Total CO2 Research Articles

Novel integration and optimization of reliable photovoltaic and biomass integrated system for rural electrification

The novel concept of using hybrid renewable resources to provide clean energy helps to address the unique shortcomings of each renewable source. This study describes an innovative concept about the design of optimal grid PV/biomass 100 % renewable and fully reliable energy systems without considering energy storage devices. By leveraging community solar and biomass resources, the proposed system can power remote villages with a minimum cost of energy. Multi-Objective Genetic Algorithm (MOGA) is employed to perform an optimal procedure. The PV-biomass deployment project's economic viability is assessed using financial metrics such as net present cost (NPC) and cost of energy (COE). In order to install a hybrid system at the chosen site, the optimal configuration (PV 87 kW, biomass1 29 kW, and biomass2 125 kW) was examined. The NPC, COE, and total system cost, in this configuration, are $118,942, $0.02/kWh, and $892,892, respectively. The combined yearly consumption of the biomass1 and biomass2 generators is 704.81 tons of wheat straw. The total annual CO2 emissions of the PV, biomass1, and biomass2 generators in this system are avoided by 729.5 tons. The findings clearly demonstrate that the suggested approach can manage a reliable power flow with a suitable configuration. The solar PV and biomass system examined in this study will probably be a specialized solution in regions with abundant biomass resources; nevertheless, it offers a reliable starting point for the creation of larger-scale bioenergy value chains with the long-term objective of generating electricity from wheat straw biomass materials.

Urban trees' potential for regulatory services in the urban environment: an exploration of carbon sequestration.

Urbanisation has emerged as a formidable challenge for urban policymakers, reaching unparalleled heights and unsettling the ecological equilibrium of the cities. Urban areas now grapple with many issues encompassing climate change, resource depletion, population surges and increased pollution levels. Many planned cities have planted trees and other vegetation within the urban sectors to enhance air quality, mitigate climate effects and provide valuable ecosystem services. This study assessed tree species diversity and their potential for carbon sequestration in Panjab University Campus, Chandigarh. We established 188 plots, each comprising randomly selected quadrats measuring 10 m × 10 m, encompassing areas with varying levels of vegetation, ranging from low to moderate and high density. We used four different allometric equations to estimate tree biomass and carbon stock. Our findings revealed that 92 tree species belong to 72 genera and 35 families, with a total tree density of 975 ha-1. The total CO2 sequestration in form of carbon stock was 18,769.46 Mg C ha-1, with Manilkara hexandra (1239.20 Mg C ha-1), Ficus benghalensis (1072.24 Mg C ha-1), Kigelia pinnata (989.89 Mg C ha-1) and Lagerstroemia floribunda (716.88 Mg C ha-1) being the top contributors. Specifically, the equation of Chave et al. (2005) without tree height yielded the highest biomass and carbon stock estimates than other equations. The present study underscores the vital role of trees on the campus as potent carbon reservoirs meet to maintain an aesthetic sense for biotic components and alleviate rising levels of CO2 in the atmospheric environment. By emphasising the role of urban trees as potent carbon reservoirs, the study underscores the importance of integrating green infrastructure into urban planning strategies. Furthermore, it offers valuable guidance for urban planners. It suggests that strategic tree planting and maintenance can enhance green spaces, regulate temperatures and ultimately support regional and global climate change mitigation goals. Incorporating these findings into urban planning processes can aid policymakers in developing resilient, ecologically sustainable cities worldwide.

Towards low-cost and sustainable activated carbon production: Influence of microwave activation time on yield and CO2 uptake of PET-derived adsorbents

Microwave (MW) heating is proposed as a method to transform polyethylene terephthalate (PET) into porous adsorbents. The yield, textural properties, and CO2 uptake of the PET-derived adsorbents irradiated at different durations (3 – 35 min) at 400 °C were assessed. MW activation time influenced both the physical properties and CO2 uptake capacities of the resulting adsorbents. The yield decreased with activation time, but the surface area, total pore volume, micropore volume, and CO2 uptake capacities all increased with MW activation time before declining. The optimal sample (produced with 5 min of MW activation time) showed improved textural properties as well as higher equilibrium and dynamic CO2 uptakes than the commercial activated carbon used as reference. This adsorbent also possesses good selectivity for CO2 in the binary 10:90%vol/vol CO2: N2 mixture. Additionally, an excellent recyclability over 20 cycles, (Regeneration Efficiency > 97%) was observed, and the CO2 adsorption kinetics best fits Lagergren’s pseudo-second-order model. This study has shown that a low activation temperature (400 °C), a short MW activation time (5 min), and a low amount of chemical agent (KOH, 0.72 M) could produce CO2 adsorbents from a cheap and abundant material (PET-waste) with better CO2 uptake to that of a commercial activated carbon.

