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2021 ◽  
Author(s):  
Amit Tiwari ◽  
Anurag Durve ◽  
Pradhan Srinivasan ◽  
Jyotirmoy Barman

Author(s):  
Youngbok Lee ◽  
Seungha Lee ◽  
Kyoungdoug Min

Nitrogen oxides (NO x) are one of the main harmful emissions from diesel engines. Regulations on emissions are becoming more stringent; consequently, research should aim at reducing both engine-out NO x and tail-pipe NO x emissions. Exhaust gas recirculation is mainly used to reduce engine-out NO x emissions. After-treatment methods such as lean NO x trap systems and selective catalyst reduction are used to minimize tail-pipe NO x emissions. Real-time feedback control during transient conditions can further reduce these emissions and be utilized when information about real-time engine-out NO x emissions is available. It would be helpful to evaluate the proportion of NO2 in NO x emissions because the conversion efficiency of an after-treatment system is affected by temperature and the NO-to-NO2 ratio. Therefore, a semi-empirical NO x model considering NO and NO2 separately was developed for a diesel engine in this study. The NO estimation model was established based on the extended Zeldovich mechanism. The NO2 estimation model focused on chemical reactions between NO and other species and was based on formation and decomposition mechanisms. This NO x model can contribute to the cost reduction of engine systems by replacing existing NO x sensors and can also be applied to real-time feedback control strategies to minimize NO x emissions.


2021 ◽  
Vol 111 ◽  
pp. 381-385
Author(s):  
Jie Bai ◽  
Shanjun Li ◽  
Danxia Xie ◽  
Hui Zhou

Under the stated goal of improving air quality, many cities in China restricted the import of used vehicles from other cities based on tail pipe emission standards. Using detailed data on new and used vehicle registration, we examine the impact of the policy by leveraging the staggered removal of the restriction during 2016-2018. We find that restriction removal led to a sharp increase in cross-city flow of used vehicles but had no significant impact on local air quality. Unilateral removal of the restriction could reduce new vehicle sales in home cities, but universal removal would boost new vehicle sales nationwide.


2021 ◽  
Author(s):  
Jean Sciare ◽  
Roland Sarda-Estève ◽  
Konstantina Oikonomou ◽  
Elie Bimenyimana ◽  
Michael Pikridas ◽  
...  

<p>Major efforts are currently put to reduce drastically PM emissions at the exhaust of the most recent vehicles, however, little is done to mitigate non-tail-pipe emissions and resuspended road dust, in particular. Such traffic-related resuspension of dust may become a major source of PM10 at a time our cars are becoming cleaner. This may be particularly true in (semi-)arid urban environments which are characterized by high deposition rates of desert dust and low rain wash-out rates of roads.</p><p>Near-real-time (10-min time resolution) on-line measurement of selected cations (Na<sup>+</sup>, Mg<sup>2+</sup>, Ca<sup>2+</sup>) in PM10 were performed using a Particle-into-liquid-sampler (PILS) coupled with an Ion Chromatograph (IC). Such high temporal resolution of these species has been rarely reported in literature and to the best of our knowledge, it is the first time that such dense observations are reported in PM10 for urban environment. These measurements were performed during a 3-month transition period between (from wet winter to dry summer) at an urban background site of Nicosia (Cyprus) a central location of the Eastern Mediterranean Middle East (EMME) region.</p><p>The consistency of these measurements was successfully assessed against 24-h integrated filter-based measurements while hypotheses related to the use of Calcium as a tracer of dust particles further verified against trace metal analysis. A comprehensive suite of co-located ancillary data (Aethalometer, Lidar, ACSM, SMPS, OPC) were used to further support the daily/weekly/monthly variability of Calcium concentration in PM10.</p><p>Diurnal variability of dust concentration in PM10 at our background urban site displayed a strong and intense traffic-related source at rush hours together with a maximum observed in the afternoon in phase with the development of the Planetary Boundary Layer and intrusion of desert dust from aloft. Interestingly, this pattern is amplified when moving from wet to dry months and encompassing the Spring dust season.</p><p>The contribution of the two dust sources in PM10 (traffic-related dust resuspension and intrusion of long-range transported desert dust) is provided here for different temporal scales (day, week, month). Estimate of traffic-related (non-)tail-pipe emissions (ie. combustion carbonaceous vs resuspended dust) is also provided here highlighting the dominant role of dust in PM10 emissions from road transport sector.</p>


