基于污染物总量控制的青岛市结构减排研究
|
摘要
产业结构不仅关系着经济增长的质量，而且决定了环境污染的水平。随着青岛市经济高速发展和人口规模逐步增大，工农业生产和居民生活产生的污染物排放量大幅增加，加之目前青岛市产业结构和生产力布局不尽合理，所形成的环境污染特别是结构性污染对青岛近海海洋生态环境造成了巨大压力，现有产业结构和布局将无法承载青岛市社会经济可持续发展的需求。亟需探索环境约束下的产业结构优化，在产业结构优化过程中实现经济与环境的协调发展。
本文以青岛市产业结构优化与海洋生态环境质量改善为主线，在系统评价青岛市现有产业污染排放强度和污染排放结构的基础上，建立青岛市生活、农业、工业和服务业全行业污染源排放强度准入基准体系，估算了青岛市生活、农业、工业和服务业污染源的分配容量，并据此提出了青岛市产业结构优化和调整措施、建议。所取得的主要研究成果如下：
1、系统评价了青岛市生活、农业、工业和服务业的污染排放强度和污染结构
（1）以不同行业排放的COD（Chemical Oxygen Demand）、总氮、总磷的排放强度为指标，对2007年青岛市生活、农业、工业和服务业的污染排放强度进行了系统评价。结果表明，青岛市生活源和服务业源排放强度分别高于全国平均水平的9.9%和54.5%，其中，居民生活源中的城镇居民生活排放强度高于全国平均水平17.5%；服务业源中的个人服务业、社会服务业、流通服务业和生产服务业排放强度都高于国家平均水平，分别达1.4%、61.2%、37.8%和41.0%，尽管农业源和工业源的污染物整体排放强度低于全国平均水平，但农业中种植业大类的排放强度高于全国平均水平12.8%，工业中电力、燃气和水的生产和供应业门类的排放强度则高于全国平均水平的158.8%。
（2）以污染结构基尼系数为指标，综合评价了2007年青岛市生活、农业、工业和服务业的污染排放结构。结果表明，青岛市生活和农业的污染结构基尼系数分别为0.12和0.32，低于0.40的污染结构均衡“警戒线”，表明青岛市生活和农业污染结构适度均衡；而工业和服务业的污染结构基尼系数分别达到0.69和0.96，工业污染源内部的制造业以及服务业污染源内的个人服务业和社会服务业的污染结构基尼系数也高于0.4的警戒线，表明青岛市工业和服务业及其行业内部的经济效益和环境污染之间矛盾突出。
2、建立了青岛市生活、农业、工业和服务业污染排放强度行业准入基准
（1）首先，以青岛市第一次污染源普查数据中污染物排放强度为基础，经过数据筛选、污染源初始层级确定、聚类分析和基准等级划分、污染层级归位、基准校验等步骤，建立了工业COD污染物排放强度（ICOD）的5等-11级行业准入基准，包括Ⅰ级（超低级，ICOD≤0.1千克/万元）、Ⅱ级（低级，0.1千克/万元100千克/万元）五个等级。继而将工业COD排放强度行业准入基准推广到生活、农业和服务业，建立了青岛市全行业COD污染物排放强度5等-11级准入基准。通过不同污染层级污染源的类间内差率和国家平均水平为参照的核参差率分析结果表明，所建立的5等-11级行业排放强度准入基准具有一定的科学性和先进性，不同污染层级的的覆盖率和匹配度结果表明，所建立的5等-11级行业排放强度准入基准的普适性和可操作性都较强。
（2）从青岛市生活、农业、工业和服务业的污染物排放强度在准入基准等级中的归位情况看，农业源COD污染物整体排放强度处于Ⅴ（超高）级，其中的种植业和畜牧业也处于Ⅴ（超高）级，仅渔业处于Ⅲ（中）级；工业源COD污染物整体排放强度处于第Ⅲ（中）级，但其中建筑业归属于Ⅰ（超低）等级，电力、燃气和水的生产和供应业归属于Ⅱ（低）等级，采矿业和制造业则都属于Ⅲ（中）等级；服务业源COD污染物整体排放强度处于第Ⅲ（中）级，但是其中的个人服务业处于第Ⅳ（高）级，社会服务业处于第Ⅱ（低）级，而流通服务业和生产服务业处于第Ⅰ（超低）级。
3、以2007年为基准年，估算了规划年（2015年和2020年）青岛市生活、农业、工业和服务业COD污染物分配容量，并规划了其产业发展。
（1）以青岛市生活、农业、工业和服务业污染物分配容量最大为目标函数，以青岛市陆源污染物的纳污海域（包括胶州湾、莱州湾和黄海）对应的三大排污管理区系COD污染物分配容量为限定值，以行业污染源排放强度、、经济总量、居民生活、污染结构等为约束条件，以2007年为基准年，以2015年和2020年分别为规划年，采用多目标非线性规划方法，分步估算了青岛市生活、农业、工业、服务业污染源的COD分配容量和各行业污染源在五级准入基准中的分配容量。结果表明，规划年即2015年和2020年青岛全市生活、农业、工业、服务业污染源的COD分配容量较基准年2007年分别提高了62%和84%；与基准年相比，规划年生活和农业污染源COD分配容量所占比重下降，而工业和服务业污染源COD分配容量所占比重上升。同时，从2007年到2015年和2020年，各排污管理区系COD分配容量呈现递增的趋势，表明各排污管理区系的分配容量利用率逐步提高，而胶州湾排污管理区系COD分配容量占全市比重呈现逐步下降的趋势，莱州湾和黄海排污管理区系分配容量占全市比重则逐步上升，表明不同排污管理区系之间分配容量的利用趋于均衡。同时，与基准年（2007年）相比，经优化分配后，规划年（2015年和2020年）农业源、工业源、服务业源处于五级准入基准的COD排放占比和产值占比基本都呈现出处于高排放强度等级的污染源的COD和产值占比下降和处于低排放强度等级的污染源的COD和产值占比上升的变化趋势。
（2）相对于基准年2007年，规划年2015年和2020年，青岛市全市国民生产总值分别提高了3.2倍和4.4倍，且呈现第一产业比重逐步下降，第二产业和第三产业比重逐步上升的变化趋势。表明青岛市产业结构逐步由“二三一”开始向“三二一”转变；经优化后，COD排放强度高的生活源和农业源的COD排放强度下降，污染物排放强度低的工业源和服务业源的COD排放强度上升。同时，从2007年到2015年和2020年，青岛市及各排污管理区系内生活、农业、工业和服务业污染源以及不同污染源在五级排放强度准入等级中的基尼系数降低，都低于或接近0.40的临界值，表明产业结构趋于合理。
（3）依据青岛市生活、农业、工业、服务业污染源的污染结构评价和产业结构调整优化分析结果，提出“优化提升第一产业，发展壮大第二产业，突破发展第三产业”的青岛市产业发展和规划建议。包括积极发展生态农业，扩大养殖规模，减少种植业和渔业污染排放，淘汰和限制低产值、高排放的传统工业发展，引导和鼓励高新技术和先进制造业的发展，大力发展现代生产和流通服务业，大力提高居民生活和个人服务业污水回收和处理率等。
Industrial structure plays an important role in the quality of economic growth aswell as in determining the level of environmental pollution. In Qingdao, pollutantsfrom industry, agriculture and household have been greatly increased with the rapideconomic development and the fast increasing population. Moreover, the industrialstructures are not reasonable. Coastal eco-environmental quality is deteriorating withthe high pollutant emissions. As a result, it is difficult to accomplish the sustainabledevelopment in the current industrial structure. Thus, extensive researches on thestructure optimization with the environmental control and management are necessaryto achieve the coordination of economic development and the environmentalregulation.
The present research focuses on the structure optimization and the improvement ofmarine ecology. After evaluating different industries’ environmentalpollution-economic benefit impact, an access standard on pollution intensities ofindustries of Qingdao was established. And then, the allocated capacity of HouseholdGroup, Agriculture Group, Industry Group and Service Group in Qingdao wasestimated and some suggestions on the structure optimization of Qingdao wereproposed based on the calculated results. The main results are as follows.
1. The pollution intensity and pollution structure of Household Group, AgricultureGroup, Industry Group and Service Group in Qingdao was evaluated.
(1) The pollution intensity of Household Group, Agriculture Group, IndustryGroup and Service Group in Qingdao was evaluated by a single proxy derived fromchemical oxygen demand (COD), total nitrogen and total phosphate. The results showthat pollution intensity of Service Group and Household Group is9.9%and54.5%higher than the national average value. Of the Household Goup, pollution intensity ofthe Urban Household Cluster is17.5%higher than the national average value. Of theService Group, pollution intensity of the Personal Service Cluster, the Social ServiceCluster, the Circulation Service Cluster and the Productive Service Cluster is1.4%, 61.2%,37.8%and41.0%higher than the national average value respectively. Thepollution intensity of the Agriculture and Industry Groups is lower than the nation’saverage value. Of the Agriculture Group, the pollution intensity of planting Class is12.8%higher than the national average value. Of the Industry Group, the pollutionintensity of Electricity, Gas and Water Production and Supply Sector is158.8%higherthan the national average value.
