High Greenhouse Gas Emissions Research Articles

Ready meals, especially those that are animal-based and cooked in an oven, have lower nutritional quality and higher greenhouse gas emissions and are more expensive than equivalent home-cooked meals.

To examine whether ready meals and equivalent home-cooked meals differ in nutritional quality indicators, greenhouse gas emissions (GHGE) and cost. We performed a cross-sectional analysis of meal data from the National Diet and Nutrition Survey (NDNS) nutrient databank (2018/19). Additional data on nutrient composition, cost and cooking-related GHGE were calculated and compared between fifty-four ready meals and equivalent home-cooked meals. The UK. Not applicable. Ready meals, overall and those that were animal-based, had significantly higher levels of free sugar compared with equivalent home-cooked meals (P < 0·0001 and P < 0·0004, respectively). Animal-based ready meals had significantly higher levels of GHGE (P < 0·001), whereas the cost of ready meals, overall, was significantly higher (P < 0·001), compared with equivalent home-cooked meals. Animal-based meals, whether ready meals or equivalent homemade meals, had significantly higher levels of protein (P < 0·0001), contained significantly more kilocalories (P = 0·001), had significantly higher levels of GHGE (P < 0·0001) and were significantly more expensive (P < 0·0001), compared with plant-based meals. Overall, plant-based meals home-cooked on the gas or electric stove had the lowest GHGE and cost, whereas animal-based oven-cooked ready meals had the highest levels of GHGE and were most expensive. Ready meals have lower nutritional quality and higher GHGE and are more expensive than equivalent home-cooked meals, especially those meals that are animal-based and prepared in an oven.

Mapping the strength of agro-ecological lightweight concrete containing oil palm by-product using artificial intelligence techniques

The critical challenge for the cement production industry is the high emission of greenhouse gases. For the sustainability in a cycling economy context civil and environmental engineers should reconsider future generations and should redesign and manufacturing in a safe and eco-friendly alternative. Previous experimental studies have shown, that using oil palm by-product in the production of sustainable lightweight structural concrete, (SLSC) presents good life cycle, land-use efficiency and economic benefits. In this work a formula-based model is proposed to evaluate the strength of SLSC, knowledge-aided modeling based on machine learning methods (e. g., for further development, Multivariate Adaptive Regression Splines (MARS), Gene Expression Programming (GEP), M5P Model Tree (M5P) and Extreme Learning Machine (ELM)) were selected. A comprehensive and reliable experimental record comprising of 449 data of SLSC containing oil palm by-product was utilized to formulate strength predictive models. The proposed models were investigated, in terms of assessment criteria, error measurements, and performance evaluation. The efficiency of the MARS model was shown by comparing its performance with GEP, M5P and ELM. As well as Monte-Carlo simulation approach was conducted to verify the proposed models. Evaluation of the relative importance of effective variables presented that the gravel (11.84%), oil palm waste aggregate (11.38%) and water to binder ratio (11.15%) were the most influential features in the strength prediction of the SLSC. Also, a parametric study is developed to provide robustness of the proposed predictive model. Results of the modeling provide a new understanding of the provision of an auto-estimated strength evaluation of SLSC incorporating oil palm by-product with superiority promotion of knowledge-aided modeling mechanism.

Impact of renewable fuels on heavy-duty engine performance and emissions

The transport sector faces two critical issues: a limited supply of fossil fuels and high greenhouse gas (GHG) emissions. Additionally, the demand for freight transport is steadily increasing, ultimately leading to higher GHG emissions. Since these emissions promote climate change, reducing the GHG emissions from the transport sector is necessary. Renewable drop-in fuels can play an essential role in this regard as those are CO2 neutral. Since these fuels come from so-called renewable sources, this represents a way to reduce carbon dioxide emissions from the current vehicle fleet to meet the EU’s Green Deal goals to become climate neutral by 2050. The drop-in fuels from renewable sources and later the purely renewable fuels serve as a bridging technology in this context.With this in mind, experiments were conducted with a Heavy-Duty Single Cylinder Engine (HD-SCE). The effects of four different renewable fuels or fuel blends – 93% RF/7% UCOME, 60% B0-Diesel/40% RF blend, 70% Diesel/30% Octanol blend and 100% Octanol – on engine performance and raw emissions were studied in comparison to fossil Diesel fuel. The investigations were conducted at three different load points — Rated Power (RP), best Brake Thermal Efficiency (BTE) and Cruise Point, covering all the relevant load points for HD engines. For all load points, the use of renewable fuels resulted in lower carbon dioxide (CO2), hydrocarbon (HC), carbon monoxide (CO) and FSN compared to fossil Diesel due to the fuel-borne oxygen and the lower C/H ratio of these alternative fuels. The blend of 60% B0-Diesel-40% RF shows the highest efficiency due to the paraffinic fuel structure, the fuel-borne oxygen, the higher calorific value, and the high cetane number. 100% Octanol resulted in a reduction in FSN by a factor of 3. All renewable fuels show a GHG emission reduction potential of around 2.5% to 5.5% in the Tank-to-Wheel (TtW) analysis.

