基于GIS的酸沉降对农作物损害的经济损益分析研究
摘要
随着中国经济的发展,能源物质的消耗与日俱增,中国已经成为了继欧洲和北美后的第三大酸雨区,酸雨问题与人民生活息息相关。
本研究选取湖南省各城市降水离子浓度和农作物损失值进行建模,将酸沉降pH、Ca~(2+)、NH_4~+、Na~+、K~+、Mg~(2+)、SO_4~(2-)、NO_3~-、Cl~-作为影响因子,分别记为x_1,x_2,……,x_9,酸沉降损失y作为目标函数,通过PLS1方法得出典型农作物酸沉降“剂量—损失”响应模型。
本文通过对湖南省降水离子浓度进行反距离加权插值,得到了湖南省各降水离子浓度的预测图,在ArcGIS中进行空间叠加分析,得到湖南省的网格化图,根据湖南省网格化区域示意图,提取不同城市降水离子的浓度属性,得到每个城市单一网格范围内降水离子的浓度值。利用建立的湖南省各城市酸沉降对农作物的“剂量—损失”响应方程,运用ArcGIS的Field Calculator功能,得到不同城市酸沉降对农作物的损失值。
Without the pollutants in the atmosphere,the precipitation acidity is made up of H_2CO_3 caused by CO_2.The range of pH is from 5.6 to 9.0.Therefore,the precipitation whose pH is below 5.6 is called acid rain.In the 1950s,the English Chemist R.A.Smith found that there are sulphuric acid and sulphate in the atmosphere of Manchester during analyzing the compomnents in precipitation.After deeper research,he first used Acid Rain in his book Atmosphere and Precipitation:The beginning of Chemical Climatology in 1872.
The precursor of acid rain is SO_2 and NO_x,while the contribution rate of SO_2 to global acid precipitation is 60%～70%.With the high-speed development of economic in Asia,the consumption of fossil fuel is growing higher and higher.The discharge amount of SO_2 and NO_x is larger than South Amercia and Europe which is in the top place of five continents.China is the third acid rain zone while the former are South Amercia and Europe and the area is becoming larger and larger.The area of acid rain zone is rapidly growing.Hunan province is located in the middle acid rain zone of China in which the phenomenon is the worst.The frequency of acid precipitation comes to 90%in Zhuzhou,Changsha,Xiangtan and so on.According to the analyzing of acid rain samples,the positive ions in it are H~+,Ca~(2+)、NH_4~+,Na~+,K~+,Mg~(2+) while the negative ions are SO_4~(2-)、NO_3~-、Cl~-、HCO_3~-.
In this research,PLS(Partial Least Squares) is selected to establish the dose-loss equation of crops in different cities in Hunan province caused by acid precipitation. The method is a effective means of solving the relativity among independent variables proposed by S.Wold and C.Albano in 1983.It can not only filter the variables much simply,but also retain all variables in the final model.In addition,it can be also used in the situation in which the number of samples is less than variables.In a word, modeling used the PLS is more reliable than other means.
In this research,the values of precipitation ions and the crops' loss are selected to establish the equation.The ions such as pH、Ca~(2+)、NH_4~+、Na~+、K~+、Mg~(2+)、SO_4~(2-)、NO_3~-、Cl~-are considered as variables respectively noted x_1,x_2,……,x_9 while the loss is considered the objective function noted y.The equation of dose-loss caused by acid precipitation is set up by using the method of PLS1.
Geographical Information System(GIS) is a system whose function is to save, manage,analyze,display and apply the geographical informations,which is also the universal technology of analyzing and processing giant geographical data.GIS is widely applied to the making of thematic map,the establishment of environmental geographical information system,environmental monitoring,environmental impact assessment,etc.
Spatial Analysis is a technology to analyze spatial data based on the characteristics of location and form of geographical targets whose aim is to refine and transport the spatial information.The theory of spatial interpolation in GIS is that the characteristics are similar as the locations are adjacency.The method is used to transform the data of discrete points to continuous numbers.The gebraeuchlich methods are IDW(Inverse Distance Weighted),GPI(Global Polynomial Interpolation), LPI(Local Polynomial Interpolation),RBF(Radial Basis Function),etc.In this research,IDW is selected to interpolate and analyze according to the data analysis. The pictures of precipitation ions are gained by spatial interpolation in different cities of Hunan province.The conclusion are as follows:
(1)The place in which the concentration of SO_4~(2-) is the lowest is located in southern Hunan which Yongzhou city is given the first place.The concentration in other places is above 12mg/L.
(2) The place in which the concentration of NO_3~-is the highest is located in estern Hunan which Changsha,Zhuzhou and Xiangtan are given the first places.
(3) The places in which the concentration of Ca~(2+) is the highest are Changsha, Yueyang and Loudi cities.
