search.noResults

search.searching

saml.title
dataCollection.invalidEmail
note.createNoteMessage

search.noResults

search.searching

orderForm.title

orderForm.productCode
orderForm.description
orderForm.quantity
orderForm.itemPrice
orderForm.price
orderForm.totalPrice
orderForm.deliveryDetails.billingAddress
orderForm.deliveryDetails.deliveryAddress
orderForm.noItems
Air Monitoring


Simple Off-The-Shelf Ceilometers Find Increasing Applications in Air Quality


In recent decades meteorological sensors based on the scattering of light have moved from specialised research applications to routine operational use. For example roadside weather stations often have forward scatter sensors measuring visibility or identifying weather and most people reading this will have seen them. Similar sensors are widely used at airports and for a variety of other applications. Ceilometers using LIDAR (LIght Detection And Ranging) techniques are now used routinely by meteorologists and at many airports to determine cloud base by measuring the time it takes for light scattered from clouds to return to the sensor. These sensors are becoming increasingly sophisticated and are able to derive a lot more information about the atmosphere than just cloud height. In particular they can derive boundary layer structure of great interest for air quality forecasts more cost- effectively than Doppler LIDAR or other techniques.


Reliable values for backscatter coeffi cients are important for air quality and research applications but checking or calibrating an instrument in the fi eld has been, until now, very diffi cult.


Basic LIDAR techniques are now widely used to determine cloud base by measuring the time it takes for light scattered from clouds to return to the sensor. In practice this is not as straightforward as it fi rst sounds. Clouds do not have an abrupt, clearly defi ned base returning a sharp ‘echo’. In practice a ceilometer measures a profi le of scattering (in units of sr-1


m-1 , in effect the proportion


of scatter over a unit solid angle over unit distance). It then uses specialised algorithms to identify a cloud base. Typically this is based on a combination of identifying a rate of change of scattering and some criteria based on the calculated horizontal visibility. For the Campbell Scientifi c CS135 ceilometer (fi gure 1) this criterion, at lower levels, is a calculated horizontal visibility of 1,000m. This is the visibility criteria for fog so is a familiar threshold for pilots. Interestingly, it might be that the pilot of an aircraft fl ying in cloud a hundred meters above its base could see the ground below if he looked straight down (an observer on the ground would also see the aircraft as it passed directly overhead) but as regards aircraft around him or obstacles ahead he would be fl ying well within fog limits.


Author/Contact Details: Mike Brettle


Product Manager, Optical Sensors Campbell Scientifi c Ldt. 80 Hathern Road, Shepshed, Lecis., LE12 9GX United Kingdom


Email: mike.brettle@campbellsci.co.uk Figure 1: A modern ceilometer.


A ceilometer such as the Campbell Scientifi c CS135 (fi gure 1) may look simple but contains sophisticated optics and signal processing. The low noise signal processing allows measurements of small backscatter signals from aerosols. The optics in this model are based on a relatively large lens allowing a large collection area. This lens is cut and divided by an opaque barrier to allow the laser emitter and photodiode detector to be very close (fi gure 2). This is important because it means there will be


signifi cant overlap between their fi elds of view at relatively low levels allowing useful measurements within the lower levels of the atmospheric boundary layer, while still maintaining good optical isolation of the channels.


Figure 2: Schematic of the optical system of the CS135 ceilometer showing how a lens split by an opaque barrier allows the laser and detector to be close together.


A ceilometer measures the profi le of scattering in the atmosphere and this raises the obvious question as to whether more can be made of this information, especially since it is available from relatively cheap ‘off the shelf’ instruments. Air quality is an obvious candidate application. It is of great importance but some of the key parameters required for forecasting the development of the atmospheric boundary layer are diffi cult to measure.


35


Figure 3: Idealised diurnal evolution of the atmospheric boundary layer.


Figure 3 gives a very simplifi ed model of the typical evolution of the atmospheric boundary layer. Note the growth of the mixing layer during the day and its collapse around sunset. This is, as it’s name implies, the layer through which air, and by implication pollution released at the surface, is mixed.


www.envirotech-online.com IET Annual Buyers’ Guide 2014/15


Page 1  |  Page 2  |  Page 3  |  Page 4  |  Page 5  |  Page 6  |  Page 7  |  Page 8  |  Page 9  |  Page 10  |  Page 11  |  Page 12  |  Page 13  |  Page 14  |  Page 15  |  Page 16  |  Page 17  |  Page 18  |  Page 19  |  Page 20  |  Page 21  |  Page 22  |  Page 23  |  Page 24  |  Page 25  |  Page 26  |  Page 27  |  Page 28  |  Page 29  |  Page 30  |  Page 31  |  Page 32  |  Page 33  |  Page 34  |  Page 35  |  Page 36  |  Page 37  |  Page 38  |  Page 39  |  Page 40  |  Page 41  |  Page 42  |  Page 43  |  Page 44  |  Page 45  |  Page 46  |  Page 47  |  Page 48  |  Page 49  |  Page 50  |  Page 51  |  Page 52  |  Page 53  |  Page 54  |  Page 55  |  Page 56  |  Page 57  |  Page 58  |  Page 59  |  Page 60  |  Page 61  |  Page 62  |  Page 63  |  Page 64  |  Page 65  |  Page 66  |  Page 67  |  Page 68  |  Page 69  |  Page 70  |  Page 71  |  Page 72  |  Page 73  |  Page 74  |  Page 75  |  Page 76  |  Page 77  |  Page 78  |  Page 79  |  Page 80  |  Page 81  |  Page 82  |  Page 83  |  Page 84  |  Page 85  |  Page 86  |  Page 87  |  Page 88  |  Page 89  |  Page 90  |  Page 91  |  Page 92  |  Page 93  |  Page 94  |  Page 95  |  Page 96  |  Page 97  |  Page 98  |  Page 99  |  Page 100  |  Page 101  |  Page 102  |  Page 103  |  Page 104  |  Page 105  |  Page 106  |  Page 107  |  Page 108  |  Page 109  |  Page 110  |  Page 111  |  Page 112  |  Page 113  |  Page 114  |  Page 115  |  Page 116  |  Page 117  |  Page 118  |  Page 119  |  Page 120  |  Page 121  |  Page 122  |  Page 123  |  Page 124  |  Page 125  |  Page 126  |  Page 127  |  Page 128  |  Page 129  |  Page 130  |  Page 131  |  Page 132  |  Page 133  |  Page 134  |  Page 135  |  Page 136  |  Page 137  |  Page 138  |  Page 139  |  Page 140  |  Page 141  |  Page 142  |  Page 143  |  Page 144  |  Page 145  |  Page 146  |  Page 147  |  Page 148