(2) The pollution structure of Household Group, Agriculture Group, IndustryGroup and Service Group in Qingdao was also evaluated based on the Gini coefficient.It is showed that the Gini coefficients of Household Group and Agriculture Group are0.12and0.32respectively, which are lower than the value of0.40, the warning line ofGini coefficient. This indicates the Household Group and Agriculture Group’spollution instucture is basically balanced. The Gini coefficients of Industry Group andService Group are0.69and0.96respectively, which are higher than the value of0.40.Furthermore, The Gini coefficients of Mannufacturing Sector in the Industry Groupand of Personal Service Cluster and the Social Service Cluster in the Service Groupare higher than the value of0.40. This indicates the serious controdictionary ofbenefits and pollution of within the Industry group and Service Group.
2. An access standard on pollution intensities of industries of Household Group,Agriculture Group, Industry Group and Service Group of Qingdao was established.
(1) First, based on the data set of COD pollution intensity from the first census ofpollution sources in Qingdao City, a5rank-11level industrial access standard isconstructed with the methods of data screening, the initial level of pollutionidentification, cluster analysis, standard classification, pollution level matching andstandard vertification. The five ranks are rankⅠ(super low rank, ICOD≤0.1kilogramper10thousand yuan), rank Ⅱ(low rank,0.1kilogram per10thousand yuan100kilogram per10thousand yuan). Second, thepollution intensities of the Household Group, Agriculture Group and Service Groupare matched with the industrial access standard. Finally, a5rank-11level accessstandard of all industries is established. Based on the pollution intensity value, the acess standard is verified and evaluated by four indexies, that is the ratio of thestandard deviation between ranks relative to the standard deviation inside every rank,the ratio of the the pollution intensity accounted relative to the pollution intensityreferenced, the proportion of the number of industries covered by the access standardand the matching degree. The results show that the access standard is scientific,advanced, generally applicable and operable.
(2) According to the matching degree of the pollution intensities of HouseholdGroup, Agriculture Group and Service Group with the industrial access standard, thewhole Agriculture Group is in rank Ⅴ, of which the PlantingClass and the LivestockFarming Class is in rank Ⅴ, and the FisheryClass is in rank Ⅲ. The whole IndustryGroup is in rank Ⅲ, of which, the Construction Sctor and the Electricity, Gas andWater Production and Supply Sector are in rankⅠand rank Ⅱrepectively, and theMining Sector and Manufacturing Sector are both in rank Ⅲ. The whole ServiceGroup is in rank Ⅲ, of which the Personal Service Cluster is in rank Ⅳ, the SocialService Cluster is in rank Ⅱand the Circulation Services Cluster and ProductionService Cluster are in rank Ⅰ.
3. Taking2007as the base year, the allocated COD capacity of Household Group,Agriculture Group, Industry Group and Service Group of Qingdao, in2015and2020,was calculated. Based on the results, an industry development plan also wasproposed..
(1) Aimed at the maximum amount of the allocated COD capacity of HouseholdGroup, Agriculture Group, Industry Group and Service Group of Qingdao, taking2007as the base year and2015and2020as the targe year, taking the allocated CODcapacity of three sewage management districts corresponding to three waters ofQingdao (including Jiaozhou Bay, Laizhou Bay and Yellow Sea), the pollutionintensity, gross domestic production, population and Gini coefficient as restrictions,using the single objective nonlinear programming method, allocated COD capacity ofAgriculture Group, Industry Group, Service Group and Household Group and theallocated COD capacity of every rank of access standard of different Groups arecalculated in two steps. The results indicate that the total allocated COD capacity offour Groups in2015and2020is62%and84%more than that in2007respectively.The percent of allocated COD capacity of Household Group and Agriculture Group is decreased, while the percent of allocated COD capacity of Industry Group and ServiceGroup is increased. Meanwhile, from2007to2020, the percent of allocated CODcapacity of three sewage management districts is increased gradually, which indicatesthat the utilization rate of allocated COD capacity of three sewage managementdistricts is also increased. On the other side, the percent of allocated COD capacity ofJiaozhou Bay sewage management district has a gradual decreasing trend, while thepercent of allocated COD capacity of Laizhou Bay sewage management district andYellow Sea sewage management district has a gradual increasing trend, whichindicates the proportion of allocated capacity of three sewage management districts ismore and more balanced and reasonable. In addition, from2007to2020, the allocatedCOD capacity of every rank of the access standard of Household Group, AgricultureGroup, Industry Group and Service Group have a trend that the proportion ofallocated COD capacity and added value of groups which are in the high rank ofaccess standard is decresing and the proportion of allocated COD capacity and addedvalue of groups which are in the low rank of access standard is increasing.
(2) The results obtained through the model also indicate that the Gross Domesticproduction（GDP）of Qingdao in2015and2020is3.2and4.4times of that in2007respectively. And a trend that the proportion of added value of the primary industry isdecreasing, but the proportion of added value of the secondary industry and thetertiary industry is increasing is observed, which indicates that the industrial structureof Qingdao is turning from the feature that the Industry Group’s added value takes thelargest proportion of GDP to the feature that the Service group’s added value takes thelargest proportion of GDP. Meanwhile, after optimization by the model, the CODpollution intensity of some Groups, including Household Group and AgricultureGroup, whose COD pollution intensity is higher than that of otherGroups in the yearof2007is decreased in the targeted year of2015and2020. The COD pollutionintensity of other Groups, including Industry Group and Service Group, whose CODpollution intensity is lower than that of other Groups in the year of2007is increasedin the targeted year of2015and2020. Finally, the Gini coefficients of HouseholdGroup, Agriculture Group, Industry Group and Service Group of different sewagemanagement districts and the Gini coefficients of different groups in the5-rank accessstandard are lower than or close to the warning value of Gini coefficient (0.4). Thisalso indicates that the industrial structure of Qingdao is becoming more and more reasonable.
(3) According to the results of pollution intensities comparation, pollutionstructures evaluation and structure optimization analysis of Household Group,Agriculture Group, Industry Group and Service Group, the followings are proposed:the Agriculture group should be optimized and improved, the Industry group need tobe expanded and the Service group should be promoted in a breakthrough way inQingdao. For the Agriculture Group, the ecological agriculture and the LivestockFarming’s expansion should be encouraged, while the Plantting Class and FisheryClass should be adjusted in the way of focusing on cutting down the amount ofpollutant. For the Industry Group, some conditional industries which are in the highrank of access standard should be limited or enen eliminated, while industries withhigh and new technology should be encouraged. For the Service Group, besidesimproving the sewage treatment rate of waste water from the Household Group andPersonal Service Cluster, Circulation Services Cluster and Production Service Clustershould be promoted.
本文以青岛市产业结构优化与海洋生态环境质量改善为主线，在系统评价青岛市现有产业污染排放强度和污染排放结构的基础上，建立青岛市生活、农业、工业和服务业全行业污染源排放强度准入基准体系，估算了青岛市生活、农业、工业和服务业污染源的分配容量，并据此提出了青岛市产业结构优化和调整措施、建议。所取得的主要研究成果如下：
1、系统评价了青岛市生活、农业、工业和服务业的污染排放强度和污染结构
（1）以不同行业排放的COD（Chemical Oxygen Demand）、总氮、总磷的排放强度为指标，对2007年青岛市生活、农业、工业和服务业的污染排放强度进行了系统评价。结果表明，青岛市生活源和服务业源排放强度分别高于全国平均水平的9.9%和54.5%，其中，居民生活源中的城镇居民生活排放强度高于全国平均水平17.5%；服务业源中的个人服务业、社会服务业、流通服务业和生产服务业排放强度都高于国家平均水平，分别达1.4%、61.2%、37.8%和41.0%，尽管农业源和工业源的污染物整体排放强度低于全国平均水平，但农业中种植业大类的排放强度高于全国平均水平12.8%，工业中电力、燃气和水的生产和供应业门类的排放强度则高于全国平均水平的158.8%。
（2）以污染结构基尼系数为指标，综合评价了2007年青岛市生活、农业、工业和服务业的污染排放结构。结果表明，青岛市生活和农业的污染结构基尼系数分别为0.12和0.32，低于0.40的污染结构均衡“警戒线”，表明青岛市生活和农业污染结构适度均衡；而工业和服务业的污染结构基尼系数分别达到0.69和0.96，工业污染源内部的制造业以及服务业污染源内的个人服务业和社会服务业的污染结构基尼系数也高于0.4的警戒线，表明青岛市工业和服务业及其行业内部的经济效益和环境污染之间矛盾突出。
2、建立了青岛市生活、农业、工业和服务业污染排放强度行业准入基准
