Diurnal pattern of nitrous oxide emissions from a sewage-enriched river : references to IPCC indirect emission factor

Poster Sessio

Managing urban development could halve nitrogen pollution in China

Halving nitrogen pollution is crucial for achieving Sustainable Development Goals (SDGs). However, how to reduce nitrogen pollution from multiple sources remains challenging. Here we show that reactive nitrogen (Nr) pollution could be roughly halved by managed urban development in China by 2050, with NH3, NOx and N2O atmospheric emissions declining by 44%, 30% and 33%, respectively, and Nr to water bodies by 53%. While rural-urban migration increases point-source nitrogen emissions in metropolitan areas, it promotes large-scale farming, reducing rural sewage and agricultural non-point-source pollution, potentially improving national air and water quality. An investment of approximately US$61 billion in waste treatment, land consolidation, and livestock relocation yields an overall benefit of US$ 245 billion. This underscores the feasibility and cost-effectiveness of halving Nr pollution through urbanization, contributing significantly to SDG1 (No poverty), SDG2 (Zero hunger), SDG6 (Clean water), SDG12 (Responsible consumption and production), SDG14 (Climate Action), and so on

Source_data.xlsx

Aquaculture systems are expected to act as potential hotspots for nitrous oxide (N2O) emissions, largely attributed to substantial nutrient loading from aquafeed applications. However, the specific dynamics and contributions of N2O fluxes from these systems to the global emissions inventory are not well characterized due to limited data. This study delves into the N2O flux patterns across 127 freshwater systems to elucidate the role of aquaculture ponds and lakes/reservoirs in the N2O emission landscape. Our findings reveal that the average N2O flux from aquaculture ponds, at 28.73 μg N2O m‒2 h‒1, is markedly elevated compared to that from lakes/reservoirs, which average 15.65 μg N2O m‒2 h‒1. This translates to an increase of 3.63 and 3.05 times, respectively, over their non-aquaculture counterparts. Smaller aquaculture ponds, in particular, stand out as significant N2O emission hotspots, disproportionately emitting higher N2O fluxes relative to their area, a result of both elevated nutrient concentrations and more vigorous biogeochemical cycles. By integrating data from 40 published literature with our field measurements, we estimated China's freshwater aquaculture contributes 9,562 ± 3,061 Mg N2O per year (an increase of 35% from 2003 to 2022), equivalent to 25.2% of total N2O emissions from China’s inland water. After subtracting background emissions from natural water bodies, the net N2O emissions arising from aquaculture in China freshwater reach as high as 7,589 ± 2,409 Mg N2O per year, highlighting the significant impact of in situ aquaculture as a hotspot for freshwater N2O fluxes. In the context of the rapid global expansion of freshwater aquaculture, our findings underscore the critical need to factor in aquaculture's contribution to global N2O emissions from inland water bodies and its implications for achieving a low-carbon future.</p

shallow water systems denitrification

<p><b>denitrification and Water-periphytic biofilm-sediment properties</b></p

Wetlands.xlsx

Fig.1-Fig.7 data source, How do variations of constructed wetland affect nutrient discharge: resolution from a conceptual model and implications to water quality management

On the Determination of the Output Power in Mono/Multicrystalline Photovoltaic Cells

In the present work, two artificial intelligence-based models were proposed to determine the output power of two types of photovoltaic cells including multicrystalline (multi-) and monocrystalline (mono-). Adaptive neuro-fuzzy inference system (ANFIS) and Least-squares support vector machine (LSSVM) are applied for the output power calculations. The estimation results are very close to the actual data based on graphical and statistical analysis. The coefficients of determination (R2) of monocrystalline cell output power for LSSVM and ANFIS models are as 0.997 and 0.962, respectively. Additionally, multicells have R2 values of 0.999 and 0.995 for LSSVM and ANFIS, respectively. The acceptable values for R2 and various error parameters prove the accuracy of suggested models. The visualization of these comparisons clarifies the accuracy of suggested models. Additionally, the proposed models are compared with previously published machine learning methods. The accurate performance of proposed models in comparison with others showed that our models can be helpful tools for the estimation of output power. Moreover, a sensitivity analysis for the effects of inputs parameters on output power has been employed. The sensitivity output shows that light intensity has more on output power. The outcomes of this study provide interesting tools which have potential to apply in different parts of renewable energy industries

Evaluation and Dynamic Evolution of the Total Factor Environmental Efficiency in China’s Mining Industry

The mining industry plays an extremely important strategic role in China’s economic and social development. In the new era of pursuing circular/green/efficient development, the evaluation of the total factor environmental efficiency (TFEE) of China’s mining industry is essential for alleviating resource waste and environmental pollution. The Epsilon-Based Measure (EBM) model effectively solves the shortcomings of radial and non-radial DEA models. In addition, the Malmquist–Luenberger (ML) index can measure the dynamic change of efficiency value. Combining the EBM model and the ML productivity index, this paper evaluates the TFEE from the static and dynamic perspective in China’s 31 provincial mining industries over the period 2007–2016. The Theil index is employed to reveal the root of the overall provincial TFEE gap (OGTFEE) in China’s mining industry. The results show that the average total factor static environmental efficiency (TFSEE) of China’s provincial mining industry exhibits a low score of 0.6589 and with significant spatio-temporal differences. The provincial TFEE gap within four major areas (WGTFEE), especially that in east and west areas, is the main cause of the OGTFEE in China’s mining industry. Technical change contributes more to the TFEE decline in China’s mining industry. There are differences in improving the TFEE among China’s 31 provincial mining industries, and corresponding countermeasures can be formulated accordingly. This study provides theoretical and practical basis for the clean and green development of China’s mining industry

Soil Drought and Water Carrying Capacity for Vegetation in the Critical Zone of the Loess Plateau: A Review

The Loess Plateau (LP) of China is a good representative area for critical zone (CZ) science studies. The LP is famous for its deep loess. In most areas, the thickness of the loess profile is deeper than 100 m, and two-thirds of the area is arid and semiarid. With the Grain-for-Green project, the vegetation of the plateau has recovered gradually. However, with the increase in vegetative coverage, especially the planted vegetation, the water content of the soil profile has decreased and the soil is much drier. In this review, particular emphasis is paid to the dry conditions of deep soil, drought, regional restoration of vegetation, and effective management of soil moisture. We reviewed the progress of research on dried soil layers (DSLs) that resulted from soil drought in the past decades on the Plateau, and then we summarized the development of the concept and models of soil water carrying capacity for vegetation (SWCCV). This review is helpful for understanding the development of DSLs, optimizing soil water management through vegetation mediation, and designing a long-term sustainable framework for water-limited ecosystems