According to the available guidelines, good practices for calculating nitrous oxide (N
O) emission factors (EFs) for livestock excreta and manure application include that sampling duration should be ...of at least one year after the nitrogen (N) application or deposition. However, the available experimental data suggest that in many cases most emissions are concentrated in the first months following N application. Therefore resources could be better deployed by measuring more intensively during a shorter period. This study aimed to assess the contribution of the N
O flux in the period directly after N application to the annual net emission. We used a database of 100 year-long plot experiments from different excreted-N sources (dung, urine, farmyard manure and slurry) used to derive EFs for the UK and Ireland. We explored different shorter potential measurement periods that could be used as proxies for cumulative annual emissions. The analysis showed that the majority of emissions occur in the first months after application, especially in experiments that i) had urine as the N source, ii) had spring N application, iii) were conducted on fine-textured soils, or iv) showed high annual emissions magnitude. Experiments that showed a smaller percentage of emissions in the first months also had a low magnitude of annual net emissions (below 370 gN
O-N ha
year
), so the impact of measuring during a shorter period would not greatly influence the calculated EF. Accurate EF estimations were obtained by measuring for at least 60 days for urine (underestimation: 7.1%), 120 days for dung and slurry (4.7 and 5.1%) and 180 days for FYM (1.4%). At least in temperate climates, these results are promising in terms of being able to estimate annual N
O fluxes accurately by collecting data for less than 12 months, with significant resource-saving when conducting experiments towards developing country-specific EFs.
Background The Antimicrobial Resistance Laboratory Network (AR Lab Network) was developed by the CDC to detect emerging antimicrobial-resistant (AR) threats and prevent outbreaks. However, low ...submission rates of AR isolates limit the potential of the AR Lab Network to address antimicrobial resistance (AMR). Aim The aim of this study was to investigate barriers to submission of AR isolates in acute care hospitals (ACHs) and critical access hospitals (CAHs) within Texas Public Health Region 8 (PHR8) counties. Methods A survey was designed and emailed to laboratory professionals to identify barriers to AR isolate submission. Responses were analyzed using 2-sided Fisher’s exact tests to identify associations between responses and respondent characteristics. Results Of the 33 hospitals within PHR8 invited to participate in the survey, responses were received from 21, a response rate of 63.6%. Lack of awareness of the AR Lab Network was the most frequently cited barrier to submission (65.4% of respondents). Other reported barriers to submission included lack of laboratory staff time (57.7%), lack of training with the submission process (34.6%), lack of personnel certified to ship infectious substances (23.1%), and lack of laboratory/shipping supplies (23.1%). Discussion Regardless of the respondent’s role, time in that role, or type of hospital in which they worked, the most common barrier to isolate submission was lack of awareness of the AR Lab Network. In the future, we will address the identified barriers by implementing educational outreach programs about AMR and the AR Lab Network for hospitals and other healthcare facilities within PHR8.
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