 |
| Titel |
Designing optimal greenhouse gas observing networks that consider performance and cost |
| VerfasserIn |
D. D. Lucas, C. Yver Kwok, P. Cameron-Smith, H. Graven, D. Bergmann, T. P. Guilderson, R. Weiss, R. Keeling |
| Medientyp |
Artikel
|
| Sprache |
Englisch
|
| ISSN |
2193-0856
|
| Digitales Dokument |
URL |
| Erschienen |
In: Geoscientific Instrumentation, Methods and Data Systems ; 4, no. 1 ; Nr. 4, no. 1 (2015-06-16), S.121-137 |
| Datensatznummer |
250115240
|
| Publikation (Nr.) |
 copernicus.org/gi-4-121-2015.pdf |
|
|
|
|
|
| Zusammenfassung |
| 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. |
| |
|
| Teil von |
|
|
|
|
|
|
|
|