Measure Greenhouse Gas Emissions Research Articles

Clinician and health service interventions to reduce the greenhouse gas emissions generated by healthcare: a systematic review

ObjectiveTo synthesise the available evidence on the effects of interventions designed to improve the delivery of healthcare that reduces the greenhouse gas (GHG) emissions of healthcare.DesignSystematic review and structured synthesis.Search...

Exploring the Impact of Alternate Wetting and Drying and the System of Rice Intensification on Greenhouse Gas Emissions: A Review of Rice Cultivation Practices

Rice provides ~20% of human dietary energy and, for many people, a similar share of their protein. Rice cultivation, however, produces significant greenhouse gas (GHG) emissions, comparable to those from the aviation sector. The main GHG from rice production is methane, mostly a result of conventional rice cultivation (CRC) keeping rice fields continuously flooded during the crop cycle. There is extensive evidence that alternate wetting and drying (AWD) of rice fields substantially reduces methane emissions. AWD is one component of the System of Rice Intensification (SRI), an agroecological approach to the management of plants, water, soil, and nutrients. This article reviews field studies measuring GHG emissions associated with the adoption of AWD and SRI. The review confirms that both AWD and SRI offer substantial reductions in methane emissions per hectare compared with CRC. These benefits are, however, partly offset by increases in emissions of nitrous oxide and carbon dioxide. The studies also show that SRI (but not AWD) improves yield and therefore further reduces GHG emissions per kg of rice. The review concludes that while both AWD and SRI substantially reduce emissions per hectare and per kilogram of rice, SRI can simultaneously contribute to food security while addressing the drivers of climate change. Further investigation of carbon emissions and sequestration under different rice cultivation methods is needed to strengthen the evidence base.

Q-commerce or E-commerce? A systematic state of the art on comparative last-mile logistics greenhouse gas emissions literature review

PurposeThe purpose of this study is to systematically review available state-of-the-art literature on comparative studies on Quick Commerce (Q-commerce) and E-commerce and their greenhouse gas (GHG) emissions.Design/methodology/approachThe literature survey methodology is based on the funneling approach of Kitchenham (2004), where results are obtained according to inclusion and exclusion criteria. The literature review methodology used for this study covers the period from 2016 to 2022. The areas considered for the survey are operations, logistics and supply chain network design for the distribution of goods in e-business. After deciding on the criteria, a total of 140 articles were extracted from 9 journal articles that study e-commerce and environmental emissions.FindingsThe result of this study reveals that GHG emissions from both modes of shopping depend on various parameters such as speed of delivery, last-mile depot locations, logistics and vehicle efficiency, customers’ order patterns and average basket size. Furthermore, the findings also highlight the difference between Q-commerce and E-commerce supply chain networks.Research limitations/implicationsThis study only accounts for GHG emissions from logistics activities, but there are other sources of GHG emissions in the overall supply chain that are not taken into consideration. Supply chain/business analysts in Q-commerce companies might refer the findings from this study to measure GHG emissions from their operations.Originality/valueThis is the first study in the Q-commerce field that uses a structured approach to find relevant literature from the years 2016 to 2022 and focuses on GHG emission measurement.

The SOLAR-HRS New High-Resolution Solar Spectra for Disk-Integrated, Disk-Center, and Intermediate Cases

