National Emissions Research Articles

Unbiased method for spectral analysis of cells with great diversity of autofluorescence spectra.

Autofluorescence is an intrinsic feature of cells, caused by the natural emission of light by photo-excitatory molecular content, which can complicate analysis of flow cytometry data. Different cell types have different autofluorescence spectra and, even within one cell type, heterogeneity of autofluorescence spectra can be present, for example, as a consequence of activation status or metabolic changes. By using full spectrum flow cytometry, the emission spectrum of a fluorochrome is captured by a set of photo detectors across a range of wavelengths, creating an unique signature for that fluorochrome. This signature is then used to identify, or unmix, that fluorochrome's unique spectrum from a multicolor sample containing different fluorescent molecules. Importantly, this means that this technology can also be used to identify intrinsic autofluorescence signal of an unstained sample, which can be used for unmixing purposes and to separate the autofluorescence signal from the fluorophore signals. However, this only works if the sample has a singular, relatively homogeneous and bright autofluorescence spectrum. To analyze samples with heterogeneous autofluorescence spectral profiles, we setup an unbiased workflow to more quickly identify differing autofluorescence spectra present in a sample to include as "autofluorescence signatures" during the unmixing of the full stained samples. First, clusters of cells with similar autofluorescence spectra are identified by unbiased dimensional reduction and clustering of unstained cells. Then, unique autofluorescence clusters are determined and are used to improve the unmixing accuracy of the full stained sample. Independent of the intensity of the autofluorescence and immunophenotyping of cell subsets, this unbiased method allows for the identification of most of the distinct autofluorescence spectra present in a sample, leading to less confounding autofluorescence spillover and spread into extrinsic phenotyping markers. Furthermore, this method is equally useful for spectral analysis of different biological samples, including tissue cell suspensions, peripheral blood mononuclear cells, and in vitro cultures of (primary) cells.

Measuring the Cost of the European Union’s Carbon Border Adjustment Mechanism on Moroccan Exports

The ‘Fit for 55’ policy package was presented in the European Commission’s Green Deal framework, comprising a set of proposals to improve existing energy and climate legislation. Among its main proposals was a revision of the European Union’s Emission Trading System to expand its sectoral coverage. Anticipating the possible loss of competitiveness with carbon pricing within the EU—which may lead to ‘carbon leakage’—a carbon border adjustment mechanism (CBAM) was included in the package. This scheme takes the form of an export tax levied by the European Union on some goods manufactured in non-carbon-taxing countries. In this paper, we provide a first-order estimate of the potential impact of CBAM on Morocco’s exports using an input–output approach. Our main findings suggest that the scheme would yield a carbon bill ranging from USD 20 to 34 million annually to Moroccan exporters in its initial phase. Morocco can mitigate such economic losses by instituting a national Emission Trading System, a tax reform, or speeding up the decarbonization of its economy.

Three years of CO2, CH4 and N2O fluxes from different sheepfolds in a semiarid steppe region, China

To better assess greenhouse gas (GHG) emissions from livestock folds in semi-arid steppe zones and reduce uncertainties in regional and national GHG emission inventories, we measured the fluxes of carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O) from sheepfolds under contrasting management regimes (i.e., summer sheepfolds under continuous and rotational grazing strategies and the winter sheepfold) for 3 consecutive years. Our results showed that these GHG fluxes had high intra-annual and interannual variations, emphasizing the importance of multi-year measurement for achieving temporally representative annual budgets. Sheep presence and temperature appeared to be the key factors driving CH4, CO2 and N2O fluxes from sheepfolds, e.g., higher GHG emissions usually occurred in seasons with sheep presence. However, the sheepfold type exerted a distinct influence on the temperature sensitivity of GHG fluxes, i.e., the Q10 values for GHG fluxes were generally higher in summer sheepfolds than in winter sheepfold. The annual CH4, CO2 and N2O emissions for the 3 sheepfolds were estimated to be 1.5–16.5 kg C ha−1 yr−1 (or 1.9–2.6 g C yr−1sheep−1), 8.6–16.0 t C ha−1 yr−1 (or 5.1–6.6 kg C yr−1sheep−1) and 28.3–41.9 kg N ha−1 yr−1 (or 19.0–26.8 g N yr−1sheep−1), respectively. Averaging across the 3 years, the annual net GHG emissions (CH4 + CO2 + N2O) for all sheepfolds ranged from 47 to 71 t CO2-eq ha−1 yr−1 (or 27–36 kg CO2-eq yr−1 sheep−1), of which CO2 and N2O emissions contributed the most; moreover, the annual net GHG emissions had no significant differences between sheepfold types or grazing strategies. Given that local steppe soils have a lower magnitude of soil respiration (CO2) and N2O emissions and are also net sink for atmospheric CH4, the sheepfold sites in this region are undoubtedly one of the significant hotspots for GHG emissions and could be key areas to focus mitigation action.

