scholarly journals MUCCnet: Munich Urban Carbon Column network

2021 ◽  
Vol 14 (2) ◽  
pp. 1111-1126
Author(s):  
Florian Dietrich ◽  
Jia Chen ◽  
Benno Voggenreiter ◽  
Patrick Aigner ◽  
Nico Nachtigall ◽  
...  

Abstract. In order to mitigate climate change, it is crucial to understand urban greenhouse gas (GHG) emissions precisely, as more than two-thirds of the anthropogenic GHG emissions worldwide originate from cities. Nowadays, urban emission estimates are mainly based on bottom-up calculation approaches with high uncertainties. A reliable and long-term top-down measurement approach could reduce the uncertainty of these emission inventories significantly. We present the Munich Urban Carbon Column network (MUCCnet), the world's first urban sensor network, which has been permanently measuring GHGs, based on the principle of differential column measurements (DCMs), since summer 2019. These column measurements and column concentration differences are relatively insensitive to vertical redistribution of tracer masses and surface fluxes upwind of the city, making them a favorable input for an inversion framework and, therefore, a well-suited candidate for the quantification of GHG emissions. However, setting up such a stationary sensor network requires an automated measurement principle. We developed our own fully automated enclosure systems for measuring column-averaged CO2, CH4 and CO concentrations with a solar-tracking Fourier transform spectrometer (EM27/SUN) in a fully automated and long-term manner. This also includes software that starts and stops the measurements autonomously and can be used independently from the enclosure system. Furthermore, we demonstrate the novel applications of such a sensor network by presenting the measurement results of our five sensor systems that are deployed in and around Munich. These results include the seasonal cycle of CO2 since 2015, as well as concentration gradients between sites upwind and downwind of the city. Thanks to the automation, we were also able to continue taking measurements during the COVID-19 lockdown in spring 2020. By correlating the CO2 column concentration gradients to the traffic amount, we demonstrate that our network is capable of detecting variations in urban emissions. The measurements from our unique sensor network will be combined with an inverse modeling framework that we are currently developing in order to monitor urban GHG emissions over years, identify unknown emission sources and assess how effective the current mitigation strategies are. In summary, our achievements in automating column measurements of GHGs will allow researchers all over the world to establish this approach for long-term greenhouse gas monitoring in urban areas.

2020 ◽  
Author(s):  
Florian Dietrich ◽  
Jia Chen ◽  
Benno Voggenreiter ◽  
Patrick Aigner ◽  
Nico Nachtigall ◽  
...  

Abstract. In order to mitigate climate change, it is crucial to understand the urban greenhouse gas (GHG) emissions precisely as more than two third of the anthropogenic GHG emissions worldwide originate from cities. Nowadays, urban emission estimates are mainly based on bottom-up calculation approaches with high uncertainties. A reliable and long-term top-down measurement approach could reduce the uncertainty of these emission inventories significantly. We present the world’s first urban sensor network that is permanently measuring GHGs based on the principle of differential column measurements (DCM) starting in summer 2019. These column measurements are relatively insensitive to vertical redistribution of tracer masses and surface fluxes upwind of the city. Therefore, they are well-suited to quantify GHG emissions. However, setting up such a stationary sensor network requires an automated measurement principle. We developed our own fully automated enclosure systems for measuring CO2, CH4 and CO column-averaged concentrations with a solar-tracking Fourier Transform spectrometer (EM27/SUN) in a fully automated and long-term manner. This includes also a software that starts and stops the measurements autonomously and can be used independently from the enclosure system. Furthermore, we demonstrate the novel applications of such a sensor network by presenting the measurement results of our five sensor systems that are deployed in and around Munich. These results include the seasonal cycle of CO2 since 2015 as well as concentration gradient measurements upwind and downwind of the city. Thanks to the automation we were also able to continue the measurements during the COVID-19 lockdown in spring 2020. By correlating the CO2 column concentration gradients to the traffic amount, we demonstrate that our network is well capable to detect variations in urban emissions. The measurements from our unique sensor network will be combined with an inverse modeling framework that we are currently developing, in order to monitor urban GHG emissions over years, identify unknown emission sources and assess how effective the current mitigation strategies are. In summary, our achievements in automating column measurements of GHGs will allow researchers all over the world to establish this novel measurement approach as a new standard for determining GHG emissions.


