Evaluation Of Mitigation Strategies Research Articles

In‐Water Bridge Construction Effects on Manatees with Implications for Marine Megafauna Species

ABSTRACTGlobally, increasing coastal development requires construction and maintenance of transportation infrastructure that affects terrestrial and aquatic ecosystems. Construction of bridges as part of transportation networks introduces a series of risks to aquatic species near construction zones. We reviewed relevant literature and obtained exemplary case studies to synthesize potential effects of bridge construction on the West Indian manatee (Trichechus manatus), a nearshore megafauna species vulnerable to human activities. Stages of bridge construction including dredging, pile driving, and installation and assembly of bridge components each involve potential direct and indirect effects on manatees. Direct effects such as vessel interactions, entanglement or ingestion, and entrainment may result in acute physical injury or mortality. Indirect effects from construction such as habitat obstruction or degradation and increased noise from construction activities can alter behavior and intraspecies communication and reduce access to essential resources. Some effects of construction may be immediately difficult to quantify, but cumulative effects through time can result in major habitat and species loss. To prevent large‐scale negative effects of construction on manatees and other aquatic species, use and evaluation of mitigation strategies should be implemented pre‐, during, and post‐construction. As the global human population increasingly occupies coastal zones, effective planning of coastal development, including bridge and other in‐water construction, will be essential to support conservation and recovery efforts for manatees and other species at risk in these areas. © 2021 The Wildlife Society.

Assessing the burden of congenital rubella syndrome in China and evaluating mitigation strategies: a metapopulation modelling study

A rubella vaccine was licensed in China in 1993 and added to the Expanded Programme on Immunization in 2008, but a national cross-sectional serological survey during 2014 indicates that many adolescents remain susceptible. Maternal infections during the first trimester often cause miscarriages, stillbirths, and, among livebirths, congenital rubella syndrome. We aimed to evaluate possible supplemental immunisation activities (SIAs) to accelerate elimination of rubella and congenital rubella syndrome. We analysed residual samples from the national serological survey done in 2014, data from monthly rubella surveillance reports from 2005 and 2016, and additional publications through a systematic review. Using an age-structured population model with provincial strata, we calculated the reproduction numbers and evaluated the gradient of the metapopulation effective reproduction number with respect to potential supplemental immunisation rates. We corroborated these analytical results and estimated times-to-elimination by simulating SIAs among adolescents (ages 10-19 years) and young adults (ages 20-29 years) using a model with regional strata. We estimated the incidence of rubella and burden of congenital rubella syndrome by simulating transmission in a relatively small population lacking only spatial structure. By 2014, childhood immunisation had reduced rubella's reproduction number from 7·6 to 1·2 and SIAs among adolescents were the optimal elimination strategy. We found that less than 10% of rubella infections were reported; that although some women with symptomatic first-trimester infections might have elected to terminate their pregnancies, 700 children could have been born with congenital rubella syndrome during 2014; and that timely SIAs would avert outbreaks that, as susceptible adolescents reached reproductive age, could greatly increase the burden of this syndrome. Our findings suggest that SIAs among adolescents would most effectively reduce congenital rubella syndrome as well as eliminate rubella, owing both to fewer infections in the immunised population and absence of infections that those immunised would otherwise have caused. Metapopulation models with realistic mixing are uniquely capable of assessing such indirect effects. WHO and National Science Foundation.

Regional CO2 impact assessment of road infrastructure improvements

Transparent methods of estimating CO2 emissions from transportation sources are necessary to evaluate mitigation strategies. This study proposes a framework to assess the regional impact of roadway designs on CO2 emissions. First, three roadway infrastructure configurations were designed to improve the traffic flow at intersections and interchanges. Second, the economical and environmental life-cycle cost assessments of constructing and maintaining new infrastructures were developed. Then, the effects of infrastructure on regional vehicle CO2 emissions were modeled using a simulation-based dynamic traffic assignment model coupled with the U.S. Environmental Protection Agency's MOtor Vehicle Emission Simulator (MOVES) model. The case study estimated that converting 72 stop signs to roundabouts within El Paso, TX, reduced daily vehicular CO2 emissions by more than 50 tonnes, paying back the CO2 from construction and maintenance within 2.5 to 2.9 years. The roundabout modifications' cost-effectiveness ranged from $30 to $130 per tonne of CO2 over a 30-year assessment.

