Total CO2 Emissions Research Articles

Design and control of a novel multi-product extractive dividing wall column process for recycling organics from wastewater

The wastewater from a pharmaceutical plant consists of a tetrahydrofuran/isopropanol/water azeotrope. This investigation utilizes dimethyl sulfoxide as an extractant and employs an extractive dividing wall column to separate the aforementioned azeotrope. The extractive dividing wall columns are constructed with single, double, and triple partition walls, and a multi-objective genetic algorithm is used to optimize the operational parameters of the separation process. Of these columns, the extractive dividing wall columns with triple partition walls show the most favorable economic, environmental, and energy utilization performance, and it has a lower risk of combustion and explosion. Compared to the conventional design, the use of triple-partition extractive dividing wall columns results in a 22.13 % and 10.54 % reduction in total annual cost and CO2 emissions, respectively, and an increase in thermodynamic efficiency of 2.66 %. Studying the dynamic characteristics of this process reveals its excellent dynamic controllability.

How much does overnutrition weigh? The environmental and social impacts of Metabolic Food Waste in Italy

Excess Food Energy Intake (EFEI), namely Metabolic Food Waste (MFW) corresponds to excess calorie intake related to overconsumption of food and is responsible for overweight (OW) and obesity (OB) conditions. Identifying its causes and impacts could be important, so that it can be prevented and reduced, generating health, environmental and societal benefits. Therefore, this research quantifies MFW among OW and OB adult populations (18–75 years) in Italy and its environmental and social implications. Life cycle assessment (LCA) through the Simapro 9.5 software was used and then, the results were monetized according to the Environmental Price Handbook to understand the real environmental cost. Finally, Social LCA (S-LCA) was considered following the Product Social Impact Assessment (PSILCA) guidelines to understand the potential social risks behind the food that ends up on our plates. The results highlight the amount of MFW in Italy is 2696 billion kcal/year corresponding to 1.59 Mtons over-consumed food/year, while the impacts are mainly related to global warming (8.78 Mtons CO2 eq/year, or 2.29 % of the total Italian CO2 emissions), terrestrial ecotoxicity (843,451 tons 1.4-DCB/year), freshwater ecotoxicity (222,483 tons 1.4 DCB eq/year), and land consumption (8 million m2a eq/year), mostly due to the meat, fats and oils and sweets overconsumption. Impacts monetization also shows that MFW could induce an environmental price of € 1340/per capita/year, and finally, the S-LCA reveals how overconsumption of food has the potential to affect gender discrimination, water depletion, trade union, and social discrimination due to the high proportion of labor migrants in the agricultural sector.

Energy Consumption and Saved Emissions of a Hydrogen Power System for Ultralight Aviation: A Case Study

The growing concern about climate change and the contemporary increase in mobility requirements call for faster, cheaper, safer, and cleaner means of transportation. The retrofitting of fossil-fueled piston engine ultralight aerial vehicles to hydrogen power systems is an option recently proposed in this direction. The goal of this investigation is a comparative analysis of the environmental impact of conventional and hydrogen-based propulsive systems. As a case study, a hybrid electric configuration consisting of a fuel cell with a nominal power of about 30 kW, a 6 kWh LFP battery, and a pressurized hydrogen vessel is proposed to replace a piston prop configuration for an ultralight aerial vehicle. Both power systems are modeled with a backward approach that allows the efficiency of the main components to be evaluated based on the load and altitude at every moment of the flight with a time step of 1 s. A typical 90 min flight mission is considered for the comparative analysis, which is performed in terms of direct and indirect emissions of carbon dioxide, water, and pollutant substances. For the hydrogen-based configuration, two possible strategies are adopted for the use of the battery: charge sustaining and charge depleting. Moreover, the effect of the altitude on the parasitic power of the fuel cell compressor and, consequently, on the net efficiency of the fuel cell system is taken into account. The results showed that even if the use of hydrogen confines the direct environmental impact to the emission of water (in a similar quantity to the fossil fuel case), the indirect emissions associated with the production, transportation, and delivery of hydrogen and electricity compromise the desired achievement of pollutant-free propulsion in terms of equivalent emissions of CO2 and VOCs if hydrogen is obtained from natural gas reforming. However, in the case of green hydrogen from electrolysis with wind energy, the total (direct and indirect) emissions of CO2 can be reduced up to 1/5 of the fossil fuel case. The proposed configuration has the additional advantage of eliminating the problem of lead, which is used as an additive in the AVGAS 100LL.

