Increase In Carbon Emissions Research Articles

Use of water in dialysis and its impact on the environment.

The climate crisis poses significant challenges across various sectors, including healthcare, where resource consumption often exacerbates environmental issues. This review addresses concerns over current levels of water use for dialysis treatment, a critical procedure for patients with kidney failure. Despite its life-saving importance, the dialysis process consumes large quantities of water, contributing to water scarcity and increased carbon emissions associated with water treatment and distribution. Through a comprehensive analysis of current practices, we identify inefficiencies and propose sustainable alternatives aimed at reducing water usage in dialysis. Findings indicate that optimizing treatment protocols and considering innovative technologies can significantly mitigate the environmental impact while maintaining patient care standards. This review underscores the urgent need for the healthcare sector to adopt sustainable practices in response to the climate crisis.

Growth vs. green: unpacking the economic–environmental dilemma in major carbon emitters with panel ARDL analysis

Today's world is facing a criticalglobal challenge of rising temperatures and disrupted ecosystems, primarily driven by increased carbon emissions. The study aims to determine the major factors leading to carbon emissions in five major carbon-emitting countries: China, the United States, India, Russia, and Japan. Specifically, it explores the interplay between economic growth, natural resource rent (Natural Resource Rent: The economic benefit a country gains from its natural resources, such as oil or minerals, after subtracting the cost of extracting and using them), technological change, renewable energy use, and carbon emissions. The study postulates that economic growth and natural resource extraction bear a substantial interaction that contributes to carbon emissions. At the same time, technological change and the usage of renewable energy could probably become imperative to alleviate such emissions. This research, therefore, provides a good insight into the determinants of CO2 emissions in these key economies and the probable pathways toward emission reduction through innovation and harnessing of renewable sources of energy. Utilizing the comprehensive dataset between 1990 and 2021 and employing the ARDL [Panel ARDL (Autoregressive Distributed Lag): A statistical method used to analyze how different factors affect each other over time in a dataset that includes multiple subjects (e.g., countries)] model on the panel data, this study examines both the short- and long-term effects of these variables on carbon emissions, considering cross-country heterogeneity. The results underscore the significance related to guidelines for sustainable development practices and the necessity for these leading economies to lead the shift towards sustainability. By identifying factors that can mitigate emissions and enhance resilience, this research provides useful inputs to the policymakers who intend to promote renewable sources of energy usage along with technological upgrades. This study’s results contribute to the existing literature by making it a significant resource for future policy formulation and academic research in the field of mitigating climate change.

Urban Management for Building-Sector Decarbonization: Focusing on the Role of Low-Carbon Policies

The building sector is a major source of anthropogenic carbon emissions worldwide. While existing studies have extensively explored the socioeconomic and technological impacts on carbon emissions generated from building operations, few have assessed the effectiveness of low-carbon policies in curbing the increasing trend of building sector carbon emissions. This study examines the impacts of low-carbon policy intensity on building sector carbon emissions using a two-way fixed effects model on a 6-year panel (2015–2020) dataset for 286 cities in China. Our findings indicate that, on average, the aggregated intensity of low-carbon policies fails to pose any significant impacts on carbon emissions from building operations. This is partly due to the variations in different types of policy. Specifically, a 10% increase in the intensity of energy conservation policy results in a 0.05% decrease in carbon emissions, whereas capacity utilization policies are associated with an increase in building-operation carbon emissions. Moreover, these policy–emission relationships vary across building types and end-use sources. In particular, energy conservation policies are negatively associated with emissions from cooking and heating, but positively related to emissions generated from appliances and cooling. In comparison, capacity utilization policies tend to encourage additional emissions from most sources. This study highlights the partial effectiveness of energy conservation policies in curbing building sector carbon emissions and underscores the need for additional efforts in tackling the rebound effects to realize building sector decarbonization.

