scholarly journals Uncertainty of hourly-average concentration values derived from non-continuous measurements

2021 ◽  
Vol 14 (5) ◽  
pp. 3561-3571
Author(s):  
László Haszpra ◽  
Ernő Prácser
Keyword(s):  
Atmospheric Transport ◽  
Spline Interpolation ◽  
Sequential Sampling ◽  
Temporal Distribution ◽  
Sampling Period ◽  
Average Concentration ◽  
Perfect Reconstruction ◽  
Monitoring Networks ◽  
Simple Arithmetic ◽  
Vertical Concentration Profile

Abstract. Continental greenhouse gas monitoring networks extensively use tall towers for higher spatial representativeness. In most cases, several intakes are built along the tower to give information also on the vertical concentration profile of the components considered. Typically, a single gas analyzer is used, and the intake points are sequentially connected to the instrument. It involves that the continuous concentration signal is only sampled for discrete short periods at each intake point, which does not allow for a perfect reconstruction of the original concentration variation. It increases the uncertainty of the calculated hourly averages usually used by the atmospheric transport and budget models. The purpose of the study is to give the data users an impression of the potential magnitude of this kind of uncertainty, as well as how it depends on the number of intakes sampled, on the length of the sampling period at each intake, on the season, and on the time of the day. It presents how much improvement can be achieved using linear or spline interpolation between the measurement periods instead of the simple arithmetic averaging of the available measurements. Although the results presented here may be site-specific, the study calls attention to the potentially rather heterogeneous spatial and temporal distribution of the uncertainty of the hourly-average concentration values derived from tall-tower measurements applying sequential sampling.

scholarly journals Uncertainty of the hourly average concentration values derived from non-continuous measurements

2020 ◽  
Author(s):  
László Haszpra ◽  
Ernő Prácser
Keyword(s):  
Spline Interpolation ◽  
Sequential Sampling ◽  
Temporal Distribution ◽  
Sampling Period ◽  
Average Concentration ◽  
Perfect Reconstruction ◽  
Monitoring Networks ◽  
Gas Analyzer ◽  
Simple Arithmetic ◽  
Vertical Concentration Profile

Abstract. Continental greenhouse gas monitoring networks extensively use tall towers for higher spatial representativeness. In most cases, several intakes are built along the tower to give information also on the vertical concentration profile of the components considered. Typically, a single gas analyzer is used, and the intake points are sequentially connected to the instrument. It involves that the continuous concentration signal is only sampled for discrete short periods at each intake points, which does not allow the perfect reconstruction of the original concentration variation. It increases the uncertainty of the calculated hourly averages usually used by the transport and budget models. The purpose of the study is to give the data users an impression on the potential magnitude of this kind of uncertainty, as well as how it depends on the number of intakes sampled, on the length of the sampling period at each intake, on the season, and on the time of the day. It presents how much improvement can be achieved using linear or spline interpolation between the measurement periods instead of the simple arithmetic averaging of the available measurements. Although the results presented here may be site-specific, the study calls attention to the potentially rather heterogeneous spatial and temporal distribution of the uncertainty of the hourly average concentration values derived from tall-tower measurements applying sequential sampling.

scholarly journals Designing optimal greenhouse gas observing networks that consider performance and cost

2014 ◽  
Vol 4 (2) ◽  
pp. 705-749
Author(s):  
D. D. Lucas ◽  
C. Yver Kwok ◽  
P. Cameron-Smith ◽  
H. Graven ◽  
D. Bergmann ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Atmospheric Transport ◽  
Pareto Frontier ◽  
Ghg Emissions ◽  
Emission Rates ◽  
Monitoring Networks ◽  
Transport Models ◽  
Hfc 134A ◽  
Scientific Accuracy ◽  
Better Than

Abstract. Emission rates of greenhouse gases (GHGs) entering into the atmosphere can be inferred using mathematical inverse approaches that combine observations from a network of stations with forward atmospheric transport models. Some locations for collecting observations are better than others for constraining GHG emissions through the inversion, but the best locations for the inversion may be inaccessible or limited by economic and other non-scientific factors. We present a method to design an optimal GHG observing network in the presence of multiple objectives that may be in conflict with each other. As a demonstration, we use our method to design a prototype network of six stations to monitor summertime emissions in California of the potent GHG 1,1,1,2-tetrafluoroethane (CH2FCF3, HFC-134a). We use a multiobjective genetic algorithm to evolve network configurations that seek to jointly maximize the scientific accuracy of the inferred HFC-134a emissions and minimize the associated costs of making the measurements. The genetic algorithm effectively determines a set of "optimal" observing networks for HFC-134a that satisfy both objectives (i.e., the Pareto frontier). The Pareto frontier is convex, and clearly shows the tradeoffs between performance and cost, and the diminishing returns in trading one for the other. Without difficulty, our method can be extended to design optimal networks to monitor two or more GHGs with different emissions patterns, or to incorporate other objectives and constraints that are important in the practical design of atmospheric monitoring networks.