The solar spectrum at the top of the atmosphere contains crucial data for solar physics, astronomy, and geophysics. Accurately determining high-resolution solar reference spectra, whether they are disk-integrated, disk-center, or intermediate cases, represents a new challenge and is of primary importance for all applications where spectral solar radiation needs to be evaluated. These spectra are also essential for interpreting remote sensing measurements that rely on sunlight, such as those obtained by Earth observation satellites or spacecraft exploring other planets. This paper lays a foundation for the implementation of multiple new solar irradiance reference spectra that have high resolution and are representative of solar minimum conditions. We developed the SOLAR high-resolution extraterrestrial reference spectra (SOLAR-HRS disk-integrated spectra) by normalizing high-spectral-resolution solar line data to the absolute irradiance scale of the SOLAR-ISS reference spectrum. The resulting one-of-a-kind SOLAR-HRS disk-integrated spectrum has a spectral resolution varying between 0.001 and 1 nm in the 0.5–4400 nm wavelength range. We also implemented a new high-resolution solar spectrum at the disk-center, covering a range of 650–4400 nm with a spectral resolution of 0.001 to 0.02 nm. We further expanded our analysis by producing several solar spectra for ten different solar view angles ranging from μ = 0.9 to μ = 0.05 (SOLAR-HRS intermediate cases). Finally, we developed new Merged Parallelised Simplified ATLAS spectra (MPS-ATLAS) based on solar modeling with Kurucz and Vald3 solar linelists for both the disk-integrated and disk-center spectra. One of the objectives of implementing all these new solar spectra is to fulfill the requirements of the MicroCarb space mission, which focuses on measuring greenhouse gas emissions. The solar data of this study are openly available.

Paddock-scale carbon and greenhouse gas budgets in the first year following the renewal of an intensively grazed perennial pasture

Pasture renewal is an important tool commonly used by land managers to maintain a healthy productive pasture sward that can be used for grazing by animals or harvesting. However, there have been few assessments of the impact of pasture renewal on greenhouse gas (GHG) emissions, particularly in grazed pastures. We investigated how pasture renewal impacted the carbon (C), nitrous oxide (N2O) and GHG budgets of an intensively managed rotationally grazed New Zealand pasture by comparing adjacent paddocks with one undergoing pasture renewal. The eddy covariance technique was used to measure carbon dioxide (CO2), N2O and methane (CH4) fluxes which were coupled to measurements and estimates of non-gaseous C flows to calculate the net ecosystem carbon balance and total GHG budget. We measured GHG emissions directly due to pasture renewal of 695 g CO2-eq m-2 during the 66 days between herbicide application and the first grazing of the new pasture sward. Using an adjacent paddock as a control, the net effect of pasture renewal was 358 g CO2-eq m-2, primarily due to an additional grazing event in the non-renewed pasture and the associated CO2 and CH4 emissions associated with digestion of the pasture by the ruminant animals. The pasture renewal emissions were primarily due to C loss with increased N2O emissions accounting for only 10% of total GHG emissions during the renewal period. Total GHG emissions were 2017 g CO2-eq m-2 y-1 for the first year (before pasture renewal), and 1452 and 1894 g CO2-eq m-2 y-1 for the non-renewed and renewed pastures, respectively, in the second (renewal) year. The only significant difference was between the first year and the non-renewed pasture in the second year. We concluded that pasture renewal increased C loss, N2O emissions and total GHG emissions during the renewal period, but when extended to the annual timescale, the effect was insignificant compared to interannual variability.

Mandatory Reporting of Emissions to Achieve Net-Zero Health Care

(N Engl J Med. 2022;387:2469–2476) Threats to human health from climate instability include food and water shortages, heat, modified disease-vector ranges and active seasons, wildfires, and severe weather-related events, all of which have the potential to disrupt health care delivery as well. With awareness of the contribution of greenhouse gasses and toxic emissions by the health care sector—~8.5% of emissions in the United States and 5% globally—many health care systems are prioritizing initiatives to achieve “net zero.” This refers to individual institution-led structures that support offsetting the release of greenhouse gas emissions by providing the means to neutralize their effect on the atmosphere. While many government organizations and consulting bodies to health care call for pledges to reduce greenhouse gas emissions, voluntary initiatives will fall short of net-zero health care goals. A consensus is growing for the need to develop a standardized metric for reporting, promoting accountability, quantifying progress, and recognizing best practices. It is recommended that all health care delivery organizations (HCOs)—all inpatient, outpatient, residential, and support services—be required to report and measure greenhouse gas emissions, in step with the climate goals of other leading organizations to achieve net-zero emissions over the coming decades.