The non-energy industrial sector: an analysis of Algeria's energy-related CO2 emissions (2006-2021)

In 2021, Algeria's CO2 emissions exceeded 178 million tons, reflecting a rise of over 73% in less than 15 years. To fight climate change, this study provides a detailed decomposition analysis of the drivers influencing Algeria's CO2 emissions related to energy use from 2006-2021 using the Logarithmic Mean Divisia Index (LMDI) approach. It emphasizes the non-energy industry sub-sectors, including food and drink products, iron and steel, mechanical, electronic and electric equipment, textiles and clothing, leather, and construction materials, which account for 24.36% of Algeria's total energy consumption. The findings indicate that industrial scale is the main driver influencing the increase in carbon emissions, contributing 26.12 Mt, followed by the emission factor effect at 9 Mt. However, the effects of industrial structure and energy intensity take an important part in reducing emissions, accounting for 14.16 Mt and 4.21 Mt, respectively. The “construction materials” industry was identified as the highest carbon emitter of non-energy industries, followed by “iron and steel, mechanical, electronics, and electric equipment”, and “food products, beverages, and tobacco” industries. Algerian policymakers can use the study's empirical results to develop sustainable energy strategies, particularly in non-energy sector, to enhance the potential for the country reaching its energy and green objectives.

LCA-TOPSIS Integration for Minimizing Material Waste in the Construction Sector: A BIM-Based Decision-Making

The construction sector is one of the industries with the highest environmental impact due to resource consumption and waste generation. Material waste exacerbates these impacts by increasing carbon emissions and energy consumption. This study introduces an innovative approach by integrating Life Cycle Assessment (LCA) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to evaluate material waste and environmental impacts simultaneously. By analyzing scenarios of material use in the design and construction phases, this study explores their effects on material efficiency and environmental performance while addressing a notable research gap. Existing studies on the integration of LCA and TOPSIS in evaluating material waste and its environmental impacts remain limited. This research not only demonstrates the applicability of these methods but also contributes to filling this gap. Material waste and efficiency were assessed through Building Information Modeling (BIM), while BIM-LCA integration was used to evaluate environmental impacts. The findings were examined in two stages: LCA and TOPSIS. The TOPSIS analysis considered two scenarios—material waste and environmental impacts. In the first scenario, cast-in-place concrete (5000 psi) and stone and ceramic tiles emerged as priorities. In the second scenario, where carbon emissions and environmental impacts were emphasized, cast-in-place concrete (5000 psi), laminated timber, and stone tiles were identified as critical materials. The results reveal that reducing material waste significantly enhances environmental performance, lowers costs, and promotes sustainability. These findings provide practical insights for developing sustainable strategies in diverse cultural and geographical contexts, particularly for residential projects. The integration of LCA and TOPSIS offers a robust decision-making framework, enabling targeted actions to minimize environmental footprints across all life cycle stages. This study contributes to the literature by providing actionable recommendations for optimizing resource use and improving sustainability in construction practices.

Deep-RNN based model for short-time forecasting photovoltaic power generation using IoT

Global warming is one of the most significant issues of the century due to climate change caused by increased carbon emissions resulting from the exploitation of fossil fuels. Consequently, renewable energies are considered an alternative that promotes cleaner production and offers a substantial reduction in carbon emissions. Therefore, accurately forecasting photovoltaic (PV) power generation is crucial for controlling and distributing electrical inventory and ensuring the stability and reliability of power systems. In this paper, we develop a model for forecasting short-term PV power generation based on deep Recurrent Neural Networks (deep-RNNs). To improve efficiency, our model uses weather and PV generation dataset on-site collected in real-time using IoT technology. Specifically, by leveraging deep-RNN, particularly the long short-term memory network (LSTM) and gated recurrent units (GRU), which excel at capturing long-term dependencies in time series data, this article proposes a combination of LSTM and GRU models to take advantage of both in different weather conditions. The results of the experiments show that the LSTM-GRU model that has been proposed performs better in PV power forecasting than both the LSTM and GRU models together.

The contradictory impact of ESG performance on corporate competitiveness: Empirical evidence from China's Capital Market

In recent years, with the increasing awareness of sustainable development, corporate ESG (Environmental, Social, and Governance) performance has garnered widespread attention from investors and has had a sustained impact on long-term business operations. The mechanisms by which ESG performance affects corporations primarily include the "governance effect" and the "window-dressing effect." Aimed at high-quality development goals, what kind of impact does ESG performance have on corporate competitiveness? This paper attempts to explore the economic relationship between corporate ESG performance and corporate competitiveness in China's capital market through theoretical analysis and empirical testing. The research results show that ESG performance significantly promotes corporate competitiveness, particularly through the "social" dimension (S) and "governance" dimension (G). ESG performance significantly enhances corporate competitiveness by increasing corporate philanthropic donations and improving total factor productivity, demonstrating the "governance effect" of ESG. However, in the "environmental" dimension (E), ESG performance instead leads to an increase in corporate carbon emissions, which may indicate that corporate efforts in environmental areas are more for superficial appearance, exhibiting the "window-dressing effect" of ESG. This study reveals the crucial role of ESG practices in enhancing corporate competitiveness, providing theoretical support and policy implications for promoting corporate competitiveness and achieving high-quality development goals.

