District heating system's development decarbonization strategy assessment by system dynamics modeling and multi-criteria analysis.

The study introduces a hybrid model that integrates system dynamics modeling and multi-criteria analysis. Through the system dynamics model, the study examines energy, economic, and environmental indicators of a District Heating (DH) company, assessing its dynamics until 2050. Various decarbonization scenarios are explored, involving the transition of the DH system to a 4th generation DH (4GDH) system based on four strategies: utilizing at least (a) 50% Renewable Energy Sources (RES), (b) 50% waste heat, (c) 75% cogenerated heat, or (d) 50% of the combined aforementioned energy and heat. Additionally, development scenarios incorporate measures to enhance energy efficiency on the consumer side and within the heating networks. The sustainability of each scenario is evaluated using the multi-criteria analysis method TOPSIS. The hybrid model establishes a ranking of the transition pathways based on their sustainability scores and benchmarks the results of the developed scenarios against a carbon-neutral DH system. This model serves as a valuable guide for DH system developers and decision-makers. The study focuses on Riga as a practical case study.

Energy and enviro-economic analysis of a solar air heater with wedge turbulators.

Solar air heaters (SAH) convert solar energy to thermal energy for food processing industries and commercial space heating applications, as solar energy is cost-free. In this experimental study, the thermal performance of the solar air heater has been successively improved using different roughness elements over the absorber. The triangle-shaped wedges in three structures (inline, serpentine, and clustered structure) are investigated in this work. Thermal performance comparison is made with a SAH with a plain absorber. A maximum air temperature rise of 19 °C is observed for the SAH with wedges in a clustered structure. The absorber surface temperature for clustered structured roughness elements is 76.8 °C with an average heat loss coefficient of 4.43 W/m2·K. The useful heat absorption using clustered structure wedges is 33%, 17.9%, and 6.6% higher than the SAH with plain, inline, and serpentine structured wedges. SAH's maximum thermal and exergy efficiency with clustered structured elements is 70.4% and 1.64%. The average thermal efficiency of inline, serpentine, and clustered arrangement is 13.3%, 25.3%, and 35.6% higher than the SAH with a plain absorber. The proposed SAH design shows a sustainability index 1.01, and lower payback periods show economic and environmental viability.

Assessment of magnetic field interactions and heating for cerebral aneurysm flow diverters during 7T MRI.

Flow diverters (FDs) are utilized for a wide range of aneurysms, but show safety issues such as adverse interactions with static magnetic fields (displacement force and torque) and radiofrequency-induced heating during magnetic resonance imaging (MRI). The present study aimed to assess these adverse interactions in a 7-tesla (7T) static magnetic field and radiofrequency-induced heating during a 7T MRI for two types of FD. Displacement force and magnetically induced torque were assessed using the deflection angle method and low friction surface method, respectively. To assess heating, each FD was set in a phantom filled with gelled-saline mixed with polyacrylic acid and underwent a 7T MRI using a three-dimensional fast spin echo method. Displacement force and magnetically induced torque in the 7T static magnetic field were undetectable, and radiofrequency-induced heating during 7T MRI remained ≤ 0.6 °C for both types of FD, suggesting that magnetic field interactions and heating on FDs during a 7T MRI are acceptable from a safety perspective.

Transient simulation of laser ablation based on Monte Carlo light transport with dynamic optical properties model.

Laser ablation is a minimally invasive therapeutic technique to denature tumors through coagulation and/or vaporization. Computational simulations of laser ablation can evaluate treatment outcomes quantitatively and provide numerical indices to determine treatment conditions, thus accelerating the technique's clinical application. These simulations involve calculations of light transport, thermal diffusion, and the extent of thermal damage. The optical properties of tissue, which govern light transport through the tissue, vary during heating, and this affects the treatment outcomes. Nevertheless, the optical properties in conventional simulations of coagulation and vaporization remain constant. Here, we propose a laser ablation simulation based on Monte Carlo light transport with a dynamic optical properties (DOP) model. The proposed simulation is validated by performing optical properties measurements and laser irradiation experiments on porcine liver tissue. The DOP model showed the replicability of the changes in tissue optical properties during heating. Furthermore, the proposed simulation estimated coagulation areas that were comparable to experimental results at low-power irradiation settings and provided more than 2.5 times higher accuracy when calculating coagulation and vaporization areas than simulations using static optical properties at high-power irradiation settings. Our results demonstrate the proposed simulation's applicability to coagulation and vaporization region calculations in tissue for retrospectively evaluating the treatment effects of laser ablation.