Exploring the potential of a novel passenger transport model to study the decarbonization of the transport sector

To explore sustainability strategies in the transport sector in a holistic way, a model dedicated to passenger transportation has been created as a part of the multiregional WILIAM model (Within Limits Integrated Assessment Model). Based on system dynamics, our model increases the diversity of existing passenger transport models within Integrated Assessments Models by offering a detailed representation of the dynamics of the transition for different technologies and transport modes combining technological and behavioural changes. It calculates the energy demand, direct emissions and additional material requirements of the transport sector and can be linked to other submodules of WILIAM to study different feedback loops. Here we report the validation of the offline model and illustrate its usefulness and practical applicability. First, a Baseline transport scenario for Spain was developed and parametrized. This scenario describes the plausible evolution of the Spanish passenger transport system in the absence of ambitious environmental policies but nevertheless achieves a reduction of total direct CO2 emissions from passenger transport from 66 Mt CO2/year in 2022 to 60 Mt CO2/year in 2035, after which emissions remain constant until 2050. Subsequently, following the Avoid-Shift-Improve approach, various behavioural change measures and technological improvements were introduced. The comparison of the different modelled measures reveals that the most effective tested strategy to reduce direct emissions is the transition to battery electric power trains for cars, buses, and motorcycles, however at the cost of the highest material requirements. Further work will be dedicated to the study of the implications of the link of this submodule with the rest of WILIAM.

A CRITICAL EXAMINATION OF THE CONSTRUCTION SECTOR IN TURKEY IN TERMS OF SUSTAINABILITY

The construction sector is of critical importance for economic growth and employment creation. However, it also has significant environmental impacts, including high energy consumption, extensive use of natural resources, and substantial waste production. Currently, the construction sector in Turkey accounts for 35% of the country’s total energy consumption, making it a significant energy consumer. Research conducted in European Union countries indicates that buildings are responsible for 40% of total energy consumption and 36% of total CO2 emissions. It is believed that a similar situation exists in Turkey. Furthermore, the long lifespan of structures built in the sector is of great importance for sustainability. The contribution of poor-quality and unhealthy structures to environmental stress further highlights the role of the construction sector in sustainability. The study addresses the impacts of strategic goals such as the design and construction of sustainable building models, the recyclability and reuse of building materials, energy efficiency, and the reduction of CO2 emissions on the construction sector. The findings indicate that the integration of energy efficiency and renewable energy technologies is crucial for the Turkish construction sector to move towards a sustainable future. In this context, it is recommended that the Turkish construction sector implement the necessary steps and engage in strategic planning in order to achieve its sustainability goals. The findings of the study emphasise the pivotal role and significance of the construction sector in this regard.

CO2 emission mitigation of a hybrid photovoltaic and cogeneration system in computer hardware manufacturing industry: A case study in Thailand

