Vol. 8, No. 1 (2020): Regular Issue

Hierarchical study of the industrial systems (ISs) of urban agglomerations, as compound systems under the interaction of multiple cities, is of great significance to the planning and management of a specific region. In the Pearl River Delta, one of the most vigorous economic zones in China, the developments of its nine component cities are unbalanced. Taking this area as a research object can not only promote its coordinated and sustainable development but can also predict and guide the industrial development of other regions. This study divides the Pearl River Delta into three levels from inside to outside as follows: Shenzhen, the urban belt composed of Guangzhou, Shenzhen and Dongguan, and the urban agglomeration composed of nine cities. According to the material flow process from resources to products, a framework of the relations between each component of an IS and the external environment as well as an evaluation index system are established. On this basis, taking China as a basic standard, the industrial characteristics of the three levels are quantitatively analyzed and compared. The results show that the concentration in the product processing and manufacture phase (PM), especially in the the manufacturing sector of computers, communication and other electronic equipment (CEM), is more significant in the Pearl River Delta compared with China and that the dominance of CEM becomes increasingly obvious with the convergence to the core city. This area also has characteristics of higher profits, lower energy consumption and lower pollutant discharges, which are 2.17%, 74.55% and 74.52% better than those of China, respectively. Shenzhen, whose discharges of smoke and dust and waste solids are as low as 0.43 ton/billion CNY and 0.51 ton/billion CNY, respectively, plays a leading role in energy saving and discharge reduction in the urban agglomeration. Huizhou, Zhaoqing and Jiangmen are key cities to increase the energy efficiency of the IS in the Pearl River Delta, whereas Dongguan is the key city to enhance the positive driving effect of the central city belt to marginal cities.

With population pressure constantly growing in India the crop productivity is struggling hard to catch up. Erratic rainfall and steady rise in temperature create widely uncertain outcomes for the farming communities. Against this backdrop, the present study has used a climate dataset constructed at a finer spatial level from a southern Indian state namely Karnataka to analyze the yield response of rice and maize crops to climate change. Using a time period from 1992 to 2012, a panel dataset has been made at the district level. The fixed effect regression results show that rice and maize productivity has been impacted adversely due to a steady rise in temperature in the state. The extent of damage is found to be 7% to 10%. Further, the study has also probed the role of irrigation as a climate adaptation strategy and has found out that adverse yield impact is reduced in the presence of irrigation. These findings provide some specific directions for policy framing to curb yield damage arising from climate variability.

The concentration of airborne pollutants is rising in recent years. Due to serious health effects of NO2, SO2 etc. their constant monitoring is important for the policy makers, as it provides early pollution estimates before it crosses permissible limits set by the state. For air quality modelling, several statistical techniques based on Artificial Neural Networks have been applied, however, Tree and meta-learning based classifiers have rarely been adopted for air pollution prediction purpose. Thus, for this study, Tree (Random Forest, Reduces Error Pruning (REP) Tree), meta-learning (Bagging, Random Subspace) and Function (Multilayer Perceptron and Support Vector Machine) based classifiers have been employed to predict atmospheric concentrations of Nitrogen dioxide (NO2). The study uses 3 atmospheric pollutants; Sulphur dioxide (SO2), Carbon monoxide (CO), and Hydrochloric acid (HCl) and 5 meteorological parameters temperature, humidity, wind speed, wind direction and atmospheric pressure. Moreover, for validation of prediction models the performance of different classifiers were compared. The results obtained suggest that Tree classifiers in general and Random Forest in particular, can outperform Function (MLP and SVM) and meta-learning (Bagging and Random Subspace) classifiers to predict the atmospheric concentration of NO2.

