Increased Greenhouse Gas Emissions Research Articles

Reducing carbon footprints and increasing net ecosystem economic benefits through dense planting with less nitrogen in double-cropping rice systems

Excessive application of nitrogen fertilization in farmland systems can cause nitrogen wastage, environmental pollution, and increase greenhouse gas (GHG) emissions. Dense planting is one of the efficient strategies for nitrogen fertilizer reduction within rice production. However, there are paying weak attention to the integrative effect of dense planting with less nitrogen (DPLN) on carbon footprint (CF), net ecosystem economic benefit (NEEB) and its components in double-cropping rice systems. Herein, this work aims to elucidate the effect via field experiments in double-cropping rice cultivation region with the treatments set to conventional cultivation (CK), three treatments of DPLN (DR1, 14 % nitrogen reduction and 40,000 hills per ha density increase from CK; DR2, 28 % nitrogen reduction and 80,000 hills density increase; DR3, 42 % nitrogen reduction and 120,000 hills density increase), and one treatment of no nitrogen (N0). Results showed that DPLN significantly reduced average CH4 emissions by 7.56 %–36 %, while increasing annual rice yield by 2.16 %–12.37 % compared to CK. Furthermore, the paddy ecosystem under DPLN served as a carbon sink. Compared with CK, DR3 increased gross primary productivity (GPP) by 16.04 % while decreasing direct GHG emissions by 13.1 %. The highest NEEB was observed in DR3, which was 25.38 % greater than CK and 1.04-fold higher than N0. Therefore, direct GHG emissions and carbon fixation of GPP were key contributors to CF in double-cropping rice systems. Our results verified that optimizing DPLN strategies can effectively increase economic benefits and reduce net GHG emissions. DR3 achieved an optimal synergy between reducing CF and enhancing NEEB in double-cropping rice systems.

Smart charging strategy for electric vehicles based on marginal carbon emission factors and time-of-use price

As the penetration of electric vehicles (EVs) has grown rapidly in recent years, the stability and safety of electric grids are inevitably affected. Uncontrolled EV charging can reduce electric grid efficiency and increase greenhouse gas emissions (GHG). This occurs when EV charging aligns with peak demand, requiring the activation of fossil fuel-powered plants to meet the electricity demand. The time-of-use (TOU) price is a traditional management strategy for smoothing the demand power curve, but it does not consider carbon emissions. This study proposes a smart charging strategy based on an improved local search genetic algorithm (LS-GA) that considers both the TOU price and marginal emission factors (MEF). Over 47,000 charging events from 45 charging stations in Tianjin, a major city in North China, were used to simulate the charging pattern and demand. Four different charging strategies are considered in the study. The results indicate that the proposed smart charging strategy can reduce the cost and carbon emissions by up to 27% and 16% compared with uncontrolled charging, respectively. This study demonstrates the significant potential of using optimization methods in the EV smart charging problem.

The spatial distribution of agricultural emissions in the United States: The role of organic farming in mitigating climate change

Agriculture is a significant contributor to greenhouse gas (GHG) emissions and organic farming practices can potentially offset some of these emissions. However, previous research on the environmental impact of organic agriculture has provided mixed or contradictory results. This study aims to analyze the role that organic farming can play in mitigating agricultural emissions across the United States. Using panel U.S. state-level data, we find evidence that farming activities increase GHG emissions. However, we also find that dedicating a larger share of farmland to organic and pasture farming reduces GHG emissions. A spatial analysis of agricultural emissions that accounts for the role of organic farming provides three key insights. First, the spatial distribution of agricultural GHG emissions in the United States is uneven. Second, agriculture is a significant contributor to GDP within high-emissions states where organic agriculture represents only a small proportion of total farmland. Third, agriculture has a substantially lower contribution to GDP within low-emissions states where organic agriculture represents a large proportion of total farmland. These findings suggest that reducing GHG emissions effectively may necessitate creating and implementing policies and initiatives tailored to specific regions rather than relying on general recommendations. Thus, low-emissions states should be explored as examples of sustainable agricultural practices that could set the stage for scaling up organic farming practices across the country.