Carbon emission reduction potential of land use in typical alpine meadow region in China

Alpine meadows are primarily situated in mountainous areas and plateaus, exhibiting a high sensitivity to both climate fluctuations and human activities. However, understanding the factors influencing land use carbon emissions change in these regions remains complex, with uncertain mechanisms. Thus, it is imperative to accurately grasp the factors affecting carbon emissions in alpine meadows. We conducted a study estimating land use carbon emissions in the Upper Yellow River in Gannan from 1990 to 2020, using the Logarithmic Mean Divisia Index decomposition model and the Tapio decoupling model to identify driving factors of land use carbon emissions. Additionally, we analyzed the correlation between these factors and economic growth. The findings showed that the land use efficiency in the Upper Yellow River in Gannan region improved substantially by 436 %. Particularly, construction land emerged as the primary source of carbon emissions. The land use carbon emission increased with the increase of carbon emission intensity of construction land and the expansion of the size of construction land. Moreover, economic development and land use carbon emissions are weak decoupled. These results suggest that economic development is considered the primary driving force behind the increase in land use carbon emissions in the region. To achieve the decoupling of economic development and land use carbon emissions, we propose to improve land use efficiency by adjusting the industrial structure as well as improving land use efficiency.

Economic growth and environmental sustainability: The role of foreign direct investment and technological innovation on carbon emissions in Ghana

Debates on foreign direct investment, technological innovation and carbon emission seem unsettling in the literature. We contribute to the literature by investigating the relationships between foreign direct investment, technological innovation, and carbon emissions in Ghana. Using the Autoregressive Distributive Lag (ARDL) method, the analysis reveals that foreign direct investment contributes to reduced emissions in the short run but significantly increases carbon emissions in the long run, aligning with the pollution haven hypothesis. This indicates that Ghana may have a robust environmental regulation that ensures eco-friendly foreign direct investments in the short run, with weak enforcement of regulations resulting in high emissions in the long term. Technological innovation in the Ghanaian context contributes to increased CO2 emissions. However, the interaction effect of foreign direct investments and technological innovation reduces carbon emissions, emphasizing the importance of aligning foreign investments with sustainable technological advancements in Ghana. The study also identifies the Environmental Kuznets Curve (EKC) effect, where emissions rise with economic growth but decelerate at higher GDP levels. The findings underscore the need for stronger environmental regulations and a shift towards sustainable, cleaner energy and technological development to mitigate the environmental impacts of economic growth in Ghana and similar developing countries.

Reinvestigating the impact of natural resource rents on carbon emissions: Novel insights from geopolitical risks and economic complexity

Understanding the relationship between natural resource rents and carbon emissions is crucial for achieving a balance between economic development and environmental sustainability. This study reinvestigates the impact of natural resource rents on carbon emissions and explores the threshold effects of geopolitical risks and economic complexity, aiming to provide a more comprehensive understanding of their relationship. Based on an empirical analysis of panel data from 38 countries between 1995 and 2021, the conclusions are as follows. (i) The panel ARDL estimation results reveal that natural resource rents increase carbon emissions over the long term, with this finding remaining robust after addressing endogeneity. (ii) The DPTR model results indicate that natural resource rents have a non-linear impact on carbon emissions, shaped by geopolitical risks and economic complexity. As geopolitical risks escalate, the effect of resource rents on carbon emissions shifts from a reduction to an increase. On the contrary, rising economic complexity reverses this impact, causing natural resource rents to reduce carbon emissions. (iii) Heterogeneity analysis results demonstrate that only the impact of oil and natural gas rents on carbon emissions is affected by high geopolitical risks. Additionally, in contexts of high economic complexity, oil, natural gas, and forest rents help reduce carbon emissions, while coal and mineral rents have a negative impact. Finally, policy implications for global resource management and environmental sustainability that combine geopolitical risk and economic complexity are proposed.

