Impact Of Greenhouse Gas Emissions Research Articles

Impact of greenhouse gas emission, renewable energy, and economic growth on health expenditure in Southeast Asia: A comparative analysis of econometric models

Purpose — The study explores the effects of greenhouse gas emissions, renewable energy, and economic growth on health expenditures across Southeast Asia while comparing the performance of different econometric models for accuracy in analysis.Method — To analyze the relationships among variables, the study employs three econometric models, the Autoregressive Distributed Lag Model, the co-integration Model, and the Quantile Regression Model, using annual data from 2000 to 2020.Findings — The results reveal that greenhouse gas emissions and GDP significantly influence health expenditure in all three models. However, the significance of renewable energy consumption varies, with only the quantile regression model indicating a significant relationship with health expenditure. Model comparison based on Mean Squared Error (MSE) suggests that the autoregressive distributed lag (ARDL) model provides the most accurate predictions. Also, it found that there is a short-run and long-run causal effect of GHG and GDP on health expenditure, as well as health spending on GDP.Implication — This study helps to understand how economic growth, environmental factors, and healthcare spending interact to develop sustainable policies to address health and environmental problems in Southeast Asia.Originality — This research contributes to the body of knowledge examining the impact of economic and environmental factors on health expenditures in Southeast Asia through a comparative analysis of different econometric models.

Biobased Compostable Plastics End-of-Life: Environmental Assessment Including Carbon Footprint and Microplastic Impacts.

In this paper, we examine how traditional life-cycle assessment (LCA) for bio-based and compostable plastics overlooks issues surrounding carbon sequestration and microplastic persistence. To outline biased comparisons drawn from these omitted environmental impacts, we provide, as an example, a comparative LCA for compostable biobased vs. non-compostable fossil-based materials. In doing so we (1) demonstrate the proper way to capture carbon footprints to make fair comparisons and (2) identify the overlooked issues of microplastics and the need for non-persistent alternatives. By ensuring accurate biogenic carbon capture, key contributors to CO2 evolution are properly identified, allowing well-informed changes to formulations that can reduce the environmental impact of greenhouse gas emissions. In a complimentary manner, we summarize the growing research surrounding microplastic persistence and toxicity. We highlight the fundamental ability and the growing number of studies that show that industrial composting can completely mineralize certified compostable materials. This mineralization exists as a viable solution to combat microplastic persistence, currently an absent impact category in LCA. In summary, we propose a new paradigm in which the value proposition of biobased materials can be accurately captured while highlighting compostables as a solution for the increasing microplastic accumulation in the environment.

Influences of economy, energy, finance, and natural resources on carbon emissions in Bangladesh

Understanding the risks posed to humankind, the environment, and overall growth requires a deep exploration of the profound impact of greenhouse gas (GHG) emissions, especially carbon dioxide (CO2), on global climate change. This study explores the complex relationships among economic extension, energy utilization, financial progress, natural resource rents, and CO2 emissions in Bangladesh. By analyzing annual data from 1974 to 2022, our analysis reveals a long-term connection between the variables, as evidenced by the autoregressive distributed lag (ARDL) bounds test. We found that for every 1% rise in economic growth, energy use, financial progress, and natural resource rents, CO2 emissions rise by 0.13%, 1.50%, 0.39%, and 0.04%, respectively. This is based on the dynamic ordinary least squares (DOLS) method. The outcomes are further supported by the canonical cointegrating regression (CCR), followed by fully modified ordinary least squares (FMOLS). By illuminating the causes of Bangladesh's environmental degradation, this study offers actionable policy suggestions aimed at fostering sustainable growth and enforcing strict regulations that effectively mitigate environmental harm.Graphical

Applying the internet of things (IoT) for raising black soldier Fly (BSF) in closed system to minimize greenhouse gas emissions

