Greenhouse Gas Emission Factors Research Articles

Uncertainties in greenhouse gas emission factors: A comprehensive analysis of switchgrass‐based biofuel production

Uncertainties in greenhouse gas emission factors: A comprehensive analysis of switchgrass‐based biofuel production

Assessment of carbon footprint of potable water production: A case from Bangladesh

Carbon footprint (CF), a measure of greenhouse gas (GHG) emissions, is currently a global concern because of its significant effects on climate change. Understanding GHG emissions from potable water production is important because water treatment and distribution consume much energy while emitting a significant amount of GHG. With economic and population growth, water demand has increased, resulting in higher GHG emissions. This study aims to assess the CF of potable water production in Bangladesh, focusing on the country’s economic capital, Chattogram. This study estimates and compares the CF of the treatment, distribution, and consumption phases. It also estimates the CF of different water treatment plants (WTPs) during the treatment phase. WTPs use electricity for a full-scale operation, during which approximately 4.5 million m3 of raw water of varying turbidity is treated. This study calculates a country-specific GHG emission factor for Bangladesh’s electricity generation method as different sources produce different quantities of GHGs. This study also considers the energy consumed to distribute water from the WTPs to household rooftop tanks in the distribution phase. For the consumption phase, the study considers the energy consumption for domestic water treatment, which involves boiling of a portion of treated water for drinking purposes. The study estimates that approximately 0.18, 0.27, and 17.52kg CO2-eq are emitted in the treatment, distribution, and consumption phases, respectively, for the production of 1 m3 of water. Boiling at the consumption phase alone generates 97.48 % of the total CF. The daily CFs for surface water and groundwater use in 2017 were 16,387.78 and 34,092.08kg CO2-eq, respectively; those in 2022 were 83,769.25 and 2130.97kg CO2-eq, respectively. The outcome of this study will assist stakeholders and policymakers in the progress of SDG-13 and in effective planning and operational decision making for sustainable water systems.

Framework for a savanna burning emissions abatement methodology applicable to fire-prone miombo woodlands in southern Africa

Background and aims To assess development of a robust emissions accounting framework for expansive miombo woodland savannas covering ~2 million km2 of southern Africa that typically are burnt under relatively severe late dry season (LDS) conditions. Methods A detailed site-based study of fuel accumulation, combustion and greenhouse gas (GHG) emission factor parameters under early dry season (EDS) and LDS conditions along a central rainfall-productivity and associated miombo vegetation structural and floristics gradient, from lower rainfallsites in northern Botswana to higher rainfall sites in northern Zambia. Key results Assembled field data inform core components of the proposed emissions reduction framework: fuel and combustion conditions sampled across the vegetation/productivity gradient can be represented by three defined Vegetation Fuel Types (VFTs); fuel accumulation, combustion and emissions parameters are presented for these. Applying this framework for an illustrative case, GHG emissions (t CO2-e) from EDS fires were one-third to half those of LDS fires per unit area in eligible miombo VFTs. Conclusions Our accounting framework supports undertaking EDS fire management to significantly reduce emissions and, realistically, burnt extent at landscape scales. We consider application of presented data to development of formal emissions abatement accounting methods, linkages with potential complementary woody biomass and soil organic carbon sequestration approaches, and necessary caveats concerning implementation issues.

Refining greenhouse gas emission factors for Indonesian peatlands and mangroves to meet ambitious climate targets

For countries' emission-reduction efforts under the Paris Agreement to be effective, baseline emission/removals levels and reporting must be as transparent and accurate as possible. For Indonesia, which holds among the largest area of tropical peatlands and mangrove forest in the world, it is particularly important for these high-carbon ecosystems to produce high-accuracy greenhouse gas inventory and to improve national forest reference emissions level/forest reference level. Here, we highlight the opportunity for refining greenhouse gas emission factors (EF) of peatlands and mangroves and describe scientific challenges to support climate policy processes in Indonesia, where 55 to 59% of national emission reduction targets by 2030 depend on mitigation in Forestry and Other Land Use. Based on the stock-difference and flux change approaches, we examine higher-tier EF for drained and rewetted peatland, peatland fires, mangrove conversions, and mangrove on peatland to improve future greenhouse gas flux reporting in Indonesia. We suggest that these refinements will be essential to support Indonesia in achieving Forest and Other Land Use net sink by 2030 and net zero emissions targets by 2060 or earlier.

