Dispersion modeling of odours emitted from pig farms: winter-spring measurements

2013 ◽  
Vol 12 (1) ◽  
pp. 46-53
Keyword(s):  
Hydrogen Sulfide ◽  
Volatile Fatty Acids ◽  
Dispersion Model ◽  
Daily Basis ◽  
Probability Of Detection ◽  
Dispersion Modeling ◽  
Emission Data ◽  
Pig Farms ◽  
Pig Farm ◽  
Odour Emissions

One of the main environmental impacts of pig farms are the swine odours emitted from the various stages of the process. The main cause of odour emissions from pig farms are the anaerobic processes in manure. Numerous factors affect odour emissions such as diet, manure management and manure age. The majority of the odorous compounds emitted from pig farms are sulfurous organic compounds, hydrogen sulfide, phenols and indoles, ammonia, volatile amines and volatile fatty acids (VFA’s) whose presence in the atmosphere causes annoyance at relatively low concentrations. However, the detection and quantification of these compounds at a daily basis is difficult because of their chemical instability and the fact that they can be tracked only using techniques of gas chromatography. For the needs of the present study many instantaneous measurements performed during the day in order to estimate the daily variation of their emissions. This is the reason why the compounds studied were hydrogen sulfide and ammonia. Both compounds have low odour threshold (0.47 ppb for hydrogen sulfide and 130 ppb for ammonia). In the present study, the results of odour concentration measurements sampled from a pig production unit placed close to the city of Rethymno (Crete, Greece) are presented. These measurements are used to estimate the emissions of hydrogen sulfide and ammonia from the various chambers of the pig farm. The emission data were used as input data for the dispersion model AERMOD for an area of 10 km2 surrounding the odour source in order to determine the maximum allowed emissions in order not to cause complaints from nearby residents. Modifications were performed in the model based on the “peak to mean” ratio in order to predict the maximum odour concentrations with few seconds time-scale. Also, relations between odour annoyance and odour exposure concentrations have been used in order to express the odour impacts in terms of probability of detection, probability of discrimination and degree of annoyance. These parameters were embedded into the AERMOD model in order to be able to use this program as an odour dispersion model. The results are provided as probability of detection and probability of annoyance instead of hourly mean concentrations. Several scenarios were examined using the modified AERMOD program taking into account the complex terrain around the pig farm. Finally, the effect of raising the height of the stacks to the concentrations around the facility was examined as a possible solution to the situation.

PROBLEMS CAUSED BY SMALL PIG FARM ODOR AROUND THE WESTERN SONGKHLA LAKE BASIN

2017 ◽  
Vol 2 (1) ◽  
pp. 1-13
Author(s):  
Papontee Teeraphan
Keyword(s):  
Air Pollution ◽  
Lake Basin ◽  
Urgent Problem ◽  
The Public ◽  
Pig Farms ◽  
Pig Farm ◽  
The Government ◽  
The Moment ◽  
Source Of Information ◽  
Proper Solutions

Pollution is currently a significant issue arising awareness throughout the world. In Thailand, pollution can often be seen in any part of the country. Air pollution is pointed as an urgent problem. This pollution has not damaged only to human health and lives, it has destroyed environment, and possibly leading to violence. In Phattalung, air pollution is affecting to the residents’ lives. Especially, when the residents who are mostly agriculturists have not managed the waste resulted from the farm. In Phattalung, at the moment, there are many pig farms, big and small. Some of them are only for consuming for a family, some, however, are being consumed for the business which pigs will be later purchased by big business companies. Therefore, concerning pollution, the researcher and the fund giver were keen to focus on the points of the air pollution of the small pig farms. This is because it has been said that those farms have not been aware on the pollution issue caused by the farms. Farm odor is very interesting which can probably lead to following problems. The researcher also hopes that this research can be used as a source of information by the government offices in order to be made even as a policy or a proper legal measurement. As the results, the study shows that, first, more than half of the samples had smelled the farm odor located nearby their communities, though it had not caused many offenses. Second, the majority had decided not to act or response in order to solve the odor problem, but some of them had informed the officers. The proper solutions in reducing offenses caused by pig farm odor were negotiation and mediation. Last, the majority does not perceive about the process under the Public Health Act B.E. 2535.

scholarly journals Determination of time- and height-resolved volcanic ash emissions and their use for quantitative ash dispersion modeling: the 2010 Eyjafjallajökull eruption