Property enhancement on neem biodiesel by varying the temperature of transesterification process

The world's energy demands, with the exception of hydroelectric and nuclear power, are met mostly by coal, natural gases and petrochemicals. At the present pace of use, all of these finite resources will be gone in no time. Using petroleum and other nonrenewable energy sources comes with a number of downsides, such as increased greenhouse gas emissions, high processing costs and energy demands, and so on. This has prompted the search for viable alternatives to petroleum-based energy. Alternate fuels for internal combustion engine are the wide range of research area. Among that field fuels from the nonedible vegetable oils got more preference. In this study focused on the improvement of the bio fuel properties by means of varying the parameter of the processing. Biodiesel can be derived from the need seed vegetable oil by transesterification process. The temperature maintained for this process was taken as influencing parameter for the properties enhancement. This temperature varied from 45 ℃ – 65 ℃ with increment of 5 ℃ in separate process. The corresponding fuel properties were measured and compared to identify the suitable temperature for the greatest fuel properties.

Utilization of Free Trade Agreements to Minimize Costs and Carbon Emissions in the Global Supply Chain for Sustainable Logistics

Background: Since global warming is a crucial worldwide issue, carbon tax has been introduced in the global supply chain as an environmental regulation for the reduction of greenhouse gas (GHG) emissions. Costs, GHG emissions, and carbon tax prices differ in each country due to economic conditions, energy mixes, and government policies. Additionally, multiple countries have signed a Free Trade Agreement (FTA). While FTAs result in their economic benefit, they also increase the risk of carbon leakage, which increases GHG emissions in the global supply chain due to relocation production sites from a country with stricter emission constraints to others with laxer ones. Method: This study proposes a mathematical model for decision support to minimize total costs involving carbon taxes with FTAs. Results: Our model determines suppliers, factory locations, and the number of transported parts and products with costs, FTAs, carbon taxes, and material-based GHG emissions estimated using the Life Cycle Inventory (LCI) database. The FTA utilization on the global low-carbon supply chain is examined by comparing the constructed supply chains with and without FTAs, and by conducting sensitivity analysis of carbon tax prices. Conclusions: We found that FTAs would not cause carbon leakage directly and would be effective for reducing GHG emissions economically.

The role of peatland degradation, protection and restoration for climate change mitigation in the SSP scenarios

Peatlands only cover a small fraction of the global land surface (∼3%) but store large amounts of carbon (∼600 GtC). Drainage of peatlands for agriculture results in the decomposition of organic matter, leading to greenhouse gas (GHG) emissions. As a result, degraded peatlands are currently responsible for 2%–3% of global anthropogenic emissions. Preventing further degradation of peatlands and restoration (i.e. rewetting) are therefore important for climate change mitigation. In this study, we show that land-use change in three SSP scenarios with optimistic, recent trends, and pessimistic assumptions leads to peatland degradation between 2020 and 2100 ranging from −7 to +10 Mha (−23% to +32%), and a continuation or even an increase in annual GHG emissions (−0.1 to +0.4 GtCO2-eq yr−1). In default mitigation scenarios without a specific focus on peatlands, peatland degradation is reduced due to synergies with forest protection and afforestation policies. However, this still leaves large amounts of GHG emissions from degraded peatlands unabated, causing cumulative CO2 emissions from 2020 to 2100 in an SSP2-1.5 °C scenario of 73 GtCO2. In a mitigation scenario with dedicated peatland restoration policy, GHG emissions from degraded peatlands can be reduced to nearly zero without major effects on projected land-use dynamics. This underlines the opportunity of peatland protection and restoration for climate change mitigation and the need to synergistically combine different land-based mitigation measures. Peatland location and extent estimates vary widely in the literature; a sensitivity analysis implementing various spatial estimates shows that especially in tropical regions degraded peatland area and peatland emissions are highly uncertain. The required protection and mitigation efforts are geographically unequally distributed, with large concentrations of peatlands in Russia, Europe, North America and Indonesia (33% of emission reductions are located in Indonesia). This indicates an important role for only a few countries that have the opportunity to protect and restore peatlands with global benefits for climate change mitigation.

