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In this study, the exposure to ambient particulate matter metrics (PM1, PM2.5, PM10, black carbon (BC), brown carbon (BrC), ultraviolet particulate matter (UVPM), particle number concentration (PNC), and lung deposited surface area (LDSA)) were measured along a fixed walking route with specific focus on three typical micro-environments (park, central business district (CBD), and traffic) in different time of day during the non-heating (May–Oct.) and heating (Nov.–Apr.2nd year) periods from 2018 to 2020 in the downtown Augsburg, Germany. The spatio-temporal exposure to ambient PM metrics exhibited substantial heterogeneity during the observation period, with park environment having lowest exposure and traffic area having the highest exposure. Generally, the higher LDSA concentrations were found in traffic area and CBD during the observation periods, while the lower concentrations were found in the park, which is similar with other ambient PM metrics (PMX, eUVPM, eBC, and PNC). The correlations between LDSA and other ambient PM metrics were higher during the heating than non-heating period in most of investigated environments, indicating the different PM sources. Overall, this study provides a comprehensive assessment of personal exposure that complements fixed-site ambient PM metrics measurements in the context of health risk assessment and epidemiological studies.

In this article, we consider results of performed research, dedicated to assessment of changes in parameters of heating period (HP) of Volga Federal District (VFD). For the first time for territory of VFD we created maps for space distribution of the main characteristics of heating period; we investigated peculiarities of multiannual dynamics of characteristics of heating period that had been previously unknown, and we assessed their multiannual tendencies; for the first time for VFD we tested tightness and directionalities of interconnections between various characteristics of heating period and estimated perspectives of the application for prognostic aims. It was stated that climate indices of heating period was characterized by high level of variability in both time and territory of the district. Temporary instability of climatic indices of heating period within the territory of the district increase at a high pace from its southern parts in the direction of North and North-East, where it reaches its maximal values, which is non-stochastic. We detected the presence of rather tight and significant connections between the dates of autumn switches of mean daily air temperature (MDAT) through 8°C and the length, which opens possibility of building one-factor regressive prognostic models with significant resolving capacity at coefficient of their determination of [R2(O,Π)]=38÷52%.

In this article, we consider results of performed research, dedicated to assessment of changes in parameters of heating period (HP) of Volga Federal District (VFD). For the first time for territory of VFD we created maps for space distribution of the main characteristics of heating period; we investigated peculiarities of multiannual dynamics of characteristics of heating period that had been previously unknown, and we assessed their multiannual tendencies; for the first time for VFD we tested tightness and directionalities of interconnections between various characteristics of heating period and estimated perspectives of the application for prognostic aims. It was stated that climate indices of heating period was characterized by high level of variability in both time and territory of the district. Temporary instability of climatic indices of heating period within the territory of the district increase at a high pace from its southern parts in the direction of North and North-East, where it reaches its maximal values, which is non-stochastic. We detected the presence of rather tight and significant connections between the dates of autumn switches of mean daily air temperature (MDAT) through 8°C and the length, which opens possibility of building one-factor regressive prognostic models with significant resolving capacity at coefficient of their determination of [R2(O,Π)]=38÷52%.