N2 solar activation: ammonia as a hydrogen vector for energy storage.

From the plethora of energy-intensive synthetic processes, ammonia production has a particularly negative impact due to the high-energy consumption caused by the Haber-Bosch process and the high greenhouse gas (GHG) emission rate. Thus, new and effective ways to activate N2 and synthesise NH3 are crucial to reduce production costs and the anthropogenic footprint derived from the current harsh reaction conditions. In this study, two-dimensional materials have been employed in the photoactivation of nitrogen in an aqueous medium; MI(II)MII(III) (with MI = Cu or CuNi, and MII = Cr or Al) layered double hydroxides have been synthesised using a simple, economical and scalable co-precipitation/filtration method. The structural and functional properties were systematically investigated by XRD, SEM, TPR and BET; the results indicate that the prepared LDHs were successfully synthesised, possess high surface areas and, in the case of CuAl LDH, the material showed a nanoplate-like structure, thus confirming the two-dimensional nature of this class of catalyst. The N2 fixation performances were evaluated using a scalable, cost-effective and low-energy-consuming setup; from the catalytic tests, a NH3 production rate of 99 μmol g-1 h-1 was observed, demonstrating LDHs' high potential and the scalability of the overall process.

Sustainable ammonia synthesis through electrochemical dinitrogen activation using an Ag2VO2PO4 catalyst.

Ammonia (NH3) is the second most produced chemical commodity with a worldwide production of 235 million tonnes in 2019, by virtue of its importance in fertilizer production, energy storage and transportation, and in the production of industrial chemicals. The most frequent method of NH3 production in large plants (1000 to 1500 t day-1) is the Haber-Bosch process, which has drawbacks of high greenhouse gas emissions (2.16 tonnes CO2 per tonne of NH3) and high energy consumption (over 30 GJ per tonne of NH3) due to high pressure and temperature conditions. For sustainable NH3 production, we require alternative green routes, wherein the electrochemical route holds huge potential due to reduced energy consumption and plant costs, higher selectivity, lower temperatures and pressures, and small to medium scale utilization of NH3. However, there are a number of challenges faced during the same viz. low production rates due to difficult N2 activation and reduced faradaic efficiency due to competing side reactions in aqueous electrolytes. Therefore, the most crucial aspect of electrochemical ammonia production technology is the design of an electrocatalyst which could activate the strong NN triple bond and effectively suppress the competing hydrogen evolution reaction (HER). In addition, the true NH3 yield estimation is of major concern due to the presence of possible N-contaminants, which may possibly lead to false estimation or overestimation of NH3. In this context, we have synthesized an Ag2VO2PO4 electrocatalyst with rice-grain like morphology via an energy efficient and less time consuming sonochemical method to carry out low temperature NH3 synthesis in an alkaline electrolyte. The choice of Ag metal and an alkaline environment effectually suppresses the HER and the bimetallic phosphate materials (Ag and V metals) induce high activity during nitrogen reduction, while rigorous analysis for tracing/elimination of N-labile and reducible species is considered for true NH3 production and assessment.

