Using a noise monitoring station in a small quarry located in an urban area

Mining plays an important role in Brazilian exports. On the other hand, large urban centers like São Paulo, with approximately 21 million inhabitants, also demand an increasing domestic consumption of natural resources, such as construction aggregate. There are many quarries located in the surroundings of urban centers in Brazil, competing with the growth of urbanized areas. Such proximity leads to a series of conflicts involving quarries and surrounding communities, where the increase in noise levels is highlighted. Operations in quarries, in general, are intermittent. Noisier equipment, such as drilling rigs and primary crushers, operates only a few hours during the day, while other operations, such as screening and secondary and tertiary crushing, are more constant. This paper presents a study carried out in a quarry located near São Paulo, where in addition to conventional short term noise measurements at surrounding receptors, one noise monitoring station was installed, allowing to identify the noisiest moments during the quarry operating time. Through data transmitted by wireless technology, it was possible to follow the noise variations emitted from mining activities in real time and observe the noisiest events that were recorded for events that exceeded the established standards. A mobile application associated to this monitoring station facilitated the quarry’s manager and employees to access immediately the monitoring information. Therefore, by using this system, it was possible to evaluate the effectiveness of noise reduction measures already taken and indicate what steps still need to be held.     

The effect of improved nowcasting of precipitation on air quality modeling

The predictive potential of air quality models and thus their value in emergency management and public health support are critically dependent on the quality of their meteorological inputs. The atmospheric flow is the primary cause of the dispersion of airborne substances. The scavenging of pollutants by cloud particles and precipitation is an important sink of atmospheric pollution and subsequently determines the spatial distribution of the deposition of pollutants. The long-standing problem of the spin-up of clouds and precipitation in numerical weather prediction models limits the accuracy of the prediction of short-range dispersion and deposition from local sources. The resulting errors in the atmospheric concentration of pollutants also affect the initial conditions for the calculation of the long-range transport of these pollutants. Customary the spin-up problem is avoided by only using NWP (Numerical Weather Prediction) forecasts with a lead time greater than the spin-up time of the model. Due to the increase of uncertainty with forecast range this reduces the quality of the associated forecasts of the atmospheric flow.In this article recent improvements through diabatic initialization in the spin-up of large-scale precipitation in the Hirlam NWP model are discussed. In a synthetic example using a puff dispersion model the effect is demonstrated of these improvements on the deposition and dispersion of pollutants with a high scavenging coefficient, such as sulphur, and a low scavenging coefficient, such as cesium-137. The analysis presented in this article leads to the conclusion that, at least for situations where large-scale precipitation dominates, the improved model has a limited spin-up so that its full forecast range can be used. The implication for dispersion modeling is that the improved model is particularly useful for short-range forecasts and the calculation of local deposition. The sensitivity of the hydrological processes to proper initialization implies that the spin-up problem may reoccur with changes in the model and increased model resolution. Spin-up should be an ongoing concern for atmospheric modelers.