Abstract In the wake of COP26 and the growing urgency of addressing climate change, achieving carbon neutrality by 2050 has become a central global objective. This imperative extends to industries like computer hardware manufacturing, which are now actively pursuing decarbonization strategies through the strategic adoption of renewable energy sources and energy efficiency enhancements. This research paper assessed the CO2 emission mitigation potential of a hybrid system of photovoltaic (PV) roof and cogeneration where a large factory of computer hardware manufacturing in tropical Thailand was selected as a study site. On one hand, a one-Megawatt photovoltaic system was installed over the roof of the production building to generate electricity from solar radiation to serve the building. On the other hand, a twenty-four-Megawatt cogeneration system of gas engines as the prime mover was used to supply power to meet the building’s electricity demand. Waste heat from the gas engine was used by the absorption chiller to generate chilled water for cooling inside the building. Based on the system equipment specifications, the annual simulation using Thailand’s solar radiation showed that the installed photovoltaic system could generate electricity of 1,412.4 MWhelec/year while the implementation of the absorption chillers for cooling helped to reduce the electrical energy consumed by the traditional electric chiller by 10,211.4 MWhelec/year. In our study case where the CO2 emission of the grid power was 0.4758 kgCO2/kWhelec in the year 2022 and was reduced to 0.350 kgCO2/kWhelec in the year 2050, the total CO2 emission mitigation from the hybrid photovoltaic and cogeneration system with the genset efficiency of 50% and the waste heat recovery of 60% could reduce approximately 207,388.5TonCO2 for over 20 years as compared to the scenario where the grid electricity alone powered the building. These findings underscored the critical role of the proposed hybrid system in addressing the climate crisis and exemplified how the industry could make meaningful strides toward more environmental sustainability.

CALCULATION OF CO2 AND O2 NEEDS AS WELL AS CO2 ABSORPTION AND O2 PRODUCING IN ZONE 5 GREEN OPEN SPACES YOGYAKARTA STATE UNIVERSITY

Carbon dioxide (CO2) produced by smoke can produce humans if there are no trees or green open spaces that can absorb CO2 and emissions resulting from human activities. Therefore, efforts to reduce air pollution such as CO2 gas in the campus environment, especially Zone 5 of Yogyakarta State University are ways to build green open spaces. This study suggests to calculate the amount of CO2 emitted and the amount of O2 needed in Zone 5 of Yogyakarta State University that emits emissions from vehicles that are channeled and breathed by humans equipped with functions that absorb CO2 and produce O2. The estimation results show that total CO2 emissions in Zone 5 of Yogyakarta State University in 2019 were 7,479,066 tons / year while the demand for O2 in Zone 5 of Yogyakarta State University in 2019 was 6,763,027 tons / year. So the ability of green open space to absorb CO2 is 3.070,1308 tons/ year and the ability to produce O2 is 131,807 tons / year

The Specific and Total CO2 Emission Activity of Wood-Decaying Fungi and Their Response to Increases in Temperature.

The CO2 emission activity of xylotrophic fungi responding to an increase in temperature in the range of 10-30 °C with pure dikaryotic cultures of Fomes fomentarius s. str., F. inzengae, Fomitopsis betulina, F. pinicola, and Phellinus igniarius was analyzed. Emission activity was assessed by the difference in CO2 concentration in 0.5 L exposure chambers with Petri dishes with mycelium growing on agar at the beginning of exposure and an hour later using a Gasmet DX-4030 FTIR spectrometer (Gasmet Technologies Oy, Finland), error measurements ±50 ppm. Specific (μg CO2/cm2/h) and total (μg CO2/h) emission activity and its relationship with temperature and size (area) of the mycelium were assessed. It is shown that in the range of 10-30 °C, the specific and total CO2 emission activity of the mycelium is closely and positively related to temperature. Specific emission, which is an indicator of the respiratory activity of the mycelium, does not depend on its size; its only driver is temperature, the relationship with which is linear: an increase in temperature by 10 °C causes an increase in the specific emission activity of the mycelium by 1.7 times. The total CO2 emission activity, which is an indicator of the total amount of CO2 emitted, is directly proportional to the specific emission activity and the size of the mycelium. In the range of 10-30 °C, an increase in temperature causes an almost equal increase in both the specific emission activity of the mycelium (Q10 1.7) and its growth (Q10 1.5) and causes an exponential increase in the total emission of CO2. This must be taken into account when predicting CO2 emissions from woody debris under climate change, as it could potentially contribute to accelerating climate change.