A review on the evaluation models and impact factors of greenhouse gas emissions from municipal solid waste management processes.

The total amount of global municipal solid waste (MSW) will reach 3.5 billion tons by 2050, thereby bringing tremendous environmental pressure, especially global warming. Large amounts of greenhouse gases (GHGs) have been released during MSW management (MSWM). Accounting for GHG emissions is a prerequisite for providing recommendations on appropriate treatment options to mitigate emissions from MSWM systems. There are many methods involved in estimating emissions. This paper summarizes the computing models commonly used in each process of the integrated MSWM system and emphasizes the influence of parameters and other factors. Compared with other disposal methods, landfilling has the highest emissions, commonly estimated using first-order decay (FOD) methods. Emission reduction can be realized through waste to energy (WtE) and resource recovery measures. IPCC is commonly used for calculating direct emissions, while LCA-based models can calculate emissions including upstream and downstream processes, whose results depend on assumptions and system boundaries. The estimation results of models vary greatly and are difficult to compare with each other. Besides, large gaps exist between the default emission factors (EFs) provided by models and those F measured in specific facilities. These findings provide a systematic view for a bettering understanding of MSW emissions as well as the estimating methods and also reveal the key points that need be developed in the future.

Greenhouse gas emissions of sewage sludge land application in urban green space: A field experiment in a Bermuda grassland

Sewage sludge land application is recognized as a strategy for recycling resource and replenishing soil nutrients. However, the subsequent greenhouse gas emissions following this practice are not yet fully understood, and the lack of quantitative research and field experiments monitoring these emissions hampers the establishment of reliable emission factors. This study investigated the greenhouse gas emission characteristics of sewage sludge land application through a field experiment that monitoring soil greenhouse gas fluxes. Seven nitrogen input treatments were implemented in a typical Bermuda grassland in China, with D and C representing the amendment of digested and composted sludge, respectively, at the nitrogen input rate of 0, 100, 200, and 300 kg N ha−1. Soil CH4, CO2, and N2O fluxes were measured throughout the entire experimental period, and soil samples from different treatments at various growth stages were analyzed. The results revealed that sewage sludge land application significantly increased soil N2O and CO2 emissions while slightly reducing soil CH4 uptake. The increased CO2 emissions were biogenic and carbon-neutral, mainly due to enhanced plant root respiration. The N2O emissions were the primary greenhouse gas emissions of sewage sludge land application, which were mainly concentrated in two 50-day periods following base and topdressing fertilization, respectively. N2O emissions following base fertilization by rotary tillage were substantially lower than those following topdressing fertilization. A logarithmic response relationship between N input rates and increased soil N2O emissions was observed, suggesting lower N2O emissions from sewage sludge land application compared to conventional N fertilizers at the same N input level. Future field experiments and meta-analysis are necessary to develop reliable greenhouse gas emission factors for sewage sludge land application.

Spatial and temporal evolution and drivers of GHG emissions from urban domestic wastewater treatment in China: a review at the provincial level.

