Potential Greenhouse Gas Emissions Research Articles

Potential contribution of water management practices under intensive crop production to climate-change-associated global warming

Optimizing water management practices to mitigate greenhouse gas (GHG) emissions in agroecosystems is of increasing interest under climate change. However, previous studies have focused more on paddy fields, little is known as to how water table management in subsurface drained fields or how irrigation practices in humid areas might affect the global warming potential (GWP). Drawing upon experimental data from four intensive crop production sites in Eastern Canada operating under different water management practices, the DeNitrification-DeComposition (DNDC) biogeochemical model was used to assess potential GHG emissions under twelve different sets of General Circulation Models coupled with Regional Climate Models (GCM-RCM) climate projections (2046–2075). Simulations showed that water table control/sub-irrigation and sprinkler irrigation might decrease GWP by allowing greater soil organic carbon (SOC) sequestration, despite increased N2O and CO2 emissions than non-irrigated systems. While drip irrigation marginally increased the SOC sequestration, GWP still increased because the C gains from the residues generated by the greater crop biomass were offset by increased CO2 and N2O emissions. Compared with surface drip irrigation, subsurface drip irrigation reduced the GWP by reducing N2O emissions, as well as increasing crop yield and SOC stock. Although greater crop biomass was expected to return to soil under projected climate change, simulations showed a consistent increase in the GWP of tomato cropping system alone under climate change.

The carbon footprint of the perioperative transurethral resection of bladder tumour pathway.

To evaluate the carbon footprint of the perioperative transurethral resection of bladder tumour (TURBT) pathway from decision to treat to postoperative discharge, and model potential greenhouse gas (GHG) emissions reduction strategies. This process-based attributional cradle-to-grave life-cycle assessment (LCA) of GHG emissions modelled the perioperative TURBT pathway at a hospital in Southwest England. We included travel, energy and water use, all reusable and consumable items, and laundry and equipment sterilisation. Resource use for 30 patients undergoing surgery was recorded to understand average GHG emissions and the inter-case variability. Sensitivity analysis was performed for manufacturing location, pharmaceutical manufacturing carbon-intensity, and theatre list utilisation. The median (interquartile range) perioperative TURBT carbon footprint was 131.8 (119.8-153.6) kg of carbon dioxide equivalent. Major pathway categories contributing to GHG emissions were surgical equipment (22.2%), travel (18.6%), gas and electricity (13.3%), and anaesthesia/drugs and associated adjuncts (27.0%), primarily due to consumable items and processes. Readily modifiable GHG emissions hotspots included patient travel for preoperative assessment, glove use, catheter use, irrigation delivery and extraction, and mitomycin C disposal. GHG emissions were higher for those admitted as inpatients after surgery. This cradle-to-grave LCA found multiple modifiable GHG emissions hotspots. Key mitigation themes include minimising avoidable patient travel, rationalising equipment use, optimally filling operating theatre lists, and safely avoiding postoperative catheterisation and hospital admission where possible. A crucial next step is to design and deliver an implementation strategy for the environmentally sustainable changes demonstrated herein.

Greenhouse gas emission potential of tropical coastal sediments in densely urbanized area inferred from metabarcoding microbial community data

Although benthic microbial community offers crucial insights into ecosystem services, they are underestimated for coastal sediment monitoring. Sepetiba Bay (SB) in Rio de Janeiro, Brazil, holds long-term metal pollution. Currently, SB pollution is majorly driven by domestic effluents discharge. Here, functional prediction analysis inferred from 16S rRNA gene metabarcoding data reveals the energy metabolism profiles of benthic microbial assemblages along the metal pollution gradient. Methanogenesis, denitrification, and N2 fixation emerge as dominant pathways in the eutrophic/polluted internal sector (Spearman; p < 0.05). These metabolisms act in the natural attenuation of sedimentary pollutants. The methane (CH4) emission (mcr genes) potential was found more abundant in the internal sector, while the external sector exhibited higher CH4 consumption (pmo + mmo genes) potential. Methanofastidiosales and Exiguobacterium, possibly involved in CH4 emission and associated with CH4 consumers respectively, are the main taxa detected in SB. Furthermore, SB exhibits higher nitrous oxide (N2O) emission potential since the norB/C gene proportions surpass nosZ up to 4 times. Blastopirellula was identified as the main responsible for N2O emissions. This study reveals fundamental contributions of the prokaryotic community to functions involved in greenhouse gas emissions, unveiling their possible use as sentinels for ecosystem monitoring.

