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巴西圣保罗州主要城区臭氧变化和趋势的二十年研究。

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

机构信息

Instituto de Astronomia, Geofísica e Ciências Atmosféricas (IAG), Universidade de São Paulo, São Paulo, Brazil.

Universidade Tecnológica Federal do Paraná, Londrina, Paraná, Brazil.

出版信息

Environ Sci Pollut Res Int. 2019 Nov;26(31):31699-31716. doi: 10.1007/s11356-019-06200-z. Epub 2019 Sep 4.

Abstract

In this paper, we analyze the variability of the ozone concentration over São 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 μg m) 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 = 0.76) providing a better representation than an ordinary least square regression model (with coefficient of determination R = 0.52); the effect of radiation and temperature are the most critical in determining the highest ozone quantiles.

摘要

本文分析了圣保罗大都市地区臭氧浓度的变化,并探讨了导致过去 20 年来臭氧浓度变化趋势的因素。本研究利用 1996 年至 2017 年期间空气质量网络中 16 个自动站的每小时臭氧浓度时间序列数据进行分析。臭氧浓度的时间变化呈现出明显的日变化和季节性变化特征。臭氧浓度与病例数(100-160μg m 阈值)呈显著正相关,与汽油和柴油的燃料销售量呈正相关。臭氧浓度没有明显的长期趋势,但一些站点呈现出正趋势,这些站点位于交通繁忙的道路附近,而另一些站点则呈现出负趋势,这些站点位于居民区或靠近树木的地方。利用分位数回归模型(QRM)分析了大气传输和臭氧形成过程的影响。该统计模型可以处理臭氧与其他变量关系中出现的非线性问题,适用于非正态分布的时间序列。结果模型解释了臭氧浓度变化的 0.76%(整体决定系数 R = 0.76),比普通最小二乘回归模型(决定系数 R = 0.52)的表示效果更好;辐射和温度的影响是确定最高臭氧分位数的最关键因素。

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