Exposed to NO2 in the center, NOx polluters in the periphery: Evidence from the Paris region

Built-in electric field mediated S-scheme charge migration and Co-N4(II) sites in cobalt phthalocyanine/MIL-68(In)-NH2 heterojunction for boosting photocatalytic nitric oxide oxidation

The efficiency of photocatalytic Nitric Oxide(NO) oxidation is limited by the lack of oxygen(O2) active sites and poor charge carrier separation. To address this challenge, we developed a molecular Cobalt Phthalocyanine modified MIL-68(In)-NH2 photocatalyst with a robust Built-in electric field(BIEF). In the 2 % CoPc-MIN sample, the BIEF strength is increased by 3.54 times and 5.83 times compared to pristine CoPc and MIL-68(In)-NH2, respectively. This BIEF facilitates the efficient S-scheme charge transfer, thereby enhancing photogenerated carrier separation. Additionally, the Co-N4(II) sites in CoPc can effectively trap the separated photoexcited electrons in the S-scheme system. In addition, the Co-N4(II) sites can also serve as active sites for O2 adsorption and activation, promoting the generation of superoxide radical (O2-), thereby driving the direct conversion of NO to nitrate(NO3-). Consequently, the 2 % CoPc-MIN sample exhibits a remarkable photocatalytic NO removal efficiency of 79.37 % while effectively suppressing the formation of harmful by-product nitrogen dioxide(NO2) to below 3.5 ppb. This study provides a feasible strategy for designing high-efficiency O2 activation photocatalysts for NO oxidation.

Long-term exposure and health risk assessment from air pollution: impact of regional scale mobility

BACKGROUND

The negative effect of air pollution on human health is widely reported in recent literature. It typically involves urbanized areas where the population is concentrated and where most primary air pollutants are produced. A comprehensive health risk assessment is therefore of strategic importance for health authorities.

METHODS

In this study we propose a methodology to perform an indirect and retrospective health risk assessment of all-cause mortality associated with long-term exposure to particulate matter less than 2.5 microns (PM2.5), nitrogen dioxide (NO2) and ozone (O3) in a typical Monday to Friday working week. A combination of satellite-based settlement data, model-based air pollution data, land use, demographics and regional scale mobility, allowed to examine the effect of population mobility and pollutants daily variations on the health risk. A Health Risk Increase (HRI) metric was derived on the basis of three components: hazard, exposure and vulnerability, utilizing the relative risk values from the World Health Organization. An additional metric, the Health Burden (HB) was formulated, which accounts for the total number of people exposed to a certain risk level.

RESULTS

The effect of regional mobility patterns on the HRI metric was assessed, resulting in an increased HRI associated with all three stressors when considering a dynamic population compared to a static one. The effect of diurnal variation of pollutants was only observed for NO2 and O3. For both, the HRI metric resulted in significantly higher values during night. Concerning the HB parameter, we identified the commuting flows of the population as the main driver in the resulting metric.

CONCLUSIONS

This indirect exposure assessment methodology provides tools to support policy makers and health authorities in planning intervention and mitigation measures. The study was carried out in Lombardy, Italy, one of the most polluted regions in Europe, but the incorporation of satellite data makes our approach valuable for studying global health.

Drive less but exposed more? Exploring social injustice in vehicular air pollution exposure

Despite growing understanding of racial and class injustice in vehicular air pollution exposure, less is known about the relationship between people's exposure to vehicular air pollution and their contribution to it. Taking Los Angeles as a case study, this study examines the injustice in vehicular PM_2.5 exposure by developing an indicator that measures local populations' vehicular PM_2.5 exposure adjusted by their vehicle trip distances. This study applies random forest regression models to assess how travel behavior, demographic, and socioeconomic characteristics affect this indicator. The results indicate that census tracts of the periphery whose residents drive longer distances are exposed to less vehicular PM_2.5 pollution than tracts in the city center whose residents drive shorter distances. Ethnic minority and low-income tracts emit little vehicular PM_2.5 and are particularly exposed to it, while White and high-income tracts generate more vehicular PM_2.5 pollution but are less exposed.