Greenhouse gas emissions embodied in electric vehicle charging infrastructure: a method and case study of Georgia, US 2021–2050

Electric vehicle (EV) charging infrastructure buildout is a major greenhouse gas (GHG) mitigation strategy among governments and municipalities. In the United States, where petroleum-based transportation is the largest single source of GHG emissions, the Infrastructure Investment and Jobs Act of 2021 will support building a national network of 500 000 EV charging units. While the climate benefits of driving electric are well established, the potential embodied climate impacts of building out the charging infrastructure are relatively unexplored. Furthermore, ‘charging infrastructure’ tends to be conceptualized in terms of plugs and stations, leaving out the electrical and communications systems that will be required to support decarbonized and efficient charging. In this study, we present an EV charging system (EVCS) model that describes the material and operational components required for charging and forecasts the scale-up of these components based on EV market share scenarios out to 2050. We develop a methodology for measuring GHG emissions embodied in the buildout of EVCS and incurred during operation of the EVCS, including vehicle recharging, and we demonstrate this model using a case study of Georgia (USA). We find that cumulative GHG emissions from EVCS buildout and use are negligible, at less than 1% of cumulative emissions from personal light duty vehicle travel (including EV recharging and conventional combustion vehicle driving). If an accelerated EVCS buildout were to stimulate a faster transition of the vehicle fleet, the emissions reduction of electrification will far outweigh emissions embodied in EVCS components, even assuming relatively high carbon inputs prior to decarbonization.

Accounting for Carbon Emissions—Current State of Sustainability Reporting Practice under the GHG Protocol

Climate-related reporting has become an integral part of firms’ disclosure. In this context, firms’ greenhouse gas (GHG) emissions are of major importance to stakeholders and management. For measuring GHG emissions, a global standard has been established with the GHG Protocol. This standard contains an important accounting policy option that significantly affects firms’ reported emissions by allowing them to use different consolidation approaches: the equity share, operational control, and financial control approach. However, there is limited evidence on firms’ use of these approaches, resulting in a lack of foundation for discussing the approaches’ sufficiency to support achieving environmental sustainability. Therefore, this paper aims to close this research gap by empirically investigating the approaches’ relevance using 16,604 firm-year observations between 2009 and 2019. We demonstrate that the operational control approach is used by most firms and that its predominance substantially increased during the last decade. However, the predominant use of the operational control approach is not fully compatible with societal and political sustainability goals as expressed in recent sustainability regulations. Therefore, policy makers need to critically assess whether current GHG reporting supports achieving their goals. Furthermore, we develop a research agenda to encourage future researchers to contribute to improvements in GHG reporting.

Pivoting to suppliers’ emissions

Apple declared 2 years ago that it had achieved carbon neutrality—a balance between carbon emitted and carbon absorbed—across its corporate operations. The claim appeared to position the tech giant as a leader among the many companies hoping to make the same announcement by 2050 as signatories to the Paris climate accords. Most companies realize, however, that corporate operations are only one source of their carbon emissions. Every Apple iPhone, iPad, Apple Watch, and Apple TV—indeed, every product the company sells—has a carbon footprint that is not figured into its claims regarding in-house activities. This leaves a lot out. By some estimates , as much as 80% of emissions associated with a company’s products, a measurement known as product carbon footprint (PCF), occur elsewhere along its supply chain. Industry efforts to measure greenhouse gas emissions date back to 1998, when a standard known as the Greenhouse Gas Protocol was introduced by