Exploring the potential and challenges of phase change materials in future heat storage systems via computations and experiments

The current work describes computational and experimental efforts to enable new heat storage technologies. Approximately 50% of the energy consumed globally is used to generate and manage heat. This is still predominantly acquired from the combustion of fossil fuels, consequently generating just over 40% of the total global CO2 emissions. To achieve a sustainable future, there is a need for sustainable, decarbonised and dependable energy sources. Heat storage is a key technology that could help achieving this goal. Recently published work by the current authors has shown the importance of heat storage in decarbonising heating (and cooling) of buildings using phase change materials (PCMs). The black-box approach followed evaluated the energetic, cost, and environmental impacts of a novel concept PCM storage scheme with microgeneration. The results obtained showed that this system had advantages over current and future competing heating technologies. However, PCM technology remains at low technological readiness levels because of the lack of understanding of the complex heat transfer physics associated with their phase change transition. For example, understanding and characterizing the propagation of the solid-liquid front during charging and discharging in such heat storage modules will be important in predicting and optimising their performance. In the current work, computations have been performed to understand and optimise the effects of container geometry and size on the charging and discharging heat flux profiles of a simple heat storage module. Furthermore, fundamental experiments have also been implemented to identify the complex governing mechanisms of heat transfer and storage in such materials during transient operation.

Optimal sizing of hybrid PV–diesel–biomass gasification plants for electrification of off-grid communities: An efficient approach based on Benders’ decomposition

Nowadays, millions of people in remote areas do not enjoy an uninterrupted power supply due to the lack of connectivity to the main power grid. Under such circumstances, the only feasible way to access electricity is typically local power generation, often relying on diesel engine–generator sets or photovoltaic arrays. However, on many occasions, this configuration does not fully exploit all available local resources, including biomass. Indeed, most isolated areas have access to local biomass production from agricultural activities, which can be used for local electricity generation through gasification. This paper addresses this challenge by developing an innovative optimal sizing tool for hybrid power plants integrating biomass gasifiers, specifically designed for isolated areas with access to local biomass production. The novel approach models the particular features of biomass gasification technologies, including long on/off times or restrictive ramping limits. To this end, an efficient methodology based on representative weeks is proposed, which is combined with a solution strategy based on the multi-cut Benders’ decomposition, thus resulting in a tractable framework that can deal with a huge amount of data efficiently. One of the most salient features of the new proposal is the consideration of local biomass production, which is included in the methodology through an original algorithm. Accordingly, a certain amount of biomass is sourced locally, leading to more accurate and reliable results. The new methodology is applied to a benchmark off-grid community in Ghana. The results demonstrate that the use of gasifiers reduces the project cost notably (by 90%) driven by the reduced biomass cost, which can be supplemented by locally generated biomass from agricultural activities. In addition, this technology constitutes a clean source of energy, reducing the total CO2 emissions by 83% compared to a baseline case in which only diesel generators are used. Moreover, it is demonstrated that biomass gasification can effectively act as base load power generation technology to reliably cover most of the local demand, thereby enabling a clean and inexpensive dispatchable local power generation. Finally, a sensitivity analysis reveals that the economic feasibility of the plant is more sensitive to the biomass cost than the selling price of biochar, resulting in a 33% increment in the total project cost when the price of biomass increases from 0 to 0.4 $/kg. Nevertheless, gasification remains as the predominant power generation technology even under unfavorable prices.

