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1.
Huan Jing Ke Xue ; 41(8): 3527-3538, 2020 Aug 08.
Artigo em Chinês | MEDLINE | ID: mdl-33124325

RESUMO

Surface ozone (O3) has become the primary air pollutant in Guangzhou. Due to the influences of topography, meteorological conditions, and differences in precursor emissions, there are also large differences in the characteristics, formation mechanisms, and influencing factors of ozone in different areas of the same city. Based on the ground measurement data for October 2015 at four air quality monitoring stations that represent different types of regions in Guangzhou [urban area:Guangzhou Monitoring Center (GMC); upwind suburbs:Huadu Normal School (HNS); downwind suburbs:Panyu Middle School (PMS); Mountain area:Maofengshan (MFS)] and the WRF simulated meteorological data, the changing characteristics, influencing factors, and sensitivity of O3 were studied at each station. The results showed that the diurnal variation of O3 and NOx exhibit unimodal and bimodal characteristics (except for NOx at the MFS station). The peak ozone concentration appeared on Saturday at the GMC, HNS, and MFS stations, and on Thursday at the PMS station. The ozone concentration at the MFS station was the highest (98.61 µg·m-3), whereas that at the GMC station was the lowest (44.83 µg·m-3). The NOx inflection point intervals for O3 at different sites were:GMC:55-90 µg·m-3; PMS:30-60 µg·m-3; MFS:10-20 µg·m-3. The temperature inflection point intervals affecting the rate of O3 formation at different sites were:GMC:28-30℃; HNS:26-28℃; PMS:24-26℃; however, this was not obvious at the MFS station. The relative humidity inflection point intervals were:GMC:55%-65% ; HNS and PMS:60%-70% ; MFS:80%-85%. The wind speed(WS) of the light wind type was proportional to the O3 concentration. The O3 concentration at the PMS site was the highest in the northwest wind direction, and the O3 concentration at the MFS site was the highest in the other wind directions. By analyzing the multivariate linear fitting of impact factors on the O3 concentration, the main controlling factors at each site were:GMC:WS and T; PMS and HNS:T and RH; MFS:RH and WS. The ozone sensitivity at each site was as follows:GMC and HNS had a VOCs-limited regime, MFS had a NOx-limited regime, and PMS had a transition regime.


Assuntos
Poluentes Atmosféricos , Ozônio , Poluentes Atmosféricos/análise , Cidades , Monitoramento Ambiental , Ozônio/análise , Estações do Ano
2.
J Environ Sci (China) ; 94: 1-13, 2020 Aug.
Artigo em Inglês | MEDLINE | ID: mdl-32563472

RESUMO

Due to the influences of precursors emissions, meteorology, geography and other factors, ozone formation sensitivity (OFS) is generally spatially and temporally heterogeneous. This study characterized detailed spatial and temporal variations of OFS in Guangdong-Hong Kong-Macao Greater Bay Area (GBA) from 2012 to 2016 based on OMI satellite data, and analyzed the relationships of OFS with precursors emissions, meteorology and land use types (LUTs). From 2012 to 2016, the OFS tended to be NOx-limited in GBA, with the value of FNR (HCHO/NO2) increasing from 2.04 to 2.22. According to the total annual emission statistics of precursors, NOx emissions decreased by 33.1% and VOCs emissions increased by 35.2% from 2012 to 2016, directly resulting in OFS tending to be NOx-limited. The Grey Relation Analysis results show that total column water (TCW), surface net solar radiation (SSR), air temperature at 2 m (T2) and surface pressure (SP) are the top four meteorological factors with the greatest influences on OFS. There are significant positive correlations between FNR and T2, SSR, TCW, and significant negative correlations between FNR and SP. In GBA, the OFS tends to be NOx-limited regime in wet season (higher T2, SSR, TCW and lower SP) and VOCs-limited regime in dry season (lower T2, SSR, TCW and higher SP). The FNR displays obvious gradient variations on different LUTs, with the highest in "Rural areas", second in "Suburban areas" and lowest in "Urban areas".


Assuntos
Poluentes Atmosféricos/análise , Meteorologia , Ozônio/análise , China , Monitoramento Ambiental , Hong Kong , Macau
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