scholarly journals Characterizing uncertainties in atmospheric inversions of fossil fuel CO<sub>2</sub> emissions in California

2019 ◽  
Vol 19 (5) ◽  
pp. 2991-3006 ◽  
Author(s):  
Kieran Brophy ◽  
Heather Graven ◽  
Alistair J. Manning ◽  
Emily White ◽  
Tim Arnold ◽  
...  
Keyword(s):  
Fossil Fuel ◽  
Transport Model ◽  
Atmospheric Transport ◽  
Temporal Distribution ◽  
Potential Effect ◽  
Spatial And Temporal Distribution ◽  
Transport Models ◽  
Total State ◽  
Pseudo Data ◽  
Atmospheric Inversions

Abstract. Atmospheric inverse modelling has become an increasingly useful tool for evaluating emissions of greenhouse gases including methane, nitrous oxide, and synthetic gases such as hydrofluorocarbons (HFCs). Atmospheric inversions for emissions of CO2 from fossil fuel combustion (ffCO2) are currently being developed. The aim of this paper is to investigate potential errors and uncertainties related to the spatial and temporal prior representation of emissions and modelled atmospheric transport for the inversion of ffCO2 emissions in the US state of California. We perform simulation experiments based on a network of ground-based observations of CO2 concentration and radiocarbon in CO2 (a tracer of ffCO2), combining prior (bottom-up) emission models and transport models currently used in many atmospheric studies. The potential effect of errors in the spatial and temporal distribution of prior emission estimates is investigated in experiments by using perturbed versions of the emission estimates used to create the pseudo-data. The potential effect of transport error was investigated by using three different atmospheric transport models for the prior and pseudo-data simulations. We find that the magnitude of biases in posterior total state emissions arising from errors in the spatial and temporal distribution in prior emissions in these experiments are 1 %–15 % of posterior total state emissions and are generally smaller than the 2σ uncertainty in posterior emissions. Transport error in these experiments introduces biases of −10 % to +6 % into posterior total state emissions. Our results indicate that uncertainties in posterior total state ffCO2 estimates arising from the choice of prior emissions or atmospheric transport model are on the order of 15 % or less for the ground-based network in California we consider. We highlight the need for temporal variations to be included in prior emissions and for continuing efforts to evaluate and improve the representation of atmospheric transport for regional ffCO2 inversions.

scholarly journals Modelling atmospheric transport of α-hexachlorocyclohexane in the Northern Hemispherewith a 3-D dynamical model: DEHM-POP

2004 ◽  
Vol 4 (4) ◽  
pp. 1125-1137 ◽  
Author(s):  
K. M. Hansen ◽  
J. H. Christensen ◽  
J. Brandt ◽  
L. M. Frohn ◽  
C. Geels
Keyword(s):  
Environmental Fate ◽  
Transport Model ◽  
Atmospheric Transport ◽  
Model Simulation ◽  
Model Development ◽  
Average Concentration ◽  
The Arctic ◽  
Atmospheric Concentration ◽  
Surface Exchange ◽  
Exchange Processes

Abstract. The Danish Eulerian Hemispheric Model (DEHM) is a 3-D dynamical atmospheric transport model originally developed to describe the atmospheric transport of sulphur into the Arctic. A new version of the model, DEHM-POP, developed to study the atmospheric transport and environmental fate of persistent organic pollutants (POPs) is presented. During environmental cycling, POPs can be deposited and re-emitted several times before reaching a final destination. A description of the exchange processes between the land/ocean surfaces and the atmosphere is included in the model to account for this multi-hop transport. The α-isomer of the pesticide hexachlorocyclohexane (α-HCH) is used as tracer in the model development. The structure of the model and processes included are described in detail. The results from a model simulation showing the atmospheric transport for the years 1991 to 1998 are presented and evaluated against measurements. The annual averaged atmospheric concentration of α-HCH for the 1990s is well described by the model; however, the shorter-term average concentration for most of the stations is not well captured. This indicates that the present simple surface description needs to be refined to get a better description of the air-surface exchange processes of POPs.

scholarly journals Characterizing Uncertainties in Atmospheric Inversions of Fossil Fuel CO<sub>2</sub> Emissions in California

