Direct Greenhouse Gas Emissions Research Articles

Measurement-based carbon intensity of US offshore oil and gas production

The United States (US) produces oil and gas from six offshore regions: the North Slope of Alaska, Cook Inlet in Alaska, offshore California, and three Gulf of Mexico (GOM) sub-regions: state shallow, federal shallow, and deep waters. Measurement-based assessment of direct greenhouse gas emissions from this production can provide real-world information on carbon emissions to inform decisions on current and future production. In evaluating the climate impact of production, the carbon intensity (CI, the ratio of greenhouse gases emitted compared to the energy of fuels produced) is often used, though it is rarely quantified with measurements. Here, we complete an observational evaluation of the US offshore sector and present the largest current set of measurement-based CIs. We collected airborne measurements of methane, carbon dioxide, and nitrogen oxides from the North Slope, Cook Inlet, and California and combined with prior GOM results. For Alaska and California, we found emissions agree with facility-level inventories, however, the inventories miss some facilities. The US offshore CI, on a 100 year GWP basis, is 5.7 g CO2e/MJ[4.5, 6.8, 95% confidence interval]. This is greater than double the CI based on the national US inventory, with the discrepancy attributed primarily to methane emissions from GOM shallow waters, with a methane dominated CI of 16[12, 22] for GOM federal shallow waters and 43[25–65] for state shallow waters. Regional intensities vary, with carbon dioxide emissions largely responsible for CI on the North Slope 11[7.5, 15], in Cook Inlet 22[13, 34], offshore California 7.2[3.2, 13], and in GOM deep waters 1.1[1.0, 1.1]. These observations indicate offshore operations outside of the GOM in the US have modest methane emissions, but the CI can still be elevated due to direct carbon dioxide emissions. Accurate assessment of different offshore basins, with differing characteristics and practices, is important for the climate considerations of expanded production.

Unlocking the potential of ponds and pondscapes as nature-based solutions for climate resilience and beyond: Hundred evidences

Unlocking the full potential of ponds (small water bodies) and pondscapes (network of ponds) as Nature-based Solutions (NbS) is critical pursuit for enhancing ecosystems and societal resilience to climate change and other societal challenges. Despite scattered initiatives for pond/pondscape creation, restoration and management—each considered here a distinct NbS—there is a significant knowledge gap in utilising ponds/pondscapes as effective NbS. We aimed to assess these NbS in terms of their objectives, outcomes, effectiveness, multifunctionality, delivery of potentially conflicting effects, and the implementation process while considering their Nature's Contributions to People (NCPs, i.e., benefits to society). We compiled data on 183 NbS actions implemented across 93 ponds/pondscapes from 24 countries, predominantly from Europe, via a questionnaire distributed to experienced stakeholders implementing NbS in ponds/pondscapes. One single pond/pondscape may imply more than one NbS action. Two-thirds were in rural areas, and one-third in urban settings. Our analysis revealed that Creation of habitat for biodiversity was a primary delivery objective (targeted NCP) in the implementation of most NbS in ponds/pondscapes, often also combined with other NCPs such as Learning and inspiration, Regulation of water quantity, and Physical and psychological experiences, showcasing their intended multifunctionality. Implemented NbS primarily focused on climate change adaptation (especially Regulation of hazards and extreme events, and water quantity) rather than mitigation, with less emphasis on measures like direct greenhouse gas emissions reduction or enhancing carbon sinks. The costs associated with pond's NbS varied significantly depending on factors such as project scope, objectives, location, socio-economic-cultural system, and specific implementation requirements. The creation of ponds/pondscapes often entailed the highest financial investment, much more than their restoration or their management. In conclusion, our study underscores the multifunctionality of ponds/pondscapes and provides insights about their significant potential as cost-effective NbS for enhancing ecosystem and societal resilience to climate change and biodiversity. It underscores the importance of further research to fully understand and measure the diverse range of NbS they offer, particularly in the context of climate change mitigation. Standardised measurements of the NCP provided by these NbS in ponds/pondscapes are essential for validating managers' claims and exploring their role in addressing climate change.

