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Paper Information

Journal:   JOURNAL OF AGRICULTURAL MACHINERY   fall 2018-winter 2019 , Volume 8 , Number 2 #b00522; Page(s) 377 To 388.
 
Paper: 

Study of Ammonia Gas Emission from Broiler Houses and the Effects of Temperature, Humidity and Age on It

 
 
Author(s):  BAGHANI M., AGHKHANI M.H.*
 
* Department of Mechanical Engineering Biosystem. Faculty of Agriculture, Ferdowsi University of Mashhad
 
Abstract: 
Introduction Iran as one of the largest producers of poultry in Asia and plays major role in feeding the world's population, particularly in the poultry industry. Research about this industry will help to improve the quality and the quantity of products. Increasing of the concentration of toxic gases such as NH3 (ammonia), CO2 (carbon dioxide), SH2 and CH4 in poultry houses comes from bird activity inside the barn is one of the basic problems of the farming. Increasing the amount of these gases more than standard level would cause heavy mortality and reductions in the production. Ammonia is one of the most toxic gases in poultry houses, which must be controlled. Different studies have been carried out on measurement of ammonia emissions from poultry houses to reduce energy consumption and reduce emissions of ammonia. But no specific study has been found on ammonia emissions in Iran and there is no reliable documents of ammonia emissions from poultry in this country. Material and Methods In this study a poultry house with 18 thousand chickens was used to measure the emission rate of ammonia, the effect of temperature, moisture and age of chickens on emissions of ammonia in Sabzevar city. The barn was equipped with semi-automatic mechanical ventilation. At the first step of this research all sensors was installed for data collection, i. e., air velocity, temperature, humidity and ammonia concentration. Recorded data information were stored in a central computer. Five digital sensors, model AM2303, have been used to measure the temperature and humidity of the ambient air quality. The concentration of ammonia in the air inputs and outputs of the farm was measured using an ammonia sensor model TGS2444 every 10 seconds throughout the study and recorded in the central system. The average speed of the exhaust air was measured using the hot wire anemometer probe for every fan. The outputs of all sensors was converted to digital data and transferred to the central computer using RS485 cable in each module. Converting of the sensors output to digital data reduces changing the data and probable errors. Ammonia emission rates was found by calculating the concentration of ammonia and measuring the rate of input air and fans exhaust air by ammonia gas equilibrium equation. Relation of the ammonia emission rate was achieved using affective factors such as age of the birds and inside air humidity and temperature by regression method. Results and Discussion The average rate of ammonia emission during broiler growing were measured 89 mg per day for each bird. Ammonia emission rates increased until the age of 37 days and then decreased after the age of 37 days. Age of birds has the highest impact coefficient and temperature and relative humidity of the barn have the least impact coefficients on the ammonia emission rate. The ammonia emission rate has also increased by increasing the age of the bird, temperature and relative humidity of the air. Comparing of the ammonia emission rate derived from regression equation with real conditions showed that the regression equation method has a high precision for estimating the ammonia emission rate. Conclusions It is showed that the results of this research can predict the ammonia emission rate in the poultry houses and predict the required ventilation rates to minimize the amount of ammonia concentration. The results of this study can be used for automatic control system to minimize energy consumption in the poultry houses. According to the results, the reduction of temperature and humidity in poultry house can be used to reduce the ammonia level.
 
Keyword(s): Ammonia emission,Broilers,Regression model,Relative humidity,Temperature
 
References: 
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