The Black Soldier Fly (BSF), scientifically known as Hermetia Illucens L., effectively reduces organic waste and decreases harmful gas emissions more efficiently than landfill or composting methods. However, it can still produce harmful gases during the rearing of BSF larvae, including carbon dioxide (CO2), methane (CH4), nitrous oxide (N2O), and ammonia (NH3), which contribute directly and indirectly to the greenhouse effect. The pH level of the food provided to the larvae affects their biomass and leads to varying levels of gas emissions. This study aims to investigate the impact of greenhouse gas emissions when different pH levels of food are used, utilizing IoT technology to measure greenhouse gases and control the environmental conditions for rearing BSF larvae. The greenhouse gases monitored in this study include carbon dioxide (CO2) and methane (CH4), with environmental factors such as air temperature, humidity, soil moisture, and light intensity being controlled. The experiment tested pH levels ranging from 2.0, 4.0, 6.0, 7.0, and 8.0 to 10.0. The results show that different pH levels in food affect the emission of CO2 and CH4. Initially, a large amount of CO2 is released, gradually decreasing over time, while CH4 emissions steadily increase. In the early days, CH4 emissions are unstable, fluctuating before stabilizing. Food with a pH of 2.0 results in the lowest average CO2 emissions (430.53 PPM) from BSF larvae, and the lowest CH4 emissions (16.11 PPM) are also observed with a pH of 2.0.

Seasonal Variations of Ice-Covered Lake Ecosystems in the Context of Climate Warming: A Review

The period of freezing is an important phenological characteristic of lakes in the Northern Hemisphere, exhibiting higher sensitivity to regional climate changes and aiding in the detection of Earth’s response to climate change. This review systematically examines 1141 articles on seasonal frozen lakes from 1991 to 2021, aiming to understand the seasonal variations and control conditions of ice-covered lakes. For the former, we discussed the physical structure and growth characteristics of seasonal ice cover, changes in water environmental conditions and primary production, accumulation and transformation of CO2 beneath the ice, and the role of winter lakes as carbon sources or sinks. We also proposed a concept of structural stratification based on the differences in physical properties of ice and solute content. The latter provided an overview of the ice-covered period (−1.2 d decade−1), lake evaporation (+16% by the end of the 21st century), the response of planktonic organisms (earlier spring blooming: 2.17 d year−1) to global climate change, the impact of greenhouse gas emissions on ice-free events, and the influence of individual characteristics such as depth, latitude, and elevation on the seasonal frozen lakes. Finally, future research directions for seasonally ice-covered lakes are discussed. Considering the limited and less systematic research conducted so far, this study aims to use bibliometric methods to synthesize and describe the trends and main research points of seasonal ice-covered lakes so as to lay an important foundation for scholars in this field to better understand the existing research progress and explore future research directions.

Integrating Engineering Innovations to Enhance Environmental Resilience: Evaluating the Impact of Greenhouse Gas Emissions, Ozone Depletion, And Aquatic Ecosystem Degradation on Public Health

Integrating Engineering Innovations to Enhance Environmental Resilience: Evaluating the Impact of Greenhouse Gas Emissions, Ozone Depletion, And Aquatic Ecosystem Degradation on Public Health

Experimental study on the effects of n-butanol and n-propanol on the spray and combustion characteristics of diesel/biodiesel blends in a constant volume combustion chamber

The depletion of fossil fuel resources and the escalating environmental impact of greenhouse gas emissions have intensified the global exploration of renewable and sustainable energy sources. Biodiesel produced from vegetable oils and animal fats has become a promising alternative to conventional diesel fuel due to its renewability and lower carbon emission. This study investigates the differences in spray, combustion and flame characteristics between soybean-based biodiesel blended with propanol and butanol at various ratios. The results indicate that the liquid spray penetration length of biodiesel mixed with propanol and butanol exceeds that of soybean-based biodiesel. And the increase of spray penetration is accompanied by a longer flame lift-off length, which indicates the improvement of spray characteristics. Regarding combustion, alcohol-fuel blends exhibit a reduction in peak combustion pressure but an increase in peak apparent heat release rate. Additionally, these fuels show a shorter ignition delay and combustion duration. The peak natural flame luminosity is lower for alcohol fuels, suggesting their potential to reduce carbon soot production and support low-carbon combustion. These experimental results contribute to advancing research on cleaner, more efficient and renewable fuels, thereby reducing reliance on conventional fossil fuels.