Measuring Greenhouse Gas Emissions from Point Sources with Mobile Systems

The traditional least squares method for the retrieval of CO2 emissions from CO2 emission sources is affected by the nonlinear characteristics of the Gaussian plume model, which leads to the optimal estimation of CO2 emissions easily falling into local minima. In this study, ACA–IPFM (ant colony algorithm and interior point penalty function) is proposed to remedy the shortcomings of the traditional least squares method, which makes full use of the global search property of the ant colony algorithm and the local exact search capability of the interior point penalty function to make the optimal estimation of CO2 emissions closer to the global optimum. We evaluate the errors of several parameters that are most likely to affect the accuracy of the CO2 emission retrieval and analyze these errors jointly. These parameters include wind speed measurement error, wind direction measurement error, CO2 concentration measurement error, and the number of CO2 concentration measurements. When the wind speed error is less than 20%, the inverse error of CO2 concentration emission is less than 1% and the uncertainty is less than 3%, when the wind direction error is less than 55 degrees, the inverse error is less than 1% and the uncertainty is less than 3%, when the CO2 concentration measurement error is less than 10%, the inverse error is less than 1% and the uncertainty is less than 3.3%, and when the measurement quantity is higher than 60, the inverse error is less than 1% and the uncertainty is less than 3%. In addition, we simulate the concentration observations on different paths under the same conditions, and invert the CO2 emissions based on these simulated values. Through the retrieval results, we evaluate the errors caused by different paths of measurements, and have demonstrated that different paths are affected by different emission sources to different degrees, resulting in different inversion accuracies for different paths under the same conditions in the end, which can provide some reference for the actual measurement route planning of the mobile system. Combined with the characteristics of the agility of the mobile system, ACA–IPFM can extend the monitoring of CO2 emissions to a wider area.

Deficit irrigation impacts on greenhouse gas emissions under drip-fertigated maize in the Great Plains of Colorado.

Precise water and fertilizer application can increase crop water productivity and reduce agricultural contributions to greenhouse gas (GHG) emissions. Regulated deficit irrigation (DI) and drip fertigation control the amount, location, and timing of water and nutrient application. Yet, few studies have measured GHG emissions under these practices, especially for maize (Zea mays L.). The objective was to quantify N2 O and CO2 emission from DI and full irrigation (FI) within a drip-fertigated maize system in northeastern Colorado. During two growing seasons of measurement, treatments consisted of mild, moderate, and extreme DI and FI. Deficit irrigation was managed based on growth stage so that full evapotranspiration (ET) was met during the yield-sensitive reproductive stage, but less than full crop ET was applied during the late vegetative and maturation growth stages. In the first year, mild DI (90% ET) reduced N2 O emissions by 50% compared with FI. In the second year, compared with FI, moderate DI (69-80% ET) reduced N2 O emissions by 15%, and extreme DI (54-68% ET) reduced N2 O emissions by 40%. Only extreme DI in the second year significantly reduced CO2 emissions (by 30%) compared with FI. Mild DI reduced yield-scaled emissions in the first year, but moderate and extreme DI had similar yield-scaled emissions as FI in the second year. The surface drip fertigation resulted in total GHG emissions that were one-tenth of literature-based measurements from sprinkler-irrigated maize systems. This study illustrates the potential of DI and drip fertigation to reduce N2 O and CO2 emissions in irrigated cropping systems.

Emission factors for Vietnamese beef cattle manure sun-drying and the effects of drying on manure microbial community.

Livestock manure and its management are significant sources of greenhouse gas (GHG). In most Southeast Asian countries, the current GHG emissions are estimated by the Intergovernmental Panel on Climate Change (IPCC) Tier 1 approach using default emission factors. Sun-drying is the dominant manure treatment in Vietnam, and in this study, we measured GHG emissions during manure drying using a chamber-based approach. Results show the emission factors for CH4 and N2O were 0.295 ± 0.078 g kg-1 volatile solids (VS) and 0.132 ± 0.136 g N2O-N kg-1 Ninitial, respectively. We monitored the total bacterial/archaeal community using 16S rRNA gene amplicon sequencing and measured the abundance of functional genes required for methanogenesis (mcrA), nitrification (amoA) and denitrification (nirK, nirS and nosZ) processes. Methane emission occurred only at the beginning of the drying process (days 1 to 3). The results of amplicon sequencing indicated that the relative abundance of methanogens also decreased during this period. Although some nitrification activity was detected, there was no significant N2O emission. These findings well describe the manure management system in south Vietnam and the GHG emission from this manure category, paving the way for higher Tier estimations using country-specific values.