(4) The place in which the concentration of NH_4~+ is the highest are Yueyang, Changsha and Zhuzhou cities where the concentration of SO_4~(2-) is the highest. Although NH_4~+ neutralizes certain SO_4~(2-),the value of pH is still high.Therefore, the relative concentration between NH_4~+ and SO_4~(2-) is not the crucial factores resolve the value of pH in Hunan province.
The grid of 40km×40km is established in the software MapInfo.The spatial overlay finished in the software of ArcGIS.In ArcGIS,the predicted map of concentration of precipitation is generated through interpolation.The predicted maps, grid and administrative maps are overlaied to gain the gridding map.The concentration of precipitation ions in each city is extracted and the concentration in each grid is gained.The function of Field Calculator in ArcGIS is used to obtain the crops' loss caused by acid precipitation.
In sum,the research is modeling on natural precipitation which breakthrough the economic loss study based on simulant acid precipitation.Apart from this,the crops' loss caused by acid precipitation is gained through the software of ArcGIS.
本研究选取湖南省各城市降水离子浓度和农作物损失值进行建模,将酸沉降pH、Ca~(2+)、NH_4~+、Na~+、K~+、Mg~(2+)、SO_4~(2-)、NO_3~-、Cl~-作为影响因子,分别记为x_1,x_2,……,x_9,酸沉降损失y作为目标函数,通过PLS1方法得出典型农作物酸沉降“剂量—损失”响应模型。
本文通过对湖南省降水离子浓度进行反距离加权插值,得到了湖南省各降水离子浓度的预测图,在ArcGIS中进行空间叠加分析,得到湖南省的网格化图,根据湖南省网格化区域示意图,提取不同城市降水离子的浓度属性,得到每个城市单一网格范围内降水离子的浓度值。利用建立的湖南省各城市酸沉降对农作物的“剂量—损失”响应方程,运用ArcGIS的Field Calculator功能,得到不同城市酸沉降对农作物的损失值。
Without the pollutants in the atmosphere,the precipitation acidity is made up of H_2CO_3 caused by CO_2.The range of pH is from 5.6 to 9.0.Therefore,the precipitation whose pH is below 5.6 is called acid rain.In the 1950s,the English Chemist R.A.Smith found that there are sulphuric acid and sulphate in the atmosphere of Manchester during analyzing the compomnents in precipitation.After deeper research,he first used Acid Rain in his book Atmosphere and Precipitation:The beginning of Chemical Climatology in 1872.
The precursor of acid rain is SO_2 and NO_x,while the contribution rate of SO_2 to global acid precipitation is 60%～70%.With the high-speed development of economic in Asia,the consumption of fossil fuel is growing higher and higher.The discharge amount of SO_2 and NO_x is larger than South Amercia and Europe which is in the top place of five continents.China is the third acid rain zone while the former are South Amercia and Europe and the area is becoming larger and larger.The area of acid rain zone is rapidly growing.Hunan province is located in the middle acid rain zone of China in which the phenomenon is the worst.The frequency of acid precipitation comes to 90%in Zhuzhou,Changsha,Xiangtan and so on.According to the analyzing of acid rain samples,the positive ions in it are H~+,Ca~(2+)、NH_4~+,Na~+,K~+,Mg~(2+) while the negative ions are SO_4~(2-)、NO_3~-、Cl~-、HCO_3~-.
In this research,PLS(Partial Least Squares) is selected to establish the dose-loss equation of crops in different cities in Hunan province caused by acid precipitation. The method is a effective means of solving the relativity among independent variables proposed by S.Wold and C.Albano in 1983.It can not only filter the variables much simply,but also retain all variables in the final model.In addition,it can be also used in the situation in which the number of samples is less than variables.In a word, modeling used the PLS is more reliable than other means.
In this research,the values of precipitation ions and the crops' loss are selected to establish the equation.The ions such as pH、Ca~(2+)、NH_4~+、Na~+、K~+、Mg~(2+)、SO_4~(2-)、NO_3~-、Cl~-are considered as variables respectively noted x_1,x_2,……,x_9 while the loss is considered the objective function noted y.The equation of dose-loss caused by acid precipitation is set up by using the method of PLS1.
Geographical Information System(GIS) is a system whose function is to save, manage,analyze,display and apply the geographical informations,which is also the universal technology of analyzing and processing giant geographical data.GIS is widely applied to the making of thematic map,the establishment of environmental geographical information system,environmental monitoring,environmental impact assessment,etc.
Spatial Analysis is a technology to analyze spatial data based on the characteristics of location and form of geographical targets whose aim is to refine and transport the spatial information.The theory of spatial interpolation in GIS is that the characteristics are similar as the locations are adjacency.The method is used to transform the data of discrete points to continuous numbers.The gebraeuchlich methods are IDW(Inverse Distance Weighted),GPI(Global Polynomial Interpolation), LPI(Local Polynomial Interpolation),RBF(Radial Basis Function),etc.In this research,IDW is selected to interpolate and analyze according to the data analysis. The pictures of precipitation ions are gained by spatial interpolation in different cities of Hunan province.The conclusion are as follows:
(1)The place in which the concentration of SO_4~(2-) is the lowest is located in southern Hunan which Yongzhou city is given the first place.The concentration in other places is above 12mg/L.
