scholarly journals Sensitivity to the sources of uncertainties in the modeling of atmospheric CO<sub>2</sub> concentration within and in the vicinity of Paris

2021 ◽  
Vol 21 (13) ◽  
pp. 10707-10726
Author(s):  
Jinghui Lian ◽  
François-Marie Bréon ◽  
Grégoire Broquet ◽  
Thomas Lauvaux ◽  
Bo Zheng ◽  
...  
Keyword(s):  
Boundary Conditions ◽  
Co2 Emissions ◽  
Vertical Mixing ◽  
Co2 Concentration ◽  
Atmospheric Modeling ◽  
Inversion Method ◽  
Model Data ◽  
Co2 Concentrations ◽  
Paris Area ◽  
The City

Abstract. The top-down atmospheric inversion method that couples atmospheric CO2 observations with an atmospheric transport model has been used extensively to quantify CO2 emissions from cities. However, the potential of the method is limited by several sources of misfits between the measured and modeled CO2 that are of different origins than the targeted CO2 emissions. This study investigates the critical sources of errors that can compromise the estimates of the city-scale emissions and identifies the signal of emissions that has to be filtered when doing inversions. A set of 1-year forward simulations is carried out using the WRF-Chem model at a horizontal resolution of 1 km focusing on the Paris area with different anthropogenic emission inventories, physical parameterizations, and CO2 boundary conditions. The simulated CO2 concentrations are compared with in situ observations from six continuous monitoring stations located within Paris and its vicinity. Results highlight large nighttime model–data misfits, especially in winter within the city, which are attributed to large uncertainties in the diurnal profile of anthropogenic emissions as well as to errors in the vertical mixing near the surface in the WRF-Chem model. The nighttime biogenic respiration to the CO2 concentration is a significant source of modeling errors during the growing season outside the city. When winds are from continental Europe and the CO2 concentration of incoming air masses is influenced by remote emissions and large-scale biogenic fluxes, differences in the simulated CO2 induced by the two different boundary conditions (CAMS and CarbonTracker) can be of up to 5 ppm. Nevertheless, our results demonstrate the potential of our optimal CO2 atmospheric modeling system to be utilized in atmospheric inversions of CO2 emissions over the Paris metropolitan area. We evaluated the model performances in terms of wind, vertical mixing, and CO2 model–data mismatches, and we developed a filtering algorithm for outliers due to local contamination and unfavorable meteorological conditions. Analysis of model–data misfit indicates that future inversions at the mesoscale should only use afternoon urban CO2 measurements in winter and suburban measurements in summer. Finally, we determined that errors related to CO2 boundary conditions can be overcome by including distant background observations to constrain the boundary inflow or by assimilating CO2 gradients of upwind–downwind stations rather than by assimilating absolute CO2 concentrations.

scholarly journals Quantitative evaluation of the uncertainty sources for the modeling of atmospheric CO<sub>2</sub> concentration within and in the vicinity of Paris city

2020 ◽  
Author(s):  
Jinghui Lian ◽  
François-Marie Bréon ◽  
Grégoire Broquet ◽  
Bo Zheng ◽  
Michel Ramonet ◽  
...  
Keyword(s):  
Boundary Conditions ◽  
Co2 Emissions ◽  
Large Scale ◽  
Transport Model ◽  
Co2 Concentration ◽  
Inversion Method ◽  
Different Boundary Conditions ◽  
Paris Area ◽  
The City ◽  
Atmospheric Inversion

Abstract. The top-down atmospheric inversion method that couples atmospheric CO2 observations with an atmospheric transport model has been used extensively to quantify CO2 emissions from cities. However, the potential of the method is limited by several sources of misfits between the measured and modeled CO2 that are of different origins than the targeted CO2 emissions. This study investigates the critical sources of errors that can compromise the estimates of the city-scale emissions and identifies the signal of emissions that has to be filtered when doing inversions. A set of one-year forward simulations is carried out using the WRF-Chem model at a horizontal resolution of 1 km focusing on the Paris area with different anthropogenic emission inventories, physical parameterizations and CO2 boundary conditions. The simulated CO2 concentrations are compared with in situ observations from six continuous monitoring stations located within Paris and its vicinity. Results highlight large nighttime observation-model misfits, especially in winter within the city, which are attributed to large uncertainties in the diurnal profile of anthropogenic emissions as well as to errors in the vertical mixing near the surface in the WRF-Chem model. The nighttime biogenic respiration to the CO2 concentration is a significant source of modeling errors during the growing season outside the city. When winds are from continental Europe and the CO2 concentration of incoming air masses is influenced by remote emissions and large-scale biogenic fluxes, differences in the simulated CO2 induced by the two different boundary conditions (CAMS and CarbonTracker) can be of up to 5 ppm. Our results suggest three selection criteria for the CO2 data to be assimilated for the inversion of CO2 emissions from Paris (i) discard data that appear as statistical outliers in the model-data misfits which are interpreted as model's deficiencies under complex meteorological conditions; (ii) use only afternoon urban measurements in winter and suburban ones in summer; (iii) test the influence of different boundary conditions in inversions. If possible, using additional observations to constrain the boundary inflow, or using CO2 gradients of upwind-downwind stations, rather than absolute CO2 concentration, as atmospheric inversion inputs.