Assessing the economic implications of carbon emissions on climate change: Estimating the impact using methane-adjusted DICE model

This study aims to highlight the importance of accurately estimating methane emissions, one of the most dangerous and important greenhouse gases in the context of climate change. By incorporating methane emissions as a variable within the integrated assessment model DICE (Dynamic Integrated Climate-Economy model), we investigate how these emissions influence temperature changes and subsequently impact economic policies, including climate economic policies, carbon pricing, and non-price factors. We use the existing DICE-2020 and DICE-2023 models as references for our analysis. In addition to industrial emissions that can be detected through satellite observations, we address the challenge of estimating natural emissions from wetlands and permafrost, which leak gradually and are difficult to detect. By considering these emissions, we account for their exogenous nature and their divergence from the current situation. Our study reveals that incorporating methane emissions into the DICE model has significant implications for global temperature outcomes and subsequent policy changes. We find that by implementing existing methane reduction policies, which includes cutting the level of methane emissions in half and increase the carbon price in 4 times to 500 USD per ton, it is possible to achieve the more ambitious goal of limiting the global temperature increase to 1.5 °C by 2100 in an optimistic scenario instead of the common target of 2 °C. More pessimistic scenarios that do not imply big change in methane emissions, but the same numerical data for carbon price, still suggests the possibility of keeping the global temperature below 2 °C. The findings of this study emphasize the importance of estimating methane emissions in efforts to mitigate climate change. Recognizing the impact of methane on global temperature change, policymakers can make informed decisions regarding economic policies, carbon pricing, to effectively address the challenges posed by climate change. This research contributes to the field by incorporating methane emissions into the DICE model, providing a more complete understanding of its influence on global climate outcomes and economic implications. Additionally, by highlighting the potential benefits of methane reduction measures, this study provides information on how to achieve more ambitious climate targets.

RadWet-L: A Novel Approach for Mapping of Inundation Dynamics of Forested Wetlands Using ALOS-2 PALSAR-2 L-Band Radar Imagery

The ability to accurately map tropical wetland dynamics can significantly contribute to a number of areas, including food and water security, protection and enhancement of ecosystems, flood hazard management, and our understanding of natural greenhouse gas emissions. Yet currently, there is not a tractable solution for mapping tropical forested wetlands at high spatial and temporal resolutions at a regional scale. This means that we lack accurate and up-to-date information about some of the world’s most significant wetlands, including the Amazon Basin. RadWet-L is an automated machine-learning classification technique for the mapping of both inundated forests and open water using ALOS ScanSAR data. We applied and validated RadWet-L for the Amazon Basin. The proposed method is computationally light and transferable across the range of landscape types in the Amazon Basin allowing, for the first time, regional inundation maps to be produced every 42 days at 50 m resolution over the period 2019–2023. Time series estimates of inundation extent from RadWet-L were significantly correlated with NASA-GFZ GRACE-FO water thickness (Pearson’s r = 0.96, p < 0.01), USDA G-REALM lake hight (Pearson’s r between 0.63 and 0.91, p < 0.01), and in situ river stage measurements (Pearson’s r between 0.78 and 0.94, p < 0.01). Additionally, we conducted an evaluation of 11,162 points against the input ScanSAR data revealing spatial and temporal consistency in the approach (F1 score = 0.97). Serial classifications of ALOS-2 PALSAR-2 ScanSAR data by RadWet-L can provide unique insights into the spatio-temporal inundation dynamics within the Amazon Basin. Understanding these dynamics can inform policy in the sustainable use of these wetlands, as well as the impacts of inundation dynamics on biodiversity and greenhouse gas budgets.