A numerical model for evaluating the long-term migration and phase transition behavior of foam-assisted injection of CO2 in saline aquifers

Geological Carbon Storage (GCS) is a rapidly developing technology with the potential to mitigate the environmental impact of excessive greenhouse gas emissions. Foam-assisted injection of CO2 can effectively alter fluid rheological properties, thereby enhancing sweep efficiency. In this paper, a numerical model to evaluate the long-term migration behavior of foam-assisted injected CO2 in saline aquifers is developed. It is found that foam-assisted injection improves storage efficiency and reduces the plume migration distance compared to direct CO2 injection. This creates higher demands on the injection pressure but minimizes the risk of leakage. The effects of injection strategy, volume fraction of foam, and reservoir heterogeneity were investigated. Modeling results show that the injection strategy with a high foam volume fraction enhances the sweep efficiency and improves the transition rate of injected CO2 to the dissolved state. This can effectively enhance the long-term security of the sequestration. Simulations of layered formations indicates that foams can potentially inhibit the rapid migration of plumes along high-permeability zones. Our study provides insights for foam-assisted injection to enhance reservoir storage efficiency and long-term safety for GCS.

Climate change impact on Indonesian firm value: Exploring the moderating role of accounting conservatism

Climate change is one of the risks that can occur in countries across the equator, such as Indonesia. Apart from its geographical location, the industrial sector is one of Indonesia’s highest contributors to emissions. This research examines the impact of climate change and greenhouse gas (GHG) emissions on firm value, moderated by accounting conservatism. Firm value is measured by Tobin’s Q and the market-to-book ratio. The sample consists of high-profile manufacturing industries listed on the Indonesia Stock Exchange in 2020-2021, totalling 208 companies. The results show that climate change, GHG emission issues, and accounting conservatism significantly affect firm value, both directly and moderately. Furthermore, firm value measured using the market-to-book ratio is more sensitive than when measured using Tobin's Q. This study provides a different perspective on sustainability issues and contributes to signalling theory by testing non-financial and financial performance using the same model. To improve sustainability performance, firms and governments should consider the research findings when developing policies and regulations addressing environmental challenges.

Fabrication of a cost-effective metal oxide-based adsorbent from industrial waste slag for efficient CO2 separation under flue gas conditions

Efficient and affordable adsorbents for CO2 capture are essential in implementing carbon capture technology to mitigate the negative impact of greenhouse gas emissions. This study focuses on synthesizing new nanoporous adsorbents from industrial waste slag using a simple and cost-effective coprecipitation method. In this method, raw slag was milled for 48 h and used as a benchmark for comparing two newly synthesized adsorbents. Selectivity and pure gas isotherm experiments were conducted for all adsorbents in the 25–65°C temperature range and under harsh industrial conditions of 65°C and 15 % CO2. This study utilized the response surface methodology (RSM) to optimize the CO2 adsorption parameters. Specifically, the optimized adsorption conditions were determined for the 15/85 % CO2/N2 condition, and the optimal values for pressure and temperature were found to be 5 bar and 45°C, resulting in CO2/N2 selectivity of 5.65. The NH3-slag adsorbent was identified as the superior choice based on its selectivity and maximum adsorption capacity. The maximum adsorption capacity and cyclic efficiency were determined to be 4.15 mmol/g and 98.1 %, respectively, at a temperature, pressure, and composition of 45°C, 5 bar, and 15 % CO2. Isotherm and thermodynamic models were employed to further investigate the adsorption process. The isotherm results indicated that the adsorption of CO2 by adsorbents occurred heterogeneously in patch-wise sites. Meanwhile, the thermodynamic parameters showed that the process was exothermic and spontaneous, with ΔH° falling below 20 (kJ/mol), showing physisorption phenomena.

Impact of GHG emission, temperature, and precipitation on rice production in Nepal

Climate variables mainly greenhouse gas (GHG) emissions, temperature, precipitation, and rainfall are affecting crop production across the world. Nepal as a vulnerable country in terms of climate change, has raised the attention of researchers and policymakers in recent years. In this scenario, this study has attempted to find the impact of GHG emissions, temperature, and precipitation on rice production in Nepal. The study is based on time serried data from 1990 to 2019. The findings show that GHG emission has a significant positive impact on rice production. However, the annual average mean temperature has a significant negative impact on rice production. Besides having a negative coefficient, precipitation did not affect rice production significantly. The study recommends concrete climate change adaptation practices in the major rice production areas of Nepal, mainly in the Terai and Hilly belts.

