•The weighted Gini coefficient approach based on the equality principle was developed for the allocation of discharge permits.•A new indicator Inequality Factor was proposed to quantify the residual inequality in the allocation results.•A case study was used to demonstrate that this approach can achieve more equality in the allocation issue.•The uncertainty analysis on the weights and the constraints was conducted.Although there are many methods based on efficiency and equality in allocating discharge permits, developing both reasonable and feasible discharge permit allocation methods remains a challenge. This study proposes an allocation method that aims to achieve equitable allocations with respect to population, land area, environmental receiving capacity, and Gross Domestic Product, which are incorporated into a multi-index Gini coefficient. Previous methodological advances are enhanced by assigning weights to each index using the Analytic Hierarchy Process; and by introducing a new Inequality Factor to quantify the residual inequality. These methods are applied to a case study of chemical oxygen demand discharge permit allocation among 13 cities in Jiangsu Province, China. The allocations obtained by optimizing this method reduce the current level of inequality and are considered more feasible for achieving pollution reduction targets than the equal ratio or average amount benchmark methods. In the case study, the Inequality Factor was used to identify the cities that are the greatest beneficiaries and losers under the allocation scheme. A potential option for improving equality is to relax the constraints imposed on the allocation reductions; however little sensitivity to this was found implying that the limits are not barriers to equality. A sensitivity analysis was conducted to exam the uncertainty in the weights, showing significance for individual cities, but low significance for province-level equality. It is concluded that the integrated use of the Weighted Gini coefficient and Inequality Factor can offer new insights into regional and the city-level equality of discharge permit allocations.

•Up to 80% of energy for water supply to a 20-story building is used in the building.•Buildings can reduce pumping energy by 45% by changing pumping systems.•We extrapolated energy use for two high-rise pumping systems to city level.•Replacing 25% of traditional pumping systems cuts annual emissions by 8600 tCO2e.•Around 9% of China’s urban population uses 32% of energy for urban water supply.Pumping water in high-rise buildings has been overlooked in energy calculations for urban water supply, despite being a major contributor. Using data for two commonly used pumping systems and extrapolating results to a megacity in China, we show that over one third of energy for water supply is associated with around one tenth of a city’s population. Buildings can achieve a 45% reduction in pumping energy by replacing traditional break tank systems with pressurized booster systems. The latter capitalize on pressure supplied by the water distribution network, whereas the former lose energy by storing water at atmospheric pressure. Electricity saved by replacing 25% of break tank systems with pressurized booster systems is 11% of high-rise pumping energy in the case city and reduces annual emissions by 8600 tCO2e. Controlled replacement represents a realistic way of reducing emissions associated with water supply as China’s urban population grows and living density increases.Download high-res image (88KB)Download full-size image

Regional industrial growth is facing the problems of no control and disorder in rapidly transitioning China, especially in mega-regional areas. These problems have significantly intensified the use of regional resources and the level of environmental stress. The integration of industrial development and the environmental pollution pressure simulation at the mega-regional level must be supported at the planning stage. In this study, a Computational System for Regional Industrial Distribution Simulation and Environmental Impact Assessment (RESEA) that combines a multi-nominal logit model and uncertainty analysis was developed. This system aimed to explore efficient industrial spatial distribution simulations and potential environmental pressures at the mega-regional level. This study also developed an uncertainty analysis framework to identify and apply a bottom-up system with aggregate and sparse data following the basic processes of an HSY algorithm and Global-Formed Regional Sensitivity Analysis, which is capable of considering both input uncertainty and parameter uncertainty. By applying the RESEA system, a process of model estimation and sensitivity analysis was implemented based on historic data from 2002 to 2008 for the Bohai Sea rim region in China. The future industry distribution for the year 2015 was later aggregated based on the chosen sizes and locations of newly added industrial plants. Finally, the pollution loads of surface water into every sub-region were calculated, and the potential environmental impacts of different strategies were discussed.

Urban wastewater infrastructures have been threatened by natural and socioeconomic disturbances. This study investigates infrastructure resilience against the risks of long-term changes rather than natural disasters. Urban expansion that leads to an increased urban runoff and massive population movements that cause fluctuations in domestic emissions are considered in this study. Pollution permits for water bodies are adopted as constraints on wastewater infrastructures. A land usebased accounting method, combined with a grid-based database, is developed to map domestic discharge and urban runoff to service areas of wastewater treatment plants. The results of a case study on downtown Sanya, the most famous seashore tourist attraction in China, show that the average resilient values of three sub-catchment areas in 2010 were −0.57, 0.10 and 0.27, respectively, a significant spatial variation. The infrastructure in the Sanya River subregion is the least flexible, and is more likely to fail due to unstable inflows. The resiliencies will increase to 0.59, 1.01 and 0.54, respectively, in 2020, a considerable improvement in robustness. The study suggests that infrastructure resilience needs to be taken into further consideration for urban planning and the related realm of urban governance to foster more robust wastewater management under various risks.

