CalEnviroScreen — client.calenviroscreen5 / client.calenviroscreen4

CalEnviroScreen cumulative impact scores by census tract — pollution burden, population characteristics, and the overall CI score, plus the disadvantaged-community (SB 535) designation. Two versions are exposed as separate resources; there’s no bare/default client.calenviroscreen, so a future CalEnviroScreen 6.0 doesn’t have to fight over what the short name means.

from sjvair import SJVAirClient

with SJVAirClient() as client:
    tract5 = client.calenviroscreen5.get('06019000100')
    tract4 = client.calenviroscreen4.get('06019000100', year=2020)

CalEnviroScreen 5.0 — client.calenviroscreen5

Method	Signature
list(**params)	Iterate scored tracts. Single-vintage dataset (2020 census tracts) — no year filter.
get(tract)	A single tract’s full indicator set.

CES5 adds zipcode, approx_loc, county, and region_name fields, plus a wider set of pollution/population-characteristic sub-indicators than CES4:

# Every tract in Fresno County above the median for the small agricultural-tox-sites indicator
tracts = list(client.calenviroscreen5.list(
    region_id='r6phe',
    pol_small_ats_p__gte=50,
))

Filters happen server-side, not client-side — pass region_id, dac_sb535 (boolean — SB 535 disadvantaged-community designation), dac_category, and __gt/__gte/__lt/__lte on any score field.

CalEnviroScreen 4.0 — client.calenviroscreen4

Method	Signature
list(year=None, **params)	Iterate scored tracts. year defaults server-side to 2020 if omitted.
get(tract, year=None)	A single tract’s full indicator set.

{
    "tract": "06019000100",
    "census_year": 2020,
    "population": 3842,
    "ci_score": 62.4,
    "ci_score_p": 84.0,
    "dac_sb535": True,
    "pollution": 71.2,
    "pol_ozone": 0.058,
    "pol_pm": 12.9,
    "pol_diesel": 38.4,
    "popchar": 55.6,
    "char_asthma": 84.3,
    "char_pov": 41.2,
    "pop_hispanic": 2891,
    # ...plus every other CalEnviroScreen indicator (pol_*, char_*, pop_*)
}

# Every tract in Fresno County in the top quartile for pollution burden
tracts = list(client.calenviroscreen4.list(
    year=2020,
    region_id='r6phe',
    pollution_p__gte=75,
))

Same filter conventions as CES5: region_id, dac_sb535, dac_category, and __gt/__gte/__lt/__lte on ci_score, ci_score_p, popchar_p, pol_pm_p, pol_ozone_p, pol_diesel_p, and pol_traffic_p.