Environmental Control Equipment Research Articles

Simulation Model Construction of Plant Height and Leaf Area Index Based on the Overground Weight of Greenhouse Tomato: Device Development and Application

Plant height and leaf area index (LAI) are crucial growth indicators that reflect the growth status of tomatoes in greenhouses, enabling accurate determinations to effectively estimate crop transpiration and formulate irrigation strategies for reducing agricultural water waste. There is a need for the increased application of related models to simulate tomato growth indices in the traditional greenhouse production in China. This study proposes a nondestructive, real-time monitoring and simulation device for measuring tomato plant height and leaf area index. The weight of aboveground tomatoes was obtained by suspending tomato plants on dynamometers, while the total weight of stem and leaf organs was determined using a distribution coefficient simulation model. The R2 value between the measurements from the electronic scale and those from the aboveground fresh weight device for tomatoes was 0.937, with an RMSE value of 0.05 kg. The monitoring device did not affect the average tomato growth during operation. The device will not affect the growth of tomatoes during monitoring. A multiple linear regression was used to compare the measured and simulated values of the plant height and leaf area index of various types of greenhouse tomatoes cultivated in different greenhouse types. The average R2 value for simulating plant height was 0.817 with an RMSE of 10.81 cm. The average R2 value for the leaf area index was 0.854, with an RMSE of 0.55 m2·m−2. The simulated values for plant height and leaf area index closely matched the measured values, indicating that the model has high accuracy and applicability in traditional Chinese greenhouses (solar greenhouses and insulated plastic greenhouses). However, further optimization is required for commercially produced, continuous plastic greenhouses equipped with greenhouse environmental control equipment.

Design of a Closed Piggery Environmental Monitoring and Control System Based on a Track Inspection Robot

To improve environmental quality in enclosed piggeries, a monitoring and control system was designed based on a track inspection robot. The system includes a track mobile monitoring platform, an environmental control system, and a monitor terminal. The track mobile monitoring platform consists of three main components: a single-track motion device, a main box containing electronic components, and an environmental sampling device. It is capable of detecting various environmental parameters such as temperature, humidity, NH3 concentration, CO2 concentration, light intensity, H2S concentration, dust concentration, and wind speed at different heights below the track. Additionally, it can control on-site environmental control equipment such as lighting systems, ventilation systems, temperature control systems, and manure cleaning systems. The networked terminal devices enable real-time monitoring of field equipment operating status. An adaptive fuzzy PID control algorithm is embedded in the system to regulate the temperature of the piggery. Field tests conducted on a closed nursery piggery revealed that the system effectively controlled the maximum temperature range within 2 °C. The concentrations of CO2, NH3, and PM2.5 were maintained at a maximum of 1092 mg∙m−3, 16.8 mg∙m−3, and 35 μg∙m−3, respectively. The light intensity ranged from 51 to 57 Lux, while the wind speed remained stable at approximately 0.35 m∙s−1. The H2S concentration was significantly lower than the standard value, and the lowest relative humidity recorded was 18% RH at high temperatures. Regular humidification is required in closed piggeries and other breeding places when the system does not trigger the wet curtain humidification and cooling function, as the relative humidity is lower than the standard value. By controlling the temperature, the system combined with a humidification device can meet environmental requirements. The control method is simple and effective, with a wide range of applications, and holds great potential in the field of agricultural environmental control.