Study on the Evolution of Spatial and Temporal Patterns of Carbon Emissions and Influencing Factors in China

Abstract: Industrialization has increased global carbon emissions, necessitating effective climate change mitigation measures. China, the most populous developing nation, faces the challenge of strategizing emissions to meet national carbon neutrality objectives. However, research on specific regions’ carbon emissions drivers and causal factors is limited, particularly across prefectural-level cities. This study estimates the spatial and temporal patterns of carbon emissions across China’s prefectural cities and utilizes both OLS regression and stepwise regression models to analyze the impact of various factors influencing carbon emissions in these cities. Results reveal the following: (1) The country’s overall 20-year carbon emissions continue to grow from 3020.29 Mt in 2001 to 9169.74 Mt in 2020, with an average annual growth rate of 5.71%; the eastern region has seen a gradual deceleration in emissions, whereas the western region continues to experience an increase. Carbon emissions in cities within each subregion consistently rise. (2) Carbon emissions in Chinese prefectural-level cities exhibit strong spatial autocorrelation and clustering (Z > 1.96, p < 0.05), with hot spots primarily in the eastern coastal areas and cold spots in the northwest to southwest regions. (3) Economic and demographic factors significantly increase carbon emissions, while climate and urbanization effects are more complex and variable. Economic growth and population increase are the most significant influencing factors, but regional variances exist in carbon emissions determinants in subregional prefectural cities. These insights provide valuable insights into national emission dynamics at the prefectural level, providing a theoretical basis for enhancing carbon emission strategies across various jurisdictions.

Interstate power interconnection along with carbon dioxide emission constraint collaboration: Effective tool for low-carbon electric power expansion in Northeast Asia

Interstate electric power integration with the formation of interstate electric ties and power interconnection in Northeast Asia has been studied for several years. Research has examined the directions, indicators, costs, and systemic (integration) benefits (technical, economic, environmental, etc.) of forming such ties and grids. Studies conducted in different Northeast Asia countries have shown that despite the significant investments required to create an interstate electric ties infrastructure, which serves as the basis for interstate power grids and electricity markets development, participants of these interstate power grids and markets gain substantial benefits. These include reduced needs for installed and reserve generation capacity, lower electricity prices, increased overall flexibility of power resources, and accordingly, greater capability to integrate renewable energy sources. This results in reduced carbon dioxide (CO2) emissions from fossil fuel power plants. The latter undoubtedly contributes to achieving the sustainable development goals set by the United Nations and reducing anthropogenic climate impact, which many countries globally (including Northeast Asia) have targeted via announced carbon neutrality by 2050–2060. The main target of the article is to conduct and present new multi-scenario study on forming a potential Northeast Asia’s interstate power grid under national and grid-wide (for the entire power system interconnection) carbon emission constraints. The mathematical model of electric power system expansion and dispatching was modified to account for carbon dioxide emission constraints and used for the study. The results of the study showed that the creation of interstate power grid in Northeast Asia accompanied by climate change collaboration among countries to control carbon dioxide emission would lead to effectively constraining of carbon dioxide emission in the subregion, which is the novelty of the study. The results of the study are useful and applicable for choosing particular ways, options, stages of formation and expansion of low-carbon power system interconnection in Northeast Asia.

ESG resilience in conflictual times

Measuring the market reaction to a series of announcements related to gas rationing, we find that stock returns of firms with high ESG scores are less affected than their peers. Negative abnormal returns caused by the escalation of the Russia–Ukraine conflict are significantly less pronounced for firms with high scores in the environmental pillar of their ESG evaluation. This effect is mainly driven by the efficient usage of natural resources and low carbon emissions. This evidence is robust to different asset-pricing model specifications. Our findings suggest that higher environmental commitment makes companies more resilient to geopolitical shocks affecting the market price of fossil resources. Interestingly, the evidence in favour of ESG resilience mainly comes from countries more dependent on energy import.

Estimation of ammonia emissions from rice fields under different N inputs in China

Rice production is essential for ensuring food security. Nitrogen fertilizers applied in rice fields are prone to loss through NH3 emissions. We need to elucidate the responses of NH3 emissions to different N inputs. With a national dataset, we identified that N application rate, N application frequency, soil temperature, and soil silt fraction were the key driving factors of NH3 emissions. 190−210 kg N ha−1 was suitable for simultaneously reducing NH3 emissions and increasing rice yields. The model showed that under the actual N application rate and N application frequency of 3, national NH3 emissions were 0.852 Mt N each rice growing season, while national NH3 emission factor was 12.7 %. We developed a portable software to conveniently assess China's NH3 emissions from rice fields under different N inputs. The findings can help to optimize N inputs in rice fields to reduce NH3 emissions and improve ecosystem health and agricultural sustainability.