Modelling ecological niches of Sclerocarya birrea subspecies in Tanzania under the current and future climates

The information on ecological niches of the Marula tree, Sclerocarya birrea (A. Rich.) Horchst. subspecies are needed for sustainable management of this tree, considering its nutritional, economic, and ecological benefits. However, despite Tanzania being regarded as a global genetic center of diversity of S. birrea, information on the subspecies ecological niches is lacking. We aimed to model ecological niches of S. birrea subspecies in Tanzania under the current and future climates. Ecological niches under the current climate were modelled by using ecological niche models in MaxEnt using climatic, edaphic, and topographical variables, and subspecies occurrence data. The Hadley Climate Center and National Center for Atmospheric Research's Earth System Models were used to predict ecological niches under the medium and high greenhouse gases emission scenarios for the years 2050 and 2080. Area under the curves (AUCs) were used to assess the accuracy of the models. The results show that the models were robust, with AUCs of 0.85–0.95. Annual and seasonal precipitation, elevation, and soil cation exchange capacity are the key environmental factors that define the ecological niches of the S. birrea subspecies. Ecological niches of subsp. caffra, multifoliata, and birrea are currently found in 30, 22, and 21 regions, and occupy 184 814 km2, 139 918 km2, and 28 446 km2 of Tanzania's land area respectively, which will contract by 0.4–44% due to climate change. Currently, 31–51% of ecological niches are under Tanzania’s protected areas network. The findings are important in guiding the development of conservation and domestication strategies for the S. birrea subspecies in Tanzania.

Statistical-machine-learning-based intelligent relaxation for set-covering location models to identify locations of charging stations for electric vehicles

Europe strengthens its policies on climate change, green transition, and sustainable energy by addressing the high greenhouse-gas emissions in the transportation sector. Europe aims to reduce such emissions and reach a state of carbon neutrality by 2030 and 2050, respectively. This is feasible only if electric vehicles dominate the transportation sector. Paving the way for electric vehicle deployment on roads is subject to the provision of electric-vehicle-charging stations on the roads such that sufficiently good driving experience without any obstacles can be achieved. To address this timely societal challenge, we proposed a novel methodology by using the well-known facility-location-allocation methodology named set-covering location models with statistical machine learning and developed it for the problem settings of identifying electric-vehicle-charging station locations. Statistical machine learning was employed in the proposed model to more precisely identify and determine feasible coverage sets. We demonstrated the efficiency of the proposed model for the Capital Region of Denmark, where the green transition is part of the political agenda and is of severe societal concern, by using the newly collected main road transportation dataset.

A new power swing detection method in power systems with large‐scale wind farms based on modified empirical‐mode decomposition method

AbstractHigh energy consumption around the world and concerns over climate change and high greenhouse gas emissions have led to a significant increase in using renewable energy resources, particularly wind power plants. In spite of using small wind farms in distribution networks as distributed generation, the interest in employing large‐scale wind farms in transmission levels has grown significantly in recent years. The presence of large‐scale wind farms with a synchronous generator to supply the energy demand can affect the power swing parameters. These effects are in a way that can mislead power swing detection methods and cause undesirable tripping of transmission line due to mal‐operation of distance relay against power swing . Therefore, in this paper, a method has been presented based on modified empirical mode decomposition (EMD) method to differentiate fault from power swing in the networks connected to the large‐scale wind farms. The results prove the efficiency of the presented method in detecting the power swing in large‐scale wind farm networks. Finally, a comparison is conducted between the proposed method and similar methods which proves the efficiency and superiority of the proposed method in terms of noise tolerance, detection fault detection speed, and multi‐mode power swing detection compared to the current methods.

Conversion of food waste to renewable energy: A techno-economic and environmental assessment

Increasing quantities of food waste have become a concern due to high disposal costs in landfills and high greenhouse gas emissions. With this increase in food waste generation, there is also an increasing demand for renewable natural gas to supplement traditional fossil fuel combustion and offset the impacts of climate change. Collecting food waste from landfills and turning it into renewable natural gas using anaerobic digestion could be a win-win option for both food waste disposal and renewable energy production. While some literature exists on the energy potential, economic feasibility, and environmental benefit of food waste disposal via anaerobic digestion, no existing study simultaneously evaluates the energy, economic and environmental effect of food waste to renewable energy via anaerobic digestion, especially on a plant and city scale. This study is focused on the techno-economic and environmental assessment of food waste to energy via anaerobic digestion in order to fill this gap. Four anaerobic digestion pathways are considered in this study: flare, pipeline natural gas, combined heat and power, and combined cycle for efficient power generation. Using a city of 1 M people the results show that renewable natural gas from food waste could supply the natural gas usage for 1.9% of residential use, 2.7% of commercial use, 1.1% of industrial use, 167.5% of the compressed natural gas vehicle fleet, 0.7% of electric power generation, or 2.5% of industrial high-temperature heating processes. All pathways except pipeline natural gas will have a positive net present value in the baseline scenario, and the pipeline natural gas pathway will become economically viable with a net present value of 31 USD/t of food waste with renewable energy credits. Lastly, all of the pathways achieve negative greenhouse gas emissions, which indicates that anaerobic digestion is a more environmentally friendly method for the handling of food waste than landfills.