Significant but Inequitable Cost-Effective Benefits of a Clean Heating Campaign in Northern China.

Residential emissions significantly contribute to air pollution. To address this issue, a clean heating campaign was implemented to replace coal with electricity or natural gas among 13.9 million rural households in northern China. Despite great success, the cost-benefits and environmental equity of this campaign have never been fully investigated. Here, we modeled the environmental and health benefits, as well as the total costs of the campaign, and analyzed the inequality and inequity. We found that even though the campaign decreased only 1.1% of the total energy consumption, PM2.5 emissions and PM2.5 exposure experienced 20% and 36% reduction, respectively, revealing the amplification effects along the causal pathway. Furthermore, the number of premature deaths attributable to residential emissions reduced by 32%, suggesting that the campaign was highly beneficial. Governments and residents shared the cost of 2,520 RMB/household. However, the benefits and the costs were unevenly distributed, as the residents in mountainous areas were not only less benefited from the campaign but also paid more because of the higher costs, resulting in a notably lower cost-effectiveness. Moreover, villages in less developed areas tended to choose natural gas with a lower initial investment but a higher total cost (2,720 RMB/household) over electricity (2,190 RMB/household). With targeted investment and subsidies in less developed areas and the promotion of electricity and other less expensive alternatives, the multidevelopment goals of improved air quality, reduced health impacts, and reduced inequity in future clean heating interventions could be achieved.

Techno-economic analysis and optimization of near-zero energy and emission neighborhoods using biomass waste.

The present study aims to simulate and design a near-Zero Energy neighborhood in one of the most significant industrial cities for reducing greenhouse gas emissions. For this building, biomass wastes are used for energy production, and also energy storage is provided using a battery pack system. Additionally, the Fanger model is used to assess the passengers' thermal comfort, and information on hot water usage is given. The transient performance of the aforementioned building is tested for one year using TRNSYS software, which was employed for this simulation. Wind turbines are considered electricity generators for this building, and any extra energy generated is stored in a battery pack for usage when the wind speed is insufficient and electricity is needed. Hot water is created using a biomass waste system and is kept in a hot water tank after being burned using a burner. A humidifier is utilized to ventilate the building, and a heat pump provides both the building's heating and cooling needs. The produced hot water is used to supply the residents' hot water. In addition, The Fanger model is considered and used for the assessment of occupants' thermal comfort. Matlab software is a powerful software used for this task. According to the findings, a wind turbine with a 6 kW generation capacity may supply the building's power needs while also charging the batteries beyond their initial capacity, and the building will have zero energy. Additionally, biomass fuel is used to give the building the required water which should be hot. On average, 200 g of biomass and biofuel are used per hour to maintain this temperature.

Risk assessment of silver and microplastics release from antibacterial food containers under conventional use and microwave heating.

The evaluation of the migration of ionic silver and nanoparticulated silver (AgNPs) from antimicrobial plastic packaging to food is crucial to ensure its safety. Migration assays were performed on reusable silver-containing polypropylene (PP) food containers and a silicone baby bottle, using food simulants, under conventional or microwave heating and repeated use. The PP containers released significant amounts of silver, increasing with temperature, contact time, acidity and lower crystallinity. Silver migration in the silicone bottle was much lower. Risk assessment of released silver was done considering European authorities safety recommendations, with some containers far exceeding these levels. No significant AgNPs release was detected in the simulants by single particle-ICPMS. Silver-containing microplastics and silicone microparticles were detected by SEM in the food simulants after the migration assays. Consumers may be continuously exposed to the harmful effects of ionic silver and microplastics, which can potentially lead to health issues.

