Performance and uncertainty assessment of green roofs for urban flood reduction in a high-density catchment in Ahmedabad, India.

Urban flooding poses a significant challenge to the rapidly growing Indian cities. Low-impact development strategies such as green roofs have shown the potential to reduce urban flooding. However, their performance assessment significantly varies across different studies. Therefore, the study's primary objective is to evaluate green roofs in the Indian context. For this evaluation, the green roofs are assessed based on building-level implementation scenarios for a high-density urban area in India for 25%,50%, and 75% application rates and different rainfall intensities (2,3 and 4-h duration and 2,5,10 and 25-year frequencies). Secondly, to probe the variations in the green roof performance across studies, uncertainty contributions to the runoff reduction from different parameters are quantified. The results show that green roofs can reduce up to 62% of flood volume and 24% of runoff. However, they are reasonably effective only beyond 25% application rates. Further, rainfall intensity contributes the most to the uncertainty of runoff reduction from green roofs. This uncertainty assessment implies that localized evaluation of green roofs depending on local rainfall conditions is required for city-wide policy planning. The study has a significant contribution to building confidence in the ability of green roofs to reduce urban floods in the context of developing countries like India.

Economic and environmental benefits of natural treatment systems for sewage treatment: A life cycle perspective.

Sewage treatment involves a trade-off of land vs. energy and the location of installing Sewage Treatment Plants (STPs) strongly impacts the decisions regarding treatment technologies. In the wake of rapid urbanization, deteriorating freshwater quality and water scarcity, it is crucial to plan adequate and low-cost sewerage infrastructure that can improve the quality of life in rural and urban areas. The present work involves a novel life cycle analysis through six scenarios generated from a holistic perspective that can aid urban planners and urban local bodies in planning the sewage treatment facilities in their cities, towns or villages. Instead of planning sewerage infrastructure for a long-term period of thirty years, it is suggested to create and operate the STPs only for the upcoming decade. Further, owing to the drawbacks of mechanized and natural treatment systems, adopting a mix of these treatment approaches in planning infrastructure is suggested and the benefits of implementing the same are quantified and discussed. Implementing these strategies results in almost 30 % cost savings and 40 % reduction in greenhouse gas emissions, hence, investing in land for natural treatment systems is suggested instead of incurring heavy electricity bills for mechanized treatment systems. The land cost significantly affects the decision-making regarding treatment technology selection; hence, the variation in the life cycle cost of different sewage treatment approaches is assessed for varying land rates in India.

Review of Circular Economy in urban water sector: Challenges and opportunities in India.

Increasing urbanization and rapid depletion of resources have forced authorities to shift from traditional linear system of take-make-use-dispose to circular system of resource conservation. Circular Economy (CE) is a sustainable development approach that works on the waste management strategy of reduce, reuse, recycle, and recover. Considerable work has been performed on CE in various sectors such as in electronic sector, construction sector, automotive sector, etc. However, CE in the water sector is gaining rapid attention, because of imbalance in water resources and the prevailing linear approach. The aim of this study is to review the world-wide growth of CE concept in the water sector from an economic, environmental, social, and technical perspective. 98 publications were selected by systematic literature review and categorized in economic, environmental, social, and technical criteria including a combination of multiple criteria. In this study, the world-wide status of CE implementation in the water sector is assessed and strategies to encourage and enhance CE implementation are proposed. The six BS8001:2017 principles and 6Rs (reduce, reuse, recycle, reclaim, recover, restore) of waste management are critically analyzed for deriving recommendations and successful implementation of CE in water sector. Finally, challenges and opportunities to implement CE in the water sector in India are discussed.

A two-stage multi-attribute decision-making model for selecting appropriate locations of waste transfer stations in urban centers.

Selecting appropriate locations for municipal solid waste (MSW) management facilities, such as transfer stations, is an important issue in rapidly developing regions. Multiple alternatives and evaluation attributes need to be analyzed for finalizing the locations of these facilities. Multi-attribute decision-making (MADM) approaches are found to be very effective for ranking several potential locations and hence selecting the best among them based on the identified attributes. However, conventional MADM approaches fail to find the rankings of alternatives derived from all possible combinations of these potential locations. Therefore, this study presents a two-stage MADM model that also accounts for all possible combinations of locations. This study evaluates economical, environmental, social and technical attributes based on realistic conditions of the study area, i.e., Nashik city (India). The results provide the ranks of all possible combinations along with their probabilities of rank reversibility. The mean and standard deviation of the relative closeness are further evaluated for the top-ranking locations under distinct schemes. The present study will help stakeholders in finding suitable locations for MSW management facilities while considering economic, environmental, social and technical attributes.

WW LCI v2: A second-generation life cycle inventory model for chemicals discharged to wastewater systems.