scholarly journals Konsentrasi Co2 Pada Ruang Kelas Dengan Sistem Ventilasi Alami, Tipe Jendela Gantung Atas

2018 ◽  
Vol 1 (1) ◽  
pp. 137-144
Author(s):  
Basaria Talarosha ◽  
Valencia Rosardy
Keyword(s):  
Natural Ventilation ◽  
Co2 Concentration ◽  
Learning Performance ◽  
Opening Angle ◽  
The Public ◽  
Public Elementary Schools ◽  
Co2 Concentrations ◽  
Size Number ◽  
Window Opening ◽  
The City

Proses pernafasan menghasilkan udara yang mengandung 4,4% volume CO2 sehingga konsentrasi CO2 di dalam ruang kelas dapat menjadi lebih tinggi dari ruang luar jika ventilasi tidak mencukupi. Konsentrasi CO2 > 1000 ppm akan mengganggu kesehatan dan konsentrasi belajar yang berdampak pada penurunan performa belajar siswa. Penelitian sebelumnya menunjukkan adanya hubungan antara konsentrasi CO2 di dalam ruang kelas dengan ukuran, jumlah, posisi dan tipe jendela pada ruang kelas yang menggunakan sistem ventilasi alami. Tipe jendela gantung atas disebutkan memiliki performa yang paling buruk dalam menetralkan konsentrasi CO2 di dalam ruang. Studi bermaksud mengukur kadar konsentrasi CO2 di dalam sebuah ruang kelas pada salah satu sekolah dasar negeri di kota Medan yang menggunakan tipe jendela gantung atas. Pengukuran konsentrasi CO2 dilakukan pada kondisi sudut bukaan jendela sisi koridor ruang kelas 10 dan 30 masing -masing selama tiga (3) hari. Hasil studi menunjukkan konsentrasi CO2 maksimum pada kondisi sudut bukaan jendela 10 lebih rendah dari pada kondisi sudut bukaan jendela 30LI, namun konsentrasi CO2 rata-rata pada kedua posisi jendela masih di bawah ambang batas konsentrasi CO2 yang diijinkan untuk kesehatan (<1000 ppm).   The breathing process produces air containing 4.4% of the volume of CO2 so that the concentration of CO2 in the classroom can be higher than the outside space if there is insufficient ventilation. CO2 concentration> 1000 ppm will interfere with the health and concentration of learning which has an impact on decreasing student learning performance. Previous research has shown a correlation between CO2 concentrations in classrooms with the size, number, position and type of windows in classrooms that use natural ventilation systems. The upper hanging window type is said to have the worst performance in neutralizing CO2 concentrations in space. The study intends to measure the level of CO2 concentration in a classroom in one of the public elementary schools in the city of Medan that uses a type of upper hanging window. Measurements of CO2 concentrations were carried out at the corridor opening angle of the class 10 and 30 for three (3) days, respectively. The results showed that the maximum CO2 concentration at the window opening angle 10 was lower than the 30LI window opening, but the average CO2 concentration in both window positions was still below the threshold of the permissible CO2 concentration for health (<1000 ppm).