（1）首先，以青岛市第一次污染源普查数据中污染物排放强度为基础，经过数据筛选、污染源初始层级确定、聚类分析和基准等级划分、污染层级归位、基准校验等步骤，建立了工业COD污染物排放强度（ICOD）的5等-11级行业准入基准，包括Ⅰ级（超低级，ICOD≤0.1千克/万元）、Ⅱ级（低级，0.1千克/万元
（2）从青岛市生活、农业、工业和服务业的污染物排放强度在准入基准等级中的归位情况看，农业源COD污染物整体排放强度处于Ⅴ（超高）级，其中的种植业和畜牧业也处于Ⅴ（超高）级，仅渔业处于Ⅲ（中）级；工业源COD污染物整体排放强度处于第Ⅲ（中）级，但其中建筑业归属于Ⅰ（超低）等级，电力、燃气和水的生产和供应业归属于Ⅱ（低）等级，采矿业和制造业则都属于Ⅲ（中）等级；服务业源COD污染物整体排放强度处于第Ⅲ（中）级，但是其中的个人服务业处于第Ⅳ（高）级，社会服务业处于第Ⅱ（低）级，而流通服务业和生产服务业处于第Ⅰ（超低）级。
3、以2007年为基准年，估算了规划年（2015年和2020年）青岛市生活、农业、工业和服务业COD污染物分配容量，并规划了其产业发展。
（1）以青岛市生活、农业、工业和服务业污染物分配容量最大为目标函数，以青岛市陆源污染物的纳污海域（包括胶州湾、莱州湾和黄海）对应的三大排污管理区系COD污染物分配容量为限定值，以行业污染源排放强度、、经济总量、居民生活、污染结构等为约束条件，以2007年为基准年，以2015年和2020年分别为规划年，采用多目标非线性规划方法，分步估算了青岛市生活、农业、工业、服务业污染源的COD分配容量和各行业污染源在五级准入基准中的分配容量。结果表明，规划年即2015年和2020年青岛全市生活、农业、工业、服务业污染源的COD分配容量较基准年2007年分别提高了62%和84%；与基准年相比，规划年生活和农业污染源COD分配容量所占比重下降，而工业和服务业污染源COD分配容量所占比重上升。同时，从2007年到2015年和2020年，各排污管理区系COD分配容量呈现递增的趋势，表明各排污管理区系的分配容量利用率逐步提高，而胶州湾排污管理区系COD分配容量占全市比重呈现逐步下降的趋势，莱州湾和黄海排污管理区系分配容量占全市比重则逐步上升，表明不同排污管理区系之间分配容量的利用趋于均衡。同时，与基准年（2007年）相比，经优化分配后，规划年（2015年和2020年）农业源、工业源、服务业源处于五级准入基准的COD排放占比和产值占比基本都呈现出处于高排放强度等级的污染源的COD和产值占比下降和处于低排放强度等级的污染源的COD和产值占比上升的变化趋势。
（2）相对于基准年2007年，规划年2015年和2020年，青岛市全市国民生产总值分别提高了3.2倍和4.4倍，且呈现第一产业比重逐步下降，第二产业和第三产业比重逐步上升的变化趋势。表明青岛市产业结构逐步由“二三一”开始向“三二一”转变；经优化后，COD排放强度高的生活源和农业源的COD排放强度下降，污染物排放强度低的工业源和服务业源的COD排放强度上升。同时，从2007年到2015年和2020年，青岛市及各排污管理区系内生活、农业、工业和服务业污染源以及不同污染源在五级排放强度准入等级中的基尼系数降低，都低于或接近0.40的临界值，表明产业结构趋于合理。
（3）依据青岛市生活、农业、工业、服务业污染源的污染结构评价和产业结构调整优化分析结果，提出“优化提升第一产业，发展壮大第二产业，突破发展第三产业”的青岛市产业发展和规划建议。包括积极发展生态农业，扩大养殖规模，减少种植业和渔业污染排放，淘汰和限制低产值、高排放的传统工业发展，引导和鼓励高新技术和先进制造业的发展，大力发展现代生产和流通服务业，大力提高居民生活和个人服务业污水回收和处理率等。
Industrial structure plays an important role in the quality of economic growth aswell as in determining the level of environmental pollution. In Qingdao, pollutantsfrom industry, agriculture and household have been greatly increased with the rapideconomic development and the fast increasing population. Moreover, the industrialstructures are not reasonable. Coastal eco-environmental quality is deteriorating withthe high pollutant emissions. As a result, it is difficult to accomplish the sustainabledevelopment in the current industrial structure. Thus, extensive researches on thestructure optimization with the environmental control and management are necessaryto achieve the coordination of economic development and the environmentalregulation.
The present research focuses on the structure optimization and the improvement ofmarine ecology. After evaluating different industries’ environmentalpollution-economic benefit impact, an access standard on pollution intensities ofindustries of Qingdao was established. And then, the allocated capacity of HouseholdGroup, Agriculture Group, Industry Group and Service Group in Qingdao wasestimated and some suggestions on the structure optimization of Qingdao wereproposed based on the calculated results. The main results are as follows.
1. The pollution intensity and pollution structure of Household Group, AgricultureGroup, Industry Group and Service Group in Qingdao was evaluated.
(1) The pollution intensity of Household Group, Agriculture Group, IndustryGroup and Service Group in Qingdao was evaluated by a single proxy derived fromchemical oxygen demand (COD), total nitrogen and total phosphate. The results showthat pollution intensity of Service Group and Household Group is9.9%and54.5%higher than the national average value. Of the Household Goup, pollution intensity ofthe Urban Household Cluster is17.5%higher than the national average value. Of theService Group, pollution intensity of the Personal Service Cluster, the Social ServiceCluster, the Circulation Service Cluster and the Productive Service Cluster is1.4%, 61.2%,37.8%and41.0%higher than the national average value respectively. Thepollution intensity of the Agriculture and Industry Groups is lower than the nation’saverage value. Of the Agriculture Group, the pollution intensity of planting Class is12.8%higher than the national average value. Of the Industry Group, the pollutionintensity of Electricity, Gas and Water Production and Supply Sector is158.8%higherthan the national average value.
(2) The pollution structure of Household Group, Agriculture Group, IndustryGroup and Service Group in Qingdao was also evaluated based on the Gini coefficient.It is showed that the Gini coefficients of Household Group and Agriculture Group are0.12and0.32respectively, which are lower than the value of0.40, the warning line ofGini coefficient. This indicates the Household Group and Agriculture Group’spollution instucture is basically balanced. The Gini coefficients of Industry Group andService Group are0.69and0.96respectively, which are higher than the value of0.40.Furthermore, The Gini coefficients of Mannufacturing Sector in the Industry Groupand of Personal Service Cluster and the Social Service Cluster in the Service Groupare higher than the value of0.40. This indicates the serious controdictionary ofbenefits and pollution of within the Industry group and Service Group.
2. An access standard on pollution intensities of industries of Household Group,Agriculture Group, Industry Group and Service Group of Qingdao was established.
(1) First, based on the data set of COD pollution intensity from the first census ofpollution sources in Qingdao City, a5rank-11level industrial access standard isconstructed with the methods of data screening, the initial level of pollutionidentification, cluster analysis, standard classification, pollution level matching andstandard vertification. The five ranks are rankⅠ(super low rank, ICOD≤0.1kilogramper10thousand yuan), rank Ⅱ(low rank,0.1kilogram per10thousand yuan
(2) According to the matching degree of the pollution intensities of HouseholdGroup, Agriculture Group and Service Group with the industrial access standard, thewhole Agriculture Group is in rank Ⅴ, of which the PlantingClass and the LivestockFarming Class is in rank Ⅴ, and the FisheryClass is in rank Ⅲ. The whole IndustryGroup is in rank Ⅲ, of which, the Construction Sctor and the Electricity, Gas andWater Production and Supply Sector are in rankⅠand rank Ⅱrepectively, and theMining Sector and Manufacturing Sector are both in rank Ⅲ. The whole ServiceGroup is in rank Ⅲ, of which the Personal Service Cluster is in rank Ⅳ, the SocialService Cluster is in rank Ⅱand the Circulation Services Cluster and ProductionService Cluster are in rank Ⅰ.
3. Taking2007as the base year, the allocated COD capacity of Household Group,Agriculture Group, Industry Group and Service Group of Qingdao, in2015and2020,was calculated. Based on the results, an industry development plan also wasproposed..
(1) Aimed at the maximum amount of the allocated COD capacity of HouseholdGroup, Agriculture Group, Industry Group and Service Group of Qingdao, taking2007as the base year and2015and2020as the targe year, taking the allocated CODcapacity of three sewage management districts corresponding to three waters ofQingdao (including Jiaozhou Bay, Laizhou Bay and Yellow Sea), the pollutionintensity, gross domestic production, population and Gini coefficient as restrictions,using the single objective nonlinear programming method, allocated COD capacity ofAgriculture Group, Industry Group, Service Group and Household Group and theallocated COD capacity of every rank of access standard of different Groups arecalculated in two steps. The results indicate that the total allocated COD capacity offour Groups in2015and2020is62%and84%more than that in2007respectively.The percent of allocated COD capacity of Household Group and Agriculture Group is decreased, while the percent of allocated COD capacity of Industry Group and ServiceGroup is increased. Meanwhile, from2007to2020, the percent of allocated CODcapacity of three sewage management districts is increased gradually, which indicatesthat the utilization rate of allocated COD capacity of three sewage managementdistricts is also increased. On the other side, the percent of allocated COD capacity ofJiaozhou Bay sewage management district has a gradual decreasing trend, while thepercent of allocated COD capacity of Laizhou Bay sewage management district andYellow Sea sewage management district has a gradual increasing trend, whichindicates the proportion of allocated capacity of three sewage management districts ismore and more balanced and reasonable. In addition, from2007to2020, the allocatedCOD capacity of every rank of the access standard of Household Group, AgricultureGroup, Industry Group and Service Group have a trend that the proportion ofallocated COD capacity and added value of groups which are in the high rank ofaccess standard is decresing and the proportion of allocated COD capacity and addedvalue of groups which are in the low rank of access standard is increasing.