(2) The place in which the concentration of NO_3~-is the highest is located in estern Hunan which Changsha,Zhuzhou and Xiangtan are given the first places.
(3) The places in which the concentration of Ca~(2+) is the highest are Changsha, Yueyang and Loudi cities.
(4) The place in which the concentration of NH_4~+ is the highest are Yueyang, Changsha and Zhuzhou cities where the concentration of SO_4~(2-) is the highest. Although NH_4~+ neutralizes certain SO_4~(2-),the value of pH is still high.Therefore, the relative concentration between NH_4~+ and SO_4~(2-) is not the crucial factores resolve the value of pH in Hunan province.
The grid of 40km×40km is established in the software MapInfo.The spatial overlay finished in the software of ArcGIS.In ArcGIS,the predicted map of concentration of precipitation is generated through interpolation.The predicted maps, grid and administrative maps are overlaied to gain the gridding map.The concentration of precipitation ions in each city is extracted and the concentration in each grid is gained.The function of Field Calculator in ArcGIS is used to obtain the crops' loss caused by acid precipitation.
In sum,the research is modeling on natural precipitation which breakthrough the economic loss study based on simulant acid precipitation.Apart from this,the crops' loss caused by acid precipitation is gained through the software of ArcGIS.
引文
[1]张苏,汪腊宝,黄向荣.安徽省新一代酸雨资料采集处理系统[J].中国农业气象,2008.29(1):104-106;
[2]郑凤琴,孙崇智,于文杰,黄海洪等.城市酸雨预报方法及业务系统[J].气象科技,2006.34(6):684-687;
[3]黄海洪,孙崇智,郑凤琴,林振敏.酸雨pH值分级短期预报方法研究初探[J].环境化学,2006.25(3):373-374;
[4]喻真英,何红兵.试论酸雨问题及控制对策[J].湖南环境生物职业技术学院学报.2004,10(2):116-118;
[5]薛梅.酸雨的形成及其危害[J].内蒙古石油化工,1999,25(4):108;
[6]杨军,刘文玲.酸性降水成因及其控制对策的探讨[J].黑龙江环境通报.2000,24(1):25-26,44;
[7]刘嘉麒.背景降水[M].北京:中国环境科学出版社,1995;
[8]刘嘉麒.降水背景值与酸雨定义研究[J].中国环境监测,1996,12(5):5-9;
[9]王文兴,丁国安.中国降水酸度和离子浓度的时空分布[J].环境科学研究,1997,10(2):1-8;
[10]王瑞斌,魏复盛,程春明等.我国南北方降水化学组分某些特征的研究[A].朱钟杰,酸雨文集[C].北京:中国环境科学出版社,1989:227-239;
[11]徐德应,尚鹤.酸雨对中国森林的影响[A].中国林业科学研究院.面向21世纪的林业——可持续发展全球战略下的林业科学技术[C].北京:中国农业科技出版社,1998,10(1):7-12;
[12]杨本宏,我国酸雨危害现状及防治对策[J].合肥联合大学学报,2006.10(2):102-106;
[13]花日茂,李湘琼.我国酸雨的研究进展(综述)[J].安徽农业大学学报,1998,25(2):206-210;