Assessing the effectiveness of an urban CO2 monitoring network through the COVID-19 lockdown natural experiment

2021 ◽  
Author(s):  
Jinghui Lian ◽  
Thomas Lauvaux ◽  
Hervé Utard ◽  
Grégoire Broquet ◽  
François-Marie Bréon ◽  
...  
Keyword(s):  
Real Time ◽  
Co2 Emissions ◽  
Transport Model ◽  
Monitoring Network ◽  
Co2 Concentration ◽  
Mitigation Measures ◽  
Potential Contribution ◽  
Activity Data ◽  
Co2 Monitoring ◽  
The City

&lt;p&gt;Quantitative monitoring of CO2 sources and sinks over cities is needed to support the urban adaptation and mitigation measures, but it is a challenging task. The Paris metropolitan area is a highly built-up and densely populated region in France. The two national COVID-19 forced confinements that are 1) effective on March 17th, with a duration of 55 days until May 11th, 2) effective on October 30th, with a duration of 46 days until December 15th provide an opportunity to assess the behaviour and robustness of the dedicated atmospheric inversion system for estimating the city-scale CO2 emissions.&lt;/p&gt;&lt;p&gt;In this study, the atmospheric Bayesian inversion approach that couples six in-situ continuous CO2 monitoring stations with the WRF-Chem transport model at 1-km horizontal resolutions has been used to quantify the impacts of lockdown on CO&lt;sub&gt;2&lt;/sub&gt; emissions for the Paris megacity. The prior emission estimate was from the Origins inventory, a near-real-time dataset of fossil fuel CO2 emissions by sector (transportation, residential, tertiary, industry and sink) at 1km&amp;#178; and hourly resolution recently developed by Origins.earth. Estimates of CO2 emissions were retrieved from the inversion by assimilating CO2 concentration gradients between upwind-downwind stations using a refined configuration of the existing Parisian inversion system developed by Br&amp;#233;on et al. (2015) and Staufer et al. (2016). A set of experiments was performed to assess the sensitivity of the posterior CO2 estimates to the changes in different inversion setups, including the selection of observations, prior flux uncertainties and error correlations. We also analyzed the potential contribution of the expanding CO2 monitoring network, in particular the two newly built urban stations in the city center since 2014, to the inverse modeling systems.&lt;/p&gt;&lt;p&gt;The optimized CO2 estimates show decreases of around 42% and 25% in anthropogenic CO2 emissions during the first and second lockdowns respectively when compared with the same period in past two years. Both lockdown emission reduction estimates from the inversion are consistent with recent estimates from activity data (resp. 37% and 19%), suggesting that our near-real time monitoring system is able to detect and quantify short-term variations at the whole-city level.&lt;/p&gt;

scholarly journals Dynamics of global atmospheric CO<sub>2</sub> concentration from 1850 to 2010: a linear approximation

2014 ◽  
Vol 11 (9) ◽  
pp. 13957-13983 ◽  
Author(s):  
W. Wang ◽  
R. Nemani
Keyword(s):  
Co2 Emissions ◽  
Co2 Concentration ◽  
Atmospheric Co2 ◽  
Box Model ◽  
Modeling Framework ◽  
Elevated Atmospheric Co2 ◽  
Atmospheric Co2 Concentration ◽  
Co2 Concentrations ◽  
Anthropogenic Co2 ◽  
Atmospheric Co2 Concentrations

Abstract. The increase in anthropogenic CO2 emissions largely followed an exponential path between 1850 and 2010, and the corresponding increases in atmospheric CO2 concentration were almost constantly proportional to the emissions by the so-called "airborne fraction". These observations suggest that the dynamics of atmospheric CO2 concentration through this time period may be properly approximated as a linear system. We demonstrate this hypothesis by deriving a linear box-model to describe carbon exchanges between the atmosphere and the surface reservoirs under the influence of disturbances such as anthropogenic CO2 emissions and global temperature changes. We show that the box model accurately simulates the observed atmospheric CO2 concentrations and growth rates across interannual to multi-decadal time scales. The model also allows us to analytically examine the dynamics of such changes/variations, linking its characteristic disturbance-response functions to bio-geophysically meaningful parameters. In particular, our results suggest that the elevated atmospheric CO2 concentrations have significantly promoted the gross carbon uptake by the terrestrial biosphere. However, such "fertilization" effects are partially offset by enhanced carbon release from surface reservoirs promoted by warmer temperatures. The result of these interactions appears to be a decline in net efficiency in sequestering atmospheric CO2 by ∼30% since 1960s. We believe that the linear modeling framework outlined in this paper provides a convenient tool to diagnose the observed atmospheric CO2 dynamics and monitor their future changes.

scholarly journals Atmospheric inversion for cost effective quantification of city CO<sub>2</sub> emissions