Unequal impacts of unidirectional freeze-thaw on different soil layers and aggregate sizes: Evidenced by microbial communities and CO2 emissions

Currently available investigations often fail to adequately recognize that soil does not freeze or thaw instantly nor uniformly, but unidirectionally and progressively. Unidirectional freeze-thaw can re-organize soil physio-, chemical- and biological-properties across layers as well among aggregates, thus posing far-reaching yet undervalued impacts on soil carbon biogeochemical cycling, especially in eroding settings. In this study, a Mollisol was refilled into soil columns, and respectively experienced complete freeze-thaw (i.e., no layer distinguished), and progressive freeze-thaw (i.e., from outer layer T1, to inner core T3). After thawing, all soils were fractionated into six size classes, and each size class was then incubated at 10℃ over 7 days to measure daily CO2 emission rate. Our results show that: (1) The soil microbial biomass carbon (SMBC) was generally reduced by 25 % after freeze-thaw, but only the finest aggregates ≤ 32 μm maintained comparable CO2 emission rates. (2) The inner core T3 thawed last and survived with significantly more SMBC and CO2, but lower respiratory quotient (qCO2), than the outer layer T1 thawed first. (3) The fine aggregates survived with more SMBC and total CO2 emissions, but significantly lower qCO2 and smaller ratios of fungal to bacterial biomass carbon, than the coarse aggregates. The disproportionally less respiratory carbon losses (i.e., lower qCO2) in T3 was probably because the lagged freezing and thus weakened water-ice phase changes in the inner core helped to better preserve the soil microbes. The fungal-dominant coarse aggregates were very responsive to freezing and evidently more respiratory active, whereas the fine aggregates were more resilient as the enhanced freezing point depression and the thus prolonged unfrozen state, fostering a better microbial survival with bacteria-dominant communities and robust basal respiration. Although limited to controlled simulation, this study may help to disentangle the role of unidirectional freeze-thaw in perturbing slope-scale soil carbon biogeochemical cycling.

Two-Layer Optimization Method for Sharing Energy Storage and Energy considering Subjectivity

The high level of integration of distributed generation systems (DGSs), especially distributed wind and solar, significantly affects the flexibility and controllability of the power system. Aggregating local DGSs and shared energy storage systems (ESSs) within an energy community offers an economically and environmentally viable solution. However, the coupling of shared ESSs with the energy community, while considering subjectivity, is often overlooked. Therefore, this study introduces a two-layer optimization framework that enables DGSs to trade energy freely, voluntarily, and independently and to share ESSs within the energy community, considering participants’ subjectivity. The upper layer optimizes the size of shared ESSs, while the lower layer, structured as a two-layer model, simulates participant interactions. The numerical case shows that, compared to DGSs operating individually, the shared ESS case indicates that community self-sufficiency and self-consumption rates increase by 16.22% and 21.98%, respectively. Additionally, the annual operating cost is reduced by approximately 27.10%, and CO2 emissions are decreased by about 33.24%. Considering DGS’ subjectivity, the self-sufficiency and self-consumption rates are 3.04% lower, and the total operating costs and CO2 emissions are 3.26% and 6.86% higher, respectively.

Effect of excess CO2 on semi-continuous microalgae systems: Carbon biofixation

Microalgae-based CO2 fixation is a promising solution for achieving carbon neutrality. However, the low rate of carbon fixation is a significant issue due to gas transfer. A closed cultivation system was employed to overcome this challenge, incorporating headspace micro-positive pressure and elevated total CO2 (TCO2) levels to minimize CO2 loss and improve CO2 mass transfer. Microalgae could thrive and maintain a higher level of system pH within the TCO2 range of 0.12–0.49 mol CO2/L absorbent, and high TCO2 levels over 0.36 mol CO2/L absorbent were the optimal range. The semi-continuous microalgae system removed up to 8.72 ± 0.85 g CO2/L/day. Simultaneously, it exhibited phosphate and nitrate removal rates of 50.95 ± 10.71 and 182.14 ± 30.71 mg/L/day, respectively. The study found that 80% of the removed carbon was fixed as organic biomass. An increased level of TCO2 resulted in the accumulation of more lipids within the cells. Moreover, microalgae released carbon fixation products into the extracellular environment, and the dissolved organic carbon fixation rate reached as high as 14.58 ± 1.89 mmol/L/day. These findings suggest that microalgae use multiple pathways for carbon fixation, including biomass organic carbon accumulation, extracellular organic carbon secretion, and inorganic carbon precipitation. Improving carbon fixation rates may benefit the industrial application of microalgae technology, which aims to mitigate carbon emissions.

