Changes in speciated PM2.5 concentrations in Fresno, California, due to NOx reductions and variations in diurnal emission profiles by day of week

Abstract

The San Joaquin Valley in California suffers from poor air quality due to a combination of local emissions and weak ventilation. Over the course of decades, there has been a concerted effort to control emissions from vehicles as well as from residential wood burning. A multiple linear regression model was used to evaluate the trends in air pollution over multiple time scales: by year, by season, by day of the week and by time of day. The model was applied to 18 years of measurements in Fresno including hourly mole fractions of NOx and concentrations of PM2.5; and daily measurements of speciated components of PM2.5. The analysis shows that there have been reductions in NOx, elemental carbon and ammonium nitrate of 4 to 6%/year. On weekends, NOx mole fractions are reduced by 15 to 30% due to fewer vehicle miles traveled and a smaller fraction of diesel traffic. These weekend reductions in NOx have not been accompanied by weekend reductions in PM2.5 however. In particular, elemental and organic carbon concentrations are higher on winter weekends. Analysis of diurnal profiles suggests that this is because of increased PM2.5 on Saturday and holiday evenings which are likely due to residential wood combustion. Furthermore, while organic carbon concentrations have decreased in the winter months, they have been variable but without a net decline in the summer, most likely as a result of forest fires offsetting other improvements in air quality. Fog was found to greatly enhance ammonium nitrate formation and was therefore associated with higher PM2.5 in the winter months. Overall the analysis shows that air quality controls have been effective at reducing NOx all year and PM2.5 in the winter, that continued reductions in emissions will further reduce pollutant concentrations, but that winter residential wood combustion and summer forest fires could offset some of the gains obtained.

Quantitative estimation of meteorological impacts and the COVID-19 lockdown reductions on NO2 and PM2.5 over the Beijing area using Generalized Additive Models (GAM)

“…The types of functions for temporal variables characterized the change of emissions and the types of functions for meteorology characterized the relationship between meteorology and air quality. The selections of function type for interannual, seasonal, weekly, diurnal and meteorology were referenced from some previous studies ( Zhou et al, 2012 ; de Foy, 2018 ; de Foy and Schauer, 2019 ) and were also tested for the Beijing area in our recent study ( Hua et al, 2021b ). The interannual variable used a linear trend to characterize the decline in air pollutant concentrations.…”

“…The meteorological candidates include 24-hr cumulative of P and 24-hr running average of RH, T2M, D2M, and SP from ERA5, ISD, and BJ, respectively. This was done to cancel out the diurnal variability of climatology such as the BLH rise, which began in the morning and reached a maximum in the afternoon ( Chu et al, 2019 ; Mehta et al, 2017 ), so that the diurnal profiles of GAM results would be closer to the emissions changes ( de Foy and Schauer, 2019 ; Wang et al, 2020a ). Meteorological parameters were linearly scaled to approximate a normal distribution of zero mean and unit standard deviation to reduce the effects of extreme observations, hence, their impacts on average baseline concentrations were close to 0.…”

“…The results can be interpreted in three ways ( de Foy and Schauer, 2019 ). The time vectors (such as ) with values of 1 represent during the time interval and values of 0 represent the other time intervals, namely baseline conditions.…”

Competing PM2.5 and NO2 holiday effects in the Beijing area vary locally due to differences in residential coal burning and traffic patterns

“…It is mainly due to changes in behavior from working on weekdays to resting on weekends. In the megacities of US, Europe, Japan, and Russia, air pollution weekend effects were identified by ground measurements and remote sensing, usually showing reductions of up to 50% or more during the weekends compared with weekdays ( Beirle et al, 2003 ; de Foy et al, 2016a ; de Foy and Schauer, 2019 ; Elansky et al, 2020 ; Marr and Harley, 2002 ; Motallebi et al, 2003 ). For the weekly cycle of Beijing, China, ozone (O 3 ) has been reported to have a clear weekly periodical variation with a maximum on weekends ( Wang et al, 2013 ; Zhao et al, 2019 ).…”

“…In general, the most relevant factors, such as time vectors and meteorological parameters, are used to identify the impact on PM 2.5 and NO 2 concentrations. MLR was applied to estimate temporal profiles of NO x emissions in Chicago ( de Foy, 2018 ), the variation of ozone, NO x and PM 2.5 in Fresno ( de Foy et al, 2020 ; de Foy and Schauer, 2019 ), the variations of NO 2 columns in China and American cities ( de Foy et al, 2016a ; de Foy et al, 2016b ). The non-linear model GAM was used to assess changes of OMI NO 2 columns over Europe ( Zhou et al, 2012 ).…”