Efficiency assessment of urban wastewater treatment plants in China: Considering greenhouse gas emissions

Characteristics of greenhouse gases emission from wastewater treatment plants operation in China (2009–2016): A case study using operational data integrated method (ODIM)

Urban wastewater treatment plants are considered important greenhouse gas resources with massive emissions of carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) during operation. Based on the emission factor approach of pollutant reduction, the 2014 emission inventory of greenhouse gases (CO2, CH4, and N2O) from urban wastewater treatment plants in China was established. In addition, the temporal and spatial distribution and influencing factors of greenhouse gas emissions were analyzed in this study. The results showed that total emissions of greenhouse gas from urban wastewater treatment plants in China was 7348.60 Gg (CO2-eq) in 2014, which included CO2, CH4, and N2O emissions of 6054.57 Gg, 27.47 Gg (769.08 Gg, CO2-eq), and 1.98 Gg (524.95 Gg, CO2-eq), respectively. The difference in greenhouse gas emissions among provinces was significant:high emissions appeared in the eastern areas of China, low emissions were observed in the northwest, and hardly any emissions were found in Xizang. From 2005 to 2014, annual greenhouse gas emissions from urban sewage treatment plants in China increased by 229.4%, and the rates of CO2, CH4, and N2O increased by 217.9%, 217.9%, and 520.3%, respectively. The regional economic development level and number of wastewater treatment plants were correlated the most with the emissions of greenhouse gasses, and the per-capita protein supply was closely related with the N2O emission.

Identifying a sustainable rice-based cropping system via on-farm evaluation of grain yield, carbon sequestration capacity and carbon footprints in Central China

Carbon footprint of a conventional wastewater treatment plant: An analysis of water-energy nexus from life cycle perspective for emission reduction

Quantifying urban wastewater treatment sector's greenhouse gas emissions using a hybrid life cycle analysis method – An application on Shenzhen city in China

In this study, the urban CO2 emission based on energy consumption (Coal, Petroleum, Electricity, and City Gas) in 16 provincial and metropolitan city governments in South Korea was evaluated. For calculation of the urban CO2 emission, direct and indirect emissions were considered. Direct emissions refer to generation of greenhouse gas (GHG) on-site from the energy consumption. Indirect emissions refer to the use of resources or goods that discharge GHG emissions during energy production. The total GHG emission was 497,083 thousand ton CO2eq. in 2007. In the indirect GHG emission, about 240,388 thousand ton CO2eq. was occurred, as 48% of total GHG emission. About 256,694 thousand ton CO2eq. (52% of total GHG emissions) was produced in the direct GHG emission. This amount shows 13% difference with 439,698 thousand ton CO2eq. which is total national GHG emission data using current calculation method. Local metropolitan governments have to try to get accuracy and reliability for quantifying their GHG emission. Therefore, it is necessary to develop and use Korean emission factors than using the IPCC (Intergovernmental Panel on Climate Change) emission factors. The method considering indirect and direct GHG emission, which is suggested in this study, should be considered and compared with previous studies.

Electricity consumption and sludge yield (SY) are important indirect greenhouse gas (GHG) emission sources in wastewater treatment plants (WWTPs). Predicting these byproducts is crucial for tailoring technology-related policy decisions. However, it challenges balancing mass balance models and mechanistic models that respectively have limited intervariable nexus representation and excessive requirements on operational parameters. Herein, we propose integrating two machine learning models, namely, gradient boosting tree (GBT) and deep learning (DL), to precisely pointwise model electricity consumption intensity (ECI) and SY for WWTPs in China. Results indicate that GBT and DL are capable of mining massive data to compensate for the lack of available parameters, providing a comprehensive modeling focusing on operation conditions and designed parameters, respectively. The proposed model reveals that lower ECI and SY were associated with higher treated wastewater volumes, more lenient effluent standards, and newer equipment. Moreover, ECI and SY showed different patterns when influent biochemical oxygen demand is above or below 100 mg/L in the anaerobic-anoxic-oxic process. Therefore, managing ECI and SY requires quantifying the coupling relationships between biochemical reactions instead of isolating each variable. Furthermore, the proposed models demonstrate potential economic-related inequalities resulting from synergizing water pollution and GHG emissions management.