Nexus between carbon stock, biomass, and CO2 emission of woody species composition: evidence from Ise-Ekiti Forest Reserve, Southwestern Nigeria

The carbon stock, biomass, and CO2 emissions in woody species play crucial roles in understanding and managing ecosystems. Understanding these aspects is crucial for sustainable forest management, conservation, and mitigating the impact of woody species on global carbon dynamics and climate change. This study examined the nexus between carbon stock, biomass, and CO2 emission of woody plant composition in disturbed and undisturbed areas in Southwestern Nigeria. The study involved the random establishment of plots in the disturbed and undisturbed areas and, in each plot, the woody plants were enumerated and identified to the species level. The results showed that total biomass (102.645 Mg ha-1), total carbon stock (51.323 Mg C ha-1), and total CO2 emission (188.354 Mg C ha-1) values of tree species in undisturbed plots were higher than the values of total biomass (70.768 Mg ha-1), total carbon stock (35.384 Mg C ha-1), and total CO2 emission (129.859 Mg C ha-1) recorded in disturbed plots. The results also revealed that total biomass (0.123 Mg ha-1), total carbon stock (0.061 Mg C ha-1), and total CO2 emission (0.225 Mg C ha-1 ) values of shrub species recorded in disturbed plots were higher than values of total biomass (0.067 Mg ha-1), total carbon stock (0.034 Mg C ha-1) and total CO2 content (0.124 Mg C ha-1) recorded in undisturbed plots, respectively. The findings showed that in undisturbed and disturbed plots of shrubs, biomass, carbon and CO2 emissions have a strong positive correlation of 1.000**. While biomass, carbon, and CO2 emission have a very strong positive correlation (0.999**) in undisturbed plots of trees, the biomass, carbon, and CO2 emission have moderate to strong positive correlations (0.458** to 0.974**) in disturbed plots of the tree. The study concluded that while biomass, carbon stock, and CO2 emission values of tree species were higher in undisturbed plots than in disturbed plots, the biomass, carbon stock, and CO2 emission values of shrub species were lower in undisturbed plots than in disturbed plots. It also concluded that the main purpose of establishing reserve forests is not totally achieved as human activities occurring in reserve forests still contribute to the increment of climate change.

Aerobic and anaerobic decomposition rates in drained peatlands: Impact of botanical composition

Drained peatlands in temperate climates are under threat from climate change and human activities. The resulting decomposition of organic matter plays a major role in regulating the associated land subsidence rates, yet the determinants of aerobic and anaerobic peat decomposition rates are not fully understood. In this study, we sought to gain insight into the drivers of decomposition rates in botanically diverse peatlands (sedge, reed, wood, and moss dominant) under oxic and anoxic conditions. Peat samples were collected from the anoxic zone and incubated for 24 h (short) and 15 weeks (long) under either oxic or anoxic conditions. CO2 emissions, hydrolytic and oxidative exoenzyme potential activities, phenolic compound concentrations, and several edaphic factors were measured at the end of each incubation period.We found that 15 weeks of oxygen exposure of anoxic peat samples accelerated the average CO2 emissions by 3.9-fold. Reed and sedge peat respired more than wood and moss peat under anoxic conditions. Interestingly, CO2 emissions from anoxic peat layers under permanently anoxic conditions were substantial and given the thickness of peat deposits in the field, such activities may play an important role in long-term land subsidence rates and total CO2 emissions from drained peatlands. The results from the long-term incubations showed that decomposition rates appear to be also controlled by factors other than oxygen intrusion such as substrate availability. In summary, the botanical composition of the peat matrix, incubation conditions and time of incubation are all important factors that need to be considered when predicting peat decomposition and subsequent land subsidence rates.

Effects of extending dairy cow longevity by adjusted reproduction management decisions on partial net return and greenhouse gas emissions: A dynamic stochastic herd simulation study

