An Environmental Tax Towards More Sustainable Food: Empirical Evidence of the Consumption of Animal Products in France

Feeding strategies and manure management for cost-effective mitigation of greenhouse gas emissions from dairy farms in Wisconsin

Hydrogen peroxide-aged biochar mitigating greenhouse gas emissions during co-composting of swine manure with rice bran.

Sewage treatment processes are considered an important source of greenhouse gas (GHG) emissions, particularly N2O and CH4. In rural sewage treatment processes, GHG emissions are often neglected owing to the small scale of treatment and dispersed distribution. In this study, the non-CO2 GHG emission quantity, spatiotemporal distribution characteristics, and influences factors were analyzed based on rural sewage from 2015 to 2020. Emissions from rural sewage treatment in 2020 reached 122.72 Gg (CO2-eq), comprising 69.81 Gg N2O and 52.91 Gg CH4, representing a 35.29% increase compared to 2015. There are large variations between province-level regions: more GHG was emitted from the eastern than the north-west of China. The treatment of rural domestic sewage can simultaneously purify water quality and decrease GHG emissions, and the improvement in the rate of treatment is beneficial to "carbon peak and carbon neutralization." GHG emissions from rural sewage treatment showed a positive correlation with both GDP and sewage discharge, and N2O was positively correlated with protein consumption per capita. This study would provide a theoretical basis for policy formulation, as it supplies basic data on carbon emissions for China's rural sewage treatment. SUMMARY: Rural sewage treatment (RST) plants contribute significantly to GHG emissions. N2O emission from rural sewage treatment in 2020 in China was 69.81 Gg. CH4 emission from rural sewage treatment in 2020 in China was 52.91 Gg. Large variations in GHG emissions were found between province-level regions. Domestic RST can simultaneously purify water quality and decrease GHG emissions.

Quantifying the impact of energy consumption sources on GHG emissions in major economies: A machine learning approach

Almost 200 nations, including the European Union, have signed the Paris Agreement that aims to limit the temperature rise to 1.5 °C above pre-industrial levels by reducing greenhouse gas (GHG) emissions. To meet this target, a significant decrease in GHG emissions by 2030 and net zero by 2050 is necessary. To determine the role of wood products in achieving a 55% reduction in GHG emissions by 2030 compared with 1990 levels, we investigated Slovenia’s potential, which has close to 60% forested areas. Therefore, the country could use wood-based products to achieve the agreed-upon climate goals. Nevertheless, uncertainties remain regarding the extent to which increased tree harvesting, local manufacturing, and the utilization of wood products can aid in substituting fossil-derived materials and reducing GHG emissions. A new model was constructed to increase the understanding of the wood products’ (throughout the forest-based industrial ecosystem, incl. construction) potential contribution to reaching the stated emissions targets. Using this linear programming (LP) mathematical optimisation model and carbon footprint calculations based on life cycle assessment methods, a wood flow distribution, the financial investment needed to process these quantities, and the GHG emissions produced and/or saved were calculated. The findings stipulated that Slovenia has the potential to achieve 55 % less GHG emissions by 2030 by expanding logging to at least 3 million m3 and converting the timber to a larger amount of long service-life wooden items made (and utilised) within the country. Such products accumulate carbon for a long time and decrease the need for materials that cause higher GHG emissions. Concomitantly, a better appreciation of the substitution effects in official carbon accounting would be needed. Moreover, to materialize the potential decrease in emissions would require Slovenia’s construction sector to replace fossil- and mineral-based materials with lignocellulosic products, and to increase the capacity to utilize lower-quality wood in high added value applications, which would require significant investment. This paper offers a comprehensive analysis of diverse optimisation outcomes obtained from the investigation into climate action through the use of wood products in Slovenia.

