This research investigated the use of two relatively cost-effective devices for determining NH3 concentrations in naturally ventilated (NV) dairy barns including an Ogawa passive sampler (Ogawa) and a passive flux sampler (PFS). These samplers were deployed adjacent to sampling ports of a photoacoustic infrared multigas spectroscope (INNOVA), in a NV dairy barn. A 3-day deployment period was deemed suitable for both passive samplers. The correlations between concentrations determined with the passive samplers and the INNOVA were statistically significant (r = 0.93 for Ogawa and 0.88 for PFS). Compared with reference measurements, Ogawa overestimated NH3 concentrations in the barn by ∼ 14%, while PFS underestimated NH3 concentrations by ∼ 41%. Barn NH3 emission factors per animal unit (20.6-21.2 g d(-1) AU(-1)) based on the two passive samplers, after calibration, were similar to those obtained with the reference method and were within the range of values reported in literature.

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.envpol.2015.10.031DOI Listing

Publication Analysis

Top Keywords

nh3 concentrations
12
passive samplers
12
naturally ventilated
8
ventilated dairy
8
dairy barns
8
ogawa passive
8
concentrations
5
passive
5
reliable low-cost
4
low-cost devices
4

Similar Publications

The simultaneous removal reaction (SRR) is a pioneering approach for achieving the simultaneous removal of anthropogenic NO and CO pollutants through catalytic reactions. To facilitate this removal across diverse industrial fields, it is crucial to understand the trade-offs and synergies among the multiple reactions involved in the SRR process. In this study, we developed mixed metal oxide nanostructures derived from layered double hydroxides as catalysts for the SRR, achieving high catalytic conversions of 93.

View Article and Find Full Text PDF

NH release during the snow evaporation process in typical cities in Northeast China.

Sci Rep

January 2025

Key Laboratory of Songliao Aquatic Environment, Ministry of Education, Jilin Jianzhu University, No.5088 Xincheng Road, Changchun, 130118, Jilin Province, China.

NH is the most important alkaline gas in the atmosphere and functions as a precursor to secondary ammonium salts. Therefore, identifying its sources and quantifying its emissions is imperative. NH represents a principal component of atmospheric particulate pollutants.

View Article and Find Full Text PDF

Human breath gas analysis is a noninvasive disease diagnostic approach used to identify different pathological conditions in the human body. Monitoring breath acetone (CHO) and ammonia (NH) as biomarkers is vital in diagnosing diabetes mellitus and liver disorders, respectively. In this article, the quartz-enhanced photoacoustic spectroscopy (QEPAS) technique is proposed and demonstrated for measuring CHO and NH in human exhaled breath samples.

View Article and Find Full Text PDF

The objective of this study was to determine the effects of dietary agro-industrial by-products (AIBP) with different amounts of metabolizable energy (ME) and crude protein (CP) on fermentation (96 h) and gas production (GP) kinetics in vitro, as well as acceptability, animal performance, digestibility, and blood parameters in lambs. The gas production technique (GPT) and fermentation characteristics were used in an in vitro trial. This experiment used diets with ME contents of 6.

View Article and Find Full Text PDF

A new prediction model based on deep learning for pig house environment.

Sci Rep

December 2024

School of Mechanical and Electrical Engineering, Qiqihar University, Qiqihar, 161006, China.

A prediction model of the pig house environment based on Bayesian optimization (BO), squeeze and excitation block (SE), convolutional neural network (CNN) and gated recurrent unit (GRU) is proposed to improve the prediction accuracy and animal welfare and take control measures in advance. To ensure the optimal model configuration, the model uses a BO algorithm to fine-tune hyper-parameters, such as the number of GRUs, initial learning rate and L2 normal form regularization factor. The environmental data are fed into the SE-CNN block, which extracts the local features of the data through convolutional operations.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!