To mitigate greenhouse gas (GHG) emissions from the wastewater treatment industry, it is crucial to explore GHG emission patterns and propose useful measures. In this study, we use the Kaya model and LMDI decomposition method to analyze the changes in GHG emissions from urban domestic wastewater treatment at the provincial level and further explore the distribution characteristics and driving factors of urban domestic wastewater treatment GHG emissions across various years and regions. The results indicate the following: (1) In the temporal dimension, urban domestic wastewater treatment GHG emissions are increasing, from 21.0 MtCO2 in 2011 to 27.1 MtCO2 in 2020, with an average annual growth rate of 2.88%. The spatial distribution is high in the southeast and low in the northwest. There is variability in the spatial evolution trend of GHG emissions by province, with the growth rate becoming slower or even negative in Jiangsu, Zhejiang, and North China, while the average annual growth rate exceeds 25% in Inner Mongolia and Xinjiang. (2) According to the decomposition results of driving factors, economic scale is the dominant positive driver, and the positive contributions of TI and the population effect are limited. The sludge disposal structure is the main negative driver, and the EEI and technology have restricted negative contributions. (3) Based on the decomposition results, for major coastal GHG emitters, such as Guangdong and Shandong, it is necessary to invest capital and technology to continuously upgrade the wastewater treatment process and reduce non-CO2 emissions. Along with adopting circular economy schemes, local governments in the northwestern region should transform the traditional sludge disposal structure and optimize the power supply structure to increase carbon offset and reduce CO2 emissions. The findings suggest a low-carbon transformation path to support the industry's dual carbon goals.

Spatial-temporal characteristics and driving factors' contribution and evolution of agricultural non-CO2 greenhouse gas emissions in China: 1995-2021.

Comprehending the spatial-temporal characteristics, contributions, and evolution of driving factors in agricultural non-CO2 greenhouse gas (GHG) emissions at a macro level is pivotal in pursuing temperature control objectives and achieving China's strategic goals related to carbon peak and carbon neutrality. This study employs the Intergovernmental Panel on Climate Change (IPCC) carbon emissions coefficient method to comprehensively evaluate agricultural non-CO2 GHG emissions at the provincial level. Subsequently, the contributions and spatial-temporal evolution of six driving factors derived from the Kaya identity were quantitatively explored using the Logarithmic Mean Divisia Index (LMDI) and Geographical and Temporal Weighted Regression (GTWR) methods. The results revealed that the distribution of agricultural non-CO2 GHG emissions is shifting from the central provinces to the northwest regions. Moreover, the dominant driving factors of agricultural non-CO2 GHG emissions were primarily economic factor (EDL) with positive impact (cumulative promotion is 2939.61 million metric tons (Mt)), alongside agricultural production efficiency factor (EI) with negative impact (cumulative reduction is 2208.98 Mt). Influence of EDL diminished in the eastern coastal regions but significantly impacted underdeveloped regions such as the northwest and southwest. In the eastern coastal regions, EI gradually became the absolute dominant driver, demonstrating a rapid reduction effect. Additionally, a declining birth rate and rural-to-urban population migration have significantly amplified the driving effects of the population factor (RP) at a national scale. These findings, in conjunction with the disparities in geographic and socioeconomic development among provinces, can serve as a guiding framework for the development of a region-specific roadmap aimed at reducing agricultural non-CO2 GHG emissions.

Synergies from off-gas analysis and mass balances for wastewater treatment — Some personal reflections on our experiences

Looking back at over a decade of research by herself and her group, the author advocates the added value of gas phase measurements and the application of mass balances, as well as the synergetic benefits obtained when combining both. The increased application of off-gas measurements for greenhouse gas emission monitoring offers a great opportunity to look at other components in the gas phase, particularly oxygen. Mass balances should not be strictly reserved for modellers but also prove useful while conducting lab experiments and studying full-scale measurement data. Combining off-gas measurements with mass balances may serve not only to quantify greenhouse gas emission factors and aeration efficiency but also to follow dynamic concentration profiles of dissolved components without dedicated sensors and/or to calculate other unmeasured variables. Mass-balance-based data reconciliation allows for obtaining reliable and accurate data, and even more when combined with off-gas analysis.

Procedures to combine estimators of greenhouse gases emission factors.

This article describes a new procedure to estimate the mean and variance of greenhouse gases (GHG) emission factors based on different, possibly conflicting, estimates for these emission factors. The procedure uses common information such as mean and standard deviation usually reported in IPCC (Intergovernmental Panel on Climate Change) database and other references in the literature that estimate emission factors. Essentially, it is a procedure in the class of meta-analysis, based on the computation of [Formula: see text], a new estimator for the variance of the emission factor. We discuss the quality of this estimator in terms of its probability distribution and show that it is unbiased. The resulting confidence interval for the mean emission factor is tighter than those that would have resulted from using other estimators such as pooled variance and thus, the new procedure improves the accuracy in estimating GHG emissions. The application of the procedure is illustrated in a case study involving the estimation of methane emissions from rice cultivation. The estimation of emission factors using [Formula: see text] was demonstrated to be more accurate because it is not biased and more precise than alternative methods.