A shared ride matching approach to low-carbon and electrified ridesplitting

Ridesplitting has the potential to enhance transportation efficiency and reduce CO2 emissions from ridesourcing services by matching multiple shared rides to the same trip. However, an inappropriate matching can significantly diminish the environmental performance of ridesplitting. This study aims to propose a shared ride matching approach to low-carbon and electrified ridesplitting. Firstly, feasible ridesplitting trips within time constraints are identified and represented using a shareability network. Subsequently, the CO2 emission reduction of each feasible ridesplitting trip is calculated by comparing it with its corresponding single ride alternative. To maximize the total CO2 emission reduction from ridesplitting trips, an optimization model for shared ride matching is established and solved using a graph-theoretic algorithm. Additionally, a priority assignment policy is designed to preferentially assign available electric vehicles to feasible ridesplitting trips that have greater potential for emission reductions. Comparative experiments conducted in Chengdu, China show that the proposed approach can achieve higher levels of CO2 emission reduction without compromising service quality in ridesplitting operations. Furthermore, significant improvements in emission reductions can be achieved by implementing the priority assignment policy instead of a random assignment policy for electrified ridesplitting trips, particularly when electric vehicles are limited. Finally, the effects of maximum tolerable delay and electric vehicle penetration are further analyzed to provide valuable insights for the government and ridesourcing companies aiming to enhance both the economic and environmental benefits associated with ridesplitting.

The research on the mechanical properties, microstructure, environmental impacts of environmentally friendly Alkali-activated ultra high performance concrete (AAUHPC) matrix with varied design parameters

Alkali-activated material prepared by the silicon aluminum solid wastes are commonly considered as the low-carbon cementitious material, which has important significance for promoting the sustainable development of construction materials. The mechanical properties, reaction mechanisms, and microstructure evolutions of Alkali-activated Ultra High Performance Concrete (AAUHPC) matrix with 7 design parameters were comprehensively studied through testing the fluidity, 28 days compressive strength, 28 days flexural strength, hydration heat, and microstructures. The environmental impacts including carbon emissions and energy consumption are evaluated. Appropriately increasing Na2O dosage, silicate modulus (Ms), and granulated blast furnace slag (GBFS) to fly ash (FA) mass ratio (GBFS/FA) and decreasing silica fume (SF) content and water to binder ratio (W/B) are conducive to accelerating the early reaction of AAUHPC. High Na2O dosage, Ms, SF content, and W/B are not conducive to increasing the 3 days reaction degree of AAUHPC, while the moderate GBFS/FA is corresponding to the higher 3 days reaction degree of AAUHPC. The optimal Na2O dosage, Ms, GBFS/FA, SF content, sand to binder ratio (S/B), fine sands content in quartz sands, W/B are 8 %, 1.4, 4.5:1, 10 %, 1.0, 50 %, and 0.34 for the 28 days mechanical properties. The acquired AAUHPC matrix with fluidity of 218 mm and the lowest porosity has 28 days compressive strength of 114.8 MPa and 28 days flexural strength of 10.6 MPa, whose microstructure has more high polymerization degree C(N)-A-S-H gels with higher Al/Si, lower Na/Al, and lower Ca/Si molar ratios. Compared to the traditional Ultra High Performance Concrete (UHPC), the environmentally friendly AAUHPC can reduce the carbon emission by 42%–52 % and the energy consumption by 5%–18 %. The total CO2 emission of per unit compressive strength (1.0 MPa) of concrete per cubic meter (CI) is in range of 2.5–3.7 kg, which is significantly lower than the traditional UHPC (6.98 kg/MPa•m3).