[14]吴丹,王式功,尚可政.中国酸雨研究综述[J].干旱气象,2006.24(2):70-77;
[15]张燕,李娟英,张雁秋.我国酸雨分布特征及控制对策[J].陕西环境,1998,5(4):39-40;
[16]杨宗慧.我国酸雨状况和对策[J].云南环境科学,2002,21(1):25-26;
[17]冯砚青.中国酸雨状况和自然成因综述及防治对策研究[J].云南地理环境研究,2004,16(1):25-28;
[18]中国环境公报,国家环境保护部,2006;
[19]张骁勇,王振红.当前酸雨形势和治理对策[J].环境科学与管理,2007,32(8):85-88,107;
[20]凌大炯,章家恩,欧阳颖.酸雨对土壤生态系统影响的研究进展[J].土壤,2007.39(4):514-521;
[21]庄捷,陈奋飞,陈岩松,吴若菁.酸雨对林木伤害的研究[J].西部林业科学,2006.3(1): 129-133;
[22]林慧萍.酸雨对陆生植物的影响机理[J].福建林业科技,2005.32(1):60-64;
[23]姜文华,张晟,陈刚才等.酸沉降对重庆南山森林生态系统土壤和植被的影响[J].环境科学研究,2002.15(6):8-11;
[24]刘喜凤,刘晓燕,张征,朱国彬.酸雨与林木和森林生态系统关系的研究[J].云南林业科技,2003.2(103):76-79;
[25]陈志远.中国酸雨研究[M].北京:中国环境科学出版社,1997;
[26]付修勇.酸雨的形成与危害[J].聊城师院学报(自然科学版),2000.13(3):67-69;
[27]王晓燕,吴甫成,邹君.湖南土壤酸沉降敏感性研究[J].湖南师范大学自然科学学报,1999.22(4):87-91;
[28]瞿忠心.三种湖南土壤吸附和解析的研究[D].长沙:湖南农业大学,2000;
[29]吴甫成,王晓燕,邹君,彭世良.湖南土壤酸缓冲性能研究[J].农业现代化研究,2001.22(1):58-62;
[30]刘丽,陈飞.合肥市酸雨污染分析及控制对策研究[J].安徽化工,2002,118(4):30-31;
[31]周涛,古田会,赵彩.贵阳市酸雨过程的天气学研究[J].贵州气象,1997,2(3:23-25;)
[32]杨本宏.我国酸雨危害现状及防治对策[J].合肥联合大学学报,2000.10(2):102-106;
[33]曹洪法,舒俭民,刘燕云,高映新等.酸雨对两广地区农作物的经济损失研究[J].环境科学研究,1994,4(2):1-6;
[34]刘鸿亮.环境费用效益分析方法及实例[J].北京:中国环境科学出版社,1998,82-85;
[35]张林波,曹洪法,沈英娃等.苏、浙、皖、闽、湘、鄂、赣7省酸沉降农业危害——农业损失估算[J].中国环境科学,1997.17(6):489-491;
[36]张林波,曹洪法,沈英娃等.苏、浙、皖、闽、湘、鄂、赣7省酸沉降农业危害——酸沉降农业生态综合危害分析[J].中国环境科学,1998.18(1):12-15;
[37]国家环保局计划司.环境规划指南[M].北京:清华大学出版社,1994,334;
[38]冯宗炜.中国酸雨的生态影响和防治对策[J].云南环境科学,2000,19(增刊):1-6;
[39]冯宗伟.中国酸雨对陆地生态系统的影响和防治对策[J].中国工程科学,2000.2(9):5-12;
[40]吴丹,王式功,尚可政.中国酸雨研究综述[J].干旱气象,2006,24(2):70-76;
[41]朱敏,孙宗修.我国酸雨的发展及对农作物的影响[J].科技通报,1998.14(5):361-364;
[42]于天仁.中国土壤的酸度特点和酸化问题[J].土壤通报,1988,19(2):49-51;
[43]唐孝炎.大气环境化学[M].北京:高等教育出版社,1990;
[44]吴劲兵,汪家权,孙世群.酸沉降农业经济损失估算[J].合肥工业大学学报,2002,25(1):100-104;
[45]牟永铭,朱光良.基于GIS技术的浙江省酸雨分布研究[J].科技通报,2003321(3):356-359;
[46]何隆华,样宏伟.应用GIS进行生态系统对酸雨的相对敏感性分析[J].地理科学,1996,16(4):317-322;
[47]刘宝章,李金龙,王敬云等.青岛酸雨天气边界层气象特征[J].中国环境科学,1997。17(4):103-107;
[48]王文兴,刘洪杰,张婉华等.我国东部沿海地区酸雨来源研究[J].中国环境科学,1997,17(5):387-392;
[49]Huang M,Wang Z,He D,et al.Modeling studies on sulfur deposition and transport in East Asia[J].Water,Air and Soil Pollution,1995,85:1927-1932;
[50]李金惠.中国降水酸度预测模型[J].中国环境科学,1998.18(1):8-11;