2017 ◽  
Vol 30 (1) ◽  
pp. 191-214 ◽  
Author(s):  
Meryl Jagarnath ◽  
Tirusha Thambiran

Because current emissions accounting approaches focus on an entire city, cities are often considered to be large emitters of greenhouse gas (GHG) emissions, with no attention to the variation within them. This makes it more difficult to identify climate change mitigation strategies that can simultaneously reduce emissions and address place-specific development challenges. In response to this gap, a bottom-up emissions inventory study was undertaken to identify high emission zones and development goals for the Durban metropolitan area (eThekwini Municipality). The study is the first attempt at creating a spatially disaggregated emissions inventory for key sectors in Durban. The results indicate that particular groups and economic activities are responsible for more emissions, and socio-spatial development and emission inequalities are found both within the city and within the high emission zone. This is valuable information for the municipality in tailoring mitigation efforts to reduce emissions and address development gaps for low-carbon spatial planning whilst contributing to objectives for social justice.


2020 ◽  
Vol 52 (1) ◽  
pp. 1
Author(s):  
Prabang Setyono ◽  
Widhi Himawan ◽  
Cynthia Permata Sari ◽  
Totok Gunawan ◽  
Sigit Heru Murti

Considered as a trigger of climate change, greenhouse gas (GHG) is a global environmental issue. The City of Surakarta in Indonesia consists mainly of urban areas with high intensities of anthropogenic fossil energy consumption and, potentially, GHG emission. It is topographically a basin area and most likely prompts a Thermal Inversion, creating a risk of accumulation and entrapment of air pollutants or GHGs at low altitudes. Vegetation has been reported to mitigate the rate of increase in emissions because it acts as a natural carbon sink. This study aimed to mitigate the GHG emissions from energy consumption in Surakarta and formulate recommendations for control. It commenced with calculating the emission factors based on the IPCC formula and determining the key categories using the Level Assessment approach. It also involved computing the vegetation density according to the NDVI values of the interpretation of Sentinel 2A imagery. The estimation results showed that in 2018, the emission loads from the energy consumption in Surakarta reached 1,217,385.05 (tons of CO2e). The key categories of these emissions were electricity consumption, transportation on highways, and the domestic sector, with transportation on highways being the top priority. These loads have exceeded the local carrying capacity because they create an imbalance between emission and natural GHG sequestration by vegetations.


2020 ◽  
Vol 10 (1) ◽  
pp. 197-208
Author(s):  
Wiktoria Loga-Księska ◽  
Justyna Sordyl ◽  
Artur Ryguła

AbstractIncreasing the number of vehicles on the road network and the growing popularity of sustainable development of urban areas have resulted in the need for implementing efficient and cost-effective traffic measurement methods. From the perspective of traffic management, up-to-date information about vehicle density and access to historical data are the key components of traffic variability analyses. Rapid technological development based on Intelligent Transport Systems (ITS) has popularised the wireless sensor networks (WSN) application. The solution enables continuous monitoring of selected area using multiple wireless and low-cost sensors connected within a network. Those systems are dynamically evolving tools for solving an effective traffic management issues in city centres and urban environments. In the study, authors have performed a traffic variability and its dynamics analysis in a selected area using a multi-sensor network for traffic volume monitoring. The article presents the results of research conducted between years 2015 - 2018 throughout the city of Bielsko-Biala with the support of OnDynamic multimodal system. Within the context of the analyses, basic traffic parameters have been determined and variability trends have been identified on selected road sections. Long-term research indicated the minor variation in a number of vehicle detections and relatively stable traffic volume in the city centre during the analysis period.


2021 ◽  
Author(s):  
Kevin Gurney ◽  
Siir Kilkis ◽  
Karen Seto ◽  
Shuaib Lwasa ◽  
Daniel Moran ◽  
...  