Association of Structural Fires in New York City With Inequities in Safe Heating for Immigrant Communities.

This cross-sectional study assesses the association of heating complaints with structural fires in New York, New York.

Can the Clean Heating Policy reduce carbon emissions? Evidence from northern China.

The Clean Heating Policy aims to solve the problems of excessive energy consumption and severe air pollution caused by central heating in northern China. Whether this policy can effectively reduce carbon emissions remains unexplored. Using panel data representing 65 cities in northern China from 2010 to 2019, this paper constructs a dynamic spatial DID model to empirically study the carbon reduction effect of the Clean Heating Policy and its influence channels. The results are summarized as follows. First, the Clean Heating Policy can significantly reduce carbon emissions, and this conclusion holds after multiple robustness tests. The policy has a lag effect, but its spatial spillover effect and long-term effect are not significant. Second, the carbon reduction effect of the Clean Heating Policy is mainly achieved by optimizing the energy structure and improving the thermal efficiency of heat consumer terminals. Third, the carbon reduction effect varies by city and emission field. It is significant only in low-subsidy cities, high-carbon cities, and household fields. Fourth, there is a synergistic reduction relationship between the Clean Heating Policy and the low-carbon city policy. Based on the results of this paper, we propose policy implications, such as promoting policies in multiple ways and improving subsidy efficiency, and provide a reference for other countries.

[Pollution Characteristics and Health Risk Assessment of Heavy Metals in PM2.5 of Different Air Masses During Heating Season in Tianjin].

In order to explore the pollution characteristics and health risks of heavy metals in PM2.5 in Tianjin, heavy metal samples (Pb, Cd, Cr, As, Zn, Mn, Co, Ni, Cu, and V) in PM2.5 were analyzed from November 2020 to March 2021 using the Xact-625 heavy metal online analyzer. The spatial and temporal distribution characteristics were analyzed using the HYSPLIT model, and the health risks of heavy metals were analyzed using the US EPA risk assessment model. The results indicated that the average total concentration of the 10 heavy metal elements was (261.56±241.74) ng·m-3, among which the concentrations of Cr ï¼»converted Cr(Ⅵ)ï¼½ and As were higher than the annual average limit of the National Ambient Air Quality Standard (GB 3095-2012). According to the back trajectory results, the medium-distance transmissions from northwest areas (NO.1), the long-distance transmissions from northwest areas (NO.2), the transmissions from southwest areas (NO.3), and the transmissions from northeast areas (NO.4) were the major sources in Tianjin City. The heavy metals of different air masses presented different pollution characteristics and health risks; the concentration of PM2.5, the total concentration of the 10 heavy metal elements, and the total carcinogenic risk of the five heavy metal elements of the NO.3 air mass were the highest, whereas the total non-carcinogenic risk of the 10 heavy metal elements of the NO.2 air mass was higher than that of the other two air mass. The health risk assessment showed that Mn posed non-carcinogenic risks to children, and Cr and As presented carcinogenic risk. Meanwhile, Cd of the NO.3 air masses also presented carcinogenic risk.

Pollution characteristics and health risk assessment of polycyclic aromatic hydrocarbons and nitrated polycyclic aromatic hydrocarbons during heating season in Beijing.

Polycyclic aromatic hydrocarbons (PAHs) and their nitrated derivatives (NPAHs) attract continuous attention due to their outstanding carcinogenicity and mutagenicity. In order to investigate the diurnal variations, sources, formation mechanism, and health risk assessment of them in heating season, particulate matter (PM) were collected in Beijing urban area from December 26, 2017 to January 17, 2018. PAHs and NPAHs in PM were quantitatively analyzed via gas chromatography-mass spectrometry (GC-MS) . Average daily concentrations of PAHs and NPAHs were (78 ± 54) ng/m3 and (783 ± 684) pg/m3, respectively. The concentrations of them were significantly higher at nighttime than at daytime, and NPAHs concentrations were 1-2 orders of magnitude lower than PAHs concentrations. In the heating season, the dominant species of PAHs include benzo[b]fluoranthene, fluoranthene, pyrene, and chrysene, while 9-nitroanthracene, 2+3-nitrofluoranthene, and 2-nitropyrene were dominant species for NPAHs. NPAHs were found to have a single peak during heating and to be primarily distributed in the 0.4-0.7 µm particle size. Primary emissions such as biomass burning, coal combustion, and traffic emissions were the major sources of PAHs. NPAHs were produced by the primary source of vehicle emissions and the secondary reaction triggered by OH radicals, as well as biomass burning during daytime. According to the health risk assessment, the total carcinogenic risk was higher in adults than in children. While upon oral ingestion, the carcinogenic risk in children was higher than that of adults, but the risk of adults was higher than children through skin contact and respiratory inhalation.