Early Detection of Pipeline Natural Gas Leakage from Hyperspectral Imaging by Vegetation Indicators and Deep Neural Networks.

The timely detection of underground natural gas (NG) leaks in pipeline transmission systems presents a promising opportunity for reducing the potential greenhouse gas (GHG) emission. However, existing techniques face notable limitations for prompt detection. This study explores the utility of Vegetation Indicators (VIs) to reflect vegetation health deterioration, thereby representing leak-induced stress. Despite the acknowledged potential of VIs, their sensitivity and separability remain understudied. In this study, we employed ground vegetation as biosensors for detecting methane emissions from underground pipelines. Hyperspectral imaging from vegetation was collected weekly at both plant and leaf scales over two months to facilitate stress detection using VIs and Deep Neural Networks (DNNs). Our findings revealed that plant pigment-related VIs, modified chlorophyll absorption reflectance index (MCARI), exhibit commendable sensitivity but limited separability in discerning stressed grasses. A NG-specialized VI, the optimized soil-adjusted vegetation index (OSAVI), demonstrates higher sensitivity and separability in early detection of methane leaks. Notably, the OSAVI proved capable of discriminating vegetation stress 21 days after methane exposure initiation. DNNs identified the methane leaks following a 3-week methane treatment with an accuracy of 98.2%. DNN results indicated an increase in visible (VIS) and a decrease in near-infrared (NIR) in spectra due to methane exposure.

Microplastics increase the microbial functional potential of greenhouse gas emissions and water pollution in a freshwater lake: A metagenomic study

Aquatic ecosystems are being increasingly polluted by microplastics (MPs), which calls for an understanding of how MPs affect microbially driven biogenic element cycling in water environments. A 28-day incubation experiment was conducted using freshwater lake water added with three polymer types of MPs (i.e., polyethylene, polypropylene, polystyrene) separately or in combination at a concentration of 1 items/L. The effects of various MPs on microbial communities and functional genes related to carbon, nitrogen, phosphorus, and sulfur cycling were analyzed using metagenomics. Results showed that Sphingomonas and Novosphingobium, which were indicator taxa (genus level) in the polyethylene treatment group, made the largest functional contribution to biogenic element cycling. Following the addition of MPs, the relative abundances of genes related to methane oxidation (e.g., hdrD, frhB, accAB) and denitrification (napABC, nirK, norB) increased. These changes were accompanied by increased relative abundances of genes involved in organic phosphorus mineralization (e.g., phoAD) and sulfate reduction (cysHIJ), as well as decreased relative abundances of genes involved in phosphate transport (phnCDE) and the SOX system. Findings of this study underscore that MPs, especially polyethylene, increase the potential of greenhouse gas emissions (CO2, N2O) and water pollution (PO43−, H2S) in freshwater lakes at the functional gene level.

Comparison of Greenhouse Gas Emission Assessments of Solar and Energy Efficiency Improvements at Small Water Resource Recovery Facilities

Small water resource recovery facilities (WRRFs) account for the majority of centralized systems in the world and have higher energy intensities than large facilities. This study compares potential greenhouse gas emission reductions based on on-site solar energy and energy efficiency (E2) improvements made at small WRRFs. Case study data from 31 existing small WRRFs in Nebraska were collected and included 35 site-specific energy efficiency (E2) recommendations and on-site solar renewable energy systems integrated at three facilities, and the data were used to compare the benefits of on-site solar energy and E2 improvements made at small WRRFs. Improvements in E2 (e.g., improved aeration control) presented the largest reduction in emissions per dollar invested. They often exhibited shorter paybacks, with operational changes in aeration strategies showing the highest impact (up to 0.2 kg CO2eq/m3 treated water). On-site solar systems showed the largest net potential for reducing environmental footprint (0.35 kg CO2eq/m3) but often showed the smallest emissions reduction per cost. While the use of both E2 improvements and the integration of on-site solar renewable energy can significantly improve the sustainability of small WRRFs, on-site solar has advantages for small facilities in that it often requires less operational involvement, allows for greater facility resiliency, and presents less uncertainty in terms of environmental benefit.