In a rapidly transitioning China, urban land use has changed dramatically, both spatially and in terms of magnitude; these changes have significantly affected the natural environment. This paper reports the development of an Integrated Environmental Assessment of Urban Land Use Change (IEA-ULUC) model, which combines cellular automata, scenario analysis, and stochastic spatial sampling with the goal of exploring urban land-use change, related environmental impacts, and various uncertainties. By applying the IEA-ULUC model to a new urban development area in Dalian in northeastern China, the evolution of spatial patterns from 1986 to 2005 was examined to identify key driving forces affecting the changing trajectories of local land use. Using these results, future urban land use in the period 2005–2020 was projected for four scenarios of economic development and land-use planning regulation. A stochastic sampling process was implemented to generate industrial land distributions for each land expansion scenario. Finally, domestic and industrial water pollution loads to the ocean were estimated, and the environmental impacts of each scenario are discussed. The results showed that the four urban expansion scenarios could lead to considerable differences in environmental responses. In principle, urban expansion scenarios along the intercity transportation rail/roadways could have higher negative environmental impacts than cluster-developing scenarios, while faster economic growth could more intensely aggravate the environment than in the moderate growth scenarios.

Forecasts of industrial emissions provide a basis for impact assessment and development planning. To date, most studies have assumed that industrial emissions are simply coupled to production value at a given stage of technical progress. It has been argued that the monetary method tends to overestimate pollution loads because it is highly influenced by market prices and fails to address spatial development schemes. This article develops a land use-based environmental performance index (L-EPI) that treats the industrial land areas as a dependent variable for pollution emissions. The basic assumption of the method is that at a planning level, industrial land use change can represent the change in industrial structure and production yield. This physical metric provides a connection between the state-of-the-art and potential impacts of future development and thus avoids the intrinsic pitfalls of the industrial Gross Domestic Product-based approach. Both methods were applied to examine future industrial emissions at the planning area of Dalian Municipality, North-west China, under a development scheme provided by the urban master plan. The results suggested that the LEPI method is highly reliable and applicable for the estimation and explanation of the spatial variation associated with industrial emissions.

Forecasting and preventing urban noise pollution are major challenges in urban environmental management. Most existing efforts, including experiment-based models, statistical models, and noise mapping, however, have limited capacity to explain the association between urban growth and corresponding noise change. Therefore, these conventional methods can hardly forecast urban noise at a given outlook of development layout. This paper, for the first time, introduces a land use regression method, which has been applied for simulating urban air quality for a decade, to construct an urban noise model (LUNOS) in Dalian Municipality, Northwest China. The LUNOS model describes noise as a dependent variable of surrounding various land areas via a regressive function. The results suggest that a linear model performs better in fitting monitoring data, and there is no significant difference of the LUNOS’s outputs when applied to different spatial scales. As the LUNOS facilitates a better understanding of the association between land use and urban environmental noise in comparison to conventional methods, it can be regarded as a promising tool for noise prediction for planning purposes and aid smart decision-making.

Environmental carrying capacity is an essential metric for measuring regional sustainability. Although the term “carrying capacity” has been applied for over a century, the concept definition, quantitative methods and comprehensive evaluation remain arguable. This study analyzed the carrying capacity of four environmental elements, including water resources, air, surface water and offshore sea, and integrated them into a comprehensive index to represent overall regional profiles of resources and environment. The method was then applied to thirteen municipalities in the Bohai Sea Rim area, one of the most rapidly developing regions in transition China. The results show that the comprehensive environmental carrying capacity of the municipalities in the south sub-region were largest in 2007, while that of the west municipalities were lowest. The regional economic development exceeded the overall environmental carrying capacity by 36% and the west sub-region area deserves overwhelming attention for future industrial allocation.