Extreme Coastal Water Levels Evolution at Dakar (Senegal, West Africa)

Increasingly, it is reported that the coastline of the Dakar region is affected by coastal flooding due to extreme water levels during wave events. Here, we quantify the extreme coastal water levels as well as the different factors contributing to coastal flooding during the period 1994–2015. Severe water levels reach values of 1.78 m and increase by 8.4 mm/year. The time spent above this threshold has already increased by 1.7 over the study period and will increase by 2100 to 8 times with 0.4 m mean sea level rise and up to 20 times with 0.8 m in the IPCC low and high greenhouse gas emission scenarios, respectively. Tide is the main contributor to the extremes when combined with large wave runup, due to wave breaking which contributes to 38% of the increase in extreme events while sea level rises to 44%. Our results show that because of its prominent location, Dakar region is affected by waves coming from the Northern and Southern Hemispheres with contrasted evolutions: wave runup events increase faster (7 mm/year) during austral winter due to a maximum of the South Atlantic storm activity, and have a decreasing trend (−3 mm/year) during boreal winter (December, January, February) driven by the evolution of corresponding climate modes.

Performance and Emission Analysis of Corn Oil and Rice Bran Oil using Ethanol, Methanal and Sodium Hydroxide Additives

The fuel consumption rate has been increased in our world compared to older days. Most of the fuels which we use are fossil fuel which has high emissions of greenhouse gases which leads to pollution and global warming. Fuels are getting higher price range nowadays. So, we are trying to find a better alternative fuel which will be cost efficient and less harmful to the planet. In this study we try to solve the problem by experimenting and evaluating the mixture of oils which may reduce emissions of harmful gases. In this project we are using corn oil, rice bran oil with additives and mixing them with conventional fuel i.e., diesel to convert the collected oils into a biodiesel. This process is commonly known as transesterification. The biodiesels are mixed in three different forms like B30, B40, and B50, in which B30 contains 70% of diesel and 15% of corn oil and 15% of rice bran oil. B40 contains 60% of diesel, 20% of corn oil and 20% of rice bran oil. B50 contains 50% of diesel, 25% of corn oil and 25% of rice bran oil. We are mixing these oils with diesel and other additives in three different ratios in-order to get the maximum performance and lowest emission from a diesel engine. These samples are used as an alternative to conventional diesel in a diesel engine and the engine’s performance was evaluated. The performance of the engine is evaluated by parameters which include brake thermal efficiency, volumetric efficiency, specific fuel consumption and torque. The emission parameters are also tested which includes the emission level of CO, CO2, NOX, SOX and HC. These tests are done under different load conditions varying form no load up to 10kg. The results from the three samples (B30, B40 and B50) are compared to the conventional diesel which is being used in most conditions.

Nutrient-sensitive approach for sustainability assessment of Australian macronutrient dietary recommendations