Directions, experience and prospects for the implementation of carbon projects in Russia

At the moment, the problem of increasing greenhouse gas emissions is global, requiring prompt action to mitigate the effects of global climate change. In recent decades, there has been a clear correlation between global climate change and an increase in greenhouse gas emissions of anthropogenic origin. The strengthening of the climate agenda is leading to an expansion of activities in the field of developing ways to decarbonize, as a result, business and industry are considering various options for reducing emissions, in particular the implementation of carbon projects. The article summarizes the experience of implementing climate projects in Russia both in the first period of the Kyoto Protocol and under the current legislation. Climate projects implemented at enterprises of various industries in various areas are considered, including projects on energy efficiency, renewable energy sources, forest carbon projects. An overview of joint implementation projects in the following industries is presented: non-ferrous metallurgy, steelmaking, oil refining, energy, chemical industry, etc. Special attention is paid to the description of the prospects for the development of new natural and climatic projects related to wetlands, aimed at the restoration and secondary watering of peatlands. Taking into account the fact that the ability of wetlands in general and peatlands in particular to sequester and store carbon has been sufficiently studied, and Russia has the world's largest peat reserves, it is therefore advisable to use the potential of wetlands for the development and implementation climate projects with subsequent issuance and sale of carbon credits on the national or international markets.

Relationship between carbon emissions, economic growth, renewable energy consumption, foreign direct investment, and urban population in Vietnam

At the 26th UN Climate Change Conference in late 2021, Vietnam set a target of achieving net-zero carbon (CO2) emissions by 2050. However, the country’s rapid economic growth, urbanization, and industrialization have historically relied on coal-based energy, a source of significant greenhouse gas (GHG) emissions. Although contributing only 0.8% of the world’s emissions over the last two decades, Vietnam currently has one of the fastest increasing GHG emissions rates per capita. Over the 2000–2015 period, Vietnam’s per capita gross domestic product increased from $390 to $2,000, and CO2 emissions nearly quadrupled. Hence, this research explores the causal relationships among CO2 emissions, economic growth, foreign direct investment, renewable energy usage, and urban population in Vietnam over the period from 1990 to 2018 using the Environment Kuznets Curve. An autoregressive distributed lag bounds testing technique for measuring integration is utilized to investigate the long-run relationship. Results indicate that economic growth increases with CO2 emissions until a certain threshold level and then CO2 emissions decrease, thereby supporting the environmental Kuznets curve theory for Vietnam. Furthermore, this study examines the causal relationship among variables using a Granger causality model and determines that FDI, urban population, and renewable energy consumption play an important role and have substantial impact on carbon emission in Vietnam.

How Striking Is the Intergenerational Difference in Exposure to Compound Heatwaves Over Southeast Asia?

AbstractSoutheast Asia (SEA) is experiencing rapid warming, leading to more extreme heatwaves. Sustained compound heatwaves, with high temperatures during day and at night, pose profound threats in highly vulnerable regions, resulting in great stress on society. We estimated the changes in the compound heatwave characteristics and population exposure over SEA at the end of the 21st century based on the model outputs from the Coupled Model Intercomparison Project Phase 6. Results show that the projected compound heatwaves have significant intensified over SEA linked to increasing greenhouse gas emissions. Contemporary younger generations will face more potential risks than their parents' generation. A child born in the 2010s will experience 1,000 discrete heatwaves in their lifetime, a threefold increase compared with the 1980s. Climate change and population growth combine to drive increased population exposure. The climate effect accounts for 125% in the 0–24‐year‐old cohort, whereas the interaction effect accounts for 85% in the 75+ age group. The relative importance of effects evolves dynamically across age groups, gradually shifting from a predominance of climate effects to a synergy of the climate and population effects. Significant regional inequalities exist in the increased population exposure over SEA. The largest increase occurs in Indonesia, where the aggregate exposure ranges from 45 billion person‐days under the SSP1‐2.6 scenario to 81 and 108 billion person‐days, respectively, in the higher SSP2‐4.5 and SSP5‐8.5 scenarios. The study emphasizes the need for the SEA countries to focus on heat‐stress adaptation strategies, while also working toward fulfilling emission reduction commitments.