Carbon footprints of tea production in smallholder plantations: A case study of Fenghuang Dancong tea in China

The high fertilizer application in tea planting and the large energy consumption in tea processing have raised concerns about greenhouse gas (GHG) emissions of tea production. China is the world's largest tea production country, but its tea production is dominated by smallholder farmers. Therefore, when it comes to GHG emission reduction in tea production, specific measures need to be developed for the smallholder mode. The purpose of this study is to reveal the characteristics and influencing factors of GHG emissions of smallholder tea plantations, as well as to develop GHG emission reduction measures suitable for the smallholder mode. Here, we focus on Fenghuang Dancong tea and two types of smallholder tea plantations, the high-altitude tea plantation (HTP11HTP: the high-altitude tea plantation; MLP: the mid-low-altitude tea plantation; CF: carbon footprint; GHG: greenhouse gas; CO2-eq: CO2 emission equivalent; LCA: life cycle assessment.) and the mid-low-altitude tea plantation (MLP), in Fenghuang Town, Chaozhou City, China. The carbon footprint (CF) method is employed, which is a widely used method for estimating GHG emissions and expressed in CO2 emission equivalent (CO2-eq). The assessment on the CF of the Fenghuang Dancong tea production and a comparative analysis between the HTP and the MLP have been made. Results show that (1) at the tea planting stage, fertilizer input is the main contributor to the CFplanting; electricity input is the primary component of the CFprocessing at the tea processing stage; (2) considering the two stages of tea planting and processing, the CFtea of the MLP is more than twice that of the HTP; (3) the production and management measures adopted by tea farmers have a significant impact on the CFtea, which are mainly driven by economic interests. In view of these findings, we emphasize the importance of balancing GHG emission reduction with economic benefits and propose GHG emission reduction measures such as formulating subsidy policies for organic fertilizers, promoting green and organic product certification, improving the energy input structure and strengthening scientific guidance. We submit that this study will not only help local managers formulate efficient GHG emission reduction measures, but also provide references for other studies on GHG emissions of tea production in the smallholder mode.

Household energy-related carbon footprint in residential neighbourhoods in high-latitude cities: A case of Edmonton in Canada

Understanding all the possible greenhouse gas (GHG) emission sources and factors is key to achieving net zero emissions by 2050, as targeted by the Paris Agreement, and thereby, averting the severe consequences of climate change. In this study, we explored household energy-related GHG (HEGHG) emissions in 265 residential neighbourhoods in a high-latitude city that experiences opposite temperature extremes. Our results revealed that the average annual per capita GHG emissions from dwellings in the city are 45% higher than those from personal transportation, highlighting the urgent need for greater emphasis on reducing GHG emissions from dwellings in high-latitude cities. We found that per capita floor area is positively correlated with GHG emissions. The findings also indicate that per capita HEGHG emissions significantly increase with increasing neighbourhood income levels (r = 0.8). An increase in the percentage of households struggling to afford homeownership is also associated with a decrease in HEGHG emissions (r = -0.3). These findings can help facilitate the focus on areas of high-latitude cities where the mitigation measures may have the most impact in reducing carbon footprint.