Multi-Objective Optimization of an Energy Community Powered by a Distributed Polygeneration System

This paper presents a multi-objective optimization model for the integration of polygeneration systems into energy communities (ECs), by analyzing a case study. The concept of ECs is increasingly seen as beneficial for reducing global energy consumption and greenhouse gas emissions. Polygeneration systems have the potential to play a crucial role in this context, since they are known for producing multiple energy services from a single energy resource, besides the possibility of being fed also by renewable energy sources. However, optimizing the configuration and operation of these systems within ECs presents complex challenges due to the variety of technologies involved, their interactions, and the dynamic behavior of buildings. Therefore, the aim of this work is developing a mathematical model using a mixed integer linear programming (MILP) algorithm to optimally design and operate polygeneration systems integrated into ECs. The model is applied to a case study of an EC comprising nine buildings in a small city in the northeast of Italy. The work rests on the single- and multi-objective optimization of the polygeneration systems taking into account the sharing of electricity among the buildings (both self-produced and/or the purchased from the grid), as well as the sharing of heating and cooling between the buildings through a district heating and cooling network (DHCN). The main results from the EC case study show the possibility of reducing the total annual CO2 emissions by around 24.3% (about 1.72 kt CO2/year) while increasing the total annual costs by 1.9% (about 0.09 M€/year) or reducing the total annual costs by 31.9% (about 1.47 M€/year) while increasing the total annual CO2 emissions by 2.2% (about 0.16 kt CO2/year). The work developed within this research can be adapted to different case studies, such as in the residential–commercial buildings and industrial sectors. Therefore, the model resulting from this work constitutes an effective tool to optimally design and operate polygeneration systems integrated into ECs.

Floodplain carbon dioxide emissions strongly exceed those of the main river stem: A case study of the Ob River, western Siberia

The importance of floodplains in carbon (C) evasion from the lotic systems is especially important in continental plains of low runoff such as the organic-rich Western Siberian Lowland (WSL). To quantify the relative importance of the floodplain compared to main stem CO2 emissions, we monitored a large region of the Ob River’s middle course (permafrost-free zone) over 3 months from spring to summer. We calculated seasonal water coverage using remote sensing, GIS and hydrologically-based approaches and measured CO2 emissions using floating chambers. There was a strongly pronounced seasonality in the water area’s extent of the floodplain with water covering > 40 % of land during the ∼ 30 days of the most intensive spring flood (May – June) and subsequently declining to ≤ 10 % during summer (July-August). Maximal CO2 emissions were recorded in most shallow water bodies of the floodplain, notably in temporary flooded fens and birch forests. The CO2 emissions during the study period ranged from 0.2 ± 0.2 to 0.9 ± 0.2 g Cm−2 d-1 for the floodplain and 0.03 ± 0.34 g C m−2 d-1 for the Ob’s main channel.CO2 emissions from the floodplain were ∼ 163 ± 20 t C per km for the river’s main stem during the 95 day study period. The partial contributions of temporary flooded zones, main stem, and permanent lakes / secondary channels to total emissions (1820 km² area) were 70, 16, and 14 %, respectively. Over spring and summer seasons, contributions from flooded zones ranged from 43 to 99 % of total CO2 emissions from water surfaces of the Ob River’s middle course. Extrapolation of obtained results to the entire territory of the Ob River floodplain indicates that not accounting for the floodplain emissions may sizably—up to an order of magnitude—underestimate the CO2 emissions from riverine systems in Western Siberia during open water period. Future work on the Ob River floodplain in the permafrost-bearing zone should be prioritized and would allow adequate upscaling of C emission from this environmentally important territory.