Wings of progress: The economic and social impacts of low-cost carriers in the Philippines

Low-cost carriers (LCCs) have become a significant force in the Philippine aviation industry, providing affordable air travel and contributing to regional economic and social development. However, the full extent of their economic, social, environmental, and infrastructural impacts has not been comprehensively studied. This study aims to evaluate the economic and social implications of LCCs in the Philippines, focusing on tourism growth, job creation, business development, and the accessibility and mobility of the population. The study also explores environmental challenges and infrastructural strains caused by the expansion of LCC operations. A mixed-methods approach was employed, incorporating quantitative data analysis of tourism statistics, employment rates, business growth, and regional economic output. Qualitative data were collected through interviews and surveys with stakeholders, including passengers, local businesses, government officials, and environmental agencies. Statistical tools such as regression analysis and chi-square tests were used to determine significance levels in the findings. The results demonstrate that LCCs have contributed significantly to regional economic growth, with a 25% increase in tourist arrivals and a 30% rise in tourism revenue. Social impacts include enhanced travel accessibility, increased cultural exchange, and improved quality of life. However, environmental challenges, such as a 15% increase in carbon emissions, highlight the need for sustainable practices. The study recommends further investment in airport infrastructure, implementation of sustainable aviation practices, and ongoing government support for regional tourism. Future studies should focus on long-term environmental impacts and strategies for reducing carbon footprints.

How Dryland-to-Paddy Conversion Affects the Carbon Emission Efficiency in the Short Term: Evidence from Soil Carbon-Fixing Bacteria and the Carbon Pool in an Experimental Study

To amplify grain production capacity, a global trend is emerging in which many regions are transitioning from dependence on rainfall to irrigated agriculture. An illustrative example of this form of land consolidation is the conversion from dryland to paddy fields, which has changed the ecological environment of farmlands, resulting in significant effects on carbon fixation and emissions. However, there currently exists a deficiency in essential understanding regarding the short-term effects of dryland-to-paddy conversion on ecological processes tied to soil carbon-fixation bacteria and carbon emission efficiency (CEE). Therefore, field monitoring and high-throughput sequencing were carried out to monitor the changes in soil carbon emission efficiency and carbon-fixation bacteria before and after the conversion. Our results indicate that while conversion from dryland to paddy fields can boost grain yield, it also results in an increase in soil carbon emissions and a consequent decrease of 25.78% in carbon emission efficiency. This transition has resulted in an increased soil carbon-fixing bacterial alpha diversity index and enhanced network complexity. The structural equation model indicates that changes in soil environmental factors, especially soil moisture, soil organic carbon (SOC), readily oxidizable carbon (ROC), and carbon-fixing bacteria, are the primary drivers of CEE variation (p < 0.05). Given the critical role that the soil carbon cycle plays in global climate change, there is a pressing need for increased global attention towards the carbon emissions triggered by the transition from rainfed to irrigated agriculture.

Assessing the Environmental Sustainability Corridor: Carbon Emissions in Relation to Gold Price, Economic Growth, Foreign Direct Investment, and Renewable Energy Consumption

The growing concerns about global warming and its perceived influence on economic sustainability require a reassessment of the environmental consequences of gold mining, with a special focus on BRICS countries: Brazil, Russia, India, China, and South Africa. This paper examines the environmental sustainability corridor, carbon emission, gold price, economic growth, foreign direct investment (FDI), and renewable energy use between 1989 and 2020. The long-run association among the variables is checked by us through the PMG technique. Our findings indicate that while the gold price, FDI, and renewable energy use decrease carbon emission, economic growth adds to the increase in carbon emissions in the long run. These findings bring out the dual challenge of promoting economic growth while managing environmental impact. The study underlines how policymakers need to provide regulatory frameworks which will encourage renewable energy and responsible foreign investment, as a means of trying to mitigate the environmental impacts of gold mining and achieve sustainable development. Our research adds to the continuing debate about how economic expansion can be balanced with environmental preservation for resource-rich countries.