2011 ◽  
Vol 11 (9) ◽  
pp. 4333-4351 ◽  
Author(s):  
A. Stohl ◽  
A. J. Prata ◽  
S. Eckhardt ◽  
L. Clarisse ◽  
A. Durant ◽  
...  
Keyword(s):  
Volcanic Ash ◽  
Dispersion Model ◽  
A Priori ◽  
Volcanic Eruptions ◽  
General Nature ◽  
Aviation Industry ◽  
Dispersion Modeling ◽  
Source Information ◽  
European Area ◽  
Ash Dispersion

Abstract. The April–May, 2010 volcanic eruptions of Eyjafjallajökull, Iceland caused significant economic and social disruption in Europe whilst state of the art measurements and ash dispersion forecasts were heavily criticized by the aviation industry. Here we demonstrate for the first time that large improvements can be made in quantitative predictions of the fate of volcanic ash emissions, by using an inversion scheme that couples a priori source information and the output of a Lagrangian dispersion model with satellite data to estimate the volcanic ash source strength as a function of altitude and time. From the inversion, we obtain a total fine ash emission of the eruption of 8.3 ± 4.2 Tg for particles in the size range of 2.8–28 μm diameter. We evaluate the results of our model results with a posteriori ash emissions using independent ground-based, airborne and space-borne measurements both in case studies and statistically. Subsequently, we estimate the area over Europe affected by volcanic ash above certain concentration thresholds relevant for the aviation industry. We find that during three episodes in April and May, volcanic ash concentrations at some altitude in the atmosphere exceeded the limits for the "Normal" flying zone in up to 14 % (6–16 %), 2 % (1–3 %) and 7 % (4–11 %), respectively, of the European area. For a limit of 2 mg m−3 only two episodes with fractions of 1.5 % (0.2–2.8 %) and 0.9 % (0.1–1.6 %) occurred, while the current "No-Fly" zone criterion of 4 mg m−3 was rarely exceeded. Our results have important ramifications for determining air space closures and for real-time quantitative estimations of ash concentrations. Furthermore, the general nature of our method yields better constraints on the distribution and fate of volcanic ash in the Earth system.

scholarly journals The Neural Network Assisted Land Use Regression

Atmosphere ◽  
2021 ◽  
Vol 12 (4) ◽  
pp. 452
Author(s):  
Jan Bitta ◽  
Vladislav Svozilík ◽  
Aneta Svozilíková Krakovská
Keyword(s):  
Neural Network ◽  
Land Use ◽  
Linear Regression ◽  
Dispersion Model ◽  
Land Use Regression ◽  
Emission Data ◽  
Pollution Dispersion ◽  
Factors Affecting ◽  
Standard Linear

Land Use Regression (LUR) is one of the air quality assessment modelling techniques. Its advantages lie mainly in a much simpler mathematical apparatus, quicker and simpler calculations, and a possibility to incorporate more factors affecting pollutant concentration than standard dispersion models. The goal of the study was to perform the LUR model in the Polish-Czech-Slovakian Tritia region, to test two sets of pollution data input factors, i.e., factors based on emission data and pollution dispersion model results, to test regression via neural networks and compare it with standard linear regression. Both input datasets, emission data and pollution dispersion model results, provided a similar quality of results in the case when standard linear regression was used, the R2 of the models was 0.639 and 0.652. Neural network regression provided a significantly higher quality of the models, their R2 was 0.937 and 0.938 for the factors based on emission data and pollution dispersion model results respectively.

scholarly journals KAJIAN KRITERIA INVESTASI KONVENSIONAL DAN LINGKUNGAN PETERNAKAN BABI DI KOTA TOMOHON

ZOOTEC ◽  
2019 ◽  
Vol 39 (1) ◽  
pp. 171
Author(s):  
Franky N.S Oroh ◽  
S A.E Moningkey ◽  
I D.R Lumenta
Keyword(s):  
Net Present Value ◽  
Economic Feasibility ◽  
Cost Ratio ◽  
Internal Rate Of Return ◽  
Benefit Cost Ratio ◽  
Investment Plan ◽  
Investment Companies ◽  
Pig Farms ◽  
Pig Farm ◽  
Benefit Cost