Environmental Prediction in Cold Chain Transportation of Agricultural Products Based on K-Means++ and LSTM Neural Network

Experiments have proven that traditional prediction research methods have limitations in practice. Proposing countermeasures for environmental changes is the key to optimal control of the cold chain environment and reducing the lag of control effects. In this paper, a cold chain transportation environment prediction method, combining k-means++ and a long short-term memory (LSTM) neural network, is proposed according to the characteristics of the cold chain transportation environment of agricultural products. The proposed prediction model can predict the trend of cold chain environment changes in the next ten minutes, which allows cold chain vehicle managers to issue control instructions to the environmental control equipment in advance. The fusion process for temperature and humidity data measured by multiple data sensors is performed with the k-means++ algorithm, and then the fused data are fed into an LSTM neural network for prediction based on time series. The prediction error of the prediction model proposed in this paper is very satisfactory, with a root-mean-square error (RMSE), mean absolute error (MAE), mean squared error (MSE), mean absolute percentage error (MAPE) and R-squared of 0.5707, 0.2484, 0.3258, 0.0312 and 0.9660, respectively, for temperature prediction, and with an RMSE, MAE, MSE, mean absolute percentage error and R-squared of 1.6015, 1.1770, 2.5648, 0.2736 and 0.9702, respectively, for humidity prediction. Finally, the LSTM neural network and back propagation (BP) neural network are compared in order to enhance the reliability of the results. In terms of the prediction effect of the temperature and humidity in cold chain vehicles transporting agricultural products, the proposed model has a higher prediction accuracy than that of existing models and can provide strategic support for the fine management and regulation of the cold chain transportation environment.

Greenhouse localized heating powered by a polygeneration system

Energy consumption in greenhouse heating could reach up to 90% of the total energy requirement depending on the type of greenhouse, environmental control equipment and location of the greenhouse. The use of climate conditioning technologies that exploit renewable energy and the application of passive systems to improve the energy efficiency and the sustainability of the greenhouse sector are recommended. During winter 2020-2021, an experimental test was carried out at the University of Bari in a Mediterranean greenhouse heated by a polygeneration system, composed of a solar system and an air-water heat pump. Three localized heating systems were tested to transfer thermal energy close to plants of Roman lettuce. Heating pipes were placed inside the cultivation substrate in the underground pipe system and on the cultivation substrate in the laid pipe system. The third system consists of metal plates heated by steel tubes and placed in the aerial area of plants. A weather climatic station and a sensor system interfaced with a data logger for continuous data acquisition and storage were used. The plate system was the best for air temperature rising, as it allowed an increase of 3.6% compared to the set-up without any localised heating system. The underground pipe system was the best for the soil heating, as it achieved a temperature increase of 92%. Localized soil heating systems contributed significantly to an earlier harvest by almost 2 weeks.

Top-down spatially-explicit probabilistic estimation of building energy performance at a scale

Achieving the energy-related and environmental targets for nations and municipalities is largely dependent on the existing built stock. It plays a pivotal role in the accomplishment of these targets through the implementation of energy efficiency and flexibility programs, involving the deployment of distributed energy resource management technologies, refurbishment of building envelopes and upgrading of indoor environmental control equipment. Spatial awareness about urban energy use enables to prioritise the areas where these solutions will be most effective and balanced with the plans for new constructions. Large-scale building energy mapping, however, must cope with heterogeneity of buildings within the built stock, absence of detailed information and multiple sources of uncertainty that stem from the complex and dynamic properties of the phenomenon at a building level. One of the key challenges in the discipline is to account for these uncertainties while maintaining the rational model complexities and data needs. This study, therefore, suggests a parsimonious top-down probabilistic modelling recipe to enable geospatial energy mapping and analysis. Under such modelling principles, an inverse propagation of uncertainties is carried out from the status quo of the built stock. The proposed framework is based on probabilistic sampling with prior parametric univariate density estimation and statistical hypothesis testing. Consolidation with the exogenous influencing factors is facilitated through the measure of statistically significant difference. This approach is exemplified with the data from two sources: the cadastral system and the energy performance certificates registry. A case study developed for Trondheim (Norway) quantified the central tendency and dispersion in the distributions of the simulated bulk total annual energy use by buildings per 1×1km grid cell over the urban territory. The results suggest that best estimates of these values vary between 11MWh·y-1 and 141GWh·y-1 depending on the grid cell. A measure of dispersion in the simulated results is highly correlated with these estimates. Robust handling of uncertainties and the possibility to accommodate a variety of modelling objectives make this approach practical for energy mapping with a flexible spatial resolution that may facilitate numerous applications in energy planning. A collection of methods for univariate density estimation discussed in this study together with the empirical data are accessible through Built Stock Explorer:https://builtstockexplorer.indecol.ntnu.no. This open web application for knowledge discovery in building energy data enables to reproduce some of the results presented in the article.