A New Measure of Climate Transition Risk Based on Distance to a Global Emission Factor Frontier

Targeted financing of transition to a "net zero" global economy entails climate transition risk. We propose a measure of transition risk at the country-sector dyad level composed of five tiers of transition risk based on two factors: i) the gap between a dyad's existing emission factor (EF) – a measure of the greenhouse gas intensity of output – and the global 'frontier' sectoral EF, and ii) a dyad's recent convergence towards the frontier EF. Dyads that are either close to the frontier or converging towards the frontier carry lower transition risk. Our measure, using 45 sectors across 66 countries, accounts for both direct greenhouse gas emissions as well as those that enter into production through complex supply chains as captured by intercountry, input-output tables, and can be applied at different levels of stringency to high-, middle-, and low-income economies. Our measure thus accounts for, and sheds light on, EF reductions through investment in lower emissions production techniques in own facilities as well as sourcing intermediate inputs with lower embodied emissions.

Evaluation of Two Species of Macroalgae from Azores Sea as Potential Reducers of Ruminal Methane Production: In Vitro Ruminal Assay.

The utilisation of seaweeds as feed supplements has been investigated for their potential to mitigate enteric methane emissions from ruminants. Enteric methane emissions are the primary source of direct greenhouse gas emissions in livestock and significantly contribute to anthropogenic methane emissions worldwide. The aim of the present study is to evaluate the nutritional role and the in vitro effect on cumulative gas and methane production of Asparagopsis taxiformis (native species) and Asparagopsis armata (invasive species), two species of red algae from the Azorean Sea, as well as the ability to reduce biogas production when incubated with single pasture (Lolium perenne and Trifollium repens) as substrate. Four levels of concentrations marine algae were used (1.25%, 2.25%, 5%, and 10% DM) and added to the substrate to evaluate ruminal fermentation using the in vitro gas production technique. The total amount of gas and methane produced by the treatment incubation was recorded during 72 h of incubation. The results indicate that both algae species under investigation contain relatively high levels of protein (22.69% and 24.23%, respectively, for Asparagopsis taxiformis and Asparagopsis armata) and significant amounts of minerals, namely magnesium (1.15% DM), sodium (8.6% DM), and iron (2851 ppm). Concerning in vitro ruminal fermentation, it was observed that A. taxiformis can reduce enteric methane production by approximately 86%, during the first 24 h when 5% is added. In the same period and at the same concentration, A. armata reduced methane production by 34%. Thus, it can be concluded that Asparagopsis species from the Azorean Sea have high potential as a protein and mineral supplement, in addition to enabling a reduction in methane production from rumen fermentation.

Direct greenhouse gases from domestic wastewater treatment plant in Bandung Regency, West Java, Indonesia

Wastewater treatment contributes direct greenhouse gas (GHG) emissions in the atmosphere. The study aims to estimate the amount of methane (CH4) and carbon dioxide (CO2) emitted from domestic wastewater treatment plants (WWTP) in Bandung Regency throughout the years 2019-2022. Wastewater treatment processes in the WWTP consist of anaerobic, facultative, and maturation ponds. Data series of water quality from each process were collected on a monthly basis from years 2019 to 2022 to estimate direct emissions. Emission factors used in this study were derived from IPCC Guidelines and using the Tier 1 method. The highest GHG emission from WWTP Bojongsoang was about 513.44 tonCO2e in December 2021. The monthly average CO2e emissions from year to year increased about 40.12%. The average GHG emission from WWTP Bojongsoang from the year 2019 to 2022 respectively was about 81.33 tonCO2e/month, 135.21 tonCO2e/month, 229.26 tonCO2e/month, and 193.89 tonCO2e/month. Overall, the percentage of CO2e emission from anaerobic pond was about 93.57%, from facultative pond was about 4.86%, and from maturation pond was about 1.57%. The highest CO2e emissions occurred in the anaerobic pond along with the highest COD reduction also took place in the anaerobic pond.

