Toxic metal concentrations and Cu–Zn–Pb isotopic compositions in tires

Background Particles from non-exhaust emissions derived from traffic activities are a dominant cause of toxic metal pollution in urban environments. Recently, studies applying multiple isotope values using the Iso-source and positive matrix factorization (PMF) models have begun to be used as useful tools to evaluate the contribution of each pollution source in urban environments. However, data on the metal concentrations and isotopic compositions of each potential source are lacking. Therefore, this study presents data on toxic metals and Cu, Zn, and Pb isotopic compositions in tires, which are one of the important non-exhaust emission sources. Findings Among the toxic metals, Zn had the highest concentration in all tire samples, and the mean concentrations were in the order of Zn > Cu > Pb > Sn > Sb > Ni > Cr > As > Cd. Ni, Zn, Sn, and Sb had higher concentrations in domestic tires (South Korea), and the Cu, Cd, and Pb concentrations were relatively higher in imported tires. The mean values of δ65CuAE647, δ66ZnIRMM3702, and 206Pb/207Pb ranged from − 1.04 to − 0.22‰, − 0.09 to − 0.03‰, and 1.1242 to 1.1747, respectively. The concentrations and isotopic compositions of Cu and Pb in the tires showed large differences depending on the product and manufacturer. However, the differences in Zn concentration and δ66ZnIRMM3702 values were very small compared with those of Cu and Pb. The relationships of the Zn concentration and isotopic composition showed that domestic tires are clearly distinguishable from imported tires. Bi-plots of Cu, Zn, and Pb isotopic compositions indicated that tires can be clearly discriminated from natural-origin and other non-exhaust traffic emission sources. Conclusions The multi-isotope signatures of Cu, Zn, and Pb exhibited different isotopic values for other non-exhaust traffic emission sources than for tires, and application of the multi-isotope technique may be a powerful method for distinguishing and managing non-exhaust sources of metal contamination in urban environments.

Contributions of Traffic and Industrial Emission Reductions to the Air Quality Improvement after the Lockdown of Wuhan and Neighboring Cities Due to COVID-19

Wuhan was locked down from 23 January to 8 April 2020 to prevent the spread of the novel coronavirus disease 2019 (COVID-19). Both public and private transportation in Wuhan and its neighboring cities in Hubei Province were suspended or restricted, and the manufacturing industry was partially shut down. This study collected and investigated ground monitoring data to prove that the lockdowns of the cities had significant influences on the air quality in Wuhan. The WRF-CMAQ (Weather Research and Forecasting-Community Multiscale Air Quality) model was used to evaluate the emission reduction from transportation and industry sectors and associated air quality impact. The results indicate that the reduction in traffic emission was nearly 100% immediately after the lockdown between 23 January and 8 February and that the industrial emission tended to decrease by about 50% during the same period. The industrial emission further deceased after 9 February. Emission reduction from transportation and that from industry was not simultaneous. The results imply that the shutdown of industry contributed significantly more to the pollutant reduction than the restricted transportation.

Does Lockdown Improve Air Quality? Evidence from the blockade policy of county-level units in Hubei Province, China

Background The COVID-19 posed a great threat to the health of people all over the world. In response to the outbreak of COVID-19, Wuhan implemented the blockade policy on January 23, 2020. Subsequently, other cities in Hubei responded one after another. The flow of people, production and consumption activities were greatly reduced, and air pollution in some cities was obviously improved. Method We used the daily air pollution and weather data of 103 county-level units in Hubei Province from 2019 to 2020 to test whether the blockade policy affected the air quality. The method of regression discontinuity designs is adopted. And the blockade policy implemented by the government during COVID-19 is regarded as exogenous policy impact, so as to investigate whether the blockade policy will affect the air quality. Results (1) Lockdown has indeed brought about an improvement in air quality. During the lockdown period, the AQI decreased by 15.316%, and the concentrations of four air pollutants (PM10, NO2, PM2.5 and SO2) decreased by 19.607%, 12.395%, 11.448% and 1.278% respectively. (2) The improvement of air quality brought about by the blockade policy is not sustainable, and every index rebounded again about 30 days after lockdown. (3) RD estimation found that the concentrations of AQI, PM2.5, PM10 and NO2 decreased by 35.402%, 29.207%, 14.809% and 7.751% respectively. This is consistent with the change trend of the above results, but the change range is obviously larger than the previous one. Conclusion Although the study confirmed that most pollutant indexes decreased during the lockdown period, the blockade policy is not applicable to the prevention and improvement of air pollution. We put forward the policy suggestions from the following two aspects: Firstly, promote green travel and reduce traffic emission sources. Secondly, promote end-of-pipe governance and improve emission reduction efficiency.