Genomic fingerprints of the world's soil ecosystems.

Despite the explosion of soil metagenomic data, we lack a synthesized understanding of patterns in the distribution and functions of soil microorganisms. These patterns are critical to predictions of soil microbiome responses to climate change and resulting feedbacks that regulate greenhouse gas release from soils. To address this gap, we assay 1,512 manually curated soil metagenomes using complementary annotation databases, read-based taxonomy, and machine learning to extract multidimensional genomic fingerprints of global soil microbiomes. Our objective is to uncover novel biogeographical patterns of soil microbiomes across environmental factors and ecological biomes with high molecular resolution. We reveal shifts in the potential for (i) microbial nutrient acquisition across pH gradients; (ii) stress-, transport-, and redox-based processes across changes in soil bulk density; and (iii) greenhouse gas emissions across biomes. We also use an unsupervised approach to reveal a collection of soils with distinct genomic signatures, characterized by coordinated changes in soil organic carbon, nitrogen, and cation exchange capacity and in bulk density and clay content that may ultimately reflect soil environments with high microbial activity. Genomic fingerprints for these soils highlight the importance of resource scavenging, plant-microbe interactions, fungi, and heterotrophic metabolisms. Across all analyses, we observed phylogenetic coherence in soil microbiomes-more closely related microorganisms tended to move congruently in response to soil factors. Collectively, the genomic fingerprints uncovered here present a basis for global patterns in the microbial mechanisms underlying soil biogeochemistry and help beget tractable microbial reaction networks for incorporation into process-based models of soil carbon and nutrient cycling.IMPORTANCEWe address a critical gap in our understanding of soil microorganisms and their functions, which have a profound impact on our environment. We analyzed 1,512 global soils with advanced analytics to create detailed genetic profiles (fingerprints) of soil microbiomes. Our work reveals novel patterns in how microorganisms are distributed across different soil environments. For instance, we discovered shifts in microbial potential to acquire nutrients in relation to soil acidity, as well as changes in stress responses and potential greenhouse gas emissions linked to soil structure. We also identified soils with putative high activity that had unique genomic characteristics surrounding resource acquisition, plant-microbe interactions, and fungal activity. Finally, we observed that closely related microorganisms tend to respond in similar ways to changes in their surroundings. Our work is a significant step toward comprehending the intricate world of soil microorganisms and its role in the global climate.

REDD implementation for greenhouse gas reduction and climate change mitigation in Hyrcanian forests: a case study of the Kojoor Watershed, Northern Iran

Reducing emissions from deforestation and forest degradation (REDD) is a specific strategy for combating deforestation and forest degradation to alleviate the effects of climate change. In this study, the potential greenhouse gas (GHG) emission reduction resulting from the implementation of a REDD project is estimated. Changes in forest cover throughout the years 1985, 1990, 1995, 2000, 2010, 2015, and 2020 were analyzed using time-series Landsat imagery (TM, ETM + , and OLI) and a random forest algorithm. Multilayer perceptron neural networks were used to model the transition potential of the forest cover, which were then predicted via Markov chain analysis. The change detection analysis revealed two discernible patterns in forest cover dynamics. Between 1985 and 2000, a notable decrease in forest cover was seen, whereas from 2000 to 2020, it significantly increased. The results suggested that the absence of REDD implementation would result in the deforestation of approximately 199,569 hectares of forest cover between 2020 and 2050, leading to the release of 1,995,695 tCO2e of emissions into the atmosphere. However, with the implementation of REDD, these emissions would be reduced to 405,512 tCO2e, effectively preventing the release of 1,590,183 tCO2e of emissions into the upper atmosphere. This study demonstrates that the implementation of REDD projects can be an effective strategy for reducing GHG emissions and mitigating climate change in the Hyrcanian forests.

