Exhaust gases multi-band air quality sensor on arduino - part 1

For my graduation project I need to develop a model of exhaust gases distribution between city buildings.
The model will made with help of PyQGIS and about this i will write later.
For source data collecting i `m  going to use the self made multiband exhaust gas detector (air quality monitor) based on arduino-like board (dccduino - with love from China) and set of specialized gas sensors.

What I'm going to use:

Components for future exhaust gas sensor 

From left to right:

1. MQ-138 with module. This sensor will be used for detecting of organic components of air. The description of this module says that it is sensitive to aldehydes, alcohols, ketones, and aromatic compounds :
   • 1 to 100ppm benzene
   • Toluene 10 to 100ppm
   • Methanol 5 to 100ppm
   • Alcohol 30 to 300ppm
   • Acetone 10 to 300ppm
• Formaldehyde 1 to 10ppm 
2. MQ-131with module. This sensor will used for ozone detection. In description is written that it is able to detect concentration range 10ppb-2ppm.
3. NAP-505 (top, grey with white round) - electrolytic CO (Carbon Monoxide) gas sensor with high selectivity and sensitivity. The only sensor from set that not depends from humidity and need own circuit with expensive operative amplifiers.
4. TGS-2201 (Figaro - 5N2201) (little black, bottom) - exhaust gases sensor. This sensor is interesting because this is dual sensor. Under one pack we have 2 sensors for diesel and petrol exhaust gases. About this one i had not found a lot of info, official website of FIGARO have not contains the datasheets, but i had found the one. As like as NAP-505 this sensor deeds own circuit but luckily this circuit needs only resistors. 
5. DHT21 (AM2301) (right, top) - digital temperature and humidity sensor - 2 in one. This is  simple digital module that needs to make correlation between humidity-temperature and data from sensors. The practice shows that this sensor is very passive for data stabilization when it is needs to be used as a mobile monitoring device. I think that this passivity is effected by big plastic casing. In future I will check this.
6. DCcduino UNO - full copy of Arduino Uno with price of 7$ (cost includes USB cable + pin dapters).

MQ modules and DHT has been connected with arduino without any problems. In MQ I had used only analog outputs because now i need only make a test.

NAP-505 i will connect later, where i will have operative amplifiers from it`s circuit.

The datasheet of NAP-505

TGS-2201 connecting process

The datasheet for this exhaust gas sensor i had found only on this page.

You can download this datasheet.

TGS-2201 circuit is not difficult

As we can see in datasheet - the R1 and R2 range can be between 10k to 200k and depends on weather and measurement environment (i think).

The pins of sensor

Resistor circuit

I had used both resistors with resistance near 15k and that was a bad idea because one channel of this exhaust gas sensor (petrol channel) shows a much big values, so it needs to be calibrated. (see screenshot of serial monitor)

The first compilation of air quality exhaust gases sensor 

This is arduino with connected air quality sensors (except carbon monoxide and humidity\temperature).  100% chaos :)

This is a beta for outdoor measurement.

This is an attempt to make it not so ugly. Unsuccessful.

In future i will make for this one the normal casing and LCD display from cellphone.

sudo screen /dev/ttyUSB0

As you see on this screenshot - values are not adequate and need to be calibrated, about which i will write later. (overall is a pseudo-overall because it considers gases "importance rate")

To be continued.. 

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Biodiversity conservation framework problems - abstract

The short review of three articles describes the main problems of biodiversity conserving. The “hotspot method” shows that this approach have more disadvantages than benefits. This method selects the limited spectrum of species only from terrestrial vertebrates and vascular plants of region that have endemic status and ignores all other species. The method from second article (the method of terrestrial ecozones) is much more objective, but not solves the question for aquatic ecosystems. Furthermore, in the map developed by authors ignored the existing of coastal ecosystems. The main problem of biodiversity conservation is determined a bit by Bjørn Lomborg. In his book “The Skeptical Environmentalist” He gives good point that we cannot properly know how many species really are.

INTRODUCTION

During the human progress, anthropogenic pressure to the Earth becomes higher and higher. This pressure causes much of phenomenons that force wildlife species extinction. In parallel with increasing of this pressure, during many years environmental scientists try to develop methods to save species and communities. However, number of scientist are very often equally to the number of methods that they are propose. Almost all of these are unique and good-looking, but sometimes noone can be used effectively because of broad spectrum of causes. In this review I will try to accent your attention on problems that I have found in three publications: “Biodiversity hotspots for conservation priorities”, “Terrestrial Ecoregions of the World”, “The Skeptical Environmentalist: Measuring the Real State of the World . Ch.23. Biodiversity”.

BIODIVERSITY CONSERVATION FRAMEWORK PROBLEMS

During the conservation studies were created two different paradigms of biodiversity measuring. The first of these two is based on counting of species number, second paradigm based on systematizing of biodiversity clusters. Both have own benefits and disadvantages. In the article named “Biodiversity hotspots for conservation priorities”, group of scientists show serious forces to develop conservation framework based on selecting regions with maximum concentration of unique endemic species. In second article, that named “Terrestrial Ecoregions of the World”, scientists try to develop conservation framework with ecoregions map. Third article, that factually is Bjørn Lomborg`s book chapter, is a critique of classic bioconservation scientists and showing the disadvantages of evaluation methods.

At first article, scientists made huge accent on the number of endemic species and made the map of 25 biodiversity hotspots. Each hotspot must consist at least 0,5 % world`s species as endemics and should have lost 70 % or more of its primary vegetation. In sum that 25 hotspots consists near 35 % vertebrate and 44 % of vascular plants. At first sight everything in this method is logic: places with maximum amount of endemic species must be saved first (500 million $ annual dotation per one point, by the all), but this hotspot method has a lot of problems. First of them is that endemic species list is not identically for each other country, territory of which hotspot covered. Concentration of species can be other by location. Io one country this specific specie can be endemic, in other country it can be the simple specie that just usual specie. Overall, problem consist in the fact that not each species that even be on Earth have been discovered and described as endemics or not. That’s mean that this method representative only for properly discovered and described species.

