An environmental impact calculator for greenhouse production systems

2013 ◽  
Vol 118 ◽  
pp. 186-195 ◽  
Author(s):  
Marta Torrellas ◽  
Assumpció Antón ◽  
Juan Ignacio Montero
2021 ◽  
Vol 192 ◽  
pp. 103170
Author(s):  
Karin Veltman ◽  
C. Alan Rotz ◽  
Larry Chase ◽  
Joyce Cooper ◽  
Chris E. Forest ◽  
...  

2015 ◽  
pp. 45-52
Author(s):  
C. Poncet ◽  
C. Bresch ◽  
H. Fatnassi ◽  
L. Mailleret ◽  
A. Bout ◽  
...  

Geoderma ◽  
2021 ◽  
Vol 385 ◽  
pp. 114899
Author(s):  
Ya'nan Fan ◽  
Yanxia Zhang ◽  
Zhikun Chen ◽  
Xinkai Wang ◽  
Biao Huang

2009 ◽  
Vol 24 (3) ◽  
pp. 234-243 ◽  
Author(s):  
Olha Sydorovych ◽  
Charles W. Raczkowski ◽  
Ada Wossink ◽  
J. Paul Mueller ◽  
Nancy G. Creamer ◽  
...  

AbstractConventional agriculture often aims to achieve high returns without allowing for sustainable natural resource management. To prevent environmental degradation, agricultural systems must be assessed and environmental standards need to be developed. This study used a multi-factor approach to assess the potential environmental impact risk of six diverse systems: five production systems and a successional system or abandoned agronomic field. Assessment factors were soil quality status, amount of pesticide and fertilizer applied and tillage intensity. The assessment identified the best management practices (BMP)–conventional tillage system as a high-risk system mostly because of extensive tillage. The certified organic system was also extensively tilled and was characterized by P build-up in the soil, but performed well based on other assessment factors. Conversely, the BMP–no tillage and the crop–animal integrated system were characterized as low risk mainly because of reduced tillage. The paper discusses assessment strengths and weaknesses, ways to improve indicators used, and the need for additional indicators. We concluded that with further development the technique will become a resourceful tool to promote agricultural sustainability and environmental stewardship and assist policy-making processes.


Author(s):  
Stephen G. Mackenzie ◽  
◽  
Ilias Kyriazakis ◽  

The focus of this chapter is on the environmental impact consequences of endemic livestock health challenges that lead to deterioration in animal health, and on the potential impacts arising from their mitigations. The first part of the chapter concentrates on the potential of animal health to affect the environmental impact of livestock systems. Subsequently, it reviews the literature to date which has quantified the impact of health challenges for the environmental impacts of livestock systems. The potential of successful health interventions to mitigate negative environmental impacts represents a point of synergy between concerns around environmental sustainability and animal welfare, both of which represent 'hot topics' in the discourse surrounding the livestock industry and its sustainability. The challenges associated with modelling health interventions and their potential to mitigate environmental impacts constitute the last section in the chapter.


2018 ◽  
Vol 226 ◽  
pp. 02019 ◽  
Author(s):  
Evgeniya P. Klyuchka ◽  
Viktor V. Radin ◽  
Leonid M. Groshev ◽  
Valeriy P. Maksimov

The fundamentals of an interdisciplinary approach to the design of greenhouse production systems are considered, in which biological objects (plants and humans) are present. The conceptual approach of the software solution is analyzed, synthesizing on the basis of the objectoriented concept such directions as disciplines on the construction of greenhouse production, dynamic simulation models, geoinformation systems. Based on the study of this issue, the conclusion was made about the advisability of applying an interdisciplinary approach for a comprehensive study of the projected complex biotechnical systems of greenhouse production.


Agronomy ◽  
2020 ◽  
Vol 10 (5) ◽  
pp. 723 ◽  
Author(s):  
Katsumi Ohyama ◽  
Junichi Yamaguchi ◽  
Ayumi Enjoji

New plant production systems with a low environmental impact (or a high resource utilization efficiency) are necessary for urban agriculture development. This study explores the benefits of closed plant production systems (CPPSs) with artificial lighting using a commercial CPPS at Osaka Prefecture University. Lettuce plants were produced continuously as a model for analyzing resource consumption rates, such as electricity, labor, water, and CO2, over two years. Monthly consumption rates of electricity, labor, water, and CO2 increased with the increase in the monthly production rate of the lettuce. The utilization efficiencies (=output/input) of electricity, energy, water, and CO2 were 1.0%, 1.0%, 4.0%, and 32.6%, respectively. If the commercial CPPS maintains the monthly production rate at a higher level, the energy utilization efficiency will increase. The number of air exchanges in a commercial CPPS should decrease to increase water and CO2 utilization efficiencies. Reusing water drained from the air conditioning system and employing a closed loop in the nutrient supply system also contribute to increasing the water utilization efficiency and lowering the environmental impact. Although a commercial CPPS still requires further improvements, it may be a good crop production system for urban agriculture provided resource utilization efficiencies improve.


Author(s):  
Maria Pessoa ◽  
Elizabeth Fernandes ◽  
Sonia Nascimento de Queiroz ◽  
Vera Ferracini ◽  
Marco Gomes ◽  
...  

The present chapter provides a brief explanation on some aspects involved in the development of models and mathematical-modelling simulations, to show their benefits to the decision-making process in the environmental impact assessment of agriculture. Aspects concerning the agroecosystems were also presented toward the sustainability of Brazilian agricultural production systems. Some applications which have been developed in Brazil were pointed out, as well as a specific case study conducted at the Guarani aquifer recharge area located in Ribeirão Preto, São Paulo state, in order to show the influence of input data on the results provided by CMLS94 simulator.


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