2018 ◽  
Author(s):  
Kieran Brophy ◽  
Heather Graven ◽  
Alistair J. Manning ◽  
Emily White ◽  
Tim Arnold ◽  
...  
Keyword(s):  
Fossil Fuel ◽  
Transport Model ◽  
Atmospheric Transport ◽  
Temporal Distribution ◽  
Temporal Variations ◽  
Potential Effect ◽  
Spatial And Temporal Distribution ◽  
Transport Models ◽  
Pseudo Data ◽  
Atmospheric Inversions

Abstract. Atmospheric inverse modelling has become an increasingly useful tool for evaluating emissions of greenhouse gases including methane, nitrous oxide and synthetic gases such as hydrofluorocarbons (HFCs). Atmospheric inversions for emissions of CO2 from fossil fuel combustion (ffCO2) are currently being developed. The aim of this paper is to investigate potential errors and uncertainties related to the spatial and temporal prior representation of emissions and modelled atmospheric transport for the inversion of ffCO2 emissions in the U.S. state of California. We perform simulation experiments based on a network of ground-based observations of CO2 concentration and radiocarbon in CO2 (a tracer of ffCO2), combining prior (bottom-up) emission models and transport models currently used in many atmospheric studies. The potential effect of errors in the spatial and temporal distribution of prior emission estimates is investigated in experiments by using perturbed versions of the emissions estimates used to create the pseudo data. The potential effect of transport error was investigated by using three different atmospheric transport models for the prior and pseudo data simulations. We find that the magnitude of biases in posterior state-total emissions arising from errors in the spatial and temporal distribution in prior emissions in these experiments are 1–15 % of posterior state-total emissions, and generally smaller than the 2-σ uncertainty in posterior emissions. Transport error in these experiments introduces biases of −10 % to +6 % in posterior state-total emissions. Our results indicate that uncertainties in posterior state-total ffCO2 estimates arising from the choice of prior emissions or atmospheric transport model are on the order of 15 % or less for the ground-based network in California we consider. We highlight the need for temporal variations to be included in prior emissions, and for continuing efforts to evaluate and improve the representation of atmospheric transport for regional ffCO2 inversions.

scholarly journals Population biology and distribution of the tanaid Kalliapseudes schubarti Mañé-Garzon, 1949, in an intertidal flat in Southeastern Brazil

2003 ◽  
Vol 63 (3) ◽  
pp. 469-479 ◽  
Author(s):  
F. P. P. Leite ◽  
A. Turra ◽  
E. C. F. Souza
Keyword(s):  
Population Biology ◽  
Temporal Distribution ◽  
Sampling Period ◽  
Positive Influence ◽  
Southeastern Brazil ◽  
Life Strategy ◽  
Intertidal Flat ◽  
Sediment Layer ◽  
High Fecundity ◽  
Seasonal Oscillation

The population biology and the spatial and temporal distribution of Kalliapseudes schubarti Mañé-Garzon, 1949, a common tanaidacean in mud flats and estuaries in southern and southeastern Brazil, was studied in the Araçá region, São Sebastião (SP), Brazil. This species showed a clustered dispersion in the area and the individuals were concentrated in the superficial sediment layer (5 cm). Higher densities of K. schubarti were recorded in areas characterized by moderately sorted fine sediment. Multiple regression analysis revealed a positive influence of the organic matter contents and a negative effect of the silt-clay contents on the abundance of K. schubarti. This species showed a marked temporal variation with very low abundance in winter and fall (March to August). Sexual dimorphism was evidenced with males being larger than females. Ovigerous females were also larger than pre-ovigerous ones. Sex ratio was skewed towards females. Seven cohorts were identified during the sampling period, the estimated longevity was 12 months, and no seasonal oscillation in growth was evidenced. The continuous reproduction, as evidenced by the presence of larval phases (manca II and neutron) and reproductive females throughout the year, and high fecundity among the tanaids associated with fast growth and limited longevity support the case for the opportunistic life strategy suggested for this species in the literature.

scholarly journals Measurement report: Spatiotemporal and policy-related variations of PM<sub>2.5</sub> composition and sources during 2015–2019 at multiple sites in a Chinese megacity

2021 ◽  
Vol 21 (21) ◽  
pp. 16219-16235
Author(s):  
Xinyao Feng ◽  
Yingze Tian ◽  
Qianqian Xue ◽  
Danlin Song ◽  
Fengxia Huang ◽  
...  
Keyword(s):  
Air Quality ◽  
Spatial Clustering ◽  
Sampling Period ◽  
Temporal Variations ◽  
Average Concentration ◽  
Biomass Combustion ◽  
Industrial Emissions ◽  
Traffic Emission ◽  
Average Percentage ◽  
Layer 2