Carbon footprint of Nepalese healthcare system: A study of Dhulikhel Hospital

Background Though direct greenhouse gas emissions cannot be observed in health care sectors, there can exist indirect emissions contributing to global climate change. This study addresses the concept of the carbon footprint and its significance in understanding the environmental impact of human activities, with a specific emphasis on the healthcare sector through gate-to-gate (GtoG) life cycle assessment. Transportation, energy consumption, and solid waste generated by hospitals are the primary sources of carbon emissions. Methods Different standards, guidelines and parameters were used to estimate emissions from both the primary and secondary data. All steps and sub-steps involved in GtoG were accessed and analyzed within the standard ISO 14040:44 guideline. An extensive review of existing literature was carried out for the evaluation and verification of secondary data. Results The total carbon footprint of generators, electricity consumption, transportation activities, LPG cylinders, PV systems was found to be 58,780 kg-CO2-eq/yr, 519,794 kg-CO2-eq/yr, 272,375 kg-CO2-eq/yr, 44,494 kg-CO2-eq/yr, 35,283 kg-CO2-eq/yr respectively and the emissions from non-biodegradable solid waste was found to be 489,835 kg-CO2/yr. Local air pollutants such as PM10, CO, SO2, NOX, and VOCs generated by generators and transportation were also estimated. The CH4 emissions from liquid waste were 1177.344 kg CH4/BOD yr, and those from biodegradables were 3821.6954 kg CH4/yr. Conclusions Healthcare professionals and policymakers can take action to reduce the sector's carbon footprint by implementing best practices and encouraging sustainable behavior. This study can be taken as foundation for further exploration of indirect emissions from healthcare sectors not only in Nepal but also in south Asian scenario.

Glass Fibre Composites Recycling Using the Fluidised Bed: A Comparative Study into the Carbon Footprint in the UK

The UK has no established process for recycling waste glass fibre-reinforced thermosets that are widely used within wind blade structures. Consequently, these materials are typically disposed of in landfills or undergo energy recovery in waste facilities. This study investigates the carbon footprint of the fluidised bed process for recycling glass fibre composite waste, considering the present and future scenarios of composite waste management in the UK. The impact was compared to conventional disposal routes and other prominent recycling technologies, such as cement kiln co-processing and mechanical recycling, by developing energy and material flow models for each waste treatment strategy. Variables, such as the type of waste, the quantity of recycling facilities in the UK, and waste haulage distance, were examined to inform the lowest impact deployment of recycling technologies. Cement kiln co-processing, mechanical, and fluidised bed recycling technologies reduced the global warming potential of processing wind blade waste compared with conventional disposal routes, with impacts of −0.25, −1.25, and −0.57 kg CO2e/kg GRP waste, respectively. Mechanical recycling had the lowest global warming potential resulting from low greenhouse gas emissions associated with the process itself and potentially high offsets by replacing glass fibre in the production of moulding compound. Composite wind turbine blade waste was found to be a particularly promising feedstock for the fluidised bed process due to relatively low resin content diminishing direct greenhouse gas emissions during thermal decomposition, as well as high material recovery offsets due to the high glass fibre content of this waste stream.

Cradle-to-Gate Life Cycle Assessment (LCA) of GaN Power Semiconductor Device

Wide Band Gap (WBG) semiconductors have the potential to provide significant improvements in energy efficiency over conventional silicon (Si) semiconductors. While the potential for energy efficiency gains is widely researched, the relation to the energy and resource use during manufacturing processes remains insufficiently studied. In order to appraise the performance of the technology thoroughly, issues such as raw material scarcity, toxicity and environmental impacts need to be investigated in detail. However, sparse Life Cycle Assessment (LCA) data are available for the two currently most widespread WBG semiconductor materials, gallium nitride (GaN or GaN/Si) and silicon carbide (SiC). This paper, for the first time, presents a cradle-to-gate life cycle assessment for a GaN/Si power device. To allow for a full range of indicators, life cycle assessment method EF 3.1 was used to analyze the results. The results identify environmental hotspots associated with different materials and processes: electricity consumption for the processes and clean room facilities, direct emissions of greenhouse gases, gold (when used), and volatile organic chemicals. Finally, we compare this result with publicly available data for Si, GaN and SiC power devices.