(2) The results obtained through the model also indicate that the Gross Domesticproduction（GDP）of Qingdao in2015and2020is3.2and4.4times of that in2007respectively. And a trend that the proportion of added value of the primary industry isdecreasing, but the proportion of added value of the secondary industry and thetertiary industry is increasing is observed, which indicates that the industrial structureof Qingdao is turning from the feature that the Industry Group’s added value takes thelargest proportion of GDP to the feature that the Service group’s added value takes thelargest proportion of GDP. Meanwhile, after optimization by the model, the CODpollution intensity of some Groups, including Household Group and AgricultureGroup, whose COD pollution intensity is higher than that of otherGroups in the yearof2007is decreased in the targeted year of2015and2020. The COD pollutionintensity of other Groups, including Industry Group and Service Group, whose CODpollution intensity is lower than that of other Groups in the year of2007is increasedin the targeted year of2015and2020. Finally, the Gini coefficients of HouseholdGroup, Agriculture Group, Industry Group and Service Group of different sewagemanagement districts and the Gini coefficients of different groups in the5-rank accessstandard are lower than or close to the warning value of Gini coefficient (0.4). Thisalso indicates that the industrial structure of Qingdao is becoming more and more reasonable.
(3) According to the results of pollution intensities comparation, pollutionstructures evaluation and structure optimization analysis of Household Group,Agriculture Group, Industry Group and Service Group, the followings are proposed:the Agriculture group should be optimized and improved, the Industry group need tobe expanded and the Service group should be promoted in a breakthrough way inQingdao. For the Agriculture Group, the ecological agriculture and the LivestockFarming’s expansion should be encouraged, while the Plantting Class and FisheryClass should be adjusted in the way of focusing on cutting down the amount ofpollutant. For the Industry Group, some conditional industries which are in the highrank of access standard should be limited or enen eliminated, while industries withhigh and new technology should be encouraged. For the Service Group, besidesimproving the sewage treatment rate of waste water from the Household Group andPersonal Service Cluster, Circulation Services Cluster and Production Service Clustershould be promoted.
引文
[1] A.A. Oketola, O. Osibanjo b. Estimating sectoral pollution load in Lagos by IndustrialPollution Projection System (IPPS). Science of the Total Environment,2007,377:125–141
[2] Aleg Cherp, Irina Kopteva, Ruben Mnatsakanian. Economic transition and environmentalsustainability: effects of economic restructuring on air pollution in the Russian Federation.Journal of Environmental Management,2003,68,141-151
[3] Bingham,T.H., Anderson,D.W. and Cooley, P.C., Distribution of the generation of airpollution. J. Environ. Econ. Manage.,1987,15(1):30-40
[4] Burn, D.H. and Lence, B. Comparison of optimization formulations for waste load allocation.Environmental Engineering,1992,11(84):597-612
[5] Cardwell H, Ells H. Stochastic dynamic programming models for water quality management.Water Resources Research,1993,29(4):803-813
[6] Carter, Brandon, Ramesh Ramankutty. Toward an Environmental Strategy for Asia: asummary of a World Bank discussion paper. Washington, D.C.: The World Bank,1993.
[7] Chih sheng Lee, Ching gung Wen. Application of muti-objective programming to waterquality management in a river basin. Journal of Environment Management,1996,47:11-26
[8] David E. Kolo. Yacov Y. Haimes. Capacity expansion and operational planning for regionalwater-resource systems.Journal of Hydrology.1977,32(3-4):363-381
[9] David E.Pingry, Andrew B.Whinston. Application of Mutigoal Water Quality Planning Model.Iournal of the Environmental Engineering Division,1974
[10] Deininger, R. A. Water Quality Management: The Planning of Economically OptimalPollution Control Systems. Ph.D. Thesis, Northwestern University,1965
[11] Donald H. B, Barbara J L. Comparison of optimization formulations for waste-loadallocations. Journal of environmental engineering,1992,118(4):597-612
[12] Donald H. B., Edward A. M. Optimization modeling of water quality in an uncertainenvironment, Water Resources Research,1985,21(7):934-940
[13] Duarte E. A., Neto I., Alegrias M., R. Barroso."Appropriate technology" for pollution controlin corrugated board industry-the Portuguese case. Water Science and Technology,1998,38(6):45-53
[14] Ecker, J.G. and Mcnamara, J. R. Geometric Programming and the Preliminary Design ofIndustrial Waste Treatment Plants. Water Resources Research,1971,8
[15] Echer G H. A Geometric Programming Model for Optimal Allocation of Stream DissolvedOxygen. Management Science,1975,21(6):581-591
[16] Ellis J H. Stochastic water quality optimization using imbedded chance constraints. WaterResource Res,1987,23(12):2227
[17] Ethan T.Smith and Alvin R.Morris. Systems Analysis for Optimal Water Quality Management.Journal of Water Quality Management,1969,41(9)
[18] Fan J, Hu H H. Studies and Applications of Environmental Kuznets Curve (EKC).Mathematics in Practice and Theory,2002,32(6):944-951
[19] Graves, G.W., Hatfield, G.B., and Whinston,A. Mathematical Programming for RegionalWater Quality Management. Water Resources Research,1972,8(2)
[20] Grossman, Gene M. and Alan Krueger. Economic Growth and the Environment. QuarterlyJournal of Economics,1995,110(2):353-373
[21] Haith D.1982. Environmental system optimization. New York: John Wiley&Sons
[22] Hakanson, L. The role of characteristic coefficients of variation in uncertainty and sensitivityanalyses, with examples related to the structuring of lake eutrophication models. EcologicalModeling,2000,131:1-20
[23] Hettige H, Martin P, Singh M, Wheeler D. The Industrial Pollution Projection System (IPPS).Policy research working paper no1431part1and2;1995.
[24] Hongyan Han, Keqiang Li, Xiulin Wang, Xiaoyong Shi, Xudong Qiao, Jing Liu.Environmental capacity of nitrogen and phosphorus pollutions in Jiaozhou Bay, China:Modeling and assessing. Marine Pollution Bulletin,63(2011):262-266
[25] James R.Marsden,David E. Pingry, Andrew Whinston.Application of NonlinearProgramming to Water Quality Control.Water, Air, and Soil Pollution,1973,2:155-169
[26] John A List, Craig A. Gallet. the Environmental Kuznets Curve: does one size fit all?Ecological Economics,1999,31:409-423
[27] Kerri, K. D..An Economic Approach to Water Quality Control. Paper presented at38thAnnual Conference of the Water Pollution Control Federation, Atlantic City, N.J.,1965.
[28] L. Somlyody and G. van Straten. Modeling and managing shallow lake eutrophication: WithApplication to Lake Balaton.1986environmental software,1(2):131
[29] L. Somlyody, G. van Straten. Modeling and managing shallow lake eutrophication: WithApplication to Lake Balaton.Environmental Software,1986,1(2):131
[30] L.Somlyody.Use of Optimization Models in River Basin Water Quality Planning.Wat.Sci.Tech,1997,36(5):209-218
[31] Leonard Ortolano. Environmental Planning and Decision Making. New York,1984
[32] Leontief,W.. Environmental repercussions and the economic structure: an input-outputapproach. Rev. Econ.Statistics,1970,52(3):262-271.
[33] Leontief, W. and Ford, D.. Air pollution and economic structure: empirical results ofinput-output computations.1972. Input-Output Techniques, Proc.5thInt. Conf. Input-OutputTechniques, Geneva,1971. Elsevier, NY, pp.9-30
[34] Li Shiyu, Tohru Morioka. Optimal allocation of waste loads in a river with probabilistictributary flow under transverse mixing. Water Environmental Research,1999,71(2):156-162.
[35] Liebman J. C., Lynn W. R. The Optimal Allocation of Stream Dissolved Oxygen, WaterResource Research,1966,2(3):581-591
[36] Loucks D. P., Revelle C. S., Lynn W. R. Management Models for Water Quality Control,Management Science, l967,14(4):166-181
[37] Mcnamara, J. R. The Optimal Design of Water Quality Management Systems. Ph.D.Thesis,Rensselaer Polytechnic Institute, Troy, New York,1971
[38] Millie DE, Schofield OM, Kirkpatrick GJ, el a1. Detection of harmful algal blooms usingphotopigments and absorption signatures: A case study of the Florida red tide，Gymnodiniumbreve. Limnology and Oceanography,1997,42:1240-1251
[39] Proops, J.L.R. Modelling the energy-output ratio. Energy Econ.,1984,6(1):47-51
[40] Revelle C. S., Loucks D. P., Lynn W. R., Linear Programming Applied to Water QualityManagement, Water Resource Research,1968,4(1): l-9
[41] Richard Calkins, et al.. Indonesia: Environment and development: Challenges for the Future.Washington, D.C.: The Word Bank,1994
[42] SasikumarK, MujumdarPP. Fuzzy optimization model for water quality management of ariver system.Journal of Water Resources Planning and Management-ASCE,1998,124(2)：79-88.
[43] Selden. T.M. and D.Song. Environment Quality and Development:Is There a kuznets Curvefor Air Pollution Emission?Journal of Environmental Economic and Management,1994,27:147-162
[44] Shih, C. S.,Kbishnan, P. Dynamic Optimization of Industrial Waste Treatment Plant Design.Jour. Water Pollution Control Federation,1969,41
[45] Sobel, M. J.. Water Quality Improvement Programming Problems. Water ResourcesResearch,1965,1(4)
[46] Thomann R V, Sobel M S. Estuarine Water Quality Management and Forecasting. Journal ofSanitary Engineering Division, ASCE,1964,89(5):9-36.