Exploring the emission spillover effects in production networks under carbon trading market: Insights into complementary and competitive industries

As the division of labor deepens, carbon emissions may easily escape through the intertwined production network and well-connected market. As a result, the effectiveness of carbon trading market can no longer be evaluated solely for the regulated regions or industries. Their spillover effects along production networks are necessary for determining whether the policy simply cuts carbon emissions radically or just drives their transmission. To this end, we regarded the pilot carbon emission trading market (PET) in China, as a quasi-natural experiment and employed the multi-regional input-output model to depict the inter-industry linkages. Its spillover impacts on their complementary (including upstream and downstream) and competitive industries have been examined separately, along with the deep mechanism and its heterogeneous feature. Results show that the PET significantly suppresses carbon emissions in upstream industries, while promoting carbon emissions in competitive ones. Furthermore, the PET reduces emissions in upstream industries mainly by decreasing production scale and improving technological innovation. In contrast, the production scale of the downstream industry is not significantly affected, though its energy structure and carbon emission intensity have been improved to a certain extent. Worse still, competitive industries seize the market share of regulated industries and expand production, leading to an increase in carbon emissions.

More than rubber: Exploring the benefits and practicalities of diverse intercropping systems in rubber plantations

Conventional monocrop rubber farming, while profitable, has led to significant environmental and socio-economic issues. These include deforestation, reduced soil fertility, loss of biodiversity, and increased carbon emissions. Economically, smallholder farmers face risks due to fluctuating rubber prices and income dependency on a single crop. This situation has resulted in low incomes, labour shortages, and, in some cases, abandonment of rubber plantations. Intercropping, or modern rubber agroforestry, offers a promising solution to these challenges. This approach involves planting other crops or trees alongside rubber, increasing revenue, enhancing soil properties, conserving moisture, reducing erosion and improving overall rubber crop yield. Various crops such as fruits (Salaca palm, gnetum, banana and lemon), vegetables (Cucumber, arrowroot, french bean, chilli, mung bean, broad leaf pumpkin, yam, cowpea and egusi melon), spices (Ginger, turmeric, coriander, fenugreek, black pepper, vanilla, cinnamon and nutmeg) and medicinal plants (Sarpagandha, kalmegh, lesser galangal, satavar and long pepper) can be successfully grown with rubber. However, implementing intercropping systems comes with challenges, including potential adverse effects on rubber growth and yield if not appropriately managed. Farmers must implement good agricultural practices and integrated farming strategies to achieve sustainable economic and ecological benefits from rubber-based intercropping. This includes careful selection of cultivars, optimal planting and spacing, regular maintenance and balanced fertilizer application. This review explored essential intercropping practices and highlighted successful case studies within rubber plantations. While more complex than traditional monocropping, a well-managed intercropping system can provide diverse income sources, improve agro-biodiversity and contribute to more sustainable rubber farming practices.

Study on the Spatial and Temporal Evolution of Building Carbon Emissions and Influencing Factors in the Urban Agglomeration of the Yangtze River Economic Belt

With the rapid urbanization process, the construction industry has become a significant source of urban carbon emissions in China. The carbon emissions from buildings in the urban clusters of the Yangtze River Economic Belt, a crucial region for China’s economic development, have attracted considerable attention. This study focuses on urban buildings and aims to investigate the primary influencing factors of building carbon emissions in the urban clusters of the Yangtze River Economic Belt. The study highlights the innovative use of nighttime light remote sensing data to analyze urban carbon emissions and provides an in-depth exploration of the spatiotemporal characteristics of building carbon emissions in the urban clusters of the Yangtze River Economic Belt. Utilizing nighttime light remote sensing data similar to DMSP-OLS and provincial-level building carbon emissions, combined with spatial autocorrelation and spatiotemporal geographically weighted regression models, the study estimates and analyzes the building carbon emissions from 2012 to 2021 in 71 prefecture-level and above administrative regions within the three major urban clusters of the Yangtze River Economic Belt. The results indicate a continuous increase in total building carbon emissions in the three major urban clusters of the Yangtze River Economic Belt, with an accelerating growth rate. Spatially, urban building carbon emissions exhibit enhanced convergence but decreasing correlation over time, demonstrating evolving spatiotemporal patterns. Furthermore, the study identifies economic development level, population size, built-up area, and industrial structure as the main factors influencing building carbon emissions, with industrial structure showing significant impact.