Topological and Thermodynamic Entropy Measures for COVID-19 Pandemic through Graph Theory

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused the global pandemic, coronavirus disease-2019 (COVID-19) which has resulted in 60.4 million infections and 1.42 million deaths worldwide. Mathematical models as an integral part of artificial intelligence are designed for contact tracing, genetic network analysis for uncovering the biological evolution of the virus, understanding the underlying mechanisms of the observed disease dynamics, evaluating mitigation strategies, and predicting the COVID-19 pandemic dynamics. This paper describes mathematical techniques to exploit and understand the progression of the pandemic through a topological characterization of underlying graphs. We have obtained several topological indices for various graphs of biological interest such as pandemic trees, Cayley trees, Christmas trees, and the corona product of Christmas trees and paths. We have also obtained an analytical expression for the thermodynamic entropies of pandemic trees as a function of R0, the reproduction number, and the level of spread, using the nested wreath product groups. Our plots of entropy and logarithms of topological indices of pandemic trees accentuate the underlying severity of COVID-19 over the 1918 Spanish flu pandemic.

Testing and modeling of hurricane wind-driven rain water ingress, propagation, and subsequent interior damage in residential buildings

Hurricanes are a main cause of economic losses in the world, including Florida. They affect exterior, interior, and the contents of residential buildings. The interior damage can be as much as half of the cost of total damage, but the estimation of the interior damage is still somewhat crude. Most damage models estimate interior damage as a percentage of the exterior damage, or through simple relationships, that relate the height of water ingress in the building to the interior damage. This paper presents a new model for interior and contents damage estimations, which takes into account the physical mechanisms of hurricane-induced interior and contents damage from rainwater ingress. The method incorporates the results of large and full-scale tests to quantify the rainwater propagation and distribution from component to component in the interior of the building, and combines the test results with estimates of water resistance characteristics of the building interior and contents, and with cost analyses. The model is part of the commercial residential low-rise vulnerability model of the Florida Public Hurricane Loss Model (FPHLM). The paper presents the impact of the model on the FPHLM vulnerability curves, and illustrates how the new model can help evaluate mitigation strategies.

P.344 Effects of antidepressants on BDNF levels in patients with major depression: a systematic review

Hurricanes are a main cause of economic losses in the world, including Florida. They affect exterior, interior, and the contents of residential buildings. The interior damage can be as much as half of the cost of total damage, but the estimation of the interior damage is still somewhat crude. Most damage models estimate interior damage as a percentage of the exterior damage, or through simple relationships, that relate the height of water ingress in the building to the interior damage. This paper presents a new model for interior and contents damage estimations, which takes into account the physical mechanisms of hurricane-induced interior and contents damage from rainwater ingress. The method incorporates the results of large and full-scale tests to quantify the rainwater propagation and distribution from component to component in the interior of the building, and combines the test results with estimates of water resistance characteristics of the building interior and contents, and with cost analyses. The model is part of the commercial residential low-rise vulnerability model of the Florida Public Hurricane Loss Model (FPHLM). The paper presents the impact of the model on the FPHLM vulnerability curves, and illustrates how the new model can help evaluate mitigation strategies.

Estimating the location of individual livestock holdings and their populations in two developing countries for use in spatial disease spread models

