Climate impact on ambient PM 2.5 elemental concentration in the - - PowerPoint PPT Presentation

Climate impact on ambient PM2.5 elemental concentration in the United States: a trend analysis over the last 30 years

Weeberb Requia, Iny Jhun, Brent Coull, Petros Koutrakis Harvard University June, 2019 HSPH/MIT ACE Center – RD83587201

Back Background und

• Weather impacts on the chemical composition of PM2.5 varies

significantly over space and time

• Diversity of particle components and the complex mechanisms

governing particle formation and removal

Temperature

Ob Obje jectives

• We quantified the impacts of climate change on ambient PM2.5

composition and levels in the US.

• Specifically, we performed a trend analysis based on a large temporal

datasets of PM2.5 species concentrations and weather over the last 30 years.

Ai Air q quality a and w weather d data c col

• llection
• n
• We evaluated the impacts of weather changes on seven major

components of ambient PM2.5, including elemental carbon (EC),

• rganic carbon (OC), nitrate, sulfate, sodium (Na+), ammonium, and

silicon.

• Daily air pollution data for the period 1988 and 2017 were obtained

from the US Environmental Protection Agency (EPA)

• Meteorological data were provided by the National Oceanic

Atmospheric Administration’s National Climatic Data Center (NOAA)

• temperature
• wind speed
• relative humidity

St Statistical a analysis

• Step 1:
• Past weather changes in ground-level temperature, wind speed, and relative

humidity

• Step 2:
• Weather-related increases in air pollution

General linear regression model GAM models Analyses were stratified by season (warm and cold) and regions Warm season (May – October); Cold season (November – April)

Based on the National Mortality Air Pollution Study by HEI

St Statistical ana nalysis

(step 2: Weather-related increases in air pollution)

§ Adjusted model:

Y = α + β!"#$%&'" %&'( + γ month + σ weekdays + s( temp + s) ws + s* rh + e

§ Unadjusted model: Y = α + β$+!"#$%&'" %&'( + γ month + σ weekdays + e

• While the weather impact is incorporated into the unadjusted trends, the adjustment with

weather variables in model 1 removes the impact of inter-annual weather variation on air pollution trends.

• We considered that any differences between the unadjusted and weather-adjusted trends

are entirely attributable to the impact of long-term weather changes.

St Statistical ana nalysis

(step 2: Weather-related increases in air pollution)

β!"#$%&'" and β$(!"#$%&'" values to quantify past weather-related increases β$(!"#$%&'" − β!"#$%&'"

“Weather penalties”

A positive penalty (β$(!"#$%&'" > β!"#$%&'") suggests that an increase in species p of PM2.5 is associated with long-term weather changes in 1988-2017.

St Statistical ana nalysis

(step 2: Weather-related increases in air pollution)

• Bootstrap analysis to estimate standard error
• Meta-analysis.

Adjusted Unadjusted Penalties

Re Results (w (weath ther tr trends) )

• Temperature increased in four regions:
• Industrial Midwest (IM) and North East (NE) during the warm and cold season
• Upper Midwest (UM) and West (W) only in the cold season.
• NE was the region with the highest increases in the study period (1988-2017).
• annual increase of 0.036 ºC (95% CI: 0.035; 0.037) during the warm season
• annual increase of 0.031 ºC (95% CI: 0.030; 0.032) during cold season
• Wind speed decreased in all regions (both warm and cold seasons), except in

the SW region during the cold season.

• Trends of relative humidity varied significantly by season and region
• During the warm season, relative humidity increased in most regions. Only the West

Coast regions (NW and W) exhibited decreases in relative humidity.

Spatial distribution of weather penalties for each ch speci cies of PM2.

2.5, r

, region ( n (and na nd nationa nal me meta-an analy alysis is), an and seas ason in in 1988 – 2017 2017

Note: unit of the scale of the bar charts (µg/m3).

Re Results (Tot

• tal

al weath ther penalty alty betw tween 1988 an and 2017)

Cold season

• EC: 0.037 µg/m3 (95%CI: 0.019 ; 0.055)
• OC: 0.19 µg/m3 (95%CI: 0.16; 0.22)
• Nitrate: 0.056 µg/m3 (95%CI: 0.048 ; 0.064 )
• Sulfate: 0.04 µg/m3 (95%CI: 0.003 ; 0.06)
• Sodium: -0.011 µg/m3 (95%CI: -0.004;-0.017 )
• Ammonium: -0.024 µg/m3 (95%CI:-0.017;-0.066)
• Silicon: 0.020 µg/m3 (95%CI: 0.012 ; 0.028)

Warm season

• EC: 0.036 µg/m3 (95%CI: 0.032 ; 0.039)
• OC: 0.21 µg/m3 (95%CI: 0.15 ; 0.24)
• Nitrate: 0.039 µg/m3 (95%CI: 0.001; 0.08)
• Sulfate: 0.35 µg/m3 (95%CI: 0.20; 0.47)
• Sodium: -0.014 µg/m3 (95%CI:-0.017;-0.010 )
• Ammonium: 0.074 µg/m3 (95%CI:0.04; 0.19 )
• Silicon: 0.026 µg/m3 (95%CI: 0.023 ; 0.028 )

Co Conclusio nclusions ns

• Ambient PM2.5 components are strongly linked to weather variables

such as temperature, relative humidity, and wind conditions.

• Our findings suggest that weather changes over the last 30 years

increased the ambient concentration of most PM2.5 components in the US.