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The purpose of this study is to systematically review available state-of-the-art literature on comparative studies on Quick Commerce (Q-commerce) and E-commerce and their greenhouse gas (GHG) emissions.

The literature survey methodology is based on the funneling approach of Kitchenham (2004), where results are obtained according to inclusion and exclusion criteria. The literature review methodology used for this study covers the period from 2016 to 2022. The areas considered for the survey are operations, logistics and supply chain network design for the distribution of goods in e-business. After deciding on the criteria, a total of 140 articles were extracted from 9 journal articles that study e-commerce and environmental emissions.

The result of this study reveals that GHG emissions from both modes of shopping depend on various parameters such as speed of delivery, last-mile depot locations, logistics and vehicle efficiency, customers’ order patterns and average basket size. Furthermore, the findings also highlight the difference between Q-commerce and E-commerce supply chain networks.

This study only accounts for GHG emissions from logistics activities, but there are other sources of GHG emissions in the overall supply chain that are not taken into consideration. Supply chain/business analysts in Q-commerce companies might refer the findings from this study to measure GHG emissions from their operations.

This is the first study in the Q-commerce field that uses a structured approach to find relevant literature from the years 2016 to 2022 and focuses on GHG emission measurement.

This study aims to explore empirical evidence of the impact of greenhouse gas (GHG) emissions on stock market volatility.

Using panel data of 35 Organization for Economic Co-operation and Development countries from 1992 to 2018, we conduct both fixed effects panel model and Prais-Winsten model with panel-corrected standard errors.

The authors document that there is a significant positive relationship between GHG emissions and stock market volatility. The results remain robust after controlling for potential endogeneity problems.

This study contributes to the literature in that it provides additional empirical evidence for the financial risk posed by climate change.

During the planting process, agricultural products produce large amounts of greenhouse gas (GHG) emissions. This has placed tremendous pressure on sustainable global development. Many countries and regions in the world have adopted intensive subsistence cultivation methods when planting maize; however, limited studies exist on these methods. The main purpose of this research is to show the impact of climate change on maize yields and carbon footprint (CF) in South Korea over 10 years, find the proper operating method and promote the advanced combination of inputs for the sustainable development of maize farmers.

This study used survey data from the South Korea Rural Development Administration of 2010, 2014 and 2019 to estimate the CF of maize planting under intensive subsistence cultivation. Life-cycle assessment was used to determine the CF. Farmers were grouped according to significant differences in yield and GHG emissions. Linear regression was used to measure the dependence of the main contributors on the CF production and carbon efficiency.

In South Korean maize planting, N in chemical fertiliser was the most significant contributor to the CF and organic fertiliser was the most significant input. The use of chemical and organic fertilisers significantly affects the production of the CF and carbon efficiency. Households in the high-yield and low-GHG emission groups are more sustainable because they generate the least GHG when producing and earning through maize cultivation. Globally, maize production in South Korea has a relatively low CF and maize production produces fewer GHG.

This study provides information for policymakers to determine key operational options for reducing GHG emissions using intensive subsistence cultivation of maize production in South Korea and other countries.

For the case of Sweden, this paper aims to determine how a range of different infrastructure fees and taxes influences modal split, port throughputs, air emissions, societal costs of greenhouse gas (GHG) emissions and air pollution, as well as logistics costs.

The Swedish national freight model is used to simulate a range of different proposed infrastructure fees, one by one and in combination. The volume of emissions of CO₂-equivalents, NOx, SOx and PM under the different scenarios is calculated in both volume and monetary terms, by applying national emission factors and EU values for external costs.

Road user fees are calculated to have the largest impact on the modal split, GHG emissions and air pollution. The impact increases slightly when road user fees are combined with higher fees for sea and rail and/or gate fees in all Swedish ports. The imposition of gate fees over €30 per truck in all ports leads to shifts in cargo to land-based modes and to ports outside Sweden. The logistics costs in Sweden are found to be three to ten times higher than the benefits of reduced GHG emissions and air pollution, although other benefits to society need to be considered as well.

