本文選題：AQI + 空間自相關(guān)��； 參考：《昆明理工大學(xué)》2015年碩士論文

【摘要】：伴隨著我國(guó)近年來(lái)頻現(xiàn)的霧霾天氣,空氣質(zhì)量愈來(lái)愈多得到公眾的關(guān)注。2012年出臺(tái)的空氣質(zhì)量新標(biāo)準(zhǔn),用空氣質(zhì)量指數(shù)(AQI)替代了原有的空氣污染指數(shù)(API)對(duì)空氣質(zhì)量狀況進(jìn)行了定量描述。將與灰霾的形成密切相關(guān)的PM2.5,以及反映機(jī)動(dòng)車尾氣造成的光化學(xué)污染的臭氧指標(biāo),均納入到AQI的評(píng)價(jià)體系中。江蘇是中國(guó)的人口大省,其社會(huì)經(jīng)濟(jì)發(fā)展現(xiàn)狀及城市規(guī)劃的需要,都對(duì)江蘇省的空氣質(zhì)量提出了更高要求。因此,探索江蘇省空氣質(zhì)量指數(shù)的時(shí)空分布特點(diǎn),建立全省范圍內(nèi)的空氣質(zhì)量指數(shù)預(yù)測(cè)模型,有著重要的現(xiàn)實(shí)意義。本文根據(jù)2013年1月-2014年2月江蘇省的日均AQI數(shù)據(jù),對(duì)全省的空氣質(zhì)量進(jìn)行分析。首先,以省會(huì)南京為例分析AQI在不同季節(jié)的變化特點(diǎn)、工作日與周末的差別,并運(yùn)用定性分析與定量分析相結(jié)合的方法考慮了氣溫、降水量因素對(duì)AQI的影響；其次,對(duì)AQI的空間自相關(guān)性進(jìn)行了探索,了解全省AQI空間聚集特征,并通過(guò)直方圖、正態(tài)QQ分布圖、趨勢(shì)分析的方法,對(duì)2013年的AQI數(shù)據(jù)進(jìn)行探索分析；最后,比較多種空間插值方法,根據(jù)預(yù)測(cè)精度選擇最合適的模型來(lái)分析全省的AQI空間分布規(guī)律,并對(duì)AQI的達(dá)標(biāo)率進(jìn)行預(yù)測(cè)。主要得到以下結(jié)論：2013年夏季,是全年中江蘇省空氣質(zhì)量最好的時(shí)段,南京市的情況也不例外。南京市周末的AQI遠(yuǎn)高于工作日,存在著周末效應(yīng)。并且,南京市的氣溫與AQI、降水量與AQI之間均具有線性相關(guān)性。江蘇省各監(jiān)測(cè)站點(diǎn)間的AQI具有很強(qiáng)的空間自相關(guān)特性。蘇州、泰州、南通三城市,在2013年7月、8月連續(xù)呈現(xiàn)出“高-高”空間集聚的情況。江蘇省AQI整體趨勢(shì)為由西向東先逐漸降低然后略有上升,南北方向上則比較穩(wěn)定。對(duì)各種插值模型的精度評(píng)價(jià)顯示,全局多項(xiàng)式的RMS最小,克里金法生成的表面可以更清楚地描述出局部細(xì)節(jié)。全省AQI的分布特征是,沿著海岸線方向由內(nèi)陸向沿海地區(qū)逐漸降低,最高值在在徐州地區(qū)。創(chuàng)建出AQI超出臨界值100的概率圖,其最大特點(diǎn)就是能輕松識(shí)別出AQI超標(biāo)的區(qū)域,使公眾對(duì)空氣狀況有更加直觀的感受,也為政府部門制定空氣質(zhì)量預(yù)測(cè)、預(yù)警提供有效的參考。
[Abstract]:With the frequent haze weather in China in recent years, the air quality is getting more and more public attention. The new air quality standard was introduced in 2012. Air quality index (AQI) was used instead of the original air pollution index (API) to describe the air quality quantitatively. PM2.5 which is closely related to haze formation and ozone index which reflects photochemical pollution caused by vehicle exhaust are all included in AQI evaluation system. Jiangsu is one of the most populous provinces in China. Its social and economic development and the needs of urban planning have put forward higher requirements for air quality in Jiangsu Province. Therefore, it is of great practical significance to explore the spatial and temporal distribution of air quality index in Jiangsu Province and to establish a prediction model of air quality index in Jiangsu province. Based on the daily AQI data of Jiangsu Province from January 2013 to February 2014, the air quality of Jiangsu Province is analyzed. First of all, taking Nanjing as an example to analyze the variation characteristics of AQI in different seasons, the difference between weekdays and weekends, and to consider the effects of temperature and precipitation factors on AQI by combining qualitative analysis with quantitative analysis. This paper explores the spatial autocorrelation of AQI, understands the spatial aggregation characteristics of AQI in the province, and explores and analyzes the AQI data in 2013 through histogram, normal QQ distribution map and trend analysis method. According to the prediction precision, the most suitable model is chosen to analyze the spatial distribution law of AQI in the province, and the rate of reaching AQI is forecasted. The main conclusions are as follows: summer 2013 is the best time for air quality in Jiangsu Province and Nanjing is no exception. The AQI of Nanjing weekend is much higher than that of working day, and there is weekend effect. Moreover, there is a linear correlation between air temperature and AQI, precipitation and AQI in Nanjing. AQI between monitoring stations in Jiangsu Province has strong spatial autocorrelation characteristics. Suzhou, Taizhou, Nantong three cities, in July and August 2013, a continuous "high-high" spatial agglomeration. The overall trend of AQI in Jiangsu Province is that the trend of AQI decreases gradually from west to east, then increases slightly, and is stable in north and south direction. The accuracy evaluation of various interpolation models shows that the RMS of the global polynomial is the smallest and the surface generated by the Crekin method can describe the local details more clearly. The distribution characteristic of AQI in the whole province is that the distribution of AQI decreases gradually from inland to coastal area along the coastline direction, and the highest value is in Xuzhou area. A probability map of AQI exceeding the critical value of 100 is created, the biggest characteristic of which is that it can easily identify the area where AQI exceeds the standard, which makes the public feel more intuitively about the air condition, and also provides an effective reference for government departments to make air quality prediction and early warning.
【學(xué)位授予單位】：昆明理工大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2015
【分類號(hào)】：X823

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本文編號(hào)：2037667