquifers. The rising groundwater table also exacerbates the risk of pluvial, fluvial, and groundwater flooding in coastal regions. However, current Earth system models (ESMs) commonly ignore the exchanges of water at the land‐ocean interface. To address this gap, we developed a novel land‐ocean hydrologic coupling scheme in a state‐of‐the‐science ESM, the Energy Exascale Earth System Model version 2 (E3SMv2). The new scheme includes the lateral exchange between seawater and groundwater and the vertical infiltration of seawater driven by the SLR‐induced inundation. Simulations were performed with the updated E3SMv2 for the global land‐ocean interface to assess the impacts of SLR on coastal groundwater under a high CO2 emission scenario. By the middle of this century, seawater infiltration on the inundated areas will be the dominant component in the land‐ocean coupling process, while the lateral subsurface flow exchange will be much smaller. The SLR‐induced seawater infiltration will raise the groundwater levels, enhance evapotranspiration, and increase runoff with distinct spatial patterns globally in the future. Although the coupling process is induced by SLR, we found topography and warming temperature have more control on the coupling impacts, probably due to the relatively modest magnitude of SLR during the selected future period. Overall, our study suggests significant groundwater and seawater exchange at the land‐ocean interface, which needs to be considered in ESMs.

Global energy transition: The vital role of cobalt in renewable energy

The metallic minerals (Cobalt & Lithium) are critical for the global transition to renewable energy. In this study, we investigate the impact of Cobalt (as a primary) and Lithium (as a secondary mineral) on the share of renewable electricity generation around the world. We test this hypothesis through a panel dataset of 69 countries from 2007 to 2022. The significant results indicate that, first, Cobalt positively impacts the rise of the share of renewable electricity generation. On the contrary, Lithium does not have an impact. Second, Cobalt played a significant role in increasing the share of renewable electricity generation during the global financial crisis and for China, the biggest importer of Cobalt. Third, Cobalt positively impacts renewable electricity generation in low-CO2 and high-CO2 emission countries. Lithium negatively and positively impacts renewable electricity generation for low-CO2 and high-CO2 emissions. Overall, we conclude that Cobalt plays a key role in renewable electricity generation through storage and enhancement of technologies and innovation. The results provide literary and policy implications for researchers and policy makers.

Decarbonizing transportation: A data-driven examination of ICE vehicle to EV transition

Transportation is one of the sectors with the highest CO2 emissions, accounting for 23% globally and significantly contributing to climate change. To address this challenge, the authorities have proposed new stringent policies that lead to decarbonization. From this perspective, this work proposes a multi-scenario analysis for the electrification of a fleet of private users. The scenarios differ on the type of charging mode adopted: slow charging (charging modes 1 and 2) and fast charging (charging modes 3 and 4). The model aims to identify the percentage of potential users who can shift from Internal Combustion Engine (ICE) to Electric Vehicles (EVs) in different scenarios. Furthermore, the model will highlight the average expenditure of users for charging, highlighting how the cost of energy could be a driver for the electrification of the sector. Finally, the model will allow us to evaluate the savings of up to 220 tons of CO2/year thanks to the electrification of the sector with Long Range vehicles, in best case scenario. The use of a multi-scenario analysis allowed several possible electrification solutions to be explored, highlighting the strengths and weaknesses of the charging mode used, supported by quantitative results. This data-driven approach allows us to identify optimal locations for public charging stations in region of northern Italy region, where the data was sourced, which will help to encourage the switch to EVs.

Modelling the multiple action pathways of projected climate change on the Pacific cod (Gadus macrocephalus) early life stages

Understanding how future ocean conditions will impact early life stages and population recruitment of fishes is critical for adapting fisheries communities to climate change. In this study, we incorporated projected changes in physical and biological ecosystem dynamics from an oceanographic model into a mechanistic individual-based model for larval and juvenile stages of the Pacific cod (Gadus macrocephalus) in the eastern Bering Sea. We particularly investigated the impacts of ocean currents, temperature, prey density, and pCO2 on the hatching success, growth, survival, and spatial distribution of this species during 2021–2100. We evaluated two CO2 emission scenarios: RCP8.5 (high CO2 emissions, low mitigation efforts) and RCP4.5 (medium CO2 emissions and mitigation efforts). We found that the increase in temperature and decrease in prey density were the main drivers of faster growth rates and lower survival through increased starvation by the end of the century. Conversely, pCO2 had negligible impacts, which suggests that this species might be resilient to ocean acidification. The largest effects were observed under the high CO2 emission scenario, while the RCP4.5 projections displayed minimal impacts. We also identified an area with favourable conditions in the southeastern Bering Sea that will likely persist in future decades. This study provides relevant information on the future impacts of climate change on Pacific cod, and our results can be used to implement and inform climate-ready management for this important stock in Alaska.