Abstract. A thorough understanding of the relationship between urbanization and PM2.5 (fine particulate matter with aerodynamic diameter less than 2.5 µm) variation is crucial for researchers and policymakers to study health effects and improve air quality. In this study, we selected a rapidly developing Chinese megacity, Chengdu, as the study area to investigate the spatiotemporal and policy-related variations of PM2.5 composition and sources based on long-term observation at multiple sites. A total of 836 samples were collected from 19 sites in winter 2015–2019. According to the specific characteristics, 19 sampling sites were assigned to three layers. Layer 1 was the most urbanized area and referred to the core zone of Chengdu, layer 2 was located in the outer circle of layer 1, and layer 3 belonged to the outermost zone with the lowest urbanization level. The average PM2.5 concentrations for 5 years were in the order of layer 2 (133 µg m−3) > layer 1 (126 µg m−3) > layer 3 (121 µg m−3). Spatial clustering of the chemical composition at the sampling sites was conducted for each year. The PM2.5 composition of layer 3 in 2019 was found to be similar to that of the other layers 2 or 3 years ago, implying that urbanization levels had a strong effect on air quality. During the sampling period, a decreasing trend was observed for the annual average concentration of PM2.5, especially at sampling sites in layer 1, where the stricter control policies were implemented. The SO42-/NO3- mass ratio at most sites exceeded 1 in 2015 but dropped to less than 1 since 2016, reflecting decreasing coal combustion and increasing traffic impacts in Chengdu, and these values can be further supported by temporal variations of the SO42- and NO3- concentrations. The positive matrix factorization (PMF) model was applied to quantify PM2.5 sources. A total of five sources were identified, with average contributions of 15.5 % (traffic emissions), 19.7 % (coal and biomass combustion), 8.8 % (industrial emissions), 39.7 % (secondary particles), and 16.2 % (resuspended dust). From 2015 to 2019, a dramatic decline was observed in the average percentage contributions of coal and biomass combustion, but the traffic emission source showed an increasing trend. For spatial variations, the high coefficient of variation (CV) values of coal and biomass combustion and industrial emissions indicated their higher spatial difference in Chengdu. High contributions of resuspended dust occurred at sites with intensive construction activities, such as subway and airport construction. Combining the PMF results, we developed the source-weighted potential source contribution function (SWPSCF) method for source localization. This new method highlighted the influences of spatial distribution for source contributions, and the effectiveness of the SWPSCF method was evaluated.

scholarly journals Spatial-Temporal Distribution and Insecticide resistance Status of Aedes Aegypti in Ghana

2021 ◽  
Author(s):  
Christopher Mfum Owusu-Asenso ◽  
Julius Abraham Addo Mingle ◽  
David Weetman ◽  
Yaw Asare Afrane
Keyword(s):  
Insecticide Resistance ◽  
Vector Control ◽  
Rural Areas ◽  
Temporal Distribution ◽  
Sampling Period ◽  
Detailed Knowledge ◽  
Phenotypic Resistance ◽  
Ecological Zones ◽  
Spatio Temporal ◽  
Study Sites

Abstract Background: Vector control is the main intervention to control arboviral diseases transmitted by Aedes mosquitoes because for most there are no effective vaccines or treatment. This vector control relies heavily on the use of insecticides, effectiveness of which may be impacted by resistance. In addition, rational insecticide application requires detailed knowledge of vector distribution, dynamics, resting, and feeding behaviours, which are poorly understood for Aedes vectors in Africa. This study investigated the spatio-temporal distribution and insecticide resistance status of Ae. aegypti from across ecological extremes of GhanaMethods: Immature mosquitoes were sampled from containers in and around human dwellings at each of seven study sites in urban, suburban, and rural areas of Ghana. Adult Aedes mosquitoes were sampled indoor and outdoor using Biogent sentinel-2 mosquito traps, human landing catches, and prokopack aspiration. Distributions of immatures and adult Aedes mosquitoes were determined indoors and outdoors during dry and rainy seasons at all sites. Phenotypic resistance status of Aedes mosquitoes to insecticides was determined using WHO bioassays. Host blood meal source was determined by PCR.Results: A total of 16,711 immature Aedes were sampled, with over 70% found in car tires. Significantly more breeding containers had Aedes immatures during the rainy season 70.95% (11,856) compared to the dry season 29.05% (4,855). A total of 1,895 adult Aedes mosquitos were collected, including Ae. aegypti (97.8%), Ae. africanus (2.1%) and Ae. Luteocephalus (0.1%). Indoor sampling of adult Aedes mosquitoes yielded a total of 381 (20.1%) and outdoor a total of 1,514 (79.9%) (z = -5.427; p = 0.0000) over the entire sampling period. Aedes aegypti populations were resistant to DDT at all study sites. Vectors showed suspected resistance to Bendiocarb (96-97%), Permethrin (90-96%) and Deltamethrin (91-96%) and were susceptible to the organophosphate malathion from all study sites.Blood meal analysis showed that the Aedes mosquitoes were mostly anthropophilic with HBI of 0.9 i.e. [(human = 90%), (human and dog = 5%), (dog and cow = 5%)].Conclusion: Aedes mosquitoes were found at high densities in all ecological zones of Ghana. Resistance to pyrethroids and carbamates may limit control efficacy and requires careful monitoring.

