Value Of Greenhouse Gas Emissions Research Articles

Switches in food and beverage product purchases can reduce greenhouse gas emissions in Australia.

Switching between similar food and beverage products may reduce greenhouse gas emissions (GHGe). Here, using consumer data linked to 23,550 product-specific GHGe values, we estimated annual GHGe attributable to product purchases consumed at home in Australia and calculated reductions from specific switches. Potential changes to mean Health Star Rating, mean energy density and the proportion of ultraprocessed foods purchased were assessed. Approximately 31 million tonnes of GHGe were attributable to products consumed at home in 2019, the three highest contributors of GHGe being 'meat and meat products' (49%), 'dairy' (17%) and 'non-alcoholic beverages' (16%). Switching higher-emission products for 'very similar' lower-emission products could reduce total emissions by 26%. Switches to 'less similar' lower-emission products could lead to a 71% reduction. Switches had little impact on the average Health Star Rating, energy density of purchases and proportion of ultraprocessed foods purchased. Directing manufacturing and marketing towards lower-environmental-impact products and signposting such options to consumers are key.

Environmental sustainability of diets among children and adolescents in the German DONALD cohort study: age and time trends, and nutrient adequacy

BackgroundIdentifying diets beneficial for both human and planetary health has become increasingly important. However, to date, there is limited research on sustainable diets for children and adolescents, a vulnerable population group with specific nutritional needs. ObjectivesWe aimed to identify 1) the main determinants; 2) age and time trends of greenhouse gas emissions (GHGE), land use (LU), and water use (WU) of diets of children and adolescents; and 3) analyze the associations of dietary GHGE, LU, and WU with nutrient adequacy. MethodsA total of 5510 3-d-weighted dietary records (n = 856; 6–17 y; 48% ♀) of the DONALD (DOrtmund Nutritional and Anthropometric Longitudinally Designed) study between 2000 and 2021 were analyzed. Values of GHGE (kgCO2eq), LU (m2 × year), and WU (L) determined by life cycle assessment were assigned to all recorded foods. For nutrient adequacy, the mean adequacy ratio (MAR = ∑(nutrient intake / recommended intake) / number of nutrients) was used. Data were analyzed using polynomial mixed-effects regression models. ResultsThe main contributors to GHGE and LU were meat products (GHGE: 25.6%; LU: 32.8%), dairy products (22.2%; 17.7%), and sweets and pastries (14.0%; 14.3%); to WU, nonalcoholic beverages (24.3%), meat products (18.9%), and vegetables and fruits (17.7%). GHGE, LU, and WU per 1000 kcal increased with age (P < 0.01). GHGE and LU per 1000 kcal increased between 2000 and 2010 and decreased after that in females (P < 0.01) and males (GHGE only: P = 0.02). No significant time trend was found for WU (P > 0.05). A higher MAR was directly associated with GHGE/1000 kcal (MAR: β: 0.011, 95% CI: 0.008, 0.013, P < 0.0001), LU/1000 kcal (MAR: β: 0.009, 95%CI: 0.005, 0.013, P < 0.0001), and WU/1000 kcal (MAR: β: 0.429, 95% CI: 0.325, 0.533, P < 0.0001). ConclusionsOur findings underscore the further need and the capacity for change toward more environmentally sustainable diets. Yet, the tradeoff between environmental sustainability and nutrient adequacy in the diets of children and adolescents requires specific attention to dietary composition.