Prolonging dairy cattle longevity is regarded as one of the options to contribute to more sustainable milk production. Because failure to conceive is one of the main reasons for culling, this study investigates how adjustments in reproduction management affect partial net return at herd level and greenhouse gas emissions per unit of milk, using a dynamic stochastic simulation model. The effects of reproduction decisions that extend cattle longevity on milk yield, calving interval and pregnancy rate were derived from actual performance of Dutch commercial dairy cows over multiple lactations. The model simulated lactations, calving, and health status events of individual cows for herds of 100 cows. Scenarios evaluated differed in the maximum number of consecutive AI attempts (4, 5, or 6 services), or the production threshold (20, 15, or 10 kg of milk/d) at which cows that failed to conceive are culled (reproductive culling). Annual partial net return was computed from revenues of sold milk, calves, and slaughtered cows, and the costs from feed consumption, rearing replacement heifers, AI services, and treatment for clinical mastitis and lameness. Greenhouse gas emissions were computed for feed production, enteric fermentation, and manure management, and were expressed as total CO2 equivalents (CO2-eq). Average age at culling increased with an increased maximum number of AI services. This increase was larger when going from a maximum of 4 to 5 AI attempts (108 d) than from a maximum of 5 to 6 attempts (47 d). Similarly, the average age at culling increased from 1,968 to 2,040 and 2,132 d when the threshold for reproductive culling decreased from 20, to 15 and 10 kg of milk/d, respectively. Average annual partial net return increased by 1.1% from €165,850 per 100 cows at a maximum of 4 AI to €167,670 per 100 cows at a maximum of 6 AI, and increased by 4.3% from €161,210 per 100 cows at a reproductive culling threshold of 10 kg/d to €168,190 per 100 cows at a threshold of 20 kg/d. Greenhouse gas emissions decreased by 1.2% from 0.926 to 0.915 kg CO2-eq per kg of fat- and protein-corrected milk (FPCM) with an increase in a maximum number of AI from 4 to 6 AI. Conversely, greenhouse gas emissions increased by 0.2% from 0.926 kg at a threshold of reproductive culling of 20 kg/d to 0.928 kg CO2-eq/kg FPCM at a threshold of 10 kg/d. Although lowering the threshold for reproductive culling has the potential to extend cattle longevity more than increasing the maximum number of AI services, only the increase in AI services benefits a farm's partial net return, while reducing greenhouse gas emissions.

Assessment of energy consumption, environmental effects and fuel costs of the bus rapid transit system in Bogotá (Colombia)

Abstract Colombia aims to boost the utilization of mass transportation systems in its major cities while simultaneously reducing greenhouse gas emissions by 20%, in alignment with the commitments of the COP21 agreement. In 2020, the transport sector in Colombia accounted for 34.4% of the country’s energy demand and was responsible for ~49% of its total CO2 emissions. This article presents an assessment of energy consumption, environmental effects and the fuel costs of Bogotá’s bus rapid transit system based on the Activity, Share, Intensity, Fuel methodology. A long-term analysis spanning from 2021 to 2040 was developed using the long-range energy alternatives planning platform. To conduct this assessment, the tool was calibrated using data from 2019 and 2020. Four distinct scenarios based on energy policies implemented in Bogotá were examined: Business as Usual, Fast Transition, High Growth and Low Growth. Regarding energy consumption and environmental effects, the results underscore the pivotal role of diversifying energy sources and reducing reliance on fossil fuels such as oil. Consequently, the analysis emphasizes the urgent need to accelerate the transition to alternative energy sources such as natural gas and electricity.

Gas CO2 foaming and intermixing in portland cement paste to sequester CO2

In this study, concentrated CO2 gas was used to create foamed cement paste, and concentrated CO2 gas was intermixed in fresh cement paste to produce regular cement paste materials that were not foamed. The potential of both methods to form CaCO3 from calcium ions that would form Ca(OH)2 was investigated. After curing the materials for different ages, the Ca(OH)2 and CaCO3 contents were measured using thermogravimetric analysis; the large void size distributions, dynamic modulus, and compressive strength were tested and compared against Control (no gas added), and N2 foamed and N2 intermixed specimens. A 10% increase in dynamic modulus and compressive strength was measured in CO2 foamed specimens compared to N2 foamed specimens. The increase in mechanical properties was the result of both a narrow void diameter distribution and CaCO3 formation in place of Ca(OH)2. The CO2 foamed cement generation method shows the potential to sequester 0.06 ton of CO2 for every ton of cement which is a CO2 emission reduction of 7.0% of the CO2 production associated with cement production. For the CO2 intermixing method, the void content, compressive strength, and dynamic modulus results were consistent between the Control and CO2 intermixed specimens while the N2 intermixed specimens showed a decrease in compressive strength and dynamic modulus. The CO2 intermixing method showed potential to sequester 0.04 ton of CO2 for every ton of cement or a 4.7% CO2 emission reduction of the total CO2 production associated with cement manufacturing. The reported CO2 emissions are not based on life cycle assessment and do not account for emissions associated with CO2 collection, transportation, and intermixing. The present paper does not investigate the mechanisms of hydration under CO2 intermixing.