Field assessment of straw pellet combustion in improved heating stoves in rural Northeast China.

Straw pellets are widely promoted and expected to be a cleaner alternative fuel to unprocessed crop residues and raw coal in rural China. However, the effectiveness of these dissemination programs is not well evaluated. In this field study, emission characteristics of burning straw pellets, raw coal, and unprocessed corn cobs in heating stoves were investigated in a pilot village in Northeast China. Emission measurements covering the whole combustion cycle (ignition, flaming, and smoldering phases) shows the promotion of improved heating stoves and straw pellets could reduce pollutant emissions (e.g., SO2 and CO), but increase NOX and PM2.5 emissions compared to the initial stove-fuel use pattern in the studied area. There is a significant variance in emission characteristics between different combustion phases. The normalized emission concentrations of the different stove-fuel combinations were higher than the limits in the Chinese national standard for heating stoves, indicating that the standard is not met for real-world emissions. Coal consumption was lower than official data. Household surveys were conducted to identify the barriers to fuel and stove access associated with existing promotion strategies, management, and policies. The pilot program was of the typical "subsidy-and-policy-dependence" pattern and was unlikely to be implemented on a large scale. Technological innovation, operational optimization, and proper policies considering the local socioeconomic factors are needed to sustain the promotion of biomass straw pellets and stoves.

Improving Building Envelope Efficiency Lowers Costs and Emissions from Rural Residential Heating in China.

In 2017, the Chinese government launched a clean heating campaign that replaced millions of rural coal stoves with various clean heaters. The clean heating program contributed to remarkable improvements in air quality. However, the benefits of reducing heating demand by improving building envelope efficiency were not sufficiently considered. This study provides a needed quantitative assessment of potential energy-savings, costs, greenhouse gas emission reductions, and adoption strategies for improving building envelope efficiency in Chinese rural residential buildings. We find that different strategies must be employed in existing and new buildings to achieve desired outcomes. For existing buildings, to encourage easy and beneficial building retrofits (e.g., air sealing, efficient windows), current fuel subsidies should be replaced with retrofit subsidies. Building retrofits can reduce the size and hence capital costs of new clean heaters. They can also reduce operating costs, hence reducing the likelihood of backsliding to coal. For new construction, whole-home insulation and heat pumps would best avoid carbon lock-in. These efficient technologies have high upfront costs but decrease heating costs and significantly reduce carbon emissions relative to current policies. Hence, subsidies and policies that encourage improvements in building envelopes as well as the uptake of clean and efficient heaters are critical.

Monitoring Immune Modulation in Season Population: Identifying Effects and Markers Related to Apis mellifera ligustica Honey Bee Health.

Honey bees play a significant role in ecology, producing biologically active substances used to promote human health. However, unlike humans, the molecular markers indicating honey bee health remain unknown. Unfortunately, numerous reports of honey bee collapse have been documented. To identify health markers, we analyzed ten defense system genes in Apis mellifera ligustica honey bees from winter (Owb) and spring (Fb for foragers and Nb for newly emerged) populations sampled in February and late April 2023, respectively. We focused on colonies free from SBV and DWV viruses. Molecular profiling revealed five molecular markers of honey bee health. Of these, two seasonal molecular markers-domeless and spz genes-were significantly downregulated in Owb compared to Nb and Fb honey bees. One task-related marker gene, apid-1, was identified as being downregulated in Owb and Nb compared to Fb honey bees. Two recommended general health markers, SOD and defensin-2, were upregulated in honey bees. These markers require further testing across various honey bee subspecies in different climatic regions. They can diagnose bee health without colony intervention, especially during low-temperature months like winter. Beekeepers can use this information to make timely adjustments to nutrients or heating to prevent seasonal losses.