EcoMRL: Deep reinforcement learning-based traffic signal control for urban air quality

As greenhouse gas (GHG) emissions from road networks significantly impact the urban environment, there has been a growing interest in integrating environmental factors into traffic controls. Traffic signal control (TSC) is an effective method to reduce air pollution by managing traffic congestion. Accordingly, several recent studies have applied artificial intelligence to TSC to improve traffic efficiency. Despite these efforts, there are a few limitations on the existing studies. First of all, a number of recent studies focus only on traffic performance rather than environmental effects. However, in some cases, the objective function related to traffic efficiency can have an adverse effect on the environment. Furthermore, the variable nature of emissions based on traffic demand is rarely considered. To address these issues, we propose a multi-agent deep reinforcement learning-based TSC to minimize GHGs in traffic networks. To this end, we first identify vehicle’s stop and delay as key factors in traffic efficiency that critically influence air quality. Subsequently, we integrate these factors into our model’s reward function. To validate the proposed model, we conduct experiments under various demand scenarios featuring different traffic volume levels. The results show that the proposed model outperforms comparative control methods in two aspects: traffic performance and environmental sustainability. Especially at a high congestion level, the proposed model reduces average delay time by 11.9–16.1% and increases total throughput by 11.5%. Additionally, it significantly lowers total CO2 emissions by up to 8.9% and average emissions by up to 18.3%.

Polystyrene microplastics facilitate formation of refractory dissolved organic matter and reduce CO2 emissions

Microplastics, as a type of anthropogenic pollution in aquatic ecosystems, affect the carbon cycle of organic matter. Although some studies have investigated the effects of microplastics on dissolved organic matter (DOM), the impact of alterations in the chemical properties of microplastics on refractory DOM and carbon release remains unclear. Here, we observed that microplastic treatments (e.g., polystyrene, PS) altered the composition and function of microbial community, notably increasing the abundance of microbial families involved in consuming easily degradable organic matter. During the process in which microbial community decomposed organic matter into DOM, PS underwent surface oxidation. The oxidized PS aggregated with DOM and microorganisms through electrostatic interactions and chemical bonds. Moreover, these interactions between oxidized PS and microbial community affect the utilization of organic matter, resulting in a significant decrease in CO2 emissions. Specifically, total CO2 emissions decreased by approximately 23.76 % with 0.1 mg/L PS treatment and by 44.97 % with 10 mg/L PS treatment compared to those in PS-free treatments over the entire reaction. These findings underscored the significance of the chemical properties of PS in the interactions among DOM and microorganisms, emphasizing the potential impact of PS microplastics on the carbon cycle in ecosystems.

Integrated Approach of Retrofitting an Existing Residential Building to a Nearly Zero Energy Building with Simultaneous Seismic Upgrading

Introduction The current study's goal is to apply an integrated approach of retrofitting a typical building in Cyprus that was designed and constructed for the refugee settlements in the period 1975-1985. The existing building is retrofitted to a nearly zero-energy building. Methods This typical type of building examined represents approximately 15,347 houses and stands for 3.57% of households in Cyprus. This percentage is considered significant with regards to energy consumption, as this type of structure has an estimated energy consumption of 1000 kWh/m2/y and CO2 emissions of 293.74kg CO2/m2/y. This corresponds to 0.293 Mt CO2/y, which stands for 4.18% of total CO2 emissions in Cyprus for 2011, based on the latest IEA (International Energy Agency) data. An integrated approach is followed for the retrofitting of the existing building, which involves both energy and structural upgrades, taking into account the earthquake resistance upgrade. Since Cyprus is in a highly seismic region, an important factor in this approach is the ability of the structure to survive a strong earthquake during its remaining lifetime, according to the design criteria. The study presents and discusses three possible coalitions with multiple scenarios of approaching the upgrade of the existing building. In each coalition, various criteria and implementation actions are considered based on the energy consumption, the CO2 footprint, and the seismic resistance. Results The study also investigates whether the extension of life expectancy of the existing structure through earthquake resistance upgrade will have a positive or negative effect on the CO2 life cycle footprint and cost of the building. Results show that for the examined typical building, simultaneous energy and earthquake resistance upgrade is more efficient in terms of cost and environmental impact. The building with the smallest construction age had the smallest Decision-Making Index (DMI) from the A, B and C coalitions. Conclusion It is important that for an existing building, the option to remain in its original state (coalition A) without any upgrading intervention is not the most favorable option. Therefore, the need to evaluate the existing building stock and plan the upgrade of the buildings in question is of utmost importance.

