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Author(s):  
Fernando Saboya ◽  
Marina de Souza Ferreira ◽  
John Scott McCartney ◽  
Sérgio Tibana

Author(s):  
A. C. O. Martins ◽  
M. C. A. Silva ◽  
A. D. Benetti

Abstract This study aimed at providing a set of optimal kinetic and stoichiometric parameters of ASM1 representative of wastewater from a subtropical climate region in Brazil. ASM1 was applied on STOAT program, and the model parameters were evaluated and optimized with sensitivity analysis and Response Surface Methodology (RSM) to reach minimum prediction errors of effluent TSS, COD, and NH3. Six sensitive parameters were identified: YH, YA, μA, KNH, bA, and kOA. Predictions of RSM regression models were strongly correlated to the STOAT predictions. YH mainly affected TSS and COD, and the other parameters affected NH3. ASM1 calibration with estimated optimal values of sensitive parameters resulted in approximately null prediction errors for modeling state variables. NH3 presented similar results in the ASM1 validation; meanwhile, TSS and COD presented high errors related to the increase in YH due to the RSM optimization. The optimal parameters, mainly YA, μA, KNH, bA, and kOA, constitute references for other studies on ASM1 modeling using wastewater data from a subtropical climate region. YH optimal value should be evaluated as well as the effect of sludge wastage methods and the simulation periods.


Energies ◽  
2021 ◽  
Vol 14 (21) ◽  
pp. 6950
Author(s):  
Chenfei Liu ◽  
Stephen Sharples ◽  
Haniyeh Mohammadpourkarbasi

Passivhaus EnerPHit is a rigorous retrofit energy standard for buildings, based on high thermal insulation and airtightness levels, which aims to significantly reduce building energy consumption during operation. However, extra retrofit materials are required to achieve this standard, which raises a contradiction between how to balance the environmental impacts of the retrofitting material inputs and extremely low energy consumption after retrofit. This motivated the analysis in this paper, which aimed to evaluate the possibilities of reducing the required retrofitting material inputs when trying to achieve the EnerPHit energy standard using a typical suburban dwelling in China’s hot summer–cold winter climate region as a case study. Firstly, how the insulation performance of each envelope component affected the building’s energy consumption was analysed. Based on this, sensitivity simulations of combinations of different insulation levels with different fabric components were investigated under four scenarios of insulation levels, airtightness and glazing choice. The final proposed retrofitting plans achieved the EnerPHit standard with insulation materials’ savings between 18% to 58% compared to a baseline retrofit plan, and this led, in turn, to 3.9 to 12.6 tonnes of carbon reductions. Moreover, an energy-saving of 87% in heating and 70% in cooling was achieved compared with the pre-retrofit dwelling.


2021 ◽  
Author(s):  
Zhengfei Li ◽  
Jani Heino ◽  
Zhuoyan Song ◽  
Xiaoming Jiang ◽  
Jun Wang ◽  
...  

2021 ◽  
Author(s):  
Ahmad Saeed Mohammad ◽  
Jabir Alshehabi Al-Ani ◽  
Dhafer Zaghar

2021 ◽  
pp. 105840
Author(s):  
H.M. Touhidul Islam ◽  
Abu Reza Md. Towfiqul Islam ◽  
Md. Abdullah-Al-Mahbub ◽  
Shamsuddin Shahid ◽  
Anjum Tasnuva ◽  
...  