2015 ◽  
Vol 15 (21) ◽  
pp. 30693-30756 ◽  
Author(s):  
L. Wu ◽  
G. Broquet ◽  
P. Ciais ◽  
V. Bellassen ◽  
F. Vogel ◽  
...  
Keyword(s):  
Co2 Emissions ◽  
Land Surface ◽  
Power Plants ◽  
Energy Use ◽  
Residential Buildings ◽  
Co2 Concentration ◽  
Road Transport ◽  
Inversion Method ◽  
Atmospheric Measurements ◽  
Atmospheric Inversion

Abstract. Cities, currently covering only a very small portion (< 3 %) of the world's land surface, directly release to the atmosphere about 44 % of global energy-related CO2, and are associated with 71–76 % of CO2 emissions from global final energy use. Although many cities have set voluntary climate plans, their CO2 emissions are not evaluated by Monitoring, Reporting and Verification (MRV) procedures that play a key role for market- or policy-based mitigation actions. Here we propose a monitoring tool that could support the development of such procedures at the city scale. It is based on an atmospheric inversion method that exploits inventory data and continuous atmospheric CO2 concentration measurements from a network of stations within and around cities to estimate city CO2 emissions. We examine the cost-effectiveness and the performance of such a tool. The instruments presently used to measure CO2 concentrations at research stations are expensive. However, cheaper sensors are currently developed and should be useable for the monitoring of CO2 emissions from a megacity in the near-term. Our assessment of the inversion method is thus based on the use of several types of hypothetical networks, with a range of numbers of sensors sampling at 25 m a.g.l. The study case for this assessment is the monitoring of the emissions of the Paris metropolitan area (~ 12 million inhabitants and 11.4 Tg C emitted in 2010) during the month of January 2011. The performance of the inversion is evaluated in terms of uncertainties in the estimates of total and sectoral CO2 emissions. These uncertainties are compared to a notional ambitious target to diagnose annual total city emissions with an uncertainty of 5 % (2-sigma). We find that, with 10 stations only, which is the typical size of current pilot networks that are deployed in some cities, the uncertainty for the 1-month total city CO2 emissions is significantly reduced by the inversion by ~ 42 % but still corresponds to an annual uncertainty that is two times larger than the target of 5 %. By extending the network from 10 to 70 stations, the inversion can meet this requirement. As for major sectoral CO2 emissions, the uncertainties in the inverted emissions using 70 stations are reduced significantly over that obtained using 10 stations by 32 % for commercial and residential buildings, by 33 % for road transport and by 18 % for the production of energy by power plants, respectively. With 70 stations, the uncertainties from the inversion become of 15 % 2-sigma annual uncertainty for dispersed building emissions, and 18 % for emissions from road transport and energy production. The inversion performance could be further improved by optimal design of station locations and/or by assimilating additional atmospheric measurements of species that are co-emitted with CO2 by fossil fuel combustion processes with a specific signature from each sector, such as carbon monoxide (CO). Atmospheric inversions based on continuous CO2 measurements from a large number of cheap sensors can thus deliver a valuable quantification tool for the monitoring and/or the verification of city CO2 emissions (baseline) and CO2 emission reductions (commitments).

scholarly journals Modeling of Atmospheric Carbon Dioxide (CO2) Concentrations as a Function of Fossil-Fuel and Land-Use Change CO2 Emissions Coupled with Oceanic and Terrestrial Sequestration

Climate ◽  
2020 ◽  
Vol 8 (5) ◽  
pp. 61
Author(s):  
John P. O’Connor
Keyword(s):  
Carbon Dioxide ◽  
Land Use ◽  
Land Use Change ◽  
Co2 Emissions ◽  
Fossil Fuel ◽  
Co2 Concentration ◽  
Fuel Combustion ◽  
Full Time ◽  
Fossil Fuel Combustion ◽  
Co2 Concentrations

In this work, a semi-empirical relationship of carbon dioxide emissions with atmospheric CO2 concentrations has been developed that is capable of closely replicating observations from 1751 to 2018. The analysis was completed using data from fossil-fuel-based and land-use change based CO2 emissions, both singly and together. Evaluation of emissions data from 1750 to 1890 yields a linear CO2 concentration component that may be attributed to the net flux from land-use changes combined with a rapidly varying component of the terrestrial sink. This linear component is then coupled across the full-time period with a CO2 concentration calculation using fossil-fuel combustion/cement production emissions with a single, fixed fossil-fuel combustion airborne fraction [AFFF] value that is determined by the ocean sink coupled with the remaining slowly varying component of the land sink. The analysis of the data shows that AFFF has remained constant at 51.3% over the past 268 years. However, considering the broad range of variables including emission and sink processes influencing the climate, it may not be expected that a single value for AFFF would accurately reproduce the measured changes in CO2 concentrations during the industrial era.

