Development of long-term dynamic BioWin® model simulation for ANAMMOX UASB micro-granular process

Chemosphere ◽  
2021 ◽  
pp. 131859
Author(s):  
Parin Izadi ◽  
Parnian Izadi ◽  
Ahmed Eldyasti
Keyword(s):  
Model Simulation

scholarly journals Long-term O<sub>3</sub>–precursor relationships in Hong Kong: field observation and model simulation

2017 ◽  
Vol 17 (18) ◽  
pp. 10919-10935 ◽  
Author(s):  
Yu Wang ◽  
Hao Wang ◽  
Hai Guo ◽  
Xiaopu Lyu ◽  
Hairong Cheng ◽  
...  
Keyword(s):  
Hong Kong ◽  
Model Simulation ◽  
Ground Level ◽  
Effective Control ◽  
Photochemical Pollution ◽  
Mixing Ratios ◽  
The Past ◽  
Total Volatile Organic Compounds

Abstract. Over the past 10 years (2005–2014), ground-level O3 in Hong Kong has consistently increased in all seasons except winter, despite the yearly reduction of its precursors, i.e. nitrogen oxides (NOx =  NO + NO2), total volatile organic compounds (TVOCs), and carbon monoxide (CO). To explain the contradictory phenomena, an observation-based box model (OBM) coupled with CB05 mechanism was applied in order to understand the influence of both locally produced O3 and regional transport. The simulation of locally produced O3 showed an increasing trend in spring, a decreasing trend in autumn, and no changes in summer and winter. The O3 increase in spring was caused by the net effect of more rapid decrease in NO titration and unchanged TVOC reactivity despite decreased TVOC mixing ratios, while the decreased local O3 formation in autumn was mainly due to the reduction of aromatic VOC mixing ratios and the TVOC reactivity and much slower decrease in NO titration. However, the decreased in situ O3 formation in autumn was overridden by the regional contribution, resulting in elevated O3 observations. Furthermore, the OBM-derived relative incremental reactivity indicated that the O3 formation was VOC-limited in all seasons, and that the long-term O3 formation was more sensitive to VOCs and less to NOx and CO in the past 10 years. In addition, the OBM results found that the contributions of aromatics to O3 formation decreased in all seasons of these years, particularly in autumn, probably due to the effective control of solvent-related sources. In contrast, the contributions of alkenes increased, suggesting a continuing need to reduce traffic emissions. The findings provide updated information on photochemical pollution and its impact in Hong Kong.

scholarly journals Possible biases in scaling-based estimates of glacier change: a case study in the Himalaya

2020 ◽  
Vol 14 (9) ◽  
pp. 3235-3247
Author(s):  
Argha Banerjee ◽  
Disha Patil ◽  
Ajinkya Jadhav
Keyword(s):  
Response Time ◽  
Climate Sensitivity ◽  
Linear Response ◽  
Model Simulation ◽  
Change Scenario ◽  
Response Model ◽  
Future Evolution ◽  
Scaling Model ◽  
Mountain Glaciers

Abstract. Approximate glacier models are routinely used to compute the future evolution of mountain glaciers under any given climate-change scenario. A majority of these models are based on statistical scaling relations between glacier volume, area, and/or length. In this paper, long-term predictions from scaling-based models are compared with those from a two-dimensional shallow-ice approximation (SIA) model. We derive expressions for climate sensitivity and response time of glaciers assuming a time-independent volume–area scaling. These expressions are validated using a scaling-model simulation of the response of 703 synthetic glaciers from the central Himalaya to a step change in climate. The same experiment repeated with the SIA model yields about 2 times larger climate sensitivity and response time than those predicted by the scaling model. In addition, the SIA model obtains area response time that is about 1.5 times larger than the corresponding volume response time, whereas scaling models implicitly assume the two response times to be equal to each other. These results indicate the possibility of a low bias in the scaling model estimates of the long-term loss of glacier area and volume. The SIA model outputs are used to obtain parameterisations, climate sensitivity, and response time of glaciers as functions of ablation rate near the terminus, mass-balance gradient, and mean thickness. Using a linear-response model based on these parameterisations, we find that the linear-response model outperforms the scaling model in reproducing the glacier response simulated by the SIA model. This linear-response model may be useful for predicting the evolution of mountain glaciers on a global scale.

scholarly journals Low-frequency variability in North Sea and Baltic Sea identified through simulations with the 3-D coupled physical–biogeochemical model ECOSMO

2017 ◽  
Vol 8 (3) ◽  
pp. 801-815 ◽  
Author(s):  
Ute Daewel ◽  
Corinna Schrum
Keyword(s):  
Baltic Sea ◽  
North Sea ◽  
Decadal Variability ◽  
Model Simulation ◽  
Ecosystem Model ◽  
Biogeochemical Model ◽  
Ecosystem Productivity ◽  
The North ◽  
The North Sea

Abstract. Here we present results from a long-term model simulation of the 3-D coupled ecosystem model ECOSMO II for a North Sea and Baltic Sea set-up. The model allows both multi-decadal hindcast simulation of the marine system and specific process studies under controlled environmental conditions. Model results have been analysed with respect to long-term multi-decadal variability in both physical and biological parameters with the help of empirical orthogonal function (EOF) analysis. The analysis of a 61-year (1948–2008) hindcast reveals a quasi-decadal variation in salinity, temperature and current fields in the North Sea in addition to singular events of major changes during restricted time frames. These changes in hydrodynamic variables were found to be associated with changes in ecosystem productivity that are temporally aligned with the timing of reported regime shifts in the areas. Our results clearly indicate that for analysing ecosystem productivity, spatially explicit methods are indispensable. Especially in the North Sea, a correlation analysis between atmospheric forcing and primary production (PP) reveals significant correlations between PP and the North Atlantic Oscillation (NAO) and wind forcing for the central part of the region, while the Atlantic Multi-decadal Oscillation (AMO) and air temperature are correlated to long-term changes in PP in the southern North Sea frontal areas. Since correlations cannot serve to identify causal relationship, we performed scenario model runs perturbing the temporal variability in forcing condition to emphasize specifically the role of solar radiation, wind and eutrophication. The results revealed that, although all parameters are relevant for the magnitude of PP in the North Sea and Baltic Sea, the dominant impact on long-term variability and major shifts in ecosystem productivity was introduced by modulations of the wind fields.

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