Infectious diseases of food animals, such as Foot-and-Mouth Disease (FMD), pose severe impacts on animal trade, animal products and subsequently endanger global food security. FMD is endemic in many parts of the world and is associated with substantial economic losses, which require risk assessments, preparedness planning, and evaluation of the effectiveness of mitigation strategies that fit within a country’s sociopolitical and socioeconomic constraints. Spatially-explicit stochastic simulation models (SESS) have become a common tool for estimating the spread and impact of FMD. SESS models incorporate uncertainty in the input and output parameters, heterogeneity in disease processes, and integrate geographic locations and spatial proximity of holdings that affect their relative exposure and transmission risk. An essential input to these models is locational data for holdings of animals and associated animal populations in each holding.Several efforts have been made to predict the location and population of livestock holdings or population density at different spatial resolutions. These methods or data cannot be used in developing countries because either the data is too coarse, or the inputs required for the methods are not available in resource-limited countries. As such, there is a need to adapt the practical and reliable existing methods to generate simulated datasets depicting the location and population of individual livestock holdings in developing countries for use in SESS models.We generated spatially-resolved simulated datasets for the location and population density of individual livestock holdings in Pakistan and Thailand. Firstly, we microsimulated and downscaled the census data to individual holdings based on statistical distributions. Second, geospatial probability surfaces were created based on a survey of expert veterinarians and empirical holding locations. Third, holdings were randomly placed on the probability surface based on a set of rules. These holdings were assigned population of livestock by joining downscaled data and random holdings. The combined dataset on the location and population of individual livestock holdings was, finally, used to generate the density of holdings.To our knowledge, this was the first attempt to estimate the locations and populations of individual livestock holdings in developing countries. These data pave the way for the application of SESS models in developing countries to understand the spread of FMD and evaluate mitigation strategies. The control of such an important animal disease would improve livestock health, improve economic gains for producers, and help alleviate poverty and hunger, which will complement efforts to attain the 2030 Sustainable Development Goals.

COVID-19 Trends Among School-Aged Children - United States, March 1-September 19, 2020.

Approximately 56 million school-aged children (aged 5-17 years) resumed education in the United States in fall 2020.* Analysis of demographic characteristics, underlying conditions, clinical outcomes, and trends in weekly coronavirus disease 2019 (COVID-19) incidence during March 1-September 19, 2020 among 277,285 laboratory-confirmed cases in school-aged children in the United States might inform decisions about in-person learning and the timing and scaling of community mitigation measures. During May-September 2020, average weekly incidence (cases per 100,000 children) among adolescents aged 12-17 years (37.4) was approximately twice that of children aged 5-11 years (19.0). In addition, among school-aged children, COVID-19 indicators peaked during July 2020: weekly percentage of positive SARS-CoV-2 test results increased from 10% on May 31 to 14% on July 5; SARS-CoV-2 test volume increased from 100,081 tests on May 31 to 322,227 on July 12, and COVID-19 incidence increased from 13.8 per 100,000 on May 31 to 37.9 on July 19. During July and August, test volume and incidence decreased then plateaued; incidence decreased further during early September and might be increasing. Percentage of positive test results decreased during August and plateaued during September. Underlying conditions were more common among school-aged children with severe outcomes related to COVID-19: among school-aged children who were hospitalized, admitted to an intensive care unit (ICU), or who died, 16%, 27%, and 28%, respectively, had at least one underlying medical condition. Schools and communities can implement multiple, concurrent mitigation strategies and tailor communications to promote mitigation strategies to prevent COVID-19 spread. These results can provide a baseline for monitoring trends and evaluating mitigation strategies.

Reductions in traffic-related black carbon and ultrafine particle number concentrations in an urban neighborhood during the COVID-19 pandemic

We investigated changes in traffic-related air pollutant concentrations in an urban area during the COVID-19 pandemic. The study was conducted in a mixed commercial-residential neighborhood in Somerville (MA, USA), where traffic is the dominant source of air pollution. Measurements were made between March 27 and May 14, 2020, coinciding with a dramatic reduction in traffic (71% drop in car and 46% drop in truck traffic) due to business shutdowns and a statewide stay-at-home advisory. Indicators of fresh vehicular emissions (ultrafine particle number concentration [PNC] and black carbon [BC]) were measured with a mobile monitoring platform on an interstate highway and major and minor roadways. Our results show that depending on road class, median PNC and BC contributions from traffic were 60–68% and 22–46% lower, respectively, during the lockdown compared to pre-pandemic conditions, and corresponding reductions in total on-road concentrations were 45-69% and 22-56%, respectively. A higher BC: PNC concentration ratio was observed during the lockdown period likely indicative of the higher fraction of diesel vehicles in the fleet during the lockdown. Overall, the scale of reductions in ultrafine particle and BC concentrations was commensurate with the reductions in traffic. This natural experiment allowed us to quantify the direct impacts of reductions in traffic emissions on neighborhood-scale air quality, which are not captured by the regional regulatory-monitoring network. These results underscore the importance of measurements of appropriate proxies for traffic emissions at relevant spatial scales. Our results are useful for exposure analysis as well as city and regional planners evaluating mitigation strategies for traffic-related air pollution.