Greenhouse gas emission prediction and impact analysis of dual-fuel engine

This study explored the profound influence of greenhouse gas (GHG) emissions on global climate change by introducing an innovative prediction model. Utilizing a backpropagation (BP) neural network with dual-hidden layer, optimized through simulated annealing particle swarm optimization (SA-PSO), the model predicted emissions from a diesel/natural gas dual-fuel engine at 1500 rpm across four torque levels: 400, 800, 1200, and 1600 N·m. The inputs included engine torque, injection timing, pressure, excess air coefficient, and natural gas substitution ratio, with CO2 and CH4 as outputs. Evaluation metrics—the coefficients of determination (R²) of 0.9975 for CO2 and 0.9951 for CH4, the root mean square error (RMSE) of 0.062 % and 278.04 ppm, and the mean relative error (MRE) of 0.82 % and 5.35 %, respectively—demonstrated the model’s accuracy. A quantitative analysis using the Mean Influence Value (MIV) algorithm showed engine torque’s pivotal role in emissions at a medium engine speed with contribution rates of 48.5 % and 40.3 % for CO2 and CH4 emissions, respectively. Notably, at a lower load condition (engine torque = 400 N·m), the natural gas substitution ratio was identified as having the most substantial impact on emissions. This study presents a novel approach to predicting and reducing GHG emissions from dual-fuel engines.

Sustainability and environmental costs in the textile industry: a case study

The impact of greenhouse gas and carbon emissions on climate change and more frequent natural disasters in recent years have increased people's and government's environmental awareness. The enactment of environmental legislation and new standards have resulted in some additional environmental costs for companies. Every additional cost is very important for companies operating under intense competitive pressure. Companies operating in the textile sector undertake the costs of prevention, use and damage at every stage of their production. In this study, the importance of the textile sector in Türkiye in terms of the country's economy has been revealed and the environmental costs of textile enterprises have been examined. The study aims to reveal the environmental costs for yarn production, yarn dyeing process, weaving-confection processes and dyeing-finishing processes separately and to calculate the share of these costs in total operating expenses. According to the results of the study, it has been determined that the share of environmental costs in total expenses in the textile company is 3.1%. It has been observed that the share of environmental costs in total expenses varies between 0.5% and 6% at different production stages.

Environmental Impacts of Transportation Network Company (TNC)/Ride-Hailing Services: Evaluating Net Vehicle Miles Traveled and Greenhouse Gas Emission Impacts within San Francisco, Los Angeles, and Washington, D.C. Using Survey and Activity Data

Transportation Network Companies (TNCs) play a prominent role in mobility within cities across the globe. However, their activity has impacts on vehicle miles traveled (VMT) and greenhouse gas (GHG) emissions. This study quantifies the change in personal vehicle ownership and total miles driven by TNC drivers in three metropolitan areas: San Francisco, CA; Los Angeles, CA; and Washington, D.C. The data sources for this analysis comprise two surveys, one for TNC passengers (N = 8630) and one for TNC drivers (N = 5034), in addition to data provided by the TNC operators Uber and Lyft. The passenger survey was deployed within the three metropolitan areas in July and August 2016, while the driver survey was deployed from October to November 2016. The TNC operator data corresponded with these time frames and informed the distance driven by vehicles, passenger frequency of use, and fleet level fuel economies. The data from these sources were analyzed to estimate the impact of TNCs on travel behavior, personal vehicle ownership and associated VMT changes, as well as the VMT of TNCs, including app-off driving. These impacts were scaled to the population level and collectively evaluated to determine the net impacts of TNCs on VMT and GHG emissions using fuel economy factors. The results showed that the presence of TNCs led to a net increase of 234 and 242 miles per passenger per year, respectively, in Los Angeles and San Francisco, while yielding a net decrease of 83 miles per passenger per year in Washington, D.C. A sensitivity analysis evaluating net VMT change resulting from vehicle activity and key behavioral impacts revealed the conditions under which TNCs can contribute to transportation sustainability goals.