BackgroundDietary guidelines that form the basis for food and nutrition policies in most countries are focused mainly on the social dimensions of health. Efforts are needed to incorporate environmental and economic sustainability. As the dietary guidelines are formulated based on nutrition principles, understanding the sustainability of dietary guidelines in relation to nutrients could support the better incorporation of environmental and economic sustainability aspects into dietary guidelines. ObjectivesThis study examines and demonstrates the potential of integrating an input–output analysis with nutritional geometry to assess the sustainability of the Australian macronutrient dietary guidelines (AMDR) relating to macronutrients. MethodsWe used daily dietary intake data of 5345 Australian adults from the most recent Australian Nutrient and Physical Activity Survey 2011–2012 and an input–output database for the Australian economy to quantify the environmental and economic impacts associated with dietary intake. Then, we examined the associations between environmental and economic impacts and dietary macronutrient composition using a multidimensional nutritional geometry representation. Thereafter, we assessed the sustainability of the AMDR regarding its alignment with key environmental and economic outcomes. ResultsWe found that diets adhering to the AMDR were associated with moderately high greenhouse gas emissions, water use, cost of dietary energy, and the contribution to wages and salaries of Australians. However, only about 20.42% of respondents adhered to the AMDR. Furthermore, high-plant protein diets adhering to the lower limit of recommended protein intake in the AMDR were associated with low environmental impacts and high incomes. ConclusionsWe conclude that encouraging consumers to adhere to the lower limit of the recommended intake of proteins and meeting the protein requirement through protein-dense plant sources could improve dietary environmental and economic sustainability in Australia. Our findings provide a means of understanding the sustainability of dietary recommendations concerning macronutrients for any country where input–output databases are available.

Greenhouse gas emissions in the food system: Current and alternative dietary scenarios

BACKGROUND: There is a growing interest in diets due to the high contribution to greenhouse gas emissions (GHGE). OBJECTIVE: The study was aimed to estimate the impact on GHGE of replacing the current diet with eight alternative diets, which would be associated with GHGE, to contribute to the discussion of how dietary changes affect the GHGE. METHODS: The latest National Nutrition and Health Survey was utilized to determine the nutrient composition of Turkey’s current diet, with eight dietary scenarios designed to meet the National Dietary Guidelines. RESULTS: The current diet had the highest GHGE with 3254.50 g CO2eq/person/day with beef, lamb, and cheese products accounting for the majority of emissions (18.61%, 17.15%, and 10.89%, respectively). The Model diet had a GHGE of 2994.18 g CO2eq/person/day, whereas vegetarian diets had the lowest (lacto-ovo vegetarian diet with 1944.95 g CO2eq/person/day and vegan diet with 1166.80 g CO2eq/person/day). Low energy efficiencies were associated with high diet-related GHGE levels. CONCLUSION: When evaluating future dietary guidelines for a sustainable diet, our study highlighted the need of integrating both health and environmental aspects. The present study found that dietary changes would significantly contribute to lowering GHGE. These findings will be beneficial in informing Turkey’s nutrition, agriculture, and public policymakers.

Water-energy-greenhouse gas nexus of a novel high-rate activated sludge-two-stage vertical up-flow constructed wetland system for low-carbon wastewater treatment

Municipal wastewater treatment which is associated with high energy consumption and excessive greenhouse gas (GHG) emissions, has been facing severe challenges toward carbon emissions. In this study, a high-rate activated sludge-two-stage vertical up-flow constructed wetland (HRAS-TVUCW) system was developed to reduce carbon emissions during municipal wastewater treatment. Through carbon management, optimized mass and energy flows were achieved, resulting in high treatment efficiency and low operational energy consumption. The carbon emission of the HRAS-TVUCW system (i.e., 0.21 kg carbon dioxide equivalent/m3 wastewater) was 4.1-folds lower than that of the conventional anaerobic/anoxic/aerobic (A2O) process. Meanwhile, the recovered energy from the HRAS-TVUCW system increased its contribution to carbon neutrality to 40.2%, 4.6-folds higher than that of the A2O process. Results of functional microbial community analysis at the genus level revealed that the controlled dissolved oxygen allocation led to distinctive microbial communities in each unit of HRAS-TVUCW system, which facilitated denitrification efficiency increase and carbon emissions reduction. Overall, the HRAS-TVUCW system could be considered as a cost-effective and sustainable low-carbon technology for municipal wastewater treatment.