Next, and more serious problem is that this 35 % of vertebrates include only high animals lake a mammals, birds and amphibian animals. This method ignores not only microbiota but also insects and fishes. 44 % of vascular plants forced to ask a question “why only vascular plants?” Are unique species of lichen and moss can’t be endemic or mustn’t to be saved at all? Considering the air pollution tendencies, exactly lichen and moss suffering first.

Second article shows a framework based on Earth zonation by biomes and biogeographic realms. This method gives widely sight on biodiversity conservation principles. The group of scientists made review of existing biogeographic maps with hi-resolution of ecoregions and proposed their own variant of such map: separate terrestrial world onto 8 biogeographic regions and 14 main biomes. Combination of this 8 and 14 gives 112 potential ecoregions with own complex of treats and unique variants of conservation. So broad zonation helps with classification that can show specific and unique zones that can be unique. The main disadvantage of ecoregion method is a difficulty with ocean zonation, as long as ecozones in oceans situated not in 2 dimensions but in 3. Furthermore, new and optimized map of scientists developed on other`s map base, but after optimization new map has lost the coastal ecological zones.

In third article Bjørn Lomborg gives constructive critic to apocalyptic posts of classicists with predictions. Especially he appellate to Mayer’s declamation that every year extents near 40 000 species, which he does in 1979. Author also make trying to determinate the real amount the annual extinction and make a conclusion that real extinction now is near to 0,7 % per 50 years.

CONCLUSION

As we can see after analyzing of these 3 articles, the main problem of biodiversity conserving is that nobody know completely how many species and communities really are, and nobody know completely, which of them really extinct. That’s why so difficult to determine the priorities in case of biodiversity conserving. Moreover, such method as “hotspots” can`t make the real objective evaluation because it makes conclusion only by concentration of terrestrial vertebrates and vascular plants species that have a label “endemic”, without taking the attention to other species that can be unique. Both of described methods accents the attention on the unique concentration of biodiversity as like as on object to save, but noone solves the problem of single unique species that can extinct too.

Maybe the better way to solve the biodiversity extinction problem is to use or develop the new approach that will based not only on the biodiversity conservation or biocenosis uniqueness but on zonation of anthropogenic pressure. This strategy is useful to save at first the live objects and ecosystems that in process of extinction.

SOURCES

1.       Norman Myers  et al. Biodiversity hotspots for conservation priorities .

[  Nature 403, 853-858 (24 February 2000)].

2.       David  M. Olson et al. Terrestrial Ecoregions of the World: A New Map of Life on Earth

[ BioScience.  Vol. 51 No. 11,2001. P. 933-938]. 

3.        Bjørn Lomborg.  The Skeptical Environmentalist: Measuring the Real State of the World . Ch.23. Biodiversity.

[Cambridge University Press , 2001].

P.S. sorry for my English :D

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OpenLayers3 GeoJSON clustering - first steps troubleshooting guide, part 2

OL2 had the specific layer strategy that makes clusters from points.
But OpenLayers3 haven't yet.
OpenLayers 3 has own method to do that, but you need use the feature array with points stack as source.

Everything is okay if we use stack of coordinates or array of independent points.
The panic starts when you should to make clusters from geojson points.
But what you should do if you want to load geojson with points created in QGIS?

At first we need to transform geojson object to stack of point objects.
How to do that without nervous i don't found, but we can to extract the lat\lng from geojson with
jQuery.getJSON() or with AJAX json request.

Example

$.getJSON( "file.geojson", function( data ) {
  var features = [];
  $.each( data, function(key, value) {
    features.push(value);
});

/// - "file.geojson" - path to your geojson

var fln = features[2].length;

/// - features contents 3 elements: ["FeatureCollection", Object, Array[92]]
We need to get length of array that includes features, so we need to use features[2].

var points = [];
for (var i = 0; i < fln; ++i) {
  points.push(new ol.Feature(new ol.geom.Point(features[2][i]['geometry']['coordinates'][0])));
}
console.log(points);

/// - now we need to extract coordinates of every feature and create point objects.
features[2][i]['geometry']['coordinates'][0]
features[2] - array with geojson points
[i] - points number (0-91)
['geometry'] - point attribute with geometry
['coordinates'] - attribute that consist coordintes
[0] - array with lat\lng that we should use to create ol.geom.Point. 

var source = new ol.source.Vector({
  features: points
});

/// - creating of vector source from array of ol.Feature point objects 

var clusterSource = new ol.source.Cluster({
  distance: 40,
  source: source
});

/// - creating of cluster source from our vector source

var styleCache = {};
var clusters = new ol.layer.Vector({
  source: clusterSource,
  style: function(feature, resolution) {
    var size = feature.get('features').length;
    var style = styleCache[size];
    if (!style) {
      style = [new ol.style.Style({
          radius: 20,
          stroke: new ol.style.Stroke({
            color: 'rgba(225,225,225,0.2)',
   width: 10
          }),
          fill: new ol.style.Fill({
            color: '#3399CC'
          })
        }),
        text: new ol.style.Text({
          text: size.toString(),
          fill: new ol.style.Fill({
            color: '#fff'
          })
        })
      })];
      styleCache[size] = style;
    }
    return style;
  }
});

/// - styling as in OL3 clustering example

map.addLayer(clusters);

/// - adding cluster layer to the map
});


About styling with response to cluster size i will write later

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