The effect of an app-based dietary intervention on diet-related greenhouse gas emissions – results from a randomized controlled trial

BackgroundDietary change towards a diet low in greenhouse gas emissions (GHGEs) can reduce climate impact and improve individual-level health. However, there is a lack of understanding if diet interventions can achieve low-GHGE diets.MethodsA randomized controlled trial was conducted to assess the effects of an app-based intervention. The intervention was designed to improve dietary intake of people with Type 2 diabetes, and was delivered via an app over 12 weeks, with each week covering one diet-related topic. Dietary intake was assessed at baseline and 3-month follow up by a 95-item food frequency questionnaire and linked to GHGE values. A total of n = 93 participants (n = 46 and n = 47 for the intervention and control group, respectively) were included in the analysis. Changes to GHGEs within and between the groups were analysed with inferential statistics.ResultsThe majority (60%) of participants were male, with a mean age of 63.2 years and body mass index of 30 kg/m2. At baseline, diet-related GHGEs were 4.8 and 4.9 kg CO2-eq/day in the intervention and control group, respectively. At 3-month follow up the corresponding GHGEs were 4.7 and 4.9 kg CO2-eq/day. We found no statistically significant changes to diet-related GHGEs within or between groups, or within food categories, from baseline to 3-month follow up.ConclusionNo evidence was found for the effectiveness of the app-based intervention to generate changes to diet-related GHGEs in a population of people with Type 2 diabetes. However, future interventions that target reducing meat consumption specifically may have the potential to result in a reduction of individual-level diet-related GHGEs.Trial registrationClinicalTrials.gov, NCT03784612. Registered 24 December 2018. www.clinicaltrials.gov/ct2/show/NCT03784612.

A novel approach to estimate product-specific greenhouse gas emissions for 23,550 Australian packaged foods and beverages

Greenhouse gas emissions (GHGe) data are predominantly available for agricultural commodities and broad dietary patterns. However, data on commonly consumed, multi-ingredient food products as sold in supermarkets and retail outlets are mostly absent. We developed a novel approach to estimate product-specific GHGe for individual packaged foods and beverages marketed in Australia in 2019. Ingredient lists for 23,550 packaged products were systematically disaggregated and a linear program was used to estimate ingredient proportions in each product. Ingredient-specific, cradle-to-farm gate GHGe values were identified from five life cycle assessment data sources. Weighted GHGe values for each ingredient were summed up to a product-specific GHGe estimate that was then additionally adjusted for processing and transport-related emissions to account for most attributable emissions from cradle-to-retail. To assess validity, GHGe for food categories, estimated as the median of product-specific GHGe estimates, were compared against existing GHGe values for analogous food groups. The included products contained 897 different ingredients for which GHGe values were determined using data from 433 life cycle assessments. The estimated median for cradle-to-retail GHGe for all products was 2.35 kg CO2eq/kg product (interquartile range, IQR, [1.24, 4.53]). Product-specific GHGe estimates varied substantially within food categories; the 25th and 75th percentile of GHGe values differed by 2-fold or more for most. ‘Meat and meat products’ had the highest median GHGe value and broadest range of estimates (6.81 kg CO2eq/kg product, IQR [5.84, 29.2]). ‘Fruit, vegetables, nuts and legumes’ had the lowest median GHGe (1.20 kg CO2eq/kg product). Median category values for product-specific GHGe estimates aligned well with values for 34 food groups previously reported (R2 = 98.6%). Our approach provides a novel method for estimating product-specific GHGe for Australian packaged foods and beverages. The study enabled clear differentiation between products within a given category due to the unique ingredient proportion estimation method, while retaining good comparability against values derived using existing methods. These data have significant potential for driving industry actions and informing government policies.

Life Cycle Assessment of a Domestic Wastewater Treatment Plant Simulated with Alternative Operational Designs