Impacts of forest plantation programs on sectoral CO2 emissions regionally in New Zealand

Investing in projects that support environmental benefits, such as tree harvesting, has the potential to reduce air pollution levels in the atmosphere in the future. However, this kind of investment may increase the current level of emissions. Therefore, it is necessary to estimate how much the policy affects the current level of CO2 emissions. This makes sure the policy doesn’t increase the level of CO2 emissions. This study aims to analyze the effect of the One Billion Trees program on CO2 emissions in New Zealand by employing the 2020 input–output table analysis. This investigation examines the direct and indirect effects of policy on both the demand and supply sides across six regions of New Zealand. The results of this study for the first year of plantation suggest that the policy increases the level of CO2 emissions in all regions, especially in the Waikato region. The direct and indirect impact of the policy leads to 64 kt of CO2 emissions on the demand side and 270 kt of CO2 emissions on the supply side. These lead to 0.19 and 0.74% of total CO2 emissions being attributed to investment shocks. Continuing the policy is recommended, as it has a low effect on CO2 emissions. However, it is crucial to prioritize the use of low-carbon machinery that uses fossil fuels during the plantation process.

Experimental investigation of BIPV/T application in winter season under Şanlıurfa's meteorological conditions

AbstractConsidering that nearly 39% of the total CO2 emission released into the atmosphere today are thought to be due to the energy consumed by buildings, the importance of taking measures through buildings to combat global warming is evident. Therefore, the concept of nearly zero‐energy buildings (NZEB) is come to the forefront. Building integrated photovoltaic thermal (BIPV/T) systems are used to enable buildings to generate their own energy. However, buildings have limited facade and roof areas required for BIPV/T systems. Therefore, in this study, various configurations of bifacial (double‐sided) and monofacial (single‐sided) panels were compared to investigate ways to enhance the efficiency of BIPV/T systems. Different air flow velocities and varying air gap distances were tested for both panel types. By placing a reflective surface on the wall behind the bifacial panel, the electrical efficiency of the bifacial panel was increased and proven through PVsyst analysis. Both panels provided maximum heat efficiency at the shortest air gap distance under high air flow conditions. In addition, it was shown in both the experimental setup and Comsol CFD analysis that it provides significant benefit in the thermal energy load of the building when heating the interior environment in winter. In terms of electrical power production surplus, the bifacial panel outperformed the monofacial panel in all configurations, with a minimum advantage of 8.33% and a maximum of 12.73%. Additionally, the maximum electrical efficiency was obtained from the bifacial panel in configurations with the longest air gap distance. Using the bifacial panel in the BIPV/T system with the shortest air gap distance during the heating season and the longest air gap distance during other seasons can provide the highest efficiency for the building throughout the year.

Travel-associated carbon emissions of patients receiving cancer treatment from an urban safety net hospital.