[51]吴甫成,吴君维,王晓燕等.湖南酸雨污染特征[J],环境科学学报,2000.20(6):807-809;
[52]陈旦华,孙庆瑞,王美蓉等.湖南省酸性降水的研究[J],环境科学研究,1998.11(2):8-12;
[53]许晶.湖南省酸性降水现状、成因及对策研究[J],环境污染治理技术与设备.2001.2(4):25-29;
[54]张龚,曾光明,蒋益民等.湖南省酸雨变化特征、现状及成因分析[J],环境科学研究.2003.16(5):14-17;
[55]蒋益民,曾光明,张现宝等.湖南省酸雨的主要特点域酸雨污染防治对策[J],湖南大学学报(自然科学版).2001.28(3):78-83;
[56]朱选祥.湖南省酸雨现状、成因及对策研究[J],企业技术开发,2006.25(10):28-30;
[57]刘丽,廖柏寒,雷鸣等.长沙市酸性降水现状与成因及对策[J],湖南农业大学学报(自然科学版).2005-31(2):216-218;
[58]方至.长沙市酸雨现状分析[J],湖南农业大学学报.1998.24(1):43-46;
[59]刘文华,刘芬,娄涛.株洲市酸雨污染特征及防治措施研究[J],环境科学动态,2002(1):21-24;
[60]王剑秋.衡阳市酸雨的成因及其污染的预测与对策[J],衡阳师专学报.1995.13(1):55-58;
[61]郭基联,张恒喜,刘晓东.飞机机体研制费用的偏最小二乘回归分析[J],数量经济技术经济研究.2001(4):121-124;
[62]郭进,刘洪霖,黄铁生等.计算机辅助材料设计的偏最小二成法——人工神经网络研究[J],计算机与应用化学,1996.13(4):253-256;
[63]王帅,范春彦,辛永平.基于偏最小二乘回归的研制费用估算模型[J].陕西师范大学学报(自然科学版),2007.35:29-32;
[64]蒋红卫,夏结来.偏最小二乘回归及其应用[J].第四军医大学学报,2003.24(3):280-283;
[65]许凤华,李述山.基于改进的偏最小二乘回归的酸雨pH值预测[J].山东科技大学学报(自然科学版).2006,25(3):110-112;
[66]李洪,代进,蒋金泉.偏最小二乘回归的神经网络模型在巷道围岩位移预测中的应用[J],煤炭学报,2004,29(3):274-278;
[67]陈南祥,黄强,曹连海.基于偏最小二乘回归与神经网络耦合的岩液泉预报模型[J],水利学报,2004(9):68～72;
[68]王文圣,熊华康,曹宏伟.酸雨pH预测的偏最小二乘回归模型[J],四川环境,2003.22(6):77-80;
[69]邓念武,徐晖.单因变量的偏最小二乘回归模型及其应用[J],武汉大学学报(工学版),2001.34(2):14-16;1
[70]王惠文,刘强,屠永平.偏最小二乘回归模型内涵分析方法研究[J],北京航空航天大学学报,2000.26(4):473-476;
[71]王惠文等.偏最小二乘回归方法及其应用[M].北京:国防工业出版社,2000;
[72]张恒喜,郭基联,朱家元等.小样本多元数据分析方法及应用[M].西北工业大学出版社,2002;
[73]徐华山,任玉芬,向中林.GIS在环境科学中的应用[J].干旱环境监测,2007.21(1):42-46;
[74]陈述彭,鲁学军,周成虎.地理信息系统导论[M].北京:科学出版社,1995,3,6-7;
[75]江东.地理信息系统及其在全球变化研究中的应用[M].北京:气象出版社,2003,4
[76]邬伦,刘瑜,马修军等.地理信息系统——原理、方法和应用[M].北京:科学出版社,2001;
[77]张丽,鄢团军.GIS在资源环境领域中的应用[J].现代商贸工业,2007.19(9):84-85;
[78]王锦慧,王燕,陈剑.GIS技术及其在环境保护中的作用[J].中国环境科学学会学术年会优秀论文集,2007:1877-1879;
[79]郝莉莉,冯启言,王华.GIS技术在环境管理信息系统中的应用研究[J].环境监测与管理,2005(4):17-20;
[80]帅方敏.地理信息系统技术在环境领域中的应用[J].山西科技,2007(1):49-51;
[81]邬伦,张晶,赵伟等.地理信息系统[M].北京:电子工业出版社,2001;
[82]郭仁忠.空间分析[M].北京:高等教育出版社,2006;
[83]胡月鹏,黄杏元,华一新.地理信息系统教程[M].武汉:武汉大学出版社;2002;
[84]龚键雅.地理信息系统基础[M].北京:科学出版社,2004;
[85]张康聪.地理信息系统导论[M].北京:科学出版社,2006;
[86]张超.地理信息系统应用教程[M].北京:科学出版社,2007;
[87]汤国安,杨昕等.ArcGIS地理信息系统空间分析实验教程[M].北京:科学出版社,2006;
[88]蔡福,明惠青,刘兵等.采用地统计学和GIS技术对东北地区不同时期降水的分析[J].中国农业气象,2006,27(4):296-299;
