發(fā)布時間：2018-06-19 01:15

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

【摘要】：伴隨著我國近年來頻現(xiàn)的霧霾天氣,空氣質(zhì)量愈來愈多得到公眾的關(guān)注。2012年出臺的空氣質(zhì)量新標準,用空氣質(zhì)量指數(shù)(AQI)替代了原有的空氣污染指數(shù)(API)對空氣質(zhì)量狀況進行了定量描述。將與灰霾的形成密切相關(guān)的PM2.5,以及反映機動車尾氣造成的光化學污染的臭氧指標,均納入到AQI的評價體系中。江蘇是中國的人口大省,其社會經(jīng)濟發(fā)展現(xiàn)狀及城市規(guī)劃的需要,都對江蘇省的空氣質(zhì)量提出了更高要求。因此,探索江蘇省空氣質(zhì)量指數(shù)的時空分布特點,建立全省范圍內(nèi)的空氣質(zhì)量指數(shù)預測模型,有著重要的現(xiàn)實意義。本文根據(jù)2013年1月-2014年2月江蘇省的日均AQI數(shù)據(jù),對全省的空氣質(zhì)量進行分析。首先,以省會南京為例分析AQI在不同季節(jié)的變化特點、工作日與周末的差別,并運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AQI的影響；其次,對AQI的空間自相關(guān)性進行了探索,了解全省AQI空間聚集特征,并通過直方圖、正態(tài)QQ分布圖、趨勢分析的方法,對2013年的AQI數(shù)據(jù)進行探索分析；最后,比較多種空間插值方法,根據(jù)預測精度選擇最合適的模型來分析全省的AQI空間分布規(guī)律,并對AQI的達標率進行預測。主要得到以下結(jié)論：2013年夏季,是全年中江蘇省空氣質(zhì)量最好的時段,南京市的情況也不例外。南京市周末的AQI遠高于工作日,存在著周末效應。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)測站點間的AQI具有很強的空間自相關(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。對各種插值模型的精度評價顯示,全局多項式的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,其最大特點就是能輕松識別出AQI超標的區(qū)域,使公眾對空氣狀況有更加直觀的感受,也為政府部門制定空氣質(zhì)量預測、預警提供有效的參考。
[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.
【學位授予單位】：昆明理工大學
【學位級別】：碩士
【學位授予年份】：2015
【分類號】：X823

【參考文獻】

相關(guān)期刊論文 前4條

1 吳志萍;王成;侯曉靜;楊偉偉;;6種城市綠地空氣PM2.5濃度變化規(guī)律的研究[J];安徽農(nóng)業(yè)大學學報;2008年04期

2 蘇志俠,程麟生;兩種客觀分析方法的比較──逐步訂正和最優(yōu)內(nèi)插[J];高原氣象;1994年02期

3 楊洪斌;鄒旭東;汪宏宇;劉玉徹;;大氣環(huán)境中PM_(2.5)的研究進展與展望[J];氣象與環(huán)境學報;2012年03期

4 姜友誼,黎曉;數(shù)字地面模型內(nèi)插方法的優(yōu)劣分析[J];西安科技學院學報;2001年03期

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本文編號：2037667