e13812 Background: Climate change is one of the grand challenges of the 21st century. The U.S. currently emits 11% of the annual global greenhouse gases, and 8-10% of its emissions result from the healthcare industry. Studies on the contribution of patients' commute for cancer treatment to healthcare-associated CO2 emissions remain limited. This study aims to determine the CO2 emissions of patients’ commute for cancer treatment among patients with malignancies at an urban safety net hospital. Methods: We conducted a retrospective study of patients seen at an oncology clinic from July 1, 2022 - June 30, 2023. Demographic data, data on visit diagnosis and indication (e.g., laboratory, infusion, or follow-up visits), and patients' home addresses were collected from the EMR. Distance between patients’ homes and the hospital was calculated using a Google Map API and a macro for distance. Total CO2 emissions from patients’ travel in miles were estimated at 400 grams of CO2 per mile based on the Environmental Protection Agency’s estimate of the average CO2 emissions for a passenger vehicle. The primary outcome was CO2 emissions from patients’ round-trip travel. The total estimated CO2 emissions were converted to equivalents of coal burned, smartphones charged, and gallons of gasoline used based on the EPA equivalencies calculator. Results: Of the 8,235 visits, 5,095 (61.8%) were follow-up/laboratory visits, and 3,137 (38.1%) were chemotherapy infusion visits. Of the 1,080 patients who attended the clinic, the mean age was 63.8 years, 700 (64.8%) were males, 379 (35.1%) were females, 525 (48.6%) were black or African American, 139 (12.9%) were whites. Breast cancer was the most common diagnosis, with 423 (39.2%) of patients. Each patient traveled an average of 9.6 miles round trip (Range = 0.7-298.6 miles) to receive cancer care. An estimated 1,520 grams of CO2 was emitted for each patient’s visit. A total of 79,582 round trip miles was made in 8,235 visits, which corresponds to 31,832 kg of CO2 emissions, equivalent to 35,658 pounds of coal burned, 1,462 propane cylinders used for a home, or 3,872,250 smartphones charged. Conclusions: Cancer care is associated with significant CO2 emissions. Efforts to decrease the overall carbon footprint of cancer treatment through adoption of telemedicine and alternative treatment schedules, are needed to reduce the effect of cancer treatment on the climate. [Table: see text]

Energy assessment in rural regions of China with various scenarios: Historical–to–futuristic

Approximately 172 million rural households in China in 2022, will still rely on traditional biofuels instead of electricity. This study explores the feasibility of achieving rural electrification in China utilization various Energy origins and assesses its potential impact on climate change mitigation. To do so, we employ the Regional Energy Model (REM) to formulate hypotheses for rural power distribution. Covering the era from 2020 until 2050. We evaluate consequences in terms of greenhouse gas discharges, principal energy consumption, associated expenses by comparing these possibilities with a Business-as-Usual (BU) scenario. Our findings reveal that diesel-based arrangements tend to produce ‘the maximum Carbon Dioxide (CO2) emissions, trailed by network-based solutions. Electrification focused on renewable energy-driven applications has the potential to reduce total CO2 emissions by up to 97 % and primary energy consumption by 43 % in 2050 compared to the BU scenario. We also find that electrification through decentralized diesel systems tends to be the priciest choice. Rural electrification utilizing renewable energy emerges as a cost-effective choice when the majority of end-use applications rely on renewable energy sources. However, it becomes less economical than network expansions when electric end-user appliances are predominant. In summary, this study investigates the viability of renewable energy for rural power distribution and its role in climate change abatement in rural China, offering policy suggestions.

Supply chain network design based on Big Data Analytics: heuristic-simulation method in a pharmaceutical case study

Digital technology is a pivotal aspect of the ongoing digital transformation upon which supply chain networks (SCNs) heavily rely. Through the utilization of Big Data Analytics (BDA), organizations can gain insights into sales, production and formulate decision support systems. The pharmaceutical supply chain emerges as a crucial player in producing and distributing medications vital for treating COVID-19 patients. In this study, we have innovatively designed a multi-echelon Pharmaceutical Supply Chain Network (PSCN) using BDA during the COVID-19 pandemic. We have developed a novel Mixed-Integer Non-Linear Programming model addressing allocation, production planning, and inventory control decisions, known as the LAPI problem. A transformation method is employed to convert the non-linear model into a linear one to enhance computational efficiency. The primary objective of our mathematical model is to minimize the total cost and CO2 emissions of the transportation system and established centres while maximizing the shelf life of medicines. Our experiments reveal that medium- and large-scale problems, characterized by the three main attributes of BDA – variety, velocity and volume (3 V‟s), pose challenges for optimal solutions. We present a case study of Iran to validate the mathematical model for large-scale problems. Employing a simulation approach, we estimate the demand for required pharmaceuticals, underscoring our proposed model’s real-world applicability and effectiveness. This research contributes to the growing necessity of eco-friendly and efficient supply chain strategies, especially in the critical domain of pharmaceuticals during pandemic situations.