Frontier model of the environmental inefficiency effects on livestock bioeconomy

Background: This work was focused on measuring environmental inefficiency in Mexican dairy farms, considering climate change variables related to the emission of greenhouse gases (GHG) and planetary geomagnetic activity. Methods: The applied methodology measures the eco-efficiency of Mexican dairy farms using the empirical application of a stochastic frontier model of the bioeconomy. The productive sector of the bioeconomy studied was the eco-intensification of the livestock production system (dairies). The environmental inefficiency effect was assumed to be a distribution-independent truncation of a normal distribution with constant variance, while the mean was a linear environmental function of the observable variable. Results: The results showed that the coefficients of the frontier model were highly significant, highlighting the investment in livestock (50%). The inefficiency model had an impact on climate variation with greenhouse gas emissions CH4 (1.96%). The results of the environmental technical efficiency in geometric average were 81.28%. The producers that reached the border with a technical efficiency equal to 1 are the references for the rest, marking the relative technical efficiency. Conclusions: It was concluded that the coefficients in the model were very significant, showing the level of investment in livestock (50%). The low-performance model estimates the impact of climate change on GHG emissions CH4 (1.96%) explaining the trend of increasing GHG emissions, keeping in view that the management of food and cattle during the study period were affected by summer feeding, which allowed considering the activity of GHG emissions. According to the results, the geometric mean environmental performance of engineering is 81.28%.

Complex supply chain structures and multi-scope GHG emissions: the moderation effect of reducing equivocality

PurposeClimate change requires the reduction of direct and indirect greenhouse gas (GHG) emissions, a task that seems to clash with increasing supply chain complexity. This study aims to analyse the upstream supply chain complexity dimensions suggesting the importance of understanding the information processing that these may entail. Reducing equivocality can be an issue in some dimensions, requiring the introduction of written guidelines to moderate the effects of supply chain complexity dimensions on GHG emissions at the firm and supply chain level.Design/methodology/approachA three-year panel data was built with information obtained from Bloomberg, Trucost and Compustat. Hypotheses were tested using random effect regressions with robust standard errors on a sample of 394 SP500 companies, addressing endogeneity through the control function approach.FindingsHorizontal complexity reduces GHG emissions at the firm level, whereas vertical and spatial complexity dimensions increase GHG emissions at the firm and supply chain level. Although the introduction of written guidelines neutralises the negative effects of vertical complexity on firm and supply chain GHG emissions, it is not sufficient in the presence of spatial complexity.Originality/valueThis paper offers novel insights by suggesting that managers need to reconcile the potential trade-off effects on GHG emissions that horizontally complex supply chain structures can present. Their priority in vertically and spatially complex supply chain structures should be to reduce equivocality.

Application of Autoregressive Distributed Lag Model to Assess the Environmental Sustainability in Bangladesh

This research inspects the associations among several macroeconomic factors in Bangladesh using yearly time series data from 1971 to 2019. It also aimed to determine if the environmental Kuznets curve (EKC) hypothesis exists in Bangladesh or not. The findings from the stationarity tests reveal that all variables are ordered I (1) integrated. The ARDL model has been used to explore the longrun and short-run connections between variables in the model. In the long term, the projected findings established the existence of the Kuznets curve hypothesis in the GDP-energy nexus. According to the study, there is a U-shaped association between economic expansion and greenhouse gas emissions. Food production and energy consumption increase emissions, however using biomass does not assist the country to attain sustainability, as an increase in biomass increases greenhouse gas emissions by 1.12%. As a result, our government should explore additional renewable energy sources to restrict emissions and take the required actions in all areas to achieve environmental sustainability. Dhaka Univ. J. Sci. 71(1): 60-68, 2023 (Jan)

Hydrological Functioning and Water Availability in a Himalayan Karst Basin under Climate Change