ABSTRACTSTUDY OF CONVENTIONAL INVESTMENT CRITERIA AND ENVIRONMENTAL OF PIG FARMING IN TOMOHON CITY. This study aims to analyze the feasibility of conventional (private) and environment (externalities) investment criteria, which determine the extent of the economic feasibility of the externalities investment criteria taking into account the private costs (conventional costs) and externalities costs (environmental costs) in the pig farm agribusiness. This research was conducted in Tomohon, where the sample pig farms that have business scale criterion of <1,000, 1,000-5,000, and > 5,000 heads. The analysis used the analysis of investment criteria to look at the externalities economic feasibility of the pig farms, with the calculation of Net Present Value (NPV), Benefit Cost Ratio (BCR) and Internal Rate of Return (IRR). NPV of conventionally and externalities was greater than zero or positive, these results suggest that the companies have been conventionally sampled financially feasibility, as well as the investment plan of externalities. IRR conventional and externalities is greater than one, these results indicate that the samples with conventional and externalities investment companies are still profitable, especially if the investment is viewed in the environment, it would be beneficial as it will reduce the environmental impact. BC ratio values conventionally and externalities is greater than one, these results suggest that the externalities investment is feasible for conducting.Keywords :Economy, Environment, Pig Farms, Tomohon

Odour creation potential of sludge during composting and drying

2009 ◽  
Vol 4 (3) ◽  
Author(s):  
L. Bouchy ◽  
E. Senante ◽  
P. Dauthuille ◽  
M. Aupetitgendre ◽  
JP Harry ◽  
...  
Keyword(s):  
Fatty Acids ◽  
Volatile Fatty Acids ◽  
Field Trials ◽  
Sulphur Compounds ◽  
Sludge Treatment ◽  
Nitrogenous Compounds ◽  
Different Types ◽  
Odour Emissions ◽  
Sludge Composting ◽  
Industrial Composting

Recent French regulations have driven people to build many composting and drying sites over the last few years. The control of odour nuisance is essential within the framework of the respect of sustainable development, However to be dealt with properly, this issue must be taken into account when designing a facility and throughout its operation. Therefore tools are required to give the means to assess and anticipate odorous emissions. Within this context, a campaign of field trials was launched on several Suez Environnement composting and drying sites. Various types of sludges were treated on different types of industrial composting and drying reactors. In each case the reactor was monitored throughout the sludge treatment and the following compounds analysed: sulphur compounds (H2S, mercaptans, sulphides), nitrogenous compounds (ammonia and amines), aldehydes, ketones, Volatile Fatty Acids, alcohols, VOCs and odours. This work has enabled relevant parameters influencing odour emissions during sludge composting and drying to be determined, and is the basis for a complete composting and drying emissions model.

Use of Source Term and Air Dispersion Modeling in Planning Demolition of Highly Alpha-Contaminated Buildings

2011 ◽  
Author(s):  
James G. Droppo ◽  
Bruce A. Napier ◽  
Jeremy P. Rishel ◽  
Richard W. Bloom
Keyword(s):  
Source Term ◽  
Dispersion Model ◽  
Dispersion Modeling ◽  
Nuclear Materials ◽  
Emission Rates ◽  
The Public ◽  
Air Dispersion Modeling ◽  
Air Dispersion ◽  
Air Dispersion Model ◽  
War Production

The current cleanup of structures related to cold-war production of nuclear materials includes the need to demolish a number of highly alpha-contaminated structures. The process of planning for the demolition of such structures includes unique challenges related to ensuring the protection of both workers and the public. Pre-demolition modeling analyses were conducted to evaluate potential exposures resulting from the proposed demolition of a number of these structures. Estimated emission rates of transuranic materials during demolition are used as input to an air-dispersion model. The climatological frequencies of occurrence of peak air and surface exposures at locations of interest are estimated based on years of hourly meteorological records. The modeling results indicate that downwind deposition is the main operational limitation for demolition of a highly alpha-contaminated building. The pre-demolition modeling directed the need for better contamination characterization and/or different demolition methods—and in the end, provided a basis for proceeding with the planned demolition activities. Post-demolition modeling was also conducted for several contaminated structures, based on the actual demolition schedule and conditions. Comparisons of modeled and monitoring results are shown. Recent monitoring data from the demolition of a UO3 plant shows increments in concentrations that were previously identified in the pre-demolition modeling predictions; these comparisons confirm the validity and value of the pre-demolition source-term and air dispersion computations for planning demolition activities for other buildings with high levels of radioactive contamination.

scholarly journals Comparison of Hydrogen Sulfide Concentrations and Odor Annoyance Frequency Predictions Downwind from Livestock Facilities