Methods which attempt to evaluate alternative approaches to the internalisation of the external costs caused by transport need to be further developed. In particular, they need to encompass a more holistic perspective on “benefits to society”, other than merely reductions in GHG emissions and air pollution. To facilitate international acceptance and adoption, such methods require agreements to be reached on common definitions and routines.

The results can be used as basis for policy-making. They illustrate the environmental impacts of the fees and taxes one by one and in combination and to what extent these reinforce each other and should be co-ordinated.

The outcomes are relevant to national and international policymakers and authorities, as well as port authorities, shippers and transport companies who need to determine unilateral strategies on how to reduce GHG emissions and air pollution, without undermining their wider business objectives.

The approach is original in facilitating the testing of policies which impact on the transport system and the environment across different dimensions. The work has additional value in informing policy because of its use of Sweden’s national freight transport model.

This paper presents a new and well-structured framework that aims to assess the current environmental impact from a Greenhouse Gas (GHG) emissions perspective. This tool includes a new set of Lean Key Performance Indicators (KPIs), which translates the well-known logic of Overall Equipment Effectiveness in the field of GHG emissions, that can progressively detect industrial losses that cause GHG emissions and support decision-making for implementing improvements.

The new metrics are presented with reference to two different perspectives: (1) to highlight the deviation of the current value of emissions from the target; (2) to adopt a diagnostic orientation not only to provide an assessment of current performance but also to search for the main causes of inefficiencies and to direct improvement implementations.

The proposed framework was applied to a major company operating in the plywood production sector. It identified emission-related losses at each stage of the production process, providing an overall performance evaluation of 53.1%. The industrial application shows how the indicators work in practice, and the framework as a whole, to assess GHG emissions related to industrial losses and to proper address improvement actions.

This paper scrutinizes a new set of Lean KPIs to assess the industrial losses causing GHG emissions and identifies some significant drawbacks. Then it proposes a new structure of losses and KPIs that not only quantify efficiency but also allow to identify viable countermeasures.

The purpose of the study is to consolidate a set of indicators for assessing design and construction phase strategies for reducing operational greenhouse gas (GHG) emission. They will also estimate the quantity of operational GHG emission and its associated reduction over assessment period.

Five steps framework adopted include defining the purpose of the indicators and selection of candidate indicators. Others are defining the criteria for indicator selection, selecting and defining the proposed indicators. Relevancy, measurability, prevalence, preference, feasibility and adaptability of the indicator were the criteria used for selecting the indicators.

The study consolidated public transport accessibility, sustainable parking space, green vehicle priority, proximity to amenities and alternative modes as indicators for design and construction phase strategies. Transportation accounting and carbon footprint (CFP) and their associated reduction are indicators for operational GHG emission while plan and policy is an indicator for policymakers and stakeholders.

The study shows that providing correct indicators for assessing direct and indirect GHG emission with easy to obtain data is essential for assessment of built environment. Stakeholder can use the indicators in developing new rating systems and researchers as an additional knowledge. Policy makers and stakeholders can use the study in monitoring and rewarding the sustainability and activities of building related industries and organisations.

The study was conducted at the Center for Energy and Industrial Environmental Studies (CEIES) Universiti Tun Hussein Onn Malaysia and utilises existing rating systems and tools, Intergovernmental Panel on Climate Change (IPCC) and GHG protocol reports and guides and several other standards, which are open for research.

Different livestock production systems contribute to globally Greenhouse gas emission (GHG) emission differently. The aim of this paper is to understand variation in emission in different production systems and it is also important for developing mitigation interventions that work for a specific production system.

In this study, the authors used the Global Livestock Environmental Assessment interactive model (GLEAM-i) to estimate the GHG emission and emission intensity and tested the effectiveness of mitigation strategies from 180 farms under three production systems in northern Ethiopia, namely, pastoral, mixed and urban production systems.