Forecasting the Mitigation Potential of Greenhouse Gas Emissions in Shenzhen through Municipal Solid Waste Treatment: A Combined Weight Forecasting Model

As a significant source of anthropogenic greenhouse gas emissions, the municipal solid waste sector’s greenhouse gas emission mode remains unknown, hampering effective decision-making on possible greenhouse gas emission reductions. Rapid urbanization and economic growth have resulted in massive volumes of municipal solid trash. As a result, identifying emission reduction routes for municipal solid waste treatment is critical. In this research, we investigate the potential of municipal solid waste treatment methods in lowering greenhouse gas (GHG) emissions in Shenzhen, a typical Chinese major city. The results showed that the combined treatment of 58% incineration, 2% landfill, and 40% anaerobic digestion (AD) had the lowest greenhouse gas emissions of about 5.91 million tons under all scenarios. The implementation of waste sorting and anaerobic digestion treatment of organic municipal solid waste after separate collection can reduce greenhouse gas emissions by simply increasing the incineration ratio.

A recipe for change: Analyzing the climate and ecosystem impacts of the Brazilian diet shift

Diet shift is an opportunity to mitigate the impacts of food systems, which are responsible for about a third of greenhouse gas (GHG) emissions globally and exert various environmental pressures on ecosystems. This study evaluates the mitigation potential of both global and local environmental impacts through dietary changes within the Brazilian context. Furthermore, the study aims to identify the potential benefits and trade-offs that may arise from these dietary transitions, thus providing a comprehensive analysis of the overall environmental implications. To this end, a life cycle assessment (LCA) was performed to evaluate the environmental impacts of a conventional diet in Brazil and seven alternatives, namely adjusted-EAT-Lancet, pescatarian, vegetarian, entomophagic (insect-based food), mycoprotein (microbial-based food), and synthetic (cell-based food) diets. Results indicate a substantial mitigation potential for GHG emissions (4-9 kg CO2e/cap/day) (39 % to 86 %) and land use (4-9 m2/cap/day) (38 % to 82 %) through a diet shift from a conventional diet to any of the seven alternative diets. However, certain trade-offs exist. A diet shift demonstrates no mitigation potential of soil acidification, and opportunities to reduce water eutrophication (0.02-0.2 g Pe/cap/day) (2 % to 24 %) and water consumption (0.2-0.5 m3/cap/day) (7 % to 14 %) were only found by completely substituting animal products for insect-based food, microbial-based food, and cell-based food. This study highlights the considerable potential of dietary changes to mitigate global environmental impacts associated with food systems. By revealing opportunities and challenges, this study supports science-based decision-making and guides efforts toward sustainable and environmentally friendly food consumption patterns.

Exploring potential diffusion pathways of biorefinery innovations—An agent‐based simulation approach for facilitating shared value creation

AbstractIn many European countries with plentiful forest resources, novel forest‐based businesses play a key role in the transition from our current fossil‐based economy towards a circular bioeconomy. For example, kraft lignin, a by‐product from the pulping industry, is produced in large amounts globally. To date, however, it is still only offered on the market by a small number of pulping companies. The successful innovation diffusion of related new technologies and businesses requires establishing a collective effort among multiple societal actors to motivate the sharing of value creation processes. In this paper, potential innovation diffusion pathways are modeled and simulated by means of an agent‐based approach (Biorefinery Products Innovation Diffusion model, BioPID). The paper investigates the conditions needed to encourage the diffusion of kraft lignin innovations as a (partial) replacement for fossil‐based feedstock in selected applications. The results reveal the basic mechanisms behind potential innovation diffusion pathways. The major barriers were found to be the high level of uncertainty surrounding the additional costs arising in lignin processing, the small number of lignin providers, and the presence of relatively homogeneous pricing strategies based on opportunity and basic preparation costs. The analysis of two product categories revealed different patterns in terms of innovation diffusion and potential greenhouse gas emissions. A novelty of BioPID is that it allows for iterative technology evaluation and technology foresight analysis of biorefinery projects (e.g., by combining techno‐economic, socio‐technical, and environmental aspects). This produces knowledge for diverse stakeholders involved in the lignin innovation ecosystem, thus enabling better communication on shared values and furthering innovation diffusion.

