Comparison of Closed Chamber and Eddy Covariance Methods to Improve the Understanding of Methane Fluxes from Rice Paddy Fields in Japan

Role of BP-ANN in simulating greenhouse gas emissions from global aquatic ecosystems via carbon component-environmental factor coupling

Inland waters (IW), estuarine areas (EA), and offshore areas (OA) function as aquatic systems in which the transport of carbon components results in the release of greenhouse gases (GHGs). Interconnected subsystems exhibit a greater greenhouse effect than individual systems. Despite this, there is a lack of research on how carbon loading and its components impact GHG emissions in various aquatic systems. In this study, we analyzed 430 aquatic sites to explore trade-off mechanisms among dissolved organic carbon (DOC), particulate organic carbon, dissolved inorganic carbon (DIC), and GHGs. The results revealed that IW emerged as the most significant GHG source, possessing a comprehensive global warming potential (GWP) of 0.78 ± 0.08 (10-2 Pg CO2-ep ha-1 year-1) for combined carbon dioxide, methane, and nitrous oxide. This surpassed the cumulative potentials of EA and OA (0.35 ± 0.05 (10-2 Pg CO2-ep ha-1 year-1)). Additionally, structural equation modeling indicated that GHG emissions resulted from a combination of carbon component loading and environmental factors. DOC exhibited a positive correlation with GWPs when influenced by biodegradable DOC. Total alkalinity and pH influenced DIC, leading to elevated pCO2 in aquatic systems, thereby enhancing GWPs. Predictive modeling using backpropagation artificial neural networks (BP-ANN) for GWPs, incorporating carbon components and environmental factors, demonstrated a good fit (R2 = 0.6078, RMSEaverage = 0.069, p > 0.05) between observed and predicted values. Enhancing the estimation of aquatic region feedback to GHG changes was achieved by incorporating corresponding water quality parameters. In summary, this study underscores the pivotal role of carbon components and environmental factors in aquatic regions for GHG emissions. The application of BP-ANN to estimate greenhouse effects from aquatic regions is highlighted, providing theoretical and experimental support for future advancements in monitoring and developing policies concerning the influence of water quality on GHG emissions.

Assessing methane emissions from paddy fields through environmental and UAV remote sensing variables

Concerns about methane (CH4) emissions from rice, a staple sustaining over 3.5 billion people globally, are heightened due to its status as the second-largest contributor to greenhouse gases, driving climate change. Accurate quantification of CH4 emissions from rice fields is crucial for understanding gas concentrations. Leveraging technological advancements, we present a groundbreaking solution that integrates machine learning and remote sensing data, challenging traditional closed chamber methods. To achieve this, our methodology involves extensive data collection using drones equipped with a Micasense Altum camera and ground sensors, effectively reducing reliance on labor-intensive and costly field sampling. In this experimental project, our research delves into the intricate relationship between environmental variables, such as soil conditions and weather patterns, and CH4 emissions. We achieved remarkable results by utilizing unmanned aerial vehicles (UAV) and evaluating over 20 regression models, emphasizing an R2 value of 0.98 and 0.95 for the training and testing data, respectively. This outcome designates the random forest regressor as the most suitable model with superior predictive capabilities. Notably, phosphorus, GRVI median, and cumulative soil and water temperature emerged as the model's fittest variables for predicting these values. Our findings underscore an innovative, cost-effective, and efficient alternative for quantifying CH4 emissions, marking a significant advancement in the technology-driven approach to evaluating rice growth parameters and vegetation indices, providing valuable insights for advancing gas emissions studies in rice paddies.

The unexpected long period of elevated CH4 emissions from an inundated fen meadow ended only with the occurrence of cattail (Typha latifolia)

Drainage and agricultural use transform natural peatlands from a net carbon (C) sink to a net C source. Rewetting of peatlands, despite of high methane (CH4 ) emissions, holds the potential to mitigate climate change by greatly reducing CO2 emissions. However, the time span for this transition is unknown because most studies are limited to a few years. Especially, nonpermanent open water areas often created after rewetting, are highly productive. Here, we present 14 consecutive years of CH4 flux measurements following rewetting of a formerly long-term drained peatland in the Peene valley. Measurements were made at two rewetted sites (non-inundated vs. inundated) using manual chambers. During the study period, significant differences in measured CH4 emissions occurred. In general, these differences overlapped with stages of ecosystem transition from a cultivated grassland to a polytrophic lake dominated by emergent helophytes, but could also be additionally explained by other variables. This transition started with a rapid vegetation shift from dying cultivated grasses to open water floating and submerged hydrophytes and significantly increased CH4 emissions. Since 2008, helophytes have gradually spread from the shoreline into the open water area, especially in drier years. This process was periodically delayed by exceptional inundation and eventually resulted in the inundated site being covered by emergent helophytes. While the period between 2009 and 2015 showed exceptionally high CH4 emissions, these decreased significantly after cattail and other emergent helophytes became dominant at the inundated site. Therefore, CH4 emissions declined only after 10 years of transition following rewetting, potentially reaching a new steady state. Overall, this study highlights the importance of an integrative approach to understand the shallow lakes CH4 biogeochemistry, encompassing the entire area with its mosaic of different vegetation forms. This should be ideally done through a study design including proper measurement site allocation as well as long-term measurements.

