Road motor vehicle emissions

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Creative Commons Attribution 3.0 New Zealand

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7403
78
Added
16 Sep 2015

This dataset was first added to MfE Data Service on 16 Sep 2015.

Road motor vehicles emit a range of air pollutants from their exhausts, and from brake and tyre wear. They are the main human-made source of nitrogen oxides and carbon monoxide emissions. Exposure to these pollutants can damage health, with effects ranging from respiratory irritation to cancer.

Road motor vehicles range from passenger vehicles to heavy commercial vehicles, including petrol and diesel vehicles. Vehicles for use in farm and construction are not included. While road motor vehicle travel predominantly involves petrol vehicles (approximately 73 percent of vehicle kilometres travelled), diesel vehicles (approximately 27 percent of vehicle kilometres travelled) contribute the majority of air pollutants from road motor vehicles – specifically particulate matter and nitrogen oxides (NIWA, 2015; Parliamentary Commissioner for the Environment, 2015).

This dataset relates to the "Road motor vehicle emissions" measure on the Environmental Indicators, Te taiao Aotearoa website.

Table ID 52433
Data type Table
Row count 130
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

Land cover, 1996–2012

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Creative Commons Attribution 4.0 International

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7201
61
Added
16 Apr 2018

This dataset was first added to MfE Data Service on 16 Apr 2018.

Land cover describes the extent of vegetation, water bodies, built environments, and bare natural surfaces (eg gravel and rock) across New Zealand. Measuring the composition of and changes in land cover can help us understand the pressures that different land uses are placing on the biodiversity and functioning of ecosystems.

This measure reports on land cover by class, regional council area, and year.

For more information on the Landcover Database please refer to: lris.scinfo.org.nz/layer/48423-lcdb-v41-land-cover...

Table ID 95348
Data type Table
Row count 3316
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

Growing degree days annual growing season averages and totals, 1972/3–2015/6

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Creative Commons Attribution 4.0 International

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6879
31
Added
12 Oct 2017

This dataset was first added to MfE Data Service on 12 Oct 2017.

Growing degree days (GDD) measures the amount of warmth available for plant and insect growth and can be used to predict when flowers will bloom and crops and insects will mature. GDD counts the total number of degrees Celsius each day is above a threshold temperature. In this report we used 10 degrees Celsius. Increased GDD means that plants and insects reach maturity faster, provided that other conditions necessary for growth are favourable, such as sufficient moisture and nutrients. As a measure of temperature, GDD experiences short-term changes in response to climate variations, such as El Niño, and in the longer-term is affected by our warming climate.
This dataset gives the average number of GDD over growing seasons (July 1 – June 30 of the following year) for New Zealand, the North and South Islands, and for all 30 sites.
More information on this dataset and how it relates to our environmental reporting indicators and topics can be found in the attached data quality pdf.

Table ID 89393
Data type Table
Row count 1389
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

Estimated contemporary and pre-human wetland area, by type (2008 estimate)

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Creative Commons Attribution 3.0 New Zealand

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5253
43
Added
29 Sep 2015

This dataset was first added to MfE Data Service on 29 Sep 2015.

Wetlands support unique biodiversity and provide important services. They clean water of excess nutrients and sediment, help absorb floodwaters, and act as carbon sinks (remove carbon dioxide from the atmosphere). They also have cultural importance for Māori, and provide valuable food and materials (eg flax). Draining wetlands for agricultural and urban development over the past 150 years has significantly reduced their extent, leading to a loss of biodiversity and natural function. This dataset contains estimates of the national extent of the different types of wetlands in contempary and pre-human times.

This dataset relates to the "Wetland extent" measure on the Environmental Indicators, Te taiao Aotearoa website.

Table ID 52541
Data type Table
Row count 14
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

BOMEC_15_Class_region

Licence

Creative Commons Attribution 3.0 New Zealand

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17799
59
Updated
03 Jul 2018

This dataset was last updated on MfE Data Service on 03 Jul 2018.

The 15 class Benthic-Optimised Marine Environment Classification (BOMEC). The BOMEC divides the benthic environment into ecosystem types. These are grouped into three inshore groups, three continental shelf groups, and nine deeper-water groups. Each group represents areas with similar environmental variables, such as depth, temperature, salinity, and suspended sediment. The classification system considers the distributions of eight benthic taxonomic groups: asteroids, bryozoans, benthic foraminiferans, octocorals, polychaetes, matrix-forming scleratinian corals, sponges, and benthic fish.