Carbon footprint and energy life cycle assessment of wind energy industry in Libya

The recent investigation has demonstrated that wind energy holds great potential as a viable and environmentally friendly energy source in Libya. The study employed a Life Cycle Assessment (LCA) methodology to evaluate various energy, economic, and environmental indicators for potential wind farm installations at multiple suitable locations across Libya. The assessment encompassed estimations of energy requirements and greenhouse gas (GHG) emissions associated with the conversion of wind energy into electricity throughout the entire life cycle of the proposed wind farms. In light of Libya not being a producer of wind energy converters, a novel approach was developed to define the system's boundaries. These boundaries included distinct subsystems, each corresponding to various stages within the life cycle of a wind energy system, encompassing factors such as shipping emissions from the manufacturer's location to Tripoli's marine ports, land transportation to the wind farm sites, energy and emissions associated with installation, operation, maintenance, and eventual disposal of wind turbines.Hourly climate data spanning a 25-year period from 1995 to 2020 were gathered from the SolarGis climate information site. The System Advisor Model (SAM) program was utilized to predict the energy yields of 100 MW capacity wind farms at 12 sites in Libya. Additionally, a novel eco-environmental indicator known as the Life Cycle Levelized Cost of Energy (LCLCOE) was introduced, which factors in all environmental damage costs throughout the entire lifespan of wind energy projects. The study's findings revealed that the Gamesa turbine, with a capital cost of $146,916,400 for a 100 MW capacity wind energy farm, exhibited the most favorable economic and environmental performance. GHG emission factors across all examined cities ranged from 32 to 70 gGHG/kWh, with carbon payback durations spanning from 4.5 to 12.3 months. The estimated energy payback period varied from 13 to 22 months, while the LCLCOE ranged from 4.8 to 8.4 ¢/kWh.

From certificate to physics - Paths to net-zero compatible buildings

The role of heat pumps in a decarbonised (thermal) energy system is pivotal. This technology is often in competition with other technologies such as district heating or boilers. When comparing different heating technologies in respect to their CO2 footprint and their costs, the calculation method of future greenhouse gas emission factors of the different energy carriers and energy prices is decisive. Emission factors need to be based on technical and physical fundamentals as (international) green certificates are not a satisfactory proxy for physical emissions, especially for the case of electricity. Currently the Swiss electricity generation system is mostly decarbonised with its high share of hydropower and nuclear energy. However, Switzerland, located in the heart of Europe, has the highest relative shares of cross border capacities, which are relevant for energy trading. In a still fossil dominated European power system, the high volatility of wholesale power prices is entailing a high (temporal) volatility of power related emissions. Thus, the overall carbon footprint of consumed electricity changes significantly over time. Heating demand also shows a dynamic behaviour. It is therefore likely, that a CO2 footprint based on annual averages in heating demand and emission factors could lead to significant errors. The aim of the research was to draw a comparison of the resulting annual CO2 emissions applying different time step aggregation levels (yearly, monthly, typical days) with the results calculated based on a complete year in hourly resolution. The aim was to determine the relative error made through aggregation.

Comprehensive analysis of greenhouse gas emissions and emission factors in a Korean domestic wastewater treatment plant: Insights into mechanisms and pathways for climate change mitigation

This study aimed to estimate greenhouse gas (GHG) emissions from the Daejeon wastewater treatment plant (WWTP) in South Korea and identify strategies for reducing its carbon footprint. Both the worksheet-based Carbon Footprint Calculation Tool and the Massflow3 simulator were used to calculate the total GHG emissions from the “D” WWTP and identify the main sources of emissions. The results revealed that electricity consumption contributed to 45 − 48 % of emissions, while direct emissions from N2O accounted for 35–38 % of the total emissions. Furthermore, it was discovered that the WWTP's GHG emissions were 33–57 % higher compared to European sewage treatment plants that had established GHG reduction programs. To decrease the plant's carbon footprint, recommendations include optimizing nitrogen removal rates while minimizing incomplete nitrification and controlling the air flow rate in the aeration tank. Additionally, there is an emphasize on the importance of establishing a strategy to reduce indirect GHG emissions resulting from power consumption. These findings have important implications for the policy and management of WWTPs, highlighting the potential environmental and economic benefits of GHG emissions reduction.