Multiyear methane and nitrous oxide emissions in different irrigation management under long-term continuous rice rotation in Arkansas

Rice paddies are one of the major sources of anthropogenic methane (CH₄ ) emissions. The alternate wetting and drying (AWD) irrigation management has been shown to reduce CH₄ emissions and total global warming potential (GWP) (CH₄ and nitrous oxide [N₂ O]). However, there is limited information about utilizing AWD management to reduce greenhouse gas (GHG) emissions from commercial-scale continuous rice fields. This study was conducted for five consecutive growing seasons (2015-2019) on a pair of adjacent fields in a commercial farm in Arkansas under long-term continuous rice rotation irrigated with either continuously flooded (CF) or AWD conditions. The cumulative CH₄ emissions in the growing season across the two fields and 5 years ranged from 41 to 123 kg CH₄ -C ha^-1 for CF and 1 to 73 kg CH₄ -C ha^-1 for AWD. On average, AWD reduced CH₄ emissions by 73% relative to CH₄ emissions in CF fields. Compared to N₂ O emissions, CH₄ emissions dominated the GWP with an average contribution of 91% in both irrigation treatments. There was no significant variation in grain yield (7.3-11.9 Mg ha^-1 ) or growing season N₂ O emissions (-0.02 to 0.51 kg N₂ O-N ha^-1 ) between the irrigation treatments. The yield-scaled GWP was 368 and 173 kg CO₂ eq. Mg^-1 season^-1 for CF and AWD, respectively, showing the feasibility of AWD on a commercial farm to reduce the total GHG emissions while sustaining grain yield. Seasonal variations of GHG emissions observed within fields showed total GHG emissions were predominantly influenced by weather (precipitation) and crop and irrigation management. The influence of air temperature and floodwater heights on GHG emissions had high degree of variability among years and fields. These findings demonstrate that the use of multiyear GHG emission datasets could better capture variability of GHG emissions associated with rice production and could improve field verification of GHG emission models and scaling factors for commercial rice farms.

Recent Advances Toward Transparent Methane Emissions Monitoring: A Review

Given that anthropogenic greenhouse gas (GHG) emissions must be immediately reduced to avoid drastic increases in global temperature, methane emissions have been placed center stage in the fight against climate change. Methane has a significantly larger warming potential than carbon dioxide. A large percentage of methane emissions are in the form of industry emissions, some of which can now be readily identified and mitigated. This review considers recent advances in methane detection that allow accurate and transparent monitoring, which are needed for reducing uncertainty in source attribution and evaluating progress in emissions reductions. A particular focus is on complementary methods operating at different scales with applications for the oil and gas industry, allowing rapid detection of large point sources and addressing inconsistencies of emissions inventories. Emerging airborne and satellite imaging spectrometers are advancing our understanding and offer new top-down assessment methods to complement bottom-up methods. Successfully merging estimates across scales is vital for increased certainty regarding greenhouse gas emissions and can inform regulatory decisions. The development of comprehensive, transparent, and spatially resolved top-down and bottom-up inventories will be crucial for holding nations accountable for their climate commitments.

Environmental factors contributing to variations in CO2 flux over a barley-rice double-cropping paddy field in the Korean Peninsula

Understanding the CO₂ flux over agricultural crop fields is critical because the temporal cycle is driven by both ecological environment and anthropogenic change. We analyzed the net ecosystem exchange of CO₂ measured over a barley-rice double-cropping field using the eddy covariance method for 5 years. We conducted gap-filling based on u_*-threshold criteria and partitioned the net ecosystem exchange into gross primary production and respiration. The relative importance analysis of solar radiation, temperature, soil heat flux, soil water content, and vapor deficit revealed that solar radiation and temperature were the dominant contributors to net ecosystem exchange. The annual variation in the net ecosystem exchange followed a bimodal pattern driven by CO₂ uptake by both barley and rice, displaying two negative peaks in late April and mid-August. The elongation stages of the crops exhibited the highest flux. Gross primary production and respiration were closely related to solar radiation and nighttime temperature, respectively. The relative importance of the other environmental variables was affected by the cultivation season and irrigation water. In the period of rice cultivation, respiration was approximately 3 µmol m^-2 s^-1 higher during rice drainage than during the flooded period. The accumulated net ecosystem production was estimated to be 315 gC m^-2 and 349 gC m^-2 for the barley and rice growing periods, respectively, and 649 gC m^-2 for the annual total. These values are comparable with the results of other studies on barley-rice double-cropping fields.