Reducing Energy Consumption and Greenhouse Gas Emissions of Industrial Drying Processes in Lithium-Ion Battery Cell Production: A Qualitative Technology Benchmark

As the world’s automotive battery cell production capacity expands, so too does the demand for sustainable production. Much of the industry’s efforts are aimed at reducing the high energy consumption in battery cell production. A key driver is electrode drying, which is currently performed in long ovens using large volumes of hot air. Several drying technologies from other industries could reduce energy consumption and greenhouse gas emissions if successfully applied to battery cell production. High process and quality requirements must be met when adapting these technologies for battery cell production. Evaluating the technologies against these requirements is difficult due to the technological novelty of this industry and the associated lack of data. Furthermore, the significant differences in drying technologies render a comparison even more challenging. One objective of this study was to evaluate drying technologies and identify those that could be best adapted to lithium-ion battery cell production. Near-infrared and laser drying were found to be the best in terms of energy efficiency, cost savings and other parameters. Another aim was to analyse, in more detail, the technological challenges and the advantages and disadvantages of the top-ranked drying technologies. Finally, the saving potential for greenhouse gas emissions of near-infrared and laser drying was calculated for a global production scenario of LIB cells in 2030. The saving potential in this scenario would amount to 2.63 million metric tonnes (Mt) CO2eq per year if near-infrared drying was applied in all global LIB cell production facilities within the mentioned scenario and 1.47 million Mt CO2eq per year for laser drying.

Realizing Low-carbon and Climate-resilient Development on Aquaculture

Aquaculture production supports food security, and it is an important commodity for Indonesia's exports. Climate change determines the sustainability of aquaculture production. Low-carbon development is an effort to control the impact of climate change from a mitigation standpoint, while climate-resilience development is an adaptation. In order to realize sustainable aquaculture in a broad and long dimension and in line with the Sustainable Development Goals (SDGs), it is necessary to develop a low-carbon and climate-resilience development strategy. A descriptive analysis was carried out on a review of published literature to develop the concept of low-carbon and climate-resilience development in aquaculture. The keywords used in the literature search are the impact of climate change on aquaculture, low-carbon development, climate-resilience development, and achievement of the SDGs in aquaculture. The research that has been published mostly discusses the potential Green House Gas emissions (GHG) from aquaculture activities, is still very limited and explains efforts to mitigate and adapt aquaculture to climate change. Efficiency and use of alternative energy sources, increased productivity, feed efficiency and effectiveness, effluent management, disease control and water quality management, and superior seeds can be applied in low-carbon emission development. Meanwhile, climate-resilience development that can be implemented includes the implementation of Integrated Multi-Tropical Aquaculture (IMTA) and Regional Integrated Multi-Tropical Aquaculture (RIMTA), closed systems, and Recirculating Aquaculture Systems (RAS), as well as ponds that integrate mangroves.

City-scale heating and cooling with aquifer thermal energy storage (ATES)

Sustainable and climate-friendly space heating and cooling is of great importance for the energy transition. Compared to conventional energy sources, Aquifer Thermal Energy Storage (ATES) systems can significantly reduce greenhouse gas emissions from space heating and cooling. Hence, the objective of this study is to quantify the technical potential of shallow low-temperature ATES systems in terms of reclaimable energy in the city of Freiburg im Breisgau, Germany. Based on 3D heat transport modeling, heating and cooling power densities are determined for different ATES configurations located in an unconsolidated gravel aquifer of varying hydrogeological subsurface characteristics. High groundwater flow velocities of up to 13 m d−1 cause high storage energy loss and thus limit power densities to a maximum of 3.2 W m−2. Nevertheless, comparison of these power densities with the existing thermal energy demands shows that ATES systems can achieve substantial heating and cooling supply rates. This is especially true for the cooling demand, for which a full supply by ATES is determined for 92% of all residential buildings in the study area. For ATES heating alone, potential greenhouse gas emission savings of up to about 70,000 tCO2eq a−1 are calculated, which equals about 40% of the current greenhouse gas emissions caused by space and water heating in the study areas’ residential building stock. The modeling approach proposed in this study can also be applied in other regions with similar hydrogeological conditions to obtain estimations of local ATES supply rates and support city-scale energy planning.