Greenhouse Gas Emissions Response to Fertilizer Application and Soil Moisture in Dry Agricultural Uplands of Central Kenya

In sub-Saharan Africa, agriculture can account for up to 66% of anthropogenic greenhouse gas (GHG) emissions. Unfortunately, due to the low number of studies in the region there is still much uncertainty on how management activities can affect these emissions. To help reduce this uncertainty, we measured GHG emissions from three maize (Zea mays) growing seasons in central Kenya. Treatments included: (1) a no N application control (C); (2) split (30% at planting and 70% 1 month after planting) mineral nitrogen (N) applications (Min—100 kg N ha−1); (3) split mineral N + irrigation (equivalent to 10 mm precipitation every three days—MI); (4) split mineral N + 40 kg N ha−1 added as manure (MM—total N = 140 kg ha−1); and (5) split mineral + intercropping with faba beans (Phaseolus vulgaris—MB). Soil CO2 fluxes were lower in season 1 compared to seasons 2 and 3 with fluxes highest in Min (p = 0.02) in season 2 and lowest in C (p = 0.02) in season 3. There was uptake of CH4 in these soils that decreased from season 1 to 3 as the mean soil moisture content increased. Cumulative N2O fluxes ranged from 0.25 to 2.45 kg N2O-N ha−1, with the highest fluxes from MI during season 3 (p = 0.01) and the lowest from C during season 1 (p = 0.03). The average fertilizer induced emission factor (0.36 ± 0.03%) was roughly one-third the default value of 1%. Soil moisture was a critical factor controlling GHG emissions in these central Kenya highlands. Under low soil moisture, the soils were CH4 sinks and minimal N2O sources.

Assessing the spatial and temporal variability of greenhouse gas emissions from different configurations of on-site wastewater treatment system using discrete and continuous gas flux measurement

Abstract. Global emissions linked to wastewater treatment are estimated to account for up to 1.5 % of total greenhouse gas (GHG) emissions globally. However, few studies have measured GHG emissions from domestic on-site treatment systems (DWWTSs) directly. In this study, two DWWTSs were monitored for 446 d and > 42 000 gas flux measurements were conducted using both discrete spot measurements and continuous flux chamber deployments. The observed GHG fluxes from biological activity in the soil and water phase were found to be highly spatially and temporally variable and correlated to environmental factors, water usage patterns and system design. In total, the results show that a septic tank discharging effluent into a well-designed soil treatment unit is estimated to emit a net 9.99 kg-CO2eq.cap-1yr-1, with approximately 63 %, 27 % and 10 % of the total CO2-equivalent net emissions in the form of CO2, CH4 and N2O, respectively. Emissions from the septic tank surface contributed over 50 % of total emissions and tended to be strongly underestimated by one-off discrete measurements, especially when episodic ebullitive events are to be considered. Fluxes from the soil treatment unit (STU) stemmed from both the soil surface and the vent system. Soil fluxes were mostly influenced by temperature but peaked regularly under conditions of rapidly changing soil water content. Vent fluxes were mostly governed by effluent, quality and a low number of high-emission events were responsible for the majority of total observed vent emissions. Owing to the strong overall spatial and temporal heterogeneity of observed fluxes from DWWTSs across all modules, future studies should focus on continuous deployments of a number of flux chambers over discrete measurements to accurately assess GHG emissions from on-site systems. This study also provided insights into managing GHG emissions from DWWTSs by different system configuration design, as well as indicating that the current IPCC emission factors for CH4 and N2O significantly overestimate emissions for on-site wastewater treatment systems.