Carbon footprint research and mitigation strategies for rice-cropping systems in China: a review

Reducing greenhouse gas (GHG) emissions and quantifying the carbon footprint (CF) of rice-cropping systems in the context of food security is an important step toward the sustainability of rice production. Exploring the key factors affecting emission reduction in rice production is important to properly evaluate the impact of China’s rice-cropping systems on global climate change. This review provides an overview of the direct and indirect CF in rice-cropping systems; analyzes the influencing factors in terms of rice-based cropping systems, varieties and agronomic practices; and proposes mitigation strategies. Different studies have shown that direct and indirect GHG emissions in rice-based cropping systems accounted for 38.3 to 95.5% and 4.5 to 61.7% of total emissions, respectively. And the CFs of ratoon rice, rice–wheat, rice–maize, rice–rapeseed, and rice–fish systems ranged from 316,9 kg CO2-eq kg−1 to 258,47 kg CO2-eq kg−1, which are lower than that in a double-rice planting system. High-yielding rice, drought-resistant rice, and other hybrids can mitigate GHG emissions from paddy fields by 3.7 ~ 21.5%. Furthermore, organic matter, water, tillage, straw incorporation, conservation tillage, reduced nitrogen fertilizer use, and added biochar and methane inhibitors could reduce emissions. Therefore, through reasonable agronomic measures, variety selection and optimal layout of rice-based rotation systems, the carbon neutral rate of rice production can be improved to help the national carbon sequestration and emission reduction target.

Assessment of Potential and Techno-Economic Performance of Solid Sorbent Direct Air Capture with CO2 Storage in Europe.

Direct air capture with CO2 storage (DACCS) is among the carbon dioxide removal (CDR) options, with the largest gap between current deployment and needed upscaling. Here, we present a geospatial analysis of the techno-economic performance of large-scale DACCS deployment in Europe using two performance indicators: CDR costs and potential. Different low-temperature heat DACCS configurations are considered, i.e., coupled to the national power grid, using waste heat and powered by curtailed electricity. Our findings reveal that the CDR potential and costs of DACCS systems are mainly driven by (i) the availability of energy sources, (ii) the location-specific climate conditions, (iii) the price and GHG intensity of electricity, and (iv) the CO2 transport distance to the nearest CO2 storage location. The results further highlight the following key findings: (i) the limited availability of waste heat, with only Sweden potentially compensating nearly 10% of national emissions through CDR, and (ii) the need for considering transport and storage of CO2 in a comprehensive techno-economic assessment of DACCS. Finally, our geospatial analysis reveals substantial differences between regions due to location-specific conditions, i.e., useful information elements and consistent insights that will contribute to assessment and feasibility studies toward effective DACCS implementation.

Assessing the Environmental and Downstream Human Health Impacts of Decentralizing Cancer Care

Greenhouse gas (GHG) emissions from health care are substantial and disproportionately harm persons with cancer. Emissions from a central component of oncology care, outpatient clinician visits, are not well described, nor are the reductions in emissions and human harms that could be obtained through decentralizing this aspect of cancer care (ie, telemedicine and local clinician care when possible). To assess potential reductions in GHG emissions and downstream health harms associated with telemedicine and fully decentralized cancer care. This population-based cohort study and counterfactual analyses using life cycle assessment methods analyzed persons receiving cancer care at Dana-Farber Cancer Institute between May 2015 and December 2020 as well as persons diagnosed with cancer over the same period from the Cancer in North America (CiNA) public dataset. Data were analyzed from October 2023 to April 2024. The adjusted per-visit day difference in GHG emissions in kilograms of carbon dioxide (CO2) equivalents between 2 periods: an in-person care model period (May 2015 to February 2020; preperiod) and a telemedicine period (March to December 2020; postperiod), and the annual decrease in disability-adjusted life-years in a counterfactual model where care during the preperiod was maximally decentralized nationwide. Of 123 890 included patients, 73 988 (59.7%) were female, and the median (IQR) age at first diagnosis was 59 (48-68) years. Patients were seen over 1.6 million visit days. In mixed-effects log-linear regression, the mean absolute reduction in per-visit day CO2 equivalent emissions between the preperiod and postperiod was 36.4 kg (95% CI, 36.2-36.6), a reduction of 81.3% (95% CI, 80.8-81.7) compared with the baseline model. In a counterfactual decentralized care model of the preperiod, there was a relative emissions reduction of 33.1% (95% CI, 32.9-33.3). When demographically matched to 10.3 million persons in the CiNA dataset, decentralized care would have reduced national emissions by 75.3 million kg of CO2 equivalents annually; this corresponded to an estimated annual reduction of 15.0 to 47.7 disability-adjusted life-years. This cohort study found that using decentralization through telemedicine and local care may substantially reduce cancer care's GHG emissions; this corresponds to small reductions in human mortality.