Goose Surface Temperature Monitoring System Based on Deep Learning Using Visible and Infrared Thermal Image Integration

Owing to increased biosecurity and industrial demands, the poultry houses in Taiwan are generally nonopen and closed types, with automatic environmental control and sensor equipment gradually being installed in such houses. Environmental sensors and poultry health monitoring systems are necessary to improve poultry feeding efficiency and safety. In this work, we developed a goose surface temperature monitoring system based on deep learning using visible image and integrated with infrared thermal image. This system could detect the geese in visible image and obtain the individual goose surface temperature automatically. This system consisted of an embedded system with the trained goose detection model, a visible camera, and an infrared thermal camera. The Mask R-convolutional neural network algorithm was employed to train the goose detection model by the collected goose images. The visible camera captured visible images in the poultry house, in which the geese could be identified by the trained goose detection model. The individual surface temperatures of the geese were obtained through integration of the visible and infrared thermal images. The developed monitoring systems were installed in the land and pool areas of a commercial goose house to monitor the surface temperature of the geese and achieved a precision of 97.1% and recall of 95.1%. In addition, the goose surface temperature of the pool area was observed to be lower than that of the land area. The collected individual goose surface temperature would be used as a management index to poultry house managers.

A laying hen breeding environment monitoring system based on internet of things

The breeding environment of laying hens has an important influence on the growth of laying hens, the prevention and control of diseases, and the yield and quality of eggs. Therefore, the real-time collection and utilization of the environment information of laying hens is the key point of breeding laying hens. In this study, the environmental information monitoring and control equipment and systems for egg-breeding laying hens were integrated and developed. The real-time monitoring of the environment information of the laying hens and the information query function on the webpage and mobile devices was realized. The stability and versatility testing of equipment and systems were completed through the pilot deployment of equipment and systems in a laying hen farm in Beijing. The design and development of the equipment and system can provide technical support for the modernization, mechanization and information management of laying hens.

Integration of operational data in building information modelling: From ontology to application

Building design, construction, and operation has been suggested to benefit from comprehensive and well-formed repository of associated information. Building Information Modeling (BIM) has pursued the supposition that repositories could facilitate seamless exchange of information amongst the multiple stakeholders in the building delivery process. Related research and development efforts have primarily focused on representation of buildings’ geometry and specifications of their constituent structural and constructional components. More recently, representations of building environmental control equipment and systems have begun to become incorporated in BIM applications. Ongoing work in this area has likewise targeted development of common schemes to incorporate, in BIM, buildings’ sensory networks and elements that serve, for instance, the operation of HVAC (Heating, Ventilation, and Air-Conditioning) systems. To achieve these targets, comprehensive and robust ontologies of building monitoring data and building performance indicators are essential. In the present contribution, we first present a recently introduced original proposal for such ontologies, covering data regarding dynamic data relevant to state, operation, and performance of buildings. This ontology was developed based on an extensive review of building monitoring data and performance indicator catalogues in thermal, air quality, visual, and acoustical domains. The ontology’s structural core basically involves a systematic specification of the generic attributes of building performance variables. We then illustrate various benefits and applications of this ontology. It is shown to support data quality check, data visualization, building operation optimization, and preventive building systems maintenance. It can also add to the clarity of building performance requirements specifications, advance the understanding of building performance principles in educational and training settings, and provide and early integration of buildings’ operational attributes in BIM applications.