Evaluation of Greenhouse Gas Emissions and Mitigation Measures at Thammasat University's Lampang Campus in Thailand.

Greenhouse gases (GHGs) are the primary drivers of global climate change. Human activities, particularly those related to energy production, transportation, and industry, have long contributed to the escalating levels of GHGs in the Earth's atmosphere. Recognizing the significance of this issue, universities, including Thammasat University, play a vital role in Greenhouse gas (GHG) emissions research and education, carrying a responsibility to address the matter. This study is aimed aims to assess the greenhouse gas emissions and mitigation measures at Thammasat University (Lampang campus), Thailand. The emissions are categorized into 3 types: (1) direct GHG emissions; (2) energy-related indirect GHG emissions; and (3) other indirect GHG emissions. Activity data from the years 2019 to 2022 was used for the calculations, resulting in GHG emissions of 1051.70, 778.28, 558.64, and 1034.531 tons of carbon dioxide equivalent. Among these emissions, energy-related indirect GHG emissions from electricity purchases represent the majority, accounting for approximately 78.55% of the total emissions. Consequently, implementing mitigation strategies, such as solar panel installations and solid waste reduction (combined scenario), has the potential to reduce GHG emissions by up to 57.78%. Furthermore, the university should actively promote GHG emissions reduction through the enactment of energy-saving policies and the adoption of energy-efficient technologies to reduce reliance on energy purchases.

Smart dispatching for low-carbon mining fleet: A deep reinforcement learning approach

As the mining sector strives to meet its greenhouse gas (GHG) reduction targets by 2030 and 2050, the need for efficient energy-saving measures becomes paramount. This study presents an improved smart dispatching solution developed using deep reinforcement learning to improve the performance of mining haul truck fleets. The proposed solution based on double deep Q-network (DDQN) trains each truck in the fleet to make real-time decisions based on various factors such as in-situ grade (ore or waste), road traffic, estimated queueing, and maintenance requirements. Scenarios based on a synthetic mine are simulated to evaluate the effectiveness of this DDQN-based artificial intelligence solution versus conventional approaches. Our results demonstrate that the proposed DDQN solution not only improves productivity and reduces fuel-related GHG emissions, but also significantly improves fleet performance in handling operational disruptions (production loss reduced by over 50%) without human intervention, including unexpected changes in fleet size and shovel grade. The cost-effectiveness and scalability of the proposed solution are also assessed. Comparative analysis revealed that upgrading the fleet with the proposed DDQN solution to reduce GHG emissions only equates, on average, 47% and 21% of fleet electrification and carbon capture and storage costs, respectively, and can be rapidly adopted in the near term. These advantages position the smart fleet dispatching system as a cost-effective approach to enhance productivity and reduce direct GHG emissions in mining operations for short-term targets, making it an adaptive technology for future automated and sustainable mining.

A potential coupling of reforming and electrolysis for producing renewable hydrogen from landfill gas