Influence of Vehicle Traffic Emissions on Spatial Variation of Ozone and its Precursors in Air of Port Harcourt City, Nigeria

This study aimed at assessing the influence of vehicle traffic on spatial variation of ozone (O3) and its vehicular emission precursors in the air of Port Harcourt city. Sampling was carried out in ten (10) sites, eight (8) located within the high traffic density area (study sites) and two (2) located within the very low traffic density area (reference sites). The precursor pollutants measured were nitrogen dioxide (NO2), carbon monoxide (CO) and volatile organic compounds (VOCSs). Ozone and the precursor pollutants were measured in situ using AeroQUAL 500 series portable ambient air analyzer while traffic flow survey was achieved by direct counting. Measurements were carried out at morning, evening and off-peak traffic periods respectively. The mean concentrations of ozone and the precursor pollutants were significantly higher (p = 0.05) in the study sites than in the reference sites. Mean concentrations were higher at peak traffic periods than at off-peak traffic periods except for ozone that was higher at off-peak than at morning peak. There was significant correlation between traffic density and each of the pollutants including ozone. The spatial variability in concentration of pollutants was influenced by vehicular traffic. VOCs and NO2 levels were higher than the National Ambient Air Quality Standard (NAAQS) limit of 0.05 ppm and 0.04 – 0.06 ppm respectively, O3 concentration was below the standard limit (0.06 ppm) but was at the verge of exceeding. Traffic emission within the city was significant and could be mitigated through regular monitoring and control.

Measurement report: Spatiotemporal and policy-related variations of PM_2.5 composition and sources during 2015–2019 at multiple sites in a Chinese megacity

A thorough understanding of the relationship between urbanization and PM2.5 (fine particulate matter with aerodynamic diameter less than 2.5 µm) variation is crucial for researchers and policymakers to study health effects and improve air quality. In this study, we selected a rapidly developing Chinese megacity, Chengdu, as the study area to investigate the spatiotemporal and policy-related variations of PM2.5 composition and sources based on long-term observation at multiple sites. A total of 836 samples were collected from 19 sites in winter 2015–2019. According to the specific characteristics, 19 sampling sites were assigned to three layers. Layer 1 was the most urbanized area and referred to the core zone of Chengdu, layer 2 was located in the outer circle of layer 1, and layer 3 belonged to the outermost zone with the lowest urbanization level. The average PM2.5 concentrations for 5 years were in the order of layer 2 (133 µg m−3) > layer 1 (126 µg m−3) > layer 3 (121 µg m−3). Spatial clustering of the chemical composition at the sampling sites was conducted for each year. The PM2.5 composition of layer 3 in 2019 was found to be similar to that of the other layers 2 or 3 years ago, implying that urbanization levels had a strong effect on air quality. During the sampling period, a decreasing trend was observed for the annual average concentration of PM2.5, especially at sampling sites in layer 1, where the stricter control policies were implemented. The SO42-/NO3- mass ratio at most sites exceeded 1 in 2015 but dropped to less than 1 since 2016, reflecting decreasing coal combustion and increasing traffic impacts in Chengdu, and these values can be further supported by temporal variations of the SO42- and NO3- concentrations. The positive matrix factorization (PMF) model was applied to quantify PM2.5 sources. A total of five sources were identified, with average contributions of 15.5 % (traffic emissions), 19.7 % (coal and biomass combustion), 8.8 % (industrial emissions), 39.7 % (secondary particles), and 16.2 % (resuspended dust). From 2015 to 2019, a dramatic decline was observed in the average percentage contributions of coal and biomass combustion, but the traffic emission source showed an increasing trend. For spatial variations, the high coefficient of variation (CV) values of coal and biomass combustion and industrial emissions indicated their higher spatial difference in Chengdu. High contributions of resuspended dust occurred at sites with intensive construction activities, such as subway and airport construction. Combining the PMF results, we developed the source-weighted potential source contribution function (SWPSCF) method for source localization. This new method highlighted the influences of spatial distribution for source contributions, and the effectiveness of the SWPSCF method was evaluated.