The influence of the fabric filter layout of in a flow mass filtrate

Nowadays, more and more companies are forced to control particulate emissions to the atmosphere, due to economic reasons, legal aspects or simply the change in policy that favors ecological commitment. This new trend induces the necessity for better particle capture equipment and has made the environmental control equipment market increase by 20% in the last few years (Rocha et al., 2012). The dry capture of fine particles is carried out by filtration, and the fabric filter has become a very popular equipment because of its high efficiency and low operational cost. In the other hand, this efficiency is dependent upon proper design and layout, and the particle–filter interactions greatly influence the filtration results and the overall efficiency.In this context, this article presents the computational fluid dynamic (CFD) simulation of the airflow inside an industrial fabric filter with a set of 49 bags and a total surface area of 75 m2. The simulations were performed using the ANSYS FLUENT v13.0. This package applies the Finite Volumes Method, using the URANS approach, as well as the realizable k–ε model for the turbulence and the SIMPLE algorithm for the pressure–velocity coupling (Miltner et al., 2015). Four inlet positions were analyzed in order to determine how the internal flow profile and the equipment filtering performance depends on the inlet position. The simulations allowed concluding that the simple and double inverted feed positions led to a more satisfactory flow, considering not only the overall efficiency but also the bag's useful lifespan.

Development of a New Energy-Saving Pipe-Framed Greenhouse

We summarize the basic techniques used to save energy in a greenhouse and discuss the development of a new energy-saving pipe-framed greenhouse, similar to the type used on most small-scale farms in Japan. To enhance the thermal insulation performance of a pipe-framed greenhouse, a multi-layered thermal curtain was installed. As a result of our experiments, both the heating load and the heating oil consumption in the greenhouse with a multi-layered thermal curtain (M-house) were approximately 40% lower than those in the control greenhouse with a conventional thermal cover (C-house). Furthermore, the heating oil consumption was also reduced by approximately 60% in the M-house equipped with water heat storage, which stored solar energy in daytime and released heat to the greenhouse at night. This multi-layered thermal curtain is expected to gain recognition as the most effective energysaving material available and immediate widespread use nationwide is expected. Another experiment was performed concerning the structural reinforcement of pipe-framed greenhouses. Pipe-framed greenhouses are usually constructed with single-arch pipes in Japan and there has been a recent increase in greenhouses collapsing due to strong winds. Accordingly, techniques to reinforce the structure of pipe-framed greenhouses were also developed. Discipline: Horticulture Additional key words: heating load, heat transmission, multi-layered thermal curtain *Corresponding author: e-mail hirokik@affrc.go.jp Received 31 March 2014; accepted 24 December 2014. Introduction In Japan, greenhouses used for protected horticulture take up an area of approximately 50,000 ha, about 40% are equipped with a heating system and more than 90% depend on fossil fuel. In Japan, protected horticulture is responsible for 45% of all carbon dioxide emissions (about 611 million tons) derived from fossil fuels used for agriculture, forestry and fisheries (Hayashi 2008). Most fossil fuels are used in protected horticulture for heating oil and the amount of fuel consumed for this purpose increased about 2.2 times from 1990 to 2005. Energy costs have also been steadily increasing, which has become an important factor influencing the management of farms. Accordingly, it has become necessary to develop energy-saving techniques for protected horticulture. In Japan, approximately 80% of all greenhouses are high-tunnel and high tunnel-like greenhouses; these are referred to as pipe-framed greenhouses, where the frames are constructed from steel pipes. The high tunnel, where sidewalls are not round like a hooped house, has no electrical service, automated ventilation or heating system (Lambert 2009). This review focuses on pipe-framed greenhouses in Japan with a heating system and other environmental control equipment. Basic energy-saving techniques for greenhouses have been classified into three groups: 1) reducing heating load, 2) introducing a high-efficiency heating system and 3) temperature management, namely, varying night temperature control, local air heating, the usage of cultivars for low-temperature tolerance and so on (Hayashi 2008). These techniques are usually used in combination. The key energy-saving technique in greenhouses involves reducing heating load or loss by installing a fixed or movable covering, an air-inflated covering, etc. (Naito 1981). Overnight, heat loss from greenhouses occurs due to overall heat transmission through coverings and structures. It is also caused by air infiltration and heat flux of the inside-air to the soil, although this is reversed in some cases. Heat transmission accounts for a large part of the total heat loss from a greenhouse, followed by heat transfer due to air