Organic sold waste disposed of in landfills undergoes a mostly anaerobic process which generates a mixture of methane (CH4), carbon dioxide (CO2) and other various gases such as nitrogen, oxygen, sulphides, and non-methane organic compounds (NMOC), known as landfill gas (LFG). Being composed mostly of CH4 and CO2, landfill gas is a potent greenhouse gas (GHG). As a result, various waste treatment interventions are required to minimize the potential catastrophic damage to the environment from direct greenhouse gas emissions from landfills. One effective solution is combustion to generate electricity exploiting methane’s flammability properties. Biomass-based power plants have been present for decades. However, the combustion process is accompanied by a remarkable production of thermal energy which is typically not exploited and therefore lost to the ambient. The current work presents an energetic solution to manage organic waste by employing green hydrogen production. To do so, a hybrid layout based on a cogeneration unit (CHP) fed with landfill gas is considered. The electrical power produced by the CHP is used to produce hydrogen through low-temperature water electrolysis. Furthermore, due to the significant waste heat available in the system, excess thermal power is employed for the methane steam reforming process through a heat recovery section. Hydrogen produced from the reforming section is green since the input is from landfill gas, which is considered renewable. The levelized cost of hydrogen produced from such a hybrid layout is obtained and compared with non-renewable sources in this field. In addition, the annual H2 production rate is calculated for a capacity factor equal to 70%. The results show an annual Hydrogen production of about 167 t/y. LCOH at the stack of about 2 €/kg is reported.

Pesticide-free arable cropping systems: performances, learnings, and technical lock-ins from a French long-term field trial

To ensure regular and high yields, current agriculture is based on intensive use of pesticides and fertilizers, which are detrimental to the environment and human health. Moreover, as pest resistance to pesticides increases, and more and more pesticides are taken off the market, national and European policies are becoming powerful drivers to deliver pesticide-free farming systems. Whereas numerous studies have compared organic versus conventional systems, our study assessed, for the first time, the performances of a pesticide-free arable cropping system (No-Pesticide), using synthetic fertilizers, specifically designed to produce high yields and meet environmental goals. This system was compared with an input-based cropping system designed with the same environmental targets (PHEP: productive with high environmental performances) in an 11-year field trial in France (Paris Basin). Banning pesticides did not result in a significant average yield gap (in GJ.ha−1.year−1 or in kg N.ha−1.year−1) calculated over the crop sequence. Yet, some crops’ yields significantly decreased, due either to pest damages, or to limited nitrogen nutrition. In the No-Pesticide system, the mycotoxin content of cereal grains was lower than the regulatory threshold, and the average wheat protein content was higher than the required standard for baking. Indirect energy consumption, total greenhouse gas emissions, number of technical operations, nitrogen fertilizer amounts, and treatment frequency indexes were significantly lower compared to the PHEP system. Conversely, results showed significantly higher direct energy consumption, direct greenhouse gas emissions, and number of work hours for weed control. We identify highly effective agricultural strategies to avoid pesticide use (e.g., widely diverse and long crop sequence; introduction of hemp) and pinpoint several technical lock-ins hampering steady production in pesticide-free systems. We argue that more experiments should be undertaken to deliver technical knowledge for managing major or orphan species within pesticide-free systems, and to provide supplementary results, including economic and social performances.

Multiperspective Decoupling Analyses between Global Embodied Carbon Chains and Global Value Chains.

Decoupling global economic growth from carbon emissions is essential for mitigating global climate change while maintaining continuous economic growth. Traditional production-side decoupling analysis alone is insufficient to capture the decoupling status between carbon emissions and the value added throughout global supply chains. This study investigates the decoupling status between value added and greenhouse gas (GHG) emissions during 1995-2019 from consumption and income perspectives. We find that the decoupling statuses of 17 regions (especially Russia, Australia, and Malta) show significant differences across multiple perspectives. For example, Malta's direct GHG emissions decreased with its GDP growth from a production perspective (i.e., achieved strong decoupling). However, its consumption-based GHG emissions increased with the growth of consumption-based value added (i.e., expansive negative decoupling). Moreover, most international pairs have not yet achieved strong decoupling from consumption and income perspectives. International multilateral cooperation is crucial for decoupling global GHG emissions from economic growth across global supply chains. This study provides insights into the decoupling between embodied GHG emissions and value added from consumption and income perspectives. The findings of this study can complement existing policies on global GHG emission mitigation and sustainable development.