Karst springs are important water sources for both human needs and environmental flows. The responses of karst springs to hydrometeorological factors vary depending on local conditions. In this study, we investigated Martandnag spring in the Liddar catchment in the Kashmir valley of northern India. We used statistical time series (autocorrelation and cross-correlation) and machine-learning (ML) techniques (random forest regression (RFR) and support vector regression (SVR)) to characterize how rainfall, temperature, and snow cover affect the karst spring flow and predict the future responses of the spring stage based on climate scenarios, in the Intergovernmental Panel on Climate Change Assessment Report 6. The statistical time series showed that the memory effect of Martandnag spring varies from 43 to 61 days, indicating moderate karstification and a relatively high storage capacity of the karst aquifer in the Liddar catchment. The delay between recharge and discharge varies from 13 to 44 days, and it is more strongly correlated to snow/ice melt than to rainfall. The ML analysis shows that SVR outperformed RFR in predicting spring flow. Under all climate scenarios, a trained SVR model showed that spring flow increased during the late winter to early spring, and decreased during the summer (except in August) and in autumn. Scenarios with increased greenhouse gas emissions further reduced flow in the summer and autumn. These predictions can be helpful for water-resource planning in similar watersheds in the Western Himalayas.

Methane emissions and growth performance of beef cattle grazing multi-species swards in different pesticide-free integrated crop-livestock systems in southern Brazil

The aim of this study was to assess the growth performance, forage intake and methane (CH4) emissions by beef cattle grazing under different spatiotemporal integrated crop-livestock systems (ICLSs). The experiment was conducted for two years (2017–2018 and 2018–2019) in warm season perennial pastures and cool season annual pastures grazed by beef steers. Three pesticide-free ICLS treatments – livestock-forestry (LF); crop-livestock (CL), and crop-livestock-forestry (CLF) – plus, a livestock control pesticide-free system (L) were conducted in randomized complete block design, with three replicates per treatment. Maize crop rotation was done with cool season cover crop under no-tillage. Eucalyptus trees (Eucalyptus benthamii) were planted in 2013 and intercropped with tree alleys. The animal performance, organic matter (OM) intake and enteric CH4 emission, yield, and intensity were assessed. We found no significant difference (P > 0.05) for average daily gain (ADG), stocking rate (SR), and daily live weight gain (LWG) per area for the different ICLS arrangements and seasons. The ICLS arrangements did not affect (P > 0.05) CH4 emission, yield, and intensity, with averages of 186 g steer−1 day−1, 26 g kg−1 OM intake and 210 g kg−1 of ADG, respectively. The average CH4 emissions per steer per day, per OM intake, per ADG and LWG per area were greater (P < 0.05) for steers when grazing warm season compared to cool season pastures. The integration or not of beef cattle with crops and/or forestry does not influence CH4 emissions, yield, and intensity by beef steers grazing pastures under moderate grazing intensity. Our results reinforce that well-managed integrated systems are a reliable climate-smart agriculture alternative for increasing production, e.g., grain, wood, meat, and mitigating or without increasing greenhouse gas emissions, such as CH4 from enteric fermentation in beef cattle.

Vehicle-cycle and life-cycle analysis of medium-duty and heavy-duty trucks in the United States