Directed Assembly of Nanoparticles along Predictable Large-Scale Patterns Using Micromolded Hydrogels

We present a new technology to organize microparticles and nanoparticles along micropatterns of variable complexity over centimeter-squared surfaces. This technology relies on the fabrication of textured hydrogels, which serve as templates for directed assembly after the deposition of a droplet of colloids on their surfaces. We show that directed assembly occurs spontaneously during water evaporation, and we demonstrate the efficiency of this mechanism for a variety of organic and inorganic nano-objects. The dynamics of this process is also uncovered by light microscopy, showing that the patterns imprinted on the gel determine fluid flow during water evaporation and allow for directed movements toward predictable positions. We finally propose different methods to transfer assembled particles from hydrogels to glass, silicon, or metallic surfaces, and we show that the assembled and transferred particles retain their surface properties for bioassays. Beyond the originality of this spontaneous assembly mechanism, it constitutes an attractive technology for nano-object large-scale integration, which does not require costly environmental control equipment.

Current status of MHI’s CO2 recovery technology and optimization of CO2 recovery plant with a PC fired power plant

It is the opinion of the authors that CO2 Capture and Storage (CCS) technology can significantly contribute as an effective countermeasure against climate change, allowing us to continue the utilization of fossil fuels for primary energy production. However for this technology to be widely deployed on a commercial basis there are three key issues that need to be addressed; (1) Reduction in energy consumption, (2) Efficient integration with other environmental control equipment of a PC power plant and (3) Reduction in the decrease of net electrical output. MHI has delivered multiple commercial CO2 recovery plants in the chemical and fertilizer industries, which recover CO2 from natural gas fired flue gas, with four commercial plants in operation and another four under construction, all utilizing the proprietary KM-CDR process. In order to gain experience with CO2 recovery from a coal fired flue gas stream, Mitsubishi Heavy Industries (MHI), together with a subsidy from RITE and cooperation from J-POWER, constructed a 10 metric ton per day (T/D) CO2 recovery demonstration plant at the 2×500 MW Matsushima power station in southern Japan. This demonstration plant has subsequently achieved more than 4,000 hours of successful test operation during 2006–2007 with a further 1,000 hours during 2008, and testing continues today. The demonstration testing confirmed that the KM-CDR process is applicable to coal fired flue gas streams. Future research priorities include the improved integration of the CO2 recovery process with the flue gas pre-treatment components and the additional optimization of removal and separation methods for coal based impurities accumulating in the absorbent. An issue of concern for power plant operators is the reduction of the net electrical output due to the demands of CO2 recovery process. MHI has made significant improvements in this area and in the efficiency of absorbents. However, it is necessary to further reduce the adverse impact on the net electrical output of the power plant via astute integration of the energy transferred between the power plant and the Post Combustion CO2 Capture (PCC) plant. MHI is investigating the following concepts; (1) Utilizing the waste heat of the PCC plant for the power plant, (2) Utilizing heat recovery from the flue gas for the CO2 recovery process and (3) Utilizing the compression heat of the CO2 compressor for the CO2 recovery process.