21 Beef Cattle and Global Warming

Abstract Beef cattle production is an important contributor to global warming both nationally and globally. Through a national life cycle assessment, we have determined that the production of beef cattle in the U.S. produces about 243 Tg of carbon dioxide equivalents (CO2e) in global warming with an intensity of 21 kg CO2e/kg of carcass weight. This is about 3.5% of the national inventory of greenhouse gas (GHG) emissions. Globally, the Food and Agriculture Organization (FAO) estimates the direct GHG emissions from all cattle other than dairy and their manure to be about 2,260 Tg or about 4.5% of the total global GHG emission. An important consideration in calculating the contribution of beef cattle is the assumed global warming potentials (GWP) used to relate the warming effect of methane and other compounds to that of CO2. Recommended values have varied over the past 20 years as we learn more about the warming potential of various gases. Values assumed affect published assessments, so it is important to consider the GWP values used when comparing studies. Methane is unique among the major compounds affecting global warming because it has a relatively short life in the atmosphere (half-life of about 8 years). Methane released by cattle and their manure oxidizes in the atmosphere returning the carbon originally fixed by growing plants back to CO2 completing a natural cycle. To better represent the warming effect of methane in the atmosphere, a model called GWP* has been introduced. To use this model, the change in emission rate over time must be quantified. Compared with 50 years ago in the U.S., we are now producing 20% more meat using about 15% fewer cattle. We estimate that the GHG intensity in cattle production has decreased 34%, and the total GHG emission related to beef cattle production has decreased 21% over this period. Considering the change that has occurred, using the GWP* model reduces the global warming impact of U.S. beef cattle by over 50% relative to the use of the commonly accepted current GWP factors. Global change is more difficult to quantify. The FAO estimates that over the past 50 years, the global number of non-dairy cattle has increased about 39% with a 78% increase in meat production and 36% increase in related methane emissions. Applying these data indicates that use of the GWP* model decreases the warming effect of global cattle by about 20%. When making policy decisions to mitigate GHG emissions, it is important to properly represent the relative warming effect of the important greenhouse gases.

Evaluating Nitrogen Management Practices for Greenhouse Gas Emission Reduction in a Maize Farmland in the North China Plain: Adapting to Climate Change.

Quantification of the trade-offs among greenhouse gas (GHG) emissions, yield, and farmers' incomes is essential for proposing economic and environmental nitrogen (N) management strategies for optimizing agricultural production. A four-year (2017-2020) field experiment (including four treatments: basic N fertilizer treatment (BF), suitable utilization of fertilization (SU), emission reduction treatment (ER), and high fertilization (HF)) was conducted on maize (Zea mays L.) in the North China Plain. The Life Cycle Assessment (LCA) method was used in this study to quantify the GHG emissions and farmers' incomes during the whole maize production process. The total GHG emissions of BF, SU, ER, and HF treatments in the process of maize production are 10,755.2, 12,908.7, 11,950.1, and 14,274.5 kg CO2-eq ha-1, respectively, of which the direct emissions account for 84.8%, 76.8%, 74.9%, and 71.0%, respectively. Adding inhibitors significantly reduced direct GHG emissions, and the N2O and CO2 emissions from the maize fields in the ER treatment decreased by 30.0% and 7.9% compared to those in the SU treatment. Insignificant differences in yield were found between the SU and ER treatments, indicating that adding fertilizer inhibitors did not affect farmers' incomes while reducing GHG emissions. The yield for SU, ER, and HF treatments all significantly increased by 12.9-24.0%, 10.0-20.7%, and 2.1-17.4% compared to BF, respectively. In comparison with BF, both SU and ER significantly promoted agricultural net profit (ANP) by 16.6% and 12.2%, with mean ANP values of 3101.0 USD ha-1 and 2980.0 USD ha-1, respectively. Due to the high agricultural inputs, the ANP values in the HF treatment were 11.2%, 16.6%, and 12.4% lower than those in the SU treatment in 2018-2020. In conclusion, the combination of N fertilizer and inhibitors proved to be an environmentally friendly, high-profit, and low-emissions production technology while sustaining or even increasing maize yields in the North China Plain, which was conducive to achieving agricultural sustainability.