The Fallow Period Plays an Important Role in Annual CH4 Emission in a Rice Paddy in Southern Brazil

Paddy fields are significant anthropogenic sources of methane (CH4) emissions. In southern Brazil, rice is grown in lowland flooded areas once a year, followed by a long fallow period. This study aimed to measure CH4 fluxes in a rice paddy field in southern Brazil during the rice-growing season of 2015/2016 and the following fallow period. The fluxes were estimated using the eddy covariance (EC) technique and soil chamber (SC). Diurnal and seasonal variations of CH4 fluxes and potential meteorological drivers were analyzed. The CH4 fluxes showed distinct diurnal variations in each analyzed subperiod (vegetative, reproductive, pre-harvest, no rice, and land preparation), characterized by a single-peak diurnal pattern. The variables that most influenced methane emissions were air and surface temperatures. In the growing season, the rice vegetative stage was responsible for most of the measured emissions. The accumulated annual emission estimated was 44.88 g CH4 m−2 y−1, being 64% (28.50 g CH4 m−2) due to the rice-growing season and 36% (16.38 g CH4 m−2) due to the fallow period. These results show the importance of including fallow periods in strategies to mitigate methane emissions in flood irrigated rice-growing areas.

Characteristics of methane emissions in the Living Water Garden in Chengdu City from 2012 to 2017

CH₄ flux measured by a portable chamber using an infrared analyzer was compared with the flux by static chamber measurement for CW at 13 different sites from May 2012 to May 2017 in the Living Water Garden (LWG) in Chengdu, Sichuan Province, China, over 4 timescales (daily, monthly, seasonal, and annual). During the measurement period, a total of 1443 data were collected. CH₄ fluxes were measured using the portable chamber method and the results showed that the annual mean and median CH₄ flux values in the LWG were 17.4 mg m^-2 h^-1 and 6.2 mg m^-2 h^-1, respectively, ranging from - 19.7 to 98.0 mg m^-2 h^-1. Cumulative CH₄ emissions for LWG ranged from - 0.17 to 0.86 kg m^-2 year^-1. Global warming potential (GWP, 25.7 kg CO_2eq m^-2 year^-1) was at a high level, which means that the LWG was a source of CH₄ emissions. Significant temporal variations on the 4 timescales were observed. And the asymmetry of measurement uncertainty of CH₄ flux increases with the timescale. Although the total mean CH₄ flux measured by the portable chamber method was 42.1% lower than that of the static chamber method, the temporal variation trends of CH₄ flux were similar. The uncertainty of CH₄ flux measured in portable chamber was more symmetrical than that in static chamber. These results suggest that the portable chamber method has considerable value as a long-term measurement method for CH₄ flux temporal variations.

Nitrous Oxide Emissions from Paddies: Understanding the Role of Rice Plants

: Paddies are a potential source of anthropogenic nitrous oxide (N2O) emission. In paddies, both the soil and the rice plants emit N2O into the atmosphere. The rice plant in the paddy is considered to act as a channel between the soil and the atmosphere for N2O emission. However, recent studies suggest that plants can also produce N2O, while the mechanism of N2O formation in plants is unknown. Consequently, the rice plant is only regarded as a channel for N2O produced by soil microorganisms. The emission of N2O by aseptically grown plants and the distinct dual isotopocule fingerprint of plant-emitted N2O, as reported by various studies, support the production of N2O in plants. Herein, we propose a potential pathway of N2O formation in the rice plant. In rice plants, N2O might be formed in the mitochondria via the nitrate-nitrite-nitric oxide (NO3-NO2-NO) pathway when the cells experience hypoxic or anoxic stress. The pathway is catalyzed by various enzymes, which have been described. So, N2O emitted from paddies might have two origins, namely soil microorganisms and rice plants. So, regarding rice plants only as a medium to transport the microorganism-produced N2O might be misleading in understanding the role of rice plants in the paddy. As rice cultivation is a major agricultural activity worldwide, not understanding the pathway of N2O formation in rice plants would create more uncertainties in the N2O budget.