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10.1016/j.scitotenv.2020.141129 http://scihub22266oqcxt.onion/10.1016/j.scitotenv.2020.141129 32745857!7384416!32745857     free     free     free Deprecated: Implicit conversion from float 215.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 215.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 215.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 215.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 215.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 215.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 215.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 215.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 249.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 249.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 249.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 249.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 249.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 249.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 249.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Sci+Total+Environ 2020 ; 746 (ä): 141129 Nephropedia Template TP {{tp|p=32745857|t=2020. Implications for air quality management of changes in air quality during lockdown in Auckland (New Zealand) in response to the 2020 SARS-CoV-2 epidemic |pdf=|usr=}}{{32745857}} gab.com Text Implications for air quality management of changes in air quality during lockdown in Auckland (New Zealand) in response to the 2020 SARS-CoV-2 epidemic JO: Sci Total Environ http://www.kidney.de/pget.php?&tw=1&pmid=32745857 #FOAvip The current changes in vehicle movement due to 'lockdown' conditions (imposed in cities worldwide in response to the COVID-19 epidemic) provide opportunities to quantify the local impact of 'controlled interventions' on air quality and establish baseline pollution concentrations in cities. Here, we present a case study from Auckland, New Zealand, an isolated Southern Hemisphere city, which is largely unaffected by long-range pollution transport or industrial sources of air pollution. In this city, traffic flows reduced by 60-80% as a result of a government-led initiative to contain the virus by limiting all transport to only essential services. In this paper, ambient pollutant concentrations of NO(2), O(3), BC, PM(2.5), and PM(10) are compared between the lockdown period and comparable periods in the historical air pollution record, while taking into account changes in the local meteorology. We show that this 'natural experiment' in source emission reductions had significant but non-linear impacts on air quality. While emission inventories and receptor modelling approaches confirm the dominance of traffic sources for NO(x) (86%), and BC (72%) across the city, observations suggest a consequent reduction in NO(2) of only 34-57% and a reduction in BC of 55-75%. The observed reductions in PM(2.5) (still likely to be dominated by traffic emissions), and PM(10) (dominated by sea salt, traffic emissions to a lesser extent, and affected by seasonality) were found to be significantly less (8-17% for PM(2.5) and 7-20% for PM(10)). The impact of this unplanned controlled intervention shows the importance of establishing accurate, local-scale emission inventories, and the potential of the local atmospheric chemistry and meteorology in limiting their accuracy. Twit Text FOAVip Implications for air quality management of changes in air quality during lockdown in Auckland (New Zealand) in response to the 2020 SARS-CoV-2 epidemic ????Sci Total Environ http://www.kidney.de/pget.php?&tw=1&pmid=32745857 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=32745857 #FOAvip English Wikipedia <ref>{{Cite pmid|32745857}}</ref> Implications for air quality management of changes in air quality during lockdown in Auckland (New Zealand) in response to the 2020 SARS-CoV-2 epidemic #MMPMID32745857 Patel H; Talbot N; Salmond J; Dirks K; Xie S; Davy P Sci Total Environ 2020[Dec]; 746 (ä): 141129 PMID32745857show ga The current changes in vehicle movement due to 'lockdown' conditions (imposed in cities worldwide in response to the COVID-19 epidemic) provide opportunities to quantify the local impact of 'controlled interventions' on air quality and establish baseline pollution concentrations in cities. Here, we present a case study from Auckland, New Zealand, an isolated Southern Hemisphere city, which is largely unaffected by long-range pollution transport or industrial sources of air pollution. In this city, traffic flows reduced by 60-80% as a result of a government-led initiative to contain the virus by limiting all transport to only essential services. In this paper, ambient pollutant concentrations of NO(2), O(3), BC, PM(2.5), and PM(10) are compared between the lockdown period and comparable periods in the historical air pollution record, while taking into account changes in the local meteorology. We show that this 'natural experiment' in source emission reductions had significant but non-linear impacts on air quality. While emission inventories and receptor modelling approaches confirm the dominance of traffic sources for NO(x) (86%), and BC (72%) across the city, observations suggest a consequent reduction in NO(2) of only 34-57% and a reduction in BC of 55-75%. The observed reductions in PM(2.5) (still likely to be dominated by traffic emissions), and PM(10) (dominated by sea salt, traffic emissions to a lesser extent, and affected by seasonality) were found to be significantly less (8-17% for PM(2.5) and 7-20% for PM(10)). The impact of this unplanned controlled intervention shows the importance of establishing accurate, local-scale emission inventories, and the potential of the local atmospheric chemistry and meteorology in limiting their accuracy. |*Coronavirus Infections[MESH] |*Pandemics[MESH] |*Pneumonia, Viral[MESH] |*Severe Acute Respiratory Syndrome[MESH] |Air Pollutants/*analysis[MESH] |Air Pollution/*analysis/*prevention & control[MESH] |Betacoronavirus[MESH] |COVID-19[MESH] |Cities[MESH] |Environmental Monitoring[MESH] |Humans[MESH] |New Zealand/epidemiology[MESH] |Particulate Matter/analysis[MESH]Implications for air quality management of changes in air quality duri(epmc).pdf DeepDyve Pubget Overpricing