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Mobile observation has been widely used in the monitoring of air pollution. However, studies on pollution sources and emission characteristics based on mobile navigational observation are rarely reported in the literature. A method for quantitative source analysis for industrial air pollutant emissions based on mobile observations is introduced in this paper. NOx pollution identified in mobile observations is used as an example of the development of the method. A dispersion modeling scheme that fine-tuned the meteorological parameters according to the actual meteorological conditions was adopted to minimize the impact of uncertainties in meteorological conditions on the accuracy of small-scale dispersion modeling. The matching degree between simulated and observed concentrations was effectively improved through this optimization search. In response to the efficiency requirements of source resolution for multiple sources, a random search algorithm was first used to generate candidate solution samples, and then the solution samples were evaluated and optimized. Meanwhile, the new index Smatch was established to evaluate the quality of candidate samples, considering both numerical error and spatial distribution error of concentration, in order to address the non-uniqueness of the solution in the multi-source problem. Then, the necessity of considering the spatial distribution error of concentration is analyzed with the case study. The average values of NOx emission rates for the two study cases were calculated as 69.8 g/s and 70.8 g/s. The Smatch scores were 0.92–0.97 and 0.92–0.99. The results were close to the online monitoring data, and this kind of pollutant emission monitoring based on the mobile observation experiment was initially considered feasible. Additional analysis and clarifications were provided in the discussion section on the impact of uncertainties in meteorological conditions, the establishment of a priori emission inventories, and the interpretation of inverse calculation results.

Increase in nitrogen (N) deposition will cause changes of root morphological and functional traits, thus deeply affecting ecosystem carbon (C) and N cycles. However, the influence of N deposition to root traits under different climatic conditions, and with different N deposition rate and durations were still unclear. Here, a meta-analysis was conducted to evaluate the effects of simulated increase in N deposition on 11 root traits under different conditions. In general, N addition significantly increased root/shoot ratio, fine root diameter, total root biomass, fine root production, fine root turnover rate, root respiration, fine root N concentration, while decreased fine root C/N at the global scale. Under N addition, the increased extents of fine root biomass and total root biomass were significantly greater in grassland ecosystems, while the increased extent of fine root turnover was greater in forests. N addition significantly increased fine root production in snow climate zone where forests with ectomycorrhizae. A pattern may be inferred that with increases in mean annual temperature (MAT) and mean annual precipitation (MAP), N addition decreased fine root N concentration and fine root C/N, while increased fine root turnover at the high-MAT and high-MAP areas. In addition, it may be ascertained that fine roots became shorter in the low-rate and short-term N addition experiments, while roots became longer in the high-rate and long-term N addition experiments. Our study indicates that increase in N deposition will cause intricate changes of root traits due to the diversity of climatic conditions and the uncertainty of increase rate and duration of N deposition in future.

Abstract With the development of the radar technology, it is required that a radar has wider bandwidth and can transmit multiple signals simultaneously. The polyphase digital channelised transmitter structure can transmit multiple signals simultaneously and increase the bandwidth of the output signal. However, in order to reduce the frequency aliasing and improve the spectrum utilisation, the prototype filter needs to have sharp transition bandwidth. The design of the prototype filter directly affects the performance of the radar transmitter. Using the complex‐exponential modulation frequency‐response masking (CEM‐FRM) approach to design the prototype filter can obtain both sharp transition bandwidth and low complexity. The application of a polyphase structure can further reduce the complexity of the filter bank and make the sampling rate of the output signal several times the field programmable gate array operating frequency. The proposed CEM‐FRM‐based low complexity polyphase channelised radar transmitter is verified by MATLAB simulation and the theoretical complexity of the proposed CEM‐FRM‐based channelised radar transmitter structure is compared with other methods.