scholarly journals Global Surface HCHO Distribution Derived from Satellite Observations with Neural Networks Technique

2021 ◽  
Vol 13 (20) ◽  
pp. 4055
Author(s):  
Jian Guan ◽  
Bohan Jin ◽  
Yizhe Ding ◽  
Wen Wang ◽  
Guoxiang Li ◽  
...  
Keyword(s):  
Neural Networks ◽  
Confidence Intervals ◽  
Amazon Basin ◽  
Surface Concentration ◽  
Average Concentration ◽  
Monitoring Networks ◽  
Vertical Column ◽  
Atmospheric Pollutant ◽  
Surface Distribution ◽  
Global Surface

Formaldehyde (HCHO) is one of the most important carcinogenic air contaminants in outdoor air. However, the lack of monitoring of the global surface concentration of HCHO is currently hindering research on outdoor HCHO pollution. Traditional methods are either restricted to small areas or, for research on a global scale, too data-demanding. To alleviate this issue, we adopted neural networks to estimate the 2019 global surface HCHO concentration with confidence intervals, utilizing HCHO vertical column density data from TROPOMI, and in-situ data from HAPs (harmful air pollutants) monitoring networks and the ATom mission. Our results show that the global surface HCHO average concentration is 2.30 μg/m3. Furthermore, in terms of regions, the concentrations in the Amazon Basin, Northern China, South-east Asia, the Bay of Bengal, and Central and Western Africa are among the highest. The results from our study provide the first dataset on global surface HCHO concentration. In addition, the derived confidence intervals of surface HCHO concentration add an extra layer of confidence to our results. As a pioneering work in adopting confidence interval estimation to AI-driven atmospheric pollutant research and the first global HCHO surface distribution dataset, our paper paves the way for rigorous study of global ambient HCHO health risk and economic loss, thus providing a basis for pollution control policies worldwide.

scholarly journals Designing optimal greenhouse gas monitoring networks for Australia

2016 ◽  
Vol 5 (1) ◽  
pp. 1-15 ◽  
Author(s):  
T. Ziehn ◽  
R. M. Law ◽  
P. J. Rayner ◽  
G. Roff
Keyword(s):  
Network Design ◽  
Greenhouse Gas ◽  
Atmospheric Transport ◽  
Dispersion Model ◽  
Network Size ◽  
Particle Dispersion ◽  
Data Uncertainty ◽  
Monitoring Networks ◽  
Modelling Framework ◽  
Reverse Mode

Abstract. Atmospheric transport inversion is commonly used to infer greenhouse gas (GHG) flux estimates from concentration measurements. The optimal location of ground-based observing stations that supply these measurements can be determined by network design. Here, we use a Lagrangian particle dispersion model (LPDM) in reverse mode together with a Bayesian inverse modelling framework to derive optimal GHG observing networks for Australia. This extends the network design for carbon dioxide (CO2) performed by Ziehn et al. (2014) to also minimise the uncertainty on the flux estimates for methane (CH4) and nitrous oxide (N2O), both individually and in a combined network using multiple objectives. Optimal networks are generated by adding up to five new stations to the base network, which is defined as two existing stations, Cape Grim and Gunn Point, in southern and northern Australia respectively. The individual networks for CO2, CH4 and N2O and the combined observing network show large similarities because the flux uncertainties for each GHG are dominated by regions of biologically productive land. There is little penalty, in terms of flux uncertainty reduction, for the combined network compared to individually designed networks. The location of the stations in the combined network is sensitive to variations in the assumed data uncertainty across locations. A simple assessment of economic costs has been included in our network design approach, considering both establishment and maintenance costs. Our results suggest that, while site logistics change the optimal network, there is only a small impact on the flux uncertainty reductions achieved with increasing network size.

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