No abstract

No abstract

To assess the effect of floor levels of high-rise apartment buildings on the accumulation of contaminants in indoor environment, residential air-conditioner filter dust (ACFD) samples from the 1 st , 10 th , 20 th and 30 th floors of a high-rise apartment building were collected for the determination of n-alkanes and polycyclic aromatic hydrocarbons (PAHs). The results show that both n-alkanes and PAHs in the residential ACFD were ubiquitous but varied greatly in concentrations. The total concentrations of 27 n-alkanes (Σ 27 AK) and 16 PAHs (Σ 16 PAH) ranged from 1.35 to 9290 µg g -1 and 278-34200 ng g -1 , respectively. Source apportionment revealed that n-alkanes were from mixed sources combining fossil fuel combustion, natural emission and solid biomass burning, but PAHs were mainly from indoor sources. Furthermore, the diagnostic ratio of paired low weight molecular PAH species may change during transportation and accumulation. Significantly higher concentrations of Σ 27 AK and Σ 16 PAH were observed in the samples from low floor levels (the 1 st and 10 th floors) compared to those from high floor levels (the 20 th and 30 th floors). The results of classification and regression tree analysis clearly suggested floor level is the most important factor influencing the accumulation of Σ 27 AK and Σ 16 PAH in the ACFD. Our findings imply that people living on lower floor levels have greater exposure risks to PAHs associated with indoor dust.

China will attempt to achieve its simultaneous goals in 2060, whereby carbon neutrality will be accomplished and the PM2.5 (fine particulate matter) level is expected to remain below 10 μg/m3. Identifying interaction patterns between air cleaning and climate action represents an important step to obtain cobenefits. Here, we used a random sampling strategy through the combination of chemical transport modeling and machine learning approach to capture the interaction effects from two perspectives in which the driving forces of both climate action and air cleaning measures were compared. We revealed that climate action where carbon emissions were decreased to 1.9 Bt (billion tons) could lead to a PM2.5 level of 12.4 μg/m3 (95% CI (confidence interval): 10.2–14.6 μg/m3) in 2060, while air cleaning could force carbon emissions to reach 1.93 Bt (95% CI: 0.79–3.19 Bt) to achieve net carbon neutrality based on the potential carbon sinks in 2060. Additional controls targeting primary PM2.5, ammonia, and volatile organic compounds were required as supplements to overcome the partial lack of climate action. Our study provides novel insights into the cobenefits of air-quality improvement and climate change mitigation, indicating that the effect of air cleaning on the simultaneous goals might have been underestimated before.

Construction of correctness is an essential issue for the implementation of a reliable software system. Formal methods based verification techniques provide programmers various ways to reason their program correctness through mathematically supported static analysis and dynamic analysis. In this paper, we introduce a tool that converts formal specifications in a subset of Object-Z to skeletal Spec# code with assertions. This tool aims at facilitating the refinement from formal specifications to Spec# and the full usage of the static and dynamic analysis techniques in Spec#.