MODEL MATEMATIKA PEMANASAN GLOBAL PADA KEHIDUPAN PESISIR

Global warming has become one of the big problems being faced in the 21st century. Global warming and depletion of the ozone layer due to excessive increases in Green House Gas (GHG) emissions in the atmosphere have a negative impact on the sustainability of coastal ecosystems. This research aims to describe the impact of rapid GHG emissions on coastal life, and this research also wants to determine the mathematical relationship between increasing GHGs and global warming. Rapid GHG emissions from various sources also drive global warming and cause several natural disasters. The method used in this research is the descriptive method. This research develops a mathematical model using four variables. Based on the results of simulation analysis, it shows that GHG and global warming can be controlled by ehriching coastal forests, but if not, the human population could lose the ability to survive and around one third of the total forest ecosystem will be lost by the end of this century

Soil Microbial Communities and Wine Terroir: Research Gaps and Data Needs.

Microbes found in soil can have a significant impact on the taste and quality of wine, also referred to as wine terroir. To date, wine terroir has been thought to be associated with the physical and chemical characteristics of the soil. However, there is a fragmented understanding of the contribution of vineyard soil microbes to wine terroir. Additionally, vineyards can play an important role in carbon sequestration since the promotion of healthy soil and microbial communities directly impacts greenhouse gas emissions in the atmosphere. We review 24 studies that explore the role of soil microbial communities in vineyards and their influence on grapevine health, grape composition, and wine quality. Studies spanning 2015 to 2018 laid a foundation by exploring soil microbial biogeography in vineyards, vineyard management effects, and the reservoir function of soil microbes for grape-associated microbiota. On the other hand, studies spanning 2019 to 2023 appear to have a more specific and targeted approach, delving into the relationships between soil microbes and grape metabolites, the microbial distribution at different soil depths, and microbial influences on wine flavor and composition. Next, we identify research gaps and make recommendations for future work. Specifically, most of the studies utilize targeted sequencing (16S, 26S, ITS), which only reveals community composition. Utilizing high-throughput omics approaches such as shotgun sequencing (to infer function) and transcriptomics (for actual function) is vital to determining the specific mechanisms by which soil microbes influence grape chemistry. Going forward, understanding the long-term effects of vineyard management practices and climate change on soil microbiology, grapevine trunk diseases, and the role of bacteriophages in vineyard soil and wine-making would be a fruitful investigation. Overall, the studies presented shed light on the importance of soil microbiomes and their interactions with grapevines in shaping wine production. However, there are still many aspects of this complex ecosystem that require further exploration and understanding to support sustainable viticulture and enhance wine quality.

Faktor - Faktor yang Mempengaruhi Biaya CSR Pada Perusahaan Transportation & Logistic

Transportation companies are one of the dominant sectors contributing to the largest negative impact of greenhouse gas emissions in Indonesia. CSR is carried out to reduce these negative impacts, but the company's economic dynamics influence the costs incurred. This research examines the factors that influence CSR costs while adding to the limited literature related to dependent variables. This research method is quantitative through documentation. Researchers used secondary data from annual and sustainability reports of transportation & logistics sector companies listed on IDX for the 2020-2023 period. The sampling technique uses purposive sampling. Multiple linear regression analysis was carried out using SPSS 26. The research results are profitability, leverage, market capitalization and company size simultaneously influence CSR costs. Meanwhile, separately, the profitability does not have an influence, each of the market capitalization and leverage have a negative influence, and the company size has a positive influence on CSR costs.

