Particulate matter (PM) is an essential source of atmospheric pollution in metropolitan areas since it has adverse effects on human health. However, previous research suggested wetlands can remove particulate matter from the atmosphere to land surfaces. This study was conducted in the Hanshiqiao Wetland National Nature Reserve in Beijing during 2016. The concentrations of PM10 and PM2.5 on a wetland and bare land in the park, as well as metrological data, were collected during the whole year. Based on the observed data, removal efficiency of each land use type was calculated by empirical models and the relationships between concentrations and metrological factors were also analyzed. The results indicated that: (1) In general, the PM10 and PM2.5 concentrations on the bare land surface were higher than those on the wetland surface, in both of which the highest value appeared at night and evening, while the lowest value appeared near noon. In terms of season, the average concentration of PM10 was higher in winter (wetland: 137.48 μg·m−3; bare land: 164.75 μg·m−3) and spring (wetland: 205.18 μg·m−3; bare land: 244.85 μg·m−3) in general. The concentration of PM2.5 on the wetland surface showed the same pattern, while that on the bare land surface was higher in spring and summer. (2) Concentrations of PM10 and PM2.5 were significantly correlated with the relative humidity (p < 0.01) and inversely correlated with wind speed (p < 0.05). The relationship between PM10 and PM2.5 concentrations and temperature was more complicated—it showed a significantly negative correlation (p < 0.01) between them in winter and spring, however, the correlation was insignificant in autumn. In summer, only the correlation between PM10 concentration and temperature on the wetland surface was significant (p < 0.01). (3) The dry removal efficiency of PM10 was greater than that of PM2.5. The dry removal efficiencies of PM10 and PM2.5 followed the order of spring > winter > autumn > summer on the wetland. This study seeks to provide practical measures to improve air quality and facilitate sustainable development in Beijing.

Human activities alter the growth of coastal wetland vegetation. In the present study, we used a spectrometer and hyperspectral data to determine and compare the biomass of Suaeda salsa in a coastal wetland under protective and destructive activities. Using typical discriminants, the hyperspectral data of Suaeda salsa were distinguished under the influence of two kinds of human activity, and the accuracy of the inversion model of biomass was established following improved differentiation of the data under the influence of human activities. The original spectral reflectance and vegetation index were selected, and the biomass-inversion model was established by linear regression and partial least-squares regression. The model established by partial least-squares regression had a good precision (R2&gt;0.85, RMSE%&lt;5.6%). Hyperspectral technology can accurately show plant biomass and the indirect effects of interference by human activities of different intensity on coastal wetlands. The accuracy of the models can be improved by distinguishing the vegetation patterns under the influence of different types of human activity, and then constructing the biomass models. This study provides technical support for the use of quantitative remote sensing-based methods to monitor the fragile ecology of coastal wetlands under the influence of human activities.

Peatlands play an essential role in the global carbon (C) and nitrogen (N) cycling. In order to ascertain the draining effects on recent accumulation rates of C (RERCA) and N (RERNA) in the Zoige peatland in the eastern Qinghai-Tibet Plateau, the core samples of peat growth, C and N accumulation for both natural and drained peatlands were measured using 210Pb and 137Cs dating methods. As a result, RERCA and RERNA showed an increasing trend from the bottom to the surface of the peatland, which was in accordance with the peat accumulation rates. However, the average RERCA in permanently flooded and seasonally flooded peatlands were 1.5–2.5 times that of drainage peatlands, and the average of RERNA were 1.2–1.7 times. Our findings indicate that the Zoige peatland is still in the stage of peat development with a large carbon sequestration capacity, and drainage from human activities leads to the decreasing of RERCA and RERNA, which will contribute to the selection of the effective ways to slow down the anthropogenic effects on the degradation of the Zoige peatland.