Countervailing impacts of fossil fuel production and exports of electrical goods on energy transitions and climate change

We analyze the implications of fossil fuel production by the U.S. and increasing exports of electrical goods by China on critical mineral prices, energy transitions, and climate change. Using a GVAR model from July 2012 to December 2019, encompassing 12 economies, we employ the dominant unit model and structural identification of shocks. Our findings reveal that increased U.S. fossil fuel production leads to a rise in global CO2 emissions, hampers domestic energy transitions, and triggers changes in critical mineral markets. Fossil fuel emerges as the primary external factor influencing national energy matrices and carbon emissions, highlighting spillover effects from the U.S. energy matrix on the global economy. While U.S. fossil fuel production negatively impacts energy transitions over the long term, Chinese exports of electrical goods contribute to cleaner energy production. These countervailing forces suggest that the global transition to clean energy may occur, but it will be slow. We discuss policy implications, which should: i) promote international trade by reducing protectionist policies and establishing multilateral or bilateral agreements; ii) incentivize the adoption of clean energy; and iii) diminish the incentive to use fossil fuel energy through fiscal and tax policies.

Mapping construction sector greenhouse gas emissions: a crucial step in sustainably meeting increasing housing demands

This paper examines the tension between needing to build more infrastructure and housing and simultaneously reduce greenhouse gas emissions (GHG) to avoid the most catastrophic impacts of climate change. This study uses an Environmentally Extended Input-Output approach to conduct a high-resolution top-down analysis of Canada’s national construction GHG emissions. Our findings highlight that Canada’s current construction practices cannot accommodate the construction required to restore housing affordability by 2030 without substantial environmental consequences. On a consumption life cycle basis, the construction sector was responsible for approximately 90 Mt CO2e in 2018, equivalent to over 8% of Canada’s total GHG emissions, while delivering less than a third of Canada’s annual housing needs. Residential construction was responsible for the largest share (42%) of total construction emissions. Overall, 84% of emissions are from material manufacturing and 35% of construction emissions are imported, underscoring the need for a comprehensive regulatory framework addressing both domestic and imported emissions. Under current construction practices (i.e. current material use patterns and emissions intensities), meeting Canada’s 2030 housing affordability and climate commitments requires an 83% reduction in GHG emissions per construction product (i.e. per home) compared to the 40% economy-wide reduction promised in Canada’s international reduction commitments. Mitigating the GHG gap between emission caps and housing demand calls for changes in the ratio of housing to other infrastructure (e.g. fewer roads, less fossil fuel infrastructure), new construction approaches (e.g. increasing material efficiency) and/or disproportionally allocating climate budget to construction. The implications of our study extend beyond Canada, offering valuable insights for other growing countries with climate goals. The results emphasize the urgency in considering and establishing sectoral GHG budgets for construction and for transformative changes in the construction sector to meet national GHG emission reduction commitments.

Efficiency and renewability in energy conversion – A system perspective on policy objectives and instruments for climate change mitigation

The use of energy from renewable sources and improved efficiency throughout energy conversion, distribution and end-use are important means for mitigating climate change. This paper provides a novel exploration of the relationship between the system boundary in national greenhouse gas (GHG) inventories and policy incentives regarding technologies for GHG emission reduction, including the use of biomass, the use of heat from combined heat and power (CHP) production, industry waste heat, and energy recovery of waste. A novel generalisable applied method for applying a system perspective on a policy coherence analysis is another contribution from this paper. Major findings include the discovery that policies largely favour the use of biomass over technologies for energy efficiency, which does not adhere to the EU energy efficiency first principle. Also, although the EU largely promotes CHP production and high-efficiency CHP production, these technologies are largely opposed by Swedish policies. The following theoretical explanations for this are proposed: (1) The use of attributional GHG inventories for geographical areas induces the use of attributional climate policy objectives; and (2) The use of attributional climate policy objectives induces policies largely supporting the domestic use of technologies which potentially improve one’s own climate objective, and largely opposing the domestic use of technologies which potentially worsens one’s own climate objective, irrespective of the impact on global GHG emissions. An expansion of the current study including other policy and geographical areas is suggested for future research to further validate the generalisability of these outlined theoretical explanations. In conclusion, as the reduction of global GHG emissions is crucial for mitigating climate change, a shift from an attributional view in national GHG emission governance towards a consequential view is suggested for better efficacy in global GHG emissions reduction.