Medium- and heavy-duty vehicles account for a substantial portion (25 %) of transport-related greenhouse gas (GHG) emissions in the United States. Efforts to reduce these emissions focus primarily on diesel hybrids, hydrogen fuel cells, and battery electric vehicles. However, these efforts ignore the high energy intensity of producing lithium (Li)-ion batteries and the carbon fiber used in fuel-cell vehicles. Here, we conduct a life-cycle analysis to compare the impacts of the vehicle manufacturing cycle for Class 6 (pickup-and-delivery, PnD) and Class 8 (day- and sleeper-cab) trucks with diesel, electric, fuel-cell, and hybrid powertrains. We assume that all trucks were manufactured in the US in 2020 and operated over 2021–2035, and we developed a comprehensive materials inventory for all trucks. Our analysis reveals that common systems (trailer/van/box, truck body, chassis, and lift-gates) dominate the vehicle-cycle GHG emissions (64–83 % share) of diesel, hybrid, and fuel-cell powertrains. Conversely, propulsion systems (lithium-ion batteries and fuel-cell systems) contribute substantially to these emissions for electric (43–77 %) and fuel-cell powertrains (16–27 %). These vehicle-cycle contributions arise from the extensive use of steel and aluminum, the high energy/GHG intensity of producing lithium-ion batteries and carbon fiber, and the assumed battery replacement schedule for Class 8 electric trucks. A switch from the conventional diesel powertrain to alternative electric and fuel-cell powertrains causes an increase in vehicle-cycle GHG emissions (by 60–287 % and 13–29 %, respectively) but leads to substantial GHG reductions when considering the combined vehicle- and fuel-cycles (Class 6: 33–61 %, Class 8: 2–32 %), highlighting the benefits of this shift in powertrains and energy supply chain. Finally, payload variation significantly influences the relative life-cycle performance of different powertrains, while LIB cathode chemistry has a negligible effect on BET life-cycle GHGs.

Estimation of Carbon Dioxide Greenhouse Gas Emissions from Household Activities in Bojonegoro Regency

The energy sector from household activities is one of the contributors to carbon dioxide greenhouse gas emissions. The increase in population is a factor that can increase greenhouse gas emissions. This study aims to determine the value of greenhouse gas emissions and to map greenhouse gas emission zones. This research is a quantitative descriptive. The sampling method is simple random sampling and emission zone mapping using ArcMap 10.6. The data in this study were obtained by using questionnaires and direct interviews with respondents. The emission sources analyzed in this study come from the consumption and type of motor vehicle fuel, the consumption and type of cooking fuel, and the consumption of electrical energy. The highest value of greenhouse gas emissions resulting from household activities in Bojonegoro Regency is Balen District with an emission value of 139,048 tons/year. Meanwhile, the lowest greenhouse gas emission is Sekar District with an emission value of 22.725 tons/year. The total emission from household activities in Bojonegoro Regency is 2048,355 tons/year. Emission zone mapping is mapped into 10 zones. Balen sub-district is a sub-district that has the highest CO2 emission value with an emission value of 139,048 tons/year. Sekar, Kasiman, and Kedewan sub-districts are classified as sub-districts that have low CO2 emission values with emission values of 22,725 tons/year, 32,041 tons/year, and 28,498 tons/year.

Adsorption of H2 in porous solid sorbents using a two-phase modelling approach

The increasing energy demand, depleting fossil fuel reserves and increasing greenhouse gas emissions have initiated the search for cleaner and more affordable energy sources. Hydrogen is considered a major energy source due to its high calorific value. The physisorption of H2 on a porous material is an attractive alternative for its storage. This paper presents a two-fluid equation-based model benchmarked against an experimental work on hydrogen storage in an activated carbon packed bed reported in the literature. The computational model is implemented in Ansys Fluent 21.1.0 to solve the hydrodynamic and thermal interaction between the gas and solid phases along with the mass transfer due to adsorption. Adsorption isotherm is calculated from the modified Dubinin-Astakhov (D-A) equation, while the resultant mass transfer is determined from the Linear Driving Force (LDF) model. These equations are incorporated into the model with the help of User Defined Functions (UDF). The predicted pressure, local bed temperature, and adsorption values show a good match with the experimental results. In addition, the sensitivity of different thermal and material properties revealed that a denser adsorbent bed and a high value of thermal properties improve the performance of the H2 storage in the tank.

Advancing the Economic and Environmental Sustainability of the NEWgenerator Nonsewered Sanitation System.