Modification of boiler operating conditions for mercury emissions reductions in coal-fired utility boilers

US EPA's studies have determined that mercury emissions from coal-fired power plants pose significant hazards to public health and must be reduced. Coal-fired power plants represent a significant fraction of the anthropogenic emissions of mercury into the atmosphere. Mercury emissions are impacted by factors such as coal type, boiler operation, fly ash characteristics and type of environmental control equipment installed on the unit. Field data show a wide variation in the fraction of mercury that is emitted in the gaseous phase, as elemental and oxidized mercury vapor, and as particulate-bound mercury. Oxidized mercury is a preferable species because is less volatile at stack temperatures, water-soluble, and tends to interact with mineral matter and char, and cold-end air pollution control devices. There is also evidence that boiler-operating conditions could be used to influence mercury behavior in the boiler, since they affect the thermo-chemical conditions for mercury formation and reduction. However, operation of boiler control settings, which result in mercury removal benefits, should also consider the tradeoff between mercury reduction and other emissions (for example, NO x and CO), the level of unburned carbon in the fly ash, unit efficiency and the performance of particulate control equipment. This paper reports fieldwork performed to investigate the feasibility of affecting mercury emissions from coal-fired plants by manipulating boiler control settings. Full-scale testing was performed at two units. One of the units is equipped with a back-end train that includes a rotary air preheater followed by two electrostatic precipitators in series. The other unit is equipped with hot and cold precipitators and a tubular air preheater. A strategy for mercury control by selectively manipulating boiler control settings, if used in combination with other control measures such as sorbent injection, should provide a cost-effective option for mercury control.

A large scale 'Microclimate' enclosure for pyritic specimens

Current environmental conditions within the Palaeontological Department of The Natural History Museum are unsuitable for the safe storage of humidity sensitive, actively pyritising plant specimens. The collections cabinets, timber framed with laminated composite doors, offer a limited amount of buffering against small environmental fluctuations, but were not designed to compensate for larger humidity changes. As an alternative to purchasing a costly environmentally controlled cupboard, a department standard free standing collections cabinet was wrapped in a moisture resistant barrier film, Marvelseal� 470, to provide a large scale 'microclimate' using Art-Sorb� as an environmental control. This wrapped cabinet currently provides a favorable humidity level of approximately 45% with a range of +/- 4.5% relative humidity, compared to the general collections area of 50% with a range of +/- 16.9% during the four month trial period. The cabinet has provided space for the installation of over three hundred humidity sensitive plant specimens whilst a systematic long term conservation programme can be undertaken. In addition, it provides a suitable storage area after conservation prior to the installation of new environmental control equipment.

New products debut at Chem Show

The latest advances in process equipment, instruments and controls, fluidshandling equipment, along with maintenance, safety, and environmental control equipment were on display at the 48th biennial Chem Show in New York City late last month. Taking up about 185,000 sq ft of space at the Jacob K. Javits Convention Center, more than 900 exhibitors showcased the newest toys for chemical engineers. First established in 1915, this hardware display of the chemical industry, run by International Exposition Co., Westport, Conn., attracted 21,108 attendees, of which 13,008 were visitors and the balance exhibitor personnel. The number of visitors has declined from the last show in 1997. In that year, International Exposition reported that 15,800 visitors came to the show. An educational conference program ran in conjunction with the show organized around the theme of the chemical process industry in the next millennium. Chem Show attendees could go to sessions on instrumentation, control, and data; environmental...

Rehabilitation after traumatic brain injury.

Head injury is a common disabling condition but regrettably facilities for rehabilitation are sparse. There is now increasing evidence of the efficacy of a comprehensive multidisciplinary rehabilitation team compared to natural recovery following brain injury. This chapter outlines some basic concepts of rehabilitation and emphasises the importance of valid and reliable outcome measures. The evidence of the efficacy of a rehabilitation programme is discussed in some detail. A number of specific rehabilitation problems are outlined including the management of spasticity, nutrition, pressure sores and urinary continence. The increasingly important role of assistive technology is illustrated, particularly in terms of communication aids and environmental control equipment. However, the major long-term difficulties after head injury focus around the cognitive, intellectual, behavioural and emotional problems. The complex management of these disorders is briefly addressed and the evidence of the efficacy of some techniques discussed. The importance of recognition of the vegetative stage and avoidance of misdiagnosis is emphasised. Finally, the important, but often neglected, area of employment rehabilitation is covered.