[47] USEPA. Eaxamples of Approved TMDLs. http://www.epa.gov/owow/tmdl/examples/
[48] USEPA. Protocol for developing nutrient TMDLs.Office of Water4503F Washington D C20460, EPA841-B-99-007,1999
[49] USEPA. Section303(d) of the Clean Water Act.http://www.epa.gov/owow/tmdl/intro.html#section303
[50] USEPA, US Environmental Protection Agency. New York/New Jersey Harbor EstuaryProgram, final comprehensive conservation and management plan, Region2, USEnvironmental Protection Agency, New York, NY.1996
[51] Wen，C-G and Lee，C-S. Fuzzy Programming Approach to Water Quality ManagementProceedings of the National Science Council，Republic of China.PartA：Physical Science andEngineering[Proc.Natl.Sci.Counc.Rep.China Pt.A：Phys.Sci.Eng.],1998,2（25）:579-590
[52] Wolff, E.N.. Industrial composition, interindustry effects and the US productivity slowdown.Rev. Econ. Stat.,1985,67(2):268-277
[53] Zhao Xixi, Wang Xiulin, Shi Xiaoyong, Li Keqiang, Ding Dongsheng. Environmentalcapacity of chemical oxygen demand in the Bohai Sea: modeling and calculation.中国海洋湖沼学报(英文版),2011(1):46-52
[54]包存宽,张敏,尚金城.流域水污染物排放总量控制研究——以吉林省松花江流域为例.地理科学,2000,20(1):61-64
[55]蔡喜明,翁文斌,史惠斌.基于宏观经济的区域水资源多目标集成系统.水科学进展,1995,6(2):2-7
[56]蔡载昌.环境污染总量控制.北京：中国环境科学出版社.1991
[57]曹利军.区域经济发展与水环境容量紧缺之间矛盾的调和一工业生产力宏观布局与产业结构调整策略.经济地理,1998,18(4):54-61
[58]曹利军.从水环境容量看我国的工业布局和产业结构调整.科技导报,1998,6:56-58
[59]曹瑞钰,顾国维.水环境治理工程费用优化模型.同济大学学报,1997,25(5):548-552.
[60]陈传明.闽江流域工业结构与布局对环境的影响.福建地理,2000,15(1):14-17
[61]陈东景.我国主要污染物排放强度的区域差异分析.生态环境，2008,17(1):133~137.
[62]陈广洲.基于水环境保护的产业结构AHP评价系统探讨.安徽建筑工业学院学报(自然科学版),2004,12(1):45-48
[63]陈仕权.生产性服务业的分类、特点及作用.郑州航空工业管理学院学报(社会科学版),2006,25(4):191-193
[64]陈治谏.模糊最优化方法在河流水质规划中的应用.中国环境科学,1989,9(1):64-68
[65]崔正国.环渤海13城市主要化学污染物排海总量控制方案研究:[博士学位论文].青岛:中国海洋大学,2008
[66]崔志清,董增川.基于水资源约束的产业结构调整模型研究.南水北调与水利科技,2008,6(2):60-63
[67]方秦华,张珞平.水污染负荷优化分配研究.环境保护,2005,12:29-31
[68]方秦华,张珞平.水污染负荷总量控制研究进展.环境污染与防治,2003,4:1-8
[69]方秦华,张珞平,王佩儿等.象山港海域环境容量的二步分配法.厦门大学学报(自然科学版)2004,43(增):217-220.
[70]方远平，毕斗斗.国内外服务业分类探索.国际经贸探索,2008,24(1):72~76.
[71]冯金鹏,吴洪寿,赵帆.水环境污染总量控制回顾、现状及发展探讨.南水北调与水利科技,2004,2(1):45-47.
[72]傅京燕.环境规划、要素禀赋与我国贸易模式的实证分析.中国人口、资源与环境,2008,18(6):51~55.
[73]葛文泉.论工业布局与环境污染及其对策.环境保护科学,1995,21(3):5-7
[74]顾春林.体制转型期的我国经济增长与环境污染水平关系研究━━环境库兹涅茨理论假说及其对我国的应用分析:[博士学位论文].上海:复旦大学,2003
[75]郭宏飞,倪晋仁,王裕东.基于宏观经济优化模型的区域污染负荷分配.应用基础与工程科学学报,2003,11(3):133-142.
[76]郭希利,李文岐.总量控制方法类型及分配原则.中国环境管理,1997,(5):47-48
[77]国家环境保护局，中国环境科学研究院.城市大气污染总量控制典型范例.北京：中国环境科学出版社,1993:5
[78]汉红燕.胶州湾陆源污染物排海总量控制行政区量化管理研究.[博士学位论文].青岛:中国海洋大学,2010
[79]贺玲,吴玲达,蔡益朝.数据挖掘中的聚类算法综述.计算机应用研究.2007,1:10-13
[80]何优选.总量控制下排污指标分配的原则.嘉应大学学报,2001,19(3):28-32
[81]何广顺,王晓惠.海洋及相关产业分类研究.2006,24(3):365~370.
[82]环境科学大辞典编委会.环境科学大辞典.北京:中国环境科学出版社,1991
[83]李名升,佟连军,李治,仇方道.基于基尼系数的经济环境协调发展及其机制.人文地理,2009(6):73-78
[84]李明霞,.淮河安徽段环境容量计算方法研究.[硕士学位论文].合肥:合肥工业大学,2003
[85]李平,施重涛.佳木斯市水污染物总量控制研究.环境污染与防治,1992,14(5):7-9
[86]李克强.胶州湾主要化学污染物海洋环境容量研究——在多介质海洋环境中主要迁移-转化过程－三维水动力输运耦合模型建立与计算.[博士学位论文].青岛:中国海洋大学,2007
[87]李如忠.区域水污染物排放总量分配方法研究.环境工程,2002,20(6):61-63
[88]李勇，王金南.经济与环境协调发展综合指标与实证分析.环境科学研究,2006,19(2):63-65
[89]李志强，王忠辉.中国工业排污强度变化及其影响因素分析.统计与信息论坛,2008,23(5):44-48
[90]李周,包晓斌.中国环境库兹涅茨曲线的估计[J].科技导报,2002,4:57-58.
[91]林巍等.基于公理体系的排污总量公平分配模型[J].环境科学,1996,17(3):35-37
[92]刘小琴.辽宁环境质量与经济增长关系的实证研究:[硕士学位论文].大连:大连理工学,2009
[93]陆学军，展卫红.连云港市主要工业污染物排放强度的区域差异分析.北方环境,2010,22(3):74-77
[94]罗宏,王金南.中国东、西部工业污染和经济发展的分析比较.上海环境科学,2001,20(7):341-346
[95]马金书，李海江.促进云南生态文明建设的产业结构调整———基于各产业与经济增长、资源及环境的灰色关联分析.中共云南省委党校学报,2008,19(2):89-92
[96]毛战坡,李怀恩.总量控制中消减污染物合理分摊问题的求解方法.西北水资源与水工程,1999,10(1):25-30.
[97]孟伟.流域水污染物总量控制技术与示范.北京:中国环境科学出版社,2008
[98]孟伟,张远,郑丙辉.水环境质量基准、标准与流域水污染物总量控制策略.环境科学研究,2006,19(3):1-6
[99]裴相斌等.基于GIS的海湾陆源污染排海总量控制的空间优化分配方法研究——以大连湾为例[J].环境科学学报,2000,20(3):294-298
[100]钱枫林等.产业结构与环境污染的关系浅析.商场现代化,2008,529:345-346
[101]乔旭东.胶州湾排污管理区及其主要排海化学污染物分配容量的准确计算研究.[博士学位论文].青岛:中国海洋大学,2009
[102]青岛市海洋与渔业局.2010年青岛海洋环境质量公报.2011
[103]青岛市人民政府.青岛市国民经济和社会发展第十二个五年规划刚要.2011
[104]青岛市史志办.青岛年鉴.青岛:青岛年鉴社,2004
[105]青岛市统计局,国家统计局青岛调查队.青岛统计年鉴.北京:中国统计出版社,2008
[106]日本环境厅.WaterEnvironmentalManagementinJapan.http://www.env.go.jp/en/water/wq/pamph/index.html
[107]沈满洪,许云华.一种新型的环境库兹涅茨曲线[J].浙江社会科学,2000,4:53-57
[108]宋国君.论中国污染物排放总量控制和浓度控制.环境保护,2000,(6):11-13
[109]孙从军，张明旭，程曦，陈漫漫.上海市大气污染物排放现状评价、预测及对策研究[J].安全与环境工程,2005,12(4):33—37．
[110]孙亚梅.面向农业污水灌溉的水污染物总量控制研究:[硕士学位论文].保定:河北农业大学,2005
[111]田海宽.基于京津走廊经济发展的廊坊市产业结构调整和空间布局优化研究:[博士学位论文].武汉:武汉理工大学,2009
[112]汪俊启,张颖.总量控制中水污染物允许排放量公平分配研究.安庆师范学院学报(自然科学版),2000,3:37-40
[113]王恒，叶宏等.四川省环境洛伦兹曲线的分析及应用研究.四川环境,2007,26(3):117-122
[114]王建,张金生.日本水质污染总量控制及其方法.环境科学与技术,1981,4:55-64
[115]王金南,潘向忠.线性规划方法在环境容量资源分配中的应用.环境科学,2005,26(6):195-198
[116]王金南,逯元堂,周劲松,李勇,曹东,熊俊.基于GDP的中国资源环境基尼系数分析.中国环境科学,2006,26(1):111-115.