Increasing temporal resolution in greenhouse gas accounting of electricity consumption divided into Scopes 2 and 3: case study of Germany

PurposeAs renewable energy sources (RES) experience short-term variability, electricity greenhouse gas (GHG) emissions also fluctuate. Increasing temporal resolution in electricity emissions accounting allows capturing these fluctuations. However, existing time-resolved models either neglect indirect impacts, adopt a generation perspective, or are based on non-public country-specific data. We provide an approach for calculating time-resolved GHG emission factors (EFs) of electricity consumption based on open access data for European countries and examine the temporal variability of German EFs.MethodsTime-resolved electricity GHG EFs are calculated within the framework of attributional life cycle assessment (LCA) with up to quarter-hourly resolution. The approach involves top-down calculation of annual combustion emissions, validation and scaling of time-resolved electricity generation data, as well as calculation of inland consumption EFs for each interval throughout a year. The EFs are divided by the stages of net generation, consumption by hydro-pumped storage (HPS), and transmission and distribution (T&D) losses, as well as Scopes 2 and 3, enabling GHG Protocol Corporate Standard-compliant reporting. The approach is exemplarily applied to Germany and its transmission system operator zones at quarter-hourly resolution for the years from 2017 to 2020 to investigate the relation between grid mix composition and temporal variability of EFs.Results and discussionThe annual average EF of the German consumption mix, encompassing direct and upstream emissions, declined from 499 (2017) to 377 g CO2e/kWh (2020), while quarter-hourly variability increased by 12%. Neglecting upstream emissions and intermediate steps between generation and consumption in Germany in 2020 resulted in an underestimation of 13% on an annual level, while quarter-hourly Scope 3 EFs reached up to 100 g CO2e/kWh. On a sub-national level, annual average EFs varied between 157 g CO2e/kWh (TenneT zone) and 505 g CO2e/kWh (50Hertz zone) in 2020. Temporal variability is the greatest in electricity systems with both fossil-fuel and renewable capacity sufficient to dominate short-term electricity generation. At an advanced level of RES integration, the fluctuations of EFs start declining, as demonstrated by the TenneT case.ConclusionAn increased temporal resolution in electricity emissions accounting can enhance a posteriori LCA results’ accuracy during the energy transition phase. The provided EFs link the life cycle-based perspective with time-resolved emissions accounting. With increasing reliance on RES, indirect emissions, including those related to energy storage, will gain in significance. The next step should focus on integrating physical cross-border electricity exchanges to complete the consumption perspective, as well as examining practical implementation to other countries.

New model for evaluating greenhouse gas emissions from sludge treatment based on fossil and biogenic carbon migration

The treatment and disposal of massive amounts of sewage sludge are potential emission sources of greenhouse gases (GHGs) which strongly depend on the migration of fossil and biogenic carbon into GHGs. Owing to the lack of fossil carbon data and suitable estimation models, CO2 emissions generated from sludge combustion and biodegradation are considered carbon-neutral according to the Intergovernmental Panel on Climate Change (IPCC), increasing the inaccuracy of GHG emissions accounting. Therefore, this study aimed to build a new comprehensive assessment model to accurately evaluate GHG emissions from four typical sludge treatment and disposal approaches. Notably, fossil and biogenic carbon migration were considered, rather than the emission factor method when measuring direct GHG emissions. The results of 14C analysis, which quantified the contributions of fossil and biogenic carbon to the sludge samples, showed significant differences in the average fossil carbon fractions among the four types of sludge: 84.11% for chemical sludge, 25.99% for tannery sludge, 79.19% for textile dyeing sludge, and 45.97% for municipal sludge. According to our model, the route of safely landfilling deep-dewatered sludge possessed the highest GHG emission factors of 1.18–3.75 tCO2eq/t dry sludge. The optimal sludge treatment option was anaerobic digestion followed by land application. This treatment maintained a low and stable level of GHG emissions (0.48–0.54 tCO2eq/t dry sludge) and exhibited low sensitivity to changes in fossil carbon fraction and carbon content according to the sensitivity analysis results. For sludge with a high calorific value and a low fossil carbon fraction, the route of dry incineration + utilization of ash and slag as building materials was carbon-negative and more suitable than anaerobic digestion to achieve carbon neutrality. This study complements the fossil carbon data gaps of sludge in the IPCC Guidelines and provides a more accurate GHG emissions accounting model, which will support the sludge treatment industry in developing effective strategies to reduce GHG emissions.