Projections of greenhouse gas (GHG) emissions are critical to better understanding and anticipating future climate change under different socio-economic conditions and mitigation strategies. The climate projections and scenarios assessed by the Intergovernmental Panel on Climate Change, following the Shared Socioeconomic Pathway (SSP)-Representative Concentration Pathway (RCP) framework, have provided a rich understanding of the constraints and opportunities for policy action. However, the current emissions scenarios lack an explicit treatment of urban emissions within the global context. Given the pace and scale of urbanization, with global urban populations expected to increase from about 4.4 billion today to about 7 billion by 2050, there is an urgent need to fill this knowledge gap. Here, we estimate the share of global GHG emissions emanating from urban areas from 1990 to 2100 based on the SSP-RCP framework. The urban GHG emissions are presented in five regional aggregates and are based on a combination of the urban population share, 2015 urban per capita CO2eq emissions, SSP-based national CO2eq emissions, and recent analysis of urban per capita CO2eq trends. We find that urban areas account for the majority of global GHG emissions in 2015 (61.8%). Moreover, the urban share of global GHG emissions progressively increases into the future, exceeding 80% in some scenarios by the end of the century. The combined urban areas in Asia and Developing Pacific, and Developed Countries account for 65.0% to 73.3% of cumulative urban emissions between 2020 and 2100 across the scenarios. Given these dominant roles, we describe the implications to potential urban mitigation in each of the scenario narratives in order to meet the goal of climate neutrality within this century.


2021 ◽  
Vol 1 (1) ◽  
Author(s):  
Pablo M. De Salazar ◽  
Nicholas B. Link ◽  
Karuna Lamarca ◽  
Mauricio Santillana

Abstract Background Residents of Long-Term Care Facilities (LTCFs) represent a major share of COVID-19 deaths worldwide. Measuring the vaccine effectiveness among the most vulnerable in these settings is essential to monitor and improve mitigation strategies. Methods We evaluate the early effect of the administration of BNT162b2-mRNA vaccine to individuals older than 64 years residing in LTCFs in Catalonia, Spain. We monitor all the SARS-CoV-2 documented infections and deaths among LTCFs residents once more than 70% of them were fully vaccinated (February–March 2021). We develop a modeling framework based on the relationship between community and LTCFs transmission during the pre-vaccination period (July–December 2020). We compute the total reduction in SARS-CoV-2 documented infections and deaths among residents of LTCFs over time, as well as the reduction in the detected transmission for all the LTCFs. We compare the true observations with the counterfactual predictions. Results We estimate that once more than 70% of the LTCFs population are fully vaccinated, 74% (58–81%, 90% CI) of COVID-19 deaths and 75% (36–86%, 90% CI) of all expected documented infections among LTCFs residents are prevented. Further, detectable transmission among LTCFs residents is reduced up to 90% (76–93%, 90% CI) relative to that expected given transmission in the community. Conclusions Our findings provide evidence that high-coverage vaccination is the most effective intervention to prevent SARS-CoV-2 transmission and death among LTCFs residents. Widespread vaccination could be a feasible avenue to control the COVID-19 pandemic conditional on key factors such as vaccine escape, roll out and coverage.


2020 ◽  
Vol 143 (1) ◽  
Author(s):  
Philip J. Ball

Abstract A review of conventional, unconventional, and advanced geothermal technologies highlights just how diverse and multi-faceted the geothermal industry has become, harnessing temperatures from 7 °C to greater than 350 °C. The cost of reducing greenhouse emissions is examined in scenarios where conventional coal or combined-cycle gas turbine (CCGT) power plants are abated. In the absence of a US policy on a carbon tax, the marginal abatement cost potential of these technologies is examined within the context of the social cost of carbon (SCC). The analysis highlights that existing geothermal heat and power technologies and emerging advanced closed-loop applications could deliver substantial cost-efficient baseload energy, leading to the long-term decarbonization. When considering an SCC of $25, in a 2025 development scenario, geothermal technologies ideally need to operate with full life cycle assessment (FLCA) emissions, lower than 50 kg(CO2)/MWh, and aim to be within the cost range of $30−60/MWh. At these costs and emissions, geothermal can provide a cost-competitive low-carbon, flexible, baseload energy that could replace existing coal and CCGT providing a significant long-term reduction in greenhouse gas (GHG) emissions. This study confirms that geothermally derived heat and power would be well positioned within a diverse low-carbon energy portfolio. The analysis presented here suggests that policy and regulatory bodies should, if serious about lowering carbon emissions from the current energy infrastructure, consider increasing incentives for geothermal energy development.