Exploring the cause of reduced production responses to feeding corn dried distillers grains in lactating dairy cows

An experiment was conducted to identify the factors that cause reduced production of cows fed a diet with high content of corn distillers grains with solubles (DDGS). We hypothesized that the factors could be high sulfur (S) content in DDGS, which may directly (S toxicity) or indirectly (DCAD) cause reduced production. We also hypothesized that high PUFA in DDGS could be another major factor. In a randomized complete block design, 60 lactating cows (15 primiparous and 45 multiparous; average ± SD at the beginning of the trial: milk yield, 44.0 ± 6.9 kg/d; DIM, 123 ± 50; BW, 672 ± 82 kg) were blocked, and cows in each block were randomly assigned to 1 of the following treatments: SBM (4.7% fatty acids [FA], 0.22% S, and 178 mEq/kg DM of DCAD), a diet containing soybean meal as the main protein source; DG, with SBM replacing mainly soybean byproducts and supplemental fat with distillers grains at 30% dietary DM (4.7% FA, 0.44% S, and 42 mEq/kg DM of DCAD); SBM+S, SBM with sodium bisulfate for additional dietary S (4.8% FA, 0.37% S, and 198 mEq/kg DM of DCAD); SBM+CO, SBM with corn oil (4.7% FA, 0.23%, and 165 mEq/kg DM of DCAD); and DG+DCAD, DG with increased DCAD (4.7% FA, 0.40% S, and 330 mEq/kg DM of DCAD). Due to the limited number of tiestalls, blocks 1 to 6 started the experiment first as phase 1, and the rest of the blocks, as phase 2, started the experiment after phase 1. All cows were fed the SBM diet for 10 d as a covariate period followed by the experimental period for 35 d. Data were analyzed using PROC MIXED of SAS (Version 9.4, SAS Institute Inc.); block and phase were random effects; and treatments, repeated week, and interaction were fixed effects. We found an interaction of week by treatment for DMI. Although milk yield did not change, milk fat concentration tended to decrease (2.78% vs. 3.34%) for DG compared with SBM. Dry matter, OM, NDF, and CP digestibilities were lower when cows were fed the DG diet compared with SBM. Additionally, cows fed DG had lower blood concentrations of HCO3-, base excess, and total (t)CO2 compared with SBM. The SBM+S diet did not affect production, nutrient digestibility, or blood parameters compared with SBM. The SBM+CO diet decreased milk fat concentration and yield compared with SBM. The DG+DCAD diet tended to increase milk fat yield and concentration (1.24 vs. 1.47 kg/d; 2.78% vs. 3.37%) and increased ECM (40.9 vs. 45.1 kg/d) compared with DG but did not improve nutrient digestibility. However, blood HCO3-, base excess, and tCO2 were greater for DG+DCAD compared with DG. In conclusion, the indirect role of S-, altering DCAD, along with the high PUFA content in DDGS, appear to be the factors causing reduced production responses to a high DDGS diet. Increasing DCAD to 300 mEq/kg DM in a high DDGS diet can be a feeding strategy to alleviate reduced production responses.

Characterization and Flame-Retardant Properties of Cobalt-Coordinated Cyclic Phosphonitrile in Thermoplastic Polyurethane Composites.