Life cycle assessment (LCA) is a powerful tool to evaluate the environmental impacts of domestic wastewater treatment plant (WWTP) operations. It involves a thorough evaluation of the main characteristics or components of the environment, human health, and resources. However, the literature to date is still lacking analysis on the widely varied designs and operational conditions of full-scale WWTPs. The aim here was to integrate analyses such as LCA, greenhouse gas (GHG) emissions, and energy consumption, when considering the environmental impacts of a full-scale WWTP, which can provide practical outputs to aid decision-making on optimum designs and operational conditions. The Russtmiya domestic WWTP, located in Iraq, was considered as the case study. Three operational alternatives were proposed as solutions to improve the WWTP’s performance, as follows: (1) conventional activated sludge with sand filter (CAS), (2) conventional activated sludge with sand filter and nitrogen removal (CAS-N), and (3) membrane bioreactor (MBR). The operation of such alternatives was investigated through modeling and simulation using GPS-X 8.0.1 software. The energy consumption of each alternative was estimated via GPS-X, while the GHG emissions were estimated using three different methods according to the intergovernmental panel on climate change (IPCC), the United States Environmental Protection Agency (USEPA), and GPS-X software. The OpenLCA software (1.10.3) was used to measure all impact categories at both the midpoint and endpoint levels using various methods. As a conclusion, comparing the three proposed alternatives indicated that: (1) the MBR alternative provided the lowest energy consumption and moderate GHG emissions, and (2) the CAS alternative provided the best environmental performance, particularly in aspects such as ozone depletion, global warming, and climate change, where the lowest GHGs emission values had the major contribution.

Optimal Design and Mathematical Modeling of Hybrid Solar PV–Biogas Generator with Energy Storage Power Generation System in Multi-Objective Function Cases

This study demonstrates how to use grid-connected hybrid PV and biogas energy with a SMES-PHES storage system in a nation with frequent grid outages. The primary goal of this work is to enhance the HRES’s capacity to favorably influence the HRES’s economic viability, reliability, and environmental impact. The net present cost (NPC), greenhouse gas (GHG) emissions, and the likelihood of a power outage are among the variables that are examined. A mixed solution involves using a variety of methodologies to compromise aspects of the economy, reliability, and the environment. Metaheuristic optimization techniques such as non-dominated sorting whale optimization algorithm (NSWOA), multi-objective grey wolf optimization (MOGWO), and multi-objective particle swarm optimization (MOPSO) are used to find the best size for hybrid systems based on evaluation parameters for financial stability, reliability, and GHG emissions and have been evaluated using MATLAB. A thorough comparison between NSWOA, MOGWO, and MOPSO and the system parameters at 150 iterations has been presented. The outcomes demonstrated NSWOA’s superiority in achieving the best optimum value of the predefined multi-objective function, with MOGWO and MOPSO coming in second and third, respectively. The comparison study has focused on NSWOA’s ability to produce the best NPC, LPSP, and GHG emissions values, which are EUR 6.997 × 106, 0.0085, and 7.3679 × 106 Kg reduced, respectively. Additionally, the simulation results demonstrated that the NSWOA technique outperforms other optimization techniques in its ability to solve the optimization problem. Furthermore, the outcomes show that the designed system has acceptable NPC, LPSP, and GHG emissions values under various operating conditions.

Continuous Improvement of VIVA-Certified Wines: Analysis and Perspective of Greenhouse Gas Emissions

The agri-food sector is one of the major contributors of Greenhouse Gas (GHG) emissions responsible for global climate change. The suitability of world areas for viticulture is evolving due to climate change, with new challenges linked to the sustainability of production. Viticulture and the wine sector in general are, at the same time, impactful sectors associated with negative environmental externalities. The VIVA certification program is focused on the sustainability performance of the vine–wine supply chain in Italy. It comprehends four scientific indicators, called “Air”, “Water”, “Vineyard”, and “Territory”. The Air indicator expresses the impact that the production of a specific wine and / or the company activities have on climate change. This paper analyzes and compares GHG emissions of 45 wines certified VIVA 2.0 (or the subsequent 2.1 update). Results showed that the most impactful phase is the bottling phase (average values of 0.58 kg CO2-eq/bottle), which accounts for 41.1% of total emissions, followed by the industrial phase (about 19.9%). The total values of GHG emissions for each wine profile ranged between 0.81 and 2.52 kg CO2-eq/bottle. A coefficient of performances of GHG emissions was calculated to show the weak phase for each wine, a useful tool with a view to continuous improvement.