Implementing congestion charges is a method that large cities in China are considering to employ as a solution to the growing traffic congestion problem in recent years. The purpose of this paper is to make a comprehensive prediction and analysis of the effect and impact of the policy. The system dynamics model of traffic congestion charge is established based on five main factors, such as per capita income, population, GDP, private car ownership and air sulfur dioxide content. In the model, the population loss measures peoples’ bearing of the policy and the amount of private car travel measures policy effects. The results show that after the implementation of the scheme is stable, private car travel volumes will decrease significantly and keep growing. This shows that congestion charging scheme can effectively control congestion, and will not have a significant impact on car demand. In addition, the high toll price will have a significantly negative impact on the low-income population, so it is vital that a moderate congestion toll price is fixed.

Urban populations typically consume large quantities of food and foods with high resource demands. To better understand the environmental support behind the food preparation and diets of a “green” urban district, this study evaluates the resource support and sustainability of three diet scenarios in Rosendal, Uppsala, Sweden using emergy synthesis. Scenario one represents actual food preparation and the average diet including meat consumption in Rosendal from Maassen (2017). Two hypothetical scenarios, a vegetarian and pescatarian diet, are examined to investigate the potential implications of different diets on environmental support and total emergy. The results show that the total emergy is lower for the vegetarian and pescatarian scenarios in comparison to the diet including meat, but the ratios and indices for all three diets are not significantly different. The ratios and indices indicate the food preparation and diet system in Rosendal is a consumer and high throughput system that is not sustainable or efficient, mainly due to strong reliance on imported and to a high degree nonrenewable inputs. The results also show that the typical resident, no matter the diet, overshoots the solar share strictly based on their food preparation and consumption alone. This indicates that the specific diet is not as significant as to where and how the food is produced, processed, packaged and delivered from farm to fork. Therefore, this study concludes that specific dietary changes may not be the main issue when considering the sustainability of food consumption in urban populations, but rather the next larger system from which the food is obtained. To improve the efficiency and sustainability of urban food preparation and diets, food should be considered from a holistic perspective that considers environmental performance and resource support in the larger scale systems from where food is sourced and food production should be integrated into urban planning policies.

Anaerobic textile wastewater treatment has become popular in industrial textile treatment for decades. Therefore, the influence of processes, microbial community and bioreactor relevance need to be updated. This paper provides reviewed literature of processes, microbial communities and bioreactors used in anaerobic textile wastewater treatment. These include; temperature, organic loading rate (OLR), up flow velocity, sludge retention time (SRT) as well as hydraulic retention time (HRT) and particle size distribution. Archaea and bacteria as the main groups of microbial communities involved in the treatment of textile wastewater compounds have been highlighted. Expanded granular sludge bed reactor, internal circulation reactor (IC), anaerobic baffled reactor (AnBR), membrane coupled high-rate reactors (MCHR), membrane coupled systems, up-flow anaerobic sludge blanket reactor (UASB) and spiral symmetry stream anaerobic reactors (SSSAB) were also reviewed.

The decision-making processes regarding projects with long-term environmental implications are strongly influenced by the estimate of the Social Discount Rate (SDR). An economic parameter that makes it possible to compare financially the Cash Flows (CFs) that occur at different time points, in the discounting the SDR reduces excessively the costs and benefits more distant over time. If this problem is particularly marked in the Cost-Benefit Analysis (CBA) conducted with time-invariant discount rates, it can be overcome by adopting time-declining discount rates. Thus, starting from the examination of the potentialities connected with the application of hyperbolic discounting in the CBAs, the aim of the work is to characterize an innovative probabilistic model for estimating the Declining Discount Rate (DDR), able to overcome the limits of the theoretical approaches recognized in the literature. The model is implemented on the data of the Italian economy and the DDRs estimated in this way are used in the economic feasibility study of an irrigation reconversion intervention. The processing proves that the adoption of time-declining discount rate allows attributing greater “weight” to the positive long-term externalities that characterize the interventions that promote sustainable development. This with decisive repercussions on the priority order of the initiatives to be financed and therefore on the entire allocation process of resources to be used to projects with intergenerational environmental implications. (*) The contribution to this paper is the result of the joint work of the two authors, to which the paper has to be attributed in equal parts.