Characterizing Spatiotemporal Dynamics of CH₄ Fluxes from Rice Paddies of Cold Region in Heilongjiang Province under Climate Change

A comprehensive review on methane's dual role: effects in climate change and potential as a carbon-neutral energy source

The unprecedented population and anthropogenic activity rise have challenged the future look up for shifts in global temperature and climate patterns. Anthropogenic activities such as land fillings, building dams, wetlands converting to lands, combustion of biomass, deforestation, mining, and the gas and coal industries have directly or indirectly increased catastrophic methane (CH4) emissions at an alarming rate. Methane is 25 times more potent trapping heat when compared to carbon dioxide (CO2) in the atmosphere. A rise in atmospheric methane, on a 20-year time scale, has an impact of 80 times greater than that of CO2. With increased population growth, waste generation is rising and is predicted to reach 6 Mt by 2025. CH4 emitted from landfills is a significant source that accounts for 40% of overall global methane emissions. Various mitigation and emissions reduction strategies could significantly reduce the global CH4 burden at a cost comparable to the parallel and necessary CO2 reduction measures, reversing the CH4 burden to pathways that achieve the goals of the Paris Agreement. CH4 mitigation directly benefits climate change, has collateral impacts on the economy, human health, and agriculture, and considerably supports CO2 mitigation. Utilizing the CO2 from the environment, methanogens produce methane and lower their carbon footprint. NGOs and the general public should act on time to overcome atmospheric methane emissions by utilizing the raw source for producing carbon-neutral fuel. However, more research potential is required for green energy production and to consider investigating the untapped potential of methanogens for dependable energy generation.

Rice Management Decisions Using Process-Based Models With Climate-Smart Indicators

Irrigation strategies are keys to fostering sustainable and climate-resilient rice production by increasing efficiency, building resilience and reducing Greenhouse Gas (GHG) emissions. These strategies are aligned with the Climate-Smart Agriculture (CSA) principles, which aim to maximize productivity whilst adapting to and mitigating climate change. Achieve such mitigation, adaptation, and productivity goals- to the extent possible- is described as climate smartness. Measuring climate smartness is challenging, with recent progress focusing on the use of agronomic indicators in a limited range of contexts. One way to broaden the ability to measure climate-smartness is to use modeling tools, expanding the scope of climate smartness assessments. Accordingly, and as a proof-of-concept, this study uses modeling tools with CSA indicators (i.e., Greenhouse Intensity and Water Productivity) to quantify the climate-smartness of irrigation management in rice and to assess sensitivity to climate. We focus on a field experiment that assessed four irrigation strategies in tropical conditions, Continuous Flooding (CF), Intermittent Irrigation (II), Intermittent Irrigation until Flowering (IIF), and Continuous soil saturation (CSS). The DNDC model was used to simulate rice yields, GHG emissions and water inputs. We used model outputs to calculate a previously developed Climate-Smartness Index (CSI) based on water productivity and greenhouse gas intensity, which score on a scale between−1 (lack of climate-smartness) to 1 (high climate smartness) the climate-smartness of irrigation strategies. The CSS exhibited the highest simulation-based CSI, and CF showed the lowest. A sensitivity analysis served to explore the impacts of climate on CSI. While higher temperatures reduced CSI, rainfall mostly showed no signal. The climate smartness decreasing in warmer temperatures was associated with increased GHG emissions and, to some extent, a reduction in Water Productivity (WP). Overall, CSI varied with the climate-management interaction, demonstrating that climate variability can influence the performance of CSA practices. We conclude that combining models with climate-smart indicators can broaden the CSA-based evidence and provide reproducible research findings. The methodological approach used in this study can be useful to fill gaps in observational evidence of climate-smartness and project the impact of future climates in regions where calibrated crop models perform well.

Study on the Water Supply and the Requirements, Yield, and Water Use Efficiency of Maize in Heilongjiang Province Based on the AquaCrop Model

Agricultural irrigation depends heavily on freshwater resources. Under the context of increasingly severe water shortages, studying the relationship among crop water requirements (ETc), actual crop evapotranspiration (ETa), irrigation water requirements (Ir), yield, and water use efficiency (WUE) would be beneficial to improve the agricultural application of irrigation water. Based on the daily data of 26 meteorological stations in Heilongjiang Province from 1960 to 2015, this study used the calibrated AquaCrop model to calculate the ETc, ETa, Ir, and yield of maize (Zea mays L.) in different hydrological years (extremely dry years, dry years, normal years, and wet years) along with WUE to evaluate the mass of yield produced per unit mass of crop evapotranspiration (ET) under rainfed and irrigated scenarios. The results showed that ETc and ETa decreased first and then increased from the west to the east during the four types of hydrological years. Ir exhibited a decreasing trend from the west to the east. Compared with the irrigation scenario, the rainfed scenario’s average yield only decreased by 2.18, 0.55, 0.03, and 0.05 ton/ha, while the WUE increased by 0.32, 0.4, 0.33, and 0.21 kg/m3 in the extremely dry years, dry years, normal years, and wet years, respectively. The results indicated that in the normal and wet years, the WUE was high in the central regions, and irrigation did not significantly increase yield; further, we determined that irrigation should not be considered in these two hydrological years in Heilongjiang Province. In the extremely dry and dry years, irrigation was necessary because it increased the yield, even though the WUE decreased. This study provides a theoretical basis for studying the regional irrigation schedule in Heilongjiang Province.