Agronomy ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 1584
Author(s):  
Sojung Kim ◽  
Sumin Kim ◽  
Chang-Yong Yoon

The aim of this study was to identify an efficient agrophotovoltaic (APV) system structure for generating electricity from solar radiation without causing an adverse impact on crop growth. In a temperate climate region, it is critical to design an APV system with appropriate structure with the maximum amount of electricity generation because, unlike in desert areas, strong solar radiation is only available for a few hours a day. In this study, APV systems with three different shading ratios (i.e., 32%, 25.6%, and 21.3%) were considered, and the optimum structure in terms of electricity efficiency and profitability was investigated via nonlinear programming. Moreover, an estimation model of electricity generation was developed via a polynomial regression model based on remote sensing data given by the APV system located at Jeollanamdo Agricultural Research and Extension Services in South Korea. To evaluate the impact of the APV on crop production, five different grain crops—sesame (Sesamum indicum), mung bean (Vigna radiata), red bean (Vigna angularis), corn (Zea mays), and soybean (Glycine max)—were cultivated in the system. As a result, the proposed optimization model successfully identified the best APV system structure without reducing existing crop production.


Agronomy ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 1563
Author(s):  
Carolina Fogliarini Parcianello ◽  
Álvaro Luís Pasquetti Berghetti ◽  
Maristela Machado Araujo ◽  
Gabriel Alberto Sans ◽  
Vanessa Marques Soares ◽  
...  

Phosphorus (P) availability in subtropical soils does not often meet the nutritional demand of native tree species such as the ipê-roxo tree (Handroanthus heptaphyllus); therefore, it is necessary to supply P at planting. However, the impact of P on root system growth remains unknown. The aim of the current study was to investigate the effect of P application on root morphology of H. heptaphyllus plants over a 36-month period in a subtropical climate region. During the experiment, the plants subjected to fertilization with 40 kg P ha−1 were compared to untreated control. Plant roots were scanned through minirhizotron system 18 and 36 months after transplant (MAT), and generated images were used to determine total root length, mean root diameter and total root volume. Plant height and leaf P concentrations were also evaluated. Phosphorus application enhanced root and whole plant growth with a more evident effect at 36 MAT, when soil P availability decreased. The results give important information on the cultivation of H. heptaphyllus plants in soils presenting low P availability.


2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Anam M. Khan ◽  
Jessica M. Finlay ◽  
Philippa Clarke ◽  
Ketlyne Sol ◽  
Robert Melendez ◽  
...  

Abstract Background Older adults are particularly vulnerable to the adverse health effects of extreme temperature-related events. A growing body of literature highlights the importance of the natural environment, including air pollution and sunlight, on cognitive health. However, the relationship between exposure to outdoor temperatures and cognitive functioning, and whether there exists any differences across climate region, remains largely unexplored. We address this gap by examining the temperature-cognition association, and whether there exists any variation across climate regions in a national cohort of aging adults. Methods In this cross-sectional study, we obtained data on temperature exposure based on geocoded residential location of participants in the REasons for Geographic And Racial Differences in Stroke (REGARDS) study. For each participant, this information was linked to their cognitive scores from Word List Learning and Recall tests to assess cognitive functioning. We used distributed lag non-linear models (dlnm) to model temperature effects over 2 days. Multivariable linear regression was used to compute temperature-cognitive functioning associations, adjusted for important covariates. Region-specific (“Dry”, “Mediterranean/oceanic”, “Tropical” and “Continental”) associations were examined by including an interaction term between climate region and temperature. Results Amongst 20,687 individuals (mean age = 67.8; standard deviation = 9.2), exposure to region-specific extreme cold temperatures in the “dry” region (e.g., Arizona) over 2 days was associated with lower cognitive scores (Mean Difference [MD]: -0.76, 95% Confidence Interval [CI]: − 1.45, − 0.07). Associations remained significant for cumulative effects of temperature over 2 days. Extremely cold exposure in the “Mediterranean/oceanic” region (e.g., California) over 2 days was also associated with significantly lower cognitive performance (MD: -0.25, 95% CI: − 0.47, − 0.04). No significant associations were observed for exposure to hot temperatures. Cognitive performance was slightly higher in late summer and fall compared to early summer. Conclusion We noted adverse cognitive associations with cold temperatures in traditionally warmer regions of the country and improved cognition in summer and early fall seasons. While we did not observe very large significant associations, this study deepens understanding of the impact of climate change on the cognitive health of aging adults and can inform clinical care and public health preparedness plans.


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