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Page 20 of 24 Luo et al. Carbon Footprints 2025, 4, 14 https://dx.doi.org/10.20517/cf.2024.53

(4) Temporal Resolution Constraints

While hourly simulations effectively capture broad trends in dynamic exposure, they lack the resolution
needed to detect minute-level pollution peaks, such as those occurring in traffic-congested areas. Future
work could incorporate higher-frequency trajectory data and real-time monitoring to refine exposure
modeling.

CONCLUSIONS
Key findings
This study, using Shanghai’s Baoshan District as a case study, developed a dynamic exposure risk
assessment framework by integrating the CALPUFF dispersion model with mobile phone signaling data,
systematically revealing the spatiotemporal distribution patterns and demographic disparities associated
with traffic-related NO pollution. The key findings include:
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Temporal Dimension: NO exposure exhibited a clear bimodal diurnal pattern, with noticeable weekday-
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weekend variations. Concentrations peaked during the morning and evening rush hours, while weekend
levels remained consistently lower. This “rhythmic” pattern highlights the strong correlation between traffic
emissions and human activity, providing a quantitative basis for “time-targeted pollution control”.

Spatial Dimension: Areas of high exposure risk clustered around ports, logistics corridors, and the outer-
ring expressways, forming a spatial distribution pattern closely tied to the city’s functional zoning. This
spatial correlation suggests that uneven transportation infrastructure may contribute to environmental
inequities.

Demographic Dimension: Exposure risks varied significantly by gender and age group. Males and working-
age adults (19-44 years) experienced the highest exposure risks, whereas older adults faced the lowest risks
due to their infrequent and short-distance travel behavior. These disparities reflect differences in mobility
patterns and highlight the “social-behavioral and structural” nature of traffic pollution exposure.

Policy implications
Time-based traffic management strategies
Traffic-related NO exposure peaks during morning and evening rush hours, especially when freight and
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commuter traffic overlap (e.g., during the evening peak). This overlap results in elevated NO
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concentrations and higher exposure levels for local residents. To address this, dynamic traffic management
strategies should be implemented to reduce pollutant loads during critical time windows. For example,
staggered commuting schedules and time-specific restrictions on heavy-duty diesel trucks should be
enforced during weekday peak hours, particularly in densely populated areas along major transport
corridors such as the Outer Ring Expressway. Diverting freight traffic away from peak residential travel
times can help reduce cumulative emissions, flatten intra-day pollution peaks, and limit short-term NO
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buildup.

Targeted protection for high-exposure populations
Exposure assessments reveal that highly mobile groups, particularly working-age males, are
disproportionately affected by traffic-related NO pollution, while elderly individuals - due to their limited
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mobility - experience the lowest exposure. To address this disparity, targeted interventions should prioritize
high-exposure populations to reduce health risks and promote environmental equity. For example,
individuals with frequent commutes and high exposure levels should benefit from tailored protective