[89]邵晓梅,严昌荣,魏红兵.基于Kriging插值的黄河流域降水的时空分布格局[J].中国农业气象,2006,27(2):65-69;
[90]蔡福,于慧波,矫玲玲等.降水要素空间插值精度的对比——以东北地区为例[J].资源科学,2006,28(6):73-79;
[91]林孝松,余倩.重庆市农业气候资源空间插值研究[J].安徽农业科学,2008.36(30):13461-13463,13470;
[92]马菲,汪亚平,李炎等.地统计法支持的北部湾东部海域沉积物粒径趋势分析[J].地理学报,2008.63(11):1207-1307;
[93]马来刚,程永政,刘婷.空间插值技术在冬小麦单产预测中的应用[J].河北农业科学,2008.12(10):4-5,26;
[94]湖南省统计年鉴 2005;
[95]http://baike.baidu.com/view/8581.htm;
[96]2007年湖南省环境状况公报;
[97]赵艳霞,侯青,徐晓斌等.2005年中国酸雨时空分布特征[J].气候变化研究进展,2006.2(5):242-245;
[98]陈雪莲.北海酸雨区的成因简析[J].广西气象,2004.25(2):35-36;
[99]黎云,孙庆瑞.氨的湿去除及氨在酸雨中的作用[J].环境科学研究,1996.9(6):41-44;
[100]蒋益民.湖南省酸雨的防治措施、危害和防治措施的初步研究[D].长沙:湖南大学.2001;
[101]朱良峰,吴信才,刘修国.GIS中矢量多边形网络化问题研究[J].地理与地理信息科学,2004.20(1):12-15;
[102]陈载林,黄临平,陈玉梁.基于MapGIS的网格化数据批量精确提取[J].西部探矿工程,2009(2):202-203;
[2]郑凤琴,孙崇智,于文杰,黄海洪等.城市酸雨预报方法及业务系统[J].气象科技,2006.34(6):684-687;
[3]黄海洪,孙崇智,郑凤琴,林振敏.酸雨pH值分级短期预报方法研究初探[J].环境化学,2006.25(3):373-374;
[4]喻真英,何红兵.试论酸雨问题及控制对策[J].湖南环境生物职业技术学院学报.2004,10(2):116-118;
[5]薛梅.酸雨的形成及其危害[J].内蒙古石油化工,1999,25(4):108;
[6]杨军,刘文玲.酸性降水成因及其控制对策的探讨[J].黑龙江环境通报.2000,24(1):25-26,44;
[7]刘嘉麒.背景降水[M].北京:中国环境科学出版社,1995;
[8]刘嘉麒.降水背景值与酸雨定义研究[J].中国环境监测,1996,12(5):5-9;
[9]王文兴,丁国安.中国降水酸度和离子浓度的时空分布[J].环境科学研究,1997,10(2):1-8;
[10]王瑞斌,魏复盛,程春明等.我国南北方降水化学组分某些特征的研究[A].朱钟杰,酸雨文集[C].北京:中国环境科学出版社,1989:227-239;
[11]徐德应,尚鹤.酸雨对中国森林的影响[A].中国林业科学研究院.面向21世纪的林业——可持续发展全球战略下的林业科学技术[C].北京:中国农业科技出版社,1998,10(1):7-12;
[12]杨本宏,我国酸雨危害现状及防治对策[J].合肥联合大学学报,2006.10(2):102-106;
[13]花日茂,李湘琼.我国酸雨的研究进展(综述)[J].安徽农业大学学报,1998,25(2):206-210;
[14]吴丹,王式功,尚可政.中国酸雨研究综述[J].干旱气象,2006.24(2):70-77;
[15]张燕,李娟英,张雁秋.我国酸雨分布特征及控制对策[J].陕西环境,1998,5(4):39-40;
[16]杨宗慧.我国酸雨状况和对策[J].云南环境科学,2002,21(1):25-26;
[17]冯砚青.中国酸雨状况和自然成因综述及防治对策研究[J].云南地理环境研究,2004,16(1):25-28;
[18]中国环境公报,国家环境保护部,2006;
[19]张骁勇,王振红.当前酸雨形势和治理对策[J].环境科学与管理,2007,32(8):85-88,107;
[20]凌大炯,章家恩,欧阳颖.酸雨对土壤生态系统影响的研究进展[J].土壤,2007.39(4):514-521;
[21]庄捷,陈奋飞,陈岩松,吴若菁.酸雨对林木伤害的研究[J].西部林业科学,2006.3(1): 129-133;
[22]林慧萍.酸雨对陆生植物的影响机理[J].福建林业科技,2005.32(1):60-64;
[23]姜文华,张晟,陈刚才等.酸沉降对重庆南山森林生态系统土壤和植被的影响[J].环境科学研究,2002.15(6):8-11;
[24]刘喜凤,刘晓燕,张征,朱国彬.酸雨与林木和森林生态系统关系的研究[J].云南林业科技,2003.2(103):76-79;
[25]陈志远.中国酸雨研究[M].北京:中国环境科学出版社,1997;
[26]付修勇.酸雨的形成与危害[J].聊城师院学报(自然科学版),2000.13(3):67-69;