Multidimensional Scenario Calculations Using Cloud‐Based Co‐Simulation

AbstractAs part of the joint research project Carbon2Chem®, mathematical models are used to simulate operating scenarios of cross‐industry networks, in particular chemical plants in industrial environments with high CO2 emissions. In this context, a cloud‐based distributed co‐simulation is used to enable the parallelized simulation of a large number of different variants. This enables optimal design of the plant networks and the efficient determination of optimal operating conditions. The architecture of this approach is described, and its performance is examined and evaluated.

Achieving climate sustainability in the Republic of Congo: The role of economic growth, biomass energy consumption, rule of law and government effectiveness- a NARDL Approach

This study explores the relationship between economic growth (GDP), biomass energy consumption (BEC), Rule of Law, and Government Effectiveness on climate change (CO2 emissions) in the Republic of Congo from 1990 to 2020. We employed a nonlinear autoregressive distributed Lag (NARDL) model to analyse data from World Bank databases. Higher GDP leads to lower CO2 emissions in the long run. Increased BEC also reduces emissions, but a decrease can have a small negative impact. Interestingly, a stronger Rule of Law and Government Effectiveness is associated with higher CO2 emissions in the short run, potentially due to relaxed environmental regulations. However, a stronger Rule of Law and Government Effectiveness leads to lower emissions in the long run, suggesting a potential shift towards sustainable practices. These findings provide valuable insights for policymakers aiming to achieve economic growth and climate stability in the Republic of Congo.

Kill two birds with one stone: Efficient leaching of germanium and recovery of lignite from germanium-rich lignite by thionyl chloride

Germanium, a critical metal, is predominantly located in lignite and lead–zinc ore. The germanium was commonly extracted from the fly ash of germanium-rich lignite (GRL), however, facing the challenges of specific combustion conditions, low lignite’s thermal efficiency and value, high CO2 emissions, and waste acid treatment. Therefore, in this work, a novel method for directly leaching germanium from the GRL was proposed, facilitating low-carbon extraction under mild conditions, and reducing lignite loss during leaching process. Results showed that leaching germanium from the GRL using thionyl chloride achieved the goals of “kill two birds with one stone”, i.e., leaching efficiency of germanium above 95 wt% and recovery yield of lignite over 95 wt%. Specifically, the theoretical leaching efficiency of germanium reached 99.60 wt% while the recovery yield of lignite reached 86.35 wt%, at the temperature of 20 °C, liquid–solid ratio of 4 mL/g, and leaching time of 6 h. Most of the leached germanium was remained in the aqueous phase after the leaching solution was quenched, facilitating the subsequent separation of germanium. In this study, efficient extraction of germanium from the GRL was achieved with a high recovery yield of lignite, preserving the matrix structure and main composition of lignite. Therefore, this method provides a feasible way for efficient extraction of germanium from lignite with low-carbon emission under mild condition.

CO2 emissions from solid biofuel consumption in rural communities in Durango, Mexico

Objective: the objective of this study was to calculate the amount, in kilotons per year (kt a-1), of CO2 emissions from firewood consumption in rural communities of Durango in managed areas (UMAFOR– Forest Management Units) and at the municipality scale. Design/ Methodology/ Approach: the firewood consumption was determined for each of the UMAFOR areas and the 39 municipalities into which the state of Durango is divided. Greenhouse Inventory Software® was used to determine CO2 emissions. Results: the annual CO2 balance due to firewood consumption in Durango was 268.05 kt of CO2. These emissions in relation to the national scale represent 1.52% per year. Those UMAFOR and the municipalities that are geographically located in the semi-arid zone of the state of Durango were those with the higher CO2 emissions. Findings/ Conclusions: it is necessary to couple the consumption of firewood with eco-technologies that favor its efficient consumption, thus mitigating CO2 emissions.