Greenhouse Gas Emission Scenarios and Vehicle Engine Performance in a Main Urban Road in Northwestern Mexico

Transport is one of the sectors with the highest greenhouse gas emissions (GHG) that is imperative to reduce in order to decrease global warming. Although modern vehicles and arterial roads have adopted technological and structural improvements to enhance fuel use efficiency, the emission of greenhouse gases (GHG) into the atmosphere by the transport sector has been increasing in different Mexican cities. In generating mitigation strategies, modeling scenarios of decreased equivalent carbon dioxide, CO2e emissions, may be useful as an evaluation tool. In this study, the aim was to model a trend scenario and a scenario, including improvements with a projection to the year 2039 on one of the main urban roads of the border city of Mexicali, Mexico. In order to create a dynamic emission model of GHG, including emission factors, the main variables for the simulation were vehicle volume, travels, motor performance, and fuel consumption. These last two parameters were the most important for vehicular emissions estimations and for the projection of them in this period. As a result of the projections, CO2e was observed to increase in a trend scenario, while modeled improvement actions resulted in emission reductions of up to 5%. The model showed that the key variable to achieve this reduction is vehicle engine performance (Pf), whose increase factor was 1.1% per year. Replicating this methodology to evaluate and mitigate the GHG emissions on different city roads or in other cities, can be a contribution for the urban designers, authorities, and involved institutions.

How do rice consumers trade off sustainability and health labels? Evidence from Vietnam

IntroductionStrategies for increasing rice production in the Asian Mega-Deltas have led to environmental degradation, resource overexploitation, and high greenhouse gas emissions. Certified sustainable production labels can support governments in their efforts to render rice value chains more sustainable by simultaneously fostering planetary and human health. Little is known, however, about how consumers trade off sustainability and health attributes in staple crops such as rice. This study aims to fill this knowledge gap by investigating Vietnamese consumers' preferences and willingness to pay for rice characterized by multi-attribute sustainability and health certification labels.MethodsWe collected empirical data from 410 supermarket consumers in Can Tho, Vietnam using a choice experiment survey. The results were analyzed using a mixed logit model to determine consumers' preferences for sustainability and health traits in rice. Four price levels were used to elicit willingness-to-pay for four certification labels: low-emission, eco-friendly, ethically produced, and low glycemic index rice. By separating the components that make up the concept of sustainability and by including a label related to personal health and diet preferences, we are able to gain an understanding of the value consumers place on attributes that benefit the common good vs. attributes that benefit the individual consumer.ResultsThe results showed that consumers were willing to pay a price premium for all certification labels, with the highest marginal utility assigned to low glycemic index rice.DiscussionCertification of eco-friendly and ethical production generated similar utility levels, while low-emission rice was valued lower, although it still fetched a significant price premium compared to the status-quo option of rice with no certifications. The results of this study can help policymakers and value chain actors develop rice value chains that integrate sustainable production practices as well as foster the nutrition and health of rice consumers.

Solutions to neutralize greenhouse gas emissions of the rice value chain — A case study in China

Rice contributes significantly to greenhouse gas (GHG) emissions from the food system. Previous studies mainly focused on emission reduction methods within the rice farming system rather than examining systematic solutions along the rice value chain. Organic and rice-fish co-culture rice are considered promising solutions for reducing environmental burdens. This study compared the GHG emissions of organic, rice-fish co-culture, and conventional rice value chains (including cultivation, processing, transportation, cooking, and waste disposal) with a cradle-to-grave system boundary and a new perspective from consumer dietary habits changes. The results indicated that organic rice had the highest carbon input, output, and net GHG emissions in the farming system, with 9.277, 9.658, and 0.380 kg CO2-eq kg−1 white rice, respectively. However, the net GHG emissions from rice-fish co-culture and conventional rice farming systems were −1.682 and −0.393 kg CO2-eq kg−1 white rice, respectively. Methane (CH4) contributed more than 60 % of the total GHG emissions of the three rice farming systems. Post-harvest systems, including processing, waste disposal, and transportation, contributed little to the GHG emissions of the three rice value chains. The cooking system was a relatively primary source of GHG emissions due to electricity consumption. Concerning the whole rice value chain, though higher consumption sustainability levels were assumed for the organic rice and rice-fish co-culture value chains, they were still carbon sources with GHG emissions of 0.770 and 0.147 kg CO2-eq kg−1 white rice mainly from the farming system, while the conventional rice value chain was a carbon sink (−1.012 CO2-eq kg−1). The results are similar to the functional unit of the capital diet. In this case study, organic rice had higher GHG emissions than rice-fish co-culture and conventional rice along the rice value chain, mainly from the farming system due to higher organic material inputs. Future studies should focus on reducing CH4 emissions from organic rice cultivation through sustainable soil and water management.

