Melanoma registration rates, 1948–2015

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875
10
Added
14 Oct 2017

This dataset was first added to MfE Data Service on 14 Oct 2017.

New Zealand and Australia have the world’s highest rates of melanoma, the most serious type of skin cancer. Melanoma is mainly caused by exposure to ultraviolet (UV) light, usually from the sun. New Zealand has naturally high UV levels, especially during summer.
The risk of developing melanoma is affected by factors such as skin colour and type, family history, and the amount of sun exposure. Melanoma can affect people at any age, but the chance of developing a melanoma increases with age. We report on age-standardised rates of melanoma to account for the increasing proportion of older people in our population.
Our data on melanoma registrations come from the New Zealand Cancer Registry and the Ministry of Health's Mortality Collection. The passing of the Cancer Registry Act 1993 and Cancer Registry Regulations 1994 led to significant improvements in data quality and coverage (Ministry of Health, 2013). A sharp increase in registrations after 1993 is likely to have been related to these legislative and regulatory changes; for this reason we have only analysed data from 1996.
2014–15 data are provisional and subject to change.
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 89458
Data type Table
Row count 204
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

Trends in greenhouse gas concentrations at Baring Head, 1972–2016

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836
4
Added
12 Oct 2017

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

We report on GHG concentrations in ‘clean air’ measured at Baring Head, near Wellington. These measurements give us a good idea of global concentrations and help us infer long-term impacts on ocean acidity, temperature, sea level and glaciers.
Trends were assessed using the Theil-Sen estimator and the Two One-Sided Test (TOST) for equivalence at the 95% confidence level.
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 89413
Data type Table
Row count 3
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

CAIT Country greenhouse gas emissions trends, 1990–2013

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823
2
Added
13 Oct 2017

This dataset was first added to MfE Data Service on 13 Oct 2017.

Data compiled are obtained from government reporting and complemented by a variety of non-governmental data sources.
The trend was assessed using the Theil-Sen estimator and the Two One-Sided Test (TOST) for equivalence at the 95% confidence level.
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 89426
Data type Table
Row count 2
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

Rainfall Intensity, 1960–2016

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Creative Commons Attribution 4.0 International

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754
40
Added
13 Oct 2017

This dataset was first added to MfE Data Service on 13 Oct 2017.

Two measures of rainfall intensity - percent of annual precipitation in the 95th percentile (r95ptot) and annual maximum one-day rainfall (rx1day).
Intense rainfall can result in flash floods or land slips that damage homes and property, disrupt transportation, and endanger lives. It can also interfere with recreation and increase erosion. Changes to the frequency of intense rainfall events can alter biodiversity.
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 89435
Data type Table
Row count 1710
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

New Zealand greenhouse gas emissions trends, 1990–2015

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726
8
Added
13 Oct 2017

This dataset was first added to MfE Data Service on 13 Oct 2017.

Greenhouse gases (GHGs) absorb heat from Earth’s surface, warming the atmosphere and changing our climate. New Zealand’s share of GHG emissions is very small, but our gross emissions per person are high. Emissions mainly come from combustion of fossil fuels that emit carbon dioxide (CO2), and agriculture which emits methane (CH4) and nitrous oxide (N2O). Carbon dioxide remains in the atmosphere much longer than other major GHGs. Because of this, today’s global CO2 emissions will continue to influence atmospheric CO2 concentrations for a very long time. Methane and N2O trap heat better than CO2 but leave the atmosphere faster. Reducing emissions of CH4 and N2O will decrease concentrations in the atmosphere more quickly. Greenhouse gases (GHGs) absorb heat from Earth’s surface, warming the atmosphere and changing our climate. New Zealand’s share of GHG emissions is very small, but our gross emissions per person are high. Emissions mainly come from combustion of fossil fuels that emit carbon dioxide (CO2), and agriculture which emits methane (CH4) and nitrous oxide (N2O). Carbon dioxide remains in the atmosphere much longer than other major GHGs. Because of this, today’s global CO2 emissions will continue to influence atmospheric CO2 concentrations for a very long time. Methane and N2O trap heat better than CO2 but leave the atmosphere faster. Reducing emissions of CH4 and N2O will decrease concentrations in the atmosphere more quickly.
Trend direction was assessed using the Theil-Sen estimator and the Two One-Sided Test (TOST) for equivalence at the 95% confidence level.
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 89432
Data type Table
Row count 2
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

CAIT Country greenhouse gas emissions, 1990–2013

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Creative Commons Attribution 4.0 International

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736
8
Added
13 Oct 2017

This dataset was first added to MfE Data Service on 13 Oct 2017.