Incorporating ecological economics into engineering education

Engineering students require an education which facilitates the development not just of functional design of technological artefacts and processes, but they also need to be equipped to understand and engage with their wider implications and context. Consequently, as part of the formation of sustainability informed engineers, there is a clear necessity to integrate the socio-economic aspects of sustainability in order to posit technology in appropriate contextualised settings. The chemical engineering degree programme at University College Cork incorporates a strong emphasis on integrating the socio-economic dimension of sustainability within the programme. This paper focuses on ecological economics, and how it can connect with engineering and why it is important that engineering students receive a grounding in ecological economics. It outlines the content of a five-lecture series on ecological economics given to fifth-year chemical engineering students. This includes environmental aspects, such ecological limits analysis and the use of strategies, including economic, to move unsustainable natural resource use and emissions discharges to within their ecological limits. It explores social aspects and the critical barriers to transitioning to a sustainable economy, as well as the impact of ecological economics on engineering. Finally, three consecutive final year classes were surveyed to elicit their feedback on being taught ecological economics and to test the hypothesis that the inclusion of ecological economics appreciably enhances students’ ability to engage productively with sustainability and the UN Sustainable Development Goals (SDGs); a key accreditation and professional requirement for contemporary engineering graduates. Overall, most students enjoyed the material, stating that is of value to engineering students, and they provided a useful qualitative assessment of the content.

Assessing the environmental and downstream human health impacts of decentralizing cancer care.

1522 Background: Greenhouse gas emissions from healthcare are substantial and harm persons with cancer. Emissions from outpatient cancer care visits are not well described, nor are the downstream reduction in human harms that could be obtained through visit “decentralization” (telemedicine and local care when possible). Methods: This life-cycle assessment (LCA)-based study evaluated changes in emissions and downstream health harms associated with (1) telemedicine visits using retrospective observational analysis and (2) fully decentralized visits using counterfactual modeling. The retrospective observational cohort included persons receiving cancer care at Dana-Farber Cancer Institute (DFCI) and 20 affiliated facilities between 5/2015-12/2020. The main outcome was the adjusted per visit-day difference in emissions (in kilograms carbon dioxide equivalents: kgCO2e) between two periods: an in-person care period (5/2015-2/2020; “Pre”) and a telemedicine period (3/2020-12/2020; “Post”). Mixed effects log-linear model assessed emissions changes adjusted for age, sex, race, ethnicity, and cancer type, with random effects on person. The counterfactual model assessed emissions changes between actual in-person visits during the Pre period and a counterfactual with maximal decentralization. Visit-day eligibility for decentralization was obtained by categorizing appointments (e.g., clinician visit, infusion) as DFCI required, local care possible, or telemedicine possible. This cohort was matched to a national population diagnosed with cancer over the same period (Cancer in North America [CiNA] dataset) using mixed-effects linear modeling, through which annual changes in disability-adjusted life-years (DALY) from clinician visit decentralization were estimated using Eckelman’s mortality cost of carbon conversion. Results: There were123,890 unique patients in the DFCI cohort seen over 1.6 million visit-days (Pre N=110,180, Post N=61,691) at a median of 6 visit-days per patient (IQR 2, 15). An estimated 72,554,006 kgCO2e were within scope of the LCA emitted during the study period. In mixed-effects log-linear regression, the adjusted mean absolute reduction in per visit-day emissions between Pre and Post periods was 36.4 kgCO2e (95%CI 36.2,36.6), or a reduction of 81.3% (95%CI 80.8,81.7) compared to the baseline model. In the counterfactual decentralized care model of the Pre period, there was a relative emissions reduction of 33.1% (95%CI 32.9,33.3). When demographically matched to 10.3 million persons in the CiNA dataset, decentralized care would have reduced national emissions by 75.3 million kgCO2e annually; this corresponds to an estimated annual reduction of 15.0-47.7 DALYs. Conclusions: Employing decentralization through telemedicine and local care can substantially reduce emissions during cancer care delivery; this corresponds to a small reduction in human mortality.

