airmosaic-ai

XQuery Patterns: Price and Quantity

Market Rows

Market rows represent GCAM Marketplace transactions. Each market has a price and supply quantity:

for $s in collection()/scenario[@name = "{scenario}"]
for $m in $s/world/Marketplace/market[number(@year) = $years
  and string(MarketRegion) = $regions
  and string(MarketGoodOrFuel) = $sectors]
let $outUnit := string(($m/Info/Pair[Key = "output-unit"]/Value)[1])
let $priceUnit := string(($m/Info/Pair[Key = "price-unit"]/Value)[1])
return string-join((
  string($s/@name), "marketplace", string($m/MarketRegion),
  string($m/MarketGoodOrFuel), string($m/@year),
  string($m/price), string($m/supply),
  $outUnit, $priceUnit
), "	")

Sector Cost Rows

Sector cost represents the department-level service price:

for $s in collection()/scenario[@name = "{scenario}"]
for $r in $s/world/*[@type = "region" and string(@name) = $regions]
for $sec in $r/*[@type = "sector" and string(@name) = $sectors]
for $cost in $sec/cost[number(@year) = $years]
let $quantity := string(sum($sec//*[@type = "output"]/physical-output[@vintage = $cost/@year]/number(.)))
let $outUnit := string((
  $sec//*[@type = "output"]/physical-output[@vintage = $cost/@year]/@unit,
  $sec//*[@type = "output"]/physical-output/@unit
)[1])
where string($cost) != ""
return string-join((
  string($s/@name), "sector_cost", string($r/@name),
  string($sec/@name), string($cost/@year),
  string($cost), $quantity, $outUnit
), "	")

Key Fields

Field	Source	Meaning
scenario	$s/@name	scenario identifier
source	“marketplace” or “sector_cost”	origin of the row
region	region name	province or China aggregate
sector	sector/market name	what is being measured
year	@year or @vintage	model year
price	cost/text() or price/text()	unit price in model units
quantity	sum of physical-output	physical output in model units
output_unit	from output-unit	unit of physical output
price_unit	from price-unit or marketplace info	unit of price

Aggregation

Province-level rows can be aggregated by computing weighted prices:

weighted_price = sum(price_i * quantity_i) / sum(quantity_i)

Or for China-reported (non-provincial) rows, use the value directly.

National total quantity = sum of all province quantities.

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