We present a second-generation wastewater treatment inventory model, WW LCI 2.0, which on many fronts represents considerable advances compared to its previous version WW LCI 1.0. WW LCI 2.0 is a novel and complete wastewater inventory model integrating WW LCI 1.0, i.e. a complete life cycle inventory, including infrastructure requirement, energy consumption and auxiliary materials applied for the treatment of wastewater and disposal of sludge and SewageLCI, i.e. fate modelling of chemicals released to the sewer. The model is expanded to account for different wastewater treatment levels, i.e. primary, secondary and tertiary treatment, independent treatment by septic tanks and also direct discharge to natural waters. Sludge disposal by means of composting is added as a new option. The model also includes a database containing statistics on wastewater treatment levels and sludge disposal patterns in 56 countries. The application of the new model is demonstrated using five chemicals assumed discharged to wastewater systems in four different countries. WW LCI 2.0 model results shows that chemicals such as diethylenetriamine penta (methylene phosphonic acid) (DTPMP) and Diclofenac, exhibit lower climate change (CC) and freshwater ecotoxicity (FET) burdens upon wastewater treatment compared to direct discharge in all country scenarios. Results for Ibuprofen and Acetaminophen (more readily degradable) show that the CC burden depends on the country-specific levels of wastewater treatment. Higher treatment levels lead to lower CC and FET burden compared to direct discharge. WW LCI 2.0 makes it possible to generate complete detailed life cycle inventories and fate analyses for chemicals released to wastewater systems. Our test of the WW LCI 2.0 model with five chemicals illustrates how the model can provide substantially different outcomes, compared to conventional wastewater inventory models, making the inventory dependent upon the atomic composition of the molecules undergoing treatment as well as the country specific wastewater treatment levels.

Personal Metabolism (PM) coupled with Life Cycle Assessment (LCA) model: Danish Case Study.

Sustainable and informed resource consumption is the key to make everyday living sustainable for entire populations. An intelligent and strategic way of addressing the challenges related with sustainable development of the everyday living of consumers is to identify consumption-determined hotspots in terms of environmental and health burdens, as well as resource consumptions. Analyzing consumer life styles in terms of consumption patterns in order to identify hotspots is hence the focus of this study. This is achieved by taking into account the entire value chain of the commodities consumed in the context of environmental and human health burdens, as well as resource consumptions. A systematic commodity consumption, commodity disposal, and life style survey of 1281 persons living in urbanized Danish areas was conducted. The findings of the survey showed new impact dimensions in terms of Personal Metabolism (PM) patterns of residents living in urbanized areas of Denmark. Extending the PM analysis with Life Cycle Assessment (LCA) provided a clear picture of the per capita environmental and human health burdens, as well as resource consumptions, and the exact origin hereof. A generic PM-LCA Model for all the 1281 persons was set-up in Gabi 6. The assessment results obtained applying the model on all 1281 personal consumption scenarios yielded the 1281 Personal Impact Profiles (PIPs). Consumption of food and energy (electricity and thermal energy) proved to be the primary impact sources of PM, followed by transport. The PIPs further revealed that behavioral factors (e.g. different diets, use of cars, household size) affect the profiles. Hence, behavioral changes are one means out of many that humanity will most likely have to rely on during the sustainable development process. The results of this study will help the Danish and other comparable populations to identify and prioritize the steps towards reducing their environmental, human health, and resource consumption burdens.

The influence of expert opinions on the selection of wastewater treatment alternatives: a group decision-making approach.

The application of multiple-attribute decision-making (MADM) to real life decision problems suggests that avoiding the loss of information through scenario-based approaches and including expert opinions in the decision-making process are two major challenges that require more research efforts. Recently, a wastewater treatment technology selection effort has been made with a 'scenario-based' method of MADM. This paper focuses on a novel approach to incorporate expert opinions into the scenario-based decision-making process, as expert opinions play a major role in the selection of treatment technologies. The sets of criteria and the indicators that are used consist of both qualitative and quantitative criteria. The group decision-making (GDM) approach that is implemented for aggregating expert opinions is based on an analytical hierarchy process (AHP), which is the most widely used MADM method. The pairwise comparison matrices (PCMs) for qualitative criteria are formed based on expert opinions, whereas, a novel approach is proposed for generating PCMs for quantitative criteria. It has been determined that the experts largely prefer natural treatment systems because they are more sustainable in any scenario. However, PCMs based on expert opinions suggest that advanced technologies such as the sequencing batch reactor (SBR) can also be appropriate for a given decision scenario. The proposed GDM approach is a rationalized process that will be more appropriate in realistic scenarios where multiple stakeholders with local and regional societal priorities are involved in the selection of treatment technology.

Selection of an appropriate wastewater treatment technology: a scenario-based multiple-attribute decision-making approach.

Many technological alternatives for wastewater treatment are available, ranging from advanced technologies to conventional treatment options. It is difficult to select the most appropriate technology from among a set of available alternatives to treat wastewater at a particular location. Many factors, such as capital costs, operation and maintenance costs and land requirement, are involved in the decision-making process. Sustainability criteria must also be incorporated into the decision-making process such that appropriate technologies are selected for developing economies such as that of India. A scenario-based multiple-attribute decision-making (MADM) methodology has been developed and applied to the selection of wastewater treatment alternative. The four most commonly used wastewater treatment technologies for treatment of municipal wastewater in India are ranked for various scenarios. Six scenarios are developed that capture the regional and local societal priorities of urban, suburban and rural areas and translate them into the mathematical algorithm of the MADM methodology. The articulated scenarios depict the most commonly encountered decision-making situations in addressing technology selection for wastewater treatment in India. A widely used compensatory MADM technique, TOPSIS, has been selected to rank the alternatives. Seven criteria with twelve indicators are formulated to evaluate the alternatives. Different weight matrices are used for each scenario, depending on the priorities of the scenario. This study shows that it is difficult to select the most appropriate wastewater treatment alternative under the "no scenario" condition (equal weights given to each attribute), and the decision-making methodology presented in this paper effectively identifies the most appropriate wastewater treatment alternative for each of the scenarios.