• 关键词：大气环境容量  大气环境压力  大气环境承载力  阈值  系统动力学  东莞市

• 基金项目：国家自然科学基金(No.71171089);东莞市PM_2.5污染特征与防治对策研究项目(No.东采单[2013]222号)

• 周业晶
• 华中科技大学环境科学与工程学院, 武汉 430074

• 周敬宣
• 华中科技大学环境科学与工程学院, 武汉 430074

• 肖人彬
• 华中科技大学系统工程研究所, 武汉 430074

• 张国斐
• 华中科技大学环境科学与工程学院, 武汉 430074

• 摘要：东莞市计划到2017年PM_2.5年均浓度达到国家二级标准(35μg·m^-3),GDP年均增长率至少不低于7%.面对复合型为特征的PM_2.5大气污染,传统的环境容量和承载力计算方法具有局限性.因此,本文基于经济、气象、能源、环境等关键信息,利用系统动力学(SD)建立了GDP-PM_2.5宏观动态统计模型.考虑到PM_2.5年均浓度等统计值本身就是污染物不断生成又不断扩散、沉降达到动态平衡的综合结果.因此,SD模型可不从理化角度去模拟复杂的大气传输和扩散过程,而是通过引入各污染物的比例系数μ,构建转化率η,建立GDP、PM_2.5年均浓度、五大污染物(VOCs、SO₂、NO_x、NH₃、一次PM_2.5)排放量等变量之间的逻辑联系,为分析和预测工作奠定基础.同时,本文梳理了大气环境压力、承载力和容量的定义,强调了三者之间的相互作用、密不可分的动态关系,建设性地提出了度量承载力的11项指标(5个显性、6个隐性).最后,利用模型模拟预测了"综合治理"模式下2012-2020年间以GDP-PM_2.5达标为约束的五大污染物的大气环境压力、容量和承载力.结果表明,预计PM_2.5浓度达标约在2017年上半年,对应的SO₂、NO_x、VOCs、NH₃、一次PM_2.5容量分别为84987、138849、100875、7751、17402 t;承载力隐性部分各项阈值分别为GDP总量7074亿元、新增绿色GDP 737亿元、煤炭2120万t(以标煤计)、石油552万t(以标煤计)、天然气663万t(以标煤计)、新能源630万t(以标煤计);承载力显性部分各阈值(相对于2012年5年累积减排量)分别为SO₂ 64271 t、NO_x128831 t、VOCs 108337 t、NH₃ 4070 t、一次PM_2.5 35863 t.本研究为东莞市大气减排提供了具体目标和参考数值.

• Abstract：The Government of Dongguan city plans to achieve national air quality standard Ⅱ of PM_2.5 of 35 μg·m^-3 in 2017 while maintaining the GDP growth rate no less than 7%. In dealing with air pollution complex characterized by PM_2.5 pollution, conventional methods are not capable of calculating atmospheric environment capacity (AEC) and atmospheric environment carrying capacity (AECC). Based on information about economy, meteorology, energy, PM_2.5 sources, etc., we have built up a macro-dynamic statistical model for the GDP-PM_2.5 relationship by System Dynamic (SD). The annual average statistical value of PM_2.5 concentration is a comprehensive output and a dynamic balance of air pollutants re-producing and diffusing. This SD model does not need to simulate the complicated physicochemical process of atmospheric transmission and diffusion. It uses the pollutants' proportionality factors and conversion rates to build connection between different variables, such as GDP, PM_2.5 and five air pollutants emissions (SO₂, NO_x, VOCs, NH₃ and Primary PM_2.5), etc, in a logical manner. This provides the foundation for future analyses and predictions. SD method has the advantages of simplicity in dealing with complex problems. We then described the definitions of AEC, AES and AECC and underlined their quantitative dynamic relationships. We proposed 11 indicators that are constrained by GDP-PM_2.5 targets, including 5 expressive and 6 recessive indicators. We used this SD model to simulate and predict the dynamic trend and quantitative results of AEC, AES and AECC in Comprehensive Management Pattern between 2012 and 2020 when the PM_2.5 concentration reaches the standard. The research outcomes indicate that the capacity of SO₂, NO_x, VOCs, NH₃ and primary PM_2.5 is 84987 t, 138849 t, 100875 t, 7751 t, and 17402 t, respectively; the recessive indicators of AECC including GDP, new green GDP and consumption of coal, oil, gas and new energy are 707.4 billion Yuan, 73.7 billion Yuan, 21.2 million t, 5.52 million t, 6.63 million t and 6.3 million t; respectively; the expressive ones including 5 pollutants' accumulated volume of emission reduction compared to in 2012 are 64271 t, 128831 t, 108337 t, 4070 t and 35863 t, respectively. The thresholds of all indicators representing AEC and AECC can then be set as emission reduction targets to optimize Dongguan city's air quality.

• Key words：atmospheric environment capacity  atmospheric environment stress  atmospheric environment carrying capacity  thresholds  system dynamic  Dongguan City

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