Seasonal variations and spatial distribution of particulate matter emissions from a ventilated laying hen house in Northeast China

With the development of concentrated animal feeding operations in China, the air pollution problem has drawn widespread public attention. Residents living near farms are suffering from the emissions of particulate matter (PM) and odors. However, scientific data on the characteristics of these emissions are limited to the establishment and evaluation of mitigation strategies in China. This study was conducted to provide fundamental information on the concentrations of PM inside and outside a typical ventilated laying hen house in northeastern China. The results showed that outdoor PM concentrations of this laying hen house did not meet the requirements of the environmental quality standard of China’s livestock and poultry farms in the two days out of six sampling days in summer, while indoor PM concentrations met the environmental requirements during this study. The indoor and outdoor PM concentrations were highly correlated in summer, and over 60% of particles indoor were emitted outside via mechanical ventilation. There were more fine particles dominated both inside and outside of the laying hen house. Besides, twelve and nine elements were measured from the PM sources inside and outside laying hen house, respectively. PM control strategies may be adjusted based on the status of exhaust fans, the ages of laying hens, atmospheric conditions, and routine house management to well reduce PM emissions and improve control efficiency. Keywords: particulate matter, ventilated laying hen house, air emission, animal feeding operation DOI: 10.25165/j.ijabe.20201303.5111 Citation: Guo L, Zhao D S, Zhao B, Ma S L, Liu X L, Li M, et al. Seasonal variations and spatial distribution of particulate matter emissions from a ventilated laying hen house in Northeast China. Int J Agric & Biol Eng, 2020; 13(3): 57–63.

Ship Emission Mitigation Strategies Choice Under Uncertainty

Various mitigation strategies have been proposed to reduce the CO2 emissions from ships, which have become a major contributor to global emissions. The fuel consumption under different mitigation strategies can be evaluated based on two data sources, real data from the real ship systems and simulated data from the simulation models. In practice, the uncertainties in the obtained data may have non-negligible impacts on the evaluation of mitigation strategies. In this paper, a Gaussian process metamodel-based approach is proposed to evaluate the ship fuel consumption under different mitigation strategies. The proposed method not only can incorporate different data sources but also consider the uncertainties in the data to obtain a more reliable evaluation. A cost-effectiveness analysis based on the fuel consumption prediction is then applied to rank the mitigation strategies under uncertainty. The accuracy and efficiency of the proposed method is illustrated in a chemical tanker case study, and the results indicate that it is critical to consider the uncertainty, as they can lead to suboptimal decisions when ignored. Here, trim optimisation is ranked more effective than draft optimisation when the uncertainty is ignored, but the reverse is the case when the uncertainty in the estimations are fully accounted for.

Life cycle assessment of fruit and vegetable production in the Region of Murcia (south-east Spain) and evaluation of impact mitigation practices

