A two decades study on ozone variability and trend over the main urban areas of the Sao Paulo state, Brazil

被引:21
|
作者
Schuch, Daniel [1 ]
de Freitas, Edmilson Dias [1 ]
Espinosa, Sergio Ibarra [1 ]
Martins, Leila Droprinchinski [2 ]
Barreto Carvalho, Vanessa Silveira [3 ]
Ramin, Bruna Ferreira [1 ]
Silva, Jayne Sousa [1 ]
Martins, Jorge Alberto [2 ]
Andrade, Maria de Fatima [1 ]
机构
[1] Univ Sao Paulo, Inst Astron Geofis & Ciencias Atmosfer IAG, Sao Paulo, SP, Brazil
[2] Univ Tecnol Fed Parana, Londrina, Parana, Brazil
[3] Univ Fed Itajuba, Itajuba, MG, Brazil
基金
巴西圣保罗研究基金会;
关键词
Air quality; Quantile regression model; Seasonal trend; AIR-QUALITY; METROPOLITAN-AREA; EXPOSURE ASSESSMENT; PARTICULATE MATTER; PUBLIC-HEALTH; TERM EXPOSURE; MEGACITY; EMISSIONS; MORTALITY; POLLUTION;
D O I
10.1007/s11356-019-06200-z
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
In this paper, we analyze the variability of the ozone concentration over Sao Paulo Macrometropolis, as well the factors, which determined the tendency observed in the last two decades. Time series of hourly ozone concentrations measured at 16 automated stations from an air quality network from 1996 to 2017 were analyzed. The temporal variability of ozone concentrations exhibits well-defined daily and seasonal patterns. Ozone presents a significant positive correlation between the number of cases (thresholds of 100-160 mu g m(-3)) and the fuel sales of gasohol and diesel. The ozone concentrations do not exhibit significant long-term trends, but some sites present positive trends that occurs in sites in the proximity of busy roads and negative trends that occurs in sites located in residential areas or next to trees. The effect of atmospheric process of transport and ozone formation was analyzed using a quantile regression model (QRM). This statistical model can deal with the nonlinearities that appear in the relationship of ozone and other variables and is applicable to time series with non-normal distribution. The resulting model explains 0.76% of the ozone concentration variability (with global coefficient of determination R-1 = 0.76) providing a better representation than an ordinary least square regression model (with coefficient of determination R-2 = 0.52); the effect of radiation and temperature are the most critical in determining the highest ozone quantiles.
引用
收藏
页码:31699 / 31716
页数:18
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