[117]王腊春,霍雨,朱继业等.区域经济发展与污水排放协调分析.环境科学,2008,29(3):125-141
[118]王亮.天津市重点水污染物容量总量控制研究:[博士学位论文].天津:天津大学,2005
[119]王亮,张宏伟,岳琳.水污染物总量行业优化分配模型研究.天津大学学报(社会科学版),2006,8(1):59-63
[120]王丽琼.中国能源利用效率区域差异基尼系数分析.生态环境学报,2009,18(3):974-978
[121]王寿兵,陶林森.中国大陆富营养化物质排放量及排放强度.复旦学报(自然科学版),2003,42(3):476-480
[122]王文森.基尼系数及其推广应用[OL].2008,http://www.gdstats.gov.cn/tjkw/tjyyc/2003/1/0009.htm
[123]王有乐.区域水污染控制多目标组合规划模型研究.环境科学学报,2002,22(1):107-110
[124]王西琴,周孝德.区域水环境经济系统优化模型及其应用.西安理工大学学报,1999,15(4):80-85
[125]王西琴,杨志峰,刘昌明.区域经济结构调整与水环境保护——以陕西关中地区为例.地理学报,2000,55(6):707-718
[126]王西琴.水环境保护与经济发展决策模型的研究.自然资源学报,2001,16(3):269-274
[127]王西琴.关中地区水环境与经济协调发展战略研究:[博士学位论文].西安:西安理工大学,1999
[128]王学东等.总量控制与线性规划[J].干旱环境监测,2001,15(1):39-40
[129]王云.区域环境承载力与工业布局研究.环境保护科学,1998,24(4):6-9
[130]王治民.基于有限水资源和环境容量的天津市工业产业结构调整方案研究:[硕士学位论文].河北:河北工业大学,2007
[131]吴开亚,陈晓剑.安徽省经济增长与环境污染水平的关系研究[J].重庆环境科学,2003,25(6):9-12
[132]吴宇哲,鲍海君.区域基尼系数及其在区域水土资源匹配分析中的应用[J].水土保持学报,2003,17(5):123-125
[133]夏军,张祥伟.河流水质灰色非线性规划的理论与应用.水利学报,1993,(12):1-9
[134]夏青,王华东,关伯仁等.总量控制技术手册.北京:中国环境科学出版社,1990
[135]夏训峰，顾雨，席北斗，徐广军.基于水环境约束的抚仙湖流域农业结构调整研究.环境科学研究,2010,23(10):1274-1278
[136]邢秀凤.经济发展与环境保护关系的计量与实证分析.中国海洋大学学报,2005(5):43-47
[137]邢秀凤.青岛市“三废”排放的环境库兹涅茨特征分析.城市环境与城市生态,2005,18(5):33-37
[138]徐鸿德,区域水污染物总量优化分配的系统分析.上海环境科学,1990,9(7):2-4
[139]徐鸿德.河流水污染物协调分配系统分析.中国环境科学,1991,11(4):275-278
[140]徐华君等.污染物允许排放总量分配的公平协调思路与方法[J].新疆大学学报(自然科学版)1996,13(3):86-89
[141]许洪余,王照之.墨水湖水污染物总量控制方案的优化研究.环境科学与技术,1993,3:10-12
[142]严如忠.污染物总量控制指标层次分配模式研究.环境导报,2002,2:12-14
[143]杨玉峰,傅国伟.区域差异与国家污染物排放总量分配.环境科学学报,2001,21(2):129-133
[144]杨志平,陆景宣.污染物排放总量控制优化分配数学模型探讨.上海环境科学,1989,8(10):9-13
[145]尹军,李晓君,宫正.水污染控制系统污染物削减量优化分配.环境科学丛刊,1989,10(3):49-53
[146]张存智等.大连湾污染排放总量控制研究——海湾纳污能力计算模型[J].海洋环境科学,1998,17(3):1-5
[147]张俊,余宗莲,王城见,孙保权.大沽河干流青岛段水环境容量研究.青岛海洋大学学报(自然科学版),2003,33(5):665-670:
[148]张平，王树华.产业结构理论与政策[M].武汉，武汉大学出版社，2009.
[149]张天柱.区域水污染物排放总量控制系统的理论模式.环境科学动态,1990,1:1-23
[150]张伟.四川省工业结构的水污染效应及对策分析.资源开发与市场,2006,22(6):561-563
[151]张晓.中国环境政策的总体评价[J].中国社会科学,1999,3:95-98
[152]张晓军,侯汉坡,吴雁军.基于水资源利用的北京市第三产业结构优化研究.北京交通大学学报(社会科学版),9(1):19-23
[153]张音波,麦志勤,陈新庚等.广东省城市资源环境基尼系数.生态学报,2008,28(2):728~734
[154]张志强.天津市水污染物容量总量控制方法研究:[硕士学位论文].天津:河北工业大学,2006
[155]赵娟.天津市资源环境基尼系数.经济与法,2009,11:254
[156]中国环境规划院.全国水环境容量核定技术指南.北京:中国环境规划院,2003
[157]中华人民共和国国家统计局.国民经济行业分类.2002
[158]中华人民共和国环境保护部.第一次全国污染源普查公报.2010
[159]中华人民共和国环境保护部.生态县、生态市、生态省建设指标.2008
[160]中华人民共和国环境保护部.中国环境统计年报.2007
[161]中华人民共和国环境保护部.《综合类生态工业园区标准HJ-2009》.2009
[162]钟晓青，张万明，李萌萌.基于生态容量的广东省资源环境基尼系数计算与分析———与张音波等商榷.生态学报,2008,28(9):4486-4493
[163]周静.江苏省工业污染排放特征及其成因分析.中国环境科学,2007,27(2):284-288
[164]朱连奇.日本水质保护的现状及趋势.中国人口资源与环境,1999,4:107-109.
[2] Aleg Cherp, Irina Kopteva, Ruben Mnatsakanian. Economic transition and environmentalsustainability: effects of economic restructuring on air pollution in the Russian Federation.Journal of Environmental Management,2003,68,141-151
[3] Bingham,T.H., Anderson,D.W. and Cooley, P.C., Distribution of the generation of airpollution. J. Environ. Econ. Manage.,1987,15(1):30-40
[4] Burn, D.H. and Lence, B. Comparison of optimization formulations for waste load allocation.Environmental Engineering,1992,11(84):597-612
[5] Cardwell H, Ells H. Stochastic dynamic programming models for water quality management.Water Resources Research,1993,29(4):803-813
[6] Carter, Brandon, Ramesh Ramankutty. Toward an Environmental Strategy for Asia: asummary of a World Bank discussion paper. Washington, D.C.: The World Bank,1993.
[7] Chih sheng Lee, Ching gung Wen. Application of muti-objective programming to waterquality management in a river basin. Journal of Environment Management,1996,47:11-26
[8] David E. Kolo. Yacov Y. Haimes. Capacity expansion and operational planning for regionalwater-resource systems.Journal of Hydrology.1977,32(3-4):363-381
[9] David E.Pingry, Andrew B.Whinston. Application of Mutigoal Water Quality Planning Model.Iournal of the Environmental Engineering Division,1974
[10] Deininger, R. A. Water Quality Management: The Planning of Economically OptimalPollution Control Systems. Ph.D. Thesis, Northwestern University,1965
[11] Donald H. B, Barbara J L. Comparison of optimization formulations for waste-loadallocations. Journal of environmental engineering,1992,118(4):597-612
[12] Donald H. B., Edward A. M. Optimization modeling of water quality in an uncertainenvironment, Water Resources Research,1985,21(7):934-940
[13] Duarte E. A., Neto I., Alegrias M., R. Barroso."Appropriate technology" for pollution controlin corrugated board industry-the Portuguese case. Water Science and Technology,1998,38(6):45-53
[14] Ecker, J.G. and Mcnamara, J. R. Geometric Programming and the Preliminary Design ofIndustrial Waste Treatment Plants. Water Resources Research,1971,8
[15] Echer G H. A Geometric Programming Model for Optimal Allocation of Stream DissolvedOxygen. Management Science,1975,21(6):581-591
[16] Ellis J H. Stochastic water quality optimization using imbedded chance constraints. WaterResource Res,1987,23(12):2227
[17] Ethan T.Smith and Alvin R.Morris. Systems Analysis for Optimal Water Quality Management.Journal of Water Quality Management,1969,41(9)
[18] Fan J, Hu H H. Studies and Applications of Environmental Kuznets Curve (EKC).Mathematics in Practice and Theory,2002,32(6):944-951
[19] Graves, G.W., Hatfield, G.B., and Whinston,A. Mathematical Programming for RegionalWater Quality Management. Water Resources Research,1972,8(2)
[20] Grossman, Gene M. and Alan Krueger. Economic Growth and the Environment. QuarterlyJournal of Economics,1995,110(2):353-373
[21] Haith D.1982. Environmental system optimization. New York: John Wiley&Sons
[22] Hakanson, L. The role of characteristic coefficients of variation in uncertainty and sensitivityanalyses, with examples related to the structuring of lake eutrophication models. EcologicalModeling,2000,131:1-20
[23] Hettige H, Martin P, Singh M, Wheeler D. The Industrial Pollution Projection System (IPPS).Policy research working paper no1431part1and2;1995.
[24] Hongyan Han, Keqiang Li, Xiulin Wang, Xiaoyong Shi, Xudong Qiao, Jing Liu.Environmental capacity of nitrogen and phosphorus pollutions in Jiaozhou Bay, China:Modeling and assessing. Marine Pollution Bulletin,63(2011):262-266
[25] James R.Marsden,David E. Pingry, Andrew Whinston.Application of NonlinearProgramming to Water Quality Control.Water, Air, and Soil Pollution,1973,2:155-169
[26] John A List, Craig A. Gallet. the Environmental Kuznets Curve: does one size fit all?Ecological Economics,1999,31:409-423
[27] Kerri, K. D..An Economic Approach to Water Quality Control. Paper presented at38thAnnual Conference of the Water Pollution Control Federation, Atlantic City, N.J.,1965.