The Region of Murcia (south-east Spain) is a world-leading agricultural producer which exports 2.5 million tonnes of fruit and vegetables per year. It holds a leading position in international sales of many fresh products including lettuce, broccoli, lemon, melon and artichoke. However, the sustainability of this highly profitable business is in the spotlight as concerns mount regarding environmental exhaustion caused by intensive farming. To gain a more objective perspective, we present the first quantification of the environmental impacts of the fruit and vegetable production systems in this region using a “cradle-to-gate” life cycle assessment. We provide standard measurable values of resource depletion; acidification and eutrophication hazards; global warming potential; and use of water resources. Once the crops and agricultural stages in critical need of intervention are identified, we propose and evaluate mitigation strategies to curb their impact.Our results show that in general woody crops have bigger footprints than vegetable crops, as they usually demand higher amounts of energy, pesticides, fertilisers and water, for considerably lower yields. Nonetheless, a turnabout in the carbon footprint was observed when CO2 fixation, which is commonly not included in Life Cycle Assessments (LCAs), was accounted for. This is due to the fact that woody crops, despite having higher emissions, are more efficient carbon sinks. When analysing impacts per agricultural stage, our results add more weight to the growing body of LCA-based evidence that irrigation, field work operations and fertiliser production have the most detrimental impacts. The most promising impact-mitigation action was the replacement of mineral fertiliser with manure, which offered potential footprint reductions of up to 10% and 21% for vegetable and woody crops, respectively. For woody crops, moderate impact reductions (up to 6% without a decline in yield) can also be achieved with deficit irrigation, which can be applied in synergy with mulching or organic fertilising. Finally, we compared our results against previous studies and highlighted comparability limitations, such as the inter-annual productivity fluctuations and the wide variability in agricultural practices.

Mathematical modeling of air pollution in city tunnels and evaluating mitigation strategies

A mаthemаtical model has been developed that is able to describe the environment of the city tunnels being affected by the road traffic, natural and forced air convective flows. The mathematical model describes the peculiarities of the traffic flows on one-lane roads with a satisfactory accuracy. The model well matches experimental data on traffic flows. Multidimensional calculations of the influence of cars on the airflow in tunnels are performed. The numerical model for simulating exhaust gas emissions by automobiles and their accumulation in a tunnel and evolution with traffic induced air flow was developed. The results of numerical investigations make it possible providing recommendations for transport researchers and policy-makers. In particular, it was shown that in the presence of long tunnels on automobile roads it is necessary to choose the traffic arrangement avoiding the necessity for vehicles to come to a full stop and then accelerate in tunnels. This could happen in the presence of traffic lights or other type of traffic regulation near the exit of the tunnel. Thus it is necessary in arranging traffic regulation avoiding placing traffic lights in the proximity of tunnel exit for the waiting cars line to be shorter than the distance from the tunnel exit. In venting the tunnel, the direction of the wind should coincide with the direction of traffic flow. Attempts to arrange venting in the opposite direction for high blockage ratio of a tunnel by vehicles could result in bringing to a worse situation with air pollution.

Seasonal variations and spatial distribution of particulate matter emissions from a ventilated laying hen house in Northeast China

With the development of concentrated animal feeding operations in China, the air pollution problem has drawn widespread public attention. Residents living near farms are suffering from the emissions of particulate matter (PM) and odors. However, scientific data on the characteristics of these emissions are limited to the establishment and evaluation of mitigation strategies in China. This study was conducted to provide fundamental information on the concentrations of PM inside and outside a typical ventilated laying hen house in northeastern China. The results showed that outdoor PM concentrations of this laying hen house did not meet the requirements of the environmental quality standard of China’s livestock and poultry farms in the two days out of six sampling days in summer, while indoor PM concentrations met the environmental requirements during this study. The indoor and outdoor PM concentrations were highly correlated in summer, and over 60% of particles indoor were emitted outside via mechanical ventilation. There were more fine particles dominated both inside and outside of the laying hen house. Besides, twelve and nine elements were measured from the PM sources inside and outside laying hen house, respectively. PM control strategies may be adjusted based on the status of exhaust fans, the ages of laying hens, atmospheric conditions, and routine house management to well reduce PM emissions and improve control efficiency. Keywords: particulate matter, ventilated laying hen house, air emission, animal feeding operation DOI: 10.25165/j.ijabe.20201303.5111 Citation: Guo L, Zhao D S, Zhao B, Ma S L, Liu X L, Li M, et al. Seasonal variations and spatial distribution of particulate matter emissions from a ventilated laying hen house in Northeast China. Int J Agric & Biol Eng, 2020; 13(3): 57–63.