Halogen-free organophosphorus flame retardants have promising application prospects due to their excellent safety and environmental protection properties. A cobalt-coordinated cyclic phosphonitrile flame retardant (Co@CPA) was synthesized via a hydrothermal method using hexachlorocyclotriphosphonitrile (HCCP), 5-amino-tetrazolium (5-AT), and cobalt nitrate hexahydrate (Co(NO3)2∙6H2O) as starting materials. The structure was characterized using Fourier transform infrared (FTIR), nuclear magnetic resonance spectroscopy (1H-NMR), scanning electron microscopy (SEM), and thermogravimetric analysis (TGA). Thermoplastic polyurethane (TPU) composites were prepared by incorporating 10-(2,5-dihydroxyphenyl)-9,10-dihydro-9-oxa-10-phosphame-10-oxide (ODOPB), Co@CPA, and silicon dioxide (SiO2) via melt blending. The flame-retardant performance and thermal stability of the TPU composites were evaluated through limiting oxygen index (LOI), vertical combustion (UL-94), TG, and cone calorimetric (CCT) tests. SEM and Raman spectroscopy were used to analyze the surface morphology and structure of the residual carbon. A synergistic flame-retardant effect of ODOPB and Co@CPA was observed, with the most effective flame retardancy achieved at a TPU:ODOPB:Co@CPA:SiO2 ratio of 75:16:8:1. This composition exhibited an LOI value of 26.5% and achieved a V-0 rating in the UL-94 test. Furthermore, compared to pure TPU, the composite showed reductions in total heat release, CO production, and CO2 production by 6.6%, 39.4%, and 48.9%, respectively. Our research findings suggest that Co@CPA demonstrates outstanding performance, with potential for further expansion in application areas. Different metal-based cyclic phosphonitrile compounds are significant in enriching phosphorus-based fine chemicals.

Unveiling the Dynamics and Influence of Water Footprints in Arid Areas: A Case Study of Xinjiang, China

A prerequisite for the rational development and utilization of regional water resources is the measurement of water stress. In this study, from the perspective of water footprints, we took the proportion of the agricultural water footprint within the total water resource usage of Xinjiang (hereafter referred to as XJ) as an example to measure its water stress index and explore the state of water stress in the region and its corresponding driving factors. The ESDA method was applied to characterize the spatial patterns of and correlations with water stress. The effects of different factors on the spatial differentiation between the water footprint and water stress were quantified using the LMDI and geoprobes, respectively. The results showed that (1) both the agricultural water footprint and the water stress index in XJ showed an upward trend, the spatial distribution of water stress was uneven, and the regional pressure difference between the east and the west was greater than that between the north and the south; (2) the water stress index has an obvious negative spatial correlation, fluctuations in its discrete nature have been enhanced, and the number of spatially correlated prefectures is decreasing; (3) water consumption of CNY 10,000 GDP, GDP per capita, and total CO2 emissions have the most significant impact on the evolution of the agricultural water footprint in XJ. Meanwhile, spatial variations in water stress are mainly determined by the area of cultivation, the area of natural oasis, and the proportion of water used in agriculture. Analysis of the characteristics of and factors influencing water stress in XJ from the perspective of its agricultural water footprint provides a new perspective for further analyzing the actual state of the water footprint and water stress in XJ and supplies a reference basis for the decision-makers of the XJ government.

Year-round CO2 emissions from the drawdown area of a tropical reservoir: Strong seasonal and spatial variation

A growing body of literature points to drawdown areas as important sources of atmospheric CO2 within reservoirs. Yet seasonal and temporal patterns of CO2 flux from periodically exposed sediments in drawdown areas remain poorly understood. Here we evaluate the annual and diel (24-hour cycle) variations in CO2 emissions from sediments periodically exposed to the atmosphere. We sampled sediments in the drawdown area of a tropical reservoir, which encompassed two primary adjacent land covers—grassland and forestland—in the watershed of a reservoir located in southeastern Brazil. We also experimentally assessed the effect of rewetting on CO2 emissions from exposed sediments. We found large variations in emissions during all hydrological periods (from 10 to 10116 mg C/m−2(−|-) d-1), except for the late rainy period. Land use and how distant dry sediments were from the open water significantly affected drawdown CO2 emissions, with higher emissions occurring in areas surrounded by forest than those adjacent to grassland. Our diel-cycle analysis did not show significant variation of emissions over daily cycles. Furthermore, a rewetting experiment indicated a significant increase in emissions 30 min after the onset of the rewetting event. Although drawdown areas only cover 20 % of the reservoir’s area, they account for 80 % of the reservoir’s total CO2 emissions. Ultimately, single-time measurements can lead to considerable underestimation (up to 52 %) or overestimation (up to 190 %) of whole-reservoir CO2 emissions.