PurposeVariability in consumer behaviour can significantly influence the environmental performance of products and their associated impacts and this is typically not quantified in life cycle assessments. The goal of this paper is to demonstrate how consumer behaviour data can be used to understand and quantify the variability in the greenhouse gas emissions from domestic laundry washing across Europe.MethodsData from a pan-European consumer survey of product usage and washing habits was combined with internal company data on product format greenhouse gas (GHG) footprints and in-home measurement of energy consumption of laundry washing as well as literature data to determine the GHG footprint of laundry washing. The variability associated with four laundry detergent product formats and four wash temperature settings in washing machines were quantified on a per wash cycle basis across 23 European countries. The variability in GHG emissions associated with country electricity grid mixes was also taken into account. Monte Carlo methods were used to convert the variability in the input parameters into variability of the life cycle GHG emissions. Rank correlation analysis was used to quantify the importance of the different sources of variability.Results and discussionBoth inter-country differences in background electricity mix as well as intra-country variation in consumer behaviour are important for determining the variability in life cycle GHG emissions of laundry detergents. The average GHG emissions related to the laundry washing process in the 23 European countries in 2014 was estimated to be 5 × 102 g CO2−eq/wash cycle, but varied by a factor of 6.5 between countries. Intra-country variability is between a factor of 3.5 and 5.0 (90% interval). For countries with a mainly fossil-based electricity system, the dominant source of variability in GHG emissions results from consumer choices in the use of washing machines. For countries with a relatively low-carbon electricity mix, variability in life cycle GHG emissions is mainly determined by laundry product-related parameters.ConclusionsThe combination of rich data sources enabled the quantification of the variability in the life cycle GHG emissions of laundry washing which is driven by a variety of consumer choices, manufacturer choices and infrastructural differences of countries. The improved understanding of the variability needs to be balanced against the cost and challenges of assessing of consumer habits.

Livestock production is under growing public and scientific scrutiny for its greenhouse gas (GHG) emissions. This article contains a preliminary assessment of the inclusion of upstream life-cycle GHG emissions in concentrated feeds design, using the most common nonlinear programming optimization algorithms to determine feed composition. First, GHG emissions are included as costs in a single criteria optimization problem. The unit price of GHG emissions was obtained using a genetic algorithm. Second, GHG emissions are included as a target function to minimize in a multi criteria optimization problem using goal attainment programming. Results obtained after both optimization methods were applied to two case studies, namely fattening pigs and rabbit feeds. Changing ingredients in concentrated feed blends has a marginal effect on GHG emissions due to mandatory nutritional constraints. If the optimization is unconstrained, the maximum possible decrease in GHG emissions is 27.5% for the pigs feed, accompanied by increasing costs and a decrease in feed nutritional quality. To maintain nutritional integrity, the maximum possible reduction in GHG emissions is 7.5%. Considering cost as an optimization variable in the problem, the maximum decreases are even lower. It is possible to decrease emissions by 71% for the rabbits feed, but the cost of the reduction is higher than the opportunity cost for farmers to reduce GHG emissions using other strategies. These results are qualitatively robust but critically depend on feed ingredients GHG emissions and cost data.

South Korean consumers’ preferences for eco-friendly gasoline sedans: Results from a choice experiment survey

This research aims to assess the socio-economic and environmental impacts of the Lithuanian long-term renovation strategy, focusing on improvements in the energy performance of renovated multi-apartment buildings in the country. The methodology used in the study is centred on the CleanProd general equilibrium model, which is based on publicly available data from the FIGARO database and Eurostat’s non-financial transaction statistics. The four renovation financing scenarios analysed are represented in the model by changes in the demand for energy resources and construction and other transactions related to the renovation programme. To reflect the dynamic nature of the renovation programme, counterfactual equilibria are sought for each year of the renovation programme. The results revealed that renovation of multi-apartment buildings brings net benefits, including long-term increases in gross domestic products (GDPs) and employment, as well as a decrease in economy-wide greenhouse gas (GHG) emissions, and is aligned with the binding European Union’s energy efficiency target to reduce energy consumption at least by 11.7% in 2030 (in comparison to 2020). The Increase in Taxes on Products scenario is modelled as the most favourable scenario. It assures annual GDP growth by 0.37%, employment growth by 2170 jobs a year, including 606 jobs for young people, and an annual decrease in GHG emissions by 929–1043 ktCO2eq. It is found that the most considerable benefits are received during the renovation of medium-size buildings when construction demand increases by EUR 600,000–800,000 per year and natural gas and district heating demand are reduced by EUR 59,000–187,000 per year. Other scenarios demonstrating different building renovation and energy efficiency support practices, including Costless, Reallocation of Governmental Expenditure, and Governmental Loan, show relevant but slightly lower benefits.