[28] L. Somlyody and G. van Straten. Modeling and managing shallow lake eutrophication: WithApplication to Lake Balaton.1986environmental software,1(2):131
[29] L. Somlyody, G. van Straten. Modeling and managing shallow lake eutrophication: WithApplication to Lake Balaton.Environmental Software,1986,1(2):131
[30] L.Somlyody.Use of Optimization Models in River Basin Water Quality Planning.Wat.Sci.Tech,1997,36(5):209-218
[31] Leonard Ortolano. Environmental Planning and Decision Making. New York,1984
[32] Leontief,W.. Environmental repercussions and the economic structure: an input-outputapproach. Rev. Econ.Statistics,1970,52(3):262-271.
[33] Leontief, W. and Ford, D.. Air pollution and economic structure: empirical results ofinput-output computations.1972. Input-Output Techniques, Proc.5thInt. Conf. Input-OutputTechniques, Geneva,1971. Elsevier, NY, pp.9-30
[34] Li Shiyu, Tohru Morioka. Optimal allocation of waste loads in a river with probabilistictributary flow under transverse mixing. Water Environmental Research,1999,71(2):156-162.
[35] Liebman J. C., Lynn W. R. The Optimal Allocation of Stream Dissolved Oxygen, WaterResource Research,1966,2(3):581-591
[36] Loucks D. P., Revelle C. S., Lynn W. R. Management Models for Water Quality Control,Management Science, l967,14(4):166-181
[37] Mcnamara, J. R. The Optimal Design of Water Quality Management Systems. Ph.D.Thesis,Rensselaer Polytechnic Institute, Troy, New York,1971
[38] Millie DE, Schofield OM, Kirkpatrick GJ, el a1. Detection of harmful algal blooms usingphotopigments and absorption signatures: A case study of the Florida red tide，Gymnodiniumbreve. Limnology and Oceanography,1997,42:1240-1251
[39] Proops, J.L.R. Modelling the energy-output ratio. Energy Econ.,1984,6(1):47-51
[40] Revelle C. S., Loucks D. P., Lynn W. R., Linear Programming Applied to Water QualityManagement, Water Resource Research,1968,4(1): l-9
[41] Richard Calkins, et al.. Indonesia: Environment and development: Challenges for the Future.Washington, D.C.: The Word Bank,1994
[42] SasikumarK, MujumdarPP. Fuzzy optimization model for water quality management of ariver system.Journal of Water Resources Planning and Management-ASCE,1998,124(2)：79-88.
[43] Selden. T.M. and D.Song. Environment Quality and Development:Is There a kuznets Curvefor Air Pollution Emission?Journal of Environmental Economic and Management,1994,27:147-162
[44] Shih, C. S.,Kbishnan, P. Dynamic Optimization of Industrial Waste Treatment Plant Design.Jour. Water Pollution Control Federation,1969,41
[45] Sobel, M. J.. Water Quality Improvement Programming Problems. Water ResourcesResearch,1965,1(4)
[46] Thomann R V, Sobel M S. Estuarine Water Quality Management and Forecasting. Journal ofSanitary Engineering Division, ASCE,1964,89(5):9-36.
[47] USEPA. Eaxamples of Approved TMDLs. http://www.epa.gov/owow/tmdl/examples/
[48] USEPA. Protocol for developing nutrient TMDLs.Office of Water4503F Washington D C20460, EPA841-B-99-007,1999
[49] USEPA. Section303(d) of the Clean Water Act.http://www.epa.gov/owow/tmdl/intro.html#section303
[50] USEPA, US Environmental Protection Agency. New York/New Jersey Harbor EstuaryProgram, final comprehensive conservation and management plan, Region2, USEnvironmental Protection Agency, New York, NY.1996
[51] Wen，C-G and Lee，C-S. Fuzzy Programming Approach to Water Quality ManagementProceedings of the National Science Council，Republic of China.PartA：Physical Science andEngineering[Proc.Natl.Sci.Counc.Rep.China Pt.A：Phys.Sci.Eng.],1998,2（25）:579-590
[52] Wolff, E.N.. Industrial composition, interindustry effects and the US productivity slowdown.Rev. Econ. Stat.,1985,67(2):268-277
[53] Zhao Xixi, Wang Xiulin, Shi Xiaoyong, Li Keqiang, Ding Dongsheng. Environmentalcapacity of chemical oxygen demand in the Bohai Sea: modeling and calculation.中国海洋湖沼学报(英文版),2011(1):46-52
[54]包存宽,张敏,尚金城.流域水污染物排放总量控制研究——以吉林省松花江流域为例.地理科学,2000,20(1):61-64
[55]蔡喜明,翁文斌,史惠斌.基于宏观经济的区域水资源多目标集成系统.水科学进展,1995,6(2):2-7
[56]蔡载昌.环境污染总量控制.北京：中国环境科学出版社.1991
[57]曹利军.区域经济发展与水环境容量紧缺之间矛盾的调和一工业生产力宏观布局与产业结构调整策略.经济地理,1998,18(4):54-61
[58]曹利军.从水环境容量看我国的工业布局和产业结构调整.科技导报,1998,6:56-58
[59]曹瑞钰,顾国维.水环境治理工程费用优化模型.同济大学学报,1997,25(5):548-552.
[60]陈传明.闽江流域工业结构与布局对环境的影响.福建地理,2000,15(1):14-17
[61]陈东景.我国主要污染物排放强度的区域差异分析.生态环境，2008,17(1):133~137.
[62]陈广洲.基于水环境保护的产业结构AHP评价系统探讨.安徽建筑工业学院学报(自然科学版),2004,12(1):45-48
[63]陈仕权.生产性服务业的分类、特点及作用.郑州航空工业管理学院学报(社会科学版),2006,25(4):191-193
[64]陈治谏.模糊最优化方法在河流水质规划中的应用.中国环境科学,1989,9(1):64-68
[65]崔正国.环渤海13城市主要化学污染物排海总量控制方案研究:[博士学位论文].青岛:中国海洋大学,2008
[66]崔志清,董增川.基于水资源约束的产业结构调整模型研究.南水北调与水利科技,2008,6(2):60-63
[67]方秦华,张珞平.水污染负荷优化分配研究.环境保护,2005,12:29-31
[68]方秦华,张珞平.水污染负荷总量控制研究进展.环境污染与防治,2003,4:1-8
[69]方秦华,张珞平,王佩儿等.象山港海域环境容量的二步分配法.厦门大学学报(自然科学版)2004,43(增):217-220.
[70]方远平，毕斗斗.国内外服务业分类探索.国际经贸探索,2008,24(1):72~76.
[71]冯金鹏,吴洪寿,赵帆.水环境污染总量控制回顾、现状及发展探讨.南水北调与水利科技,2004,2(1):45-47.
[72]傅京燕.环境规划、要素禀赋与我国贸易模式的实证分析.中国人口、资源与环境,2008,18(6):51~55.
[73]葛文泉.论工业布局与环境污染及其对策.环境保护科学,1995,21(3):5-7
[74]顾春林.体制转型期的我国经济增长与环境污染水平关系研究━━环境库兹涅茨理论假说及其对我国的应用分析:[博士学位论文].上海:复旦大学,2003
[75]郭宏飞,倪晋仁,王裕东.基于宏观经济优化模型的区域污染负荷分配.应用基础与工程科学学报,2003,11(3):133-142.
[76]郭希利,李文岐.总量控制方法类型及分配原则.中国环境管理,1997,(5):47-48
[77]国家环境保护局，中国环境科学研究院.城市大气污染总量控制典型范例.北京：中国环境科学出版社,1993:5
[78]汉红燕.胶州湾陆源污染物排海总量控制行政区量化管理研究.[博士学位论文].青岛:中国海洋大学,2010
[79]贺玲,吴玲达,蔡益朝.数据挖掘中的聚类算法综述.计算机应用研究.2007,1:10-13
[80]何优选.总量控制下排污指标分配的原则.嘉应大学学报,2001,19(3):28-32
[81]何广顺,王晓惠.海洋及相关产业分类研究.2006,24(3):365~370.
[82]环境科学大辞典编委会.环境科学大辞典.北京:中国环境科学出版社,1991
[83]李名升,佟连军,李治,仇方道.基于基尼系数的经济环境协调发展及其机制.人文地理,2009(6):73-78
[84]李明霞,.淮河安徽段环境容量计算方法研究.[硕士学位论文].合肥:合肥工业大学,2003
[85]李平,施重涛.佳木斯市水污染物总量控制研究.环境污染与防治,1992,14(5):7-9
[86]李克强.胶州湾主要化学污染物海洋环境容量研究——在多介质海洋环境中主要迁移-转化过程－三维水动力输运耦合模型建立与计算.[博士学位论文].青岛:中国海洋大学,2007
[87]李如忠.区域水污染物排放总量分配方法研究.环境工程,2002,20(6):61-63
[88]李勇，王金南.经济与环境协调发展综合指标与实证分析.环境科学研究,2006,19(2):63-65
[89]李志强，王忠辉.中国工业排污强度变化及其影响因素分析.统计与信息论坛,2008,23(5):44-48
[90]李周,包晓斌.中国环境库兹涅茨曲线的估计[J].科技导报,2002,4:57-58.
