This document summarizes the Carbosense4D project, which aims to monitor CO2 emissions in Zurich using a low-cost sensor network. Over 200 low-cost CO2 sensors have been deployed throughout Zurich to measure CO2 concentrations. The sensors require calibration and correction for drift. Initial results show the influence of biospheric CO2 fluxes even in urban Zurich. Atmospheric modelling is also being used and shows potential after improvements to vertical mixing and emission inputs. Future work involves further sensor deployment and data improvement, model refinement integrating sensor data, and developing a city-scale model to estimate CO2 emissions.
Green House Gas and Automatic Weather Station data analysis. We compare seasonal variation of CO2 & CH4 vs Wind Speed and Wind direction. How to analyze wind rose diagram.
Second SC5 Pilot: Identifying the Release Location of a SubstanceBigData_Europe
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Green House Gas and Automatic Weather Station data analysis. We compare seasonal variation of CO2 & CH4 vs Wind Speed and Wind direction. How to analyze wind rose diagram.
Second SC5 Pilot: Identifying the Release Location of a SubstanceBigData_Europe
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On 15th October 2013 geo.admin.ch, the geoportal of the Swiss Confederation has achieved the 2nd place in the EuroCloud Award 2013 in the category of «Best Cloud Service Use Case Public Sector» (the award ceremony took place in the context of the EuroCloud Congress in Luxembourg on October 15th 2013). This award honors the most innovative cloud solution characterized by originality, innovation, creativity and efficiency.
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Geodata Processing and Webservices with Python and AzureAndré Zehnder
Python can be used not only for geoprocessing but also for web services. In this short talk for GeoPython 2019 we at EBP show you how to compute isochrones and make them available through an API.
About the potential of novel, alternative rain sensors, such as microwave links (MWL) used for telecommunication, crowd sensing, or cheap ubiquitous sensors.
An Open Solution for Next-generation Real-time Power System SimulationSteffen Vogel
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Building Science-Heat exchange analysis of residential buildingShyam Anandjiwala
The thermal performance of a building refers to the process of modelling the energy transfer between a building and its surroundings. For a conditioned building, it estimates the heating and cooling load and hence, the sizing and selection of HVAC equipment can be correctly made. For a non-conditioned building, it calculates temperature variation inside the building over a specified time and helps one to estimate the duration of uncomfortable periods. These quantifications enable one to determine the effectiveness of the design of a building and help in evolving improved designs for realising energy efficient buildings with comfortable indoor conditions. The lack of proper quantification is one of the reasons why passive solar architecture is not popular among architects. Clients would like to know how much energy might be saved, or the temperature reduced to justify any additional expense or design change. Architects too need to know the relative performance of buildings to choose a suitable alternative. Thus, knowledge of the methods of estimating the performance of buildings is essential to the design of passive solar buildings.
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On 15th October 2013 geo.admin.ch, the geoportal of the Swiss Confederation has achieved the 2nd place in the EuroCloud Award 2013 in the category of «Best Cloud Service Use Case Public Sector» (the award ceremony took place in the context of the EuroCloud Congress in Luxembourg on October 15th 2013). This award honors the most innovative cloud solution characterized by originality, innovation, creativity and efficiency.
Final Presentation given at the conclusion of the 2018 IMSM by the US EPA Student Working Group.
Group Members: Elizabeth Herman, Jeonghwa Lee, Kartik Lovekar, Dorcas Ofori-Boateng, Fatemeh Norouzi, Benazir Rowe and Jianhui Sun
Statistical Technique in Gas Dispersion Modeling Based on Linear InterpolationTELKOMNIKA JOURNAL
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Advanced weather forecasting for RES applications: Smart4RES developments tow...Leonardo ENERGY
Recording at: https://youtu.be/45Zpjog95QU
This is the 3rd Smart4RES webinar that will address technological and market challenges in RES prediction and will introduce the Smart4RES strategy to improve weather forecasting models with high resolution.