2021 ◽  
Author(s):  
Venkatesh T. Lamani ◽  
Adithya U. Baliga M. ◽  
Ajay Kumar Yadav ◽  
Kumar G. N. ◽  
Rudra Naik ◽  
...  
Keyword(s):  

2020 ◽  
Vol 41 (S1) ◽  
pp. s108-s108
Author(s):  
Lauren Franco ◽  
Christine Ganim ◽  
Windy Tanner

Background: Handwashing sinks in healthcare environments are reservoirs for healthcare pathogens and antibiotic-resistant microorganisms (ARO). We investigated the distribution of HCP and ARO within and among handwashing sinks in healthcare settings. To do this, we determined the differences in the number of ARO between samples within a sink (biofilm vs planktonic samples), between sink types (healthcare worker [HCW] vs patient room sinks), and between hospitals in the same city. Methods: Tap water, sink surface, drain cover, tail pipe, p-trap water and p-trap samples were collected from 2 patient room sinks and 2 HCW sinks over 11 months in 2 acute-care hospitals. Suspected pathogens were isolated from selective media (Pseudosel, Chromagar KPC, and MacConkey with 2 mg/L cefotaxime) and identified via MALDI-ToF. Isolates confirmed to be healthcare pathogens were characterized via disk diffusion to determine their antibiotic susceptibility according to CLSI guidelines. Isolates not susceptible to carbapenems (meropenem or ertapenem) were tested further via the modified carbapenem inactivation method to detect carbapenemase production. Results:Pseudomonas aeruginosa and Enterobacteriaceae (Enterobacter spp, Klebsiella spp, and Citrobacter spp) were the most frequently isolated pathogens. Among these isolates (195 P. aeruginosa and 42 Enterobacteriaceae isolates), 28.5% of P. aeruginosa and 85.7% of Enterobacteriaceae were nonsusceptible to 1 or more of the antibiotics tested. Of the isolates that were nonsusceptible to a carbapenem (46 of 237; 19%), none displayed phenotypic carbapenemase production. Other mechanisms of resistance have not been confirmed. There was no significant difference in the percentage of nonsusceptible HCP isolated from biofilm samples (from p-trap and tail pipe) compared to planktonic (p-trap water) samples (P > .05 for P. aeruginosa and Enterobacteriaceae). A greater percentage of resistant or intermediate isolates was recovered from patient room sinks than from HCW sinks (P < .05) for both P. aeruginosa and Enterobacteriaceae isolates (76.4 vs 32.9% for Enterobacteriaceae, 25.6 vs 0.3% for P. aeruginosa). We detected no significant difference in percentage of nonsusceptible isolates between the 2 hospitals sampled (P > .05). Conclusions: This survey of healthcare sinks supports previous work citing that they are reservoirs for HCP and ARO. This work further examines the distribution of HCP and ARO within and among sinks in these environments. Our findings thus far in the 2 hospitals studied reveal a higher percentage of ARO in patient sinks than in HCW sinks. This finding may suggest a higher input of ARO from patient use or greater selective pressure in patient room sinks.Disclosures: NoneFunding: Lauren Franco, Centers for Disease Control and Prevention


2020 ◽  
Vol 17 ◽  
pp. 100653
Author(s):  
V. Dheeraj Alshetty ◽  
Sudheer Kumar Kuppili ◽  
S.M. Shiva Nagendra ◽  
Gitakrishnan Ramadurai ◽  
Virendra Sethi ◽  
...  

2020 ◽  
Vol 108 ◽  
pp. 104353 ◽  
Author(s):  
Qingbo Lai ◽  
Jie Chen ◽  
Libin Hu ◽  
Jingying Cao ◽  
Yue Xie ◽  
...  
Keyword(s):  

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