Bireysel Derin Kuyu Sulama İşletmesinde Enerji Kullanımı ve Sera Gazı Emisyonunun Belirlenmesi

This study was conducted to determine the annual energy use and related greenhouse gas (GHG) emissions of individual deep well irrigation enterprise. That study was conducted at deep well farm belonging to one farmer with volunteer preforming farming activities in Konya-Meram-Çarıklar location for the growing season of 2021. In that regard, the activities using alfalfa and dry bean production, and total production inputs with their amounts as well as crop yields were determined separately. By considering unit energy equivalent values and GHG emission factors of each input, annual energy consumption and GHG emission values were calculated. Similarly, by examining energy content and crop yield in accordance of crop production unit (kg), annual produced energy amount was calculated. The evaluation was made using energy used and energy produced as well as GHG emission values indicators at individual deep well irrigation farm. According to the results obtained, annual energy use and energy production were calculated 253035 mega-joule (MJ), and 487960 MJ, respectively for individual well irrigation farm. The electricity used during the irrigation processes resulted around 71% of annual energy consumption. The annual GHG emission amount as an equivalent to the carbon dioxide (CO2eqv) for research farm with GWI was determined as 18575 kg (18575 kgCO2eqv year-1). Almost 52% of annual GHG emission was resulted from electricity used in irrigation.

Life Cycle Greenhouse Gas Emission Assessment of Photovoltaic System in Indonesia

Climate crisis is arguably the biggest challenge that the world is currently facing. Extreme weather events are becoming more frequent while the continuous rise in sea level is putting billions of lives will be at risk. Solving the climate crisis requires global carbon emission to peak by 2025, which means that carbon-intensive fossil fuels must be replaced by low-carbon renewable sources in fulfilling our energy needs. Solar energy, due to its abundance, rapidly decreasing cost, and low carbon emission, is one of the most promising energy sources. Many studies have calculated and compared the life cycle greenhouse gas (GHG) emissions of solar photovoltaic (PV) systems with conventional fuel generation. Nevertheless, the life cycle GHG emission values are affected by many location- and technology-dependent factors. This work provides an up-to-date and realistic assessment of the life cycle GHG emission for PV systems in Indonesia through thorough literature review and harmonization according to Indonesian parameters. The study shows that PV GHG emission of 37.3-64.3 gCO2eq/kWh are much lower than the current emission intensity of the Indonesian power sector. By fulfilling rising electricity demand using PV, up to 654 MtCO2eq can be avoided annually by 2050.

Optimization of Hybrid Renewable Energy Microgrid for Rural Agricultural Area in Southern Philippines

Microgrids, or distributed systems of local energy generation, transmission, and demand, are now technologically and operationally capable of providing power to communities, especially in rural and peri-urban regions of developing nations. The reliability of the system, the cost of power generation, and the operating environmental impact are the major issues when designing and evaluating the performance of an off-grid hybrid renewable energy microgrid (HREM). This paper presents an integrated method for optimal sizing and operation of an HREM for rural agricultural communities in the Southern Philippines composed of run-of-the-river hydropower, photovoltaics (PV), diesel generator, and a battery energy storage system (BESS) using multi-objective particle swarm optimization (MOPSO) and a proposed multi-case power management strategy. The three conflicting objective functions that were simultaneously minimized were: loss of power supply probability (LPSP), levelized cost of energy (LCOE), and greenhouse gas (GHG) emissions, subject to several constraints. The optimization generated 200 non-dominated or Pareto optimal alternative solutions, 4 of which were selected as solutions of interest. Based on the results, the optimal sizes of the main components for the reliable operation of the system are 100 panels with a rating of 0.25 kW for PV, 100 kWh for BESS, and 13 kW for the diesel generator, with corresponding LCOE, LPSP, and GHG emission values of 0.1795 USD/kWh, 0.05%, and 7874 kg, respectively, for 1 year. The effectiveness of the proposed HREM design was also analyzed, and the study yielded plenty of useful findings that could aid the electrification of the area.