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Innovatie estafette DEMO Consultants - TNO- Gemeente Rotterdam - 2013DEMOConsultants
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3. 3ICOS Science Conference 2018, Prague, 11-13 Sep 2018 | dominik.brunner@empa.ch
Project Carbosense4D (www.carbosense.ch)
Goals:
Determine CO2 emissions of the city of Zurich over multiple years
Enhance understanding of biospheric CO2 fluxes over Switzerland
Describe accurately the 4-D evolution of CO2 over Switzerland
Learn about sensor networks
sensor integration and characterization
network setup and operation
communication and data processing
Quality Assurance & Quality Control
low-cost
sensors
low-cost
network=
5. 5ICOS Science Conference 2018, Prague, 11-13 Sep 2018 | dominik.brunner@empa.ch
Sensor calibration and characterization
CO2 sensors respond to temperature, pressure, humidity
Multi-factor model using Beer-Lambert’s law applied to IR detector output
CO2 (350 – 1000 ppm)
T (-5°C – 50°C)
CO2 (400 – 900 ppm)
p (770 – 1050 hPa), T
Climate chamber Pressure chamber
CO2, T, RH
Ambient measurements
6. 6ICOS Science Conference 2018, Prague, 11-13 Sep 2018 | dominik.brunner@empa.ch
First year of operation of low-cost LP8 sensors in Zurich
10-17 Jul 2017
Sensors not stable enough for accurate long-term measurements
Frequent recalibration too demanding
13-20 Aug 2018
Can we correct for drifts while sensors are in operation?
7. 7ICOS Science Conference 2018, Prague, 11-13 Sep 2018 | dominik.brunner@empa.ch
Operational sensor data processing
Outlier removal
specifying valid operating range
accounting for sensor drift and ageing
Including
outliers
Outliers
removed
T (°C) T (°C)
-log(IR)
-log(IR)
Sensor drift adjustment
using periods of strong winds
(> 2 m s-1 during at least 1 h)
July 2017 Aug 2018
CO2adjustment[ppm]
8. 8ICOS Science Conference 2018, Prague, 11-13 Sep 2018 | dominik.brunner@empa.ch
Before drift correction
Sensor drift adjustment
July 2017 Aug 2018
Offset relative to nearby accurate sensor
CO2adjustment[ppm]Operational sensor data processing
Periods of strong winds
After drift correction
9. 9ICOS Science Conference 2018, Prague, 11-13 Sep 2018 | dominik.brunner@empa.ch
Amplitude of diurnal variation
July 2018
Jan 2018
10. 10ICOS Science Conference 2018, Prague, 11-13 Sep 2018 | dominik.brunner@empa.ch
CO2 modelling with COSMO-GHG
Weather prediction model COSMO with GHG tracer extension
Domain centered over Switzerland, 1 km x 1 km resolution, 60 levels
Highly efficient code, fully ported to GPUs
CO2-boundary conditions
Global CO2 model CAMS
(ECMWF, experiment ghqy)
Emissions
TNO/MACC-3 (Europe) +
CarboCount (Switzerland)
Biosphere fluxes
VPRM (MPI Jena)
11. 11ICOS Science Conference 2018, Prague, 11-13 Sep 2018 | dominik.brunner@empa.ch
Animation of anthropogenic CO2 in last week of Oct 2017
12. 12ICOS Science Conference 2018, Prague, 11-13 Sep 2018 | dominik.brunner@empa.ch
Comparison with observations, Oct 2017
Beromünster, rural, 212 m a.g.l. Dübendorf, suburban, 4 m a.g.l
CO2CO2
anthrop.
biospheric
background
RESP x 4, GPP x 2
T T
Wind speedWind speed
Too strong vertical mixing,
surface not sufficiently
decoupled from higher levels
model
observations
13. 13ICOS Science Conference 2018, Prague, 11-13 Sep 2018 | dominik.brunner@empa.ch
Conclusions and outlook
Conclusions
First year of data from ~200 LP8 sensors, HPP just starting
Approx. accuracy: Picarro 0.1 ppm, HPP 1.0 ppm, LP8 10 ppm
Strong contribution from biosphere even in Zurich
First model results encouraging, areas of improvement identified
Outlook
Sensors: Deployment of HPPs, further improvement of LP8 data
Model: Meteo data assimilation, PBL mixing, online emissions & VPRM
Integration of model and sensor data:
Use model as transfer standard between Picarro/HPP and LP8
Geostatistical modeling of differences COSMO-GHG and sensor data
Further develop city-scale model with final goal of estimating emissions
14. 14ICOS Science Conference 2018, Prague, 11-13 Sep 2018 | dominik.brunner@empa.ch O. Wehrli 2013
With a special thanks to
Swisscom, MeteoSwiss, UGZ Zurich, NABEL and others
for generous support of our sensor network
Markus Leuenberger (University of Bern) for Beromünster CO2 observations
Christoph Gerbig (MPI Jena)
for VPRM data
Copernicus Atmospheric Monitoring Service (CAMS)
for global CO2 model data
Funding through Swiss Data Science Center (SDSC) and EU / Eurostars