Sensors and Methods for Measuring Greenhouse Gas Emissions from Different Components of Livestock Production Facilities

Greenhouse gas monitoring on a broader scale is necessary to ensure that a cap-and-trade system is effective, reduces measurement uncertainty, and detects fraudulent or illegal activities. The recent strict air quality regulation in livestock production facilities has accelerated the need for accurate on-farm determination of greenhouse gas (GHG) emission rates (ERs) from livestock operations in the United States under a wide range of production, management, and climate conditions. The estimation of GHG emissions from different ground-level sources or at a property line is a very complicated process, and such measurements require multidirectional expertise including engineering, micrometeorology, agronomy, applied physics, and chemistry. Accurate measurement of gaseous concentration from an emitting source is a prerequisite and of paramount importance for estimating emissions rates (ERs) using any micro-meteorological and sampling device-based method. This paper provides an overview of the state-of-the-art sensors and analyzers used to measure GHG concentrations. Sensor and analyzer selection and their performance in the laboratory and field were discussed. In addition, protocols for data quality control (QC) and quality assurance (QA) when deploying sensors in the area for long-term use were also discussed. In addition, the preparation of measurement systems, coupling of air samplers with sensing systems for measuring gaseous concentrations, and uncertainties inherent to such measurement methods as a whole to estimate ERs were discussed in this paper.

Impact of organic fertilizer substitution and biochar amendment on net greenhouse gas budget in a tea plantation

Tailoring agricultural practices to enhance the soil carbon (C) stock is seen as a promising mitigation tactic to offset greenhouse gas (GHG) emissions in croplands. Tea plantations are not only the important part of economic industry but also one of the crucial agricultural sources of non-carbon dioxide emissions. Although many studies have measured GHG emissions from tea plantations, it remains unknown about the effect of knowledge-based mitigation options on the entire C budget from Chinese rapidly expanding tea plantations. Thus, we carried out a 2-year field trial to provide an insight into the influence of organic fertilizer substitution for synthetic fertilizer and biochar amendment on net ecosystem carbon budget (NECB), net greenhouse gas budget (NGB), and yield-scaled greenhouse gas intensity (GHGI) from a subtropical tea plantation. Results showed that when averaged a 2-year experimental period, both full organic substitution and biochar amendment contributed significantly to the increment in NECB, mainly due to the enhanced soil organic C content in the tea field. Compared with the conventional farm practice, the application of full organic substitution can induce a 52% decrease in both NGB and GHGI. Regardless of fertilizer type, both NGB and GHGI were negative and 2.4 times lower in the treatments with biochar amendment relative to the control. In addition to their roles in maintaining soil health and alleviating soil acidification, our results suggest that organic fertilizer substitution and biochar addition may achieve low carbon development for tea plantations. Our findings will inform efforts to implement and evaluate these tailored mitigation options in tea plantations at a national scale.

How digital technologies can reduce greenhouse gas emissions in the energy sector's legacy assets

The global community is increasingly committed to transitioning to green energy technologies. However, while the percentage of the worldʼs energy coming from renewables is growing, the absolute amount of energy delivered to the global marketplace in the form of fossil fuels is also getting bigger, causing the International Energy Agency to recently declare that “it is too soon to see a rapid decline of oil.” This realization carries with it some sobering perspective about what needs to be done by the energy industry to mitigate climate change. Based on a keynote address delivered at the United Nations’ “Resource Management Week 2021” conference, this viewpoint argues that, in tandem to sowing the seeds of tomorrow's renewable energy systems, we also need to reduce the emissions from the systems that we have right now because the evidence in front of us strongly suggests that these legacy energy sources will continue to be around for the short- to medium-term future. To this end, this paper highlights four digital technological developments that have the potential to significantly help the oil & gas industry to make progress on this front: (1) continuing the industry's journey to “smartness,” (2) edge computing, (3) the emergence of global data standards for measuring greenhouse gas emissions, and (4) improving the efficiency of digital infrastructure.