Production systems varied in terms of herd composition, livestock productivity, livestock reproductive parameters and manure management systems, which resulted in difference in total GHG emission. Methane (82.77%) was the largest contributor followed by carbon dioxide (13.40%) and nitrous oxide (3.83%). While both total carbon dioxide and methane were significantly higher (p < 0.05) in urban production system than the other systems emission intensities of cow’s milk and goat and sheep’s meat were lower in urban systems. Improvement in feed, manure management and herd parameters resulted in reduction of total GHG emission by 30, 29 and 21% in pastoral, mixed and urban production systems, respectively.

This study is a first time comparison of the GHG emission production by various production systems in northern Ethiopia. Moreover, it uses the GLEAM-i program for the first time in the ex ante settings for measuring and comparing emissions as well as for developing mitigation scenarios. By doing so, it provides information on the various livestock production system properties that contribute to the increase or decrease in GHG emission and helps in developing guidelines for low emission livestock production systems.

This study aims to investigate patterns in international travel behavior of scientific staff depending on the categories of gender, scientific field and scientific seniority level. The learning from salient differences possibly revealed may inform measures for reducing travel greenhouse gas (GHG) emissions, especially for high-emitting staff groups, and help strengthen the equality between scientists of different categories concerning their travel behavior.

The study collected and used novel empirical data on travel GHG emissions from University of Graz scientific staff for five consecutive years (2015–2019) and used statistical analysis and inference to test and answer three distinct research questions on patterns of travel behavior.

The travel footprint of scientific staff, in terms of annual GHG emissions per scientist, exhibits various highly significant differences across scientific fields, seniority and gender, such as male senior natural scientists showing ten times higher per-person emissions than female junior social scientists.

The five-year travel GHG emissions data set across all fields from natural sciences via social sciences to humanities at a large university (Uni Graz, Austria, about 2,000 scientific staff) and across seniority levels from predocs to professors, both for female and male scientists, enabled a robust empirical study revealing distinct differences in travel GHG footprints of academic staff. In this way, the study adds valuable insights for higher research institutions toward effective GHG reduction policies.

This paper aims to focus on scrutinizing the economics of greenhouse gas (GHG) emissions in Vietnam's rice production sector.

Using surveyed data from household rice producers, the smallest available production scale, the author delves into the economics of GHG emissions, constructs a data-driven bottom-up marginal abatement cost curve for Vietnam’s rice production, and evaluates the impacts of carbon pricing on production outputs and GHG emissions.

The author’s estimates reveal that the average profit earned per tonne of GHG emissions is $240/tCO2. Notably, the profit earning per tonne of GHG emissions varies substantially across producers, indicating significant opportunities for improvement among low-efficiency producers. The analysis suggests that a reasonable carbon price would yield a modest impact on the national rice output. The quantitative analysis also reaffirms that the primary driver of GHG emissions in Vietnam’s rice production stems from non-energy inputs and industrial processes rather than the utilisation of energy inputs, emphasizing the importance of improving cultivation techniques.

This research is original.

The relationship between farm size and greenhouse gas (GHG) emissions has not been clearly defined. This paper aims to assess and compare the impact of farm size on greenhouse gas (GHG) emissions derived from wheat and maize production in the North China Plain (NCP), one of the most important agricultural regions in China.

A field survey through face-to-face interviews was conducted to collect the primary data, and life cycle assessment method, a worldwide comparable framework, was then adopted to characterize the farm-size effect on greenhouse gas (GHG) wheat and maize production in NCP.

It was confirmed that GHG emissions from N fertilizer production and use were the primary contributor to total carbon footprint (CF). As farm size increased, maize yield increased but wheat yield barely changed, while area-scaled and yield-scaled CF declined for both crops. These results were supposed to relate to utilize the inputs more efficiently resulting from increased application of modern agriculture methods on larger operations. It was also found maize not only had higher grain yields, but possessed much smaller CFs. More notably, the reduction of CF with farm size seemed to be more sensitive for maize as compared to wheat. To further mitigate GHG emissions, farm size should better be larger for wheat than for maize.

This study provides useful information guide for Chinese agriculture in increasing crop production, raising farm income and relieving environmental burdens caused by the misuse of agricultural resources.