Estimating the greenhouse gas emission factor of motorcycles under real-world driving conditions in Hanoi: a case study

The lack of country-specific greenhouse gas (GHG) emission factors vehicles in Vietnam makes the emissions inventory in the transport sector more difficult. This study developed the country-specific GHG emission factor in terms of CO2 equivalent for motorcycles (MCs) in Hanoi to overcome the above impediment. The real-world driving data, instantaneous speed versus time, were collected on the 30 road routes in Hanoi using a GPS device. A filtering process of nine-step was designed to repair misleading speed values and denoise signals before entering the International Vehicle Emissions (IVE) model. The typical GHG emission factor for the MC fleet in Hanoi was approximately 90.83 g/km. This study also found a remarkable difference in the MC’s specific power-related bins distribution between the real-world driving characteristics of the MC in Hanoi and the ones of the World Motorcycle Test Cycle. This contributes to reconfirming the necessity of developing the GHG emission factor based on the very real-world driving data of Vietnam

Industrially relevant pyrolysis of diverse contaminated organic wastes: Gas compositions and emissions to air

Pyrolysis is a promising waste handling technique compared to incineration, especially due to its potential for greenhouse gas reduction through biochar carbon removal. This study investigated greenhouse gas and air pollutant emissions and emission factors from waste feedstocks and a reference clean wood pyrolyzed at 500–800 °C in an industrially relevant small version Biogreen® unit with condensation prior to pyrolysis gas combustion. Emissions were generally lower than literature values, except for nitrogen oxides (NOX) and sulfur dioxide (SO2). Methane (CH4) and nitrous oxide (N2O) emissions ranged 30–570 mg CH4 and 0–32 mg N2O per kg biochar produced. Waste lignocellulosics (waste timber and garden waste) had comparable emissions to clean wood, except for higher NOX emissions. All waste feedstocks exceeded the EU NOX emission limit value for waste incineration (>200 mg NOX/Nm3 at 11% oxygen, O2), while no carbon monoxide (CO) was measured (<0.6 mg/Nm3) suggesting possible compliance with EU emission limit values for waste incineration with simple pollution control measures such as air-to-fuel ratio regulation, or other NOX reducing measures such as flue gas recirculation or selective (non-)catalytic reduction. Sludges and food waste reject also exceeded the SO2 EU emission limit value (50 mg SO2/Nm3 at 11% O2) for waste incineration, emissions ranging 61–298 mg SO2/Nm3 at 11% O2, indicating the potential need for SO2 pollution control. In conclusion, this study shows continuous pyrolysis with condensation as a promising alternative for waste management with potential for simplified air pollution control compared to incineration. Future work should focus on optimized combustion systems for waste pyrolysis and emissions from waste pyrolysis without condensation.

Retrospective dynamic life cycle assessment of residential heating and cooling systems in four locations in the United States

Heating, ventilation, and air conditioning systems (HVAC) and water heaters are responsible for a relevant portion of the total Greenhouse Gas (GHG) emissions related to the building life cycle. A significant effort will be needed to substantially reduce building-related GHG emissions to meet the increasing demand to meet goals for energy use and GHG emission reduction. This study evaluates the GHG emissions of two alternative residential HVAC systems: natural gas furnace and electric air conditioning, and an electric heat pump, in a typical single-family house located in four different climate zones in the U.S. using a life cycle assessment model that includes spatial variations such as climate and electricity generation mix and temporal variations such as the changes in the generation mix and greenhouse gas emission factors for electricity generation over time. The locations selected are in very cold, cold, marine (temperate), and hot-humid climate zones in the U.S. The reduction in GHG emissions over time occurred due primarily to the changes in the electricity grid mix. As a result, the heat pump system had the greatest reduction in GHG emissions over time and had the lowest GHG emissions over the study period in two of the four locations. If the decarbonization of electricity production continues and refrigerants with low GHG potential are widely used, the heat pump can be the HVAC system with the lowest GHG emissions in all climate zones studied.