Benchmarking GHG Emissions Forecasting Models for Global Climate Policy

Climate change and pollution fighting have become prominent global concerns in the twenty-first century. In this context, accurate estimates for polluting emissions and their evolution are critical for robust policy-making processes and ultimately for solving stringent global climate challenges. As such, the primary objective of this study is to produce more accurate forecasts of greenhouse gas (GHG) emissions. This in turn contributes to the timely evaluation of the progress achieved towards meeting global climate goals set by international agendas and also acts as an early-warning system. We forecast the evolution of GHG emissions in 12 top polluting economies by using data for the 1970–2018 period and employing six econometric and machine-learning models (the exponential smoothing state-space model (ETS), the Holt–Winters model (HW), the TBATS model, the ARIMA model, the structural time series model (STS), and the neural network autoregression model (NNAR)), along with a naive model. A battery of robustness checks is performed. Results confirm a priori expectations and consistently indicate that the neural network autoregression model (NNAR) presents the best out-of-sample forecasting performance for GHG emissions at different forecasting horizons by reporting the lowest average RMSE (root mean square error) and MASE (mean absolute scaled error) within the array of predictive models. Predictions made by the NNAR model for the year 2030 indicate that total GHG emissions are projected to increase by 3.67% on average among the world’s 12 most polluting countries until 2030. Only four top polluters will record decreases in total GHG emissions values in the coming decades (i.e., Canada, the Russian Federation, the US, and China), although their emission levels will remain in the upper decile. Emission increases in a handful of developing economies will see significant growth rates (a 22.75% increase in GHG total emissions in Brazil, a 15.75% increase in Indonesia, and 7.45% in India) that are expected to offset the modest decreases in GHG emissions projected for the four countries. Our findings, therefore, suggest that the world’s top polluters cannot meet assumed pollution reduction targets in the form of NDCs under the Paris agreement. Results thus highlight the necessity for more impactful policies and measures to bring the set targets within reach.

Factors affecting changes of greenhouse gas emissions in Belt and Road countries

Promoting the sustainable economic development along the “Belt and Road Initiative” (BRI) requires to identify the driving force of total factor productivity (TFP) with the constrains of environmental variables. This study firstly, both theoretically and empirically, investigates the factors affecting changes of greenhouse gas (GHG) emissions (including CO2, CH4, and N2O) along BRI countries. Here, during 2000–2012, results show that overall average environmental inefficiency value of GHG emissions in the BRI countries was 0.29, 66% of which was contributed by energy and environmental variables. In addition, the average growth rate of TFP incorporating GHG emissions was 0.43%. In terms of source-specific decomposition of TFP, the contribution of technical progress is negative (−0.02%) while that of efficiency change is 0.44%. Turning to variable-specific decomposition, N2O, CH4, CO2, fossil fuel energy consumption, and renewable energy consumption have exhibited significant effects on the environmental progress index of GHG emissions, with the highest share of N2O. Moreover, the growth of N2O and CH4 emissions is primarily attributable to the factor of production of economic growth. The energy cleanliness and emission intensity factors play a significant role in reducing emissions. The increase in CO2 emissions is related to the economic growth factor, while the reduction due to the factor of energy emissions intensity is limited.

How does soil carbon sequestration affect greenhouse gas emissions from a sheep farming system? Results of a life cycle assessment case study