Emissions data are from the Climate Analysis Indicators Tool (CAIT) version 2.0 produced by the World Resources Institute (WRI). WRI compiles country-level emissions data from governmental sources, complemented by non-governmental sources “based on criteria such as completeness and relative accuracy and country datasets are produced by applying a consistent methodology.” For detailed information see World Resources Institute (2015).
Data compiled are obtained from government reporting and complemented by a variety of non-governmental data sources.
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 89443
Data type Table
Row count 90240
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

Growing degree days trend assessment, for New Zealand, the North Island, and the South Island, 1972/3–2015/6

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714
11
Added
17 Oct 2017

This dataset was first added to MfE Data Service on 17 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.
Growing degree days (GDD) counts the number of days that are warmer than a threshold temperature (Tbase) in a year. GDD is calculated by subtracting the Tbase from the average daily temperature (maximum plus minimum temperature divided by two). If the average daily temperature is less than Tbase the GDD for that day is assigned a value of zero.
This dataset gives the trend in GDD over growing seasons (July 1 – June 30 of the following year) for New Zealand and the North and South Islands.
Trend direction was assessed using the Theil-Sen estimator and the Two One-Sided Test (TOST) for equivalence at the 95% confidence level
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 89476
Data type Table
Row count 3
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

Deforestation trend, 1990–2015

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699
21
Added
12 Oct 2017

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

New Zealand’s indigenous and exotic forests absorb carbon dioxide (CO2) from the atmosphere through photosynthesis and store the carbon as biomass and in the soil. On average, more than twice as much carbon per hectare is stored in New Zealand’s mature indigenous forests than in exotic forests planted for wood production. Regenerating indigenous forests are also an important store of carbon, adding carbon every year as they grow. Total carbon stored in exotic forests will fluctuate over decades as the forests grow from seedlings to mature trees, are harvested, and replanted. Because CO2 is the major driver of climate change, forests provide important mitigation services and help New Zealand meet its climate change commitments.
Trend direction was assessed using the Theil-Sen estimator and the Two One-Sided Test (TOST) for equivalence at the 95% confidence level.
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 89408
Data type Table
Row count 3
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

Campylobacteriosis, cryptosporidiosis, and salmonellosis notifications, 1997–2016

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Creative Commons Attribution 4.0 International

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692
3
Added
12 Oct 2017

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

Bacteria and parasites are influenced by climate variables, and infection rates may increase in response to climate change and rising temperatures. Campylobacter, Cryptosporidium, and Salmonella are three such organisms that can contaminate our food and water, leading to serious illness. Monitoring the incidence rates of illnesses can help us assess the health risks related to climate change and better prepare for disease outbreaks.
The numbers of notified cases of infection are sourced from EpiSurv, New Zealand’s national notifiable disease surveillance system. Various factors influence disease notification, and therefore the calculation of notifiable disease rates. For example, people are less likely to consult a medical practitioner when an illness is not severe (ESR, 2016a). The number of notified cases vary greatly from year to year due to New Zealand’s small population and low number of cases for some diseases (Environmental Science and Research, 2016). The August 2016 Camplylobacter outbreak in Havelock provides an example of this variation (ESR, 2016b).
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 89386
Data type Table
Row count 816
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

Global and New Zealand temperature anomalies, 1909–2016

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676
9
Added
14 Oct 2017

This dataset was first added to MfE Data Service on 14 Oct 2017.

This dataset compares temperatures anomalies from NIWA's 'seven-station' temperature series with three global temperature series.
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 89452
Data type Table
Row count 855
Services Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed
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