Design and commissioning of a valve-regulated lead/acid battery energy-storage system for backing up critical environmental loads

Momentary and sustained electrical power interruptions and voltage depressions represent two of the most difficult and important power quality and delivery problems that face many industrial and commercial users. There is a definite need at many industrial processing plants and commercial users of electrical power to have a dependable, efficient and controllable source of real and reactive power that is available instantly to support large electrical loads (greater than 5 MVA), even if the incoming utility a.c. connection is lost. When power is interrupted or lost, the results can be extremely disruptive for critical processes and cause lost production, costly downtime and loss of customer good will, and in certain industries, can lead to environmental damage through the release of toxic emissions into the air. Recently, this challenge was faced by GNB Technologies at its lead reclaiming and smelting facility in Vernon, CA, USA. This study describes a versatile, cost-effective, workable solution to the problem that has resulted in the design and installation of a 5 MVA, 3.5 MWh battery energy storage system (BESS) which provides uninterruptible power to the critical environmental control equipment throughout the plant. The BESS at Vernon provides the required power, combined with both voltage and frequency control, to allow the plant to tolerate disconnection from the utility grid without suffering unacceptable impacts on critical loads. The system also provides the company with a demand-side energy management system for conducting daily peak shaving of energy demand and, thereby, reduces its electrical bills.

園芸施設における環境調節機器の開発と普及

園芸施設における環境調節機器の開発と普及

Potential Consequences of the Clean Coal Program for Air and Waste Issues.

The U.S. Department of Energy's Clean Coal Technology Demonstration Program (CCTDP) was funded by Congress to demonstrate more efficient, economically feasible, and environmentally acceptable coal technologies. Although the environmental focus at first was on sulfur dioxide (SO2) and nitrogen oxides (NOX) because of their relationship to acid precipitation, the CCTDP may also lead to reductions in carbon dioxide (CO2) emissions and in solid waste produced, relative to conventional technologies. Environmental benefits that maybe realized from clean coal technologies (CCTs) will depend upon the degree of acceptance in the marketplace achieved by each of the individual technologies. In general, technologies that replace a major portion of an existing facility (repowering technologies) show the most promise for achieving reductions in all four categories (SO2, NOX, CO2, and solid waste). Technologies that modify existing facilities by adding environmental control equipment or changing feedstocks (retrofit technologies), used singly or in combination, appear capable of achieving substantial reductions in SO2 and NOX, but in general have little effect on CO2, and only a few of these technologies appear capable of reducing solid waste. However, even if decreases in solid waste volume are not always achieved, much of the solid waste from CCTs would be dry and therefore easier to dispose of than scrubber sludge from conventional technologies.

SIMULATION FOR DETERMINING GREENHOUSE TEMPERATURE SETPOINTS

ABSTRACT Two separately developed simulation models were linked and used to evaluate different environmental control strategies in Florida tomato production greenhouses. POLY-2 is a model of a double poly, quonset-style greenhouse typical of Florida. It is a dynamic model that realistically simulates environmental control equipment actions. TOMGRO is a dynamic crop model that simulates 1) growth, 2) development, and 3) quantity and timing of yield of tomatoes. Both models are based on independent empirical data sets used for calibration and validation, respectively. The two models were linked by incorporating POLY-2 into TOMGRO as a sub-routine. Historical weather data for Tallahassee, Rorida and Raleigh, North Carolina are used by the POLY-2 subroutine to simulate greenhouse environmental conditions which are used in turn by TOMGRO to simulate development and growth of the tomato crop. During simulation runs POLY-2 keeps track of heating fuel requirements and TOMGRO keeps track of tomato yield. Simulations over a range of setpoints showed that the optimal setpoint depends directly on the price of fuel, the value of the tomatoes, and location.