A plant-wide wastewater treatment plant model for carbon and energy footprint: Model application and scenario analysis

Climate-smart livestock production at landscape level in Kenya

Analyzing greenhouse gas emissions from municipal wastewater treatment plants using pollutants parameter normalizing method：a case study of Beijing

The development and application of light aggregate concrete blocks are considered as one of the key issue that promote the energy saving and emission reduction in construction and building materials industries. In this paper, the greenhouse gas (GHG) emissions of light aggregate concrete blocks during the whole life cycle were analyzed based on life cycle assessment (LCA) methodology. The results demonstrated that the amount of GHG emissions of the light aggregate concrete block was 174 kg/m3 in the system boundary of ‘from cradle to gate’. The direct GHG emissions was 51.31 kg/m3 accounting for 28.46% of the aggregate emission, while the indirect GHG emissions was 124 kg/m3. The cement production and the concrete block production were the main contributors to the total emissions. According to the sensitivity analysis, the GHG emissions amount was quite sensitive to the amount of cement and ceramsite consumption.

Aktualnie ważnym wyzwaniem dla sektora rolniczego jest redukcja emisji gazów cieplarnianych (GHG) w celu złagodzenia skutków zmian klimatycznych. Istnieje potrzeba dokładnej identyfikacji źródeł emisji oraz upowszechnienia praktyk rolniczych, które przyczyniałyby się do zmniejszenia emisji we wszystkich ogniwach produkcji roślinnej. Do przeprowadzenia obiektywnych porównań i wyboru najlepszych rozwiązań technologicznych według kryterium emisyjności potrzebna jest szczegółowa ocena ilościowa emisji GHG. W opracowaniu przedstawiono ocenę emisji GHG w produkcji roślinnej za pomocą śladu węglowego (CF). Udział operacji technologicznych w powstawaniu CF scharakteryzowano na przykładzie rzepaku ozimego. Wyniki badań wskazują, że największe znaczenie w kształtowaniu CF ma proces nawożenia mineralnego. Wpływ pozostałych procesów na CF jest wielokrotnie mniejszy. Miejscem głównych emisji GHG w nawożeniu mineralnym rzepaku są emisje bezpośrednie i pośrednie GHG z pól. Po emisjach GHG z pól, produkcja nawozów stanowi drugie źródło emisji z nawożenia. Zmiany praktyk rolniczych polegających na zwiększeniu efektywności nawożenia azotowego oraz stosowaniu nawozów o niskich współczynnikach emisji stwarzają obecnie możliwość redukcji emisji GHG i przez to, tym samym mogą przyczynić się do zmniejszenia CF produktów roślinnych.

GHG evaluation and mitigation planning for low carbon city case study: Dan Sai Municipality

Occurrence, fate, and ecological risk of antibiotics in wastewater treatment plants in China: A review

Industrial wastewater and sewage are both important sources of heavy metals and metalloids in urban wastewater treatment plants (WWTPs). China has made great efforts to control heavy metal and metalloid pollution by setting discharge limits for WWTPs. There is, however, limited discharge data and no systematic methodology for the derivation of discharge limits. In this study, 14 heavy metals and metalloids (Hg, alkyl mercury, As, Cd, Cr, Cr6+, Pb, Ni, Be, Ag, Cu, Zn, Mn, Se) that are listed in the Discharge Standard of Pollutants for Municipal Wastewater Treatment Plant (GB 18918-2002) were selected for the analysis of discharge characteristics while using the supervised monitoring data from more than 800 WWTPs located in nine provinces in China. Of the 14 heavy metals and metalloids, all but alkyl mercury were detected in the discharge water. There was a high rate of detection of As, Cu, Mn, Se, and there were some samples that exceeded the standard concentrations of Cr, Cr6+, Pb, and Ni. Removal rates of Hg, As, Cd, Cr, Cr6+, Pb, Ni, Cu, Zn, Mn, and Se were higher than 40%, comparable to values from other countries. Hg and As were selected to analyze the influencing factors of effluent and derive discharge limits of WWTPs using a statistical method, because these two metals had more detected data than other metals. The study used supervised monitoring data from Zhejiang WWTPs with 99 for Hg and 112 for As. Based on the delta-lognormal distribution, the results showed that geographic location was significantly closely correlated with Hg (P = 0.027 < 0.05) and As (P ≈ 0 < 0.05) discharge concentrations, while size (for Hg P = 0.695 > 0.05, for As P = 0.088 > 0.05) and influent concentration (R2 < 0.5) were not. Derived Hg and As discharge limits suggest that it is necessary to establish stricter discharge limits for WWTPs, which is more consistent with the real-world situation in China. The study here comprehensively researches the discharge characteristics of heavy metals and metalloids in effluent of WWTPs in China, and developed for the first time in China heavy metals and metalloids discharge limits based on statistical methods. The results may inform special discharge limit settings for WWTPs in China.