Impact of the COVID-19 Lockdown in a European Regional Monitoring Network (Spain): Are We Free from Pollution Episodes?

The impact of the lockdown, during the period from March to June in 2020, upon the air quality of the Basque Country in northern Spain is analyzed. The evaluation accounts for the meteorology of the period. Daily and sub-daily analysis of aerosol and ozone records show that the territory was repeatedly affected by episodes of pollutants from outer regions. Three episodes of PM10 and ten of PM2.5 were caused by transported anthropogenic European sulfates, African dust, and wildland fires. The region, with a varied orographic climatology, shows high and diverse industrial activity. Urban and interurban road traffic of the region decreased by 49% and 53%, respectively, whereas industrial activity showed a lower reduction of 20%. Consequently, the average concentrations of NO2 in the cities during the period fell to 12.4 µg·m−3 (−45%). Ozone showed up to five exceedances of the WHOAQG for the daily maximum 8-h average in both rural and urban sites, associated with transport through France and the Bay of Biscay, under periods of European blocking anticyclones. However, averages showed a moderate decrease (−11%) in rural environments, in line with the precursor reductions, and disparate changes in the cities, which reproduced the weekend effect of their historical records. The PM10 decreased less than expected (−10% and −21%, in the urban and rural environments, respectively), probably caused by the modest decrease of industrial activity around urban sites and favorable meteorology for secondary aerosol formation, which could also influence the lower changes observed in the PM2.5 (−1% and +3% at the urban and rural sites, respectively). Consequently, in a future low NOx traffic emission scenario, the inter-regional PM and ozone control will require actions across various sectors, including the industry and common pollution control strategies.

Associations of ultrafine and fine particles with childhood emergency room visits for respiratory diseases in a megacity

BackgroundAmbient fine particulate matter with aerodynamic diameter less than 2.5 µm (PM2.5) has been associated with deteriorated respiratory health, but evidence on particles in smaller sizes and childhood respiratory health has been limited.MethodsWe collected time-series data on daily respiratory emergency room visits (ERVs) among children under 14 years old in Beijing, China, during 2015–2017. Concurrently, size-fractioned number concentrations of particles in size ranges of 5–560 nm (PNC5–560) and mass concentrations of PM2.5, black carbon (BC) and nitrogen dioxide (NO2) were measured from a fixed-location monitoring station in the urban area of Beijing. Confounder-adjusted Poisson regression models were used to estimate excessive risks (ERs) of particle size fractions on childhood respiratory ERVs, and positive matrix factorisation models were applied to apportion the sources of PNC5–560.ResultsAmong the 136 925 cases of all-respiratory ERVs, increased risks were associated with IQR increases in PNC25–100 (ER=5.4%, 95% CI 2.4% to 8.6%), PNC100–560 (4.9%, 95% CI 2.5% to 7.3%) and PM2.5 (1.3%, 95% CI 0.1% to 2.5%) at current and 1 prior days (lag0–1). Major sources of PNC5–560 were identified, including nucleation (36.5%), gasoline vehicle emissions (27.9%), diesel vehicle emissions (18.9%) and secondary aerosols (10.6%). Emissions from gasoline and diesel vehicles were found of significant associations with all-respiratory ERVs, with increased ERs of 6.0% (95% CI 2.5% to 9.7%) and 4.4% (95% CI 1.7% to 7.1%) at lag0–1 days, respectively. Exposures to other traffic-related pollutants (BC and NO2) were also associated with increased respiratory ERVs.ConclusionOur findings suggest that exposures to higher levels of PNC5–560 from traffic emissions could be attributed to increased childhood respiratory morbidity, which supports traffic emission control priority in urban areas.