A multiobjective approach for weekly Green Home Health Care routing and scheduling problem with care continuity and synchronized services

Home Health Care (HHC) services are essential for delivering healthcare programs to patients in their homes, with the goal of reducing hospitalization rates and improving patients’ quality of life. However, HHC organizations face significant challenges in scheduling and routing caregivers for home care visits due to complex criteria and constraints. This paper addresses these challenges by considering both caregiver assignments and transportation logistics. The objective is to minimize the total travel distance and CO2 emissions while ensuring a balanced workload for caregivers, meeting patients’ preferences, synchronization, precedence, and availability constraints. To tackle this problem, we propose a multiperiodic Green Home Health Care (GHHC) framework. In the first stage, we utilize multiobjective programming and the NSGA-II algorithm to generate Pareto front solutions that consider travel distance and CO2 emissions. In the second stage, a Mixed-Integer Linear Programming (MILP) model is proposed to balance caregivers’ workload by assigning them to the patient routes generated in the first stage. The results highlight the trade-off between shorter routes and lower emissions. Furthermore, we examine the impact of prioritizing continuity of care and patient satisfaction. This research provides valuable insights into addressing the scheduling and routing challenges in HHC services, contributing to a more efficient and environmentally friendly healthcare delivery.

Soil respiration and its response to climate change and anthropogenic factors in a karst plateau wetland, southwest China.

It is important to investigate the responses of greenhouse gases to climate change (temperature, precipitation) and anthropogenic factors in plateau wetland. Based on the DNDC model, we used meteorological, soil, and land cover data to simulate the soil CO2 emission pattern and its responses to climate change and anthropogenic factors in Guizhou, China. The results showed that the mean soil CO2 emission flux in the Caohai Karst Plateau Wetland was 5.89 ± 0.17 t·C·ha-1·yr-1 from 2000 to 2019, and the annual variation showed an increasing trend with the rate of 23.02 kg·C·ha-1·yr-1. The soil total annual mean CO2 emissions were 70.62 ± 2.04 Gg·C·yr-1 (annual growth rate was 0.28 Gg·C·yr-1). Caohai wetland has great spatial heterogeneity. The emissions around Caohai Lake were high (the areas with high, middle, and low values accounted for 3.07%, 70.96%, and 25.97%, respectively), and the emission pattern was characterized by a decrease in radiation from Caohai Lake to the periphery. In addition, the cropland and forest areas exhibited high intensities (7.21 ± 0.15 t·C·ha-1·yr-1 and 6.73 ± 0.58 t·C·ha-1·yr-1, respectively) and high total emissions (54.97 ± 1.16 Gg·C·yr-1 and 10.24 ± 0.88 Gg·C·yr-1, respectively). Croplands and forests were the major land cover types controlling soil CO2 emissions in the Caohai wetland, while anthropogenic factors (cultivation) significantly increased soil CO2 emissions. Results showed that the soil CO2 emissions were positively correlated with temperature and precipitation; and the temperature change had a greater impact on soil respiration than the change in precipitation. Our results indicated that future climate change (increased temperature and precipitation) may promote an increase in soil CO2 emissions in karst plateau wetlands, and reasonable control measures (e.g. returning cropland to lakes and reducing anthropogenic factors) are the keys to controlling CO2 emissions.

Collaborative modeling and optimization of energy hubs and multi-energy network considering hydrogen energy

To achieve the goal of carbon neutrality, integrated energy hubs (EHs) based on coupled energy sources such as electricity, gas and heat are gaining increasing attention due to their efficient and flexible energy supply characteristics. The introduction of integrated EHs may lead to the reconstruction of the existing superior energy network to accommodate the suitable flow of the new network. In this study, a multi-objective optimization model is proposed that synergistically considers the optimal configuration of EHs and the reconstruction of higher-level energy networks, with the objectives of minimizing total annual energy supply costs and CO2 emissions. First, an EH and multi-energy network (MEN) topology model considering hydrogen energy is developed. Secondly, the joint output of wind and solar power under typical scenarios is sampled and obtained by employing the Monte Carlo sampling method and the synchronous back-propagation scenario analysis method. To address the nonlinear constraint problem associated with multi-energy storage output, the Big-M method is introduced to improve the optimization capability of spatial-temporal coupling of energy storage. Moreover, the utilization potential of hydrogen and renewable energy is explored by considering constraints on the nonlinear dynamic pricing of hydrogen. Finally, a numerical analysis is conducted using an illustrative example. The Pareto frontier optimal results, derived from fuzzy theory membership functions, are achieved using both classical and heuristic algorithms. The classical mixed-integer linear programming algorithm yields relatively superior optimization outcomes in terms of annual energy costs and carbon emissions compared to the heuristic algorithm. However, it suffers from longer computation times.