2020 ◽  
Author(s):  
Theresa Klausner ◽  
Mariano Mertens ◽  
Heidi Huntrieser ◽  
Michal Galkowski ◽  
Gerrit Kuhlmann ◽  
...  

<p>Urban areas are recognised as a significant source of greenhouse gas emissions (GHG), such as carbon dioxide (CO<sub>2</sub>) and methane (CH<sub>4</sub>). The total amount of urban GHG emissions, especially for CH<sub>4</sub>, however, is not well quantified. Here we report on airborne in situ measurements using a Picarro G1301-m analyser aboard the DLR Cessna Grand Caravan to study GHG emissions downwind of the German capital city Berlin. In total, five aircraft-based mass balance experiments were conducted in July 2018 within the Urban Climate Under Change [UC]<sup>2</sup> project. The detection and isolation of the Berlin plume was often challenging because of comparatively small GHG signals above variable atmospheric background concentrations. However, on July 20<sup>th</sup> enhancements of up to 4 ppm CO<sub>2</sub> and 21 ppb CH<sub>4</sub> were observed over a horizontal extent of roughly 45 to 65 km downwind of Berlin. These enhanced mixing ratios are clearly distinguishable from the background and can partly be assigned to city emissions. The estimated CO<sub>2</sub> emission flux of 1.39 ± 0.75 t s<sup>-1 </sup>is in agreement with current inventories, while the CH<sub>4</sub> emission flux of 5.20 ± 1.61 kg s<sup>-1</sup> is almost two times larger than the highest reported value in the inventories. We localized the source area with HYSPLIT trajectory calculations and the high resolution numerical model MECO(n) (down to ~1 km), and investigated the contribution from sewage-treatment plants and waste deposition to CH<sub>4</sub>, which are treated differently by the emission inventories. Our work highlights the importance of a) strong CH<sub>4</sub> sources in the surroundings of Berlin and b) a detailed knowledge of GHG inflow mixing ratios to suitably estimate emission rates.</p>


2021 ◽  
Author(s):  
Corinna Peters

This study assesses changes in mobility behaviour in the City of Barcelona due the COVID‐19pandemic and its impact on air pollution and GHG emissions. Urban transport is an important sourceof global greenhouse gas (GHG) emissions. Improving urban mobility patterns is therefore crucial formitigating climate change. This study combines quantitative survey data and official governmentdata with in‐depth interviews with public administration officials of the City. Data illustrates thatBarcelona has experienced an unprecedented reduction in mobility during the lockdown (a 90%drop) and mobility remained at comparatively low levels throughout the year 2020. Most remarkableis the decrease in the use of public transport in 2020 compared to pre‐pandemic levels, whereas roadtraffic has decreased to a lesser extent and cycling surged at times to levels up to 60% higher thanpre‐pandemic levels. These changes in mobility have led to a radical and historic reduction in airpollution, with NO2 and PM10 concentration complying with WHO guidelines in 2020. Reductions inGHG emissions for Barcelona’s transport sector are estimated at almost 250.000 t CO2eq in 2020 (7%of the City’s overall annual emissions). The study derives policy implications aimed at achieving along‐term shift towards climate‐friendlier, low‐emission transport in Barcelona, namely how torecover lost demand in public transport and seize the opportunity that the crisis brings for reform byfurther reducing road traffic and establishing a 'cycling culture' in Barcelona, as already achieved inother European cities.


2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Xin He ◽  
Shiqi Ou ◽  
Yu Gan ◽  
Zifeng Lu ◽  
Steven Victor Przesmitzki ◽  
...  

Abstract For over ten years, China has been the largest vehicle market in the world. In order to address energy security and air quality concerns, China issued the Dual Credit policy to improve vehicle efficiency and accelerate New Energy Vehicle adoption. In this paper, a market-penetration model is combined with a vehicle fleet model to assess implications on greenhouse gas (GHG) emissions and energy demand. Here we use this integrated modeling framework to study several scenarios, including hypothetical policy tweaks, oil price, battery cost and charging infrastructure for the Chinese passenger vehicle fleet. The model shows that the total GHGs of the Chinese passenger vehicle fleet are expected to peak in 2032 under the Dual Credit policy. A significant reduction in GHG emissions is possible if more efficient internal combustion engines continue to be part of the technology mix in the short term with more New Energy Vehicle penetration in the long term.


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