An optimized water table depth detected for mitigating global warming potential of greenhouse gas emissions in wetland of Qinghai-Tibetan Plateau

An optimized water table depth detected for mitigating global warming potential of greenhouse gas emissions in wetland of Qinghai-Tibetan Plateau

Urban Mobility Mode Shift to Active Transport: Sociodemographic Dependency and Potential Greenhouse Gas Emission Reduction

The aim of this study was to explore the association between travel mode choice and individual sociodemographic characteristics among urban city dwellers, as the selection of daily travel modes is influenced by several factors. The study collected 1,290 short daily trips data from 415 respondents living in Klang Valley using a random sampling technique. Logit regression models were utilized to identify the impact of sociodemographic traits on travel mode choices. Men, low education levels, students, and households without children and do not own private vehicles are more likely to choose active transportation. Besides, the study examines the potential for greenhouse gas (GHG) emission reduction. Based on Life Cycle Assessment (LCA), 142 kgCO2e or 108 kgCO2e/km of GHG were released by automobiles from the collected travel trip data. The result shows that active transport could potentially achieve 14.52% GHG emission reduction by stated preference and nearly 17% GHG emission reduction by criteria fulfillment. These findings could provide valuable information for developing practical planning policies aimed at reducing GHG emissions from the road transport sector.

Self-determined or non-self-determined? Exploring consumer motivation for sustainable food choices

Agricultural production is one of the major sources of greenhouse gas emissions with livestock farming accounting for half of the mitigation potential of greenhouse gas emissions of agriculture, forestry, and land-use sectors. Hence, a sustainable transition of the agricultural sector is urgently needed to achieve the objectives outlined in the Paris Agreement. Considering the amount of scientific evidence emphasizing the urgency of changing current dietary patterns to mitigate climate change, international and national public as well as private initiatives were introduced aiming to promote sustainable food choices. However, little is known so far about whether external pressure, initiated, for instance, through socio-political campaigns, motivates consumers to adopt a more sustainable dietary style. This study closes this research gap by applying the self-determination theory (SDT) to investigate Danish consumers' motivation for eating more sustainably by taking the example of reducing meat consumption. The structural equation model applied to a representative sample of 838 Danish consumers reveals the continuing importance of intrinsic and internalized extrinsic motivation, while external motivation fails to encourage consumers to eat less meat. The subsequent latent class analysis identified four segments, with 12.4 % of Danish consumers highly intrinsically motivated, 30.4 % slightly intrinsically motivated, 27.3 % amotivated, and the remaining 29.8 % undecided. The results suggest that the level of perceived external pressure to foster more sustainable food choices have no effect on consumers' food decision. High perceived self-determined motivation and personal identification with eating more sustainably emerged as a crucial driver. Therefore, policy interventions and private measures should prioritize individuals' values over external pressure to foster more sustainable food choices. This research contributes to a better understanding of consumers' food-related behavioral changes, while also providing a theoretical contribution by applying the SDT to sustainable food choices.

An appropriate amount of straw replaced chemical fertilizers returning reduced net greenhouse gas emissions and improved net ecological economic benefits

With the increasing application of crop straw, the greenhouse gas emissions caused due to crop straw have received increasing attention. However, the current studies have not explored the greenhouse gas emissions from on-farmland consumption of returned straw. Based on a long-term positioning experiment, three treatments were set up in double-cropping rice fields: chemical fertilizer (CF), straw replacing 1/3 nitrogen fertilizer (MS), and straw replacing 2/3 nitrogen fertilizer (HS). We measured the biomass, soil properties, and greenhouse gas emissions of double-cropping rice and then comprehensively evaluated the global warming potential, carbon footprint, and net ecological and economic benefits. The straw treatments (MS and HS) increased the cumulative annual emissions of CH4 (98.44% and 261.23%), CO2 (30.85% and 122.29%), and N2O (7.37% and 52.50%), the cumulative annual global warming potential (74.15% and 206.12%), average GHG intensity (43.26% and 138.07%), and the annual cumulative net ecosystem carbon budget (52.96% and 100.97%) in the early and late rice growing seasons, respectively. We observed that the real-time greenhouse gas emissions were significantly correlated to the soil microbial functional genes and total carbon, NH4+-N, and NO3−-N. The results of the random forest model showed that total carbon (13.87%) and nirK abundance (9.80%) were the highest predictors of global warming potential at the booting and maturity stages, respectively during rice growing season. Combining the resource inputs for agricultural production and the greenhouse gas emission potential of the returned straw on its own, MS showed the lowest net greenhouse gas emission, and MS and HS showed significantly increased annual cumulative net ecological economic benefits (38.08% and 34.30%). Overall, MS showed the lowest net greenhouse gas emission and the highest net ecological economic benefits, which is a straw-returning measure with low environmental impact and high economic returns.