This paper examines the impact on the life cycle greenhouse gas (GHG) emissions reduction when fossil-fueled ICE gasoline, diesel and natural gas vehicles, hybrid electric vehicles (HEVs) and plug-in hybrid electric vehicles (PHEVs) are banned in a step-by-step manner from 2035. We examine the impact of vehicle bans on life cycle GHG emissions and on the marginal cost (MC) of emissions reduction using four different scenarios defined by hydrogen production method, renewable energy share, and infrastructure development for refueling stations. The vehicle penetration and the fuel demand are determined by a consumer choice model characterized by a multinomial logit algorithm. Our analysis found that vehicle bans significantly promote battery electric vehicles (BEVs) for mini-sized vehicles and hydrogen fuel cell vehicles (FCVs) for light and heavy-duty vehicles. A vehicle ban that excludes BEVs and FCVs from 2035 under an enhanced infrastructure plan can reduce the life cycle GHG emissions as much as 438 million tonnes by 2060 compared to the 2017 level. The MC of the life cycle GHG mitigation decreases continuously and reaches as low as $482 per tonne CO2eq in 2060. However, if PHEVs are excluded from the ban, the life cycle GHG emissions are reduced more by 88 Mt-CO2eq in 2060 at a lower MC of $122 per tonne CO2eq. This is due to decreases in GHG emissions from VP where the replacement of PHEVs for BEVs and FCVs reduces the production of batteries and fuel cells. The main structure of the model.

Over the last decades, all countries have pursued an ambitious climate policy, thus showing a growing concern about climate change, global warming, greenhouse gas (GHG) emissions, or environmental taxes. Water, air, and soil pollution caused by gas emissions directly affect human health, but also the economies of states. As people’s ability to adapt to novel changes becomes increasingly difficult, globally, they are constantly trying to reduce their greenhouse gas emissions in a variety of ways. Environmental taxes, in general, and energy taxes, in particular, are considered effective tools, being recommended by specialists, among other instruments used in environmental policy. The aim of this research is to assess, empirically, the influence of environmental taxes levels on greenhouse gas emissions in 28 European countries, with a time span between 1995 and 2019. Regarding the empirical research, the proposed methods are related to Autoregressive Distributed Lag (ARDL) models in panel data and also at country level. At panel level, we used the estimation of non-stationary heterogeneous panels and also the dynamic common-correlated effects model with heterogeneous coefficients over cross-sectional units and time periods. The results obtained show that the increase in environmental taxes leads, in most countries, to a decrease in greenhouse gas emissions. To test the robustness of our results, we have included supplementary economic and social control variables in the model, such as gross domestic product (GDP), population density, exports, or imports. Overall, our paper focuses on the role of environmental policy decisions on greenhouse gas emissions, the results of the study showing, in most cases, an inverse impact of the taxation level on the reduction of gas emissions.

Polyethylene terephthalate (PET) is a prominent plastic polymer known for its significant growth rates in recent decades, and it is utilized in nearly every aspect of daily life, particularly in textiles and for water bottles. PET resin demand is expected to increase from 25 million tonnes to 61 million tonnes between 2019 and 2060, and subsequent greenhouse gas (GHG) emissions are expected to peak from 42.25 million tonnes to 103.09 million tonnes of CO2 equivalent. The carbon neutrality in PET production is anchored mainly on two fronts: shifting from traditional fossil-based boilers to renewable alternatives, such as renewable natural gas or electric boilers, and low-carbon feedstocks based on biomass and carbon capture and utilization (CCU). This study investigates the emission intensities of these mitigation measures, leveraging a life cycle assessment of the production stage. The analysis underscores the importance of solar-electrified boilers, which can reduce emissions by 12%. On the other hand, the GHG reduction potential of biobased feedstocks depends on the specific pathway through which they are produced. For example, bioparaxylene made from isobutanol derived from ammonia fiber explosion corn stover can significantly reduce GHG emissions, while that made from isobutanol sourced from dilute acid pretreatment may increase business-as-usual emissions. Furthermore, recent innovations in CCU can significantly reduce GHG emissions. The production of ethanol from CO2 can achieve a 37% decrease in GHG emissions, while the electrochemical reduction of CO2 to produce ethylene for PET manufacturing results in a 66% decrease in GHG emissions.