A life cycle assessment (LCA) study of a transition from semiintensive to semi-extensive Mediterranean dairy sheep farm suggests that the latter has a strong potential for offsetting greenhouse gas (GHG) emissions through the soil C sequestration (Cseq) in permanent grasslands. The extensification process shows clear environmental advantage when emission intensity is referred to the area-based functional unit (FU). Several LCA studies reported that extensive livestock systems have greater GHG emissions per mass of product than intensive one, due to their lower productivity. However, these studies did not account for soil Cseq of temporary and permanent grasslands, that have a strong potential to partly mitigate the GHG balance of ruminant production systems. Our LCA study was carried out considering the transition from a semiintensive (SI) towards a semi-extensive (SE) production system, adopted in a dairy sheep farm located in North-Western Sardinia (Italy). Impact scope included enteric methane emissions, feed production, on-farm energy use and transportation, infrastructures as well as the potential C sink from soil Cseq compared to emission intensity. In order to provide a more comprehensive analysis, we used the following FUs: 1 kg of fat and protein corrected milk (FPCM) and 1 ha of utilised agricultural area (UAA). We observed that the extensification of production system determined contrasting environmental effects when using different FUs accounting for soil Cseq. When soil Cseq in emission intensity estimate was included, we observed slightly lower values of GHG emissions per kg of FPCM in the SI production system (from 3.37 to 3.12 kg CO2 equivalents – CO2-eq), whereas a greater variation we observed in the SE one (from 3.54 to 2.90 kg CO2-eq). Considering 1 ha of UAA as FU and including the soil Cseq, the emission intensity in SI moved from 6257 to 5793 kg CO2-eq, whereas values varied from 4020 to 3299 kg CO2-eq in SE. These results indicated that the emission intensity from semi-extensive Mediterranean dairy sheep farms can be considerably reduced through the soil Cseq, although its measurement is influenced by the models used in the estimation. Highlights - Extensification of dairy sheep systems provides an environmental benefit when soil C sequestration is considered. - Extensification of dairy sheep systems determines lower environmental impact per hectare of utilized agricultural area. - Enteric methane emissions are the main source of GHG emissions of the sheep milk life cycle. - Carbon sequestration in permanent grasslands can considerably contribute to climate change mitigation.

Biofuels – Towards Objectives Of 2030 And Beyond

The European (and global) energy sector is in a process of profound transformation, making it essential for changes to take place that influence energy producers, operators, and regulators, as well as consumers themselves, as they are the ones who interact in the energy market. The RED II Directive changes the paradigm of the use of biomass in the heat and electricity sectors, by introducing sustainability criteria with mandatory minimum greenhouse gas (GHG) emission reductions and by establishing energy efficiency criteria. For the transport sector, the extension of the introduction of renewables to all forms of transport (aviation, maritime, rail and road short and long distance), between 2021-2030, the strengthening of energy efficiency and the strong need to reduce GHG emissions, are central to achieving the national targets for renewables in transport, representing the main structural changes in the European decarbonisation policy in that sector. It is necessary to add that biomass is potentially the only source of renewable energy that makes it possible to obtain negative GHG emission values, considering the entire life cycle including CO2 capture and storage. Hence, this work aims to analyse the relevance of biomass for CHP and in particular, the use of biomass for biofuels that contribute to achieving carbon neutrality in 2050. The following thematic sub-areas are addressed in this work: i) the new environmental criteria for the use of biomass for electricity in the EU in light of now renewable energy directive; ii) current and emerging biofuel production technologies and their respective decarbonization potential; iii) the relevance or not of the development of new infrastructures for distribution renewable fuels, alternatives to the existing ones (biomethane, hydrogen, ethanol); iv) the identification of the necessary measures for biomass in the period 2020-2030

Greenhouse gases emissions from the diet and risk of death and chronic diseases in the EPIC-Spain cohort.

Evidence from the scientific literature shows a significant variation in greenhouse gas (GHG) emissions from the diet, according to the type of food consumed. We aim to analyze the relationship between the daily dietary GHG emissions according to red meat, fruit and vegetables consumption and their relationship with risk of total mortality, and incident risk of chronic diseases. We examined data on the EPIC-Spain prospective study, with a sample of 40621 participants. Dietary GHG emission values were calculated for 57 food items of the EPIC study using mean emission data from a systematic review of 369 published studies. Dietary GHG emissions (kgCO2eq/day), per 2000kcal, were 4.7 times higher in those with high red-meat consumption (>140g/day) than those with low consumption (<70g/day). The average dietary GHG emissions were similar in males and females, but it was significantly higher in youngest people and in those individuals with lower educational level, as well as for northern EPIC centers of Spain. We found a significant association with the risk of mortality comparing the third vs. the first tertile of dietary GHG emissions [hazard ratio (HR) 1.095; 95% confidence interval (CI) 1.007-1.19; trend test 0.037]. Risk of coronary heart disease (HR 1.26; 95% CI 1.08-1.48; trend test 0.003) and risk of type 2 diabetes (HR 1.24; 95% CI 1.11-1.38; trend test 0.002) showed significant association as well. Decreasing red-meat consumption would lead to reduce GHG emissions from diet and would reduce risk of mortality, coronary heart disease and type 2 diabetes.