scholarly journals Relation between CO2 emissions and crude oil combustion in Iraq

2021 ◽  
Vol 30 (3) ◽  
pp. 379-387
Author(s):  
Ahmed Hassan ◽  
Hasan Azeez
Keyword(s):  
Carbon Dioxide ◽  
Crude Oil ◽  
Co2 Emissions ◽  
Carbon Dioxide Emissions ◽  
Co2 Concentration ◽  
Annual Data ◽  
Co2 Concentrations ◽  
Starting Point ◽  
The World ◽  
Analysis Center

Fossil fuel is the main source for CO2 emissions that causes global warming. This fact is the starting point for this paper, that consider on three different sources of data: crude oil used to calculate CO2 emissions for Iraq for the period from 1980 to 2018; annual data of total CO2 emissions available from the Carbon Dioxide Information Analysis Center (CDIAC) for Iraq and the world for the period from 1980 to 2014; and CO2 concentrations for Iraq for the period from 2002 to 2006 and for the world for the period from 1980 to 2018. The result is a multifaceted according to the dataset sources. Carbon dioxide emissions calculated from Iraqi crude oil was increased from 1.29 Mt in 2012 to 1.97 Mt in 2018. The world and Iraq CO2 emissions with different slop of average line that was 0.5 for world, 0.003 for Iraq, while increased exponential function from 2008 to 2014 to reach 36 and 0.17 Mt, respectively. The highest value of Iraqi CO2 concentration was 403 ppm in 2016, while the global CO2 concentrations slowly increased with slop line equal to 1.75 ppm per year, from minimum value of 338.6 ppm was in 1980, while maximum value of 407.05 ppm was in 2018, that’s mean no decreased in CO2 concentration unless emissions addressed.

scholarly journals Assessment of Urban CO2 Measurement and Source Attribution in Munich Based on TDLAS-WMS and Trajectory Analysis

Atmosphere ◽  
2020 ◽  
Vol 11 (1) ◽  
pp. 58 ◽  
Author(s):  
Lijuan Lan ◽  
Homa Ghasemifard ◽  
Ye Yuan ◽  
Stephan Hachinger ◽  
Xinxu Zhao ◽  
...  
Keyword(s):  
Co2 Emissions ◽  
Urban Areas ◽  
Anthropogenic Activities ◽  
Co2 Concentration ◽  
Tunable Diode Laser ◽  
Cavity Surface ◽  
Emission Sources ◽  
Source Attribution ◽  
The North ◽  
Co2 Concentrations

Anthropogenic carbon dioxide (CO2) emissions mainly come from cities and their surrounding areas. Thus, continuous measuring of CO2 in urban areas is of great significance to studying human CO2 emissions. We developed a compact, precise, and self-calibrated in-situ CO2/H2O sensor based on TDLAS (tunable diode laser absorption spectroscopy), WMS (wavelength modulation spectroscopy), and VCSEL (vertical-cavity surface-emitting laser). Multi-harmonic detection is utilized to improve the precision of both measurements to 0.02 ppm for CO2 and 1.0 ppm for H2O. Using the developed sensor, we measured CO2 concentrations continuously in the city center of Munich, Germany, from February 2018 to January 2019. Urban CO2 concentrations are strongly affected by several factors, including vegetation photosynthesis and respiration (VPR), planetary boundary layer (PBL) height, and anthropogenic activities. In order to further understand the anthropogenic contribution in terms of CO2 sources, the HySPLIT (Hybrid Single-Particle Lagrangian Integrated Trajectory) model was applied to calculate six-hour backward trajectories. We analyzed the winter CO2 with the trajectory clustering, PSCF (potential source contribution function), and CWT (concentration weighted trajectory) methods, and found that local emissions have a great impact on urban CO2 concentration, with main emission sources in the north and southeast directions of the measurement site. In situations with an uneven trajectory distribution, PSCF proves somewhat superior in predicting the potential emission sources compared to CWT.