The impact of controlling diseases of significant global importance on greenhouse gas emissions from livestock production

BackgroundA considerable body of evidence has reported the beneficial effects of improving productivity on reducing environmental impacts from livestock production. However, despite the negative impacts of animal diseases on reproduction, growth and milk production, there is little information available upon the impacts of animal disease on greenhouse gas emissions (GHGe). This study aimed to partially address this knowledge gap by investigating the effects of globally important vaccine-preventable diseases on GHGe from various livestock systems, namely: intensive dairy, extensive beef, commercial swine and backyard poultry production.MethodsSimple deterministic models were developed within Microsoft Excel to quantify the impacts of livestock disease on productivity (defined as total milk and/or meat yield, MMY) adjusted for disease prevalence both at the population level (high or low), and at the herd or flock level. Disease-induced changes in MMY were applied to the GHGe per kg of milk or meat according to the consequent changes in livestock populations required to maintain milk or meat production. Diseases investigated comprised foot and mouth, brucellosis, anthrax, lumpy skin disease, classical swine fever, porcine reproductive and respiratory syndrome (PRRS), low and high pathogenicity avian influenza (LPAI and HPAI), avian infectious bronchitis and Newcastle disease.ResultsAll diseases investigated had multifactorial impacts on total MMY, yet diseases that increased mortality in breeding or growing livestock (e.g. anthrax, classical swine fever and HPAI) showed greater impacts on GHGe per unit of milk or meat produced than those that primarily affecting yields or reproduction (e.g. brucellosis or LPAI). Prevalence also had considerable effects on potential GHGe. For example, maintaining backyard poultry meat production from a 100,000 hen population with 70% prevalence of HPAI increased GHGe by 11,255 MT CO2eq compared to a 30% prevalence at 3475 MT CO2eq above the baseline (0% prevalence). Effective reduction of the prevalence of PRRS in swine from 60 to 10%, FMD in beef cattle from 45 to 5% prevalence, or AIB in poultry from 75 to 20% prevalence would reduce GHGe intensities (CO2eq/kg CW) by 22.5%, 9.11% and 11.3% respectively.ConclusionsControlling livestock disease can reduce MMY losses at the farm level, which improves food security, reduces GHGe and enhances livestock system sustainability.

Reduction of Greenhouse Gas Emissions through Community-Scale Pyrolysis Technology in Bogor City and its Financial Feasibility

Population growth affects the generation of plastic waste and could potentially increase greenhouse gas (GHG) emissions through the burning process. This has become a severe problem as it contributes to global warming. Therefore, plastic waste management is required, for instance, by using pyrolysis technology on a community scale. Such a project will reduce plastic waste and GHG emissions by processing plastic into valuable products. This study aims (1) to estimate potential GHG emissions before the project implementation, (2) to estimate potential GHG emissions reduction after the project implementation, and (3) to assess both potential revenue and profit of pyrolysis products. This study employs SNI 19-3694-1994 method to estimate household waste generated, the clean development mechanism (CDM) method to estimate GHGs emissions reduction, and the profit comparison method (PCM) to asses both revenue and profit of pyrolysis products. The results show that GHG emissions before the project will be 3.69 t CO2e in 2021 and could increase to 4.61 t CO2e in 2030. Potential GHG emissions reduction depends on the fuel types to heat the reactor. Only electric pyrolysis will reduce GHG emissions by up to 0.46 t CO2e (13%) annually. This project is not financially feasible because operational costs (15,772,779 IDR) exceed the annual revenue (1,014,000 IDR).