[27]王晓燕,吴甫成,邹君.湖南土壤酸沉降敏感性研究[J].湖南师范大学自然科学学报,1999.22(4):87-91;
[28]瞿忠心.三种湖南土壤吸附和解析的研究[D].长沙:湖南农业大学,2000;
[29]吴甫成,王晓燕,邹君,彭世良.湖南土壤酸缓冲性能研究[J].农业现代化研究,2001.22(1):58-62;
[30]刘丽,陈飞.合肥市酸雨污染分析及控制对策研究[J].安徽化工,2002,118(4):30-31;
[31]周涛,古田会,赵彩.贵阳市酸雨过程的天气学研究[J].贵州气象,1997,2(3:23-25;)
[32]杨本宏.我国酸雨危害现状及防治对策[J].合肥联合大学学报,2000.10(2):102-106;
[33]曹洪法,舒俭民,刘燕云,高映新等.酸雨对两广地区农作物的经济损失研究[J].环境科学研究,1994,4(2):1-6;
[34]刘鸿亮.环境费用效益分析方法及实例[J].北京:中国环境科学出版社,1998,82-85;
[35]张林波,曹洪法,沈英娃等.苏、浙、皖、闽、湘、鄂、赣7省酸沉降农业危害——农业损失估算[J].中国环境科学,1997.17(6):489-491;
[36]张林波,曹洪法,沈英娃等.苏、浙、皖、闽、湘、鄂、赣7省酸沉降农业危害——酸沉降农业生态综合危害分析[J].中国环境科学,1998.18(1):12-15;
[37]国家环保局计划司.环境规划指南[M].北京:清华大学出版社,1994,334;
[38]冯宗炜.中国酸雨的生态影响和防治对策[J].云南环境科学,2000,19(增刊):1-6;
[39]冯宗伟.中国酸雨对陆地生态系统的影响和防治对策[J].中国工程科学,2000.2(9):5-12;
[40]吴丹,王式功,尚可政.中国酸雨研究综述[J].干旱气象,2006,24(2):70-76;
[41]朱敏,孙宗修.我国酸雨的发展及对农作物的影响[J].科技通报,1998.14(5):361-364;
[42]于天仁.中国土壤的酸度特点和酸化问题[J].土壤通报,1988,19(2):49-51;
[43]唐孝炎.大气环境化学[M].北京:高等教育出版社,1990;
[44]吴劲兵,汪家权,孙世群.酸沉降农业经济损失估算[J].合肥工业大学学报,2002,25(1):100-104;
[45]牟永铭,朱光良.基于GIS技术的浙江省酸雨分布研究[J].科技通报,2003321(3):356-359;
[46]何隆华,样宏伟.应用GIS进行生态系统对酸雨的相对敏感性分析[J].地理科学,1996,16(4):317-322;
[47]刘宝章,李金龙,王敬云等.青岛酸雨天气边界层气象特征[J].中国环境科学,1997。17(4):103-107;
[48]王文兴,刘洪杰,张婉华等.我国东部沿海地区酸雨来源研究[J].中国环境科学,1997,17(5):387-392;
[49]Huang M,Wang Z,He D,et al.Modeling studies on sulfur deposition and transport in East Asia[J].Water,Air and Soil Pollution,1995,85:1927-1932;
[50]李金惠.中国降水酸度预测模型[J].中国环境科学,1998.18(1):8-11;
[51]吴甫成,吴君维,王晓燕等.湖南酸雨污染特征[J],环境科学学报,2000.20(6):807-809;
[52]陈旦华,孙庆瑞,王美蓉等.湖南省酸性降水的研究[J],环境科学研究,1998.11(2):8-12;
[53]许晶.湖南省酸性降水现状、成因及对策研究[J],环境污染治理技术与设备.2001.2(4):25-29;
[54]张龚,曾光明,蒋益民等.湖南省酸雨变化特征、现状及成因分析[J],环境科学研究.2003.16(5):14-17;
[55]蒋益民,曾光明,张现宝等.湖南省酸雨的主要特点域酸雨污染防治对策[J],湖南大学学报(自然科学版).2001.28(3):78-83;
[56]朱选祥.湖南省酸雨现状、成因及对策研究[J],企业技术开发,2006.25(10):28-30;
[57]刘丽,廖柏寒,雷鸣等.长沙市酸性降水现状与成因及对策[J],湖南农业大学学报(自然科学版).2005-31(2):216-218;
[58]方至.长沙市酸雨现状分析[J],湖南农业大学学报.1998.24(1):43-46;
[59]刘文华,刘芬,娄涛.株洲市酸雨污染特征及防治措施研究[J],环境科学动态,2002(1):21-24;
[60]王剑秋.衡阳市酸雨的成因及其污染的预测与对策[J],衡阳师专学报.1995.13(1):55-58;
[61]郭基联,张恒喜,刘晓东.飞机机体研制费用的偏最小二乘回归分析[J],数量经济技术经济研究.2001(4):121-124;
[62]郭进,刘洪霖,黄铁生等.计算机辅助材料设计的偏最小二成法——人工神经网络研究[J],计算机与应用化学,1996.13(4):253-256;