A Colourful Way to Unravel the Important Fluidization-Related Granule Size Effect on Semi-Continuous Drying.

Continuous twin screw wet granulation (TSWG) systems are possible pathways for oral solid dosage manufacturing in the pharmaceutical industry. TSWG requires a drying step after granulation before the tableting process. Typically, semi-continuous fluidized bed dryers (FBDs) are used for this purpose. At the same time, the pharmaceutical sector is interested in mathematical prediction models to save resources during the early drug product development (DPD) stage or to control manufacturing. Several authors have already developed prediction models for semi-continuous drying processes. However, these model structures reported systematic prediction offsets, which could be related to the incomplete implementation of fluidization and granule segregation phenomena. This study evaluates the complex fluidization behavior of wet granules in industrially relevant semi-continuous FBDs. A transparent perspex version of the dryer was used for the analysis of bed height, pressure drop, porosity, segregation, and spatial heating patterns at varying process settings. The investigated behaviors of the fluidizing bed will be helpful to derive phenomenological (sub)models for the detailed description of segregation in the semi-continuous fluidized bed system. In this study, it was found that semi-continuous FBDs are characterized by a change in fluidization regime from plug flow to a bubbling bed at the moment that the granule bed slumps. Secondly, the presence of size-based vertical segregation phenomena as well as spatial temperature differences were proven. The experimental results suggest that larger granules are dried under more intense drying conditions than smaller granules.

Energy Poverty and Personal Health in the EU.

The aim of this paper is to assess the impact of energy poverty on health in the EU-27 countries for the period from 2003-2020 using Panel Autoregressive Distributed Lag models and generalized ridge regressions. Arrears on utility bills exerts positive long-run effects on capacity to keep the home adequately warm, current health expenditures, and self-perceived health as bad or very bad, but a negative long-run influence on energy import dependency. In the long-term, the population being unable to keep their home adequately warm positively affects self-perceived health as bad and very bad and negatively influences number of cooling days. Current health expenditure has a long-run influence on self-perceived health as bad and very bad and the number of heating days. Positive short-run impacts were observed for energy import dependency, arrears on utility bills, and number of heating days on current health expenditure and the population unable to keep their home adequately warm. People at risk of poverty or social exclusion in different zones had a significant impact on energy poverty indicators. A separate analysis is made for those EU states with the highest energy import dependency and the implications of the results are discussed.

Waste-to-energy as a tool of circular economy: Prediction of higher heating value of biomass by artificial neural network (ANN) and multivariate linear regression (MLR).

Circular economy is a global trend as a promising strategy for the sustainable use of natural resources. In this context, waste-to-energy presents an effective solution to respond to the ever-increasing waste generation and energy demand duality. However, waste diversity makes their management a serious challenge. Among their categories, biomass waste valorization is an attractive solution energy regarding its low cost and raw materials availability. Nevertheless, the knowledge of biomass waste characteristics, such as composition and energy content, is a necessity. In this research, new models are developed to estimate biomass wastes higher heating value (HHV) based on the ultimate analysis using linear regression and artificial neural network (ANN). The quality-measure of the two models for new dataset was evaluated with statistical metrics such as coefficient of correlation (R), root mean squared error (RMSE), mean absolute error (MAE) and mean absolute percentage error (MAPE). The methods developed in this work provided attractive accuracies comparing to other literature models. Additionally, it is found that the ANN, as machine learning method, is the best model for biomass HHV prediction (R = 0.75377, RMSE = 1.17527, MAE = 0.93315 and MAPE = 5.73%). Therefore, obtained results can be widely employed to design and optimize the reactors of combustion. In fact, the developed ANN software is a simple and accurate tool for HHV estimation based on ultimate analysis. Indeed, ANN is one of the most applicable and widely used software in the field of waste-to-energy.