Add to ORKGAbstract: PM10 monitoring networks are equipped with heterogeneous samplers. Some of these samplers are known to underestimate true levels of concentrations (non-reference samplers). In this paper we propose a hierarchical spatio-temporal Bayesian model for the calibration of measurements recorded by non-reference samplers by borrowing strength from non co-located reference sampler measurements
In this paper our objective is to propose a flexible model able to integrate different environmental...
Particulate matter (PM) is one of the most critical air pollutants because of its effects on the hum...
he PM2.5 air quality index (AQI) measurements from government-built supersites are accurate but cann...
PM10 monitoring networks are equipped with heterogeneous samplers. Some of these samplers are known ...
During an USEPA study in the Phoenix area from 1995-1998, measurements from a federal reference meth...
the city of Taranto. In the present work the attention is focused on PM10 concentrations monitored b...
In this paper we propose a hierarchical spatio-temporal model for daily mean concentrations of PM10 ...
The statistical evaluation of an air quality model is part of a broader process, generally referred ...
Particulate matter (PM) air quality in Europe has improved substantially over the past decades, but ...
Statistical methods are needed for evaluating many aspects of air pollution regulations increasingly...
In the last two decades, increasing attention has been given to air pollution around the world, main...
The PM10 concentrations are often measured by different instruments situated in different sites. As ...
This paper describes a Bayesian hierarchical approach to predict short-term concentrations of partic...
In environmental monitoring, the ability to obtain high-quality data across space and time is often ...
Recent literature on long-range spatial exposure assessment focused on Kriging or atmospheric pollut...
In this paper our objective is to propose a flexible model able to integrate different environmental...
Particulate matter (PM) is one of the most critical air pollutants because of its effects on the hum...
he PM2.5 air quality index (AQI) measurements from government-built supersites are accurate but cann...
PM10 monitoring networks are equipped with heterogeneous samplers. Some of these samplers are known ...
During an USEPA study in the Phoenix area from 1995-1998, measurements from a federal reference meth...
the city of Taranto. In the present work the attention is focused on PM10 concentrations monitored b...
In this paper we propose a hierarchical spatio-temporal model for daily mean concentrations of PM10 ...
The statistical evaluation of an air quality model is part of a broader process, generally referred ...
Particulate matter (PM) air quality in Europe has improved substantially over the past decades, but ...
Statistical methods are needed for evaluating many aspects of air pollution regulations increasingly...
In the last two decades, increasing attention has been given to air pollution around the world, main...
The PM10 concentrations are often measured by different instruments situated in different sites. As ...
This paper describes a Bayesian hierarchical approach to predict short-term concentrations of partic...
In environmental monitoring, the ability to obtain high-quality data across space and time is often ...
Recent literature on long-range spatial exposure assessment focused on Kriging or atmospheric pollut...
In this paper our objective is to propose a flexible model able to integrate different environmental...
Particulate matter (PM) is one of the most critical air pollutants because of its effects on the hum...
he PM2.5 air quality index (AQI) measurements from government-built supersites are accurate but cann...