scholarly journals An attempt at estimating Paris area CO<sub>2</sub> emissions from atmospheric concentration measurements

2015 ◽  
Vol 15 (4) ◽  
pp. 1707-1724 ◽  
Author(s):  
F. M. Bréon ◽  
G. Broquet ◽  
V. Puygrenier ◽  
F. Chevallier ◽  
I. Xueref-Remy ◽  
...  
Keyword(s):  
Urban Area ◽  
Co2 Emissions ◽  
Transport Model ◽  
Atmospheric Transport ◽  
Co2 Concentration ◽  
Surface Fluxes ◽  
Atmospheric Concentration ◽  
Paris Area ◽  
Direct Model ◽  
Concentration Measurements

Abstract. Atmospheric concentration measurements are used to adjust the daily to monthly budget of fossil fuel CO2 emissions of the Paris urban area from the prior estimates established by the Airparif local air quality agency. Five atmospheric monitoring sites are available, including one at the top of the Eiffel Tower. The atmospheric inversion is based on a Bayesian approach, and relies on an atmospheric transport model with a spatial resolution of 2 km with boundary conditions from a global coarse grid transport model. The inversion adjusts prior knowledge about the anthropogenic and biogenic CO2 fluxes from the Airparif inventory and an ecosystem model, respectively, with corrections at a temporal resolution of 6 h, while keeping the spatial distribution from the emission inventory. These corrections are based on assumptions regarding the temporal autocorrelation of prior emissions uncertainties within the daily cycle, and from day to day. The comparison of the measurements against the atmospheric transport simulation driven by the a priori CO2 surface fluxes shows significant differences upwind of the Paris urban area, which suggests a large and uncertain contribution from distant sources and sinks to the CO2 concentration variability. This contribution advocates that the inversion should aim at minimising model–data misfits in upwind–downwind gradients rather than misfits in mole fractions at individual sites. Another conclusion of the direct model–measurement comparison is that the CO2 variability at the top of the Eiffel Tower is large and poorly represented by the model for most wind speeds and directions. The model's inability to reproduce the CO2 variability at the heart of the city makes such measurements ill-suited for the inversion. This and the need to constrain the budgets for the whole city suggests the assimilation of upwind–downwind mole fraction gradients between sites at the edge of the urban area only. The inversion significantly improves the agreement between measured and modelled concentration gradients. Realistic emissions are retrieved for two 30-day periods and suggest a significant overestimate by the AirParif inventory. Similar inversions over longer periods are necessary for a proper evaluation of the optimised CO2 emissions against independent data.

scholarly journals Effects of Climatic Conditions, Season and Environmental Factors on CO2 Concentrations in Naturally Ventilated Primary Schools in Chile

2021 ◽  
Vol 13 (8) ◽  
pp. 4139
Author(s):  
Muriel Diaz ◽  
Mario Cools ◽  
Maureen Trebilcock ◽  
Beatriz Piderit-Moreno ◽  
Shady Attia
Keyword(s):  
Air Quality ◽  
Indoor Air Quality ◽  
Indoor Air ◽  
Primary Schools ◽  
Co2 Concentration ◽  
Building Design ◽  
Climatic Conditions ◽  
Indoor Environmental Quality ◽  
Co2 Concentrations ◽  
The Impact

Between the ages of 6 and 18, children spend between 30 and 42 h a week at school, mostly indoors, where indoor environmental quality is usually deficient and does not favor learning. The difficulty of delivering indoor air quality (IAQ) in learning facilities is related to high occupancy rates and low interaction levels with windows. In non-industrialized countries, as in the cases presented, most classrooms have no mechanical ventilation, due to energy poverty and lack of normative requirements. This fact heavily impacts the indoor air quality and students’ learning outcomes. The aim of the paper is to identify the factors that determine acceptable CO2 concentrations. Therefore, it studies air quality in free-running and naturally ventilated primary schools in Chile, aiming to identify the impact of contextual, occupant, and building design factors, using CO2 concentration as a proxy for IAQ. The monitoring of CO2, temperature, and humidity revealed that indoor air CO2 concentration is above 1400 ppm most of the time, with peaks of 5000 ppm during the day, especially in winter. The statistical analysis indicates that CO2 is dependent on climate, seasonality, and indoor temperature, while it is independent of outside temperature in heated classrooms. The odds of having acceptable concentrations of CO2 are bigger when indoor temperatures are high, and there is a need to ventilate for cooling.

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