[91]林巍等.基于公理体系的排污总量公平分配模型[J].环境科学,1996,17(3):35-37
[92]刘小琴.辽宁环境质量与经济增长关系的实证研究:[硕士学位论文].大连:大连理工学,2009
[93]陆学军，展卫红.连云港市主要工业污染物排放强度的区域差异分析.北方环境,2010,22(3):74-77
[94]罗宏,王金南.中国东、西部工业污染和经济发展的分析比较.上海环境科学,2001,20(7):341-346
[95]马金书，李海江.促进云南生态文明建设的产业结构调整———基于各产业与经济增长、资源及环境的灰色关联分析.中共云南省委党校学报,2008,19(2):89-92
[96]毛战坡,李怀恩.总量控制中消减污染物合理分摊问题的求解方法.西北水资源与水工程,1999,10(1):25-30.
[97]孟伟.流域水污染物总量控制技术与示范.北京:中国环境科学出版社,2008
[98]孟伟,张远,郑丙辉.水环境质量基准、标准与流域水污染物总量控制策略.环境科学研究,2006,19(3):1-6
[99]裴相斌等.基于GIS的海湾陆源污染排海总量控制的空间优化分配方法研究——以大连湾为例[J].环境科学学报,2000,20(3):294-298
[100]钱枫林等.产业结构与环境污染的关系浅析.商场现代化,2008,529:345-346
[101]乔旭东.胶州湾排污管理区及其主要排海化学污染物分配容量的准确计算研究.[博士学位论文].青岛:中国海洋大学,2009
[102]青岛市海洋与渔业局.2010年青岛海洋环境质量公报.2011
[103]青岛市人民政府.青岛市国民经济和社会发展第十二个五年规划刚要.2011
[104]青岛市史志办.青岛年鉴.青岛:青岛年鉴社,2004
[105]青岛市统计局,国家统计局青岛调查队.青岛统计年鉴.北京:中国统计出版社,2008
[106]日本环境厅.WaterEnvironmentalManagementinJapan.http://www.env.go.jp/en/water/wq/pamph/index.html
[107]沈满洪,许云华.一种新型的环境库兹涅茨曲线[J].浙江社会科学,2000,4:53-57
[108]宋国君.论中国污染物排放总量控制和浓度控制.环境保护,2000,(6):11-13
[109]孙从军，张明旭，程曦，陈漫漫.上海市大气污染物排放现状评价、预测及对策研究[J].安全与环境工程,2005,12(4):33—37．
[110]孙亚梅.面向农业污水灌溉的水污染物总量控制研究:[硕士学位论文].保定:河北农业大学,2005
[111]田海宽.基于京津走廊经济发展的廊坊市产业结构调整和空间布局优化研究:[博士学位论文].武汉:武汉理工大学,2009
[112]汪俊启,张颖.总量控制中水污染物允许排放量公平分配研究.安庆师范学院学报(自然科学版),2000,3:37-40
[113]王恒，叶宏等.四川省环境洛伦兹曲线的分析及应用研究.四川环境,2007,26(3):117-122
[114]王建,张金生.日本水质污染总量控制及其方法.环境科学与技术,1981,4:55-64
[115]王金南,潘向忠.线性规划方法在环境容量资源分配中的应用.环境科学,2005,26(6):195-198
[116]王金南,逯元堂,周劲松,李勇,曹东,熊俊.基于GDP的中国资源环境基尼系数分析.中国环境科学,2006,26(1):111-115.
[117]王腊春,霍雨,朱继业等.区域经济发展与污水排放协调分析.环境科学,2008,29(3):125-141
[118]王亮.天津市重点水污染物容量总量控制研究:[博士学位论文].天津:天津大学,2005
[119]王亮,张宏伟,岳琳.水污染物总量行业优化分配模型研究.天津大学学报(社会科学版),2006,8(1):59-63
[120]王丽琼.中国能源利用效率区域差异基尼系数分析.生态环境学报,2009,18(3):974-978
[121]王寿兵,陶林森.中国大陆富营养化物质排放量及排放强度.复旦学报(自然科学版),2003,42(3):476-480
[122]王文森.基尼系数及其推广应用[OL].2008,http://www.gdstats.gov.cn/tjkw/tjyyc/2003/1/0009.htm
[123]王有乐.区域水污染控制多目标组合规划模型研究.环境科学学报,2002,22(1):107-110
[124]王西琴,周孝德.区域水环境经济系统优化模型及其应用.西安理工大学学报,1999,15(4):80-85
[125]王西琴,杨志峰,刘昌明.区域经济结构调整与水环境保护——以陕西关中地区为例.地理学报,2000,55(6):707-718
[126]王西琴.水环境保护与经济发展决策模型的研究.自然资源学报,2001,16(3):269-274
[127]王西琴.关中地区水环境与经济协调发展战略研究:[博士学位论文].西安:西安理工大学,1999
[128]王学东等.总量控制与线性规划[J].干旱环境监测,2001,15(1):39-40
[129]王云.区域环境承载力与工业布局研究.环境保护科学,1998,24(4):6-9
[130]王治民.基于有限水资源和环境容量的天津市工业产业结构调整方案研究:[硕士学位论文].河北:河北工业大学,2007
[131]吴开亚,陈晓剑.安徽省经济增长与环境污染水平的关系研究[J].重庆环境科学,2003,25(6):9-12
[132]吴宇哲,鲍海君.区域基尼系数及其在区域水土资源匹配分析中的应用[J].水土保持学报,2003,17(5):123-125
[133]夏军,张祥伟.河流水质灰色非线性规划的理论与应用.水利学报,1993,(12):1-9
[134]夏青,王华东,关伯仁等.总量控制技术手册.北京:中国环境科学出版社,1990
[135]夏训峰，顾雨，席北斗，徐广军.基于水环境约束的抚仙湖流域农业结构调整研究.环境科学研究,2010,23(10):1274-1278
[136]邢秀凤.经济发展与环境保护关系的计量与实证分析.中国海洋大学学报,2005(5):43-47
[137]邢秀凤.青岛市“三废”排放的环境库兹涅茨特征分析.城市环境与城市生态,2005,18(5):33-37
[138]徐鸿德,区域水污染物总量优化分配的系统分析.上海环境科学,1990,9(7):2-4
[139]徐鸿德.河流水污染物协调分配系统分析.中国环境科学,1991,11(4):275-278
[140]徐华君等.污染物允许排放总量分配的公平协调思路与方法[J].新疆大学学报(自然科学版)1996,13(3):86-89
[141]许洪余,王照之.墨水湖水污染物总量控制方案的优化研究.环境科学与技术,1993,3:10-12
[142]严如忠.污染物总量控制指标层次分配模式研究.环境导报,2002,2:12-14
[143]杨玉峰,傅国伟.区域差异与国家污染物排放总量分配.环境科学学报,2001,21(2):129-133
[144]杨志平,陆景宣.污染物排放总量控制优化分配数学模型探讨.上海环境科学,1989,8(10):9-13
[145]尹军,李晓君,宫正.水污染控制系统污染物削减量优化分配.环境科学丛刊,1989,10(3):49-53
[146]张存智等.大连湾污染排放总量控制研究——海湾纳污能力计算模型[J].海洋环境科学,1998,17(3):1-5
[147]张俊,余宗莲,王城见,孙保权.大沽河干流青岛段水环境容量研究.青岛海洋大学学报(自然科学版),2003,33(5):665-670:
[148]张平，王树华.产业结构理论与政策[M].武汉，武汉大学出版社，2009.
[149]张天柱.区域水污染物排放总量控制系统的理论模式.环境科学动态,1990,1:1-23
[150]张伟.四川省工业结构的水污染效应及对策分析.资源开发与市场,2006,22(6):561-563
[151]张晓.中国环境政策的总体评价[J].中国社会科学,1999,3:95-98
[152]张晓军,侯汉坡,吴雁军.基于水资源利用的北京市第三产业结构优化研究.北京交通大学学报(社会科学版),9(1):19-23
[153]张音波,麦志勤,陈新庚等.广东省城市资源环境基尼系数.生态学报,2008,28(2):728~734
[154]张志强.天津市水污染物容量总量控制方法研究:[硕士学位论文].天津:河北工业大学,2006
[155]赵娟.天津市资源环境基尼系数.经济与法,2009,11:254
[156]中国环境规划院.全国水环境容量核定技术指南.北京:中国环境规划院,2003
[157]中华人民共和国国家统计局.国民经济行业分类.2002
[158]中华人民共和国环境保护部.第一次全国污染源普查公报.2010
[159]中华人民共和国环境保护部.生态县、生态市、生态省建设指标.2008
[160]中华人民共和国环境保护部.中国环境统计年报.2007
[161]中华人民共和国环境保护部.《综合类生态工业园区标准HJ-2009》.2009
[162]钟晓青，张万明，李萌萌.基于生态容量的广东省资源环境基尼系数计算与分析———与张音波等商榷.生态学报,2008,28(9):4486-4493
[163]周静.江苏省工业污染排放特征及其成因分析.中国环境科学,2007,27(2):284-288
[164]朱连奇.日本水质保护的现状及趋势.中国人口资源与环境,1999,4:107-109.
© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号 地址：北京市海淀区学院路29号 邮编：100083 电话：办公室：(+86 10)66554848；文献借阅、咨询服务、科技查新：66554700 |