Enhancing carbon sequestration efficiency and safety through albumin-optimized CO2 hydrate distribution and geological layer stability: An innovative approach

The persistently high global CO2 emissions are exacerbating the greenhouse effect issue. Scientists have explored methods such as carbon sequestration via subsea hydrate formation in response to global warming. However, this method faces a series of challenges when injecting CO2 on a large scale, including the slow formation rate of CO2 hydrates and potential leakage risks. Specially, the direct injection of promoters could lead to excessively high concentrations of additives close to the injection wells. This would consequently accelerate the local hydrate conversion, potentially causing reservoir blockage problems. The current study proposes a novel strategy involving additives that exhibit varying effects with concentrations. The high-concentration areas close to the wellbore can maintain the permeability by inhibiting hydrate formation; while the reduced concentration further away upon gas migration facilitates the rapid formation of CO2 hydrates. We successfully demonstrate the spatial and temporal differences in hydrate formation when using such additives. This can also facilitate the rapid formation of a dense hydrate cap layer over the reservoir, potentially preventing the leakage of CO2 gas. A new type of additive based on egg albumin was developed, which possesses the dual function and exhibits good biocompatibility and specific reservoir stability.

Techno-economic and environmental analysis of hybrid energy systems for remote areas: A sustainable case study in Bangladesh

This study provides a comprehensive evaluation of the techno-economic and environmental performance of six hybrid energy systems (HESs) in Kunder Char, Bangladesh, incorporating both conventional (diesel and natural gas) and renewable energy sources (solar and wind). Using HOMER Pro software, a comparative analysis of five off-grid systems and one on-grid system are conducted for assessing their cost-effectiveness, energy efficiencies, and environmental impacts under various sensitivity conditions. After thorough evaluation the on-grid system has emerged as the most economically viable option, with a levelized cost of energy (LCOE) of $0.0436/kWh and a net present cost (NPC) of $1.43 million. It also produced minimal waste energy (0.381 %) but with high CO2 emissions. In contrast, the PV-Battery setup, though the most expensive with an LCOE of $0.266/kWh and an NPC of $3.36 million, offered the benefit of zero emissions and generated 40 % excess electricity. Sensitivity analyses highlighted the influence of solar radiation (4.45 kWh/m2/day), wind speed (4.81 m/s), and fuel price (Diesel: $1/L) on these systems, providing insights into their operational dynamics under varying environmental and economic scenarios. The findings highlight the trade-offs between cost, sustainability, and efficiency, promoting energy solutions customized to meet the specific needs of remote regions like Kunder Char. This study also helps in understanding the potential of hybrid systems to meet energy demands sustainably in challenging geographical and economic landscapes.

Transforming waste to wealth: Impact of food waste‐derived soil amendments and synthetic nitrogen fertilizer on soil dynamics

AbstractApproximately one‐third of all food produced globally goes to waste, highlighting the need for sustainable waste management technologies like composting and anaerobic digestion. These technologies convert food waste into soil amendment products such as compost, liquid digestate (LD) and solid digestate (SD). However, these food waste‐derived soil amendments have relatively low nutrient contents compared with synthetic nitrogen (N) fertilizers such as urea, making their agricultural use challenging. Despite this, food waste‐derived soil amendments can enhance the physical and biological properties of soil, potentially creating synergistic effects when combined with synthetic N fertilizers. This study aimed to investigate effects of food waste‐derived amendments in soil applied at 50 kg ha−1 total N (compost, LD or SD) and synthetic N fertilizer [urea ammonium nitrate (UAN)] at 50 and 100 kg ha−1 total N. Over 56 days of soil incubation, greenhouse gases (CO2, N2O), soil chemistry (–N, –N, pH) and microbial biomass C (MBC) were measured. Results showed that LD + UAN 50 reduced cumulative N2O emissions by 23% compared with UAN 100, despite having the same total N and similar available N rate applied to soil. Replacing UAN with LD in farming practices can supply equivalent available N while lowering N2O emissions, offering a sustainable nutrient strategy. Moreover, applying food waste‐derived soil amendments can enhance N retention in soils, reducing the need for increased applications of synthetic N fertilizers to compensate for N deficits in farming. Food waste‐derived soil amendments can also act as a slower N release compared with UAN, reducing nitrogen run‐off. SD had the highest CO2 emissions, followed by LD and compost. SD + UAN 50 increased MBC levels because of higher carbon content and labile carbon, and available N because of the application of UAN. The major drawback of using SD compared with LD is that the process of evaporating LD to form SD causes high ammonia volatilization (ammonium in solution into ammonia gas) rates, reducing the available N in SD. Therefore, future studies should explore strategies to reduce ammonia volatilization of LD.