Atmosphere ◽  
2020 ◽  
Vol 11 (3) ◽  
pp. 249
Author(s):  
Suraiya Akter ◽  
Erin L. Cortus
Keyword(s):  
Hydrogen Sulfide ◽  
Single Point ◽  
Weighted Average ◽  
Weather Conditions ◽  
Time Of Day ◽  
Dispersion Modeling ◽  
Emission Rates ◽  
Weather Patterns ◽  
Odor Emission ◽  
Odor Annoyance

Estimating and measuring the occurrence of a sensation, odor, around livestock facilities is challenging. This research compares the estimated frequency of odor nuisance with measured hydrogen sulfide (H2S) concentrations at various distances around a swine and a dairy operation, and discusses the results based on time of day, weather conditions, distance, and topography. The estimated odor annoyance-free and odor annoyance frequencies were based on a publically available calculator of odor impact derived from average odor emission rates, historical, and regional weather patterns, and dispersion modeling. Continuous monitoring of H2S was by single point monitors (SPM) at locations around the operations. Time-weighted average H2S concentrations were less than 10 ppb for odor annoyance-free frequencies, and less than 10 to at least 73 ppb for odor-annoyance frequencies. Verifying a proxy odor indicator can help update odor annoyance models and respond to site-specific concerns for existing facilities.

scholarly journals MBR-Assisted VFAs Production from Excess Sewage Sludge and Food Waste Slurry for Sustainable Wastewater Treatment

2020 ◽  
Vol 10 (8) ◽  
pp. 2921 ◽  
Author(s):  
Mohsen Parchami ◽  
Steven Wainaina ◽  
Amir Mahboubi ◽  
David I’Ons ◽  
Mohammad J. Taherzadeh
Keyword(s):  
Wastewater Treatment ◽  
Sewage Sludge ◽  
Food Waste ◽  
Volatile Fatty Acids ◽  
Wastewater Treatment Plants ◽  
Biogas Production ◽  
Economic Assessment ◽  
Ph Control ◽  
Daily Basis ◽  
Solids Concentration

The significant amount of excess sewage sludge (ESS) generated on a daily basis by wastewater treatment plants (WWTPs) is mainly subjected to biogas production, as for other organic waste streams such as food waste slurry (FWS). However, these organic wastes can be further valorized by production of volatile fatty acids (VFAs) that have various applications such as the application as an external carbon source for the denitrification stage at a WWTP. In this study, an immersed membrane bioreactor set-up was proposed for the stable production and in situ recovery of clarified VFAs from ESS and FWS. The VFAs yields from ESS and FWS reached 0.38 and 0.34 gVFA/gVSadded, respectively, during a three-month operation period without pH control. The average flux during the stable VFAs production phase with the ESS was 5.53 L/m2/h while 16.18 L/m2/h was attained with FWS. Moreover, minimal flux deterioration was observed even during operation at maximum suspended solids concentration of 32 g/L, implying that the membrane bioreactors could potentially guarantee the required volumetric productivities. In addition, the techno-economic assessment of retrofitting the membrane-assisted VFAs production process in an actual WWTP estimated savings of up to 140 €/h for replacing 300 kg/h of methanol with VFAs.

scholarly journals Prediction of Ambient Nitrogen Dioxide Concentrations in the Vicinity of Industrial Complex Area, Thailand

2017 ◽  
Vol 10 ◽  
pp. 117862211770090 ◽  
Author(s):  
Supitchaya Tunlathorntham ◽  
Sarawut Thepanondh
Keyword(s):  
Nitrogen Dioxide ◽  
Dispersion Model ◽  
Ground Level ◽  
Ambient Air ◽  
Industrial Complex ◽  
Emission Data ◽  
Mobile Sources ◽  
Tier 1 ◽  
Ambient Air Monitoring ◽  
Full Conversion

The AERMOD dispersion model was evaluated for its performance in predicting 1-hour average nitrogen dioxide (NO2) concentrations in the vicinity of the largest petrochemical industrial complex in Thailand during the period between January 2012 and December 2013. Measured data from 10 ambient air monitoring stations were intensively used to compare with modeled results. Model results indicated that the tier 1 approach (full conversion of NOx to NO2) provided the most accurate results compared with other tiers. It also performed very well in predicting the extreme end of NO2 concentrations. With an absence of emission data from mobile sources, tier 1 was concluded as the most appropriate scheme for prediction of ambient NO2 ground-level concentrations in this study.

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