Previous studies of greenhouse gas emissions (GHGE) from beef production systems in northern Australia have been based on models of ‘steady-state’ herd structures that do not take into account the considerable inter-annual variation in liveweight gain, reproduction and mortality rates that occurs due to seasonal conditions. Nor do they consider the implications of flexible stocking strategies designed to adapt these production systems to the highly variable climate. The aim of the present study was to quantify the variation in total GHGE (t CO2e) and GHGE intensity (t CO2e/t liveweight sold) for the beef industry in northern Australia when variability in these factors was considered. A combined GRASP–Enterprise modelling platform was used to simulate a breeding–finishing beef cattle property in the Burdekin River region of northern Queensland, using historical climate data from 1982–2011. GHGE was calculated using the method of Australian National Greenhouse Gas Inventory. Five different stocking-rate strategies were simulated with fixed stocking strategies at moderate and high rates, and three flexible stocking strategies where the stocking rate was adjusted annually by up to 5%, 10% or 20%, according to pasture available at the end of the growing season. Variation in total annual GHGE was lowest in the ‘fixed moderate’ (~9.5 ha/adult equivalent (AE)) stocking strategy, ranging from 3799 to 4471 t CO2e, and highest in the ‘fixed high’ strategy (~5.9 ha/AE), which ranged from 3771 to 7636 t CO2e. The ‘fixed moderate’ strategy had the least variation in GHGE intensity (15.7–19.4 t CO2e/t liveweight sold), while the ‘flexible 20’ strategy (up to 20% annual change in AE) had the largest range (10.5–40.8 t CO2e/t liveweight sold). Across the five stocking strategies, the ‘fixed moderate’ stocking-rate strategy had the highest simulated perennial grass percentage and pasture growth, highest average rate of liveweight gain (121 kg/steer), highest average branding percentage (74%) and lowest average breeding-cow mortality rate (3.9%), resulting in the lowest average GHGE intensity (16.9 t CO2e/t liveweight sold). The ‘fixed high’ stocking rate strategy (~5.9 ha/AE) performed the poorest in each of these measures, while the three flexible stocking strategies were intermediate. The ‘fixed moderate’ stocking strategy also yielded the highest average gross margin per AE carried and per hectare. These results highlight the importance of considering the influence of climate variability on stocking-rate management strategies and herd performance when estimating GHGE. The results also support a body of previous work that has recommended the adoption of moderate stocking strategies to enhance the profitability and ecological stability of beef production systems in northern Australia.

Intensive cultivation and post-harvest vegetable oil production stages are major sources of greenhouse gas (GHG) emissions. Variation between production systems and reporting disparity have resulted in discordance in previous emissions estimates. The aim of this study was to assess global systems-wide variation in GHG emissions resulting from palm, soybean, rapeseed and sunflower oil production. Such an analysis is critical to understand the implications of meeting increasing edible oil demand. To achieve this, we performed a unified re-analysis of life cycle input data from diverse palm, soybean, rapeseed, and sunflower oil production systems, from a saturating search of published literature. The resulting dataset reflects almost 6000 producers in 38 countries, and is representative of over 71% of global vegetable oil production. Across all oil crop systems, median GHG emissions were 3.81 kg CO2e per kg refined oil. Crop specific median emissions ranged from 2.49 kg CO2e for rapeseed oil to 4.25 kg CO2e for soybean oil per kg refined oil. Determination of the carbon cost of agricultural land occupation revealed that carbon storage potential in native compared to agricultural land cover drives variation in production GHG emissions, and indicates that expansion of production in low carbon storage potential land, whilst reforesting areas of high carbon storage potential, could reduce net GHG emissions whilst boosting productivity. Nevertheless, there remains considerable scope to improve sustainability within current production systems, including through increasing yields whilst limiting application of inputs with high carbon footprints, and in the case of palm oil through more widespread adoption of methane capture technologies in processing stages.

A significant amount of embodied greenhouse gas (GHG) emissions have been and are currently being traded in the globalized economy. The conventional territorial approach to the control of GHGs released within a country fails to account for a large portion of GHGs for which a country may take responsibility, particularly from the perspective of consumption. Given the large volume of products traded among nations, a series of studies have underscored the need for the global monitoring of GHG emissions not only generated from production but also driven by consumptive activities. This study develops time-series GHG emission inventories from 1995 to 2009 from both production- and consumption-based perspectives in the case of South Korea and analyzes the factors that influence the increase and the decrease of GHG emissions. This empirical analysis has determined that production-based activities are more responsible for GHG emissions in South Korea than consumption-based activities. The analysis also found that the trade surplus of embodied GHG emissions in South Korea ranged from 0.31 to 1.01 tons per capita. A decomposition analysis showed that developments in environmental technology play a significant role in the reduction of GHG emissions, associated with a 45 % gross change in GHG emissions. However, this reduction was offset by increases in demand and changes in the input structure to energy-intensive sectors. The change of input structure is a critical factor contributing to trend in increasing embodied GHG emissions in not only South Korea but also nations linked with global trade.