Carbon footprint of a conventional wastewater treatment plant: An analysis of water-energy nexus from life cycle perspective for emission reduction

Reducing greenhouse gas (GHG) emissions is of far-reaching implications for the sustainable development of a conventional domestic wastewater treatment plant (WWTP). GHG emissions of the WWTP in different working loads were monitored to quantify the influence of critical processes on GHG emissions and shed light on the relations between direct and indirect GHG emissions with the water-energy nexus. The life cycle carbon footprint of the WWTP was assessed to find the most critical impact factor. A conceptual model of direct and indirect GHG emissions was established based on the water-energy nexus and life cycle assessment (LCA). Results showed that direct GHG emissions were highest in medium working load in May. While high indirect GHG emissions were in February, with the highest working load. Methane (CH4) emission rates, from 44.39 ± 42.49 to 4.94 ± 2.29 kg CO2e·d−1, decreased along the treatment processes due to oxidation. Dissolved CH4 in wastewater mainly came from the influent that was 0.08 ± 0.04 kg CH4·d−1. The increase of nitrous oxide (N2O) emissions and dissolved N2O occurred in the secondary treatment stage and was affected by the C/N ratio. The operation and maintenance phase had the most significant carbon footprint due to 86.4% of indirect GHG emissions from electricity usage through LCA. Electricity usage and glucose dosing were significantly correlated with N2O emissions but had no contribution to CH4 emissions. The conceptual model qualitatively demonstrated that direct and indirect GHG emissions reduced as electricity usage decreased based on the water-energy nexus. This study provided new insight into the analysis of GHG emissions from WWTPs.

Going beyond carbon: An "Earth system impact" score to better capture corporate and investment impacts on the earth system

Corporations are responsible for a significant portion of observed impacts on the Earth system, including green-house gas (GHG) emissions, but also water extraction, landuse change and other pressures on nature. These nature-related impacts are essential to consider and capture because they have local impacts on a range of ecosystem functions on which companies and economies depend, but they also fundamentally affect our ability to mitigate and adapt to a changing climate. Furthermore, climate, land and water interact and affect each other in various ways, such that climate change can be exacerbated by degraded ecosystems, which in turn are dependent on water.This paper tests a novel metric developed to capture corporate Earth system impact (ESI) beyond merely direct GHG emissions and explores how such a tool could be used to improve assessments of corporate environmental impacts and support decisions on where to direct public and private investments. We use the mining sector as a test case to illustrate the applicability of the ESI score and examine the impact of the the five largest (by market cap) mining companies in the precious metal mining sector and the top five in the non-precious metal mining sector. We find that many of the mining assets have non-negligible impacts on land and water, and we show that the ESI metric identifies a different set of asset for targeted action than conventional carbon intensity scores would do.

Nitrous oxide emissions from two full-scale membrane-aerated biofilm reactors

The upcoming change of legislation in some European countries where wastewater treatment facilities will start to be taxed based on direct greenhouse gas (GHG) emissions will force water utilities to take a closer look at nitrous oxide (N2O) production. In this study, we report for the first time N2O emissions from two full-scale size membrane aerated biofilm reactors (MABR) (R1, R2) from two different manufacturers treating municipal wastewater. N2O was monitored continuously for 12 months in both the MABR exhaust gas and liquid phase. Multivariate analysis was used to assess process performance. Results show that emission factors (EFN2O) for both R1 and R2 (0.88 ± 1.28 and 0.82 ± 0.86 %) were very similar to each other and below the standard value from the Intergovernmental Panel on Climate Change (IPCC) 2019 (1.6 %). More specifically, N2O was predominantly emitted in the MABR exhaust gas (NTRexh) and was strongly correlated to the ammonia/um load (NHx,load). Nevertheless, the implemented Oxidation Reduction Potential (ORP) control strategy increased the bulk contribution (NTRbulk), impacting the overall EFN2O. A thorough analysis of dynamic data reveals that the changes in the external aeration (EA)/loading rate patterns suggested by ORP control substantially impacted N2O mass transfer and biological production processes. It also suggests that NTRexh is mainly caused by ammonia-oxidizing organisms (AOO) activity, while ordinary heterotrophic organisms (OHO) are responsible for NTRbulk. Different methods for calculating EFN2O were compared, and results showed EFN2O would range from 0.6 to 5.5 depending on the assumptions made. Based on existing literature, a strong correlation between EFN2O and nitrogen loading rate (R2 = 0.73) was found for different technologies. Overall, an average EFN2O of 0.86 % N2O-N per N load was found with a nitrogen loading rate >200 g N m−3 d−1, which supports the hypothesis that MABR technology can achieve intensified biological nutrient removal without increasing N2O emissions.