Integrating life-cycle GHG emissions into a building’s economic evaluation

Buildings contribute to greenhouse gas (GHG) emissions throughout their life—from material extraction and production to building demolition and disposal. Current GHG emission reduction efforts largely focus on building operation, typically ignoring embodied emissions. One of the main barriers affecting the uptake of embodied GHG emissions considerations is the uncertainty related to the economic value of a building with reduced life-cycle GHG emissions. A conceptual approach is presented for integrating the life-cycle GHG emissions of a building into an economic evaluation. A case study detached residential dwelling located in Melbourne, Australia, is used to demonstrate the approach using a range of economic valuation approaches. One approach, using a carbon tax, shows that the effective cost for a single household would be over A$2000 for the first year, rising to almost A$5000 in 10 years. Across the range of evaluation approaches considered, the total cost to the householder is found to be between A$4600 and A$7860. With the embodied GHG emissions accounting for over 66% of the case study’s life-cycle GHG emissions, the majority of the economic liability for the householder relates to the initial construction and ongoing material replacement of the building. Policy relevance This research provides a comprehensive and integrated approach to GHG emissions and economic assessment of residential buildings. This could be used to drive better decisions in building construction and operation through policy improvement, generating greater understanding of the GHG emissions of buildings and the economic value of GHG emissions. By quantifying the total GHG emissions over a building’s life-cycle and examining ecological and financial implications, new data can provide the basis for policy measures that transform the value of GHG emissions in property. The total life-cycle approach to GHG emissions can be used by developers or builders, for example, to demonstrate the potential financial implications of their choices. However, given its current format, there is a need to improve policy measures such as improved carbon tax strategies and the generation of an annual tax for the economic value implications to be realised.

Diet-related greenhouse gas emissions and major food contributors among Japanese adults: comparison of different calculation methods.

To develop a greenhouse gas emissions (GHGE) database for Japanese foods using three different approaches, compare the results of estimated diet-related GHGE and determine major food contributors among Japanese adults. Cross-sectional. Three GHGE databases were developed: (1) a literature-based method including a literature review of life cycle assessment studies of Japanese foods and (2) production- and (3) consumption-based input-output tables (IOT)-applied methods using the Japanese IOT. All databases were linked to the Japanese food composition table and food consumption data. Diet-related GHGE was estimated based on each database and the 4-d dietary record data. Diet-related GHGE were compared in both total and food group level between the databases. Japan. 392 healthy adults aged 20-69 years. The mean diet-related GHGE significantly differed according to the calculation methods: 4145 g CO2-equivalent (CO2-eq)/d by the literature-based method, 4031 g CO2-eq/d by the production-based method and 7392 g CO2-eq/d by the consumption-based IOT-applied methods. It significantly differed in food group level as well. Spearman's correlation coefficients between three methods ranged from 0·82 to 0·86. Irrespective of the methods, the top contributor to GHGE was meat (19·7-28·8 %) followed by fish and seafood (13·8-18·3 %). Although the identified major food contributors to GHGE were comparable between the three methods, the estimated GHGE values significantly differed by calculation methods. This finding suggested that caution must be taken when interpreting the estimated diet-related GHGE values obtained using the different calculation methods of GHGE.

Inventory of main greenhouse gas emissions from energy sector in Palestine.