Estimating Herd-Scale Methane Emissions from Cattle in a Feedlot Using Eddy Covariance Measurements and the Carbon Dioxide Tracer Method.

Measurements of methane (CH) emissions from ruminants could provide invaluable data to reduce uncertainties in the global CH budget and to evaluate mitigation strategies to lower greenhouse gas emissions. The main objective of this study was to evaluate a new CO tracer (COT) approach that combined CH and CO atmospheric concentrations with eddy covariance (EC) CO flux measurements to estimate CH emissions from cattle in a feedlot. A closed-path EC system was used to measure CH and CO fluxes from a feedlot in Kansas. The EC flux measurements were scaled from landscape to animal scale using footprint analyses. Emissions of CH from the cattle were also estimated using the COT approach and measured CO and CH concentration, and scaled EC CO fluxes. The CH and CO concentration ratios showed a distinct diel trend with greater values during the daytime. Average monthly CH emission estimates using the COT approach ranged from 72 to 127 g animal d, which was consistent with the values reported in other studies that had similar animal characteristics. The COT method CH emission estimates showed good agreement with scaled CH EC fluxes (slope = 0.9 and = 0.8) for cold and dry months. However, the agreement between the two techniques was significantly reduced (slope = 1.5 and = 0.6) during wet and warm months. On average, the COT method CH emission estimates were 3% greater than the EC CH emissions. Overall, our results suggest that the COT method can be used to estimate enteric feedlot CH emissions.

Pollution characteristics and risk assessment of ambient PM2.5-bound PAHs and NPAHs in typical Japanese and New Zealand cities and rural sites

Nine polycyclic aromatic hydrocarbons (PAHs) and six nitro-PAHs (NPAHs) were measured in PM2.5 samples collected over one year (2016–2017) in two cities: Kanazawa (Japan) and Auckland (New Zealand) and their respective rural background sites: Wajima in Noto Peninsula (Japan) and Tapora in Okahukura Peninsula (New Zealand). The mean concentrations of ΣPAHs and ΣNPAHs followed similar distribution profiles in both countries, with higher concentrations in the urban than rural sites. The mean of ΣPAHs in Kanazawa City was 0.53 ng/m3 and represented the highest total concentration compared to the other three sites. Conversely, the highest ΣNPAHs concentrations were measured in Auckland City (48.2 pg/m3). Diagnostic ratios and principal component analysis revealed that automobiles were the main sources of PAHs and NPAHs in both cities, whereas coal combustion and domestic wood burning were the dominant sources of PAHs and NPAHs in rural sites in Japan and New Zealand. Back trajectory analyses showed that high levels of PAHs detected at Wajima were the result of long-range transport from China and Mongolia in winter, which was not observed at the other sites. Considering the adverse health effects of PM2.5, further studies and continuous monitoring of atmospheric PAHs and NPAHs are necessary to evaluate mitigation strategies in both hemispheres.

Evaluation of Mitigation Strategies in Shipping Industry Using a Metamodel Based Method

Shipping is a major contributor to the global CO2 emissions. In order to reduce the ship emissions, various mitigation strategies have been proposed including technical and operational strategies. As it is usually not possible to implement all these mitigation strategies, it is important to evaluate the efficiency of these strategies. For mitigation strategies evaluation, ship energy systems are often used for assessment from a systems perspective. However, ship energy systems are usually quite complex for analysis. This is because they are constructed by many components and these components may have non-linear correlations. In this paper, a Gaussian process metamodel based method is proposed to evaluate the ship mitigation strategies. This method is much more efficient than directly analyzing the ship energy systems when they are computationally expensive to assess. A ship energy system of a chemical tanker is analyzed in this paper. The results indicate that speed reduction has a large abatement potential and all the considered strategies have correlations with each other.