Carbon disclosure, greenhouse gas emissions and market value of FTSE 350 firms – evidence from voluntary carbon disclosers versus non-disclosers

ABSTRACT In 2013, a carbon disclosure mandate was adopted by UK-listed companies. This motivated our study to explore the effects of the 2013 carbon disclosure regulation (CDR) and Greenhouse Gas (GHG) emissions on firms’ market value for voluntary disclosers versus non-disclosers pre- and post-2013 CDR. Using a sample of FTSE 350 firms in a short (2010–2016) and long window (2010–2020), our difference-in-differences design shows a beneficial (adverse) effect of the 2013 CDR on market value for voluntary carbon disclosers (non-disclosers). Also, we document the negative impact of GHG emissions on market value after the 2013 CDR for voluntary disclosers. In contrast, a somewhat positive GHG-market value nexus is noted in the case of non-disclosers post-2013 CDR. Our evidence suggests that voluntary carbon disclosers are heavier GHG emitters and, hence, bear much higher environmental risks/liabilities, a negative attribute that became ever more taxing to their market value after the 2013 CDR. HIGHLIGHTS The UK's 2013 carbon disclosure regulation (CDR) influenced the market values differently for firms based on their disclosure behaviours, showing a positive (negative) impact for voluntary carbon disclosers (non-disclosers). In the post-CDR era, the GHG emissions of voluntary disclosers were penalized with lower market value while the GHG emissions of non-disclosers were somewhat rewarded with higher valuation. Compared to non-disclosers, voluntary disclosers are typically larger emitters facing greater environmental risks after the CDR; a negative attribute that continues to undermine their market valuation.

Environmental Impact of Footwear Using Life Cycle Assessment—Case Study of Professional Footwear

Life cycle assessment (LCA) is a method for assessing the environmental impact of a product, activity, or system across all the stages of its life cycle. LCA can identify the activities with a major impact on the environment throughout the life cycle of a product. To analyze the environmental implications of footwear, the LCA was applied to a pair of shoes designed for professional use. In this paper, the impact of a single pair of shoes was studied. Every year, footwear production worldwide is over 22 billion pairs, which has a significant impact on the environment. In this case study, the “cradle-to-grave” approach was used, which refers to all the activities involved in the life cycle of a footwear product, starting from raw material extraction, manufacturing, use, maintenance, and, in the end, disposal. The LCA was conducted using the SimaPro software. The environmental impact assessment of the analyzed shoe needed the acquisition of two crucial datasets. Background inventory data were sourced from the Ecoinvent database (version 3.3). The impact was quantified using the Global Warming Potential (GWP) metric, which calculates the contribution of emissions to global warming over a 100-year time limit according to the established values provided by the Intergovernmental Panel on Climate Change (IPCC). The impact of greenhouse gas (GHG) emissions was measured in relative carbon dioxide equivalents (kg CO2eq) to facilitate a standardized comparison. The results show that the total carbon footprint for a pair of safety boots is 18.65 kg of CO2eq with the “component manufacture” stage as a major contributor accumulating almost 80%.

Metaproteomics-informed stoichiometric modeling reveals the responses of wetland microbial communities to oxygen and sulfate exposure

Climate changes significantly impact greenhouse gas emissions from wetland soil. Specifically, wetland soil may be exposed to oxygen (O2) during droughts, or to sulfate (SO42-) as a result of sea level rise. How these stressors – separately and together – impact microbial food webs driving carbon cycling in the wetlands is still not understood. To investigate this, we integrated geochemical analysis, proteogenomics, and stoichiometric modeling to characterize the impact of elevated SO42- and O2 levels on microbial methane (CH4) and carbon dioxide (CO2) emissions. The results uncovered the adaptive responses of this community to changes in SO42- and O2 availability and identified altered microbial guilds and metabolic processes driving CH4 and CO2 emissions. Elevated SO42- reduced CH4 emissions, with hydrogenotrophic methanogenesis more suppressed than acetoclastic. Elevated O2 shifted the greenhouse gas emissions from CH4 to CO2. The metabolic effects of combined SO42- and O2 exposures on CH4 and CO2 emissions were similar to those of O2 exposure alone. The reduction in CH4 emission by increased SO42- and O2 was much greater than the concomitant increase in CO2 emission. Thus, greater SO42- and O2 exposure in wetlands is expected to reduce the aggregate warming effect of CH4 and CO2. Metaproteomics and stoichiometric modeling revealed a unique subnetwork involving carbon metabolism that converts lactate and SO42- to produce acetate, H2S, and CO2 when SO42- is elevated under oxic conditions. This study provides greater quantitative resolution of key metabolic processes necessary for the prediction of CH4 and CO2 emissions from wetlands under future climate scenarios.