This paper analyzes the building process of the main greenhouse gas (GHG) emissions (CO2, CH4 and N2O) inventory from the energy sector in Palestine. The paper includes determination tools, i.e., emission factors, to estimate the amounts of national GHG emissions from sub-sectors of energy including energy industries, manufacturing industries and construction, transport and other sectors (households, agriculture and commerce and public services). The results show that the total amount of national GHG emissions from the energy sector in 2016 was 4131 thousand metric tons of CO2-equivalent (TtCO2e), which represented 0.011% of the total global GHG emissions. The average value of GHG emissions per capita from the energy sector was 0.86 tCO2e in Palestine, and its gross domestic product was estimated at 3212$/ton of CO2e. The estimated amounts of CO2, CH4 and N2O emission from the energy sector were 4022, 49 and 60 TtCO2e, respectively. The transport and household sub-sectors dominated the national GHG emissions from the entire energy sector by 58 and 32%, respectively. In general, fuels including diesel, gasoline, wood and charcoal and liquefied petroleum gas made most of the total amount of the national GHG emissions from the energy sector at 50, 18, 18 and 12%, respectively. Finally, the mitigation actions included in the first nationally determined contribution of Palestine and recommendations to help lower the national GHG emissions from the Palestinian energy sector are provided.

Simulating the future energy consumption and greenhouse gas emissions of Turkish cement industry up to 2030 in a global context

Turkey ranked seventh among cement-producing countries in the world, and the country is also one of the extensive producers in the world cement market with cement production nearly 77 million tons. There are more than 50 functional cement plants over 90 Mt/year production capacity in Turkey. In this study, we present the ways of Turkish cement sector emissions fit into the global context, and simulate the impacts of energy efficiency scenarios on Greenhouse Gas (GHG) emitted from energy consumption of Turkish cement production and on total energy demands relevant with the cement production/tons from 2015 to 2030. We employ Long-range Energy Alternatives Planning System (LEAP) software for the simulation of the GHGs emitted from the Turkish cement industry in a global context, and we establish business as usual (BAU) and five alternative energy efficiency scenarios for this study. We suggest six possible mitigation strategy recommendations to reduce CO2 emissions in cement production. Among them, three of them are related to policy and strategy applying, such as increasing awareness, applying different strategies, and improving the governmental policies; and another three of them are directly linked to technological mitigation applications as improving the technology and materials, fuel and energy saving, and CO2 capture and disposal. For 2030; we simulate that more than 15 Mtoe energy consumption will be the main reason for more than 53 million tons of CO2-e emissions per year. The low GHG emissions value is found by applying the energy efficiency 3% (ENE3) scenario where the emission trend starts at 21.12 million tons of CO2-e per year in 2014 and ends up 33.2 million tons of CO2-e per year in 2030.

INFLUENCE OF THE MOTOR VEHICLE PARKING STRUCTURE BY FUEL TYPE AND ECOLOGICAL CLASS ON GREENHOUSE GAS EMISSIONS

Introduction. The results of estimating greenhouse gas (GHG) emissions by a vehicle fleet are described, using the COPERT-4 methodology and the baseline data contained in 1-BDD form, concerning the number of vehicle fleets in Russia and three options for detailing the fleet structure by the fuel type and ecological class in different organizations. Such data is not provided in the forms of state statistical reports and is generated by the researchers.Materials and methods. Various approaches to the structuring of the park by the fuel type and the ecological class give a slight variation in the values of GHG emissions’ gross (up to 4.1%), which confirms the correctness and approaches’ validity to the generation of the required initial data. The authors introduce the concept of total conditional transport work in order to adjust the values of the average annual mileage to the generation of the required initial data in the calculation of GHG emissions gross by the fleet of cars. Moreover, the value of total conditional transport work for all considered GHG variants should be the same.Results. As a result, if such adjustment is not made, the difference between the obtained calculated values of GHG emissions gross by the vehicle fleet for different authors would reach 25-30%. Discussion and conclusions. The reliability of the GHG emission values estimation is confirmed by the indirect method or by comparing the data of statistical reporting on the volumes of motor fuel consumption depending on different consumers in the fuel and energy balance, and on the fuel consumption values, and on the greenhouse gas emissions gross by the COPERT-4 method.