The effects of a motorway on movement behaviour and gene flow in a forest carnivore: Joint evidence from road mortality, radio tracking and genetics

Roads represent barriers to animal movement due to physical obstruction, mortality, or behavioural avoidance. The population-level consequences of such constraints remain poorly understood, because successful crossings may be sufficient to counteract negative effects of fragmentation and isolation. Here we examine the individual- and population-level barrier effects of a motorway on the common genet Genetta genetta, by combining long-term road mortality, radio tracking and population genetics data. We found 84 genets killed at roads, of which 68% were subadults, with a peak mortality during the dispersal period. The home ranges of resident adults often bordered the motorway, and their sizes were similar close to (314 ha, n = 9) and far from (258 ha, n = 10) the motorway. The crossing rate was much higher for dispersing subadults (4.1 crossings/100 nights, n = 3) than for resident adults living near the motorway (0.2 crossings/100 nights, n = 9), though the number of tracked subadults crossing the motorway was low. Genetic kinship analysis revealed seven crossings based on father-offspring and half-sibling relationships. There was no significant genetic differentiation related to the motorway. The movement of residents were strongly constrained by the motorway, though gene flow mediated by successful crossings, particularly by subadults, likely prevented genetic differentiation. Genet movements across the motorway were probably facilitated by low traffic flow and the presence of crossing structures. Our study implies that evaluating mitigation strategies to reduce the barrier effects of roads would benefit from the integration of mortality, animal behaviour, and population genetics data, to increase effectiveness and avoid wasting scarce conservation resources.

Comparing methane emissions estimated using a backward-Lagrangian stochastic model and the eddy covariance technique in a beef cattle feedlot

Accurate methodologies to measure emissions of greenhouse gases (GHG) from livestock systems are necessary to improve the emission coefficients used in national GHG inventories and to evaluate mitigation strategies. The objective of this study was to compare methane (CH4) emissions estimated using the eddy covariance (EC) technique and a backward-Lagrangian stochastic (bLS) model. A closed-path EC system was used to measure CH4 fluxes in a commercial beef cattle feedlot. The EC fluxes were scaled from the feedlot to the animal scale using a footprint analysis. The EC measurements of CH4 concentration and wind data were used with the bLS model to infer CH4 emissions. The average CH4 emissions (±standard deviation) during the experiment were 87 (±30) g animal−1 d−1 and 85 (± 27) g animal−1 d−1 for EC and bLS techniques, respectively. These values are consistent with the results from previous studies with similar animal and feed characteristics. Both techniques were able to capture a pronounced daytime and nighttime variation in CH4 emissions, with higher CH4 emissions during the day and lower emissions at night. Our results indicate that the eddy covariance technique combined with footprint models can be successfully used to accurately measure enteric CH4 from cattle.

EFFECTS OF COVER CROPPPING ON NITROGEN DIOXIDE, CARBON DIOXIDE AND METHANE FLUXES AND SOIL ENZYME ACTIVITIES IN CORN-SOYBEAN ROTATION SYSTEM

The effect of cover crops (ryegrass, hairy vetch, and oilseed radish) in terms of microbial biomass carbon (MBC), C and N mineralization, and enzymatic activities in a corn-wheat-soybean cropping systems under a Mollisol was evaluated. The distributions of total organic C (TOC), total Kjeldahl N (TKN), microbial biomass C (MBC), readily mineralizable C and N, and five enzyme activities (β-glucosidase, β-glucosaminidase, acid phosphatase, arylamidase, and fluorescein diacetate hydrolysis) involved in the cycling of C, N, P and S were studied in three soil depths (0-5. 5-10, 10-20 cm) while soil surface fluxes of carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) were estimated. Ryegrass showed higher activity in acid phosphatase, β-glucosidase and β-glucosaminidase. Ryegrass and hairy vetch significantly increased organic C and N, and MBC. Level of mineralized C and N were the same in ryegrass and hairy vetch. There was no clear variation in CO2, N2O and CH4 fluxes from the cover crop treatments. N2O fluxes increased with an increase in soil moisture. The negative CH4 fluxes manifest the soil as CH4 sink. No significant differences among cover crop treatments in terms of CO2-C, N2O-N and CH4-C emissions, a reflection that their emissions are highly variable. Empirical data on carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O) fluxes are important in management systems to evaluate mitigation strategies, while microbial biomass and enzyme activities can be used as sensitive indicators of ecological stability.