Urban atmospheric environmental capacity and atmospheric environmental carrying capacity constrained by GDP–PM2.5 |
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| Institution: | 1. Laboratório de Ensaios Farmacológicos e Toxicológicos, Instituto de Ciências Biológicas, Universidade Federal do Rio Grande – FURG, Av. Itália, km 8, Campus Carreiros, CEP 96203-900 Rio Grande, RS, Brazil;2. Centro de Estudos do Ambiente e Mar, Departamento de Biologia Animal – Faculdade de Ciências da Universidade de Lisboa, Campo Grande, 1749-016 Lisboa, Portugal;1. Centre of Excellence for Environmental Decisions, School of Biosciences, The University of Melbourne, Parkville, Victoria, Australia;2. CSIRO, Dutton Park, Queensland, Australia;3. OSUR, UMR CNRS 6553 ECOBIO, University Rennes1, Ave. Gal. Leclerc, 35042 Rennes Cedex, France;1. Faculty of Science and Technology, Campus of Gambelas, University of Algarve, 8005-139 Faro, Portugal;2. Centre of Marine Sciences, Campus of Gambelas, University of Algarve, 8005-139 Faro, Portugal;3. Department of Ecology and Vertebrate Zoology, Faculty of Biology and Environmental Protection, University of Łódź, 90-237 Łódź, 12/16 Banacha Str., Poland;4. Department of Applied Ecology, Faculty of Biology and Environmental Protection, University of Łódź, 90-237 Łódź, 12/16 Banacha Str., Poland;5. Department of Biological and Environmental Sciences, College of Arts and Sciences, Qatar University, Doha, Qatar |
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| Abstract: | China faces a contradictory period of economic development and environmental protection, with it being essential to control total emissions within the limit of atmospheric environmental capacity (AEC) by promoting atmospheric environmental carrying capacity (AECC). This implies that well-calculated AEC and AECC values are the key macro-criteria for improving environmental quality and supporting the challenging coordinated development of economy and environment. When considering compound air pollution characterised as fine particulate matter (PM2.5), conventional methods are not capable of calculating AEC and AECC, but the system dynamics (SD) method retains the advantage of simplicity in resolving complex problems. In the present study, we first describe the background and definitions of AEC and AECC, which are different from Western concepts, and their dialectical relationships. Then, with the statistical data from Wuhan city in 2014, we establish an ‘economy–energy–atmospheric environment’ dynamic model using the SD method, which does not need to simulate the complicated physicochemical processes of atmospheric transmission and diffusion. Instead, it uses the pollutants’ proportionality factors and conversion rates to establish quantitative connections among different types of variables. Finally, we simulate the dynamic trends of gross domestic production (GDP), PM2.5, and six air pollutant emissions between 2015 and 2030 in four different scenarios and calculate the results of AEC and AECC constrained by GDP and PM2.5. |
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| Keywords: | GDP Atmospheric environmental capacity Atmospheric environmental carrying capacity System dynamics Wuhan city |
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