Spatiotemporal Analysis of Maize Water Requirement in the Heilongjiang Province of China during 1960–2015

Climate change will have a significant effect on crop water requirement (ETc). The spatial and temporal variations of water requirement of maize under climate change are essential elements when conducting a global water security assessment. In this paper, annual reference crop evapotranspiration (ET0) and the crop water requirement of maize were calculated by the single crop coefficient method. The crop water surplus deficit index (CWSDI) and coupling degree of ETc and effective precipitation (Pe) were calculated to analyze the relationship between ETc, ET0, and Pe. The result shows that maize average annual ET0, ETc, and precipitation were 552.97, 383.05, and 264.97 mm, respectively. Moreover, ET0, ETc, and Pe decreased by 3.28, 2.56, and 6.25 mm every decade from 1960 to 2015. The ETc decreased less than Pe did, which led to the decreasing of both CWSDI and the coupling degree of ETc and Pe. The tendency of ET0, ETc decreased first and then increased, while Pe and CWSDI increased first and then decreased, from west to east of the Heilongjiang Province. In addition, the highest ET0, ETc, and lowest CWSDI and Pe were found in the western part of Heilongjiang Province. This study indicated that even though the water deficit in the western region was alleviated and the water deficit in the eastern region grew gradually serious from 1960 to 2015, the drought situation in western Heilongjiang Province should still be taken seriously.

Emissions of CO2, CH4, and N2O Fluxes from Forest Soil in Permafrost Region of Daxing'an Mountains, Northeast China

With global warming, the large amount of greenhouse gas emissions released by permafrost degradation is important in the global carbon and nitrogen cycle. To study the feedback effect of greenhouse gases on climate change in permafrost regions, emissions of CO₂, CH₄, and N₂O were continuously measured by using the static chamber-gas chromatograph method, in three forest soil ecosystems (Larix gmelinii, Pinus sylvestris var. mongolica, and Betula platyphylla) of the Daxing’an Mountains, northeast China, from May 2016 to April 2018. Their dynamic characteristics, as well as the key environmental affecting factors, were also analyzed. The results showed that the flux variation ranges of CO₂, CH₄, and N₂O were 7.92 ± 1.30~650.93 ± 28.12 mg·m⁻²·h⁻¹, −57.71 ± 4.65~32.51 ± 13.03 ug·m⁻²·h⁻¹, and −3.87 ± 1.35~31.1 ± 2.92 ug·m⁻²·h⁻¹, respectively. The three greenhouse gas fluxes showed significant seasonal variations, and differences in soil CO₂ and CH₄ fluxes between different forest types were significant. The calculation fluxes indicated that the permafrost soil of the Daxing’an Mountains may be a potential source of CO₂ and N₂O, and a sink of CH₄. Each greenhouse gas was controlled using different key environmental factors. Based on the analysis of Q₁₀ values and global warming potential, the obtained results demonstrated that greenhouse gas emissions from forest soil ecosystems in the permafrost region of the Daxing’an Mountains, northeast China, promote the global greenhouse effect.

Effects of Different Types of Water and Nitrogen Fertilizer Management on Greenhouse Gas Emissions, Yield, and Water Consumption of Paddy Fields in Cold Region of China

Water management and nitrogen (N) fertilizers are the two main driving factors of greenhouse gas emissions. In this paper, two irrigation modes, controlled irrigation (CI) and flood irrigation (FI), and four nitrogen fertilizer levels (N0: 0, N1:,85, N2:,110, and N3:,135 kg·hm^-2) were set to study the effect of different irrigation modes and N fertilizer amount on greenhouse-gas emissions of paddy fields in cold region by using the static chamber-gas chromatograph method; yield and water consumption were also analyzed. The results showed that, compared with FI, CI significantly reduced CH₄ emissions by 19.42~46.94%, but increased N₂O emissions by 5.66~11.85%. Under the two irrigation modes, N fertilizers could significantly increase N₂O emissions, but the CH₄ emissions of each N treatment showed few differences. Compared with FI, appropriate N application under CI could significantly increase grain number per spike, seed-setting rate, and 1000-grain weight, thus increasing yield. Under the two irrigation modes, water consumption increased with the increase of N application rate, and the total water consumption of CI was significantly lower than that of FI. The global warming potential (GWP) of CI was significantly smaller than that of FI. The trend of GWP in each treatment was similar to that of CH₄. Through comprehensive comparison and analysis of water productivity (WP), gas emission intensity (GHGI), and the yield of each treatment, we found that CI+N2 treatment had the highest WP (2.05 kg·m^-3) and lowest GHGI (0.37 kg CO₂-eq·kg^-1), while maintaining high yield (10224.4 kg·hm^-2). The results of this study provide an important basis for guiding high yield, water-savings, and emission reduction of paddy fields in cold regions.