Strategic emerging enterprises drive city-level carbon emission efficiency in China

Given the substantial economic and environmental challenges faced by global cities, enhancing carbon emission efficiency at the city level is critical for achieving urban carbon neutrality. In this context, strategic emerging enterprises play a dual role, not only driving economic expansion but also acting as catalysts for environmental sustainability. By analyzing time series data from 2013 to 2022, covering 1805 listed companies in 30 provinces and 293 cities across China, this study explores the relationship between the growth of strategic emerging enterprises and carbon emission efficiency at both the city and regional levels. The findings show a positive spatial correlation between the expansion of these enterprises and increased carbon emission efficiency, with clear spillover effects across neighboring regions. Specifically, 1 % increase in carbon emission efficiency in one city or province leads to corresponding increases of 0.168 % and 0.187 % in surrounding areas. Furthermore, the results reveal a “U-shaped” nonlinear relationship between strategic emerging enterprise growth and carbon emission efficiency, where efficiency initially declines before improving. These results underscore the critical importance of balancing economic expansion with decarbonization objectives at the city level, offering valuable insights for shaping city-focused carbon reduction strategies across sub-national regions.

A Rooftop Solar Photovoltaic Tree Solution for Small-Scale Industries

With the increase in population and the growing demands of industrialization, carbon emissions across the globe are increasing exponentially. Furthermore, the demand for clean energy from renewable sources (solar, wind, etc.) is growing at an unparalleled rate to fight against the climate change caused by these increased carbon emissions. However, at present, it is very difficult for small-scale industries in urban areas to install solar power systems due to constraints around the operation area and on rooftops. Therefore, these small-scale industries are not able to install any solar plants and, thus, are not able to reduce their carbon emissions. In the context of this problem regarding the generation of cleaner energy and reducing carbon emissions by small-scale industries in urban areas, a model of a rooftop solar photovoltaic tree (SPVT) has been proposed that may be considered by small-scale industries in the place of a conventional rooftop solar photovoltaic (SPV) system. It is also noted that various models of SPVT systems are commercially available on the market, each with their own unique features. However, no new SPVT model has been designed or provided in this paper, which simply presents simulation studies comparing a conventional rooftop SPV system and an SPVT system. The results show that a 9.12 kWp SPVT system can be installed in just 6 Sq.mt, while a 3.8 kWp conventional SPV system requires 40 Sq.mt of rooftop area. Consequently, an SPVT generates around 128% more electricity than a conventional SPV, leading to greater reductions in carbon emissions. Thus, the objective of this study is to identify the most suitable option for small-scale industries in densely populated urban areas to generate electricity and maximize carbon emission reduction.

Urban travel carbon emission mitigation approach using deep reinforcement learning

The urbanization process has led to a significant increase in energy consumption and carbon emissions, which can be mitigated through scientific urban planning and management. This research proposes a bottom-up urban carbon emission mitigation strategy based on deep reinforcement learning (DRL). Using Ningbo City as a case study, multi-source urban data, including points of interest (POI) data and urban transportation system data, are utilized, along with varying carbon emission coefficients for different travel modes, to construct a comprehensive carbon emission environment for urban areas. The proposed DRL model adopts an Actor-Critic framework, which iteratively optimizes the land use configuration and building type proportions within the urban matrix to achieve the goal of mitigating travel carbon emissions. Experimental results demonstrate that this approach exhibits significant carbon reduction effects in urban scenario. By adjusting the discount rate of the reward function, various optimization strategies can be obtained, such as short-term and long-term strategies, achieving reductions of 0.47% and 0.61%, respectively, which are notably higher than the 0.39% reduction expected if travel emissions were uniformly distributed across the matrix. The findings highlight the potential of DRL-based approaches in urban planning to achieve adaptive and data-driven strategies for carbon emission mitigation.

Sipping Sustainability: Exploring the Green Marketing Mix Driving the Purchase of Oat M*lk Oatside

The issue of climate change due to global warming has occurred partly due to the significant increase in carbon emissions over the last few decades. This has created a market demand for products that have minimal adverse effects on the environment, also known as eco-friendly products. One of the popular eco-friendly products is oat milk. Despite the environmental issues highlighted and the product quality offered, the popularity of Oat M*lk Oatside remains low, and its higher price compared to cow's milk may influence purchasing decisions. This study aims to determine whether green product, green price, green place, and green promotion have an impact on the purchasing decisions of Oat M*lk Oatside. This study uses a quantitative approach, targeting the Instagram followers of @oatside, totaling 52,807, and a sample size of 100 people was obtained using purposive sampling, with criteria being Oat M*lk Oatside consumers residing in Jakarta. Data processing results show that Green Product and Green Promotion do not influence Purchasing Decisions, whereas Green Price and Green Place positively influence Purchasing Decisions. Green Price has a weak influence of 34.4%, and Green Place has a weak influence of 21.6% on Oat M*lk Oatside purchasing decisions.