Optimization of green open space in Ambon City

The increase in population in Ambon City has resulted in increased space requirements and impacts the conversion of green areas into built-up areas. This indirectly impacts the decline in environmental quality, marked by an increase in the concentration of greenhouse gas (GHG) emissions in the air. The Green Open Space (GOS) arrangement program involves efforts to reduce GHG emissions in Ambon City. However, in reality, the allocation of space to develop green open space in Ambon City still does not meet the 30% standard or is still lacking 737.8 ha. This study aims to obtain information about the arrangement of green open spaces in Ambon City. The interview method was conducted in a structured manner with a questionnaire. SWOT analysis was used to analyze internal factors and external factors. The results showed that the critical strategies in optimizing Ambon City's green open space were to improve the quality of green open space by planting plants that have high GHG emissions absorption potentials, such as Samanea saman, Pterocarpus indicus, and Acacia mangium. Conduct harmonization and socialization with other institutions such as the Ambon City Satpol PP and green open space users to increase the supervision of green open space. Using the basic green coefficient as the primary condition for obtaining a Building Permit (IMB). The present study recommended that future research on green open spaces in Ambon City should focus on other influencing elements including geography, climate, socio-culture, and so on.

Estimating the use of materials and their GHG emissions in the German building sector

The construction and building sector is one of the largest emitters of greenhouse gases. In this study, we calculated the material used in shell construction in the German building sector from 2012 to 2020 using material flow analysis. Subsequently, the annual greenhouse gas emissions in the German building sector were simulated using the environmental product declarations from the Ökobaudat database and the modeled materials. We can show that biogenic materials account for an ever-larger share of value creation and are growing disproportionately. We can also show that by increasing biogenic materials, construction is becoming lighter and more efficient, and greenhouse gas emissions of shell construction are reduced during this period. In summary, the building sector in Germany still has very high greenhouse gas emissions of around 26 million metric tons of CO 2 eq. Still, it is in a better overall position than at the beginning of the study period, thanks to the efficient use of available resources. • Material consumption in German building construction has increased in recent years. • In terms of mass, the strongest increase took place in mineral building materials. • The strongest percentage increase was in biogenic building materials. • Emissions from the building construction sector have not changed significantly.

Provision of High-Quality Molasses Blocks to Improve Productivity and Address Greenhouse Gas Emissions from Smallholder Cattle and Buffalo: Studies from Lao PDR.

Large ruminant production in developing countries is inefficient with low growth rates and likely high greenhouse gas emissions per unit of meat or milk produced. Trials conducted in Lao PDR from 2017 to 2020, studied ad libitum supplementation for 12 weeks with 20 kg high-quality molasses nutrient blocks (Four Seasons Pty Ltd., Brisbane, Australia), that were either non-medicated; fenbendazole-medicated (Panacur100®, Coopers Australia, 5 g/kg); triclabendazole-medicated (Fasinex®, Novartis Australia, 5 g/kg or 10 g/kg, respectively); or formulated with urea (8% or 10% urea, respectively). Average daily gains were determined for access to all molasses blocks and compared with access to control blocks, no supplementation, or previously determined free-grazing baseline average daily gains (55-84 g in cattle; 92-106 g in buffalo). Productivity was significantly improved following access to all molasses blocks. Average daily gains following access to 8% urea and control blocks were calculated for three age cohorts of cattle: young calves &lt;8 m (238-298 g), growing cattle (143-214 g) and lactating cows (179-191 g). Modelling using IPCC Inventory software model V 2.69 of published data demonstrated a conservative net abatement of 350 kg CO2e was achievable over a 200-day feeding period. An additional trial of Emissions control blocks (n = 200) distributed to farmers (n = 60) and two educational institutions were conducted. Consumption rates (156 g/day) and farmer and institutional acceptance of these blocks were similar to our published findings with other molasses blocks, confirming all formulations of blocks improved animal productivity and body condition score, with healthier animals that were easier to manage. Modelling of changes in greenhouse gas emissions intensity identified an abatement of 470 kg CO2e per Emissions control blocks consumed, delivering a total project emissions abatement of 94 t CO2e. Provision of high-quality molasses blocks significantly improved smallholder large ruminant productivity and addition of greenhouse gas reducing agents is likely to achieve impressive abatement of greenhouse gas emissions due to improved efficiency of rumen fermentation and productivity.