Achieving safely managed sanitation and resource recovery in areas that are rural, geographically challenged, or experiencing rapidly increasing population density may not be feasible with centralized facilities due to space requirements, site-specific concerns, and high costs of sewer installation. Nonsewered sanitation (NSS) systems have the potential to provide safely managed sanitation and achieve strict wastewater treatment standards. One such NSS treatment technology is the NEWgenerator, which includes an anaerobic membrane bioreactor (AnMBR), nutrient recovery via ion exchange, and electrochlorination. The system has been shown to achieve robust treatment of real waste for over 100 users, but the technology's relative life cycle sustainability remains unclear. This study characterizes the financial viability and life cycle environmental impacts of the NEWgenerator and prioritizes opportunities to advance system sustainability through targeted improvements and deployment. The costs and greenhouse gas (GHG) emissions of the NEWgenerator (general case) leveraging grid electricity were 0.139 [0.113-0.168] USD cap-1 day-1 and 79.7 [55.0-112.3] kg CO2-equiv cap-1 year-1, respectively. A transition to photovoltaic-generated electricity would increase costs to 0.145 [0.118-0.181] USD cap-1 day-1 but decrease GHG emissions to 56.1 [33.8-86.2] kg CO2-equiv cap-1 year-1. The deployment location analysis demonstrated reduced median costs for deployment in China (-38%), India (-53%), Senegal (-31%), South Africa (-31%), and Uganda (-35%), but at comparable or increased GHG emissions (-2 to +16%). Targeted improvements revealed the relative change in median cost and GHG emissions to be -21 and -3% if loading is doubled (i.e., doubled users per unit), -30 and -12% with additional sludge drying, and +9 and -25% with the addition of a membrane contactor, respectively, with limited benefits (0-5% reductions) from an alternative photovoltaic battery, low-cost housing, or improved frontend operation. This research demonstrates that the NEWgenerator is a low-cost, low-emission NSS treatment technology with the potential for resource recovery to increase access to safe sanitation.

Life cycle assessment of carbon capture, utilisation and storage technologies: An analytical review

The impact of climate change is more evident now than ever due to the environmental burden accumulated over the past two decades. Decarbonising methods such as carbon capture, utilisation and storage (CCUS) technologies are the future of the green economy and are considered one of the most significant alternatives for mitigating carbon emissions. Therefore, this review mainly focuses on life cycle assessment (LCA), the current state-of-the-art tool to determine the environmental performance of the technologies. This paper aims to assess papers published from the year 2019 to 2022 from all around the world to understand the trend, challenges, and prospects of CCUS technologies in reducing carbon and environmental impacts. This review concludes that the employment of carbon capture technologies can significantly reduce greenhouse gas (GHG) emissions but also increase other environmental burdens such as acidification, eutrophication and ecotoxicity depending on the type of carbon capture method used, energy penalty and the rate of oxides of nitrogen (NOx) emitted from the carbon capture infrastructure. Furthermore, Carbon Capture Utilisation (CCU) is a viable option to be employed in industries mainly to produce chemicals and use the captured carbon directly to combat GHG emissions with the proper modification of the carbon conversion method of the plant and the application of renewable energy. Although the Carbon Capture Storage (CCS) technology has an overall great impact on reducing Global Warming Potential (GWP), the increasing demand for fuel for the infrastructure causes environmental trade-offs with an increase in GHG emissions and other impact categories. The findings of this research would help in developing and implementing improvised methods and will provide a clear view of the prospects of CCUS technologies which will assist in decision-making.

A New Macroscopic Traffic Flow Characterization Incorporating Traffic Emissions

Densely populated cities have led to increased traffic congestion and, consequently, increased greenhouse gas emissions from vehicles. Thus, it is important to develop traffic models to overcome congestion and increased air pollution. In the literature, traffic model characterizations rely predominantly on traffic dynamics and ignore traffic emissions. In this study, a new macroscopic model targeting traffic emissions and drivers’ presumption based on traffic emissions is proposed to overcome traffic congestion and pollution. The traffic emissions characterization was based on the CO2 data employed in the second traffic system. For the performance analysis, the results of the proposed and Zhang’s traffic models were compared. The results were obtained using the ROE technique to predict traffic evolution. The scheme was implemented in MATLAB. Compared with Zhang’s traffic model, the suggested traffic model based on emissions reflected traffic behavior more realistically.