How to control China's total amount of carbon emissions? An analysis of provincial allowance demands

Establishing a total amount control system for carbon emissions is crucial for China to achieve its carbon peak and neutrality targets. Given the heterogeneity among provinces, it is essential to consider provincial demands for carbon emission allowances (CEA) when allocating China's total amount target of carbon emissions. By identifying provincial preferences for different allocation criteria (equality, responsibility, capability, and efficiency), this study proposed a CEA allocation scheme that contributes to achieving China's 2030 carbon emission target with the least compromise among provinces. The results show that emission reduction efforts vary widely across provinces under any single-criterion scheme. Preferences for allocation criteria diverge among provinces, with a notable preference towards responsibility and equality. However, adhering to provincial expectations for CEA could jeopardize the attainment of national emission reduction target. The least-compromise allocation scheme integrates various criteria while weighting them differently: equality (0.42), responsibility (0.28), efficiency (0.16), and capability (0.14). Considering the varying pressure for emission reduction among provinces, it is vital to formulate differentiated policies and measures.

Challenges in Standardizing Global Emission Factors for Peatlands

Peatlands have a crucial role in the global carbon cycle, acting as significant carbon sinks, but become a significant source of greenhouse gas (GHG) emissions when peat extraction is taking place. This article presents a comprehensive overview of peatland ecosystems, emphasizing their classification across various climatic zones and the complex set of different characteristics that determine contribution to GHG emissions. Currently, inconsistency exists in definition of emission factors used between countries leading to varied approaches in estimating peatland emissions and posing significant challenges in the comparison and aggregation of global data on peat extraction related GHG. The aim of the study is to analyse the disparities in emission factors and calculation methodologies employed by different countries. Data from national GHG emission reports are submitted under the UNFCCC and the Kyoto Protocol. Emissions report data calculations and emission factors can be based either on nationally determined data or on data specified in the IPCC guidelines. Consequently, emission factor data for four countries - Latvia, Finland, Sweden and Germany - are collected and processed, which were compared with IPCC guideline data. The data were compared in two ways: by equating units of measurement and by modeling. The results show there is a pronounced difference between the emission factors of each country, however, all these factors are lower than the maximum values specified in the IPCC guidelines. It was also determined that comparing the total emission factors with the modeled results, no significant difference is observed between these results. The study concludes that emission factors are predetermined differently for each country, and it is not possible to specify the differences among assumptions for parameters included in the determination of the emission factors. The results suggest there is a need for development of more transparent accounting of emissions with regard to the diverse environmental and anthropogenic factors influencing peatland ecosystems. Factors like composition, depth of peat, water table levels, and local land-use practices further compound this variability in emission accounting. Addressing these challenges is crucial for enhancing the accuracy and reliability of GHG emission reporting under international frameworks like the United Nations Framework Convention on Climate Change and the Kyoto Protocol.

Unlocking bacterial potential to reduce farmland N2O emissions

Farmed soils contribute substantially to global warming by emitting N2O (ref. 1), and mitigation has proved difficult2. Several microbial nitrogen transformations produce N2O, but the only biological sink for N2O is the enzyme NosZ, catalysing the reduction of N2O to N2 (ref. 3). Although strengthening the NosZ activity in soils would reduce N2O emissions, such bioengineering of the soil microbiota is considered challenging4,5. However, we have developed a technology to achieve this, using organic waste as a substrate and vector for N2O-respiring bacteria selected for their capacity to thrive in soil6–8. Here we have analysed the biokinetics of N2O reduction by our most promising N2O-respiring bacterium, Cloacibacterium sp. CB-01, its survival in soil and its effect on N2O emissions in field experiments. Fertilization with waste from biogas production, in which CB-01 had grown aerobically to about 6 × 109 cells per millilitre, reduced N2O emissions by 50–95%, depending on soil type. The strong and long-lasting effect of CB-01 is ascribed to its tenacity in soil, rather than its biokinetic parameters, which were inferior to those of other strains of N2O-respiring bacteria. Scaling our data up to the European level, we find that national anthropogenic N2O emissions could be reduced by 5–20%, and more if including other organic wastes. This opens an avenue for cost-effective reduction of N2O emissions for which other mitigation options are lacking at present.