US 12,031,967 B2
Emissions detection system and methods
Nathan C. Eichenlaub, Denver, CO (US); Kieran J. Lynn, Denver, CO (US); William J. Foiles, Denver, CO (US); and Jason D. Clark, Fort Lupton, CO (US)
Assigned to Project Canary, PBC, Denver, CO (US)
Filed by Project Canary, PBC, Denver, CO (US)
Filed on Oct. 3, 2023, as Appl. No. 18/376,259.
Application 18/376,259 is a continuation of application No. 17/813,602, filed on Jul. 19, 2022, granted, now 11,774,426.
Application 18/376,259 is a continuation of application No. 17/813,585, filed on Jul. 19, 2022, granted, now 11,802,860.
Claims priority of provisional application 63/323,703, filed on Mar. 25, 2022.
Prior Publication US 2024/0027415 A1, Jan. 25, 2024
This patent is subject to a terminal disclaimer.
Int. Cl. G01N 33/00 (2006.01); G01D 21/02 (2006.01)
CPC G01N 33/0062 (2013.01) [G01D 21/02 (2013.01); G01N 33/0031 (2013.01); G01N 2033/0068 (2013.01)] 24 Claims
OG exemplary drawing
 
1. A total emissions quantification method for quantifying emissions of a target substance at a site, the total emissions quantification method comprising:
providing a first air quality monitor comprising:
a first sensor responsive to the target substance; and
a first location at which the first air quality monitor is located on the site;
measuring a first set of onsite parameters with the first air quality monitor over a period of time to obtain a plurality of individual measurements, the plurality of individual measurements comprising:
a first measured substance concentration of the target substance measured with the first air quality monitor; and
a first set of individual atmospheric readings;
transmitting the first set of onsite parameters to a first server;
procuring a regional atmospheric parameter for the site from a second server;
training a prediction model associated with the first air quality monitor, by:
generating a plurality of first predicted substance concentrations of the target substance corresponding to the first air quality monitor;
obtaining over a predefined period at a predefined frequency, the plurality of first predicted substance concentrations and the plurality of individual measurements of the first set of onsite parameters;
generating a mapping of a weighted mean of the plurality of first predicted substance concentrations grouped in each wind-direction bucket of a predetermined number of wind-direction buckets, wherein the predetermined number of wind-direction buckets together are representative of wind directions in a full circle; and
obtaining a location map of a plurality of emission sources at the site, the location map comprising:
a location and an identity associated with each of the plurality of emission sources;
generating a simulated plume model for each emission source of the plurality of emission sources with a wind-direction;
calculating a plurality of representative circular normal distributions for each air quality monitor, using the simulated plume model, by:
setting a plurality of presumed flux values to the simulated plume model;
analyzing the plurality of representative circular normal distributions in relation with the mapping of the weighted mean to identify:
a relevant representative circular normal distribution from the plurality of representative circular normal distributions,
wherein the relevant representative circular normal distribution is indicative of a target emission source from the plurality of emission sources; and
quantifying a total emission of the target substance at the site by aggregating the plurality of emission sources.