Urban planning has been widely applied as a regulatory measure to guide a city’s construction and management. It represents official expectations on future population and economic growth and land use over the urban area. No doubt, significant variations often occur between planning schemes and actual development; in particular in China, the world’s largest developing country experiencing rapid urbanization and industrialization. This in turn leads to difficulty in estimating the environmental consequences of the urban plan. Aiming to quantitatively analyze the uncertain environmental impacts of the urban plan’s implementation, this article developed an integrated methodology combining a scenario analysis approach and a stochastic simulation technique for strategic environmental assessment (SEA). Based on industrial development scenarios, Monte Carlo sampling is applied to generate all possibilities of the spatial distribution of newly emerged industries. All related environmental consequences can be further estimated given the industrial distributions as input to environmental quality models. By applying a HSY algorithm, environmentally unacceptable urban growth, regarding both economic development and land use spatial layout, can be systematically identified, providing valuable information to urban planners and decision makers. A case study in Dalian Municipality, Northeast China, is used to illustrate applicability of this methodology. The impacts of Urban Development Plan for Dalian Municipality (2003−2020) (UDP) on atmospheric environment are also discussed in this article.

Uncertainties hamper the implementation of strategic environmental assessment (SEA). In order to quantitatively characterize the uncertainties of environmental impacts, this paper develops an integrated methodology through uncertainty analysis on land use change, which combines the scenario analysis approach, stochastic simulation technique, and statistics. Dalian city in China was taken as a case study in the present work. The results predict that the Fuzhou River poses the highest environmental pollution risk with a probability of 89.63% for COD in 2020. Furthermore, the Biliu River, Fuzhou River, Zhuang River, and Dasha River have 100% probabilities for NH3-N. NH3-N is a more critical pollutant than COD for all rivers. For COD, industry is the critical pollution source for all rivers except the Zhuang River. For NH3-N, agriculture is the critical pollution source for the Biliu River, Yingna River, and Dasha River, sewage for the Fuzhou River and Zhuang River, and industry for the Dengsha River. This methodology can provide useful information, such as environmental risk, environmental pressure, and extremely environmental impact, especially under considerations of uncertainties. It can also help to ascertain the significance of each pollution source and its priority for control in urban planning.

Material/substance flow analysis (MFA/SFA) approaches have been broadly applied to bridge the knowledge gaps in material metabolism within modern economies—and the environmental consequences it cause. While the structural feature of material use can vary along a physical dimension, there is a need to analytically normalize the implications derived from various material flow models to facilitate policy making, with respect to the associated socio-economic profiles. This is particularly important in accounting for material throughput, given various data uncertainties. This study attempts to develop an illustrative framework combining the mass balance approach [Adriaanse A, Bringezu S, Hammond A, et al. Resource flows: the material basis of industrial economies. Washington, DC: World Resources Institute; 1997] and proposed material use indictors at a substance level. The methodology is then applied for the case of the phosphorus cycle in China, the largest developing country currently in transition. Our discussion is conducted on the basis of two updated static SFA models which have been developed recently [Liu Y, Mol APJ, Chen JN. Material flow and ecological restructuring in China: the case of phosphorus. J Ind Ecol 2004;8(3):103–20; Liu Y, Chen JN, Mol APJ. Evaluation of phosphorus flows in the Dianchi Watershed, southwest of China. Popul Environ 2004;25(6):637–56]. Taking mineral reserve, commodities trading and environmental accumulation into account, the aggregated physical features of phosphorus flows are identified at both the national and local levels, respectively, by treating the overall lifespan of substance use within these economies as a whole. Material use efficiencies of six subsystems – involving the phosphate industry, crop farming, intensive livestock husbandry, family-based animal rearing and urban and rural households – are analyzed. The results highlight that both the aggregate and sectoral features of phosphorus use varies significantly with the shift in geographic boundary from national to local economies. With respect to the substantial differentiations, the discussion on desired structural adjustment strategies and efficiency-enhancement options towards a systematical improvement of phosphorus use could facilitate future rational policy-making.

Environmental carrying capacity is an essential metric for measuring regional sustainability. Although the term “carrying capacity” has been applied for over a century, the concept definition, quantitative methods and comprehensive evaluation remain arguable. This study analyzed the carrying capacity of four environmental elements, including water resources, air, surface water and offshore sea, and integrated them into a comprehensive index to represent overall regional profiles of resources and environment. The method was then applied to thirteen municipalities in the Bohai Sea Rim area, one of the most rapidly developing regions in transition China. The results show that the comprehensive environmental carrying capacity of the municipalities in the south sub-region were largest in 2007, while that of the west municipalities were lowest. The regional economic development exceeded the overall environmental carrying capacity by 36% and the west sub-region area deserves overwhelming attention for future industrial allocation.