[63]王帅,范春彦,辛永平.基于偏最小二乘回归的研制费用估算模型[J].陕西师范大学学报(自然科学版),2007.35:29-32;
[64]蒋红卫,夏结来.偏最小二乘回归及其应用[J].第四军医大学学报,2003.24(3):280-283;
[65]许凤华,李述山.基于改进的偏最小二乘回归的酸雨pH值预测[J].山东科技大学学报(自然科学版).2006,25(3):110-112;
[66]李洪,代进,蒋金泉.偏最小二乘回归的神经网络模型在巷道围岩位移预测中的应用[J],煤炭学报,2004,29(3):274-278;
[67]陈南祥,黄强,曹连海.基于偏最小二乘回归与神经网络耦合的岩液泉预报模型[J],水利学报,2004(9):68～72;
[68]王文圣,熊华康,曹宏伟.酸雨pH预测的偏最小二乘回归模型[J],四川环境,2003.22(6):77-80;
[69]邓念武,徐晖.单因变量的偏最小二乘回归模型及其应用[J],武汉大学学报(工学版),2001.34(2):14-16;1
[70]王惠文,刘强,屠永平.偏最小二乘回归模型内涵分析方法研究[J],北京航空航天大学学报,2000.26(4):473-476;
[71]王惠文等.偏最小二乘回归方法及其应用[M].北京:国防工业出版社,2000;
[72]张恒喜,郭基联,朱家元等.小样本多元数据分析方法及应用[M].西北工业大学出版社,2002;
[73]徐华山,任玉芬,向中林.GIS在环境科学中的应用[J].干旱环境监测,2007.21(1):42-46;
[74]陈述彭,鲁学军,周成虎.地理信息系统导论[M].北京:科学出版社,1995,3,6-7;
[75]江东.地理信息系统及其在全球变化研究中的应用[M].北京:气象出版社,2003,4
[76]邬伦,刘瑜,马修军等.地理信息系统——原理、方法和应用[M].北京:科学出版社,2001;
[77]张丽,鄢团军.GIS在资源环境领域中的应用[J].现代商贸工业,2007.19(9):84-85;
[78]王锦慧,王燕,陈剑.GIS技术及其在环境保护中的作用[J].中国环境科学学会学术年会优秀论文集,2007:1877-1879;
[79]郝莉莉,冯启言,王华.GIS技术在环境管理信息系统中的应用研究[J].环境监测与管理,2005(4):17-20;
[80]帅方敏.地理信息系统技术在环境领域中的应用[J].山西科技,2007(1):49-51;
[81]邬伦,张晶,赵伟等.地理信息系统[M].北京:电子工业出版社,2001;
[82]郭仁忠.空间分析[M].北京:高等教育出版社,2006;
[83]胡月鹏,黄杏元,华一新.地理信息系统教程[M].武汉:武汉大学出版社;2002;
[84]龚键雅.地理信息系统基础[M].北京:科学出版社,2004;
[85]张康聪.地理信息系统导论[M].北京:科学出版社,2006;
[86]张超.地理信息系统应用教程[M].北京:科学出版社,2007;
[87]汤国安,杨昕等.ArcGIS地理信息系统空间分析实验教程[M].北京:科学出版社,2006;
[88]蔡福,明惠青,刘兵等.采用地统计学和GIS技术对东北地区不同时期降水的分析[J].中国农业气象,2006,27(4):296-299;
[89]邵晓梅,严昌荣,魏红兵.基于Kriging插值的黄河流域降水的时空分布格局[J].中国农业气象,2006,27(2):65-69;
[90]蔡福,于慧波,矫玲玲等.降水要素空间插值精度的对比——以东北地区为例[J].资源科学,2006,28(6):73-79;
[91]林孝松,余倩.重庆市农业气候资源空间插值研究[J].安徽农业科学,2008.36(30):13461-13463,13470;
[92]马菲,汪亚平,李炎等.地统计法支持的北部湾东部海域沉积物粒径趋势分析[J].地理学报,2008.63(11):1207-1307;
[93]马来刚,程永政,刘婷.空间插值技术在冬小麦单产预测中的应用[J].河北农业科学,2008.12(10):4-5,26;
[94]湖南省统计年鉴 2005;
[95]http://baike.baidu.com/view/8581.htm;
[96]2007年湖南省环境状况公报;
[97]赵艳霞,侯青,徐晓斌等.2005年中国酸雨时空分布特征[J].气候变化研究进展,2006.2(5):242-245;
[98]陈雪莲.北海酸雨区的成因简析[J].广西气象,2004.25(2):35-36;
[99]黎云,孙庆瑞.氨的湿去除及氨在酸雨中的作用[J].环境科学研究,1996.9(6):41-44;
[100]蒋益民.湖南省酸雨的防治措施、危害和防治措施的初步研究[D].长沙:湖南大学.2001;
[101]朱良峰,吴信才,刘修国.GIS中矢量多边形网络化问题研究[J].地理与地理信息科学,2004.20(1):12-15;
[102]陈载林,黄临平,陈玉梁.基于MapGIS的网格化数据批量精确提取[J].西部探矿工程,2009(2):202-203;