A purposeful approach for measuring greenhouse gas emissions of material flow accounts for the accomplishment of territorial sustainable development and cultural economy goals on climate. The case of the Basque Country

This study aims at developing a purposeful approach for estimating greenhouse gas (GHG) emissions and its possible use to recreate alternative scenarios that might potentially facilitate the attainment of the material productivity (MP) ratio needed for achieving territorial sustainable development (SDGs) and circular economy goals on climate. The propounded method associates these two key concepts (GHG-MP) with the domestic material consumption (DMC) and international trade of materials, including product life cycle emissions in the overarching GHG total estimation. Developed utilizing the United Nations Framework Convention on Climate Change (UNFCCC) and diverse data, linked to the suggested scheme, from the Basque Country (Spain), this work also relies its scientific foundation upon leading literature in this field to align territorial models of production and consumption with a more localized measurement of GHG emissions. According to its results, the emissions estimated allow advising more contextualized scenarios for the potential achievement of local MP target indicator, when expressed as the amount of economic output―based on gross domestic product (GDP)—generated per unit of materials consumed and traded―in terms of DMC. From a theoretical perspective, this work contributes to the local strategic management of circular economy research and 2030 Agenda, particularly on the subject of measuring progress in the achievement of territorial climate and circular economy goals. From a utilitarian perspective, the findings comprise promising implications for both multilevel policy makers and public/private organizations that further sustainable development and actions against climate change.

Emission factors and global warming potential as influenced by fertilizer management for the cultivation of rice under varied growing seasons

Greenhouse gas (GHG) emissions from paddy fields are intensified during rice production, and are generally reported based on single or double cropping. It needs to be known how emission factors, GHG emission patterns, and global warming potential are affected by growing three rice crops yearly under the principle of integrated plant nutrient system fertilization (IPNSF). Cowdung and vermicompost were used as IPNSF and compared with commercial fertilization alone. A static close chamber technique was used to measure GHG emissions. The peak periods of CH4 emissions were 20–37, 22–42, and 19–38 days after transplanting during dry, wet, and premonsoon seasons, respectively. The use of cow dung significantly enhanced total N2O, CH4, and CO2 fluxes by 5–10%, 15–23%, and 9–20%, respectively, compared to vermicompost. CH4 emissions for each kg grain production were 39–80, 45–63, and 43–57 gm in the dry, premonsoon, and wet seasons, respectively. Vermicompost significantly reduced CH4, CO2, and N2O fluxes by 13–19%, 17–21%, and 4–9%, respectively, along with a reduction in GHG emission factors by 8–17% and global warming potential by 13–17% compared to cow dung. Moreover, vermicompost and cow dung significantly improved rice grain yields in all three growing seasons compared to commercial fertilizer alone. In conclusion, the use of vermicompost as an IPNSF could be a viable technique for improving grain yield and for reducing GHG emissions from paddy fields during year-round rice cultivation.

APPLICATION OF THE KOLMOGOROV-SMIRNOV TEST TO COMPARE GREENHOUSE GAS EMISSIONS OVER TIME

The national inventories of greenhouse gas (GHG) emissions, which are periodically prepared by countries that signed the Climate Change Convention, compute emissions from anthropogenic sources among them agricultural activities. The protocols established within the scope of the International Panel on Climate Change (IPCC) make it possible to estimate these emissions. These protocols use standard emission factors that vary according to the characteristics of the monitored activities and only scientific research, published in journals of recognized quality, can establish other local factors. Brazilian researchers carry out experiments to measure GHG emissions from agricultural activities, aiming to calculate specific parameters for the national climatic and management conditions. These field experiments are complex, costly, with a limited number of repetitions and, eventually, high natural variability. Often, these limitations result in the inability of the analysis of variance (ANOVA) to identify differences between treatments. The objective of this work is to present the non-parametric Kolmogorov-Smirnov (KS) test as an alternative to compare the effect of flooded irrigation management on methane (CH4) emission throughout the rice crop cycle. We present a case study in which ANOVA produced non-significant results for the adjustment of the model while the KS identified the emission curves as significantly different. The KS test could be adapted, via the SAS NPAR1WAY routine, to compare events with responses over time, such as methane emissions in flooded rice, resulting in test values and graphs that are easy to understand and interpret.