Carbon footprint of Nepalese healthcare system: A study of Dhulikhel Hospital.

Though direct greenhouse gas emissions cannot be observed in health care sectors, there can exist indirect emissions contributing to global climate change. This study addresses the concept of the carbon footprint and its significance in understanding the environmental impact of human activities, with a specific emphasis on the healthcare sector through gate-to-gate (GtoG) life cycle assessment. Transportation, energy consumption, and solid waste generated by hospitals are the primary sources of carbon emissions. Different standards, guidelines and parameters were used to estimate emissions from both the primary and secondary data. All steps and sub-steps involved in GtoG were accessed and analyzed within the standard ISO 14040:44 guideline. An extensive review of existing literature was carried out for the evaluation and verification of secondary data. The total carbon footprint of generators, electricity consumption, transportation activities, LPG cylinders, PV systems was found to be 58,780 kg-CO2-eq/yr, 519,794 kg-CO2-eq/yr, 272,375 kg-CO2-eq/yr, 44,494 kg-CO2-eq/yr, 35,283 kg-CO2-eq/yr respectively and the emissions from non-biodegradable solid waste was found to be 489,835 kg-CO2/yr. Local air pollutants such as PM 10, CO, SO 2, NO X, and VOCs generated by generators and transportation were also estimated. The CH 4 emissions from liquid waste were 1177.344 kg CH 4/BOD yr, and those from biodegradables were 3821.6954 kg CH4/yr. Healthcare professionals and policymakers can take action to reduce the sector's carbon footprint by implementing best practices and encouraging sustainable behavior. This study can be taken as foundation for further exploration of indirect emissions from healthcare sectors not only in Nepal but also in south Asian scenario.

Modelling greenhouse gas emissions from biological wastewater treatment by GPS-X: The full-scale case study of Corleone (Italy)

Greenhouse gas (GHG) emissions from wastewater treatment plants (WWTPs) can affect climate change and must be measured and reduced. Mathematical modelling is an attractive solution to get a tool for GHG mitigation. However, although many efforts have been made to create reliable tools that can simulate “sustainable” full-scale WWTP operation, these studies are not considered complete enough to include GHG emissions and energy consumption of biological processes under long-term dynamic conditions. In this study, activated sludge model no. 1 (ASM1) was modified to model nitrous oxide (N2O) emissions with a plant-wide modelling approach. The model is novel compared to the state of the art since it includes three steps denitrification, all N2O production pathways and its stripping in an ASM1. The model has been calibrated and validated through long-term water quality and short-term N2O emissions data collected from Corleone (Italy) WWTP. Different dissolved oxygen (DO) concentrations and return sludge (RAS) ratios were tested with dynamic simulations to optimise the full-scale WWTP. The scenarios have been compared synergistically with effluent quality, direct GHG emissions, and energy footprint by the water-energy‑carbon coupling index (WECCI). This modelling study is novel as it fully covers long-term calibration/validation of the model with N2O measurements and tests the dynamic optimisation. Decision-makers and operators can use this new model to optimise GHG emissions and treatment costs.