Layer ID 52748
Data type Vector multipolygon
Feature count 15
Services Vector Query API, Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

Estimated forest carbon stocks - Change in forest carbon stocks, 1990–2012

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Creative Commons Attribution 3.0 New Zealand

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4776
13
Added
28 Sep 2015

This dataset was first added to MfE Data Service on 28 Sep 2015.

New Zealand’s indigenous and exotic forests absorb and store carbon from the atmosphere through photosynthesis. As forests grow, the carbon stored in them increases. These carbon stocks help offset greenhouse gas emissions from sources such as agriculture, energy production, and transport.

Column headings:
type = vegetation type of forest
vol_tC = volume of carbon in tonnes

This dataset relates to the "Estimated forest carbon stocks" measure on the Environmental Indicators, Te taiao Aotearoa website.

Table ID 52476
Data type Table
Row count 46
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

Land use - Land cover classes, 1996, 2001, 2008, and 2012

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Creative Commons Attribution 3.0 New Zealand

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9063
232
Added
28 Sep 2015

This dataset was first added to MfE Data Service on 28 Sep 2015.

Land use that results in a change from indigenous to exotic cover can cause biodiversity loss and reduce functioning of ecosystems. Using more land for agriculture, forestry, and urbanisation is the main driver reducing indigenous land cover across New Zealand.

Column headings:
area_ha = area of land cover measured in hectares

This dataset relates to the "Land use" measure on the Environmental Indicators, Te taiao Aotearoa website.

Table ID 52469
Data type Table
Row count 272
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

Shark catch use (2003–2015)

Licence

Creative Commons Attribution 3.0 New Zealand

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5773
39
Added
19 Oct 2016

This dataset was first added to MfE Data Service on 19 Oct 2016.

New Zealand waters have at least 117 species of chondrichthyans (sharks, rays, and other cartilaginous fish species). They are particularly vulnerable to overfishing because they are long-lived, mature slowly, and have a low reproductive rate. Chondrichthyans are important for healthy ocean ecosystems, and reporting their commercial catch and bycatch helps us understand the sustainability of our fisheries.

Table ID 53482
Data type Table
Row count 52
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

Land cover, Area of land cover, 1996, 2001, 2008, and 2012

Licence

Creative Commons Attribution 3.0 New Zealand

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5731
71
Added
28 Sep 2015

This dataset was first added to MfE Data Service on 28 Sep 2015.

Land cover describes the extent of vegetation, water bodies, built environment, and bare natural surfaces (eg gravel and rock) across New Zealand. Measuring the composition and changes in land cover can help us better understand the pressures that different land uses are placing on the biodiversity and functioning of ecosystems.

Column headings:
area_ha = area of land cover measured in hectares

This dataset relates to the "Land cover" measure on the Environmental Indicators, Te taiao Aotearoa website.

Table ID 52478
Data type Table
Row count 884
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

Extreme wind, 1972–2016

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Creative Commons Attribution 4.0 International

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5811
78
Added
12 Oct 2017

This dataset was first added to MfE Data Service on 12 Oct 2017.

Extreme wind annual statistics for 30 regionally representative sites. The number of days with a maximum gust in the 99th percentile provides information on the frequency of extreme wind events. Percentiles are obtained from all available daily maximum wind gust data. On average, the 99th percentile daily maximum wind gust will be exceeded on approximately 3.6 days per year. Therefore, annual counts higher than this indicate more days than usual with very strong wind gusts recorded; annual counts lower than 3.6 indicate fewer strong wind gust days than usual. By using a percentile threshold we can identify events that are extreme for a particular location. Some places are naturally subject to stronger winds than others, so vegetation can become ‘wind-hardened’ and may have a higher tolerance to high wind gusts (eg a 100 km/hr wind gust may be damaging at one location, but not at another). Using a relative threshold accounts for these differences and better captures extreme wind gust occurrences. The highest maximum gust per year and the average annual highest maximum wind gust both provide information on the magnitude of extreme wind events.
Steady wind can be an important resource, but strong gusts can damage property, topple trees, and disrupt transportation, communications, and electricity. Extreme wind events can occur with frontal weather systems, around strong convective storms such as thunderstorms, and with ex-tropical cyclones. Projections indicate climate change may alter the occurrence of extreme wind events, with the strength of extreme winds expected to increase over the southern half of the North Island and the South Island, especially east of the Southern Alps, and decrease from Northland to Bay of Plenty. Monitoring can help us gauge the potential of, and prepare for, such events.
More information on this dataset and how it relates to our environmental reporting indicators and topics can be found in the attached data quality pdf.

Table ID 89425
Data type Table
Row count 1327
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed
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